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begin:vcard
fn:Noelia Ventura Campos
n:Ventura Campos;Noelia
org;quoted-printable:Universitat Jaume I;Departament de Psicolog=C3=ADa B=C3=A0sica, Cl=C3=ADnica y Psicobiolog=C3=
=ADa
adr;quoted-printable;quoted-printable;quoted-printable:Avda. Sos Baynat, s/n;;Edifici d'investigaci=C3=B3 II;Castell=C3=B3 de la Plana;;E-12071;Espa=C3=B1a (Spain)
title:PDI
tel;work:+34 964 387658
tel;fax:+34 964 729267
url:www.fmri.uji.es
version:2.1
end:vcard
--------------060505030407090607090906--
=========================================================================
Date: Thu, 5 May 2011 22:15:34 +1000
Reply-To: Alex Fornito <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Alex Fornito <[log in to unmask]>
Subject: Re: PPI question
Comments: To: Torben Ellegaard Lund <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset="ISO-8859-1"
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Hi Torben,
Sorry, I just wanted to clarify: do you mean leaving SPM.xX.iG empty? It
seems like this is done by default by spm_fmri_design (?)
Are you suggesting manually entering motion parameters into this field?
On 05/05/2011 18:16, "Torben Ellegaard Lund" <[log in to unmask]> wrote:
> Just as a kind reminder. Leaving SPM.xX.iG is a bit unfortunate, because
> voxels where motion artefacts are significant then constitutes a large pa=
rt of
> the F-test derived mask used to estimate serial correlations. If you are =
picky
> about this you can change it yourselves, but it is not as easy as it shou=
ld
> be.
>=20
>=20
> Best
> Torben
>=20
>=20
>=20
> Den Uge:18 05/05/2011 kl. 05.03 skrev Alex Fornito:
>=20
>> Ahh, I see. I was assuming that SPM.xX.iG contained the indices to the
>> nuisance covariates in the design matrix, but you're right - spm_fMRI_de=
sign
>> leaves it empty.
>>=20
>> Thanks for your help!
>> A
>>=20
>>=20
>> On 05/05/2011 12:54, "MCLAREN, Donald" <[log in to unmask]> wrote:
>>=20
>>> I agree that nuisance covariates, such as motion should be removed;
>>> however, motion covariates are not generally stored in X0 in my
>>> reading of the SPM code (spm_fMRI_design, spm_regions). They should be
>>> removed in the spm_regions filtering based on the null-space of the
>>> contrast.
>>>=20
>>> As for the motion parameters being in the model, if they were in the
>>> standard analysis, they should be included in the PPI analysis. My
>>> gPPI code will do this automatically as well.
>>>=20
>>> X0 is made of SPM.xX.iB (block effects -- so removing the mean) and
>>> SPM.xX.iG (nuisance variable that is empty as far as I can tell (line
>>> 369 of spm_fMRI_design)) and the high-pass filtering (K.X0).
>>>=20
>>> Best Regards, Donald McLaren
>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>> D.G. McLaren, Ph.D.
>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>> Research Fellow, Department of Neurology, Massachusetts General
>>> Hospital and Harvard Medical School
>>> Office: (773) 406-2464
>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>>> and which is intended only for the use of the individual or entity
>>> named above. If the reader of the e-mail is not the intended recipient
>>> or the employee or agent responsible for delivering it to the intended
>>> recipient, you are hereby notified that you are in possession of
>>> confidential and privileged information. Any unauthorized use,
>>> disclosure, copying or the taking of any action in reliance on the
>>> contents of this information is strictly prohibited and may be
>>> unlawful. If you have received this e-mail unintentionally, please
>>> immediately notify the sender via telephone at (773) 406-2464 or
>>> email.
>>>=20
>>>=20
>>>=20
>>> On Wed, May 4, 2011 at 10:16 PM, Alex Fornito <[log in to unmask]>
>>> wrote:
>>>> Hi Donald,
>>>> Thanks for your response. When you say "you don't want
>>>> to filter out anything related to neural activity", I'm presuming that=
you
>>>> are referring to the deconvolved neural signal?
>>>>=20
>>>> If so, that makes sense. However, X0 also contains user-specified nuis=
ance
>>>> covariates. I would have thought it would make sense to remove those,
>>>> depending on what they were (e.g., movement parameters)? I guess they =
can
>>>> always be entered into the PPI regression model...
>>>>=20
>>>>=20
>>>> On 05/05/2011 11:57, "MCLAREN, Donald" <[log in to unmask]> wrot=
e:
>>>>=20
>>>>> I could be wrong, Karl or Darren please correct me if I am.
>>>>>=20
>>>>> X0 is composed of the high-pass filter and constant term. Thus, you
>>>>> want to filter these out of the Yc regressor. However, you don't want
>>>>> to filter out anything related to neural activity, so you wouldn't
>>>>> want to filter your signal and then predict the neural activity from
>>>>> the filtered signal, especially filtering frequencies.
>>>>>=20
>>>>> Best Regards, Donald McLaren
>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>> D.G. McLaren, Ph.D.
>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>> Hospital and Harvard Medical School
>>>>> Office: (773) 406-2464
>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>>>>> and which is intended only for the use of the individual or entity
>>>>> named above. If the reader of the e-mail is not the intended recipien=
t
>>>>> or the employee or agent responsible for delivering it to the intende=
d
>>>>> recipient, you are hereby notified that you are in possession of
>>>>> confidential and privileged information. Any unauthorized use,
>>>>> disclosure, copying or the taking of any action in reliance on the
>>>>> contents of this information is strictly prohibited and may be
>>>>> unlawful. If you have received this e-mail unintentionally, please
>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>> email.
>>>>>=20
>>>>>=20
>>>>>=20
>>>>> On Sat, Apr 30, 2011 at 8:03 PM, Alex Fornito <[log in to unmask]
u>
>>>>> wrote:
>>>>>> Hi Donald,
>>>>>> As far as I can tell, spm_regions filters and whitens the VOI time
>>>>>> series,
>>>>>> and adjusts for the null space of the contrast if an adjustment is
>>>>>> specified
>>>>>> in xY.Ic. It defines the confound matrix, X0, but does not correct f=
or
>>>>>> it.
>>>>>> The following line in spm_peb_ppi corrects for the confounds.
>>>>>>=20
>>>>>> Yc =3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>=20
>>>>>> So the above correction does seem to be doing something different to
>>>>>> spm_regions. I'm wondering why the uncorrected data, Y, is used when
>>>>>> generating the ppi interaction term, while the corrected data Yc is =
to be
>>>>>> used as a covariate of no interest in the PPI model. I would has tho=
ught
>>>>>> that Yc should be used to generate the ppi interaction term as well.
>>>>>>=20
>>>>>> In my data, my X0 is a 195 x 7 matrix (I have 195 volumes per sessio=
n).
>>>>>>=20
>>>>>> Regards,
>>>>>> Alex
>>>>>>=20
>>>>>>=20
>>>>>> On 30/04/2011 02:22, "MCLAREN, Donald" <[log in to unmask]> wr=
ote:
>>>>>>=20
>>>>>>> I'm actually travelling at the moment. However, I know Y has alread=
y
>>>>>>> been adjusted as part of the VOI processing.
>>>>>>>=20
>>>>>>> Can you check what X0 looks like?
>>>>>>>=20
>>>>>>> Best Regards, Donald McLaren
>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>> D.G. McLaren, Ph.D.
>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>> Hospital and Harvard Medical School
>>>>>>> Office: (773) 406-2464
>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>>>>>>> and which is intended only for the use of the individual or entity
>>>>>>> named above. If the reader of the e-mail is not the intended recipi=
ent
>>>>>>> or the employee or agent responsible for delivering it to the inten=
ded
>>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>> disclosure, copying or the taking of any action in reliance on the
>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>> unlawful. If you have received this e-mail unintentionally, please
>>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>>> email.
>>>>>>>=20
>>>>>>>=20
>>>>>>>=20
>>>>>>> On Fri, Apr 29, 2011 at 2:55 AM, Alex Fornito <[log in to unmask]
.au>
>>>>>>> wrote:
>>>>>>>> Hi all,
>>>>>>>> I have a question concerning the code used to implement a PPI anal=
ysis.
>>>>>>>>=20
>>>>>>>> In the spm_peb_ppi.m function packaged with SPM8, lines 329-332 re=
move
>>>>>>>> confounds from the input seed region=B9s time course:
>>>>>>>>=20
>>>>>>>> % Remove confounds and save Y in ouput structure
>>>>>>>> %-----------------------------------------------------------------=
-----
>>>>>>>> --
>>>>>>>> --
>>>>>>>> Yc =3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>=20
>>>>>>>> PPI.Y is then to be used as a covariate of no interest when buildi=
ng
>>>>>>>> the
>>>>>>>> PPI
>>>>>>>> regression model. However, on line 488, it is the uncorrected seed=
time
>>>>>>>> course, Y, that is input to the deconvolution routine and used to
>>>>>>>> generate
>>>>>>>> the ppi term:
>>>>>>>>=20
>>>>>>>> C =3D spm_PEB(Y,P);
>>>>>>>> xn =3D xb*C{2}.E(1:N);
>>>>>>>> xn =3D spm_detrend(xn);
>>>>>>>>=20
>>>>>>>> % Setup psychological variable from inputs and contast weights
>>>>>>>> =20
>>>>>>>> %-----------------------------------------------------------------=
-----
>>>>>>>> PSY =3D zeros(N*NT,1);
>>>>>>>> for i =3D 1:size(U.u,2)
>>>>>>>> PSY =3D PSY + full(U.u(:,i)*U.w(:,i));
>>>>>>>> end
>>>>>>>> % PSY =3D spm_detrend(PSY); <- removed centering of psych variabl=
e
>>>>>>>> % prior to multiplication with xn. Based on discussion with Karl
>>>>>>>> % and Donald McLaren.
>>>>>>>>=20
>>>>>>>> % Multiply psychological variable by neural signal
>>>>>>>> =20
>>>>>>>> =20
>>>>>>>> %-----------------------------------------------------------------=
-----
>>>>>>>> PSYxn =3D PSY.*xn;
>>>>>>>>=20
>>>>>>>> Is there any specific reason why Y, rather than Yc(:,1), is used t=
o
>>>>>>>> compute
>>>>>>>> PSYxn? I thought Yc might be more appropriate (?).
>>>>>>>> Thanks for your help,
>>>>>>>> Alex
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>> ------------------------------------------
>>>>>>>>=20
>>>>>>>> Alex Fornito
>>>>>>>> Research Fellow
>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>> University of Melbourne
>>>>>>>> National Neuroscience Facility
>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>> 161 Barry St
>>>>>>>> Carlton South 3053
>>>>>>>> Victoria, Australia
>>>>>>>>=20
>>>>>>>> Email: [log in to unmask]
>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>=20
>>>>>>=20
>>>>>>=20
>>>>>> ------------------------------------------
>>>>>>=20
>>>>>> Alex Fornito
>>>>>> Research Fellow
>>>>>> Melbourne Neuropsychiatry Centre
>>>>>> University of Melbourne
>>>>>> National Neuroscience Facility
>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>> 161 Barry St
>>>>>> Carlton South 3053
>>>>>> Victoria, Australia
>>>>>>=20
>>>>>> Email: [log in to unmask]
>>>>>> Phone: +61 3 8344 1876
>>>>>> Fax: +61 3 9348 0469
>>>>>>=20
>>>>>>=20
>>>>>>=20
>>>>>>=20
>>>>>=20
>>>>=20
>>>>=20
>>>> ------------------------------------------
>>>>=20
>>>> Alex Fornito
>>>> Research Fellow
>>>> Melbourne Neuropsychiatry Centre
>>>> University of Melbourne
>>>> National Neuroscience Facility
>>>> Levels 1 & 2, Alan Gilbert Building
>>>> 161 Barry St
>>>> Carlton South 3053
>>>> Victoria, Australia
>>>>=20
>>>> Email: [log in to unmask]
>>>> Phone: +61 3 8344 1876
>>>> Fax: +61 3 9348 0469
>>>>=20
>>>>=20
>>>>=20
>>>>=20
>>>=20
>>=20
>>=20
>> ------------------------------------------
>>=20
>> Alex Fornito
>> Research Fellow
>> Melbourne Neuropsychiatry Centre
>> University of Melbourne
>> National Neuroscience Facility
>> Levels 1 & 2, Alan Gilbert Building
>> 161 Barry St=20
>> Carlton South 3053
>> Victoria, Australia
>>=20
>> Email: [log in to unmask]
>> Phone: +61 3 8344 1876
>> Fax: +61 3 9348 0469
>=20
>=20
------------------------------------------
Alex Fornito
Research Fellow
Melbourne Neuropsychiatry Centre
University of Melbourne
National Neuroscience Facility
Levels 1 & 2, Alan Gilbert Building
161 Barry St=A0
Carlton South 3053
Victoria, Australia
Email: [log in to unmask]
Phone: +61 3 8344 1876
Fax: +61 3 9348 0469 =A0
=========================================================================
Date: Thu, 5 May 2011 14:51:12 +0200
Reply-To: Emilia Lentini <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Emilia Lentini <[log in to unmask]>
Subject: flipped images
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=002215046ca7fc6d1604a286d383
Message-ID: <[log in to unmask]>
--002215046ca7fc6d1604a286d383
Content-Type: text/plain; charset=ISO-8859-1
Hi.
I would like to do a full-factorial analysis with both flipped (right-left)
and non-flipped images.
To flip the images I use:
Display --> resize {x}: -1 and then reorient images..
When I try to run the analysis I get following error:
"Error running job: Error using ==> spm_check_orientations"
How can I correct for this error?
Can I flip the images in any other way?
Best regards
Emilia
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Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Hi.<br><br>I would like to do a full-factorial analysis with both flipped (=
right-left) and non-flipped images.<br><br>To flip the images I use: <br>Di=
splay --> resize {x}: -1 and then reorient images..<br><br>When I try to=
run the analysis I get following error:<br>
<br>"Error running job: Error using =3D=3D> spm_check_orientations&=
quot;<br><br><br>How can I correct for this error?<br><br>Can I flip the im=
ages in any other way?<br><br><br>Best regards<br>Emilia<br>
--002215046ca7fc6d1604a286d383--
=========================================================================
Date: Thu, 5 May 2011 07:58:00 -0500
Reply-To: Darren Gitelman <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Darren Gitelman <[log in to unmask]>
Subject: Re: PPI question
Comments: To: "MCLAREN, Donald" <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
SPM:
What Donald says below is correct about Yc.
I agree with the comments about SPM.xX.iB and SPM.xX.iG.
As Donald notes SPM.xX.iG is not filled in by SPM as SPM has no
"understanding" of effects of interest vs. effects of no interest.
Columns of the design become effects of no interest by weighting them
as 0 in your contrasts.
Regards,
Darren
On Wed, May 4, 2011 at 8:57 PM, MCLAREN, Donald
<[log in to unmask]> wrote:
> I could be wrong, Karl or Darren please correct me if I am.
>
> X0 is composed of the high-pass filter and constant term. Thus, you
> want to filter these out of the Yc regressor. However, you don't want
> to filter out anything related to neural activity, so you wouldn't
> want to filter your signal and then predict the neural activity from
> the filtered signal, especially filtering frequencies.
>
> Best Regards, Donald McLaren
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> D.G. McLaren, Ph.D.
> Postdoctoral Research Fellow, GRECC, Bedford VA
> Research Fellow, Department of Neurology, Massachusetts General
> Hospital and Harvard Medical School
> Office: (773) 406-2464
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> This e-mail contains CONFIDENTIAL INFORMATION which may contain
> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
> and which is intended only for the use of the individual or entity
> named above. If the reader of the e-mail is not the intended recipient
> or the employee or agent responsible for delivering it to the intended
> recipient, you are hereby notified that you are in possession of
> confidential and privileged information. Any unauthorized use,
> disclosure, copying or the taking of any action in reliance on the
> contents of this information is strictly prohibited and may be
> unlawful. If you have received this e-mail unintentionally, please
> immediately notify the sender via telephone at (773) 406-2464 or
> email.
>
>
>
> On Sat, Apr 30, 2011 at 8:03 PM, Alex Fornito <[log in to unmask]> w=
rote:
>> Hi Donald,
>> As far as I can tell, spm_regions filters and whitens the VOI time serie=
s,
>> and adjusts for the null space of the contrast if an adjustment is speci=
fied
>> in xY.Ic. It defines the confound matrix, X0, but does not correct for i=
t.
>> The following line in spm_peb_ppi corrects for the confounds.
>>
>> =A0Yc =A0=A0=A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>> =A0PPI.Y =3D Yc(:,1);
>>
>> So the above correction does seem to be doing something different to
>> spm_regions. I'm wondering why the uncorrected data, Y, is used when
>> generating the ppi interaction term, while the corrected data Yc is to b=
e
>> used as a covariate of no interest in the PPI model. I would has thought
>> that Yc should be used to generate the ppi interaction term as well.
>>
>> In my data, my X0 is a 195 x 7 matrix (I have 195 volumes per session).
>>
>> Regards,
>> Alex
>>
>>
>> On 30/04/2011 02:22, "MCLAREN, Donald" <[log in to unmask]> wrote:
>>
>>> I'm actually travelling at the moment. However, I know Y has already
>>> been adjusted as part of the VOI processing.
>>>
>>> Can you check what X0 looks like?
>>>
>>> Best Regards, Donald McLaren
>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>> D.G. McLaren, Ph.D.
>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>> Research Fellow, Department of Neurology, Massachusetts General
>>> Hospital and Harvard Medical School
>>> Office: (773) 406-2464
>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>>> and which is intended only for the use of the individual or entity
>>> named above. If the reader of the e-mail is not the intended recipient
>>> or the employee or agent responsible for delivering it to the intended
>>> recipient, you are hereby notified that you are in possession of
>>> confidential and privileged information. Any unauthorized use,
>>> disclosure, copying or the taking of any action in reliance on the
>>> contents of this information is strictly prohibited and may be
>>> unlawful. If you have received this e-mail unintentionally, please
>>> immediately notify the sender via telephone at (773) 406-2464 or
>>> email.
>>>
>>>
>>>
>>> On Fri, Apr 29, 2011 at 2:55 AM, Alex Fornito <[log in to unmask]>=
wrote:
>>>> Hi all,
>>>> I have a question concerning the code used to implement a PPI analysis=
.
>>>>
>>>> In the spm_peb_ppi.m function packaged with SPM8, lines 329-332 remove
>>>> confounds from the input seed region=B9s time course:
>>>>
>>>> % Remove confounds and save Y in ouput structure
>>>> %---------------------------------------------------------------------=
-----
>>>> Yc =A0=A0=A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>> PPI.Y =3D Yc(:,1);
>>>>
>>>> PPI.Y is then to be used as a covariate of no interest when building t=
he PPI
>>>> regression model. However, on line 488, it is the uncorrected seed tim=
e
>>>> course, Y, that is input to the deconvolution routine and used to gene=
rate
>>>> the ppi term:
>>>>
>>>> =A0=A0C =A0=3D spm_PEB(Y,P);
>>>> =A0=A0=A0=A0xn =3D xb*C{2}.E(1:N);
>>>> =A0=A0=A0=A0xn =3D spm_detrend(xn);
>>>>
>>>> =A0=A0% Setup psychological variable from inputs and contast weights
>>>> =A0=A0%---------------------------------------------------------------=
-------
>>>> =A0=A0PSY =3D zeros(N*NT,1);
>>>> =A0=A0for i =3D 1:size(U.u,2)
>>>> =A0=A0=A0=A0=A0=A0PSY =3D PSY + full(U.u(:,i)*U.w(:,i));
>>>> =A0=A0end
>>>> =A0=A0% PSY =3D spm_detrend(PSY); =A0<- removed centering of psych var=
iable
>>>> =A0=A0% prior to multiplication with xn. Based on discussion with Karl
>>>> =A0=A0% and Donald McLaren.
>>>>
>>>> =A0% Multiply psychological variable by neural signal
>>>> =A0 =A0%--------------------------------------------------------------=
--------
>>>> =A0 =A0PSYxn =3D PSY.*xn;
>>>>
>>>> Is there any specific reason why Y, rather than Yc(:,1), is used to co=
mpute
>>>> PSYxn? I thought Yc might be more appropriate (?).
>>>> Thanks for your help,
>>>> Alex
>>>>
>>>>
>>>>
>>>>
>>>> ------------------------------------------
>>>>
>>>> Alex Fornito
>>>> Research Fellow
>>>> Melbourne Neuropsychiatry Centre
>>>> University of Melbourne
>>>> National Neuroscience Facility
>>>> Levels 1 & 2, Alan Gilbert Building
>>>> 161 Barry St
>>>> Carlton South 3053
>>>> Victoria, Australia
>>>>
>>>> Email: [log in to unmask]
>>>> Phone: +61 3 8344 1876
>>>> Fax: +61 3 9348 0469
>>>>
>>>>
>>>
>>
>>
>> ------------------------------------------
>>
>> Alex Fornito
>> Research Fellow
>> Melbourne Neuropsychiatry Centre
>> University of Melbourne
>> National Neuroscience Facility
>> Levels 1 & 2, Alan Gilbert Building
>> 161 Barry St
>> Carlton South 3053
>> Victoria, Australia
>>
>> Email: [log in to unmask]
>> Phone: +61 3 8344 1876
>> Fax: +61 3 9348 0469
>>
>>
>>
>>
>
--=20
Darren Gitelman, MD
Northwestern University
710 N. Lake Shore Dr.
Abbott 11th Floor
Chicago, IL 60611
Ph: (312) 908-8614
Fax: (312) 908-5073
=========================================================================
Date: Thu, 5 May 2011 21:34:14 +0800
Reply-To: "shiye.chen" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "shiye.chen" <[log in to unmask]>
Subject: Repeated Coregistration Error
MIME-Version: 1.0
Content-Type: multipart/alternative;
boundary="----=_NextPart_000_0025_01CC0B6C.37C48020"
Message-ID: <[log in to unmask]>
This is a multipart message in MIME format.
------=_NextPart_000_0025_01CC0B6C.37C48020
Content-Type: text/plain;
charset="us-ascii"
Content-Transfer-Encoding: 7bit
Dear SPM list,
Sorry to interrupt, but I was encountered this repeated coregistration
error, which I cannot fix.
Running "Coreg: Estimate & Reslice"
Error running job: Attempted to access fwhm(2); index out of bounds because
numel(fwhm)=1.
In file "D:\spm5\spm_coreg.m" (v1007), function "optfun" at line 160.
In file "D:\spm5\spm_coreg.m" (v1007), function "spm_coreg" at line 82.
In file "D:\spm5\spm_powell.m" (v691), function "spm_powell" at line 27.
In file "D:\spm5\spm_coreg.m" (v1007), function "spm_coreg" at line 134.
In file "D:\spm5\spm_config_coreg.m" (v1032), function "estimate_reslice" at
line 322.
--------------------------
Done.
Could someone help me on this?
Thanks very much!
------=_NextPart_000_0025_01CC0B6C.37C48020
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</o:shapelayout></xml><![endif]--></head><body lang=3DEN-US link=3Dblue =
vlink=3Dpurple><div class=3DWordSection1><p class=3DMsoPlainText>Dear =
SPM list,<o:p></o:p></p><p class=3DMsoNormal><o:p> </o:p></p><p =
class=3DMsoNormal>Sorry to interrupt, but I was encountered this =
repeated coregistration error, which I cannot fix. <o:p></o:p></p><p =
class=3DMsoNormal><o:p> </o:p></p><p class=3DMsoNormal>Running =
"Coreg: Estimate & Reslice"<o:p></o:p></p><p =
class=3DMsoNormal><o:p> </o:p></p><p class=3DMsoNormal><span =
style=3D'background:yellow;mso-highlight:yellow'>Error running job: =
Attempted to access fwhm(2); index out of bounds because =
numel(fwhm)=3D1.<o:p></o:p></span></p><p class=3DMsoNormal><span =
style=3D'background:yellow;mso-highlight:yellow'>In file =
"D:\spm5\spm_coreg.m" (v1007), function "optfun" at =
line 160.<o:p></o:p></span></p><p class=3DMsoNormal><span =
style=3D'background:yellow;mso-highlight:yellow'>In file =
"D:\spm5\spm_coreg.m" (v1007), function "spm_coreg" =
at line 82.<o:p></o:p></span></p><p class=3DMsoNormal><span =
style=3D'background:yellow;mso-highlight:yellow'>In file =
"D:\spm5\spm_powell.m" (v691), function "spm_powell" =
at line 27.<o:p></o:p></span></p><p class=3DMsoNormal><span =
style=3D'background:yellow;mso-highlight:yellow'>In file =
"D:\spm5\spm_coreg.m" (v1007), function "spm_coreg" =
at line 134.<o:p></o:p></span></p><p class=3DMsoNormal><span =
style=3D'background:yellow;mso-highlight:yellow'>In file =
"D:\spm5\spm_config_coreg.m" (v1032), function =
"estimate_reslice" at line 322.<o:p></o:p></span></p><p =
class=3DMsoNormal><span =
style=3D'background:yellow;mso-highlight:yellow'>------------------------=
--<o:p></o:p></span></p><p class=3DMsoNormal><span =
style=3D'background:yellow;mso-highlight:yellow'>Done.</span><o:p></o:p><=
/p><p class=3DMsoNormal><o:p> </o:p></p><p class=3DMsoNormal>Could =
someone help me on this? <o:p></o:p></p><p =
class=3DMsoNormal><o:p> </o:p></p><p class=3DMsoNormal>Thanks very =
much!<o:p></o:p></p><p =
class=3DMsoNormal><o:p> </o:p></p></div></body></html>
------=_NextPart_000_0025_01CC0B6C.37C48020--
=========================================================================
Date: Thu, 5 May 2011 15:48:08 +0200
Reply-To: Torben Ellegaard Lund <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Torben Ellegaard Lund <[log in to unmask]>
Subject: Re: PPI question
Comments: To: Alex Fornito <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-version: 1.0
Content-type: text/plain; charset=windows-1252
Content-transfer-encoding: quoted-printable
Message-ID: <[log in to unmask]>
Hi Alex
Den Uge:18 05/05/2011 kl. 14.15 skrev Alex Fornito:
> Hi Torben,
> Sorry, I just wanted to clarify: do you mean leaving SPM.xX.iG empty? =
It
> seems like this is done by default by spm_fmri_design (?)
leaving it empty will include all user defined regressors in the effects =
of interest F-test which determines the mask where the serial =
correlation is estimated. I think it would make sense if the motion =
regressors did not go into this test, just like the DCS HP-filter does =
not go into the F-contrast.
> Are you suggesting manually entering motion parameters into this =
field?
Yes, or their indices that is. It should be done after specification, =
but before model estimation. You can check if SPM recognized your =
changes by looking at the automatically generated effects of interest =
F-contrast.
Best
Torben
>=20
> On 05/05/2011 18:16, "Torben Ellegaard Lund" <[log in to unmask]> =
wrote:
>=20
>> Just as a kind reminder. Leaving SPM.xX.iG is a bit unfortunate, =
because
>> voxels where motion artefacts are significant then constitutes a =
large part of
>> the F-test derived mask used to estimate serial correlations. If you =
are picky
>> about this you can change it yourselves, but it is not as easy as it =
should
>> be.
>>=20
>>=20
>> Best
>> Torben
>>=20
>>=20
>>=20
>> Den Uge:18 05/05/2011 kl. 05.03 skrev Alex Fornito:
>>=20
>>> Ahh, I see. I was assuming that SPM.xX.iG contained the indices to =
the
>>> nuisance covariates in the design matrix, but you're right - =
spm_fMRI_design
>>> leaves it empty.
>>>=20
>>> Thanks for your help!
>>> A
>>>=20
>>>=20
>>> On 05/05/2011 12:54, "MCLAREN, Donald" <[log in to unmask]> =
wrote:
>>>=20
>>>> I agree that nuisance covariates, such as motion should be removed;
>>>> however, motion covariates are not generally stored in X0 in my
>>>> reading of the SPM code (spm_fMRI_design, spm_regions). They should =
be
>>>> removed in the spm_regions filtering based on the null-space of the
>>>> contrast.
>>>>=20
>>>> As for the motion parameters being in the model, if they were in =
the
>>>> standard analysis, they should be included in the PPI analysis. My
>>>> gPPI code will do this automatically as well.
>>>>=20
>>>> X0 is made of SPM.xX.iB (block effects -- so removing the mean) and
>>>> SPM.xX.iG (nuisance variable that is empty as far as I can tell =
(line
>>>> 369 of spm_fMRI_design)) and the high-pass filtering (K.X0).
>>>>=20
>>>> Best Regards, Donald McLaren
>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>> D.G. McLaren, Ph.D.
>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>> Hospital and Harvard Medical School
>>>> Office: (773) 406-2464
>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>>>> and which is intended only for the use of the individual or entity
>>>> named above. If the reader of the e-mail is not the intended =
recipient
>>>> or the employee or agent responsible for delivering it to the =
intended
>>>> recipient, you are hereby notified that you are in possession of
>>>> confidential and privileged information. Any unauthorized use,
>>>> disclosure, copying or the taking of any action in reliance on the
>>>> contents of this information is strictly prohibited and may be
>>>> unlawful. If you have received this e-mail unintentionally, please
>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>> email.
>>>>=20
>>>>=20
>>>>=20
>>>> On Wed, May 4, 2011 at 10:16 PM, Alex Fornito =
<[log in to unmask]>
>>>> wrote:
>>>>> Hi Donald,
>>>>> Thanks for your response. When you say "you don't want
>>>>> to filter out anything related to neural activity", I'm presuming =
that you
>>>>> are referring to the deconvolved neural signal?
>>>>>=20
>>>>> If so, that makes sense. However, X0 also contains user-specified =
nuisance
>>>>> covariates. I would have thought it would make sense to remove =
those,
>>>>> depending on what they were (e.g., movement parameters)? I guess =
they can
>>>>> always be entered into the PPI regression model...
>>>>>=20
>>>>>=20
>>>>> On 05/05/2011 11:57, "MCLAREN, Donald" <[log in to unmask]> =
wrote:
>>>>>=20
>>>>>> I could be wrong, Karl or Darren please correct me if I am.
>>>>>>=20
>>>>>> X0 is composed of the high-pass filter and constant term. Thus, =
you
>>>>>> want to filter these out of the Yc regressor. However, you don't =
want
>>>>>> to filter out anything related to neural activity, so you =
wouldn't
>>>>>> want to filter your signal and then predict the neural activity =
from
>>>>>> the filtered signal, especially filtering frequencies.
>>>>>>=20
>>>>>> Best Regards, Donald McLaren
>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>> D.G. McLaren, Ph.D.
>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>> Hospital and Harvard Medical School
>>>>>> Office: (773) 406-2464
>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY =
PRIVILEGED
>>>>>> and which is intended only for the use of the individual or =
entity
>>>>>> named above. If the reader of the e-mail is not the intended =
recipient
>>>>>> or the employee or agent responsible for delivering it to the =
intended
>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>> disclosure, copying or the taking of any action in reliance on =
the
>>>>>> contents of this information is strictly prohibited and may be
>>>>>> unlawful. If you have received this e-mail unintentionally, =
please
>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>> email.
>>>>>>=20
>>>>>>=20
>>>>>>=20
>>>>>> On Sat, Apr 30, 2011 at 8:03 PM, Alex Fornito =
<[log in to unmask]>
>>>>>> wrote:
>>>>>>> Hi Donald,
>>>>>>> As far as I can tell, spm_regions filters and whitens the VOI =
time
>>>>>>> series,
>>>>>>> and adjusts for the null space of the contrast if an adjustment =
is
>>>>>>> specified
>>>>>>> in xY.Ic. It defines the confound matrix, X0, but does not =
correct for
>>>>>>> it.
>>>>>>> The following line in spm_peb_ppi corrects for the confounds.
>>>>>>>=20
>>>>>>> Yc =3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>=20
>>>>>>> So the above correction does seem to be doing something =
different to
>>>>>>> spm_regions. I'm wondering why the uncorrected data, Y, is used =
when
>>>>>>> generating the ppi interaction term, while the corrected data Yc =
is to be
>>>>>>> used as a covariate of no interest in the PPI model. I would has =
thought
>>>>>>> that Yc should be used to generate the ppi interaction term as =
well.
>>>>>>>=20
>>>>>>> In my data, my X0 is a 195 x 7 matrix (I have 195 volumes per =
session).
>>>>>>>=20
>>>>>>> Regards,
>>>>>>> Alex
>>>>>>>=20
>>>>>>>=20
>>>>>>> On 30/04/2011 02:22, "MCLAREN, Donald" =
<[log in to unmask]> wrote:
>>>>>>>=20
>>>>>>>> I'm actually travelling at the moment. However, I know Y has =
already
>>>>>>>> been adjusted as part of the VOI processing.
>>>>>>>>=20
>>>>>>>> Can you check what X0 looks like?
>>>>>>>>=20
>>>>>>>> Best Regards, Donald McLaren
>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>>> Hospital and Harvard Medical School
>>>>>>>> Office: (773) 406-2464
>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY =
PRIVILEGED
>>>>>>>> and which is intended only for the use of the individual or =
entity
>>>>>>>> named above. If the reader of the e-mail is not the intended =
recipient
>>>>>>>> or the employee or agent responsible for delivering it to the =
intended
>>>>>>>> recipient, you are hereby notified that you are in possession =
of
>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>> disclosure, copying or the taking of any action in reliance on =
the
>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>> unlawful. If you have received this e-mail unintentionally, =
please
>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 =
or
>>>>>>>> email.
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>> On Fri, Apr 29, 2011 at 2:55 AM, Alex Fornito =
<[log in to unmask]>
>>>>>>>> wrote:
>>>>>>>>> Hi all,
>>>>>>>>> I have a question concerning the code used to implement a PPI =
analysis.
>>>>>>>>>=20
>>>>>>>>> In the spm_peb_ppi.m function packaged with SPM8, lines =
329-332 remove
>>>>>>>>> confounds from the input seed region=92s time course:
>>>>>>>>>=20
>>>>>>>>> % Remove confounds and save Y in ouput structure
>>>>>>>>> =
%----------------------------------------------------------------------
>>>>>>>>> --
>>>>>>>>> --
>>>>>>>>> Yc =3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>>=20
>>>>>>>>> PPI.Y is then to be used as a covariate of no interest when =
building
>>>>>>>>> the
>>>>>>>>> PPI
>>>>>>>>> regression model. However, on line 488, it is the uncorrected =
seed time
>>>>>>>>> course, Y, that is input to the deconvolution routine and used =
to
>>>>>>>>> generate
>>>>>>>>> the ppi term:
>>>>>>>>>=20
>>>>>>>>> C =3D spm_PEB(Y,P);
>>>>>>>>> xn =3D xb*C{2}.E(1:N);
>>>>>>>>> xn =3D spm_detrend(xn);
>>>>>>>>>=20
>>>>>>>>> % Setup psychological variable from inputs and contast =
weights
>>>>>>>>>=20
>>>>>>>>> =
%----------------------------------------------------------------------
>>>>>>>>> PSY =3D zeros(N*NT,1);
>>>>>>>>> for i =3D 1:size(U.u,2)
>>>>>>>>> PSY =3D PSY + full(U.u(:,i)*U.w(:,i));
>>>>>>>>> end
>>>>>>>>> % PSY =3D spm_detrend(PSY); <- removed centering of psych =
variable
>>>>>>>>> % prior to multiplication with xn. Based on discussion with =
Karl
>>>>>>>>> % and Donald McLaren.
>>>>>>>>>=20
>>>>>>>>> % Multiply psychological variable by neural signal
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>> =
%----------------------------------------------------------------------
>>>>>>>>> PSYxn =3D PSY.*xn;
>>>>>>>>>=20
>>>>>>>>> Is there any specific reason why Y, rather than Yc(:,1), is =
used to
>>>>>>>>> compute
>>>>>>>>> PSYxn? I thought Yc might be more appropriate (?).
>>>>>>>>> Thanks for your help,
>>>>>>>>> Alex
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>> ------------------------------------------
>>>>>>>>>=20
>>>>>>>>> Alex Fornito
>>>>>>>>> Research Fellow
>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>> University of Melbourne
>>>>>>>>> National Neuroscience Facility
>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>> 161 Barry St
>>>>>>>>> Carlton South 3053
>>>>>>>>> Victoria, Australia
>>>>>>>>>=20
>>>>>>>>> Email: [log in to unmask]
>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>=20
>>>>>>>=20
>>>>>>>=20
>>>>>>> ------------------------------------------
>>>>>>>=20
>>>>>>> Alex Fornito
>>>>>>> Research Fellow
>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>> University of Melbourne
>>>>>>> National Neuroscience Facility
>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>> 161 Barry St
>>>>>>> Carlton South 3053
>>>>>>> Victoria, Australia
>>>>>>>=20
>>>>>>> Email: [log in to unmask]
>>>>>>> Phone: +61 3 8344 1876
>>>>>>> Fax: +61 3 9348 0469
>>>>>>>=20
>>>>>>>=20
>>>>>>>=20
>>>>>>>=20
>>>>>>=20
>>>>>=20
>>>>>=20
>>>>> ------------------------------------------
>>>>>=20
>>>>> Alex Fornito
>>>>> Research Fellow
>>>>> Melbourne Neuropsychiatry Centre
>>>>> University of Melbourne
>>>>> National Neuroscience Facility
>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>> 161 Barry St
>>>>> Carlton South 3053
>>>>> Victoria, Australia
>>>>>=20
>>>>> Email: [log in to unmask]
>>>>> Phone: +61 3 8344 1876
>>>>> Fax: +61 3 9348 0469
>>>>>=20
>>>>>=20
>>>>>=20
>>>>>=20
>>>>=20
>>>=20
>>>=20
>>> ------------------------------------------
>>>=20
>>> Alex Fornito
>>> Research Fellow
>>> Melbourne Neuropsychiatry Centre
>>> University of Melbourne
>>> National Neuroscience Facility
>>> Levels 1 & 2, Alan Gilbert Building
>>> 161 Barry St=20
>>> Carlton South 3053
>>> Victoria, Australia
>>>=20
>>> Email: [log in to unmask]
>>> Phone: +61 3 8344 1876
>>> Fax: +61 3 9348 0469
>>=20
>>=20
>=20
>=20
> ------------------------------------------
>=20
> Alex Fornito
> Research Fellow
> Melbourne Neuropsychiatry Centre
> University of Melbourne
> National Neuroscience Facility
> Levels 1 & 2, Alan Gilbert Building
> 161 Barry St=20
> Carlton South 3053
> Victoria, Australia
>=20
> Email: [log in to unmask]
> Phone: +61 3 8344 1876
> Fax: +61 3 9348 0469 =20
>=20
>=20
>=20
=========================================================================
Date: Thu, 5 May 2011 15:55:33 +0200
Reply-To: Michael Erb <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michael Erb <[log in to unmask]>
Subject: Re: flipped images
Comments: To: Emilia Lentini <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Content-Transfer-Encoding: 7bit
Message-ID: <[log in to unmask]>
Am 05.05.2011 14:51, schrieb Emilia Lentini:
> Hi.
>
> I would like to do a full-factorial analysis with both flipped
> (right-left) and non-flipped images.
>
> To flip the images I use:
> Display --> resize {x}: -1 and then reorient images..
>
> When I try to run the analysis I get following error:
>
> "Error running job: Error using ==> spm_check_orientations"
>
>
> How can I correct for this error?
You have to reslice the images e.g. with Coregister(Reslice).
Image Defining Space: a non-flipped image
Images to Reslice: your flipped images
afterwards you can delete your flipped images and use the resliced r*
images.
Regards,
Michael.
>
> Can I flip the images in any other way?
>
>
> Best regards
> Emilia
--
<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
Dr. Michael Erb
Sektion f. experimentelle Kernspinresonanz des ZNS
Abteilung Neuroradiologie, Universitaetsklinikum
Hoppe-Seyler_Str. 3, D-72076 Tuebingen
Tel.: +49(0)7071/2987753 priv. +49(0)7071/61559
Fax.: +49(0)7071/294371
e-mail: <[log in to unmask]>
www: http://www.medizin.uni-tuebingen.de/nrad/sektion/
<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
=========================================================================
Date: Thu, 5 May 2011 16:33:11 +0200
Reply-To: "Eickhoff, Simon" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Eickhoff, Simon" <[log in to unmask]>
Subject: SPM Anatomy Toolbox Update (and new website)
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=========================================================================
Date: Thu, 5 May 2011 16:34:25 +0200
Reply-To: "Buchert, Ralph" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Buchert, Ralph" <[log in to unmask]>
Subject: truncation
Content-Type: multipart/related;
boundary="_004_196D7E1E24668447984E319A6656DDB802ACB57434A2EXCHANGE21c_";
type="multipart/alternative"
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
--_004_196D7E1E24668447984E319A6656DDB802ACB57434A2EXCHANGE21c_
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Content-Type: text/plain; charset="iso-8859-1"
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Dear SPMers,
we are using SPM 8 for stereotactical normalization of mouse brain perfusio=
n SPECT images (middle) into the reference space of the 3D mouse atlas (rig=
ht) provided by Ma and colleagues (Neuroscience 2005). We first coregister =
the SPECT to an individual MRI (left), estimate only. Then we normalise the=
individual MRI to the atlas and apply the same transformation to the coreg=
istered SPECT. This results in truncation of the SPECT images to the field =
of view of the individual MRI (yellow lines), although the coregistered SPE=
CT has not been resliced to the MRI. Is there a way to avoid this truncatio=
n? I would very much appreciate your help.
With very best wishes,
Ralph.
---------------------------------------------
Ralph Buchert, PhD
Charit=E9 Universit=E4tsmedizin Berlin
Department of Nuclear Medicine
Charit=E9platz 1
10117 Berlin, Germany
Email: [log in to unmask]
Tel +49 30 450 627 059
Fax +49 30 450 527 912
---------------------------------------------
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<p class=3DMsoNormal><font size=3D2 face=3DArial><span style=3D'font-size:1=
0.0pt;
font-family:Arial'>Dear SPMers,<o:p></o:p></span></font></p>
<p class=3DMsoNormal><font size=3D2 face=3DArial><span style=3D'font-size:1=
0.0pt;
font-family:Arial'><o:p> </o:p></span></font></p>
<p class=3DMsoNormal><font size=3D2 face=3DArial><span lang=3DEN-US style=
=3D'font-size:
10.0pt;font-family:Arial'>we are using SPM 8 for stereotactical normalizati=
on
of mouse brain perfusion SPECT images (middle) into the reference space of =
the
3D mouse atlas (right) provided by Ma and colleagues (Neuroscience 2005). W=
e
first coregister the SPECT to an individual MRI (left), estimate only. Then=
we normalise
the individual MRI to the atlas and apply the same transformation to the
coregistered SPECT. This results in truncation of the SPECT images to the f=
ield
of view of the individual MRI (yellow lines), although the coregistered SPE=
CT
has not been resliced to the MRI. Is there a way to avoid this truncation? =
I
would very much appreciate your help.<o:p></o:p></span></font></p>
<p class=3DMsoNormal><font size=3D2 face=3DArial><span lang=3DEN-US style=
=3D'font-size:
10.0pt;font-family:Arial'><o:p> </o:p></span></font></p>
<p class=3DMsoNormal><font size=3D2 face=3DArial><span lang=3DEN-US style=
=3D'font-size:
10.0pt;font-family:Arial'>With very best wishes,<o:p></o:p></span></font></=
p>
<p class=3DMsoNormal><font size=3D2 face=3DArial><span lang=3DEN-US style=
=3D'font-size:
10.0pt;font-family:Arial'><o:p> </o:p></span></font></p>
<p class=3DMsoNormal><font size=3D2 face=3DArial><span lang=3DEN-US style=
=3D'font-size:
10.0pt;font-family:Arial'>Ralph.<o:p></o:p></span></font></p>
<p class=3DMsoNormal><font size=3D2 face=3DArial><span lang=3DEN-US style=
=3D'font-size:
10.0pt;font-family:Arial'><o:p> </o:p></span></font></p>
<p class=3DMsoAutoSig><font size=3D2 face=3D"Times New Roman"><span style=
=3D'font-size:
10.0pt'>---------------------------------------------<o:p></o:p></span></fo=
nt></p>
<p class=3DMsoAutoSig><font size=3D2 face=3D"Times New Roman"><span style=
=3D'font-size:
10.0pt'>Ralph Buchert, PhD<o:p></o:p></span></font></p>
<p class=3DMsoAutoSig><font size=3D2 face=3D"Times New Roman"><span style=
=3D'font-size:
10.0pt'>Charit=E9 Universit=E4tsmedizin Berlin<o:p></o:p></span></font></p>
<p class=3DMsoAutoSig><font size=3D2 face=3D"Times New Roman"><span lang=3D=
EN-US
style=3D'font-size:10.0pt'>Department of Nuclear Medicine<o:p></o:p></span>=
</font></p>
<p class=3DMsoAutoSig><font size=3D2 face=3D"Times New Roman"><span lang=3D=
EN-US
style=3D'font-size:10.0pt'>Charit=E9platz 1<o:p></o:p></span></font></p>
<p class=3DMsoAutoSig><font size=3D2 face=3D"Times New Roman"><span lang=3D=
EN-US
style=3D'font-size:10.0pt'>10117 <st1:place w:st=3D"on"><st1:City w:st=3D"o=
n">Berlin</st1:City>,
<st1:country-region w:st=3D"on">Germany</st1:country-region></st1:place><o=
:p></o:p></span></font></p>
<p class=3DMsoAutoSig><font size=3D2 face=3D"Times New Roman"><span lang=3D=
EN-US
style=3D'font-size:10.0pt'>Email: [log in to unmask]<o:p></o:p></span=
></font></p>
<p class=3DMsoAutoSig><font size=3D2 face=3D"Times New Roman"><span style=
=3D'font-size:
10.0pt'>Tel=A0 +49 30 450 627 059<o:p></o:p></span></font></p>
<p class=3DMsoAutoSig><font size=3D2 face=3D"Times New Roman"><span style=
=3D'font-size:
10.0pt'>Fax +49 30 450 527 912<o:p></o:p></span></font></p>
<p class=3DMsoAutoSig><font size=3D2 face=3D"Times New Roman"><span style=
=3D'font-size:
10.0pt'>---------------------------------------------<o:p></o:p></span></fo=
nt></p>
<p class=3DMsoAutoSig><font size=3D2 face=3D"Times New Roman"><span style=
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10.0pt'><o:p> </o:p></span></font></p>
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--_004_196D7E1E24668447984E319A6656DDB802ACB57434A2EXCHANGE21c_--
=========================================================================
Date: Thu, 5 May 2011 15:43:12 +0100
Reply-To: Soufiane Carde <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Soufiane Carde <[log in to unmask]>
Subject: VBM stat with 2 groups
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Hello SPMers,
I have 2 groups of 15 subjects for a VBM study and made the preprocessing=
.=20
Now I'd like to do the stats and I'm a little bit lost to covariate with =
age and sex.
How to put the vectors for sex (-1; 1?) and age (difference with the mea=
n?)=20
Is the order of the value the order of the subjects successively in the 2=
groups (the 16th value is the one for the 1st subject of the 2d group fo=
r example)?
Thank you in advance for your response.
Friendly
Soufiane Carde
=========================================================================
Date: Thu, 5 May 2011 15:49:01 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: truncation
Comments: To: "Buchert, Ralph" <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/related; boundary=20cf300fafbf5bb99204a2887919
Message-ID: <[log in to unmask]>
--20cf300fafbf5bb99204a2887919
Content-Type: multipart/alternative; boundary=20cf300fafbf5bb98f04a2887918
--20cf300fafbf5bb98f04a2887918
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
The truncation is usually desirable behaviour for spatially normalising
fMRI, but I guess it is not so useful here. If you use the same parameter
set, but spatially normalise the MRI separately from the SPECT, then the
restricted FOV of the MRI should not result in parts of your spatially
normalised SPECT being set to zero.
Note also that there should be a masking option somewhere among the options
for writing spatially normalised images. You could also try changing this.
Best regards,
-John
On 5 May 2011 15:34, Buchert, Ralph <[log in to unmask]> wrote:
> Dear SPMers,
>
>
>
> we are using SPM 8 for stereotactical normalization of mouse brain
> perfusion SPECT images (middle) into the reference space of the 3D mouse
> atlas (right) provided by Ma and colleagues (Neuroscience 2005). We first
> coregister the SPECT to an individual MRI (left), estimate only. Then we
> normalise the individual MRI to the atlas and apply the same transformati=
on
> to the coregistered SPECT. This results in truncation of the SPECT images=
to
> the field of view of the individual MRI (yellow lines), although the
> coregistered SPECT has not been resliced to the MRI. Is there a way to av=
oid
> this truncation? I would very much appreciate your help.
>
>
>
> With very best wishes,
>
>
>
> Ralph.
>
>
>
> ---------------------------------------------
>
> Ralph Buchert, PhD
>
> Charit=E9 Universit=E4tsmedizin Berlin
>
> Department of Nuclear Medicine
>
> Charit=E9platz 1
>
> 10117 Berlin, Germany
>
> Email: [log in to unmask]
>
> Tel +49 30 450 627 059
>
> Fax +49 30 450 527 912
>
> ---------------------------------------------
>
>
>
>
>
>
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The truncation is usually desirable behaviour for spatially normalising fMR=
I, but I guess it is not so useful here.=A0 If you use the same parameter s=
et, but spatially normalise the MRI separately from the SPECT, then the res=
tricted FOV of the MRI should not result in parts of your spatially normali=
sed SPECT being set to zero.<br>
<br>Note also that there should be a masking option somewhere among the opt=
ions for writing spatially normalised images.=A0 You could also try changin=
g this.<br><br>Best regards,<br>-John<br><br><div class=3D"gmail_quote">On =
5 May 2011 15:34, Buchert, Ralph <span dir=3D"ltr"><<a href=3D"mailto:Ra=
[log in to unmask]">[log in to unmask]</a>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; borde=
r-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
<div link=3D"blue" vlink=3D"purple" lang=3D"DE">
<div>
<p class=3D"MsoNormal"><font size=3D"2" face=3D"Arial"><span style=3D"font-=
size: 10pt; font-family: Arial;">Dear SPMers,</span></font></p>
<p class=3D"MsoNormal"><font size=3D"2" face=3D"Arial"><span style=3D"font-=
size: 10pt; font-family: Arial;">=A0</span></font></p>
<p class=3D"MsoNormal"><font size=3D"2" face=3D"Arial"><span style=3D"font-=
size: 10pt; font-family: Arial;" lang=3D"EN-US">we are using SPM 8 for ster=
eotactical normalization
of mouse brain perfusion SPECT images (middle) into the reference space of =
the
3D mouse atlas (right) provided by Ma and colleagues (Neuroscience 2005). W=
e
first coregister the SPECT to an individual MRI (left), estimate only. Then=
we normalise
the individual MRI to the atlas and apply the same transformation to the
coregistered SPECT. This results in truncation of the SPECT images to the f=
ield
of view of the individual MRI (yellow lines), although the coregistered SPE=
CT
has not been resliced to the MRI. Is there a way to avoid this truncation? =
I
would very much appreciate your help.</span></font></p>
<p class=3D"MsoNormal"><font size=3D"2" face=3D"Arial"><span style=3D"font-=
size: 10pt; font-family: Arial;" lang=3D"EN-US">=A0</span></font></p>
<p class=3D"MsoNormal"><font size=3D"2" face=3D"Arial"><span style=3D"font-=
size: 10pt; font-family: Arial;" lang=3D"EN-US">With very best wishes,</spa=
n></font></p>
<p class=3D"MsoNormal"><font size=3D"2" face=3D"Arial"><span style=3D"font-=
size: 10pt; font-family: Arial;" lang=3D"EN-US">=A0</span></font></p>
<p class=3D"MsoNormal"><font size=3D"2" face=3D"Arial"><span style=3D"font-=
size: 10pt; font-family: Arial;" lang=3D"EN-US">Ralph.</span></font></p>
<p class=3D"MsoNormal"><font size=3D"2" face=3D"Arial"><span style=3D"font-=
size: 10pt; font-family: Arial;" lang=3D"EN-US">=A0</span></font></p>
<p><font size=3D"2" face=3D"Times New Roman"><span style=3D"font-size: 10pt=
;">---------------------------------------------</span></font></p>
<p><font size=3D"2" face=3D"Times New Roman"><span style=3D"font-size: 10pt=
;">Ralph Buchert, PhD</span></font></p>
<p><font size=3D"2" face=3D"Times New Roman"><span style=3D"font-size: 10pt=
;">Charit=E9 Universit=E4tsmedizin Berlin</span></font></p>
<p><font size=3D"2" face=3D"Times New Roman"><span style=3D"font-size: 10pt=
;" lang=3D"EN-US">Department of Nuclear Medicine</span></font></p>
<p><font size=3D"2" face=3D"Times New Roman"><span style=3D"font-size: 10pt=
;" lang=3D"EN-US">Charit=E9platz 1</span></font></p>
<p><font size=3D"2" face=3D"Times New Roman"><span style=3D"font-size: 10pt=
;" lang=3D"EN-US">10117 Berlin,
Germany</span></font></p>
<p><font size=3D"2" face=3D"Times New Roman"><span style=3D"font-size: 10pt=
;" lang=3D"EN-US">Email: <a href=3D"mailto:[log in to unmask]" target=
=3D"_blank">[log in to unmask]</a></span></font></p>
<p><font size=3D"2" face=3D"Times New Roman"><span style=3D"font-size: 10pt=
;">Tel=A0 +49 30 450 627 059</span></font></p>
<p><font size=3D"2" face=3D"Times New Roman"><span style=3D"font-size: 10pt=
;">Fax +49 30 450 527 912</span></font></p>
<p><font size=3D"2" face=3D"Times New Roman"><span style=3D"font-size: 10pt=
;">---------------------------------------------</span></font></p>
<p><font size=3D"2" face=3D"Times New Roman"><span style=3D"font-size: 10pt=
;">=A0</span></font></p>
<p class=3D"MsoNormal"><font size=3D"3" face=3D"Times New Roman"><span styl=
e=3D"font-size: 12pt;">=A0</span></font></p>
<p class=3D"MsoNormal"><font size=3D"3" face=3D"Times New Roman"><span styl=
e=3D"font-size: 12pt;"><img src=3D"cid:image002.jpg@01CC0B41.E4F65370" widt=
h=3D"1014" height=3D"408"></span></font></p>
</div>
</div>
</blockquote></div><br>
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--20cf300fafbf5bb99204a2887919--
=========================================================================
Date: Thu, 5 May 2011 15:54:58 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: Repeated Coregistration Error
Comments: To: "shiye.chen" <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Are you running SPM5 from the user interface, or via some script
files? What values are you using for 'Histogram Smoothing'?
Best regards,
-John
On 5 May 2011 14:34, shiye.chen <[log in to unmask]> wrote:
> Dear SPM list,
>
>
>
> Sorry to interrupt, but I was encountered this repeated coregistration
> error, which I cannot fix.
>
>
>
> Running "Coreg: Estimate & Reslice"
>
>
>
> Error running job: Attempted to access fwhm(2); index out of bounds because
> numel(fwhm)=1.
>
> In file "D:\spm5\spm_coreg.m" (v1007), function "optfun" at line 160.
>
> In file "D:\spm5\spm_coreg.m" (v1007), function "spm_coreg" at line 82.
>
> In file "D:\spm5\spm_powell.m" (v691), function "spm_powell" at line 27.
>
> In file "D:\spm5\spm_coreg.m" (v1007), function "spm_coreg" at line 134.
>
> In file "D:\spm5\spm_config_coreg.m" (v1032), function "estimate_reslice" at
> line 322.
>
> --------------------------
>
> Done.
>
>
>
> Could someone help me on this?
>
>
>
> Thanks very much!
>
>
=========================================================================
Date: Thu, 5 May 2011 16:49:45 +0100
Reply-To: Elsa B <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Elsa B <[log in to unmask]>
Subject: FWE: Bonferroni or RFT?
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear SPM-experts,
I am analyzing data in SPM8 and I was wondering whether the FWE corrected=
p-value involves Bonferroni corrected values or is it based on something=
else? I have read some very old related posts related to this topic here=
and I am a bit confused. Is the FWE p value based on random field theory=
, Bonferroni or does it use both Bonferroni and RFT methods?=20
How is the FWE corrected p value calculated in SPM 8?=20
Many thanks!
=========================================================================
Date: Thu, 5 May 2011 12:18:35 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: PPI question
Comments: To: Torben Ellegaard Lund <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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I haven't thoroughly tested this, but if you set iG to be the movement
parameters columns. Then still adjust for the null space (motion
parameters). You will get the best of both. If you don't adjust for
the null space, then movement will contribute to the deconvolution. In
summary, if you have iG be the motion parameter columns AND adjust for
the null-space (motion columns), then:
Y will have the effect of motion removed. Yc (removal of motion twice)
will be minimally different since Y is orthogonal to the motion
parameters. So, you have motion removed from both the autocorrelation
estimate, the Y for deconvolution, and Yc.
Best Regards, Donald McLaren
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General
Hospital and Harvard Medical School
Office: (773) 406-2464
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
This e-mail contains CONFIDENTIAL INFORMATION which may contain
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On Thu, May 5, 2011 at 9:48 AM, Torben Ellegaard Lund
<[log in to unmask]> wrote:
> Hi Alex
>
>
> Den Uge:18 05/05/2011 kl. 14.15 skrev Alex Fornito:
>
>> Hi Torben,
>> Sorry, I just wanted to clarify: do you mean leaving SPM.xX.iG empty? It
>> seems like this is done by default by spm_fmri_design (?)
>
> leaving it empty will include all user defined regressors in the effects =
of interest F-test which determines the mask where the serial correlation i=
s estimated. I think it would make sense if the motion regressors did not g=
o into this test, just like the DCS HP-filter does not go into the F-contra=
st.
>
>> Are you suggesting manually entering motion parameters into this field?
>
> Yes, or their indices that is. It should be done after specification, but=
before model estimation. You can check if SPM recognized your changes by l=
ooking at the automatically generated effects of interest F-contrast.
>
>
> Best
> Torben
>
>
>
>
>>
>> On 05/05/2011 18:16, "Torben Ellegaard Lund" <[log in to unmask]> wrote:
>>
>>> Just as a kind reminder. Leaving SPM.xX.iG is a bit unfortunate, becaus=
e
>>> voxels where motion artefacts are significant then constitutes a large =
part of
>>> the F-test derived mask used to estimate serial correlations. If you ar=
e picky
>>> about this you can change it yourselves, but it is not as easy as it sh=
ould
>>> be.
>>>
>>>
>>> Best
>>> Torben
>>>
>>>
>>>
>>> Den Uge:18 05/05/2011 kl. 05.03 skrev Alex Fornito:
>>>
>>>> Ahh, I see. I was assuming that SPM.xX.iG contained the indices to the
>>>> nuisance covariates in the design matrix, but you're right - spm_fMRI_=
design
>>>> leaves it empty.
>>>>
>>>> Thanks for your help!
>>>> A
>>>>
>>>>
>>>> On 05/05/2011 12:54, "MCLAREN, Donald" <[log in to unmask]> wrot=
e:
>>>>
>>>>> I agree that nuisance covariates, such as motion should be removed;
>>>>> however, motion covariates are not generally stored in X0 in my
>>>>> reading of the SPM code (spm_fMRI_design, spm_regions). They should b=
e
>>>>> removed in the spm_regions filtering based on the null-space of the
>>>>> contrast.
>>>>>
>>>>> As for the motion parameters being in the model, if they were in the
>>>>> standard analysis, they should be included in the PPI analysis. My
>>>>> gPPI code will do this automatically as well.
>>>>>
>>>>> X0 is made of SPM.xX.iB (block effects -- so removing the mean) and
>>>>> SPM.xX.iG (nuisance variable that is empty as far as I can tell (line
>>>>> 369 of spm_fMRI_design)) and the high-pass filtering (K.X0).
>>>>>
>>>>> Best Regards, Donald McLaren
>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>> D.G. McLaren, Ph.D.
>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>> Hospital and Harvard Medical School
>>>>> Office: (773) 406-2464
>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>>>>> and which is intended only for the use of the individual or entity
>>>>> named above. If the reader of the e-mail is not the intended recipien=
t
>>>>> or the employee or agent responsible for delivering it to the intende=
d
>>>>> recipient, you are hereby notified that you are in possession of
>>>>> confidential and privileged information. Any unauthorized use,
>>>>> disclosure, copying or the taking of any action in reliance on the
>>>>> contents of this information is strictly prohibited and may be
>>>>> unlawful. If you have received this e-mail unintentionally, please
>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>> email.
>>>>>
>>>>>
>>>>>
>>>>> On Wed, May 4, 2011 at 10:16 PM, Alex Fornito <[log in to unmask]
u>
>>>>> wrote:
>>>>>> Hi Donald,
>>>>>> Thanks for your response. When you say "you don't want
>>>>>> to filter out anything related to neural activity", I'm presuming th=
at you
>>>>>> are referring to the deconvolved neural signal?
>>>>>>
>>>>>> If so, that makes sense. However, X0 also contains user-specified nu=
isance
>>>>>> covariates. I would have thought it would make sense to remove those=
,
>>>>>> depending on what they were (e.g., movement parameters)? I guess the=
y can
>>>>>> always be entered into the PPI regression model...
>>>>>>
>>>>>>
>>>>>> On 05/05/2011 11:57, "MCLAREN, Donald" <[log in to unmask]> wr=
ote:
>>>>>>
>>>>>>> I could be wrong, Karl or Darren please correct me if I am.
>>>>>>>
>>>>>>> X0 is composed of the high-pass filter and constant term. Thus, you
>>>>>>> want to filter these out of the Yc regressor. However, you don't wa=
nt
>>>>>>> to filter out anything related to neural activity, so you wouldn't
>>>>>>> want to filter your signal and then predict the neural activity fro=
m
>>>>>>> the filtered signal, especially filtering frequencies.
>>>>>>>
>>>>>>> Best Regards, Donald McLaren
>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>> D.G. McLaren, Ph.D.
>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>> Hospital and Harvard Medical School
>>>>>>> Office: (773) 406-2464
>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>>>>>>> and which is intended only for the use of the individual or entity
>>>>>>> named above. If the reader of the e-mail is not the intended recipi=
ent
>>>>>>> or the employee or agent responsible for delivering it to the inten=
ded
>>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>> disclosure, copying or the taking of any action in reliance on the
>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>> unlawful. If you have received this e-mail unintentionally, please
>>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>>> email.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> On Sat, Apr 30, 2011 at 8:03 PM, Alex Fornito <[log in to unmask]
.au>
>>>>>>> wrote:
>>>>>>>> Hi Donald,
>>>>>>>> As far as I can tell, spm_regions filters and whitens the VOI time
>>>>>>>> series,
>>>>>>>> and adjusts for the null space of the contrast if an adjustment is
>>>>>>>> specified
>>>>>>>> in xY.Ic. It defines the confound matrix, X0, but does not correct=
for
>>>>>>>> it.
>>>>>>>> The following line in spm_peb_ppi corrects for the confounds.
>>>>>>>>
>>>>>>>> Yc =A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>
>>>>>>>> So the above correction does seem to be doing something different =
to
>>>>>>>> spm_regions. I'm wondering why the uncorrected data, Y, is used wh=
en
>>>>>>>> generating the ppi interaction term, while the corrected data Yc i=
s to be
>>>>>>>> used as a covariate of no interest in the PPI model. I would has t=
hought
>>>>>>>> that Yc should be used to generate the ppi interaction term as wel=
l.
>>>>>>>>
>>>>>>>> In my data, my X0 is a 195 x 7 matrix (I have 195 volumes per sess=
ion).
>>>>>>>>
>>>>>>>> Regards,
>>>>>>>> Alex
>>>>>>>>
>>>>>>>>
>>>>>>>> On 30/04/2011 02:22, "MCLAREN, Donald" <[log in to unmask]> =
wrote:
>>>>>>>>
>>>>>>>>> I'm actually travelling at the moment. However, I know Y has alre=
ady
>>>>>>>>> been adjusted as part of the VOI processing.
>>>>>>>>>
>>>>>>>>> Can you check what X0 looks like?
>>>>>>>>>
>>>>>>>>> Best Regards, Donald McLaren
>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>>>> Hospital and Harvard Medical School
>>>>>>>>> Office: (773) 406-2464
>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEG=
ED
>>>>>>>>> and which is intended only for the use of the individual or entit=
y
>>>>>>>>> named above. If the reader of the e-mail is not the intended reci=
pient
>>>>>>>>> or the employee or agent responsible for delivering it to the int=
ended
>>>>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>>> disclosure, copying or the taking of any action in reliance on th=
e
>>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>>> unlawful. If you have received this e-mail unintentionally, pleas=
e
>>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>>>>> email.
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> On Fri, Apr 29, 2011 at 2:55 AM, Alex Fornito <[log in to unmask]
du.au>
>>>>>>>>> wrote:
>>>>>>>>>> Hi all,
>>>>>>>>>> I have a question concerning the code used to implement a PPI an=
alysis.
>>>>>>>>>>
>>>>>>>>>> In the spm_peb_ppi.m function packaged with SPM8, lines 329-332 =
remove
>>>>>>>>>> confounds from the input seed region=92s time course:
>>>>>>>>>>
>>>>>>>>>> % Remove confounds and save Y in ouput structure
>>>>>>>>>> %---------------------------------------------------------------=
-------
>>>>>>>>>> --
>>>>>>>>>> --
>>>>>>>>>> Yc =A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>>>
>>>>>>>>>> PPI.Y is then to be used as a covariate of no interest when buil=
ding
>>>>>>>>>> the
>>>>>>>>>> PPI
>>>>>>>>>> regression model. However, on line 488, it is the uncorrected se=
ed time
>>>>>>>>>> course, Y, that is input to the deconvolution routine and used t=
o
>>>>>>>>>> generate
>>>>>>>>>> the ppi term:
>>>>>>>>>>
>>>>>>>>>> =A0C =A0=3D spm_PEB(Y,P);
>>>>>>>>>> =A0 =A0xn =3D xb*C{2}.E(1:N);
>>>>>>>>>> =A0 =A0xn =3D spm_detrend(xn);
>>>>>>>>>>
>>>>>>>>>> =A0% Setup psychological variable from inputs and contast weight=
s
>>>>>>>>>>
>>>>>>>>>> %---------------------------------------------------------------=
-------
>>>>>>>>>> =A0PSY =3D zeros(N*NT,1);
>>>>>>>>>> =A0for i =3D 1:size(U.u,2)
>>>>>>>>>> =A0 =A0 =A0PSY =3D PSY + full(U.u(:,i)*U.w(:,i));
>>>>>>>>>> =A0end
>>>>>>>>>> =A0% PSY =3D spm_detrend(PSY); =A0<- removed centering of psych =
variable
>>>>>>>>>> =A0% prior to multiplication with xn. Based on discussion with K=
arl
>>>>>>>>>> =A0% and Donald McLaren.
>>>>>>>>>>
>>>>>>>>>> % Multiply psychological variable by neural signal
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> %---------------------------------------------------------------=
-------
>>>>>>>>>> =A0 PSYxn =3D PSY.*xn;
>>>>>>>>>>
>>>>>>>>>> Is there any specific reason why Y, rather than Yc(:,1), is used=
to
>>>>>>>>>> compute
>>>>>>>>>> PSYxn? I thought Yc might be more appropriate (?).
>>>>>>>>>> Thanks for your help,
>>>>>>>>>> Alex
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> ------------------------------------------
>>>>>>>>>>
>>>>>>>>>> Alex Fornito
>>>>>>>>>> Research Fellow
>>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>>> University of Melbourne
>>>>>>>>>> National Neuroscience Facility
>>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>>> 161 Barry St
>>>>>>>>>> Carlton South 3053
>>>>>>>>>> Victoria, Australia
>>>>>>>>>>
>>>>>>>>>> Email: [log in to unmask]
>>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> ------------------------------------------
>>>>>>>>
>>>>>>>> Alex Fornito
>>>>>>>> Research Fellow
>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>> University of Melbourne
>>>>>>>> National Neuroscience Facility
>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>> 161 Barry St
>>>>>>>> Carlton South 3053
>>>>>>>> Victoria, Australia
>>>>>>>>
>>>>>>>> Email: [log in to unmask]
>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>>
>>>>>> ------------------------------------------
>>>>>>
>>>>>> Alex Fornito
>>>>>> Research Fellow
>>>>>> Melbourne Neuropsychiatry Centre
>>>>>> University of Melbourne
>>>>>> National Neuroscience Facility
>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>> 161 Barry St
>>>>>> Carlton South 3053
>>>>>> Victoria, Australia
>>>>>>
>>>>>> Email: [log in to unmask]
>>>>>> Phone: +61 3 8344 1876
>>>>>> Fax: +61 3 9348 0469
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>
>>>>
>>>> ------------------------------------------
>>>>
>>>> Alex Fornito
>>>> Research Fellow
>>>> Melbourne Neuropsychiatry Centre
>>>> University of Melbourne
>>>> National Neuroscience Facility
>>>> Levels 1 & 2, Alan Gilbert Building
>>>> 161 Barry St
>>>> Carlton South 3053
>>>> Victoria, Australia
>>>>
>>>> Email: [log in to unmask]
>>>> Phone: +61 3 8344 1876
>>>> Fax: +61 3 9348 0469
>>>
>>>
>>
>>
>> ------------------------------------------
>>
>> Alex Fornito
>> Research Fellow
>> Melbourne Neuropsychiatry Centre
>> University of Melbourne
>> National Neuroscience Facility
>> Levels 1 & 2, Alan Gilbert Building
>> 161 Barry St
>> Carlton South 3053
>> Victoria, Australia
>>
>> Email: [log in to unmask]
>> Phone: +61 3 8344 1876
>> Fax: +61 3 9348 0469
>>
>>
>>
>
=========================================================================
Date: Thu, 5 May 2011 12:44:24 -0400
Reply-To: Jonathan Peelle <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jonathan Peelle <[log in to unmask]>
Subject: Re: VBM stat with 2 groups
Comments: To: Soufiane Carde <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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Dear Soufiane,
> I have 2 groups of 15 subjects for a VBM study and made the preprocessing=
.
> Now I'd like to do the stats and I'm a little bit lost to covariate with =
age and sex.
> How to put the vectors for sex (-1; 1?) and =A0age (difference with the m=
ean?)
> Is the order of the value the order of the subjects successively in the 2=
groups (the 16th value is the one for the 1st subject of the 2d group for =
example)?
It sounds as if you want to compare tissue volume in two groups while
controlling for age and sex differences. To start with, let's say you
just want to control for age differences. In this case you would
specify a 2-sample t-test and add a covariate for age; this will give
you 3 columns in your design matrix (group 1, group 2, age).
In this case, as with any covariate, you need one value per image, and
these values are in the same order as the images you select. So in
this case, you've selected 30 images (15 group 1, 15 group 2). You
are exactly right that the 16th value in the age covariate should be
the age for the 16th image =3D first subject in group 2. You will want
to mean center the covariate (which is the default in SPM8).
To test the difference between group 1 and group 2, you could then do
a t-test of:
[1 -1 0] (group 1 > group 2)
or
[-1 1 0] (group 2 > group 1)
You could look at the effect of age with [0 0 1] or [0 0 -1].
In the case where you want to control for sex differences, one common
approach is to model males and females separately within each group,
which would require a slightly different model. However, since you
only have 15 subjects per group, I don't know that this will be
particularly productive.
A general comment with regard to covariates is that if your groups are
fairly evenly matched, then including an additional covariate will
reduce the error (which is good) but probably not change the overall
result. If your groups are not particularly well balanced, then your
group difference is confounded with these other factors, and including
them as covariates cannot undo this.
Hope this helps!
Best regards,
Jonathan
--=20
Dr. Jonathan Peelle
Department of Neurology
University of Pennsylvania
3 West Gates
3400 Spruce Street
Philadelphia, PA 19104
USA
http://jonathanpeelle.net/
=========================================================================
Date: Thu, 5 May 2011 12:59:06 -0400
Reply-To: Jonathan Peelle <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jonathan Peelle <[log in to unmask]>
Subject: Re: FWE: Bonferroni or RFT?
Comments: To: Elsa B <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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Dear Elsa,
> I am analyzing data in SPM8 and I was wondering whether the FWE corrected=
p-value involves Bonferroni corrected values or is it based on something e=
lse? I have read some very old related posts related to this topic here and=
I am a bit confused. Is the FWE p value based on random field theory, Bonf=
erroni or does it use both Bonferroni and RFT methods?
> How is the FWE corrected p value calculated in SPM 8?
For voxelwise correction, SPM uses random field theory to calculate a
corrected p value. This is generally more lenient than the Bonferroni
correction because the topology of the data are taken into account
(the smoothness; i.e. that nearby voxels are not independent). SPM
also calculates the Bonferroni value and reports the value (random
field theory or Bonferroni-corrected) which is more lenient (which is
usually the random field corrected one). See spm_P.m.
Hope this helps!
Best regards,
Jonathan
--=20
Dr. Jonathan Peelle
Department of Neurology
University of Pennsylvania
3 West Gates
3400 Spruce Street
Philadelphia, PA 19104
USA
http://jonathanpeelle.net/
=========================================================================
Date: Thu, 5 May 2011 19:41:17 +0200
Reply-To: swann pichon <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: swann pichon <[log in to unmask]>
Subject: Changing ANOVA design matrix according to the SPM8 version
Comments: cc: Judith DOMINGUEZ BORRAS <[log in to unmask]>
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--90e6ba53af32975f9a04a28ae2fe
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--90e6ba53af32975f9104a28ae2fc
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Dear SPMers,
Performing a standard 1-way ANOVA within-subjects using SPM8, the matrix is
weighted very differently depending on whether the model is estimated using
SPM8 v3684 or v4010. Both models below have been generated using the same
batch job.
Any idea of what has changed between the two versions ?
Thanks
Swann
Left:
v3684
Right: v4010
[image: Design_matrix_spm8_v3684.jpg][image: Design_matrix_spm8_v4010.jpg]
--
Swann Pichon, PhD
Laboratory for Behavioral Neurology and Imaging of Cognition
Department of Neuroscience, University Medical Center
1 rue Michel-Servet, 1211 GENEVA 4, Switzerland
Tel: +41 (0)22 379 5979
Fax: +41 (0)22 379 5402
Gsm: +33 (0)6 26 43 83 61
http://labnic.unige.ch/
--90e6ba53af32975f9104a28ae2fc
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Dear SPMers,<br><br>Performing a standard 1-way ANOVA within-subjects using=
SPM8, the matrix is weighted very differently depending on whether the mod=
el is estimated using SPM8 v3684 or v4010. Both models below have been gene=
rated using the same batch job.<br>
<br>Any idea of what has changed between the two versions ?<br><br>Thanks<b=
r><br>Swann<br><br>Left: v3684=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=
=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=
=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=
=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=
=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=
=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Right: v401=
0<br><img title=3D"Design_matrix_spm8_v3684.jpg" alt=3D"Design_matrix_spm8_=
v3684.jpg" src=3D"cid:ii_12fc0c4c106a43c7" width=3D"291" height=3D"420"><im=
g title=3D"Design_matrix_spm8_v4010.jpg" alt=3D"Design_matrix_spm8_v4010.jp=
g" src=3D"cid:ii_12fc0c52a5d298ee" width=3D"291" height=3D"420"><br clear=
=3D"all">
<br>-- <br><span style=3D"color:rgb(102, 102, 102)"></span><span style=3D"c=
olor:rgb(0, 0, 0)">Swann Pichon, PhD </span><br style=3D"color:rgb(0, 0, 0)=
"><span style=3D"color:rgb(0, 0, 0)">
Laboratory for Behavioral Neurology and Imaging of Cognition</span><br styl=
e=3D"color:rgb(0, 0, 0)"><span style=3D"color:rgb(0, 0, 0)">
Department of Neuroscience, University Medical Center</span><br style=3D"co=
lor:rgb(0, 0, 0)"><span style=3D"color:rgb(0, 0, 0)">
1 rue Michel-Servet, 1211 GENEVA 4, Switzerland</span><br style=3D"color:rg=
b(0, 0, 0)"><span style=3D"color:rgb(0, 0, 0)">
Tel: +41 (0)22 379 5979</span><br style=3D"color:rgb(0, 0, 0)"><span style=
=3D"color:rgb(0, 0, 0)">
Fax: +41 (0)22 379 5402</span><br style=3D"color:rgb(0, 0, 0)"><span style=
=3D"color:rgb(0, 0, 0)">
Gsm: +33 (0)6 26 43 83 61</span><br style=3D"color:rgb(102, 102, 102)">
<a style=3D"color:rgb(102, 102, 102)" href=3D"http://labnic.unige.ch/" targ=
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--90e6ba53af32975f9a04a28ae2fe--
=========================================================================
Date: Thu, 5 May 2011 10:57:40 -0700
Reply-To: Bob Spunt <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Bob Spunt <[log in to unmask]>
Subject: Deletion of Voxels in Group Analyses
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=bcaec5215bc701ac2304a28b1cd6
Message-ID: <[log in to unmask]>
--bcaec5215bc701ac2304a28b1cd6
Content-Type: text/plain; charset=ISO-8859-1
Hi, I searched the listserv and failed to find answers to this question.
From what I understand, during second-level estimation (e.g., one-sample
t-test) SPM performs the test only for voxels in which ALL subjects have
data. In areas of the brain in which signal quality is highly variable from
subject-to-subject (e.g., high susceptibility areas such as ventral frontal
and temporal), this procedure is quite problematic, especially for large
samples. Has any one customized the SPM algorithm to bypass the all-or-none
exclusion procedure? I imagine this would require also producing a
degrees-of-freedom image (e.g., to use when reporting statistics).
Any tips would be much appreciated. Thanks in advance.
Bob Spunt
Doctoral Student
Department of Psychology
University of California, Los Angeles
--bcaec5215bc701ac2304a28b1cd6
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Hi, I searched the listserv and failed to find answers to this question.=A0=
<div><br></div><div>From what I understand, during second-level estimation =
(e.g., one-sample t-test) SPM performs the test only for voxels in which AL=
L subjects have data. In areas of the brain in which signal quality is high=
ly variable from subject-to-subject (e.g., high susceptibility areas such a=
s ventral frontal and temporal), this procedure is quite problematic, espec=
ially for large samples. Has any one customized the SPM algorithm to bypass=
the all-or-none exclusion procedure? I imagine this would require also pro=
ducing a degrees-of-freedom image (e.g., to use when reporting statistics).=
=A0<div>
<br></div><div>Any tips would be much appreciated. Thanks in advance.=A0</d=
iv><div><br></div><div><div><div><div><div><div><div>Bob Spunt<br>Doctoral =
Student<br>Department of Psychology<br>University of California, Los Angele=
s<br>
</div></div></div></div></div></div></div></div>
--bcaec5215bc701ac2304a28b1cd6--
=========================================================================
Date: Thu, 5 May 2011 19:06:08 +0100
Reply-To: Nancy Dennis <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Nancy Dennis <[log in to unmask]>
Subject: Research Assistant / Lab Manager position - Penn State
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
The Cognitive Aging and Neuroimaging (CAN) Lab at Penn State is hiring a =
full time Human Research Technologist (Research Assistant/Lab Manager). =
The lab employs both behavioral and neuroimaging methods, including diffu=
sion tensor imaging (DTI) and functional MRI (fMRI) to explore the intera=
ction of cognitive and neural processes involved in cognitive control and=
episodic memory (including item memory, false memories & source memories=
). Responsibilities will include, but are not limited to, the recruitment=
of both young and older research participants, maintaining the participa=
nt database, behavioral testing and fMRI scanning, fMRI data processing a=
nd data analysis.=20
=20
Typically requires an Associate=E2=80=99s Degree or higher (B.S. or B.A. =
preferred) preferably in psychology, neuroscience, computer science, biom=
edical engineering, or related fields plus one year of related experience=
or an equivalent combination of education and experience. The successf=
ul candidate should also have excellent interpersonal skills. Experience =
with programming skills (e.g., MATLAB), and analysis of fMRI data (e.g., =
SPM8) and other administrative skills (e.g., network administration) is a=
plus.=20
Scanning will take place on a Siemen=E2=80=99s Magnetom Trio 3T scanner l=
ocated at the Social and Life and Engineering Sciences Imaging Center (SL=
EIC) on the Penn State campus (http://www.imaging.psu.edu/).=20
Salary will be commensurate with experience. This is a fixed-term appoint=
ment funded for one year from date of hire with possibility of re-funding=
. To apply, send resume, cover letter, and the names/contact information=
of three professional references to Dr. Nancy Dennis at [log in to unmask] =
Review of applications will begin immediately and continue until the job =
is filled. Information on the CANLab can be found at http://canlab.psych=
.psu.edu.=20
=========================================================================
Date: Thu, 5 May 2011 14:33:51 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Deletion of Voxels in Group Analyses
Comments: To: Bob Spunt <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
We are currently working on this issue. It involves computing maps for
every combination of subjects.
On Thursday, May 5, 2011, Bob Spunt <[log in to unmask]> wrote:
> Hi, I searched the listserv and failed to find answers to this question.
> From what I understand, during second-level estimation (e.g., one-sample =
t-test) SPM performs the test only for voxels in which ALL subjects have da=
ta. In areas of the brain in which signal quality is highly variable from s=
ubject-to-subject (e.g., high susceptibility areas such as ventral frontal =
and temporal), this procedure is quite problematic, especially for large sa=
mples. Has any one customized the SPM algorithm to bypass the all-or-none e=
xclusion procedure? I imagine this would require also producing a degrees-o=
f-freedom image (e.g., to use when reporting statistics).
>
> Any tips would be much appreciated. Thanks in advance.
> Bob Spunt
> Doctoral Student
> Department of Psychology
> University of California, Los Angeles
>
>
--=20
Best Regards, Donald McLaren
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital an=
d
Harvard Medical School
Office: (773) 406-2464
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
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intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773=
)
406-2464 or email.
=========================================================================
Date: Thu, 5 May 2011 14:42:35 -0400
Reply-To: Jonathan Peelle <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jonathan Peelle <[log in to unmask]>
Subject: Re: Deletion of Voxels in Group Analyses
Comments: To: Bob Spunt <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Dear Bob,
> From what I understand, during second-level estimation (e.g., one-sample
> t-test) SPM performs the test only for voxels in which ALL subjects have
> data. In areas of the brain in which signal quality is highly variable from
> subject-to-subject (e.g., high susceptibility areas such as ventral frontal
> and temporal), this procedure is quite problematic, especially for large
> samples. Has any one customized the SPM algorithm to bypass the all-or-none
> exclusion procedure? I imagine this would require also producing a
> degrees-of-freedom image (e.g., to use when reporting statistics).
I'm not aware of anyone who has dealt with this, although some folks
(like Donald) are working on solving this in an elegant fashion.
In the meantime, I imagine you could get around this by adjusting the
threshold SPM uses on the 1st level to be less restrictive to the
voxels it includes in the analysis; see, for example:
https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1104&L=SPM&P=R65987
If there are subjects for whom you don't think you have useful data,
you could include additional regressors in your second level design to
remove their contribution, which should also appropriately adjust the
degrees of freedom (although this would obviously get tricky if it
varied across voxels/regions that you are interested in). If there
are specific areas you care about, you could also extract the values
and do statistics outside of SPM, which may offer you some additional
flexibility in how you model things.
Best regards,
Jonathan
--
Dr. Jonathan Peelle
Department of Neurology
University of Pennsylvania
3 West Gates
3400 Spruce Street
Philadelphia, PA 19104
USA
http://jonathanpeelle.net/
=========================================================================
Date: Thu, 5 May 2011 15:01:16 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Deletion of Voxels in Group Analyses
Comments: To: Jonathan Peelle <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Your posting made me think of another potential solution -- at least
in the short term. You could leverage the power of WFU_BPM.
You could create an ANOVA design, or 1 sample t-test. Then you could
create N imaging covariates. Where each covariate has all 0s except
for the the location that subject n has bad data. Then you could run
your analysis.
This would have the effect of excluding certain subjects from certain
voxels. Just make sure you don't have NaNs at the bad locations in
your DV. Converting them to -100 should work. These values would be
put into the imaging covariates as only 1 subject would have values in
each imaging covariate.
Best Regards, Donald McLaren
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General
Hospital and Harvard Medical School
Office: (773) 406-2464
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
This e-mail contains CONFIDENTIAL INFORMATION which may contain
PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
and which is intended only for the use of the individual or entity
named above. If the reader of the e-mail is not the intended recipient
or the employee or agent responsible for delivering it to the intended
recipient, you are hereby notified that you are in possession of
confidential and privileged information. Any unauthorized use,
disclosure, copying or the taking of any action in reliance on the
contents of this information is strictly prohibited and may be
unlawful. If you have received this e-mail unintentionally, please
immediately notify the sender via telephone at (773) 406-2464 or
email.
On Thu, May 5, 2011 at 2:42 PM, Jonathan Peelle <[log in to unmask]> wrote:
> Dear Bob,
>
>> From what I understand, during second-level estimation (e.g., one-sample
>> t-test) SPM performs the test only for voxels in which ALL subjects have
>> data. In areas of the brain in which signal quality is highly variable f=
rom
>> subject-to-subject (e.g., high susceptibility areas such as ventral fron=
tal
>> and temporal), this procedure is quite problematic, especially for large
>> samples. Has any one customized the SPM algorithm to bypass the all-or-n=
one
>> exclusion procedure? I imagine this would require also producing a
>> degrees-of-freedom image (e.g., to use when reporting statistics).
>
> I'm not aware of anyone who has dealt with this, although some folks
> (like Donald) are working on solving this in an elegant fashion.
>
> In the meantime, I imagine you could get around this by adjusting the
> threshold SPM uses on the 1st level to be less restrictive to the
> voxels it includes in the analysis; see, for example:
>
> https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=3Dind1104&L=3DSPM&P=3DR659=
87
>
> If there are subjects for whom you don't think you have useful data,
> you could include additional regressors in your second level design to
> remove their contribution, which should also appropriately adjust the
> degrees of freedom (although this would obviously get tricky if it
> varied across voxels/regions that you are interested in). =A0If there
> are specific areas you care about, you could also extract the values
> and do statistics outside of SPM, which may offer you some additional
> flexibility in how you model things.
>
> Best regards,
> Jonathan
>
> --
> Dr. Jonathan Peelle
> Department of Neurology
> University of Pennsylvania
> 3 West Gates
> 3400 Spruce Street
> Philadelphia, PA 19104
> USA
> http://jonathanpeelle.net/
>
=========================================================================
Date: Thu, 5 May 2011 13:05:29 -0600
Reply-To: Vince Calhoun <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vince Calhoun <[log in to unmask]>
Subject: Re: Deletion of Voxels in Group Analyses
Comments: To: Jonathan Peelle <[log in to unmask]>
In-Reply-To: <BANLkTi=QQXv+[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset="us-ascii"
Content-Transfer-Encoding: 7bit
Message-ID: <[log in to unmask]>
FYI...this issue was address by Tom Nichols et al a few years ago as
well....we implemented their solution in spm5 (happy to share, probably
would work fine for spm8 as well) and it works quite well. For details see
the poster below:
http://www.sph.umich.edu/~nichols/Docs/HBM2007-Huang-MissingData.pdf
> -----Original Message-----
> From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] On
> Behalf Of Jonathan Peelle
> Sent: Thursday, May 05, 2011 12:43 PM
> To: [log in to unmask]
> Subject: Re: [SPM] Deletion of Voxels in Group Analyses
>
> Dear Bob,
>
> > From what I understand, during second-level estimation (e.g., one-sample
> > t-test) SPM performs the test only for voxels in which ALL subjects have
> > data. In areas of the brain in which signal quality is highly variable
from
> > subject-to-subject (e.g., high susceptibility areas such as ventral
frontal
> > and temporal), this procedure is quite problematic, especially for large
> > samples. Has any one customized the SPM algorithm to bypass the
all-or-none
> > exclusion procedure? I imagine this would require also producing a
> > degrees-of-freedom image (e.g., to use when reporting statistics).
>
> I'm not aware of anyone who has dealt with this, although some folks
> (like Donald) are working on solving this in an elegant fashion.
>
> In the meantime, I imagine you could get around this by adjusting the
> threshold SPM uses on the 1st level to be less restrictive to the
> voxels it includes in the analysis; see, for example:
>
> https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1104&L=SPM&P=R65987
>
> If there are subjects for whom you don't think you have useful data,
> you could include additional regressors in your second level design to
> remove their contribution, which should also appropriately adjust the
> degrees of freedom (although this would obviously get tricky if it
> varied across voxels/regions that you are interested in). If there
> are specific areas you care about, you could also extract the values
> and do statistics outside of SPM, which may offer you some additional
> flexibility in how you model things.
>
> Best regards,
> Jonathan
>
> --
> Dr. Jonathan Peelle
> Department of Neurology
> University of Pennsylvania
> 3 West Gates
> 3400 Spruce Street
> Philadelphia, PA 19104
> USA
> http://jonathanpeelle.net/
=========================================================================
Date: Thu, 5 May 2011 16:13:21 -0400
Reply-To: Fred Sanders <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Fred Sanders <[log in to unmask]>
Subject: DCM with a task with 1 factor, 2 levels
MIME-Version: 1.0
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--00151743f88436faa604a28d0185
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I am trying to run DCM with a task that just has a single factor with 2
levels (i.e, OFF..ON...OFF...ON...). I am interested in the modulatory
effects (DCM.Ep.B) of the ON blocks,
When running a DCM, I can include just the ON blocks or both the ON and OFF
blocks. Given that I am interested in the modulatory effects (DCM.Ep.B) of
the ON blocks, then I should just include the ON blocks in my DCM models -
correct? In that case, are the OFF blocks used to specify the intrinsic
connectivity (DCM.Ep.A)? Alternatively, if I include both the ON and OFF
blocks in the model, what data are used to test the intrinsic connectivity?
Thanks!!
Fred
--00151743f88436faa604a28d0185
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I am trying to run DCM with a task that just has a single factor with 2 lev=
els (i.e, OFF..ON...OFF...ON...).=A0I am interested in the modulatory effec=
ts (DCM.Ep.B) of the ON blocks,<div><br></div><div>When running a DCM, I ca=
n include just the ON blocks or both the ON and OFF blocks. =A0Given that I=
am interested in the modulatory effects (DCM.Ep.B) of the ON blocks, then =
I should just include the ON blocks in my DCM models - correct? =A0In that =
case, are the OFF blocks used to specify the intrinsic connectivity (DCM.Ep=
.A)? =A0 Alternatively, if I include both the ON and OFF blocks in the mode=
l, what data are used to test the=A0intrinsic connectivity?</div>
<div><br></div><div><br></div><div>Thanks!!</div><div>Fred</div>
--00151743f88436faa604a28d0185--
=========================================================================
Date: Thu, 5 May 2011 16:49:11 -0400
Reply-To: Jadzia Jagiellowicz <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jadzia Jagiellowicz <[log in to unmask]>
Subject: Undefined command error
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Message-ID: <[log in to unmask]>
--0015177405fe67aee804a28d813a
Content-Type: text/plain; charset=ISO-8859-1
Hello All,
I'm getting an error
" Undefined command/function 'nifti'.
16 N = nifti(fname);"
every time I try to run command on a series of epi scans.
I've spent about 14 hours trying to figure this out by searching the web,
and can't quite understand the problem.
I think it is something to do with setting a path, or the directory the
files are in, but am not sure what.
The scans are in ANALYZE format and I'm using SPM5.
Do my scans need to be in "nifti" format before I can realign and estimate
them? I had done the realignment previouisly with ANALYZE files and it
worked.
I've ran the Matlab debugger on the error and get the following response:
Can anyone help me interpret what to do next and what is causing the error?
V = spm_vol_nifti(fname,n)
% Get header information for a NIFTI-1 image.
% FORMAT V = spm_vol_nifti(P)
% P - filename.
% n - volume id (a 1x2 array, e.g. [3,1])
% V - a structure containing the image volume information.
%____________________________________________________________________________
% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience
% John Ashburner
% $Id: spm_vol_nifti.m 112 2005-05-04 18:20:52Z john $
if nargin<2, n = [1 1]; end;
if ischar(n), n = str2num(n); end;
N = nifti(fname);
n = [n 1 1];
n = n(1:2);
dm = [N.dat.dim 1 1 1 1];
if any(n>dm(4:5)), V = []; return; end;
dt = struct(N.dat);
dt = double([dt.dtype dt.be]);
if isfield(N.extras,'mat') && size(N.extras.mat,3)>=n(1) &&
sum(sum(N.extras.mat(:,:,n(1))))~=0,
mat = N.extras.mat(:,:,n(1));
else
mat = N.mat;
end;
off = (n(1)-1+dm(4)*(n(2)-1))*ceil(spm_type(dt(1),'bits')*dm(1)*dm(2)/8)*dm(3)
+ N.dat.offset;
V = struct('fname', N.dat.fname,...
'dim', dm(1:3),...
'dt', dt,...
'pinfo', [N.dat.scl_slope N.dat.scl_inter off]',...
'mat', mat,...
'n', n,...
'descrip', N.descrip,...
'private',N);
Thanks in advance,
Jadzia
--
Jadzia Jagiellowicz
Doctoral Candidate
Psychology Department B-207
Stony Brook University,
Stony Brook, NY 11794-2500 USA
http://www.psychology.stonybrook.edu/aronlab-/
"The brave shall inherit the earth."
--0015177405fe67aee804a28d813a
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
<font color=3D"#0000ff" size=3D"2" face=3D"Monospaced"><font color=3D"#0000=
ff" size=3D"2" face=3D"Monospaced"><font color=3D"#0000ff" size=3D"2" face=
=3D"Monospaced">
<div>Hello All,</div>
<div>=A0</div>
<div>I'm getting an error</div>
<div>"=A0Undefined command/function 'nifti'.</div>
<div>16=A0 N=A0 =3D nifti(fname);"</div>
<div>=A0</div>
<div>every time I try to run command on a series of epi scans. </div>
<div>=A0</div>
<div>I've spent about 14 hours trying to figure this out by searching t=
he web, and can't quite understand the problem. </div>
<div>
<div>I think it is something to do with setting a path, or the directory th=
e files are in, but am not sure what.</div>The scans=A0are in ANALYZE forma=
t and I'm using SPM5.</div>
<div>Do my scans need to be in "nifti" format before I can realig=
n and estimate them? I had done the realignment previouisly with ANALYZE fi=
les and it worked. </div>
<div>=A0</div>
<div>=A0</div>
<div>I've ran the Matlab debugger on the error and get the following re=
sponse:</div>
<div>Can anyone help me interpret what to do next and what is causing the e=
rror?</div>
<div>=A0</div>
<div></div></font></font></font><font size=3D"2" face=3D"Monospaced"><font =
size=3D"2" face=3D"Monospaced">V =3D spm_vol_nifti(fname,n)</font></font><f=
ont color=3D"#228b22" size=3D"2" face=3D"Monospaced"><font color=3D"#228b22=
" size=3D"2" face=3D"Monospaced"><font color=3D"#228b22" size=3D"2" face=3D=
"Monospaced">
<p>% Get header information for a NIFTI-1 image.</p>
<p>% FORMAT V =3D spm_vol_nifti(P)</p>
<p>% P - filename.</p>
<p>% n - volume id (a 1x2 array, e.g. [3,1])</p>
<p>% V - a structure containing the image volume information.</p>
<p>%_______________________________________________________________________=
_____</p>
<p>% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience</p>
<p></p>
<p>% John Ashburner</p>
<p>% $Id: spm_vol_nifti.m 112 2005-05-04 18:20:52Z john $</p>
<p></p>
<p></p></font></font></font><font color=3D"#0000ff" size=3D"2" face=3D"Mono=
spaced"><font color=3D"#0000ff" size=3D"2" face=3D"Monospaced"><font color=
=3D"#0000ff" size=3D"2" face=3D"Monospaced">
<p>if</p></font></font></font><font size=3D"2" face=3D"Monospaced"><font si=
ze=3D"2" face=3D"Monospaced"> nargin<2, n =3D [1 1]; </font></font><font=
color=3D"#0000ff" size=3D"2" face=3D"Monospaced"><font color=3D"#0000ff" s=
ize=3D"2" face=3D"Monospaced"><font color=3D"#0000ff" size=3D"2" face=3D"Mo=
nospaced">end</font></font></font><font size=3D"2" face=3D"Monospaced"><fon=
t size=3D"2" face=3D"Monospaced">;</font></font><font color=3D"#0000ff" siz=
e=3D"2" face=3D"Monospaced"><font color=3D"#0000ff" size=3D"2" face=3D"Mono=
spaced"><font color=3D"#0000ff" size=3D"2" face=3D"Monospaced">
<p>if</p></font></font></font><font size=3D"2" face=3D"Monospaced"><font si=
ze=3D"2" face=3D"Monospaced"> ischar(n), n =3D str2num(n); </font></font><f=
ont color=3D"#0000ff" size=3D"2" face=3D"Monospaced"><font color=3D"#0000ff=
" size=3D"2" face=3D"Monospaced"><font color=3D"#0000ff" size=3D"2" face=3D=
"Monospaced">end</font></font></font><font size=3D"2" face=3D"Monospaced"><=
font size=3D"2" face=3D"Monospaced">;
<p>N =3D nifti(fname);</p>
<p>n =3D [n 1 1];</p>
<p>n =3D n(1:2);</p>
<p>dm =3D [N.dat.dim 1 1 1 1];</p></font></font><font color=3D"#0000ff" siz=
e=3D"2" face=3D"Monospaced"><font color=3D"#0000ff" size=3D"2" face=3D"Mono=
spaced"><font color=3D"#0000ff" size=3D"2" face=3D"Monospaced">
<p>if</p></font></font></font><font size=3D"2" face=3D"Monospaced"><font si=
ze=3D"2" face=3D"Monospaced"> any(n>dm(4:5)), V =3D []; </font></font><f=
ont color=3D"#0000ff" size=3D"2" face=3D"Monospaced"><font color=3D"#0000ff=
" size=3D"2" face=3D"Monospaced"><font color=3D"#0000ff" size=3D"2" face=3D=
"Monospaced">return</font></font></font><font size=3D"2" face=3D"Monospaced=
"><font size=3D"2" face=3D"Monospaced">; </font></font><font color=3D"#0000=
ff" size=3D"2" face=3D"Monospaced"><font color=3D"#0000ff" size=3D"2" face=
=3D"Monospaced"><font color=3D"#0000ff" size=3D"2" face=3D"Monospaced">end<=
/font></font></font><font size=3D"2" face=3D"Monospaced"><font size=3D"2" f=
ace=3D"Monospaced">;
<p></p>
<p>dt =3D struct(N.dat);</p>
<p>dt =3D double([dt.dtype <a href=3D"http://dt.be">dt.be</a>]);</p>
<p></p></font></font><font color=3D"#0000ff" size=3D"2" face=3D"Monospaced"=
><font color=3D"#0000ff" size=3D"2" face=3D"Monospaced"><font color=3D"#000=
0ff" size=3D"2" face=3D"Monospaced">
<p>if</p></font></font></font><font size=3D"2" face=3D"Monospaced"><font si=
ze=3D"2" face=3D"Monospaced"> isfield(N.extras,</font></font><font color=3D=
"#a020f0" size=3D"2" face=3D"Monospaced"><font color=3D"#a020f0" size=3D"2"=
face=3D"Monospaced"><font color=3D"#a020f0" size=3D"2" face=3D"Monospaced"=
>'mat'</font></font></font><font size=3D"2" face=3D"Monospaced"><fo=
nt size=3D"2" face=3D"Monospaced">) && size(N.extras.mat,3)>=3Dn=
(1) && sum(sum(N.extras.mat(:,:,n(1))))~=3D0,
<p>mat =3D N.extras.mat(:,:,n(1));</p></font></font><font color=3D"#0000ff"=
size=3D"2" face=3D"Monospaced"><font color=3D"#0000ff" size=3D"2" face=3D"=
Monospaced"><font color=3D"#0000ff" size=3D"2" face=3D"Monospaced">
<p>else</p></font></font></font><font size=3D"2" face=3D"Monospaced"><font =
size=3D"2" face=3D"Monospaced">
<p>mat =3D N.mat;</p></font></font><font color=3D"#0000ff" size=3D"2" face=
=3D"Monospaced"><font color=3D"#0000ff" size=3D"2" face=3D"Monospaced"><fon=
t color=3D"#0000ff" size=3D"2" face=3D"Monospaced">
<p>end</p></font></font></font><font size=3D"2" face=3D"Monospaced"><font s=
ize=3D"2" face=3D"Monospaced">;
<p></p>
<p>off =3D (n(1)-1+dm(4)*(n(2)-1))*ceil(spm_type(dt(1),</p></font></font><f=
ont color=3D"#a020f0" size=3D"2" face=3D"Monospaced"><font color=3D"#a020f0=
" size=3D"2" face=3D"Monospaced"><font color=3D"#a020f0" size=3D"2" face=3D=
"Monospaced">'bits'</font></font></font><font size=3D"2" face=3D"Mo=
nospaced"><font size=3D"2" face=3D"Monospaced">)*dm(1)*dm(2)/8)*dm(3) + N.d=
at.offset;
<p>V =3D struct(</p></font></font><font color=3D"#a020f0" size=3D"2" face=
=3D"Monospaced"><font color=3D"#a020f0" size=3D"2" face=3D"Monospaced"><fon=
t color=3D"#a020f0" size=3D"2" face=3D"Monospaced">'fname'</font></=
font></font><font size=3D"2" face=3D"Monospaced"><font size=3D"2" face=3D"M=
onospaced">, N.dat.fname,</font></font><font color=3D"#0000ff" size=3D"2" f=
ace=3D"Monospaced"><font color=3D"#0000ff" size=3D"2" face=3D"Monospaced"><=
font color=3D"#0000ff" size=3D"2" face=3D"Monospaced">...</font></font></fo=
nt><font size=3D"2" face=3D"Monospaced"><font size=3D"2" face=3D"Monospaced=
">
<p></p></font></font><font color=3D"#a020f0" size=3D"2" face=3D"Monospaced"=
><font color=3D"#a020f0" size=3D"2" face=3D"Monospaced"><font color=3D"#a02=
0f0" size=3D"2" face=3D"Monospaced">'dim'</font></font></font><font=
size=3D"2" face=3D"Monospaced"><font size=3D"2" face=3D"Monospaced">, dm(1=
:3),</font></font><font color=3D"#0000ff" size=3D"2" face=3D"Monospaced"><f=
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ff" size=3D"2" face=3D"Monospaced"><font color=3D"#0000ff" size=3D"2" face=
=3D"Monospaced"><font color=3D"#0000ff" size=3D"2" face=3D"Monospaced">...<=
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ze=3D"2" face=3D"Monospaced">...</font></font></font><font size=3D"2" face=
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0f0" size=3D"2" face=3D"Monospaced">'descrip'</font></font></font><=
font size=3D"2" face=3D"Monospaced"><font size=3D"2" face=3D"Monospaced">, =
N.descrip,</font></font><font color=3D"#0000ff" size=3D"2" face=3D"Monospac=
ed"><font color=3D"#0000ff" size=3D"2" face=3D"Monospaced"><font color=3D"#=
0000ff" size=3D"2" face=3D"Monospaced">...</font></font></font><font size=
=3D"2" face=3D"Monospaced"><font size=3D"2" face=3D"Monospaced">
<div></div></font></font><font color=3D"#a020f0" size=3D"2" face=3D"Monospa=
ced"><font color=3D"#a020f0" size=3D"2" face=3D"Monospaced"><font color=3D"=
#a020f0" size=3D"2" face=3D"Monospaced">'private'</font></font></fo=
nt><font size=3D"2" face=3D"Monospaced"><font size=3D"2" face=3D"Monospaced=
">,N);</font></font>
<div><font size=3D"2" face=3D"Monospaced"><font size=3D"2" face=3D"Monospac=
ed"></font></font>=A0</div>
<div><font size=3D"2" face=3D"Monospaced"><font size=3D"2" face=3D"Monospac=
ed">Thanks in advance,</font></font></div>
<div><font size=3D"2" face=3D"Monospaced"><font size=3D"2" face=3D"Monospac=
ed">Jadzia</font></font></div><br>-- <br>Jadzia Jagiellowicz<br>Doctoral Ca=
ndidate <br>Psychology Department B-207<br>Stony Brook University, <br>Ston=
y Brook, NY 11794-2500 USA<br>
<a href=3D"http://www.psychology.stonybrook.edu/aronlab-/">http://www.psych=
ology.stonybrook.edu/aronlab-/</a><br><br>"The brave shall inherit the=
earth."<br>
--0015177405fe67aee804a28d813a--
=========================================================================
Date: Thu, 5 May 2011 19:17:43 -0300
Reply-To: edson amaro junior <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: edson amaro junior <[log in to unmask]>
Subject: position available at Albert Einstein Research Institute - Brazil
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Dear All,
A full time post-doctoral position is available in the Brain Institute =
at Albert Einstein Institute for Research and Education (Ince =96 =
IIEPAE). The main goals is the development of preclinical models for =
neurodegenerative diseases. The facilities include a micro SPECT =
integraded with a micro CT system, a radiopharmacy lab, a fully equiped =
stereotaxic surgical unit, a Neurolucida system for 3D histological =
quantification. We are certified to work with knock out disease models, =
and have support for cell culture, genomic, proteinomic and metabolic =
experiments.
Successful applicant should have a PhD in neuroscience, biomedical =
engineering or in related fields. The ideal candidate would have a =
background in experimental setup using animal models in neurology =
research projects. Good communication skills are required to interact =
with a multidisciplinary team of experienced molecular imaging =
scientists, engineers and other students.
Portuguese speaking would be desirable but not required. Salary is =
provided by an UNIEMP grant (equivalent to a top salary for post-doc =
scholarships in the country). The position (12 months renewable) is open =
in June 2011.
Contact information: please email CV, two letters of recomendation, =
contact information of references and statement of research interests, =
to:
Dr. Edson Amaro Jr ([log in to unmask])
Brain Institute =96 Albert Einstein Research and Education Institute
Albert Einstein Hospital
S=E3o Paulo =96 SP
Brazil
Phone ++55 (0)11 2151 3727
--Apple-Mail-14--90850614
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charset=windows-1252
<html><head></head><body style=3D"word-wrap: break-word; =
-webkit-nbsp-mode: space; -webkit-line-break: after-white-space; =
"><div>Dear All,<br><br>A full time post-doctoral position is available =
in the Brain Institute at Albert Einstein Institute for Research and =
Education (Ince =96 IIEPAE). The main goals is the development of =
preclinical models for neurodegenerative diseases. The facilities =
include a micro SPECT integraded with a micro =
CT system, a radiopharmacy lab, a fully equiped stereotaxic =
surgical unit, a Neurolucida system for 3D histological quantification. =
We are certified to work with knock out disease models, and have support =
for cell culture, genomic, proteinomic and metabolic =
experiments.</div><div><br>Successful applicant should have a PhD in =
neuroscience, biomedical engineering or in related fields. The ideal =
candidate would have a background in experimental setup using animal =
models in neurology research projects. Good communication skills =
are required to interact with a multidisciplinary team of experienced =
molecular imaging scientists, engineers and other =
students.<br><br>Portuguese speaking would be desirable but not =
required. Salary is provided by an UNIEMP grant (equivalent to a top =
salary for post-doc scholarships in the country). The position (12 =
months renewable) is open in June 2011.<br><br>Contact information: =
please email CV, two letters of recomendation, contact information of =
references and statement of research interests, to:<br><br>Dr. Edson =
Amaro Jr (<a =
href=3D"mailto:[log in to unmask]">[log in to unmask]</a>)<br>Brain =
Institute =96 Albert Einstein Research and Education Institute<br>Albert =
Einstein Hospital<br>S=E3o Paulo =96 SP<br>Brazil<br>Phone ++55 (0)11 =
2151 3727</div><div>
<span class=3D"Apple-style-span" style=3D"border-collapse: separate; =
color: rgb(0, 0, 0); font-family: Helvetica; font-style: normal; =
font-variant: normal; font-weight: normal; letter-spacing: normal; =
line-height: normal; orphans: 2; text-align: auto; text-indent: 0px; =
text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; =
-webkit-border-horizontal-spacing: 0px; -webkit-border-vertical-spacing: =
0px; -webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: =
auto; -webkit-text-stroke-width: 0px; font-size: medium; "><span =
class=3D"Apple-style-span" style=3D"border-collapse: separate; color: =
rgb(0, 0, 0); font-family: Helvetica; font-style: normal; font-variant: =
normal; font-weight: normal; letter-spacing: normal; line-height: =
normal; orphans: 2; text-indent: 0px; text-transform: none; white-space: =
normal; widows: 2; word-spacing: 0px; -webkit-border-horizontal-spacing: =
0px; -webkit-border-vertical-spacing: 0px; =
-webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: =
auto; -webkit-text-stroke-width: 0px; font-size: medium; "><div =
style=3D"word-wrap: break-word; -webkit-nbsp-mode: space; =
-webkit-line-break: after-white-space; "><span class=3D"Apple-style-span" =
style=3D"border-collapse: separate; color: rgb(0, 0, 0); font-family: =
Helvetica; font-style: normal; font-variant: normal; font-weight: =
normal; letter-spacing: normal; line-height: normal; orphans: 2; =
text-indent: 0px; text-transform: none; white-space: normal; widows: 2; =
word-spacing: 0px; -webkit-border-horizontal-spacing: 0px; =
-webkit-border-vertical-spacing: 0px; =
-webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: =
auto; -webkit-text-stroke-width: 0px; font-size: medium; "><div =
style=3D"word-wrap: break-word; -webkit-nbsp-mode: space; =
-webkit-line-break: after-white-space; "><span class=3D"Apple-style-span" =
style=3D"border-collapse: separate; color: rgb(0, 0, 0); font-family: =
Helvetica; font-style: normal; font-variant: normal; font-weight: =
normal; letter-spacing: normal; line-height: normal; orphans: 2; =
text-indent: 0px; text-transform: none; white-space: normal; widows: 2; =
word-spacing: 0px; -webkit-border-horizontal-spacing: 0px; =
-webkit-border-vertical-spacing: 0px; =
-webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: =
auto; -webkit-text-stroke-width: 0px; font-size: medium; "><div =
style=3D"word-wrap: break-word; -webkit-nbsp-mode: space; =
-webkit-line-break: after-white-space; "><span class=3D"Apple-style-span" =
style=3D"border-collapse: separate; color: rgb(0, 0, 0); font-family: =
Helvetica; font-size: medium; font-style: normal; font-variant: normal; =
font-weight: normal; letter-spacing: normal; line-height: normal; =
orphans: 2; text-indent: 0px; text-transform: none; white-space: normal; =
widows: 2; word-spacing: 0px; -webkit-border-horizontal-spacing: 0px; =
-webkit-border-vertical-spacing: 0px; =
-webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: =
auto; -webkit-text-stroke-width: 0px; "><span class=3D"Apple-style-span" =
style=3D"border-collapse: separate; color: rgb(0, 0, 0); font-family: =
Helvetica; font-size: medium; font-style: normal; font-variant: normal; =
font-weight: normal; letter-spacing: normal; line-height: normal; =
orphans: 2; text-indent: 0px; text-transform: none; white-space: normal; =
widows: 2; word-spacing: 0px; -webkit-border-horizontal-spacing: 0px; =
-webkit-border-vertical-spacing: 0px; =
-webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: =
auto; -webkit-text-stroke-width: 0px; "><div style=3D"word-wrap: =
break-word; -webkit-nbsp-mode: space; -webkit-line-break: =
after-white-space; "><span class=3D"Apple-style-span" =
style=3D"border-collapse: separate; color: rgb(0, 0, 0); font-family: =
Helvetica; font-size: 18px; font-style: normal; font-variant: normal; =
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-webkit-border-vertical-spacing: 0px; =
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auto; -webkit-text-stroke-width: 0px; "><div style=3D"word-wrap: =
break-word; -webkit-nbsp-mode: space; -webkit-line-break: =
after-white-space; =
"><div><div><br></div></div></div></span></div></span></span></div></span>=
</div></span></div></span></span>
</div>
</body></html>=
--Apple-Mail-14--90850614--
=========================================================================
Date: Thu, 5 May 2011 23:33:33 +0100
Reply-To: Jasmine Song <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jasmine Song <[log in to unmask]>
Subject: EEG: Prepare SPM file
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I have some problems to convert an eeg file into spm.
When I click the "Prepare SPM file", the M/EEG prepare window does not po=
p up. Does anyone have same problem? I am running spm8 updated with r42=
90 under MATLAB 2011a on MAC.=20
Best,=20
Jasmine=20
=========================================================================
Date: Fri, 6 May 2011 11:46:23 +1000
Reply-To: Alex Fornito <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Alex Fornito <[log in to unmask]>
Subject: Re: PPI question
Comments: To: "MCLAREN, Donald" <[log in to unmask]>,
Darren Gitelman <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
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Hi Donald, Torben and Darren,
Thanks for your responses.
Form each of your responses, it seems like best practice would be to remove
motion (and/or other confounds) from the VOI time series prior to
deconvolution.=20
It also seems like you are recommending NOT to frequency filter the VOI tim=
e
series.=20
In my reading though, spm_regions does this by default with the call to
spm_filter (line 135). So, if spm_regions is used to extract a VOI time
series, the time series that is input to spm_peb_ppi will already frequency
filtered. So it seems like, in standard practice, the deconvolution is
applied to frequency-filtered data. In this case, if xX.iG is empty, the
only difference between Y and Yc in spm_peb_ppi is the additional removal o=
f
block effects (xX.iB).
Based on the current chain of emails, it seems you are recommending that a
confound-corrected, whitened, but non-frequency filtered time course should
be input to spm_peb_ppi. IS that correct, or am I missing something?
Finally, can I clarify exactly what the null space of the contrast is? Most
of the time in my analyses I don't get the option to adjust for it, so xY.I=
c
is empty.=20
Thanks again for all your help,
A
On 06/05/2011 02:18, "MCLAREN, Donald" <[log in to unmask]> wrote:
> I haven't thoroughly tested this, but if you set iG to be the movement
> parameters columns. Then still adjust for the null space (motion
> parameters). You will get the best of both. If you don't adjust for
> the null space, then movement will contribute to the deconvolution. In
> summary, if you have iG be the motion parameter columns AND adjust for
> the null-space (motion columns), then:
>=20
> Y will have the effect of motion removed. Yc (removal of motion twice)
> will be minimally different since Y is orthogonal to the motion
> parameters. So, you have motion removed from both the autocorrelation
> estimate, the Y for deconvolution, and Yc.
>=20
> Best Regards, Donald McLaren
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> D.G. McLaren, Ph.D.
> Postdoctoral Research Fellow, GRECC, Bedford VA
> Research Fellow, Department of Neurology, Massachusetts General
> Hospital and Harvard Medical School
> Office: (773) 406-2464
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> This e-mail contains CONFIDENTIAL INFORMATION which may contain
> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
> and which is intended only for the use of the individual or entity
> named above. If the reader of the e-mail is not the intended recipient
> or the employee or agent responsible for delivering it to the intended
> recipient, you are hereby notified that you are in possession of
> confidential and privileged information. Any unauthorized use,
> disclosure, copying or the taking of any action in reliance on the
> contents of this information is strictly prohibited and may be
> unlawful. If you have received this e-mail unintentionally, please
> immediately notify the sender via telephone at (773) 406-2464 or
> email.
>=20
>=20
>=20
> On Thu, May 5, 2011 at 9:48 AM, Torben Ellegaard Lund
> <[log in to unmask]> wrote:
>> Hi Alex
>>=20
>>=20
>> Den Uge:18 05/05/2011 kl. 14.15 skrev Alex Fornito:
>>=20
>>> Hi Torben,
>>> Sorry, I just wanted to clarify: do you mean leaving SPM.xX.iG empty? I=
t
>>> seems like this is done by default by spm_fmri_design (?)
>>=20
>> leaving it empty will include all user defined regressors in the effects=
of
>> interest F-test which determines the mask where the serial correlation i=
s
>> estimated. I think it would make sense if the motion regressors did not =
go
>> into this test, just like the DCS HP-filter does not go into the F-contr=
ast.
>>=20
>>> Are you suggesting manually entering motion parameters into this field?
>>=20
>> Yes, or their indices that is. It should be done after specification, bu=
t
>> before model estimation. You can check if SPM recognized your changes by
>> looking at the automatically generated effects of interest F-contrast.
>>=20
>>=20
>> Best
>> Torben
>>=20
>>=20
>>=20
>>=20
>>>=20
>>> On 05/05/2011 18:16, "Torben Ellegaard Lund" <[log in to unmask]> wrote=
:
>>>=20
>>>> Just as a kind reminder. Leaving SPM.xX.iG is a bit unfortunate, becau=
se
>>>> voxels where motion artefacts are significant then constitutes a large=
part
>>>> of
>>>> the F-test derived mask used to estimate serial correlations. If you a=
re
>>>> picky
>>>> about this you can change it yourselves, but it is not as easy as it s=
hould
>>>> be.
>>>>=20
>>>>=20
>>>> Best
>>>> Torben
>>>>=20
>>>>=20
>>>>=20
>>>> Den Uge:18 05/05/2011 kl. 05.03 skrev Alex Fornito:
>>>>=20
>>>>> Ahh, I see. I was assuming that SPM.xX.iG contained the indices to th=
e
>>>>> nuisance covariates in the design matrix, but you're right -
>>>>> spm_fMRI_design
>>>>> leaves it empty.
>>>>>=20
>>>>> Thanks for your help!
>>>>> A
>>>>>=20
>>>>>=20
>>>>> On 05/05/2011 12:54, "MCLAREN, Donald" <[log in to unmask]> wro=
te:
>>>>>=20
>>>>>> I agree that nuisance covariates, such as motion should be removed;
>>>>>> however, motion covariates are not generally stored in X0 in my
>>>>>> reading of the SPM code (spm_fMRI_design, spm_regions). They should =
be
>>>>>> removed in the spm_regions filtering based on the null-space of the
>>>>>> contrast.
>>>>>>=20
>>>>>> As for the motion parameters being in the model, if they were in the
>>>>>> standard analysis, they should be included in the PPI analysis. My
>>>>>> gPPI code will do this automatically as well.
>>>>>>=20
>>>>>> X0 is made of SPM.xX.iB (block effects -- so removing the mean) and
>>>>>> SPM.xX.iG (nuisance variable that is empty as far as I can tell (lin=
e
>>>>>> 369 of spm_fMRI_design)) and the high-pass filtering (K.X0).
>>>>>>=20
>>>>>> Best Regards, Donald McLaren
>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>> D.G. McLaren, Ph.D.
>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>> Hospital and Harvard Medical School
>>>>>> Office: (773) 406-2464
>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>>>>>> and which is intended only for the use of the individual or entity
>>>>>> named above. If the reader of the e-mail is not the intended recipie=
nt
>>>>>> or the employee or agent responsible for delivering it to the intend=
ed
>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>> disclosure, copying or the taking of any action in reliance on the
>>>>>> contents of this information is strictly prohibited and may be
>>>>>> unlawful. If you have received this e-mail unintentionally, please
>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>> email.
>>>>>>=20
>>>>>>=20
>>>>>>=20
>>>>>> On Wed, May 4, 2011 at 10:16 PM, Alex Fornito <[log in to unmask]
au>
>>>>>> wrote:
>>>>>>> Hi Donald,
>>>>>>> Thanks for your response. When you say "you don't want
>>>>>>> to filter out anything related to neural activity", I'm presuming t=
hat
>>>>>>> you
>>>>>>> are referring to the deconvolved neural signal?
>>>>>>>=20
>>>>>>> If so, that makes sense. However, X0 also contains user-specified
>>>>>>> nuisance
>>>>>>> covariates. I would have thought it would make sense to remove thos=
e,
>>>>>>> depending on what they were (e.g., movement parameters)? I guess th=
ey
>>>>>>> can
>>>>>>> always be entered into the PPI regression model...
>>>>>>>=20
>>>>>>>=20
>>>>>>> On 05/05/2011 11:57, "MCLAREN, Donald" <[log in to unmask]> w=
rote:
>>>>>>>=20
>>>>>>>> I could be wrong, Karl or Darren please correct me if I am.
>>>>>>>>=20
>>>>>>>> X0 is composed of the high-pass filter and constant term. Thus, yo=
u
>>>>>>>> want to filter these out of the Yc regressor. However, you don't w=
ant
>>>>>>>> to filter out anything related to neural activity, so you wouldn't
>>>>>>>> want to filter your signal and then predict the neural activity fr=
om
>>>>>>>> the filtered signal, especially filtering frequencies.
>>>>>>>>=20
>>>>>>>> Best Regards, Donald McLaren
>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>>> Hospital and Harvard Medical School
>>>>>>>> Office: (773) 406-2464
>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGE=
D
>>>>>>>> and which is intended only for the use of the individual or entity
>>>>>>>> named above. If the reader of the e-mail is not the intended recip=
ient
>>>>>>>> or the employee or agent responsible for delivering it to the inte=
nded
>>>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>> disclosure, copying or the taking of any action in reliance on the
>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>> unlawful. If you have received this e-mail unintentionally, please
>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>>>> email.
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>> On Sat, Apr 30, 2011 at 8:03 PM, Alex Fornito <[log in to unmask]
u.au>
>>>>>>>> wrote:
>>>>>>>>> Hi Donald,
>>>>>>>>> As far as I can tell, spm_regions filters and whitens the VOI tim=
e
>>>>>>>>> series,
>>>>>>>>> and adjusts for the null space of the contrast if an adjustment i=
s
>>>>>>>>> specified
>>>>>>>>> in xY.Ic. It defines the confound matrix, X0, but does not correc=
t for
>>>>>>>>> it.
>>>>>>>>> The following line in spm_peb_ppi corrects for the confounds.
>>>>>>>>>=20
>>>>>>>>> Yc =A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>>=20
>>>>>>>>> So the above correction does seem to be doing something different=
to
>>>>>>>>> spm_regions. I'm wondering why the uncorrected data, Y, is used w=
hen
>>>>>>>>> generating the ppi interaction term, while the corrected data Yc =
is to
>>>>>>>>> be
>>>>>>>>> used as a covariate of no interest in the PPI model. I would has
>>>>>>>>> thought
>>>>>>>>> that Yc should be used to generate the ppi interaction term as we=
ll.
>>>>>>>>>=20
>>>>>>>>> In my data, my X0 is a 195 x 7 matrix (I have 195 volumes per
>>>>>>>>> session).
>>>>>>>>>=20
>>>>>>>>> Regards,
>>>>>>>>> Alex
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>> On 30/04/2011 02:22, "MCLAREN, Donald" <[log in to unmask]>
>>>>>>>>> wrote:
>>>>>>>>>=20
>>>>>>>>>> I'm actually travelling at the moment. However, I know Y has alr=
eady
>>>>>>>>>> been adjusted as part of the VOI processing.
>>>>>>>>>>=20
>>>>>>>>>> Can you check what X0 looks like?
>>>>>>>>>>=20
>>>>>>>>>> Best Regards, Donald McLaren
>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>>>>> Hospital and Harvard Medical School
>>>>>>>>>> Office: (773) 406-2464
>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILE=
GED
>>>>>>>>>> and which is intended only for the use of the individual or enti=
ty
>>>>>>>>>> named above. If the reader of the e-mail is not the intended
>>>>>>>>>> recipient
>>>>>>>>>> or the employee or agent responsible for delivering it to the
>>>>>>>>>> intended
>>>>>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>>>> disclosure, copying or the taking of any action in reliance on t=
he
>>>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>>>> unlawful. If you have received this e-mail unintentionally, plea=
se
>>>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>>>>>> email.
>>>>>>>>>>=20
>>>>>>>>>>=20
>>>>>>>>>>=20
>>>>>>>>>> On Fri, Apr 29, 2011 at 2:55 AM, Alex Fornito
>>>>>>>>>> <[log in to unmask]>
>>>>>>>>>> wrote:
>>>>>>>>>>> Hi all,
>>>>>>>>>>> I have a question concerning the code used to implement a PPI
>>>>>>>>>>> analysis.
>>>>>>>>>>>=20
>>>>>>>>>>> In the spm_peb_ppi.m function packaged with SPM8, lines 329-332
>>>>>>>>>>> remove
>>>>>>>>>>> confounds from the input seed region=B9s time course:
>>>>>>>>>>>=20
>>>>>>>>>>> % Remove confounds and save Y in ouput structure
>>>>>>>>>>> %--------------------------------------------------------------=
-----
>>>>>>>>>>> ---
>>>>>>>>>>> --
>>>>>>>>>>> --
>>>>>>>>>>> Yc =A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>>>>=20
>>>>>>>>>>> PPI.Y is then to be used as a covariate of no interest when bui=
lding
>>>>>>>>>>> the
>>>>>>>>>>> PPI
>>>>>>>>>>> regression model. However, on line 488, it is the uncorrected s=
eed
>>>>>>>>>>> time
>>>>>>>>>>> course, Y, that is input to the deconvolution routine and used =
to
>>>>>>>>>>> generate
>>>>>>>>>>> the ppi term:
>>>>>>>>>>>=20
>>>>>>>>>>> =A0C =A0=3D spm_PEB(Y,P);
>>>>>>>>>>> =A0 =A0xn =3D xb*C{2}.E(1:N);
>>>>>>>>>>> =A0 =A0xn =3D spm_detrend(xn);
>>>>>>>>>>>=20
>>>>>>>>>>> =A0% Setup psychological variable from inputs and contast weights
>>>>>>>>>>>=20
>>>>>>>>>>> %--------------------------------------------------------------=
-----
>>>>>>>>>>> ---
>>>>>>>>>>> =A0PSY =3D zeros(N*NT,1);
>>>>>>>>>>> =A0for i =3D 1:size(U.u,2)
>>>>>>>>>>> =A0 =A0 =A0PSY =3D PSY + full(U.u(:,i)*U.w(:,i));
>>>>>>>>>>> =A0end
>>>>>>>>>>> =A0% PSY =3D spm_detrend(PSY); =A0<- removed centering of psych varia=
ble
>>>>>>>>>>> =A0% prior to multiplication with xn. Based on discussion with Ka=
rl
>>>>>>>>>>> =A0% and Donald McLaren.
>>>>>>>>>>>=20
>>>>>>>>>>> % Multiply psychological variable by neural signal
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>> %--------------------------------------------------------------=
-----
>>>>>>>>>>> ---
>>>>>>>>>>> =A0 PSYxn =3D PSY.*xn;
>>>>>>>>>>>=20
>>>>>>>>>>> Is there any specific reason why Y, rather than Yc(:,1), is use=
d to
>>>>>>>>>>> compute
>>>>>>>>>>> PSYxn? I thought Yc might be more appropriate (?).
>>>>>>>>>>> Thanks for your help,
>>>>>>>>>>> Alex
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>> ------------------------------------------
>>>>>>>>>>>=20
>>>>>>>>>>> Alex Fornito
>>>>>>>>>>> Research Fellow
>>>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>>>> University of Melbourne
>>>>>>>>>>> National Neuroscience Facility
>>>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>>>> 161 Barry St
>>>>>>>>>>> Carlton South 3053
>>>>>>>>>>> Victoria, Australia
>>>>>>>>>>>=20
>>>>>>>>>>> Email: [log in to unmask]
>>>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>> ------------------------------------------
>>>>>>>>>=20
>>>>>>>>> Alex Fornito
>>>>>>>>> Research Fellow
>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>> University of Melbourne
>>>>>>>>> National Neuroscience Facility
>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>> 161 Barry St
>>>>>>>>> Carlton South 3053
>>>>>>>>> Victoria, Australia
>>>>>>>>>=20
>>>>>>>>> Email: [log in to unmask]
>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>=20
>>>>>>>=20
>>>>>>>=20
>>>>>>> ------------------------------------------
>>>>>>>=20
>>>>>>> Alex Fornito
>>>>>>> Research Fellow
>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>> University of Melbourne
>>>>>>> National Neuroscience Facility
>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>> 161 Barry St
>>>>>>> Carlton South 3053
>>>>>>> Victoria, Australia
>>>>>>>=20
>>>>>>> Email: [log in to unmask]
>>>>>>> Phone: +61 3 8344 1876
>>>>>>> Fax: +61 3 9348 0469
>>>>>>>=20
>>>>>>>=20
>>>>>>>=20
>>>>>>>=20
>>>>>>=20
>>>>>=20
>>>>>=20
>>>>> ------------------------------------------
>>>>>=20
>>>>> Alex Fornito
>>>>> Research Fellow
>>>>> Melbourne Neuropsychiatry Centre
>>>>> University of Melbourne
>>>>> National Neuroscience Facility
>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>> 161 Barry St
>>>>> Carlton South 3053
>>>>> Victoria, Australia
>>>>>=20
>>>>> Email: [log in to unmask]
>>>>> Phone: +61 3 8344 1876
>>>>> Fax: +61 3 9348 0469
>>>>=20
>>>>=20
>>>=20
>>>=20
>>> ------------------------------------------
>>>=20
>>> Alex Fornito
>>> Research Fellow
>>> Melbourne Neuropsychiatry Centre
>>> University of Melbourne
>>> National Neuroscience Facility
>>> Levels 1 & 2, Alan Gilbert Building
>>> 161 Barry St
>>> Carlton South 3053
>>> Victoria, Australia
>>>=20
>>> Email: [log in to unmask]
>>> Phone: +61 3 8344 1876
>>> Fax: +61 3 9348 0469
>>>=20
>>>=20
>>>=20
>>=20
>=20
------------------------------------------
Alex Fornito
Research Fellow
Melbourne Neuropsychiatry Centre
University of Melbourne
National Neuroscience Facility
Levels 1 & 2, Alan Gilbert Building
161 Barry St=A0
Carlton South 3053
Victoria, Australia
Email: [log in to unmask]
Phone: +61 3 8344 1876
Fax: +61 3 9348 0469 =A0
=========================================================================
Date: Fri, 6 May 2011 11:13:01 +0800
Reply-To: =?gbk?B?zrHTsCA=?= <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?gbk?B?zrHTsCA=?= <[log in to unmask]>
Subject: Why the FDR result is different between the SPM5 and REST?
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=========================================================================
Date: Fri, 6 May 2011 10:16:22 +0530
Reply-To: Kavita Vemuri <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Kavita Vemuri <[log in to unmask]>
Subject: SPM8 - DICOM to nii conversion error
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=utf-8
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Message-ID: <[log in to unmask]>
Hi,
I am using SPM8 for fMRI. For each session of the experiment, there
are around 2500-3200 images. When I use the DICOM to nii converter
provided in SPM8, I notice that only 84 nii format data is generated.
On the matlab console, I see a message that says something like
-acquisition number not changing or DICOM images are repeated'.
Is there something wrong in the way I am converting?
regards Kavita
=========================================================================
Date: Fri, 6 May 2011 01:01:06 -0500
Reply-To: Joshua Buckholtz <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Joshua Buckholtz <[log in to unmask]>
Subject: Research Assistant Position at Harvard University
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--20cf30025ae259e41a04a2953863
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Content-Transfer-Encoding: quoted-printable
The Systems Neuroscience of Psychopathology laboratory at Harvard Universit=
y
(SNPlab) is seeking a Full-time Research Assistant (RA) for an exciting,
large-scale project aimed at understanding how genes affect the brain to
influence risk for addiction, aggression, and antisocial behavior.
*Responsibilities*
The RA=92s primary responsibilities will include: (1) data acquisition usin=
g
behavioral and neuroimaging techniques (MRI and radioligand PET); (2) data
entry, data checking, and quality control procedures; and (3) subject
recruitment and enrollment through community outreach and advertising.
Other responsibilities include serving as an interface among several
collaborating
lab groups in the Boston area, maintaining participant databases, scoring
and processing data and assisting with administrative tasks.
*Requirements*
B.A., B.S. or equivalent with background in psychology, neuroscience,
biomedical engineering or related field. Candidates should have proficiency
with basic computing packages such as MS Word and Excel, and will be
familiar with experimental presentation packages (e.g. E-Prime,
Psychophysics Toolbox, Presentation) and standard statistical analysis
software (e.g. MATLAB, R, SPSS).
Familiarity with neuroimaging data analysis (e.g. SPM, FSL, AFNI,
BrainVoyager) will confer an advantage, as will prior experience with
molecular genetics and/or bioinformatics, but neither are necessary to
receive consideration.
Strong interpersonal skills, prior research experience, high level of
organization with careful attention to detail, and comfort with technical
skills are absolutely required. This position requires a high degree of
motivation and self-sufficiency, although extensive training and supervisio=
n
will be provided.
* *
*Details*
To apply, please email a brief cover letter describing relevant experience,
research interests and career goals, CV and contact information to Dr.
Joshua Buckholtz (Director, SNPlab) at [log in to unmask]
All formal offers will be made by Harvard FAS Human Resources. This is a
two-year term position that is based in the Department of Psychology, with
renewal dependent upon continuation of funding. Expected start date: late
summer 2011. This is an excellent and unique opportunity for a motivated
individual to gain experience with cutting-edge neuroscience in preparation
for a graduate career.
--20cf30025ae259e41a04a2953863
Content-Type: text/html; charset=windows-1252
Content-Transfer-Encoding: quoted-printable
<p class=3D"MsoNormal"><span style=3D"font-family:Arial"><span style=3D"fon=
t-size:large">The Systems Neuroscience of
Psychopathology laboratory at Harvard University (SNPlab) is seeking a
Full-time Research Assistant (RA) for an exciting, large-scale project aime=
d at
understanding how genes affect the brain to influence risk for addiction,
aggression, and antisocial behavior.</span></span></p>
<p class=3D"MsoNormal" style=3D"text-autospace:none"><span style=3D"font-si=
ze:9.0pt;font-family:Arial">=A0</span></p>
<p class=3D"MsoNormal"><u><span style=3D"font-family:Arial"><b>Responsibili=
ties</b></span></u></p>
<p class=3D"MsoNormal"><span style=3D"font-family:Arial">The</span><span st=
yle=3D"font-family:Helvetica"> </span><span style=3D"font-family:Arial">RA=
=92s primary responsibilities will include: (1) data acquisition using beha=
vioral and</span><font face=3D"Helvetica">=A0</font><span style=3D"font-fam=
ily:Arial">neuroimaging techniques (MRI and
radioligand PET); (2) data entry, data checking, and quality control=A0</sp=
an><span style=3D"font-family:Arial">procedures; and (3) subject
recruitment and enrollment through community outreach=A0</span><span style=
=3D"font-family:Arial">and advertising.=A0 Other responsibilities include s=
erving
as an interface among several=A0</span><span style=3D"font-family:Arial">co=
llaborating lab groups in the
Boston area, maintaining participant databases, scoring and processing=A0</=
span><span class=3D"Apple-style-span" style=3D"font-family: Arial; ">data a=
nd assisting with
administrative tasks.</span></p>
<p class=3D"MsoNormal"><span style=3D"font-family:'Arial Black'">=
=A0</span></p>
<p class=3D"MsoNormal"><u><span style=3D"font-family:Arial"><b>Requirements=
</b></span></u></p>
<p class=3D"MsoNormal"><span style=3D"font-family:Arial">B.A., B.S. or equi=
valent with
background in psychology, neuroscience, biomedical engineering or related
field.</span><span style=3D"font-family:Helvetica">
</span><span style=3D"font-family:Arial">Candidates should have proficiency=
with basic computing packages such as
MS Word</span><span style=3D"font-family:Helvetica">
</span><span style=3D"font-family:Arial">and Excel, and will be familiar wi=
th experimental presentation packages
(e.g. E-Prime, Psychophysics Toolbox, Presentation) and standard statistica=
l
analysis software (e.g. MATLAB, R, SPSS).</span><span style=3D"font-family:=
Helvetica"> </span></p>
<p class=3D"MsoNormal"><span style=3D"font-family:Helvetica">=A0</span></p>
<p class=3D"MsoNormal"><span style=3D"font-family:Arial">Familiarity
with neuroimaging data analysis (e.g. SPM, FSL, AFNI, BrainVoyager) will co=
nfer
an advantage, as will prior experience with molecular genetics and/or
bioinformatics, but neither are necessary to receive consideration.=A0 </sp=
an></p>
<p class=3D"MsoNormal"><span style=3D"font-family:Arial">=A0</span></p>
<p class=3D"MsoNormal"><span style=3D"font-family:Arial">Strong interperson=
al skills,
prior research experience, high</span><span style=3D"font-family:Helvetica"=
> </span><span style=3D"font-family:Arial">level of organization with
careful attention to detail, and comfort with technical skills are</span><s=
pan style=3D"font-family:Helvetica">=A0absolutely=A0</span><span style=3D"f=
ont-family:Arial">required.
This position requires a high degree of motivation and self-sufficiency,</s=
pan><span style=3D"font-family:Helvetica"> </span><span style=3D"font-famil=
y:Arial">although
extensive training and supervision will be provided.</span><span style=3D"f=
ont-family:Helvetica"> </span></p>
<p class=3D"MsoNormal"><b><span style=3D"font-family:'Arial Black'"=
>=A0</span></b></p>
<p class=3D"MsoNormal"><u><span style=3D"font-family:Arial"><b>Details</b><=
/span></u></p>
<p class=3D"MsoNormal"><span style=3D"font-family:Arial">To apply, please e=
mail a brief
cover letter describing relevant experience, research interests and career
goals, CV and contact information to Dr. Joshua Buckholtz (Director, SNPlab=
) at=A0<a href=3D"mailto:[log in to unmask]" target=3D"_blank">harvar=
[log in to unmask]</a></span></p>
<p class=3D"MsoNormal"><span style=3D"font-family:Arial">=A0</span></p>
<p class=3D"MsoNormal"><span style=3D"font-family:Arial">All formal offers =
will be made by
Harvard FAS Human Resources.=A0 This
is a two-year term</span><span style=3D"font-family:Helvetica"> </span><spa=
n style=3D"font-family:Arial">position that is based in the Department of P=
sychology, with renewal dependent upon continuation of funding. Expected
start date: late summer 2011. This is an excellent and</span><span style=3D=
"font-family:Helvetica"> </span><span style=3D"font-family:Arial">unique
opportunity for a motivated individual to gain experience with cutting-edge
neuroscience in preparation for a graduate career.</span><span style=3D"fon=
t-family:Helvetica"> </span></p>
--20cf30025ae259e41a04a2953863--
=========================================================================
Date: Fri, 6 May 2011 09:49:27 +0200
Reply-To: "S.F.W. Neggers" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "S.F.W. Neggers" <[log in to unmask]>
Subject: PhD position at UMC Utrecht
MIME-Version: 1.0
Content-Type: multipart/mixed; boundary="------------000902040707040108010502"
Message-ID: <[log in to unmask]>
This is a multi-part message in MIME format.
--------------000902040707040108010502
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
content-transfer-encoding: 7bit
Dear list members,
there is a PhD position vacancy at the UMC Utrecht, the Netherlands, for
the project:
"brain connectomics: exploring the functional and structural brain network".
For more information, see attached or email Martijn van den Heuvel
(PhD). For contact information also see the attachment.
Regards,
Bas Neggers
--
--------------------------------------------------
Dr. S.F.W. Neggers
Division of Brain Research
Rudolf Magnus Institute for Neuroscience
Utrecht University Medical Center
Visiting : Heidelberglaan 100, 3584 CX Utrecht
Room B.01.1.03
Mail : Huispost B01.206, P.O. Box
3508 GA Utrecht, the Netherlands
Tel : +31 (0)88 7559609
Fax : +31 (0)88 7555443
E-mail : [log in to unmask]
Web : http://www.neuromri.nl/people/bas-neggers
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--------------000902040707040108010502--
=========================================================================
Date: Fri, 6 May 2011 10:48:37 +0200
Reply-To: Martin Dietz <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Martin Dietz <[log in to unmask]>
Subject: Re: EEG: Prepare SPM file
Comments: To: Jasmine Song <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Content-Type: text/plain; charset="us-ascii"
Content-Transfer-Encoding: quoted-printable
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
Hi Jasmine,
You should use the 'Convert' button to convert data. If this doesn't work h=
ave a look at the spm_eeg_convert_arbitrary_data in */spm8/man/example_scri=
pts/
Best wishes,
mMartin =20
On May 6, 2011, at 12:33 AM, Jasmine Song wrote:
> I have some problems to convert an eeg file into spm.
>=20
> When I click the "Prepare SPM file", the M/EEG prepare window does not po=
p up. Does anyone have same problem? I am running spm8 updated with r4290=
under MATLAB 2011a on MAC.=20
>=20
>=20
> Best,=20
> Jasmine=20
=========================================================================
Date: Fri, 6 May 2011 17:09:24 +0800
Reply-To: YAN Chao-Gan <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: YAN Chao-Gan <[log in to unmask]>
Subject: Re: Why the FDR result is different between the SPM5 and REST?
Comments: To: =?UTF-8?B?5Lyq5b2x?= <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=90e6ba6e8bce966c6904a297d8d1
Message-ID: <[log in to unmask]>
--90e6ba6e8bce966c6904a297d8d1
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Dear Li,
According to my understanding,
1. Can anyone tell me why the t value is even lower than the uncorrected t
value?
t=3D2.533749 (p<0.05, FDR corrected) would be higher than the t value o=
f
p<0.05 uncorrected. But if you compare p<0.05 (FDR corrected) with p<0.001
uncorrected, then it depends on the data.
2. The difference of FDR correction between SPM and REST .
SPM's FDR correction is based ONE-TAILED t test. However, it's suggeste=
d
to based on TWO-TAILED t test for REST's FDR correction in comparing two
groups .
3. The difference between SPM and REST's one-tailed FDR correction.
Basically, the FDR correction in SPM and in REST (if one-tailed
selected) are the same. However, I guess you have not choose any mask file
in REST FDR correction. In SPM, the FDR correction will use an implicit mas=
k
which generated in the "estimate" step (mask.img in the SPM.mat's
directory). If you set this mask for REST, then the FDR correction results
would be the same.
Hope these information helpful.
Best wishes!
Yours Sincerly,
Chao-Gan
2011/5/6 =E4=BC=AA=E5=BD=B1 <[log in to unmask]>
> Hi, everyone
>
> I found a problem. I used SPM5 to process the data and got the
> signifinance between two groups(p=3D0.001,t=3D3.929633, uncorrected). How=
ever,
> When I used FDR method(p=3D0.05) to correct the result, the output was
> t=3D2.533749. I am very confounded. Can anyone tell me why the t value is=
even
> lower than the uncorrected t value? In order to verify its reliability, I
> used another softerware(REST http://restfmri.net/) to test the result wit=
h
> FDR method(p=3D0.05). Strangely, I found the result was t=3D3.5232(one ta=
iled)
> and t=3D4.2774=EF=BC=81Can you explain this? I wonder whether there is so=
me problems
> with the SPM5 OR REST. Those who offer the help would be greatly
> appreciated.
>
> Li
>
--=20
YAN Chao-Gan, Ph.D.
State Key Laboratory of Cognitive Neuroscience and Learning
Beijing Normal University
Beijing, China, 100875
Phone: +86-10-58801023
[log in to unmask]
http://www.restfmri.net/forum/yanchaogan
--90e6ba6e8bce966c6904a297d8d1
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Dear Li,<br><br>According to my understanding, <br><br>1. Can anyone tell m=
e why the t value is even lower than the uncorrected t value?<br>=C2=A0=C2=
=A0=C2=A0 t=3D2.533749 (p<0.05, FDR corrected) would be higher than the =
t value of p<0.05 uncorrected. But if you compare p<0.05 (FDR correct=
ed) with p<0.001 uncorrected, then it depends on the data.<br>
<br>2. The difference of FDR correction between SPM and REST .<br>=C2=A0=C2=
=A0=C2=A0 SPM's FDR correction is based ONE-TAILED t test. However, it&=
#39;s suggested to based on TWO-TAILED t test for REST's FDR correction=
in comparing two groups .<br>
<br>3. The difference between SPM and REST's one-tailed FDR correction.=
<br>=C2=A0=C2=A0=C2=A0 Basically, the FDR correction in SPM and in REST (if=
one-tailed selected) are the same. However, I guess you have not choose an=
y mask file in REST FDR correction. In SPM, the FDR correction will use an =
implicit mask which generated in the "estimate" step (mask.img in=
the SPM.mat's directory). If you set this mask for REST, then the FDR =
correction results would be the same.<br>
<br>Hope these information helpful.<br><br>Best wishes!<br><br>Yours Sincer=
ly,<br>Chao-Gan<br><br><br><div class=3D"gmail_quote">2011/5/6 =E4=BC=AA=E5=
=BD=B1 <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">td=
[log in to unmask]</a>></span><br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex;"><div>Hi, everyone</div>
<div>=C2=A0</div>
<div>=C2=A0=C2=A0 =C2=A0 I found a problem. I used SPM5 to process the data=
and got the signifinance between two groups(p=3D0.001,t=3D3.929633, uncorr=
ected). However, When I used FDR method(p=3D0.05) to correct the result, th=
e output was t=3D2.533749. I am very confounded. Can anyone tell me why the=
t value is even lower than the uncorrected t value? In order to verify its=
reliability, I used another softerware(REST <a href=3D"http://restfmri.net=
/" target=3D"_blank">http://restfmri.net/</a>) to test the result with FDR =
method(p=3D0.05). Strangely, I found the result was t=3D3.5232(one tailed) =
and t=3D4.2774=EF=BC=81Can you explain this? I wonder whether there is some=
problems with the SPM5 OR REST. Those who offer the help would be greatly =
appreciated.</div>
<div>=C2=A0</div>
<div>Li</div></blockquote></div><br><br clear=3D"all"><br>-- <br>YAN Chao-G=
an, Ph.D.<br>State Key Laboratory of Cognitive Neuroscience and Learning<br=
>Beijing Normal University<br>Beijing, China, 100875 <br>Phone: +86-10-5880=
1023<br>
<a href=3D"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]</a=
><br><a href=3D"http://www.restfmri.net/forum/yanchaogan" target=3D"_blank"=
>http://www.restfmri.net/forum/yanchaogan</a><br>
--90e6ba6e8bce966c6904a297d8d1--
=========================================================================
Date: Fri, 6 May 2011 10:54:18 +0100
Reply-To: Saideh Ferdosi <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Saideh Ferdosi <[log in to unmask]>
Subject: Fwd: EEG-fMRI data
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0016364ecb7425be1804a2987950
Message-ID: <[log in to unmask]>
--0016364ecb7425be1804a2987950
Content-Type: text/plain; charset=ISO-8859-1
---------- Forwarded message ----------
From: Saideh Ferdosi <[log in to unmask]>
Date: Tue, Apr 26, 2011 at 12:31 PM
Subject: EEG-fMRI data
To: [log in to unmask]
Hi all,
'Does anyone know about a simultaneous EEG-fMRI data to download? I need
such a data preferably ERP for my research.
I really appreciate if anyone can help me.
Thanks
Saideh
--0016364ecb7425be1804a2987950
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
<br><br><div class=3D"gmail_quote">---------- Forwarded message ----------<=
br>From: <b class=3D"gmail_sendername">Saideh Ferdosi</b> <span dir=3D"ltr"=
><<a href=3D"mailto:[log in to unmask]">[log in to unmask]</=
a>></span><br>
Date: Tue, Apr 26, 2011 at 12:31 PM<br>Subject: EEG-fMRI data<br>To: <a hre=
f=3D"mailto:[log in to unmask]">[log in to unmask]</a><br><br><br><span sty=
le=3D"border-collapse:collapse;font-family:arial, sans-serif;font-size:13px=
">Hi all,<div>
<br></div><div>'Does anyone know about a=A0simultaneous EEG-fMRI data t=
o download? I need such a data preferably ERP for my research.</div>
<div>I really=A0appreciate if anyone can help me.=A0</div><div><br></div><d=
iv>Thanks</div><div>Saideh=A0</div></span>
</div><br>
--0016364ecb7425be1804a2987950--
=========================================================================
Date: Fri, 6 May 2011 11:59:20 +0200
Reply-To: "Zangl, Maria" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Zangl, Maria" <[log in to unmask]>
Subject: PostDoc- and PhD-positions at the Central Institute of Mental
Health in Germany (ZI Mannheim)
MIME-Version: 1.0
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boundary="----_=_NextPart_001_01CC0BD4.453D7B53"
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------_=_NextPart_001_01CC0BD4.453D7B53
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Dear list members, please notice the following open positions in our
neuroimaging lab.
=20
Best regards, Maria Zangl=20
=20
------------------------------------------------------------------------
--------------------------------------
=20
The Central Institute of Mental Health in Mannheim, Germany, is an
internationally renowned research institute in the field of psychiatry
and neuroscience, home of the Department of Psychiatry and Psychotherapy
of the Medical Faculty Mannheim of the University of Heidelberg, and a
psychiatric hospital with 255 inpatient and 52 day-clinic beds.
=20
=20
To strengthen our recently established independent neuroscience research
group funded by the Federal Ministry of Education and Research (BMBF),
the Clinic for Psychiatry and Psychotherapy (Medical Director: Prof. Dr.
med. Andreas Meyer-Lindenberg) offers =20
=20
1 PostDoc and 1 PhD-Student Position
=20
=20
in the area of functional and structural magnetic resonance imaging
(MRI). Positions are initially limited to 2 years, a prolongation is
intended.
=20
The Central Institute of Mental Health is equipped, among others, with
two Siemens 3 Tesla research MR scanners. Our research group consists of
an interdisciplinary team of psychologists, psychiatrists, neurologists,
biologists and technical assistants
(http://www.zi-mannheim.de/ag_imaging.html).
=20
The main goal of the international research project is to examine
fronto-striatal plasticity processes and their molecular genetic basis
in healthy individuals and psychiatric patients using multimodal
magnetic resonance imaging techniques (fMRI, morphometry, DTI,
spectroscopy). =20
=20
Ideally, potential applicants will have previous experience with the
acquisition, processing and analysis of MRI data, as well as a strong
interest in the application of systems neuroscience methods in the
context of neuropsychiatric research questions.=20
=20
We offer an interesting job in a pleasant working environment at a
leading German research institute. Salary is according to the German
TV-L pay scale, including the social benefits of the German public
service sector.
=20
For further information please contact Dr. Dr. Heike Tost, Tel. +49 621
1703-6508, E-Mail [log in to unmask]
<mailto:[log in to unmask]> .
____________________________________
=20
Maria Zangl, PhD-Student
Central Institute of Mental Health
Research Group Imaging in Psychiatry
J5, 68159 Mannheim, Germany
Phone: +49-621-1703-6514
Email: [log in to unmask] <mailto:[log in to unmask]>=20
=20
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vlink=3Dpurple><div class=3DWordSection1><p class=3DMsoNormal><span =
lang=3DEN-US>Dear list members, please notice the following open =
positions in our neuroimaging lab.<o:p></o:p></span></p><p =
class=3DMsoNormal><span lang=3DEN-US><o:p> </o:p></span></p><p =
class=3DMsoNormal><span lang=3DEN-US>Best regards, Maria Zangl =
<o:p></o:p></span></p><p class=3DMsoNormal><span =
lang=3DEN-US><o:p> </o:p></span></p><p class=3DMsoNormal><span =
lang=3DEN-US>------------------------------------------------------------=
--------------------------------------------------<o:p></o:p></span></p><=
p class=3DMsoNormal><span lang=3DEN-US><o:p> </o:p></span></p><p =
class=3DMsoNormal style=3D'text-align:justify;text-autospace:none'><span =
lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif"'>The =
Central Institute of Mental Health in Mannheim, Germany, is an =
internationally renowned research institute in the field of psychiatry =
and neuroscience, home of the Department of Psychiatry and Psychotherapy =
of the Medical Faculty Mannheim of the University of Heidelberg, and a =
psychiatric hospital with 255 inpatient and 52 day-clinic =
beds.<o:p></o:p></span></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif"'><o:p> =
</o:p></span></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif"'><o:p> =
</o:p></span></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif"'>To =
strengthen our recently established independent neuroscience research =
group funded by the Federal Ministry of Education and Research (BMBF), =
the Clinic for Psychiatry and Psychotherapy (Medical Director: Prof. Dr. =
med. Andreas Meyer-Lindenberg) offers <o:p></o:p></span></p><p =
class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><b><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif"'><o:p> =
</o:p></span></b></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><b><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif"'>1 PostDoc =
and 1 PhD-Student Position<o:p></o:p></span></b></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><b><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif"'><o:p> =
</o:p></span></b></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:black'=
><o:p> </o:p></span></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:black'=
>in the area of functional and structural magnetic resonance imaging =
(MRI). Positions are initially limited to 2 years, a prolongation is =
intended.<o:p></o:p></span></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:black'=
><o:p> </o:p></span></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:black'=
>The Central Institute of Mental Health is equipped, among others, with =
two Siemens 3 Tesla research MR scanners. Our research group consists of =
an interdisciplinary team of psychologists, psychiatrists, neurologists, =
biologists and technical assistants (</span><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:blue'>=
http://www.zi-mannheim.de/ag_imaging.html</span><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:black'=
>).<o:p></o:p></span></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:black'=
><o:p> </o:p></span></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:black'=
>The main goal of the international research project is to examine =
fronto-striatal plasticity processes and their molecular genetic basis =
in healthy individuals and psychiatric patients using multimodal =
magnetic resonance imaging techniques (fMRI, morphometry, DTI, =
spectroscopy). <o:p></o:p></span></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:black'=
><o:p> </o:p></span></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:black'=
>Ideally, potential applicants will have previous experience with the =
acquisition, processing and analysis of MRI data, as well as a strong =
interest in the application of systems neuroscience methods in the =
context of neuropsychiatric research questions. <o:p></o:p></span></p><p =
class=3DMsoNormal style=3D'text-align:justify;text-autospace:none'><span =
lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif"'><o:p> =
</o:p></span></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:black'=
>We offer an interesting job in a pleasant working environment at a =
leading German research institute. Salary is according to the German =
TV-L pay scale, including the social benefits of the German public =
service sector.<o:p></o:p></span></p><p class=3DMsoNormal =
style=3D'text-align:justify;text-autospace:none'><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:black'=
><o:p> </o:p></span></p><p class=3DMsoNormal><span lang=3DEN-US =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:black'=
>For further information please contact Dr. Dr. Heike Tost, Tel. =
</span><span =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:black'=
>+49 621 1703-6508, E-Mail </span><span style=3D'font-size:10.0pt'><a =
href=3D"mailto:[log in to unmask]"><span =
style=3D'font-family:"Verdana","sans-serif"'>[log in to unmask]</s=
pan></a></span><span =
style=3D'font-size:10.0pt;font-family:"Verdana","sans-serif";color:blue'>=
.</span><o:p></o:p></p><p class=3DMsoNormal><span =
style=3D'font-size:10.0pt;mso-fareast-language:DE'>______________________=
______________<o:p></o:p></span></p><p class=3DMsoNormal><span =
style=3D'font-size:10.0pt;mso-fareast-language:DE'><o:p> </o:p></spa=
n></p><p class=3DMsoNormal><span =
style=3D'font-size:10.0pt;mso-fareast-language:DE'>Maria Zangl, =
PhD-Student<o:p></o:p></span></p><p class=3DMsoNormal><span lang=3DEN-US =
style=3D'font-size:10.0pt;mso-fareast-language:DE'>Central Institute of =
Mental Health<o:p></o:p></span></p><p class=3DMsoNormal><span =
lang=3DEN-US style=3D'font-size:10.0pt;mso-fareast-language:DE'>Research =
Group Imaging in Psychiatry<o:p></o:p></span></p><p =
class=3DMsoNormal><span lang=3DEN-US =
style=3D'font-size:10.0pt;mso-fareast-language:DE'>J5, 68159 Mannheim, =
Germany<o:p></o:p></span></p><p class=3DMsoNormal><span =
style=3D'font-size:10.0pt;mso-fareast-language:DE'>Phone: =
+49-621-1703-6514<o:p></o:p></span></p><p class=3DMsoNormal><span =
lang=3DEN-US style=3D'font-size:10.0pt;mso-fareast-language:DE'>Email: =
</span><span style=3D'font-size:10.0pt;mso-fareast-language:DE'><a =
href=3D"mailto:[log in to unmask]"><span =
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<p class=3DMsoNormal><span =
lang=3DEN-US><o:p> </o:p></span></p></div></body></html>
------_=_NextPart_001_01CC0BD4.453D7B53--
=========================================================================
Date: Fri, 6 May 2011 11:35:29 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: Undefined command error
Comments: To: Jadzia Jagiellowicz <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
IOt sounds like you may not have installed SPM correctly. You should
have a directory somewhere called @nifti , which contains a file
called nifti.m . If this isn't the case, then it would appear that
there was an installation problem.
Best regards,
-John
On 5 May 2011 21:49, Jadzia Jagiellowicz <[log in to unmask]> wrote=
:
> Hello All,
>
> I'm getting an error
> "=A0Undefined command/function 'nifti'.
> 16=A0 N=A0 =3D nifti(fname);"
>
> every time I try to run command on a series of epi scans.
>
> I've spent about 14 hours trying to figure this out by searching the web,
> and can't quite understand the problem.
> I think it is something to do with setting a path, or the directory the
> files are in, but am not sure what.
> The scans=A0are in ANALYZE format and I'm using SPM5.
> Do my scans need to be in "nifti" format before I can realign and estimat=
e
> them? I had done the realignment previouisly with ANALYZE files and it
> worked.
>
>
> I've ran the Matlab debugger on the error and get the following response:
> Can anyone help me interpret what to do next and what is causing the erro=
r?
>
> V =3D spm_vol_nifti(fname,n)
>
> % Get header information for a NIFTI-1 image.
>
> % FORMAT V =3D spm_vol_nifti(P)
>
> % P - filename.
>
> % n - volume id (a 1x2 array, e.g. [3,1])
>
> % V - a structure containing the image volume information.
>
> %________________________________________________________________________=
____
>
> % Copyright (C) 2005 Wellcome Department of Imaging Neuroscience
>
> % John Ashburner
>
> % $Id: spm_vol_nifti.m 112 2005-05-04 18:20:52Z john $
>
> if
>
> nargin<2, n =3D [1 1]; end;
>
> if
>
> ischar(n), n =3D str2num(n); end;
>
> N =3D nifti(fname);
>
> n =3D [n 1 1];
>
> n =3D n(1:2);
>
> dm =3D [N.dat.dim 1 1 1 1];
>
> if
>
> any(n>dm(4:5)), V =3D []; return; end;
>
> dt =3D struct(N.dat);
>
> dt =3D double([dt.dtype dt.be]);
>
> if
>
> isfield(N.extras,'mat') && size(N.extras.mat,3)>=3Dn(1) &&
> sum(sum(N.extras.mat(:,:,n(1))))~=3D0,
>
> mat =3D N.extras.mat(:,:,n(1));
>
> else
>
> mat =3D N.mat;
>
> end
>
> ;
>
> off =3D (n(1)-1+dm(4)*(n(2)-1))*ceil(spm_type(dt(1),
>
> 'bits')*dm(1)*dm(2)/8)*dm(3) + N.dat.offset;
>
> V =3D struct(
>
> 'fname', N.dat.fname,...
>
> 'dim', dm(1:3),...
>
> 'dt', dt,...
>
> 'pinfo', [N.dat.scl_slope N.dat.scl_inter off]',...
>
> 'mat', mat,...
>
> 'n', n,...
>
> 'descrip', N.descrip,...
> 'private',N);
>
> Thanks in advance,
> Jadzia
> --
> Jadzia Jagiellowicz
> Doctoral Candidate
> Psychology Department B-207
> Stony Brook University,
> Stony Brook, NY 11794-2500 USA
> http://www.psychology.stonybrook.edu/aronlab-/
>
> "The brave shall inherit the earth."
>
=========================================================================
Date: Fri, 6 May 2011 12:39:49 +0200
Reply-To: Emilia Lentini <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Emilia Lentini <[log in to unmask]>
Subject: Re: flipped images
Comments: To: Michael Erb <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=002215046ca7eeb7e404a2991bfc
Message-ID: <[log in to unmask]>
--002215046ca7eeb7e404a2991bfc
Content-Type: text/plain; charset=ISO-8859-1
Thank you!
I want to evaluate regional asymmetries in grey and white matter, by using
flipped and non-flipped images in the same analysis e.g If Rhemisphere pre
frontal gyrus are different from Lhemisphere pre frontal gyrus.
How should I best set up the analysis?
Should I adjust for different sized hemispheres?
Do I need to normalize the flipped images in any other way than the
non-flipped images?
Best regards
Emilia
2011/5/5 Michael Erb <[log in to unmask]>
>
> Am 05.05.2011 14:51, schrieb Emilia Lentini:
>
> Hi.
>>
>> I would like to do a full-factorial analysis with both flipped
>> (right-left) and non-flipped images.
>>
>> To flip the images I use:
>> Display --> resize {x}: -1 and then reorient images..
>>
>> When I try to run the analysis I get following error:
>>
>> "Error running job: Error using ==> spm_check_orientations"
>>
>>
>> How can I correct for this error?
>>
> You have to reslice the images e.g. with Coregister(Reslice).
> Image Defining Space: a non-flipped image
> Images to Reslice: your flipped images
> afterwards you can delete your flipped images and use the resliced r*
> images.
>
> Regards,
> Michael.
>
>
>> Can I flip the images in any other way?
>>
>>
>> Best regards
>> Emilia
>>
>
> --
> <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
> Dr. Michael Erb
> Sektion f. experimentelle Kernspinresonanz des ZNS
> Abteilung Neuroradiologie, Universitaetsklinikum
> Hoppe-Seyler_Str. 3, D-72076 Tuebingen
> Tel.: +49(0)7071/2987753 priv. +49(0)7071/61559
> Fax.: +49(0)7071/294371
> e-mail: <[log in to unmask]>
> www: http://www.medizin.uni-tuebingen.de/nrad/sektion/
> <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
>
--002215046ca7eeb7e404a2991bfc
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
<br><div>Thank you!<br></div><div><br></div><div>I want to evaluate regiona=
l asymmetries in grey and white matter, by using flipped and non-flipped im=
ages in the same analysis e.g If Rhemisphere pre frontal gyrus are differen=
t from Lhemisphere pre frontal gyrus.</div>
<div><br></div><div>How should I best set up the analysis?</div><div>Should=
I adjust for different sized hemispheres?</div><div><br></div><div>Do I ne=
ed to normalize the flipped images in any other way than the non-flipped im=
ages?</div>
<div><br></div><div>Best regards</div><div>Emilia</div><div><br></div><div =
class=3D"gmail_quote">2011/5/5 Michael Erb <span dir=3D"ltr"><<a href=3D=
"mailto:[log in to unmask]">[log in to unmask]<=
/a>></span><br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex;"><br>
Am 05.05.2011 14:51, schrieb Emilia Lentini:<div class=3D"im"><br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex">
Hi.<br>
<br>
I would like to do a full-factorial analysis with both flipped<br>
(right-left) and non-flipped images.<br>
<br>
To flip the images I use:<br>
Display --> resize {x}: -1 and then reorient images..<br>
<br>
When I try to run the analysis I get following error:<br>
<br>
"Error running job: Error using =3D=3D> spm_check_orientations"=
;<br>
<br>
<br>
How can I correct for this error?<br>
</blockquote></div>
You have to reslice the images e.g. with Coregister(Reslice).<br>
Image Defining Space: a non-flipped image<br>
Images to Reslice: your flipped images<br>
afterwards you can delete your flipped images and use the resliced r* image=
s.<br>
<br>
Regards,<br>
Michael.<div class=3D"im"><br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex">
<br>
Can I flip the images in any other way?<br>
<br>
<br>
Best regards<br>
Emilia<br>
</blockquote>
<br></div>
-- <br>
<<<<<<<<<<<<<<<<<<<=
;<<<<<<<<<<<<<<<<<<&l=
t;<<<<<<<<<<<<<<<br>
Dr. Michael Erb<br>
Sektion f. experimentelle Kernspinresonanz des ZNS<br>
Abteilung Neuroradiologie, Universitaetsklinikum<br>
Hoppe-Seyler_Str. 3, =A0D-72076 Tuebingen<br>
Tel.: +49(0)7071/2987753 =A0 =A0priv. +49(0)7071/61559<br>
Fax.: +49(0)7071/294371<br>
e-mail: <<a href=3D"mailto:[log in to unmask]" target=3D"_=
blank">[log in to unmask]</a>><br>
www: <a href=3D"http://www.medizin.uni-tuebingen.de/nrad/sektion/" target=
=3D"_blank">http://www.medizin.uni-tuebingen.de/nrad/sektion/</a><br>
<<<<<<<<<<<<<<<<<<<=
;<<<<<<<<<<<<<<<<<<&l=
t;<<<<<<<<<<<<<<<br>
</blockquote></div><br>
--002215046ca7eeb7e404a2991bfc--
=========================================================================
Date: Fri, 6 May 2011 11:53:36 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: SPM8 - DICOM to nii conversion error
Comments: To: Kavita Vemuri <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Is it possible that there are 2500-3200 2D slices (each in a separate
file), which get concatenated to give 84 3D volumes?
The warning is there because the DICOM headers do not seem to contain
all the information needed to put the slices of data together in an
unambiguous way. The suggested fix would be to buy a scanner from a
different manufacturer (or maybe ask your local MR pulse-sequence
programmers about it). Hopefully, the heuristic approach used by the
DICOM conversion in SPM will work in most cases, but I can't
necessarily guarantee this.
Best regards,
-John
On 6 May 2011 05:46, Kavita Vemuri <[log in to unmask]> wrote:
> =A0Hi,
> =A0I am using SPM8 for fMRI. For each session of the experiment, there
> =A0are around 2500-3200 images. When I use the DICOM to nii converter
> =A0provided in SPM8, I notice that only 84 nii format data is generated.
> =A0On the matlab console, I see a message that says something like
> =A0-acquisition number not changing or DICOM images are repeated'.
> =A0Is there something wrong in the way I am converting?
>
> regards Kavita
>
>
>
>
=========================================================================
Date: Fri, 6 May 2011 12:39:29 +0100
Reply-To: "Stephen J. Fromm" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Stephen J. Fromm" <[log in to unmask]>
Subject: Re: Changing ANOVA design matrix according to the SPM8 version
Comments: To: [log in to unmask]
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
My first impression is that it's something to do with the nonsphericity c=
alculation.
I don't see that much difference in the code responsible for that, howeve=
r.
Only thing I can suggest is that you compare the contents of SPM.mat for =
the two models, specifically SPM.xVi, and see specifically where the diff=
erence is there. From that perhaps you can work backwards to see where t=
he difference is.
=========================================================================
Date: Fri, 6 May 2011 15:04:42 +0300
Reply-To: DANAY DIMA <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: DANAY DIMA <[log in to unmask]>
Subject: Comparing MEG-DCM models with different number of volumes of
interest
In-Reply-To: <[log in to unmask]>
Content-Type: multipart/alternative;
boundary="_f9e2c3c8-b1e7-4294-993c-b5e5e1897c6f_"
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
--_f9e2c3c8-b1e7-4294-993c-b5e5e1897c6f_
Content-Type: text/plain; charset="iso-8859-7"
Content-Transfer-Encoding: quoted-printable
Hi everyone
=20
I just wanted to check if we can compare directly MEG-DCM models with diffe=
rent number of volumes of interest?
Thanks in advance to anyone that answers!
=20
Best wishes=2C
=20
Danai =
--_f9e2c3c8-b1e7-4294-993c-b5e5e1897c6f_
Content-Type: text/html; charset="iso-8859-7"
Content-Transfer-Encoding: quoted-printable
<html>
<head>
<style><!--
.hmmessage P
{
margin:0px=3B
padding:0px
}
body.hmmessage
{
font-size: 10pt=3B
font-family:Tahoma
}
--></style>
</head>
<body class=3D'hmmessage'>
Hi everyone<BR>
 =3B<BR>
I just wanted to check if =3Bwe can compare directly MEG-DCM models wit=
h different number of volumes of interest?<BR><BR>
Thanks in advance to anyone that answers!<BR>
 =3B<BR>
Best wishes=2C<BR>
 =3B<BR>
Danai =3B<BR> </body>
</html>=
--_f9e2c3c8-b1e7-4294-993c-b5e5e1897c6f_--
=========================================================================
Date: Fri, 6 May 2011 13:41:19 +0100
Reply-To: Marta Garrido <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Marta Garrido <[log in to unmask]>
Subject: Re: Comparing MEG-DCM models with different number of volumes of
interest
Comments: To: DANAY DIMA <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf30549f057fc25d04a29aced2
Message-ID: <[log in to unmask]>
--20cf30549f057fc25d04a29aced2
Content-Type: text/plain; charset=ISO-8859-1
Dear Danai,
Yes, you can compare models with different number of sources - see
http://www.ncbi.nlm.nih.gov/pubmed/19261714
When you do this though, make sure that all your models contain all the
sources of the most complete model, and then turn off the connections you
don't need (for simpler models).
Hope this helps!
Marta
2011/5/6 DANAY DIMA <[log in to unmask]>
> Hi everyone
>
> I just wanted to check if we can compare directly MEG-DCM models with
> different number of volumes of interest?
>
> Thanks in advance to anyone that answers!
>
> Best wishes,
>
> Danai
>
--
Dr. Marta I. Garrido
Research Associate
Wellcome Trust Centre for Neuroimaging
University College London
12 Queen Square
London
WC1N 3BG
United Kingdom
Tel: +44(0)20 7833 7472 (ext: 4366)
Fax: +44(0)20 7813 1420
Email: [log in to unmask]
www: http://www.fil.ion.ucl.ac.uk
--20cf30549f057fc25d04a29aced2
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Dear Danai,<br><br>Yes, you can compare models with different number of sou=
rces - see <a href=3D"http://www.ncbi.nlm.nih.gov/pubmed/19261714">http://w=
ww.ncbi.nlm.nih.gov/pubmed/19261714</a><br>When you do this though, make su=
re that all your models contain all the sources of the most complete model,=
and then turn off the connections you don't need (for simpler models).=
=A0 <br>
<br>Hope this helps!<br><br>Marta<br><br><br><div class=3D"gmail_quote">201=
1/5/6 DANAY DIMA <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]
com">[log in to unmask]</a>></span><br><blockquote class=3D"gmail_quo=
te" style=3D"margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;=
">
<div>
Hi everyone<br>
=A0<br>
I just wanted to check if=A0we can compare directly MEG-DCM models with dif=
ferent number of volumes of interest?<br><br>
Thanks in advance to anyone that answers!<br>
=A0<br>
Best wishes,<br>
=A0<br>
Danai=A0<br> </div>
</blockquote></div><br><br clear=3D"all"><br>-- <br>Dr. Marta I. Garrido<br=
>Research Associate<br>Wellcome Trust Centre for Neuroimaging<br>University=
College London<br>12 Queen Square<br>London<br>WC1N 3BG<br>United Kingdom<=
br>
<br>Tel: +44(0)20 7833 7472 (ext: 4366)<br>Fax: +44(0)20 7813 1420<br>Email=
: <a href=3D"mailto:[log in to unmask]" target=3D"_blank">m.garrid=
[log in to unmask]</a><br>www: <a href=3D"http://www.fil.ion.ucl.ac.uk" ta=
rget=3D"_blank">http://www.fil.ion.ucl.ac.uk</a><br>
<br>
--20cf30549f057fc25d04a29aced2--
=========================================================================
Date: Fri, 6 May 2011 14:16:19 +0100
Reply-To: Michel Grothe <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michel Grothe <[log in to unmask]>
Subject: apply deformations VBM8/deformation utility
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear SPM-Experts (especially John and Christian :-)),
I=C2=B4m using DARTEL for intra- and subsequent inter-subject alignment o=
f VBM8-segments in a longitudinal study design. Segments (Intra-subject b=
ias-corrected) are written out as native (p1, p2, p3) and DARTEL-imported=
/rigidly aligned (rp1, rp2) images. Latter are used for DARTEL intra-subj=
ect alignment in SPM8 (create Template, rp1 and rp2 of BL and FU image; s=
moothing set to zero) and the resulting intra-subject (half-way) DARTEL_6=
-templates of all subjects are used for inter-subject alignment.
To reduce interpolation artifacts I aim to combine the individual intra-s=
ubject flow-fields (that map to the subject-specific DARTEL template) wit=
h the inter-subject flow-fields (subject-specific DARTEL_6 to group DARTE=
L-template) and apply just one warp. When specifying the flow-field combi=
nation in the Deformation Utility as outlined in the DARTEL-manual (i.e. =
first (top) the intra-subject and second (bottom) the inter-subject flow,=
both backwards) I get a y-field that accomplishes the desired warp from =
native VBM8-segment to the group DARTEL template (here I specify the p*-s=
egments; the information about the rigid-transform of the rp*-images seem=
s to get lost by combining the flow-fields, resulting in shifted/rotated =
wrp*-images compared to wp*-images and the group DARTEL-template respecti=
vely).
So far so good, but now I want to have the images modulated (i.e. mwp*), =
which seems not to be possible with the Deformations Utility and brings m=
e back to the VBM8-toolbox 'apply deformations'-tool. The unmodulated war=
p of this tool seems to be identical to the unmodulated warp of the Defor=
mation Utility, BUT voxel-values of the modulated warped segment are all =
negative (and 0 outside). Given that I=C2=B4ve succesfully used the VBM8 =
'apply deformations'-tool with modulation in previous studies it might be=
a bug that came with the last update. So I repeated the warp with an ear=
lier version of the VBM8-toolbox (which I had stored for reproducibility =
of previous studies), resulting in the following error:
Running 'Apply Deformations'
Failed 'Apply Deformations'
Undefined function or method 'spm_def2det' for input arguments of type 's=
ingle'.
In file "D:\spm8\toolbox\vbm8\cg_vbm8_defs.m" (v266), function "apply_def=
" at line 52.
In file "D:\spm8\toolbox\vbm8\cg_vbm8_defs.m" (v266), function "cg_vbm8_d=
efs" at line 13.
The following modules did not run:
Failed: Apply Deformations
Any idea what might have gone wrong here? Is there a fix for this or will=
I have to stick to the old approach of 'double-warping' and live with in=
terpolation effects?
Any help will be highly appreciated.
Best regards,
Michel=20=20=20=20
=========================================================================
Date: Fri, 6 May 2011 10:03:47 -0400
Reply-To: "Lee, Irene" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Lee, Irene" <[log in to unmask]>
Subject: About sample size determination based on the results of SPM
analysis
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=========================================================================
Date: Fri, 6 May 2011 17:19:46 +0200
Reply-To: Tatiana Usnich <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Tatiana Usnich <[log in to unmask]>
Subject: MSU for SPM8?
MIME-Version: 1.0
Content-Type: text/plain;charset=UTF-8
Content-Transfer-Encoding: 8bit
Message-ID: <[log in to unmask]>
Dear all,
We are looking for a tool for labeling brain regions in SPM8 as MSU tool
did for earlier versions.
Is there anything for that purpose?
Best regards,
Tatiana Usnich
=========================================================================
Date: Fri, 6 May 2011 15:25:02 +0000
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Comparing MEG-DCM models with different number of volumes of
interest
Comments: To: Marta Garrido <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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=========================================================================
Date: Fri, 6 May 2011 11:36:28 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: MSU for SPM8?
Comments: To: Tatiana Usnich <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Look at the VOI extraction tool at
http://www.martinos.org/~mclaren/peak_nii and earlier posts describing
the tool. It won't convert MNI coordinates to Talairach though.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General
Hospital and Harvard Medical School
Office: (773) 406-2464
=====================
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email.
On Fri, May 6, 2011 at 11:19 AM, Tatiana Usnich
<[log in to unmask]> wrote:
> Dear all,
>
> We are looking for a tool for labeling brain regions in SPM8 as MSU tool
> did for earlier versions.
>
> Is there anything for that purpose?
>
> Best regards,
> Tatiana Usnich
>
=========================================================================
Date: Fri, 6 May 2011 11:54:04 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: flipped images
Comments: To: Emilia Lentini <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
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Message-ID: <[log in to unmask]>
I'd recommend the following article:
Good et al. Cerebral asymmetry and the effects of sex and handedness
on brain structure: a voxel-based morphometric analysis of 465 normal
adult human brains. 2001
Briefly,
You segment and normalize your brains, then you flip them the brains
and the segments, then you average all the brains and segments (so 2
times as many images). Now you will have a customized set of tissue
priors. Now, flip the original images. Next, take the flipped and
unflipped images and normalize them to the new template. Now you can
do the statistics.
Best Regards, Donald McLaren
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General
Hospital and Harvard Medical School
Office: (773) 406-2464
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
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On Fri, May 6, 2011 at 6:39 AM, Emilia Lentini <[log in to unmask]> wr=
ote:
>
> Thank you!
>
> I want to evaluate regional asymmetries in grey and white matter, by usin=
g
> flipped and non-flipped images in the same analysis e.g If Rhemisphere pr=
e
> frontal gyrus are different from Lhemisphere pre frontal gyrus.
> How should I best set up the analysis?
> Should I adjust for different sized hemispheres?
> Do I need to normalize the flipped images in any other way than the
> non-flipped images?
> Best regards
> Emilia
> 2011/5/5 Michael Erb <[log in to unmask]>
>>
>> Am 05.05.2011 14:51, schrieb Emilia Lentini:
>>>
>>> Hi.
>>>
>>> I would like to do a full-factorial analysis with both flipped
>>> (right-left) and non-flipped images.
>>>
>>> To flip the images I use:
>>> Display --> resize {x}: -1 and then reorient images..
>>>
>>> When I try to run the analysis I get following error:
>>>
>>> "Error running job: Error using =3D=3D> spm_check_orientations"
>>>
>>>
>>> How can I correct for this error?
>>
>> You have to reslice the images e.g. with Coregister(Reslice).
>> Image Defining Space: a non-flipped image
>> Images to Reslice: your flipped images
>> afterwards you can delete your flipped images and use the resliced r*
>> images.
>>
>> Regards,
>> Michael.
>>>
>>> Can I flip the images in any other way?
>>>
>>>
>>> Best regards
>>> Emilia
>>
>> --
>> <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
>> Dr. Michael Erb
>> Sektion f. experimentelle Kernspinresonanz des ZNS
>> Abteilung Neuroradiologie, Universitaetsklinikum
>> Hoppe-Seyler_Str. 3, =A0D-72076 Tuebingen
>> Tel.: +49(0)7071/2987753 =A0 =A0priv. +49(0)7071/61559
>> Fax.: +49(0)7071/294371
>> e-mail: <[log in to unmask]>
>> www: http://www.medizin.uni-tuebingen.de/nrad/sektion/
>> <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
>
>
=========================================================================
Date: Fri, 6 May 2011 09:11:22 -0700
Reply-To: Siddharth Srivastava <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Siddharth Srivastava <[log in to unmask]>
Subject: Re: spm_affreg
Comments: To: John Ashburner <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
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--20cf307cfcb6af5c6204a29dbdcd
Content-Type: text/plain; charset=ISO-8859-1
Hi everyone,
Can someone help me check the 2D versions of the spm_matrix and
spm_imatrix? My
implementation currently is as follows:
---2D spm_matrix ---
function [A] = spm_matrix2D(P)
% P = [Tx, Ty, R, Zx, Zy, Sx,Sy]
p0 = [0,0,0,1,1,0,0];
P = [P, p0((length(P)+1):7)]
A = eye(3);
% T -> R -> Zoom -> Shear
A = A * [1,0,P(1); ...
0,1,P(2); ...
0,0, 1];
A = A * [cos(P(3)), sin(P(3)), 0; ...
-sin(P(3)), cos(P(3)), 0; ...
0, 0, 1];
A = A * [P(4), 0, 0; ...
0, P(5), 0; ...
0, 0, 1];
A = A * [1, P(6), 0; ...
P(7) , 1, 0; ...
0, 0, 1];
--------------------------------------------------
-----2D spm_imatrix ------------------------
function P = spm_imatrix2D(M);
R = M(1:2,1:2);
C = chol(R' * R);
P = [M(1:2,3)',0,diag(C)',0,0];
if(det(R) < 0) P(4) = -P(4); end
C = diag(diag(C))\C;
P(6:7) = C([2,3]);
R0 = spm_matrix2D([0,0,0,P(4:end)]);
R0 = R0(1:2,1:2);
R1 = R/R0;
th = asin(rang(R1(1,2)));
P(3) = th;
% There may be slight rounding errors making b>1 or b<-1.
function a = rang(b)
a = min(max(b, -1), 1);
return;
---------------------------------------------------------------------------
I know there is something not correct, since when, for a parameter set 'p',
i do spm_imatrix2D(spm_matrix2D(p)), I do not recover P for all entries,
specially
rotation and shears. C(2) above always evaluates to zero. The result is that
these errors
accumulate (or are not accounted for) on repeated application of this
sequence of
operations in the registration routine.
Thanks in anticipation,
Sid.
On Fri, Apr 22, 2011 at 9:13 AM, Siddharth Srivastava <[log in to unmask]>wrote:
> Hi John,
> Thanks a lot for your answer, and it has been very helpful for my
> understanding
> of the details of the implementation, and my own development efforts. I
> have
> 2 very quick questions, though:
>
> 1) the parameter set x(:) that is returned from spm_mireg, and the "params"
> that
> spm_affsub3 returns (in spm99, which is also the version that I am looking
> at) ,
> are they equivalent? In other words, If I am collating the parameters from
> the mireg
> routine, would the distribution x(7:12) be used to estimate the icovar0
> entries in affsub3?
>
> 2) also would VG.mat\spm_matrix(x)*VF.mat transform G to F similar to
> VG.mat\spm_matrix(params)*VF.mat , or do I have to do
> M = VG.mat\spm_matrix(x(:)')*VF.mat
> pp = spm_imatrix(M)
> and use pp(7:12) ?
>
>
>
> Thanks again.
> Sid.
>
> On Thu, Apr 14, 2011 at 2:13 PM, John Ashburner <[log in to unmask]>wrote:
>
>> > I had a look at the code in spm_maff, and
>> > it looks like it also uses the values of isig and mu in the call to
>> > affreg(). My guess is
>> > that during the initial registration on a large data set for estimating
>> the
>> > prior
>> > distribution of parameters, this will be called with typ = 'none' . Is
>> this
>> > correct?
>>
>> Once the registration has locked in on a solution, the priors have
>> less influence. Their main influence is in the early stages of the
>> registration, or when there are relatively few slices in the data. I
>> don't actually remember if the registration was regularised when I
>> computed their values.
>>
>> >
>> > Further, do we have to do a non-rigid registration for the estimation
>> > (since, in the comments the selected
>> > files are filtered as *seg_inv_sn.mat"? Since only p.Affine is being
>> used,
>> > can this work with only
>> > an affine / rigid transformation?
>>
>> Only the affine transform in the files is used, so basically yes. You
>> could just do affine registration.
>>
>> >
>> > I would also be happy if you could also answer my other question about
>> > examining the
>> > effects of the values in isig and mu (what are the units of mu?) on the
>> > transformed image.
>>
>> They are unit-less, and are just a measure of the zooms and shears.
>>
>> > For example,
>> > if i set a mu of [mu1, mu2, ...] and a isig of [sig1, 0, 0...; 0, sig2,
>> 0,
>> > 0..; ...] (with only diagonal components),
>> > based on the Hencky tensor penalty, it seems that large deviations of
>> > parameter 1 estimate (T - mu) from
>> > mu1 will be penalized. How is the value of isig1 modifying the penalty?
>>
>> Its assuming that the elements of the matrix log of the part that does
>> shears and zooms has a multivariate normal distribution, so the
>> penalty is a kind of negative log likelhood. The isig is essentially
>> a precision matrix, which is the inverse of a covariance matrix.
>>
>> p(x|mu,S) = 1/sqrt(det(2*pi*S)) * exp(-0.5*(x-mu)'*inv(S)*(x-mu))
>>
>> Taking logs and negating, you get 0.5*(x-mu)'*inv(S)*(x-mu) + const
>>
>> > How
>> > do the off diagonal terms affect
>> > the penalty?
>>
>> The inverse of isig would just encode the covariance between the
>> various shears and zooms.
>>
>> >
>> > Could you also point me to a reference where I can learn more about
>> Hencky
>> > strain tensor (specifically
>> > what information it carries in the context of image processing etc.)
>>
>> I don't know if this is of any use:
>>
>> http://en.wikipedia.org/wiki/Deformation_(mechanics)
>>
>> Best regards,
>> -John
>>
>>
>> > On Thu, Apr 14, 2011 at 10:17 AM, John Ashburner <[log in to unmask]>
>> > wrote:
>> >>
>> >> They were computed by affine registering loads of (227) images to MNI
>> >> space. This gave the affine transforms, which were then used to build
>> >> up a mean and inverse covariance matrix. In the comments of
>> >> spm_maff.m, you should see the following...
>> >>
>> >> %% Values can be derived by...
>> >> %sn = spm_select(Inf,'.*seg_inv_sn.mat$');
>> >> %X = zeros(size(sn,1),12);
>> >> %for i=1:size(sn,1),
>> >> % p = load(deblank(sn(i,:)));
>> >> % M = p.VF(1).mat*p.Affine/p.VG(1).mat;
>> >> % J = M(1:3,1:3);
>> >> % V = sqrtm(J*J');
>> >> % R = V\J;
>> >> % lV = logm(V);
>> >> % lR = -logm(R);
>> >> % P = zeros(12,1);
>> >> % P(1:3) = M(1:3,4);
>> >> % P(4:6) = lR([2 3 6]);
>> >> % P(7:12) = lV([1 2 3 5 6 9]);
>> >> % X(i,:) = P';
>> >> %end;
>> >> %mu = mean(X(:,7:12));
>> >> %XR = X(:,7:12) - repmat(mu,[size(X,1),1]);
>> >> %isig = inv(XR'*XR/(size(X,1)-1))
>> >>
>> >> You may be able to re-code this to work with your 2D transforms. Note
>> >> that I only use the components that describe shears and zooms. Also,
>> >> if I was re-coding it all again, I would probably do things slightly
>> >> differently, using the following decomposition:
>> >>
>> >> J=M(1:3,1:3);
>> >> L=real(logm(J));
>> >> S=(L+L')/2; % Symmetric part (for zooms and shears, which should be
>> >> penalised)
>> >> A=(L-L')/2; % Anti-symmetric part (for rotations)
>> >>
>> >> I might even base the penalty on lambda(2)*trace(S)^2 +
>> >> lambda(1)*trace(S*S'), which is often used as a measure of "elastic
>> >> energy" for penalising non-linear registration. Of course, there
>> >> would also be a bit of annoying extra stuff to deal with due to MNI
>> >> space being a bit bigger than average brains are. Figuring out the
>> >> mean would require (I think) an iterative process similar to the one
>> >> described in "Characterizing volume and surface deformations in an
>> >> atlas framework: theory, applications, and implementation", by Woods
>> >> in NeuroImage (2003).
>> >>
>> >> Best regards,
>> >> -John
>> >>
>> >> On 14 April 2011 17:15, Siddharth Srivastava <[log in to unmask]> wrote:
>> >> > Hi all,
>> >> > My question pertains specifically to the values of isig and mu
>> that
>> >> > are
>> >> > incorporated
>> >> > in the code, and I wish to disentangle the effect that these numbers
>> >> > have on
>> >> > individual parameters
>> >> > during the optimization stage. I am trying to map it to a 2D case,
>> and
>> >> > these
>> >> > numbers
>> >> > will have to be calculated ab-initio for my case. Before I begin with
>> >> > estimating the prior distribution
>> >> > for these parameters, I need to check the effect that they have on
>> the
>> >> > registered images. Regarding this
>> >> > 1) Can someone suggest a way I can examine the effect on each
>> parameter
>> >> > separately, if it is
>> >> > at all possible.
>> >> > 2) Some advise on how to estimate these parameters, if it has been
>> done
>> >> > for
>> >> > images other
>> >> > than brain images, will be really helpful for me.
>> >> >
>> >> > Thanks,
>> >> > Sid.
>> >> >
>> >> > On Mon, Mar 28, 2011 at 7:04 PM, Siddharth Srivastava <
>> [log in to unmask]>
>> >> > wrote:
>> >> >>
>> >> >> Dear John,
>> >> >> Thanks for your answer. I was able to correctly run my 2D
>> >> >> implementation
>> >> >> based on your advise. However, I am am not very confident of my
>> results
>> >> >> and wanted to
>> >> >> consult you on certain aspects of my mapping from 3D to 2D.
>> >> >> 1) In function reg(..), the comment says that the
>> >> >> derivatives
>> >> >> w.r.t rotations and
>> >> >> translations is zero. Consequently, I ran the indices from 4:7.
>> >> >> According
>> >> >> to your previous
>> >> >> reply, rotations will be lumped together with scaling and affine in
>> 4
>> >> >> parameters, and
>> >> >> translations, independently, in the last two. I understand that in
>> this
>> >> >> case, the indices
>> >> >> run over parameters that have been separated into individual
>> components
>> >> >> (similar to
>> >> >> the form accepted by spm_matrix). Is this correct for the function
>> >> >> reg(..)? In fact, I went back to the
>> >> >> old spm code (spm99), and found parameters pdesc and free, and got
>> more
>> >> >> confused as to when I should
>> >> >> use the 6 parameter, and when to use separate parameters (as if I
>> was
>> >> >> passing them to spm_matrix).
>> >> >> So, when the loop runs over p1 and perturbs p1(i) by ds, does it run
>> >> >> over
>> >> >> translations/rotations etc
>> >> >> or does it run over the martix elements that define these
>> >> >> transformations
>> >> >> (2x2 + 1x2)?
>> >> >>
>> >> >> 2) In function penalty(..), I have used unique elements
>> as
>> >> >> [1,3,4], and my code looks like
>> >> >> T = my_matrix(p)*M;
>> >> >> T = T(1:2,1:2);
>> >> >> T = 0.5*logm(T'*T);
>> >> >> T
>> >> >> T = T(els)' - mu;
>> >> >> h = T'*isig*T
>> >> >>
>> >> >> Assuming an application specific isig, is this correct?
>> >> >> 3) I have not yet incorporated the prior information in my
>> >> >> code,
>> >> >> But for testing purposes,
>> >> >> can you suggest some neutral values for mu and isig that I can try
>> to
>> >> >> concentrate on the
>> >> >> accuracy of the implementation minus the priors for now?
>> >> >> 4) My solution curently seems to oscillate around an
>> optimum.
>> >> >> I
>> >> >> am hoping that after
>> >> >> I have removed any errors after your replies, it will converge
>> >> >> gracefully.
>> >> >>
>> >> >> Thanks again for all the help.
>> >> >> Siddharth.
>> >> >>
>> >> >>
>> >> >> On Fri, Mar 18, 2011 at 2:05 AM, John Ashburner <
>> [log in to unmask]>
>> >> >> wrote:
>> >> >>>
>> >> >>> A 2D affine transform would use 6 parameters, rather than 7: a 2x2
>> >> >>> matrix to encode rotations, zooms and shears, and a 2x1 vector for
>> >> >>> translations.
>> >> >>>
>> >> >>> Best regards,
>> >> >>> -John
>> >> >>>
>> >> >>> On 18 March 2011 05:05, Siddharth Srivastava <[log in to unmask]>
>> wrote:
>> >> >>> > Dear list users,
>> >> >>> > I am currently trying to understand the implementation
>> in
>> >> >>> > spm_affreg, and
>> >> >>> > to make matters simple, I tried to work out a 2D version of the
>> >> >>> > registration
>> >> >>> > procedure. I struck a roadblock, however...
>> >> >>> >
>> >> >>> > The function make_A creates part of the design matrix. For the 3D
>> >> >>> > case,
>> >> >>> > the
>> >> >>> > 13 parameters
>> >> >>> > are encoded in columns of A1, which then is used to generate AA +
>> >> >>> > A1'
>> >> >>> > A1. AA
>> >> >>> > is 13x13, and everything
>> >> >>> > works. For the 2D case, however, there will be 7+1 parameters( 2
>> >> >>> > translations, 1 rotation, 2 zoom, 2 shears and 1 intensity
>> scaling).
>> >> >>> > The A1 matrix for 2D, then, will be (in make_A)
>> >> >>> > A = [x1.*dG1 x1.*dG2 ...
>> >> >>> > x2.*dG1 x2.*dG2 ...
>> >> >>> > dG1 dG2 t];
>> >> >>> >
>> >> >>> > which is (number of sampled points) x 7. The AA matrix (in
>> function
>> >> >>> > costfun)
>> >> >>> > is 8x8
>> >> >>> > so, which is the parameter I am missing in modeling a 2D example?
>> I
>> >> >>> > hope I
>> >> >>> > have got the number of parameters
>> >> >>> > right for the 2D case? Is there an extra column that I have to
>> add
>> >> >>> > to
>> >> >>> > A1 to
>> >> >>> > make the rest of the matrix computation
>> >> >>> > consistent?
>> >> >>> >
>> >> >>> > Thanks for the help
>> >> >>> >
>> >> >>
>> >> >
>> >> >
>> >
>> >
>>
>
>
--20cf307cfcb6af5c6204a29dbdcd
Content-Type: text/html; charset=ISO-8859-1
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Hi everyone,<br>=A0=A0=A0=A0=A0 Can someone help me check the 2D versions o=
f the spm_matrix and spm_imatrix? My <br>implementation currently is as fol=
lows:<br><br>---2D spm_matrix ---<br>function [A] =3D spm_matrix2D(P)<br>% =
P =3D [Tx, Ty, R, Zx, Zy, Sx,Sy] <br>
p0 =3D [0,0,0,1,1,0,0];<br>P =3D [P, p0((length(P)+1):7)]<br><br>A =3D eye(=
3);<br>% T -> R -> Zoom -> Shear<br>=A0A =3D=A0=A0=A0=A0 A * [1,0,=
P(1); ...<br>=A0=A0=A0=A0=A0=A0=A0=A0=A0 0,1,P(2); ...<br>=A0 =A0=A0=A0 =A0=
0,0,=A0=A0 1];<br>=A0A =3D=A0=A0=A0=A0 A * [cos(P(3)), sin(P(3)), 0; ...<b=
r>
=A0=A0=A0=A0=A0=A0=A0=A0=A0 -sin(P(3)),=A0 cos(P(3)), 0; ...<br>=A0=A0=A0 =
=A0 0,=A0=A0=A0=A0=A0=A0=A0=A0=A0 0,=A0=A0=A0=A0=A0=A0=A0=A0 1];<br>=A0A =
=3D=A0=A0=A0=A0 A * [P(4), 0, 0; ...<br>=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=
=A0=A0 0,=A0=A0 P(5), 0; ...<br>=A0=A0=A0 =A0=A0=A0=A0=A0 0, 0, 1];<br>=A0A=
=3D=A0=A0=A0=A0 A * [1, P(6), 0; ...<br>=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=
=A0=A0 P(7)=A0 , 1, 0; ...<br>
=A0=A0=A0 =A0=A0=A0=A0=A0 0, 0, 1];<br>------------------------------------=
--------------<br>-----2D spm_imatrix ------------------------<br>function =
P =3D=A0 spm_imatrix2D(M);<br><br><br><br>R =3D M(1:2,1:2);<br>C =3D chol(R=
' * R);<br>P =3D [M(1:2,3)',0,diag(C)',0,0];<br>
if(det(R) < 0) P(4) =3D -P(4); end<br>C =3D diag(diag(C))\C;<br>P(6:7) =
=3D C([2,3]);<br><br>R0 =3D spm_matrix2D([0,0,0,P(4:end)]);<br>R0 =3D R0(1:=
2,1:2);<br>R1 =3D R/R0;<br><br>th =3D asin(rang(R1(1,2)));<br>P(3) =3D th;<=
br><br>% There may be slight rounding errors making b>1 or b<-1.<br>
function=A0 a =3D rang(b)<br>a =3D min(max(b, -1), 1);<br>return;<br>------=
---------------------------------------------------------------------<br><b=
r>I know there is something not correct, since when, for a parameter set &#=
39;p',<br>
i do spm_imatrix2D(spm_matrix2D(p)), I do not recover P for all entries, sp=
ecially<br>rotation and shears. C(2) above always evaluates to zero. The re=
sult is that these errors <br>accumulate (or are not accounted for) on repe=
ated application of this sequence of<br>
operations in the registration routine.<br><br>Thanks in anticipation,<br>S=
id. <br><br><br><br><div class=3D"gmail_quote">On Fri, Apr 22, 2011 at 9:13=
AM, Siddharth Srivastava <span dir=3D"ltr"><<a href=3D"mailto:siddys@gm=
ail.com">[log in to unmask]</a>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; borde=
r-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">Hi John,<br>=A0=
=A0=A0=A0=A0 Thanks a lot for your answer, and it has been very helpful for=
my understanding <br>
of the details of the implementation, and my own development efforts. I hav=
e <br>2 very quick questions, though:<br><br>
1) the parameter set x(:) that is returned from spm_mireg, and the "pa=
rams" that<br>spm_affsub3 returns (in spm99, which is also the version=
that I am looking at) , <br>are they equivalent? In other words, If I am c=
ollating the parameters from the mireg<br>
routine, would the distribution x(7:12) be used to estimate the icovar0 ent=
ries in affsub3?<br><br>2) also would VG.mat\spm_matrix(x)*VF.mat transform=
G to F similar to <br>=A0=A0=A0=A0 VG.mat\spm_matrix(params)*VF.mat , or d=
o I have to do<br>
=A0=A0=A0=A0=A0 M =3D VG.mat\spm_matrix(x(:)')*VF.mat<br>=A0=A0=A0=A0=
=A0 pp =3D spm_imatrix(M)<br>=A0=A0=A0=A0=A0 and use pp(7:12) ? <br><br><br=
><br>Thanks again.<br>Sid. <br><div><div></div><div class=3D"h5"><br><div c=
lass=3D"gmail_quote">On Thu, Apr 14, 2011 at 2:13 PM, John Ashburner <span =
dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]" target=3D"_blank">j=
[log in to unmask]</a>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; borde=
r-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;"><div>> I had a=
look at the code in spm_maff, and<br>
> it looks like it also uses the values of isig and mu in the call to<br=
>
> affreg(). My guess is<br>
> that during the initial registration on a large data set for estimatin=
g the<br>
> prior<br>
> distribution of parameters, this will be called with typ =3D 'none=
' . Is this<br>
> correct?<br>
<br>
</div>Once the registration has locked in on a solution, the priors have<br=
>
less influence. =A0Their main influence is in the early stages of the<br>
registration, or when there are relatively few slices in the data. =A0I<br>
don't actually remember if the registration was regularised when I<br>
computed their values.<br>
<div><br>
><br>
> Further, do we have to do a non-rigid registration for the estimation<=
br>
> (since, in the comments the selected<br>
> files are filtered as *seg_inv_sn.mat"? Since only p.Affine is be=
ing used,<br>
> can this work with only<br>
> an affine / rigid transformation?<br>
<br>
</div>Only the affine transform in the files is used, so basically yes. =A0=
You<br>
could just do affine registration.<br>
<div><br>
><br>
> I would also be happy if you could also answer my other question about=
<br>
> examining the<br>
> effects of the values in isig and mu (what are the units of mu?) on th=
e<br>
> transformed image.<br>
<br>
</div>They are unit-less, and are just a measure of the zooms and shears.<b=
r>
<div><br>
> For example,<br>
> if i set a mu of [mu1, mu2, ...] and a isig of [sig1, 0, 0...; 0, sig2=
, 0,<br>
> 0..; ...] (with only diagonal components),<br>
> based on the Hencky tensor penalty, it seems that large deviations of<=
br>
> parameter 1=A0 estimate (T - mu) from<br>
> mu1 will be penalized. How is the value of isig1 modifying the penalty=
?<br>
<br>
</div>Its assuming that the elements of the matrix log of the part that doe=
s<br>
shears and zooms has a multivariate normal distribution, so the<br>
penalty is a kind of negative log likelhood. =A0The isig is essentially<br>
a precision matrix, which is the inverse of a covariance matrix.<br>
<br>
p(x|mu,S) =3D 1/sqrt(det(2*pi*S)) * exp(-0.5*(x-mu)'*inv(S)*(x-mu))<br>
<br>
Taking logs and negating, you get 0.5*(x-mu)'*inv(S)*(x-mu) + const<br>
<div><br>
> How<br>
> do the off diagonal terms affect<br>
> the penalty?<br>
<br>
</div>The inverse of isig would just encode the covariance between the<br>
various shears and zooms.<br>
<div><br>
><br>
> Could you also point me to a reference where I can learn more about He=
ncky<br>
> strain tensor (specifically<br>
> what information it carries in the context of image processing etc.)<b=
r>
<br>
</div>I don't know if this is of any use:<br>
<br>
<a href=3D"http://en.wikipedia.org/wiki/Deformation_%28mechanics%29" target=
=3D"_blank">http://en.wikipedia.org/wiki/Deformation_(mechanics)</a><br>
<br>
Best regards,<br>
<font color=3D"#888888">-John<br>
</font><div><div></div><div><br>
<br>
> On Thu, Apr 14, 2011 at 10:17 AM, John Ashburner <<a href=3D"mailto=
:[log in to unmask]" target=3D"_blank">[log in to unmask]</a>><br>
> wrote:<br>
>><br>
>> They were computed by affine registering loads of (227) images to =
MNI<br>
>> space. =A0This gave the affine transforms, which were then used to=
build<br>
>> up a mean and inverse covariance matrix. =A0In the comments of<br>
>> spm_maff.m, you should see the following...<br>
>><br>
>> %% Values can be derived by...<br>
>> %sn =3D spm_select(Inf,'.*seg_inv_sn.mat$');<br>
>> %X =A0=3D zeros(size(sn,1),12);<br>
>> %for i=3D1:size(sn,1),<br>
>> % =A0 =A0p =A0=3D load(deblank(sn(i,:)));<br>
>> % =A0 =A0M =A0=3D p.VF(1).mat*p.Affine/p.VG(1).mat;<br>
>> % =A0 =A0J =A0=3D M(1:3,1:3);<br>
>> % =A0 =A0V =A0=3D sqrtm(J*J');<br>
>> % =A0 =A0R =A0=3D V\J;<br>
>> % =A0 =A0lV =A0 =A0 =A0=3D =A0logm(V);<br>
>> % =A0 =A0lR =A0 =A0 =A0=3D -logm(R);<br>
>> % =A0 =A0P =A0 =A0 =A0 =3D zeros(12,1);<br>
>> % =A0 =A0P(1:3) =A0=3D M(1:3,4);<br>
>> % =A0 =A0P(4:6) =A0=3D lR([2 3 6]);<br>
>> % =A0 =A0P(7:12) =3D lV([1 2 3 5 6 9]);<br>
>> % =A0 =A0X(i,:) =A0=3D P';<br>
>> %end;<br>
>> %mu =A0 =3D mean(X(:,7:12));<br>
>> %XR =A0 =3D X(:,7:12) - repmat(mu,[size(X,1),1]);<br>
>> %isig =3D inv(XR'*XR/(size(X,1)-1))<br>
>><br>
>> You may be able to re-code this to work with your 2D transforms. =
=A0Note<br>
>> that I only use the components that describe shears and zooms. =A0=
Also,<br>
>> if I was re-coding it all again, I would probably do things slight=
ly<br>
>> differently, using the following decomposition:<br>
>><br>
>> J=3DM(1:3,1:3);<br>
>> L=3Dreal(logm(J));<br>
>> S=3D(L+L')/2; % Symmetric part (for zooms and shears, which sh=
ould be<br>
>> penalised)<br>
>> A=3D(L-L')/2; % Anti-symmetric part (for rotations)<br>
>><br>
>> I might even base the penalty on lambda(2)*trace(S)^2 +<br>
>> lambda(1)*trace(S*S'), which is often used as a measure of &qu=
ot;elastic<br>
>> energy" for penalising non-linear registration. =A0Of course,=
there<br>
>> would also be a bit of annoying extra stuff to deal with due to MN=
I<br>
>> space being a bit bigger than average brains are. =A0Figuring out =
the<br>
>> mean would require (I think) an iterative process similar to the o=
ne<br>
>> described in "Characterizing volume and surface deformations =
in an<br>
>> atlas framework: theory, applications, and implementation", b=
y Woods<br>
>> in NeuroImage (2003).<br>
>><br>
>> Best regards,<br>
>> -John<br>
>><br>
>> On 14 April 2011 17:15, Siddharth Srivastava <<a href=3D"mailto=
:[log in to unmask]" target=3D"_blank">[log in to unmask]</a>> wrote:<br>
>> > Hi all,<br>
>> > =A0=A0=A0=A0 My question pertains specifically to the values =
of isig and mu that<br>
>> > are<br>
>> > incorporated<br>
>> > in the code, and I wish to disentangle the effect that these =
numbers<br>
>> > have on<br>
>> > individual parameters<br>
>> > during the optimization stage. I am trying to map it to a 2D =
case, and<br>
>> > these<br>
>> > numbers<br>
>> > will have to be calculated ab-initio for my case. Before I be=
gin with<br>
>> > estimating the prior distribution<br>
>> > for these parameters, I need to check the effect that they ha=
ve on the<br>
>> > registered images. Regarding this<br>
>> > 1) Can someone suggest a way I can examine the effect on each=
parameter<br>
>> > separately, if it is<br>
>> > =A0=A0=A0=A0 at all possible.<br>
>> > 2) Some advise on how to estimate these parameters, if it has=
been done<br>
>> > for<br>
>> > images other<br>
>> > =A0=A0=A0=A0 than brain images, will be really helpful for me=
.<br>
>> ><br>
>> > Thanks,<br>
>> > Sid.<br>
>> ><br>
>> > On Mon, Mar 28, 2011 at 7:04 PM, Siddharth Srivastava <<a =
href=3D"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]</a>>=
<br>
>> > wrote:<br>
>> >><br>
>> >> Dear John,<br>
>> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 Thanks for your answer. I was=
able to correctly run my 2D<br>
>> >> implementation<br>
>> >> based on your advise. However, I am am not very confident=
of my results<br>
>> >> and wanted to<br>
>> >> consult you on certain aspects of my mapping from 3D to 2=
D.<br>
>> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 1) In function reg(..), th=
e comment says that the<br>
>> >> derivatives<br>
>> >> w.r.t rotations and<br>
>> >> translations is zero. Consequently, I ran the indices fro=
m 4:7.<br>
>> >> According<br>
>> >> to your previous<br>
>> >> reply, rotations will be lumped together with scaling and=
affine in 4<br>
>> >> parameters, and<br>
>> >> translations, independently, in the last two. I understan=
d that in this<br>
>> >> case, the indices<br>
>> >> run over parameters that have been separated into individ=
ual components<br>
>> >> (similar to<br>
>> >> the form accepted by spm_matrix). Is this correct for the=
function<br>
>> >> reg(..)?=A0 In fact, I went back to the<br>
>> >> old spm code (spm99), and found parameters pdesc and free=
, and got more<br>
>> >> confused as to when I should<br>
>> >> use the 6 parameter, and when to use separate parameters =
(as if I was<br>
>> >> passing them to spm_matrix).<br>
>> >> So, when the loop runs over p1 and perturbs p1(i) by ds, =
does it run<br>
>> >> over<br>
>> >> translations/rotations etc<br>
>> >> or does it run over the martix elements that define these=
<br>
>> >> transformations<br>
>> >> (2x2 + 1x2)?<br>
>> >><br>
>> >> =A0 =A0 =A0 =A0 =A0=A0 2) In function penalty(..), I have=
used unique elements as<br>
>> >> [1,3,4], and my code looks like<br>
>> >> T =3D my_matrix(p)*M;<br>
>> >> T =3D T(1:2,1:2);<br>
>> >> T =3D 0.5*logm(T'*T);<br>
>> >> T<br>
>> >> T =3D T(els)' - mu;<br>
>> >> h =3D T'*isig*T<br>
>> >><br>
>> >> Assuming an application specific isig, is this correct?<b=
r>
>> >> =A0=A0=A0=A0=A0=A0=A0=A0 3) I have not yet incorporated t=
he prior information in my<br>
>> >> code,<br>
>> >> But for testing purposes,<br>
>> >> can you suggest some neutral values=A0 for mu and isig th=
at I can try to<br>
>> >> concentrate on the<br>
>> >> accuracy of the implementation minus the priors for now?<=
br>
>> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 4) My solution curently seems=
to oscillate around an optimum.<br>
>> >> I<br>
>> >> am hoping that after<br>
>> >> I have removed any errors after your replies, it will con=
verge<br>
>> >> gracefully.<br>
>> >><br>
>> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 Thanks again for all the help=
.<br>
>> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 Siddharth.<br>
>> >><br>
>> >><br>
>> >> On Fri, Mar 18, 2011 at 2:05 AM, John Ashburner <<a hr=
ef=3D"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]</=
a>><br>
>> >> wrote:<br>
>> >>><br>
>> >>> A 2D affine transform would use 6 parameters, rather =
than 7: a 2x2<br>
>> >>> matrix to encode rotations, zooms and shears, and a 2=
x1 vector for<br>
>> >>> translations.<br>
>> >>><br>
>> >>> Best regards,<br>
>> >>> -John<br>
>> >>><br>
>> >>> On 18 March 2011 05:05, Siddharth Srivastava <<a h=
ref=3D"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]</a>> =
wrote:<br>
>> >>> > Dear list users,<br>
>> >>> > =A0=A0=A0=A0=A0=A0=A0=A0=A0 I am currently tryin=
g to understand the implementation in<br>
>> >>> > spm_affreg, and<br>
>> >>> > to make matters simple, I tried to work out a 2D=
version of the<br>
>> >>> > registration<br>
>> >>> > procedure. I struck a roadblock, however...<br>
>> >>> ><br>
>> >>> > The function make_A creates part of the design m=
atrix. For the 3D<br>
>> >>> > case,<br>
>> >>> > the<br>
>> >>> > 13 parameters<br>
>> >>> > are encoded in columns of A1, which then is used=
to generate AA +<br>
>> >>> > A1'<br>
>> >>> > A1. AA<br>
>> >>> > is 13x13, and everything<br>
>> >>> > works. For the 2D case, however, there will be 7=
+1 parameters( 2<br>
>> >>> > translations, 1 rotation, 2 zoom, 2 shears and 1=
intensity scaling).<br>
>> >>> > The A1 matrix for 2D, then,=A0 will be (in make_=
A)<br>
>> >>> > A=A0 =3D [x1.*dG1 x1.*dG2 ...<br>
>> >>> > =A0=A0=A0=A0=A0 x2.*dG1 x2.*dG2 ...<br>
>> >>> > =A0=A0=A0 =A0 dG1=A0=A0=A0=A0 dG2=A0 t];<br>
>> >>> ><br>
>> >>> > which is (number of sampled points) x 7. The AA =
matrix (in function<br>
>> >>> > costfun)<br>
>> >>> > is 8x8<br>
>> >>> > so, which is the parameter I am missing in model=
ing a 2D example? I<br>
>> >>> > hope I<br>
>> >>> > have got the number of parameters<br>
>> >>> > right for the 2D case? Is there an extra column =
that I have to add<br>
>> >>> > to<br>
>> >>> > A1 to<br>
>> >>> > make the rest of the matrix computation<br>
>> >>> > consistent?<br>
>> >>> ><br>
>> >>> > Thanks for the help<br>
>> >>> ><br>
>> >><br>
>> ><br>
>> ><br>
><br>
><br>
</div></div></blockquote></div><br>
</div></div></blockquote></div><br>
--20cf307cfcb6af5c6204a29dbdcd--
=========================================================================
Date: Fri, 6 May 2011 18:23:53 +0200
Reply-To: swann pichon <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: swann pichon <[log in to unmask]>
Subject: Re: Changing ANOVA design matrix according to the SPM8 version
Comments: To: Guillaume Flandin <[log in to unmask]>
Comments: cc: [log in to unmask], Judith DOMINGUEZ BORRAS
<[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=000e0cd2577e99540d04a29deb60
Message-ID: <[log in to unmask]>
--000e0cd2577e99540d04a29deb60
Content-Type: text/plain; charset=UTF-8
Dear Guillaume,
Thanks for your useful advice. Indeed the weird weighting of the ANOVA
arises from the inclusion, in the same model, of two sets of conditions that
are slightly different. Two conditions have been estimated using three times
more trials than for the six others. These are the two first conditions that
appear darkish in the matrix. As they correspond to two different controls,
so will make relevant contrasts at the first level and remove them from the
2nd level analysis. Performing the ANOVA with the six others conditions
gives a nice eye-looking ANOVA matrix.
I guess it means that the latest versions of SPM8 achieve a much better
estimation of the dataset sphericity than the earlier ones.
Thanks for your input !
Swann
nb: Replacing spm_inv by inv do not change anything
2011/5/6 Guillaume Flandin <[log in to unmask]>
> Dear Swann and Judith,
>
> could you let me know a bit more what the input data for this model are?
> for example, are they coming from contrasts on parametric modulations at
> the first level?
> Looking at SPM.xVi.Cy, there seems to be some scans that are quite
> different than the others (eg the last one): are there any outlier?
> At last, using latest version of SPM8, if you replace spm_inv by inv in
> spm_spm.m at line 426:
> W = spm_sqrtm((xVi.V);
> doest it get better?
>
> Many thanks,
> Guillaume.
>
>
> On 05/05/11 23:20, swann pichon wrote:
> > Dear Guillaume,
> >
> > As you suggested, my colleague downloaded the lastest SPM release and
> > the result appears similar to what r4010 produces.
> >
> > Thanks for your input if you have any suggestion
> >
> > All the best
> >
> > Swann
> >
> > ---------- Forwarded message ----------
> > From: *Judith DOMINGUEZ BORRAS* <[log in to unmask]
> > <mailto:[log in to unmask]>>
> > Date: 2011/5/6
> > Subject: It seems to do the same strange weighting..
> > To: swann pichon <[log in to unmask] <mailto:[log in to unmask]>>
> >
> >
> > Hey Swann,
> >
> > I just tried this newest version but still we get the same strange
> > weighting (attached the design matrix + orthogonality, which
> > doesn't seem ok)..
> >
> > [...]
> >
> >
> > --
> > Swann Pichon, PhD
> > Laboratory for Behavioral Neurology and Imaging of Cognition
> > Department of Neuroscience, University Medical Center
> > 1 rue Michel-Servet, 1211 GENEVA 4, Switzerland
> > Tel: +41 (0)22 379 5979
> > Fax: +41 (0)22 379 5402
> > Gsm: +33 (0)6 26 43 83 61
> > http://labnic.unige.ch/
>
>
> --
> Guillaume Flandin, PhD
> Wellcome Trust Centre for Neuroimaging
> University College London
> 12 Queen Square
> London WC1N 3BG
>
--
Swann Pichon, PhD
Laboratory for Behavioral Neurology and Imaging of Cognition
Department of Neuroscience, University Medical Center
1 rue Michel-Servet, 1211 GENEVA 4, Switzerland
Tel: +41 (0)22 379 5979
Fax: +41 (0)22 379 5402
Gsm: +33 (0)6 26 43 83 61
http://labnic.unige.ch/
--000e0cd2577e99540d04a29deb60
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Dear Guillaume,<br><br>Thanks for your useful advice. Indeed the weird weig=
hting of the ANOVA arises from the inclusion, in the same model, of two set=
s of conditions that are slightly different. Two conditions have been estim=
ated using three times more trials than for the six others. These are the t=
wo first conditions that appear darkish in the matrix. As they correspond t=
o two different controls, so will make relevant contrasts at the first leve=
l and remove them from the 2nd level analysis. Performing the ANOVA with th=
e six others conditions gives a nice eye-looking ANOVA matrix.<br>
<br>I guess it means that the latest versions of SPM8 achieve a much better=
estimation of the dataset sphericity than the earlier ones.<br><br>Thanks =
for your input !<br><br>Swann<br><br>nb: Replacing spm_inv by inv do not ch=
ange anything<br>
<br><br><div class=3D"gmail_quote">2011/5/6 Guillaume Flandin <span dir=3D"=
ltr"><<a href=3D"mailto:[log in to unmask]">[log in to unmask]
.ac.uk</a>></span><br><blockquote class=3D"gmail_quote" style=3D"margin:=
0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
Dear Swann and Judith,<br>
<br>
could you let me know a bit more what the input data for this model are?<br=
>
for example, are they coming from contrasts on parametric modulations at<br=
>
the first level?<br>
Looking at <a href=3D"http://SPM.xVi.Cy" target=3D"_blank">SPM.xVi.Cy</a>, =
there seems to be some scans that are quite<br>
different than the others (eg the last one): are there any outlier?<br>
At last, using latest version of SPM8, if you replace spm_inv by inv in<br>
spm_spm.m at line 426:<br>
=C2=A0 W =C2=A0 =C2=A0 =3D spm_sqrtm((xVi.V);<br>
doest it get better?<br>
<br>
Many thanks,<br>
<font color=3D"#888888">Guillaume.<br>
</font><div class=3D"im"><br>
<br>
On 05/05/11 23:20, swann pichon wrote:<br>
> Dear Guillaume,<br>
><br>
> As you suggested, my colleague downloaded the lastest SPM release and<=
br>
> the result appears similar to what r4010 produces.<br>
><br>
> Thanks for your input if you have any suggestion<br>
><br>
> All the best<br>
><br>
> Swann<br>
><br>
> ---------- Forwarded message ----------<br>
> From: *Judith DOMINGUEZ BORRAS* <<a href=3D"mailto:Judith.Dominguez=
[log in to unmask]">[log in to unmask]</a><br>
</div><div class=3D"im">> <mailto:<a href=3D"mailto:Judith.DominguezB=
[log in to unmask]">[log in to unmask]</a>>><br>
> Date: 2011/5/6<br>
> Subject: It seems to do the same strange weighting..<br>
</div><div class=3D"im">> To: swann pichon <<a href=3D"mailto:Swann.P=
[log in to unmask]">[log in to unmask]</a> <mailto:<a href=3D"mailto:Swan=
[log in to unmask]">[log in to unmask]</a>>><br>
><br>
><br>
> Hey Swann,<br>
><br>
> I just tried this newest version but still we get the same strange<br>
> weighting (attached the design matrix + orthogonality, which<br>
> doesn't seem ok)..<br>
><br>
> =C2=A0[...]<br>
><br>
><br>
> --<br>
> Swann Pichon, PhD<br>
> Laboratory for Behavioral Neurology and Imaging of Cognition<br>
> Department of Neuroscience, University Medical Center<br>
> 1 rue Michel-Servet, 1211 GENEVA 4, Switzerland<br>
> Tel: +41 (0)22 379 5979<br>
> Fax: +41 (0)22 379 5402<br>
> Gsm: +33 (0)6 26 43 83 61<br>
> <a href=3D"http://labnic.unige.ch/" target=3D"_blank">http://labnic.un=
ige.ch/</a><br>
<br>
<br>
</div><div><div></div><div class=3D"h5">--<br>
Guillaume Flandin, PhD<br>
Wellcome Trust Centre for Neuroimaging<br>
University College London<br>
12 Queen Square<br>
London WC1N 3BG<br>
</div></div></blockquote></div><div style=3D"margin: 0pt;" name=3D"sig_d41d=
8cd98f"></div><br><br clear=3D"all"><br>-- <br><span style=3D"color:rgb(102=
, 102, 102)"></span><span style=3D"color:rgb(0, 0, 0)">Swann Pichon, PhD </=
span><br style=3D"color:rgb(0, 0, 0)">
<span style=3D"color:rgb(0, 0, 0)">
Laboratory for Behavioral Neurology and Imaging of Cognition</span><br styl=
e=3D"color:rgb(0, 0, 0)"><span style=3D"color:rgb(0, 0, 0)">
Department of Neuroscience, University Medical Center</span><br style=3D"co=
lor:rgb(0, 0, 0)"><span style=3D"color:rgb(0, 0, 0)">
1 rue Michel-Servet, 1211 GENEVA 4, Switzerland</span><br style=3D"color:rg=
b(0, 0, 0)"><span style=3D"color:rgb(0, 0, 0)">
Tel: +41 (0)22 379 5979</span><br style=3D"color:rgb(0, 0, 0)"><span style=
=3D"color:rgb(0, 0, 0)">
Fax: +41 (0)22 379 5402</span><br style=3D"color:rgb(0, 0, 0)"><span style=
=3D"color:rgb(0, 0, 0)">
Gsm: +33 (0)6 26 43 83 61</span><br style=3D"color:rgb(102, 102, 102)">
<a style=3D"color:rgb(102, 102, 102)" href=3D"http://labnic.unige.ch/" targ=
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Date: Fri, 6 May 2011 13:19:26 -0400
Reply-To: shaza zaghlool <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: shaza zaghlool <[log in to unmask]>
Subject: Modelling Categorical Responses
MIME-Version: 1.0
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Hello,
I'm working with a dataset that has the following task:
STOP SIGNAL TASK: A task in which an external stimulus signals the
participant to interrupt an already-initiated motor response.
These are the task conditions:
-Go trial
Trials on which a go stimulus is presented and the subject is expected to
respond
-Stop trial
Trials on which a stop signal is presented at some delay (stop-signal delay)
following the go stimulus, and the subject is expected to stop
-Successful Stop Trial
A trial on which a stop signal is presented at a delay following the go
stimulus, and the subject successfully withholds their response
-Unsuccessful stop trial
A trial on which a stop signal is presented at a delay following the go
stimulus, and the subject fails to withhold their response
I have 15 subjects which I specified a 1st-level model for and then
estimated the model using the classical method. The cluster sizes and
locations I got weren't consistent for the 15 subjects at all though. I'm
not sure where I could have gone wrong...
I attached a sample of behavioral files for one of the sessions for one of
the subjects.
The behav data columns are:
Onset: onset ime of the trial in seconds
TrialType: 0=go trial, 1=stop trial
Stimulus: right versus left arrow
SSD: stop signal delay (for stop trials only)
Response: response code (0=no response)
RT: response time
CorrectGo: 1=correct go response, 0=incorrect response
SuccStop: 1=response successfully withheld, 0=response executed (stop trials
only)
During my fmri model specification, under "timing parameters" and "units for
design" I chose "scans" as opposed to "seconds".
I specified 3 conditions (go_onsets, stopfail_onsets, and
stopsuccessful_onsets). I took the onsets for those 3 conditions from the
first column of task001_run001_go_ons.txt, task001_run001_stopfail_ons.txt,
and task001_run001_stopsucc_ons.txt respectively. (I wasn't sure what to do
with the other 2 columns in each of those files)
I also entered "0" for all the durations under all the conditions. Finally,
under "Multiple Regressors" I entered the realignment parameters I got from
the realignment stage in the preprocessing.
After I estimated the model, I used the contrast manager to specify 3
T-contrasts. The contrasts I specified were Go>NoGo, Go>Baseline, and
Go<Bassline.
None of these contrasts gave me similar activation pattern results
throughout the 15 subjects. (I didn't mask these contrasts with anything,and
used a p value of 0.001 and an extent threshold of 0 for all experiments.
Any help would be greatly appreciated.
Regards
--001636b14cb0187f5b04a29eb105
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<div>Hello,<br>I'm working with a dataset that has the following task:<=
br>=A0<br>STOP SIGNAL TASK: A task in which an external stimulus signals th=
e participant to interrupt an already-initiated motor response.<br>=A0<br>T=
hese are the task conditions:<br>
-Go trial<br>Trials on which a go stimulus is presented and the subject is =
expected to respond<br>-Stop trial<br>Trials on which a stop signal is pres=
ented at some delay (stop-signal delay) following the go stimulus, and the =
subject is expected to stop<br>
-Successful Stop Trial<br>A trial on which a stop signal is presented at a =
delay following the go stimulus, and the subject successfully withholds the=
ir response<br>-Unsuccessful stop trial<br>A trial on which a stop signal i=
s presented at a delay following the go stimulus, and the subject fails to =
withhold their response</div>
<div>=A0</div>
<div>I have 15 subjects which I specified a 1st-level model for and then es=
timated the model using the classical method. The cluster sizes and locatio=
ns I got weren't consistent for the 15 subjects at all though. I'm =
not sure where I could have gone wrong...</div>
<div>=A0</div>
<div>I attached a sample of behavioral files for one of the sessions for on=
e of the subjects. </div>
<div><span lang=3D"EN">
<p>The behav data columns are:</p>
<p>Onset: onset ime of the trial in seconds</p>
<p>TrialType: 0=3Dgo trial, 1=3Dstop trial</p>
<p>Stimulus: right versus left arrow</p>
<p>SSD: stop signal delay (for stop trials only)</p>
<p>Response: response code (0=3Dno response)</p>
<p>RT: response time</p>
<p>CorrectGo: 1=3Dcorrect go response, 0=3Dincorrect response</p>
<p>SuccStop: 1=3Dresponse successfully withheld, 0=3Dresponse executed (sto=
p trials only)</p>
<p>=A0</p>
<p>During my fmri model specification, under "timing parameters" =
and "units for design" I chose "scans" as opposed to &q=
uot;seconds". </p>
<p>I specified 3 conditions (go_onsets, stopfail_onsets, and stopsuccessful=
_onsets). I took the onsets for those 3 conditions from the first column of=
task001_run001_go_ons.txt, task001_run001_stopfail_ons.txt, and task001_ru=
n001_stopsucc_ons.txt respectively. (I wasn't sure what to do with the =
other 2 columns in each of those files)</p>
<p>I also entered "0" for all the durations under all the conditi=
ons. Finally, under "Multiple Regressors" I=A0entered the realign=
ment parameters I got from the realignment stage in the preprocessing. </p>
<p>=A0</p>
<p>After I estimated the model, I used the contrast manager to specify 3 T-=
contrasts. The contrasts I specified were Go>NoGo, Go>Baseline, and G=
o<Baseline. </p>
<p>None of these contrasts gave me similar activation pattern results throu=
ghout the 15 subjects. (I didn't mask these contrasts with anything,and=
used a p value of 0.001 and an extent threshold of 0 for all experiments. =
</p>
<p>=A0</p>
<p>Any help would be greatly appreciated.</p>
<p>Regards</p></span></div>
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--001636b14cb0187f6704a29eb107--
=========================================================================
Date: Fri, 6 May 2011 13:26:43 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Modelling Categorical Responses
Comments: To: shaza zaghlool <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
You entered onsets times in seconds and told the program they were in
scans. This means that your design doesn't reflect what the subject
was doing.
Change Scans to Seconds and they should be similar.
Best Regards, Donald McLaren
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General
Hospital and Harvard Medical School
Office: (773) 406-2464
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
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immediately notify the sender via telephone at (773) 406-2464 or
email.
On Fri, May 6, 2011 at 1:19 PM, shaza zaghlool <[log in to unmask]> w=
rote:
> Hello,
> I'm working with a dataset that has the following task:
>
> STOP SIGNAL TASK: A task in which an external stimulus signals the
> participant to interrupt an already-initiated motor response.
>
> These are the task conditions:
> -Go trial
> Trials on which a go stimulus is presented and the subject is expected to
> respond
> -Stop trial
> Trials on which a stop signal is presented at some delay (stop-signal del=
ay)
> following the go stimulus, and the subject is expected to stop
> -Successful Stop Trial
> A trial on which a stop signal is presented at a delay following the go
> stimulus, and the subject successfully withholds their response
> -Unsuccessful stop trial
> A trial on which a stop signal is presented at a delay following the go
> stimulus, and the subject fails to withhold their response
>
> I have 15 subjects which I specified a 1st-level model for and then
> estimated the model using the classical method. The cluster sizes and
> locations I got weren't consistent for the 15 subjects at all though. I'm
> not sure where I could have gone wrong...
>
> I attached a sample of behavioral files for one of the sessions for one o=
f
> the subjects.
>
> The behav data columns are:
>
> Onset: onset ime of the trial in seconds
>
> TrialType: 0=3Dgo trial, 1=3Dstop trial
>
> Stimulus: right versus left arrow
>
> SSD: stop signal delay (for stop trials only)
>
> Response: response code (0=3Dno response)
>
> RT: response time
>
> CorrectGo: 1=3Dcorrect go response, 0=3Dincorrect response
>
> SuccStop: 1=3Dresponse successfully withheld, 0=3Dresponse executed (stop=
trials
> only)
>
>
>
> During my fmri model specification, under "timing parameters" and "units =
for
> design" I chose "scans" as opposed to "seconds".
>
> I specified 3 conditions (go_onsets, stopfail_onsets, and
> stopsuccessful_onsets). I took the onsets for those 3 conditions from the
> first column of task001_run001_go_ons.txt, task001_run001_stopfail_ons.tx=
t,
> and task001_run001_stopsucc_ons.txt respectively. (I wasn't sure what to =
do
> with the other 2 columns in each of those files)
>
> I also entered "0" for all the durations under all the conditions. Finall=
y,
> under "Multiple Regressors" I=A0entered the realignment parameters I got =
from
> the realignment stage in the preprocessing.
>
>
>
> After I estimated the model, I used the contrast manager to specify 3
> T-contrasts. The contrasts I specified were Go>NoGo, Go>Baseline, and
> Go<Bassline.
>
> None of these contrasts gave me similar activation pattern results
> throughout the 15 subjects. (I didn't mask these contrasts with anything,=
and
> used a p value of 0.001 and an extent threshold of 0 for all experiments.
>
>
>
> Any help would be greatly appreciated.
>
> Regards
=========================================================================
Date: Fri, 6 May 2011 19:01:08 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: spm_affreg
Comments: To: Siddharth Srivastava <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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--002354470f8836910904a29f46c0
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Your model uses 7 parameters, but there are only 6 elements in
A(1:2,1:3). Also, you need to be able to deal with a broader range of
angles, so atan2(s,c) is used to compute the angle. I've tested it
with the following code, so hopefully it works for all cases.
for i=3D1:10000
P=3Drandn(1,6)*10;
M0=3Dspm_matrix2D(P);
P1=3Dspm_imatrix2D(M0);
M1=3Dspm_matrix2D(P1);
t=3Dsum(sum((M1-M0).^2));
if t>1e-9, disp('Problem'); break; end
end
Note that spm_imatrix2D(spm_matrix2D(P)) does not necessarily have to
equal P, but the matrices generated from the two parameter sets should
be the same.
Best regards,
-John
On 6 May 2011 17:11, Siddharth Srivastava <[log in to unmask]> wrote:
> Hi everyone,
> =A0=A0=A0=A0=A0 Can someone help me check the 2D versions of the spm_matr=
ix and
> spm_imatrix? My
> implementation currently is as follows:
>
> ---2D spm_matrix ---
> function [A] =3D spm_matrix2D(P)
> % P =3D [Tx, Ty, R, Zx, Zy, Sx,Sy]
> p0 =3D [0,0,0,1,1,0,0];
> P =3D [P, p0((length(P)+1):7)]
>
> A =3D eye(3);
> % T -> R -> Zoom -> Shear
> =A0A =3D=A0=A0=A0=A0 A * [1,0,P(1); ...
> =A0=A0=A0=A0=A0=A0=A0=A0=A0 0,1,P(2); ...
> =A0 =A0=A0=A0 =A0 0,0,=A0=A0 1];
> =A0A =3D=A0=A0=A0=A0 A * [cos(P(3)), sin(P(3)), 0; ...
> =A0=A0=A0=A0=A0=A0=A0=A0=A0 -sin(P(3)),=A0 cos(P(3)), 0; ...
> =A0=A0=A0 =A0 0,=A0=A0=A0=A0=A0=A0=A0=A0=A0 0,=A0=A0=A0=A0=A0=A0=A0=A0 1]=
;
> =A0A =3D=A0=A0=A0=A0 A * [P(4), 0, 0; ...
> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 0,=A0=A0 P(5), 0; ...
> =A0=A0=A0 =A0=A0=A0=A0=A0 0, 0, 1];
> =A0A =3D=A0=A0=A0=A0 A * [1, P(6), 0; ...
> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 P(7)=A0 , 1, 0; ...
> =A0=A0=A0 =A0=A0=A0=A0=A0 0, 0, 1];
> --------------------------------------------------
> -----2D spm_imatrix ------------------------
> function P =3D=A0 spm_imatrix2D(M);
>
>
>
> R =3D M(1:2,1:2);
> C =3D chol(R' * R);
> P =3D [M(1:2,3)',0,diag(C)',0,0];
> if(det(R) < 0) P(4) =3D -P(4); end
> C =3D diag(diag(C))\C;
> P(6:7) =3D C([2,3]);
>
> R0 =3D spm_matrix2D([0,0,0,P(4:end)]);
> R0 =3D R0(1:2,1:2);
> R1 =3D R/R0;
>
> th =3D asin(rang(R1(1,2)));
> P(3) =3D th;
>
> % There may be slight rounding errors making b>1 or b<-1.
> function=A0 a =3D rang(b)
> a =3D min(max(b, -1), 1);
> return;
> -------------------------------------------------------------------------=
--
>
> I know there is something not correct, since when, for a parameter set 'p=
',
> i do spm_imatrix2D(spm_matrix2D(p)), I do not recover P for all entries,
> specially
> rotation and shears. C(2) above always evaluates to zero. The result is t=
hat
> these errors
> accumulate (or are not accounted for) on repeated application of this
> sequence of
> operations in the registration routine.
>
> Thanks in anticipation,
> Sid.
>
>
>
> On Fri, Apr 22, 2011 at 9:13 AM, Siddharth Srivastava <[log in to unmask]>
> wrote:
>>
>> Hi John,
>> =A0=A0=A0=A0=A0 Thanks a lot for your answer, and it has been very helpf=
ul for my
>> understanding
>> of the details of the implementation, and my own development efforts. I
>> have
>> 2 very quick questions, though:
>>
>> 1) the parameter set x(:) that is returned from spm_mireg, and the
>> "params" that
>> spm_affsub3 returns (in spm99, which is also the version that I am looki=
ng
>> at) ,
>> are they equivalent? In other words, If I am collating the parameters fr=
om
>> the mireg
>> routine, would the distribution x(7:12) be used to estimate the icovar0
>> entries in affsub3?
>>
>> 2) also would VG.mat\spm_matrix(x)*VF.mat transform G to F similar to
>> =A0=A0=A0=A0 VG.mat\spm_matrix(params)*VF.mat , or do I have to do
>> =A0=A0=A0=A0=A0 M =3D VG.mat\spm_matrix(x(:)')*VF.mat
>> =A0=A0=A0=A0=A0 pp =3D spm_imatrix(M)
>> =A0=A0=A0=A0=A0 and use pp(7:12) ?
>>
>>
>>
>> Thanks again.
>> Sid.
>>
>> On Thu, Apr 14, 2011 at 2:13 PM, John Ashburner <[log in to unmask]>
>> wrote:
>>>
>>> > I had a look at the code in spm_maff, and
>>> > it looks like it also uses the values of isig and mu in the call to
>>> > affreg(). My guess is
>>> > that during the initial registration on a large data set for estimati=
ng
>>> > the
>>> > prior
>>> > distribution of parameters, this will be called with typ =3D 'none' .=
Is
>>> > this
>>> > correct?
>>>
>>> Once the registration has locked in on a solution, the priors have
>>> less influence. =A0Their main influence is in the early stages of the
>>> registration, or when there are relatively few slices in the data. =A0I
>>> don't actually remember if the registration was regularised when I
>>> computed their values.
>>>
>>> >
>>> > Further, do we have to do a non-rigid registration for the estimation
>>> > (since, in the comments the selected
>>> > files are filtered as *seg_inv_sn.mat"? Since only p.Affine is being
>>> > used,
>>> > can this work with only
>>> > an affine / rigid transformation?
>>>
>>> Only the affine transform in the files is used, so basically yes. =A0Yo=
u
>>> could just do affine registration.
>>>
>>> >
>>> > I would also be happy if you could also answer my other question abou=
t
>>> > examining the
>>> > effects of the values in isig and mu (what are the units of mu?) on t=
he
>>> > transformed image.
>>>
>>> They are unit-less, and are just a measure of the zooms and shears.
>>>
>>> > For example,
>>> > if i set a mu of [mu1, mu2, ...] and a isig of [sig1, 0, 0...; 0, sig=
2,
>>> > 0,
>>> > 0..; ...] (with only diagonal components),
>>> > based on the Hencky tensor penalty, it seems that large deviations of
>>> > parameter 1=A0 estimate (T - mu) from
>>> > mu1 will be penalized. How is the value of isig1 modifying the penalt=
y?
>>>
>>> Its assuming that the elements of the matrix log of the part that does
>>> shears and zooms has a multivariate normal distribution, so the
>>> penalty is a kind of negative log likelhood. =A0The isig is essentially
>>> a precision matrix, which is the inverse of a covariance matrix.
>>>
>>> p(x|mu,S) =3D 1/sqrt(det(2*pi*S)) * exp(-0.5*(x-mu)'*inv(S)*(x-mu))
>>>
>>> Taking logs and negating, you get 0.5*(x-mu)'*inv(S)*(x-mu) + const
>>>
>>> > How
>>> > do the off diagonal terms affect
>>> > the penalty?
>>>
>>> The inverse of isig would just encode the covariance between the
>>> various shears and zooms.
>>>
>>> >
>>> > Could you also point me to a reference where I can learn more about
>>> > Hencky
>>> > strain tensor (specifically
>>> > what information it carries in the context of image processing etc.)
>>>
>>> I don't know if this is of any use:
>>>
>>> http://en.wikipedia.org/wiki/Deformation_(mechanics)
>>>
>>> Best regards,
>>> -John
>>>
>>>
>>> > On Thu, Apr 14, 2011 at 10:17 AM, John Ashburner <[log in to unmask]
m>
>>> > wrote:
>>> >>
>>> >> They were computed by affine registering loads of (227) images to MN=
I
>>> >> space. =A0This gave the affine transforms, which were then used to b=
uild
>>> >> up a mean and inverse covariance matrix. =A0In the comments of
>>> >> spm_maff.m, you should see the following...
>>> >>
>>> >> %% Values can be derived by...
>>> >> %sn =3D spm_select(Inf,'.*seg_inv_sn.mat$');
>>> >> %X =A0=3D zeros(size(sn,1),12);
>>> >> %for i=3D1:size(sn,1),
>>> >> % =A0 =A0p =A0=3D load(deblank(sn(i,:)));
>>> >> % =A0 =A0M =A0=3D p.VF(1).mat*p.Affine/p.VG(1).mat;
>>> >> % =A0 =A0J =A0=3D M(1:3,1:3);
>>> >> % =A0 =A0V =A0=3D sqrtm(J*J');
>>> >> % =A0 =A0R =A0=3D V\J;
>>> >> % =A0 =A0lV =A0 =A0 =A0=3D =A0logm(V);
>>> >> % =A0 =A0lR =A0 =A0 =A0=3D -logm(R);
>>> >> % =A0 =A0P =A0 =A0 =A0 =3D zeros(12,1);
>>> >> % =A0 =A0P(1:3) =A0=3D M(1:3,4);
>>> >> % =A0 =A0P(4:6) =A0=3D lR([2 3 6]);
>>> >> % =A0 =A0P(7:12) =3D lV([1 2 3 5 6 9]);
>>> >> % =A0 =A0X(i,:) =A0=3D P';
>>> >> %end;
>>> >> %mu =A0 =3D mean(X(:,7:12));
>>> >> %XR =A0 =3D X(:,7:12) - repmat(mu,[size(X,1),1]);
>>> >> %isig =3D inv(XR'*XR/(size(X,1)-1))
>>> >>
>>> >> You may be able to re-code this to work with your 2D transforms. =A0=
Note
>>> >> that I only use the components that describe shears and zooms. =A0Al=
so,
>>> >> if I was re-coding it all again, I would probably do things slightly
>>> >> differently, using the following decomposition:
>>> >>
>>> >> J=3DM(1:3,1:3);
>>> >> L=3Dreal(logm(J));
>>> >> S=3D(L+L')/2; % Symmetric part (for zooms and shears, which should b=
e
>>> >> penalised)
>>> >> A=3D(L-L')/2; % Anti-symmetric part (for rotations)
>>> >>
>>> >> I might even base the penalty on lambda(2)*trace(S)^2 +
>>> >> lambda(1)*trace(S*S'), which is often used as a measure of "elastic
>>> >> energy" for penalising non-linear registration. =A0Of course, there
>>> >> would also be a bit of annoying extra stuff to deal with due to MNI
>>> >> space being a bit bigger than average brains are. =A0Figuring out th=
e
>>> >> mean would require (I think) an iterative process similar to the one
>>> >> described in "Characterizing volume and surface deformations in an
>>> >> atlas framework: theory, applications, and implementation", by Woods
>>> >> in NeuroImage (2003).
>>> >>
>>> >> Best regards,
>>> >> -John
>>> >>
>>> >> On 14 April 2011 17:15, Siddharth Srivastava <[log in to unmask]> wrot=
e:
>>> >> > Hi all,
>>> >> > =A0=A0=A0=A0 My question pertains specifically to the values of is=
ig and mu
>>> >> > that
>>> >> > are
>>> >> > incorporated
>>> >> > in the code, and I wish to disentangle the effect that these numbe=
rs
>>> >> > have on
>>> >> > individual parameters
>>> >> > during the optimization stage. I am trying to map it to a 2D case,
>>> >> > and
>>> >> > these
>>> >> > numbers
>>> >> > will have to be calculated ab-initio for my case. Before I begin
>>> >> > with
>>> >> > estimating the prior distribution
>>> >> > for these parameters, I need to check the effect that they have on
>>> >> > the
>>> >> > registered images. Regarding this
>>> >> > 1) Can someone suggest a way I can examine the effect on each
>>> >> > parameter
>>> >> > separately, if it is
>>> >> > =A0=A0=A0=A0 at all possible.
>>> >> > 2) Some advise on how to estimate these parameters, if it has been
>>> >> > done
>>> >> > for
>>> >> > images other
>>> >> > =A0=A0=A0=A0 than brain images, will be really helpful for me.
>>> >> >
>>> >> > Thanks,
>>> >> > Sid.
>>> >> >
>>> >> > On Mon, Mar 28, 2011 at 7:04 PM, Siddharth Srivastava
>>> >> > <[log in to unmask]>
>>> >> > wrote:
>>> >> >>
>>> >> >> Dear John,
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 Thanks for your answer. I was able to=
correctly run my 2D
>>> >> >> implementation
>>> >> >> based on your advise. However, I am am not very confident of my
>>> >> >> results
>>> >> >> and wanted to
>>> >> >> consult you on certain aspects of my mapping from 3D to 2D.
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 1) In function reg(..), the commen=
t says that the
>>> >> >> derivatives
>>> >> >> w.r.t rotations and
>>> >> >> translations is zero. Consequently, I ran the indices from 4:7.
>>> >> >> According
>>> >> >> to your previous
>>> >> >> reply, rotations will be lumped together with scaling and affine =
in
>>> >> >> 4
>>> >> >> parameters, and
>>> >> >> translations, independently, in the last two. I understand that i=
n
>>> >> >> this
>>> >> >> case, the indices
>>> >> >> run over parameters that have been separated into individual
>>> >> >> components
>>> >> >> (similar to
>>> >> >> the form accepted by spm_matrix). Is this correct for the functio=
n
>>> >> >> reg(..)?=A0 In fact, I went back to the
>>> >> >> old spm code (spm99), and found parameters pdesc and free, and go=
t
>>> >> >> more
>>> >> >> confused as to when I should
>>> >> >> use the 6 parameter, and when to use separate parameters (as if I
>>> >> >> was
>>> >> >> passing them to spm_matrix).
>>> >> >> So, when the loop runs over p1 and perturbs p1(i) by ds, does it
>>> >> >> run
>>> >> >> over
>>> >> >> translations/rotations etc
>>> >> >> or does it run over the martix elements that define these
>>> >> >> transformations
>>> >> >> (2x2 + 1x2)?
>>> >> >>
>>> >> >> =A0 =A0 =A0 =A0 =A0=A0 2) In function penalty(..), I have used un=
ique elements
>>> >> >> as
>>> >> >> [1,3,4], and my code looks like
>>> >> >> T =3D my_matrix(p)*M;
>>> >> >> T =3D T(1:2,1:2);
>>> >> >> T =3D 0.5*logm(T'*T);
>>> >> >> T
>>> >> >> T =3D T(els)' - mu;
>>> >> >> h =3D T'*isig*T
>>> >> >>
>>> >> >> Assuming an application specific isig, is this correct?
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0 3) I have not yet incorporated the prior=
information in my
>>> >> >> code,
>>> >> >> But for testing purposes,
>>> >> >> can you suggest some neutral values=A0 for mu and isig that I can=
try
>>> >> >> to
>>> >> >> concentrate on the
>>> >> >> accuracy of the implementation minus the priors for now?
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 4) My solution curently seems to osci=
llate around an
>>> >> >> optimum.
>>> >> >> I
>>> >> >> am hoping that after
>>> >> >> I have removed any errors after your replies, it will converge
>>> >> >> gracefully.
>>> >> >>
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 Thanks again for all the help.
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 Siddharth.
>>> >> >>
>>> >> >>
>>> >> >> On Fri, Mar 18, 2011 at 2:05 AM, John Ashburner
>>> >> >> <[log in to unmask]>
>>> >> >> wrote:
>>> >> >>>
>>> >> >>> A 2D affine transform would use 6 parameters, rather than 7: a 2=
x2
>>> >> >>> matrix to encode rotations, zooms and shears, and a 2x1 vector f=
or
>>> >> >>> translations.
>>> >> >>>
>>> >> >>> Best regards,
>>> >> >>> -John
>>> >> >>>
>>> >> >>> On 18 March 2011 05:05, Siddharth Srivastava <[log in to unmask]>
>>> >> >>> wrote:
>>> >> >>> > Dear list users,
>>> >> >>> > =A0=A0=A0=A0=A0=A0=A0=A0=A0 I am currently trying to understan=
d the implementation
>>> >> >>> > in
>>> >> >>> > spm_affreg, and
>>> >> >>> > to make matters simple, I tried to work out a 2D version of th=
e
>>> >> >>> > registration
>>> >> >>> > procedure. I struck a roadblock, however...
>>> >> >>> >
>>> >> >>> > The function make_A creates part of the design matrix. For the
>>> >> >>> > 3D
>>> >> >>> > case,
>>> >> >>> > the
>>> >> >>> > 13 parameters
>>> >> >>> > are encoded in columns of A1, which then is used to generate A=
A
>>> >> >>> > +
>>> >> >>> > A1'
>>> >> >>> > A1. AA
>>> >> >>> > is 13x13, and everything
>>> >> >>> > works. For the 2D case, however, there will be 7+1 parameters(=
2
>>> >> >>> > translations, 1 rotation, 2 zoom, 2 shears and 1 intensity
>>> >> >>> > scaling).
>>> >> >>> > The A1 matrix for 2D, then,=A0 will be (in make_A)
>>> >> >>> > A=A0 =3D [x1.*dG1 x1.*dG2 ...
>>> >> >>> > =A0=A0=A0=A0=A0 x2.*dG1 x2.*dG2 ...
>>> >> >>> > =A0=A0=A0 =A0 dG1=A0=A0=A0=A0 dG2=A0 t];
>>> >> >>> >
>>> >> >>> > which is (number of sampled points) x 7. The AA matrix (in
>>> >> >>> > function
>>> >> >>> > costfun)
>>> >> >>> > is 8x8
>>> >> >>> > so, which is the parameter I am missing in modeling a 2D
>>> >> >>> > example? I
>>> >> >>> > hope I
>>> >> >>> > have got the number of parameters
>>> >> >>> > right for the 2D case? Is there an extra column that I have to
>>> >> >>> > add
>>> >> >>> > to
>>> >> >>> > A1 to
>>> >> >>> > make the rest of the matrix computation
>>> >> >>> > consistent?
>>> >> >>> >
>>> >> >>> > Thanks for the help
>>> >> >>> >
>>> >> >>
>>> >> >
>>> >> >
>>> >
>>> >
>>
>
>
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=========================================================================
Date: Fri, 6 May 2011 14:07:10 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: PPI question
Comments: To: Alex Fornito <[log in to unmask]>
Comments: cc: Darren Gitelman <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
The null-space of the contrast are any columns of the contrast (which
must be an F-contrast) that are 0. Thus, you remove the effects of
motion when you do the adjustment and don't need to worry about them
being included in the deconvolved data. The code that I have supplied
has N rows for N conditions of interest after I talked to Darren about
the ideal contrast to use for adjustment.
As for removing the frequencies, I think it is probably fine to remove
them, I was just under the impression that they weren't being removed
because of me commenting out that line during testing of spm_regions.
I would go with the SPM defaults until their effect is tested. If you
don't set a high-pass filter, then you won't remove the frequencies,
so you could test it that way as well.
Best Regards, Donald McLaren
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General
Hospital and Harvard Medical School
Office: (773) 406-2464
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
This e-mail contains CONFIDENTIAL INFORMATION which may contain
PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
and which is intended only for the use of the individual or entity
named above. If the reader of the e-mail is not the intended recipient
or the employee or agent responsible for delivering it to the intended
recipient, you are hereby notified that you are in possession of
confidential and privileged information. Any unauthorized use,
disclosure, copying or the taking of any action in reliance on the
contents of this information is strictly prohibited and may be
unlawful. If you have received this e-mail unintentionally, please
immediately notify the sender via telephone at (773) 406-2464 or
email.
On Thu, May 5, 2011 at 9:46 PM, Alex Fornito <[log in to unmask]> wrot=
e:
> Hi Donald, Torben and Darren,
> Thanks for your responses.
>
> Form each of your responses, it seems like best practice would be to remo=
ve
> motion (and/or other confounds) from the VOI time series prior to
> deconvolution.
>
> It also seems like you are recommending NOT to frequency filter the VOI t=
ime
> series.
>
> In my reading though, spm_regions does this by default with the call to
> spm_filter (line 135). So, if spm_regions is used to extract a VOI time
> series, the time series that is input to spm_peb_ppi will already frequen=
cy
> filtered. So it seems like, in standard practice, the deconvolution is
> applied to frequency-filtered data. In this case, if xX.iG is empty, the
> only difference between Y and Yc in spm_peb_ppi is the additional removal=
of
> block effects (xX.iB).
>
> Based on the current chain of emails, it seems you are recommending that =
a
> confound-corrected, whitened, but non-frequency filtered time course shou=
ld
> be input to spm_peb_ppi. IS that correct, or am I missing something?
>
> Finally, can I clarify exactly what the null space of the contrast is? Mo=
st
> of the time in my analyses I don't get the option to adjust for it, so xY=
.Ic
> is empty.
>
> Thanks again for all your help,
> A
>
>
>
> On 06/05/2011 02:18, "MCLAREN, Donald" <[log in to unmask]> wrote:
>
>> I haven't thoroughly tested this, but if you set iG to be the movement
>> parameters columns. Then still adjust for the null space (motion
>> parameters). You will get the best of both. If you don't adjust for
>> the null space, then movement will contribute to the deconvolution. In
>> summary, if you have iG be the motion parameter columns AND adjust for
>> the null-space (motion columns), then:
>>
>> Y will have the effect of motion removed. Yc (removal of motion twice)
>> will be minimally different since Y is orthogonal to the motion
>> parameters. So, you have motion removed from both the autocorrelation
>> estimate, the Y for deconvolution, and Yc.
>>
>> Best Regards, Donald McLaren
>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>> D.G. McLaren, Ph.D.
>> Postdoctoral Research Fellow, GRECC, Bedford VA
>> Research Fellow, Department of Neurology, Massachusetts General
>> Hospital and Harvard Medical School
>> Office: (773) 406-2464
>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>> and which is intended only for the use of the individual or entity
>> named above. If the reader of the e-mail is not the intended recipient
>> or the employee or agent responsible for delivering it to the intended
>> recipient, you are hereby notified that you are in possession of
>> confidential and privileged information. Any unauthorized use,
>> disclosure, copying or the taking of any action in reliance on the
>> contents of this information is strictly prohibited and may be
>> unlawful. If you have received this e-mail unintentionally, please
>> immediately notify the sender via telephone at (773) 406-2464 or
>> email.
>>
>>
>>
>> On Thu, May 5, 2011 at 9:48 AM, Torben Ellegaard Lund
>> <[log in to unmask]> wrote:
>>> Hi Alex
>>>
>>>
>>> Den Uge:18 05/05/2011 kl. 14.15 skrev Alex Fornito:
>>>
>>>> Hi Torben,
>>>> Sorry, I just wanted to clarify: do you mean leaving SPM.xX.iG empty? =
It
>>>> seems like this is done by default by spm_fmri_design (?)
>>>
>>> leaving it empty will include all user defined regressors in the effect=
s of
>>> interest F-test which determines the mask where the serial correlation =
is
>>> estimated. I think it would make sense if the motion regressors did not=
go
>>> into this test, just like the DCS HP-filter does not go into the F-cont=
rast.
>>>
>>>> Are you suggesting manually entering motion parameters into this field=
?
>>>
>>> Yes, or their indices that is. It should be done after specification, b=
ut
>>> before model estimation. You can check if SPM recognized your changes b=
y
>>> looking at the automatically generated effects of interest F-contrast.
>>>
>>>
>>> Best
>>> Torben
>>>
>>>
>>>
>>>
>>>>
>>>> On 05/05/2011 18:16, "Torben Ellegaard Lund" <[log in to unmask]> wrot=
e:
>>>>
>>>>> Just as a kind reminder. Leaving SPM.xX.iG is a bit unfortunate, beca=
use
>>>>> voxels where motion artefacts are significant then constitutes a larg=
e part
>>>>> of
>>>>> the F-test derived mask used to estimate serial correlations. If you =
are
>>>>> picky
>>>>> about this you can change it yourselves, but it is not as easy as it =
should
>>>>> be.
>>>>>
>>>>>
>>>>> Best
>>>>> Torben
>>>>>
>>>>>
>>>>>
>>>>> Den Uge:18 05/05/2011 kl. 05.03 skrev Alex Fornito:
>>>>>
>>>>>> Ahh, I see. I was assuming that SPM.xX.iG contained the indices to t=
he
>>>>>> nuisance covariates in the design matrix, but you're right -
>>>>>> spm_fMRI_design
>>>>>> leaves it empty.
>>>>>>
>>>>>> Thanks for your help!
>>>>>> A
>>>>>>
>>>>>>
>>>>>> On 05/05/2011 12:54, "MCLAREN, Donald" <[log in to unmask]> wr=
ote:
>>>>>>
>>>>>>> I agree that nuisance covariates, such as motion should be removed;
>>>>>>> however, motion covariates are not generally stored in X0 in my
>>>>>>> reading of the SPM code (spm_fMRI_design, spm_regions). They should=
be
>>>>>>> removed in the spm_regions filtering based on the null-space of the
>>>>>>> contrast.
>>>>>>>
>>>>>>> As for the motion parameters being in the model, if they were in th=
e
>>>>>>> standard analysis, they should be included in the PPI analysis. My
>>>>>>> gPPI code will do this automatically as well.
>>>>>>>
>>>>>>> X0 is made of SPM.xX.iB (block effects -- so removing the mean) and
>>>>>>> SPM.xX.iG (nuisance variable that is empty as far as I can tell (li=
ne
>>>>>>> 369 of spm_fMRI_design)) and the high-pass filtering (K.X0).
>>>>>>>
>>>>>>> Best Regards, Donald McLaren
>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>> D.G. McLaren, Ph.D.
>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>> Hospital and Harvard Medical School
>>>>>>> Office: (773) 406-2464
>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>>>>>>> and which is intended only for the use of the individual or entity
>>>>>>> named above. If the reader of the e-mail is not the intended recipi=
ent
>>>>>>> or the employee or agent responsible for delivering it to the inten=
ded
>>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>> disclosure, copying or the taking of any action in reliance on the
>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>> unlawful. If you have received this e-mail unintentionally, please
>>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>>> email.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> On Wed, May 4, 2011 at 10:16 PM, Alex Fornito <[log in to unmask]
.au>
>>>>>>> wrote:
>>>>>>>> Hi Donald,
>>>>>>>> Thanks for your response. When you say "you don't want
>>>>>>>> to filter out anything related to neural activity", I'm presuming =
that
>>>>>>>> you
>>>>>>>> are referring to the deconvolved neural signal?
>>>>>>>>
>>>>>>>> If so, that makes sense. However, X0 also contains user-specified
>>>>>>>> nuisance
>>>>>>>> covariates. I would have thought it would make sense to remove tho=
se,
>>>>>>>> depending on what they were (e.g., movement parameters)? I guess t=
hey
>>>>>>>> can
>>>>>>>> always be entered into the PPI regression model...
>>>>>>>>
>>>>>>>>
>>>>>>>> On 05/05/2011 11:57, "MCLAREN, Donald" <[log in to unmask]> =
wrote:
>>>>>>>>
>>>>>>>>> I could be wrong, Karl or Darren please correct me if I am.
>>>>>>>>>
>>>>>>>>> X0 is composed of the high-pass filter and constant term. Thus, y=
ou
>>>>>>>>> want to filter these out of the Yc regressor. However, you don't =
want
>>>>>>>>> to filter out anything related to neural activity, so you wouldn'=
t
>>>>>>>>> want to filter your signal and then predict the neural activity f=
rom
>>>>>>>>> the filtered signal, especially filtering frequencies.
>>>>>>>>>
>>>>>>>>> Best Regards, Donald McLaren
>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>>>> Hospital and Harvard Medical School
>>>>>>>>> Office: (773) 406-2464
>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEG=
ED
>>>>>>>>> and which is intended only for the use of the individual or entit=
y
>>>>>>>>> named above. If the reader of the e-mail is not the intended reci=
pient
>>>>>>>>> or the employee or agent responsible for delivering it to the int=
ended
>>>>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>>> disclosure, copying or the taking of any action in reliance on th=
e
>>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>>> unlawful. If you have received this e-mail unintentionally, pleas=
e
>>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>>>>> email.
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> On Sat, Apr 30, 2011 at 8:03 PM, Alex Fornito <[log in to unmask]
du.au>
>>>>>>>>> wrote:
>>>>>>>>>> Hi Donald,
>>>>>>>>>> As far as I can tell, spm_regions filters and whitens the VOI ti=
me
>>>>>>>>>> series,
>>>>>>>>>> and adjusts for the null space of the contrast if an adjustment =
is
>>>>>>>>>> specified
>>>>>>>>>> in xY.Ic. It defines the confound matrix, X0, but does not corre=
ct for
>>>>>>>>>> it.
>>>>>>>>>> The following line in spm_peb_ppi corrects for the confounds.
>>>>>>>>>>
>>>>>>>>>> Yc =A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>>>
>>>>>>>>>> So the above correction does seem to be doing something differen=
t to
>>>>>>>>>> spm_regions. I'm wondering why the uncorrected data, Y, is used =
when
>>>>>>>>>> generating the ppi interaction term, while the corrected data Yc=
is to
>>>>>>>>>> be
>>>>>>>>>> used as a covariate of no interest in the PPI model. I would has
>>>>>>>>>> thought
>>>>>>>>>> that Yc should be used to generate the ppi interaction term as w=
ell.
>>>>>>>>>>
>>>>>>>>>> In my data, my X0 is a 195 x 7 matrix (I have 195 volumes per
>>>>>>>>>> session).
>>>>>>>>>>
>>>>>>>>>> Regards,
>>>>>>>>>> Alex
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> On 30/04/2011 02:22, "MCLAREN, Donald" <[log in to unmask]
>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>>> I'm actually travelling at the moment. However, I know Y has al=
ready
>>>>>>>>>>> been adjusted as part of the VOI processing.
>>>>>>>>>>>
>>>>>>>>>>> Can you check what X0 looks like?
>>>>>>>>>>>
>>>>>>>>>>> Best Regards, Donald McLaren
>>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>>>>>> Hospital and Harvard Medical School
>>>>>>>>>>> Office: (773) 406-2464
>>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVIL=
EGED
>>>>>>>>>>> and which is intended only for the use of the individual or ent=
ity
>>>>>>>>>>> named above. If the reader of the e-mail is not the intended
>>>>>>>>>>> recipient
>>>>>>>>>>> or the employee or agent responsible for delivering it to the
>>>>>>>>>>> intended
>>>>>>>>>>> recipient, you are hereby notified that you are in possession o=
f
>>>>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>>>>> disclosure, copying or the taking of any action in reliance on =
the
>>>>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>>>>> unlawful. If you have received this e-mail unintentionally, ple=
ase
>>>>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 o=
r
>>>>>>>>>>> email.
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> On Fri, Apr 29, 2011 at 2:55 AM, Alex Fornito
>>>>>>>>>>> <[log in to unmask]>
>>>>>>>>>>> wrote:
>>>>>>>>>>>> Hi all,
>>>>>>>>>>>> I have a question concerning the code used to implement a PPI
>>>>>>>>>>>> analysis.
>>>>>>>>>>>>
>>>>>>>>>>>> In the spm_peb_ppi.m function packaged with SPM8, lines 329-33=
2
>>>>>>>>>>>> remove
>>>>>>>>>>>> confounds from the input seed region=B9s time course:
>>>>>>>>>>>>
>>>>>>>>>>>> % Remove confounds and save Y in ouput structure
>>>>>>>>>>>> %-------------------------------------------------------------=
------
>>>>>>>>>>>> ---
>>>>>>>>>>>> --
>>>>>>>>>>>> --
>>>>>>>>>>>> Yc =A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>>>>>
>>>>>>>>>>>> PPI.Y is then to be used as a covariate of no interest when bu=
ilding
>>>>>>>>>>>> the
>>>>>>>>>>>> PPI
>>>>>>>>>>>> regression model. However, on line 488, it is the uncorrected =
seed
>>>>>>>>>>>> time
>>>>>>>>>>>> course, Y, that is input to the deconvolution routine and used=
to
>>>>>>>>>>>> generate
>>>>>>>>>>>> the ppi term:
>>>>>>>>>>>>
>>>>>>>>>>>> =A0C =A0=3D spm_PEB(Y,P);
>>>>>>>>>>>> =A0 =A0xn =3D xb*C{2}.E(1:N);
>>>>>>>>>>>> =A0 =A0xn =3D spm_detrend(xn);
>>>>>>>>>>>>
>>>>>>>>>>>> =A0% Setup psychological variable from inputs and contast weig=
hts
>>>>>>>>>>>>
>>>>>>>>>>>> %-------------------------------------------------------------=
------
>>>>>>>>>>>> ---
>>>>>>>>>>>> =A0PSY =3D zeros(N*NT,1);
>>>>>>>>>>>> =A0for i =3D 1:size(U.u,2)
>>>>>>>>>>>> =A0 =A0 =A0PSY =3D PSY + full(U.u(:,i)*U.w(:,i));
>>>>>>>>>>>> =A0end
>>>>>>>>>>>> =A0% PSY =3D spm_detrend(PSY); =A0<- removed centering of psyc=
h variable
>>>>>>>>>>>> =A0% prior to multiplication with xn. Based on discussion with=
Karl
>>>>>>>>>>>> =A0% and Donald McLaren.
>>>>>>>>>>>>
>>>>>>>>>>>> % Multiply psychological variable by neural signal
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> %-------------------------------------------------------------=
------
>>>>>>>>>>>> ---
>>>>>>>>>>>> =A0 PSYxn =3D PSY.*xn;
>>>>>>>>>>>>
>>>>>>>>>>>> Is there any specific reason why Y, rather than Yc(:,1), is us=
ed to
>>>>>>>>>>>> compute
>>>>>>>>>>>> PSYxn? I thought Yc might be more appropriate (?).
>>>>>>>>>>>> Thanks for your help,
>>>>>>>>>>>> Alex
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> ------------------------------------------
>>>>>>>>>>>>
>>>>>>>>>>>> Alex Fornito
>>>>>>>>>>>> Research Fellow
>>>>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>>>>> University of Melbourne
>>>>>>>>>>>> National Neuroscience Facility
>>>>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>>>>> 161 Barry St
>>>>>>>>>>>> Carlton South 3053
>>>>>>>>>>>> Victoria, Australia
>>>>>>>>>>>>
>>>>>>>>>>>> Email: [log in to unmask]
>>>>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> ------------------------------------------
>>>>>>>>>>
>>>>>>>>>> Alex Fornito
>>>>>>>>>> Research Fellow
>>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>>> University of Melbourne
>>>>>>>>>> National Neuroscience Facility
>>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>>> 161 Barry St
>>>>>>>>>> Carlton South 3053
>>>>>>>>>> Victoria, Australia
>>>>>>>>>>
>>>>>>>>>> Email: [log in to unmask]
>>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> ------------------------------------------
>>>>>>>>
>>>>>>>> Alex Fornito
>>>>>>>> Research Fellow
>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>> University of Melbourne
>>>>>>>> National Neuroscience Facility
>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>> 161 Barry St
>>>>>>>> Carlton South 3053
>>>>>>>> Victoria, Australia
>>>>>>>>
>>>>>>>> Email: [log in to unmask]
>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>>
>>>>>> ------------------------------------------
>>>>>>
>>>>>> Alex Fornito
>>>>>> Research Fellow
>>>>>> Melbourne Neuropsychiatry Centre
>>>>>> University of Melbourne
>>>>>> National Neuroscience Facility
>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>> 161 Barry St
>>>>>> Carlton South 3053
>>>>>> Victoria, Australia
>>>>>>
>>>>>> Email: [log in to unmask]
>>>>>> Phone: +61 3 8344 1876
>>>>>> Fax: +61 3 9348 0469
>>>>>
>>>>>
>>>>
>>>>
>>>> ------------------------------------------
>>>>
>>>> Alex Fornito
>>>> Research Fellow
>>>> Melbourne Neuropsychiatry Centre
>>>> University of Melbourne
>>>> National Neuroscience Facility
>>>> Levels 1 & 2, Alan Gilbert Building
>>>> 161 Barry St
>>>> Carlton South 3053
>>>> Victoria, Australia
>>>>
>>>> Email: [log in to unmask]
>>>> Phone: +61 3 8344 1876
>>>> Fax: +61 3 9348 0469
>>>>
>>>>
>>>>
>>>
>>
>
>
> ------------------------------------------
>
> Alex Fornito
> Research Fellow
> Melbourne Neuropsychiatry Centre
> University of Melbourne
> National Neuroscience Facility
> Levels 1 & 2, Alan Gilbert Building
> 161 Barry St
> Carlton South 3053
> Victoria, Australia
>
> Email: [log in to unmask]
> Phone: +61 3 8344 1876
> Fax: +61 3 9348 0469
>
>
>
>
=========================================================================
Date: Fri, 6 May 2011 12:23:57 -0700
Reply-To: Siddharth Srivastava <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Siddharth Srivastava <[log in to unmask]>
Subject: Re: spm_affreg
Comments: To: John Ashburner <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
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Message-ID: <[log in to unmask]>
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Thanks John, for the answers. The code, however exits with "Problem". M0
and M1 differ.
Also, why is there just one shear component in the matrix? I have seen
general shears modeled as [1,h;g,1]: is this superfluous, and just one "h"
will be sufficient for 2d case?
Thanks,
Sid.
On Fri, May 6, 2011 at 11:01 AM, John Ashburner <[log in to unmask]>wrote:
> Your model uses 7 parameters, but there are only 6 elements in
> A(1:2,1:3). Also, you need to be able to deal with a broader range of
> angles, so atan2(s,c) is used to compute the angle. I've tested it
> with the following code, so hopefully it works for all cases.
>
> for i=1:10000
> P=randn(1,6)*10;
> M0=spm_matrix2D(P);
> P1=spm_imatrix2D(M0);
> M1=spm_matrix2D(P1);
> t=sum(sum((M1-M0).^2));
> if t>1e-9, disp('Problem'); break; end
> end
>
> Note that spm_imatrix2D(spm_matrix2D(P)) does not necessarily have to
> equal P, but the matrices generated from the two parameter sets should
> be the same.
>
> Best regards,
> -John
>
> On 6 May 2011 17:11, Siddharth Srivastava <[log in to unmask]> wrote:
> > Hi everyone,
> > Can someone help me check the 2D versions of the spm_matrix and
> > spm_imatrix? My
> > implementation currently is as follows:
> >
> > ---2D spm_matrix ---
> > function [A] = spm_matrix2D(P)
> > % P = [Tx, Ty, R, Zx, Zy, Sx,Sy]
> > p0 = [0,0,0,1,1,0,0];
> > P = [P, p0((length(P)+1):7)]
> >
> > A = eye(3);
> > % T -> R -> Zoom -> Shear
> > A = A * [1,0,P(1); ...
> > 0,1,P(2); ...
> > 0,0, 1];
> > A = A * [cos(P(3)), sin(P(3)), 0; ...
> > -sin(P(3)), cos(P(3)), 0; ...
> > 0, 0, 1];
> > A = A * [P(4), 0, 0; ...
> > 0, P(5), 0; ...
> > 0, 0, 1];
> > A = A * [1, P(6), 0; ...
> > P(7) , 1, 0; ...
> > 0, 0, 1];
> > --------------------------------------------------
> > -----2D spm_imatrix ------------------------
> > function P = spm_imatrix2D(M);
> >
> >
> >
> > R = M(1:2,1:2);
> > C = chol(R' * R);
> > P = [M(1:2,3)',0,diag(C)',0,0];
> > if(det(R) < 0) P(4) = -P(4); end
> > C = diag(diag(C))\C;
> > P(6:7) = C([2,3]);
> >
> > R0 = spm_matrix2D([0,0,0,P(4:end)]);
> > R0 = R0(1:2,1:2);
> > R1 = R/R0;
> >
> > th = asin(rang(R1(1,2)));
> > P(3) = th;
> >
> > % There may be slight rounding errors making b>1 or b<-1.
> > function a = rang(b)
> > a = min(max(b, -1), 1);
> > return;
> >
> ---------------------------------------------------------------------------
> >
> > I know there is something not correct, since when, for a parameter set
> 'p',
> > i do spm_imatrix2D(spm_matrix2D(p)), I do not recover P for all entries,
> > specially
> > rotation and shears. C(2) above always evaluates to zero. The result is
> that
> > these errors
> > accumulate (or are not accounted for) on repeated application of this
> > sequence of
> > operations in the registration routine.
> >
> > Thanks in anticipation,
> > Sid.
> >
> >
> >
> > On Fri, Apr 22, 2011 at 9:13 AM, Siddharth Srivastava <[log in to unmask]>
> > wrote:
> >>
> >> Hi John,
> >> Thanks a lot for your answer, and it has been very helpful for my
> >> understanding
> >> of the details of the implementation, and my own development efforts. I
> >> have
> >> 2 very quick questions, though:
> >>
> >> 1) the parameter set x(:) that is returned from spm_mireg, and the
> >> "params" that
> >> spm_affsub3 returns (in spm99, which is also the version that I am
> looking
> >> at) ,
> >> are they equivalent? In other words, If I am collating the parameters
> from
> >> the mireg
> >> routine, would the distribution x(7:12) be used to estimate the icovar0
> >> entries in affsub3?
> >>
> >> 2) also would VG.mat\spm_matrix(x)*VF.mat transform G to F similar to
> >> VG.mat\spm_matrix(params)*VF.mat , or do I have to do
> >> M = VG.mat\spm_matrix(x(:)')*VF.mat
> >> pp = spm_imatrix(M)
> >> and use pp(7:12) ?
> >>
> >>
> >>
> >> Thanks again.
> >> Sid.
> >>
> >> On Thu, Apr 14, 2011 at 2:13 PM, John Ashburner <[log in to unmask]>
> >> wrote:
> >>>
> >>> > I had a look at the code in spm_maff, and
> >>> > it looks like it also uses the values of isig and mu in the call to
> >>> > affreg(). My guess is
> >>> > that during the initial registration on a large data set for
> estimating
> >>> > the
> >>> > prior
> >>> > distribution of parameters, this will be called with typ = 'none' .
> Is
> >>> > this
> >>> > correct?
> >>>
> >>> Once the registration has locked in on a solution, the priors have
> >>> less influence. Their main influence is in the early stages of the
> >>> registration, or when there are relatively few slices in the data. I
> >>> don't actually remember if the registration was regularised when I
> >>> computed their values.
> >>>
> >>> >
> >>> > Further, do we have to do a non-rigid registration for the estimation
> >>> > (since, in the comments the selected
> >>> > files are filtered as *seg_inv_sn.mat"? Since only p.Affine is being
> >>> > used,
> >>> > can this work with only
> >>> > an affine / rigid transformation?
> >>>
> >>> Only the affine transform in the files is used, so basically yes. You
> >>> could just do affine registration.
> >>>
> >>> >
> >>> > I would also be happy if you could also answer my other question
> about
> >>> > examining the
> >>> > effects of the values in isig and mu (what are the units of mu?) on
> the
> >>> > transformed image.
> >>>
> >>> They are unit-less, and are just a measure of the zooms and shears.
> >>>
> >>> > For example,
> >>> > if i set a mu of [mu1, mu2, ...] and a isig of [sig1, 0, 0...; 0,
> sig2,
> >>> > 0,
> >>> > 0..; ...] (with only diagonal components),
> >>> > based on the Hencky tensor penalty, it seems that large deviations of
> >>> > parameter 1 estimate (T - mu) from
> >>> > mu1 will be penalized. How is the value of isig1 modifying the
> penalty?
> >>>
> >>> Its assuming that the elements of the matrix log of the part that does
> >>> shears and zooms has a multivariate normal distribution, so the
> >>> penalty is a kind of negative log likelhood. The isig is essentially
> >>> a precision matrix, which is the inverse of a covariance matrix.
> >>>
> >>> p(x|mu,S) = 1/sqrt(det(2*pi*S)) * exp(-0.5*(x-mu)'*inv(S)*(x-mu))
> >>>
> >>> Taking logs and negating, you get 0.5*(x-mu)'*inv(S)*(x-mu) + const
> >>>
> >>> > How
> >>> > do the off diagonal terms affect
> >>> > the penalty?
> >>>
> >>> The inverse of isig would just encode the covariance between the
> >>> various shears and zooms.
> >>>
> >>> >
> >>> > Could you also point me to a reference where I can learn more about
> >>> > Hencky
> >>> > strain tensor (specifically
> >>> > what information it carries in the context of image processing etc.)
> >>>
> >>> I don't know if this is of any use:
> >>>
> >>> http://en.wikipedia.org/wiki/Deformation_(mechanics)
> >>>
> >>> Best regards,
> >>> -John
> >>>
> >>>
> >>> > On Thu, Apr 14, 2011 at 10:17 AM, John Ashburner <
> [log in to unmask]>
> >>> > wrote:
> >>> >>
> >>> >> They were computed by affine registering loads of (227) images to
> MNI
> >>> >> space. This gave the affine transforms, which were then used to
> build
> >>> >> up a mean and inverse covariance matrix. In the comments of
> >>> >> spm_maff.m, you should see the following...
> >>> >>
> >>> >> %% Values can be derived by...
> >>> >> %sn = spm_select(Inf,'.*seg_inv_sn.mat$');
> >>> >> %X = zeros(size(sn,1),12);
> >>> >> %for i=1:size(sn,1),
> >>> >> % p = load(deblank(sn(i,:)));
> >>> >> % M = p.VF(1).mat*p.Affine/p.VG(1).mat;
> >>> >> % J = M(1:3,1:3);
> >>> >> % V = sqrtm(J*J');
> >>> >> % R = V\J;
> >>> >> % lV = logm(V);
> >>> >> % lR = -logm(R);
> >>> >> % P = zeros(12,1);
> >>> >> % P(1:3) = M(1:3,4);
> >>> >> % P(4:6) = lR([2 3 6]);
> >>> >> % P(7:12) = lV([1 2 3 5 6 9]);
> >>> >> % X(i,:) = P';
> >>> >> %end;
> >>> >> %mu = mean(X(:,7:12));
> >>> >> %XR = X(:,7:12) - repmat(mu,[size(X,1),1]);
> >>> >> %isig = inv(XR'*XR/(size(X,1)-1))
> >>> >>
> >>> >> You may be able to re-code this to work with your 2D transforms.
> Note
> >>> >> that I only use the components that describe shears and zooms.
> Also,
> >>> >> if I was re-coding it all again, I would probably do things slightly
> >>> >> differently, using the following decomposition:
> >>> >>
> >>> >> J=M(1:3,1:3);
> >>> >> L=real(logm(J));
> >>> >> S=(L+L')/2; % Symmetric part (for zooms and shears, which should be
> >>> >> penalised)
> >>> >> A=(L-L')/2; % Anti-symmetric part (for rotations)
> >>> >>
> >>> >> I might even base the penalty on lambda(2)*trace(S)^2 +
> >>> >> lambda(1)*trace(S*S'), which is often used as a measure of "elastic
> >>> >> energy" for penalising non-linear registration. Of course, there
> >>> >> would also be a bit of annoying extra stuff to deal with due to MNI
> >>> >> space being a bit bigger than average brains are. Figuring out the
> >>> >> mean would require (I think) an iterative process similar to the one
> >>> >> described in "Characterizing volume and surface deformations in an
> >>> >> atlas framework: theory, applications, and implementation", by Woods
> >>> >> in NeuroImage (2003).
> >>> >>
> >>> >> Best regards,
> >>> >> -John
> >>> >>
> >>> >> On 14 April 2011 17:15, Siddharth Srivastava <[log in to unmask]>
> wrote:
> >>> >> > Hi all,
> >>> >> > My question pertains specifically to the values of isig and
> mu
> >>> >> > that
> >>> >> > are
> >>> >> > incorporated
> >>> >> > in the code, and I wish to disentangle the effect that these
> numbers
> >>> >> > have on
> >>> >> > individual parameters
> >>> >> > during the optimization stage. I am trying to map it to a 2D case,
> >>> >> > and
> >>> >> > these
> >>> >> > numbers
> >>> >> > will have to be calculated ab-initio for my case. Before I begin
> >>> >> > with
> >>> >> > estimating the prior distribution
> >>> >> > for these parameters, I need to check the effect that they have on
> >>> >> > the
> >>> >> > registered images. Regarding this
> >>> >> > 1) Can someone suggest a way I can examine the effect on each
> >>> >> > parameter
> >>> >> > separately, if it is
> >>> >> > at all possible.
> >>> >> > 2) Some advise on how to estimate these parameters, if it has been
> >>> >> > done
> >>> >> > for
> >>> >> > images other
> >>> >> > than brain images, will be really helpful for me.
> >>> >> >
> >>> >> > Thanks,
> >>> >> > Sid.
> >>> >> >
> >>> >> > On Mon, Mar 28, 2011 at 7:04 PM, Siddharth Srivastava
> >>> >> > <[log in to unmask]>
> >>> >> > wrote:
> >>> >> >>
> >>> >> >> Dear John,
> >>> >> >> Thanks for your answer. I was able to correctly run my
> 2D
> >>> >> >> implementation
> >>> >> >> based on your advise. However, I am am not very confident of my
> >>> >> >> results
> >>> >> >> and wanted to
> >>> >> >> consult you on certain aspects of my mapping from 3D to 2D.
> >>> >> >> 1) In function reg(..), the comment says that the
> >>> >> >> derivatives
> >>> >> >> w.r.t rotations and
> >>> >> >> translations is zero. Consequently, I ran the indices from 4:7.
> >>> >> >> According
> >>> >> >> to your previous
> >>> >> >> reply, rotations will be lumped together with scaling and affine
> in
> >>> >> >> 4
> >>> >> >> parameters, and
> >>> >> >> translations, independently, in the last two. I understand that
> in
> >>> >> >> this
> >>> >> >> case, the indices
> >>> >> >> run over parameters that have been separated into individual
> >>> >> >> components
> >>> >> >> (similar to
> >>> >> >> the form accepted by spm_matrix). Is this correct for the
> function
> >>> >> >> reg(..)? In fact, I went back to the
> >>> >> >> old spm code (spm99), and found parameters pdesc and free, and
> got
> >>> >> >> more
> >>> >> >> confused as to when I should
> >>> >> >> use the 6 parameter, and when to use separate parameters (as if I
> >>> >> >> was
> >>> >> >> passing them to spm_matrix).
> >>> >> >> So, when the loop runs over p1 and perturbs p1(i) by ds, does it
> >>> >> >> run
> >>> >> >> over
> >>> >> >> translations/rotations etc
> >>> >> >> or does it run over the martix elements that define these
> >>> >> >> transformations
> >>> >> >> (2x2 + 1x2)?
> >>> >> >>
> >>> >> >> 2) In function penalty(..), I have used unique
> elements
> >>> >> >> as
> >>> >> >> [1,3,4], and my code looks like
> >>> >> >> T = my_matrix(p)*M;
> >>> >> >> T = T(1:2,1:2);
> >>> >> >> T = 0.5*logm(T'*T);
> >>> >> >> T
> >>> >> >> T = T(els)' - mu;
> >>> >> >> h = T'*isig*T
> >>> >> >>
> >>> >> >> Assuming an application specific isig, is this correct?
> >>> >> >> 3) I have not yet incorporated the prior information in
> my
> >>> >> >> code,
> >>> >> >> But for testing purposes,
> >>> >> >> can you suggest some neutral values for mu and isig that I can
> try
> >>> >> >> to
> >>> >> >> concentrate on the
> >>> >> >> accuracy of the implementation minus the priors for now?
> >>> >> >> 4) My solution curently seems to oscillate around an
> >>> >> >> optimum.
> >>> >> >> I
> >>> >> >> am hoping that after
> >>> >> >> I have removed any errors after your replies, it will converge
> >>> >> >> gracefully.
> >>> >> >>
> >>> >> >> Thanks again for all the help.
> >>> >> >> Siddharth.
> >>> >> >>
> >>> >> >>
> >>> >> >> On Fri, Mar 18, 2011 at 2:05 AM, John Ashburner
> >>> >> >> <[log in to unmask]>
> >>> >> >> wrote:
> >>> >> >>>
> >>> >> >>> A 2D affine transform would use 6 parameters, rather than 7: a
> 2x2
> >>> >> >>> matrix to encode rotations, zooms and shears, and a 2x1 vector
> for
> >>> >> >>> translations.
> >>> >> >>>
> >>> >> >>> Best regards,
> >>> >> >>> -John
> >>> >> >>>
> >>> >> >>> On 18 March 2011 05:05, Siddharth Srivastava <[log in to unmask]>
> >>> >> >>> wrote:
> >>> >> >>> > Dear list users,
> >>> >> >>> > I am currently trying to understand the
> implementation
> >>> >> >>> > in
> >>> >> >>> > spm_affreg, and
> >>> >> >>> > to make matters simple, I tried to work out a 2D version of
> the
> >>> >> >>> > registration
> >>> >> >>> > procedure. I struck a roadblock, however...
> >>> >> >>> >
> >>> >> >>> > The function make_A creates part of the design matrix. For the
> >>> >> >>> > 3D
> >>> >> >>> > case,
> >>> >> >>> > the
> >>> >> >>> > 13 parameters
> >>> >> >>> > are encoded in columns of A1, which then is used to generate
> AA
> >>> >> >>> > +
> >>> >> >>> > A1'
> >>> >> >>> > A1. AA
> >>> >> >>> > is 13x13, and everything
> >>> >> >>> > works. For the 2D case, however, there will be 7+1 parameters(
> 2
> >>> >> >>> > translations, 1 rotation, 2 zoom, 2 shears and 1 intensity
> >>> >> >>> > scaling).
> >>> >> >>> > The A1 matrix for 2D, then, will be (in make_A)
> >>> >> >>> > A = [x1.*dG1 x1.*dG2 ...
> >>> >> >>> > x2.*dG1 x2.*dG2 ...
> >>> >> >>> > dG1 dG2 t];
> >>> >> >>> >
> >>> >> >>> > which is (number of sampled points) x 7. The AA matrix (in
> >>> >> >>> > function
> >>> >> >>> > costfun)
> >>> >> >>> > is 8x8
> >>> >> >>> > so, which is the parameter I am missing in modeling a 2D
> >>> >> >>> > example? I
> >>> >> >>> > hope I
> >>> >> >>> > have got the number of parameters
> >>> >> >>> > right for the 2D case? Is there an extra column that I have to
> >>> >> >>> > add
> >>> >> >>> > to
> >>> >> >>> > A1 to
> >>> >> >>> > make the rest of the matrix computation
> >>> >> >>> > consistent?
> >>> >> >>> >
> >>> >> >>> > Thanks for the help
> >>> >> >>> >
> >>> >> >>
> >>> >> >
> >>> >> >
> >>> >
> >>> >
> >>
> >
> >
>
--20cf307cfcb663f52c04a2a06e2e
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Thanks John, for the answers. The code, however exits with "Problem&qu=
ot;. M0<br>and M1 differ. <br>Also, why is there just one shear component i=
n the matrix? I have seen <br>general shears modeled as [1,h;g,1]: is this =
superfluous, and just one "h"<br>
will be sufficient for 2d case? <br><br>Thanks,<br>Sid.<br><br><br><br><div=
class=3D"gmail_quote">On Fri, May 6, 2011 at 11:01 AM, John Ashburner <spa=
n dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">[log in to unmask]
com</a>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; borde=
r-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">Your model uses 7=
parameters, but there are only 6 elements in<br>
A(1:2,1:3). =A0Also, you need to be able to deal with a broader range of<br=
>
angles, so atan2(s,c) is used to compute the angle. =A0I've tested it<b=
r>
with the following code, so hopefully it works for all cases.<br>
<br>
for i=3D1:10000<br>
=A0P=3Drandn(1,6)*10;<br>
=A0M0=3Dspm_matrix2D(P);<br>
=A0P1=3Dspm_imatrix2D(M0);<br>
=A0M1=3Dspm_matrix2D(P1);<br>
=A0t=3Dsum(sum((M1-M0).^2));<br>
=A0if t>1e-9, disp('Problem'); break; end<br>
end<br>
<br>
Note that spm_imatrix2D(spm_matrix2D(P)) does not necessarily have to<br>
equal P, but the matrices generated from the two parameter sets should<br>
be the same.<br>
<br>
Best regards,<br>
<font color=3D"#888888">-John<br>
</font><div><div></div><div class=3D"h5"><br>
On 6 May 2011 17:11, Siddharth Srivastava <<a href=3D"mailto:siddys@gmai=
l.com">[log in to unmask]</a>> wrote:<br>
> Hi everyone,<br>
> =A0=A0=A0=A0=A0 Can someone help me check the 2D versions of the spm_m=
atrix and<br>
> spm_imatrix? My<br>
> implementation currently is as follows:<br>
><br>
> ---2D spm_matrix ---<br>
> function [A] =3D spm_matrix2D(P)<br>
> % P =3D [Tx, Ty, R, Zx, Zy, Sx,Sy]<br>
> p0 =3D [0,0,0,1,1,0,0];<br>
> P =3D [P, p0((length(P)+1):7)]<br>
><br>
> A =3D eye(3);<br>
> % T -> R -> Zoom -> Shear<br>
> =A0A =3D=A0=A0=A0=A0 A * [1,0,P(1); ...<br>
> =A0=A0=A0=A0=A0=A0=A0=A0=A0 0,1,P(2); ...<br>
> =A0 =A0=A0=A0 =A0 0,0,=A0=A0 1];<br>
> =A0A =3D=A0=A0=A0=A0 A * [cos(P(3)), sin(P(3)), 0; ...<br>
> =A0=A0=A0=A0=A0=A0=A0=A0=A0 -sin(P(3)),=A0 cos(P(3)), 0; ...<br>
> =A0=A0=A0 =A0 0,=A0=A0=A0=A0=A0=A0=A0=A0=A0 0,=A0=A0=A0=A0=A0=A0=A0=A0=
1];<br>
> =A0A =3D=A0=A0=A0=A0 A * [P(4), 0, 0; ...<br>
> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 0,=A0=A0 P(5), 0; ...<br>
> =A0=A0=A0 =A0=A0=A0=A0=A0 0, 0, 1];<br>
> =A0A =3D=A0=A0=A0=A0 A * [1, P(6), 0; ...<br>
> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 P(7)=A0 , 1, 0; ...<br>
> =A0=A0=A0 =A0=A0=A0=A0=A0 0, 0, 1];<br>
> --------------------------------------------------<br>
> -----2D spm_imatrix ------------------------<br>
> function P =3D=A0 spm_imatrix2D(M);<br>
><br>
><br>
><br>
> R =3D M(1:2,1:2);<br>
> C =3D chol(R' * R);<br>
> P =3D [M(1:2,3)',0,diag(C)',0,0];<br>
> if(det(R) < 0) P(4) =3D -P(4); end<br>
> C =3D diag(diag(C))\C;<br>
> P(6:7) =3D C([2,3]);<br>
><br>
> R0 =3D spm_matrix2D([0,0,0,P(4:end)]);<br>
> R0 =3D R0(1:2,1:2);<br>
> R1 =3D R/R0;<br>
><br>
> th =3D asin(rang(R1(1,2)));<br>
> P(3) =3D th;<br>
><br>
> % There may be slight rounding errors making b>1 or b<-1.<br>
> function=A0 a =3D rang(b)<br>
> a =3D min(max(b, -1), 1);<br>
> return;<br>
> ----------------------------------------------------------------------=
-----<br>
><br>
> I know there is something not correct, since when, for a parameter set=
'p',<br>
> i do spm_imatrix2D(spm_matrix2D(p)), I do not recover P for all entrie=
s,<br>
> specially<br>
> rotation and shears. C(2) above always evaluates to zero. The result i=
s that<br>
> these errors<br>
> accumulate (or are not accounted for) on repeated application of this<=
br>
> sequence of<br>
> operations in the registration routine.<br>
><br>
> Thanks in anticipation,<br>
> Sid.<br>
><br>
><br>
><br>
> On Fri, Apr 22, 2011 at 9:13 AM, Siddharth Srivastava <<a href=3D"m=
ailto:[log in to unmask]">[log in to unmask]</a>><br>
> wrote:<br>
>><br>
>> Hi John,<br>
>> =A0=A0=A0=A0=A0 Thanks a lot for your answer, and it has been very=
helpful for my<br>
>> understanding<br>
>> of the details of the implementation, and my own development effor=
ts. I<br>
>> have<br>
>> 2 very quick questions, though:<br>
>><br>
>> 1) the parameter set x(:) that is returned from spm_mireg, and the=
<br>
>> "params" that<br>
>> spm_affsub3 returns (in spm99, which is also the version that I am=
looking<br>
>> at) ,<br>
>> are they equivalent? In other words, If I am collating the paramet=
ers from<br>
>> the mireg<br>
>> routine, would the distribution x(7:12) be used to estimate the ic=
ovar0<br>
>> entries in affsub3?<br>
>><br>
>> 2) also would VG.mat\spm_matrix(x)*VF.mat transform G to F similar=
to<br>
>> =A0=A0=A0=A0 VG.mat\spm_matrix(params)*VF.mat , or do I have to do=
<br>
>> =A0=A0=A0=A0=A0 M =3D VG.mat\spm_matrix(x(:)')*VF.mat<br>
>> =A0=A0=A0=A0=A0 pp =3D spm_imatrix(M)<br>
>> =A0=A0=A0=A0=A0 and use pp(7:12) ?<br>
>><br>
>><br>
>><br>
>> Thanks again.<br>
>> Sid.<br>
>><br>
>> On Thu, Apr 14, 2011 at 2:13 PM, John Ashburner <<a href=3D"mai=
lto:[log in to unmask]">[log in to unmask]</a>><br>
>> wrote:<br>
>>><br>
>>> > I had a look at the code in spm_maff, and<br>
>>> > it looks like it also uses the values of isig and mu in t=
he call to<br>
>>> > affreg(). My guess is<br>
>>> > that during the initial registration on a large data set =
for estimating<br>
>>> > the<br>
>>> > prior<br>
>>> > distribution of parameters, this will be called with typ =
=3D 'none' . Is<br>
>>> > this<br>
>>> > correct?<br>
>>><br>
>>> Once the registration has locked in on a solution, the priors =
have<br>
>>> less influence. =A0Their main influence is in the early stages=
of the<br>
>>> registration, or when there are relatively few slices in the d=
ata. =A0I<br>
>>> don't actually remember if the registration was regularise=
d when I<br>
>>> computed their values.<br>
>>><br>
>>> ><br>
>>> > Further, do we have to do a non-rigid registration for th=
e estimation<br>
>>> > (since, in the comments the selected<br>
>>> > files are filtered as *seg_inv_sn.mat"? Since only p=
.Affine is being<br>
>>> > used,<br>
>>> > can this work with only<br>
>>> > an affine / rigid transformation?<br>
>>><br>
>>> Only the affine transform in the files is used, so basically y=
es. =A0You<br>
>>> could just do affine registration.<br>
>>><br>
>>> ><br>
>>> > I would also be happy if you could also answer my other q=
uestion about<br>
>>> > examining the<br>
>>> > effects of the values in isig and mu (what are the units =
of mu?) on the<br>
>>> > transformed image.<br>
>>><br>
>>> They are unit-less, and are just a measure of the zooms and sh=
ears.<br>
>>><br>
>>> > For example,<br>
>>> > if i set a mu of [mu1, mu2, ...] and a isig of [sig1, 0, =
0...; 0, sig2,<br>
>>> > 0,<br>
>>> > 0..; ...] (with only diagonal components),<br>
>>> > based on the Hencky tensor penalty, it seems that large d=
eviations of<br>
>>> > parameter 1=A0 estimate (T - mu) from<br>
>>> > mu1 will be penalized. How is the value of isig1 modifyin=
g the penalty?<br>
>>><br>
>>> Its assuming that the elements of the matrix log of the part t=
hat does<br>
>>> shears and zooms has a multivariate normal distribution, so th=
e<br>
>>> penalty is a kind of negative log likelhood. =A0The isig is es=
sentially<br>
>>> a precision matrix, which is the inverse of a covariance matri=
x.<br>
>>><br>
>>> p(x|mu,S) =3D 1/sqrt(det(2*pi*S)) * exp(-0.5*(x-mu)'*inv(S=
)*(x-mu))<br>
>>><br>
>>> Taking logs and negating, you get 0.5*(x-mu)'*inv(S)*(x-mu=
) + const<br>
>>><br>
>>> > How<br>
>>> > do the off diagonal terms affect<br>
>>> > the penalty?<br>
>>><br>
>>> The inverse of isig would just encode the covariance between t=
he<br>
>>> various shears and zooms.<br>
>>><br>
>>> ><br>
>>> > Could you also point me to a reference where I can learn =
more about<br>
>>> > Hencky<br>
>>> > strain tensor (specifically<br>
>>> > what information it carries in the context of image proce=
ssing etc.)<br>
>>><br>
>>> I don't know if this is of any use:<br>
>>><br>
>>> <a href=3D"http://en.wikipedia.org/wiki/Deformation_%28mechani=
cs%29" target=3D"_blank">http://en.wikipedia.org/wiki/Deformation_(mechanic=
s)</a><br>
>>><br>
>>> Best regards,<br>
>>> -John<br>
>>><br>
>>><br>
>>> > On Thu, Apr 14, 2011 at 10:17 AM, John Ashburner <<a h=
ref=3D"mailto:[log in to unmask]">[log in to unmask]</a>><br>
>>> > wrote:<br>
>>> >><br>
>>> >> They were computed by affine registering loads of (22=
7) images to MNI<br>
>>> >> space. =A0This gave the affine transforms, which were=
then used to build<br>
>>> >> up a mean and inverse covariance matrix. =A0In the co=
mments of<br>
>>> >> spm_maff.m, you should see the following...<br>
>>> >><br>
>>> >> %% Values can be derived by...<br>
>>> >> %sn =3D spm_select(Inf,'.*seg_inv_sn.mat$');<=
br>
>>> >> %X =A0=3D zeros(size(sn,1),12);<br>
>>> >> %for i=3D1:size(sn,1),<br>
>>> >> % =A0 =A0p =A0=3D load(deblank(sn(i,:)));<br>
>>> >> % =A0 =A0M =A0=3D p.VF(1).mat*p.Affine/p.VG(1).mat;<b=
r>
>>> >> % =A0 =A0J =A0=3D M(1:3,1:3);<br>
>>> >> % =A0 =A0V =A0=3D sqrtm(J*J');<br>
>>> >> % =A0 =A0R =A0=3D V\J;<br>
>>> >> % =A0 =A0lV =A0 =A0 =A0=3D =A0logm(V);<br>
>>> >> % =A0 =A0lR =A0 =A0 =A0=3D -logm(R);<br>
>>> >> % =A0 =A0P =A0 =A0 =A0 =3D zeros(12,1);<br>
>>> >> % =A0 =A0P(1:3) =A0=3D M(1:3,4);<br>
>>> >> % =A0 =A0P(4:6) =A0=3D lR([2 3 6]);<br>
>>> >> % =A0 =A0P(7:12) =3D lV([1 2 3 5 6 9]);<br>
>>> >> % =A0 =A0X(i,:) =A0=3D P';<br>
>>> >> %end;<br>
>>> >> %mu =A0 =3D mean(X(:,7:12));<br>
>>> >> %XR =A0 =3D X(:,7:12) - repmat(mu,[size(X,1),1]);<br>
>>> >> %isig =3D inv(XR'*XR/(size(X,1)-1))<br>
>>> >><br>
>>> >> You may be able to re-code this to work with your 2D =
transforms. =A0Note<br>
>>> >> that I only use the components that describe shears a=
nd zooms. =A0Also,<br>
>>> >> if I was re-coding it all again, I would probably do =
things slightly<br>
>>> >> differently, using the following decomposition:<br>
>>> >><br>
>>> >> J=3DM(1:3,1:3);<br>
>>> >> L=3Dreal(logm(J));<br>
>>> >> S=3D(L+L')/2; % Symmetric part (for zooms and she=
ars, which should be<br>
>>> >> penalised)<br>
>>> >> A=3D(L-L')/2; % Anti-symmetric part (for rotation=
s)<br>
>>> >><br>
>>> >> I might even base the penalty on lambda(2)*trace(S)^2=
+<br>
>>> >> lambda(1)*trace(S*S'), which is often used as a m=
easure of "elastic<br>
>>> >> energy" for penalising non-linear registration. =
=A0Of course, there<br>
>>> >> would also be a bit of annoying extra stuff to deal w=
ith due to MNI<br>
>>> >> space being a bit bigger than average brains are. =A0=
Figuring out the<br>
>>> >> mean would require (I think) an iterative process sim=
ilar to the one<br>
>>> >> described in "Characterizing volume and surface =
deformations in an<br>
>>> >> atlas framework: theory, applications, and implementa=
tion", by Woods<br>
>>> >> in NeuroImage (2003).<br>
>>> >><br>
>>> >> Best regards,<br>
>>> >> -John<br>
>>> >><br>
>>> >> On 14 April 2011 17:15, Siddharth Srivastava <<a h=
ref=3D"mailto:[log in to unmask]">[log in to unmask]</a>> wrote:<br>
>>> >> > Hi all,<br>
>>> >> > =A0=A0=A0=A0 My question pertains specifically t=
o the values of isig and mu<br>
>>> >> > that<br>
>>> >> > are<br>
>>> >> > incorporated<br>
>>> >> > in the code, and I wish to disentangle the effec=
t that these numbers<br>
>>> >> > have on<br>
>>> >> > individual parameters<br>
>>> >> > during the optimization stage. I am trying to ma=
p it to a 2D case,<br>
>>> >> > and<br>
>>> >> > these<br>
>>> >> > numbers<br>
>>> >> > will have to be calculated ab-initio for my case=
. Before I begin<br>
>>> >> > with<br>
>>> >> > estimating the prior distribution<br>
>>> >> > for these parameters, I need to check the effect=
that they have on<br>
>>> >> > the<br>
>>> >> > registered images. Regarding this<br>
>>> >> > 1) Can someone suggest a way I can examine the e=
ffect on each<br>
>>> >> > parameter<br>
>>> >> > separately, if it is<br>
>>> >> > =A0=A0=A0=A0 at all possible.<br>
>>> >> > 2) Some advise on how to estimate these paramete=
rs, if it has been<br>
>>> >> > done<br>
>>> >> > for<br>
>>> >> > images other<br>
>>> >> > =A0=A0=A0=A0 than brain images, will be really h=
elpful for me.<br>
>>> >> ><br>
>>> >> > Thanks,<br>
>>> >> > Sid.<br>
>>> >> ><br>
>>> >> > On Mon, Mar 28, 2011 at 7:04 PM, Siddharth Sriva=
stava<br>
>>> >> > <<a href=3D"mailto:[log in to unmask]">siddys@g=
mail.com</a>><br>
>>> >> > wrote:<br>
>>> >> >><br>
>>> >> >> Dear John,<br>
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 Thanks for your =
answer. I was able to correctly run my 2D<br>
>>> >> >> implementation<br>
>>> >> >> based on your advise. However, I am am not v=
ery confident of my<br>
>>> >> >> results<br>
>>> >> >> and wanted to<br>
>>> >> >> consult you on certain aspects of my mapping=
from 3D to 2D.<br>
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 1) In functio=
n reg(..), the comment says that the<br>
>>> >> >> derivatives<br>
>>> >> >> w.r.t rotations and<br>
>>> >> >> translations is zero. Consequently, I ran th=
e indices from 4:7.<br>
>>> >> >> According<br>
>>> >> >> to your previous<br>
>>> >> >> reply, rotations will be lumped together wit=
h scaling and affine in<br>
>>> >> >> 4<br>
>>> >> >> parameters, and<br>
>>> >> >> translations, independently, in the last two=
. I understand that in<br>
>>> >> >> this<br>
>>> >> >> case, the indices<br>
>>> >> >> run over parameters that have been separated=
into individual<br>
>>> >> >> components<br>
>>> >> >> (similar to<br>
>>> >> >> the form accepted by spm_matrix). Is this co=
rrect for the function<br>
>>> >> >> reg(..)?=A0 In fact, I went back to the<br>
>>> >> >> old spm code (spm99), and found parameters p=
desc and free, and got<br>
>>> >> >> more<br>
>>> >> >> confused as to when I should<br>
>>> >> >> use the 6 parameter, and when to use separat=
e parameters (as if I<br>
>>> >> >> was<br>
>>> >> >> passing them to spm_matrix).<br>
>>> >> >> So, when the loop runs over p1 and perturbs =
p1(i) by ds, does it<br>
>>> >> >> run<br>
>>> >> >> over<br>
>>> >> >> translations/rotations etc<br>
>>> >> >> or does it run over the martix elements that=
define these<br>
>>> >> >> transformations<br>
>>> >> >> (2x2 + 1x2)?<br>
>>> >> >><br>
>>> >> >> =A0 =A0 =A0 =A0 =A0=A0 2) In function penalt=
y(..), I have used unique elements<br>
>>> >> >> as<br>
>>> >> >> [1,3,4], and my code looks like<br>
>>> >> >> T =3D my_matrix(p)*M;<br>
>>> >> >> T =3D T(1:2,1:2);<br>
>>> >> >> T =3D 0.5*logm(T'*T);<br>
>>> >> >> T<br>
>>> >> >> T =3D T(els)' - mu;<br>
>>> >> >> h =3D T'*isig*T<br>
>>> >> >><br>
>>> >> >> Assuming an application specific isig, is th=
is correct?<br>
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0 3) I have not yet i=
ncorporated the prior information in my<br>
>>> >> >> code,<br>
>>> >> >> But for testing purposes,<br>
>>> >> >> can you suggest some neutral values=A0 for m=
u and isig that I can try<br>
>>> >> >> to<br>
>>> >> >> concentrate on the<br>
>>> >> >> accuracy of the implementation minus the pri=
ors for now?<br>
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 4) My solution c=
urently seems to oscillate around an<br>
>>> >> >> optimum.<br>
>>> >> >> I<br>
>>> >> >> am hoping that after<br>
>>> >> >> I have removed any errors after your replies=
, it will converge<br>
>>> >> >> gracefully.<br>
>>> >> >><br>
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 Thanks again for=
all the help.<br>
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 Siddharth.<br=
>
>>> >> >><br>
>>> >> >><br>
>>> >> >> On Fri, Mar 18, 2011 at 2:05 AM, John Ashbur=
ner<br>
>>> >> >> <<a href=3D"mailto:[log in to unmask]">=
[log in to unmask]</a>><br>
>>> >> >> wrote:<br>
>>> >> >>><br>
>>> >> >>> A 2D affine transform would use 6 parame=
ters, rather than 7: a 2x2<br>
>>> >> >>> matrix to encode rotations, zooms and sh=
ears, and a 2x1 vector for<br>
>>> >> >>> translations.<br>
>>> >> >>><br>
>>> >> >>> Best regards,<br>
>>> >> >>> -John<br>
>>> >> >>><br>
>>> >> >>> On 18 March 2011 05:05, Siddharth Srivas=
tava <<a href=3D"mailto:[log in to unmask]">[log in to unmask]</a>><br>
>>> >> >>> wrote:<br>
>>> >> >>> > Dear list users,<br>
>>> >> >>> > =A0=A0=A0=A0=A0=A0=A0=A0=A0 I am cu=
rrently trying to understand the implementation<br>
>>> >> >>> > in<br>
>>> >> >>> > spm_affreg, and<br>
>>> >> >>> > to make matters simple, I tried to =
work out a 2D version of the<br>
>>> >> >>> > registration<br>
>>> >> >>> > procedure. I struck a roadblock, ho=
wever...<br>
>>> >> >>> ><br>
>>> >> >>> > The function make_A creates part of=
the design matrix. For the<br>
>>> >> >>> > 3D<br>
>>> >> >>> > case,<br>
>>> >> >>> > the<br>
>>> >> >>> > 13 parameters<br>
>>> >> >>> > are encoded in columns of A1, which=
then is used to generate AA<br>
>>> >> >>> > +<br>
>>> >> >>> > A1'<br>
>>> >> >>> > A1. AA<br>
>>> >> >>> > is 13x13, and everything<br>
>>> >> >>> > works. For the 2D case, however, th=
ere will be 7+1 parameters( 2<br>
>>> >> >>> > translations, 1 rotation, 2 zoom, 2=
shears and 1 intensity<br>
>>> >> >>> > scaling).<br>
>>> >> >>> > The A1 matrix for 2D, then,=A0 will=
be (in make_A)<br>
>>> >> >>> > A=A0 =3D [x1.*dG1 x1.*dG2 ...<br>
>>> >> >>> > =A0=A0=A0=A0=A0 x2.*dG1 x2.*dG2 ...=
<br>
>>> >> >>> > =A0=A0=A0 =A0 dG1=A0=A0=A0=A0 dG2=
=A0 t];<br>
>>> >> >>> ><br>
>>> >> >>> > which is (number of sampled points)=
x 7. The AA matrix (in<br>
>>> >> >>> > function<br>
>>> >> >>> > costfun)<br>
>>> >> >>> > is 8x8<br>
>>> >> >>> > so, which is the parameter I am mis=
sing in modeling a 2D<br>
>>> >> >>> > example? I<br>
>>> >> >>> > hope I<br>
>>> >> >>> > have got the number of parameters<b=
r>
>>> >> >>> > right for the 2D case? Is there an =
extra column that I have to<br>
>>> >> >>> > add<br>
>>> >> >>> > to<br>
>>> >> >>> > A1 to<br>
>>> >> >>> > make the rest of the matrix computa=
tion<br>
>>> >> >>> > consistent?<br>
>>> >> >>> ><br>
>>> >> >>> > Thanks for the help<br>
>>> >> >>> ><br>
>>> >> >><br>
>>> >> ><br>
>>> >> ><br>
>>> ><br>
>>> ><br>
>><br>
><br>
><br>
</div></div></blockquote></div><br>
--20cf307cfcb663f52c04a2a06e2e--
=========================================================================
Date: Sat, 7 May 2011 06:47:09 +1000
Reply-To: Alex Fornito <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Alex Fornito <[log in to unmask]>
Subject: Re: PPI question
Comments: To: "MCLAREN, Donald" <[log in to unmask]>
Comments: cc: Darren Gitelman <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset="ISO-8859-1"
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Great. Thanks for clariyfing.
One last question...
In some cases, I want to correlate the PPI term with another time course.
Given that both the PPI term and the other time course are whitened by
spm_regions, can I assume that the autocorrelation has been removed and I
can safely use the standard p-value for that correlation?
Thanks again!
Alex
On 07/05/2011 04:07, "MCLAREN, Donald" <[log in to unmask]> wrote:
> The null-space of the contrast are any columns of the contrast (which
> must be an F-contrast) that are 0. Thus, you remove the effects of
> motion when you do the adjustment and don't need to worry about them
> being included in the deconvolved data. The code that I have supplied
> has N rows for N conditions of interest after I talked to Darren about
> the ideal contrast to use for adjustment.
>=20
> As for removing the frequencies, I think it is probably fine to remove
> them, I was just under the impression that they weren't being removed
> because of me commenting out that line during testing of spm_regions.
> I would go with the SPM defaults until their effect is tested. If you
> don't set a high-pass filter, then you won't remove the frequencies,
> so you could test it that way as well.
>=20
> Best Regards, Donald McLaren
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> D.G. McLaren, Ph.D.
> Postdoctoral Research Fellow, GRECC, Bedford VA
> Research Fellow, Department of Neurology, Massachusetts General
> Hospital and Harvard Medical School
> Office: (773) 406-2464
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> This e-mail contains CONFIDENTIAL INFORMATION which may contain
> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
> and which is intended only for the use of the individual or entity
> named above. If the reader of the e-mail is not the intended recipient
> or the employee or agent responsible for delivering it to the intended
> recipient, you are hereby notified that you are in possession of
> confidential and privileged information. Any unauthorized use,
> disclosure, copying or the taking of any action in reliance on the
> contents of this information is strictly prohibited and may be
> unlawful. If you have received this e-mail unintentionally, please
> immediately notify the sender via telephone at (773) 406-2464 or
> email.
>=20
>=20
>=20
> On Thu, May 5, 2011 at 9:46 PM, Alex Fornito <[log in to unmask]> wr=
ote:
>> Hi Donald, Torben and Darren,
>> Thanks for your responses.
>>=20
>> Form each of your responses, it seems like best practice would be to rem=
ove
>> motion (and/or other confounds) from the VOI time series prior to
>> deconvolution.
>>=20
>> It also seems like you are recommending NOT to frequency filter the VOI =
time
>> series.
>>=20
>> In my reading though, spm_regions does this by default with the call to
>> spm_filter (line 135). So, if spm_regions is used to extract a VOI time
>> series, the time series that is input to spm_peb_ppi will already freque=
ncy
>> filtered. So it seems like, in standard practice, the deconvolution is
>> applied to frequency-filtered data. In this case, if xX.iG is empty, the
>> only difference between Y and Yc in spm_peb_ppi is the additional remova=
l of
>> block effects (xX.iB).
>>=20
>> Based on the current chain of emails, it seems you are recommending that=
a
>> confound-corrected, whitened, but non-frequency filtered time course sho=
uld
>> be input to spm_peb_ppi. IS that correct, or am I missing something?
>>=20
>> Finally, can I clarify exactly what the null space of the contrast is? M=
ost
>> of the time in my analyses I don't get the option to adjust for it, so x=
Y.Ic
>> is empty.
>>=20
>> Thanks again for all your help,
>> A
>>=20
>>=20
>>=20
>> On 06/05/2011 02:18, "MCLAREN, Donald" <[log in to unmask]> wrote:
>>=20
>>> I haven't thoroughly tested this, but if you set iG to be the movement
>>> parameters columns. Then still adjust for the null space (motion
>>> parameters). You will get the best of both. If you don't adjust for
>>> the null space, then movement will contribute to the deconvolution. In
>>> summary, if you have iG be the motion parameter columns AND adjust for
>>> the null-space (motion columns), then:
>>>=20
>>> Y will have the effect of motion removed. Yc (removal of motion twice)
>>> will be minimally different since Y is orthogonal to the motion
>>> parameters. So, you have motion removed from both the autocorrelation
>>> estimate, the Y for deconvolution, and Yc.
>>>=20
>>> Best Regards, Donald McLaren
>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>> D.G. McLaren, Ph.D.
>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>> Research Fellow, Department of Neurology, Massachusetts General
>>> Hospital and Harvard Medical School
>>> Office: (773) 406-2464
>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>>> and which is intended only for the use of the individual or entity
>>> named above. If the reader of the e-mail is not the intended recipient
>>> or the employee or agent responsible for delivering it to the intended
>>> recipient, you are hereby notified that you are in possession of
>>> confidential and privileged information. Any unauthorized use,
>>> disclosure, copying or the taking of any action in reliance on the
>>> contents of this information is strictly prohibited and may be
>>> unlawful. If you have received this e-mail unintentionally, please
>>> immediately notify the sender via telephone at (773) 406-2464 or
>>> email.
>>>=20
>>>=20
>>>=20
>>> On Thu, May 5, 2011 at 9:48 AM, Torben Ellegaard Lund
>>> <[log in to unmask]> wrote:
>>>> Hi Alex
>>>>=20
>>>>=20
>>>> Den Uge:18 05/05/2011 kl. 14.15 skrev Alex Fornito:
>>>>=20
>>>>> Hi Torben,
>>>>> Sorry, I just wanted to clarify: do you mean leaving SPM.xX.iG empty?=
It
>>>>> seems like this is done by default by spm_fmri_design (?)
>>>>=20
>>>> leaving it empty will include all user defined regressors in the effec=
ts of
>>>> interest F-test which determines the mask where the serial correlation=
is
>>>> estimated. I think it would make sense if the motion regressors did no=
t go
>>>> into this test, just like the DCS HP-filter does not go into the
>>>> F-contrast.
>>>>=20
>>>>> Are you suggesting manually entering motion parameters into this fiel=
d?
>>>>=20
>>>> Yes, or their indices that is. It should be done after specification, =
but
>>>> before model estimation. You can check if SPM recognized your changes =
by
>>>> looking at the automatically generated effects of interest F-contrast.
>>>>=20
>>>>=20
>>>> Best
>>>> Torben
>>>>=20
>>>>=20
>>>>=20
>>>>=20
>>>>>=20
>>>>> On 05/05/2011 18:16, "Torben Ellegaard Lund" <[log in to unmask]> wro=
te:
>>>>>=20
>>>>>> Just as a kind reminder. Leaving SPM.xX.iG is a bit unfortunate, bec=
ause
>>>>>> voxels where motion artefacts are significant then constitutes a lar=
ge
>>>>>> part
>>>>>> of
>>>>>> the F-test derived mask used to estimate serial correlations. If you=
are
>>>>>> picky
>>>>>> about this you can change it yourselves, but it is not as easy as it
>>>>>> should
>>>>>> be.
>>>>>>=20
>>>>>>=20
>>>>>> Best
>>>>>> Torben
>>>>>>=20
>>>>>>=20
>>>>>>=20
>>>>>> Den Uge:18 05/05/2011 kl. 05.03 skrev Alex Fornito:
>>>>>>=20
>>>>>>> Ahh, I see. I was assuming that SPM.xX.iG contained the indices to =
the
>>>>>>> nuisance covariates in the design matrix, but you're right -
>>>>>>> spm_fMRI_design
>>>>>>> leaves it empty.
>>>>>>>=20
>>>>>>> Thanks for your help!
>>>>>>> A
>>>>>>>=20
>>>>>>>=20
>>>>>>> On 05/05/2011 12:54, "MCLAREN, Donald" <[log in to unmask]> w=
rote:
>>>>>>>=20
>>>>>>>> I agree that nuisance covariates, such as motion should be removed=
;
>>>>>>>> however, motion covariates are not generally stored in X0 in my
>>>>>>>> reading of the SPM code (spm_fMRI_design, spm_regions). They shoul=
d be
>>>>>>>> removed in the spm_regions filtering based on the null-space of th=
e
>>>>>>>> contrast.
>>>>>>>>=20
>>>>>>>> As for the motion parameters being in the model, if they were in t=
he
>>>>>>>> standard analysis, they should be included in the PPI analysis. My
>>>>>>>> gPPI code will do this automatically as well.
>>>>>>>>=20
>>>>>>>> X0 is made of SPM.xX.iB (block effects -- so removing the mean) an=
d
>>>>>>>> SPM.xX.iG (nuisance variable that is empty as far as I can tell (l=
ine
>>>>>>>> 369 of spm_fMRI_design)) and the high-pass filtering (K.X0).
>>>>>>>>=20
>>>>>>>> Best Regards, Donald McLaren
>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>>> Hospital and Harvard Medical School
>>>>>>>> Office: (773) 406-2464
>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGE=
D
>>>>>>>> and which is intended only for the use of the individual or entity
>>>>>>>> named above. If the reader of the e-mail is not the intended recip=
ient
>>>>>>>> or the employee or agent responsible for delivering it to the inte=
nded
>>>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>> disclosure, copying or the taking of any action in reliance on the
>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>> unlawful. If you have received this e-mail unintentionally, please
>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>>>> email.
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>> On Wed, May 4, 2011 at 10:16 PM, Alex Fornito <[log in to unmask]
u.au>
>>>>>>>> wrote:
>>>>>>>>> Hi Donald,
>>>>>>>>> Thanks for your response. When you say "you don't want
>>>>>>>>> to filter out anything related to neural activity", I'm presuming=
that
>>>>>>>>> you
>>>>>>>>> are referring to the deconvolved neural signal?
>>>>>>>>>=20
>>>>>>>>> If so, that makes sense. However, X0 also contains user-specified
>>>>>>>>> nuisance
>>>>>>>>> covariates. I would have thought it would make sense to remove th=
ose,
>>>>>>>>> depending on what they were (e.g., movement parameters)? I guess =
they
>>>>>>>>> can
>>>>>>>>> always be entered into the PPI regression model...
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>> On 05/05/2011 11:57, "MCLAREN, Donald" <[log in to unmask]>
>>>>>>>>> wrote:
>>>>>>>>>=20
>>>>>>>>>> I could be wrong, Karl or Darren please correct me if I am.
>>>>>>>>>>=20
>>>>>>>>>> X0 is composed of the high-pass filter and constant term. Thus, =
you
>>>>>>>>>> want to filter these out of the Yc regressor. However, you don't=
want
>>>>>>>>>> to filter out anything related to neural activity, so you wouldn=
't
>>>>>>>>>> want to filter your signal and then predict the neural activity =
from
>>>>>>>>>> the filtered signal, especially filtering frequencies.
>>>>>>>>>>=20
>>>>>>>>>> Best Regards, Donald McLaren
>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>>>>> Hospital and Harvard Medical School
>>>>>>>>>> Office: (773) 406-2464
>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILE=
GED
>>>>>>>>>> and which is intended only for the use of the individual or enti=
ty
>>>>>>>>>> named above. If the reader of the e-mail is not the intended
>>>>>>>>>> recipient
>>>>>>>>>> or the employee or agent responsible for delivering it to the
>>>>>>>>>> intended
>>>>>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>>>> disclosure, copying or the taking of any action in reliance on t=
he
>>>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>>>> unlawful. If you have received this e-mail unintentionally, plea=
se
>>>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>>>>>> email.
>>>>>>>>>>=20
>>>>>>>>>>=20
>>>>>>>>>>=20
>>>>>>>>>> On Sat, Apr 30, 2011 at 8:03 PM, Alex Fornito
>>>>>>>>>> <[log in to unmask]>
>>>>>>>>>> wrote:
>>>>>>>>>>> Hi Donald,
>>>>>>>>>>> As far as I can tell, spm_regions filters and whitens the VOI t=
ime
>>>>>>>>>>> series,
>>>>>>>>>>> and adjusts for the null space of the contrast if an adjustment=
is
>>>>>>>>>>> specified
>>>>>>>>>>> in xY.Ic. It defines the confound matrix, X0, but does not corr=
ect
>>>>>>>>>>> for
>>>>>>>>>>> it.
>>>>>>>>>>> The following line in spm_peb_ppi corrects for the confounds.
>>>>>>>>>>>=20
>>>>>>>>>>> Yc =A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>>>>=20
>>>>>>>>>>> So the above correction does seem to be doing something differe=
nt to
>>>>>>>>>>> spm_regions. I'm wondering why the uncorrected data, Y, is used=
when
>>>>>>>>>>> generating the ppi interaction term, while the corrected data Y=
c is
>>>>>>>>>>> to
>>>>>>>>>>> be
>>>>>>>>>>> used as a covariate of no interest in the PPI model. I would ha=
s
>>>>>>>>>>> thought
>>>>>>>>>>> that Yc should be used to generate the ppi interaction term as =
well.
>>>>>>>>>>>=20
>>>>>>>>>>> In my data, my X0 is a 195 x 7 matrix (I have 195 volumes per
>>>>>>>>>>> session).
>>>>>>>>>>>=20
>>>>>>>>>>> Regards,
>>>>>>>>>>> Alex
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>> On 30/04/2011 02:22, "MCLAREN, Donald" <[log in to unmask]
m>
>>>>>>>>>>> wrote:
>>>>>>>>>>>=20
>>>>>>>>>>>> I'm actually travelling at the moment. However, I know Y has
>>>>>>>>>>>> already
>>>>>>>>>>>> been adjusted as part of the VOI processing.
>>>>>>>>>>>>=20
>>>>>>>>>>>> Can you check what X0 looks like?
>>>>>>>>>>>>=20
>>>>>>>>>>>> Best Regards, Donald McLaren
>>>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>>>>>> Research Fellow, Department of Neurology, Massachusetts Genera=
l
>>>>>>>>>>>> Hospital and Harvard Medical School
>>>>>>>>>>>> Office: (773) 406-2464
>>>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contai=
n
>>>>>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVI=
LEGED
>>>>>>>>>>>> and which is intended only for the use of the individual or en=
tity
>>>>>>>>>>>> named above. If the reader of the e-mail is not the intended
>>>>>>>>>>>> recipient
>>>>>>>>>>>> or the employee or agent responsible for delivering it to the
>>>>>>>>>>>> intended
>>>>>>>>>>>> recipient, you are hereby notified that you are in possession =
of
>>>>>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>>>>>> disclosure, copying or the taking of any action in reliance on=
the
>>>>>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>>>>>> unlawful. If you have received this e-mail unintentionally, pl=
ease
>>>>>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 =
or
>>>>>>>>>>>> email.
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>> On Fri, Apr 29, 2011 at 2:55 AM, Alex Fornito
>>>>>>>>>>>> <[log in to unmask]>
>>>>>>>>>>>> wrote:
>>>>>>>>>>>> Hi all,
>>>>>>>>>>>> I have a question concerning the code used to implement a PPI
>>>>>>>>>>>> analysis.
>>>>>>>>>>>>=20
>>>>>>>>>>>> In the spm_peb_ppi.m function packaged with SPM8, lines 329-33=
2
>>>>>>>>>>>> remove
>>>>>>>>>>>> confounds from the input seed region=B9s time course:
>>>>>>>>>>>>=20
>>>>>>>>>>>> % Remove confounds and save Y in ouput structure
>>>>>>>>>>>>=20
%------------------------------------------------------------------>>>>>>>>=
>>>>
-
>>>>>>>>>>>> ---
>>>>>>>>>>>> --
>>>>>>>>>>>> --
>>>>>>>>>>>> Yc =A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>>>>>=20
>>>>>>>>>>>> PPI.Y is then to be used as a covariate of no interest when
>>>>>>>>>>>> building
>>>>>>>>>>>> the
>>>>>>>>>>>> PPI
>>>>>>>>>>>> regression model. However, on line 488, it is the uncorrected =
seed
>>>>>>>>>>>> time
>>>>>>>>>>>> course, Y, that is input to the deconvolution routine and used=
to
>>>>>>>>>>>> generate
>>>>>>>>>>>> the ppi term:
>>>>>>>>>>>>=20
>>>>>>>>>>>> =A0C =A0=3D spm_PEB(Y,P);
>>>>>>>>>>>> =A0 =A0xn =3D xb*C{2}.E(1:N);
>>>>>>>>>>>> =A0 =A0xn =3D spm_detrend(xn);
>>>>>>>>>>>>=20
>>>>>>>>>>>> =A0% Setup psychological variable from inputs and contast weight=
s
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
%------------------------------------------------------------------>>>>>>>>=
>>>>
-
>>>>>>>>>>>> ---
>>>>>>>>>>>> =A0PSY =3D zeros(N*NT,1);
>>>>>>>>>>>> =A0for i =3D 1:size(U.u,2)
>>>>>>>>>>>> =A0 =A0 =A0PSY =3D PSY + full(U.u(:,i)*U.w(:,i));
>>>>>>>>>>>> =A0end
>>>>>>>>>>>> =A0% PSY =3D spm_detrend(PSY); =A0<- removed centering of psych vari=
able
>>>>>>>>>>>> =A0% prior to multiplication with xn. Based on discussion with K=
arl
>>>>>>>>>>>> =A0% and Donald McLaren.
>>>>>>>>>>>>=20
>>>>>>>>>>>> % Multiply psychological variable by neural signal
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
%------------------------------------------------------------------>>>>>>>>=
>>>>
-
>>>>>>>>>>>> ---
>>>>>>>>>>>> =A0 PSYxn =3D PSY.*xn;
>>>>>>>>>>>>=20
>>>>>>>>>>>> Is there any specific reason why Y, rather than Yc(:,1), is us=
ed to
>>>>>>>>>>>> compute
>>>>>>>>>>>> PSYxn? I thought Yc might be more appropriate (?).
>>>>>>>>>>>> Thanks for your help,
>>>>>>>>>>>> Alex
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>> ------------------------------------------
>>>>>>>>>>>>=20
>>>>>>>>>>>> Alex Fornito
>>>>>>>>>>>> Research Fellow
>>>>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>>>>> University of Melbourne
>>>>>>>>>>>> National Neuroscience Facility
>>>>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>>>>> 161 Barry St
>>>>>>>>>>>> Carlton South 3053
>>>>>>>>>>>> Victoria, Australia
>>>>>>>>>>>>=20
>>>>>>>>>>>> Email: [log in to unmask]
>>>>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>> ------------------------------------------
>>>>>>>>>>>=20
>>>>>>>>>>> Alex Fornito
>>>>>>>>>>> Research Fellow
>>>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>>>> University of Melbourne
>>>>>>>>>>> National Neuroscience Facility
>>>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>>>> 161 Barry St
>>>>>>>>>>> Carlton South 3053
>>>>>>>>>>> Victoria, Australia
>>>>>>>>>>>=20
>>>>>>>>>>> Email: [log in to unmask]
>>>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>> ------------------------------------------
>>>>>>>>>=20
>>>>>>>>> Alex Fornito
>>>>>>>>> Research Fellow
>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>> University of Melbourne
>>>>>>>>> National Neuroscience Facility
>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>> 161 Barry St
>>>>>>>>> Carlton South 3053
>>>>>>>>> Victoria, Australia
>>>>>>>>>=20
>>>>>>>>> Email: [log in to unmask]
>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>=20
>>>>>>>=20
>>>>>>>=20
>>>>>>> ------------------------------------------
>>>>>>>=20
>>>>>>> Alex Fornito
>>>>>>> Research Fellow
>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>> University of Melbourne
>>>>>>> National Neuroscience Facility
>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>> 161 Barry St
>>>>>>> Carlton South 3053
>>>>>>> Victoria, Australia
>>>>>>>=20
>>>>>>> Email: [log in to unmask]
>>>>>>> Phone: +61 3 8344 1876
>>>>>>> Fax: +61 3 9348 0469
>>>>>>=20
>>>>>>=20
>>>>>=20
>>>>>=20
>>>>> ------------------------------------------
>>>>>=20
>>>>> Alex Fornito
>>>>> Research Fellow
>>>>> Melbourne Neuropsychiatry Centre
>>>>> University of Melbourne
>>>>> National Neuroscience Facility
>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>> 161 Barry St
>>>>> Carlton South 3053
>>>>> Victoria, Australia
>>>>>=20
>>>>> Email: [log in to unmask]
>>>>> Phone: +61 3 8344 1876
>>>>> Fax: +61 3 9348 0469
>>>>>=20
>>>>>=20
>>>>>=20
>>>>=20
>>>=20
>>=20
>>=20
>> ------------------------------------------
>>=20
>> Alex Fornito
>> Research Fellow
>> Melbourne Neuropsychiatry Centre
>> University of Melbourne
>> National Neuroscience Facility
>> Levels 1 & 2, Alan Gilbert Building
>> 161 Barry St
>> Carlton South 3053
>> Victoria, Australia
>>=20
>> Email: [log in to unmask]
>> Phone: +61 3 8344 1876
>> Fax: +61 3 9348 0469
>>=20
>>=20
>>=20
>>=20
>=20
------------------------------------------
Alex Fornito
Research Fellow
Melbourne Neuropsychiatry Centre
University of Melbourne
National Neuroscience Facility
Levels 1 & 2, Alan Gilbert Building
161 Barry St=A0
Carlton South 3053
Victoria, Australia
Email: [log in to unmask]
Phone: +61 3 8344 1876
Fax: +61 3 9348 0469 =A0
=========================================================================
Date: Fri, 6 May 2011 13:48:29 -0700
Reply-To: Siddharth Srivastava <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Siddharth Srivastava <[log in to unmask]>
Subject: Re: spm_affreg
Comments: To: John Ashburner <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=bcaec517a9c8b3440a04a2a19c38
Message-ID: <[log in to unmask]>
--bcaec517a9c8b3440a04a2a19c38
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Hi John, please ignore the first part of my previous mail: made some errors
in
cut and paste. It runs fine now. The question about the shears, however,
still lingers: do I have
to somehow use both Sx and Sy, or as your implementation suggests, only one
would suffice?
thanks again, and sorry for being such a bother...
sid.
On Fri, May 6, 2011 at 12:23 PM, Siddharth Srivastava <[log in to unmask]>wrote:
> Thanks John, for the answers. The code, however exits with "Problem". M0
> and M1 differ.
> Also, why is there just one shear component in the matrix? I have seen
> general shears modeled as [1,h;g,1]: is this superfluous, and just one "h"
> will be sufficient for 2d case?
>
> Thanks,
> Sid.
>
>
>
>
> On Fri, May 6, 2011 at 11:01 AM, John Ashburner <[log in to unmask]>wrote:
>
>> Your model uses 7 parameters, but there are only 6 elements in
>> A(1:2,1:3). Also, you need to be able to deal with a broader range of
>> angles, so atan2(s,c) is used to compute the angle. I've tested it
>> with the following code, so hopefully it works for all cases.
>>
>> for i=1:10000
>> P=randn(1,6)*10;
>> M0=spm_matrix2D(P);
>> P1=spm_imatrix2D(M0);
>> M1=spm_matrix2D(P1);
>> t=sum(sum((M1-M0).^2));
>> if t>1e-9, disp('Problem'); break; end
>> end
>>
>> Note that spm_imatrix2D(spm_matrix2D(P)) does not necessarily have to
>> equal P, but the matrices generated from the two parameter sets should
>> be the same.
>>
>> Best regards,
>> -John
>>
>> On 6 May 2011 17:11, Siddharth Srivastava <[log in to unmask]> wrote:
>> > Hi everyone,
>> > Can someone help me check the 2D versions of the spm_matrix and
>> > spm_imatrix? My
>> > implementation currently is as follows:
>> >
>> > ---2D spm_matrix ---
>> > function [A] = spm_matrix2D(P)
>> > % P = [Tx, Ty, R, Zx, Zy, Sx,Sy]
>> > p0 = [0,0,0,1,1,0,0];
>> > P = [P, p0((length(P)+1):7)]
>> >
>> > A = eye(3);
>> > % T -> R -> Zoom -> Shear
>> > A = A * [1,0,P(1); ...
>> > 0,1,P(2); ...
>> > 0,0, 1];
>> > A = A * [cos(P(3)), sin(P(3)), 0; ...
>> > -sin(P(3)), cos(P(3)), 0; ...
>> > 0, 0, 1];
>> > A = A * [P(4), 0, 0; ...
>> > 0, P(5), 0; ...
>> > 0, 0, 1];
>> > A = A * [1, P(6), 0; ...
>> > P(7) , 1, 0; ...
>> > 0, 0, 1];
>> > --------------------------------------------------
>> > -----2D spm_imatrix ------------------------
>> > function P = spm_imatrix2D(M);
>> >
>> >
>> >
>> > R = M(1:2,1:2);
>> > C = chol(R' * R);
>> > P = [M(1:2,3)',0,diag(C)',0,0];
>> > if(det(R) < 0) P(4) = -P(4); end
>> > C = diag(diag(C))\C;
>> > P(6:7) = C([2,3]);
>> >
>> > R0 = spm_matrix2D([0,0,0,P(4:end)]);
>> > R0 = R0(1:2,1:2);
>> > R1 = R/R0;
>> >
>> > th = asin(rang(R1(1,2)));
>> > P(3) = th;
>> >
>> > % There may be slight rounding errors making b>1 or b<-1.
>> > function a = rang(b)
>> > a = min(max(b, -1), 1);
>> > return;
>> >
>> ---------------------------------------------------------------------------
>> >
>> > I know there is something not correct, since when, for a parameter set
>> 'p',
>> > i do spm_imatrix2D(spm_matrix2D(p)), I do not recover P for all entries,
>> > specially
>> > rotation and shears. C(2) above always evaluates to zero. The result is
>> that
>> > these errors
>> > accumulate (or are not accounted for) on repeated application of this
>> > sequence of
>> > operations in the registration routine.
>> >
>> > Thanks in anticipation,
>> > Sid.
>> >
>> >
>> >
>> > On Fri, Apr 22, 2011 at 9:13 AM, Siddharth Srivastava <[log in to unmask]
>> >
>> > wrote:
>> >>
>> >> Hi John,
>> >> Thanks a lot for your answer, and it has been very helpful for my
>> >> understanding
>> >> of the details of the implementation, and my own development efforts. I
>> >> have
>> >> 2 very quick questions, though:
>> >>
>> >> 1) the parameter set x(:) that is returned from spm_mireg, and the
>> >> "params" that
>> >> spm_affsub3 returns (in spm99, which is also the version that I am
>> looking
>> >> at) ,
>> >> are they equivalent? In other words, If I am collating the parameters
>> from
>> >> the mireg
>> >> routine, would the distribution x(7:12) be used to estimate the icovar0
>> >> entries in affsub3?
>> >>
>> >> 2) also would VG.mat\spm_matrix(x)*VF.mat transform G to F similar to
>> >> VG.mat\spm_matrix(params)*VF.mat , or do I have to do
>> >> M = VG.mat\spm_matrix(x(:)')*VF.mat
>> >> pp = spm_imatrix(M)
>> >> and use pp(7:12) ?
>> >>
>> >>
>> >>
>> >> Thanks again.
>> >> Sid.
>> >>
>> >> On Thu, Apr 14, 2011 at 2:13 PM, John Ashburner <[log in to unmask]>
>> >> wrote:
>> >>>
>> >>> > I had a look at the code in spm_maff, and
>> >>> > it looks like it also uses the values of isig and mu in the call to
>> >>> > affreg(). My guess is
>> >>> > that during the initial registration on a large data set for
>> estimating
>> >>> > the
>> >>> > prior
>> >>> > distribution of parameters, this will be called with typ = 'none' .
>> Is
>> >>> > this
>> >>> > correct?
>> >>>
>> >>> Once the registration has locked in on a solution, the priors have
>> >>> less influence. Their main influence is in the early stages of the
>> >>> registration, or when there are relatively few slices in the data. I
>> >>> don't actually remember if the registration was regularised when I
>> >>> computed their values.
>> >>>
>> >>> >
>> >>> > Further, do we have to do a non-rigid registration for the
>> estimation
>> >>> > (since, in the comments the selected
>> >>> > files are filtered as *seg_inv_sn.mat"? Since only p.Affine is being
>> >>> > used,
>> >>> > can this work with only
>> >>> > an affine / rigid transformation?
>> >>>
>> >>> Only the affine transform in the files is used, so basically yes. You
>> >>> could just do affine registration.
>> >>>
>> >>> >
>> >>> > I would also be happy if you could also answer my other question
>> about
>> >>> > examining the
>> >>> > effects of the values in isig and mu (what are the units of mu?) on
>> the
>> >>> > transformed image.
>> >>>
>> >>> They are unit-less, and are just a measure of the zooms and shears.
>> >>>
>> >>> > For example,
>> >>> > if i set a mu of [mu1, mu2, ...] and a isig of [sig1, 0, 0...; 0,
>> sig2,
>> >>> > 0,
>> >>> > 0..; ...] (with only diagonal components),
>> >>> > based on the Hencky tensor penalty, it seems that large deviations
>> of
>> >>> > parameter 1 estimate (T - mu) from
>> >>> > mu1 will be penalized. How is the value of isig1 modifying the
>> penalty?
>> >>>
>> >>> Its assuming that the elements of the matrix log of the part that does
>> >>> shears and zooms has a multivariate normal distribution, so the
>> >>> penalty is a kind of negative log likelhood. The isig is essentially
>> >>> a precision matrix, which is the inverse of a covariance matrix.
>> >>>
>> >>> p(x|mu,S) = 1/sqrt(det(2*pi*S)) * exp(-0.5*(x-mu)'*inv(S)*(x-mu))
>> >>>
>> >>> Taking logs and negating, you get 0.5*(x-mu)'*inv(S)*(x-mu) + const
>> >>>
>> >>> > How
>> >>> > do the off diagonal terms affect
>> >>> > the penalty?
>> >>>
>> >>> The inverse of isig would just encode the covariance between the
>> >>> various shears and zooms.
>> >>>
>> >>> >
>> >>> > Could you also point me to a reference where I can learn more about
>> >>> > Hencky
>> >>> > strain tensor (specifically
>> >>> > what information it carries in the context of image processing etc.)
>> >>>
>> >>> I don't know if this is of any use:
>> >>>
>> >>> http://en.wikipedia.org/wiki/Deformation_(mechanics)
>> >>>
>> >>> Best regards,
>> >>> -John
>> >>>
>> >>>
>> >>> > On Thu, Apr 14, 2011 at 10:17 AM, John Ashburner <
>> [log in to unmask]>
>> >>> > wrote:
>> >>> >>
>> >>> >> They were computed by affine registering loads of (227) images to
>> MNI
>> >>> >> space. This gave the affine transforms, which were then used to
>> build
>> >>> >> up a mean and inverse covariance matrix. In the comments of
>> >>> >> spm_maff.m, you should see the following...
>> >>> >>
>> >>> >> %% Values can be derived by...
>> >>> >> %sn = spm_select(Inf,'.*seg_inv_sn.mat$');
>> >>> >> %X = zeros(size(sn,1),12);
>> >>> >> %for i=1:size(sn,1),
>> >>> >> % p = load(deblank(sn(i,:)));
>> >>> >> % M = p.VF(1).mat*p.Affine/p.VG(1).mat;
>> >>> >> % J = M(1:3,1:3);
>> >>> >> % V = sqrtm(J*J');
>> >>> >> % R = V\J;
>> >>> >> % lV = logm(V);
>> >>> >> % lR = -logm(R);
>> >>> >> % P = zeros(12,1);
>> >>> >> % P(1:3) = M(1:3,4);
>> >>> >> % P(4:6) = lR([2 3 6]);
>> >>> >> % P(7:12) = lV([1 2 3 5 6 9]);
>> >>> >> % X(i,:) = P';
>> >>> >> %end;
>> >>> >> %mu = mean(X(:,7:12));
>> >>> >> %XR = X(:,7:12) - repmat(mu,[size(X,1),1]);
>> >>> >> %isig = inv(XR'*XR/(size(X,1)-1))
>> >>> >>
>> >>> >> You may be able to re-code this to work with your 2D transforms.
>> Note
>> >>> >> that I only use the components that describe shears and zooms.
>> Also,
>> >>> >> if I was re-coding it all again, I would probably do things
>> slightly
>> >>> >> differently, using the following decomposition:
>> >>> >>
>> >>> >> J=M(1:3,1:3);
>> >>> >> L=real(logm(J));
>> >>> >> S=(L+L')/2; % Symmetric part (for zooms and shears, which should be
>> >>> >> penalised)
>> >>> >> A=(L-L')/2; % Anti-symmetric part (for rotations)
>> >>> >>
>> >>> >> I might even base the penalty on lambda(2)*trace(S)^2 +
>> >>> >> lambda(1)*trace(S*S'), which is often used as a measure of "elastic
>> >>> >> energy" for penalising non-linear registration. Of course, there
>> >>> >> would also be a bit of annoying extra stuff to deal with due to MNI
>> >>> >> space being a bit bigger than average brains are. Figuring out the
>> >>> >> mean would require (I think) an iterative process similar to the
>> one
>> >>> >> described in "Characterizing volume and surface deformations in an
>> >>> >> atlas framework: theory, applications, and implementation", by
>> Woods
>> >>> >> in NeuroImage (2003).
>> >>> >>
>> >>> >> Best regards,
>> >>> >> -John
>> >>> >>
>> >>> >> On 14 April 2011 17:15, Siddharth Srivastava <[log in to unmask]>
>> wrote:
>> >>> >> > Hi all,
>> >>> >> > My question pertains specifically to the values of isig and
>> mu
>> >>> >> > that
>> >>> >> > are
>> >>> >> > incorporated
>> >>> >> > in the code, and I wish to disentangle the effect that these
>> numbers
>> >>> >> > have on
>> >>> >> > individual parameters
>> >>> >> > during the optimization stage. I am trying to map it to a 2D
>> case,
>> >>> >> > and
>> >>> >> > these
>> >>> >> > numbers
>> >>> >> > will have to be calculated ab-initio for my case. Before I begin
>> >>> >> > with
>> >>> >> > estimating the prior distribution
>> >>> >> > for these parameters, I need to check the effect that they have
>> on
>> >>> >> > the
>> >>> >> > registered images. Regarding this
>> >>> >> > 1) Can someone suggest a way I can examine the effect on each
>> >>> >> > parameter
>> >>> >> > separately, if it is
>> >>> >> > at all possible.
>> >>> >> > 2) Some advise on how to estimate these parameters, if it has
>> been
>> >>> >> > done
>> >>> >> > for
>> >>> >> > images other
>> >>> >> > than brain images, will be really helpful for me.
>> >>> >> >
>> >>> >> > Thanks,
>> >>> >> > Sid.
>> >>> >> >
>> >>> >> > On Mon, Mar 28, 2011 at 7:04 PM, Siddharth Srivastava
>> >>> >> > <[log in to unmask]>
>> >>> >> > wrote:
>> >>> >> >>
>> >>> >> >> Dear John,
>> >>> >> >> Thanks for your answer. I was able to correctly run my
>> 2D
>> >>> >> >> implementation
>> >>> >> >> based on your advise. However, I am am not very confident of my
>> >>> >> >> results
>> >>> >> >> and wanted to
>> >>> >> >> consult you on certain aspects of my mapping from 3D to 2D.
>> >>> >> >> 1) In function reg(..), the comment says that the
>> >>> >> >> derivatives
>> >>> >> >> w.r.t rotations and
>> >>> >> >> translations is zero. Consequently, I ran the indices from 4:7.
>> >>> >> >> According
>> >>> >> >> to your previous
>> >>> >> >> reply, rotations will be lumped together with scaling and affine
>> in
>> >>> >> >> 4
>> >>> >> >> parameters, and
>> >>> >> >> translations, independently, in the last two. I understand that
>> in
>> >>> >> >> this
>> >>> >> >> case, the indices
>> >>> >> >> run over parameters that have been separated into individual
>> >>> >> >> components
>> >>> >> >> (similar to
>> >>> >> >> the form accepted by spm_matrix). Is this correct for the
>> function
>> >>> >> >> reg(..)? In fact, I went back to the
>> >>> >> >> old spm code (spm99), and found parameters pdesc and free, and
>> got
>> >>> >> >> more
>> >>> >> >> confused as to when I should
>> >>> >> >> use the 6 parameter, and when to use separate parameters (as if
>> I
>> >>> >> >> was
>> >>> >> >> passing them to spm_matrix).
>> >>> >> >> So, when the loop runs over p1 and perturbs p1(i) by ds, does it
>> >>> >> >> run
>> >>> >> >> over
>> >>> >> >> translations/rotations etc
>> >>> >> >> or does it run over the martix elements that define these
>> >>> >> >> transformations
>> >>> >> >> (2x2 + 1x2)?
>> >>> >> >>
>> >>> >> >> 2) In function penalty(..), I have used unique
>> elements
>> >>> >> >> as
>> >>> >> >> [1,3,4], and my code looks like
>> >>> >> >> T = my_matrix(p)*M;
>> >>> >> >> T = T(1:2,1:2);
>> >>> >> >> T = 0.5*logm(T'*T);
>> >>> >> >> T
>> >>> >> >> T = T(els)' - mu;
>> >>> >> >> h = T'*isig*T
>> >>> >> >>
>> >>> >> >> Assuming an application specific isig, is this correct?
>> >>> >> >> 3) I have not yet incorporated the prior information in
>> my
>> >>> >> >> code,
>> >>> >> >> But for testing purposes,
>> >>> >> >> can you suggest some neutral values for mu and isig that I can
>> try
>> >>> >> >> to
>> >>> >> >> concentrate on the
>> >>> >> >> accuracy of the implementation minus the priors for now?
>> >>> >> >> 4) My solution curently seems to oscillate around an
>> >>> >> >> optimum.
>> >>> >> >> I
>> >>> >> >> am hoping that after
>> >>> >> >> I have removed any errors after your replies, it will converge
>> >>> >> >> gracefully.
>> >>> >> >>
>> >>> >> >> Thanks again for all the help.
>> >>> >> >> Siddharth.
>> >>> >> >>
>> >>> >> >>
>> >>> >> >> On Fri, Mar 18, 2011 at 2:05 AM, John Ashburner
>> >>> >> >> <[log in to unmask]>
>> >>> >> >> wrote:
>> >>> >> >>>
>> >>> >> >>> A 2D affine transform would use 6 parameters, rather than 7: a
>> 2x2
>> >>> >> >>> matrix to encode rotations, zooms and shears, and a 2x1 vector
>> for
>> >>> >> >>> translations.
>> >>> >> >>>
>> >>> >> >>> Best regards,
>> >>> >> >>> -John
>> >>> >> >>>
>> >>> >> >>> On 18 March 2011 05:05, Siddharth Srivastava <[log in to unmask]
>> >
>> >>> >> >>> wrote:
>> >>> >> >>> > Dear list users,
>> >>> >> >>> > I am currently trying to understand the
>> implementation
>> >>> >> >>> > in
>> >>> >> >>> > spm_affreg, and
>> >>> >> >>> > to make matters simple, I tried to work out a 2D version of
>> the
>> >>> >> >>> > registration
>> >>> >> >>> > procedure. I struck a roadblock, however...
>> >>> >> >>> >
>> >>> >> >>> > The function make_A creates part of the design matrix. For
>> the
>> >>> >> >>> > 3D
>> >>> >> >>> > case,
>> >>> >> >>> > the
>> >>> >> >>> > 13 parameters
>> >>> >> >>> > are encoded in columns of A1, which then is used to generate
>> AA
>> >>> >> >>> > +
>> >>> >> >>> > A1'
>> >>> >> >>> > A1. AA
>> >>> >> >>> > is 13x13, and everything
>> >>> >> >>> > works. For the 2D case, however, there will be 7+1
>> parameters( 2
>> >>> >> >>> > translations, 1 rotation, 2 zoom, 2 shears and 1 intensity
>> >>> >> >>> > scaling).
>> >>> >> >>> > The A1 matrix for 2D, then, will be (in make_A)
>> >>> >> >>> > A = [x1.*dG1 x1.*dG2 ...
>> >>> >> >>> > x2.*dG1 x2.*dG2 ...
>> >>> >> >>> > dG1 dG2 t];
>> >>> >> >>> >
>> >>> >> >>> > which is (number of sampled points) x 7. The AA matrix (in
>> >>> >> >>> > function
>> >>> >> >>> > costfun)
>> >>> >> >>> > is 8x8
>> >>> >> >>> > so, which is the parameter I am missing in modeling a 2D
>> >>> >> >>> > example? I
>> >>> >> >>> > hope I
>> >>> >> >>> > have got the number of parameters
>> >>> >> >>> > right for the 2D case? Is there an extra column that I have
>> to
>> >>> >> >>> > add
>> >>> >> >>> > to
>> >>> >> >>> > A1 to
>> >>> >> >>> > make the rest of the matrix computation
>> >>> >> >>> > consistent?
>> >>> >> >>> >
>> >>> >> >>> > Thanks for the help
>> >>> >> >>> >
>> >>> >> >>
>> >>> >> >
>> >>> >> >
>> >>> >
>> >>> >
>> >>
>> >
>> >
>>
>
>
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Hi John, please ignore the first part of my previous mail: made some errors=
in<br>cut and paste. It runs fine now. The question about the shears, howe=
ver, still lingers: do I have<br>to somehow use both Sx and Sy, or as your =
implementation suggests, only one<br>
would suffice?<br><br>thanks again, and sorry for being such a bother...<br=
>sid. <br><br><div class=3D"gmail_quote">On Fri, May 6, 2011 at 12:23 PM, S=
iddharth Srivastava <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]
m">[log in to unmask]</a>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; borde=
r-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">Thanks John, for =
the answers. The code, however exits with "Problem". M0<br>and M1=
differ. <br>
Also, why is there just one shear component in the matrix? I have seen <br>=
general shears modeled as [1,h;g,1]: is this superfluous, and just one &quo=
t;h"<br>
will be sufficient for 2d case? <br><br>Thanks,<br>Sid.<div><div></div><div=
class=3D"h5"><br><br><br><br><div class=3D"gmail_quote">On Fri, May 6, 201=
1 at 11:01 AM, John Ashburner <span dir=3D"ltr"><<a href=3D"mailto:jashb=
[log in to unmask]" target=3D"_blank">[log in to unmask]</a>></span> wrot=
e:<br>
<blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; borde=
r-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">Your model uses 7=
parameters, but there are only 6 elements in<br>
A(1:2,1:3). =A0Also, you need to be able to deal with a broader range of<br=
>
angles, so atan2(s,c) is used to compute the angle. =A0I've tested it<b=
r>
with the following code, so hopefully it works for all cases.<br>
<br>
for i=3D1:10000<br>
=A0P=3Drandn(1,6)*10;<br>
=A0M0=3Dspm_matrix2D(P);<br>
=A0P1=3Dspm_imatrix2D(M0);<br>
=A0M1=3Dspm_matrix2D(P1);<br>
=A0t=3Dsum(sum((M1-M0).^2));<br>
=A0if t>1e-9, disp('Problem'); break; end<br>
end<br>
<br>
Note that spm_imatrix2D(spm_matrix2D(P)) does not necessarily have to<br>
equal P, but the matrices generated from the two parameter sets should<br>
be the same.<br>
<br>
Best regards,<br>
<font color=3D"#888888">-John<br>
</font><div><div></div><div><br>
On 6 May 2011 17:11, Siddharth Srivastava <<a href=3D"mailto:siddys@gmai=
l.com" target=3D"_blank">[log in to unmask]</a>> wrote:<br>
> Hi everyone,<br>
> =A0=A0=A0=A0=A0 Can someone help me check the 2D versions of the spm_m=
atrix and<br>
> spm_imatrix? My<br>
> implementation currently is as follows:<br>
><br>
> ---2D spm_matrix ---<br>
> function [A] =3D spm_matrix2D(P)<br>
> % P =3D [Tx, Ty, R, Zx, Zy, Sx,Sy]<br>
> p0 =3D [0,0,0,1,1,0,0];<br>
> P =3D [P, p0((length(P)+1):7)]<br>
><br>
> A =3D eye(3);<br>
> % T -> R -> Zoom -> Shear<br>
> =A0A =3D=A0=A0=A0=A0 A * [1,0,P(1); ...<br>
> =A0=A0=A0=A0=A0=A0=A0=A0=A0 0,1,P(2); ...<br>
> =A0 =A0=A0=A0 =A0 0,0,=A0=A0 1];<br>
> =A0A =3D=A0=A0=A0=A0 A * [cos(P(3)), sin(P(3)), 0; ...<br>
> =A0=A0=A0=A0=A0=A0=A0=A0=A0 -sin(P(3)),=A0 cos(P(3)), 0; ...<br>
> =A0=A0=A0 =A0 0,=A0=A0=A0=A0=A0=A0=A0=A0=A0 0,=A0=A0=A0=A0=A0=A0=A0=A0=
1];<br>
> =A0A =3D=A0=A0=A0=A0 A * [P(4), 0, 0; ...<br>
> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 0,=A0=A0 P(5), 0; ...<br>
> =A0=A0=A0 =A0=A0=A0=A0=A0 0, 0, 1];<br>
> =A0A =3D=A0=A0=A0=A0 A * [1, P(6), 0; ...<br>
> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 P(7)=A0 , 1, 0; ...<br>
> =A0=A0=A0 =A0=A0=A0=A0=A0 0, 0, 1];<br>
> --------------------------------------------------<br>
> -----2D spm_imatrix ------------------------<br>
> function P =3D=A0 spm_imatrix2D(M);<br>
><br>
><br>
><br>
> R =3D M(1:2,1:2);<br>
> C =3D chol(R' * R);<br>
> P =3D [M(1:2,3)',0,diag(C)',0,0];<br>
> if(det(R) < 0) P(4) =3D -P(4); end<br>
> C =3D diag(diag(C))\C;<br>
> P(6:7) =3D C([2,3]);<br>
><br>
> R0 =3D spm_matrix2D([0,0,0,P(4:end)]);<br>
> R0 =3D R0(1:2,1:2);<br>
> R1 =3D R/R0;<br>
><br>
> th =3D asin(rang(R1(1,2)));<br>
> P(3) =3D th;<br>
><br>
> % There may be slight rounding errors making b>1 or b<-1.<br>
> function=A0 a =3D rang(b)<br>
> a =3D min(max(b, -1), 1);<br>
> return;<br>
> ----------------------------------------------------------------------=
-----<br>
><br>
> I know there is something not correct, since when, for a parameter set=
'p',<br>
> i do spm_imatrix2D(spm_matrix2D(p)), I do not recover P for all entrie=
s,<br>
> specially<br>
> rotation and shears. C(2) above always evaluates to zero. The result i=
s that<br>
> these errors<br>
> accumulate (or are not accounted for) on repeated application of this<=
br>
> sequence of<br>
> operations in the registration routine.<br>
><br>
> Thanks in anticipation,<br>
> Sid.<br>
><br>
><br>
><br>
> On Fri, Apr 22, 2011 at 9:13 AM, Siddharth Srivastava <<a href=3D"m=
ailto:[log in to unmask]" target=3D"_blank">[log in to unmask]</a>><br>
> wrote:<br>
>><br>
>> Hi John,<br>
>> =A0=A0=A0=A0=A0 Thanks a lot for your answer, and it has been very=
helpful for my<br>
>> understanding<br>
>> of the details of the implementation, and my own development effor=
ts. I<br>
>> have<br>
>> 2 very quick questions, though:<br>
>><br>
>> 1) the parameter set x(:) that is returned from spm_mireg, and the=
<br>
>> "params" that<br>
>> spm_affsub3 returns (in spm99, which is also the version that I am=
looking<br>
>> at) ,<br>
>> are they equivalent? In other words, If I am collating the paramet=
ers from<br>
>> the mireg<br>
>> routine, would the distribution x(7:12) be used to estimate the ic=
ovar0<br>
>> entries in affsub3?<br>
>><br>
>> 2) also would VG.mat\spm_matrix(x)*VF.mat transform G to F similar=
to<br>
>> =A0=A0=A0=A0 VG.mat\spm_matrix(params)*VF.mat , or do I have to do=
<br>
>> =A0=A0=A0=A0=A0 M =3D VG.mat\spm_matrix(x(:)')*VF.mat<br>
>> =A0=A0=A0=A0=A0 pp =3D spm_imatrix(M)<br>
>> =A0=A0=A0=A0=A0 and use pp(7:12) ?<br>
>><br>
>><br>
>><br>
>> Thanks again.<br>
>> Sid.<br>
>><br>
>> On Thu, Apr 14, 2011 at 2:13 PM, John Ashburner <<a href=3D"mai=
lto:[log in to unmask]" target=3D"_blank">[log in to unmask]</a>><br=
>
>> wrote:<br>
>>><br>
>>> > I had a look at the code in spm_maff, and<br>
>>> > it looks like it also uses the values of isig and mu in t=
he call to<br>
>>> > affreg(). My guess is<br>
>>> > that during the initial registration on a large data set =
for estimating<br>
>>> > the<br>
>>> > prior<br>
>>> > distribution of parameters, this will be called with typ =
=3D 'none' . Is<br>
>>> > this<br>
>>> > correct?<br>
>>><br>
>>> Once the registration has locked in on a solution, the priors =
have<br>
>>> less influence. =A0Their main influence is in the early stages=
of the<br>
>>> registration, or when there are relatively few slices in the d=
ata. =A0I<br>
>>> don't actually remember if the registration was regularise=
d when I<br>
>>> computed their values.<br>
>>><br>
>>> ><br>
>>> > Further, do we have to do a non-rigid registration for th=
e estimation<br>
>>> > (since, in the comments the selected<br>
>>> > files are filtered as *seg_inv_sn.mat"? Since only p=
.Affine is being<br>
>>> > used,<br>
>>> > can this work with only<br>
>>> > an affine / rigid transformation?<br>
>>><br>
>>> Only the affine transform in the files is used, so basically y=
es. =A0You<br>
>>> could just do affine registration.<br>
>>><br>
>>> ><br>
>>> > I would also be happy if you could also answer my other q=
uestion about<br>
>>> > examining the<br>
>>> > effects of the values in isig and mu (what are the units =
of mu?) on the<br>
>>> > transformed image.<br>
>>><br>
>>> They are unit-less, and are just a measure of the zooms and sh=
ears.<br>
>>><br>
>>> > For example,<br>
>>> > if i set a mu of [mu1, mu2, ...] and a isig of [sig1, 0, =
0...; 0, sig2,<br>
>>> > 0,<br>
>>> > 0..; ...] (with only diagonal components),<br>
>>> > based on the Hencky tensor penalty, it seems that large d=
eviations of<br>
>>> > parameter 1=A0 estimate (T - mu) from<br>
>>> > mu1 will be penalized. How is the value of isig1 modifyin=
g the penalty?<br>
>>><br>
>>> Its assuming that the elements of the matrix log of the part t=
hat does<br>
>>> shears and zooms has a multivariate normal distribution, so th=
e<br>
>>> penalty is a kind of negative log likelhood. =A0The isig is es=
sentially<br>
>>> a precision matrix, which is the inverse of a covariance matri=
x.<br>
>>><br>
>>> p(x|mu,S) =3D 1/sqrt(det(2*pi*S)) * exp(-0.5*(x-mu)'*inv(S=
)*(x-mu))<br>
>>><br>
>>> Taking logs and negating, you get 0.5*(x-mu)'*inv(S)*(x-mu=
) + const<br>
>>><br>
>>> > How<br>
>>> > do the off diagonal terms affect<br>
>>> > the penalty?<br>
>>><br>
>>> The inverse of isig would just encode the covariance between t=
he<br>
>>> various shears and zooms.<br>
>>><br>
>>> ><br>
>>> > Could you also point me to a reference where I can learn =
more about<br>
>>> > Hencky<br>
>>> > strain tensor (specifically<br>
>>> > what information it carries in the context of image proce=
ssing etc.)<br>
>>><br>
>>> I don't know if this is of any use:<br>
>>><br>
>>> <a href=3D"http://en.wikipedia.org/wiki/Deformation_%28mechani=
cs%29" target=3D"_blank">http://en.wikipedia.org/wiki/Deformation_(mechanic=
s)</a><br>
>>><br>
>>> Best regards,<br>
>>> -John<br>
>>><br>
>>><br>
>>> > On Thu, Apr 14, 2011 at 10:17 AM, John Ashburner <<a h=
ref=3D"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]<=
/a>><br>
>>> > wrote:<br>
>>> >><br>
>>> >> They were computed by affine registering loads of (22=
7) images to MNI<br>
>>> >> space. =A0This gave the affine transforms, which were=
then used to build<br>
>>> >> up a mean and inverse covariance matrix. =A0In the co=
mments of<br>
>>> >> spm_maff.m, you should see the following...<br>
>>> >><br>
>>> >> %% Values can be derived by...<br>
>>> >> %sn =3D spm_select(Inf,'.*seg_inv_sn.mat$');<=
br>
>>> >> %X =A0=3D zeros(size(sn,1),12);<br>
>>> >> %for i=3D1:size(sn,1),<br>
>>> >> % =A0 =A0p =A0=3D load(deblank(sn(i,:)));<br>
>>> >> % =A0 =A0M =A0=3D p.VF(1).mat*p.Affine/p.VG(1).mat;<b=
r>
>>> >> % =A0 =A0J =A0=3D M(1:3,1:3);<br>
>>> >> % =A0 =A0V =A0=3D sqrtm(J*J');<br>
>>> >> % =A0 =A0R =A0=3D V\J;<br>
>>> >> % =A0 =A0lV =A0 =A0 =A0=3D =A0logm(V);<br>
>>> >> % =A0 =A0lR =A0 =A0 =A0=3D -logm(R);<br>
>>> >> % =A0 =A0P =A0 =A0 =A0 =3D zeros(12,1);<br>
>>> >> % =A0 =A0P(1:3) =A0=3D M(1:3,4);<br>
>>> >> % =A0 =A0P(4:6) =A0=3D lR([2 3 6]);<br>
>>> >> % =A0 =A0P(7:12) =3D lV([1 2 3 5 6 9]);<br>
>>> >> % =A0 =A0X(i,:) =A0=3D P';<br>
>>> >> %end;<br>
>>> >> %mu =A0 =3D mean(X(:,7:12));<br>
>>> >> %XR =A0 =3D X(:,7:12) - repmat(mu,[size(X,1),1]);<br>
>>> >> %isig =3D inv(XR'*XR/(size(X,1)-1))<br>
>>> >><br>
>>> >> You may be able to re-code this to work with your 2D =
transforms. =A0Note<br>
>>> >> that I only use the components that describe shears a=
nd zooms. =A0Also,<br>
>>> >> if I was re-coding it all again, I would probably do =
things slightly<br>
>>> >> differently, using the following decomposition:<br>
>>> >><br>
>>> >> J=3DM(1:3,1:3);<br>
>>> >> L=3Dreal(logm(J));<br>
>>> >> S=3D(L+L')/2; % Symmetric part (for zooms and she=
ars, which should be<br>
>>> >> penalised)<br>
>>> >> A=3D(L-L')/2; % Anti-symmetric part (for rotation=
s)<br>
>>> >><br>
>>> >> I might even base the penalty on lambda(2)*trace(S)^2=
+<br>
>>> >> lambda(1)*trace(S*S'), which is often used as a m=
easure of "elastic<br>
>>> >> energy" for penalising non-linear registration. =
=A0Of course, there<br>
>>> >> would also be a bit of annoying extra stuff to deal w=
ith due to MNI<br>
>>> >> space being a bit bigger than average brains are. =A0=
Figuring out the<br>
>>> >> mean would require (I think) an iterative process sim=
ilar to the one<br>
>>> >> described in "Characterizing volume and surface =
deformations in an<br>
>>> >> atlas framework: theory, applications, and implementa=
tion", by Woods<br>
>>> >> in NeuroImage (2003).<br>
>>> >><br>
>>> >> Best regards,<br>
>>> >> -John<br>
>>> >><br>
>>> >> On 14 April 2011 17:15, Siddharth Srivastava <<a h=
ref=3D"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]</a>> =
wrote:<br>
>>> >> > Hi all,<br>
>>> >> > =A0=A0=A0=A0 My question pertains specifically t=
o the values of isig and mu<br>
>>> >> > that<br>
>>> >> > are<br>
>>> >> > incorporated<br>
>>> >> > in the code, and I wish to disentangle the effec=
t that these numbers<br>
>>> >> > have on<br>
>>> >> > individual parameters<br>
>>> >> > during the optimization stage. I am trying to ma=
p it to a 2D case,<br>
>>> >> > and<br>
>>> >> > these<br>
>>> >> > numbers<br>
>>> >> > will have to be calculated ab-initio for my case=
. Before I begin<br>
>>> >> > with<br>
>>> >> > estimating the prior distribution<br>
>>> >> > for these parameters, I need to check the effect=
that they have on<br>
>>> >> > the<br>
>>> >> > registered images. Regarding this<br>
>>> >> > 1) Can someone suggest a way I can examine the e=
ffect on each<br>
>>> >> > parameter<br>
>>> >> > separately, if it is<br>
>>> >> > =A0=A0=A0=A0 at all possible.<br>
>>> >> > 2) Some advise on how to estimate these paramete=
rs, if it has been<br>
>>> >> > done<br>
>>> >> > for<br>
>>> >> > images other<br>
>>> >> > =A0=A0=A0=A0 than brain images, will be really h=
elpful for me.<br>
>>> >> ><br>
>>> >> > Thanks,<br>
>>> >> > Sid.<br>
>>> >> ><br>
>>> >> > On Mon, Mar 28, 2011 at 7:04 PM, Siddharth Sriva=
stava<br>
>>> >> > <<a href=3D"mailto:[log in to unmask]" target=
=3D"_blank">[log in to unmask]</a>><br>
>>> >> > wrote:<br>
>>> >> >><br>
>>> >> >> Dear John,<br>
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 Thanks for your =
answer. I was able to correctly run my 2D<br>
>>> >> >> implementation<br>
>>> >> >> based on your advise. However, I am am not v=
ery confident of my<br>
>>> >> >> results<br>
>>> >> >> and wanted to<br>
>>> >> >> consult you on certain aspects of my mapping=
from 3D to 2D.<br>
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 1) In functio=
n reg(..), the comment says that the<br>
>>> >> >> derivatives<br>
>>> >> >> w.r.t rotations and<br>
>>> >> >> translations is zero. Consequently, I ran th=
e indices from 4:7.<br>
>>> >> >> According<br>
>>> >> >> to your previous<br>
>>> >> >> reply, rotations will be lumped together wit=
h scaling and affine in<br>
>>> >> >> 4<br>
>>> >> >> parameters, and<br>
>>> >> >> translations, independently, in the last two=
. I understand that in<br>
>>> >> >> this<br>
>>> >> >> case, the indices<br>
>>> >> >> run over parameters that have been separated=
into individual<br>
>>> >> >> components<br>
>>> >> >> (similar to<br>
>>> >> >> the form accepted by spm_matrix). Is this co=
rrect for the function<br>
>>> >> >> reg(..)?=A0 In fact, I went back to the<br>
>>> >> >> old spm code (spm99), and found parameters p=
desc and free, and got<br>
>>> >> >> more<br>
>>> >> >> confused as to when I should<br>
>>> >> >> use the 6 parameter, and when to use separat=
e parameters (as if I<br>
>>> >> >> was<br>
>>> >> >> passing them to spm_matrix).<br>
>>> >> >> So, when the loop runs over p1 and perturbs =
p1(i) by ds, does it<br>
>>> >> >> run<br>
>>> >> >> over<br>
>>> >> >> translations/rotations etc<br>
>>> >> >> or does it run over the martix elements that=
define these<br>
>>> >> >> transformations<br>
>>> >> >> (2x2 + 1x2)?<br>
>>> >> >><br>
>>> >> >> =A0 =A0 =A0 =A0 =A0=A0 2) In function penalt=
y(..), I have used unique elements<br>
>>> >> >> as<br>
>>> >> >> [1,3,4], and my code looks like<br>
>>> >> >> T =3D my_matrix(p)*M;<br>
>>> >> >> T =3D T(1:2,1:2);<br>
>>> >> >> T =3D 0.5*logm(T'*T);<br>
>>> >> >> T<br>
>>> >> >> T =3D T(els)' - mu;<br>
>>> >> >> h =3D T'*isig*T<br>
>>> >> >><br>
>>> >> >> Assuming an application specific isig, is th=
is correct?<br>
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0 3) I have not yet i=
ncorporated the prior information in my<br>
>>> >> >> code,<br>
>>> >> >> But for testing purposes,<br>
>>> >> >> can you suggest some neutral values=A0 for m=
u and isig that I can try<br>
>>> >> >> to<br>
>>> >> >> concentrate on the<br>
>>> >> >> accuracy of the implementation minus the pri=
ors for now?<br>
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 4) My solution c=
urently seems to oscillate around an<br>
>>> >> >> optimum.<br>
>>> >> >> I<br>
>>> >> >> am hoping that after<br>
>>> >> >> I have removed any errors after your replies=
, it will converge<br>
>>> >> >> gracefully.<br>
>>> >> >><br>
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 Thanks again for=
all the help.<br>
>>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 Siddharth.<br=
>
>>> >> >><br>
>>> >> >><br>
>>> >> >> On Fri, Mar 18, 2011 at 2:05 AM, John Ashbur=
ner<br>
>>> >> >> <<a href=3D"mailto:[log in to unmask]" =
target=3D"_blank">[log in to unmask]</a>><br>
>>> >> >> wrote:<br>
>>> >> >>><br>
>>> >> >>> A 2D affine transform would use 6 parame=
ters, rather than 7: a 2x2<br>
>>> >> >>> matrix to encode rotations, zooms and sh=
ears, and a 2x1 vector for<br>
>>> >> >>> translations.<br>
>>> >> >>><br>
>>> >> >>> Best regards,<br>
>>> >> >>> -John<br>
>>> >> >>><br>
>>> >> >>> On 18 March 2011 05:05, Siddharth Srivas=
tava <<a href=3D"mailto:[log in to unmask]" target=3D"_blank">siddys@gmail=
.com</a>><br>
>>> >> >>> wrote:<br>
>>> >> >>> > Dear list users,<br>
>>> >> >>> > =A0=A0=A0=A0=A0=A0=A0=A0=A0 I am cu=
rrently trying to understand the implementation<br>
>>> >> >>> > in<br>
>>> >> >>> > spm_affreg, and<br>
>>> >> >>> > to make matters simple, I tried to =
work out a 2D version of the<br>
>>> >> >>> > registration<br>
>>> >> >>> > procedure. I struck a roadblock, ho=
wever...<br>
>>> >> >>> ><br>
>>> >> >>> > The function make_A creates part of=
the design matrix. For the<br>
>>> >> >>> > 3D<br>
>>> >> >>> > case,<br>
>>> >> >>> > the<br>
>>> >> >>> > 13 parameters<br>
>>> >> >>> > are encoded in columns of A1, which=
then is used to generate AA<br>
>>> >> >>> > +<br>
>>> >> >>> > A1'<br>
>>> >> >>> > A1. AA<br>
>>> >> >>> > is 13x13, and everything<br>
>>> >> >>> > works. For the 2D case, however, th=
ere will be 7+1 parameters( 2<br>
>>> >> >>> > translations, 1 rotation, 2 zoom, 2=
shears and 1 intensity<br>
>>> >> >>> > scaling).<br>
>>> >> >>> > The A1 matrix for 2D, then,=A0 will=
be (in make_A)<br>
>>> >> >>> > A=A0 =3D [x1.*dG1 x1.*dG2 ...<br>
>>> >> >>> > =A0=A0=A0=A0=A0 x2.*dG1 x2.*dG2 ...=
<br>
>>> >> >>> > =A0=A0=A0 =A0 dG1=A0=A0=A0=A0 dG2=
=A0 t];<br>
>>> >> >>> ><br>
>>> >> >>> > which is (number of sampled points)=
x 7. The AA matrix (in<br>
>>> >> >>> > function<br>
>>> >> >>> > costfun)<br>
>>> >> >>> > is 8x8<br>
>>> >> >>> > so, which is the parameter I am mis=
sing in modeling a 2D<br>
>>> >> >>> > example? I<br>
>>> >> >>> > hope I<br>
>>> >> >>> > have got the number of parameters<b=
r>
>>> >> >>> > right for the 2D case? Is there an =
extra column that I have to<br>
>>> >> >>> > add<br>
>>> >> >>> > to<br>
>>> >> >>> > A1 to<br>
>>> >> >>> > make the rest of the matrix computa=
tion<br>
>>> >> >>> > consistent?<br>
>>> >> >>> ><br>
>>> >> >>> > Thanks for the help<br>
>>> >> >>> ><br>
>>> >> >><br>
>>> >> ><br>
>>> >> ><br>
>>> ><br>
>>> ><br>
>><br>
><br>
><br>
</div></div></blockquote></div><br>
</div></div></blockquote></div><br>
--bcaec517a9c8b3440a04a2a19c38--
=========================================================================
Date: Sat, 7 May 2011 07:14:27 +1000
Reply-To: Alex Fornito <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Alex Fornito <[log in to unmask]>
Subject: Re: PPI question
Comments: To: "MCLAREN, Donald" <[log in to unmask]>
Comments: cc: Darren Gitelman <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset="ISO-8859-1"
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Actually, sorry one more question:
If Y in spm_peb_ppi is already frequency filtered by spm_regions, then the
only difference (barring any additional confounds specified with xX.iG)
between Y and Yc is the additional removal of block effects.
Since the ppi interaction term is generated from Y and not Yc, I am
presuming then that is solely because it is not desirable to deconvolve a
time course with block effects removed. Is this correct?
On 07/05/2011 04:07, "MCLAREN, Donald" <[log in to unmask]> wrote:
> The null-space of the contrast are any columns of the contrast (which
> must be an F-contrast) that are 0. Thus, you remove the effects of
> motion when you do the adjustment and don't need to worry about them
> being included in the deconvolved data. The code that I have supplied
> has N rows for N conditions of interest after I talked to Darren about
> the ideal contrast to use for adjustment.
>=20
> As for removing the frequencies, I think it is probably fine to remove
> them, I was just under the impression that they weren't being removed
> because of me commenting out that line during testing of spm_regions.
> I would go with the SPM defaults until their effect is tested. If you
> don't set a high-pass filter, then you won't remove the frequencies,
> so you could test it that way as well.
>=20
> Best Regards, Donald McLaren
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> D.G. McLaren, Ph.D.
> Postdoctoral Research Fellow, GRECC, Bedford VA
> Research Fellow, Department of Neurology, Massachusetts General
> Hospital and Harvard Medical School
> Office: (773) 406-2464
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> This e-mail contains CONFIDENTIAL INFORMATION which may contain
> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
> and which is intended only for the use of the individual or entity
> named above. If the reader of the e-mail is not the intended recipient
> or the employee or agent responsible for delivering it to the intended
> recipient, you are hereby notified that you are in possession of
> confidential and privileged information. Any unauthorized use,
> disclosure, copying or the taking of any action in reliance on the
> contents of this information is strictly prohibited and may be
> unlawful. If you have received this e-mail unintentionally, please
> immediately notify the sender via telephone at (773) 406-2464 or
> email.
>=20
>=20
>=20
> On Thu, May 5, 2011 at 9:46 PM, Alex Fornito <[log in to unmask]> wr=
ote:
>> Hi Donald, Torben and Darren,
>> Thanks for your responses.
>>=20
>> Form each of your responses, it seems like best practice would be to rem=
ove
>> motion (and/or other confounds) from the VOI time series prior to
>> deconvolution.
>>=20
>> It also seems like you are recommending NOT to frequency filter the VOI =
time
>> series.
>>=20
>> In my reading though, spm_regions does this by default with the call to
>> spm_filter (line 135). So, if spm_regions is used to extract a VOI time
>> series, the time series that is input to spm_peb_ppi will already freque=
ncy
>> filtered. So it seems like, in standard practice, the deconvolution is
>> applied to frequency-filtered data. In this case, if xX.iG is empty, the
>> only difference between Y and Yc in spm_peb_ppi is the additional remova=
l of
>> block effects (xX.iB).
>>=20
>> Based on the current chain of emails, it seems you are recommending that=
a
>> confound-corrected, whitened, but non-frequency filtered time course sho=
uld
>> be input to spm_peb_ppi. IS that correct, or am I missing something?
>>=20
>> Finally, can I clarify exactly what the null space of the contrast is? M=
ost
>> of the time in my analyses I don't get the option to adjust for it, so x=
Y.Ic
>> is empty.
>>=20
>> Thanks again for all your help,
>> A
>>=20
>>=20
>>=20
>> On 06/05/2011 02:18, "MCLAREN, Donald" <[log in to unmask]> wrote:
>>=20
>>> I haven't thoroughly tested this, but if you set iG to be the movement
>>> parameters columns. Then still adjust for the null space (motion
>>> parameters). You will get the best of both. If you don't adjust for
>>> the null space, then movement will contribute to the deconvolution. In
>>> summary, if you have iG be the motion parameter columns AND adjust for
>>> the null-space (motion columns), then:
>>>=20
>>> Y will have the effect of motion removed. Yc (removal of motion twice)
>>> will be minimally different since Y is orthogonal to the motion
>>> parameters. So, you have motion removed from both the autocorrelation
>>> estimate, the Y for deconvolution, and Yc.
>>>=20
>>> Best Regards, Donald McLaren
>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>> D.G. McLaren, Ph.D.
>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>> Research Fellow, Department of Neurology, Massachusetts General
>>> Hospital and Harvard Medical School
>>> Office: (773) 406-2464
>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>>> and which is intended only for the use of the individual or entity
>>> named above. If the reader of the e-mail is not the intended recipient
>>> or the employee or agent responsible for delivering it to the intended
>>> recipient, you are hereby notified that you are in possession of
>>> confidential and privileged information. Any unauthorized use,
>>> disclosure, copying or the taking of any action in reliance on the
>>> contents of this information is strictly prohibited and may be
>>> unlawful. If you have received this e-mail unintentionally, please
>>> immediately notify the sender via telephone at (773) 406-2464 or
>>> email.
>>>=20
>>>=20
>>>=20
>>> On Thu, May 5, 2011 at 9:48 AM, Torben Ellegaard Lund
>>> <[log in to unmask]> wrote:
>>>> Hi Alex
>>>>=20
>>>>=20
>>>> Den Uge:18 05/05/2011 kl. 14.15 skrev Alex Fornito:
>>>>=20
>>>>> Hi Torben,
>>>>> Sorry, I just wanted to clarify: do you mean leaving SPM.xX.iG empty?=
It
>>>>> seems like this is done by default by spm_fmri_design (?)
>>>>=20
>>>> leaving it empty will include all user defined regressors in the effec=
ts of
>>>> interest F-test which determines the mask where the serial correlation=
is
>>>> estimated. I think it would make sense if the motion regressors did no=
t go
>>>> into this test, just like the DCS HP-filter does not go into the
>>>> F-contrast.
>>>>=20
>>>>> Are you suggesting manually entering motion parameters into this fiel=
d?
>>>>=20
>>>> Yes, or their indices that is. It should be done after specification, =
but
>>>> before model estimation. You can check if SPM recognized your changes =
by
>>>> looking at the automatically generated effects of interest F-contrast.
>>>>=20
>>>>=20
>>>> Best
>>>> Torben
>>>>=20
>>>>=20
>>>>=20
>>>>=20
>>>>>=20
>>>>> On 05/05/2011 18:16, "Torben Ellegaard Lund" <[log in to unmask]> wro=
te:
>>>>>=20
>>>>>> Just as a kind reminder. Leaving SPM.xX.iG is a bit unfortunate, bec=
ause
>>>>>> voxels where motion artefacts are significant then constitutes a lar=
ge
>>>>>> part
>>>>>> of
>>>>>> the F-test derived mask used to estimate serial correlations. If you=
are
>>>>>> picky
>>>>>> about this you can change it yourselves, but it is not as easy as it
>>>>>> should
>>>>>> be.
>>>>>>=20
>>>>>>=20
>>>>>> Best
>>>>>> Torben
>>>>>>=20
>>>>>>=20
>>>>>>=20
>>>>>> Den Uge:18 05/05/2011 kl. 05.03 skrev Alex Fornito:
>>>>>>=20
>>>>>>> Ahh, I see. I was assuming that SPM.xX.iG contained the indices to =
the
>>>>>>> nuisance covariates in the design matrix, but you're right -
>>>>>>> spm_fMRI_design
>>>>>>> leaves it empty.
>>>>>>>=20
>>>>>>> Thanks for your help!
>>>>>>> A
>>>>>>>=20
>>>>>>>=20
>>>>>>> On 05/05/2011 12:54, "MCLAREN, Donald" <[log in to unmask]> w=
rote:
>>>>>>>=20
>>>>>>>> I agree that nuisance covariates, such as motion should be removed=
;
>>>>>>>> however, motion covariates are not generally stored in X0 in my
>>>>>>>> reading of the SPM code (spm_fMRI_design, spm_regions). They shoul=
d be
>>>>>>>> removed in the spm_regions filtering based on the null-space of th=
e
>>>>>>>> contrast.
>>>>>>>>=20
>>>>>>>> As for the motion parameters being in the model, if they were in t=
he
>>>>>>>> standard analysis, they should be included in the PPI analysis. My
>>>>>>>> gPPI code will do this automatically as well.
>>>>>>>>=20
>>>>>>>> X0 is made of SPM.xX.iB (block effects -- so removing the mean) an=
d
>>>>>>>> SPM.xX.iG (nuisance variable that is empty as far as I can tell (l=
ine
>>>>>>>> 369 of spm_fMRI_design)) and the high-pass filtering (K.X0).
>>>>>>>>=20
>>>>>>>> Best Regards, Donald McLaren
>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>>> Hospital and Harvard Medical School
>>>>>>>> Office: (773) 406-2464
>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGE=
D
>>>>>>>> and which is intended only for the use of the individual or entity
>>>>>>>> named above. If the reader of the e-mail is not the intended recip=
ient
>>>>>>>> or the employee or agent responsible for delivering it to the inte=
nded
>>>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>> disclosure, copying or the taking of any action in reliance on the
>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>> unlawful. If you have received this e-mail unintentionally, please
>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>>>> email.
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>> On Wed, May 4, 2011 at 10:16 PM, Alex Fornito <[log in to unmask]
u.au>
>>>>>>>> wrote:
>>>>>>>>> Hi Donald,
>>>>>>>>> Thanks for your response. When you say "you don't want
>>>>>>>>> to filter out anything related to neural activity", I'm presuming=
that
>>>>>>>>> you
>>>>>>>>> are referring to the deconvolved neural signal?
>>>>>>>>>=20
>>>>>>>>> If so, that makes sense. However, X0 also contains user-specified
>>>>>>>>> nuisance
>>>>>>>>> covariates. I would have thought it would make sense to remove th=
ose,
>>>>>>>>> depending on what they were (e.g., movement parameters)? I guess =
they
>>>>>>>>> can
>>>>>>>>> always be entered into the PPI regression model...
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>> On 05/05/2011 11:57, "MCLAREN, Donald" <[log in to unmask]>
>>>>>>>>> wrote:
>>>>>>>>>=20
>>>>>>>>>> I could be wrong, Karl or Darren please correct me if I am.
>>>>>>>>>>=20
>>>>>>>>>> X0 is composed of the high-pass filter and constant term. Thus, =
you
>>>>>>>>>> want to filter these out of the Yc regressor. However, you don't=
want
>>>>>>>>>> to filter out anything related to neural activity, so you wouldn=
't
>>>>>>>>>> want to filter your signal and then predict the neural activity =
from
>>>>>>>>>> the filtered signal, especially filtering frequencies.
>>>>>>>>>>=20
>>>>>>>>>> Best Regards, Donald McLaren
>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>>>>> Hospital and Harvard Medical School
>>>>>>>>>> Office: (773) 406-2464
>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILE=
GED
>>>>>>>>>> and which is intended only for the use of the individual or enti=
ty
>>>>>>>>>> named above. If the reader of the e-mail is not the intended
>>>>>>>>>> recipient
>>>>>>>>>> or the employee or agent responsible for delivering it to the
>>>>>>>>>> intended
>>>>>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>>>> disclosure, copying or the taking of any action in reliance on t=
he
>>>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>>>> unlawful. If you have received this e-mail unintentionally, plea=
se
>>>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>>>>>> email.
>>>>>>>>>>=20
>>>>>>>>>>=20
>>>>>>>>>>=20
>>>>>>>>>> On Sat, Apr 30, 2011 at 8:03 PM, Alex Fornito
>>>>>>>>>> <[log in to unmask]>
>>>>>>>>>> wrote:
>>>>>>>>>>> Hi Donald,
>>>>>>>>>>> As far as I can tell, spm_regions filters and whitens the VOI t=
ime
>>>>>>>>>>> series,
>>>>>>>>>>> and adjusts for the null space of the contrast if an adjustment=
is
>>>>>>>>>>> specified
>>>>>>>>>>> in xY.Ic. It defines the confound matrix, X0, but does not corr=
ect
>>>>>>>>>>> for
>>>>>>>>>>> it.
>>>>>>>>>>> The following line in spm_peb_ppi corrects for the confounds.
>>>>>>>>>>>=20
>>>>>>>>>>> Yc =A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>>>>=20
>>>>>>>>>>> So the above correction does seem to be doing something differe=
nt to
>>>>>>>>>>> spm_regions. I'm wondering why the uncorrected data, Y, is used=
when
>>>>>>>>>>> generating the ppi interaction term, while the corrected data Y=
c is
>>>>>>>>>>> to
>>>>>>>>>>> be
>>>>>>>>>>> used as a covariate of no interest in the PPI model. I would ha=
s
>>>>>>>>>>> thought
>>>>>>>>>>> that Yc should be used to generate the ppi interaction term as =
well.
>>>>>>>>>>>=20
>>>>>>>>>>> In my data, my X0 is a 195 x 7 matrix (I have 195 volumes per
>>>>>>>>>>> session).
>>>>>>>>>>>=20
>>>>>>>>>>> Regards,
>>>>>>>>>>> Alex
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>> On 30/04/2011 02:22, "MCLAREN, Donald" <[log in to unmask]
m>
>>>>>>>>>>> wrote:
>>>>>>>>>>>=20
>>>>>>>>>>>> I'm actually travelling at the moment. However, I know Y has
>>>>>>>>>>>> already
>>>>>>>>>>>> been adjusted as part of the VOI processing.
>>>>>>>>>>>>=20
>>>>>>>>>>>> Can you check what X0 looks like?
>>>>>>>>>>>>=20
>>>>>>>>>>>> Best Regards, Donald McLaren
>>>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>>>>>> Research Fellow, Department of Neurology, Massachusetts Genera=
l
>>>>>>>>>>>> Hospital and Harvard Medical School
>>>>>>>>>>>> Office: (773) 406-2464
>>>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contai=
n
>>>>>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVI=
LEGED
>>>>>>>>>>>> and which is intended only for the use of the individual or en=
tity
>>>>>>>>>>>> named above. If the reader of the e-mail is not the intended
>>>>>>>>>>>> recipient
>>>>>>>>>>>> or the employee or agent responsible for delivering it to the
>>>>>>>>>>>> intended
>>>>>>>>>>>> recipient, you are hereby notified that you are in possession =
of
>>>>>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>>>>>> disclosure, copying or the taking of any action in reliance on=
the
>>>>>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>>>>>> unlawful. If you have received this e-mail unintentionally, pl=
ease
>>>>>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 =
or
>>>>>>>>>>>> email.
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>> On Fri, Apr 29, 2011 at 2:55 AM, Alex Fornito
>>>>>>>>>>>> <[log in to unmask]>
>>>>>>>>>>>> wrote:
>>>>>>>>>>>> Hi all,
>>>>>>>>>>>> I have a question concerning the code used to implement a PPI
>>>>>>>>>>>> analysis.
>>>>>>>>>>>>=20
>>>>>>>>>>>> In the spm_peb_ppi.m function packaged with SPM8, lines 329-33=
2
>>>>>>>>>>>> remove
>>>>>>>>>>>> confounds from the input seed region=B9s time course:
>>>>>>>>>>>>=20
>>>>>>>>>>>> % Remove confounds and save Y in ouput structure
>>>>>>>>>>>>=20
%------------------------------------------------------------------>>>>>>>>=
>>>>
-
>>>>>>>>>>>> ---
>>>>>>>>>>>> --
>>>>>>>>>>>> --
>>>>>>>>>>>> Yc =A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>>>>>=20
>>>>>>>>>>>> PPI.Y is then to be used as a covariate of no interest when
>>>>>>>>>>>> building
>>>>>>>>>>>> the
>>>>>>>>>>>> PPI
>>>>>>>>>>>> regression model. However, on line 488, it is the uncorrected =
seed
>>>>>>>>>>>> time
>>>>>>>>>>>> course, Y, that is input to the deconvolution routine and used=
to
>>>>>>>>>>>> generate
>>>>>>>>>>>> the ppi term:
>>>>>>>>>>>>=20
>>>>>>>>>>>> =A0C =A0=3D spm_PEB(Y,P);
>>>>>>>>>>>> =A0 =A0xn =3D xb*C{2}.E(1:N);
>>>>>>>>>>>> =A0 =A0xn =3D spm_detrend(xn);
>>>>>>>>>>>>=20
>>>>>>>>>>>> =A0% Setup psychological variable from inputs and contast weight=
s
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
%------------------------------------------------------------------>>>>>>>>=
>>>>
-
>>>>>>>>>>>> ---
>>>>>>>>>>>> =A0PSY =3D zeros(N*NT,1);
>>>>>>>>>>>> =A0for i =3D 1:size(U.u,2)
>>>>>>>>>>>> =A0 =A0 =A0PSY =3D PSY + full(U.u(:,i)*U.w(:,i));
>>>>>>>>>>>> =A0end
>>>>>>>>>>>> =A0% PSY =3D spm_detrend(PSY); =A0<- removed centering of psych vari=
able
>>>>>>>>>>>> =A0% prior to multiplication with xn. Based on discussion with K=
arl
>>>>>>>>>>>> =A0% and Donald McLaren.
>>>>>>>>>>>>=20
>>>>>>>>>>>> % Multiply psychological variable by neural signal
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
%------------------------------------------------------------------>>>>>>>>=
>>>>
-
>>>>>>>>>>>> ---
>>>>>>>>>>>> =A0 PSYxn =3D PSY.*xn;
>>>>>>>>>>>>=20
>>>>>>>>>>>> Is there any specific reason why Y, rather than Yc(:,1), is us=
ed to
>>>>>>>>>>>> compute
>>>>>>>>>>>> PSYxn? I thought Yc might be more appropriate (?).
>>>>>>>>>>>> Thanks for your help,
>>>>>>>>>>>> Alex
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>> ------------------------------------------
>>>>>>>>>>>>=20
>>>>>>>>>>>> Alex Fornito
>>>>>>>>>>>> Research Fellow
>>>>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>>>>> University of Melbourne
>>>>>>>>>>>> National Neuroscience Facility
>>>>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>>>>> 161 Barry St
>>>>>>>>>>>> Carlton South 3053
>>>>>>>>>>>> Victoria, Australia
>>>>>>>>>>>>=20
>>>>>>>>>>>> Email: [log in to unmask]
>>>>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>> ------------------------------------------
>>>>>>>>>>>=20
>>>>>>>>>>> Alex Fornito
>>>>>>>>>>> Research Fellow
>>>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>>>> University of Melbourne
>>>>>>>>>>> National Neuroscience Facility
>>>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>>>> 161 Barry St
>>>>>>>>>>> Carlton South 3053
>>>>>>>>>>> Victoria, Australia
>>>>>>>>>>>=20
>>>>>>>>>>> Email: [log in to unmask]
>>>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>> ------------------------------------------
>>>>>>>>>=20
>>>>>>>>> Alex Fornito
>>>>>>>>> Research Fellow
>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>> University of Melbourne
>>>>>>>>> National Neuroscience Facility
>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>> 161 Barry St
>>>>>>>>> Carlton South 3053
>>>>>>>>> Victoria, Australia
>>>>>>>>>=20
>>>>>>>>> Email: [log in to unmask]
>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>=20
>>>>>>>=20
>>>>>>>=20
>>>>>>> ------------------------------------------
>>>>>>>=20
>>>>>>> Alex Fornito
>>>>>>> Research Fellow
>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>> University of Melbourne
>>>>>>> National Neuroscience Facility
>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>> 161 Barry St
>>>>>>> Carlton South 3053
>>>>>>> Victoria, Australia
>>>>>>>=20
>>>>>>> Email: [log in to unmask]
>>>>>>> Phone: +61 3 8344 1876
>>>>>>> Fax: +61 3 9348 0469
>>>>>>=20
>>>>>>=20
>>>>>=20
>>>>>=20
>>>>> ------------------------------------------
>>>>>=20
>>>>> Alex Fornito
>>>>> Research Fellow
>>>>> Melbourne Neuropsychiatry Centre
>>>>> University of Melbourne
>>>>> National Neuroscience Facility
>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>> 161 Barry St
>>>>> Carlton South 3053
>>>>> Victoria, Australia
>>>>>=20
>>>>> Email: [log in to unmask]
>>>>> Phone: +61 3 8344 1876
>>>>> Fax: +61 3 9348 0469
>>>>>=20
>>>>>=20
>>>>>=20
>>>>=20
>>>=20
>>=20
>>=20
>> ------------------------------------------
>>=20
>> Alex Fornito
>> Research Fellow
>> Melbourne Neuropsychiatry Centre
>> University of Melbourne
>> National Neuroscience Facility
>> Levels 1 & 2, Alan Gilbert Building
>> 161 Barry St
>> Carlton South 3053
>> Victoria, Australia
>>=20
>> Email: [log in to unmask]
>> Phone: +61 3 8344 1876
>> Fax: +61 3 9348 0469
>>=20
>>=20
>>=20
>>=20
>=20
------------------------------------------
Alex Fornito
Research Fellow
Melbourne Neuropsychiatry Centre
University of Melbourne
National Neuroscience Facility
Levels 1 & 2, Alan Gilbert Building
161 Barry St=A0
Carlton South 3053
Victoria, Australia
Email: [log in to unmask]
Phone: +61 3 8344 1876
Fax: +61 3 9348 0469 =A0
=========================================================================
Date: Fri, 6 May 2011 16:17:37 -0500
Reply-To: John Fredy <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Fredy <[log in to unmask]>
Subject: using mri3dx
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0016e6d77df6ed46f204a2a204da
Message-ID: <[log in to unmask]>
--0016e6d77df6ed46f204a2a204da
Content-Type: text/plain; charset=ISO-8859-1
hello all,
I am trying to show some activations in the spm5 template in mri3dx
(template spm5 command) but the activations appear more higher than the
template. Is necessary any conversion to show the activations?
I think that maybe the mri3dX uses tailarach space, I can convert my
normalized activations to tailarach space?
Thanks in advance
--0016e6d77df6ed46f204a2a204da
Content-Type: text/html; charset=ISO-8859-1
hello all,<div><br></div><div>I am trying to show some activations in the spm5 template in mri3dx (template spm5 command) but the activations appear more higher than the template. Is necessary any conversion to show the activations?</div>
<div><br></div><div>I think that maybe the mri3dX uses tailarach space, I can convert my normalized activations to tailarach space?</div><div><br></div><div>Thanks in advance</div>
--0016e6d77df6ed46f204a2a204da--
=========================================================================
Date: Sat, 7 May 2011 04:59:23 +0100
Reply-To: David Yang <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: David Yang <[log in to unmask]>
Subject: How to interpret the result of extract data from ROI in Volumes
Toolbox?
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Dear SPMers
I tried to calculate standardized uptake value (SUV)/Binding potential in=
receptor SPECT imaging by SPM8 and every subject had his own structure M=
RI image concurrently.
After finishing DARTEL process of MRI, I applied following analysis as pr=
oposed by John in previous SPM archives:
1. Within subject coregistration of all the T1 and SPECT images without a=
ny reslicing.
2. Use the normalise to MNI space option, with the flow fields and SPECT =
images, to generate spatially normalised and smoothed versions of SPECT d=
ata.
Then, I made mask files by WFU Pick_Atlas and applied such mask files to =
normalised and smoothed SPECT images.
Extract data from ROI in Volumes Toolbox was used with "Pass Output to Wo=
rkspace" (as suggested by Volkmar in previous SPM archives) under followi=
ng paramters:
Data source: source images
ROI Specification: source image
Average: no averaing
Interpolation: Trilinear
Then, I got an output file in Workpalce but I had no idea for interpretin=
g such.
I wondering if the value in each cell of "raw field" revealed "intensity =
values per voxel"?
If such was correct, how can I got mean and SD values of all raw values?
What were the meaning of the values in "posmm" and "posvx" fields?
Thanks for your kind help and also appreciated for any resources of learn=
ing more about Volumes Toolbox
Sincerely yours,=20
David
=========================================================================
Date: Sat, 7 May 2011 15:19:13 +0200
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Roberto Viviani <[log in to unmask]>
Subject: Reference for "New Segment" toolbox option
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1; DelSp="Yes"; format="flowed"
Content-Disposition: inline
Content-Transfer-Encoding: 7bit
Message-ID: <[log in to unmask]>
Dear SPM list,
I am looking for a reference/description for the 'New Segment' method
as implemented in an SPM8 toolbox. I understand (from the SPM8 manual)
that it is an extension of the unified segmentation / normalization
algorithm introduced in SPM5, but is the 2005 NeuroImage paper,
"Unified segmentation", still appropriate, or is there a paper other
than the chapter 25 in the handbook?
Thank you in advance
Roberto Viviani
=========================================================================
Date: Sat, 7 May 2011 22:39:01 +0800
Reply-To: =?GBK?B?t8nE8Q==?= <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?GBK?B?t8nE8Q==?= <[log in to unmask]>
Subject: =?GBK?Q?=A3=DBspm8=A3=DDversion_problem=A1=AAS.timeonset?=
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------=_Part_83580_1288539194.1304779141455--
=========================================================================
Date: Sat, 7 May 2011 17:45:20 +0100
Reply-To: Bettina Studer <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Bettina Studer <[log in to unmask]>
Subject: SPM8 combine an exclusive and and inclusive mask
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Dear all
I have a problem with an ROI analysis I am trying to run in SPM8. Here is
what I want to do:
I want to check which voxels are NOT commonly activated in two contrasts
(derived from different models) in predefined ROIs.
So essentially I want to mask contrast1 with contrast2 using the exclusive
function and then limit this to the ROIs, ie an inclusive mask of an
ROI-image from WFU_Pickatlas.
Unfortunately WFU_Pickatlas doesn't work properly on the version of SPM8 we
have (it doesn't load the ROI-analysis prompt), however I thought I could
get around this by just entering the ROI_image I have previously saved from
Pickatlas in the SPM8 masking command. But this means I have to mask
contrast1 using an EXCLUSIVE mask with contrast2 and an INCLUSIVE mask with
the ROI. How do I do this? I can select two images, but can only apply them
either both as an inclusive or both as an exclusive mask.
Any help would be greatly appreciated!
Yours sincerely,
Bettina Studer
**********************************************************************
Bettina Studer
PhD Student
Department of Experimental Psychology
University of Cambridge
Downing Street, Cambridge, CB2 3EB, UK.
Tel (+44) 01223 333560
Email [log in to unmask]
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</o:shapelayout></xml><![endif]--></head><body lang=3DEN-US link=3Dblue =
vlink=3Dpurple><div class=3DWordSection1><p class=3DMsoNormal>Dear =
all<o:p></o:p></p><p class=3DMsoNormal><o:p> </o:p></p><p =
class=3DMsoNormal>I have a problem with an ROI analysis I am trying to =
run in SPM8. Here is what I want to do:<o:p></o:p></p><p =
class=3DMsoNormal>I want to check which voxels are NOT commonly =
activated in two contrasts (derived from different models) in predefined =
ROIs.<o:p></o:p></p><p class=3DMsoNormal>So essentially I want to mask =
contrast1 with contrast2 using the exclusive function and then limit =
this to the ROIs, ie an inclusive mask of an ROI-image from =
WFU_Pickatlas.<o:p></o:p></p><p =
class=3DMsoNormal><o:p> </o:p></p><p =
class=3DMsoNormal>Unfortunately WFU_Pickatlas doesn’t work =
properly on the version of SPM8 we have (it doesn’t load the =
ROI-analysis prompt), however I thought I could get around this by just =
entering the ROI_image I have previously saved from Pickatlas in the =
SPM8 masking command. But this means I have to mask contrast1 using an =
EXCLUSIVE mask with contrast2 and an INCLUSIVE mask with the ROI. How do =
I do this? I can select two images, but can only apply them either both =
as an inclusive or both as an exclusive mask.<o:p></o:p></p><p =
class=3DMsoNormal><o:p> </o:p></p><p class=3DMsoNormal>Any help =
would be greatly appreciated!<o:p></o:p></p><p =
class=3DMsoNormal><o:p> </o:p></p><p class=3DMsoNormal>Yours =
sincerely,<o:p></o:p></p><p class=3DMsoNormal>Bettina =
Studer<o:p></o:p></p><p class=3DMsoNormal><span =
lang=3DEN-GB>************************************************************=
**********<o:p></o:p></span></p><p class=3DMsoNormal><span =
lang=3DEN-GB><o:p> </o:p></span></p><p class=3DMsoNormal><span =
lang=3DEN-GB>Bettina Studer<o:p></o:p></span></p><p =
class=3DMsoNormal><span lang=3DEN-GB>PhD Student<o:p></o:p></span></p><p =
class=3DMsoNormal><span lang=3DEN-GB>Department of Experimental =
Psychology<o:p></o:p></span></p><p class=3DMsoNormal><span =
lang=3DEN-GB>University of Cambridge<o:p></o:p></span></p><p =
class=3DMsoNormal><span lang=3DEN-GB>Downing Street, Cambridge, CB2 3EB, =
UK.<o:p></o:p></span></p><p class=3DMsoNormal><span lang=3DEN-GB>Tel =
(+44) 01223 333560<o:p></o:p></span></p><p class=3DMsoNormal><span =
lang=3DEN-GB>Email <a =
href=3D"mailto:[log in to unmask]">[log in to unmask]</a><o:p></o:p></span></p>=
<p class=3DMsoNormal><o:p> </o:p></p></div></body></html>
------=_NextPart_000_001D_01CC0CDE.88D9CD30--
=========================================================================
Date: Sat, 7 May 2011 13:07:15 -0700
Reply-To: Bob Spunt <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Bob Spunt <[log in to unmask]>
Subject: Which contrast to adjust for?
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
This topic has been discussed on numerous occasions on the listserv,
but I'm still unsure about a few things. When extracting a VOI
timecourse (e.g., for a PPI analysis):
1. Can adjusting for different contrasts produce large differences in
results? In other words, is the decision important? And if so, why
don't folks typically report this in empirical articles using PPI?
2. Is there ever a case in which it is desirable to adjust for a
t-test contrast (e.g., the comparison of only two conditions)? In
spm_regions the default is to only allow adjustment for F-contrasts,
but of course adjustment can be made for t-contrasts if desired.
3. My understanding is that the F-test omnibus (coding for all effects
of interest) is the favored option for adjustment. But there is some
ambiguity in what "all effects of interest" refers to. Should all
effects expected to relate to neural activity be included (so that
only motion regressors/constants are removed), or only effects "of
interest"? For example, if I've modeled response time and skipped
trials as covariates of no interest, should these be included in the
omnibus (because they are expected to relate to neural activity, not
to artifactual changes in signal intensity)?
Many thanks in advance for any tips.
Cheers,
Bob Spunt
Doctoral Student
Department of Psychology
University of California, Los Angeles
=========================================================================
Date: Sun, 8 May 2011 11:01:15 +1000
Reply-To: Alex Fornito <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Alex Fornito <[log in to unmask]>
Subject: Re: PPI question
Comments: To: "MCLAREN, Donald" <[log in to unmask]>,
Darren Gitelman <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset="ISO-8859-1"
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Hmmm... I've tried testing this.
I generated a whitened, frequency-filtered time course, Y, as per usual
using spm_regions. xY.X0 contained the block effects and low frequency
confounds. I then removed the block effects from xY.X0 and applied the
correction used in spm_peb_ppi (line 415) to generated Yc. So, This time I
was only correcting the time course for the low frequency confounds for a
second time. The correction is given by
Yc =3D Y - X0*inv(X0'*X0)*X0'*Y;
However, this left Yc unchanged from Y. So, unless additional confounds are
specified, the only difference between Y and Yc in a standard implementatio=
n
of ppi seems to be the removal of block effects in Yc. Since this shouldn't
really affect the deconvolution, and since Y is already frequency filtered
by spm_regions, it seems to be like best practice would be to deconvolve Yc=
,
rather than Y, given the additional removal of nuisance confounds if they
are pre-specified. Does this seem like a reasonable conclusion?
Thanks again,
Alex =20
On 07/05/2011 12:33, "MCLAREN, Donald" <[log in to unmask]> wrote:
> There might be some residual effects of filtering a second time since
> X0 consists of K.X0 and iB.
>=20
> The iB is just a constant, so it wouldn't have any effect on the
> deconvolution either way, just shifts the values up or down.
>=20
> Best Regards, Donald McLaren
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> D.G. McLaren, Ph.D.
> Postdoctoral Research Fellow, GRECC, Bedford VA
> Research Fellow, Department of Neurology, Massachusetts General
> Hospital and Harvard Medical School
> Office: (773) 406-2464
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> This e-mail contains CONFIDENTIAL INFORMATION which may contain
> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
> and which is intended only for the use of the individual or entity
> named above. If the reader of the e-mail is not the intended recipient
> or the employee or agent responsible for delivering it to the intended
> recipient, you are hereby notified that you are in possession of
> confidential and privileged information. Any unauthorized use,
> disclosure, copying or the taking of any action in reliance on the
> contents of this information is strictly prohibited and may be
> unlawful. If you have received this e-mail unintentionally, please
> immediately notify the sender via telephone at (773) 406-2464 or
> email.
>=20
>=20
>=20
> On Fri, May 6, 2011 at 5:14 PM, Alex Fornito <[log in to unmask]> wr=
ote:
>> Actually, sorry one more question:
>>=20
>> If Y in spm_peb_ppi is already frequency filtered by spm_regions, then t=
he
>> only difference (barring any additional confounds specified with xX.iG)
>> between Y and Yc is the additional removal of block effects.
>>=20
>> Since the ppi interaction term is generated from Y and not Yc, I am
>> presuming then that is solely because it is not desirable to deconvolve =
a
>> time course with block effects removed. Is this correct?
>>=20
>>=20
>> On 07/05/2011 04:07, "MCLAREN, Donald" <[log in to unmask]> wrote:
>>=20
>>> The null-space of the contrast are any columns of the contrast (which
>>> must be an F-contrast) that are 0. Thus, you remove the effects of
>>> motion when you do the adjustment and don't need to worry about them
>>> being included in the deconvolved data. The code that I have supplied
>>> has N rows for N conditions of interest after I talked to Darren about
>>> the ideal contrast to use for adjustment.
>>>=20
>>> As for removing the frequencies, I think it is probably fine to remove
>>> them, I was just under the impression that they weren't being removed
>>> because of me commenting out that line during testing of spm_regions.
>>> I would go with the SPM defaults until their effect is tested. If you
>>> don't set a high-pass filter, then you won't remove the frequencies,
>>> so you could test it that way as well.
>>>=20
>>> Best Regards, Donald McLaren
>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>> D.G. McLaren, Ph.D.
>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>> Research Fellow, Department of Neurology, Massachusetts General
>>> Hospital and Harvard Medical School
>>> Office: (773) 406-2464
>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>>> and which is intended only for the use of the individual or entity
>>> named above. If the reader of the e-mail is not the intended recipient
>>> or the employee or agent responsible for delivering it to the intended
>>> recipient, you are hereby notified that you are in possession of
>>> confidential and privileged information. Any unauthorized use,
>>> disclosure, copying or the taking of any action in reliance on the
>>> contents of this information is strictly prohibited and may be
>>> unlawful. If you have received this e-mail unintentionally, please
>>> immediately notify the sender via telephone at (773) 406-2464 or
>>> email.
>>>=20
>>>=20
>>>=20
>>> On Thu, May 5, 2011 at 9:46 PM, Alex Fornito <[log in to unmask]>
>>> wrote:
>>>> Hi Donald, Torben and Darren,
>>>> Thanks for your responses.
>>>>=20
>>>> Form each of your responses, it seems like best practice would be to r=
emove
>>>> motion (and/or other confounds) from the VOI time series prior to
>>>> deconvolution.
>>>>=20
>>>> It also seems like you are recommending NOT to frequency filter the VO=
I
>>>> time
>>>> series.
>>>>=20
>>>> In my reading though, spm_regions does this by default with the call t=
o
>>>> spm_filter (line 135). So, if spm_regions is used to extract a VOI tim=
e
>>>> series, the time series that is input to spm_peb_ppi will already freq=
uency
>>>> filtered. So it seems like, in standard practice, the deconvolution is
>>>> applied to frequency-filtered data. In this case, if xX.iG is empty, t=
he
>>>> only difference between Y and Yc in spm_peb_ppi is the additional remo=
val
>>>> of
>>>> block effects (xX.iB).
>>>>=20
>>>> Based on the current chain of emails, it seems you are recommending th=
at a
>>>> confound-corrected, whitened, but non-frequency filtered time course s=
hould
>>>> be input to spm_peb_ppi. IS that correct, or am I missing something?
>>>>=20
>>>> Finally, can I clarify exactly what the null space of the contrast is?=
Most
>>>> of the time in my analyses I don't get the option to adjust for it, so
>>>> xY.Ic
>>>> is empty.
>>>>=20
>>>> Thanks again for all your help,
>>>> A
>>>>=20
>>>>=20
>>>>=20
>>>> On 06/05/2011 02:18, "MCLAREN, Donald" <[log in to unmask]> wrot=
e:
>>>>=20
>>>>> I haven't thoroughly tested this, but if you set iG to be the movemen=
t
>>>>> parameters columns. Then still adjust for the null space (motion
>>>>> parameters). You will get the best of both. If you don't adjust for
>>>>> the null space, then movement will contribute to the deconvolution. I=
n
>>>>> summary, if you have iG be the motion parameter columns AND adjust fo=
r
>>>>> the null-space (motion columns), then:
>>>>>=20
>>>>> Y will have the effect of motion removed. Yc (removal of motion twice=
)
>>>>> will be minimally different since Y is orthogonal to the motion
>>>>> parameters. So, you have motion removed from both the autocorrelation
>>>>> estimate, the Y for deconvolution, and Yc.
>>>>>=20
>>>>> Best Regards, Donald McLaren
>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>> D.G. McLaren, Ph.D.
>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>> Hospital and Harvard Medical School
>>>>> Office: (773) 406-2464
>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
>>>>> and which is intended only for the use of the individual or entity
>>>>> named above. If the reader of the e-mail is not the intended recipien=
t
>>>>> or the employee or agent responsible for delivering it to the intende=
d
>>>>> recipient, you are hereby notified that you are in possession of
>>>>> confidential and privileged information. Any unauthorized use,
>>>>> disclosure, copying or the taking of any action in reliance on the
>>>>> contents of this information is strictly prohibited and may be
>>>>> unlawful. If you have received this e-mail unintentionally, please
>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>> email.
>>>>>=20
>>>>>=20
>>>>>=20
>>>>> On Thu, May 5, 2011 at 9:48 AM, Torben Ellegaard Lund
>>>>> <[log in to unmask]> wrote:
>>>>>> Hi Alex
>>>>>>=20
>>>>>>=20
>>>>>> Den Uge:18 05/05/2011 kl. 14.15 skrev Alex Fornito:
>>>>>>=20
>>>>>>> Hi Torben,
>>>>>>> Sorry, I just wanted to clarify: do you mean leaving SPM.xX.iG empt=
y? It
>>>>>>> seems like this is done by default by spm_fmri_design (?)
>>>>>>=20
>>>>>> leaving it empty will include all user defined regressors in the eff=
ects
>>>>>> of
>>>>>> interest F-test which determines the mask where the serial correlati=
on is
>>>>>> estimated. I think it would make sense if the motion regressors did =
not
>>>>>> go
>>>>>> into this test, just like the DCS HP-filter does not go into the
>>>>>> F-contrast.
>>>>>>=20
>>>>>>> Are you suggesting manually entering motion parameters into this fi=
eld?
>>>>>>=20
>>>>>> Yes, or their indices that is. It should be done after specification=
, but
>>>>>> before model estimation. You can check if SPM recognized your change=
s by
>>>>>> looking at the automatically generated effects of interest F-contras=
t.
>>>>>>=20
>>>>>>=20
>>>>>> Best
>>>>>> Torben
>>>>>>=20
>>>>>>=20
>>>>>>=20
>>>>>>=20
>>>>>>>=20
>>>>>>> On 05/05/2011 18:16, "Torben Ellegaard Lund" <[log in to unmask]> w=
rote:
>>>>>>>=20
>>>>>>>> Just as a kind reminder. Leaving SPM.xX.iG is a bit unfortunate,
>>>>>>>> because
>>>>>>>> voxels where motion artefacts are significant then constitutes a l=
arge
>>>>>>>> part
>>>>>>>> of
>>>>>>>> the F-test derived mask used to estimate serial correlations. If y=
ou
>>>>>>>> are
>>>>>>>> picky
>>>>>>>> about this you can change it yourselves, but it is not as easy as =
it
>>>>>>>> should
>>>>>>>> be.
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>> Best
>>>>>>>> Torben
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>> Den Uge:18 05/05/2011 kl. 05.03 skrev Alex Fornito:
>>>>>>>>=20
>>>>>>>>> Ahh, I see. I was assuming that SPM.xX.iG contained the indices t=
o the
>>>>>>>>> nuisance covariates in the design matrix, but you're right -
>>>>>>>>> spm_fMRI_design
>>>>>>>>> leaves it empty.
>>>>>>>>>=20
>>>>>>>>> Thanks for your help!
>>>>>>>>> A
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>> On 05/05/2011 12:54, "MCLAREN, Donald" <[log in to unmask]>
>>>>>>>>> wrote:
>>>>>>>>>=20
>>>>>>>>>> I agree that nuisance covariates, such as motion should be remov=
ed;
>>>>>>>>>> however, motion covariates are not generally stored in X0 in my
>>>>>>>>>> reading of the SPM code (spm_fMRI_design, spm_regions). They sho=
uld
>>>>>>>>>> be
>>>>>>>>>> removed in the spm_regions filtering based on the null-space of =
the
>>>>>>>>>> contrast.
>>>>>>>>>>=20
>>>>>>>>>> As for the motion parameters being in the model, if they were in=
the
>>>>>>>>>> standard analysis, they should be included in the PPI analysis. =
My
>>>>>>>>>> gPPI code will do this automatically as well.
>>>>>>>>>>=20
>>>>>>>>>> X0 is made of SPM.xX.iB (block effects -- so removing the mean) =
and
>>>>>>>>>> SPM.xX.iG (nuisance variable that is empty as far as I can tell =
(line
>>>>>>>>>> 369 of spm_fMRI_design)) and the high-pass filtering (K.X0).
>>>>>>>>>>=20
>>>>>>>>>> Best Regards, Donald McLaren
>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
>>>>>>>>>> Hospital and Harvard Medical School
>>>>>>>>>> Office: (773) 406-2464
>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
>>>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILE=
GED
>>>>>>>>>> and which is intended only for the use of the individual or enti=
ty
>>>>>>>>>> named above. If the reader of the e-mail is not the intended
>>>>>>>>>> recipient
>>>>>>>>>> or the employee or agent responsible for delivering it to the
>>>>>>>>>> intended
>>>>>>>>>> recipient, you are hereby notified that you are in possession of
>>>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>>>> disclosure, copying or the taking of any action in reliance on t=
he
>>>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>>>> unlawful. If you have received this e-mail unintentionally, plea=
se
>>>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
>>>>>>>>>> email.
>>>>>>>>>>=20
>>>>>>>>>>=20
>>>>>>>>>>=20
>>>>>>>>>> On Wed, May 4, 2011 at 10:16 PM, Alex Fornito
>>>>>>>>>> <[log in to unmask]>
>>>>>>>>>> wrote:
>>>>>>>>>>> Hi Donald,
>>>>>>>>>>> Thanks for your response. When you say "you don't want
>>>>>>>>>>> to filter out anything related to neural activity", I'm presumi=
ng
>>>>>>>>>>> that
>>>>>>>>>>> you
>>>>>>>>>>> are referring to the deconvolved neural signal?
>>>>>>>>>>>=20
>>>>>>>>>>> If so, that makes sense. However, X0 also contains user-specifi=
ed
>>>>>>>>>>> nuisance
>>>>>>>>>>> covariates. I would have thought it would make sense to remove
>>>>>>>>>>> those,
>>>>>>>>>>> depending on what they were (e.g., movement parameters)? I gues=
s
>>>>>>>>>>> they
>>>>>>>>>>> can
>>>>>>>>>>> always be entered into the PPI regression model...
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>> On 05/05/2011 11:57, "MCLAREN, Donald" <[log in to unmask]
m>
>>>>>>>>>>> wrote:
>>>>>>>>>>>=20
>>>>>>>>>>>> I could be wrong, Karl or Darren please correct me if I am.
>>>>>>>>>>>>=20
>>>>>>>>>>>> X0 is composed of the high-pass filter and constant term. Thus=
, you
>>>>>>>>>>>> want to filter these out of the Yc regressor. However, you don=
't
>>>>>>>>>>>> want
>>>>>>>>>>>> to filter out anything related to neural activity, so you woul=
dn't
>>>>>>>>>>>> want to filter your signal and then predict the neural activit=
y
>>>>>>>>>>>> from
>>>>>>>>>>>> the filtered signal, especially filtering frequencies.
>>>>>>>>>>>>=20
>>>>>>>>>>>> Best Regards, Donald McLaren
>>>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>>>>>> Research Fellow, Department of Neurology, Massachusetts Genera=
l
>>>>>>>>>>>> Hospital and Harvard Medical School
>>>>>>>>>>>> Office: (773) 406-2464
>>>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contai=
n
>>>>>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVI=
LEGED
>>>>>>>>>>>> and which is intended only for the use of the individual or en=
tity
>>>>>>>>>>>> named above. If the reader of the e-mail is not the intended
>>>>>>>>>>>> recipient
>>>>>>>>>>>> or the employee or agent responsible for delivering it to the
>>>>>>>>>>>> intended
>>>>>>>>>>>> recipient, you are hereby notified that you are in possession =
of
>>>>>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>>>>>> disclosure, copying or the taking of any action in reliance on=
the
>>>>>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>>>>>> unlawful. If you have received this e-mail unintentionally, pl=
ease
>>>>>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 =
or
>>>>>>>>>>>> email.
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>> On Sat, Apr 30, 2011 at 8:03 PM, Alex Fornito
>>>>>>>>>>>> <[log in to unmask]>
>>>>>>>>>>>> wrote:
>>>>>>>>>>>> Hi Donald,
>>>>>>>>>>>> As far as I can tell, spm_regions filters and whitens the VOI =
time
>>>>>>>>>>>> series,
>>>>>>>>>>>> and adjusts for the null space of the contrast if an adjustmen=
t is
>>>>>>>>>>>> specified
>>>>>>>>>>>> in xY.Ic. It defines the confound matrix, X0, but does not cor=
rect
>>>>>>>>>>>> for
>>>>>>>>>>>> it.
>>>>>>>>>>>> The following line in spm_peb_ppi corrects for the confounds.
>>>>>>>>>>>>=20
>>>>>>>>>>>> Yc =A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>>>>>=20
>>>>>>>>>>>> So the above correction does seem to be doing something differ=
ent
>>>>>>>>>>>> to
>>>>>>>>>>>> spm_regions. I'm wondering why the uncorrected data, Y, is use=
d
>>>>>>>>>>>> when
>>>>>>>>>>>> generating the ppi interaction term, while the corrected data =
Yc is
>>>>>>>>>>>> to
>>>>>>>>>>>> be
>>>>>>>>>>>> used as a covariate of no interest in the PPI model. I would h=
as
>>>>>>>>>>>> thought
>>>>>>>>>>>> that Yc should be used to generate the ppi interaction term as
>>>>>>>>>>>> well.
>>>>>>>>>>>>=20
>>>>>>>>>>>> In my data, my X0 is a 195 x 7 matrix (I have 195 volumes per
>>>>>>>>>>>> session).
>>>>>>>>>>>>=20
>>>>>>>>>>>> Regards,
>>>>>>>>>>>> Alex
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>> On 30/04/2011 02:22, "MCLAREN, Donald" <[log in to unmask]
om>
>>>>>>>>>>>> wrote:
>>>>>>>>>>>>=20
>>>>>>>>>>>> I'm actually travelling at the moment. However, I know Y has
>>>>>>>>>>>> already
>>>>>>>>>>>> been adjusted as part of the VOI processing.
>>>>>>>>>>>>=20
>>>>>>>>>>>> Can you check what X0 looks like?
>>>>>>>>>>>>=20
>>>>>>>>>>>> Best Regards, Donald McLaren
>>>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>>>> D.G. McLaren, Ph.D.
>>>>>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
>>>>>>>>>>>> Research Fellow, Department of Neurology, Massachusetts Genera=
l
>>>>>>>>>>>> Hospital and Harvard Medical School
>>>>>>>>>>>> Office: (773) 406-2464
>>>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>>>>>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contai=
n
>>>>>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVI=
LEGED
>>>>>>>>>>>> and which is intended only for the use of the individual or en=
tity
>>>>>>>>>>>> named above. If the reader of the e-mail is not the intended
>>>>>>>>>>>> recipient
>>>>>>>>>>>> or the employee or agent responsible for delivering it to the
>>>>>>>>>>>> intended
>>>>>>>>>>>> recipient, you are hereby notified that you are in possession =
of
>>>>>>>>>>>> confidential and privileged information. Any unauthorized use,
>>>>>>>>>>>> disclosure, copying or the taking of any action in reliance on=
the
>>>>>>>>>>>> contents of this information is strictly prohibited and may be
>>>>>>>>>>>> unlawful. If you have received this e-mail unintentionally, pl=
ease
>>>>>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 =
or
>>>>>>>>>>>> email.
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>> On Fri, Apr 29, 2011 at 2:55 AM, Alex Fornito
>>>>>>>>>>>> <[log in to unmask]>
>>>>>>>>>>>> wrote:
>>>>>>>>>>>> Hi all,
>>>>>>>>>>>> I have a question concerning the code used to implement a PPI
>>>>>>>>>>>> analysis.
>>>>>>>>>>>>=20
>>>>>>>>>>>> In the spm_peb_ppi.m function packaged with SPM8, lines 329-33=
2
>>>>>>>>>>>> remove
>>>>>>>>>>>> confounds from the input seed region=B9s time course:
>>>>>>>>>>>>=20
>>>>>>>>>>>> % Remove confounds and save Y in ouput structure
>>>>>>>>>>>>=20
>> %------------------------------------------------------------------>>>>>=
>>>>>
>> >>
>> -
>>>>>>>>>>>> ---
>>>>>>>>>>>> --
>>>>>>>>>>>> --
>>>>>>>>>>>> Yc =A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;
>>>>>>>>>>>> PPI.Y =3D Yc(:,1);
>>>>>>>>>>>>=20
>>>>>>>>>>>> PPI.Y is then to be used as a covariate of no interest when
>>>>>>>>>>>> building
>>>>>>>>>>>> the
>>>>>>>>>>>> PPI
>>>>>>>>>>>> regression model. However, on line 488, it is the uncorrected =
seed
>>>>>>>>>>>> time
>>>>>>>>>>>> course, Y, that is input to the deconvolution routine and used=
to
>>>>>>>>>>>> generate
>>>>>>>>>>>> the ppi term:
>>>>>>>>>>>>=20
>>>>>>>>>>>> =A0C =A0=3D spm_PEB(Y,P);
>>>>>>>>>>>> =A0 =A0xn =3D xb*C{2}.E(1:N);
>>>>>>>>>>>> =A0 =A0xn =3D spm_detrend(xn);
>>>>>>>>>>>>=20
>>>>>>>>>>>> =A0% Setup psychological variable from inputs and contast weight=
s
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>> %------------------------------------------------------------------>>>>>=
>>>>>
>> >>
>> -
>>>>>>>>>>>> ---
>>>>>>>>>>>> =A0PSY =3D zeros(N*NT,1);
>>>>>>>>>>>> =A0for i =3D 1:size(U.u,2)
>>>>>>>>>>>> =A0 =A0 =A0PSY =3D PSY + full(U.u(:,i)*U.w(:,i));
>>>>>>>>>>>> =A0end
>>>>>>>>>>>> =A0% PSY =3D spm_detrend(PSY); =A0<- removed centering of psych vari=
able
>>>>>>>>>>>> =A0% prior to multiplication with xn. Based on discussion with K=
arl
>>>>>>>>>>>> =A0% and Donald McLaren.
>>>>>>>>>>>>=20
>>>>>>>>>>>> % Multiply psychological variable by neural signal
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>> %------------------------------------------------------------------>>>>>=
>>>>>
>> >>
>> -
>>>>>>>>>>>> ---
>>>>>>>>>>>> =A0 PSYxn =3D PSY.*xn;
>>>>>>>>>>>>=20
>>>>>>>>>>>> Is there any specific reason why Y, rather than Yc(:,1), is us=
ed to
>>>>>>>>>>>> compute
>>>>>>>>>>>> PSYxn? I thought Yc might be more appropriate (?).
>>>>>>>>>>>> Thanks for your help,
>>>>>>>>>>>> Alex
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>> ------------------------------------------
>>>>>>>>>>>>=20
>>>>>>>>>>>> Alex Fornito
>>>>>>>>>>>> Research Fellow
>>>>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>>>>> University of Melbourne
>>>>>>>>>>>> National Neuroscience Facility
>>>>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>>>>> 161 Barry St
>>>>>>>>>>>> Carlton South 3053
>>>>>>>>>>>> Victoria, Australia
>>>>>>>>>>>>=20
>>>>>>>>>>>> Email: [log in to unmask]
>>>>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>> ------------------------------------------
>>>>>>>>>>>>=20
>>>>>>>>>>>> Alex Fornito
>>>>>>>>>>>> Research Fellow
>>>>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>>>>> University of Melbourne
>>>>>>>>>>>> National Neuroscience Facility
>>>>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>>>>> 161 Barry St
>>>>>>>>>>>> Carlton South 3053
>>>>>>>>>>>> Victoria, Australia
>>>>>>>>>>>>=20
>>>>>>>>>>>> Email: [log in to unmask]
>>>>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>> ------------------------------------------
>>>>>>>>>>>=20
>>>>>>>>>>> Alex Fornito
>>>>>>>>>>> Research Fellow
>>>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>>>> University of Melbourne
>>>>>>>>>>> National Neuroscience Facility
>>>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>>>> 161 Barry St
>>>>>>>>>>> Carlton South 3053
>>>>>>>>>>> Victoria, Australia
>>>>>>>>>>>=20
>>>>>>>>>>> Email: [log in to unmask]
>>>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>>=20
>>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>>=20
>>>>>>>>> ------------------------------------------
>>>>>>>>>=20
>>>>>>>>> Alex Fornito
>>>>>>>>> Research Fellow
>>>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>>>> University of Melbourne
>>>>>>>>> National Neuroscience Facility
>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>>>> 161 Barry St
>>>>>>>>> Carlton South 3053
>>>>>>>>> Victoria, Australia
>>>>>>>>>=20
>>>>>>>>> Email: [log in to unmask]
>>>>>>>>> Phone: +61 3 8344 1876
>>>>>>>>> Fax: +61 3 9348 0469
>>>>>>>>=20
>>>>>>>>=20
>>>>>>>=20
>>>>>>>=20
>>>>>>> ------------------------------------------
>>>>>>>=20
>>>>>>> Alex Fornito
>>>>>>> Research Fellow
>>>>>>> Melbourne Neuropsychiatry Centre
>>>>>>> University of Melbourne
>>>>>>> National Neuroscience Facility
>>>>>>> Levels 1 & 2, Alan Gilbert Building
>>>>>>> 161 Barry St
>>>>>>> Carlton South 3053
>>>>>>> Victoria, Australia
>>>>>>>=20
>>>>>>> Email: [log in to unmask]
>>>>>>> Phone: +61 3 8344 1876
>>>>>>> Fax: +61 3 9348 0469
>>>>>>>=20
>>>>>>>=20
>>>>>>>=20
>>>>>>=20
>>>>>=20
>>>>=20
>>>>=20
>>>> ------------------------------------------
>>>>=20
>>>> Alex Fornito
>>>> Research Fellow
>>>> Melbourne Neuropsychiatry Centre
>>>> University of Melbourne
>>>> National Neuroscience Facility
>>>> Levels 1 & 2, Alan Gilbert Building
>>>> 161 Barry St
>>>> Carlton South 3053
>>>> Victoria, Australia
>>>>=20
>>>> Email: [log in to unmask]
>>>> Phone: +61 3 8344 1876
>>>> Fax: +61 3 9348 0469
>>>>=20
>>>>=20
>>>>=20
>>>>=20
>>>=20
>>=20
>>=20
>> ------------------------------------------
>>=20
>> Alex Fornito
>> Research Fellow
>> Melbourne Neuropsychiatry Centre
>> University of Melbourne
>> National Neuroscience Facility
>> Levels 1 & 2, Alan Gilbert Building
>> 161 Barry St
>> Carlton South 3053
>> Victoria, Australia
>>=20
>> Email: [log in to unmask]
>> Phone: +61 3 8344 1876
>> Fax: +61 3 9348 0469
>>=20
>=20
------------------------------------------
Alex Fornito
Research Fellow
Melbourne Neuropsychiatry Centre
University of Melbourne
National Neuroscience Facility
Levels 1 & 2, Alan Gilbert Building
161 Barry St=A0
Carlton South 3053
Victoria, Australia
Email: [log in to unmask]
Phone: +61 3 8344 1876
Fax: +61 3 9348 0469 =A0
=========================================================================
Date: Sun, 8 May 2011 14:14:06 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re:
=?UTF-8?Q?=EF=BC=BBspm8=EF=BC=BDversion_problem=E2=80=94S.timeonset?=
Comments: To: =?UTF-8?B?6aOe6bif?= <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Dear Haoran,
Yes there was a change in the Neuromag reader so that now we always
assume that a file starts at zero whereas previously we used the time
axis stored in the dataset. This should not be important once you
epoch, However there were some pathological cases so the latest
version should be safer.
Best,
Vladimir
2011/5/7 =E9=A3=9E=E9=B8=9F <[log in to unmask]>:
> Dear SPM's user,
> =E3=80=80=E3=80=80I have just found that different=C2=A0version of SPM8 w=
ill result in different
> ''S.timeonset'' which=C2=A0appeared in the history script file. When I
> preprocessed(Convert and Epoching) my MEG data with the latest
> SPM8(spm8_updates_r4010.zip),=C2=A0 I would get ''S.timeonset=3D0''. Howe=
ver, with
> old SPM8(original version without any update) I would get ''S.timeonset=
=3D -2
> ''. Thus, I wonder that =C2=A0whether this difference will make any effec=
ts on my
> data when I continue.
> =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0I will be grateful for any help=
!
>
>
> --
> Haoran LI (MS)
> Brain Imaging Lab,
> Research Center for Learning Science,
> Southeast University
> 2 Si Pai Lou , Nanjing, 210096, P.R.China
>
>
=========================================================================
Date: Mon, 9 May 2011 15:44:20 +0800
Reply-To: =?GBK?B?t8nE8Q==?= <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?GBK?B?t8nE8Q==?= <[log in to unmask]>
Subject: Re: =?GBK?Q?=A3=DBspm8=A3=DDversion_problem=A1=AAS.timeonset?=
Comments: To: Vladimir Litvak <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
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------=_Part_103762_666515174.1304927060547--
=========================================================================
Date: Mon, 9 May 2011 11:17:36 +0200
Reply-To: Noelia Ventura <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Noelia Ventura <[log in to unmask]>
Subject: Compare conjunction
MIME-Version: 1.0
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Message-ID: <[log in to unmask]>
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Hi all,
We would like to compare directly the results of two conjunction
analyses.These conjunctions show overlapping clusters. One conjunction
shows a larger cluster then the other. We would like to examine whether
the voxels that show up for one conjunction but not for the other differ
significantly from each other.
In more detail, we have two tasks in the native (L1) and non-native
language (L2). Each task consists of 3 conditions, (A, B, C).In the
random effects we use a full factorial within subjects design and create
a contrast : (and we do this conjunction for L1 and L2. We would like to
know in which voxels the conjunction of L1 > L2.
However, in spm you cannot directly compare to conjunctions with each
other. Or can you?
We would like to use imcalc to test where i1 = conj L1, i2 = conj L2 and
our expression is i1 -i2> 0. However, i think we obtain a binary image
from that but we need a statistical image. Can anyone provide a solution
for this?
Thanks for your help,
Noelia
--------------010508000706010105010307
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<html>
<head>
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charset=ISO-8859-1">
</head>
<body bgcolor="#ffffff" text="#000000">
<span style="" lang="EN-GB">Hi all,</span>
<p class="MsoNormal"><span style="" lang="EN-GB">We would like to
compare directly the results of two conjunction analyses.<span
style=""> </span>These conjunctions show overlapping
clusters. One conjunction shows a larger cluster then the other.
We would like to examine whether the voxels that show up for one
conjunction but not for the other differ significantly from each
other. </span></p>
<p class="MsoNormal"><span style="" lang="EN-GB">In more detail, we
have two tasks in the native (L1) and non-native language (L2).
<span style=""> </span>Each task consists of 3 conditions, (A,
B, C).<span style=""> </span>In the random effects we use a
full factorial within subjects design and create a contrast : </span><span
style="" lang="EN-GB">(</span><span style="font-size: 11pt;
line-height: 115%; font-family:
"Calibri","sans-serif"; position: relative;
top: 5.5pt;"><img src="cid:part1.08060200.03070207@psb.uji.es"
width="246" height="20"></span><span style="" lang="EN-GB"><span
style=""> </span>and we do this conjunction for L1 and L2. <span
style=""> </span>We would like to know in which voxels the
conjunction of L1 > L2. </span></p>
<p class="MsoNormal"><span style="" lang="EN-GB"> </span></p>
<p class="MsoNormal"><span style="" lang="EN-GB">However, in spm you
cannot directly compare to conjunctions with each other. Or can
you?</span></p>
<p class="MsoNormal"><span style="" lang="EN-GB">We would like to
use imcalc to test where i1 = conj L1, i2 = conj L2 and our
expression is i1 -i2> 0. However, i think we obtain a binary
image from that but we need a statistical image. Can anyone
provide a solution for this? <br>
</span></p>
<p class="MsoNormal"><span style="" lang="EN-GB">Thanks for your
help,<br>
Noelia<br>
</span></p>
</body>
</html>
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begin:vcard
fn:Noelia Ventura Campos
n:Ventura Campos;Noelia
org;quoted-printable:Universitat Jaume I;Departament de Psicolog=C3=ADa B=C3=A0sica, Cl=C3=ADnica y Psicobiolog=C3=
=ADa
adr;quoted-printable;quoted-printable;quoted-printable:Avda. Sos Baynat, s/n;;Edifici d'investigaci=C3=B3 II;Castell=C3=B3 de la Plana;;E-12071;Espa=C3=B1a (Spain)
title:PDI
tel;work:+34 964 387658
tel;fax:+34 964 729267
url:www.fmri.uji.es
version:2.1
end:vcard
--------------040605090108090809010206--
=========================================================================
Date: Mon, 9 May 2011 11:36:13 +0200
Reply-To: =?UTF-8?B?546L5aqb?= <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?UTF-8?B?546L5aqb?= <[log in to unmask]>
Subject: First Level Analysis
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf305643090c4a4904a2d492c4
Message-ID: <[log in to unmask]>
--20cf305643090c4a4904a2d492c4
Content-Type: text/plain; charset=ISO-8859-1
Hello SPMs:
I wanna write a mfile which can automatically do the first level analysis
for all the animal datas I have. However, the only three commands I find can
be used are:
spm_fmri_design,
spm_fmri_spm_ui,
spm_spm
All of them are using SPM as both input and output, I wonder how to get the
input SPM.mat.
Now the only thing I have are the animal imgs after smoothing, the multiple
regressors (a txt file) and Explicit mask.
Are there any standard procedure to do the first level analysis?
And what command should I use to initialize the SPM.mat?
Thank you so much.
Best Regards,
Yuan
--20cf305643090c4a4904a2d492c4
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
<div>Hello SPMs:</div>
<div>=A0</div>
<div>I wanna write a mfile which can automatically do the first level analy=
sis for all the animal datas I have. However, the only three commands I fin=
d can be used are:</div>
<div>spm_fmri_design,</div>
<div>spm_fmri_spm_ui,</div>
<div>spm_spm</div>
<div>All of them are using SPM as both input and output, I wonder how to ge=
t the input SPM.mat.</div>
<div>=A0</div>
<div>Now the only thing I have are the animal imgs after smoothing, the mul=
tiple regressors (a txt file) and Explicit mask.</div>
<div>Are there any standard procedure to do the first level analysis?</div>
<div>And what command should I use to=A0initialize the SPM.mat?</div>
<div>Thank you so much.</div>
<div>=A0</div>
<div>Best=A0Regards,</div>
<div>Yuan=A0</div>
<div>=A0</div>
<div>=A0</div>
--20cf305643090c4a4904a2d492c4--
=========================================================================
Date: Mon, 9 May 2011 11:37:23 +0200
Reply-To: "Moeller, C." <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Moeller, C." <[log in to unmask]>
Subject: inaccurate segmentation of gray matter
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/mixed; boundary="----_=_NextPart_001_01CC0E2C.B2FD8E83"
Message-ID: <[log in to unmask]>
This is a multi-part message in MIME format.
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charset="us-ascii"
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Dear SPM experts,
I am doing VBM analysis on scans of AD patients and healthy controls. I
just finished the segmentation and found a lot of inaccurate
segmentations, especially in scans with a lot of atrophy. I attached a
screenshot of the segmentation for illustration of the problem. It seems
as if the space between the cortex and the dura is also segmented as
gray matter. I used 'New Segment' of SPM8.
Does anyone have an idea why this happens and how I can solve this
problem?
Another issue is, that often the dura around the brain is also segmented
as gray matter. In the older version of the 'Segment' step there was a
'Clean up' option. Does anyone know how to solve this in the 'New
Segment' step of SPM?
Thanks in advance.
Best regards,
Christiane
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------_=_NextPart_001_01CC0E2C.B2FD8E83--
=========================================================================
Date: Mon, 9 May 2011 12:24:34 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: Reference for "New Segment" toolbox option
Comments: To: [log in to unmask]
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
The "Unified Segmentation" paper is still the one to cite. The
changes to the algorithm were a bit too incremental to make it
worthwhile even attempting to get them published.
Best regards,
-John
On 7 May 2011 14:19, Roberto Viviani <[log in to unmask]> wrote:
> Dear SPM list,
>
> I am looking for a reference/description for the 'New Segment' method as
> implemented in an SPM8 toolbox. I understand (from the SPM8 manual) that =
it
> is an extension of the unified segmentation / normalization algorithm
> introduced in SPM5, but is the 2005 NeuroImage paper, =A0"Unified
> segmentation", still appropriate, or is there a paper other than the chap=
ter
> 25 in the handbook?
>
> Thank you in advance
> Roberto Viviani
>
=========================================================================
Date: Mon, 9 May 2011 13:01:02 +0100
Reply-To: Jonathan Berrebi <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jonathan Berrebi <[log in to unmask]>
Subject: Re: Siemens 32-channel Trio headcoil
Comments: To: Rik Henson <[log in to unmask]>
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear Rik,
Although we are running a GE scanner and not a Siemens we have noticed th=
e inhomogeneity of GE's 32 channels coil as well and we are wondering wha=
t answers you may have got concerning the inhomogeneity of the Siemens 32=
channels coil and its effect on segmentation and VBM.
Should we first make the pictures homogeneous using GE's built-in softwar=
e tome come (PURE) or could we process the inhomogeneous data directly?
Regards,
Jonathan Berrebi
Karolinska Institute
Stockholm,
Sweden
=========================================================================
Date: Mon, 9 May 2011 12:12:55 +0000
Reply-To: Benjamin Wagner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Benjamin Wagner <[log in to unmask]>
Subject: Re: SPM8 combine an exclusive and and inclusive mask
Comments: To: Bettina Studer <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Content-Type: multipart/alternative;
boundary="_000_F413A51CAE02744BAE6A63300AADC8BE022EC7exchdb7medctradwf_"
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
--_000_F413A51CAE02744BAE6A63300AADC8BE022EC7exchdb7medctradwf_
Content-Type: text/plain; charset="us-ascii"
Content-Transfer-Encoding: quoted-printable
Hello Bettina,
Please contact me off list see about fixing your installation of PickAtl=
as.
Ben Wagner
ANSIR Lab
________________________________
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] On B=
ehalf Of Bettina Studer
Sent: Saturday, May 07, 2011 12:45 PM
To: [log in to unmask]
Subject: [SPM] SPM8 combine an exclusive and and inclusive mask
Dear all
I have a problem with an ROI analysis I am trying to run in SPM8. Here is w=
hat I want to do:
I want to check which voxels are NOT commonly activated in two contrasts (d=
erived from different models) in predefined ROIs.
So essentially I want to mask contrast1 with contrast2 using the exclusive =
function and then limit this to the ROIs, ie an inclusive mask of an ROI-im=
age from WFU_Pickatlas.
Unfortunately WFU_Pickatlas doesn't work properly on the version of SPM8 we=
have (it doesn't load the ROI-analysis prompt), however I thought I could =
get around this by just entering the ROI_image I have previously saved from=
Pickatlas in the SPM8 masking command. But this means I have to mask contr=
ast1 using an EXCLUSIVE mask with contrast2 and an INCLUSIVE mask with the =
ROI. How do I do this? I can select two images, but can only apply them eit=
her both as an inclusive or both as an exclusive mask.
Any help would be greatly appreciated!
Yours sincerely,
Bettina Studer
**********************************************************************
Bettina Studer
PhD Student
Department of Experimental Psychology
University of Cambridge
Downing Street, Cambridge, CB2 3EB, UK.
Tel (+44) 01223 333560
Email [log in to unmask]<mailto:[log in to unmask]>
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<div dir=3D"ltr" align=3D"left"><span class=3D"033161212-09052011"><font fa=
ce=3D"Arial" color=3D"#0000ff" size=3D"2">Hello Bettina,</font></span></div=
>
<div dir=3D"ltr" align=3D"left"><span class=3D"033161212-09052011"><font fa=
ce=3D"Arial" color=3D"#0000ff" size=3D"2"> Please contact me of=
f list see about fixing your installation of PickAtlas.</font></span></div>
<div> </div>
<div><span class=3D"033161212-09052011"></span><font face=3D"Arial"><font c=
olor=3D"#0000ff"><font size=3D"2">B<span class=3D"033161212-09052011">en Wa=
gner</span></font></font></font></div>
<div><font><font color=3D"#0000ff"><font size=3D"2"><span class=3D"03316121=
2-09052011"></span></font></font></font><span class=3D"033161212-09052011">=
</span><font face=3D"Arial"><font color=3D"#0000ff"><font size=3D"2">A<span=
class=3D"033161212-09052011">NSIR Lab</span></font></font></font><br>
</div>
<div class=3D"OutlookMessageHeader" lang=3D"en-us" dir=3D"ltr" align=3D"lef=
t">
<hr tabindex=3D"-1">
<font face=3D"Tahoma" size=3D"2"><b>From:</b> SPM (Statistical Parametric M=
apping) [mailto:[log in to unmask]]
<b>On Behalf Of </b>Bettina Studer<br>
<b>Sent:</b> Saturday, May 07, 2011 12:45 PM<br>
<b>To:</b> [log in to unmask]<br>
<b>Subject:</b> [SPM] SPM8 combine an exclusive and and inclusive mask<br>
</font><br>
</div>
<div></div>
<div class=3D"WordSection1">
<p class=3D"MsoNormal">Dear all<o:p></o:p></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">I have a problem with an ROI analysis I am trying to=
run in SPM8. Here is what I want to do:<o:p></o:p></p>
<p class=3D"MsoNormal">I want to check which voxels are NOT commonly activa=
ted in two contrasts (derived from different models) in predefined ROIs.<o:=
p></o:p></p>
<p class=3D"MsoNormal">So essentially I want to mask contrast1 with contras=
t2 using the exclusive function and then limit this to the ROIs, ie an incl=
usive mask of an ROI-image from WFU_Pickatlas.<o:p></o:p></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">Unfortunately WFU_Pickatlas doesn’t work prope=
rly on the version of SPM8 we have (it doesn’t load the ROI-analysis =
prompt), however I thought I could get around this by just entering the ROI=
_image I have previously saved from Pickatlas
in the SPM8 masking command. But this means I have to mask contrast1 using=
an EXCLUSIVE mask with contrast2 and an INCLUSIVE mask with the ROI. How d=
o I do this? I can select two images, but can only apply them either both a=
s an inclusive or both as an exclusive
mask.<o:p></o:p></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">Any help would be greatly appreciated!<o:p></o:p></p=
>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">Yours sincerely,<o:p></o:p></p>
<p class=3D"MsoNormal">Bettina Studer<o:p></o:p></p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">*******************************=
***************************************<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB"><o:p> </o:p></span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">Bettina Studer<o:p></o:p></span=
></p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">PhD Student<o:p></o:p></span></=
p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">Department of Experimental Psyc=
hology<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">University of Cambridge<o:p></o=
:p></span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">Downing Street, Cambridge, CB2 =
3EB, UK.<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">Tel (+44) 01223 333560<o:p>=
</o:p></span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">Email <a href=3D"mailto:bs410@c=
am.ac.uk">[log in to unmask]</a><o:p></o:p></span></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
</div>
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--_000_F413A51CAE02744BAE6A63300AADC8BE022EC7exchdb7medctradwf_--
=========================================================================
Date: Mon, 9 May 2011 12:58:02 +0000
Reply-To: Giuseppe Signorello <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Giuseppe Signorello <[log in to unmask]>
Subject: preprocessing dti
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Hi=2C
I load in Spm8=2C the toolbox Diffusion II to analyze dti files.
I have any problems:
there's a wide licterature about FSL processing=2C but not if I would like=
use SPM.
What are the steps of dti preprocessing? And I can implement them with Diff=
usion II toolbox in SPM?
Thanks for your answers.
=
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Hi=2C<br>I load in Spm8=2C the toolbox Diffusion II to analyze dti files.<b=
r>I have any problems:<br>there's a wide licterature about =3B FSL proc=
essing=2C but not if I would like use SPM.<br>What are the steps of dti pre=
processing? And I can implement them with Diffusion II toolbox in SPM?<br>T=
hanks for your answers.<br><br> </body>
</html>=
--_37aa5636-328d-4619-8a75-153f04cc1354_--
=========================================================================
Date: Mon, 9 May 2011 15:14:09 +0200
Reply-To: Anne Kathrin Rehme <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Anne Kathrin Rehme <[log in to unmask]>
Subject: Weird results from partial correlation analysis
MIME-version: 1.0
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Dear SPM users,
I have a question regarding the logical model underlying a partial correlation. I have two behavioral variables, A and B, and a region C. There is no correlation between A and activity in C and no correlation between B and activity in C, but A and B are correlated. However, when I adjust A for the variance of B and vice versa (i.e. B for the variance of A), both adjusted variables now show a positive correlation with region C. I wonder whether this is logic from a causal analytic point of view? If A and B share common variance, shouldn't there be a correlation between those variables and region C and not only between the adjusted A-/B-values and region C?
Kind regards,
Anne
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Dear SPM users,<br><br>I have a question regarding the logical model underlying a partial correlation. I have two behavioral variables, A and B, and a region C. There is no correlation between A and activity in C and no correlation between B and activity in C, but A and B are correlated. However, when I adjust A for the variance of B and vice versa (i.e. B for the variance of A), both adjusted variables now show a positive correlation with region C. I wonder whether this is logic from a causal analytic point of view? If A and B share common variance, shouldn't there be a correlation between those variables and region C and not only between the adjusted A-/B-values and region C?<br><br>Kind regards,<br>Anne
--Boundary_(ID_4CKWfffcGcVQ+ST06XaL7A)--
=========================================================================
Date: Mon, 9 May 2011 15:04:03 +0100
Reply-To: Mike Sugarman <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Mike Sugarman <[log in to unmask]>
Subject: Model Design
Mime-Version: 1.0
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Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Hello SPM experts,
I am setting up a flexible factorial design with a library of PET scans a=
nd have chosen global normalisation as one of my options, with overall gr=
and mean scaling. When my model design is outputted by SPM, it includes a=
column titled "global", and most of scans are represented different shad=
es of gray. However, for one of my subjects, all of the scans are black, =
could anybody tell me what this might represent?
Thanks,
-Mike Sugarman
Wayne State University
=========================================================================
Date: Mon, 9 May 2011 15:14:48 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: SPM8 3D Source Reconstruction
Comments: To: Urs Bachofner <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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Dear Urs,
On 9 May 2011, at 14:23, Urs Bachofner wrote:
> Dear Mr. Litvak,
>
> I am a neuropsychology student and I'm currently working on my final
> work at the University of Zurich.
> I am trying to virtually analyze auditory evoked potentials in study
> participants of various ages.
>
> I am very fond of your research article "EEG and MEG Data Analysis
> in SPM8" which helped me a lot and made me understand the source
> reconstruction in SPM8 a lot better.
> Still there are certain questions that I cannot figure out and any
> help or suggestions from your side would be greatly appreciated. I'm
> sure you could easily help me a lot getting rid of the final problems.
>
> So if you could take the time to help me with the following
> questions I would really appreciate it:
>
>
>
> 1. First off, if I want to use the Artefact Detection SPM8 offers, I
> cannot figure out which one of the four possibilities would be best
> for my data. As mentioned above, I want to analyze auditory evoked
> potentials and my data is epoched (-100 500 ms) and I have 250+
> trials in each set of data. The sample rate is 1000.
> Also, if I choose "Peak to Peak Amplitude" I can assign a certain
> Threshold. Still, I cannot find any information about this
> Threshold, what exactly it is and how big it should be.
Since SPM does not enforce particular units on the data the threshold
value depends on the typical values of your data and artefacts. You
can open the data in the reviewing tool and look at a few trials and
channels to figure out what the typical range of your data is. Then
you can adjust the value so that not too much and not too little is
rejected.
>
> 2. After I run the inverse solution, I get the choice between
> "Evoked", "Induced" and "Trials". Intuitively I would go for
> "Evoked". From your paper I understand that "evoked" applies the
> settings made to each and every trial and then averages the results,
> whereas "induced" averages the trials and then applies the settings
> made.
It's actually the opposite.
> I am clearly undecided what would be better for my data.
>
>
That depends on what you are looking for. If you are looking for
evoked activity, i.e. activity which is phase-locked to the stimulus
and you want to do a source analysis of ERP/ERF then you should choose
the 'evoked' option. If you are interested also in activity that is
not phase-locked the things that one-usually looks at with time-
frequency analysis then you should use the 'induced' option.
Best,
Vladimir
>
> Thank you very much for every bit of help you can offer and thank
> you for your time.
>
> Sincerely,
>
> Urs Bachofner
>
>
>
> --
> NEU: FreePhone - kostenlos mobil telefonieren und surfen!
> Jetzt informieren: http://www.gmx.net/de/go/freephone
--Apple-Mail-1-225773680
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<html><body style=3D"word-wrap: break-word; -webkit-nbsp-mode: space; =
-webkit-line-break: after-white-space; "><div>Dear =
Urs,</div><div><br></div><br><div><div>On 9 May 2011, at 14:23, Urs =
Bachofner wrote:</div><br class=3D"Apple-interchange-newline"><blockquote =
type=3D"cite"><span class=3D"Apple-style-span" style=3D"border-collapse: =
separate; color: rgb(0, 0, 0); font-family: Helvetica; font-style: =
normal; font-variant: normal; font-weight: normal; letter-spacing: =
normal; line-height: normal; orphans: 2; text-align: auto; text-indent: =
0px; text-transform: none; white-space: normal; widows: 2; word-spacing: =
0px; -webkit-border-horizontal-spacing: 0px; =
-webkit-border-vertical-spacing: 0px; =
-webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: =
auto; -webkit-text-stroke-width: 0px; font-size: medium; "><div =
style=3D"font-family: verdana, arial, helvetica, sans-serif; font-size: =
12px; padding-top: 5px; padding-right: 5px; padding-bottom: 5px; =
padding-left: 5px; margin-top: 0px; margin-right: 0px; margin-bottom: =
0px; margin-left: 0px; background-color: rgb(255, 255, 255); position: =
static; z-index: auto; ">Dear Mr. Litvak,<br><br>I am a neuropsychology =
student and I'm currently working on my final work at the University of =
Zurich.<br>I am trying to virtually analyze auditory evoked potentials =
in study participants of various ages.<br><br>I am very fond of your =
research article "EEG and MEG Data Analysis in SPM8" which helped me a =
lot and made me understand the source reconstruction in SPM8 a lot =
better.<br>Still there are certain questions that I cannot figure out =
and any help or suggestions from your side would be greatly appreciated. =
I'm sure you could easily help me a lot getting rid of the final =
problems.<br><br>So if you could take the time to help me with the =
following questions I would really appreciate it:<br><br><br><br>1. =
First off, if I want to use the Artefact Detection SPM8 offers, I cannot =
figure out which one of the four possibilities would be best for my =
data. As mentioned above, I want to analyze auditory evoked potentials =
and my data is epoched (-100 500 ms) and I have 250+ trials in each set =
of data. The sample rate is 1000.<span =
class=3D"Apple-converted-space"> </span><br>Also, if I choose "Peak =
to Peak Amplitude" I can assign a certain Threshold. Still, I cannot =
find any information about this Threshold, what exactly it is and how =
big it should =
be.<br></div></span></blockquote><div><br></div><div><br></div><div>Since =
SPM does not enforce particular units on the data the threshold value =
depends on the typical values of your data and artefacts. You can open =
the data in the reviewing tool and look at a few trials and channels to =
figure out what the typical range of your data is. Then you can adjust =
the value so that not too much and not too little is =
rejected. </div><div><br></div><br><blockquote type=3D"cite"><span =
class=3D"Apple-style-span" style=3D"border-collapse: separate; color: =
rgb(0, 0, 0); font-family: Helvetica; font-style: normal; font-variant: =
normal; font-weight: normal; letter-spacing: normal; line-height: =
normal; orphans: 2; text-align: auto; text-indent: 0px; text-transform: =
none; white-space: normal; widows: 2; word-spacing: 0px; =
-webkit-border-horizontal-spacing: 0px; -webkit-border-vertical-spacing: =
0px; -webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: =
auto; -webkit-text-stroke-width: 0px; font-size: medium; "><div =
style=3D"font-family: verdana, arial, helvetica, sans-serif; font-size: =
12px; padding-top: 5px; padding-right: 5px; padding-bottom: 5px; =
padding-left: 5px; margin-top: 0px; margin-right: 0px; margin-bottom: =
0px; margin-left: 0px; background-color: rgb(255, 255, 255); position: =
static; z-index: auto; "><br>2. After I run the inverse solution, I get =
the choice between "Evoked", "Induced" and "Trials". Intuitively I would =
go for "Evoked". =46rom your paper I understand that "evoked" applies =
the settings made to each and every trial and then averages the results, =
whereas "induced" averages the trials and then applies the settings =
made. </div></span></blockquote><div><br></div><div>It's actually the =
opposite.</div><br><blockquote type=3D"cite"><span =
class=3D"Apple-style-span" style=3D"border-collapse: separate; color: =
rgb(0, 0, 0); font-family: Helvetica; font-style: normal; font-variant: =
normal; font-weight: normal; letter-spacing: normal; line-height: =
normal; orphans: 2; text-align: auto; text-indent: 0px; text-transform: =
none; white-space: normal; widows: 2; word-spacing: 0px; =
-webkit-border-horizontal-spacing: 0px; -webkit-border-vertical-spacing: =
0px; -webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: =
auto; -webkit-text-stroke-width: 0px; font-size: medium; "><div =
style=3D"font-family: verdana, arial, helvetica, sans-serif; font-size: =
12px; padding-top: 5px; padding-right: 5px; padding-bottom: 5px; =
padding-left: 5px; margin-top: 0px; margin-right: 0px; margin-bottom: =
0px; margin-left: 0px; background-color: rgb(255, 255, 255); position: =
static; z-index: auto; ">I am clearly undecided what would be better for =
my data.<br><br><br></div></span></blockquote><div><br></div><div>That =
depends on what you are looking for. If you are looking for evoked =
activity, i.e. activity which is phase-locked to the stimulus and =
you want to do a source analysis of ERP/ERF then you should choose the =
'evoked' option. If you are interested also in activity that is not =
phase-locked the things that one-usually looks at with time-frequency =
analysis then you should use the 'induced' =
option.</div><div><br></div><div>Best,</div><div><br></div><div>Vladimir</=
div><div><br></div><br><blockquote type=3D"cite"><span =
class=3D"Apple-style-span" style=3D"border-collapse: separate; color: =
rgb(0, 0, 0); font-family: Helvetica; font-style: normal; font-variant: =
normal; font-weight: normal; letter-spacing: normal; line-height: =
normal; orphans: 2; text-align: auto; text-indent: 0px; text-transform: =
none; white-space: normal; widows: 2; word-spacing: 0px; =
-webkit-border-horizontal-spacing: 0px; -webkit-border-vertical-spacing: =
0px; -webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: =
auto; -webkit-text-stroke-width: 0px; font-size: medium; "><div =
style=3D"font-family: verdana, arial, helvetica, sans-serif; font-size: =
12px; padding-top: 5px; padding-right: 5px; padding-bottom: 5px; =
padding-left: 5px; margin-top: 0px; margin-right: 0px; margin-bottom: =
0px; margin-left: 0px; background-color: rgb(255, 255, 255); position: =
static; z-index: auto; "><br>Thank you very much for every bit of help =
you can offer and thank you for your time.<br><br>Sincerely,<br><br>Urs =
Bachofner<div class=3D"signature" style=3D"color: rgb(102, 102, 102); =
font-size: 0.9em; "><br><br><br>--<span =
class=3D"Apple-converted-space"> </span><br>NEU: FreePhone - =
kostenlos mobil telefonieren und surfen! <br>Jetzt =
informieren:<span class=3D"Apple-converted-space"> </span><a =
href=3D"http://www.gmx.net/de/go/freephone">http://www.gmx.net/de/go/freep=
hone</a></div></div></span></blockquote></div><br></body></html>=
--Apple-Mail-1-225773680--
=========================================================================
Date: Mon, 9 May 2011 09:10:52 -0500
Reply-To: "Sivapurapu, Aparna Pisupati" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Sivapurapu, Aparna Pisupati" <[log in to unmask]>
Subject: SPM flip parameters
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MIME-Version: 1.0
Message-ID: <C7F70118510C5F[log in to unmask]>
--_000_C7F70118510C5F44B939884396D9A861056A1E7905ITSHCWNEM02ds_
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Hi all,
I have a question about moving from Spm2 to SPM 5/SPM8 and I did not find a=
n answer on the SPM forum and was wondering if you could help me find the r=
ight answer.
We have a large amount of data analyzed in spm2 (with flip set to 0 in the =
spm_defaults file). We want to move forward and use these images to make si=
ngle subject models in SPM5/SPM8. I modified the flip to 0 in SPM5 and I wa=
s not able to produce the same results that we produced in SPM2, the left/r=
ight was flipped. I am able to say this because we did this analysis on a t=
ask that has clear left/right motor activation. After changing the flip to =
1 in SPM5 and remodeling the files, I think the results match with SPM2. Th=
is is quite confusing because I thought that the flip was supposed to be sa=
me between versions and I was not able to find anything in the archives tha=
t suggests that the function of flip parameter itself changed between the t=
wo versions. I have read a lot about how changing/constantly modifying the =
flip would really start to get confusing and quite honestly I have been car=
eful with modifying the flip and making sure that I document the changes, s=
o I know this is not caused by a random mistake I committed. So my question=
really is, did the flip parameter fundamentally change between SPM2 and SP=
M5? If so, to ensure data compatibility between both version what flip woul=
d be recommended for SPM5. Please note that moving forward we are analyzing=
all the data in SPM8 and in NIFTI format to avoid all the confusion once a=
nd for all. But this data that I am talking about is in Analyze format. We =
used a program to convert our Rec/Par files to analyze format and used MRIc=
ro to split the bundle into independent volumes.
Thank you so much for your help in this matter. I appreciate your time and =
patience.
Sincerely,
-a
Aparna. P.Sivapurapu, MS
Neuroimaging Analyst
Education and Brain Research Lab,
Vanderbilt University,
PMB 328,
230 Appleton Place,
Nashville, TN 37203-5721.
Phone: 615-936-1151
Email: [log in to unmask]
Web: http://kc.vanderbilt.edu/educationandbrainlab/
Disclaimer:
The materials in this e-mail are private and may contain Protected Health I=
nformation. Please note that e-mail is not necessarily confidential or secu=
re. Your use of e-mail constitutes your acknowledgment of these confidentia=
lity and security limitations. If you are not the intended recipient, be ad=
vised that any unauthorized use, disclosure, copying, distribution, or the =
taking of any action in reliance on the contents of this information is str=
ictly prohibited. If you have received this e-mail in error, please immedia=
tely notify the sender via telephone or return e-mail.
--_000_C7F70118510C5F44B939884396D9A861056A1E7905ITSHCWNEM02ds_
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</xml><![endif]--><!--[if gte mso 9]><xml>
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<o:idmap v:ext=3D"edit" data=3D"1" />
</o:shapelayout></xml><![endif]--></head><body lang=3DEN-US link=3Dblue vli=
nk=3Dpurple><div class=3DWordSection1><p class=3DMsoNormal><span style=3D'f=
ont-family:"Century Schoolbook","serif";color:black'>Hi all, <o:p></o:p></s=
pan></p><p class=3DMsoNormal><span style=3D'font-family:"Century Schoolbook=
","serif";color:black'><o:p> </o:p></span></p><p class=3DMsoNormal><sp=
an style=3D'font-family:"Century Schoolbook","serif";color:black'>I have a =
question about moving from Spm2 to SPM 5/SPM8 and I did not find an answer =
on the SPM forum and was wondering if you could help me find the right answ=
er. <o:p></o:p></span></p><p class=3DMsoNormal><span style=3D'font-family:"=
Century Schoolbook","serif";color:black'><o:p> </o:p></span></p><p cla=
ss=3DMsoNormal><span style=3D'font-family:"Century Schoolbook","serif";colo=
r:black'>We have a large amount of data analyzed in spm2 (with flip set to =
0 in the spm_defaults file). We want to move forward and use these images t=
o make single subject models in SPM5/SPM8. I modified the flip to 0 in SPM5=
and I was not able to produce the same results that we produced in SPM2, t=
he left/right was flipped. I am able to say this because we did this analys=
is on a task that has clear left/right motor activation. After changing the=
flip to 1 in SPM5 and remodeling the files, I think the results match with=
SPM2. This is quite confusing because I thought that the flip was supposed=
to be same between versions and I was not able to find anything in the arc=
hives that suggests that the function of flip parameter itself changed betw=
een the two versions. I have read a lot about how changing/constantly modif=
ying the flip would really start to get confusing and quite honestly I have=
been careful with modifying the flip and making sure that I document the c=
hanges, so I know this is not caused by a random mistake I committed. So my=
question really is, did the flip parameter fundamentally change between SP=
M2 and SPM5? If so, to ensure data compatibility between both version what =
flip would be recommended for SPM5. Please note that moving forward we are =
analyzing all the data in SPM8 and in NIFTI format to avoid all the confusi=
on once and for all. But this data that I am talking about is in Analyze fo=
rmat. We used a program to convert our Rec/Par files to analyze format and =
used MRIcro to split the bundle into independent volumes. <o:p></o:p></span=
></p><p class=3DMsoNormal><span style=3D'font-family:"Century Schoolbook","=
serif";color:black'><o:p> </o:p></span></p><p class=3DMsoNormal><span =
style=3D'font-family:"Century Schoolbook","serif";color:black'>Thank you so=
much for your help in this matter. I appreciate your time and patience. <o=
:p></o:p></span></p><p class=3DMsoNormal><span style=3D'font-family:"Centur=
y Schoolbook","serif";color:black'><o:p> </o:p></span></p><p class=3DM=
soNormal><span style=3D'font-family:"Century Schoolbook","serif";color:blac=
k'>Sincerely, <o:p></o:p></span></p><p class=3DMsoNormal><span style=3D'fon=
t-family:"Century Schoolbook","serif";color:black'><o:p> </o:p></span>=
</p><p class=3DMsoNormal><span style=3D'font-family:"Century Schoolbook","s=
erif";color:black'>-a<o:p></o:p></span></p><p class=3DMsoNormal><span style=
=3D'font-family:"Century Schoolbook","serif";color:black'><o:p> </o:p>=
</span></p><p class=3DMsoNormal><span style=3D'font-family:"Century Schoolb=
ook","serif";color:black'><o:p> </o:p></span></p><p class=3DMsoNormal>=
<b><i><span style=3D'font-family:"Century Schoolbook","serif";color:#215868=
'>Aparna. P.Sivapurapu, MS<o:p></o:p></span></i></b></p><p class=3DMsoNorma=
l><b><i><span style=3D'font-size:9.0pt;font-family:"Century Schoolbook","se=
rif";color:#0F243E'>Neuroimaging Analyst<o:p></o:p></span></i></b></p><p cl=
ass=3DMsoNormal><b><i><span style=3D'font-size:9.0pt;font-family:"Century S=
choolbook","serif";color:#0F243E'>Education and Brain Research Lab, <o:p></=
o:p></span></i></b></p><p class=3DMsoNormal><b><i><span style=3D'font-size:=
9.0pt;font-family:"Century Schoolbook","serif";color:#0F243E'>Vanderbilt Un=
iversity, <o:p></o:p></span></i></b></p><p class=3DMsoNormal><b><i><span st=
yle=3D'font-size:9.0pt;font-family:"Century Schoolbook","serif";color:#0F24=
3E'>PMB 328,<o:p></o:p></span></i></b></p><p class=3DMsoNormal><b><i><span =
style=3D'font-size:9.0pt;font-family:"Century Schoolbook","serif";color:#0F=
243E'>230 Appleton Place,<o:p></o:p></span></i></b></p><p class=3DMsoNormal=
><b><i><span style=3D'font-size:9.0pt;font-family:"Century Schoolbook","ser=
if";color:#0F243E'>Nashville, TN </span></i></b><b><i><span style=3D'font-s=
ize:9.0pt;font-family:"Century Schoolbook","serif";color:black'>37203-5721.=
</span></i></b><b><i><span style=3D'font-size:9.0pt;font-family:"Century Sc=
hoolbook","serif";color:#0F243E'><o:p></o:p></span></i></b></p><p class=3DM=
soNormal><b><i><span style=3D'font-size:8.0pt;font-family:"Century Schoolbo=
ok","serif";color:#0F243E'>Phone: 615-936-1151<o:p></o:p></span></i></b></p=
><p class=3DMsoNormal><b><i><span style=3D'font-size:8.0pt;font-family:"Cen=
tury Schoolbook","serif";color:#0F243E'><o:p> </o:p></span></i></b></p=
><p class=3DMsoNormal><b><i><span style=3D'font-size:9.0pt;font-family:"Cen=
tury Schoolbook","serif";color:#0F243E'>Email: <u><a href=3D"a.sivapurapu@v=
anderbilt.edu">[log in to unmask]</a><o:p></o:p></u></span></i></b=
></p><p class=3DMsoNormal><b><i><span style=3D'font-size:9.0pt;font-family:=
"Century Schoolbook","serif";color:#0F243E'>Web: </span></i></b><b><i><u><s=
pan style=3D'font-size:9.0pt;font-family:"Century Schoolbook","serif";color=
:black'><a href=3D"http://kc.vanderbilt.edu/educationandbrainlab/">http://k=
c.vanderbilt.edu/educationandbrainlab/</a></span></u></i></b><b><i><u><span=
style=3D'font-size:9.0pt;font-family:"Century Schoolbook","serif";color:#0=
F243E'><o:p></o:p></span></u></i></b></p><p class=3DMsoNormal><span style=
=3D'color:black'><o:p> </o:p></span></p><p class=3DMsoNormal><span sty=
le=3D'color:black'><o:p> </o:p></span></p><p class=3DMsoNormal><span s=
tyle=3D'font-size:9.0pt;font-family:"Century Schoolbook","serif";color:blac=
k'>Disclaimer:<br><br><o:p></o:p></span></p><p class=3DMsoNormal><span styl=
e=3D'font-size:9.0pt;font-family:"Century Schoolbook","serif";color:black'>=
<o:p> </o:p></span></p><p class=3DMsoNormal><span style=3D'font-size:9=
.0pt;font-family:"Century Schoolbook","serif";color:black'><o:p> </o:p=
></span></p><p class=3DMsoNormal><span style=3D'font-size:9.0pt;font-family=
:"Century Schoolbook","serif";color:black'>The materials in this e-mail are=
private and may contain Protected Health Information. Please note that e-m=
ail is not necessarily confidential or secure. Your use of e-mail constitut=
es your acknowledgment of these confidentiality and security limitations. I=
f you are not the intended recipient, be advised that any unauthorized use,=
disclosure, copying, distribution, or the taking of any action in reliance=
on the contents of this information is strictly prohibited. If you have re=
ceived this e-mail in error, please immediately notify the sender via telep=
hone or return e-mail.<o:p></o:p></span></p><p class=3DMsoNormal><o:p> =
;</o:p></p></div></body></html>=
--_000_C7F70118510C5F44B939884396D9A861056A1E7905ITSHCWNEM02ds_--
=========================================================================
Date: Mon, 9 May 2011 16:23:34 +0100
Reply-To: antonia hamilton <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: antonia hamilton <[log in to unmask]>
Subject: cogent & windows 7
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0016364ee88047ad6004a2d96c78
Message-ID: <[log in to unmask]>
--0016364ee88047ad6004a2d96c78
Content-Type: text/plain; charset=ISO-8859-1
Hi,
I know this isn't an SPM question, but does anyone use Cogent with Matlab
7.10 and Windows 7? Does it all run smoothly or are there any issues I
should be aware of before upgrading from Windows XP?
Thanks,
Antonia
--0016364ee88047ad6004a2d96c78
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Hi,<div><br></div><div>I know this isn't an SPM question, but does anyo=
ne use Cogent with Matlab 7.10 and Windows 7? =A0Does it all run smoothly o=
r are there any issues I should be aware of before upgrading from Windows X=
P?</div>
<div><br></div><div>Thanks,</div><div><br></div><div>Antonia</div>
--0016364ee88047ad6004a2d96c78--
=========================================================================
Date: Mon, 9 May 2011 15:31:37 +0000
Reply-To: "Chait, Maria" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Chait, Maria" <[log in to unmask]>
Subject: Re: cogent & windows 7
Comments: To: antonia hamilton <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Content-Type: multipart/alternative;
boundary="_000_3BA3DF582C0B7542AE0CB625F0119AB80B0B3012DB3PRD0104MB103_"
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
--_000_3BA3DF582C0B7542AE0CB625F0119AB80B0B3012DB3PRD0104MB103_
Content-Type: text/plain; charset="us-ascii"
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Hi Antonia,
Cogent runs fine, *HOWEVER* if you care about stimulus timing (particularly=
auditory timing) then do not switch from windows XP.
We found that under windows 7, COGENT stimulus timing has a large jitter (a=
bout 20 ms), which is quite a big problem.
--Maria
Maria Chait PhD
[log in to unmask]<mailto:[log in to unmask]>
Research Fellow
UCL Ear Institute
332 Gray's Inn Road
London WC1X 8EE
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] On B=
ehalf Of antonia hamilton
Sent: 09 May 2011 16:24
To: [log in to unmask]
Subject: [SPM] cogent & windows 7
Hi,
I know this isn't an SPM question, but does anyone use Cogent with Matlab 7=
.10 and Windows 7? Does it all run smoothly or are there any issues I shou=
ld be aware of before upgrading from Windows XP?
Thanks,
Antonia
--_000_3BA3DF582C0B7542AE0CB625F0119AB80B0B3012DB3PRD0104MB103_
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//www.w3.org/TR/REC-html40">
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<div class=3D"WordSection1">
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";color:#1F497D">Hi Antonia,<o:p></o:p></s=
pan></p>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";color:#1F497D">Cogent runs fine, *<b>HOW=
EVER</b>* if you care about stimulus timing (particularly auditory timing) =
then do not switch from windows XP.<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";color:#1F497D">We found that under windo=
ws 7, COGENT stimulus timing has a large jitter (about 20 ms), which is qui=
te a big problem.<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";color:#1F497D"><o:p> </o:p></span><=
/p>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";color:#1F497D">--Maria<o:p></o:p></span>=
</p>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";color:#1F497D"><o:p> </o:p></span><=
/p>
<p class=3D"MsoNormal"><span lang=3D"FR" style=3D"font-size:10.5pt;font-fam=
ily:Consolas;color:#1F497D">Maria Chait PhD<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:10.5pt;font-family:Consolas=
;color:#1F497D"><a href=3D"mailto:[log in to unmask]"><span lang=3D"FR" styl=
e=3D"color:blue">[log in to unmask]</span></a></span><span lang=3D"FR" style=
=3D"font-size:10.5pt;font-family:Consolas;color:#1F497D"><o:p></o:p></span>=
</p>
<p class=3D"MsoNormal"><span lang=3D"FR" style=3D"font-size:10.5pt;font-fam=
ily:Consolas;color:#1F497D"><o:p> </o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:10.5pt;font-family:Consolas=
;color:#1F497D">Research Fellow<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:10.5pt;font-family:Consolas=
;color:#1F497D">UCL Ear Institute<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:10.5pt;font-family:Consolas=
;color:#1F497D">332 Gray's Inn Road<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";color:#1F497D">London WC1X 8EE</span><sp=
an style=3D"font-size:11.0pt;font-family:"Calibri","sans-ser=
if";color:#1F497D"><o:p></o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";color:#1F497D"><o:p> </o:p></span><=
/p>
<p class=3D"MsoNormal"><b><span lang=3D"EN-US" style=3D"font-size:10.0pt;fo=
nt-family:"Tahoma","sans-serif"">From:</span></b><span =
lang=3D"EN-US" style=3D"font-size:10.0pt;font-family:"Tahoma",&qu=
ot;sans-serif""> SPM (Statistical Parametric Mapping) [mailto:SPM@JISC=
MAIL.AC.UK]
<b>On Behalf Of </b>antonia hamilton<br>
<b>Sent:</b> 09 May 2011 16:24<br>
<b>To:</b> [log in to unmask]<br>
<b>Subject:</b> [SPM] cogent & windows 7<o:p></o:p></span></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">Hi,<o:p></o:p></p>
<div>
<p class=3D"MsoNormal"><o:p> </o:p></p>
</div>
<div>
<p class=3D"MsoNormal">I know this isn't an SPM question, but does anyone u=
se Cogent with Matlab 7.10 and Windows 7? Does it all run smoothly or=
are there any issues I should be aware of before upgrading from Windows XP=
?<o:p></o:p></p>
</div>
<div>
<p class=3D"MsoNormal"><o:p> </o:p></p>
</div>
<div>
<p class=3D"MsoNormal">Thanks,<o:p></o:p></p>
</div>
<div>
<p class=3D"MsoNormal"><o:p> </o:p></p>
</div>
<div>
<p class=3D"MsoNormal">Antonia<o:p></o:p></p>
</div>
</div>
</body>
</html>
--_000_3BA3DF582C0B7542AE0CB625F0119AB80B0B3012DB3PRD0104MB103_--
=========================================================================
Date: Mon, 9 May 2011 11:44:42 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Which contrast to adjust for?
Comments: To: Bob Spunt <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=001517478582cc0a5104a2d9b7b8
Message-ID: <[log in to unmask]>
--001517478582cc0a5104a2d9b7b8
Content-Type: text/plain; charset=ISO-8859-1
See inline responses below.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Sat, May 7, 2011 at 4:07 PM, Bob Spunt <[log in to unmask]> wrote:
> This topic has been discussed on numerous occasions on the listserv,
> but I'm still unsure about a few things. When extracting a VOI
> timecourse (e.g., for a PPI analysis):
>
> 1. Can adjusting for different contrasts produce large differences in
> results? In other words, is the decision important? And if so, why
> don't folks typically report this in empirical articles using PPI?
>
I'm not sure anyone has looked at this closely enough.
>
> 2. Is there ever a case in which it is desirable to adjust for a
> t-test contrast (e.g., the comparison of only two conditions)? In
> spm_regions the default is to only allow adjustment for F-contrasts,
> but of course adjustment can be made for t-contrasts if desired.
>
No. Even in the case of two conditions, you'd still want an F-test with 2
rows.
>
> 3. My understanding is that the F-test omnibus (coding for all effects
> of interest) is the favored option for adjustment. But there is some
> ambiguity in what "all effects of interest" refers to. Should all
> effects expected to relate to neural activity be included (so that
> only motion regressors/constants are removed), or only effects "of
> interest"? For example, if I've modeled response time and skipped
> trials as covariates of no interest, should these be included in the
> omnibus (because they are expected to relate to neural activity, not
> to artifactual changes in signal intensity)?
>
Effects of interest, in my conceptualization, means any signal related to
neural activity. I believe that my gPPI code, uses all columns identified as
being associated with a task. The code can be found at (
http://www.martinos.org/~mclaren/ftp/Utilities_DGM)
>
> Many thanks in advance for any tips.
>
> Cheers,
>
> Bob Spunt
> Doctoral Student
> Department of Psychology
> University of California, Los Angeles
>
--001517478582cc0a5104a2d9b7b8
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
See inline responses below.<br clear=3D"all"><br>Best Regards, Donald McLar=
en<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D<br>D.G. McLaren, =
Ph.D.<br>Postdoctoral Research Fellow, GRECC, Bedford VA<br>Research Fellow=
, Department of Neurology, Massachusetts General Hospital and Harvard Medic=
al School<br>
Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which may =
contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED=
and which is intended only for the use of the individual or entity named a=
bove. If the reader of the e-mail is not the intended recipient or the empl=
oyee or agent responsible for delivering it to the intended recipient, you =
are hereby notified that you are in possession of confidential and privileg=
ed information. Any unauthorized use, disclosure, copying or the taking of =
any action in reliance on the contents of this information is strictly proh=
ibited and may be unlawful. If you have received this e-mail unintentionall=
y, please immediately notify the sender via telephone at (773) 406-2464 or =
email.<br>
<br><br><div class=3D"gmail_quote">On Sat, May 7, 2011 at 4:07 PM, Bob Spun=
t <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">bobspunt@gmai=
l.com</a>></span> wrote:<br><blockquote class=3D"gmail_quote" style=3D"m=
argin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); paddin=
g-left: 1ex;">
This topic has been discussed on numerous occasions on the listserv,<br>
but I'm still unsure about a few things. When extracting a VOI<br>
timecourse (e.g., for a PPI analysis):<br>
<br>
1. Can adjusting for different contrasts produce large differences in<br>
results? In other words, is the decision important? And if so, why<br>
don't folks typically report this in empirical articles using PPI?<br><=
/blockquote><div><br>I'm not sure anyone has looked at this closely eno=
ugh.<br><br>=A0</div><blockquote class=3D"gmail_quote" style=3D"margin: 0pt=
0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1e=
x;">
<br>
2. Is there ever a case in which it is desirable to adjust for a<br>
t-test contrast (e.g., the comparison of only two conditions)? In<br>
spm_regions the default is to only allow adjustment for F-contrasts,<br>
but of course adjustment can be made for t-contrasts if desired.<br></block=
quote><div><br>No. Even in the case of two conditions, you'd still want=
an F-test with 2 rows.<br>=A0</div><blockquote class=3D"gmail_quote" style=
=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); p=
adding-left: 1ex;">
<br>
3. My understanding is that the F-test omnibus (coding for all effects<br>
of interest) is the favored option for adjustment. But there is some<br>
ambiguity in what "all effects of interest" refers to. Should all=
<br>
effects expected to relate to neural activity be included (so that<br>
only motion regressors/constants are removed), or only effects "of<br>
interest"? For example, if I've modeled response time and skipped<=
br>
trials as covariates of no interest, should these be included in the<br>
omnibus (because they are expected to relate to neural activity, not<br>
to artifactual changes in signal intensity)?<br></blockquote><div><br>Effec=
ts of interest, in my conceptualization, means any signal related to neural=
activity. I believe that my gPPI code, uses all columns identified as bein=
g associated with a task. The code can be found at (<a href=3D"http://www.m=
artinos.org/~mclaren/ftp/Utilities_DGM">http://www.martinos.org/~mclaren/ft=
p/Utilities_DGM</a>)<br>
=A0</div><blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8=
ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
<br>
Many thanks in advance for any tips.<br>
<br>
Cheers,<br>
<font color=3D"#888888"><br>
Bob Spunt<br>
Doctoral Student<br>
Department of Psychology<br>
University of California, Los Angeles<br>
</font></blockquote></div><br>
--001517478582cc0a5104a2d9b7b8--
=========================================================================
Date: Mon, 9 May 2011 09:19:15 -0700
Reply-To: Bob Spunt <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Bob Spunt <[log in to unmask]>
Subject: Re: Which contrast to adjust for?
Comments: To: "MCLAREN, Donald" <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Many thanks... as a quick follow-up to the question of "Does the
adjustment decision matter?", consider the case of a PPI comparing two
conditions, A > B. If one were to adjust using either the contrasts A
> Baseline or A > B, this would bias the VOI timecourse to look more
like the timecourse of A, which presumably would spuriously increase
the correlation among the VOI and regions of the brain associated with
A. Is this reasoning correct?
On Mon, May 9, 2011 at 8:44 AM, MCLAREN, Donald
<[log in to unmask]> wrote:
> See inline responses below.
>
> Best Regards, Donald McLaren
> =================
> D.G. McLaren, Ph.D.
> Postdoctoral Research Fellow, GRECC, Bedford VA
> Research Fellow, Department of Neurology, Massachusetts General Hospital and
> Harvard Medical School
> Office: (773) 406-2464
> =====================
> This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
> HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
> intended only for the use of the individual or entity named above. If the
> reader of the e-mail is not the intended recipient or the employee or agent
> responsible for delivering it to the intended recipient, you are hereby
> notified that you are in possession of confidential and privileged
> information. Any unauthorized use, disclosure, copying or the taking of any
> action in reliance on the contents of this information is strictly
> prohibited and may be unlawful. If you have received this e-mail
> unintentionally, please immediately notify the sender via telephone at (773)
> 406-2464 or email.
>
>
> On Sat, May 7, 2011 at 4:07 PM, Bob Spunt <[log in to unmask]> wrote:
>>
>> This topic has been discussed on numerous occasions on the listserv,
>> but I'm still unsure about a few things. When extracting a VOI
>> timecourse (e.g., for a PPI analysis):
>>
>> 1. Can adjusting for different contrasts produce large differences in
>> results? In other words, is the decision important? And if so, why
>> don't folks typically report this in empirical articles using PPI?
>
> I'm not sure anyone has looked at this closely enough.
>
>
>>
>> 2. Is there ever a case in which it is desirable to adjust for a
>> t-test contrast (e.g., the comparison of only two conditions)? In
>> spm_regions the default is to only allow adjustment for F-contrasts,
>> but of course adjustment can be made for t-contrasts if desired.
>
> No. Even in the case of two conditions, you'd still want an F-test with 2
> rows.
>
>>
>> 3. My understanding is that the F-test omnibus (coding for all effects
>> of interest) is the favored option for adjustment. But there is some
>> ambiguity in what "all effects of interest" refers to. Should all
>> effects expected to relate to neural activity be included (so that
>> only motion regressors/constants are removed), or only effects "of
>> interest"? For example, if I've modeled response time and skipped
>> trials as covariates of no interest, should these be included in the
>> omnibus (because they are expected to relate to neural activity, not
>> to artifactual changes in signal intensity)?
>
> Effects of interest, in my conceptualization, means any signal related to
> neural activity. I believe that my gPPI code, uses all columns identified as
> being associated with a task. The code can be found at
> (http://www.martinos.org/~mclaren/ftp/Utilities_DGM)
>
>>
>> Many thanks in advance for any tips.
>>
>> Cheers,
>>
>> Bob Spunt
>> Doctoral Student
>> Department of Psychology
>> University of California, Los Angeles
>
>
=========================================================================
Date: Mon, 9 May 2011 18:59:40 +0100
Reply-To: Ryan Herringa <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Ryan Herringa <[log in to unmask]>
Subject: Ancova in SPM8
Mime-Version: 1.0
Content-Type: multipart/mixed;
boundary="part-zfL2Odt10R1J23Sy3AcHFB3i8yAWmVFRlLCZBCMgAJnEc"
Message-ID: <[log in to unmask]>
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Hi all,
I haven't seen any replies on this yet, so I thought I would try posting =
again:
I am trying to analyze the effect of 2 covariates (both continuous variab=
les) on 4 different emotion conditions in spm8. I have tried setting thi=
s up in the 2nd level analysis, as full factorial, using one factor with =
4 levels, then specifying my 2 covariates of interest. I had to repeat e=
ach covariate 4 times to match each emotion condition within the same sub=
ject.
For each covariate, there is the option to create an interaction term wit=
h the factor (emotion). In design1, I selected no for this option. In d=
esign2, I selected yes which seems more appropriate.
Is this the correct way to essentially set up an Ancova in spm, or does a=
nyone have a better suggestion? Also, how would you set up the contrast =
manager to look at the effect of each covariate on each condition?
Thanks!
Ryan Herringa, MD, PhD
University of Pittsburgh
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=========================================================================
Date: Mon, 9 May 2011 19:32:25 +0100
Reply-To: "Stephen J. Fromm" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Stephen J. Fromm" <[log in to unmask]>
Subject: Re: Weird results from partial correlation analysis
Comments: To: Anne Rehme <[log in to unmask]>
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
I'll restate this to ensure we're addressing the same issue:
There's regressors A and B which themselves are correlated. The result o=
f the regression is that neither A nor B show an effect. Yet when A is c=
orrected for B or vice versa, then there is an effect.
This is known issue when regressors are confounded; the explanation has t=
o do with the nature of the t-test for betas or contrasts. A nice exposi=
tion of the issue can be found in Andrade et al. (=E2=80=9CAmbiguous Resu=
lts in Functional Neuroimaging Data Analysis Due to Covariate Correlation=
=E2=80=9D, NeuroImage 10, 483=E2=80=93486 (1999)), at e.g. http://people.=
hnl.bcm.tmc.edu/jli/reference/209.pdf
=20
A more general exposition is given in _ Applied Linear Statistical Models=
_, Neter et al., 4th ed. in the case of correlated explanatory variables.=
In summary, if you do a t-test on each beta separately, you might find =
none of them significant, but if you test all of them together with an F-=
test, they can be highly significant (together).
=20
=========================================================================
Date: Mon, 9 May 2011 14:26:10 -0400
Reply-To: Franziska Korb <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Franziska Korb <[log in to unmask]>
Subject: spatial FWHM values for AFNI's 3dClustSim
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Content-Transfer-Encoding: 7bit
Message-ID: <[log in to unmask]>
Dear SPM/fMRI experts,
On my SPM8 T-maps I am performing cluster-size thresholding using
3dClustSim of the AFNI package (formerly known as AlphaSim), which
requires an estimation of the correlation of the voxels in a 3D dataset.
I use a tool of the same package (3dFWHMx) to estimate the degree of
voxel spatial correlation, based on an algorithm by Forman and
colleagues (http://onlinelibrary.wiley.com/doi/10.1002/mrm.1910330508/pdf)
However, a colleague uses a different approach by extracting the FWHM
values for the 3 axes from the SPM.mat file - SPM.xVol.FWHM.
I tried both methods and noticed that they produce different results -
here is an example for one contrast where the values don't seem to
differ that much, but sometimes the differences are greater than 1.0:
*** 3dFWHMx:
FWHMx = 9.82782
FWHMy = 10.0744
FWHMz = 9.31861
*** SPM.xVol.FWHM:
FWHMx = 10.2832
FWHMy = 10.3741
FWHMz = 9.4135
My questions are:
(1) Do the values in the SPM.mat file even reflect the voxel spatial
correlation of the contrast/the T-map?
(2) If so, what algorithm is their estimation based on (or: are they
based on a different calculation than Forman et al.)? and
(3) What would be the recommended method?
Last but not least:
(4) Is there an (SPM-based) alternative method for cluster-size
thresholding?
Thanks in advance!
All the best,
Franziska
--
Franziska M. Korb, Ph.D.
Postdoctoral Associate (Egner Lab)
Center for Cognitive Neuroscience
LSRC Building, Room C03D, Research Dr
Box 90999
Duke University
Durham, NC 27708
phone: ++1-919-684.1034
http://sites.google.com/site/egnerlab/
=========================================================================
Date: Mon, 9 May 2011 19:48:45 +0100
Reply-To: "Stephen J. Fromm" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Stephen J. Fromm" <[log in to unmask]>
Subject: Re: Ancova in SPM8
Comments: To: Ryan Herringa <[log in to unmask]>
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
I'm assuming that by "I had to repeat each covariate 4 times to match eac=
h emotion condition within the same subject" you mean that the covariates=
vary across subjects but not across conditions.
A comment: it looks like you don't have subject effects modeled. The go=
od thing is that if did model them, it would be tricky to assess the effe=
cts of the covariates (because they're constant on a given subject), thou=
gh maybe you could do so using the ideas of the Glascher/Gitelman monogra=
ph people refer to on this list. The bad thing is that you lose power by=
not modeling subject effects. Though if the scans you brought to the se=
cond (group) level are already differences at the first (subject) level, =
then one could argue the subject effects have already been subtracted out=
, I believe.
It seems like design 1 models only the main effect of each covariate, whe=
reas design 2 models the condition X covariate interaction. If you reall=
y want to look at the interaction, and believe it's not insignificant, th=
en you should use model 2. The one disadvantage of model 2 is that it's =
difficult to consider the main effect of condition alone.
=========================================================================
Date: Mon, 9 May 2011 15:00:46 -0400
Reply-To: adams adams <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: adams adams <[log in to unmask]>
Subject: Contrast
Comments: To: [log in to unmask]
In-Reply-To: <[log in to unmask]>
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Message-ID: <[log in to unmask]>
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Hi=2C
Can Plz confirm if my contrast is correct=2C Thank you all
=
A Positive B Positive C Positive D Positive A Neutral B=
Neutral C Neutral D neutral=20
[Positive((C+B) vs (A+D))] VS [Neutral((C+B) vs (A+D)) ] -1 =
1 1 -1 =
1 -1 -1 1=20
=20
=
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<body class=3D'hmmessage'>
<br>Hi=2C<br>Can Plz confirm if my contrast is correct=2C Thank you all<br>=
<br><br> =3B =3B =3B =3B =3B =3B =3B =3B&nb=
sp=3B =3B =3B =3B =3B =3B =3B =3B =3B =
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--_197d4f9a-bc74-4c62-99b8-e98e88e54f40_--
=========================================================================
Date: Mon, 9 May 2011 20:51:10 +0100
Reply-To: Rebecca Ray <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Rebecca Ray <[log in to unmask]>
Subject: Dartel Difficulty
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I have created a template and flow field for each subject. I am having d=
ifficulty normalizing the functionals in MNI space. It is cutting off the=
backs of the brains. Any thoughts?
Becky
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--part-kQZHzDBmqfkAYBsE4CH1siAx3D37niOTmm1JpWdjnZTux--
=========================================================================
Date: Mon, 9 May 2011 20:58:04 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: Dartel Difficulty
Comments: To: Rebecca Ray <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
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Message-ID: <[log in to unmask]>
You should not have a template for each subject. Instead, there
should be a single template for your whole group of subjects. The
chapter in the SPM8 manual on Using Dartel may be helpful here.
Best regards,
-John
On 9 May 2011 20:51, Rebecca Ray <[log in to unmask]> wrote:
> I have created a template and flow field for each subject. =A0I am having=
difficulty normalizing the functionals in MNI space. It is cutting off the=
backs of the brains. =A0Any thoughts?
>
> Becky
>
>
>
=========================================================================
Date: Mon, 9 May 2011 21:11:27 +0100
Reply-To: Ryan Herringa <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Ryan Herringa <[log in to unmask]>
Subject: Re: Ancova in SPM8
Comments: To: "Stephen J. Fromm" <[log in to unmask]>
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
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Message-ID: <[log in to unmask]>
Thanks Stephen,
Your first assumption is correct, that the covariates vary across subject=
s but not condition. (not that I explained it terribly well)
The second level scans represent intra-subject contrasts (emotion vs. sha=
pe) so I think you are right that the subject effects should have been su=
btracted out.
Thanks for helping to clarify the models - sounds like there is some util=
ity in both which I'll have to give some more thought.
For model 2, am I correct in assuming that if I select either a single co=
ndition, or a single covariate interaction term in the contrast manager, =
that I will be looking at the condition x covariate interaction?
=========================================================================
Date: Mon, 9 May 2011 22:18:11 +0200
Reply-To: Alexander Hammers <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Alexander Hammers <[log in to unmask]>
Subject: Re: flipped images
Comments: To: Donald MCLAREN <[log in to unmask]>,
Emilia Lentini <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Mime-Version: 1.0 (Apple Message framework v1084)
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--Apple-Mail-215-247577432
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charset=windows-1252
Dear Emilia and Donald,
Just to add to the previous comments, the creation of the symmetrical =
template is important, but can be tricky if the midline is a bit offset. =
Some practical tips are in
Didelot A, Maugui=E8re F, Redout=E9 J, Bouvard S, Lothe A, Reilhac A, =
Hammers A, Costes N, Ryvlin P. Voxel based analysis of asymmetry index =
maps increases the specificity of [18F]MPPF PET abnormalities for =
localizing the epileptogenic zone in Temporal Lobe Epilepsies. J Nucl =
Med, 2010; 51(11):1732-9.
All the best,
Alexander
PS: Please note that there is of course no "pre"frontal gyrus ;-)...
-----------------------------
Alexander Hammers, MD PhD
Chair in Functional Neuroimaging
Neurodis Foundation
http://www.fondation-neurodis.org/
Postal Address:
CERMEP =96 Imagerie du Vivant
H=F4pital Neurologique Pierre Wertheimer
59 Boulevard Pinel, 69003 Lyon, France
Telephone +33-(0)4-72 68 86 34
Fax +33-(0)4-72 68 86 10
Email =
[log in to unmask];[log in to unmask]
---------------------------------
Other affiliations:
Visiting Reader; Honorary Consultant Neurologist
Division of Neuroscience and Mental Health, Faculty of Medicine
Imperial College London, UK
---------------------------------
Honorary Reader in Neurology; Honorary Consultant Neurologist
Department of Clinical and Experimental Epilepsy
National Hospital for Neurology and Neurosurgery/ Institute of =
Neurology, University College London, UK
On 6 May 2011, at 17:54, MCLAREN, Donald wrote:
> I'd recommend the following article:
> Good et al. Cerebral asymmetry and the effects of sex and handedness
> on brain structure: a voxel-based morphometric analysis of 465 normal
> adult human brains. 2001
>=20
> Briefly,
> You segment and normalize your brains, then you flip them the brains
> and the segments, then you average all the brains and segments (so 2
> times as many images). Now you will have a customized set of tissue
> priors. Now, flip the original images. Next, take the flipped and
> unflipped images and normalize them to the new template. Now you can
> do the statistics.
>=20
> Best Regards, Donald McLaren
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> D.G. McLaren, Ph.D.
> Postdoctoral Research Fellow, GRECC, Bedford VA
> Research Fellow, Department of Neurology, Massachusetts General
> Hospital and Harvard Medical School
> Office: (773) 406-2464
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> This e-mail contains CONFIDENTIAL INFORMATION which may contain
> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
> and which is intended only for the use of the individual or entity
> named above. If the reader of the e-mail is not the intended recipient
> or the employee or agent responsible for delivering it to the intended
> recipient, you are hereby notified that you are in possession of
> confidential and privileged information. Any unauthorized use,
> disclosure, copying or the taking of any action in reliance on the
> contents of this information is strictly prohibited and may be
> unlawful. If you have received this e-mail unintentionally, please
> immediately notify the sender via telephone at (773) 406-2464 or
> email.
>=20
>=20
>=20
> On Fri, May 6, 2011 at 6:39 AM, Emilia Lentini =
<[log in to unmask]> wrote:
>>=20
>> Thank you!
>>=20
>> I want to evaluate regional asymmetries in grey and white matter, by =
using
>> flipped and non-flipped images in the same analysis e.g If =
Rhemisphere pre
>> frontal gyrus are different from Lhemisphere pre frontal gyrus.
>> How should I best set up the analysis?
>> Should I adjust for different sized hemispheres?
>> Do I need to normalize the flipped images in any other way than the
>> non-flipped images?
>> Best regards
>> Emilia
>> 2011/5/5 Michael Erb <[log in to unmask]>
>>>=20
>>> Am 05.05.2011 14:51, schrieb Emilia Lentini:
>>>>=20
>>>> Hi.
>>>>=20
>>>> I would like to do a full-factorial analysis with both flipped
>>>> (right-left) and non-flipped images.
>>>>=20
>>>> To flip the images I use:
>>>> Display --> resize {x}: -1 and then reorient images..
>>>>=20
>>>> When I try to run the analysis I get following error:
>>>>=20
>>>> "Error running job: Error using =3D=3D> spm_check_orientations"
>>>>=20
>>>>=20
>>>> How can I correct for this error?
>>>=20
>>> You have to reslice the images e.g. with Coregister(Reslice).
>>> Image Defining Space: a non-flipped image
>>> Images to Reslice: your flipped images
>>> afterwards you can delete your flipped images and use the resliced =
r*
>>> images.
>>>=20
>>> Regards,
>>> Michael.
>>>>=20
>>>> Can I flip the images in any other way?
>>>>=20
>>>>=20
>>>> Best regards
>>>> Emilia
>>>=20
>>> --
>>> <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
>>> Dr. Michael Erb
>>> Sektion f. experimentelle Kernspinresonanz des ZNS
>>> Abteilung Neuroradiologie, Universitaetsklinikum
>>> Hoppe-Seyler_Str. 3, D-72076 Tuebingen
>>> Tel.: +49(0)7071/2987753 priv. +49(0)7071/61559
>>> Fax.: +49(0)7071/294371
>>> e-mail: <[log in to unmask]>
>>> www: http://www.medizin.uni-tuebingen.de/nrad/sektion/
>>> <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
>>=20
>>=20
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charset=windows-1252
<html><head></head><body style=3D"word-wrap: break-word; =
-webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">Dear =
Emilia and Donald,<div><br></div><div><br></div><div>Just to add to the =
previous comments, the creation of the symmetrical template is =
important, but can be tricky if the midline is a bit offset. Some =
practical tips are in</div><div><font class=3D"Apple-style-span" =
face=3D"Arial"><br></font></div><div><!--StartFragment--><span =
lang=3D"EN-GB" style=3D"color: black; "><font class=3D"Apple-style-span" =
face=3D"Arial">Didelot A, Maugui=E8re F, Redout=E9 J, Bouvard S, Lothe
A, Reilhac A, Hammers A, Costes N, Ryvlin P. Voxel based analysis of
asymmetry index maps increases the specificity of [</font><sup><font =
class=3D"Apple-style-span" face=3D"Arial" size=3D"3"><span =
class=3D"Apple-style-span" style=3D"font-size: =
12px;">18</span></font></sup><font class=3D"Apple-style-span" =
face=3D"Arial">F]MPPF PET
abnormalities for localizing the epileptogenic zone in Temporal Lobe
Epilepsies. J Nucl Med, 2010; =
51(11):1732-9.</font></span><!--EndFragment--><font =
class=3D"Apple-style-span" face=3D"Arial">
</font></div><div><span lang=3D"EN-GB" style=3D"color: black; "><font =
class=3D"Apple-style-span" =
face=3D"Arial"><br></font></span></div><div><span lang=3D"EN-GB" =
style=3D"color: black; "><font class=3D"Apple-style-span" =
face=3D"Arial">All the best,</font></span></div><div><span lang=3D"EN-GB" =
style=3D"color: black; "><font class=3D"Apple-style-span" =
face=3D"Arial"><br></font></span></div><div><span lang=3D"EN-GB" =
style=3D"color: black; "><font class=3D"Apple-style-span" =
face=3D"Arial">Alexander</font></span></div><div><span lang=3D"EN-GB" =
style=3D"color: black; "><font class=3D"Apple-style-span" =
face=3D"Arial">PS: Please note that there is of course no "pre"frontal =
gyrus ;-)...</font></span></div><div><span lang=3D"EN-GB" style=3D"color: =
black; "><font class=3D"Apple-style-span" =
face=3D"Arial"><br></font></span></div><div>-----------------------------<=
/div><div><div><span class=3D"Apple-style-span" style=3D"border-collapse: =
separate; color: rgb(0, 0, 0); font-family: Helvetica; font-style: =
normal; font-variant: normal; font-weight: normal; letter-spacing: =
normal; line-height: normal; orphans: 2; text-align: auto; text-indent: =
0px; text-transform: none; white-space: normal; widows: 2; word-spacing: =
0px; -webkit-border-horizontal-spacing: 0px; =
-webkit-border-vertical-spacing: 0px; =
-webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: =
auto; -webkit-text-stroke-width: 0px; font-size: medium; =
"><div><div>Alexander Hammers, MD =
PhD</div><div><br></div></div><br><span></span><span><img height=3D"58" =
width=3D"176" id=3D"8f4ecb9e-c906-453f-a907-beada75383af" =
apple-width=3D"yes" apple-height=3D"yes" =
src=3D"cid:3335947574_1343002"></span><span class=3D"Apple-style-span" =
style=3D"border-collapse: separate; color: rgb(0, 0, 0); font-family: =
Helvetica; font-style: normal; font-variant: normal; font-weight: =
normal; letter-spacing: normal; line-height: normal; orphans: 2; =
text-align: auto; text-indent: 0px; text-transform: none; white-space: =
normal; widows: 2; word-spacing: 0px; -webkit-border-horizontal-spacing: =
0px; -webkit-border-vertical-spacing: 0px; =
-webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: =
auto; -webkit-text-stroke-width: 0px; font-size: medium; "><div><br =
class=3D"Apple-interchange-newline"><br><br>Chair in Functional =
Neuroimaging<br>Neurodis Foundation<br><a =
href=3D"http://www.fondation-neurodis.org/">http://www.fondation-neurodis.=
org/</a><br>Postal Address:<br>CERMEP =96 Imagerie du Vivant<br>H=F4pital =
Neurologique Pierre Wertheimer<br>59 Boulevard Pinel, 69003 =
Lyon, France<br><br>Telephone<span class=3D"Apple-tab-span" =
style=3D"white-space: pre; "> </span>+33-(0)4-72 68 86 34<br>Fax<span =
class=3D"Apple-tab-span" style=3D"white-space: pre; "> =
</span>+33-(0)4-72 68 86 10<br>Email<span class=3D"Apple-tab-span" =
style=3D"white-space: pre; "> =
</span>[log in to unmask];alexander.hammers@imperial=
.ac.uk<br>---------------------------------<br>Other =
affiliations:<br><br>Visiting Reader; Honorary Consultant =
Neurologist<br>Division of Neuroscience and Mental Health, Faculty of =
Medicine<br>Imperial College London, =
UK<br>---------------------------------<br>Honorary Reader in Neurology; =
Honorary Consultant Neurologist<br>Department of Clinical and =
Experimental Epilepsy<br>National Hospital for Neurology and =
Neurosurgery/ Institute of Neurology, University College London, =
UK<div><br></div></div><br><br></span>
</span></div>
<br><div><div>On 6 May 2011, at 17:54, MCLAREN, Donald wrote:</div><br =
class=3D"Apple-interchange-newline"><blockquote type=3D"cite"><div>I'd =
recommend the following article:<br>Good et al. Cerebral asymmetry and =
the effects of sex and handedness<br>on brain structure: a voxel-based =
morphometric analysis of 465 normal<br>adult human brains. =
2001<br><br>Briefly,<br>You segment and normalize your brains, then you =
flip them the brains<br>and the segments, then you average all the =
brains and segments (so 2<br>times as many images). Now you will have a =
customized set of tissue<br>priors. Now, flip the original images. Next, =
take the flipped and<br>unflipped images and normalize them to the new =
template. Now you can<br>do the statistics.<br><br>Best Regards, Donald =
McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D<br>D.G. =
McLaren, Ph.D.<br>Postdoctoral Research Fellow, GRECC, Bedford =
VA<br>Research Fellow, Department of Neurology, Massachusetts =
General<br>Hospital and Harvard Medical School<br>Office: (773) =
406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
<br>This e-mail contains CONFIDENTIAL INFORMATION which may =
contain<br>PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY =
PRIVILEGED<br>and which is intended only for the use of the individual =
or entity<br>named above. If the reader of the e-mail is not the =
intended recipient<br>or the employee or agent responsible for =
delivering it to the intended<br>recipient, you are hereby notified that =
you are in possession of<br>confidential and privileged information. Any =
unauthorized use,<br>disclosure, copying or the taking of any action in =
reliance on the<br>contents of this information is strictly prohibited =
and may be<br>unlawful. If you have received this e-mail =
unintentionally, please<br>immediately notify the sender via telephone =
at (773) 406-2464 or<br>email.<br><br><br><br>On Fri, May 6, 2011 at =
6:39 AM, Emilia Lentini <<a =
href=3D"mailto:[log in to unmask]">[log in to unmask]</a>> =
wrote:<br><blockquote type=3D"cite"><br></blockquote><blockquote =
type=3D"cite">Thank you!<br></blockquote><blockquote =
type=3D"cite"><br></blockquote><blockquote type=3D"cite">I want to =
evaluate regional asymmetries in grey and white matter, by =
using<br></blockquote><blockquote type=3D"cite">flipped and non-flipped =
images in the same analysis e.g If Rhemisphere =
pre<br></blockquote><blockquote type=3D"cite">frontal gyrus are =
different from Lhemisphere pre frontal =
gyrus.<br></blockquote><blockquote type=3D"cite">How should I best set =
up the analysis?<br></blockquote><blockquote type=3D"cite">Should I =
adjust for different sized hemispheres?<br></blockquote><blockquote =
type=3D"cite">Do I need to normalize the flipped images in any other way =
than the<br></blockquote><blockquote type=3D"cite">non-flipped =
images?<br></blockquote><blockquote type=3D"cite">Best =
regards<br></blockquote><blockquote =
type=3D"cite">Emilia<br></blockquote><blockquote type=3D"cite">2011/5/5 =
Michael Erb <<a =
href=3D"mailto:[log in to unmask]">[log in to unmask]
ngen.de</a>><br></blockquote><blockquote type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite">Am 05.05.2011 14:51, schrieb =
Emilia Lentini:<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote =
type=3D"cite">Hi.<br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote type=3D"cite">I =
would like to do a full-factorial analysis with both =
flipped<br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote =
type=3D"cite">(right-left) and non-flipped =
images.<br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote type=3D"cite">To =
flip the images I =
use:<br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote type=3D"cite">Display =
--> resize {x}: -1 and then reorient =
images..<br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote type=3D"cite">When I =
try to run the analysis I get following =
error:<br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote type=3D"cite">"Error =
running job: Error using =3D=3D> =
spm_check_orientations"<br></blockquote></blockquote></blockquote><blockqu=
ote type=3D"cite"><blockquote type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote type=3D"cite">How =
can I correct for this =
error?<br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite">You have to reslice the images =
e.g. with Coregister(Reslice).<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite">Image Defining Space: a =
non-flipped image<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite">Images to Reslice: your flipped =
images<br></blockquote></blockquote><blockquote type=3D"cite"><blockquote =
type=3D"cite">afterwards you can delete your flipped images and use the =
resliced r*<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote =
type=3D"cite">images.<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote =
type=3D"cite">Regards,<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote =
type=3D"cite">Michael.<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote type=3D"cite">Can I =
flip the images in any other =
way?<br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote type=3D"cite">Best =
regards<br></blockquote></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite"><blockquote =
type=3D"cite">Emilia<br></blockquote></blockquote></blockquote><blockquote=
type=3D"cite"><blockquote =
type=3D"cite"><br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote =
type=3D"cite">--<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote =
type=3D"cite"><<<<<<<<<<<<<<<=
<<<<<<<<<<<<<<<<<<&l=
t;<<<<<<<<<<<<<<<<<<=
<br></blockquote></blockquote><blockquote type=3D"cite"><blockquote =
type=3D"cite">Dr. Michael Erb<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite">Sektion f. experimentelle =
Kernspinresonanz des ZNS<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite">Abteilung Neuroradiologie, =
Universitaetsklinikum<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite">Hoppe-Seyler_Str. 3, =
D-72076 Tuebingen<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite">Tel.: +49(0)7071/2987753 =
priv. +49(0)7071/61559<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite">Fax.: =
+49(0)7071/294371<br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite">e-mail: <<a =
href=3D"mailto:[log in to unmask]">[log in to unmask]
ngen.de</a>><br></blockquote></blockquote><blockquote =
type=3D"cite"><blockquote type=3D"cite">www: <a =
href=3D"http://www.medizin.uni-tuebingen.de/nrad/sektion/">http://www.medi=
zin.uni-tuebingen.de/nrad/sektion/</a><br></blockquote></blockquote><block=
quote type=3D"cite"><blockquote =
type=3D"cite"><<<<<<<<<<<<<<<=
<<<<<<<<<<<<<<<<<<&l=
t;<<<<<<<<<<<<<<<<<<=
<br></blockquote></blockquote><blockquote =
type=3D"cite"><br></blockquote><blockquote =
type=3D"cite"><br></blockquote></div></blockquote></div><br></div></body><=
/html>=
--Apple-Mail-216-247577432
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=========================================================================
Date: Tue, 10 May 2011 01:12:24 +0100
Reply-To: Francesca Antonelli <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Francesca Antonelli <[log in to unmask]>
Subject: anova with 3 factors
Mime-Version: 1.0
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Message-ID: <[log in to unmask]>
Dear SPM users,
I'm trying to analyze in a PET study, the effect of medication in 2 diffe=
rents task and a rest condition. Basically this is my design:
task 1 off medication
rest off medication
task 2 off medication
task 1on medication
rest on medication
task 2 on medication
Each subject have performed 2 scan for each condition.
I'm using SPM8.=20
Now, if I'd like to see if the effect of meds for the tasks is different,=
in theory I should do a one-way anova- with 3 factors. Factor 1 =3D res=
ton - restoff, factor 2 =3D task1on - task1off, etc. If significant, I t=
hen do post-hoc t-tests. Well my question is, how I can do this kind of =
anova in SPM?
Another way it should be to conduct three different double t test (task1o=
n-task1off)-(reston-restoff); (task2on-task2off)-(reston-restoff); (task1=
on-task1off)-(task2on-task2off). Doing that I should correct for Bonferro=
ni correction?
Thanks for any help
=========================================================================
Date: Mon, 9 May 2011 19:20:54 -0700
Reply-To: Matthew Tryon <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Matthew Tryon <[log in to unmask]>
Subject: SnPM error
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Content-type: multipart/alternative; boundary="B_3387813658_847569"
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> This message is in MIME format. Since your mail reader does not understand
this format, some or all of this message may not be legible.
--B_3387813658_847569
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charset="US-ASCII"
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Hi All,
I'm a novice with using SnPM and I'd be very grateful for any assistance.
I'm in the process of trying to execute the fMRI example as outlined in the
SnPM documentation. The SnPMcfg.mat file is generated fine, but I get the
following error when I click on the compute button:
SnPM: snpm_cp
=======================================================================
Initialising...
??? Maximum recursion limit of 500 reached. Use set(0,'RecursionLimit',N)
to change the limit. Be aware that exceeding your available stack space can
crash MATLAB and/or your computer.
Error in ==> spm_create_image
??? Error while evaluating uicontrol Callback
I'm using MATLAB 7.10 on OSX. I sincerely appreciate any help.
Kind Regards,
Matthew Tryon
--
--B_3387813658_847569
Content-type: text/html;
charset="US-ASCII"
Content-transfer-encoding: quoted-printable
<html><head></head><body style=3D"word-wrap: break-word; -webkit-nbsp-mode: s=
pace; -webkit-line-break: after-white-space; color: rgb(0, 0, 0); font-size:=
14px; font-family: Helvetica, sans-serif; "><div><div><div><div>Hi All,</di=
v><div><br></div><div>I'm a novice with using SnPM and I'd be very grateful =
for any assistance. I'm in the process of trying to execute the f=
MRI example as outlined in the SnPM documentation. The SnPMcfg.mat fil=
e is generated fine, but I get the following error when I click on the compu=
te button:</div><div><br></div><div><div>SnPM: snpm_cp</div><div>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D</div><div>Init=
ialising...</div><div>??? Maximum recursion limit of 500 reached. Use set(0,=
'RecursionLimit',N)</div><div>to change the limit. Be aware that excee=
ding your available stack space can</div><div>crash MATLAB and/or your compu=
ter.</div><div><br></div><div>Error in =3D=3D> spm_create_image</div><div><br=
></div><div><br></div><div>??? Error while evaluating uicontrol Callback</di=
v></div><div><br></div><div><br></div><div>I'm using MATLAB 7.10 on OSX. &nb=
sp;I sincerely appreciate any help.</div><div><br></div><div>Kind Regards,</=
div><div><br></div><div>Matthew Tryon</div></div><div><div>-- </div><div><br=
></div></div></div></div></body></html>
--B_3387813658_847569--
=========================================================================
Date: Tue, 10 May 2011 09:02:06 +0000
Reply-To: James Rowe <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: James Rowe <[log in to unmask]>
Subject: Re: DCM question: disconnected regions
Content-Type: multipart/alternative;
boundary="_000_E639F95C329FB7489DCB4B0C33A8403639355C46WSR21mrccbsuloc_"
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--_000_E639F95C329FB7489DCB4B0C33A8403639355C46WSR21mrccbsuloc_
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Dear Klaas, Darren, Rik, Chris et al,
Can I revisit the issue of disconnected regions in DCM models (archive # 04=
5837<http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3Dind1103&L=3DSPM&P=3DR759=
99&I=3D-3&d=3DNo+Match%3BMatch%3BMatches>) for your opinion. It is a common=
question about DCM and model selection. We agree that for comparisons of m=
odel evidences the same data are required in all models, which means that f=
or DCM of fMRI (unlike M/EEG) the same regions must exist in all models. Th=
ere are three cases one may wish to compare:
Case A: all regions are connected by one or more paths, and subject to netw=
ork perturbation from driving inputs (directly or indirectly). A 'normal' m=
odel by current practice in other words, with variations on model structure=
comparable in terms of their Free energy. These variations include differe=
nces in intrinsic and modulatory influences, but always with all nodes conn=
ected to the main network. So far so good.
Case B: the regions fall into two groups or sub-networks, each with interna=
l connections and subject to driving inputs (Rik's question 1 below). Chris=
' accepted case B as "modelling 2 parallel and independent processes a sing=
le model" ,provided that each component network had driving inputs. DCM the=
n opimtises parameters jointly over both parts. An obvious case would be to=
compare models with and without inter-hemispheric connections between homo=
logous regions, thereby connecting or disconnecting symmetrical intra-hemis=
pheric networks.
Case C: all but one region are interconnected, and subject to driving input=
s. One region is not connected to the rest of the network (Rik's question 2=
below). Case C is the problem. I look forward to the extended version of =
klaas' recent answer (below) but note the comment on this issue last year (=
archive # 040700<http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3Dind1003&L=3D=
SPM&P=3DR46041&I=3D-3&d=3DNo+Match%3BMatch%3BMatches>) that "Technically, y=
our approach is fine, but one may debate whether it is conceptually sensibl=
e."
If the disconnected region has driving inputs, but no afferents from the re=
st of the network, then it seems to be a special type of case B (a very lim=
ited parallel network) and therefore technically and conceptually ok.
However, if the disconnected region is wholly unexplained (no driving input=
s and no afferents) then two things happen. First, the model has no means =
to explain the activity of the region, and therefore the model accuracy wou=
ld be very poor (lowering F: Darren and Chris' points). The reduced complex=
ity in the model that disconnects this region would elevate F slightly, but=
may be not enough to outweigh a wholly unexplained time series (an empiric=
al issue). The Second problem is the loss of validity of the network model.=
Of the vast potential model space, we choose a subspace of say 2-50 models=
to compare, and base this selection of models on face-, structural- and pr=
edictive- validity of the models. The models are justified on their neurobi=
ological plausibility, and theoretical relevance. An active but wholly dis=
connected region without driving inputs or afferents is inexplicable within=
DCM and implausible biologically (for the activity to be task related, no=
t including spontaneous activity, epilepsy etc).
In summary, a model may include a region that lacks intrinsic connections w=
ith other parts of the network, provided that the model includes a potentia=
l explanation of the activity of the isolated region (e.g. driving inputs, =
or using stochastic DCM). DCM will then indicate whether adding intrinsic c=
onnections to the main network increases F (as evidence for an enriched, fu=
lly connected model). But, this is not an inference about whether the regio=
n is "missing", since it was not missing from either model. It cannot be us=
ed to add or subtract regions from the model (in contrast to say GOF indice=
s in iterative model building in SEM).
Is this a fair summary under current DCM?
Best wishes,
James
Dear Darren
Apologies for a brief reply (due to lack of time). This question is releva=
nt for any hypothesis-driven modeling approach, not only DCM. In all brevi=
ty, my answer would be that simply comparing the evidence of two models in =
which a region X is connected vs. disconnected to the rest of the system is=
not sufficient to establish whether or not X is "missing" in the reduced m=
odel. Instead, what one would need to do is to compute the evidence for th=
e reduced model under presence vs. absence of the changes in system dynamic=
s that *would have been induced in the reduced system* had X been allowed t=
o interact with it. More details on this (hopefully) soon ;-)
All the best,
Klaas
Christophe and others,
I would like to get further clarification on #2 below- is it ok to have dis=
connected regions and to compare the models.
So if I understand what you are saying it is OK to disconnect regions and t=
hen test that model vs. ones with that region connected? I guess these mode=
ls would be considered to have the "same data" even though the region was d=
isconnected?
I understand the disconnected region wouldn't have any activity since it is=
n't being driven by anything, but I presume this would be reflected in a re=
duced free energy term?
Would it be possible to use the change in the free energy term to decide if=
a region truly belonged in the model?
Darren
On Thu, Mar 17, 2011 at 9:11 AM, Christophe Phillips <[log in to unmask]<ht=
tps://www.jiscmail.ac.uk/cgi-bin/webadmin?LOGON=3DA3%3Dind1103%26L%3DSPM%26=
E%3Dquoted-printable%26P%3D4473433%26B%3D--0-715813789-1300727401%253D%253A=
66396%26T%3Dtext%252Fhtml%3B%2520charset%3Dutf-8%26pending%3D>> wrote:
Hi Rik,
Let me have a go at your questions.
See interleaved text here under.
Le 17/03/2011 11:09, Rik Henson a =E9crit :
Dear DCMers -
A few, hopefully simple questions for DCM(10) for fMRI:
1. Does it make sense to have a model with 4 regions, in which 2 regions w=
ithin each of 2 pairs are interconnected, but there are no connections acro=
ss pairs (ie, two "isolated" subnetworks; eg, with regions E1<->E2 F1<->F2,=
DCM.a =3D [1 1 0 0; 1 1 0 0; 0 0 1 1; 0 0 1 1])?
Yes it does.
You're "simply" modelling 2 parrallel and independent processes a single mo=
del.
2. A related question to above: does it make sense to compare the free ener=
gy of two models, one in which a region is "isolated" (ie has no connectio=
ns apart from a self-connection) with one in which it has connections to ot=
her regions? And could this be used to ask whether that region needs to be =
in the model? (I realise one cannot use the free energy to compare models w=
ith different regions - ie different data - but wonder whether this approac=
h could be a useful heuristic answer to that question?).
The residual term of the isolated region will be its own signal (no drive -=
> flat modelled activity).
So your question would rather be: is the activity in my last/isolated regio=
n better explained, or not, when it is driven by the rest of the network? T=
he model comparison will thus be between a simple model where the activity =
of one area is not explained at all, and another one with an extra paramete=
r and a bit more signal explained.
This doesn't really answer your question whether the region should (or not)=
be part of the network though...
I would say that choice of regions to include in the model is more empirica=
l: you should include the areas necessary to build a model which models as =
accurately as possible (or sufficiently realistically) the "brain function=
" you want to study.
--_000_E639F95C329FB7489DCB4B0C33A8403639355C46WSR21mrccbsuloc_
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<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">Dear Klaas, Darren, R=
ik, Chris et al,
<o:p></o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">Can I revisit the iss=
ue of disconnected regions in DCM models (archive #
<span style=3D"font-size:9.0pt;font-family:"Arial","sans-ser=
if";color:black"><a href=3D"http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A=
2=3Dind1103&L=3DSPM&P=3DR75999&I=3D-3&d=3DNo+Match%3BMa=
tch%3BMatches"><span style=3D"font-size:11.0pt;font-family:"Calibri&qu=
ot;,"sans-serif"">045837</span></a>)
for your opinion</span>. It is a common question about DCM and model selec=
tion. We agree that for comparisons of model evidences the same data are re=
quired in all models, which means that for DCM of fMRI (unlike M/EEG) the s=
ame regions must exist in all models.
There are three cases one may wish to compare:<o:p></o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">Case A: all regions a=
re connected by one or more paths, and subject to network perturbation from=
driving inputs (directly or indirectly). A ‘normal’ model by c=
urrent practice in other words, with variations
on model structure comparable in terms of their Free energy. These variati=
ons include differences in intrinsic and modulatory influences, but always =
with all nodes connected to the main network. So far so good.
<o:p></o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">Case B: the regions f=
all into two groups or sub-networks, each with internal connections and sub=
ject to driving inputs (Rik’s question 1 below). Chris’ accepte=
d case B as “modelling 2 parallel and independent
processes a single model” ,provided that each component network had =
driving inputs. DCM then opimtises parameters jointly over both parts. An o=
bvious case would be to compare models with and without inter-hemispheric c=
onnections between homologous regions,
thereby connecting or disconnecting symmetrical intra-hemispheric networks=
. <o:p>
</o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">Case C: all but one r=
egion are interconnected, and subject to driving inputs. One region is not =
connected to the rest of the network (Rik’s question 2 below). Case C=
is the problem. I look forward to the extended
version of klaas’ recent answer (below) but note the comment on this=
issue last year (archive #<span style=3D"font-size:9.0pt;font-family:"=
;Arial","sans-serif";color:black">
<a href=3D"http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3Dind1003&L=3DSP=
M&P=3DR46041&I=3D-3&d=3DNo+Match%3BMatch%3BMatches">
<span style=3D"font-size:11.0pt;font-family:"Calibri","sans-=
serif"">040700</span></a>) that “</span>Technically, your approa=
ch is fine, but one may debate whether it is conceptually sensible.”&=
nbsp;
<o:p></o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">If the disconnected r=
egion has driving inputs, but no afferents from the rest of the network, th=
en it seems to be a special type of case B (a very limited parallel network=
) and therefore technically and conceptually
ok.<o:p></o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">However, if the disco=
nnected region is wholly unexplained (no driving inputs and no afferents) t=
hen two things happen. First, the model has no means to explain the a=
ctivity of the region, and therefore the
model accuracy would be very poor (lowering F: Darren and Chris’ poi=
nts). The reduced complexity in the model that disconnects this region woul=
d elevate F slightly, but may be not enough to outweigh a wholly unexplaine=
d time series (an empirical issue). The
Second problem is the loss of validity of the network model. Of the vast p=
otential model space, we choose a subspace of say 2-50 models to compare, a=
nd base this selection of models on face-, structural- and predictive- vali=
dity of the models. The models are
justified on their neurobiological plausibility, and theoretical relevance=
. An active but wholly disconnected region without driving inputs or =
afferents is inexplicable within DCM and implausible biologically (fo=
r the activity to be task related, not including
spontaneous activity, epilepsy etc). <o:p></o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">In summary, a model m=
ay include a region that lacks intrinsic connections with other parts of th=
e network,
<b><i>provided</i></b> that the model includes a potential explanation of t=
he activity of the isolated region (e.g. driving inputs, or using stochasti=
c DCM). DCM will then indicate whether adding intrinsic connections to the =
main network increases F (as evidence
for an enriched, fully connected model). But, this is not an inference abo=
ut whether the region is “missing”, since it was not missing fr=
om either model. It cannot be used to add or subtract regions from the mode=
l (in contrast to say GOF indices in iterative
model building in SEM). <o:p></o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">Is this a fair summar=
y under current DCM?<o:p></o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">Best wishes, <o:p></o=
:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">James<o:p></o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt"><o:p> </o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt"><o:p> </o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt"><o:p> </o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt"><o:p> </o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt"><o:p> </o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt"><o:p> </o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt"><o:p> </o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">Dear Darren<br>
Apologies for a brief reply (due to lack of time). This question is r=
elevant for any hypothesis-driven modeling approach, not only DCM. In=
all brevity, my answer would be that simply comparing the evidence of two =
models in which a region X is connected vs.
disconnected to the rest of the system is not sufficient to establish whet=
her or not X is "missing" in the reduced model. Instead, wh=
at one would need to do is to compute the evidence for the reduced model un=
der presence vs. absence of the changes in system
dynamics that *would have been induced in the reduced system* had X been a=
llowed to interact with it. More details on this (hopefully) soon&nbs=
p; ;-)<br>
All the best,<br>
Klaas<br>
<br>
<o:p></o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">Christophe and others=
,<br>
<br>
I would like to get further clarification on #2 below- is it ok to have dis=
connected regions and to compare the models.<br>
So if I understand what you are saying it is OK to disconnect regions and t=
hen test that model vs. ones with that region connected? I guess these mode=
ls would be considered to have the "same data" even though the re=
gion was disconnected?<br>
I understand the disconnected region wouldn't have any activity since it is=
n't being driven by anything, but I presume this would be reflected in a re=
duced free energy term?<br>
Would it be possible to use the change in the free energy term to decide if=
a region truly belonged in the model?<br>
Darren<span style=3D"font-size:12.0pt;font-family:"Times New Roman&quo=
t;,"serif""><o:p></o:p></span></p>
<p class=3D"MsoNormal">On Thu, Mar 17, 2011 at 9:11 AM, Christophe Phillips=
<<a href=3D"https://www.jiscmail.ac.uk/cgi-bin/webadmin?LOGON=3DA3%3Din=
d1103%26L%3DSPM%26E%3Dquoted-printable%26P%3D4473433%26B%3D--0-715813789-13=
00727401%253D%253A66396%26T%3Dtext%252Fhtml%3B%2520charset%3Dutf-8%26pendin=
g%3D" target=3D"_parent">[log
in to unmask]</a>> wrote:<o:p></o:p></p>
<p class=3D"MsoNormal">Hi Rik,<br>
Let me have a go at your questions.<br>
See interleaved text here under.<br>
Le 17/03/2011 11:09, Rik Henson a =E9crit : <o:p></o:p></p>
<p class=3D"MsoNormal"> <o:p></o:p></p>
<p class=3D"MsoNormal">Dear DCMers –<o:p></o:p></p>
<p class=3D"MsoNormal"> A few, hopefully simple questions for DCM(10) =
for fMRI:<o:p></o:p></p>
<p class=3D"MsoNormal"> 1. Does it make sense to have a model with 4 r=
egions, in which 2 regions within each of 2 pairs are interconnected, but t=
here are no connections across pairs (ie, two “isolated” subnet=
works; eg, with regions E1<->E2 F1<->F2, DCM.a =3D [1
1 0 0; 1 1 0 0; 0 0 1 1; 0 0 1 1])?<o:p></o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt">Yes it does.<br>
You're "simply" modelling 2 parrallel and independent processes a=
single model. <span style=3D"font-size:12.0pt;font-family:"Times New =
Roman","serif"">
<o:p></o:p></span></p>
<p class=3D"MsoNormal">2. A related question to above: does it make sense t=
o compare the free energy of two models, one in which a region is “is=
olated” (ie has no connections apart from a self-connection) wi=
th one in which it has connections to other regions?
And could this be used to ask whether that region needs to be in the model=
? (I realise one cannot use the free energy to compare models with differen=
t regions – ie different data – but wonder whether this approac=
h could be a useful heuristic answer to that
question?).<o:p></o:p></p>
<p class=3D"MsoNormal">The residual term of the isolated region will be its=
own signal (no drive -> flat modelled activity).<br>
So your question would rather be: is the activity in my last/isolated regio=
n better explained, or not, when it is driven by the rest of the network? T=
he model comparison will thus be between a simple model where the activity =
of one area is not explained at
all, and another one with an extra parameter and a bit more signal explain=
ed.<br>
This doesn't really answer your question whether the region should (or not)=
be part of the network though...<br>
I would say that choice of regions to include in the model is more empirica=
l: you should include the areas necessary to build a model which models as =
accurately as possible (or sufficiently realistically) the "brai=
n function" you want to study.
<span style=3D"font-size:12.0pt;font-family:"Times New Roman",&qu=
ot;serif""><o:p></o:p></span></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
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--_000_E639F95C329FB7489DCB4B0C33A8403639355C46WSR21mrccbsuloc_--
=========================================================================
Date: Tue, 10 May 2011 10:02:14 +0000
Reply-To: Fredrik Ullen <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Fredrik Ullen <[log in to unmask]>
Subject: open PhD position at Karolinska Institutet
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See attached information.
Fredrik Ull=E9n
Professor of Cognitive Neuroscience
Dept of Women's and Children's Health
Karolinska Institutet
SE-171 76 Stockholm
Sweden
--_000_E524EB9295E9D74982684F9B2854287F12037FD5KIMSX03userkise_
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<p class=3D"MsoNormal"><span style=3D"color:#1F497D">See attached informati=
on.<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"color:#1F497D"><o:p> </o:p></spa=
n></p>
<p class=3D"MsoNormal"><span style=3D"color:#1F497D"><o:p> </o:p></spa=
n></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"color:#1F497D">Fredrik=
Ull=E9n<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"color:#1F497D">Profess=
or of Cognitive Neuroscience<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"color:#1F497D">Dept of=
Women's and Children's Health<br>
Karolinska Institutet<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"color:#1F497D">SE-171 76 Stockholm<o:=
p></o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"color:#1F497D">Sweden<o:p></o:p></spa=
n></p>
<p class=3D"MsoNormal"><span style=3D"color:#1F497D"><o:p> </o:p></spa=
n></p>
<p class=3D"MsoNormal"><span style=3D"color:#1F497D"><o:p> </o:p></spa=
n></p>
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--_004_E524EB9295E9D74982684F9B2854287F12037FD5KIMSX03userkise_--
=========================================================================
Date: Tue, 10 May 2011 11:27:48 +0100
Reply-To: Min <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Min <[log in to unmask]>
Subject: SPM2 Versus SPM8
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear SPM's users,
I ran spm2 and spm8, respectively, for the same set of fMRI data. Howeve=
r, though I followed the same steps for the two versions of spm, there ar=
e considerable differences in the results. With spm8, no suprathreshold =
clusters were found with fdr(0.05) corrected, while with spm 2, more than=
8 clusters survive the threshold (T values of height threshold are nearl=
y the same for the two analysis).=20=20=20
I am unsure how to explain such a big difference between the results from=
two versions of spm.
I will be grateful for any help!
Sincerely,
Min
=========================================================================
Date: Tue, 10 May 2011 11:49:59 +0100
Reply-To: Helen Beaumont <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Helen Beaumont <[log in to unmask]>
Subject: Image intensity read with spm_read_vols
MIME-Version: 1.0
Content-Type: multipart/alternative;
boundary="----_=_NextPart_001_01CC0F00.02005A20"
Message-ID: <[log in to unmask]>
This is a multi-part message in MIME format.
------_=_NextPart_001_01CC0F00.02005A20
Content-Type: text/plain;
charset="us-ascii"
Content-Transfer-Encoding: quoted-printable
I am writing an image using writeanalyze (from Colin Humphries at
University of California, Irvine). Image intensity is written in float,
but I have the same problem if I use int32 or int64.
Values are typically ~30000.=20
When I read the image back with spm_read_vols, the values come back as
e-39.
I've looked at the code, but spm_read_vols calls spm_slice_vol, which is
compiled.
Can someone please help me sort this.
=20
Helen Beaumont
ISBE
University of Manchester=20
Stopford Building, Oxford Rd
Manchester M13 9PT
Tel: 0161 275 1259
=20
=20
------_=_NextPart_001_01CC0F00.02005A20
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vlink=3Dpurple><div class=3DWordSection1><p class=3DMsoNormal>I am =
writing an image using writeanalyze (from Colin Humphries at University =
of California, Irvine). Image intensity is written in float, but I have =
the same problem if I use int32 or int64.<o:p></o:p></p><p =
class=3DMsoNormal>Values are typically ~30000. <o:p></o:p></p><p =
class=3DMsoNormal>When I read the image back with spm_read_vols, the =
values come back as e-39.<o:p></o:p></p><p class=3DMsoNormal>I’ve =
looked at the code, but spm_read_vols calls spm_slice_vol, which is =
compiled.<o:p></o:p></p><p class=3DMsoNormal>Can someone please help me =
sort this.<o:p></o:p></p><p class=3DMsoNormal><o:p> </o:p></p><p =
class=3DMsoNormal><span =
style=3D'font-size:10.0pt;font-family:"Arial","sans-serif";mso-fareast-la=
nguage:EN-GB'>Helen Beaumont<o:p></o:p></span></p><p =
class=3DMsoNormal><span =
style=3D'font-size:7.5pt;font-family:"Arial","sans-serif";mso-fareast-lan=
guage:EN-GB'>ISBE<o:p></o:p></span></p><p class=3DMsoNormal><span =
style=3D'font-size:7.5pt;font-family:"Arial","sans-serif";mso-fareast-lan=
guage:EN-GB'>University of Manchester <o:p></o:p></span></p><p =
class=3DMsoNormal><span =
style=3D'font-size:7.5pt;font-family:"Arial","sans-serif";mso-fareast-lan=
guage:EN-GB'>Stopford Building, Oxford Rd<o:p></o:p></span></p><p =
class=3DMsoNormal><span =
style=3D'font-size:7.5pt;font-family:"Arial","sans-serif";mso-fareast-lan=
guage:EN-GB'>Manchester M13 9PT</span><span =
style=3D'font-size:10.0pt;font-family:"Arial","sans-serif";mso-fareast-la=
nguage:EN-GB'><o:p></o:p></span></p><p class=3DMsoNormal><span =
style=3D'font-size:7.5pt;font-family:"Arial","sans-serif";mso-fareast-lan=
guage:EN-GB'>Tel: 0161 275 1259<o:p></o:p></span></p><p =
class=3DMsoNormal><span =
style=3D'font-size:10.0pt;font-family:"Arial","sans-serif";mso-fareast-la=
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------_=_NextPart_001_01CC0F00.02005A20--
=========================================================================
Date: Tue, 10 May 2011 12:04:38 +0100
Reply-To: John Ashburner <jas[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: Image intensity read with spm_read_vols
Comments: To: Helen Beaumont <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=windows-1252
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
There's a scalefactor in the headers that should be set correctly.
See the NIfTI web pages for more info.
Best regards,
-John
On 10 May 2011 11:49, Helen Beaumont
<[log in to unmask]> wrote:
> I am writing an image using writeanalyze (from Colin Humphries at Univers=
ity
> of California, Irvine). Image intensity is written in float, but I have t=
he
> same problem if I use int32 or int64.
>
> Values are typically ~30000.
>
> When I read the image back with spm_read_vols, the values come back as e-=
39.
>
> I=92ve looked at the code, but spm_read_vols calls spm_slice_vol, which i=
s
> compiled.
>
> Can someone please help me sort this.
>
>
>
> Helen Beaumont
>
> ISBE
>
> University of Manchester
>
> Stopford Building, Oxford Rd
>
> Manchester M13 9PT
>
> Tel: 0161 275 1259
>
>
>
>
=========================================================================
Date: Tue, 10 May 2011 12:29:27 +0100
Reply-To: Paul Downing <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Paul Downing <[log in to unmask]>
Subject: PhD studentship at Bangor University, School of Psychology
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Funded PhD Studentship
School of Psychology, Bangor University
Supervisor: Prof Paul Downing
Applications are invited for a three-year fully funded PhD studentship
in the School of Psychology, Bangor University under the supervision of
Prof Paul Downing. The studentship is available from October 1st 2011
(or as soon as possible thereafter) and includes payment of UK / EU
level tuition fees, a maintenance allowance of approximately =A313,590 and
a research allowance of =A3750 per year for 3 years.
Project
A highly-motivated, enthusiastic student, with strong written and oral
presentation skills and a strong grasp of experimental psychology and/or
neuroimaging methods is required to fill this position, and some
programming skills (e.g. Matlab) would be desirable.
Information about some of the ongoing projects in the lab are listed
below. An interest in these specific themes is welcome but not essential:
- An ESRC-funded project (with Steve Tipper) using multi-voxel pattern
analysis (MVPA) and other fMRI methods in order to investigate the human
'mirror system'. Are there brain areas for which local patterns of BOLD
activity distinguish among different actions, across the visual and
motor domains?
- A Leverhulme-funded project using online and offline TMS. We are
examining how disruption of activity in various nodes of the proposed
human "action perception network" changes both the BOLD activity in
other parts of the network as well as action-perception behavioural
performance.
- A new collaborative project (with Kim Graham, Cardiff) that is funded
by the BBSRC will focus on using fMRI (primarily with MVPA) to assess
the perceptual functions of the medial temporal lobes, and to compare
these directly to the functions of category-selective areas of the
extrastriate cortex.
More information about the lab is available at http://pages.bangor.ac.uk/
~pss811
Applications for this studentship will be considered from June 15th,
2011 until the position is filled.
Informal enquiries about the project should be directed to
[log in to unmask], and enquiries about the application process to
[log in to unmask]
How to Apply
Applicants are expected to have a first or upper second-class honours
degree or equivalent in Psychology, and we would normally expect
applicants to have completed an appropriate Masters degree.
International students are welcome to apply, however our studentships
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Date: Tue, 10 May 2011 21:44:57 +0800
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=========================================================================
Date: Tue, 10 May 2011 15:54:26 +0200
Reply-To: Noelia Ventura <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Noelia Ventura <[log in to unmask]>
Subject: Re: Compare conjunction
Comments: To: sarika cherodath <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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--------------030402050907080000060103
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X-MIME-Autoconverted: from 8bit to quoted-printable by bifur.jiscmail.ac.uk id p4AE9nsj004559
Hi Sarika,
Thank you for your response.
This does not function for our particular data set as we include a 3=20
conditions: A =3D auditory, B =3D visual and C =3D audiovisual. We are no=
w=20
examining the multimodal region. In this region there is no response for=20
the unisensory conditions and therefore this leads to a null result in=20
the conjunction you suggested.
Do you have a solution for this? Or anyone else?
Thanks,
Noelia
El 09/05/2011 11:58, sarika cherodath escribi=F3:
> Hi,
>
> I am not sure whether this could work, but you can make a subtraction=20
> of L1 and L2 for each condition and then do a conjunction to create=20
> the required contrast.
>
> On Mon, May 9, 2011 at 2:47 PM, Noelia Ventura <[log in to unmask]
> <mailto:[log in to unmask]>> wrote:
>
> Hi all,
>
> We would like to compare directly the results of two conjunction
> analyses.These conjunctions show overlapping clusters. One
> conjunction shows a larger cluster then the other. We would like
> to examine whether the voxels that show up for one conjunction but
> not for the other differ significantly from each other.
>
> In more detail, we have two tasks in the native (L1) and
> non-native language (L2). Each task consists of 3 conditions, (A,
> B, C).In the random effects we use a full factorial within
> subjects design and create a contrast : (and we do this
> conjunction for L1 and L2. We would like to know in which voxels
> the conjunction of L1 > L2.
>
> However, in spm you cannot directly compare to conjunctions with
> each other. Or can you?
>
> We would like to use imcalc to test where i1 =3D conj L1, i2 =3D co=
nj
> L2 and our expression is i1 -i2> 0. However, i think we obtain a
> binary image from that but we need a statistical image. Can anyone
> provide a solution for this?
>
> Thanks for your help,
> Noelia
>
>
>
>
> --=20
> Sarika Cherodath
> Graduate Student
> National Brain Research Centre
> Manesar, Gurgaon -122050
> India
>
--------------030402050907080000060103
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boundary="------------020004020700080804020702"
--------------020004020700080804020702
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<html>
<head>
<meta content="text/html; charset=ISO-8859-1"
http-equiv="Content-Type">
</head>
<body bgcolor="#ffffff" text="#000000">
Hi Sarika,<br>
<br>
Thank you for your response.<br>
<br>
This does not function for our particular data set as we include a 3
conditions: A = auditory, B = visual and C = audiovisual. We are now
examining the multimodal region. In this region there is no response
for the unisensory conditions and therefore this leads to a null
result in the conjunction you suggested. <br>
<br>
Do you have a solution for this? Or anyone else?<br>
<br>
Thanks,<br>
<br>
Noelia<br>
<br>
<br>
El 09/05/2011 11:58, sarika cherodath escribió:
<blockquote
cite="mid:[log in to unmask]"
type="cite">
<div dir="ltr">
<div>Hi,</div>
<div><br>
</div>
I am not sure whether this could work, but you can make a
subtraction of L1 and L2 for each condition and then do a
conjunction to create the required contrast.<br>
<br>
<div class="gmail_quote">
On Mon, May 9, 2011 at 2:47 PM, Noelia Ventura <span
dir="ltr"><<a moz-do-not-send="true"
href="mailto:[log in to unmask]">[log in to unmask]</a>></span>
wrote:<br>
<blockquote class="gmail_quote" style="margin: 0pt 0pt 0pt
0.8ex; border-left: 1px solid rgb(204, 204, 204);
padding-left: 1ex;">
<div bgcolor="#ffffff" text="#000000"> <span lang="EN-GB">Hi
all,</span>
<p class="MsoNormal"><span lang="EN-GB">We would like to
compare directly the results of two conjunction
analyses.<span> </span>These conjunctions show
overlapping clusters. One conjunction shows a larger
cluster then the other. We would like to examine
whether the voxels that show up for one conjunction
but not for the other differ significantly from each
other. </span></p>
<p class="MsoNormal"><span lang="EN-GB">In more detail, we
have two tasks in the native (L1) and non-native
language (L2). <span> </span>Each task consists of 3
conditions, (A, B, C).<span> </span>In the random
effects we use a full factorial within subjects design
and create a contrast : </span><span lang="EN-GB">(</span><span
style="font-size: 11pt; line-height: 115%;"><img
src="cid:part1.07020506.07040003@psb.uji.es"
width="246" height="20"></span><span lang="EN-GB"><span>
</span>and we do this conjunction for L1 and L2. <span> </span>We
would like to know in which voxels the conjunction of
L1 > L2. </span></p>
<p class="MsoNormal"><span lang="EN-GB"> </span></p>
<p class="MsoNormal"><span lang="EN-GB">However, in spm
you cannot directly compare to conjunctions with each
other. Or can you?</span></p>
<p class="MsoNormal"><span lang="EN-GB">We would like to
use imcalc to test where i1 = conj L1, i2 = conj L2
and our expression is i1 -i2> 0. However, i think
we obtain a binary image from that but we need a
statistical image. Can anyone provide a solution for
this? <br>
</span></p>
<p class="MsoNormal"><span lang="EN-GB">Thanks for your
help,<br>
Noelia<br>
</span></p>
</div>
</blockquote>
</div>
<br>
<br clear="all">
<br>
-- <br>
Sarika Cherodath<br>
Graduate Student<br>
National Brain Research Centre<br>
Manesar, Gurgaon -122050<br>
India<br>
<br>
</div>
</blockquote>
<br>
</body>
</html>
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fn:Noelia Ventura Campos
n:Ventura Campos;Noelia
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title:PDI
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=========================================================================
Date: Tue, 10 May 2011 15:44:25 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: inaccurate segmentation of gray matter
Comments: To: "Moeller, C." <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
I don't have any good suggestions at the moment, other than maybe try
Christian Gaser's toolbox to see if this handles the data better. I
suspect that it might, as its final segmentation relies less heavily
on the tissue probability maps.
Best regards,
-John
On 9 May 2011 10:37, Moeller, C. <[log in to unmask]> wrote:
> Dear SPM experts,
>
> I am doing VBM analysis on scans of AD patients and healthy controls. I
> just finished the segmentation and found a lot of inaccurate
> segmentations, especially in scans with a lot of atrophy. I attached a
> screenshot of the segmentation for illustration of the problem. It seems
> as if the space between the cortex and the dura is also segmented as
> gray matter. I used 'New Segment' of SPM8.
>
> Does anyone have an idea why this happens and how I can solve this
> problem?
>
> Another issue is, that often the dura around the brain is also segmented
> as gray matter. In the older version of the 'Segment' step there was a
> 'Clean up' option. Does anyone know how to solve this in the 'New
> Segment' step of SPM?
>
> Thanks in advance.
>
> Best regards,
> Christiane
>
=========================================================================
Date: Tue, 10 May 2011 10:49:35 -0400
Reply-To: "Fromm, Stephen (NIH/NIMH) [C]" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Fromm, Stephen (NIH/NIMH) [C]" <[log in to unmask]>
Subject: Re: Ancova in SPM8
Comments: To: Ryan Herringa <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Content-Type: text/plain; charset="us-ascii"
Content-Transfer-Encoding: quoted-printable
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
Did you mean-center the covariate-condition interaction terms in design2?
There's often more than one way to do mean centering. I don't recall how S=
PM sets things up here. Obviously if you take the first such term, ie the =
first such column, the entries are nontrivial for the first (13?) rows, and=
all zeros after that. I think that means the mean centering was done "ove=
r condition", _if_ it was done. (Which would be the right way to do it in =
this case.)
The model without mean centering is equivalent (but not identical) to the o=
ne with mean centering; the one with mean centering is easily to understand=
, I think.
Stephen J. Fromm, PhD
Contractor, NIMH/MAP
(301) 451--9265
________________________________________
From: Ryan Herringa [[log in to unmask]]
Sent: Monday, May 09, 2011 4:11 PM
To: [log in to unmask]; Fromm, Stephen (NIH/NIMH) [C]
Subject: Re: Ancova in SPM8
Thanks Stephen,
Your first assumption is correct, that the covariates vary across subjects =
but not condition. (not that I explained it terribly well)
The second level scans represent intra-subject contrasts (emotion vs. shape=
) so I think you are right that the subject effects should have been subtra=
cted out.
Thanks for helping to clarify the models - sounds like there is some utilit=
y in both which I'll have to give some more thought.
For model 2, am I correct in assuming that if I select either a single cond=
ition, or a single covariate interaction term in the contrast manager, that=
I will be looking at the condition x covariate interaction?=
=========================================================================
Date: Tue, 10 May 2011 15:57:39 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: spm_affreg
Comments: To: Siddharth Srivastava <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
You only need the one shear, so that you have 6 parameters in total.
You can test this by looking for affine transforms that can not be
represented by those six parameters:
for i=3D1:10000
M0=3D[randn(2,3)*10; 0 0 1];
P1=3Dspm_imatrix2D(M0);
M1=3Dspm_matrix2D(P1);
t=3Dsum(sum((M1-M0).^2));
if t>1e-9, disp('Problem'); break; end
end
Best regards,
-John
On 6 May 2011 21:48, Siddharth Srivastava <[log in to unmask]> wrote:
> Hi John, please ignore the first part of my previous mail: made some erro=
rs
> in
> cut and paste. It runs fine now. The question about the shears, however,
> still lingers: do I have
> to somehow use both Sx and Sy, or as your implementation suggests, only o=
ne
> would suffice?
>
> thanks again, and sorry for being such a bother...
> sid.
>
> On Fri, May 6, 2011 at 12:23 PM, Siddharth Srivastava <[log in to unmask]>
> wrote:
>>
>> Thanks John, for the answers. The code, however exits with "Problem". M0
>> and M1 differ.
>> Also, why is there just one shear component in the matrix? I have seen
>> general shears modeled as [1,h;g,1]: is this superfluous, and just one "=
h"
>> will be sufficient for 2d case?
>>
>> Thanks,
>> Sid.
>>
>>
>>
>> On Fri, May 6, 2011 at 11:01 AM, John Ashburner <[log in to unmask]>
>> wrote:
>>>
>>> Your model uses 7 parameters, but there are only 6 elements in
>>> A(1:2,1:3). =A0Also, you need to be able to deal with a broader range o=
f
>>> angles, so atan2(s,c) is used to compute the angle. =A0I've tested it
>>> with the following code, so hopefully it works for all cases.
>>>
>>> for i=3D1:10000
>>> =A0P=3Drandn(1,6)*10;
>>> =A0M0=3Dspm_matrix2D(P);
>>> =A0P1=3Dspm_imatrix2D(M0);
>>> =A0M1=3Dspm_matrix2D(P1);
>>> =A0t=3Dsum(sum((M1-M0).^2));
>>> =A0if t>1e-9, disp('Problem'); break; end
>>> end
>>>
>>> Note that spm_imatrix2D(spm_matrix2D(P)) does not necessarily have to
>>> equal P, but the matrices generated from the two parameter sets should
>>> be the same.
>>>
>>> Best regards,
>>> -John
>>>
>>> On 6 May 2011 17:11, Siddharth Srivastava <[log in to unmask]> wrote:
>>> > Hi everyone,
>>> > =A0=A0=A0=A0=A0 Can someone help me check the 2D versions of the spm_=
matrix and
>>> > spm_imatrix? My
>>> > implementation currently is as follows:
>>> >
>>> > ---2D spm_matrix ---
>>> > function [A] =3D spm_matrix2D(P)
>>> > % P =3D [Tx, Ty, R, Zx, Zy, Sx,Sy]
>>> > p0 =3D [0,0,0,1,1,0,0];
>>> > P =3D [P, p0((length(P)+1):7)]
>>> >
>>> > A =3D eye(3);
>>> > % T -> R -> Zoom -> Shear
>>> > =A0A =3D=A0=A0=A0=A0 A * [1,0,P(1); ...
>>> > =A0=A0=A0=A0=A0=A0=A0=A0=A0 0,1,P(2); ...
>>> > =A0 =A0=A0=A0 =A0 0,0,=A0=A0 1];
>>> > =A0A =3D=A0=A0=A0=A0 A * [cos(P(3)), sin(P(3)), 0; ...
>>> > =A0=A0=A0=A0=A0=A0=A0=A0=A0 -sin(P(3)),=A0 cos(P(3)), 0; ...
>>> > =A0=A0=A0 =A0 0,=A0=A0=A0=A0=A0=A0=A0=A0=A0 0,=A0=A0=A0=A0=A0=A0=A0=
=A0 1];
>>> > =A0A =3D=A0=A0=A0=A0 A * [P(4), 0, 0; ...
>>> > =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 0,=A0=A0 P(5), 0; ...
>>> > =A0=A0=A0 =A0=A0=A0=A0=A0 0, 0, 1];
>>> > =A0A =3D=A0=A0=A0=A0 A * [1, P(6), 0; ...
>>> > =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 P(7)=A0 , 1, 0; ...
>>> > =A0=A0=A0 =A0=A0=A0=A0=A0 0, 0, 1];
>>> > --------------------------------------------------
>>> > -----2D spm_imatrix ------------------------
>>> > function P =3D=A0 spm_imatrix2D(M);
>>> >
>>> >
>>> >
>>> > R =3D M(1:2,1:2);
>>> > C =3D chol(R' * R);
>>> > P =3D [M(1:2,3)',0,diag(C)',0,0];
>>> > if(det(R) < 0) P(4) =3D -P(4); end
>>> > C =3D diag(diag(C))\C;
>>> > P(6:7) =3D C([2,3]);
>>> >
>>> > R0 =3D spm_matrix2D([0,0,0,P(4:end)]);
>>> > R0 =3D R0(1:2,1:2);
>>> > R1 =3D R/R0;
>>> >
>>> > th =3D asin(rang(R1(1,2)));
>>> > P(3) =3D th;
>>> >
>>> > % There may be slight rounding errors making b>1 or b<-1.
>>> > function=A0 a =3D rang(b)
>>> > a =3D min(max(b, -1), 1);
>>> > return;
>>> >
>>> > ---------------------------------------------------------------------=
------
>>> >
>>> > I know there is something not correct, since when, for a parameter se=
t
>>> > 'p',
>>> > i do spm_imatrix2D(spm_matrix2D(p)), I do not recover P for all
>>> > entries,
>>> > specially
>>> > rotation and shears. C(2) above always evaluates to zero. The result =
is
>>> > that
>>> > these errors
>>> > accumulate (or are not accounted for) on repeated application of this
>>> > sequence of
>>> > operations in the registration routine.
>>> >
>>> > Thanks in anticipation,
>>> > Sid.
>>> >
>>> >
>>> >
>>> > On Fri, Apr 22, 2011 at 9:13 AM, Siddharth Srivastava
>>> > <[log in to unmask]>
>>> > wrote:
>>> >>
>>> >> Hi John,
>>> >> =A0=A0=A0=A0=A0 Thanks a lot for your answer, and it has been very h=
elpful for
>>> >> my
>>> >> understanding
>>> >> of the details of the implementation, and my own development efforts=
.
>>> >> I
>>> >> have
>>> >> 2 very quick questions, though:
>>> >>
>>> >> 1) the parameter set x(:) that is returned from spm_mireg, and the
>>> >> "params" that
>>> >> spm_affsub3 returns (in spm99, which is also the version that I am
>>> >> looking
>>> >> at) ,
>>> >> are they equivalent? In other words, If I am collating the parameter=
s
>>> >> from
>>> >> the mireg
>>> >> routine, would the distribution x(7:12) be used to estimate the
>>> >> icovar0
>>> >> entries in affsub3?
>>> >>
>>> >> 2) also would VG.mat\spm_matrix(x)*VF.mat transform G to F similar t=
o
>>> >> =A0=A0=A0=A0 VG.mat\spm_matrix(params)*VF.mat , or do I have to do
>>> >> =A0=A0=A0=A0=A0 M =3D VG.mat\spm_matrix(x(:)')*VF.mat
>>> >> =A0=A0=A0=A0=A0 pp =3D spm_imatrix(M)
>>> >> =A0=A0=A0=A0=A0 and use pp(7:12) ?
>>> >>
>>> >>
>>> >>
>>> >> Thanks again.
>>> >> Sid.
>>> >>
>>> >> On Thu, Apr 14, 2011 at 2:13 PM, John Ashburner <[log in to unmask]
m>
>>> >> wrote:
>>> >>>
>>> >>> > I had a look at the code in spm_maff, and
>>> >>> > it looks like it also uses the values of isig and mu in the call =
to
>>> >>> > affreg(). My guess is
>>> >>> > that during the initial registration on a large data set for
>>> >>> > estimating
>>> >>> > the
>>> >>> > prior
>>> >>> > distribution of parameters, this will be called with typ =3D 'non=
e' .
>>> >>> > Is
>>> >>> > this
>>> >>> > correct?
>>> >>>
>>> >>> Once the registration has locked in on a solution, the priors have
>>> >>> less influence. =A0Their main influence is in the early stages of t=
he
>>> >>> registration, or when there are relatively few slices in the data. =
=A0I
>>> >>> don't actually remember if the registration was regularised when I
>>> >>> computed their values.
>>> >>>
>>> >>> >
>>> >>> > Further, do we have to do a non-rigid registration for the
>>> >>> > estimation
>>> >>> > (since, in the comments the selected
>>> >>> > files are filtered as *seg_inv_sn.mat"? Since only p.Affine is
>>> >>> > being
>>> >>> > used,
>>> >>> > can this work with only
>>> >>> > an affine / rigid transformation?
>>> >>>
>>> >>> Only the affine transform in the files is used, so basically yes.
>>> >>> =A0You
>>> >>> could just do affine registration.
>>> >>>
>>> >>> >
>>> >>> > I would also be happy if you could also answer my other question
>>> >>> > about
>>> >>> > examining the
>>> >>> > effects of the values in isig and mu (what are the units of mu?) =
on
>>> >>> > the
>>> >>> > transformed image.
>>> >>>
>>> >>> They are unit-less, and are just a measure of the zooms and shears.
>>> >>>
>>> >>> > For example,
>>> >>> > if i set a mu of [mu1, mu2, ...] and a isig of [sig1, 0, 0...; 0,
>>> >>> > sig2,
>>> >>> > 0,
>>> >>> > 0..; ...] (with only diagonal components),
>>> >>> > based on the Hencky tensor penalty, it seems that large deviation=
s
>>> >>> > of
>>> >>> > parameter 1=A0 estimate (T - mu) from
>>> >>> > mu1 will be penalized. How is the value of isig1 modifying the
>>> >>> > penalty?
>>> >>>
>>> >>> Its assuming that the elements of the matrix log of the part that
>>> >>> does
>>> >>> shears and zooms has a multivariate normal distribution, so the
>>> >>> penalty is a kind of negative log likelhood. =A0The isig is essenti=
ally
>>> >>> a precision matrix, which is the inverse of a covariance matrix.
>>> >>>
>>> >>> p(x|mu,S) =3D 1/sqrt(det(2*pi*S)) * exp(-0.5*(x-mu)'*inv(S)*(x-mu))
>>> >>>
>>> >>> Taking logs and negating, you get 0.5*(x-mu)'*inv(S)*(x-mu) + const
>>> >>>
>>> >>> > How
>>> >>> > do the off diagonal terms affect
>>> >>> > the penalty?
>>> >>>
>>> >>> The inverse of isig would just encode the covariance between the
>>> >>> various shears and zooms.
>>> >>>
>>> >>> >
>>> >>> > Could you also point me to a reference where I can learn more abo=
ut
>>> >>> > Hencky
>>> >>> > strain tensor (specifically
>>> >>> > what information it carries in the context of image processing
>>> >>> > etc.)
>>> >>>
>>> >>> I don't know if this is of any use:
>>> >>>
>>> >>> http://en.wikipedia.org/wiki/Deformation_(mechanics)
>>> >>>
>>> >>> Best regards,
>>> >>> -John
>>> >>>
>>> >>>
>>> >>> > On Thu, Apr 14, 2011 at 10:17 AM, John Ashburner
>>> >>> > <[log in to unmask]>
>>> >>> > wrote:
>>> >>> >>
>>> >>> >> They were computed by affine registering loads of (227) images t=
o
>>> >>> >> MNI
>>> >>> >> space. =A0This gave the affine transforms, which were then used =
to
>>> >>> >> build
>>> >>> >> up a mean and inverse covariance matrix. =A0In the comments of
>>> >>> >> spm_maff.m, you should see the following...
>>> >>> >>
>>> >>> >> %% Values can be derived by...
>>> >>> >> %sn =3D spm_select(Inf,'.*seg_inv_sn.mat$');
>>> >>> >> %X =A0=3D zeros(size(sn,1),12);
>>> >>> >> %for i=3D1:size(sn,1),
>>> >>> >> % =A0 =A0p =A0=3D load(deblank(sn(i,:)));
>>> >>> >> % =A0 =A0M =A0=3D p.VF(1).mat*p.Affine/p.VG(1).mat;
>>> >>> >> % =A0 =A0J =A0=3D M(1:3,1:3);
>>> >>> >> % =A0 =A0V =A0=3D sqrtm(J*J');
>>> >>> >> % =A0 =A0R =A0=3D V\J;
>>> >>> >> % =A0 =A0lV =A0 =A0 =A0=3D =A0logm(V);
>>> >>> >> % =A0 =A0lR =A0 =A0 =A0=3D -logm(R);
>>> >>> >> % =A0 =A0P =A0 =A0 =A0 =3D zeros(12,1);
>>> >>> >> % =A0 =A0P(1:3) =A0=3D M(1:3,4);
>>> >>> >> % =A0 =A0P(4:6) =A0=3D lR([2 3 6]);
>>> >>> >> % =A0 =A0P(7:12) =3D lV([1 2 3 5 6 9]);
>>> >>> >> % =A0 =A0X(i,:) =A0=3D P';
>>> >>> >> %end;
>>> >>> >> %mu =A0 =3D mean(X(:,7:12));
>>> >>> >> %XR =A0 =3D X(:,7:12) - repmat(mu,[size(X,1),1]);
>>> >>> >> %isig =3D inv(XR'*XR/(size(X,1)-1))
>>> >>> >>
>>> >>> >> You may be able to re-code this to work with your 2D transforms.
>>> >>> >> =A0Note
>>> >>> >> that I only use the components that describe shears and zooms.
>>> >>> >> =A0Also,
>>> >>> >> if I was re-coding it all again, I would probably do things
>>> >>> >> slightly
>>> >>> >> differently, using the following decomposition:
>>> >>> >>
>>> >>> >> J=3DM(1:3,1:3);
>>> >>> >> L=3Dreal(logm(J));
>>> >>> >> S=3D(L+L')/2; % Symmetric part (for zooms and shears, which shou=
ld
>>> >>> >> be
>>> >>> >> penalised)
>>> >>> >> A=3D(L-L')/2; % Anti-symmetric part (for rotations)
>>> >>> >>
>>> >>> >> I might even base the penalty on lambda(2)*trace(S)^2 +
>>> >>> >> lambda(1)*trace(S*S'), which is often used as a measure of
>>> >>> >> "elastic
>>> >>> >> energy" for penalising non-linear registration. =A0Of course, th=
ere
>>> >>> >> would also be a bit of annoying extra stuff to deal with due to
>>> >>> >> MNI
>>> >>> >> space being a bit bigger than average brains are. =A0Figuring ou=
t
>>> >>> >> the
>>> >>> >> mean would require (I think) an iterative process similar to the
>>> >>> >> one
>>> >>> >> described in "Characterizing volume and surface deformations in =
an
>>> >>> >> atlas framework: theory, applications, and implementation", by
>>> >>> >> Woods
>>> >>> >> in NeuroImage (2003).
>>> >>> >>
>>> >>> >> Best regards,
>>> >>> >> -John
>>> >>> >>
>>> >>> >> On 14 April 2011 17:15, Siddharth Srivastava <[log in to unmask]>
>>> >>> >> wrote:
>>> >>> >> > Hi all,
>>> >>> >> > =A0=A0=A0=A0 My question pertains specifically to the values o=
f isig and
>>> >>> >> > mu
>>> >>> >> > that
>>> >>> >> > are
>>> >>> >> > incorporated
>>> >>> >> > in the code, and I wish to disentangle the effect that these
>>> >>> >> > numbers
>>> >>> >> > have on
>>> >>> >> > individual parameters
>>> >>> >> > during the optimization stage. I am trying to map it to a 2D
>>> >>> >> > case,
>>> >>> >> > and
>>> >>> >> > these
>>> >>> >> > numbers
>>> >>> >> > will have to be calculated ab-initio for my case. Before I beg=
in
>>> >>> >> > with
>>> >>> >> > estimating the prior distribution
>>> >>> >> > for these parameters, I need to check the effect that they hav=
e
>>> >>> >> > on
>>> >>> >> > the
>>> >>> >> > registered images. Regarding this
>>> >>> >> > 1) Can someone suggest a way I can examine the effect on each
>>> >>> >> > parameter
>>> >>> >> > separately, if it is
>>> >>> >> > =A0=A0=A0=A0 at all possible.
>>> >>> >> > 2) Some advise on how to estimate these parameters, if it has
>>> >>> >> > been
>>> >>> >> > done
>>> >>> >> > for
>>> >>> >> > images other
>>> >>> >> > =A0=A0=A0=A0 than brain images, will be really helpful for me.
>>> >>> >> >
>>> >>> >> > Thanks,
>>> >>> >> > Sid.
>>> >>> >> >
>>> >>> >> > On Mon, Mar 28, 2011 at 7:04 PM, Siddharth Srivastava
>>> >>> >> > <[log in to unmask]>
>>> >>> >> > wrote:
>>> >>> >> >>
>>> >>> >> >> Dear John,
>>> >>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 Thanks for your answer. I was abl=
e to correctly run
>>> >>> >> >> my 2D
>>> >>> >> >> implementation
>>> >>> >> >> based on your advise. However, I am am not very confident of =
my
>>> >>> >> >> results
>>> >>> >> >> and wanted to
>>> >>> >> >> consult you on certain aspects of my mapping from 3D to 2D.
>>> >>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 1) In function reg(..), the co=
mment says that the
>>> >>> >> >> derivatives
>>> >>> >> >> w.r.t rotations and
>>> >>> >> >> translations is zero. Consequently, I ran the indices from 4:=
7.
>>> >>> >> >> According
>>> >>> >> >> to your previous
>>> >>> >> >> reply, rotations will be lumped together with scaling and
>>> >>> >> >> affine in
>>> >>> >> >> 4
>>> >>> >> >> parameters, and
>>> >>> >> >> translations, independently, in the last two. I understand th=
at
>>> >>> >> >> in
>>> >>> >> >> this
>>> >>> >> >> case, the indices
>>> >>> >> >> run over parameters that have been separated into individual
>>> >>> >> >> components
>>> >>> >> >> (similar to
>>> >>> >> >> the form accepted by spm_matrix). Is this correct for the
>>> >>> >> >> function
>>> >>> >> >> reg(..)?=A0 In fact, I went back to the
>>> >>> >> >> old spm code (spm99), and found parameters pdesc and free, an=
d
>>> >>> >> >> got
>>> >>> >> >> more
>>> >>> >> >> confused as to when I should
>>> >>> >> >> use the 6 parameter, and when to use separate parameters (as =
if
>>> >>> >> >> I
>>> >>> >> >> was
>>> >>> >> >> passing them to spm_matrix).
>>> >>> >> >> So, when the loop runs over p1 and perturbs p1(i) by ds, does
>>> >>> >> >> it
>>> >>> >> >> run
>>> >>> >> >> over
>>> >>> >> >> translations/rotations etc
>>> >>> >> >> or does it run over the martix elements that define these
>>> >>> >> >> transformations
>>> >>> >> >> (2x2 + 1x2)?
>>> >>> >> >>
>>> >>> >> >> =A0 =A0 =A0 =A0 =A0=A0 2) In function penalty(..), I have use=
d unique
>>> >>> >> >> elements
>>> >>> >> >> as
>>> >>> >> >> [1,3,4], and my code looks like
>>> >>> >> >> T =3D my_matrix(p)*M;
>>> >>> >> >> T =3D T(1:2,1:2);
>>> >>> >> >> T =3D 0.5*logm(T'*T);
>>> >>> >> >> T
>>> >>> >> >> T =3D T(els)' - mu;
>>> >>> >> >> h =3D T'*isig*T
>>> >>> >> >>
>>> >>> >> >> Assuming an application specific isig, is this correct?
>>> >>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0 3) I have not yet incorporated the p=
rior information
>>> >>> >> >> in my
>>> >>> >> >> code,
>>> >>> >> >> But for testing purposes,
>>> >>> >> >> can you suggest some neutral values=A0 for mu and isig that I=
can
>>> >>> >> >> try
>>> >>> >> >> to
>>> >>> >> >> concentrate on the
>>> >>> >> >> accuracy of the implementation minus the priors for now?
>>> >>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 4) My solution curently seems to =
oscillate around an
>>> >>> >> >> optimum.
>>> >>> >> >> I
>>> >>> >> >> am hoping that after
>>> >>> >> >> I have removed any errors after your replies, it will converg=
e
>>> >>> >> >> gracefully.
>>> >>> >> >>
>>> >>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0 Thanks again for all the help.
>>> >>> >> >> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 Siddharth.
>>> >>> >> >>
>>> >>> >> >>
>>> >>> >> >> On Fri, Mar 18, 2011 at 2:05 AM, John Ashburner
>>> >>> >> >> <[log in to unmask]>
>>> >>> >> >> wrote:
>>> >>> >> >>>
>>> >>> >> >>> A 2D affine transform would use 6 parameters, rather than 7:=
a
>>> >>> >> >>> 2x2
>>> >>> >> >>> matrix to encode rotations, zooms and shears, and a 2x1 vect=
or
>>> >>> >> >>> for
>>> >>> >> >>> translations.
>>> >>> >> >>>
>>> >>> >> >>> Best regards,
>>> >>> >> >>> -John
>>> >>> >> >>>
>>> >>> >> >>> On 18 March 2011 05:05, Siddharth Srivastava
>>> >>> >> >>> <[log in to unmask]>
>>> >>> >> >>> wrote:
>>> >>> >> >>> > Dear list users,
>>> >>> >> >>> > =A0=A0=A0=A0=A0=A0=A0=A0=A0 I am currently trying to under=
stand the
>>> >>> >> >>> > implementation
>>> >>> >> >>> > in
>>> >>> >> >>> > spm_affreg, and
>>> >>> >> >>> > to make matters simple, I tried to work out a 2D version o=
f
>>> >>> >> >>> > the
>>> >>> >> >>> > registration
>>> >>> >> >>> > procedure. I struck a roadblock, however...
>>> >>> >> >>> >
>>> >>> >> >>> > The function make_A creates part of the design matrix. For
>>> >>> >> >>> > the
>>> >>> >> >>> > 3D
>>> >>> >> >>> > case,
>>> >>> >> >>> > the
>>> >>> >> >>> > 13 parameters
>>> >>> >> >>> > are encoded in columns of A1, which then is used to genera=
te
>>> >>> >> >>> > AA
>>> >>> >> >>> > +
>>> >>> >> >>> > A1'
>>> >>> >> >>> > A1. AA
>>> >>> >> >>> > is 13x13, and everything
>>> >>> >> >>> > works. For the 2D case, however, there will be 7+1
>>> >>> >> >>> > parameters( 2
>>> >>> >> >>> > translations, 1 rotation, 2 zoom, 2 shears and 1 intensity
>>> >>> >> >>> > scaling).
>>> >>> >> >>> > The A1 matrix for 2D, then,=A0 will be (in make_A)
>>> >>> >> >>> > A=A0 =3D [x1.*dG1 x1.*dG2 ...
>>> >>> >> >>> > =A0=A0=A0=A0=A0 x2.*dG1 x2.*dG2 ...
>>> >>> >> >>> > =A0=A0=A0 =A0 dG1=A0=A0=A0=A0 dG2=A0 t];
>>> >>> >> >>> >
>>> >>> >> >>> > which is (number of sampled points) x 7. The AA matrix (in
>>> >>> >> >>> > function
>>> >>> >> >>> > costfun)
>>> >>> >> >>> > is 8x8
>>> >>> >> >>> > so, which is the parameter I am missing in modeling a 2D
>>> >>> >> >>> > example? I
>>> >>> >> >>> > hope I
>>> >>> >> >>> > have got the number of parameters
>>> >>> >> >>> > right for the 2D case? Is there an extra column that I hav=
e
>>> >>> >> >>> > to
>>> >>> >> >>> > add
>>> >>> >> >>> > to
>>> >>> >> >>> > A1 to
>>> >>> >> >>> > make the rest of the matrix computation
>>> >>> >> >>> > consistent?
>>> >>> >> >>> >
>>> >>> >> >>> > Thanks for the help
>>> >>> >> >>> >
>>> >>> >> >>
>>> >>> >> >
>>> >>> >> >
>>> >>> >
>>> >>> >
>>> >>
>>> >
>>> >
>>
>
>
=========================================================================
Date: Tue, 10 May 2011 16:37:48 +0100
Reply-To: Lorelei Howard <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Lorelei Howard <[log in to unmask]>
Subject: contrast specification error
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/mixed;boundary="----=_20110510163748_41792"
Message-ID: <[log in to unmask]>
------=_20110510163748_41792
Content-Type: text/plain; charset="iso-8859-1"
Content-Transfer-Encoding: 8bit
Hi everyone,
I am getting an error that I can't diagnose... any help would be appreciated.
Attached are the .mat files for a first level specification. Everything
seems to be running fine until it gets to contrast 11 when it crashes. The
only hint at a problem I have is from looking at the design matrix (image
also attached). Contrast 11 is '1' contrast above the regressor in session
2 where there looks like there is a problem. I've looked at my code, the
mat files attached, and the matlabbatch stucture generated by my script to
specify all the .mat files and i can't find a problem.
Anyone have any idea what's going on?
Thanks,
Lorelei
--
Lorelei Howard
Ph.D. Student
Institute of Behavioural Neuroscience
Cognitive, Perceptual and Brain Sciences Department
University College London
26 Bedford Way
WC1H 0AP
+44 (0)20 7679 8553
------=_20110510163748_41792
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------=_20110510163748_41792--
=========================================================================
Date: Tue, 10 May 2011 11:48:33 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: contrast specification error
Comments: To: Lorelei Howard <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=002354186d846eacec04a2ede3cd
Message-ID: <[log in to unmask]>
--002354186d846eacec04a2ede3cd
Content-Type: text/plain; charset=ISO-8859-1
That column looks to be all 0s. This is the problem.
Basically, you can't form a contrast for a regressor that does not exist.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Tue, May 10, 2011 at 11:37 AM, Lorelei Howard <[log in to unmask]> wrote:
> Hi everyone,
>
> I am getting an error that I can't diagnose... any help would be
> appreciated.
>
> Attached are the .mat files for a first level specification. Everything
> seems to be running fine until it gets to contrast 11 when it crashes. The
> only hint at a problem I have is from looking at the design matrix (image
> also attached). Contrast 11 is '1' contrast above the regressor in session
> 2 where there looks like there is a problem. I've looked at my code, the
> mat files attached, and the matlabbatch stucture generated by my script to
> specify all the .mat files and i can't find a problem.
>
> Anyone have any idea what's going on?
>
> Thanks,
> Lorelei
>
>
>
>
> --
> Lorelei Howard
>
> Ph.D. Student
>
> Institute of Behavioural Neuroscience
> Cognitive, Perceptual and Brain Sciences Department
> University College London
> 26 Bedford Way
> WC1H 0AP
> +44 (0)20 7679 8553
--002354186d846eacec04a2ede3cd
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
That column looks to be all 0s. This is the problem. <br><br>Basically, you=
can't form a contrast for a regressor that does not exist.<br clear=3D=
"all"><br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>
Postdoctoral Research Fellow, GRECC, Bedford VA<br>Research Fellow, Departm=
ent of Neurology, Massachusetts General Hospital and Harvard Medical School=
<br>Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which m=
ay contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILE=
GED and which is intended only for the use of the individual or entity name=
d above. If the reader of the e-mail is not the intended recipient or the e=
mployee or agent responsible for delivering it to the intended recipient, y=
ou are hereby notified that you are in possession of confidential and privi=
leged information. Any unauthorized use, disclosure, copying or the taking =
of any action in reliance on the contents of this information is strictly p=
rohibited and may be unlawful. If you have received this e-mail unintention=
ally, please immediately notify the sender via telephone at (773) 406-2464 =
or email.<br>
<br><br><div class=3D"gmail_quote">On Tue, May 10, 2011 at 11:37 AM, Lorele=
i Howard <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">l.howa=
[log in to unmask]</a>></span> wrote:<br><blockquote class=3D"gmail_quote" sty=
le=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204);=
padding-left: 1ex;">
Hi everyone,<br>
<br>
I am getting an error that I can't diagnose... any help would be apprec=
iated.<br>
<br>
Attached are the .mat files for a first level specification. Everything<br>
seems to be running fine until it gets to contrast 11 when it crashes. The<=
br>
only hint at a problem I have is from looking at the design matrix (image<b=
r>
also attached). Contrast 11 is '1' contrast above the regressor in =
session<br>
2 where there looks like there is a problem. I've looked at my code, th=
e<br>
mat files attached, and the matlabbatch stucture generated by my script to<=
br>
specify all the .mat files and i can't find a problem.<br>
<br>
Anyone have any idea what's going on?<br>
<br>
Thanks,<br>
Lorelei<br>
<br>
<br>
<br>
<br>
--<br>
Lorelei Howard<br>
<br>
Ph.D. Student<br>
<br>
Institute of Behavioural Neuroscience<br>
Cognitive, Perceptual and Brain Sciences Department<br>
University College London<br>
26 Bedford Way<br>
WC1H 0AP<br>
<a href=3D"tel:%2B44%20%280%2920%207679%208553" value=3D"+442076798553">+44=
(0)20 7679 8553</a></blockquote></div><br>
--002354186d846eacec04a2ede3cd--
=========================================================================
Date: Tue, 10 May 2011 16:56:24 +0100
Reply-To: Lorelei Howard <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Lorelei Howard <[log in to unmask]>
Subject: Re: contrast specification error
Comments: To: "MCLAREN, Donald" <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/mixed;boundary="----=_20110510165623_38470"
Message-ID: <[log in to unmask]>
------=_20110510165623_38470
Content-Type: text/plain; charset="iso-8859-1"
Content-Transfer-Encoding: 8bit
Dear Donald I appreciate the reply, thank you. I was aware that it is a
column of zeros. The problem is that I am unsure why this is. As I said in
the previous email, all my specification seems to be working correctly.
The .mat files I attached to the previous email may not come through as I
got an error message through after sending the email. I will try to attach
these again here and also a copy of my script and the .mat files they use
for regressor specification for the first subject (where the error is
occuring).
Thanks,
Lorelei
> That column looks to be all 0s. This is the problem.
>
> Basically, you can't form a contrast for a regressor that does not exist.
>
> Best Regards, Donald McLaren
> =================
> D.G. McLaren, Ph.D.
> Postdoctoral Research Fellow, GRECC, Bedford VA
> Research Fellow, Department of Neurology, Massachusetts General Hospital
> and
> Harvard Medical School
> Office: (773) 406-2464
> =====================
> This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
> HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
> intended only for the use of the individual or entity named above. If the
> reader of the e-mail is not the intended recipient or the employee or
> agent
> responsible for delivering it to the intended recipient, you are hereby
> notified that you are in possession of confidential and privileged
> information. Any unauthorized use, disclosure, copying or the taking of
> any
> action in reliance on the contents of this information is strictly
> prohibited and may be unlawful. If you have received this e-mail
> unintentionally, please immediately notify the sender via telephone at
> (773)
> 406-2464 or email.
>
>
> On Tue, May 10, 2011 at 11:37 AM, Lorelei Howard <[log in to unmask]>
> wrote:
>
>> Hi everyone,
>>
>> I am getting an error that I can't diagnose... any help would be
>> appreciated.
>>
>> Attached are the .mat files for a first level specification. Everything
>> seems to be running fine until it gets to contrast 11 when it crashes.
>> The
>> only hint at a problem I have is from looking at the design matrix
>> (image
>> also attached). Contrast 11 is '1' contrast above the regressor in
>> session
>> 2 where there looks like there is a problem. I've looked at my code, the
>> mat files attached, and the matlabbatch stucture generated by my script
>> to
>> specify all the .mat files and i can't find a problem.
>>
>> Anyone have any idea what's going on?
>>
>> Thanks,
>> Lorelei
>>
>>
>>
>>
>> --
>> Lorelei Howard
>>
>> Ph.D. Student
>>
>> Institute of Behavioural Neuroscience
>> Cognitive, Perceptual and Brain Sciences Department
>> University College London
>> 26 Bedford Way
>> WC1H 0AP
>> +44 (0)20 7679 8553
>
--
Lorelei Howard
Ph.D. Student
Institute of Behavioural Neuroscience
Cognitive, Perceptual and Brain Sciences Department
University College London
26 Bedford Way
WC1H 0AP
+44 (0)20 7679 8553
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=========================================================================
Date: Tue, 10 May 2011 17:03:36 +0100
Reply-To: Marta Garrido <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Marta Garrido <[log in to unmask]>
Subject: Re: DCM question
Comments: To: Keith Kawabata Duncan <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf30549f05459f9604a2ee19ab
Message-ID: <[log in to unmask]>
--20cf30549f05459f9604a2ee19ab
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Hi Keith,
If you are interested in model comparison, then I'd say you can use
whichever number of subjects, irrespectively of the number of connections.
In fact, you can make statistical inferences about models in only one
individual subject.
However, if you then want to go on and do classical statistical tests on the
connectivity parameters, then it might be a good idea to increase the number
subjects/parameters per cell.
I'm CCing this to the SPM list in case other people want to comment on it.
Hope this helps!
Marta
On 9 May 2011 10:44, Keith Kawabata Duncan <[log in to unmask]> wrote:
> Hi Marta,
>
> Maria thought you might be able to help me with a DCM question. I was
> wondering if increasing the number of connections in a model requires
> increasing the number of subjects - a bit like increasing the number of
> cells in a factorial design?
>
> Keith
>
--
Dr. Marta I. Garrido
Research Associate
Wellcome Trust Centre for Neuroimaging
University College London
12 Queen Square
London
WC1N 3BG
United Kingdom
Tel: +44(0)20 7833 7472 (ext: 4366)
Fax: +44(0)20 7813 1420
Email: [log in to unmask]
www: http://www.fil.ion.ucl.ac.uk
--20cf30549f05459f9604a2ee19ab
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Hi Keith,<br><br>If you are interested in model comparison, then I'd sa=
y you can use whichever number of subjects, irrespectively of the number of=
connections. In fact, you can make statistical inferences about models in =
only one individual subject. <br>
However, if you then want to go on and do classical statistical tests on th=
e connectivity parameters, then it might be a good idea to increase the num=
ber subjects/parameters per cell.<br><br>I'm CCing this to the SPM list=
in case other people want to comment on it.<br>
Hope this helps!<br>
<br>Marta<br><br><br><div class=3D"gmail_quote">On 9 May 2011 10:44, Keith =
Kawabata Duncan <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]"=
target=3D"_blank">[log in to unmask]</a>></span> wrote:<br><blockquote =
class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1px #ccc solid=
;padding-left:1ex">
=A0Hi Marta,<br>
<br>
Maria thought you might be able to help me with a DCM question. I was wonde=
ring if increasing the number of connections in a model requires increasing=
the number of subjects - a bit like increasing the number of cells in a fa=
ctorial design?<br>
<font color=3D"#888888">
<br>
Keith<br>
</font></blockquote></div><br><br clear=3D"all"><br>-- <br>Dr. Marta I. Gar=
rido<br>Research Associate<br>Wellcome Trust Centre for Neuroimaging<br>Uni=
versity College London<br>12 Queen Square<br>London<br>WC1N 3BG<br>United K=
ingdom<br>
<br>Tel: +44(0)20 7833 7472 (ext: 4366)<br>Fax: +44(0)20 7813 1420<br>Email=
: <a href=3D"mailto:[log in to unmask]" target=3D"_blank">m.garrid=
[log in to unmask]</a><br>www: <a href=3D"http://www.fil.ion.ucl.ac.uk" ta=
rget=3D"_blank">http://www.fil.ion.ucl.ac.uk</a><br>
<br>
--20cf30549f05459f9604a2ee19ab--
=========================================================================
Date: Tue, 10 May 2011 18:22:48 +0200
Reply-To: Marine Lazouret <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Marine Lazouret <[log in to unmask]>
Subject: reverse from MNI space to native space
Comments: cc: Marie-Christine Ottet <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/mixed; boundary=90e6ba6e8d42e9620004a2ee5db4
Message-ID: <[log in to unmask]>
--90e6ba6e8d42e9620004a2ee5db4
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--90e6ba6e8d42e961f004a2ee5db2
Content-Type: text/plain; charset=ISO-8859-1
Dear SPMers,
We would like to extract the activation clusters for each subject in its own
native space.
I need to transform back the activation clusters from MNI to native space.
I tried using the deformation batch but I'm not sure which images to use in
"Apply to", the originally normalized images?
For the parameter file I should use the seg_inv_sn file right?
Should I keep the default parameters for bounding box and voxel size?
I added the screen shot of the batch to make myself more clear,
Best Regards,
--
*Marine*
--90e6ba6e8d42e961f004a2ee5db2
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Dear SPMers,<div><br></div><div>We would like to extract the activation clu=
sters for each subject in its own native space.<br><div>I need to transform=
back the activation clusters from MNI to native space.</div><div>I tried u=
sing the deformation batch but I'm not sure which images to use in &quo=
t;Apply to", the originally normalized images?</div>
<div>For the parameter file I should use the seg_inv_sn file right?</div><d=
iv>Should I keep the default parameters for bounding box and voxel size?</d=
iv><div><br></div><div>I added the screen shot of the batch to make myself =
more clear,</div>
<div><font class=3D"Apple-style-span" face=3D"monospace"><span class=3D"App=
le-style-span" style=3D"white-space: pre-wrap;"><font class=3D"Apple-style-=
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e=3D"monospace"><span class=3D"Apple-style-span" style=3D"white-space: pre-=
wrap;"><font class=3D"Apple-style-span" face=3D"arial"><span class=3D"Apple=
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an></font></div>
<div><br>-- <br><b><i><font face=3D"georgia, serif">Marine</font></i></b><b=
r>
</div></div>
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--90e6ba6e8d42e9620004a2ee5db4--
=========================================================================
Date: Tue, 10 May 2011 18:32:38 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: reverse from MNI space to native space
Comments: To: Marine Lazouret <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
You may want to add an additional component to the job, (by selecting
"Identity (reference image)". This should make sure that the inverse
warped images are written out with the same dimensions etc as the
reference image that you select.
You would use the seg_inv_sn file, and if the idea is to warp t
statistic images back to native space, you'd specify the spmT images
that you hope to inverse warp. I would suggest leaving the bounding
box and voxel sizes as they are.
Overall, the batch (if saved as a .m file) should have the following structure:
matlabbatch{1}.spm.util.defs.comp{1}.sn2def.matname = {'image_seg_inv_sn.mat'};
matlabbatch{1}.spm.util.defs.comp{1}.sn2def.vox = [NaN NaN NaN];
matlabbatch{1}.spm.util.defs.comp{1}.sn2def.bb = [NaN NaN NaN
NaN NaN NaN];
matlabbatch{1}.spm.util.defs.comp{2}.id.space = {'image.nii,1'};
matlabbatch{1}.spm.util.defs.ofname = '';
matlabbatch{1}.spm.util.defs.fnames = {'wimage.nii,1'};
matlabbatch{1}.spm.util.defs.savedir.savepwd = 1;
matlabbatch{1}.spm.util.defs.interp = 1;
Best regards,
-John
On 10 May 2011 17:22, Marine Lazouret <[log in to unmask]> wrote:
> Dear SPMers,
> We would like to extract the activation clusters for each subject in its own
> native space.
> I need to transform back the activation clusters from MNI to native space.
> I tried using the deformation batch but I'm not sure which images to use in
> "Apply to", the originally normalized images?
> For the parameter file I should use the seg_inv_sn file right?
> Should I keep the default parameters for bounding box and voxel size?
> I added the screen shot of the batch to make myself more clear,
> Best Regards,
> --
> Marine
>
=========================================================================
Date: Tue, 10 May 2011 19:51:18 +0100
Reply-To: Andrew Westphal <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Andrew Westphal <[log in to unmask]>
Subject: Con Image Issue - Validity
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Hello fellow SPM users,
With some investigation into con images, my lab found that con images app=
ear to be sums of the beta images that one specifies depending on the wei=
ght that is assigned (i.e. 1 0 0 0 0 1 0 0 0 0 - you would add the two be=
ta images together). This appears to be the way it is calculated instead =
of a mean value. So does SPM account for the fact that subjects will have=
varied block counts, such as one subject having 5 sessions and another h=
aving 2 sessions? Or is the subject with 5 sessions going to contribute 2=
.5 times as much at the group level as the subject with two sessions? For=
it to be valid, does one have to put in a contrast vector like 1/5 0 0 0=
0 1/5 0 0 for the 5 session subject and 1/2 0 0 0 0 1/2 0 0 for the 2 se=
ssion subject?
Andrew
=========================================================================
Date: Tue, 10 May 2011 15:09:42 -0400
Reply-To: Bedda Rosario <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Bedda Rosario <[log in to unmask]>
Subject: Cluster information without corresponding SPM.mat
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=90e6ba6e8eccc8748304a2f0b2a2
Message-ID: <[log in to unmask]>
--90e6ba6e8eccc8748304a2f0b2a2
Content-Type: text/plain; charset=ISO-8859-1
Dear SPM users,
I have created an image (and hdr file) using the results of a t test
analysis in SPM8 (that is, using spmT_0001.img). I would like to know if it
possible to get a cluster report from the image without a corresponding
SPM.mat file.
Thanks for the help,
Bedda
--90e6ba6e8eccc8748304a2f0b2a2
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Dear SPM users, <br><br>I have created an image (and hdr file) using the re=
sults of a t test analysis in SPM8 (that is, using spmT_0001.img).=A0 I wou=
ld like to know if it possible to get a cluster report from the image witho=
ut a corresponding SPM.mat file.=A0 <br>
<br>Thanks for the help, <br>Bedda<br>
--90e6ba6e8eccc8748304a2f0b2a2--
=========================================================================
Date: Tue, 10 May 2011 15:11:50 -0400
Reply-To: zhang sheng <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: zhang sheng <[log in to unmask]>
Subject: Flexible factorial questions
MIME-Version: 1.0
Content-Type: multipart/mixed; boundary=0016e657b16a74e69304a2f0bae2
Message-ID: <[log in to unmask]>
--0016e657b16a74e69304a2f0bae2
Content-Type: multipart/alternative; boundary=0016e657b16a74e68504a2f0bae0
--0016e657b16a74e68504a2f0bae0
Content-Type: text/plain; charset=ISO-8859-1
Dear all,
I have a problem for the Flexible factorial analysis.
In second level analysis, I tried to do a Flexible factorial analysis with
two factors: "group" (e.g. patient vs. control) and "gender". So in the
design, I have three factors: subject, group, and gender. As I have only one
scan for each subject, the factor matrices should be [1 1] for group1 and
male, [1 2] for group1 and female, [2 1] for group2 and male, and [2 2] for
group2 and female for each subject (see attached file for design matrix)?
However, when I estimated the model, I got an error message: *Please check*your
*data*: *There* are *no significant voxels. *So, first, did I do something
wrong with the model design? If I'm right, could someone tell me what
happened for the estimating?
Thanks, and any suggestion is highly appreciated!
Sheng
--0016e657b16a74e68504a2f0bae0
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Dear all,<br><br>I have a problem for the Flexible factorial analysis. <br>=
<br>In second level analysis, I tried to do a Flexible factorial analysis w=
ith two factors: "group" (e.g. patient vs. control) and "gen=
der". So in the design, I have three factors: subject, group, and gend=
er. As I have only one scan for each subject, the factor matrices should be=
[1 1] for group1 and male, [1 2] for group1 and female, [2 1] for group2 a=
nd male, and [2 2] for group2 and female for each subject (see attached fil=
e for design matrix)? However, when I estimated the model, I got an error m=
essage: <em>Please check</em> your <em>data</em>: <em>There</em> are <em>no=
significant voxels.=A0</em>So, first, did I do something wrong with the mo=
del design? If I'm right, could someone tell me what happened for the e=
stimating? <br>
<br>Thanks, and any suggestion is highly appreciated!<br><br>Sheng<br>=20
--0016e657b16a74e68504a2f0bae0--
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--0016e657b16a74e69304a2f0bae2--
=========================================================================
Date: Tue, 10 May 2011 16:46:23 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Con Image Issue - Validity
Comments: To: Andrew Westphal <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0023545309c897c1ed04a2f20c06
Message-ID: <[log in to unmask]>
--0023545309c897c1ed04a2f20c06
Content-Type: text/plain; charset=ISO-8859-1
Andrew,
If you are wanting to say what the activity is in a subject, the best thing
to do is to average across runs based on the number of trials. If its a
block design, you probably have equal number of blocks in each run, and it
can be simplified to averaging across runs.
The idea of using 1s and 0s was simple that it was easier than entering
fractions and as long as all subjects had the same number of runs, then it
wasn't a problem. Additionally, the spmT or spmF maps are the same for the
1s and 0s or if you use 1/N and 0s where N is the numebr of runs.
Since you want to compare across subjects with varying numbers of
runs/sessions, you need to make the sum of the contrast (assuming its A
versus baseline) equal to 1.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Tue, May 10, 2011 at 2:51 PM, Andrew Westphal <[log in to unmask]>wrote:
> Hello fellow SPM users,
>
> With some investigation into con images, my lab found that con images
> appear to be sums of the beta images that one specifies depending on the
> weight that is assigned (i.e. 1 0 0 0 0 1 0 0 0 0 - you would add the two
> beta images together). This appears to be the way it is calculated instead
> of a mean value. So does SPM account for the fact that subjects will have
> varied block counts, such as one subject having 5 sessions and another
> having 2 sessions? Or is the subject with 5 sessions going to contribute 2.5
> times as much at the group level as the subject with two sessions? For it to
> be valid, does one have to put in a contrast vector like 1/5 0 0 0 0 1/5 0 0
> for the 5 session subject and 1/2 0 0 0 0 1/2 0 0 for the 2 session subject?
>
> Andrew
>
--0023545309c897c1ed04a2f20c06
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Andrew,<br><br>If you are wanting to say what the activity is in a subject,=
the best thing to do is to average across runs based on the number of tria=
ls. If its a block design, you probably have equal number of blocks in each=
run, and it can be simplified to averaging across runs.<br>
<br>The idea of using 1s and 0s was simple that it was easier than entering=
fractions and as long as all subjects had the same number of runs, then it=
wasn't a problem. Additionally, the spmT or spmF maps are the same for=
the 1s and 0s or if you use 1/N and 0s where N is the numebr of runs.<br>
<br>Since you want to compare across subjects with varying numbers of runs/=
sessions, you need to make the sum of the contrast (assuming its A versus b=
aseline) equal to 1.<br clear=3D"all"><br>Best Regards, Donald McLaren<br>
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<=
br>Postdoctoral Research Fellow, GRECC, Bedford VA<br>Research Fellow, Depa=
rtment of Neurology, Massachusetts General Hospital and Harvard Medical Sch=
ool<br>Office: (773) 406-2464<br>
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D<br>This e-m=
ail contains CONFIDENTIAL INFORMATION which may contain PROTECTED HEALTHCAR=
E INFORMATION and may also be LEGALLY PRIVILEGED and which is intended only=
for the use of the individual or entity named above. If the reader of the =
e-mail is not the intended recipient or the employee or agent responsible f=
or delivering it to the intended recipient, you are hereby notified that yo=
u are in possession of confidential and privileged information. Any unautho=
rized use, disclosure, copying or the taking of any action in reliance on t=
he contents of this information is strictly prohibited and may be unlawful.=
If you have received this e-mail unintentionally, please immediately notif=
y the sender via telephone at (773) 406-2464 or email.<br>
<br><br><div class=3D"gmail_quote">On Tue, May 10, 2011 at 2:51 PM, Andrew =
Westphal <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">aj=
[log in to unmask]</a>></span> wrote:<br><blockquote class=3D"gmail_qu=
ote" style=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 20=
4, 204); padding-left: 1ex;">
Hello fellow SPM users,<br>
<br>
With some investigation into con images, my lab found that con images appea=
r to be sums of the beta images that one specifies depending on the weight =
that is assigned (i.e. 1 0 0 0 0 1 0 0 0 0 - you would add the two beta ima=
ges together). This appears to be the way it is calculated instead of a mea=
n value. So does SPM account for the fact that subjects will have varied bl=
ock counts, such as one subject having 5 sessions and another having 2 sess=
ions? Or is the subject with 5 sessions going to contribute 2.5 times as mu=
ch at the group level as the subject with two sessions? For it to be valid,=
does one have to put in a contrast vector like 1/5 0 0 0 0 1/5 0 0 for the=
5 session subject and 1/2 0 0 0 0 1/2 0 0 for the 2 session subject?<br>
<font color=3D"#888888"><br>
Andrew<br>
</font></blockquote></div><br>
--0023545309c897c1ed04a2f20c06--
=========================================================================
Date: Tue, 10 May 2011 21:59:55 +0100
Reply-To: Andrew Westphal <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Andrew Westphal <[log in to unmask]>
Subject: Re: Con Image Issue - Validity
Comments: To: Donald McLaren <[log in to unmask]>
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Dear Dr. McLaren,
Thanks for responding to me. The design is event-related with varying num=
bers of sessions due to blocks being removed due to movement and such. Is=
the weighting with whole integers still a problem in the second level an=
alysis if the contrast sums to zero? For example, 2 session subject (1 -1=
0 0 1 -1 0 0) and 5 session subject (1 -1 0 0 1 -1 0 0 1 -1 0 0 1 -1 0 0=
1 -1 0 0).
Andrew
=========================================================================
Date: Tue, 10 May 2011 17:05:09 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Con Image Issue - Validity
Comments: To: Andrew Westphal <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0015174beb46b4a85904a2f24f2c
Message-ID: <[log in to unmask]>
--0015174beb46b4a85904a2f24f2c
Content-Type: text/plain; charset=ISO-8859-1
You want the positives to sum to 1 and the negatives sum to 1.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Tue, May 10, 2011 at 4:59 PM, Andrew Westphal <[log in to unmask]>wrote:
> Dear Dr. McLaren,
>
> Thanks for responding to me. The design is event-related with varying
> numbers of sessions due to blocks being removed due to movement and such. Is
> the weighting with whole integers still a problem in the second level
> analysis if the contrast sums to zero? For example, 2 session subject (1 -1
> 0 0 1 -1 0 0) and 5 session subject (1 -1 0 0 1 -1 0 0 1 -1 0 0 1 -1 0 0 1
> -1 0 0).
>
> Andrew
>
>
>
--0015174beb46b4a85904a2f24f2c
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
You want the positives to sum to 1 and the negatives sum to 1.<br clear=3D"=
all"><br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdoctoral Research Fellow, =
GRECC, Bedford VA<br>Research Fellow, Department of Neurology, Massachusett=
s General Hospital and Harvard Medical School<br>
Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which may =
contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED=
and which is intended only for the use of the individual or entity named a=
bove. If the reader of the e-mail is not the intended recipient or the empl=
oyee or agent responsible for delivering it to the intended recipient, you =
are hereby notified that you are in possession of confidential and privileg=
ed information. Any unauthorized use, disclosure, copying or the taking of =
any action in reliance on the contents of this information is strictly proh=
ibited and may be unlawful. If you have received this e-mail unintentionall=
y, please immediately notify the sender via telephone at (773) 406-2464 or =
email.<br>
<br><br><div class=3D"gmail_quote">On Tue, May 10, 2011 at 4:59 PM, Andrew =
Westphal <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">aj=
[log in to unmask]</a>></span> wrote:<br><blockquote class=3D"gmail_qu=
ote" style=3D"margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex=
;">
Dear Dr. McLaren,<br>
<br>
Thanks for responding to me. The design is event-related with varying numbe=
rs of sessions due to blocks being removed due to movement and such. Is the=
weighting with whole integers still a problem in the second level analysis=
if the contrast sums to zero? For example, 2 session subject (1 -1 0 0 1 -=
1 0 0) and 5 session subject (1 -1 0 0 1 -1 0 0 1 -1 0 0 1 -1 0 0 1 -1 0 0)=
.<br>
<font color=3D"#888888"><br>
Andrew<br>
<br>
<br>
</font></blockquote></div><br>
--0015174beb46b4a85904a2f24f2c--
=========================================================================
Date: Tue, 10 May 2011 17:21:42 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Cluster information without corresponding SPM.mat
Comments: To: Bedda Rosario <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0023545309c8d97cc104a2f28a9c
Message-ID: <[log in to unmask]>
--0023545309c8d97cc104a2f28a9c
Content-Type: text/plain; charset=ISO-8859-1
See the following posts:
http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=ind1103&L=SPM&P=R25661&I=-3&d=No+Match%3BMatch%3BMatches&m=41734
http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=ind1103&L=SPM&P=R16468&I=-3&d=No+Match%3BMatch%3BMatches&m=41734
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Tue, May 10, 2011 at 3:09 PM, Bedda Rosario <[log in to unmask]> wrote:
> Dear SPM users,
>
> I have created an image (and hdr file) using the results of a t test
> analysis in SPM8 (that is, using spmT_0001.img). I would like to know if it
> possible to get a cluster report from the image without a corresponding
> SPM.mat file.
>
> Thanks for the help,
> Bedda
>
--0023545309c8d97cc104a2f28a9c
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
See the following posts:<div><a href=3D"http://www.jiscmail.ac.uk/cgi-bin/w=
a.exe?A2=3Dind1103&L=3DSPM&P=3DR25661&I=3D-3&d=3DNo+Match%3=
BMatch%3BMatches&m=3D41734">http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=
=3Dind1103&L=3DSPM&P=3DR25661&I=3D-3&d=3DNo+Match%3BMatch%3=
BMatches&m=3D41734</a></div>
<div><br></div><div><a href=3D"http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=
=3Dind1103&L=3DSPM&P=3DR16468&I=3D-3&d=3DNo+Match%3BMatch%3=
BMatches&m=3D41734">http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3Dind11=
03&L=3DSPM&P=3DR16468&I=3D-3&d=3DNo+Match%3BMatch%3BMatches=
&m=3D41734</a><br clear=3D"all">
<br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdoctoral Research Fellow, GRECC,=
Bedford VA<br>Research Fellow, Department of Neurology, Massachusetts Gene=
ral Hospital and Harvard Medical School<br>
Office: <a href=3D"tel:%28773%29%20406-2464" value=3D"+17734062464" target=
=3D"_blank">(773) 406-2464</a><br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION w=
hich may contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY P=
RIVILEGED and which is intended only for the use of the individual or entit=
y named above. If the reader of the e-mail is not the intended recipient or=
the employee or agent responsible for delivering it to the intended recipi=
ent, you are hereby notified that you are in possession of confidential and=
privileged information. Any unauthorized use, disclosure, copying or the t=
aking of any action in reliance on the contents of this information is stri=
ctly prohibited and may be unlawful. If you have received this e-mail unint=
entionally, please immediately notify the sender via telephone at <a href=
=3D"tel:%28773%29%20406-2464" value=3D"+17734062464" target=3D"_blank">(773=
) 406-2464</a> or email.<br>
<br><br><div class=3D"gmail_quote">On Tue, May 10, 2011 at 3:09 PM, Bedda R=
osario <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]" target=
=3D"_blank">[log in to unmask]</a>></span> wrote:<br><blockquote class=
=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1px #ccc solid;padd=
ing-left:1ex">
Dear SPM users, <br><br>I have created an image (and hdr file) using the re=
sults of a t test analysis in SPM8 (that is, using spmT_0001.img).=A0 I wou=
ld like to know if it possible to get a cluster report from the image witho=
ut a corresponding SPM.mat file.=A0 <br>
<br>Thanks for the help, <br><font color=3D"#888888">Bedda<br>
</font></blockquote></div><br>
</div>
--0023545309c8d97cc104a2f28a9c--
=========================================================================
Date: Tue, 10 May 2011 17:38:41 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Flexible factorial questions
Comments: To: zhang sheng <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf3054a4bf9f614704a2f2c721
Message-ID: <[log in to unmask]>
--20cf3054a4bf9f614704a2f2c721
Content-Type: text/plain; charset=ISO-8859-1
Zhang,
Remove subject from the model and the flexible factorial setup. Subject CAN
only be AND MUST be included in within-subject designs. Your design is
purely between subjects.
When you specify subjects the error term goes to 0. When this happens, SPM
produces this message. There are several other potential causes as well
(e.g. no overlapping voxels in ALL subjects, using the same scan twice,
etc.), but this is why it appeared in this case.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Tue, May 10, 2011 at 3:11 PM, zhang sheng <[log in to unmask]> wrote:
> Dear all,
>
> I have a problem for the Flexible factorial analysis.
>
> In second level analysis, I tried to do a Flexible factorial analysis with
> two factors: "group" (e.g. patient vs. control) and "gender". So in the
> design, I have three factors: subject, group, and gender. As I have only one
> scan for each subject, the factor matrices should be [1 1] for group1 and
> male, [1 2] for group1 and female, [2 1] for group2 and male, and [2 2] for
> group2 and female for each subject (see attached file for design matrix)?
> However, when I estimated the model, I got an error message: *Please check
> * your *data*: *There* are *no significant voxels. *So, first, did I do
> something wrong with the model design? If I'm right, could someone tell me
> what happened for the estimating?
>
> Thanks, and any suggestion is highly appreciated!
>
> Sheng
>
--20cf3054a4bf9f614704a2f2c721
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Zhang,<div><br></div><div>Remove subject from the model and the flexible fa=
ctorial setup. Subject CAN only be AND MUST be included in within-subject d=
esigns. Your design is purely between subjects.</div><div><br></div><div>
When you specify subjects the error term goes to 0. When this happens, SPM =
produces this message. There are several other potential causes as well (e.=
g. no overlapping voxels in ALL subjects, using the same scan twice, etc.),=
but this is why it appeared in this case.<br>
<div><br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdoctoral Research Fellow, =
GRECC, Bedford VA<br>Research Fellow, Department of Neurology, Massachusett=
s General Hospital and Harvard Medical School<br>
Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which may =
contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED=
and which is intended only for the use of the individual or entity named a=
bove. If the reader of the e-mail is not the intended recipient or the empl=
oyee or agent responsible for delivering it to the intended recipient, you =
are hereby notified that you are in possession of confidential and privileg=
ed information. Any unauthorized use, disclosure, copying or the taking of =
any action in reliance on the contents of this information is strictly proh=
ibited and may be unlawful. If you have received this e-mail unintentionall=
y, please immediately notify the sender via telephone at (773) 406-2464 or =
email.<br>
<br><br><div class=3D"gmail_quote">On Tue, May 10, 2011 at 3:11 PM, zhang s=
heng <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">szhang570=
@gmail.com</a>></span> wrote:<br><blockquote class=3D"gmail_quote" style=
=3D"margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
Dear all,<br><br>I have a problem for the Flexible factorial analysis. <br>=
<br>In second level analysis, I tried to do a Flexible factorial analysis w=
ith two factors: "group" (e.g. patient vs. control) and "gen=
der". So in the design, I have three factors: subject, group, and gend=
er. As I have only one scan for each subject, the factor matrices should be=
[1 1] for group1 and male, [1 2] for group1 and female, [2 1] for group2 a=
nd male, and [2 2] for group2 and female for each subject (see attached fil=
e for design matrix)? However, when I estimated the model, I got an error m=
essage: <em>Please check</em> your <em>data</em>: <em>There</em> are <em>no=
significant voxels.=A0</em>So, first, did I do something wrong with the mo=
del design? If I'm right, could someone tell me what happened for the e=
stimating? <br>
<br>Thanks, and any suggestion is highly appreciated!<br><font color=3D"#88=
8888"><br>Sheng<br>=20
</font></blockquote></div><br></div></div>
--20cf3054a4bf9f614704a2f2c721--
=========================================================================
Date: Wed, 11 May 2011 08:01:20 +0000
Reply-To: "Fellhauer, Iven" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Fellhauer, Iven" <[log in to unmask]>
Subject: AW: [SPM] inaccurate segmentation of gray matter
In-Reply-To: <[log in to unmask]>
Content-Type: text/plain; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
Dear Christiane,
Maybe you can use the TOM8 toolbox (https://irc.cchmc.org/software/tom.php)=
to create your own Tissue Probability Map (TPM). Take a look in Christian =
Gaser's vbm8 manual on page 24.
Best regards,
Iven
-----Urspr=FCngliche Nachricht-----
Von: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] Im Au=
ftrag von John Ashburner
Gesendet: Dienstag, 10. Mai 2011 16:44
An: [log in to unmask]
Betreff: Re: [SPM] inaccurate segmentation of gray matter
I don't have any good suggestions at the moment, other than maybe try Chris=
tian Gaser's toolbox to see if this handles the data better. I suspect tha=
t it might, as its final segmentation relies less heavily on the tissue pro=
bability maps.
Best regards,
-John
On 9 May 2011 10:37, Moeller, C. <[log in to unmask]> wrote:
> Dear SPM experts,
>
> I am doing VBM analysis on scans of AD patients and healthy controls.=20
> I just finished the segmentation and found a lot of inaccurate=20
> segmentations, especially in scans with a lot of atrophy. I attached a=20
> screenshot of the segmentation for illustration of the problem. It=20
> seems as if the space between the cortex and the dura is also=20
> segmented as gray matter. I used 'New Segment' of SPM8.
>
> Does anyone have an idea why this happens and how I can solve this=20
> problem?
>
> Another issue is, that often the dura around the brain is also=20
> segmented as gray matter. In the older version of the 'Segment' step=20
> there was a 'Clean up' option. Does anyone know how to solve this in=20
> the 'New Segment' step of SPM?
>
> Thanks in advance.
>
> Best regards,
> Christiane
>
=========================================================================
Date: Wed, 11 May 2011 10:55:10 +0200
Reply-To: Nicole David <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Nicole David <[log in to unmask]>
Subject: Job Announcement (PhD Position)
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--Apple-Mail-7-379396246--
=========================================================================
Date: Wed, 11 May 2011 11:37:11 +0100
Reply-To: Subscribe Spm J <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Subscribe Spm J <[log in to unmask]>
Subject: MAUDSLEY ANNUAL REVIEWS 2011 (Monday, 27 June 2011 to Wednesday,
29 June 2011)
Mime-Version: 1.0
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Message-ID: <[log in to unmask]>
MAUDSLEY ANNUAL REVIEWS 2011=20
Institute of Psychiatry, London, UK=20
Monday, 27 June 2011 to Wednesday, 29 June 2011
(event website: http://www.iop.kcl.ac.uk/events/?id=3D1202)=20
=20
We are delighted to announce the 2011 Maudsley Annual Reviews of Psychiat=
ry that build on the success of our inaugural meeting and aim to bridge t=
he gap between scientific developments in mental health and their applica=
tion in clinical care.=20
Each year we select three themes that represent topics in psychiatry wher=
e substantial developments were achieved in understanding or treating men=
tal illness that are directly relevant to clinical practice. Each year we=
bring together internationally renowned researchers and clinicians to di=
scuss their findings and share their perspective on each of their expert =
themes in a clinically relevant manner.=20
The three themes covered in the 2011 Maudsley Annual Reviews of Psychiatr=
y focus on advances in Major Depressive Disorder, in promoting the physic=
al wellbeing of patients with mental disorders and in improving clinical =
and functional outcomes through better adherence.=20
Key Speakers for the Core Scientific programme: Norman Sartorius, Rudolf =
Uher, Marieke Wichers, George Papakostas, Mark De Hert, Peter Haddad, And=
re Tylee, John Hague, Munk-J=C3=B9rgensen and Francesc Colom.=20
=20
Meeting Chairs: Sophia Frangou, Philip McGuire, Rudolf Uher=20
=20
The event has been awarded 9 ECMEC credits from the European Accreditatio=
n Council for Continuing Medical Education=20
=20
Programme, Registration form, Venue and Accommodation details are availab=
le from the website
=20
=========================================================================
Date: Wed, 11 May 2011 12:57:36 +0100
Reply-To: Michael Thomas Smith <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michael Thomas Smith <[log in to unmask]>
Subject: After estimation design matrix loses most regressors.
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1; DelSp="Yes"; format="flowed"
Content-Disposition: inline
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Message-ID: <[log in to unmask]>
I'm interested in the correlation between a time series and the voxels =20
in the brain. To find out more I made a GLM
(see http://www.sal.mvm.ed.ac.uk/images/problem1.png ).
Before estimation it looks fine (I think?).
During estimation however, 6 of the 8 columns are set to zero (see =20
inset in bottom-left corner of the linked image). Just sessions 1 and =20
3 output beta images. There are no errors or warnings expressed during =20
estimation, and the matlab output appears ok.
- I've confirmed the number of images in each session is equal to the =20
number of values in the .txt regressor files.
- I've tried adding conditions to each session (just a single event =20
near the start of each session) to see if it's the lack of conditions =20
that's upsetting SPM. (this didn't make any difference).
- I've rebuilt the design matrix from scratch by hand, using the =20
interface, but that didn't make any difference.
Looking forward to any suggestions!
Thanks,
Mike Smith
--=20
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.
=========================================================================
Date: Wed, 11 May 2011 14:10:12 +0100
Reply-To: Ryan Herringa <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Ryan Herringa <[log in to unmask]>
Subject: Re: Ancova in SPM8
Comments: To: "Stephen J. Fromm" <[log in to unmask]>
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Thanks Stephen,
For each covariate in spm8, I selected:
Interactions: "with Factor 1"
Centering: "Overall mean"
spm8 gives other options for centering:
Factor 1 mean
Factor 2 mean
Factor 3 mean
No centering
User specified value
As implied by Ancova
GM
My understanding was that it is centering on the condition mean so I thin=
k this was the correct selection?
Best,
Ryan Herringa, MD, PhD
University of Pittsburgh
=========================================================================
Date: Wed, 11 May 2011 21:16:42 +0800
Reply-To: Linling Li <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Linling Li <[log in to unmask]>
Subject: How to make a mask in order to exclude activation located within
ventricles
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=========================================================================
Date: Tue, 10 May 2011 19:39:41 +0000
Reply-To: James Rowe <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: James Rowe <[log in to unmask]>
Subject: Re: DCM question
Comments: To: Marta Garrido <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Content-Type: multipart/alternative;
boundary="_000_E639F95C329FB7489DCB4B0C33A840363935A208WSR21mrccbsuloc_"
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
--_000_E639F95C329FB7489DCB4B0C33A840363935A208WSR21mrccbsuloc_
Content-Type: text/plain; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
Hi Keith,
Increasing the number of connections does not require more subjects, but th=
ere are two other considerations to bear in mind.
More complex models face a higher penalty in the Free energy estimate of lo=
g-model-evidence (F), as this depends on the difference between model accur=
acy and model complexity. Unlike AIC and BIC (SPM2.SPM5), the F penalty fo=
r complexity (SPM8, DCM10) is not fixed by the number of parameters/observa=
tions. Rather, it also accomodates the dependencies among parameters (via t=
he KL divergence). Bayesian model selection will then be able help you fi=
nd the right balance of model complexity and accuracy, for a given data set=
, for one or more subjects.
The dependencies among parameters need careful consideration, especially if=
you wish to go on to perform classical statistics on the connectivity para=
meters, as Marta suggests (and as have been successfully undertaken in many=
published DCM papers). Relevant parameter dependecies are more likely for =
complex models. If the parameters do covary, then the estimates of indidual=
parameters become unreliable, increasing type II error in the classical st=
ats. Note that this does not affect F-based model comparisons (e.g. RFX & F=
FX Bayesian model selection). Klaas offered a clear account of these issues=
with useful refs in his recent mail #046065<http://www.jiscmail.ac.uk/cgi-=
bin/wa.exe?A2=3Dind1104&L=3DSPM&P=3DR18510&1=3DSPM&9=3DA&J=3Don&d=3DNo+Matc=
h%3BMatch%3BMatches&z=3D4> "DCM-conditional dependencies". If you frame you=
r hypothesis in terms of model selection (with one or many subjects) then t=
his problem does not arise.
Best wishes,
James
.
________________________________
From: SPM (Statistical Parametric Mapping) [[log in to unmask]] on behalf o=
f Marta Garrido [[log in to unmask]]
Sent: 10 May 2011 17:03
To: [log in to unmask]
Subject: Re: [SPM] DCM question
Hi Keith,
If you are interested in model comparison, then I'd say you can use whichev=
er number of subjects, irrespectively of the number of connections. In fact=
, you can make statistical inferences about models in only one individual s=
ubject.
However, if you then want to go on and do classical statistical tests on th=
e connectivity parameters, then it might be a good idea to increase the num=
ber subjects/parameters per cell.
I'm CCing this to the SPM list in case other people want to comment on it.
Hope this helps!
Marta
On 9 May 2011 10:44, Keith Kawabata Duncan <[log in to unmask]<mailto:k.dun=
[log in to unmask]>> wrote:
Hi Marta,
Maria thought you might be able to help me with a DCM question. I was wonde=
ring if increasing the number of connections in a model requires increasing=
the number of subjects - a bit like increasing the number of cells in a fa=
ctorial design?
Keith
--
Dr. Marta I. Garrido
Research Associate
Wellcome Trust Centre for Neuroimaging
University College London
12 Queen Square
London
WC1N 3BG
United Kingdom
Tel: +44(0)20 7833 7472 (ext: 4366)
Fax: +44(0)20 7813 1420
Email: [log in to unmask]<mailto:[log in to unmask]>
www: http://www.fil.ion.ucl.ac.uk
--_000_E639F95C329FB7489DCB4B0C33A840363935A208WSR21mrccbsuloc_
Content-Type: text/html; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
<html dir=3D"ltr">
<head>
<meta http-equiv=3D"Content-Type" content=3D"text/html; charset=3Diso-8859-=
1">
<style id=3D"owaParaStyle">P {
MARGIN-TOP: 0px; MARGIN-BOTTOM: 0px
}
</style>
</head>
<body fPStyle=3D"1" ocsi=3D"0">
<div style=3D"direction: ltr;font-family: Tahoma;color: #000000;font-size: =
10pt;">
<p>Hi Keith, </p>
<p> </p>
<p>Increasing the number of connections does not require more subjects, but=
there are two other considerations to bear in mind.
</p>
<p> </p>
<p>More complex models face a higher penalty in the Free energy estimate of=
log-model-evidence (F), as this depends on the difference between model ac=
curacy and model complexity. Unlike AIC and BIC (SPM2.SPM5), the =
;F penalty for complexity (SPM8, DCM10) is
not fixed by the number of parameters/observations. Rather, it also accomo=
dates the dependencies among parameters (via the KL divergence).  =
; Bayesian model selection will then be able help you find the right balanc=
e of model complexity and accuracy, for a
given data set, for one or more subjects.</p>
<p> </p>
<p>The dependencies among parameters need careful consideration, especially=
if you wish to go on to perform classical statistics on the connectivity p=
arameters, as Marta suggests (and as have been successfully undertaken in m=
any published DCM papers). Relevant
parameter dependecies are more likely for complex models. If the parameter=
s do covary, then the estimates of indidual parameters become unreliable, i=
ncreasing type II error in the classical stats. Note that this does not aff=
ect F-based model comparisons (e.g.
RFX & FFX Bayesian model selection). Klaas offered a clear account of =
these issues with useful refs in his recent mail #<a href=3D"http://www.jis=
cmail.ac.uk/cgi-bin/wa.exe?A2=3Dind1104&L=3DSPM&P=3DR18510&1=3D=
SPM&9=3DA&J=3Don&d=3DNo+Match%3BMatch%3BMatches&z=3D4">=
<strong><font color=3D"#3366cc">046065</font></strong></a> "DCM-c=
onditional
dependencies". If you frame your hypothesis in terms of model selecti=
on (with one or many subjects) then this problem does not arise.
</p>
<p> </p>
<p>Best wishes, </p>
<p> </p>
<p>James</p>
<p> </p>
<p>. </p>
<p> </p>
<p> </p>
<p> </p>
<div style=3D"FONT-FAMILY: Times New Roman; COLOR: #000000; FONT-SIZE: 16px=
">
<hr tabindex=3D"-1">
<div style=3D"DIRECTION: ltr" id=3D"divRpF279207"><font color=3D"#000000" s=
ize=3D"2" face=3D"Tahoma"><b>From:</b> SPM (Statistical Parametric Mapping)=
[[log in to unmask]] on behalf of Marta Garrido [[log in to unmask]
UK]<br>
<b>Sent:</b> 10 May 2011 17:03<br>
<b>To:</b> [log in to unmask]<br>
<b>Subject:</b> Re: [SPM] DCM question<br>
</font><br>
</div>
<div></div>
<div>Hi Keith,<br>
<br>
If you are interested in model comparison, then I'd say you can use whichev=
er number of subjects, irrespectively of the number of connections. In fact=
, you can make statistical inferences about models in only one individual s=
ubject.
<br>
However, if you then want to go on and do classical statistical tests on th=
e connectivity parameters, then it might be a good idea to increase the num=
ber subjects/parameters per cell.<br>
<br>
I'm CCing this to the SPM list in case other people want to comment on it.<=
br>
Hope this helps!<br>
<br>
Marta<br>
<br>
<br>
<div class=3D"gmail_quote">On 9 May 2011 10:44, Keith Kawabata Duncan <span=
dir=3D"ltr">
<<a href=3D"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]
.uk</a>></span> wrote:<br>
<blockquote style=3D"BORDER-LEFT: #ccc 1px solid; MARGIN: 0px 0px 0px 0.8ex=
; PADDING-LEFT: 1ex" class=3D"gmail_quote">
Hi Marta,<br>
<br>
Maria thought you might be able to help me with a DCM question. I was wonde=
ring if increasing the number of connections in a model requires increasing=
the number of subjects - a bit like increasing the number of cells in a fa=
ctorial design?<br>
<font color=3D"#888888"><br>
Keith<br>
</font></blockquote>
</div>
<br>
<br clear=3D"all">
<br>
-- <br>
Dr. Marta I. Garrido<br>
Research Associate<br>
Wellcome Trust Centre for Neuroimaging<br>
University College London<br>
12 Queen Square<br>
London<br>
WC1N 3BG<br>
United Kingdom<br>
<br>
Tel: +44(0)20 7833 7472 (ext: 4366)<br>
Fax: +44(0)20 7813 1420<br>
Email: <a href=3D"mailto:[log in to unmask]" target=3D"_blank">m.g=
[log in to unmask]</a><br>
www: <a href=3D"http://www.fil.ion.ucl.ac.uk" target=3D"_blank">http://www.=
fil.ion.ucl.ac.uk</a><br>
<br>
</div>
</div>
</div>
</body>
</html>
--_000_E639F95C329FB7489DCB4B0C33A840363935A208WSR21mrccbsuloc_--
=========================================================================
Date: Wed, 11 May 2011 16:34:35 +0100
Reply-To: Carolina Valencia <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Carolina Valencia <[log in to unmask]>
Subject: Activation orbit
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Deas SPM users,
I have some weird results for a task of thinking in verbs related, I got =
activation in both orbits, how I interpret this? is an error for some pre=
processing step?
Thanks a lot,
Best regards,
Carolina
=========================================================================
Date: Wed, 11 May 2011 16:43:07 +0100
Reply-To: Soha Saleh <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Soha Saleh <[log in to unmask]>
Subject: SPM5 Missing ResMS.hdr file after design matrix estimation..
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Dear listserv users:
I am using SPM5 to process some data, and I am getting no ResMS.hdr file =
after estimating the design matrix of a subject's data while all beta ima=
ges and mask image are produced as both ".img" and ".hdr" files. I do not=
have this problem with any of my other subjects. I appreciate if anybody=
has an idea about what is causing this problem and how to fix it.
Thanks in advance,
Regards,
Soha
=========================================================================
Date: Wed, 11 May 2011 18:48:02 +0200
Reply-To: "S.F.W. Neggers" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "S.F.W. Neggers" <[log in to unmask]>
Subject: question regarding matlabbatch struct/class
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Message-ID: <[log in to unmask]>
Dear list,
I created a matlab batch job in the SPM8 batching system, and saved it
to disk as a mat file. Now I want to use it in my own pipeline (matlab
software) to do some repetative number crunching. I work with matlab
version 7.9.0529 (R2009b), and SPM8 rev 4290.
When loading this matlabbatch structure from disk, I obtained the
following warning:
--- snip ---
> load testbatch_spm8.mat
Warning: Class ':all:' is an unknown object class. Element(s) of
this class in array 'matlabbatch' have been converted to
structures.
---
When I now fill in some fields according to my needs, and save this
structure again to disk, will all be OK?
Apparently matlabbatch originally is a class with methods in an OOP
sense, and I dont want to break things by irreversibly convert classes
to fields of a structure. I never had this warning in SPM5, and I am in
the process of moving my pipeline to spm8.
Thanks for your pointers,
Bas
--
--------------------------------------------------
Dr. S.F.W. Neggers
Division of Brain Research
Rudolf Magnus Institute for Neuroscience
Utrecht University Medical Center
Visiting : Heidelberglaan 100, 3584 CX Utrecht
Room B.01.1.03
Mail : Huispost B01.206, P.O. Box
3508 GA Utrecht, the Netherlands
Tel : +31 (0)88 7559609
Fax : +31 (0)88 7555443
E-mail : [log in to unmask]
Web : http://www.neuromri.nl/people/bas-neggers
--------------------------------------------------
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=========================================================================
Date: Wed, 11 May 2011 18:36:06 +0100
Reply-To: Markus Bauer <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Markus Bauer <[log in to unmask]>
Subject: Channel labels for converting and reading EEG data
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Dear all
I have a question concerning the image conversion of individual virtual
EEG channels (time-frequency data)
The data were imported from fieldtrip with the spm_eeg_ft2spm routine
Presumably since the labels are arbitrary (and only 4 channels) SPM did
not assign a channel type, meaning that the image conversion routine
does not recognize these channels.
How can I force it to assign the type 'MEEG' / manipulate the
data-structure in such a way that they can be treated that way?
I also had problems converting an EEG raw data set (from BrainVision
*.eeg file) - this gets stuck in ft_senstype (even when converting from
raw format)
Our cap was custom-made and therefore has arbitrary channel names (from
1 to 128), apparently SPM cant deal with that situation ???
thanks
Markus
=========================================================================
Date: Wed, 11 May 2011 21:18:50 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Channel labels for converting and reading EEG data
Comments: To: Markus Bauer <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Hi Markus,
On Wed, May 11, 2011 at 6:36 PM, Markus Bauer <[log in to unmask]> wrote:
> Dear all
>
> I have a question concerning the image conversion of individual virtual EEG
> channels (time-frequency data)
> The data were imported from fieldtrip with the spm_eeg_ft2spm routine
>
> Presumably since the labels are arbitrary (and only 4 channels) SPM did not
> assign a channel type, meaning that the image conversion routine does not
> recognize these channels.
> How can I force it to assign the type 'MEEG' / manipulate the data-structure
> in such a way that they can be treated that way?
Use Other/Prepare
>
> I also had problems converting an EEG raw data set (from BrainVision *.eeg
> file) - this gets stuck in ft_senstype (even when converting from raw
> format)
> Our cap was custom-made and therefore has arbitrary channel names (from 1 to
> 128), apparently SPM cant deal with that situation ???
>
ft_senstype is a Fieldtrip function so if it can't deal with this
situation, neither can SPM ;-) I suspect this might be related to the
fact that your channel labels are actually numbers. This is not what
SPM or Fieldtrip would expect. I suggest that you look at
ft_read_header and make sure that the labels are read as strings, i.e.
'1', '2'... rather than 1, 2... Then you will have to use Prepare
again to set the channel types and load sensor locations because SPM
will not be able to do it automatically.
Best,
Vladimir
> thanks
> Markus
>
=========================================================================
Date: Thu, 12 May 2011 10:50:35 +0530
Reply-To: megha sharda <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: megha sharda <[log in to unmask]>
Subject: Interpreting parametric modulation
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Message-ID: <[log in to unmask]>
Hello all,
I have a task with three conditions A, B, C. The trials in each of the
conditions are varied on a parameter which is a feature of the trial
stimulus. I used two models to assess activation differences across
three categories. The first model looked at each condition, A, B, C
and i compared across conditions (A-B, A-C, B-C...etc). In the next
model, I additionally used a parametric modulator for each of the
conditions A, Apm, B, Bpm, C, Cpm and used the second column as the
regressor for each condition. However, now when i compare across
conditions I do not see any differences. My question is, would it be
correct to infer that the difference I see across the conditions A, B,
and C is due to the parameter in question and not any other feature of
the stimulus?
Thanks!
Megha
--
Megha Sharda
Graduate Student
National Brain Research Centre
Manesar, Gurgaon -122050
India
Ph: +919810943202
=========================================================================
Date: Thu, 12 May 2011 11:23:31 +0200
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "<Frank> <lJessen>" <[log in to unmask]>
Subject: job offer: 2 post-doc positions (structural imaging,
functional imaging) in Bonn
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Boundary="0__=4EBBF21DDFA00AA28f9e8a93df938690918c4EBBF21DDFA00AA2"
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Message-ID: <[log in to unmask]>
--0__=4EBBF21DDFA00AA28f9e8a93df938690918c4EBBF21DDFA00AA2
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Two post-doc positions for neuroimaging are offered at the Department o=
f
Psychiatry, University of Bonn, within the clinical dementia research g=
roup
(Prof. Dr. F. Jessen). The positions focus on MR-imaging in early
neurodegenerative disease and risk states. The research group operates
within the Clinical Research Center for Neurodegenerative Disorders at =
the
University of Bonn and the MR facilities of Life&Brain. The Clinical
Research Center for Neurodegenerative Disorders is the partner of the
German Center of Neurodegenerative Diseases (DZNE) clinical research
branch. In addition, the research group closely interacts with partner
groups from basis science, genomics and epidemiology.One post-doc posit=
ion
will focus on advanced structural MRI analyses, including DTI. The seco=
nd
position will focus on functional MR imaging. The position will be for =
two
years and can be extended. Please send CV and publication record to:
Prof. Dr. Frank Jessen
Klinik f=FCr Psychiatrie und Psychotherapie
Sigmund-Freud-Str. 25, 53125 Bonn
Germany
[log in to unmask]
=
--0__=4EBBF21DDFA00AA28f9e8a93df938690918c4EBBF21DDFA00AA2
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<html><body>
<p><font size=3D"3" face=3D"sans-serif">Two post-doc positions for neur=
oimaging are offered at the Department of Psychiatry, University of Bon=
n, within the clinical dementia research group (Prof. Dr. F. Jessen). T=
he positions focus on MR-imaging in early neurodegenerative disease and=
risk states. The research group operates within the Clinical Research =
Center for Neurodegenerative Disorders at the University of Bonn and th=
e MR facilities of Life&Brain. The Clinical Research Center for Neu=
rodegenerative Disorders is the partner of the German Center of Neurode=
generative Diseases (DZNE) clinical research branch. In addition, the r=
esearch group closely interacts with partner groups from basis science,=
genomics and epidemiology.One post-doc position will focus on advanced=
structural MRI analyses, including DTI. The second position will focus=
on functional MR imaging. The position will be for two years and can b=
e extended. Please send CV and publication record to:<br>
<br>
Prof. Dr. Frank Jessen<br>
Klinik f=FCr Psychiatrie und Psychotherapie<br>
Sigmund-Freud-Str. 25, 53125 Bonn<br>
Germany<br>
[log in to unmask]</font><font size=3D"2" face=3D"sans-serif"=
><br>
</font><font size=3D"2" face=3D"sans-serif"><br>
<br>
<br>
<br>
</font></body></html>=
--0__=4EBBF21DDFA00AA28f9e8a93df938690918c4EBBF21DDFA00AA2--
=========================================================================
Date: Thu, 12 May 2011 11:06:23 +0100
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jing Kan <[log in to unmask]>
Subject: "the MNE toolbox is not installed"
MIME-Version: 1.0
Content-Type: text/plain;charset=iso-8859-1
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Message-ID: <[log in to unmask]>
Dear SPM experts,
I am quite new on using SPM now. There is a initial problem which stuck my
operation here. I am trying to import the MEG data (.fif) into the SPM
with "spm_eeg_convert". Each time the matlab shows the problem as
follows:
spm_eeg_convert('mathieu_pilotebis_session1_mc.fif')
??? Error using ==> hastoolbox at 250
the MNE toolbox is not installed, see
http://www.nmr.mgh.harvard.edu/martinos/userInfo/data/sofMNE.php
Error in ==> ft_read_header at 893
hastoolbox('mne', 1);
Error in ==> spm_eeg_convert at 72
hdr = ft_read_header(S.dataset, 'fallback', 'biosig', 'headerformat',
S.inputformat);
I actually have MNE and Fieldtrip installed and path added in my matlab.
May I ask how to fix this problem?
Many thanks,
Jing.
=========================================================================
Date: Thu, 12 May 2011 10:24:26 +0000
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: "the MNE toolbox is not installed"
Comments: To: [log in to unmask]
In-Reply-To: <[log in to unmask]>
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aW5nLg0K
=========================================================================
Date: Thu, 12 May 2011 18:23:27 +0800
Reply-To: Syu-Jyun Peng <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Syu-JyunPeng <[log in to unmask]>
Subject: Consult
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Message-ID: <1627981024.1305195808016.JavaMail.nobody@sg2000-ap-1>
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<div><br />Dear Sir</div>
<div>
<div>
<div>
<div>
<p>I'm a&nbsp;EE PhD student in Taiwan.</p>
<p>I have a question.</p>
<p>I have 20 sets of control subject&nbsp;SPGR MRI.</p>
<p>How could I use SPM&nbsp; software to&nbsp;obtain template=
&nbsp;like as&nbsp;the attached file?</p>
<p>Could you&nbsp;<span lang=3D"EN-US" style=3D"=
;font-size: 10pt; color: black; font-family: &quot;Times New Roman&=
quot;; mso-fareast-font-family: =B7s=B2=D3=A9=FA=C5=E9; mso-bidi-font-famil=
y: Arial; mso-ansi-language: EN-US; mso-fareast-language: ZH-TW; mso-bidi-l=
anguage: AR-SA;">give the&nbsp;instructions step by step for me=
?<br /><br /></span></p>
<div v:shape=3D"_x0000_s1026" class=3D"O">
<div style=3D"mso-char-wrap: 1; mso-kinsoku-overflow: 1;">&=
lt;span lang=3D"EN-US" style=3D"mso-fareast-font-family: =B7=
s=B2=D3=A9=FA=C5=E9; mso-fareast-language: ZH-TW; mso-hansi-font-family: Ar=
ial; text-shadow: auto;"><span style=3D"font-size: small;&q=
uot;>It would be greatly appreciated, if you could look<span style=3D=
"mso-spacerun: yes;">&nbsp; </span>into this for us.=
<br /></span></span></div>
<div style=3D"mso-char-wrap: 1; mso-kinsoku-overflow: 1;">&=
lt;span lang=3D"EN-US" style=3D"mso-fareast-font-family: =B7=
s=B2=D3=A9=FA=C5=E9; mso-fareast-language: ZH-TW; mso-hansi-font-family: Ar=
ial; text-shadow: auto;"><span style=3D"font-size: small;&q=
uot;><br />Thank you. <br /></span></span><br=
/>Best regards,<br /><br />Syu-Jyun Peng</div>
</div>
</div>
</div>
</div>
</div>
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<div><br />Dear Sir</div>
<div>
<div>
<div>
<div>
<p>I'm a EE PhD student in Taiwan.</p>
<p>I have a question.</p>
<p>I have 20 sets of control subject SPGR MRI.</p>
<p>How could I use SPM software to obtain template like as&=
nbsp;the attached file?</p>
<p>Could you <span lang=3D"EN-US" style=3D"font-size: 10pt; color: bla=
ck; font-family: "Times New Roman"; mso-fareast-font-family: =B7s=
=B2=D3=A9=FA=C5=E9; mso-bidi-font-family: Arial; mso-ansi-language: EN-US; =
mso-fareast-language: ZH-TW; mso-bidi-language: AR-SA;">give the instr=
uctions step by step for me?<br /><br /></span></p>
<div v:shape=3D"_x0000_s1026" class=3D"O">
<div style=3D"mso-char-wrap: 1; mso-kinsoku-overflow: 1;"><span lang=3D"EN-=
US" style=3D"mso-fareast-font-family: =B7s=B2=D3=A9=FA=C5=E9; mso-fareast-l=
anguage: ZH-TW; mso-hansi-font-family: Arial; text-shadow: auto;"><span sty=
le=3D"font-size: small;">It would be greatly appreciated, if you could look=
<span style=3D"mso-spacerun: yes;"> </span>into this for us. <br /></=
span></span></div>
<div style=3D"mso-char-wrap: 1; mso-kinsoku-overflow: 1;"><span lang=3D"EN-=
US" style=3D"mso-fareast-font-family: =B7s=B2=D3=A9=FA=C5=E9; mso-fareast-l=
anguage: ZH-TW; mso-hansi-font-family: Arial; text-shadow: auto;"><span sty=
le=3D"font-size: small;"><br />Thank you. <br /></span></span><br />Best re=
gards,<br /><br />Syu-Jyun Peng</div>
</div>
</div>
</div>
</div>
</div>
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FFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUU
UUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRR
QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFA
BRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAF
FFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUU
UUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRR
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FFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUU
UUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRR
QAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFA
BRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAF
FFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUU
UUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRR
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BRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAF
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FFFABRRRQAUUUUAf/9k=
------=_Part_280034_767240815.1305195807457--
=========================================================================
Date: Thu, 12 May 2011 11:51:43 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: Consult
Comments: To: Syu-Jyun Peng <[log in to unmask]>
In-Reply-To: <1627981024.1305195808016.JavaMail.nobody@sg2000-ap-1>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Chapter 41 (Using DARTEL) of the spm8 manual would be a good place to
begin. You can find it in spm8/man/manual.pdf
Best regards,
-John
2011/5/12 Syu-JyunPeng <[log in to unmask]>:
>
> Dear Sir
>
> I'm a=A0EE PhD student in Taiwan.
>
> I have a question.
>
> I have 20 sets of control subject=A0SPGR MRI.
>
> How could I use SPM=A0 software to=A0obtain template=A0like as=A0the atta=
ched file?
>
> Could you=A0give the=A0instructions step by step for me?
>
> It would be greatly appreciated, if you could look=A0 into this for us.
>
> Thank you.
>
> Best regards,
>
> Syu-Jyun Peng
=========================================================================
Date: Thu, 12 May 2011 12:46:51 +0100
Reply-To: Charalampos Styliadis <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Charalampos Styliadis <[log in to unmask]>
Subject: SPM ANOVA
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Hi to all
I used the 2nd level analysis in SPM to do a factorial design for MEG dat=
a with gender as the between participants factor and two factors A and B =
with two levels (high-low) as the within participants factors.. I got F-=
images and T-images with the later denoted as positive effect of gender o=
r positive interaction of gender by factor A etc...Are the t-images the a=
ctivations and the f-Images activations and deactivations?
Thanks in advance for any reply
Haris
=========================================================================
Date: Thu, 12 May 2011 08:14:10 -0400
Reply-To: hekmatyar <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: hekmatyar <[log in to unmask]>
Subject: Re: SPM resting state
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset="us-ascii"
Content-Transfer-Encoding: 7bit
Message-ID: <[log in to unmask]>
Hello SPM experts
Is there anyway, I can do detrending and low pass filtering in the SPM for
resting state functional connectivity measurements for my rat brain? Is
there any procedure or method available in SPM? Please suggest me if you
have come across.
Thanks
Regards
Khan Hekmatyar PhD
Bioimaging Research Center.
University of Georgia,
Athens, GA
=========================================================================
Date: Thu, 12 May 2011 21:05:56 +0800
Reply-To: =?utf-8?B?5p6X5LqR?= <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?utf-8?B?5p6X5LqR?= <[log in to unmask]>
Subject: Re: SPM resting state
Comments: To: hekmatyar <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; format=flowed; charset="utf-8"; reply-type=original
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Dear Khan,
There's a software package dedicated to the processing of resting state f=
MRI=20
data (Rest, http://www.restfmri.net/forum/).
The software is designed for human subjects, but I think it is feasible t=
o=20
replace the MNI template by a rat brain template, which may do the trick.
Best regards
Yun Lin
-------------------------------------------------------------------------=
-------
Physician, Master Candidate
Department of Radiology, Southwest Hospital
3rd Military Medical University, Chongqing, China
Phone: +86 150 2312 2673
MSN: [log in to unmask]
Skype: lin.yun83
-----=E5=8E=9F=E5=A7=8B=E9=82=AE=E4=BB=B6-----=20
From: hekmatyar
Sent: Thursday, May 12, 2011 8:14 PM
To: [log in to unmask]
Subject: Re: [SPM] SPM resting state
Hello SPM experts
Is there anyway, I can do detrending and low pass filtering in the SPM fo=
r
resting state functional connectivity measurements for my rat brain? Is
there any procedure or method available in SPM? Please suggest me if you
have come across.
Thanks
Regards
Khan Hekmatyar PhD
Bioimaging Research Center.
University of Georgia,
Athens, GA
=========================================================================
Date: Thu, 12 May 2011 14:42:07 +0100
Reply-To: "Stephen J. Fromm" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Stephen J. Fromm" <[log in to unmask]>
Subject: Re: question regarding matlabbatch struct/class
Comments: To: Bas Neggers <[log in to unmask]>
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
What happens if you put SPM in your matlab path? Usually for me that's e=
nough to make the warning disappear.
=========================================================================
Date: Thu, 12 May 2011 16:02:22 +0200
Reply-To: "S.F.W. Neggers" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "S.F.W. Neggers" <[log in to unmask]>
Subject: Re: question regarding matlabbatch struct/class
Comments: To: "Stephen J. Fromm" <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8; format=flowed
content-transfer-encoding: 7bit
Message-ID: <[log in to unmask]>
Thanks, that kind of worked, it had to do with SPM indeed. I just
updated my spm8 version to latest revision, and the warning disappeared.
I have to admit I didnt do that in a while.
Cheers,
Bas
Op 12-05-11 15:42, Stephen J. Fromm schreef:
> What happens if you put SPM in your matlab path? Usually for me that's enough to make the warning disappear.
>
>
--
--------------------------------------------------
Dr. S.F.W. Neggers
Division of Brain Research
Rudolf Magnus Institute for Neuroscience
Utrecht University Medical Center
Visiting : Heidelberglaan 100, 3584 CX Utrecht
Room B.01.1.03
Mail : Huispost B01.206, P.O. Box
3508 GA Utrecht, the Netherlands
Tel : +31 (0)88 7559609
Fax : +31 (0)88 7555443
E-mail : [log in to unmask]
Web : http://www.neuromri.nl/people/bas-neggers
--------------------------------------------------
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=========================================================================
Date: Thu, 12 May 2011 11:31:14 -0400
Reply-To: Cornelia McCormick <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Cornelia McCormick <[log in to unmask]>
Subject: 2nd level resting state problem
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Dear SPM users,
I am analyzing resting state data of a group of healthy individuals
with a seed-based approach. In my regression model, I added the
extracted timeseries of the seed voxel as well as a few other
regressors (motion parameters, CSF, WM). The first level analysis
(t-test) shows strong activation in the common default mode areas.
However, when I set up the second level random effects model (all con
files combined in a one-sample t-test), there is no activation left.
No even the seed voxel lights up anymore. There is clearly some
mistake in setting up the second level analysis but I don't know what.
Does anybody have an idea? Any help would be aprreciated!
Thanks a lot,
Cornelia
=========================================================================
Date: Thu, 12 May 2011 12:24:53 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: 2nd level resting state problem
Comments: To: Cornelia McCormick <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0016368e30e911927704a316a1ad
Message-ID: <[log in to unmask]>
--0016368e30e911927704a316a1ad
Content-Type: text/plain; charset=ISO-8859-1
A couple of quick questions, then some thoughts.
(1) Are the seeds in the same voxel in all subjects?
(2) How big are the seeds?
The analysis that you have done is not the typical analysis that others have
reported. If you notice, almost all papers use Z-scores as the second level
input; rather than the con_ images. To get the Z, you need to convert the
t-statistic image to an r-value and then use the fisher Z-transform to get a
Z-score.
However, it is probably useful also to do the analysis with the con images,
although there could be scaling issues. In the past, although not published,
I converted to percent signal change to make all the voxels on the same
magnitude scale.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Thu, May 12, 2011 at 11:31 AM, Cornelia McCormick <
[log in to unmask]> wrote:
> Dear SPM users,
>
> I am analyzing resting state data of a group of healthy individuals
> with a seed-based approach. In my regression model, I added the
> extracted timeseries of the seed voxel as well as a few other
> regressors (motion parameters, CSF, WM). The first level analysis
> (t-test) shows strong activation in the common default mode areas.
> However, when I set up the second level random effects model (all con
> files combined in a one-sample t-test), there is no activation left.
> No even the seed voxel lights up anymore. There is clearly some
> mistake in setting up the second level analysis but I don't know what.
> Does anybody have an idea? Any help would be aprreciated!
>
> Thanks a lot,
> Cornelia
>
--0016368e30e911927704a316a1ad
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
A couple of quick questions, then some thoughts.=A0<div>(1) Are the seeds i=
n the same voxel in all subjects?</div><div>(2) How big are the seeds?</div=
><div><br></div><div>The analysis that you have done is not the typical ana=
lysis that others have reported. If you notice, almost all papers use Z-sco=
res as the second level input; rather than the con_ images. To get the Z, y=
ou need to convert the t-statistic image to an r-value and then use the fis=
her Z-transform to get a Z-score.</div>
<div><br></div><div>However, it is probably useful also to do the analysis =
with the con images, although there could be scaling issues. In the past, a=
lthough not published, I converted to percent signal change to make all the=
voxels on the same magnitude scale.<br clear=3D"all">
<br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdoctoral Research Fellow, GRECC,=
Bedford VA<br>Research Fellow, Department of Neurology, Massachusetts Gene=
ral Hospital and Harvard Medical School<br>
Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which may =
contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED=
and which is intended only for the use of the individual or entity named a=
bove. If the reader of the e-mail is not the intended recipient or the empl=
oyee or agent responsible for delivering it to the intended recipient, you =
are hereby notified that you are in possession of confidential and privileg=
ed information. Any unauthorized use, disclosure, copying or the taking of =
any action in reliance on the contents of this information is strictly proh=
ibited and may be unlawful. If you have received this e-mail unintentionall=
y, please immediately notify the sender via telephone at (773) 406-2464 or =
email.<br>
<br><br><div class=3D"gmail_quote">On Thu, May 12, 2011 at 11:31 AM, Cornel=
ia McCormick <span dir=3D"ltr"><<a href=3D"mailto:cornelia.mccormick@goo=
glemail.com">[log in to unmask]</a>></span> wrote:<br><bl=
ockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1px #=
ccc solid;padding-left:1ex;">
Dear SPM users,<br>
<br>
I am analyzing resting state data of a group of healthy individuals<br>
with a seed-based approach. In my regression model, I added the<br>
extracted timeseries of the seed voxel as well as a few other<br>
regressors (motion parameters, CSF, WM). The first level analysis<br>
(t-test) shows strong activation in the common default mode areas.<br>
However, when I set up the second level random effects model (all con<br>
files combined in a one-sample t-test), there is no activation left.<br>
No even the seed voxel lights up anymore. There is clearly some<br>
mistake in setting up the second level analysis but I don't know what.<=
br>
Does anybody have an idea? Any help would be aprreciated!<br>
<br>
Thanks a lot,<br>
<font color=3D"#888888">Cornelia<br>
</font></blockquote></div><br></div>
--0016368e30e911927704a316a1ad--
=========================================================================
Date: Thu, 12 May 2011 16:47:36 +0000
Reply-To: Rik Henson <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Rik Henson <[log in to unmask]>
Content-Type: multipart/alternative;
boundary="_000_3822A22C3FB6974099045A8DB62D39F9391CD531WSR21mrccbsuloc_"
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
--_000_3822A22C3FB6974099045A8DB62D39F9391CD531WSR21mrccbsuloc_
Content-Type: text/plain; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
MRC Cognition and Brain Sciences Unit - Cambridge
Neuroimaging Post to study Ageing
The MRC Cognition and Brain Sciences Unit (CBSU) is an internationally reno=
wned research institute with state-of-the-art cognitive neuroscience facili=
ties including MRI, MEG and EEG.
A post-doctoral position is available as part of the Cambridge Centre for A=
geing and Neuroscience (Cam-CAN), a large group of researchers who seek to =
relate changes in the brain to changes in cognition across the adult lifesp=
an. You will help develop multivariate, multimodal neuroimaging approaches =
to understanding the extent to which the brain can functionally reorganise =
despite extensive structural changes with age. This will be an 11.5 month =
appointment in the first instance.
You will have or be in the final stages of obtaining a PhD in cognitive, co=
mputational or systems neuroscience, and experience in human neuroimaging. =
You should have skills in MRI, fMRI and/or EEG/MEG, plus good computer prog=
ramming skills. It would be desirable, but is not essential, for you to hav=
e experience of studying changes in the brain with ageing. Experience in mu=
ltivariate statistics is also desirable. You will be thorough, efficient, e=
ffective, a good communicator, and enjoy working as part of a diverse and e=
nergetic, interdisciplinary team.
The starting salary will be in the range of =A326,022 - =A331,758 per annum=
, supported by a flexible pay and reward policy, 30 days annual leave enti=
tlement, and an optional MRC final salary Pension Scheme. On site car and =
cycle parking is available. The appointment is for 11.5 months in the first=
instance.
For informal discussion please contact Dr Rik Henson by email: rik.henson@m=
rc-cbu.cam.ac.uk<mailto:[log in to unmask]>.
Applications are handled by the RCUK Shared Services Centre; to apply pleas=
e visit our job board at https://ext.ssc.rcuk.ac.uk<https://ext.ssc.rcuk.ac=
.uk/> and complete an online application form. Applicants who would like t=
o receive this advert in an alternative format (e.g. large print, Braille, =
audio or hard copy), or who are unable to apply online should contact us by=
telephone on 01793 867003, please quote reference number IRC22048.
Closing date: 15th June 2011
This position is subject to pre-employment screening
The Medical Research Council is an Equal Opportunities Employer
-------------------------------------------------------
Dr Richard Henson
Assistant Director, Neuroimaging
MRC Cognition & Brain Sciences Unit
15 Chaucer Road
Cambridge, CB2 7EF, UK
Office: +44 (0)1223 355 294 x522
Mob: +44 (0)794 1377 345
Fax: +44 (0)1223 359 062
http://www.mrc-cbu.cam.ac.uk/people/rik.henson
-------------------------------------------------------
--_000_3822A22C3FB6974099045A8DB62D39F9391CD531WSR21mrccbsuloc_
Content-Type: text/html; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
<html>
<head>
<meta http-equiv=3D"Content-Type" content=3D"text/html; charset=3Diso-8859-=
1">
<meta name=3D"Generator" content=3D"Microsoft Exchange Server">
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#800000 2px solid; } --></style>
</head>
<body>
<font face=3D"Calibri" size=3D"2"><span style=3D"font-size:11pt;">
<div> </div>
<div><b>MRC Cognition and Brain Sciences Unit – Cambridge</b></div>
<div> </div>
<div><b>Neuroimaging Post to study Ageing</b></div>
<div> </div>
<div>The MRC Cognition and Brain Sciences Unit (CBSU) is an internationally=
renowned research institute with state-of-the-art cognitive neuroscience f=
acilities including MRI, MEG and EEG.</div>
<div> </div>
<div>A post-doctoral position is available as part of the Cambridge Centre =
for Ageing and Neuroscience (Cam-CAN), a large group of researchers who see=
k to relate changes in the brain to changes in cognition across the adult l=
ifespan. You will help develop multivariate,
multimodal neuroimaging approaches to understanding the extent to which the=
brain can functionally reorganise despite extensive structural changes wit=
h age. This will be an 11.5 month appointment in the first instance.<=
/div>
<div> </div>
<div>You will have or be in the final stages of obtaining a PhD in cog=
nitive, computational or systems neuroscience, and experience in human neur=
oimaging. You should have skills in MRI, fMRI and/or EEG/MEG, plus good com=
puter programming skills. It would be
desirable, but is not essential, for you to have experience of studying cha=
nges in the brain with ageing. Experience in multivariate statistics is als=
o desirable. You will be thorough, efficient, effective, a good communicato=
r, and enjoy working as part of
a diverse and energetic, interdisciplinary team.</div>
<div> </div>
<div>The starting salary will be in the range of =A326,022 - =A331,758 per =
annum , supported by a flexible pay and reward policy, 30 days annual leave=
entitlement, and an optional MRC final salary Pension Scheme. On sit=
e car and cycle parking is available. The
appointment is for 11.5 months in the first instance.</div>
<div> </div>
<div>For informal discussion please contact Dr Rik Henson by email: <a href=
=3D"mailto:[log in to unmask]"><font color=3D"blue"><u>rik.henson=
@mrc-cbu.cam.ac.uk</u></font></a>.</div>
<div> </div>
<div>Applications are handled by the RCUK Shared Services Centre; to apply =
please visit our job board at <a href=3D"https://ext.ssc.rcuk.ac.uk/"><font=
color=3D"blue"><u>https://ext.ssc.rcuk.ac.uk</u></font></a> and complete a=
n online application form. Applicants
who would like to receive this advert in an alternative format (e.g. large =
print, Braille, audio or hard copy), or who are unable to apply online shou=
ld contact us by telephone on 01793 867003, please quote reference number I=
RC22048<b>. </b></div>
<div> </div>
<div><b>Closing date: 15</b><font size=3D"1"><span style=3D"font-size:7.3pt=
;"><b><sup>th</sup></b></span></font><b> June 2011 </b></div>
<div> </div>
<div><i>This position is subject to pre-employment screening</i></div>
<div><i>The Medical Research Council is an Equal Opportunities Employer</i>=
</div>
<div> </div>
<div> </div>
<div> </div>
<div>-------------------------------------------------------</div>
<div><font face=3D"Courier New"> &=
nbsp; Dr Richard Henson</fo=
nt></div>
<div><font face=3D"Courier New"> &=
nbsp; Assistant Director, Neuroimaging</font></div>
<div><font face=3D"Courier New"> &=
nbsp; MRC Cognition & Brain Sciences Unit</font></div>
<div><font face=3D"Courier New"> &=
nbsp; 15 Chaucer Road</font=
></div>
<div><font face=3D"Courier New"> &=
nbsp; Cambridge, CB2 7EF, UK</font></div>
<div><font face=3D"Courier New"> </font></div>
<div><font face=3D"Courier New"> &=
nbsp; Office: +44 (0)1223 355 294 x522</font></div>
<div><font face=3D"Courier New"> &=
nbsp; Mob: +44 (0)794 1377 345</font></div>
<div><font face=3D"Courier New"> &=
nbsp; Fax: +44 (0)1223 359 062</font></div>
<div><font face=3D"Courier New"> </font></div>
<div><font face=3D"Courier New"> <a href=3D"http://www.mr=
c-cbu.cam.ac.uk/people/rik.henson">
http://www.mrc-cbu.cam.ac.uk/people/rik.henson</a></font></div>
<div><font face=3D"Courier New">-------------------------------------------=
------------</font></div>
<div> </div>
<div> </div>
<div> </div>
</span></font>
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--_000_3822A22C3FB6974099045A8DB62D39F9391CD531WSR21mrccbsuloc_--
=========================================================================
Date: Thu, 12 May 2011 12:02:08 -0700
Reply-To: "Zakrzewski, Jessica" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Zakrzewski, Jessica" <[log in to unmask]>
Subject: Post-Doc Position at UCSF Memory & Aging Center
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The UCSF Memory and Aging Center (MAC), in the Department of Neurology, is =
looking for a candidate interested in post-doctoral fellowship training in =
cognitive neuroscience, specifically studying self-awareness in neurodegene=
rative disease with an emphasis on psychophysiological recording. Appropria=
te candidates would include individuals completing a PhD in clinical psycho=
logy, neuropsychology or cognitive neuroscience that focused on emotions re=
search, psychophysiology and/or dementia, or MDs with similar skills and in=
terests. The work would focus primarily on analysis of psychophysiological =
data (including, but not limited to skin conductance, heart rate, facial ex=
pression) and structural brain imaging.
The MAC is a large, multidisciplinary group that provides clinical services=
and has an extensive research program on aging and neurodegenerative disea=
se, and is a world leader in research on frontotemporal dementia. MAC inves=
tigators direct many projects looking at the clinical, imaging, genetic and=
pathological features of aging and typical and atypical neurodegenerative =
syndromes. The context for this fellowship would be a study of self-awarene=
ss in frontotemporal dementia and Alzheimer's disease, but the fellowship w=
ould also give broad exposure to imaging in a variety of other clinical con=
texts including Alzheimer's disease and mild cognitive impairment, progress=
ive supranuclear palsy, corticobasal degeneration and other disorders. Inte=
rested candidates should contact Howard Rosen ([log in to unmask]<mailt=
o:[log in to unmask]>) and Jessica Zakrzewski ([log in to unmask]
edu<mailto:[log in to unmask]>) for more information.
UCSF seeks candidates whose experience, teaching, research, or community se=
rvice has prepared them to contribute to our commitment to diversity and ex=
cellence. UCSF is an Affirmative Action/Equal Opportunity Employer. The Uni=
versity undertakes affirmative action to assure equal employment opportunit=
y for underutilized minorities and women, for person with disabilities, and=
for covered veterans
Jessica Zakrzewski
Research Associate
UCSF Department of Neurology
Memory & Aging Center
432A Irving Street
San Francisco, CA 94122
[log in to unmask]<mailto:[log in to unmask]>
p: 415-476-9246
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<div class=3DSection1>
<p class=3DMsoNormal><span style=3D'font-family:"Cambria","serif"'>The UCSF=
Memory
and Aging Center (MAC), in the Department of Neurology, is looking for a
candidate interested in post-doctoral fellowship training in cognitive
neuroscience, specifically studying self-awareness in neurodegenerative dis=
ease
with an emphasis on psychophysiological recording. Appropriate candidates w=
ould
include individuals completing a PhD in clinical psychology, neuropsycholog=
y or
cognitive neuroscience that focused on emotions research, psychophysiology
and/or dementia, or MDs with similar skills and interests. The work would f=
ocus
primarily on analysis of psychophysiological data (including, but not limit=
ed
to skin conductance, heart rate, facial expression) and structural brain
imaging. <o:p></o:p></span></p>
<p class=3DMsoNormal><span style=3D'font-family:"Cambria","serif"'><o:p>&nb=
sp;</o:p></span></p>
<p class=3DMsoNormal><span style=3D'font-family:"Cambria","serif"'>The MAC =
is a
large, multidisciplinary group that provides clinical services and has an
extensive research program on aging and neurodegenerative disease, and is a
world leader in research on frontotemporal dementia. MAC investigators dire=
ct
many projects looking at the clinical, imaging, genetic and pathological
features of aging and typical and atypical neurodegenerative syndromes. The
context for this fellowship would be a study of self-awareness in
frontotemporal dementia and Alzheimer’s disease, but the fellowship w=
ould
also give broad exposure to imaging in a variety of other clinical contexts
including Alzheimer’s disease and mild cognitive impairment, progress=
ive
supranuclear palsy, corticobasal degeneration and other disorders. Interest=
ed
candidates should contact Howard Rosen (<a href=3D"mailto:[log in to unmask]
f.edu">[log in to unmask]</a>)
and Jessica Zakrzewski (<a href=3D"mailto:[log in to unmask]">jzak=
[log in to unmask]</a>)
for more information.</span><span style=3D'font-size:10.0pt;font-family:"Ca=
mbria","serif"'>
<o:p></o:p></span></p>
<p class=3DMsoNormal><span style=3D'font-size:10.0pt;font-family:"Cambria",=
"serif"'><o:p> </o:p></span></p>
<p class=3DMsoNormal><span style=3D'font-family:"Cambria","serif"'>UCSF see=
ks
candidates whose experience, teaching, research, or community service has
prepared them to contribute to our commitment to diversity and excellence.&=
nbsp;UCSF
is an Affirmative Action/Equal Opportunity Employer. The University
undertakes affirmative action to assure equal employment opportunity for
underutilized minorities and women, for person with disabilities, and for
covered veterans</span><span style=3D'font-family:"Cambria","serif"'><o:p><=
/o:p></span></p>
<p class=3DMsoNormal><o:p> </o:p></p>
<p class=3DMsoNormal><o:p> </o:p></p>
<p class=3DMsoNormal><span style=3D'font-family:"Palatino Linotype","serif"=
'>Jessica
Zakrzewski<o:p></o:p></span></p>
<p class=3DMsoNormal><span style=3D'font-family:"Palatino Linotype","serif"=
'>Research
Associate <o:p></o:p></span></p>
<p class=3DMsoNormal><span style=3D'font-family:"Palatino Linotype","serif"=
'><o:p> </o:p></span></p>
<p class=3DMsoNormal><span style=3D'font-family:"Palatino Linotype","serif"=
'>UCSF
Department of Neurology</span><span style=3D'font-family:"Palatino Linotype=
","serif"'><o:p></o:p></span></p>
<p class=3DMsoNormal><span style=3D'font-family:"Palatino Linotype","serif"=
'>Memory
& Aging Center</span><span style=3D'font-family:"Palatino Linotype","se=
rif"'><o:p></o:p></span></p>
<p class=3DMsoNormal><span style=3D'font-family:"Palatino Linotype","serif"=
'>432A
Irving Street</span><span style=3D'font-family:"Palatino Linotype","serif"'=
><o:p></o:p></span></p>
<p class=3DMsoNormal><span style=3D'font-family:"Palatino Linotype","serif"=
'>San
Francisco, CA 94122</span><span style=3D'font-family:"Palatino Linoty=
pe","serif"'><o:p></o:p></span></p>
<p class=3DMsoNormal><span style=3D'font-family:"Palatino Linotype","serif"=
'><a
href=3D"mailto:[log in to unmask]"><span style=3D'color:blue'>jzak=
[log in to unmask]</span></a></span><span
style=3D'font-family:"Palatino Linotype","serif"'><o:p></o:p></span></p>
<p class=3DMsoNormal><span style=3D'font-family:"Palatino Linotype","serif"=
'>p:
415-476-9246</span><span style=3D'font-family:"Palatino Linotype","serif"'>=
<o:p></o:p></span></p>
<p class=3DMsoNormal><o:p> </o:p></p>
</div>
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--_000_25B6F6D6457E2240B2AFFD35C9C8455515B8B2E057EX03netucsfed_--
=========================================================================
Date: Thu, 12 May 2011 15:15:49 -0400
Reply-To: Bedda Rosario <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Bedda Rosario <[log in to unmask]>
Subject: Re: Cluster information without corresponding SPM.mat
Comments: To: "MCLAREN, Donald" <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=90e6ba6e8ecc5c2b5204a31904d1
Message-ID: <[log in to unmask]>
--90e6ba6e8ecc5c2b5204a31904d1
Content-Type: text/plain; charset=ISO-8859-1
Hello Donald,
Thank you for your response and the information. It is very useful,
peak.nii and cluster.nii provides information about cluster size, peak
statistic, coordinates, cluster number and region name. Do you know if it
is possible to also get the volume for each cluster (or the value (e.g.
t-value) from each voxel for a specific cluster)?
Thanks for the help,
Bedda
On Tue, May 10, 2011 at 5:21 PM, MCLAREN, Donald
<[log in to unmask]>wrote:
> See the following posts:
>
> http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=ind1103&L=SPM&P=R25661&I=-3&d=No+Match%3BMatch%3BMatches&m=41734
>
>
> http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=ind1103&L=SPM&P=R16468&I=-3&d=No+Match%3BMatch%3BMatches&m=41734
>
> Best Regards, Donald McLaren
> =================
> D.G. McLaren, Ph.D.
> Postdoctoral Research Fellow, GRECC, Bedford VA
> Research Fellow, Department of Neurology, Massachusetts General Hospital
> and Harvard Medical School
> Office: (773) 406-2464
> =====================
> This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
> HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
> intended only for the use of the individual or entity named above. If the
> reader of the e-mail is not the intended recipient or the employee or agent
> responsible for delivering it to the intended recipient, you are hereby
> notified that you are in possession of confidential and privileged
> information. Any unauthorized use, disclosure, copying or the taking of any
> action in reliance on the contents of this information is strictly
> prohibited and may be unlawful. If you have received this e-mail
> unintentionally, please immediately notify the sender via telephone at (773)
> 406-2464 or email.
>
>
>
> On Tue, May 10, 2011 at 3:09 PM, Bedda Rosario <[log in to unmask]> wrote:
>
>> Dear SPM users,
>>
>> I have created an image (and hdr file) using the results of a t test
>> analysis in SPM8 (that is, using spmT_0001.img). I would like to know if it
>> possible to get a cluster report from the image without a corresponding
>> SPM.mat file.
>>
>> Thanks for the help,
>> Bedda
>>
>
>
--90e6ba6e8ecc5c2b5204a31904d1
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Hello Donald, <br><br>Thank you for your response and the information.=A0 I=
t is very useful, peak.nii and cluster.nii provides information about clust=
er size, peak statistic, coordinates, cluster number and region name.=A0 Do=
you know if it is possible to also get the volume for each cluster (or the=
value (e.g. t-value) from each voxel for a specific cluster)? <br>
<br>Thanks for the help, <br>Bedda<br><br><div class=3D"gmail_quote">On Tue=
, May 10, 2011 at 5:21 PM, MCLAREN, Donald <span dir=3D"ltr"><<a href=3D=
"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]
m</a>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex">See the following posts:<div><a href=3D"http=
://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3Dind1103&L=3DSPM&P=3DR2566=
1&I=3D-3&d=3DNo+Match%3BMatch%3BMatches&m=3D41734" target=3D"_b=
lank">http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3Dind1103&L=3DSPM&=
;P=3DR25661&I=3D-3&d=3DNo+Match%3BMatch%3BMatches&m=3D41734</a>=
</div>
<div><br></div><div><a href=3D"http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=
=3Dind1103&L=3DSPM&P=3DR16468&I=3D-3&d=3DNo+Match%3BMatch%3=
BMatches&m=3D41734" target=3D"_blank">http://www.jiscmail.ac.uk/cgi-bin=
/wa.exe?A2=3Dind1103&L=3DSPM&P=3DR16468&I=3D-3&d=3DNo+Match=
%3BMatch%3BMatches&m=3D41734</a><br clear=3D"all">
<br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdoctoral Research Fellow, GRECC,=
Bedford VA<br>Research Fellow, Department of Neurology, Massachusetts Gene=
ral Hospital and Harvard Medical School<br>
Office: <a href=3D"tel:%28773%29%20406-2464" value=3D"+17734062464" target=
=3D"_blank">(773) 406-2464</a><br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION w=
hich may contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY P=
RIVILEGED and which is intended only for the use of the individual or entit=
y named above. If the reader of the e-mail is not the intended recipient or=
the employee or agent responsible for delivering it to the intended recipi=
ent, you are hereby notified that you are in possession of confidential and=
privileged information. Any unauthorized use, disclosure, copying or the t=
aking of any action in reliance on the contents of this information is stri=
ctly prohibited and may be unlawful. If you have received this e-mail unint=
entionally, please immediately notify the sender via telephone at <a href=
=3D"tel:%28773%29%20406-2464" value=3D"+17734062464" target=3D"_blank">(773=
) 406-2464</a> or email.<div>
<div></div><div><br>
<br><br><div class=3D"gmail_quote">On Tue, May 10, 2011 at 3:09 PM, Bedda R=
osario <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]" target=
=3D"_blank">[log in to unmask]</a>></span> wrote:<br><blockquote class=
=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1px #ccc solid;padd=
ing-left:1ex">
Dear SPM users, <br><br>I have created an image (and hdr file) using the re=
sults of a t test analysis in SPM8 (that is, using spmT_0001.img).=A0 I wou=
ld like to know if it possible to get a cluster report from the image witho=
ut a corresponding SPM.mat file.=A0 <br>
<br>Thanks for the help, <br><font color=3D"#888888">Bedda<br>
</font></blockquote></div><br>
</div></div></div>
</blockquote></div><br>
--90e6ba6e8ecc5c2b5204a31904d1--
=========================================================================
Date: Thu, 12 May 2011 15:54:26 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Cluster information without corresponding SPM.mat
Comments: To: Bedda Rosario <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=001517491d5471e90404a3198e05
Message-ID: <[log in to unmask]>
--001517491d5471e90404a3198e05
Content-Type: text/plain; charset=ISO-8859-1
Bedda,
The volume of each cluster is simply the number of voxels*voxelsize, where
voxel size is xdim*ydim*zdim. This is easiest enough to do post-hoc on your
own. The reason this isn't implemented automatically is that cluster extent
is defined using number of contiguous voxels.
The output image will be a map of T-statistics in all clusters. If you want
to extract those values, I'd recommend AFNI. Specifically, they have a tool
called 3dmaskdump that could dump the T-statistics from all voxels using a
mask image. Something like:
3dmaskdump -mask *clusters.nii -mrange a b spmT_*.nii/.img
where a and b are the numbers above and below the actual cluster number.
AFNI is free and easily runs on Mac and Linux boxes.
Hope this helps.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Thu, May 12, 2011 at 3:15 PM, Bedda Rosario <[log in to unmask]> wrote:
> Hello Donald,
>
> Thank you for your response and the information. It is very useful,
> peak.nii and cluster.nii provides information about cluster size, peak
> statistic, coordinates, cluster number and region name. Do you know if it
> is possible to also get the volume for each cluster (or the value (e.g.
> t-value) from each voxel for a specific cluster)?
>
> Thanks for the help,
> Bedda
>
> On Tue, May 10, 2011 at 5:21 PM, MCLAREN, Donald <[log in to unmask]
> > wrote:
>
>> See the following posts:
>>
>> http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=ind1103&L=SPM&P=R25661&I=-3&d=No+Match%3BMatch%3BMatches&m=41734
>>
>>
>> http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=ind1103&L=SPM&P=R16468&I=-3&d=No+Match%3BMatch%3BMatches&m=41734
>>
>> Best Regards, Donald McLaren
>> =================
>> D.G. McLaren, Ph.D.
>> Postdoctoral Research Fellow, GRECC, Bedford VA
>> Research Fellow, Department of Neurology, Massachusetts General Hospital
>> and Harvard Medical School
>> Office: (773) 406-2464
>> =====================
>> This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
>> HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
>> intended only for the use of the individual or entity named above. If the
>> reader of the e-mail is not the intended recipient or the employee or agent
>> responsible for delivering it to the intended recipient, you are hereby
>> notified that you are in possession of confidential and privileged
>> information. Any unauthorized use, disclosure, copying or the taking of any
>> action in reliance on the contents of this information is strictly
>> prohibited and may be unlawful. If you have received this e-mail
>> unintentionally, please immediately notify the sender via telephone at (773)
>> 406-2464 or email.
>>
>>
>>
>> On Tue, May 10, 2011 at 3:09 PM, Bedda Rosario <[log in to unmask]>wrote:
>>
>>> Dear SPM users,
>>>
>>> I have created an image (and hdr file) using the results of a t test
>>> analysis in SPM8 (that is, using spmT_0001.img). I would like to know if it
>>> possible to get a cluster report from the image without a corresponding
>>> SPM.mat file.
>>>
>>> Thanks for the help,
>>> Bedda
>>>
>>
>>
>
--001517491d5471e90404a3198e05
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Bedda,<br><br>The volume of each cluster is simply the number of voxels*vox=
elsize, where voxel size is xdim*ydim*zdim. This is easiest enough to do po=
st-hoc on your own. The reason this isn't implemented automatically is =
that cluster extent is defined using number of contiguous voxels.<br>
<br>The output image will be a map of T-statistics in all clusters. If you =
want to extract those values, I'd recommend AFNI. Specifically, they ha=
ve a tool called 3dmaskdump that could dump the T-statistics from all voxel=
s using a mask image. Something like:<br>
3dmaskdump -mask *clusters.nii -mrange a b spmT_*.nii/.img<br>where a and b=
are the numbers above and below the actual cluster number.<br><br>AFNI is =
free and easily runs on Mac and Linux boxes.<br><br>Hope this helps.<br>
<br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdoctoral Research Fellow, GRECC,=
Bedford VA<br>Research Fellow, Department of Neurology, Massachusetts Gene=
ral Hospital and Harvard Medical School<br>
Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which may =
contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED=
and which is intended only for the use of the individual or entity named a=
bove. If the reader of the e-mail is not the intended recipient or the empl=
oyee or agent responsible for delivering it to the intended recipient, you =
are hereby notified that you are in possession of confidential and privileg=
ed information. Any unauthorized use, disclosure, copying or the taking of =
any action in reliance on the contents of this information is strictly proh=
ibited and may be unlawful. If you have received this e-mail unintentionall=
y, please immediately notify the sender via telephone at (773) 406-2464 or =
email.<br>
<br><br><div class=3D"gmail_quote">On Thu, May 12, 2011 at 3:15 PM, Bedda R=
osario <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">brosario=
@gmail.com</a>></span> wrote:<br><blockquote class=3D"gmail_quote" style=
=3D"border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; p=
adding-left: 1ex;">
Hello Donald, <br><br>Thank you for your response and the information.=A0 I=
t is very useful, peak.nii and cluster.nii provides information about clust=
er size, peak statistic, coordinates, cluster number and region name.=A0 Do=
you know if it is possible to also get the volume for each cluster (or the=
value (e.g. t-value) from each voxel for a specific cluster)? <br>
<div class=3D"im">
<br>Thanks for the help, <br>Bedda<br><br></div><div class=3D"gmail_quote">=
<div class=3D"im">On Tue, May 10, 2011 at 5:21 PM, MCLAREN, Donald <span di=
r=3D"ltr"><<a href=3D"mailto:[log in to unmask]" target=3D"_blank"=
>[log in to unmask]</a>></span> wrote:<br>
</div><div><div></div><div class=3D"h5"><blockquote class=3D"gmail_quote" s=
tyle=3D"border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8e=
x; padding-left: 1ex;">See the following posts:<div><a href=3D"http://www.j=
iscmail.ac.uk/cgi-bin/wa.exe?A2=3Dind1103&L=3DSPM&P=3DR25661&I=
=3D-3&d=3DNo+Match%3BMatch%3BMatches&m=3D41734" target=3D"_blank">h=
ttp://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3Dind1103&L=3DSPM&P=3DR2=
5661&I=3D-3&d=3DNo+Match%3BMatch%3BMatches&m=3D41734</a></div>
<div><br></div><div><a href=3D"http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=
=3Dind1103&L=3DSPM&P=3DR16468&I=3D-3&d=3DNo+Match%3BMatch%3=
BMatches&m=3D41734" target=3D"_blank">http://www.jiscmail.ac.uk/cgi-bin=
/wa.exe?A2=3Dind1103&L=3DSPM&P=3DR16468&I=3D-3&d=3DNo+Match=
%3BMatch%3BMatches&m=3D41734</a><br clear=3D"all">
<br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdoctoral Research Fellow, GRECC,=
Bedford VA<br>Research Fellow, Department of Neurology, Massachusetts Gene=
ral Hospital and Harvard Medical School<br>
Office: <a href=3D"tel:%28773%29%20406-2464" value=3D"+17734062464" target=
=3D"_blank">(773) 406-2464</a><br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION w=
hich may contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY P=
RIVILEGED and which is intended only for the use of the individual or entit=
y named above. If the reader of the e-mail is not the intended recipient or=
the employee or agent responsible for delivering it to the intended recipi=
ent, you are hereby notified that you are in possession of confidential and=
privileged information. Any unauthorized use, disclosure, copying or the t=
aking of any action in reliance on the contents of this information is stri=
ctly prohibited and may be unlawful. If you have received this e-mail unint=
entionally, please immediately notify the sender via telephone at <a href=
=3D"tel:%28773%29%20406-2464" value=3D"+17734062464" target=3D"_blank">(773=
) 406-2464</a> or email.<div>
<div></div><div><br>
<br><br><div class=3D"gmail_quote">On Tue, May 10, 2011 at 3:09 PM, Bedda R=
osario <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]" target=
=3D"_blank">[log in to unmask]</a>></span> wrote:<br><blockquote class=
=3D"gmail_quote" style=3D"border-left: 1px solid rgb(204, 204, 204); margin=
: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
Dear SPM users, <br><br>I have created an image (and hdr file) using the re=
sults of a t test analysis in SPM8 (that is, using spmT_0001.img).=A0 I wou=
ld like to know if it possible to get a cluster report from the image witho=
ut a corresponding SPM.mat file.=A0 <br>
<br>Thanks for the help, <br><font color=3D"#888888">Bedda<br>
</font></blockquote></div><br>
</div></div></div>
</blockquote></div></div></div><br>
</blockquote></div><br>
--001517491d5471e90404a3198e05--
=========================================================================
Date: Thu, 12 May 2011 20:57:23 +0100
Reply-To: Shamil Hadi <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Shamil Hadi <[log in to unmask]>
Subject: Modulatory Input in DCM
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Hello DCM members,
=20
Is there any reason to modulate forward connections (B matrix)=20
rather than backward connections in effective connectivity?
=20
=20
Sincerely,
Shamil,
=========================================================================
Date: Thu, 12 May 2011 16:42:46 -0400
Reply-To: Jiansong Xu <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jiansong Xu <[log in to unmask]>
Subject: Henson's batch code
Content-Type: multipart/mixed; boundary=Apple-Mail-91-508252663
Mime-Version: 1.0 (Apple Message framework v936)
Message-ID: <[log in to unmask]>
--Apple-Mail-91-508252663
Content-Type: text/plain;
charset=US-ASCII;
format=flowed;
delsp=yes
Content-Transfer-Encoding: 7bit
Dear all:
I'm trying to use Henson's batch code for spm5 but got following error
message. Any suggestions are appreciated.
--Apple-Mail-91-508252663
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YNZfrggh9+EBgVEQcqfNdM01XXjW0+aIIlMgIBAQCMBmGtt7gcOXQQD71y5lpi8jUxe32WOn3NLq
rXMx6LqeO1dO0ZtAQCDwFUNAkPdX7AsX0xUICAQEAgKBvR+BHrU23/vhEzMQCAgEBAICAYFA9yMg
yLv7MRcjCgQEAgIBgYBAYLcQEOS9W/CJxgIBgYBAQCAgEOh+BAR5dz/mYkSBgEBAICAQEAjsFgKC
vHcLPtFYICAQEAgIBAQC3Y+AIO/ux1yMKBAQCAgEBAICgd1CQJD3bsEnGgsEBAICAYGAQKD7ERDk
3f2YixEFAgIBgYBAQCCwWwgI8t4t+ERjgYBAQCAgEBAIdD8C/wd9gTSqByueNQAAAABJRU5ErkJg
gg==
--Apple-Mail-91-508252663
Content-Type: text/plain;
charset=US-ASCII;
format=flowed;
delsp=yes
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Best Regards
Jiansong
The information contained in this message may be privileged and
confidential. If you are NOT the intended recipient, please notify the
sender immediately with a copy to [log in to unmask] and destroy
this message. Please be aware that email communication can be
intercepted in transmission or misdirected. Your use of email to
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acknowledge and accept the possible risks associated with such
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sent by email, please contact the sender immediately.
===============
Jiansong Xu, M.D., Ph.D.
Assistant Professor
Dept. of Psychiatry
Yale Medical School
2 Church St., Suite 215
New Haven, CT 06519
Tel: 203-785-5306
Fax: 203-737-3591
--Apple-Mail-91-508252663--
=========================================================================
Date: Thu, 12 May 2011 21:57:15 -0400
Reply-To: Jonathan Peelle <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jonathan Peelle <[log in to unmask]>
Subject: Re: Interpreting parametric modulation
Comments: To: megha sharda <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Dear Megha,
> I have a task with three conditions A, B, C. The trials in each of the
> conditions are varied on a parameter which is a feature of the trial
> stimulus. I used two models to assess activation differences across
> three categories. The first model looked at each condition, A, B, C
> and i compared across conditions (A-B, A-C, B-C...etc). In the next
> model, I additionally used a parametric modulator for each of the
> conditions A, Apm, B, Bpm, C, Cpm and used the second column as the
> regressor for each condition. However, now when i compare across
> conditions I do not see any differences. My question is, would it be
> correct to infer that the difference I see across the conditions A, B,
> and C is due to the parameter in question and not any other feature of
> the stimulus?
You say that in the case in which you added the parametric modulators,
you used the second column as the regressor for each condition. Does
this mean that if your conditions were
A Apm B Bpm C Cpm
you did a contrast looking at, for example, for A-B:
[0 1 0 -1 0 0]
I.e., Apm - Bpm? Or did I misunderstand what you meant about using
the second column? If this is the case, it's not surprising that you
got different results, as you are testing something different. It
could well be that conditions A and B differ (contrast [1 0 -1 0 0
0]), but that the effect of the parametric modulator does not differ
by condition (contrast [0 1 0 -1 0 0]).
If you want to say that the difference across condition cannot be
attributed to the parametric modulator, you would need a slightly
different model. As it stands now the parametric modulator tells you
how that factor affects activity within each condition, but not about
how it may contribute across the whole experiment. To look at this, I
think you would want a single column that codes for every event
(assuming you have the same number of events in each A,B,C condition),
a single parametric modulator, and then additional columns that code
for condition A, B, C. So:
[any_event pm A B C]
In this case, because the parametric modulator goes across all
trials/conditions, I think you would be safer in concluding that an
A>B difference exists apart from anything that could be explained by
the parametric modulator.
Hope this helps!
Best regards,
Jonathan
--
Dr. Jonathan Peelle
Department of Neurology
University of Pennsylvania
3 West Gates
3400 Spruce Street
Philadelphia, PA 19104
USA
http://jonathanpeelle.net/
=========================================================================
Date: Thu, 12 May 2011 19:52:24 -0700
Reply-To: Elsa Baena <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Elsa Baena <[log in to unmask]>
Subject: Negative contrast values
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Dear SPMers,
There seems to be much confusion about what a negative contrast value means.
My understanding is that a negative contrast value indicates that
significant activation is elicited by the a condition for which a -1
was assigned to in a contrast, not the condition that a 1 was assigned
to. For example, if a contrast comparing semantic memory retrieval and
a control condition yielded a -3 contrast value for a particular brain
region, this brain region would show enhanced activation during the
control task compared to the semantic memory task. Is this correct?
Additionally, what does a negative contrast value mean when performing
a parametric modulation examining the linear increase in activation
given two conditions (e.g. easier vs. hard)? Does it hold the same
principle?
Thanks in advance for the help.
Best,
Elsa Baena
--
_________________________________
_________________________________
Elsa Baena
Graduate Student
Clinical Neuropsychology Program
Cognitive Neuroscience Laboratory
University of Arizona
[log in to unmask]
=========================================================================
Date: Thu, 12 May 2011 23:29:33 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Negative contrast values
Comments: To: Elsa Baena <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0016368e30e90f89bd04a31fea99
Message-ID: <[log in to unmask]>
--0016368e30e90f89bd04a31fea99
Content-Type: text/plain; charset=ISO-8859-1
See responses below.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Thu, May 12, 2011 at 10:52 PM, Elsa Baena <[log in to unmask]>wrote:
> Dear SPMers,
> There seems to be much confusion about what a negative contrast value
> means.
>
> My understanding is that a negative contrast value indicates that
> significant activation is elicited by the a condition for which a -1
> was assigned to in a contrast, not the condition that a 1 was assigned
> to. For example, if a contrast comparing semantic memory retrieval and
> a control condition yielded a -3 contrast value for a particular brain
> region, this brain region would show enhanced activation during the
> control task compared to the semantic memory task. Is this correct?
>
Almost. Whenever you are comparing two conditions, you don't know if one the
-1 has enhanced activation or decreased deactivation.
>
> Additionally, what does a negative contrast value mean when performing
> a parametric modulation examining the linear increase in activation
> given two conditions (e.g. easier vs. hard)? Does it hold the same
> principle?
>
If the PM is -1 for easier and 1 for harder, then a -1 would mean that the
activity is less for the harder conditions.
>
> Thanks in advance for the help.
>
> Best,
>
> Elsa Baena
>
> --
> _________________________________
> _________________________________
> Elsa Baena
> Graduate Student
> Clinical Neuropsychology Program
> Cognitive Neuroscience Laboratory
> University of Arizona
> [log in to unmask]
>
--0016368e30e90f89bd04a31fea99
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
See responses below.<br clear=3D"all"><br>Best Regards, Donald McLaren<br>=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<=
br>Postdoctoral Research Fellow, GRECC, Bedford VA<br>Research Fellow, Depa=
rtment of Neurology, Massachusetts General Hospital and Harvard Medical Sch=
ool<br>
Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which may =
contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED=
and which is intended only for the use of the individual or entity named a=
bove. If the reader of the e-mail is not the intended recipient or the empl=
oyee or agent responsible for delivering it to the intended recipient, you =
are hereby notified that you are in possession of confidential and privileg=
ed information. Any unauthorized use, disclosure, copying or the taking of =
any action in reliance on the contents of this information is strictly proh=
ibited and may be unlawful. If you have received this e-mail unintentionall=
y, please immediately notify the sender via telephone at (773) 406-2464 or =
email.<br>
<br><br><div class=3D"gmail_quote">On Thu, May 12, 2011 at 10:52 PM, Elsa B=
aena <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">ebae=
[log in to unmask]</a>></span> wrote:<br><blockquote class=3D"gmail_qu=
ote" style=3D"border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0p=
t 0.8ex; padding-left: 1ex;">
Dear SPMers,<br>
There seems to be much confusion about what a negative contrast value means=
.<br>
<br>
My understanding is that a negative contrast value indicates that<br>
significant activation is elicited by the a condition for which a -1<br>
was assigned to in a contrast, not the condition that a 1 was assigned<br>
to. For example, if a contrast comparing semantic memory retrieval and<br>
a control condition yielded a -3 contrast value for a particular brain<br>
region, this brain region would show enhanced activation during the<br>
control task compared to the semantic memory task. Is this correct?<br></bl=
ockquote><div><br>Almost. Whenever you are comparing two conditions, you do=
n't know if one the -1 has enhanced activation or decreased deactivatio=
n.<br>
=A0</div><blockquote class=3D"gmail_quote" style=3D"border-left: 1px solid =
rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
<br>
Additionally, what does a negative contrast value mean when performing<br>
a parametric modulation examining the linear increase in activation<br>
given two conditions (e.g. easier vs. hard)? Does it hold the same<br>
principle?<br></blockquote><div><br>If the PM is -1 for easier and 1 for ha=
rder, then a -1 would mean that the activity is less for the harder conditi=
ons.<br>=A0</div><blockquote class=3D"gmail_quote" style=3D"border-left: 1p=
x solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
<br>
Thanks in advance for the help.<br>
<br>
Best,<br>
<br>
Elsa Baena<br>
<br>
--<br>
_________________________________<br>
_________________________________<br>
<font color=3D"#888888">Elsa Baena<br>
Graduate Student<br>
Clinical Neuropsychology Program<br>
Cognitive Neuroscience Laboratory<br>
University of Arizona<br>
<a href=3D"mailto:[log in to unmask]">[log in to unmask]</a><br=
>
</font></blockquote></div><br>
--0016368e30e90f89bd04a31fea99--
=========================================================================
Date: Thu, 12 May 2011 22:40:57 -0500
Reply-To: John Fredy <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Fredy <[log in to unmask]>
Subject: rest toolbox aal time series
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf30364013e0082104a3201284
Message-ID: <[log in to unmask]>
--20cf30364013e0082104a3201284
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Hello all,
Someone knows in which order the rest toolbox gives the aal times series? I
see the .mat and the .txt data but I don=B4t know to which region correspon=
d
each time serie
Thanks in advance
John Ochoa
--20cf30364013e0082104a3201284
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Hello all,<br><br>Someone knows in which order the rest toolbox gives the a=
al times series? I see the .mat and the .txt data but I don=B4t know to whi=
ch region correspond each time serie<br><br>Thanks in advance<br><br>John O=
choa<br>
<br>
--20cf30364013e0082104a3201284--
=========================================================================
Date: Fri, 13 May 2011 05:34:15 +0100
Reply-To: Krishna Miyapuram <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Krishna Miyapuram <[log in to unmask]>
Subject: Re: Interpreting parametric modulation
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
In addition to what Jonathan mentioned, The design matrix specified in th=
e the two cases is as follows
Y =3D beta*X+epsilon
and in once case, X is simply A B C and in other case X is A Apm B Bpm C =
Cpm
Firstly, the parametric odulator should not be highly correlated with the=
condition itself. You can look at both the design matrices and there sho=
uld be row below those design matrices (when you explore design) that men=
tions contrast / parameter estimability. This should be ideally white. Gr=
ay is still okay, but if you see that, it could be one of the explanation=
s of the results you observe.=20
Second, The brain activation in the second design matrix is distributed t=
o condition and parametric modulation. As i mentioned earlier the same co=
ntrast i.e. differences between conditions A and B should not be severly =
affected if your parametric modulator is orthogonal to the conditions. Th=
is is rarely the case. When the modulator is highly correlated then the a=
ctivation is shown in the regressor contrast instead of the condition con=
trast.=20
By extracting the timecourse of activation, you can independently verify =
your claim that the activation is related to the parametric modulator.
HTH
-krishna
=========================================================================
Date: Fri, 13 May 2011 08:21:22 +0000
Reply-To: Rik Henson <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Rik Henson <[log in to unmask]>
Subject: Re: Henson's batch code
Comments: To: Jiansong Xu <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Content-Type: text/plain; charset="us-ascii"
Content-Transfer-Encoding: quoted-printable
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
From the error message, it looks like you haven't quite specified the names=
of each condition correctly (in U(i).name{k}) - so trying changing how you=
specify the names as cell arrays of strings (which may require a bit of Ma=
tlab training) - but without seeing your actual modifications to the script=
, I cannot help - and apologies that those scripts are provided for use, wi=
thout promise of support.
BW,R
> -----Original Message-----
> From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] On
> Behalf Of Jiansong Xu
> Sent: 12 May 2011 21:43
> To: [log in to unmask]
> Subject: [SPM] Henson's batch code
>=20
> Dear all:
>=20
> I'm trying to use Henson's batch code for spm5 but got following error
> message. Any suggestions are appreciated.
=========================================================================
Date: Fri, 13 May 2011 10:54:33 +0100
Reply-To: Patrick Fisher <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Patrick Fisher <[log in to unmask]>
Subject: viewing individual slices for a single volume
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear SPMers,
Is there a way to view each individual slice of a functional volume at =
the same time? This seems like something that should have a straight-for=
ward solution, but I cannot figure it out. Perhaps this is not possible =
within SPM?
Any help would be greatly appreciated.
Regards,
Patrick
=========================================================================
Date: Fri, 13 May 2011 19:06:57 +0800
Reply-To: Brahim HAMADICHAREF <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Brahim HAMADICHAREF <[log in to unmask]>
Subject: Re: viewing individual slices for a single volume
In-Reply-To: <[log in to unmask]>
Content-Type: multipart/alternative;
boundary="_14f04319-6aba-4123-9959-b99c124e6f29_"
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
--_14f04319-6aba-4123-9959-b99c124e6f29_
Content-Type: text/plain; charset="gb2312"
Content-Transfer-Encoding: 8bit
This should help youhttp://imaging.mrc-cbu.cam.ac.uk/imaging/DisplaySlices
Brahim
> Date: Fri, 13 May 2011 10:54:33 +0100
> From: [log in to unmask]
> Subject: [SPM] viewing individual slices for a single volume
> To: [log in to unmask]
>
> Dear SPMers,
> Is there a way to view each individual slice of a functional volume at the same time? This seems like something that should have a straight-forward solution, but I cannot figure it out. Perhaps this is not possible within SPM?
>
> Any help would be greatly appreciated.
>
> Regards,
> Patrick
--_14f04319-6aba-4123-9959-b99c124e6f29_
Content-Type: text/html; charset="gb2312"
Content-Transfer-Encoding: 8bit
<html>
<head>
<style><!--
.hmmessage P
{
margin:0px;
padding:0px
}
body.hmmessage
{
font-size: 10pt;
font-family:Tahoma
}
--></style>
</head>
<body class='hmmessage'>
This should help you<div><a href="http://imaging.mrc-cbu.cam.ac.uk/imaging/DisplaySlices">http://imaging.mrc-cbu.cam.ac.uk/imaging/DisplaySlices</a> <br><br>Brahim <br><br>> Date: Fri, 13 May 2011 10:54:33 +0100<br>> From: [log in to unmask]<br>> Subject: [SPM] viewing individual slices for a single volume<br>> To: [log in to unmask]<br>> <br>> Dear SPMers,<br>> Is there a way to view each individual slice of a functional volume at the same time? This seems like something that should have a straight-forward solution, but I cannot figure it out. Perhaps this is not possible within SPM?<br>> <br>> Any help would be greatly appreciated.<br>> <br>> Regards,<br>> Patrick<br></div> </body>
</html>
--_14f04319-6aba-4123-9959-b99c124e6f29_--
=========================================================================
Date: Fri, 13 May 2011 12:17:24 +0100
Reply-To: "<Branislava> <Curcic-Blake>" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "<Branislava> <Curcic-Blake>" <[log in to unmask]>
Subject: Re: Modulatory Input in DCM
Comments: To: Shamil Hadi <[log in to unmask]>
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear Shamill,
It all depends on your research question i.e. what do you want to answer =
with the DCM. If you are interested if the connections are forward or bac=
kward, than you might model 4 possibilities (no modulatory, modulatory on=
forward, modulatory on backward and modulatory on both), and compare the=
outcome using model selection.
But I assume that you are not sure if you may question modulatory on back=
ward if it is not on forward? I believe you may.
Kind Regards
Branislava
=========================================================================
Date: Fri, 13 May 2011 12:42:16 +0100
Reply-To: Christian Gaser <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Christian Gaser <[log in to unmask]>
Subject: Postdoctoral Position or PhD Student Position
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Postdoctoral Position or PhD Student Position
Departments of Psychiatry and Neurology, University of Jena
----------------------------------------------------------------------
Applications are invited for a postdoctoral position or a PhD-student pos=
ition at the Departments=20
of Psychiatry and Neurology, University of Jena. The focus of the positio=
ns is on developing and applying new=20
methods for computational morphometry. The candidates should have a Ph.D.=
or degree in=20
Psychology, Neuroinformatics, Neuroscience, Physics or a related area. Ex=
perience in anatomical=20
MRI (data acquisition, processing, statistics) and programming skills (Ma=
tlab, C/C++) are=20
desirable.
This post is based in the Structural Brain Mapping Group in Jena (http://=
dbm.neuro.uni-jena.de), a=20
multi-disciplinary research team in the Departments of Neurology and Psyc=
hiatry. The departments have=20
excellent research facilities including an on-site, research-dedicated Si=
emens Tim Trio 3T MRI scanner.
Salary will be according to "EG 13 TV-L" (PostDoc 100%, PhD Student 50%).=
The appointment is=20
initially for 2 years with the option of extension. Expected start date i=
s July 2011.
Please email CV, and statement of research interests to=20
Christian Gaser, Ph.D.
Departments of Psychiatry and Neurology
Friedrich-Schiller-University of Jena
Jahnstrasse 3, D-07743 Jena, Germany
Tel: ++49-3641-934752=09Fax: ++49-3641-934755
e-mail: [log in to unmask]
http://dbm.neuro.uni-jena.de
=========================================================================
Date: Fri, 13 May 2011 08:12:27 -0400
Reply-To: Fred Sanders <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Fred Sanders <[log in to unmask]>
Subject: Simple scripting question - batch loading scans
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf3054a8ef25942d04a32738b9
Message-ID: <[log in to unmask]>
--20cf3054a8ef25942d04a32738b9
Content-Type: text/plain; charset=ISO-8859-1
Hi All,
For a second level analysis, I've create a .mat file with the names of all
of the scans that I'd like to load into my second level factorial model.
Using the SPM batch interface, is there a way to load this .mat into the
Scan <-X prompt? Right now, I have to manually select each file. I suspect
there's an easy way to input the files as a matlab variable, but I can
figure it out - any suggestions?? For example, with a first level analysis,
one can easily use a .mat file to load vectors for the onset and duration
times. Anyway to do that with scan names?
Thanks!
--20cf3054a8ef25942d04a32738b9
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Hi All,<div><br></div><div>For a second level analysis, I've create a .=
mat file with the names of all of the scans that I'd like to load into =
my second level factorial model. =A0Using the SPM batch interface, is there=
a way to load this .mat into the Scan <-X prompt? Right now, I have to =
manually select each file. =A0I suspect there's an easy way to input th=
e files as a matlab variable, but I can figure it out - any suggestions?? =
=A0For example, with a first level analysis, one can easily use a .mat file=
to load vectors for the onset and duration times. Anyway to do that with s=
can names?<br>
<br></div><div><br></div><div>Thanks! =A0</div>
--20cf3054a8ef25942d04a32738b9--
=========================================================================
Date: Fri, 13 May 2011 14:28:22 +0200
Reply-To: =?UTF-8?B?546L5aqb?= <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?UTF-8?B?546L5aqb?= <[log in to unmask]>
Subject: Simple question: In the 2nd level analysis,
which file discribe the P-value map.
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf305643090b799504a3277103
Message-ID: <[log in to unmask]>
--20cf305643090b799504a3277103
Content-Type: text/plain; charset=ISO-8859-1
Hello,
Just a simple question as the subject.
The second level analysis produces a lot of files, I wonder which one
contains or is the p-value map.
RPV? mask? ResMS?
And what exactly does the p-value map show? Is it simply a mask which sets
'1s' for the pixels larger than the value,'0s' for others?
I am totally a freshman for the analysis procedure, maybe you can explain in
a easier way:)
Thank you so much.
Best Regards,
Yuan
--20cf305643090b799504a3277103
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<div>Hello,</div>
<div>=A0</div>
<div>Just a simple question as the subject.</div>
<div>The second level analysis produces a lot of files, I wonder which one =
contains or is the p-value map.</div>
<div>RPV? mask? ResMS?</div>
<div>And what exactly does the p-value map show? Is it simply a mask which =
sets '1s' for the pixels larger than the value,'0s' for oth=
ers?</div>
<div>I am totally a freshman for the analysis procedure, maybe you can expl=
ain in a easier way:)</div>
<div>Thank you so much.</div>
<div>=A0</div>
<div>Best Regards,</div>
<div>Yuan</div>
--20cf305643090b799504a3277103--
=========================================================================
Date: Fri, 13 May 2011 13:45:47 +0100
Reply-To: Ciara Greene <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Ciara Greene <[log in to unmask]>
Subject: resel size in batch script
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Hi, I've just recently started using batch scripts to run my SPM analyses=
instead of the GUI, and I've come across a problem. I found that when ru=
nning the second level analysis on exactly the same first level files and=
with identical parameters, the scripted analysis results in much smoothe=
r activations and larger resels, altering the cluster sizes reported. I'm=
not sure how this has come about, or where I can amend this setting in e=
ither the script or in the GUI batch interface. Is there some default tha=
t I have failed to specify in my script?
Thanks for your help,
Ciara
=========================================================================
Date: Fri, 13 May 2011 09:53:38 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Simple question: In the 2nd level analysis,
which file discribe the P-value map.
Comments: To: =?UTF-8?B?546L5aqb?= <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=001517478f04fce12404a328a1db
Message-ID: <[log in to unmask]>
--001517478f04fce12404a328a1db
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
There is no p-value map. Rather, you create contrasts (after you estimate
the model) that create either: (1) spmT_ and con_ images or (2) spmF_ and
ess_ images. The con_ images provide you with a measure of the magnitude of
the contrast. The spmT_ and spmF_ images provide you with either the
T-statsistics and F-stastistics at each voxel. From those values, you can
determine the p-value.
The ess_ is the extra sums of squares associated with the numerator for the
F-test.
For a general introduction, I'd read up on statistics and the general linea=
r
model. All of the classical analyses in SPM use the general linear model.
Best Regards, Donald McLaren
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital an=
d
Harvard Medical School
Office: (773) 406-2464
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773=
)
406-2464 or email.
On Fri, May 13, 2011 at 8:28 AM, =E7=8E=8B=E5=AA=9B <[log in to unmask]
> wrote:
> Hello,
>
> Just a simple question as the subject.
> The second level analysis produces a lot of files, I wonder which one
> contains or is the p-value map.
> RPV? mask? ResMS?
> And what exactly does the p-value map show? Is it simply a mask which set=
s
> '1s' for the pixels larger than the value,'0s' for others?
> I am totally a freshman for the analysis procedure, maybe you can explain
> in a easier way:)
> Thank you so much.
>
> Best Regards,
> Yuan
>
--001517478f04fce12404a328a1db
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
There is no p-value map. Rather, you create contrasts (after you estimate t=
he model) that create either: (1) spmT_ and con_ images or (2) spmF_ and es=
s_ images. The con_ images provide you with a measure of the magnitude of t=
he contrast. The spmT_ and spmF_ images provide you with either the T-stats=
istics and F-stastistics at each voxel. From those values, you can determin=
e the p-value.<div>
<br></div><div>The ess_ is the extra sums of squares associated with the nu=
merator for the F-test.</div><div><br></div><div>For a general introduction=
, I'd read up on statistics and the general linear model. All of the cl=
assical analyses in SPM use the general linear model.<br>
<div><br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdoctoral Research Fellow, =
GRECC, Bedford VA<br>Research Fellow, Department of Neurology, Massachusett=
s General Hospital and Harvard Medical School<br>
Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which may =
contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED=
and which is intended only for the use of the individual or entity named a=
bove. If the reader of the e-mail is not the intended recipient or the empl=
oyee or agent responsible for delivering it to the intended recipient, you =
are hereby notified that you are in possession of confidential and privileg=
ed information. Any unauthorized use, disclosure, copying or the taking of =
any action in reliance on the contents of this information is strictly proh=
ibited and may be unlawful. If you have received this e-mail unintentionall=
y, please immediately notify the sender via telephone at (773) 406-2464 or =
email.<br>
<br><br><div class=3D"gmail_quote">On Fri, May 13, 2011 at 8:28 AM, =E7=8E=
=8B=E5=AA=9B <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]
">[log in to unmask]</a>></span> wrote:<br><blockquote class=3D"gmai=
l_quote" style=3D"margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left=
:1ex;">
<div>Hello,</div>
<div>=C2=A0</div>
<div>Just a simple question as the subject.</div>
<div>The second level analysis produces a lot of files, I wonder which one =
contains or is the p-value map.</div>
<div>RPV? mask? ResMS?</div>
<div>And what exactly does the p-value map show? Is it simply a mask which =
sets '1s' for the pixels larger than the value,'0s' for oth=
ers?</div>
<div>I am totally a freshman for the analysis procedure, maybe you can expl=
ain in a easier way:)</div>
<div>Thank you so much.</div>
<div>=C2=A0</div>
<div>Best Regards,</div>
<div>Yuan</div>
</blockquote></div><br></div></div>
--001517478f04fce12404a328a1db--
=========================================================================
Date: Fri, 13 May 2011 15:09:41 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: source priors for MEG source inversion
Comments: To: Sonja Schall <[log in to unmask]>
In-Reply-To: <1613249220.234129.1303994236572.JavaMail.root@zimbra>
MIME-Version: 1.0
Content-Type: multipart/mixed; boundary=20cf300fb38f5f88d504a328dbed
Message-ID: <[log in to unmask]>
--20cf300fb38f5f88d504a328dbed
Content-Type: text/plain; charset=ISO-8859-1
Dear Sonja,
Sorry for the delay. I was a little preoccupied with other things.
There are indeed some bugs in the batch and you were apparently the
first user to try out that particular option and discover them. Please
put the attached file in spm/config and restart your SPM. It should
work then.
Best,
Vladimir
On Thu, Apr 28, 2011 at 1:37 PM, Sonja Schall <[log in to unmask]> wrote:
> Dear SPM experts,
>
> I encountered some technical difficulties when I tried to run the M/EEG source inversion batch with source priors. The source prior option seems to work fine for the GUI, but when I use the batch it results in an error.
> It seems I don't have the option to specify "MNI" as the image space using the batch, but I don't know whether this is related to the problem.
>
> Is there any easy way to fix/work around this problem?
>
> best,
> sonja
>
--20cf300fb38f5f88d504a328dbed
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LCdEJyk7DQolIHRoaXMgY2FuIGJlIGVudGVyZWQgaW50byBhbnkgZXZhbHVhdGVkIGlucHV0DQpk
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--20cf300fb38f5f88d504a328dbed--
=========================================================================
Date: Fri, 13 May 2011 15:06:06 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Batch problem--3D Source Reconstruction
Comments: To: =?UTF-8?B?6aOe6bif?= <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Dear Haoran,
I tried and everything works fine for me. Make sure your SPM version
is up to date and if you can't make it work, send me your saved batch
and I'll take another look.
Best,
Vladimir
2011/5/10 =E9=A3=9E=E9=B8=9F <[log in to unmask]>:
> Dear SPM's users,
> =E3=80=80=E3=80=80Have you ever used batch interface to do 3D source reco=
nstruction for
> EEG/MEG data?=C2=A0I choosed three separate=C2=A0modules=C2=A0 "M/EEG hea=
d model
> specification" "M/EEG source inversion" and "M/EEG inversion results"=C2=
=A0so=C2=A0as
> to reconstruct the sources.=C2=A0In the "M/EEG head model specification" =
module,
> I specified ''Meshes<Meshes source<individual structual image'' and then
> selected a mri file named "sDP74-0003-00000-000001-01.img,1".=C2=A0 When =
all was
> ready and then I ran the batch, however,=C2=A0I found that it din't excut=
ed the
> specified structual image ( as you can see below 'template=3D1') and the
> matlab command window appeared those:
>
> SPM8: spm_eeg_inv_mesh_ui (v3731)=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=
=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 21:39:06 - =
09/05/2011
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 template: 1
> =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Affine: [4x4 double]
> =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 sMRI: 'C:\Pr=
ogram
> Files\MATLAB\toolbox\spm8\canonical\single_subj_T1.nii'
> =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Msize: 2
> =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 tess_mni: [1x1 struct]
> =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 tess_ctx: 'C:\Program
> Files\MATLAB\toolbox\spm8\canonical\cortex_8196.surf.gii'
> =C2=A0=C2=A0=C2=A0=C2=A0 tess_scalp: 'C:\Program
> Files\MATLAB\toolbox\spm8\canonical\scalp_2562.surf.gii'
> =C2=A0=C2=A0=C2=A0 tess_oskull: 'C:\Program
> Files\MATLAB\toolbox\spm8\canonical\oskull_2562.surf.gii'
> =C2=A0=C2=A0=C2=A0 tess_iskull: 'C:\Program
> Files\MATLAB\toolbox\spm8\canonical\iskull_2562.surf.gii'
> =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 fid: [=
1x1 struct]
>
> =C2=A0 =E3=80=80I didn't understand why. Anyone who knows the reason ? Th=
anks very much
> for any help !
>
> --
> Haoran LI (MS)
> Brain Imaging Lab,
> Research Center for Learning Science,
> Southeast University
> 2 Si Pai Lou , Nanjing, 210096, P.R.China
>
>
=========================================================================
Date: Fri, 13 May 2011 17:31:03 +0200
Reply-To: Laura Zapparoli <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Laura Zapparoli <[log in to unmask]>
Subject: SPM8 and visualization of cortical activations
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf303f6c946699a104a329fef9
Message-ID: <[log in to unmask]>
--20cf303f6c946699a104a329fef9
Content-Type: text/plain; charset=ISO-8859-1
Dear SPM users,
I have a problem with SPM8 and the visualization of cortical activations.
With SPM2, I usually select the contrast of interest in "Results"; then I
select "Render" and I obtain an image like this (activations on 6 little 3-d
brains):
In SPM8 I can't do this anymore.
Any suggestion to obtain the same result?
Thank you,
Laura
--20cf303f6c946699a104a329fef9
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Dear SPM users,<div><br></div><div>I have a problem with SPM8 and the visua=
lization of cortical activations.</div><div>With SPM2, I usually select the=
contrast of interest in "Results"; then I select "Render&qu=
ot; and I obtain an image like this (activations on 6 little 3-d brains):</=
div>
<div><br></div><div><img src=3D"webkit-fake-url://0426A476-5A38-4BDD-BF26-1=
BF9DF363834/image.tiff"></div><div><br></div><div>In SPM8 I can't do th=
is anymore.</div><div><br></div><div>Any suggestion to obtain the same resu=
lt?</div>
<div><br></div><div>Thank you,</div><div>Laura</div>
--20cf303f6c946699a104a329fef9--
=========================================================================
Date: Fri, 13 May 2011 16:52:07 +0100
Reply-To: Iwo Bohr <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Iwo Bohr <[log in to unmask]>
Subject: Re: SPM8 and visualization of cortical activations
Comments: To: Laura Zapparoli <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Mime-Version: 1.0
Content-Type: text/plain; format=flowed; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Dear Laura,
Unfortunately I cannot see your image (it would have been better to attach
it), however to render activations you need to (after specifying/selecting
your contrast)press button "Overlay" (in "Results" window), select "Render"
and then choose a Matlab file to use for rendering From "Previous" drop
down menu choose the rend subdirectory in spm installation directory, from
somehing like this:
/your_installation_dir/spm8/rend/... eg rend_single_subj.mat
Once you've done it, you can use "previous render" option from Overlay.
Hope it helps
Iwo
On May 13 2011, Laura Zapparoli wrote:
>Dear SPM users,
>
> I have a problem with SPM8 and the visualization of cortical activations.
> With SPM2, I usually select the contrast of interest in "Results"; then I
> select "Render" and I obtain an image like this (activations on 6 little
> 3-d brains):
>
>
>In SPM8 I can't do this anymore.
>
>Any suggestion to obtain the same result?
>
>Thank you,
>Laura
>
--
Iwo Bohr, PhD (Torun)
University of Cambridge
Research Centre for English and Applied Linguistics
9 West Road
Cambridge
CB3 9DP
UK
Tel: +44 1223 767 354
Fax: +44 1223 767 398
http://www.rceal.cam.ac.uk/People/Staffpages/ijb25.html
=========================================================================
Date: Fri, 13 May 2011 17:08:50 +0100
Reply-To: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Subject: Re: Simple scripting question - batch loading scans
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Dear Fred,
unfortunately, file selector does not allow to load a list of filenames f=
rom MATLAB variables or .mat files. However, I could think of a number of=
ways to help you select the files:=20
* If all files have the same name, but live in different folders in your =
project (e.g. all con_0001.img files from all your subjects), then you co=
uld navigate to the top level of your project, enter ^con_0001\.img$ into=
the filter field and press the 'Rec' button. This will go through all fo=
lders and eventually collect all con_0001.img files that are found.
* If your files are spread in a more complicated way, you should consider=
the 'Save Batch and Script' option of the batch GUI. If you leave the 'S=
cans' items blank in the GUI, the script skeleton will allow to fill the=
m using standard MATLAB commands. Note, that for the batch system file na=
mes are always cell arrays of strings.
Hope this helps,
Volkmar
=========================================================================
Date: Fri, 13 May 2011 17:46:00 +0100
Reply-To: Iwo Bohr <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Iwo Bohr <[log in to unmask]>
Subject: Re: Simple scripting question - batch loading scans
Comments: To: Volkmar Glauche <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/mixed;
boundary="----=_NextPart_000_0041_01CC1195.9EFA8800"
Message-ID: <[log in to unmask]>
This is a multi-part message in MIME format.
------=_NextPart_000_0041_01CC1195.9EFA8800
Content-Type: text/plain;
charset="us-ascii"
Content-Transfer-Encoding: 7bit
This a good quick method with the record button, however in my case it
returns many unwanted images from some subdirectories.
I've written a small and easy script to go around this problem. It creates a
text file with directories to cons of interest (works only for one and
two-digit affixes though; didn't need more :), then after using Edit button
in 2nd level window you can paste the text, either from a text file or
straight from the Matlab command window
Of course no guarantee of perfection but easy to test and doesn't mess up
your actual data, even if there are bugs in it.
I've just played around with comments only, so there shouldn't be any
errors.
Iwo
-----Original Message-----
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] On
Behalf Of Volkmar Glauche
Sent: 13 May 2011 17:09
To: [log in to unmask]
Subject: Re: [SPM] Simple scripting question - batch loading scans
Dear Fred,
unfortunately, file selector does not allow to load a list of filenames from
MATLAB variables or .mat files. However, I could think of a number of ways
to help you select the files:
* If all files have the same name, but live in different folders in your
project (e.g. all con_0001.img files from all your subjects), then you could
navigate to the top level of your project, enter ^con_0001\.img$ into the
filter field and press the 'Rec' button. This will go through all folders
and eventually collect all con_0001.img files that are found.
* If your files are spread in a more complicated way, you should consider
the 'Save Batch and Script' option of the batch GUI. If you leave the
'Scans' items blank in the GUI, the script skeleton will allow to fill them
using standard MATLAB commands. Note, that for the batch system file names
are always cell arrays of strings.
Hope this helps,
Volkmar
------=_NextPart_000_0041_01CC1195.9EFA8800
Content-Type: application/octet-stream;
name="Level2.m"
Content-Transfer-Encoding: 7bit
Content-Disposition: attachment;
filename="Level2.m"
% print to file con images directories to enter into 2nd level
% # of subjects:
first=3;
last=17;
% contrasts to print to file
con1=73;
con2=73;
% components of directory strings
dir='/home/ijb25/CGproject/Subject';
dir2='model/';
dir3='con_00';
dir4='.img';
% clear previous version
fID=fopen('conIms.txt', 'w');
fclose(fID);
% open for appending
fID=fopen('conIms.txt', 'a+');
for i=con1:con2
for j=first:last
% accounts for two-digit affixes of contrast images names, but not higher!
if i<10; dir3=[dir3 '0']; end
path=[dir num2str(j) '/' dir2 dir3 num2str(i) dir4];
fprintf(fID, '%s \n', path);
end
end
type ('conIms.txt');
fclose(fID);
------=_NextPart_000_0041_01CC1195.9EFA8800--
=========================================================================
Date: Fri, 13 May 2011 10:47:19 -0700
Reply-To: Shabnam Hakimi <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Shabnam Hakimi <[log in to unmask]>
Subject: Magnitude of Z-scores in PPI
MIME-Version: 1.0
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Message-ID: <[log in to unmask]>
--000e0cd48464e05edd04a32be689
Content-Type: multipart/alternative; boundary=000e0cd48464e05ed604a32be687
--000e0cd48464e05ed604a32be687
Content-Type: text/plain; charset=ISO-8859-1
Hi revered PPI experts,
After implementing the PPI code in SPM8 (where there is no mean-centering of
the psychological variable; i.e., spm_detrend has been commented out in
spm_peb_ppi.m) as per Donald's helpful instruction, we are running into an
interesting issue. When we use a dummy variable that only takes values 1 and
0 for the psychological variable with the new algorithm, we end up with
z-scores that are several orders of magnitude more significant than we have
seen previously. The entire brain is significant until p<10E-7, at which
point we begin to see results that are somewhat consistent with previous
work.
We wanted to look at PPI during intertemporal choice. We chose a seed region
in ventromedial PFC, a region that was modulated by subjective value at the
time of choice. The psychological variable corresponded to the time of
choice (i.e., the dummy variable took the value 1 whenever a choice was made
and 0 otherwise). The top figure on the slide shows the results of this
model when demeaning of the psychological variable is done (the old method).
When we updated our analysis to be consistent with the current
implementation of SPM, we got the results on the bottom of the slide. The
only difference between the two analyses is the treatment of the
psychological variable; everything else is exactly the same.
Any ideas on what's going on here? We'd greatly appreciate any help!
Thanks,
Shabnam
--
*Shabnam Hakimi*
Graduate Student
Rangel Neuroeconomics Laboratory
California Institute of Technology
Baxter Hall, Room 332E
Pasadena, CA 91125
phone: 626-395-5988 | fax: 626-405-9841
e-mail: [log in to unmask]
--000e0cd48464e05ed604a32be687
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
<meta charset=3D"utf-8"><span class=3D"Apple-style-span" style=3D"border-co=
llapse: collapse; font-family: arial, sans-serif; font-size: 12px; ">Hi rev=
ered PPI experts,<div><br></div><div>After implementing the PPI code in SPM=
8 (where there is no mean-centering of the psychological variable; i.e., sp=
m_detrend has been commented out in spm_peb_ppi.m) as per Donald's help=
ful instruction, we are running into an interesting issue.=A0When we use a =
dummy variable that only takes values 1 and 0 for the psychological variabl=
e with the new algorithm, we end up with z-scores that are several orders o=
f magnitude more significant than we have seen previously. The entire brain=
is significant until p<10E-7, at which point we begin to see results th=
at are somewhat consistent with previous work.</div>
<div><br></div><div>We wanted to look at PPI during intertemporal choice. W=
e chose a seed region in ventromedial PFC, a region that was modulated by s=
ubjective value at the time of choice. The psychological variable correspon=
ded to the time of choice (i.e., the dummy variable took the value 1 whenev=
er a choice was made and 0 otherwise). The top figure on the slide shows th=
e results of this model when demeaning of the psychological variable is don=
e (the old method). When we updated our analysis to be consistent with the =
current implementation of SPM, we got the results on the bottom of the slid=
e. The only difference between the two analyses is the treatment of the psy=
chological variable; everything else is exactly the same.=A0</div>
<div><br></div><div>Any ideas on what's going on here? We'd greatly=
appreciate any help!</div><div><br></div><div>Thanks,</div><div>Shabnam</d=
iv></span><br clear=3D"all"><br>-- <br><b>Shabnam Hakimi</b><div>Graduate S=
tudent</div>
<div>Rangel Neuroeconomics Laboratory</div><div>California Institute of Tec=
hnology</div><div>Baxter Hall, Room 332E</div><div>Pasadena, CA 91125</div>=
<div>phone: 626-395-5988 | fax: 626-405-9841</div><div><div>e-mail:=A0<a hr=
ef=3D"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]</a>=
</div>
</div><br>
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--000e0cd48464e05edd04a32be689--
=========================================================================
Date: Fri, 13 May 2011 19:06:42 +0100
Reply-To: Carlos Faraco <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Carlos Faraco <[log in to unmask]>
Subject: SPM8 Reorients, but gives errors
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear SPMers,
I am reorienting some files with SPM8 and even though it seems to success=
fully reorient, it gives some errors.
They output is:
??? Error using =3D=3D> spm_input at 843
Input window cleared whilst waiting for response: Bailing out!
Error in =3D=3D> spm_orthviews>zoom_op at 795
thr =3D spm_input('Threshold (Y > ...)', '+1', 'r', '0', 1);
Error in =3D=3D> spm_orthviews at 449
zoom_op(varargin{:});
Error in =3D=3D> spm_image at 267
spm_orthviews('Zoom',zl(cz),rl(cz));
??? Error using =3D=3D> waitfor
Error while evaluating uicontrol Callback
??? Error using =3D=3D> spm_input at 843
Input window cleared whilst waiting for response: Bailing out!
Error in =3D=3D> spm_image at 172
spm_orthviews('Window',1,spm_input('Range','+1','e','',2));
??? Error using =3D=3D> waitfor
Error while evaluating uicontrol Callback
??? Error using =3D=3D> spm_input at 843
Input window cleared whilst waiting for response: Bailing out!
Error in =3D=3D> spm_image at 172
spm_orthviews('Window',1,spm_input('Range','+1','e','',2));
??? Error while evaluating uicontrol Callback
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D
Is this just a Display error? Should I be worrying about this?
Thanks,
Carlos
=========================================================================
Date: Fri, 13 May 2011 15:32:47 -0400
Reply-To: Hekmatyar <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Hekmatyar <[log in to unmask]>
Subject: Re: imcalc
In-Reply-To: <[log in to unmask]>
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Hi SPM experts
I created a mask from functional and would like to multiply this mask =
with a thousand of images. How do I do that? I know, I can do that with =
few images. Is that prod(X) work? Please throw me some suggestions.
Thanks
Khan=20
=========================================================================
Date: Fri, 13 May 2011 20:38:20 +0100
Reply-To: "Stephen J. Fromm" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Stephen J. Fromm" <[log in to unmask]>
Subject: Re: Ancova in SPM8
Comments: To: Ryan Herringa <[log in to unmask]>
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Hmm...it's hard for me to tell about centering just by reading the SPM op=
tions for it. I tried to load your job into SPM but it doesn't generate =
the design matrix, because obviously I don't have the data files.
That said, I think the centering is probably correct just based on the de=
sign matrix schematic that you'd posted previously.
First, an aside: when I loaded the job, it showed you had set ANCOVA to =
"yes" under the "factor" part of the design spec. That's a "different" A=
NCOVA; it's for PET. So change that to "no". (That said, I don't think =
it affected the way your design was set up.)
So, getting back to the main question:
I think the design is fine. It's just a matter of knowing how to interpr=
et the results, ie what the betas are. So you can make appropriate contr=
asts.
In rough, verbal terms, the betas for the first four columns are the main=
effect of condition, and the other columns are the condition-by-covariat=
e interactions.
If you want to more precisely delineate what's going on, write the model =
down symbolically:
Condition: 1 <=3D i <=3D 4
Subject: 1 <=3D j <=3D 13
Covariate: 1 <=3D k <=3D 2
y_ij =3D beta_i + C_jk * gamma_ik + error
(say). It's Einstein summation notation (sum over repeated indices), so =
it means
y_ij =3D beta_i + C_j1 * gamma_i1 + C_j2 * gamma_i2 =
+ error
* y is the data; it's indexed by condition and subject, but not by covari=
ate
* beta_i is the "beta" for condition i
* C_jk {k=3D1,2} are the mean-centered covariates. They don't depend on =
condition, i, but only on subject, j.
* gamma_ik is the "beta" for the condition-by-covariate interaction
If we average over subject but not over condition, we get
y^hat_i. =3D beta_i
Why? The C_j1 and C_j2 are mean-centered so go away. The error goes awa=
y since we're looking at predicted values in this type of formulation.
So, the parameter estimates for the first four columns are the effect of =
condition. (Perhaps technically it's the differences of these...I'm not =
sure what conditions you're using, though you said in a previous post tha=
t they're already differences.) And the remaining parameters, what I've =
called the gammas, pretty clearly give the appropriate interactions. You=
can think of them as similar to the textbook ANCOVA examples, where the =
horizontal axis is the value of the covariate. Only difference with your=
case here is that you have two covariates not one.
There's a subtlety to ANCOVA that always comes up. Here, e.g., beta_3 is=
the mean for condition three. But the meaning of that number is clouded=
because it's for a "typical" subject in your set of subjects, and for th=
e average such subject the covariate is zero (precisely because it's been=
mean-centered). But that's not necessarily indicative of a truly generi=
c subject. Though this issue is typically more at hand in cases where AN=
COVA is used with a group factor, not a within-subject factor.
=========================================================================
Date: Sat, 14 May 2011 11:01:17 +0530
Reply-To: thamodharan <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: thamodharan <[log in to unmask]>
Subject: SPM8 second level Analysis-reg
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=00163683303a463add04a335bb66
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--00163683303a463add04a335bb66
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Hi All,
Here i have a request that, We are (our team) working with SPM8. We are
able to Process the Pre processing levels (1.SliceTiming 2.ReAlignment
3.CoRegister 4.Normalization and 5.Smoothing) and also upto First level
analysis. We are able to get the images with activation in the first level
analysis. at the end of the first level analysis we are getting con images
as well as SPM.img images. while processing the second level analysis we
are getting doubts with the images. which images we can take for second
level analysis? Please help us to tackle this problem.
--
Best Regards,
A.Dhamu BE.,
(09976413557,07760662060)
--00163683303a463add04a335bb66
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<div>Hi All,</div>
<div>=A0</div>
<div>Here i have a request that,=A0=A0=A0 We are (our team)=A0 working with=
SPM8. We are able to Process the =A0Pre processing levels (1.SliceTiming=
=A0 2.ReAlignment 3.CoRegister 4.Normalization=A0 and 5.Smoothing) and also=
upto First level analysis. We are able to get the images with activation i=
n the first level analysis. at the end of the first level analysis we are g=
etting con images as well as SPM.img images.=A0 while processing the second=
level analysis we are getting doubts with the images. which images=A0we =
=A0can take for second level analysis? Please help us to tackle this proble=
m.</div>
<div><br clear=3D"all"><br>-- <br></div>
<div><font color=3D"#000099">Best Regards,</font></div>
<div><font color=3D"#000099">A.Dhamu BE.,</font></div>
<div><font color=3D"#000099">(09976413557,07760662060)</font></div><br>
--00163683303a463add04a335bb66--
=========================================================================
Date: Sat, 14 May 2011 11:02:55 +0530
Reply-To: thamodharan <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: thamodharan <[log in to unmask]>
Subject: SPM8 Second level Analysis-Reg
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0016e65aef9225e5fa04a335c13a
Message-ID: <[log in to unmask]>
--0016e65aef9225e5fa04a335c13a
Content-Type: text/plain; charset=ISO-8859-1
Hi All,
Here i have a request that, We are (our team) working with SPM8. We are
able to Process the Pre processing levels (1.SliceTiming 2.ReAlignment
3.CoRegister 4.Normalization and 5.Smoothing) and also upto First level
analysis. We are able to get the images with activation in the first level
analysis. at the end of the first level analysis we are getting con images
as well as SPM.img images. while processing the second level analysis we
are getting doubts with the images. which images we can take for second
level analysis? Please help us to tackle this problem.
Thanking You All.
--
Best Regards,
A.Dhamu BE.,
(09976413557,07760662060)
--0016e65aef9225e5fa04a335c13a
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
<div><br clear=3D"all">Hi All,<br>=A0<br>Here i have a request that,=A0=A0=
=A0 We are (our team)=A0 working with SPM8. We are able to Process the=A0 P=
re processing levels (1.SliceTiming=A0 2.ReAlignment 3.CoRegister 4.Normali=
zation=A0 and 5.Smoothing) and also upto First level analysis. We are able =
to get the images with activation in the first level analysis. at the end o=
f the first level analysis we are getting con images as well as SPM.img ima=
ges.=A0 while processing the second level analysis we are getting doubts wi=
th the images. which images we=A0 can take for second level analysis? Pleas=
e help us to tackle this problem.</div>
<div>=A0</div>
<div>=A0</div>
<div>=A0</div>
<div>=A0</div>
<div>=A0</div>
<div>=A0</div>
<div>Thanking You All.</div>
<div>=A0</div>
<div><br>-- <br></div>
<div><font color=3D"#000099">Best Regards,</font></div>
<div><font color=3D"#000099">A.Dhamu BE.,</font></div>
<div><font color=3D"#000099">(09976413557,07760662060)</font></div><br>
--0016e65aef9225e5fa04a335c13a--
=========================================================================
Date: Sat, 14 May 2011 19:46:05 +0800
Reply-To: Linling Li <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Linling Li <[log in to unmask]>
Subject: Problem about how to deal with the activation within ventricles
of the brain
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=========================================================================
Date: Sat, 14 May 2011 09:31:35 -0700
Reply-To: Gui Xue <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Gui Xue <[log in to unmask]>
Subject: Postdoctoral Scholar positions at USC
Comments: To: FSL - FMRIB's Software Library <[log in to unmask]>
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*The Department of Psychology at the University of Southern
California*announces one or more Postdoctoral Scholar positions to
study the neural
mechanisms of risky decision-making (under the direction of Professor
Stephen J. Read).
The postdoctoral fellow is expected to contribute to NIMH-funded research
investigating the neural mechanisms of risky sexual decision making in Meth
and non-Meth using men who have sex with men (MSM) at USC, as part of a tea=
m
including Zhong-Lin Lu, Antoine Bechara, Lynn C. Miller, and Robert Appleby=
.
Using behavioral testing, fMRI, and computational modeling techniques (e.g,
Neural Networks), the goal of the decision making project is to develop a
detailed model of the neural mechanisms involved in risky sexual
decision-making. The individual in this position will be involved in the
design and conduct of behavioral experiments in the scanner, in data
analysis, and in the computational modeling of the relevant neural
circuits/mechanisms. Opportunities exist for interaction with social
psychology faculty and with faculty in the Dornsife Cognitive Neuroscience
Imaging Center.
*Requirements* =96 Candidates should have a Ph.D. in a relevant discipline,
experience with fMRI, and experience with behavioral and/or computational
approaches to decision-making and cognitive processing. Familiarity with
computational and statistical methods (e.g. MatLab, Psychtoolbox, Neural
Networks, statistical programs) is highly advantageous.
The appointment could begin as early as September 2011 for a period of one
year. Renewal is based on performance and availability of grant support.
Salary will be commensurate with experience, minimum salary: $40,000.
*Application Procedures* =96 Please send a cover letter (including a
description of research skills), a CV, and the names/contact information of
three (3) references to:
Stephen J. Read ([log in to unmask])
--001636284b10ad215504a33ef4dd
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<style>@font-face {
font-family: "Cambria";
}p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0in 0in 10pt; font-size=
: 12pt; font-family: "Times New Roman"; }div.Section1 { page: Section1; }</=
style>
<p class=3D"MsoNormal" style=3D"margin-bottom: 0.0001pt;"><b style=3D""><sp=
an style=3D"font-family: Helvetica;">The
Department of Psychology at the University of Southern California</span></b=
><span style=3D"font-family: Helvetica;"> announces one or
more Postdoctoral Scholar positions to study the neural mechanisms of risky
decision-making (under the direction of Professor Stephen J. Read).</span><=
/p>
<p class=3D"MsoNormal" style=3D"margin-bottom: 0.0001pt;"><span style=3D"fo=
nt-family: Helvetica;">=A0</span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom: 0.0001pt;"><span style=3D"fo=
nt-family: Helvetica;">The postdoctoral fellow is expected to
contribute to NIMH-funded research investigating the neural mechanisms of r=
isky
sexual decision making in Meth and non-Meth using men who have sex with men
(MSM) at USC, as part of a team including Zhong-Lin Lu, Antoine Bechara, Ly=
nn
C. Miller, and Robert Appleby. Using behavioral testing, fMRI, and
computational modeling techniques (e.g, Neural Networks), the goal of the
decision making project is to develop a detailed model of the neural mechan=
isms
involved in risky sexual decision-making. <span style=3D"">=A0</span>The in=
dividual in this position will be involved in the
design and conduct of behavioral experiments in the scanner, in data analys=
is,
and in the computational modeling of the relevant neural circuits/mechanism=
s.<span style=3D"">=A0 </span>Opportunities exist for interaction
with social psychology faculty and with faculty in the Dornsife Cognitive
Neuroscience Imaging Center. </span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom: 0.0001pt;"><span style=3D"fo=
nt-family: Helvetica;">=A0</span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom: 0.0001pt;"><b style=3D""><sp=
an style=3D"font-family: Helvetica;">Requirements</span></b><span style=3D"=
font-family: Helvetica;"> =96 Candidates
should have a Ph.D. in a relevant discipline, experience with fMRI, and
experience with behavioral and/or computational approaches to decision-maki=
ng
and cognitive processing. Familiarity with computational and statistical
methods (e.g. MatLab, Psychtoolbox, Neural Networks, statistical programs) =
is
highly advantageous.</span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom: 0.0001pt;"><span style=3D"fo=
nt-family: Helvetica;">=A0</span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom: 0.0001pt;"><span style=3D"fo=
nt-family: Helvetica;">The appointment could begin as early as
September 2011 for a period of one year. Renewal is based on performance an=
d
availability of grant support. Salary will be commensurate with experience,
minimum salary: $40,000.</span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom: 0.0001pt;"><span style=3D"fo=
nt-family: Helvetica;">=A0</span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom: 0.0001pt;"><b style=3D""><sp=
an style=3D"font-family: Helvetica;">Application
Procedures</span></b><span style=3D"font-family: Helvetica;"> =96 Please se=
nd a cover letter (including a description of research
skills), a CV, and the names/contact information of three (3) references to=
:</span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom: 0.0001pt;"><span style=3D"fo=
nt-family: Helvetica;">=A0</span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom: 0.0001pt;"><span style=3D"fo=
nt-family: Helvetica;">Stephen J. Read (<a href=3D"mailto:[log in to unmask]">rea=
[log in to unmask]</a>)</span></p>
--001636284b10ad215504a33ef4dd--
=========================================================================
Date: Sat, 14 May 2011 17:04:27 -0400
Reply-To: "Watson, Christopher" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Watson, Christopher" <[log in to unmask]>
Subject: Re: SPM8 Second level Analysis-Reg
Comments: To: thamodharan <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Content-Type: text/plain; charset="us-ascii"
Content-Transfer-Encoding: quoted-printable
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
Use the con_???? image of interest.
________________________________________
From: SPM (Statistical Parametric Mapping) [[log in to unmask]] On Behalf O=
f thamodharan [[log in to unmask]]
Sent: Saturday, May 14, 2011 1:32 AM
To: [log in to unmask]
Subject: [SPM] SPM8 Second level Analysis-Reg
Hi All,
Here i have a request that, We are (our team) working with SPM8. We are=
able to Process the Pre processing levels (1.SliceTiming 2.ReAlignment 3=
.CoRegister 4.Normalization and 5.Smoothing) and also upto First level ana=
lysis. We are able to get the images with activation in the first level ana=
lysis. at the end of the first level analysis we are getting con images as =
well as SPM.img images. while processing the second level analysis we are =
getting doubts with the images. which images we can take for second level =
analysis? Please help us to tackle this problem.
Thanking You All.
--
Best Regards,
A.Dhamu BE.,
(09976413557,07760662060)
=========================================================================
Date: Sat, 14 May 2011 22:29:31 +0100
Reply-To: Thomas Nichols <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Thomas Nichols <[log in to unmask]>
Subject: Re: Compare conjunction
Comments: To: Noelia Ventura <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/related; boundary=90e6ba53ab7832445c04a3431ecd
Message-ID: <[log in to unmask]>
--90e6ba53ab7832445c04a3431ecd
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Dear Noelia,
I wanted to second Sarika's suggestion. But I am confused by your response=
:
"in this region there is no response for unisensory conditions"; if there
is no response for either A>0 or B>0, then you don't have a conjunction of
(A>0)(B>0)(C>A)(C>B). So isn't this negative result appropriate?
-Tom
On Tue, May 10, 2011 at 2:54 PM, Noelia Ventura <[log in to unmask]> wrote=
:
> Hi Sarika,
>
> Thank you for your response.
>
> This does not function for our particular data set as we include a 3
> conditions: A =3D auditory, B =3D visual and C =3D audiovisual. We are no=
w
> examining the multimodal region. In this region there is no response for =
the
> unisensory conditions and therefore this leads to a null result in the
> conjunction you suggested.
>
> Do you have a solution for this? Or anyone else?
>
> Thanks,
>
> Noelia
>
>
> El 09/05/2011 11:58, sarika cherodath escribi=F3:
>
> Hi,
>
> I am not sure whether this could work, but you can make a subtraction of
> L1 and L2 for each condition and then do a conjunction to create the
> required contrast.
>
>
> On Mon, May 9, 2011 at 2:47 PM, Noelia Ventura <[log in to unmask]>wrot=
e:
>
>> Hi all,
>>
>> We would like to compare directly the results of two conjunction analyse=
s.
>> These conjunctions show overlapping clusters. One conjunction shows a
>> larger cluster then the other. We would like to examine whether the voxe=
ls
>> that show up for one conjunction but not for the other differ significan=
tly
>> from each other.
>>
>> In more detail, we have two tasks in the native (L1) and non-native
>> language (L2). Each task consists of 3 conditions, (A, B, C). In the
>> random effects we use a full factorial within subjects design and create=
a
>> contrast : ( and we do this conjunction for L1 and L2. We would like t=
o
>> know in which voxels the conjunction of L1 > L2.
>>
>>
>>
>> However, in spm you cannot directly compare to conjunctions with each
>> other. Or can you?
>>
>> We would like to use imcalc to test where i1 =3D conj L1, i2 =3D conj L2=
and
>> our expression is i1 -i2> 0. However, i think we obtain a binary image f=
rom
>> that but we need a statistical image. Can anyone provide a solution for
>> this?
>>
>> Thanks for your help,
>> Noelia
>>
>
>
>
> --
> Sarika Cherodath
> Graduate Student
> National Brain Research Centre
> Manesar, Gurgaon -122050
> India
>
>
>
--=20
____________________________________________
Thomas Nichols, PhD
Principal Research Fellow, Head of Neuroimaging Statistics
Department of Statistics & Warwick Manufacturing Group
University of Warwick
Coventry CV4 7AL
United Kingdom
Email: [log in to unmask]
Phone, Stats: +44 24761 51086, WMG: +44 24761 50752
Fax: +44 24 7652 4532
--90e6ba53ab7832445104a3431ecc
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Dear=A0Noelia,<div><br></div><div>I wanted to second Sarika's suggestio=
n. =A0But I am confused by your response: =A0"in this region there is =
no response for unisensory conditions"; if there is no response for ei=
ther A>0 or B>0, then you don't have a conjunction of (A>0)<me=
ta charset=3D"utf-8">(B>0)<meta charset=3D"utf-8">(C>A)<meta charset=
=3D"utf-8">(C>B). =A0So isn't this negative result appropriate?</div=
>
<div><br></div><div>-Tom<br><br><div class=3D"gmail_quote">On Tue, May 10, =
2011 at 2:54 PM, Noelia Ventura <span dir=3D"ltr"><<a href=3D"mailto:ven=
[log in to unmask]">[log in to unmask]</a>></span> wrote:<br><blockquote =
class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1px #ccc solid=
;padding-left:1ex;">
=20
=20
=20
<div bgcolor=3D"#ffffff" text=3D"#000000">
Hi Sarika,<br>
<br>
Thank you for your response.<br>
<br>
This does not function for our particular data set as we include a 3
conditions: A =3D auditory, B =3D visual and C =3D audiovisual. We are =
now
examining the multimodal region. In this region there is no response
for the unisensory conditions and therefore this leads to a null
result in the conjunction you suggested. <br>
<br>
Do you have a solution for this? Or anyone else?<br>
<br>
Thanks,<br>
<br>
Noelia<br>
<br>
<br>
El 09/05/2011 11:58, sarika cherodath escribi=F3:
<blockquote type=3D"cite">
<div dir=3D"ltr">
<div>Hi,</div>
<div><br>
</div>
I am not sure whether this could work, but you can make a
subtraction of L1 and L2 for each condition and then do a
conjunction to create the required contrast.<div><div></div><div cl=
ass=3D"h5"><br>
<br>
<div class=3D"gmail_quote">
On Mon, May 9, 2011 at 2:47 PM, Noelia Ventura <span dir=3D"ltr">=
<<a href=3D"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]
ji.es</a>></span>
wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin:0pt 0pt 0pt 0.8=
ex;border-left:1px solid rgb(204, 204, 204);padding-left:1ex">
<div bgcolor=3D"#ffffff" text=3D"#000000"> <span lang=3D"EN-GB"=
>Hi
all,</span>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">We would like to
compare directly the results of two conjunction
analyses.<span>=A0 </span>These conjunctions show
overlapping clusters. One conjunction shows a larger
cluster then the other. We would like to examine
whether the voxels that show up for one conjunction
but not for the other differ significantly from each
other. </span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">In more detail, w=
e
have two tasks in the native (L1) and non-native
language (L2). <span>=A0</span>Each task consists of 3
conditions, (A, B, C).<span>=A0 </span>In the random
effects we use a full factorial within subjects design
and create a contrast : </span><span lang=3D"EN-GB">(</sp=
an><span style=3D"font-size:11pt;line-height:115%"><img src=3D"cid:part1.07=
[log in to unmask]" width=3D"246" height=3D"20"></span><span lang=
=3D"EN-GB"><span>=A0
</span>and we do this conjunction for L1 and L2. <span>=
=A0</span>We
would like to know in which voxels the conjunction of
L1 > L2. </span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">=A0</span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">However, in spm
you cannot directly compare to conjunctions with each
other. Or can you?</span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">We would like to
use imcalc to test where i1 =3D conj L1, i2 =3D conj L2
and our expression is i1 -i2> 0. However, i think
we obtain a binary image from that but we need a
statistical image. Can anyone provide a solution for
this? <br>
</span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-GB">Thanks for your
help,<br>
Noelia<br>
</span></p>
</div>
</blockquote>
</div>
<br>
<br clear=3D"all">
<br></div></div>
-- <br>
Sarika Cherodath<br>
Graduate Student<br>
National Brain Research Centre<br>
Manesar, Gurgaon -122050<br>
India<br>
<br>
</div>
</blockquote>
<br>
</div>
</blockquote></div><br><br clear=3D"all"><br>-- <br>_______________________=
_____________________<br>Thomas Nichols, PhD<br>Principal Research Fellow, =
Head of Neuroimaging Statistics<br>Department of Statistics & Warwick M=
anufacturing Group<br>
University of Warwick<br>Coventry=A0 CV4 7AL<br>United Kingdom<br><br>Email=
: <a href=3D"mailto:[log in to unmask]">[log in to unmask]</a=
><br>Phone, Stats: +44 24761 51086, WMG: +44 24761 50752<br>Fax:=A0 +44 24 =
7652 4532<br>
<br>
</div>
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--90e6ba53ab7832445c04a3431ecd--
=========================================================================
Date: Sat, 14 May 2011 22:35:10 +0100
Reply-To: Thomas Nichols <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Thomas Nichols <[log in to unmask]>
Subject: Re: SnPM error
Comments: To: Matthew Tryon <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
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Dear Matthew,
Can you let me know what version of SPM and SnPM you're using? I just
checked and that function (spm_create_image) hasn't been part of the main
SnPM code since SnPM3. It does live on in snpm_combo_pp, a toolbox inside
the SnPM toolbox; were you trying to do combining inference?
-Tom
On Tue, May 10, 2011 at 3:20 AM, Matthew Tryon <[log in to unmask]>wrote:
> Hi All,
>
> I'm a novice with using SnPM and I'd be very grateful for any assistance.
> I'm in the process of trying to execute the fMRI example as outlined in the
> SnPM documentation. The SnPMcfg.mat file is generated fine, but I get the
> following error when I click on the compute button:
>
> SnPM: snpm_cp
> ========================================================================
> Initialising...
> ??? Maximum recursion limit of 500 reached. Use set(0,'RecursionLimit',N)
> to change the limit. Be aware that exceeding your available stack space
> can
> crash MATLAB and/or your computer.
>
> Error in ==> spm_create_image
>
>
> ??? Error while evaluating uicontrol Callback
>
>
> I'm using MATLAB 7.10 on OSX. I sincerely appreciate any help.
>
> Kind Regards,
>
> Matthew Tryon
> --
>
>
--
____________________________________________
Thomas Nichols, PhD
Principal Research Fellow, Head of Neuroimaging Statistics
Department of Statistics & Warwick Manufacturing Group
University of Warwick
Coventry CV4 7AL
United Kingdom
Email: [log in to unmask]
Phone, Stats: +44 24761 51086, WMG: +44 24761 50752
Fax: +44 24 7652 4532
--90e6ba53aab069a96504a34332c5
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Dear Matthew,<div><br></div><div>Can you let me know what version of SPM an=
d SnPM you're using? =A0I just checked and that function (spm_create_im=
age) hasn't been part of the main SnPM code since SnPM3. =A0It does liv=
e on in snpm_combo_pp, a toolbox inside the SnPM toolbox; were you trying t=
o do combining inference?</div>
<div><br></div><div>-Tom<br><br><div class=3D"gmail_quote">On Tue, May 10, =
2011 at 3:20 AM, Matthew Tryon <span dir=3D"ltr"><<a href=3D"mailto:matt=
[log in to unmask]">[log in to unmask]</a>></span> wrote:<br><bloc=
kquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1px #cc=
c solid;padding-left:1ex;">
<div style=3D"word-wrap:break-word;color:rgb(0, 0, 0);font-size:14px;font-f=
amily:Helvetica, sans-serif"><div><div><div><div>Hi All,</div><div><br></di=
v><div>I'm a novice with using SnPM and I'd be very grateful for an=
y assistance. =A0I'm in the process of=A0trying to execute the fMRI exa=
mple as outlined in the SnPM documentation. =A0The SnPMcfg.mat file is gene=
rated fine, but I get the following error when I click on the compute butto=
n:</div>
<div><br></div><div><div>SnPM: snpm_cp</div><div>=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D</div><div>Initialising...</div><=
div>??? Maximum recursion limit of 500 reached. Use set(0,'RecursionLim=
it',N)</div>
<div>to change the limit. =A0Be aware that exceeding your available stack s=
pace can</div><div>crash MATLAB and/or your computer.</div><div><br></div><=
div>Error in =3D=3D> spm_create_image</div><div><br></div><div><br></div=
><div>
??? Error while evaluating uicontrol Callback</div></div><div><br></div><di=
v><br></div><div>I'm using MATLAB 7.10 on OSX. =A0I sincerely appreciat=
e any help.</div><div><br></div><div>Kind Regards,</div><div><br></div><div=
>
Matthew Tryon</div></div><div><div>-- </div><div><br></div></div></div></di=
v></div>
</blockquote></div><br><br clear=3D"all"><br>-- <br>_______________________=
_____________________<br>Thomas Nichols, PhD<br>Principal Research Fellow, =
Head of Neuroimaging Statistics<br>Department of Statistics & Warwick M=
anufacturing Group<br>
University of Warwick<br>Coventry=A0 CV4 7AL<br>United Kingdom<br><br>Email=
: <a href=3D"mailto:[log in to unmask]">[log in to unmask]</a=
><br>Phone, Stats: +44 24761 51086, WMG: +44 24761 50752<br>Fax:=A0 +44 24 =
7652 4532<br>
<br>
</div>
--90e6ba53aab069a96504a34332c5--
=========================================================================
Date: Sat, 14 May 2011 22:49:22 +0100
Reply-To: Thomas Nichols <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Thomas Nichols <[log in to unmask]>
Subject: Re: SPM2 Versus SPM8
Comments: To: Min <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
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Dear Min,
In SPM8 FDR topological inference was introduced, and voxel-wise
FDR inference hidden. Topological inference means inference on peaks and
clusters; voxel-wise inference is based on every individual voxel in the
image (instead of spatial features of the image). Thus "Topological FDR"
means inference on clusters based on cluster size (or local peaks based on
peak height), controlling the fraction of false positive clusters among all
clusters (or false positive peaks among all peaks) on average, over many
experiments.
While topological FDR results may be easier to interpret, in my experience
it is is generally not very sensitivity and yields similar results to
FWE-corrected inferences. This would explain your reduction in sensitivity
moving from SPM2 to SPM8.
If you would like to use voxel-wise FDR in SPM8, edit spm_defaults, changin=
g
"topoFDR" line to read
defaults.stats.topoFDR =3D 0;
(quit and re-start SPM to take effect).
For more on this see references below.
-Tom
Chumbley, J., Worsley, K., Flandin, G., & Friston, K. (2010). Topological
FDR for neuroimaging. *NeuroImage*, *49*(4), 3057-64. doi:
10.1016/j.neuroimage.2009.10.090.
Chumbley, J. R., & Friston, K. J. (2009). False discovery rate revisited:
FDR and topological inference using Gaussian random fields. *Neuroimage*, *
44*(1), 62=9670. doi: 10.1016/j.neuroimage.2008.05.021.
On Tue, May 10, 2011 at 11:27 AM, Min <[log in to unmask]> wrote:
> Dear SPM's users,
>
> I ran spm2 and spm8, respectively, for the same set of fMRI data. Howeve=
r,
> though I followed the same steps for the two versions of spm, there are
> considerable differences in the results. With spm8, no suprathreshold
> clusters were found with fdr(0.05) corrected, while with spm 2, more than=
8
> clusters survive the threshold (T values of height threshold are nearly t=
he
> same for the two analysis).
>
> I am unsure how to explain such a big difference between the results from
> two versions of spm.
>
> I will be grateful for any help!
>
> Sincerely,
> Min
>
--=20
____________________________________________
Thomas Nichols, PhD
Principal Research Fellow, Head of Neuroimaging Statistics
Department of Statistics & Warwick Manufacturing Group
University of Warwick
Coventry CV4 7AL
United Kingdom
Email: [log in to unmask]
Phone, Stats: +44 24761 51086, WMG: +44 24761 50752
Fax: +44 24 7652 4532
--bcaec517ae5a2c378404a3436557
Content-Type: text/html; charset=windows-1252
Content-Transfer-Encoding: quoted-printable
Dear Min,<div><br></div><div>In SPM8 FDR topological inference was introduc=
ed, and voxel-wise FDR=A0inference=A0hidden. =A0Topological inference means=
inference on peaks and clusters; voxel-wise inference is based on every in=
dividual voxel in the image (instead of spatial features of the image). =A0=
Thus "Topological FDR" means inference on clusters based on clust=
er size (or local peaks based on peak height), controlling the fraction of =
false positive=A0clusters among all clusters=A0(or false positive peaks amo=
ng all peaks) on average, over many experiments.</div>
<div><br></div><div>While=A0topological=A0FDR results may be easier to inte=
rpret, in my experience it is is generally not very sensitivity and=A0yield=
s=A0similar results to FWE-corrected inferences. =A0This would explain your=
reduction in sensitivity moving from SPM2 to SPM8.</div>
<div><br></div><div>If you would like to use voxel-wise FDR in SPM8, edit s=
pm_defaults, changing "topoFDR" line to read</div><blockquote cla=
ss=3D"webkit-indent-blockquote" style=3D"margin: 0 0 0 40px; border: none; =
padding: 0px;">
<div><div><font class=3D"Apple-style-span" face=3D"'courier new', m=
onospace">defaults.stats.topoFDR =A0 =A0 =A0=3D 0;</font></div></div></bloc=
kquote><div>(quit and re-start SPM to take effect).</div><div><br></div><di=
v>For more on this see references below.</div>
<div><br></div><div>-Tom</div><div><br></div><div><p style=3D"margin-left:2=
4pt;text-indent:-24.0pt">Chumbley, J., Worsley, K., Flandin, G., & Fris=
ton, K. (2010). Topological FDR for neuroimaging. <i>NeuroImage</i>, <i>49<=
/i>(4), 3057-64. doi: 10.1016/j.neuroimage.2009.10.090.</p>
<p style=3D"margin-left:24pt;text-indent:-24.0pt">Chumbley, J. R., & Fr=
iston, K. J. (2009). False discovery rate revisited: FDR and topological in=
ference using Gaussian random fields. <i>Neuroimage</i>, <i>44</i>(1), 62=
=9670. doi: 10.1016/j.neuroimage.2008.05.021.</p>
</div><div><br><div class=3D"gmail_quote">On Tue, May 10, 2011 at 11:27 AM,=
Min <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">minxu86@gma=
il.com</a>></span> wrote:<br><blockquote class=3D"gmail_quote" style=3D"=
margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
Dear SPM's users,<br>
<br>
I ran spm2 and spm8, respectively, for the same set of fMRI data. =A0Howeve=
r, though I followed the same steps for the two versions of spm, there are =
considerable differences in the results. =A0With spm8, no suprathreshold cl=
usters were found with fdr(0.05) corrected, while with spm 2, more than 8 c=
lusters survive the threshold (T values of height threshold are nearly the =
same for the two analysis).<br>
<br>
I am unsure how to explain such a big difference between the results from t=
wo versions of spm.<br>
<br>
I will be grateful for any help!<br>
<br>
Sincerely,<br>
<font color=3D"#888888">Min<br>
</font></blockquote></div><br><br clear=3D"all"><br>-- <br>________________=
____________________________<br>Thomas Nichols, PhD<br>Principal Research F=
ellow, Head of Neuroimaging Statistics<br>Department of Statistics & Wa=
rwick Manufacturing Group<br>
University of Warwick<br>Coventry=A0 CV4 7AL<br>United Kingdom<br><br>Email=
: <a href=3D"mailto:[log in to unmask]">[log in to unmask]</a=
><br>Phone, Stats: +44 24761 51086, WMG: +44 24761 50752<br>Fax:=A0 +44 24 =
7652 4532<br>
<br>
</div>
--bcaec517ae5a2c378404a3436557--
=========================================================================
Date: Sun, 15 May 2011 19:29:15 +0800
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Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?GBK?B?t8nE8Q==?= <[log in to unmask]>
Subject: Re: Batch problem--3D Source Reconstruction
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=========================================================================
Date: Sun, 15 May 2011 23:38:23 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Batch problem--3D Source Reconstruction
Comments: To: =?UTF-8?B?6aOe6bif?= <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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=========================================================================
Date: Sun, 15 May 2011 23:45:30 +0100
Reply-To: G Elliott Wimmer <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: G Elliott Wimmer <[log in to unmask]>
Subject: variable use in spm_imcalc
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Hi,
I'm having a simple problem with spm_imcalc / spm_imcalc_ui. I need to r=
ead in a variable to be used in the imcalc equation.=20=20
The basic idea is to do this:
spm_imcalc_ui({'input1.img','input2.img'},'output.img','i2.*(i1>thresh1)'=
)
in a batch script, where 'thresh1' is a value previously calculated for e=
ach subject. The function works if I use a simple number, e.g. '1', in p=
lace of the variable.
However, adapting the command to read in the extra variable, for example:=
spm_imcalc({'input1.img','input2.img'},'output.img','i2.*(i1>thresh1)',{[=
],[],[],[]},thresh1);=20
has not worked. I think I must be missing something about the syntax. (=
Judging by the lack of questions posted to the board on imcalc and variab=
les, it's something obvious, or it's a function that SPM people never use=
.)
Thank you for any help!
Best regards,
Elliott
Dept. of Psychology
Columbia University
New York, NY
=========================================================================
Date: Sun, 15 May 2011 20:17:51 -0400
Reply-To: "Watson, Christopher" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Watson, Christopher" <[log in to unmask]>
Subject: Re: variable use in spm_imcalc
Comments: To: G Elliott Wimmer <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Content-Type: text/plain; charset="us-ascii"
Content-Transfer-Encoding: quoted-printable
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
It'll probably work if you use sprintf
________________________________________
From: SPM (Statistical Parametric Mapping) [[log in to unmask]] On Behalf O=
f G Elliott Wimmer [[log in to unmask]]
Sent: Sunday, May 15, 2011 6:45 PM
To: [log in to unmask]
Subject: [SPM] variable use in spm_imcalc
Hi,
I'm having a simple problem with spm_imcalc / spm_imcalc_ui. I need to rea=
d in a variable to be used in the imcalc equation.
The basic idea is to do this:
spm_imcalc_ui({'input1.img','input2.img'},'output.img','i2.*(i1>thresh1)')
in a batch script, where 'thresh1' is a value previously calculated for eac=
h subject. The function works if I use a simple number, e.g. '1', in place=
of the variable.
However, adapting the command to read in the extra variable, for example:
spm_imcalc({'input1.img','input2.img'},'output.img','i2.*(i1>thresh1)',{[],=
[],[],[]},thresh1);
has not worked. I think I must be missing something about the syntax. (Ju=
dging by the lack of questions posted to the board on imcalc and variables,=
it's something obvious, or it's a function that SPM people never use.)
Thank you for any help!
Best regards,
Elliott
Dept. of Psychology
Columbia University
New York, NY
=========================================================================
Date: Sun, 15 May 2011 20:44:06 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: variable use in spm_imcalc
Comments: To: G Elliott Wimmer <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0023545309c8e42b7804a359f3e4
Message-ID: <[log in to unmask]>
--0023545309c8e42b7804a359f3e4
Content-Type: text/plain; charset=ISO-8859-1
I believe the issue is that you are entering a string that contains thresh1,
since its a string, it's not looking for a variable.
Try changing 'i2.*(i1>thresh1)' to ['i2.*(i1>' thresh1 ')']
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Sun, May 15, 2011 at 6:45 PM, G Elliott Wimmer <[log in to unmask]>wrote:
> Hi,
>
> I'm having a simple problem with spm_imcalc / spm_imcalc_ui. I need to
> read in a variable to be used in the imcalc equation.
>
> The basic idea is to do this:
>
> spm_imcalc_ui({'input1.img','input2.img'},'output.img','i2.*(i1>thresh1)')
>
> in a batch script, where 'thresh1' is a value previously calculated for
> each subject. The function works if I use a simple number, e.g. '1', in
> place of the variable.
>
> However, adapting the command to read in the extra variable, for example:
>
>
> spm_imcalc({'input1.img','input2.img'},'output.img','i2.*(i1>thresh1)',{[],[],[],[]},thresh1);
>
> has not worked. I think I must be missing something about the syntax.
> (Judging by the lack of questions posted to the board on imcalc and
> variables, it's something obvious, or it's a function that SPM people never
> use.)
>
> Thank you for any help!
>
> Best regards,
>
> Elliott
>
>
> Dept. of Psychology
> Columbia University
> New York, NY
>
--0023545309c8e42b7804a359f3e4
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
I believe the issue is that you are entering a string that contains thresh1=
, since its a string, it's not looking for a variable.<div><br></div><d=
iv>Try changing=A0<meta charset=3D"utf-8"><span class=3D"Apple-style-span" =
style=3D"border-collapse: collapse; font-family: arial, sans-serif; font-si=
ze: 13px; ">'i2.*(i1>thresh1)' to [</span><meta charset=3D"utf-8=
"><span class=3D"Apple-style-span" style=3D"border-collapse: collapse; font=
-family: arial, sans-serif; font-size: 13px; ">'i2.*(i1>' thresh=
1 ')']</span><br clear=3D"all">
<br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdoctoral Research Fellow, GRECC,=
Bedford VA<br>Research Fellow, Department of Neurology, Massachusetts Gene=
ral Hospital and Harvard Medical School<br>
Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which may =
contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED=
and which is intended only for the use of the individual or entity named a=
bove. If the reader of the e-mail is not the intended recipient or the empl=
oyee or agent responsible for delivering it to the intended recipient, you =
are hereby notified that you are in possession of confidential and privileg=
ed information. Any unauthorized use, disclosure, copying or the taking of =
any action in reliance on the contents of this information is strictly proh=
ibited and may be unlawful. If you have received this e-mail unintentionall=
y, please immediately notify the sender via telephone at (773) 406-2464 or =
email.<br>
<br><br><div class=3D"gmail_quote">On Sun, May 15, 2011 at 6:45 PM, G Ellio=
tt Wimmer <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">gew=
[log in to unmask]</a>></span> wrote:<br><blockquote class=3D"gmail_quote=
" style=3D"margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
Hi,<br>
<br>
I'm having a simple problem with spm_imcalc / spm_imcalc_ui. =A0I need =
to read in a variable to be used in the imcalc equation.<br>
<br>
The basic idea is to do this:<br>
<br>
spm_imcalc_ui({'input1.img','input2.img'},'output.img&#=
39;,'i2.*(i1>thresh1)')<br>
<br>
in a batch script, where 'thresh1' is a value previously calculated=
for each subject. =A0The function works if I use a simple number, e.g. =
9;1', in place of the variable.<br>
<br>
However, adapting the command to read in the extra variable, for example:<b=
r>
<br>
spm_imcalc({'input1.img','input2.img'},'output.img'=
,'i2.*(i1>thresh1)',{[],[],[],[]},thresh1);<br>
<br>
has not worked. =A0I think I must be missing something about the syntax. =
=A0(Judging by the lack of questions posted to the board on imcalc and vari=
ables, it's something obvious, or it's a function that SPM people n=
ever use.)<br>
<br>
Thank you for any help!<br>
<br>
Best regards,<br>
<br>
Elliott<br>
<br>
<br>
Dept. of Psychology<br>
Columbia University<br>
New York, NY<br>
</blockquote></div><br></div>
--0023545309c8e42b7804a359f3e4--
=========================================================================
Date: Sun, 15 May 2011 20:52:22 -0400
Reply-To: "G. Elliott Wimmer" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "G. Elliott Wimmer" <[log in to unmask]>
Subject: Re: variable use in spm_imcalc
Comments: To: "Watson, Christopher" <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf30549ff1a58ab804a35a1210
Message-ID: <[log in to unmask]>
--20cf30549ff1a58ab804a35a1210
Content-Type: text/plain; charset=ISO-8859-1
Dear Christopher,
Of course - thank you!
For the record, both of these work to enter variables into spm_imcalc:
spm_imcalc_ui({'input1.img','input2.img'},'output.img',['i2.*(i1>'
sprintf('%d',val1) ')']);
spm_imcalc_ui({'input1.img','input2.img'},'output.img',['i2.*(i1>'
num2str(thresh1) ')']);
(It was a silly issue of brackets; I'd tried num2str before, but failed.)
Best regards,
Elliott
On Sun, May 15, 2011 at 8:17 PM, Watson, Christopher <
[log in to unmask]> wrote:
> It'll probably work if you use sprintf
> ________________________________________
> From: SPM (Statistical Parametric Mapping) [[log in to unmask]] On Behalf
> Of G Elliott Wimmer [[log in to unmask]]
> Sent: Sunday, May 15, 2011 6:45 PM
> To: [log in to unmask]
> Subject: [SPM] variable use in spm_imcalc
>
> Hi,
>
> I'm having a simple problem with spm_imcalc / spm_imcalc_ui. I need to
> read in a variable to be used in the imcalc equation.
>
> The basic idea is to do this:
>
> spm_imcalc_ui({'input1.img','input2.img'},'output.img','i2.*(i1>thresh1)')
>
> in a batch script, where 'thresh1' is a value previously calculated for
> each subject. The function works if I use a simple number, e.g. '1', in
> place of the variable.
>
> However, adapting the command to read in the extra variable, for example:
>
>
> spm_imcalc({'input1.img','input2.img'},'output.img','i2.*(i1>thresh1)',{[],[],[],[]},thresh1);
>
> has not worked. I think I must be missing something about the syntax.
> (Judging by the lack of questions posted to the board on imcalc and
> variables, it's something obvious, or it's a function that SPM people never
> use.)
>
> Thank you for any help!
>
> Best regards,
>
> Elliott
>
>
> Dept. of Psychology
> Columbia University
> New York, NY
>
>
--20cf30549ff1a58ab804a35a1210
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Content-Transfer-Encoding: quoted-printable
Dear Christopher,<div><br></div><div>Of course - thank you!</div><div><br><=
/div><div>For the record, both of these work to enter variables into spm_im=
calc:</div><div><br></div><div><br></div><div>spm_imcalc_ui({'input1.im=
g','input2.img'},'output.img',['i2.*(i1>' sp=
rintf('%d',val1) ')']);</div>
<div><br></div><div><div>spm_imcalc_ui({'input1.img','input2.im=
g'},'output.img',['i2.*(i1>' num2str(thresh1) ')=
']);</div><div><br></div><div><br></div><div>(It was a silly issue of b=
rackets; I'd tried num2str before, but failed.)</div>
<div><br></div><div><br></div><div><div>Best regards,</div><div><br></div><=
div>Elliott</div></div><div><br></div><br><div class=3D"gmail_quote">On Sun=
, May 15, 2011 at 8:17 PM, Watson, Christopher <span dir=3D"ltr"><<a hre=
f=3D"mailto:[log in to unmask]">Christopher.Watson@ch=
ildrens.harvard.edu</a>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex;">It'll probably work if you use sprintf<=
br>
________________________________________<br>
From: SPM (Statistical Parametric Mapping) [<a href=3D"mailto:[log in to unmask]
AC.UK">[log in to unmask]</a>] On Behalf Of G Elliott Wimmer [<a href=3D"ma=
ilto:[log in to unmask]">[log in to unmask]</a>]<br>
Sent: Sunday, May 15, 2011 6:45 PM<br>
To: <a href=3D"mailto:[log in to unmask]">[log in to unmask]</a><br>
Subject: [SPM] variable use in spm_imcalc<br>
<div><div></div><div class=3D"h5"><br>
Hi,<br>
<br>
I'm having a simple problem with spm_imcalc / spm_imcalc_ui. =A0I need =
to read in a variable to be used in the imcalc equation.<br>
<br>
The basic idea is to do this:<br>
<br>
spm_imcalc_ui({'input1.img','input2.img'},'output.img&#=
39;,'i2.*(i1>thresh1)')<br>
<br>
in a batch script, where 'thresh1' is a value previously calculated=
for each subject. =A0The function works if I use a simple number, e.g. =
9;1', in place of the variable.<br>
<br>
However, adapting the command to read in the extra variable, for example:<b=
r>
<br>
spm_imcalc({'input1.img','input2.img'},'output.img'=
,'i2.*(i1>thresh1)',{[],[],[],[]},thresh1);<br>
<br>
has not worked. =A0I think I must be missing something about the syntax. =
=A0(Judging by the lack of questions posted to the board on imcalc and vari=
ables, it's something obvious, or it's a function that SPM people n=
ever use.)<br>
<br>
Thank you for any help!<br>
<br>
Best regards,<br>
<br>
Elliott<br>
<br>
<br>
Dept. of Psychology<br>
Columbia University<br>
New York, NY<br>
<br>
</div></div></blockquote></div><br></div>
--20cf30549ff1a58ab804a35a1210--
=========================================================================
Date: Sun, 15 May 2011 22:42:48 -0400
Reply-To: Jadzia Jagiellowicz <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jadzia Jagiellowicz <[log in to unmask]>
Subject: Re: SPM Digest - 6 May 2011 (#2011-133)
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=005045015ed170643e04a35b9c79
Message-ID: <[log in to unmask]>
--005045015ed170643e04a35b9c79
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Thank you John and Don for all the help with the fMRI processing errors.
I've finally figured out the problem. It was actually a problem with the
files themselves.
Best
jadzia
On 6 May 2011 19:00, SPM automatic digest system <[log in to unmask]>w=
rote:
> There are 3 messages totaling 1723 lines in this issue.
>
> Topics of the day:
>
> 1. spm_affreg
> 2. PPI question
> 3. using mri3dx
>
> ----------------------------------------------------------------------
>
> Date: Fri, 6 May 2011 13:48:29 -0700
> From: Siddharth Srivastava <[log in to unmask]>
> Subject: Re: spm_affreg
>
> Hi John, please ignore the first part of my previous mail: made some erro=
rs
> in
> cut and paste. It runs fine now. The question about the shears, however,
> still lingers: do I have
> to somehow use both Sx and Sy, or as your implementation suggests, only o=
ne
> would suffice?
>
> thanks again, and sorry for being such a bother...
> sid.
>
> On Fri, May 6, 2011 at 12:23 PM, Siddharth Srivastava <[log in to unmask]
> >wrote:
>
> > Thanks John, for the answers. The code, however exits with "Problem". M=
0
> > and M1 differ.
> > Also, why is there just one shear component in the matrix? I have seen
> > general shears modeled as [1,h;g,1]: is this superfluous, and just one
> "h"
> > will be sufficient for 2d case?
> >
> > Thanks,
> > Sid.
> >
> >
> >
> >
> > On Fri, May 6, 2011 at 11:01 AM, John Ashburner <[log in to unmask]
> >wrote:
> >
> >> Your model uses 7 parameters, but there are only 6 elements in
> >> A(1:2,1:3). Also, you need to be able to deal with a broader range of
> >> angles, so atan2(s,c) is used to compute the angle. I've tested it
> >> with the following code, so hopefully it works for all cases.
> >>
> >> for i=3D1:10000
> >> P=3Drandn(1,6)*10;
> >> M0=3Dspm_matrix2D(P);
> >> P1=3Dspm_imatrix2D(M0);
> >> M1=3Dspm_matrix2D(P1);
> >> t=3Dsum(sum((M1-M0).^2));
> >> if t>1e-9, disp('Problem'); break; end
> >> end
> >>
> >> Note that spm_imatrix2D(spm_matrix2D(P)) does not necessarily have to
> >> equal P, but the matrices generated from the two parameter sets should
> >> be the same.
> >>
> >> Best regards,
> >> -John
> >>
> >> On 6 May 2011 17:11, Siddharth Srivastava <[log in to unmask]> wrote:
> >> > Hi everyone,
> >> > Can someone help me check the 2D versions of the spm_matrix an=
d
> >> > spm_imatrix? My
> >> > implementation currently is as follows:
> >> >
> >> > ---2D spm_matrix ---
> >> > function [A] =3D spm_matrix2D(P)
> >> > % P =3D [Tx, Ty, R, Zx, Zy, Sx,Sy]
> >> > p0 =3D [0,0,0,1,1,0,0];
> >> > P =3D [P, p0((length(P)+1):7)]
> >> >
> >> > A =3D eye(3);
> >> > % T -> R -> Zoom -> Shear
> >> > A =3D A * [1,0,P(1); ...
> >> > 0,1,P(2); ...
> >> > 0,0, 1];
> >> > A =3D A * [cos(P(3)), sin(P(3)), 0; ...
> >> > -sin(P(3)), cos(P(3)), 0; ...
> >> > 0, 0, 1];
> >> > A =3D A * [P(4), 0, 0; ...
> >> > 0, P(5), 0; ...
> >> > 0, 0, 1];
> >> > A =3D A * [1, P(6), 0; ...
> >> > P(7) , 1, 0; ...
> >> > 0, 0, 1];
> >> > --------------------------------------------------
> >> > -----2D spm_imatrix ------------------------
> >> > function P =3D spm_imatrix2D(M);
> >> >
> >> >
> >> >
> >> > R =3D M(1:2,1:2);
> >> > C =3D chol(R' * R);
> >> > P =3D [M(1:2,3)',0,diag(C)',0,0];
> >> > if(det(R) < 0) P(4) =3D -P(4); end
> >> > C =3D diag(diag(C))\C;
> >> > P(6:7) =3D C([2,3]);
> >> >
> >> > R0 =3D spm_matrix2D([0,0,0,P(4:end)]);
> >> > R0 =3D R0(1:2,1:2);
> >> > R1 =3D R/R0;
> >> >
> >> > th =3D asin(rang(R1(1,2)));
> >> > P(3) =3D th;
> >> >
> >> > % There may be slight rounding errors making b>1 or b<-1.
> >> > function a =3D rang(b)
> >> > a =3D min(max(b, -1), 1);
> >> > return;
> >> >
> >>
> -------------------------------------------------------------------------=
--
> >> >
> >> > I know there is something not correct, since when, for a parameter s=
et
> >> 'p',
> >> > i do spm_imatrix2D(spm_matrix2D(p)), I do not recover P for all
> entries,
> >> > specially
> >> > rotation and shears. C(2) above always evaluates to zero. The result
> is
> >> that
> >> > these errors
> >> > accumulate (or are not accounted for) on repeated application of thi=
s
> >> > sequence of
> >> > operations in the registration routine.
> >> >
> >> > Thanks in anticipation,
> >> > Sid.
> >> >
> >> >
> >> >
> >> > On Fri, Apr 22, 2011 at 9:13 AM, Siddharth Srivastava <
> [log in to unmask]
> >> >
> >> > wrote:
> >> >>
> >> >> Hi John,
> >> >> Thanks a lot for your answer, and it has been very helpful fo=
r
> my
> >> >> understanding
> >> >> of the details of the implementation, and my own development effort=
s.
> I
> >> >> have
> >> >> 2 very quick questions, though:
> >> >>
> >> >> 1) the parameter set x(:) that is returned from spm_mireg, and the
> >> >> "params" that
> >> >> spm_affsub3 returns (in spm99, which is also the version that I am
> >> looking
> >> >> at) ,
> >> >> are they equivalent? In other words, If I am collating the paramete=
rs
> >> from
> >> >> the mireg
> >> >> routine, would the distribution x(7:12) be used to estimate the
> icovar0
> >> >> entries in affsub3?
> >> >>
> >> >> 2) also would VG.mat\spm_matrix(x)*VF.mat transform G to F similar =
to
> >> >> VG.mat\spm_matrix(params)*VF.mat , or do I have to do
> >> >> M =3D VG.mat\spm_matrix(x(:)')*VF.mat
> >> >> pp =3D spm_imatrix(M)
> >> >> and use pp(7:12) ?
> >> >>
> >> >>
> >> >>
> >> >> Thanks again.
> >> >> Sid.
> >> >>
> >> >> On Thu, Apr 14, 2011 at 2:13 PM, John Ashburner <
> [log in to unmask]>
> >> >> wrote:
> >> >>>
> >> >>> > I had a look at the code in spm_maff, and
> >> >>> > it looks like it also uses the values of isig and mu in the call
> to
> >> >>> > affreg(). My guess is
> >> >>> > that during the initial registration on a large data set for
> >> estimating
> >> >>> > the
> >> >>> > prior
> >> >>> > distribution of parameters, this will be called with typ =3D 'no=
ne'
> .
> >> Is
> >> >>> > this
> >> >>> > correct?
> >> >>>
> >> >>> Once the registration has locked in on a solution, the priors have
> >> >>> less influence. Their main influence is in the early stages of th=
e
> >> >>> registration, or when there are relatively few slices in the data.
> I
> >> >>> don't actually remember if the registration was regularised when I
> >> >>> computed their values.
> >> >>>
> >> >>> >
> >> >>> > Further, do we have to do a non-rigid registration for the
> >> estimation
> >> >>> > (since, in the comments the selected
> >> >>> > files are filtered as *seg_inv_sn.mat"? Since only p.Affine is
> being
> >> >>> > used,
> >> >>> > can this work with only
> >> >>> > an affine / rigid transformation?
> >> >>>
> >> >>> Only the affine transform in the files is used, so basically yes.
> You
> >> >>> could just do affine registration.
> >> >>>
> >> >>> >
> >> >>> > I would also be happy if you could also answer my other question
> >> about
> >> >>> > examining the
> >> >>> > effects of the values in isig and mu (what are the units of mu?)
> on
> >> the
> >> >>> > transformed image.
> >> >>>
> >> >>> They are unit-less, and are just a measure of the zooms and shears=
.
> >> >>>
> >> >>> > For example,
> >> >>> > if i set a mu of [mu1, mu2, ...] and a isig of [sig1, 0, 0...; 0=
,
> >> sig2,
> >> >>> > 0,
> >> >>> > 0..; ...] (with only diagonal components),
> >> >>> > based on the Hencky tensor penalty, it seems that large deviatio=
ns
> >> of
> >> >>> > parameter 1 estimate (T - mu) from
> >> >>> > mu1 will be penalized. How is the value of isig1 modifying the
> >> penalty?
> >> >>>
> >> >>> Its assuming that the elements of the matrix log of the part that
> does
> >> >>> shears and zooms has a multivariate normal distribution, so the
> >> >>> penalty is a kind of negative log likelhood. The isig is
> essentially
> >> >>> a precision matrix, which is the inverse of a covariance matrix.
> >> >>>
> >> >>> p(x|mu,S) =3D 1/sqrt(det(2*pi*S)) * exp(-0.5*(x-mu)'*inv(S)*(x-mu)=
)
> >> >>>
> >> >>> Taking logs and negating, you get 0.5*(x-mu)'*inv(S)*(x-mu) + cons=
t
> >> >>>
> >> >>> > How
> >> >>> > do the off diagonal terms affect
> >> >>> > the penalty?
> >> >>>
> >> >>> The inverse of isig would just encode the covariance between the
> >> >>> various shears and zooms.
> >> >>>
> >> >>> >
> >> >>> > Could you also point me to a reference where I can learn more
> about
> >> >>> > Hencky
> >> >>> > strain tensor (specifically
> >> >>> > what information it carries in the context of image processing
> etc.)
> >> >>>
> >> >>> I don't know if this is of any use:
> >> >>>
> >> >>> http://en.wikipedia.org/wiki/Deformation_(mechanics)
> >> >>>
> >> >>> Best regards,
> >> >>> -John
> >> >>>
> >> >>>
> >> >>> > On Thu, Apr 14, 2011 at 10:17 AM, John Ashburner <
> >> [log in to unmask]>
> >> >>> > wrote:
> >> >>> >>
> >> >>> >> They were computed by affine registering loads of (227) images =
to
> >> MNI
> >> >>> >> space. This gave the affine transforms, which were then used t=
o
> >> build
> >> >>> >> up a mean and inverse covariance matrix. In the comments of
> >> >>> >> spm_maff.m, you should see the following...
> >> >>> >>
> >> >>> >> %% Values can be derived by...
> >> >>> >> %sn =3D spm_select(Inf,'.*seg_inv_sn.mat$');
> >> >>> >> %X =3D zeros(size(sn,1),12);
> >> >>> >> %for i=3D1:size(sn,1),
> >> >>> >> % p =3D load(deblank(sn(i,:)));
> >> >>> >> % M =3D p.VF(1).mat*p.Affine/p.VG(1).mat;
> >> >>> >> % J =3D M(1:3,1:3);
> >> >>> >> % V =3D sqrtm(J*J');
> >> >>> >> % R =3D V\J;
> >> >>> >> % lV =3D logm(V);
> >> >>> >> % lR =3D -logm(R);
> >> >>> >> % P =3D zeros(12,1);
> >> >>> >> % P(1:3) =3D M(1:3,4);
> >> >>> >> % P(4:6) =3D lR([2 3 6]);
> >> >>> >> % P(7:12) =3D lV([1 2 3 5 6 9]);
> >> >>> >> % X(i,:) =3D P';
> >> >>> >> %end;
> >> >>> >> %mu =3D mean(X(:,7:12));
> >> >>> >> %XR =3D X(:,7:12) - repmat(mu,[size(X,1),1]);
> >> >>> >> %isig =3D inv(XR'*XR/(size(X,1)-1))
> >> >>> >>
> >> >>> >> You may be able to re-code this to work with your 2D transforms=
.
> >> Note
> >> >>> >> that I only use the components that describe shears and zooms.
> >> Also,
> >> >>> >> if I was re-coding it all again, I would probably do things
> >> slightly
> >> >>> >> differently, using the following decomposition:
> >> >>> >>
> >> >>> >> J=3DM(1:3,1:3);
> >> >>> >> L=3Dreal(logm(J));
> >> >>> >> S=3D(L+L')/2; % Symmetric part (for zooms and shears, which sho=
uld
> be
> >> >>> >> penalised)
> >> >>> >> A=3D(L-L')/2; % Anti-symmetric part (for rotations)
> >> >>> >>
> >> >>> >> I might even base the penalty on lambda(2)*trace(S)^2 +
> >> >>> >> lambda(1)*trace(S*S'), which is often used as a measure of
> "elastic
> >> >>> >> energy" for penalising non-linear registration. Of course, the=
re
> >> >>> >> would also be a bit of annoying extra stuff to deal with due to
> MNI
> >> >>> >> space being a bit bigger than average brains are. Figuring out
> the
> >> >>> >> mean would require (I think) an iterative process similar to th=
e
> >> one
> >> >>> >> described in "Characterizing volume and surface deformations in
> an
> >> >>> >> atlas framework: theory, applications, and implementation", by
> >> Woods
> >> >>> >> in NeuroImage (2003).
> >> >>> >>
> >> >>> >> Best regards,
> >> >>> >> -John
> >> >>> >>
> >> >>> >> On 14 April 2011 17:15, Siddharth Srivastava <[log in to unmask]>
> >> wrote:
> >> >>> >> > Hi all,
> >> >>> >> > My question pertains specifically to the values of isig
> and
> >> mu
> >> >>> >> > that
> >> >>> >> > are
> >> >>> >> > incorporated
> >> >>> >> > in the code, and I wish to disentangle the effect that these
> >> numbers
> >> >>> >> > have on
> >> >>> >> > individual parameters
> >> >>> >> > during the optimization stage. I am trying to map it to a 2D
> >> case,
> >> >>> >> > and
> >> >>> >> > these
> >> >>> >> > numbers
> >> >>> >> > will have to be calculated ab-initio for my case. Before I
> begin
> >> >>> >> > with
> >> >>> >> > estimating the prior distribution
> >> >>> >> > for these parameters, I need to check the effect that they ha=
ve
> >> on
> >> >>> >> > the
> >> >>> >> > registered images. Regarding this
> >> >>> >> > 1) Can someone suggest a way I can examine the effect on each
> >> >>> >> > parameter
> >> >>> >> > separately, if it is
> >> >>> >> > at all possible.
> >> >>> >> > 2) Some advise on how to estimate these parameters, if it has
> >> been
> >> >>> >> > done
> >> >>> >> > for
> >> >>> >> > images other
> >> >>> >> > than brain images, will be really helpful for me.
> >> >>> >> >
> >> >>> >> > Thanks,
> >> >>> >> > Sid.
> >> >>> >> >
> >> >>> >> > On Mon, Mar 28, 2011 at 7:04 PM, Siddharth Srivastava
> >> >>> >> > <[log in to unmask]>
> >> >>> >> > wrote:
> >> >>> >> >>
> >> >>> >> >> Dear John,
> >> >>> >> >> Thanks for your answer. I was able to correctly ru=
n
> my
> >> 2D
> >> >>> >> >> implementation
> >> >>> >> >> based on your advise. However, I am am not very confident of
> my
> >> >>> >> >> results
> >> >>> >> >> and wanted to
> >> >>> >> >> consult you on certain aspects of my mapping from 3D to 2D.
> >> >>> >> >> 1) In function reg(..), the comment says that the
> >> >>> >> >> derivatives
> >> >>> >> >> w.r.t rotations and
> >> >>> >> >> translations is zero. Consequently, I ran the indices from
> 4:7.
> >> >>> >> >> According
> >> >>> >> >> to your previous
> >> >>> >> >> reply, rotations will be lumped together with scaling and
> affine
> >> in
> >> >>> >> >> 4
> >> >>> >> >> parameters, and
> >> >>> >> >> translations, independently, in the last two. I understand
> that
> >> in
> >> >>> >> >> this
> >> >>> >> >> case, the indices
> >> >>> >> >> run over parameters that have been separated into individual
> >> >>> >> >> components
> >> >>> >> >> (similar to
> >> >>> >> >> the form accepted by spm_matrix). Is this correct for the
> >> function
> >> >>> >> >> reg(..)? In fact, I went back to the
> >> >>> >> >> old spm code (spm99), and found parameters pdesc and free, a=
nd
> >> got
> >> >>> >> >> more
> >> >>> >> >> confused as to when I should
> >> >>> >> >> use the 6 parameter, and when to use separate parameters (as
> if
> >> I
> >> >>> >> >> was
> >> >>> >> >> passing them to spm_matrix).
> >> >>> >> >> So, when the loop runs over p1 and perturbs p1(i) by ds, doe=
s
> it
> >> >>> >> >> run
> >> >>> >> >> over
> >> >>> >> >> translations/rotations etc
> >> >>> >> >> or does it run over the martix elements that define these
> >> >>> >> >> transformations
> >> >>> >> >> (2x2 + 1x2)?
> >> >>> >> >>
> >> >>> >> >> 2) In function penalty(..), I have used unique
> >> elements
> >> >>> >> >> as
> >> >>> >> >> [1,3,4], and my code looks like
> >> >>> >> >> T =3D my_matrix(p)*M;
> >> >>> >> >> T =3D T(1:2,1:2);
> >> >>> >> >> T =3D 0.5*logm(T'*T);
> >> >>> >> >> T
> >> >>> >> >> T =3D T(els)' - mu;
> >> >>> >> >> h =3D T'*isig*T
> >> >>> >> >>
> >> >>> >> >> Assuming an application specific isig, is this correct?
> >> >>> >> >> 3) I have not yet incorporated the prior informatio=
n
> in
> >> my
> >> >>> >> >> code,
> >> >>> >> >> But for testing purposes,
> >> >>> >> >> can you suggest some neutral values for mu and isig that I
> can
> >> try
> >> >>> >> >> to
> >> >>> >> >> concentrate on the
> >> >>> >> >> accuracy of the implementation minus the priors for now?
> >> >>> >> >> 4) My solution curently seems to oscillate around =
an
> >> >>> >> >> optimum.
> >> >>> >> >> I
> >> >>> >> >> am hoping that after
> >> >>> >> >> I have removed any errors after your replies, it will conver=
ge
> >> >>> >> >> gracefully.
> >> >>> >> >>
> >> >>> >> >> Thanks again for all the help.
> >> >>> >> >> Siddharth.
> >> >>> >> >>
> >> >>> >> >>
> >> >>> >> >> On Fri, Mar 18, 2011 at 2:05 AM, John Ashburner
> >> >>> >> >> <[log in to unmask]>
> >> >>> >> >> wrote:
> >> >>> >> >>>
> >> >>> >> >>> A 2D affine transform would use 6 parameters, rather than 7=
:
> a
> >> 2x2
> >> >>> >> >>> matrix to encode rotations, zooms and shears, and a 2x1
> vector
> >> for
> >> >>> >> >>> translations.
> >> >>> >> >>>
> >> >>> >> >>> Best regards,
> >> >>> >> >>> -John
> >> >>> >> >>>
> >> >>> >> >>> On 18 March 2011 05:05, Siddharth Srivastava <
> [log in to unmask]
> >> >
> >> >>> >> >>> wrote:
> >> >>> >> >>> > Dear list users,
> >> >>> >> >>> > I am currently trying to understand the
> >> implementation
> >> >>> >> >>> > in
> >> >>> >> >>> > spm_affreg, and
> >> >>> >> >>> > to make matters simple, I tried to work out a 2D version =
of
> >> the
> >> >>> >> >>> > registration
> >> >>> >> >>> > procedure. I struck a roadblock, however...
> >> >>> >> >>> >
> >> >>> >> >>> > The function make_A creates part of the design matrix. Fo=
r
> >> the
> >> >>> >> >>> > 3D
> >> >>> >> >>> > case,
> >> >>> >> >>> > the
> >> >>> >> >>> > 13 parameters
> >> >>> >> >>> > are encoded in columns of A1, which then is used to
> generate
> >> AA
> >> >>> >> >>> > +
> >> >>> >> >>> > A1'
> >> >>> >> >>> > A1. AA
> >> >>> >> >>> > is 13x13, and everything
> >> >>> >> >>> > works. For the 2D case, however, there will be 7+1
> >> parameters( 2
> >> >>> >> >>> > translations, 1 rotation, 2 zoom, 2 shears and 1 intensit=
y
> >> >>> >> >>> > scaling).
> >> >>> >> >>> > The A1 matrix for 2D, then, will be (in make_A)
> >> >>> >> >>> > A =3D [x1.*dG1 x1.*dG2 ...
> >> >>> >> >>> > x2.*dG1 x2.*dG2 ...
> >> >>> >> >>> > dG1 dG2 t];
> >> >>> >> >>> >
> >> >>> >> >>> > which is (number of sampled points) x 7. The AA matrix (i=
n
> >> >>> >> >>> > function
> >> >>> >> >>> > costfun)
> >> >>> >> >>> > is 8x8
> >> >>> >> >>> > so, which is the parameter I am missing in modeling a 2D
> >> >>> >> >>> > example? I
> >> >>> >> >>> > hope I
> >> >>> >> >>> > have got the number of parameters
> >> >>> >> >>> > right for the 2D case? Is there an extra column that I ha=
ve
> >> to
> >> >>> >> >>> > add
> >> >>> >> >>> > to
> >> >>> >> >>> > A1 to
> >> >>> >> >>> > make the rest of the matrix computation
> >> >>> >> >>> > consistent?
> >> >>> >> >>> >
> >> >>> >> >>> > Thanks for the help
> >> >>> >> >>> >
> >> >>> >> >>
> >> >>> >> >
> >> >>> >> >
> >> >>> >
> >> >>> >
> >> >>
> >> >
> >> >
> >>
> >
> >
>
> ------------------------------
>
> Date: Sat, 7 May 2011 07:14:27 +1000
> From: Alex Fornito <[log in to unmask]>
> Subject: Re: PPI question
>
> Actually, sorry one more question:
>
> If Y in spm_peb_ppi is already frequency filtered by spm_regions, then th=
e
> only difference (barring any additional confounds specified with xX.iG)
> between Y and Yc is the additional removal of block effects.
>
> Since the ppi interaction term is generated from Y and not Yc, I am
> presuming then that is solely because it is not desirable to deconvolve a
> time course with block effects removed. Is this correct?
>
>
> On 07/05/2011 04:07, "MCLAREN, Donald" <[log in to unmask]> wrote:
>
> > The null-space of the contrast are any columns of the contrast (which
> > must be an F-contrast) that are 0. Thus, you remove the effects of
> > motion when you do the adjustment and don't need to worry about them
> > being included in the deconvolved data. The code that I have supplied
> > has N rows for N conditions of interest after I talked to Darren about
> > the ideal contrast to use for adjustment.
> >
> > As for removing the frequencies, I think it is probably fine to remove
> > them, I was just under the impression that they weren't being removed
> > because of me commenting out that line during testing of spm_regions.
> > I would go with the SPM defaults until their effect is tested. If you
> > don't set a high-pass filter, then you won't remove the frequencies,
> > so you could test it that way as well.
> >
> > Best Regards, Donald McLaren
> > =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> > D.G. McLaren, Ph.D.
> > Postdoctoral Research Fellow, GRECC, Bedford VA
> > Research Fellow, Department of Neurology, Massachusetts General
> > Hospital and Harvard Medical School
> > Office: (773) 406-2464
> > =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> > This e-mail contains CONFIDENTIAL INFORMATION which may contain
> > PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
> > and which is intended only for the use of the individual or entity
> > named above. If the reader of the e-mail is not the intended recipient
> > or the employee or agent responsible for delivering it to the intended
> > recipient, you are hereby notified that you are in possession of
> > confidential and privileged information. Any unauthorized use,
> > disclosure, copying or the taking of any action in reliance on the
> > contents of this information is strictly prohibited and may be
> > unlawful. If you have received this e-mail unintentionally, please
> > immediately notify the sender via telephone at (773) 406-2464 or
> > email.
> >
> >
> >
> > On Thu, May 5, 2011 at 9:46 PM, Alex Fornito <[log in to unmask]>
> wrote:
> >> Hi Donald, Torben and Darren,
> >> Thanks for your responses.
> >>
> >> Form each of your responses, it seems like best practice would be to
> remove
> >> motion (and/or other confounds) from the VOI time series prior to
> >> deconvolution.
> >>
> >> It also seems like you are recommending NOT to frequency filter the VO=
I
> time
> >> series.
> >>
> >> In my reading though, spm_regions does this by default with the call t=
o
> >> spm_filter (line 135). So, if spm_regions is used to extract a VOI tim=
e
> >> series, the time series that is input to spm_peb_ppi will already
> frequency
> >> filtered. So it seems like, in standard practice, the deconvolution is
> >> applied to frequency-filtered data. In this case, if xX.iG is empty, t=
he
> >> only difference between Y and Yc in spm_peb_ppi is the additional
> removal of
> >> block effects (xX.iB).
> >>
> >> Based on the current chain of emails, it seems you are recommending th=
at
> a
> >> confound-corrected, whitened, but non-frequency filtered time course
> should
> >> be input to spm_peb_ppi. IS that correct, or am I missing something?
> >>
> >> Finally, can I clarify exactly what the null space of the contrast is?
> Most
> >> of the time in my analyses I don't get the option to adjust for it, so
> xY.Ic
> >> is empty.
> >>
> >> Thanks again for all your help,
> >> A
> >>
> >>
> >>
> >> On 06/05/2011 02:18, "MCLAREN, Donald" <[log in to unmask]>
> wrote:
> >>
> >>> I haven't thoroughly tested this, but if you set iG to be the movemen=
t
> >>> parameters columns. Then still adjust for the null space (motion
> >>> parameters). You will get the best of both. If you don't adjust for
> >>> the null space, then movement will contribute to the deconvolution. I=
n
> >>> summary, if you have iG be the motion parameter columns AND adjust fo=
r
> >>> the null-space (motion columns), then:
> >>>
> >>> Y will have the effect of motion removed. Yc (removal of motion twice=
)
> >>> will be minimally different since Y is orthogonal to the motion
> >>> parameters. So, you have motion removed from both the autocorrelation
> >>> estimate, the Y for deconvolution, and Yc.
> >>>
> >>> Best Regards, Donald McLaren
> >>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> >>> D.G. McLaren, Ph.D.
> >>> Postdoctoral Research Fellow, GRECC, Bedford VA
> >>> Research Fellow, Department of Neurology, Massachusetts General
> >>> Hospital and Harvard Medical School
> >>> Office: (773) 406-2464
> >>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> >>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
> >>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED
> >>> and which is intended only for the use of the individual or entity
> >>> named above. If the reader of the e-mail is not the intended recipien=
t
> >>> or the employee or agent responsible for delivering it to the intende=
d
> >>> recipient, you are hereby notified that you are in possession of
> >>> confidential and privileged information. Any unauthorized use,
> >>> disclosure, copying or the taking of any action in reliance on the
> >>> contents of this information is strictly prohibited and may be
> >>> unlawful. If you have received this e-mail unintentionally, please
> >>> immediately notify the sender via telephone at (773) 406-2464 or
> >>> email.
> >>>
> >>>
> >>>
> >>> On Thu, May 5, 2011 at 9:48 AM, Torben Ellegaard Lund
> >>> <[log in to unmask]> wrote:
> >>>> Hi Alex
> >>>>
> >>>>
> >>>> Den Uge:18 05/05/2011 kl. 14.15 skrev Alex Fornito:
> >>>>
> >>>>> Hi Torben,
> >>>>> Sorry, I just wanted to clarify: do you mean leaving SPM.xX.iG empt=
y?
> It
> >>>>> seems like this is done by default by spm_fmri_design (?)
> >>>>
> >>>> leaving it empty will include all user defined regressors in the
> effects of
> >>>> interest F-test which determines the mask where the serial correlati=
on
> is
> >>>> estimated. I think it would make sense if the motion regressors did
> not go
> >>>> into this test, just like the DCS HP-filter does not go into the
> >>>> F-contrast.
> >>>>
> >>>>> Are you suggesting manually entering motion parameters into this
> field?
> >>>>
> >>>> Yes, or their indices that is. It should be done after specification=
,
> but
> >>>> before model estimation. You can check if SPM recognized your change=
s
> by
> >>>> looking at the automatically generated effects of interest F-contras=
t.
> >>>>
> >>>>
> >>>> Best
> >>>> Torben
> >>>>
> >>>>
> >>>>
> >>>>
> >>>>>
> >>>>> On 05/05/2011 18:16, "Torben Ellegaard Lund" <[log in to unmask]>
> wrote:
> >>>>>
> >>>>>> Just as a kind reminder. Leaving SPM.xX.iG is a bit unfortunate,
> because
> >>>>>> voxels where motion artefacts are significant then constitutes a
> large
> >>>>>> part
> >>>>>> of
> >>>>>> the F-test derived mask used to estimate serial correlations. If y=
ou
> are
> >>>>>> picky
> >>>>>> about this you can change it yourselves, but it is not as easy as =
it
> >>>>>> should
> >>>>>> be.
> >>>>>>
> >>>>>>
> >>>>>> Best
> >>>>>> Torben
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>> Den Uge:18 05/05/2011 kl. 05.03 skrev Alex Fornito:
> >>>>>>
> >>>>>>> Ahh, I see. I was assuming that SPM.xX.iG contained the indices t=
o
> the
> >>>>>>> nuisance covariates in the design matrix, but you're right -
> >>>>>>> spm_fMRI_design
> >>>>>>> leaves it empty.
> >>>>>>>
> >>>>>>> Thanks for your help!
> >>>>>>> A
> >>>>>>>
> >>>>>>>
> >>>>>>> On 05/05/2011 12:54, "MCLAREN, Donald" <[log in to unmask]>
> wrote:
> >>>>>>>
> >>>>>>>> I agree that nuisance covariates, such as motion should be
> removed;
> >>>>>>>> however, motion covariates are not generally stored in X0 in my
> >>>>>>>> reading of the SPM code (spm_fMRI_design, spm_regions). They
> should be
> >>>>>>>> removed in the spm_regions filtering based on the null-space of
> the
> >>>>>>>> contrast.
> >>>>>>>>
> >>>>>>>> As for the motion parameters being in the model, if they were in
> the
> >>>>>>>> standard analysis, they should be included in the PPI analysis. =
My
> >>>>>>>> gPPI code will do this automatically as well.
> >>>>>>>>
> >>>>>>>> X0 is made of SPM.xX.iB (block effects -- so removing the mean)
> and
> >>>>>>>> SPM.xX.iG (nuisance variable that is empty as far as I can tell
> (line
> >>>>>>>> 369 of spm_fMRI_design)) and the high-pass filtering (K.X0).
> >>>>>>>>
> >>>>>>>> Best Regards, Donald McLaren
> >>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> >>>>>>>> D.G. McLaren, Ph.D.
> >>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
> >>>>>>>> Research Fellow, Department of Neurology, Massachusetts General
> >>>>>>>> Hospital and Harvard Medical School
> >>>>>>>> Office: (773) 406-2464
> >>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> >>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contain
> >>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY
> PRIVILEGED
> >>>>>>>> and which is intended only for the use of the individual or enti=
ty
> >>>>>>>> named above. If the reader of the e-mail is not the intended
> recipient
> >>>>>>>> or the employee or agent responsible for delivering it to the
> intended
> >>>>>>>> recipient, you are hereby notified that you are in possession of
> >>>>>>>> confidential and privileged information. Any unauthorized use,
> >>>>>>>> disclosure, copying or the taking of any action in reliance on t=
he
> >>>>>>>> contents of this information is strictly prohibited and may be
> >>>>>>>> unlawful. If you have received this e-mail unintentionally, plea=
se
> >>>>>>>> immediately notify the sender via telephone at (773) 406-2464 or
> >>>>>>>> email.
> >>>>>>>>
> >>>>>>>>
> >>>>>>>>
> >>>>>>>> On Wed, May 4, 2011 at 10:16 PM, Alex Fornito <
> [log in to unmask]>
> >>>>>>>> wrote:
> >>>>>>>>> Hi Donald,
> >>>>>>>>> Thanks for your response. When you say "you don't want
> >>>>>>>>> to filter out anything related to neural activity", I'm presumi=
ng
> that
> >>>>>>>>> you
> >>>>>>>>> are referring to the deconvolved neural signal?
> >>>>>>>>>
> >>>>>>>>> If so, that makes sense. However, X0 also contains user-specifi=
ed
> >>>>>>>>> nuisance
> >>>>>>>>> covariates. I would have thought it would make sense to remove
> those,
> >>>>>>>>> depending on what they were (e.g., movement parameters)? I gues=
s
> they
> >>>>>>>>> can
> >>>>>>>>> always be entered into the PPI regression model...
> >>>>>>>>>
> >>>>>>>>>
> >>>>>>>>> On 05/05/2011 11:57, "MCLAREN, Donald" <[log in to unmask]
m
> >
> >>>>>>>>> wrote:
> >>>>>>>>>
> >>>>>>>>>> I could be wrong, Karl or Darren please correct me if I am.
> >>>>>>>>>>
> >>>>>>>>>> X0 is composed of the high-pass filter and constant term. Thus=
,
> you
> >>>>>>>>>> want to filter these out of the Yc regressor. However, you don=
't
> want
> >>>>>>>>>> to filter out anything related to neural activity, so you
> wouldn't
> >>>>>>>>>> want to filter your signal and then predict the neural activit=
y
> from
> >>>>>>>>>> the filtered signal, especially filtering frequencies.
> >>>>>>>>>>
> >>>>>>>>>> Best Regards, Donald McLaren
> >>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> >>>>>>>>>> D.G. McLaren, Ph.D.
> >>>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
> >>>>>>>>>> Research Fellow, Department of Neurology, Massachusetts Genera=
l
> >>>>>>>>>> Hospital and Harvard Medical School
> >>>>>>>>>> Office: (773) 406-2464
> >>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D
> >>>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may contai=
n
> >>>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY
> PRIVILEGED
> >>>>>>>>>> and which is intended only for the use of the individual or
> entity
> >>>>>>>>>> named above. If the reader of the e-mail is not the intended
> >>>>>>>>>> recipient
> >>>>>>>>>> or the employee or agent responsible for delivering it to the
> >>>>>>>>>> intended
> >>>>>>>>>> recipient, you are hereby notified that you are in possession =
of
> >>>>>>>>>> confidential and privileged information. Any unauthorized use,
> >>>>>>>>>> disclosure, copying or the taking of any action in reliance on
> the
> >>>>>>>>>> contents of this information is strictly prohibited and may be
> >>>>>>>>>> unlawful. If you have received this e-mail unintentionally,
> please
> >>>>>>>>>> immediately notify the sender via telephone at (773) 406-2464 =
or
> >>>>>>>>>> email.
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>> On Sat, Apr 30, 2011 at 8:03 PM, Alex Fornito
> >>>>>>>>>> <[log in to unmask]>
> >>>>>>>>>> wrote:
> >>>>>>>>>>> Hi Donald,
> >>>>>>>>>>> As far as I can tell, spm_regions filters and whitens the VOI
> time
> >>>>>>>>>>> series,
> >>>>>>>>>>> and adjusts for the null space of the contrast if an adjustme=
nt
> is
> >>>>>>>>>>> specified
> >>>>>>>>>>> in xY.Ic. It defines the confound matrix, X0, but does not
> correct
> >>>>>>>>>>> for
> >>>>>>>>>>> it.
> >>>>>>>>>>> The following line in spm_peb_ppi corrects for the confounds.
> >>>>>>>>>>>
> >>>>>>>>>>> Yc =3D Y - X0*inv(X0'*X0)*X0'*Y;
> >>>>>>>>>>> PPI.Y =3D Yc(:,1);
> >>>>>>>>>>>
> >>>>>>>>>>> So the above correction does seem to be doing something
> different to
> >>>>>>>>>>> spm_regions. I'm wondering why the uncorrected data, Y, is us=
ed
> when
> >>>>>>>>>>> generating the ppi interaction term, while the corrected data
> Yc is
> >>>>>>>>>>> to
> >>>>>>>>>>> be
> >>>>>>>>>>> used as a covariate of no interest in the PPI model. I would
> has
> >>>>>>>>>>> thought
> >>>>>>>>>>> that Yc should be used to generate the ppi interaction term a=
s
> well.
> >>>>>>>>>>>
> >>>>>>>>>>> In my data, my X0 is a 195 x 7 matrix (I have 195 volumes per
> >>>>>>>>>>> session).
> >>>>>>>>>>>
> >>>>>>>>>>> Regards,
> >>>>>>>>>>> Alex
> >>>>>>>>>>>
> >>>>>>>>>>>
> >>>>>>>>>>> On 30/04/2011 02:22, "MCLAREN, Donald" <
> [log in to unmask]>
> >>>>>>>>>>> wrote:
> >>>>>>>>>>>
> >>>>>>>>>>>> I'm actually travelling at the moment. However, I know Y has
> >>>>>>>>>>>> already
> >>>>>>>>>>>> been adjusted as part of the VOI processing.
> >>>>>>>>>>>>
> >>>>>>>>>>>> Can you check what X0 looks like?
> >>>>>>>>>>>>
> >>>>>>>>>>>> Best Regards, Donald McLaren
> >>>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> >>>>>>>>>>>> D.G. McLaren, Ph.D.
> >>>>>>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford VA
> >>>>>>>>>>>> Research Fellow, Department of Neurology, Massachusetts
> General
> >>>>>>>>>>>> Hospital and Harvard Medical School
> >>>>>>>>>>>> Office: (773) 406-2464
> >>>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D
> >>>>>>>>>>>> This e-mail contains CONFIDENTIAL INFORMATION which may
> contain
> >>>>>>>>>>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY
> PRIVILEGED
> >>>>>>>>>>>> and which is intended only for the use of the individual or
> entity
> >>>>>>>>>>>> named above. If the reader of the e-mail is not the intended
> >>>>>>>>>>>> recipient
> >>>>>>>>>>>> or the employee or agent responsible for delivering it to th=
e
> >>>>>>>>>>>> intended
> >>>>>>>>>>>> recipient, you are hereby notified that you are in possessio=
n
> of
> >>>>>>>>>>>> confidential and privileged information. Any unauthorized us=
e,
> >>>>>>>>>>>> disclosure, copying or the taking of any action in reliance =
on
> the
> >>>>>>>>>>>> contents of this information is strictly prohibited and may =
be
> >>>>>>>>>>>> unlawful. If you have received this e-mail unintentionally,
> please
> >>>>>>>>>>>> immediately notify the sender via telephone at (773) 406-246=
4
> or
> >>>>>>>>>>>> email.
> >>>>>>>>>>>>
> >>>>>>>>>>>>
> >>>>>>>>>>>>
> >>>>>>>>>>>> On Fri, Apr 29, 2011 at 2:55 AM, Alex Fornito
> >>>>>>>>>>>> <[log in to unmask]>
> >>>>>>>>>>>> wrote:
> >>>>>>>>>>>> Hi all,
> >>>>>>>>>>>> I have a question concerning the code used to implement a PP=
I
> >>>>>>>>>>>> analysis.
> >>>>>>>>>>>>
> >>>>>>>>>>>> In the spm_peb_ppi.m function packaged with SPM8, lines
> 329-332
> >>>>>>>>>>>> remove
> >>>>>>>>>>>> confounds from the input seed region=B9s time course:
> >>>>>>>>>>>>
> >>>>>>>>>>>> % Remove confounds and save Y in ouput structure
> >>>>>>>>>>>>
>
> %------------------------------------------------------------------>>>>>>=
>>>>>>
> -
> >>>>>>>>>>>> ---
> >>>>>>>>>>>> --
> >>>>>>>>>>>> --
> >>>>>>>>>>>> Yc =3D Y - X0*inv(X0'*X0)*X0'*Y;
> >>>>>>>>>>>> PPI.Y =3D Yc(:,1);
> >>>>>>>>>>>>
> >>>>>>>>>>>> PPI.Y is then to be used as a covariate of no interest when
> >>>>>>>>>>>> building
> >>>>>>>>>>>> the
> >>>>>>>>>>>> PPI
> >>>>>>>>>>>> regression model. However, on line 488, it is the uncorrecte=
d
> seed
> >>>>>>>>>>>> time
> >>>>>>>>>>>> course, Y, that is input to the deconvolution routine and us=
ed
> to
> >>>>>>>>>>>> generate
> >>>>>>>>>>>> the ppi term:
> >>>>>>>>>>>>
> >>>>>>>>>>>> C =3D spm_PEB(Y,P);
> >>>>>>>>>>>> xn =3D xb*C{2}.E(1:N);
> >>>>>>>>>>>> xn =3D spm_detrend(xn);
> >>>>>>>>>>>>
> >>>>>>>>>>>> % Setup psychological variable from inputs and contast
> weights
> >>>>>>>>>>>>
> >>>>>>>>>>>>
>
> %------------------------------------------------------------------>>>>>>=
>>>>>>
> -
> >>>>>>>>>>>> ---
> >>>>>>>>>>>> PSY =3D zeros(N*NT,1);
> >>>>>>>>>>>> for i =3D 1:size(U.u,2)
> >>>>>>>>>>>> PSY =3D PSY + full(U.u(:,i)*U.w(:,i));
> >>>>>>>>>>>> end
> >>>>>>>>>>>> % PSY =3D spm_detrend(PSY); <- removed centering of psych
> variable
> >>>>>>>>>>>> % prior to multiplication with xn. Based on discussion with
> Karl
> >>>>>>>>>>>> % and Donald McLaren.
> >>>>>>>>>>>>
> >>>>>>>>>>>> % Multiply psychological variable by neural signal
> >>>>>>>>>>>>
> >>>>>>>>>>>>
> >>>>>>>>>>>>
>
> %------------------------------------------------------------------>>>>>>=
>>>>>>
> -
> >>>>>>>>>>>> ---
> >>>>>>>>>>>> PSYxn =3D PSY.*xn;
> >>>>>>>>>>>>
> >>>>>>>>>>>> Is there any specific reason why Y, rather than Yc(:,1), is
> used to
> >>>>>>>>>>>> compute
> >>>>>>>>>>>> PSYxn? I thought Yc might be more appropriate (?).
> >>>>>>>>>>>> Thanks for your help,
> >>>>>>>>>>>> Alex
> >>>>>>>>>>>>
> >>>>>>>>>>>>
> >>>>>>>>>>>>
> >>>>>>>>>>>>
> >>>>>>>>>>>> ------------------------------------------
> >>>>>>>>>>>>
> >>>>>>>>>>>> Alex Fornito
> >>>>>>>>>>>> Research Fellow
> >>>>>>>>>>>> Melbourne Neuropsychiatry Centre
> >>>>>>>>>>>> University of Melbourne
> >>>>>>>>>>>> National Neuroscience Facility
> >>>>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
> >>>>>>>>>>>> 161 Barry St
> >>>>>>>>>>>> Carlton South 3053
> >>>>>>>>>>>> Victoria, Australia
> >>>>>>>>>>>>
> >>>>>>>>>>>> Email: [log in to unmask]
> >>>>>>>>>>>> Phone: +61 3 8344 1876
> >>>>>>>>>>>> Fax: +61 3 9348 0469
> >>>>>>>>>>>>
> >>>>>>>>>>>>
> >>>>>>>>>>>>
> >>>>>>>>>>>
> >>>>>>>>>>>
> >>>>>>>>>>> ------------------------------------------
> >>>>>>>>>>>
> >>>>>>>>>>> Alex Fornito
> >>>>>>>>>>> Research Fellow
> >>>>>>>>>>> Melbourne Neuropsychiatry Centre
> >>>>>>>>>>> University of Melbourne
> >>>>>>>>>>> National Neuroscience Facility
> >>>>>>>>>>> Levels 1 & 2, Alan Gilbert Building
> >>>>>>>>>>> 161 Barry St
> >>>>>>>>>>> Carlton South 3053
> >>>>>>>>>>> Victoria, Australia
> >>>>>>>>>>>
> >>>>>>>>>>> Email: [log in to unmask]
> >>>>>>>>>>> Phone: +61 3 8344 1876
> >>>>>>>>>>> Fax: +61 3 9348 0469
> >>>>>>>>>>>
> >>>>>>>>>>>
> >>>>>>>>>>>
> >>>>>>>>>>>
> >>>>>>>>>>
> >>>>>>>>>
> >>>>>>>>>
> >>>>>>>>> ------------------------------------------
> >>>>>>>>>
> >>>>>>>>> Alex Fornito
> >>>>>>>>> Research Fellow
> >>>>>>>>> Melbourne Neuropsychiatry Centre
> >>>>>>>>> University of Melbourne
> >>>>>>>>> National Neuroscience Facility
> >>>>>>>>> Levels 1 & 2, Alan Gilbert Building
> >>>>>>>>> 161 Barry St
> >>>>>>>>> Carlton South 3053
> >>>>>>>>> Victoria, Australia
> >>>>>>>>>
> >>>>>>>>> Email: [log in to unmask]
> >>>>>>>>> Phone: +61 3 8344 1876
> >>>>>>>>> Fax: +61 3 9348 0469
> >>>>>>>>>
> >>>>>>>>>
> >>>>>>>>>
> >>>>>>>>>
> >>>>>>>>
> >>>>>>>
> >>>>>>>
> >>>>>>> ------------------------------------------
> >>>>>>>
> >>>>>>> Alex Fornito
> >>>>>>> Research Fellow
> >>>>>>> Melbourne Neuropsychiatry Centre
> >>>>>>> University of Melbourne
> >>>>>>> National Neuroscience Facility
> >>>>>>> Levels 1 & 2, Alan Gilbert Building
> >>>>>>> 161 Barry St
> >>>>>>> Carlton South 3053
> >>>>>>> Victoria, Australia
> >>>>>>>
> >>>>>>> Email: [log in to unmask]
> >>>>>>> Phone: +61 3 8344 1876
> >>>>>>> Fax: +61 3 9348 0469
> >>>>>>
> >>>>>>
> >>>>>
> >>>>>
> >>>>> ------------------------------------------
> >>>>>
> >>>>> Alex Fornito
> >>>>> Research Fellow
> >>>>> Melbourne Neuropsychiatry Centre
> >>>>> University of Melbourne
> >>>>> National Neuroscience Facility
> >>>>> Levels 1 & 2, Alan Gilbert Building
> >>>>> 161 Barry St
> >>>>> Carlton South 3053
> >>>>> Victoria, Australia
> >>>>>
> >>>>> Email: [log in to unmask]
> >>>>> Phone: +61 3 8344 1876
> >>>>> Fax: +61 3 9348 0469
> >>>>>
> >>>>>
> >>>>>
> >>>>
> >>>
> >>
> >>
> >> ------------------------------------------
> >>
> >> Alex Fornito
> >> Research Fellow
> >> Melbourne Neuropsychiatry Centre
> >> University of Melbourne
> >> National Neuroscience Facility
> >> Levels 1 & 2, Alan Gilbert Building
> >> 161 Barry St
> >> Carlton South 3053
> >> Victoria, Australia
> >>
> >> Email: [log in to unmask]
> >> Phone: +61 3 8344 1876
> >> Fax: +61 3 9348 0469
> >>
> >>
> >>
> >>
> >
>
>
> ------------------------------------------
>
> Alex Fornito
> Research Fellow
> Melbourne Neuropsychiatry Centre
> University of Melbourne
> National Neuroscience Facility
> Levels 1 & 2, Alan Gilbert Building
> 161 Barry St
> Carlton South 3053
> Victoria, Australia
>
> Email: [log in to unmask]
> Phone: +61 3 8344 1876
> Fax: +61 3 9348 0469
>
> ------------------------------
>
> Date: Fri, 6 May 2011 16:17:37 -0500
> From: John Fredy <[log in to unmask]>
> Subject: using mri3dx
>
> hello all,
>
> I am trying to show some activations in the spm5 template in mri3dx
> (template spm5 command) but the activations appear more higher than the
> template. Is necessary any conversion to show the activations?
>
> I think that maybe the mri3dX uses tailarach space, I can convert my
> normalized activations to tailarach space?
>
> Thanks in advance
>
> ------------------------------
>
> End of SPM Digest - 6 May 2011 (#2011-133)
> ******************************************
>
--=20
Jadzia Jagiellowicz
Doctoral Candidate
Psychology Department B-207
Stony Brook University,
Stony Brook, NY 11794-2500 USA
http://www.psychology.stonybrook.edu/aronlab-/
"The brave shall inherit the earth."
--005045015ed170643e04a35b9c79
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
<div>Thank you John and Don for all the help with the fMRI processing error=
s. I've finally figured out the problem. It was actually a problem with=
the files themselves. </div>
<div>Best</div>
<div>jadzia<br><br></div>
<div class=3D"gmail_quote">On 6 May 2011 19:00, SPM automatic digest system=
<span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">LISTSERV@=
jiscmail.ac.uk</a>></span> wrote:<br>
<blockquote style=3D"BORDER-LEFT: #ccc 1px solid; MARGIN: 0px 0px 0px 0.8ex=
; PADDING-LEFT: 1ex" class=3D"gmail_quote">There are 3 messages totaling 17=
23 lines in this issue.<br><br>Topics of the day:<br><br>=A01. spm_affreg<b=
r>
=A02. PPI question<br>=A03. using mri3dx<br><br>---------------------------=
-------------------------------------------<br><br>Date: =A0 =A0Fri, 6 May =
2011 13:48:29 -0700<br>From: =A0 =A0Siddharth Srivastava <<a href=3D"mai=
lto:[log in to unmask]">[log in to unmask]</a>><br>
Subject: Re: spm_affreg<br><br>Hi John, please ignore the first part of my =
previous mail: made some errors<br>in<br>cut and paste. It runs fine now. T=
he question about the shears, however,<br>still lingers: do I have<br>to so=
mehow use both Sx and Sy, or as your implementation suggests, only one<br>
would suffice?<br><br>thanks again, and sorry for being such a bother...<br=
>sid.<br><br>On Fri, May 6, 2011 at 12:23 PM, Siddharth Srivastava <<a h=
ref=3D"mailto:[log in to unmask]">[log in to unmask]</a>>wrote:<br><br>> =
Thanks John, for the answers. The code, however exits with "Problem&qu=
ot;. M0<br>
> and M1 differ.<br>> Also, why is there just one shear component in =
the matrix? I have seen<br>> general shears modeled as [1,h;g,1]: is thi=
s superfluous, and just one "h"<br>> will be sufficient for 2d=
case?<br>
><br>> Thanks,<br>> Sid.<br>><br>><br>><br>><br>> O=
n Fri, May 6, 2011 at 11:01 AM, John Ashburner <<a href=3D"mailto:jashbu=
[log in to unmask]">[log in to unmask]</a>>wrote:<br>><br>>> Your=
model uses 7 parameters, but there are only 6 elements in<br>
>> A(1:2,1:3). =A0Also, you need to be able to deal with a broader ra=
nge of<br>>> angles, so atan2(s,c) is used to compute the angle. =A0I=
've tested it<br>>> with the following code, so hopefully it work=
s for all cases.<br>
>><br>>> for i=3D1:10000<br>>> =A0P=3Drandn(1,6)*10;<br>&=
gt;> =A0M0=3Dspm_matrix2D(P);<br>>> =A0P1=3Dspm_imatrix2D(M0);<br>=
>> =A0M1=3Dspm_matrix2D(P1);<br>>> =A0t=3Dsum(sum((M1-M0).^2));=
<br>>> =A0if t>1e-9, disp('Problem'); break; end<br>
>> end<br>>><br>>> Note that spm_imatrix2D(spm_matrix2D(P=
)) does not necessarily have to<br>>> equal P, but the matrices gener=
ated from the two parameter sets should<br>>> be the same.<br>>>=
;<br>
>> Best regards,<br>>> -John<br>>><br>>> On 6 May 2=
011 17:11, Siddharth Srivastava <<a href=3D"mailto:[log in to unmask]">sid=
[log in to unmask]</a>> wrote:<br>>> > Hi everyone,<br>>> >=
=A0 =A0 =A0 Can someone help me check the 2D versions of the spm_matrix an=
d<br>
>> > spm_imatrix? My<br>>> > implementation currently is =
as follows:<br>>> ><br>>> > ---2D spm_matrix ---<br>>&=
gt; > function [A] =3D spm_matrix2D(P)<br>>> > % P =3D [Tx, Ty,=
R, Zx, Zy, Sx,Sy]<br>
>> > p0 =3D [0,0,0,1,1,0,0];<br>>> > P =3D [P, p0((length=
(P)+1):7)]<br>>> ><br>>> > A =3D eye(3);<br>>> >=
% T -> R -> Zoom -> Shear<br>>> > =A0A =3D =A0 =A0 A * [=
1,0,P(1); ...<br>
>> > =A0 =A0 =A0 =A0 =A0 0,1,P(2); ...<br>>> > =A0 =A0 =
=A0 =A0 0,0, =A0 1];<br>>> > =A0A =3D =A0 =A0 A * [cos(P(3)), sin(=
P(3)), 0; ...<br>>> > =A0 =A0 =A0 =A0 =A0 -sin(P(3)), =A0cos(P(3))=
, 0; ...<br>>> > =A0 =A0 =A0 0, =A0 =A0 =A0 =A0 =A00, =A0 =A0 =A0 =
=A0 1];<br>
>> > =A0A =3D =A0 =A0 A * [P(4), 0, 0; ...<br>>> > =A0 =
=A0 =A0 =A0 =A0 =A0 =A0 0, =A0 P(5), 0; ...<br>>> > =A0 =A0 =A0 =
=A0 =A0 0, 0, 1];<br>>> > =A0A =3D =A0 =A0 A * [1, P(6), 0; ...<br=
>>> > =A0 =A0 =A0 =A0 =A0 =A0 =A0 P(7) =A0, 1, 0; ...<br>
>> > =A0 =A0 =A0 =A0 =A0 0, 0, 1];<br>>> > --------------=
------------------------------------<br>>> > -----2D spm_imatrix -=
-----------------------<br>>> > function P =3D =A0spm_imatrix2D(M)=
;<br>>> ><br>
>> ><br>>> ><br>>> > R =3D M(1:2,1:2);<br>>&g=
t; > C =3D chol(R' * R);<br>>> > P =3D [M(1:2,3)',0,dia=
g(C)',0,0];<br>>> > if(det(R) < 0) P(4) =3D -P(4); end<br>&=
gt;> > C =3D diag(diag(C))\C;<br>
>> > P(6:7) =3D C([2,3]);<br>>> ><br>>> > R0 =3D=
spm_matrix2D([0,0,0,P(4:end)]);<br>>> > R0 =3D R0(1:2,1:2);<br>&g=
t;> > R1 =3D R/R0;<br>>> ><br>>> > th =3D asin(rang=
(R1(1,2)));<br>
>> > P(3) =3D th;<br>>> ><br>>> > % There may be=
slight rounding errors making b>1 or b<-1.<br>>> > function=
=A0a =3D rang(b)<br>>> > a =3D min(max(b, -1), 1);<br>>> &g=
t; return;<br>
>> ><br>>> -------------------------------------------------=
--------------------------<br>>> ><br>>> > I know there i=
s something not correct, since when, for a parameter set<br>>> 'p=
',<br>
>> > i do spm_imatrix2D(spm_matrix2D(p)), I do not recover P for a=
ll entries,<br>>> > specially<br>>> > rotation and shears=
. C(2) above always evaluates to zero. The result is<br>>> that<br>
>> > these errors<br>>> > accumulate (or are not accounte=
d for) on repeated application of this<br>>> > sequence of<br>>=
> > operations in the registration routine.<br>>> ><br>>&=
gt; > Thanks in anticipation,<br>
>> > Sid.<br>>> ><br>>> ><br>>> ><br>&g=
t;> > On Fri, Apr 22, 2011 at 9:13 AM, Siddharth Srivastava <<a hr=
ef=3D"mailto:[log in to unmask]">[log in to unmask]</a><br>>> ><br>>=
;> > wrote:<br>
>> >><br>>> >> Hi John,<br>>> >> =A0 =
=A0 =A0 Thanks a lot for your answer, and it has been very helpful for my<b=
r>>> >> understanding<br>>> >> of the details of th=
e implementation, and my own development efforts. I<br>
>> >> have<br>>> >> 2 very quick questions, though:=
<br>>> >><br>>> >> 1) the parameter set x(:) that i=
s returned from spm_mireg, and the<br>>> >> "params" =
that<br>
>> >> spm_affsub3 returns (in spm99, which is also the version =
that I am<br>>> looking<br>>> >> at) ,<br>>> >&g=
t; are they equivalent? In other words, If I am collating the parameters<br=
>
>> from<br>>> >> the mireg<br>>> >> routine, =
would the distribution x(7:12) be used to estimate the icovar0<br>>> =
>> entries in affsub3?<br>>> >><br>>> >> 2) a=
lso would VG.mat\spm_matrix(x)*VF.mat transform G to F similar to<br>
>> >> =A0 =A0 =A0VG.mat\spm_matrix(params)*VF.mat , or do I hav=
e to do<br>>> >> =A0 =A0 =A0 M =3D VG.mat\spm_matrix(x(:)')=
*VF.mat<br>>> >> =A0 =A0 =A0 pp =3D spm_imatrix(M)<br>>> =
>> =A0 =A0 =A0 and use pp(7:12) ?<br>
>> >><br>>> >><br>>> >><br>>> >=
;> Thanks again.<br>>> >> Sid.<br>>> >><br>>&=
gt; >> On Thu, Apr 14, 2011 at 2:13 PM, John Ashburner <<a href=3D=
"mailto:[log in to unmask]">[log in to unmask]</a>><br>
>> >> wrote:<br>>> >>><br>>> >>> =
> I had a look at the code in spm_maff, and<br>>> >>> >=
; it looks like it also uses the values of isig and mu in the call to<br>
>> >>> > affreg(). My guess is<br>>> >>> &=
gt; that during the initial registration on a large data set for<br>>>=
; estimating<br>>> >>> > the<br>>> >>> >=
; prior<br>
>> >>> > distribution of parameters, this will be called =
with typ =3D 'none' .<br>>> Is<br>>> >>> > =
this<br>>> >>> > correct?<br>>> >>><br>>=
;> >>> Once the registration has locked in on a solution, the p=
riors have<br>
>> >>> less influence. =A0Their main influence is in the ear=
ly stages of the<br>>> >>> registration, or when there are r=
elatively few slices in the data. =A0I<br>>> >>> don't a=
ctually remember if the registration was regularised when I<br>
>> >>> computed their values.<br>>> >>><br>&g=
t;> >>> ><br>>> >>> > Further, do we have =
to do a non-rigid registration for the<br>>> estimation<br>>> &=
gt;>> > (since, in the comments the selected<br>
>> >>> > files are filtered as *seg_inv_sn.mat"? Sin=
ce only p.Affine is being<br>>> >>> > used,<br>>> &=
gt;>> > can this work with only<br>>> >>> > an a=
ffine / rigid transformation?<br>
>> >>><br>>> >>> Only the affine transform in=
the files is used, so basically yes. =A0You<br>>> >>> could=
just do affine registration.<br>>> >>><br>>> >>=
> ><br>
>> >>> > I would also be happy if you could also answer m=
y other question<br>>> about<br>>> >>> > examining =
the<br>>> >>> > effects of the values in isig and mu (wha=
t are the units of mu?) on<br>
>> the<br>>> >>> > transformed image.<br>>> &=
gt;>><br>>> >>> They are unit-less, and are just a mea=
sure of the zooms and shears.<br>>> >>><br>>> >>=
> > For example,<br>
>> >>> > if i set a mu of [mu1, mu2, ...] and a isig of [=
sig1, 0, 0...; 0,<br>>> sig2,<br>>> >>> > 0,<br>>=
;> >>> > 0..; ...] (with only diagonal components),<br>>&=
gt; >>> > based on the Hencky tensor penalty, it seems that lar=
ge deviations<br>
>> of<br>>> >>> > parameter 1 =A0estimate (T - mu) =
from<br>>> >>> > mu1 will be penalized. How is the value =
of isig1 modifying the<br>>> penalty?<br>>> >>><br>>=
;> >>> Its assuming that the elements of the matrix log of the =
part that does<br>
>> >>> shears and zooms has a multivariate normal distributi=
on, so the<br>>> >>> penalty is a kind of negative log likel=
hood. =A0The isig is essentially<br>>> >>> a precision matri=
x, which is the inverse of a covariance matrix.<br>
>> >>><br>>> >>> p(x|mu,S) =3D 1/sqrt(det(2*p=
i*S)) * exp(-0.5*(x-mu)'*inv(S)*(x-mu))<br>>> >>><br>>=
;> >>> Taking logs and negating, you get 0.5*(x-mu)'*inv(S)=
*(x-mu) + const<br>
>> >>><br>>> >>> > How<br>>> >>=
;> > do the off diagonal terms affect<br>>> >>> > t=
he penalty?<br>>> >>><br>>> >>> The inverse o=
f isig would just encode the covariance between the<br>
>> >>> various shears and zooms.<br>>> >>><br=
>>> >>> ><br>>> >>> > Could you also po=
int me to a reference where I can learn more about<br>>> >>>=
> Hencky<br>
>> >>> > strain tensor (specifically<br>>> >>=
> > what information it carries in the context of image processing et=
c.)<br>>> >>><br>>> >>> I don't know if t=
his is of any use:<br>
>> >>><br>>> >>> <a href=3D"http://en.wikiped=
ia.org/wiki/Deformation_(mechanics)" target=3D"_blank">http://en.wikipedia.=
org/wiki/Deformation_(mechanics)</a><br>>> >>><br>>> &=
gt;>> Best regards,<br>
>> >>> -John<br>>> >>><br>>> >>&g=
t;<br>>> >>> > On Thu, Apr 14, 2011 at 10:17 AM, John Ash=
burner <<br>>> <a href=3D"mailto:[log in to unmask]">jashburner@=
gmail.com</a>><br>
>> >>> > wrote:<br>>> >>> >><br>>=
> >>> >> They were computed by affine registering loads o=
f (227) images to<br>>> MNI<br>>> >>> >> space. =
=A0This gave the affine transforms, which were then used to<br>
>> build<br>>> >>> >> up a mean and inverse cova=
riance matrix. =A0In the comments of<br>>> >>> >> spm_=
maff.m, you should see the following...<br>>> >>> >><b=
r>
>> >>> >> %% Values can be derived by...<br>>> &=
gt;>> >> %sn =3D spm_select(Inf,'.*seg_inv_sn.mat$');<b=
r>>> >>> >> %X =A0=3D zeros(size(sn,1),12);<br>>>=
; >>> >> %for i=3D1:size(sn,1),<br>
>> >>> >> % =A0 =A0p =A0=3D load(deblank(sn(i,:)));<br=
>>> >>> >> % =A0 =A0M =A0=3D p.VF(1).mat*p.Affine/p.VG=
(1).mat;<br>>> >>> >> % =A0 =A0J =A0=3D M(1:3,1:3);<br=
>>> >>> >> % =A0 =A0V =A0=3D sqrtm(J*J');<br>
>> >>> >> % =A0 =A0R =A0=3D V\J;<br>>> >>&=
gt; >> % =A0 =A0lV =A0 =A0 =A0=3D =A0logm(V);<br>>> >>>=
; >> % =A0 =A0lR =A0 =A0 =A0=3D -logm(R);<br>>> >>> &g=
t;> % =A0 =A0P =A0 =A0 =A0 =3D zeros(12,1);<br>
>> >>> >> % =A0 =A0P(1:3) =A0=3D M(1:3,4);<br>>>=
>>> >> % =A0 =A0P(4:6) =A0=3D lR([2 3 6]);<br>>> >=
>> >> % =A0 =A0P(7:12) =3D lV([1 2 3 5 6 9]);<br>>> >&=
gt;> >> % =A0 =A0X(i,:) =A0=3D P';<br>
>> >>> >> %end;<br>>> >>> >> %mu =
=A0 =3D mean(X(:,7:12));<br>>> >>> >> %XR =A0 =3D X(:,=
7:12) - repmat(mu,[size(X,1),1]);<br>>> >>> >> %isig =
=3D inv(XR'*XR/(size(X,1)-1))<br>
>> >>> >><br>>> >>> >> You may be=
able to re-code this to work with your 2D transforms.<br>>> =A0Note<=
br>>> >>> >> that I only use the components that descr=
ibe shears and zooms.<br>
>> =A0Also,<br>>> >>> >> if I was re-coding it a=
ll again, I would probably do things<br>>> slightly<br>>> >&=
gt;> >> differently, using the following decomposition:<br>>>=
; >>> >><br>
>> >>> >> J=3DM(1:3,1:3);<br>>> >>> >=
;> L=3Dreal(logm(J));<br>>> >>> >> S=3D(L+L')/2=
; % Symmetric part (for zooms and shears, which should be<br>>> >&=
gt;> >> penalised)<br>
>> >>> >> A=3D(L-L')/2; % Anti-symmetric part (for=
rotations)<br>>> >>> >><br>>> >>> >=
> I might even base the penalty on lambda(2)*trace(S)^2 +<br>>> &g=
t;>> >> lambda(1)*trace(S*S'), which is often used as a mea=
sure of "elastic<br>
>> >>> >> energy" for penalising non-linear regis=
tration. =A0Of course, there<br>>> >>> >> would also b=
e a bit of annoying extra stuff to deal with due to MNI<br>>> >>=
;> >> space being a bit bigger than average brains are. =A0Figurin=
g out the<br>
>> >>> >> mean would require (I think) an iterative pr=
ocess similar to the<br>>> one<br>>> >>> >> desc=
ribed in "Characterizing volume and surface deformations in an<br>
>> >>> >> atlas framework: theory, applications, and i=
mplementation", by<br>>> Woods<br>>> >>> >>=
in NeuroImage (2003).<br>>> >>> >><br>>> >&g=
t;> >> Best regards,<br>
>> >>> >> -John<br>>> >>> >><br>&=
gt;> >>> >> On 14 April 2011 17:15, Siddharth Srivastava =
<<a href=3D"mailto:[log in to unmask]">[log in to unmask]</a>><br>>>=
; wrote:<br>
>> >>> >> > Hi all,<br>>> >>> >&g=
t; > =A0 =A0 =A0My question pertains specifically to the values of isig =
and<br>>> mu<br>>> >>> >> > that<br>>> =
>>> >> > are<br>
>> >>> >> > incorporated<br>>> >>> &=
gt;> > in the code, and I wish to disentangle the effect that these<b=
r>>> numbers<br>>> >>> >> > have on<br>>&g=
t; >>> >> > individual parameters<br>
>> >>> >> > during the optimization stage. I am try=
ing to map it to a 2D<br>>> case,<br>>> >>> >> &=
gt; and<br>>> >>> >> > these<br>>> >>&g=
t; >> > numbers<br>
>> >>> >> > will have to be calculated ab-initio fo=
r my case. Before I begin<br>>> >>> >> > with<br>&g=
t;> >>> >> > estimating the prior distribution<br>
>> >>> >> > for these parameters, I need to check t=
he effect that they have<br>>> on<br>>> >>> >> &=
gt; the<br>>> >>> >> > registered images. Regarding=
this<br>
>> >>> >> > 1) Can someone suggest a way I can exam=
ine the effect on each<br>>> >>> >> > parameter<br>=
>> >>> >> > separately, if it is<br>>> >&g=
t;> >> > =A0 =A0 =A0at all possible.<br>
>> >>> >> > 2) Some advise on how to estimate these=
parameters, if it has<br>>> been<br>>> >>> >> &=
gt; done<br>>> >>> >> > for<br>>> >>>=
; >> > images other<br>
>> >>> >> > =A0 =A0 =A0than brain images, will be r=
eally helpful for me.<br>>> >>> >> ><br>>> &g=
t;>> >> > Thanks,<br>>> >>> >> > Sid=
.<br>
>> >>> >> ><br>>> >>> >> > =
On Mon, Mar 28, 2011 at 7:04 PM, Siddharth Srivastava<br>>> >>&=
gt; >> > <<a href=3D"mailto:[log in to unmask]">[log in to unmask]<=
/a>><br>
>> >>> >> > wrote:<br>>> >>> >>=
; >><br>>> >>> >> >> Dear John,<br>>>=
; >>> >> >> =A0 =A0 =A0 =A0 =A0 Thanks for your answer=
. I was able to correctly run my<br>
>> 2D<br>>> >>> >> >> implementation<br>&g=
t;> >>> >> >> based on your advise. However, I am a=
m not very confident of my<br>>> >>> >> >> resul=
ts<br>
>> >>> >> >> and wanted to<br>>> >>&=
gt; >> >> consult you on certain aspects of my mapping from 3D =
to 2D.<br>>> >>> >> >> =A0 =A0 =A0 =A0 =A0 =A01)=
In function reg(..), the comment says that the<br>
>> >>> >> >> derivatives<br>>> >>>=
; >> >> w.r.t rotations and<br>>> >>> >> &=
gt;> translations is zero. Consequently, I ran the indices from 4:7.<br>
>> >>> >> >> According<br>>> >>> =
>> >> to your previous<br>>> >>> >> >&g=
t; reply, rotations will be lumped together with scaling and affine<br>
>> in<br>>> >>> >> >> 4<br>>> >&g=
t;> >> >> parameters, and<br>>> >>> >> =
>> translations, independently, in the last two. I understand that<br=
>
>> in<br>>> >>> >> >> this<br>>> >=
;>> >> >> case, the indices<br>>> >>> >=
> >> run over parameters that have been separated into individual<=
br>
>> >>> >> >> components<br>>> >>>=
>> >> (similar to<br>>> >>> >> >> t=
he form accepted by spm_matrix). Is this correct for the<br>>> functi=
on<br>
>> >>> >> >> reg(..)? =A0In fact, I went back to=
the<br>>> >>> >> >> old spm code (spm99), and f=
ound parameters pdesc and free, and<br>>> got<br>>> >>>=
; >> >> more<br>
>> >>> >> >> confused as to when I should<br>>=
;> >>> >> >> use the 6 parameter, and when to use s=
eparate parameters (as if<br>>> I<br>>> >>> >> &=
gt;> was<br>
>> >>> >> >> passing them to spm_matrix).<br>>=
;> >>> >> >> So, when the loop runs over p1 and per=
turbs p1(i) by ds, does it<br>>> >>> >> >> run<b=
r>
>> >>> >> >> over<br>>> >>> >&=
gt; >> translations/rotations etc<br>>> >>> >> &=
gt;> or does it run over the martix elements that define these<br>>&g=
t; >>> >> >> transformations<br>
>> >>> >> >> (2x2 + 1x2)?<br>>> >>&g=
t; >> >><br>>> >>> >> >> =A0 =A0 =A0=
=A0 =A0 =A02) In function penalty(..), I have used unique<br>>> elem=
ents<br>
>> >>> >> >> as<br>>> >>> >>=
; >> [1,3,4], and my code looks like<br>>> >>> >>=
; >> T =3D my_matrix(p)*M;<br>>> >>> >> >>=
T =3D T(1:2,1:2);<br>
>> >>> >> >> T =3D 0.5*logm(T'*T);<br>>&g=
t; >>> >> >> T<br>>> >>> >> >&=
gt; T =3D T(els)' - mu;<br>>> >>> >> >> h =
=3D T'*isig*T<br>
>> >>> >> >><br>>> >>> >> &=
gt;> Assuming an application specific isig, is this correct?<br>>>=
>>> >> >> =A0 =A0 =A0 =A0 =A03) I have not yet incorp=
orated the prior information in<br>
>> my<br>>> >>> >> >> code,<br>>> &g=
t;>> >> >> But for testing purposes,<br>>> >>=
> >> >> can you suggest some neutral values =A0for mu and is=
ig that I can<br>
>> try<br>>> >>> >> >> to<br>>> >=
>> >> >> concentrate on the<br>>> >>> >=
> >> accuracy of the implementation minus the priors for now?<br>
>> >>> >> >> =A0 =A0 =A0 =A0 =A0 4) My solution =
curently seems to oscillate around an<br>>> >>> >> >=
;> optimum.<br>>> >>> >> >> I<br>>> >=
;>> >> >> am hoping that after<br>
>> >>> >> >> I have removed any errors after you=
r replies, it will converge<br>>> >>> >> >> grac=
efully.<br>>> >>> >> >><br>>> >>>=
>> >> =A0 =A0 =A0 =A0 =A0 Thanks again for all the help.<br>
>> >>> >> >> =A0 =A0 =A0 =A0 =A0 =A0Siddharth.<b=
r>>> >>> >> >><br>>> >>> >>=
>><br>>> >>> >> >> On Fri, Mar 18, 2011 a=
t 2:05 AM, John Ashburner<br>
>> >>> >> >> <<a href=3D"mailto:jashburner@gm=
ail.com">[log in to unmask]</a>><br>>> >>> >> >=
;> wrote:<br>>> >>> >> >>><br>>> >=
;>> >> >>> A 2D affine transform would use 6 parameter=
s, rather than 7: a<br>
>> 2x2<br>>> >>> >> >>> matrix to encod=
e rotations, zooms and shears, and a 2x1 vector<br>>> for<br>>>=
>>> >> >>> translations.<br>>> >>> =
>> >>><br>
>> >>> >> >>> Best regards,<br>>> >&=
gt;> >> >>> -John<br>>> >>> >> >&=
gt;><br>>> >>> >> >>> On 18 March 2011 05:=
05, Siddharth Srivastava <<a href=3D"mailto:[log in to unmask]">siddys@gma=
il.com</a><br>
>> ><br>>> >>> >> >>> wrote:<br>>=
> >>> >> >>> > Dear list users,<br>>> &=
gt;>> >> >>> > =A0 =A0 =A0 =A0 =A0 I am currently t=
rying to understand the<br>
>> implementation<br>>> >>> >> >>> >=
in<br>>> >>> >> >>> > spm_affreg, and<br>=
>> >>> >> >>> > to make matters simple, I =
tried to work out a 2D version of<br>
>> the<br>>> >>> >> >>> > registrati=
on<br>>> >>> >> >>> > procedure. I struck =
a roadblock, however...<br>>> >>> >> >>> >=
<br>
>> >>> >> >>> > The function make_A create=
s part of the design matrix. For<br>>> the<br>>> >>> &=
gt;> >>> > 3D<br>>> >>> >> >>>=
> case,<br>
>> >>> >> >>> > the<br>>> >>&g=
t; >> >>> > 13 parameters<br>>> >>> >&g=
t; >>> > are encoded in columns of A1, which then is used to ge=
nerate<br>
>> AA<br>>> >>> >> >>> > +<br>>&g=
t; >>> >> >>> > A1'<br>>> >>>=
>> >>> > A1. AA<br>>> >>> >> >&g=
t;> > is 13x13, and everything<br>
>> >>> >> >>> > works. For the 2D case, ho=
wever, there will be 7+1<br>>> parameters( 2<br>>> >>>=
>> >>> > translations, 1 rotation, 2 zoom, 2 shears and =
1 intensity<br>
>> >>> >> >>> > scaling).<br>>> >=
>> >> >>> > The A1 matrix for 2D, then, =A0will be =
(in make_A)<br>>> >>> >> >>> > A =A0=3D [x=
1.*dG1 x1.*dG2 ...<br>
>> >>> >> >>> > =A0 =A0 =A0 x2.*dG1 x2.*dG=
2 ...<br>>> >>> >> >>> > =A0 =A0 =A0 dG1 =
=A0 =A0 dG2 =A0t];<br>>> >>> >> >>> ><br>&=
gt;> >>> >> >>> > which is (number of sampled=
points) x 7. The AA matrix (in<br>
>> >>> >> >>> > function<br>>> >&=
gt;> >> >>> > costfun)<br>>> >>> >&g=
t; >>> > is 8x8<br>>> >>> >> >>> =
> so, which is the parameter I am missing in modeling a 2D<br>
>> >>> >> >>> > example? I<br>>> >=
;>> >> >>> > hope I<br>>> >>> >&g=
t; >>> > have got the number of parameters<br>>> >>=
> >> >>> > right for the 2D case? Is there an extra co=
lumn that I have<br>
>> to<br>>> >>> >> >>> > add<br>>=
> >>> >> >>> > to<br>>> >>> &g=
t;> >>> > A1 to<br>>> >>> >> >>&g=
t; > make the rest of the matrix computation<br>
>> >>> >> >>> > consistent?<br>>> &g=
t;>> >> >>> ><br>>> >>> >> >=
;>> > Thanks for the help<br>>> >>> >> >&g=
t;> ><br>
>> >>> >> >><br>>> >>> >> &=
gt;<br>>> >>> >> ><br>>> >>> ><br=
>>> >>> ><br>>> >><br>>> ><br>>&g=
t; ><br>
>><br>><br>><br><br>------------------------------<br><br>Date:=
=A0 =A0Sat, 7 May 2011 07:14:27 +1000<br>From: =A0 =A0Alex Fornito <<a =
href=3D"mailto:[log in to unmask]">[log in to unmask]</a>><br>=
Subject: Re: PPI question<br>
<br>Actually, sorry one more question:<br><br>If Y in spm_peb_ppi is alread=
y frequency filtered by spm_regions, then the<br>only difference (barring a=
ny additional confounds specified with xX.iG)<br>between Y and Yc is the ad=
ditional removal of block effects.<br>
<br>Since the ppi interaction term is generated from Y and not Yc, I am<br>=
presuming then that is solely because it is not desirable to deconvolve a<b=
r>time course with block effects removed. Is this correct?<br><br><br>On 07=
/05/2011 04:07, "MCLAREN, Donald" <<a href=3D"mailto:mclaren.d=
[log in to unmask]">[log in to unmask]</a>> wrote:<br>
<br>> The null-space of the contrast are any columns of the contrast (wh=
ich<br>> must be an F-contrast) that are 0. Thus, you remove the effects=
of<br>> motion when you do the adjustment and don't need to worry a=
bout them<br>
> being included in the deconvolved data. The code that I have supplied<=
br>> has N rows for N conditions of interest after I talked to Darren ab=
out<br>> the ideal contrast to use for adjustment.<br>><br>> As fo=
r removing the frequencies, I think it is probably fine to remove<br>
> them, I was just under the impression that they weren't being remo=
ved<br>> because of me commenting out that line during testing of spm_re=
gions.<br>> I would go with the SPM defaults until their effect is teste=
d. If you<br>
> don't set a high-pass filter, then you won't remove the freque=
ncies,<br>> so you could test it that way as well.<br>><br>> Best =
Regards, Donald McLaren<br>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D<br>> D.G. McLaren, Ph.D.<br>
> Postdoctoral Research Fellow, GRECC, Bedford VA<br>> Research Fello=
w, Department of Neurology, Massachusetts General<br>> Hospital and Harv=
ard Medical School<br>> Office: (773) 406-2464<br>> =3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D<br>
> This e-mail contains CONFIDENTIAL INFORMATION which may contain<br>>=
; PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED<br>&g=
t; and which is intended only for the use of the individual or entity<br>
> named above. If the reader of the e-mail is not the intended recipient=
<br>> or the employee or agent responsible for delivering it to the inte=
nded<br>> recipient, you are hereby notified that you are in possession =
of<br>
> confidential and privileged information. Any unauthorized use,<br>>=
disclosure, copying or the taking of any action in reliance on the<br>>=
contents of this information is strictly prohibited and may be<br>> unl=
awful. If you have received this e-mail unintentionally, please<br>
> immediately notify the sender via telephone at (773) 406-2464 or<br>&g=
t; email.<br>><br>><br>><br>> On Thu, May 5, 2011 at 9:46 PM, A=
lex Fornito <<a href=3D"mailto:[log in to unmask]">fornitoa@unimelb=
.edu.au</a>> wrote:<br>
>> Hi Donald, Torben and Darren,<br>>> Thanks for your response=
s.<br>>><br>>> Form each of your responses, it seems like best =
practice would be to remove<br>>> motion (and/or other confounds) fro=
m the VOI time series prior to<br>
>> deconvolution.<br>>><br>>> It also seems like you are =
recommending NOT to frequency filter the VOI time<br>>> series.<br>&g=
t;><br>>> In my reading though, spm_regions does this by default w=
ith the call to<br>
>> spm_filter (line 135). So, if spm_regions is used to extract a VOI=
time<br>>> series, the time series that is input to spm_peb_ppi will=
already frequency<br>>> filtered. So it seems like, in standard prac=
tice, the deconvolution is<br>
>> applied to frequency-filtered data. In this case, if xX.iG is empt=
y, the<br>>> only difference between Y and Yc in spm_peb_ppi is the a=
dditional removal of<br>>> block effects (xX.iB).<br>>><br>
>> Based on the current chain of emails, it seems you are recommendin=
g that a<br>>> confound-corrected, whitened, but non-frequency filter=
ed time course should<br>>> be input to spm_peb_ppi. IS that correct,=
or am I missing something?<br>
>><br>>> Finally, can I clarify exactly what the null space of =
the contrast is? Most<br>>> of the time in my analyses I don't ge=
t the option to adjust for it, so xY.Ic<br>>> is empty.<br>>><b=
r>
>> Thanks again for all your help,<br>>> A<br>>><br>>&=
gt;<br>>><br>>> On 06/05/2011 02:18, "MCLAREN, Donald"=
; <<a href=3D"mailto:[log in to unmask]">[log in to unmask]<=
/a>> wrote:<br>
>><br>>>> I haven't thoroughly tested this, but if you s=
et iG to be the movement<br>>>> parameters columns. Then still adj=
ust for the null space (motion<br>>>> parameters). You will get th=
e best of both. If you don't adjust for<br>
>>> the null space, then movement will contribute to the deconvolu=
tion. In<br>>>> summary, if you have iG be the motion parameter co=
lumns AND adjust for<br>>>> the null-space (motion columns), then:=
<br>
>>><br>>>> Y will have the effect of motion removed. Yc (=
removal of motion twice)<br>>>> will be minimally different since =
Y is orthogonal to the motion<br>>>> parameters. So, you have moti=
on removed from both the autocorrelation<br>
>>> estimate, the Y for deconvolution, and Yc.<br>>>><br>=
>>> Best Regards, Donald McLaren<br>>>> =3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D<br>>>> D.G. McLaren, Ph.D.<br=
>>>> Postdoctoral Research Fellow, GRECC, Bedford VA<br>
>>> Research Fellow, Department of Neurology, Massachusetts Genera=
l<br>>>> Hospital and Harvard Medical School<br>>>> Offic=
e: (773) 406-2464<br>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D<br>>>> This e-mail contains CONFIDENTIAL =
INFORMATION which may contain<br>
>>> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVI=
LEGED<br>>>> and which is intended only for the use of the individ=
ual or entity<br>>>> named above. If the reader of the e-mail is n=
ot the intended recipient<br>
>>> or the employee or agent responsible for delivering it to the =
intended<br>>>> recipient, you are hereby notified that you are in=
possession of<br>>>> confidential and privileged information. Any=
unauthorized use,<br>
>>> disclosure, copying or the taking of any action in reliance on=
the<br>>>> contents of this information is strictly prohibited an=
d may be<br>>>> unlawful. If you have received this e-mail uninten=
tionally, please<br>
>>> immediately notify the sender via telephone at (773) 406-2464 =
or<br>>>> email.<br>>>><br>>>><br>>>><b=
r>>>> On Thu, May 5, 2011 at 9:48 AM, Torben Ellegaard Lund<br>
>>> <<a href=3D"mailto:[log in to unmask]">[log in to unmask]</=
a>> wrote:<br>>>>> Hi Alex<br>>>>><br>>>&g=
t;><br>>>>> Den Uge:18 05/05/2011 kl. 14.15 skrev Alex Forni=
to:<br>
>>>><br>>>>>> Hi Torben,<br>>>>>>=
Sorry, I just wanted to clarify: do you mean leaving SPM.xX.iG empty? It<b=
r>>>>>> seems like this is done by default by spm_fmri_desig=
n (?)<br>
>>>><br>>>>> leaving it empty will include all user=
defined regressors in the effects of<br>>>>> interest F-test w=
hich determines the mask where the serial correlation is<br>>>>>=
; estimated. I think it would make sense if the motion regressors did not g=
o<br>
>>>> into this test, just like the DCS HP-filter does not go in=
to the<br>>>>> F-contrast.<br>>>>><br>>>>&=
gt;> Are you suggesting manually entering motion parameters into this fi=
eld?<br>
>>>><br>>>>> Yes, or their indices that is. It shou=
ld be done after specification, but<br>>>>> before model estima=
tion. You can check if SPM recognized your changes by<br>>>>> l=
ooking at the automatically generated effects of interest F-contrast.<br>
>>>><br>>>>><br>>>>> Best<br>>>&g=
t;> Torben<br>>>>><br>>>>><br>>>>><b=
r>>>>><br>>>>>><br>>>>>> On 05/05=
/2011 18:16, "Torben Ellegaard Lund" <<a href=3D"mailto:torben=
[log in to unmask]">[log in to unmask]</a>> wrote:<br>
>>>>><br>>>>>>> Just as a kind reminder. L=
eaving SPM.xX.iG is a bit unfortunate, because<br>>>>>>> =
voxels where motion artefacts are significant then constitutes a large<br>
>>>>>> part<br>>>>>>> of<br>>>>=
;>>> the F-test derived mask used to estimate serial correlations.=
If you are<br>>>>>>> picky<br>>>>>>> a=
bout this you can change it yourselves, but it is not as easy as it<br>
>>>>>> should<br>>>>>>> be.<br>>>=
>>>><br>>>>>>><br>>>>>>> Be=
st<br>>>>>>> Torben<br>>>>>>><br>>&g=
t;>>>><br>
>>>>>><br>>>>>>> Den Uge:18 05/05/2011 =
kl. 05.03 skrev Alex Fornito:<br>>>>>>><br>>>>&g=
t;>>> Ahh, I see. I was assuming that SPM.xX.iG contained the indi=
ces to the<br>
>>>>>>> nuisance covariates in the design matrix, but =
you're right -<br>>>>>>>> spm_fMRI_design<br>>&=
gt;>>>>> leaves it empty.<br>>>>>>>><br=
>
>>>>>>> Thanks for your help!<br>>>>>>&=
gt;> A<br>>>>>>>><br>>>>>>>><b=
r>>>>>>>> On 05/05/2011 12:54, "MCLAREN, Donald&q=
uot; <<a href=3D"mailto:[log in to unmask]">[log in to unmask]
om</a>> wrote:<br>
>>>>>>><br>>>>>>>>> I agree th=
at nuisance covariates, such as motion should be removed;<br>>>>&g=
t;>>>> however, motion covariates are not generally stored in X=
0 in my<br>
>>>>>>>> reading of the SPM code (spm_fMRI_design, =
spm_regions). They should be<br>>>>>>>>> removed in=
the spm_regions filtering based on the null-space of the<br>>>>&g=
t;>>>> contrast.<br>
>>>>>>>><br>>>>>>>>> As for=
the motion parameters being in the model, if they were in the<br>>>&=
gt;>>>>> standard analysis, they should be included in the P=
PI analysis. My<br>
>>>>>>>> gPPI code will do this automatically as we=
ll.<br>>>>>>>>><br>>>>>>>>>=
X0 is made of SPM.xX.iB (block effects -- so removing the mean) and<br>
>>>>>>>> SPM.xX.iG (nuisance variable that is empty=
as far as I can tell (line<br>>>>>>>>> 369 of spm_=
fMRI_design)) and the high-pass filtering (K.X0).<br>>>>>>&g=
t;>><br>
>>>>>>>> Best Regards, Donald McLaren<br>>>&g=
t;>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D<=
br>>>>>>>>> D.G. McLaren, Ph.D.<br>>>>>=
>>>> Postdoctoral Research Fellow, GRECC, Bedford VA<br>
>>>>>>>> Research Fellow, Department of Neurology, =
Massachusetts General<br>>>>>>>>> Hospital and Harv=
ard Medical School<br>>>>>>>>> Office: (773) 406-24=
64<br>
>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D<br>>>>>>>>> This e-mail conta=
ins CONFIDENTIAL INFORMATION which may contain<br>>>>>>>&=
gt;> PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED=
<br>
>>>>>>>> and which is intended only for the use of =
the individual or entity<br>>>>>>>>> named above. I=
f the reader of the e-mail is not the intended recipient<br>>>>>=
;>>>> or the employee or agent responsible for delivering it to=
the intended<br>
>>>>>>>> recipient, you are hereby notified that yo=
u are in possession of<br>>>>>>>>> confidential and=
privileged information. Any unauthorized use,<br>>>>>>>&=
gt;> disclosure, copying or the taking of any action in reliance on the<=
br>
>>>>>>>> contents of this information is strictly p=
rohibited and may be<br>>>>>>>>> unlawful. If you h=
ave received this e-mail unintentionally, please<br>>>>>>>=
;>> immediately notify the sender via telephone at (773) 406-2464 or<=
br>
>>>>>>>> email.<br>>>>>>>>>=
<br>>>>>>>>><br>>>>>>>>><br=
>>>>>>>>> On Wed, May 4, 2011 at 10:16 PM, Alex For=
nito <<a href=3D"mailto:[log in to unmask]">[log in to unmask]
</a>><br>
>>>>>>>> wrote:<br>>>>>>>>>=
> Hi Donald,<br>>>>>>>>>> Thanks for your res=
ponse. When you say "you don't want<br>>>>>>>>=
;>> to filter out anything related to neural activity", I'm =
presuming that<br>
>>>>>>>>> you<br>>>>>>>>>=
;> are referring to the deconvolved neural signal?<br>>>>>&g=
t;>>>><br>>>>>>>>>> If so, that make=
s sense. However, X0 also contains user-specified<br>
>>>>>>>>> nuisance<br>>>>>>>&g=
t;>> covariates. I would have thought it would make sense to remove t=
hose,<br>>>>>>>>>> depending on what they were (=
e.g., movement parameters)? I guess they<br>
>>>>>>>>> can<br>>>>>>>>>=
;> always be entered into the PPI regression model...<br>>>>>=
;>>>>><br>>>>>>>>>><br>>>&g=
t;>>>>>> On 05/05/2011 11:57, "MCLAREN, Donald"=
<<a href=3D"mailto:[log in to unmask]">[log in to unmask]</=
a>><br>
>>>>>>>>> wrote:<br>>>>>>>>=
>><br>>>>>>>>>>> I could be wrong, Karl=
or Darren please correct me if I am.<br>>>>>>>>>&g=
t;><br>
>>>>>>>>>> X0 is composed of the high-pass fi=
lter and constant term. Thus, you<br>>>>>>>>>>&g=
t; want to filter these out of the Yc regressor. However, you don't wan=
t<br>
>>>>>>>>>> to filter out anything related to =
neural activity, so you wouldn't<br>>>>>>>>>>=
;> want to filter your signal and then predict the neural activity from<=
br>
>>>>>>>>>> the filtered signal, especially fi=
ltering frequencies.<br>>>>>>>>>>><br>>>=
;>>>>>>>> Best Regards, Donald McLaren<br>>>&=
gt;>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D<br>
>>>>>>>>>> D.G. McLaren, Ph.D.<br>>>>=
;>>>>>>> Postdoctoral Research Fellow, GRECC, Bedford =
VA<br>>>>>>>>>>> Research Fellow, Department =
of Neurology, Massachusetts General<br>
>>>>>>>>>> Hospital and Harvard Medical Schoo=
l<br>>>>>>>>>>> Office: (773) 406-2464<br>>=
;>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D<br>>>>>>>>>>> Thi=
s e-mail contains CONFIDENTIAL INFORMATION which may contain<br>
>>>>>>>>>> PROTECTED HEALTHCARE INFORMATION a=
nd may also be LEGALLY PRIVILEGED<br>>>>>>>>>>&g=
t; and which is intended only for the use of the individual or entity<br>
>>>>>>>>>> named above. If the reader of the =
e-mail is not the intended<br>>>>>>>>>>> reci=
pient<br>>>>>>>>>>> or the employee or agent =
responsible for delivering it to the<br>
>>>>>>>>>> intended<br>>>>>>&g=
t;>>>> recipient, you are hereby notified that you are in posse=
ssion of<br>>>>>>>>>>> confidential and privi=
leged information. Any unauthorized use,<br>
>>>>>>>>>> disclosure, copying or the taking =
of any action in reliance on the<br>>>>>>>>>>>=
; contents of this information is strictly prohibited and may be<br>>>=
;>>>>>>>> unlawful. If you have received this e-mai=
l unintentionally, please<br>
>>>>>>>>>> immediately notify the sender via =
telephone at (773) 406-2464 or<br>>>>>>>>>>> =
email.<br>>>>>>>>>>><br>>>>>>&=
gt;>>>><br>
>>>>>>>>>><br>>>>>>>>>=
;>> On Sat, Apr 30, 2011 at 8:03 PM, Alex Fornito<br>>>>>=
>>>>>> <<a href=3D"mailto:[log in to unmask]">for=
[log in to unmask]</a>><br>
>>>>>>>>>> wrote:<br>>>>>>>=
>>>>> Hi Donald,<br>>>>>>>>>>>=
> As far as I can tell, spm_regions filters and whitens the VOI time<br>
>>>>>>>>>>> series,<br>>>>>>=
;>>>>>> and adjusts for the null space of the contrast if=
an adjustment is<br>>>>>>>>>>>> specified=
<br>
>>>>>>>>>>> in xY.Ic. It defines the confo=
und matrix, X0, but does not correct<br>>>>>>>>>>=
;>> for<br>>>>>>>>>>>> it.<br>>&g=
t;>>>>>>>>> The following line in spm_peb_ppi co=
rrects for the confounds.<br>
>>>>>>>>>>><br>>>>>>>>=
;>>>> Yc =A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;<br>>&g=
t;>>>>>>>>> PPI.Y =3D Yc(:,1);<br>>>>&g=
t;>>>>>>><br>
>>>>>>>>>>> So the above correction does s=
eem to be doing something different to<br>>>>>>>>>&=
gt;>> spm_regions. I'm wondering why the uncorrected data, Y, is =
used when<br>
>>>>>>>>>>> generating the ppi interaction=
term, while the corrected data Yc is<br>>>>>>>>>&g=
t;>> to<br>>>>>>>>>>>> be<br>>>=
;>>>>>>>>> used as a covariate of no interest in=
the PPI model. I would has<br>
>>>>>>>>>>> thought<br>>>>>>=
;>>>>>> that Yc should be used to generate the ppi intera=
ction term as well.<br>>>>>>>>>>>><br>
>>>>>>>>>>> In my data, my X0 is a 195 x 7=
matrix (I have 195 volumes per<br>>>>>>>>>>>=
> session).<br>>>>>>>>>>>><br>>>&=
gt;>>>>>>>> Regards,<br>
>>>>>>>>>>> Alex<br>>>>>>&g=
t;>>>>><br>>>>>>>>>>>><br>&=
gt;>>>>>>>>>> On 30/04/2011 02:22, "MCLA=
REN, Donald" <<a href=3D"mailto:[log in to unmask]">mclaren.d=
[log in to unmask]</a>><br>
>>>>>>>>>>> wrote:<br>>>>>>=
>>>>>><br>>>>>>>>>>>>>=
; I'm actually travelling at the moment. However, I know Y has<br>>&=
gt;>>>>>>>>>> already<br>
>>>>>>>>>>>> been adjusted as part of t=
he VOI processing.<br>>>>>>>>>>>>><br>&=
gt;>>>>>>>>>>> Can you check what X0 looks=
like?<br>
>>>>>>>>>>>><br>>>>>>>=
;>>>>>> Best Regards, Donald McLaren<br>>>>>&=
gt;>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D<br>>>>>>>>>>>>> D.G. McLaren,=
Ph.D.<br>
>>>>>>>>>>>> Postdoctoral Research Fell=
ow, GRECC, Bedford VA<br>>>>>>>>>>>>> R=
esearch Fellow, Department of Neurology, Massachusetts General<br>>>&=
gt;>>>>>>>>> Hospital and Harvard Medical School=
<br>
>>>>>>>>>>>> Office: (773) 406-2464<br>=
>>>>>>>>>>>> =3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D<br>>>>>>>>>=
>>>> This e-mail contains CONFIDENTIAL INFORMATION which may co=
ntain<br>
>>>>>>>>>>>> PROTECTED HEALTHCARE INFOR=
MATION and may also be LEGALLY PRIVILEGED<br>>>>>>>>&g=
t;>>>> and which is intended only for the use of the individual=
or entity<br>
>>>>>>>>>>>> named above. If the reader=
of the e-mail is not the intended<br>>>>>>>>>>&=
gt;>> recipient<br>>>>>>>>>>>>> o=
r the employee or agent responsible for delivering it to the<br>
>>>>>>>>>>>> intended<br>>>>&g=
t;>>>>>>>> recipient, you are hereby notified that =
you are in possession of<br>>>>>>>>>>>>>=
; confidential and privileged information. Any unauthorized use,<br>
>>>>>>>>>>>> disclosure, copying or the=
taking of any action in reliance on the<br>>>>>>>>>=
;>>>> contents of this information is strictly prohibited and m=
ay be<br>
>>>>>>>>>>>> unlawful. If you have rece=
ived this e-mail unintentionally, please<br>>>>>>>>>=
;>>>> immediately notify the sender via telephone at (773) 406-=
2464 or<br>
>>>>>>>>>>>> email.<br>>>>>=
>>>>>>>><br>>>>>>>>>>>=
;>><br>>>>>>>>>>>>><br>>>&g=
t;>>>>>>>>> On Fri, Apr 29, 2011 at 2:55 AM, Ale=
x Fornito<br>
>>>>>>>>>>>> <<a href=3D"mailto:forn=
[log in to unmask]">[log in to unmask]</a>><br>>>>>>=
;>>>>>>> wrote:<br>>>>>>>>>>=
;>>> Hi all,<br>
>>>>>>>>>>>> I have a question concerni=
ng the code used to implement a PPI<br>>>>>>>>>>=
>>> analysis.<br>>>>>>>>>>>>><=
br>
>>>>>>>>>>>> In the spm_peb_ppi.m funct=
ion packaged with SPM8, lines 329-332<br>>>>>>>>>&g=
t;>>> remove<br>>>>>>>>>>>>> c=
onfounds from the input seed region=B9s time course:<br>
>>>>>>>>>>>><br>>>>>>>=
;>>>>>> % Remove confounds and save Y in ouput structure<=
br>>>>>>>>>>>>><br>%-------------------=
----------------------------------------------->>>>>>>=
>>>>><br>
-<br>>>>>>>>>>>>> ---<br>>>>&g=
t;>>>>>>>> --<br>>>>>>>>>&g=
t;>>> --<br>>>>>>>>>>>>> Yc =
=A0 =A0=3D Y - X0*inv(X0'*X0)*X0'*Y;<br>
>>>>>>>>>>>> PPI.Y =3D Yc(:,1);<br>>=
>>>>>>>>>>><br>>>>>>>>=
;>>>>> PPI.Y is then to be used as a covariate of no interes=
t when<br>
>>>>>>>>>>>> building<br>>>>&g=
t;>>>>>>>> the<br>>>>>>>>>&=
gt;>>> PPI<br>>>>>>>>>>>>> reg=
ression model. However, on line 488, it is the uncorrected seed<br>
>>>>>>>>>>>> time<br>>>>>&g=
t;>>>>>>> course, Y, that is input to the deconvolutio=
n routine and used to<br>>>>>>>>>>>>> g=
enerate<br>
>>>>>>>>>>>> the ppi term:<br>>>&=
gt;>>>>>>>>><br>>>>>>>>>=
>>>> =A0C =A0=3D spm_PEB(Y,P);<br>>>>>>>>&=
gt;>>>> =A0 =A0xn =3D xb*C{2}.E(1:N);<br>
>>>>>>>>>>>> =A0 =A0xn =3D spm_detrend(=
xn);<br>>>>>>>>>>>>><br>>>>>=
;>>>>>>>> =A0% Setup psychological variable from in=
puts and contast weights<br>
>>>>>>>>>>>><br>>>>>>>=
;>>>>>><br>%---------------------------------------------=
--------------------->>>>>>>>>>>><br>
-<br>>>>>>>>>>>>> ---<br>>>>&g=
t;>>>>>>>> =A0PSY =3D zeros(N*NT,1);<br>>>>=
;>>>>>>>>> =A0for i =3D 1:size(U.u,2)<br>>>=
;>>>>>>>>>> =A0 =A0 =A0PSY =3D PSY + full(U.u=
(:,i)*U.w(:,i));<br>
>>>>>>>>>>>> =A0end<br>>>>>=
>>>>>>>> =A0% PSY =3D spm_detrend(PSY); =A0<- re=
moved centering of psych variable<br>>>>>>>>>>&g=
t;>> =A0% prior to multiplication with xn. Based on discussion with K=
arl<br>
>>>>>>>>>>>> =A0% and Donald McLaren.<b=
r>>>>>>>>>>>>><br>>>>>>&=
gt;>>>>>> % Multiply psychological variable by neural sig=
nal<br>
>>>>>>>>>>>><br>>>>>>>=
;>>>>>><br>>>>>>>>>>>>&g=
t;<br>%------------------------------------------------------------------&g=
t;>>>>>>>>>>><br>
-<br>>>>>>>>>>>>> ---<br>>>>&g=
t;>>>>>>>> =A0 PSYxn =3D PSY.*xn;<br>>>>&g=
t;>>>>>>>><br>>>>>>>>>>&=
gt;>> Is there any specific reason why Y, rather than Yc(:,1), is use=
d to<br>
>>>>>>>>>>>> compute<br>>>>>=
;>>>>>>>> PSYxn? I thought Yc might be more appropr=
iate (?).<br>>>>>>>>>>>>> Thanks for yo=
ur help,<br>
>>>>>>>>>>>> Alex<br>>>>>&g=
t;>>>>>>><br>>>>>>>>>>>&=
gt;><br>>>>>>>>>>>>><br>>>>=
>>>>>>>>><br>
>>>>>>>>>>>> --------------------------=
----------------<br>>>>>>>>>>>>><br>>=
;>>>>>>>>>>> Alex Fornito<br>>>>&=
gt;>>>>>>>> Research Fellow<br>
>>>>>>>>>>>> Melbourne Neuropsychiatry =
Centre<br>>>>>>>>>>>>> University of Me=
lbourne<br>>>>>>>>>>>>> National Neuros=
cience Facility<br>
>>>>>>>>>>>> Levels 1 & 2, Alan Gil=
bert Building<br>>>>>>>>>>>>> 161 Barry=
St<br>>>>>>>>>>>>> Carlton South 3053<=
br>
>>>>>>>>>>>> Victoria, Australia<br>>=
;>>>>>>>>>>><br>>>>>>>&g=
t;>>>>> Email: <a href=3D"mailto:[log in to unmask]">fo=
[log in to unmask]</a><br>
>>>>>>>>>>>> Phone: +61 3 8344 1876<br>=
>>>>>>>>>>>> Fax: +61 3 9348 0469<br>&g=
t;>>>>>>>>>>><br>>>>>>>&=
gt;>>>>><br>
>>>>>>>>>>>><br>>>>>>>=
;>>>>><br>>>>>>>>>>>><br>&g=
t;>>>>>>>>>> --------------------------------=
----------<br>
>>>>>>>>>>><br>>>>>>>>=
;>>>> Alex Fornito<br>>>>>>>>>>>&=
gt; Research Fellow<br>>>>>>>>>>>> Melbour=
ne Neuropsychiatry Centre<br>
>>>>>>>>>>> University of Melbourne<br>>=
;>>>>>>>>>> National Neuroscience Facility<br=
>>>>>>>>>>>> Levels 1 & 2, Alan Gilber=
t Building<br>
>>>>>>>>>>> 161 Barry St<br>>>>&g=
t;>>>>>>> Carlton South 3053<br>>>>>>&g=
t;>>>>> Victoria, Australia<br>>>>>>>>&=
gt;>>><br>
>>>>>>>>>>> Email: <a href=3D"mailto:forni=
[log in to unmask]">[log in to unmask]</a><br>>>>>>>=
>>>>> Phone: +61 3 8344 1876<br>>>>>>>>=
>>>> Fax: +61 3 9348 0469<br>
>>>>>>>>>>><br>>>>>>>>=
;>>>><br>>>>>>>>>>>><br>>&g=
t;>>>>>>>>><br>>>>>>>>>&=
gt;><br>
>>>>>>>>><br>>>>>>>>>>=
;<br>>>>>>>>>> ---------------------------------=
---------<br>>>>>>>>>><br>>>>>>&g=
t;>>> Alex Fornito<br>
>>>>>>>>> Research Fellow<br>>>>>>=
;>>>> Melbourne Neuropsychiatry Centre<br>>>>>>&=
gt;>>> University of Melbourne<br>>>>>>>>>=
> National Neuroscience Facility<br>
>>>>>>>>> Levels 1 & 2, Alan Gilbert Buildin=
g<br>>>>>>>>>> 161 Barry St<br>>>>>&=
gt;>>>> Carlton South 3053<br>>>>>>>>>&=
gt; Victoria, Australia<br>
>>>>>>>>><br>>>>>>>>>>=
; Email: <a href=3D"mailto:[log in to unmask]">[log in to unmask]
</a><br>>>>>>>>>> Phone: +61 3 8344 1876<br>>=
>>>>>>>> Fax: +61 3 9348 0469<br>
>>>>>>>>><br>>>>>>>>>>=
;<br>>>>>>>>>><br>>>>>>>>&g=
t;><br>>>>>>>>><br>>>>>>>><=
br>
>>>>>>><br>>>>>>>> --------------=
----------------------------<br>>>>>>>><br>>>>=
;>>>> Alex Fornito<br>>>>>>>> Research Fel=
low<br>
>>>>>>> Melbourne Neuropsychiatry Centre<br>>>&g=
t;>>>> University of Melbourne<br>>>>>>>> =
National Neuroscience Facility<br>>>>>>>> Levels 1 &am=
p; 2, Alan Gilbert Building<br>
>>>>>>> 161 Barry St<br>>>>>>>> C=
arlton South 3053<br>>>>>>>> Victoria, Australia<br>&g=
t;>>>>>><br>>>>>>>> Email: <a href=
=3D"mailto:[log in to unmask]">[log in to unmask]</a><br>
>>>>>>> Phone: +61 3 8344 1876<br>>>>>>=
>> Fax: +61 3 9348 0469<br>>>>>>><br>>>>&g=
t;>><br>>>>>><br>>>>>><br>>>>&=
gt;> ------------------------------------------<br>
>>>>><br>>>>>> Alex Fornito<br>>>>&g=
t;> Research Fellow<br>>>>>> Melbourne Neuropsychiatry Ce=
ntre<br>>>>>> University of Melbourne<br>>>>>>=
; National Neuroscience Facility<br>
>>>>> Levels 1 & 2, Alan Gilbert Building<br>>>>=
;>> 161 Barry St<br>>>>>> Carlton South 3053<br>>&g=
t;>>> Victoria, Australia<br>>>>>><br>>>>&=
gt;> Email: <a href=3D"mailto:[log in to unmask]">[log in to unmask]
edu.au</a><br>
>>>>> Phone: +61 3 8344 1876<br>>>>>> Fax: +6=
1 3 9348 0469<br>>>>>><br>>>>>><br>>>&g=
t;>><br>>>>><br>>>><br>>><br>>><br>
>> ------------------------------------------<br>>><br>>>=
Alex Fornito<br>>> Research Fellow<br>>> Melbourne Neuropsychi=
atry Centre<br>>> University of Melbourne<br>>> National Neuros=
cience Facility<br>
>> Levels 1 & 2, Alan Gilbert Building<br>>> 161 Barry St<b=
r>>> Carlton South 3053<br>>> Victoria, Australia<br>>><b=
r>>> Email: <a href=3D"mailto:[log in to unmask]">fornitoa@unime=
lb.edu.au</a><br>
>> Phone: +61 3 8344 1876<br>>> Fax: +61 3 9348 0469<br>>>=
;<br>>><br>>><br>>><br>><br><br><br>------------------=
------------------------<br><br>Alex Fornito<br>Research Fellow<br>Melbourn=
e Neuropsychiatry Centre<br>
University of Melbourne<br>National Neuroscience Facility<br>Levels 1 &=
2, Alan Gilbert Building<br>161 Barry St=A0<br>Carlton South 3053<br>Victo=
ria, Australia<br><br>Email: <a href=3D"mailto:[log in to unmask]">for=
[log in to unmask]</a><br>
Phone: +61 3 8344 1876<br>Fax: +61 3 9348 0469 =A0<br><br>-----------------=
-------------<br><br>Date: =A0 =A0Fri, 6 May 2011 16:17:37 -0500<br>From: =
=A0 =A0John Fredy <<a href=3D"mailto:[log in to unmask]">jfochoaster@=
GMAIL.COM</a>><br>
Subject: using mri3dx<br><br>hello all,<br><br>I am trying to show some act=
ivations in the spm5 template in mri3dx<br>(template spm5 command) but the =
activations appear more higher than the<br>template. Is necessary any conve=
rsion to show the activations?<br>
<br>I think that maybe the mri3dX uses tailarach space, I can convert my<br=
>normalized activations to tailarach space?<br><br>Thanks in advance<br><br=
>------------------------------<br><br>End of SPM Digest - 6 May 2011 (#201=
1-133)<br>
******************************************<br></blockquote></div><br><br cl=
ear=3D"all"><br>-- <br>Jadzia Jagiellowicz<br>Doctoral Candidate <br>Psycho=
logy Department B-207<br>Stony Brook University, <br>Stony Brook, NY 11794-=
2500 USA<br>
<a href=3D"http://www.psychology.stonybrook.edu/aronlab-/">http://www.psych=
ology.stonybrook.edu/aronlab-/</a><br><br>"The brave shall inherit the=
earth."<br>
--005045015ed170643e04a35b9c79--
=========================================================================
Date: Mon, 16 May 2011 14:54:28 +0800
Reply-To: min xu <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: min xu <[log in to unmask]>
Subject: Re: SPM2 Versus SPM8
Comments: To: Thomas Nichols <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=001636e0b7ac7bb3ac04a35f2038
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--001636e0b7ac7bb3ac04a35f2038
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Dear Tom,
Thanks a lot for you kind reply. Actually, the topoFDR in spm_defaults has
been set to 0 in my analysis.
Besides, comparisons between uncorrected results of these two versions of
spm also reveal large differences. I also try to analyze auditory fMRI
sample data (http://www.fil.ion.ucl.ac.uk/spm/data/auditory/<http://www.fi=
l.ion.ucl.ac.uk/spm/data/auditory/>)
following steps in spm 8 manual with both spm2 and spm8. There's also much
more activation for spm2 than spm8 for both uncorrected and FDR05 corrected
(topoFDR has been set to 0) results. I am wondering whether there's any
other factor or defaut setting affecting results of these two versions of
spm.
Thank you very much for your help!
Best regards,
Xu Min
On Sun, May 15, 2011 at 5:49 AM, Thomas Nichols
<[log in to unmask]>wrote:
> Dear Min,
>
> In SPM8 FDR topological inference was introduced, and voxel-wise
> FDR inference hidden. Topological inference means inference on peaks and
> clusters; voxel-wise inference is based on every individual voxel in the
> image (instead of spatial features of the image). Thus "Topological FDR"
> means inference on clusters based on cluster size (or local peaks based o=
n
> peak height), controlling the fraction of false positive clusters among a=
ll
> clusters (or false positive peaks among all peaks) on average, over many
> experiments.
>
> While topological FDR results may be easier to interpret, in my experienc=
e
> it is is generally not very sensitivity and yields similar results to
> FWE-corrected inferences. This would explain your reduction in sensitivi=
ty
> moving from SPM2 to SPM8.
>
> If you would like to use voxel-wise FDR in SPM8, edit spm_defaults,
> changing "topoFDR" line to read
>
> defaults.stats.topoFDR =3D 0;
>
> (quit and re-start SPM to take effect).
>
> For more on this see references below.
>
> -Tom
>
> Chumbley, J., Worsley, K., Flandin, G., & Friston, K. (2010). Topologica=
l
> FDR for neuroimaging. *NeuroImage*, *49*(4), 3057-64. doi:
> 10.1016/j.neuroimage.2009.10.090.
>
> Chumbley, J. R., & Friston, K. J. (2009). False discovery rate revisited:
> FDR and topological inference using Gaussian random fields. *Neuroimage*,
> *44*(1), 62=9670. doi: 10.1016/j.neuroimage.2008.05.021.
>
> On Tue, May 10, 2011 at 11:27 AM, Min <[log in to unmask]> wrote:
>
>> Dear SPM's users,
>>
>> I ran spm2 and spm8, respectively, for the same set of fMRI data.
>> However, though I followed the same steps for the two versions of spm,
>> there are considerable differences in the results. With spm8, no
>> suprathreshold clusters were found with fdr(0.05) corrected, while with =
spm
>> 2, more than 8 clusters survive the threshold (T values of height thresh=
old
>> are nearly the same for the two analysis).
>>
>> I am unsure how to explain such a big difference between the results fro=
m
>> two versions of spm.
>>
>> I will be grateful for any help!
>>
>> Sincerely,
>> Min
>>
>
>
>
> --
> ____________________________________________
> Thomas Nichols, PhD
> Principal Research Fellow, Head of Neuroimaging Statistics
> Department of Statistics & Warwick Manufacturing Group
> University of Warwick
> Coventry CV4 7AL
> United Kingdom
>
> Email: [log in to unmask]
> Phone, Stats: +44 24761 51086, WMG: +44 24761 50752
> Fax: +44 24 7652 4532
>
>
--001636e0b7ac7bb3ac04a35f2038
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<div>Dear Tom,</div>
<div>=A0</div>
<div>Thanks a lot for you kind reply. Actually, the topoFDR in spm_defaults=
has been set to 0=A0in=A0my analysis.</div>
<div>=A0</div>
<div>Besides, comparisons between uncorrected results of these two versions=
of spm=A0also reveal large differences. I also try to=A0analyze auditory f=
MRI sample data=A0 <a href=3D"http://www.fil.ion.ucl.ac.uk/spm/data/auditor=
y/">(http://www.fil.ion.ucl.ac.uk/spm/data/auditory/</a>) following steps i=
n spm 8 manual=A0with both spm2 and spm8. There's also much more activa=
tion for spm2 than spm8 for both uncorrected and FDR05 corrected (topoFDR=
=A0has=A0been set to 0) results. I am wondering whether there's any oth=
er factor or defaut setting affecting results of these two versions of spm.=
</div>
<div>=A0</div>
<div>Thank you very much for your help!</div>
<div>=A0</div>
<div>Best regards,</div>
<div>Xu Min</div>
<div><font face=3D"Courier New"></font><br>=A0</div>
<div class=3D"gmail_quote">On Sun, May 15, 2011 at 5:49 AM, Thomas Nichols =
<span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">t.e.nich=
[log in to unmask]</a>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"PADDING-LEFT: 1ex; MARGIN: 0px 0=
px 0px 0.8ex; BORDER-LEFT: #ccc 1px solid">Dear Min,=20
<div><br></div>
<div>In SPM8 FDR topological inference was introduced, and voxel-wise FDR=
=A0inference=A0hidden. =A0Topological inference means inference on peaks an=
d clusters; voxel-wise inference is based on every individual voxel in the =
image (instead of spatial features of the image). =A0Thus "Topological=
FDR" means inference on clusters based on cluster size (or local peak=
s based on peak height), controlling the fraction of false positive=A0clust=
ers among all clusters=A0(or false positive peaks among all peaks) on avera=
ge, over many experiments.</div>
<div><br></div>
<div>While=A0topological=A0FDR results may be easier to interpret, in my ex=
perience it is is generally not very sensitivity and=A0yields=A0similar res=
ults to FWE-corrected inferences. =A0This would explain your reduction in s=
ensitivity moving from SPM2 to SPM8.</div>
<div><br></div>
<div>If you would like to use voxel-wise FDR in SPM8, edit spm_defaults, ch=
anging "topoFDR" line to read</div>
<blockquote style=3D"BORDER-RIGHT: medium none; PADDING-RIGHT: 0px; BORDER-=
TOP: medium none; PADDING-LEFT: 0px; PADDING-BOTTOM: 0px; MARGIN: 0px 0px 0=
px 40px; BORDER-LEFT: medium none; PADDING-TOP: 0px; BORDER-BOTTOM: medium =
none">
<div>
<div><font face=3D"'courier new', monospace">defaults.stats.topoFDR=
=A0 =A0 =A0=3D 0;</font></div></div></blockquote>
<div>(quit and re-start SPM to take effect).</div>
<div><br></div>
<div>For more on this see references below.</div>
<div><br></div>
<div>-Tom</div>
<div><br></div>
<div>
<p style=3D"MARGIN-LEFT: 24pt">Chumbley, J., Worsley, K., Flandin, G., &=
; Friston, K. (2010). Topological FDR for neuroimaging. <i>NeuroImage</i>, =
<i>49</i>(4), 3057-64. doi: 10.1016/j.neuroimage.2009.10.090.</p>
<p style=3D"MARGIN-LEFT: 24pt">Chumbley, J. R., & Friston, K. J. (2009)=
. False discovery rate revisited: FDR and topological inference using Gauss=
ian random fields. <i>Neuroimage</i>, <i>44</i>(1), 62=9670. doi: 10.1016/j=
.neuroimage.2008.05.021.</p>
</div>
<div>
<div>
<div></div>
<div class=3D"h5"><br>
<div class=3D"gmail_quote">On Tue, May 10, 2011 at 11:27 AM, Min <span dir=
=3D"ltr"><<a href=3D"mailto:[log in to unmask]" target=3D"_blank">minxu86=
@gmail.com</a>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"PADDING-LEFT: 1ex; MARGIN: 0px 0=
px 0px 0.8ex; BORDER-LEFT: #ccc 1px solid">Dear SPM's users,<br><br>I r=
an spm2 and spm8, respectively, for the same set of fMRI data. =A0However, =
though I followed the same steps for the two versions of spm, there are con=
siderable differences in the results. =A0With spm8, no suprathreshold clust=
ers were found with fdr(0.05) corrected, while with spm 2, more than 8 clus=
ters survive the threshold (T values of height threshold are nearly the sam=
e for the two analysis).<br>
<br>I am unsure how to explain such a big difference between the results fr=
om two versions of spm.<br><br>I will be grateful for any help!<br><br>Sinc=
erely,<br><font color=3D"#888888">Min<br></font></blockquote></div><br><br =
clear=3D"all">
<br></div></div>-- <br>____________________________________________<br>Thom=
as Nichols, PhD<br>Principal Research Fellow, Head of Neuroimaging Statisti=
cs<br>Department of Statistics & Warwick Manufacturing Group<br>Univers=
ity of Warwick<br>
Coventry=A0 CV4 7AL<br>United Kingdom<br><br>Email: <a href=3D"mailto:t.e.n=
[log in to unmask]" target=3D"_blank">[log in to unmask]</a><br>Ph=
one, Stats: +44 24761 51086, WMG: +44 24761 50752<br>Fax:=A0 +44 24 7652 45=
32<br>
<br></div></blockquote></div><br>
--001636e0b7ac7bb3ac04a35f2038--
=========================================================================
Date: Mon, 16 May 2011 10:06:29 +0200
Reply-To: Urs Bachofner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Urs Bachofner <[log in to unmask]>
Subject: Re-referencing of EEG-Data
Comments: To: [log in to unmask]
Content-Type: multipart/alternative;
boundary="========GMXBoundary71961305533189851811"
MIME-Version: 1.0
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--========GMXBoundary71961305533189851811
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I have a question regarding the concept of EEG data Re-referencing in Spm=
8.
The way I see it, re-referencing is a very important step prior to Source=
=20
Analysis. To get useful data, the Signals should be re-referenced to=20
average.=20
According to the SPM8 Manual P. 110 we can use spm_eeg_montage to do this=
.=20
The data I'd like to process is recorded with a 128-channel EEG-net with=20
the reference electrode at CZ.=20
According to the SPM8 Manual, for average reference the matrix should hav=
e=20
(N-1)/N at the diagonal and -1/N elsewhere.
In my case this results in 0.9921875 at the diagonal and -0.0078125=20
elsewhere.
Two questions:
1. These numbers are so close to the original matrix (1 at diagonal and 0=
=20
elsewhere) which is said to not change anything. Is this matrix correct?
2. Since electrodes that are closer to the reference (in this case CZ) ha=
ve=20
a higher amplitude recorded, shouldn't such electrodes be weighted=20
differently than electrodes that are more distant to CZ? Am I missing the=
=20
point here?
And finally, besides Filtering, epoching, Artefact Detection (removing ba=
d=20
channels and bad trials), Re-referencing, and baseline correction are the=
re=20
other preprocessing steps that are necessary to get good data from my=20
evoked potentials? And is there a certain order in which these steps shou=
ld=20
be executed?
Thank you very much for you help.
=20
=C2=A0 =20
=20
=20
--=20
NEU: FreePhone - kostenlos mobil telefonieren und surfen! =09
Jetzt informieren: http://www.gmx.net/de/go/freephone
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<html>
<head>
<title></title>
<style type=3D"text/css" media=3D"screen">
body {font-family: verdana, arial, helvetica, sans-serif;font-size: 12px;pa=
dding: 5px;margin: 0;background-color: #FFF;}
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blockquote {margin-left: 5px;}
div.signature {color: #666;font-size: 0.9em;}
</style>
</head>
<body>
<br /><br />I have a question regarding the concept of EEG data Re-=
referencing in Spm8.<br />The way I see it, re-referencing is a very import=
ant step prior to Source Analysis. To get useful data, the Signals should b=
e re-referenced to average. <br />According to the SPM8 Manual P. 110 we ca=
n use spm_eeg_montage to do this. <br /><br />The data I'd like to process =
is recorded with a 128-channel EEG-net with the reference electrode at CZ. =
<br />According to the SPM8 Manual, for average reference the matrix should=
have (N-1)/N at the diagonal and -1/N elsewhere.<br />In my case this resu=
lts in 0.9921875 at the diagonal and -0.0078125 elsewhere.<br /><br />Two q=
uestions:<br />1. These numbers are so close to the original matrix (1 at d=
iagonal and 0 elsewhere) which is said to not change anything. Is this matr=
ix correct?<br /><br />2. Since electrodes that are closer to the reference=
(in this case CZ) have a higher amplitude recorded, shouldn't such electro=
des be weighted differently than electrodes that are more distant to CZ? Am=
I missing the point here?<br /><br /><br />And finally, besides Filtering,=
epoching, Artefact Detection (removing bad channels and bad trials), Re-re=
ferencing, and baseline correction are there other preprocessing steps that=
are necessary to get good data from my evoked potentials? And is there a c=
ertain order in which these steps should be executed?<br /><br />Thank you =
very much for you help.<br /><br /><br /><br /><br /><br /><br /><br /><br =
/><br />
<table width=3D"80" cellspacing=3D"0" cellpadding=3D"0" border=3D"0=
" style=3D"border-collapse: collapse; width: 60pt;" x:str=3D"">
<col width=3D"80" style=3D"width: 60pt;"></col>
<tr height=3D"17" style=3D"height: 12.75pt;">
<td height=3D"17" width=3D"80" align=3D"right" x:num=3D"-7.=
8125E-3" style=3D"height: 12.75pt; width: 60pt;"> </td>
</tr>
</table>
<br />
<div class=3D"signature"><br /><br /><br />-- <br />NEU: FreePhone - ko=
stenlos mobil telefonieren und surfen! <br />Jetzt informieren: http://ww=
w.gmx.net/de/go/freephone</div></body>
</html>
--========GMXBoundary71961305533189851811--
=========================================================================
Date: Mon, 16 May 2011 17:13:18 +0800
Reply-To: =?GBK?B?t8nE8Q==?= <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?GBK?B?t8nE8Q==?= <[log in to unmask]>
Subject: Re: Batch problem--3D Source Reconstruction
Comments: To: Vladimir Litvak <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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O0NlbnRlciZuYnNwO2ZvciZuYnNwO0xlYXJuaW5nJm5ic3A7U2NpZW5jZSw8QlI+Jmd0OyZndDsm
Z3Q7Jmd0OyZuYnNwO1NvdXRoZWFzdCZuYnNwO1VuaXZlcnNpdHk8QlI+Jmd0OyZndDsmZ3Q7Jmd0
OyZuYnNwOzImbmJzcDtTaSZuYnNwO1BhaSZuYnNwO0xvdSZuYnNwOywmbmJzcDtOYW5qaW5nLCZu
YnNwOzIxMDA5NiwmbmJzcDtQLlIuQ2hpbmE8QlI+Jmd0OyZndDsmZ3Q7Jmd0OzxCUj4mZ3Q7Jmd0
OyZndDsmZ3Q7PEJSPiZndDsmZ3Q7PEJSPiZndDsmZ3Q7PEJSPiZndDsmZ3Q7PEJSPiZndDsmZ3Q7
PEJSPiZndDsmZ3Q7PEJSPjwvRElWPjxicj48YnI+PHNwYW4gdGl0bGU9Im5ldGVhc2Vmb290ZXIi
PjxzcGFuIGlkPSJuZXRlYXNlX21haWxfZm9vdGVyIj48L3NwYW4+PC9zcGFuPg==
------=_Part_130052_17267360.1305537198329--
=========================================================================
Date: Mon, 16 May 2011 11:48:56 +0200
Reply-To: Lars Meyer <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Lars Meyer <[log in to unmask]>
Subject: dipole waveforms |=?iso-8859-1?Q?=A0units?=
Content-Type: text/plain; charset=utf-8
Content-Transfer-Encoding: quoted-printable
Mime-Version: 1.0 (Apple Message framework v1084)
Message-ID: <[log in to unmask]>
dear all,
i am using spm_eeg_dipole_waveforms.m to retrieve dipole timecourses for =
two dipole priors in a vb-ecd- localisation. everything works fine, so =
no worries there, but i was wondering on what the units of the dipole =
amplitudes are=E2=80=A6 i remember some older post on the exact same =
question, have talked to the asker, but it seems there is no answer yet.
or is there a working solution from the programmers of the above =
function?
thanks in advance, and all best,
l.
Lars Meyer
Max Planck Institute for Human Cognitive & Brain Sciences
Department of Neuropsychology
Stephanstra=EF=AC=82e 1a
04103 Leipzig | Germany
Office | +49 341 99 40 22 66
Mail | [log in to unmask]
Web | www.cbs.mpg.de/~lmeyer
=========================================================================
Date: Mon, 16 May 2011 17:57:36 +0800
Reply-To: Syu-Jyun Peng <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Syu-JyunPeng <[log in to unmask]>
Subject: Re: produce T1W and T2W template
Comments: To: JohnAshburner <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative;
boundary="----=_Part_348646_1661673744.1305539856561"
Message-ID: <1767218365.1305539856983.JavaMail.nobody@sg2000-ap-1>
------=_Part_348646_1661673744.1305539856561
Content-Type: text/plain;charset=utf-8
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<div>Dear Sir<br /><br />Thank you very much for your messages.<br /><br />We can&nbsp;obtain&nbsp;information how to produce template&nbsp;in chapter 41.<br /><br />We would like obtain the T1W and T2W template, but the chaper 41 show the WM and GM template.<br /><br />How to get the T1W and T2W template using SPM?<br /><br />It would be greatly appreciated, if you could look&nbsp; into this for us.<br /><br />Best regards,<br /><br />SJ<br /><br /><br /></div>
<div id="HiNet_separatrix"></div>
<div id="HiNet_advert"></div>
<div></div>
<div>&gt;&gt;&gt;&gt;&gt; Original Message &lt;&lt;&lt;&lt;&lt;</div>
<div><b>From:</b> <a href="mailto:[log in to unmask]">JohnAshburner</a></div>
<div><b>To:</b> <a href="mailto:[log in to unmask]">[log in to unmask]</a></div>
<div><b>Sent:</b> Thu,12 May 2011 18:51:43 Asia/Taipei</div>
<div><b>Subject:</b> Re: [SPM] Consult</div>
<div>
<pre>Chapter 41 (Using DARTEL) of the spm8 manual would be a good place to
begin. You can find it in spm8/man/manual.pdf
Best regards,
-John
2011/5/12 Syu-JyunPeng &lt;[log in to unmask]&gt;:
&gt;
&gt; Dear Sir
&gt;
&gt; I'm a&nbsp;EE PhD student in Taiwan.
&gt;
&gt; I have a question.
&gt;
&gt; I have 20 sets of control subject&nbsp;SPGR MRI.
&gt;
&gt; How could I use SPM&nbsp; software to&nbsp;obtain template&nbsp;like as&nbsp;the attached file?
&gt;
&gt; Could you&nbsp;give the&nbsp;instructions step by step for me?
&gt;
&gt; It would be greatly appreciated, if you could look&nbsp; into this for us.
&gt;
&gt; Thank you.
&gt;
&gt; Best regards,
&gt;
&gt; Syu-Jyun Peng
</pre>
</div>
------=_Part_348646_1661673744.1305539856561
Content-Type: text/html;charset=utf-8
Content-Transfer-Encoding: 7bit
<div>Dear Sir<br /><br />Thank you very much for your messages.<br /><br />We can obtain information how to produce template in chapter 41.<br /><br />We would like obtain the T1W and T2W template, but the chaper 41 show the WM and GM template.<br /><br />How to get the T1W and T2W template using SPM?<br /><br />It would be greatly appreciated, if you could look into this for us.<br /><br />Best regards,<br /><br />SJ<br /><br /><br /></div>
<div id="HiNet_separatrix"></div>
<div id="HiNet_advert"></div>
<div></div>
<div>>>>>> Original Message <<<<<</div>
<div><b>From:</b> <a href="mailto:[log in to unmask]">JohnAshburner</a></div>
<div><b>To:</b> <a href="mailto:[log in to unmask]">[log in to unmask]</a></div>
<div><b>Sent:</b> Thu,12 May 2011 18:51:43 Asia/Taipei</div>
<div><b>Subject:</b> Re: [SPM] Consult</div>
<div>
<pre>Chapter 41 (Using DARTEL) of the spm8 manual would be a good place to
begin. You can find it in spm8/man/manual.pdf
Best regards,
-John
2011/5/12 Syu-JyunPeng <[log in to unmask]>:
>
> Dear Sir
>
> I'm a EE PhD student in Taiwan.
>
> I have a question.
>
> I have 20 sets of control subject SPGR MRI.
>
> How could I use SPM software to obtain template like as the attached file?
>
> Could you give the instructions step by step for me?
>
> It would be greatly appreciated, if you could look into this for us.
>
> Thank you.
>
> Best regards,
>
> Syu-Jyun Peng
</pre>
</div>
------=_Part_348646_1661673744.1305539856561--
=========================================================================
Date: Mon, 16 May 2011 12:04:19 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Batch problem--3D Source Reconstruction
Comments: To: =?UTF-8?B?6aOe6bif?= <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Mime-Version: 1.0 (iPad Mail 8C148)
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Message-ID: <4553222900002898154@unknownmsgid>
Dear Haoran,
On 16 May 2011, at 10:13, "=E9=A3=9E=E9=B8=9F" <[log in to unmask]> wrote=
:
> Dear Vladimir,
> =E3=80=80=E3=80=80Your guess was right. I really couldn't do 3D sources r=
econstruction of that data by GUI. It reminded me ''checkmeeg: data scale m=
issing, assigning default
> checkmeeg: no fiducials are defined''. Then I did preprocess steps again,=
and found that I couldn't obtain the fiducials automatically(when I finish=
ed Converting step). I checked the other datasets, luckily, they didn't hav=
e this problem. I guess there must be some wrongs of my original dataset (o=
nly that one), right ?
right
> =E3=80=80=E3=80=80As for reconstruction batch problem, with the latest ve=
rsion of spm8(4029) and normal dataset, I can do reconstruction by that sav=
ed "renconstruction_batch" successfully. Thus, the problems related to reco=
nstruction batch that I confronted previously may result from the different=
versions of spm8.
> By the way, in ''MEEG head model specification> EEG head modle'' m=
odule, must I specify the ''EEG head modle'' if I just process MEG dataset?
One peculiarity of batch is that when you build the configuration you
can't use information from the dataset which only becomes available
when you run the batch. In particular you can't know if the dataset in
question is EEG or MEG. So don't worry about the EEG head model. If
your dataset is MEG it will be ignored.
Best,
Vladimir
> =E3=80=80=E3=80=80Thank you very much for helping me solve these tiny pro=
blems!
>
> =E3=80=80=E3=80=80Haoran.
>
>
> At 2011-05-16 06:38:23=EF=BC=8C"Vladimir Litvak" <[log in to unmask]
om> wrote:
>
> >Dear Haoran,
> >
> >The problem seems to be not in the batch but in your MEG data (or was
> >it EEG?). There are no valid fiducials in that dataset. Could you
> >perform source reconstruction using the GUI? I'd be surprised if you
> >could. So we need to focus on how to get fiducials into your dataset
> >and for that you need to tell me more about where that data comes
> >from.
> >
> >Best,
> >
> >Vladimir
> >
> >2011/5/15 =E9=A3=9E=E9=B8=9F <[log in to unmask]>:
> >> Dear Vladimir,
> >> =E3=80=80=E3=80=80I tried again with the latest version of spm8(4029),=
the previous problem(
> >> template=3D1) disappeared. But this time, I confronted a new problem. =
It
> >> reminded me "No executable modules, but still unresolved dependencies =
or
> >> incomplete module inputs." But I don't know where the problems are. Co=
uld
> >> you help me see my reconstruction_batch.mat and give me some advice ? =
Thanks
> >> a lot.
> >>
> >> Haoran.
> >>
> >> These code appears in the matlab command window when I ran the =
batch:
> >> SPM8: spm_eeg_inv_mesh_ui (v4027) 11:09:13 - 15/05/20=
11
> >> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> >> template: 0
> >> sMRI: 'D:\Processed\DP01\sKEYAN-0002-00000-000001-01.img,1'
> >> def: 'D:\Processed\DP01\y_sKEYAN-0002-00000-000001-01.nii'
> >> Affine: [4x4 double]
> >> Msize: 2
> >> tess_mni: [1x1 struct]
> >> tess_ctx:
> >> 'D:\Processed\DP01\sKEYAN-0002-00000-000001-01cortex_8196.surf.gii'
> >> tess_scalp:
> >> 'D:\Processed\DP01\sKEYAN-0002-00000-000001-01scalp_2562.surf.gii'
> >> tess_oskull:
> >> 'D:\Processed\DP01\sKEYAN-0002-00000-000001-01oskull_2562.surf.gii'
> >> tess_iskull:
> >> 'D:\Processed\DP01\sKEYAN-0002-00000-000001-01iskull_2562.surf.gii'
> >> fid: [1x1 struct]
> >> Failed 'M/EEG head model specification'
> >> Reference to non-existent field 'fid'.
> >> In file "C:\Program Files\MATLAB\spm8new\config\spm_cfg_eeg_inv_headmo=
del.m"
> >> (v4118), function "specify_headmodel" at line 209.
> >> No executable modules, but still unresolved dependencies or incomplete
> >> module inputs.
> >> The following modules did not run:
> >> Failed: M/EEG head model specification
> >> Skipped: M/EEG source inversion
> >> Skipped: M/EEG inversion results
> >>
> >>
> >> At 2011-05-13 22:06:06=EF=BC=8C"Vladimir Litvak" <litvak.vladimir@gmai=
l.com
> >>> wrote:
> >>
> >>>Dear Haoran,
> >>>
> >>>I tried and everything works fine for me. Make sure your SPM version
> >>>is up to date and if you can't make it work, send me your saved batch
> >>>and I'll take another look.
> >>>
> >>>Best,
> >>>
> >>>Vladimir
> >>>
> >>>2011/5/10 =E9=A3=9E=E9=B8=9F <[log in to unmask]>:
> >>>> Dear SPM's users,
> >>>> =E3=80=80=E3=80=80Have you ever used batch interface to do 3D source=
reconstruction for
> >>>> EEG/MEG data? I choosed three separate modules "M/EEG head model
> >>>> specification" "M/EEG source inversion" and "M/EEG inversion results=
" so as
> >>>> to reconstruct the sources. In the "M/EEG head model specification" =
module,
> >>>> I specified ''Meshes<Meshes source<individual structual image'' and =
then
> >>>> selected a mri file named "sDP74-0003-00000-000001-01.img,1". When =
all was
> >>>> ready and then I ran the batch, however, I found that it din't excut=
ed the
> >>>> specified structual image ( as you can see below 'template=3D1') and=
the
> >>>> matlab command window appeared those:
> >>>>
> >>>> SPM8: spm_eeg_inv_mesh_ui (v3731) 21:39:06 - 09/05/=
2011
> >>>> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> >>>> template: 1
> >>>> Affine: [4x4 double]
> >>>> sMRI: 'C:\Program
> >>>> Files\MATLAB\toolbox\spm8\canonical\single_subj_T1.nii'
> >>>> Msize: 2
> >>>> tess_mni: [1x1 struct]
> >>>> tess_ctx: 'C:\Program
> >>>> Files\MATLAB\toolbox\spm8\canonical\cortex_8196.surf.gii'
> >>>> tess_scalp: 'C:\Program
> >>>> Files\MATLAB\toolbox\spm8\canonical\scalp_2562.surf.gii'
> >>>> tess_oskull: 'C:\Program
> >>>> Files\MATLAB\toolbox\spm8\canonical\oskull_2562.surf.gii'
> >>>> tess_iskull: 'C:\Program
> >>>> Files\MATLAB\toolbox\spm8\canonical\iskull_2562.surf.gii'
> >>>> fid: [1x1 struct]
> >>>>
> >>>> =E3=80=80I didn't understand why. Anyone who knows the reason ? Th=
anks very much
> >>>> for any help !
> >>>>
> >>>> --
> >>>> Haoran LI (MS)
> >>>> Brain Imaging Lab,
> >>>> Research Center for Learning Science,
> >>>> Southeast University
> >>>> 2 Si Pai Lou , Nanjing, 210096, P.R.China
> >>>>
> >>>>
> >>
> >>
> >>
> >>
> >>
>
>
=========================================================================
Date: Mon, 16 May 2011 14:33:37 +0100
Reply-To: Ralph Schnitker <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Ralph Schnitker <[log in to unmask]>
Subject: Open position as a Leader of Core Facility for Brain Imaging in
Aachen Germany
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Leader of Core Facility for Brain Imaging in Aachen Germany
=20
The Core Facility "Brain Imaging" at the Interdisciplinary Centre for Cli=
nical=20
Research (IZKF-Aachen) of the RWTH Aachen University, Germany, is seeking=
for a new technical and operative leader (1.0 TVL 14 for 3 years). We ar=
e looking for a researcher at the postdoctoral level with a strong backgr=
ound in imaging neuroscience. The position requires training in cognitive=
neuroscience, computer sciences or related areas as well as experience i=
n functional imaging data analysis (e.g. SPM5/8) and in designing fMRI ex=
periments.=20
The successful candidate will not only coordinate and supervise the inter=
disciplinary team in cooperation with the methodical leader of the Core F=
acility but also develop own research ideas and projects. The Core Facili=
ty supports researchers from the medical faculty and affiliated institute=
s in conducting brain imaging research projects. It hosts a large computi=
ng facility, offers single and group trainings and carries out the MRI ac=
quisitions. Beside these support tasks the member will have access to one=
3T and two 1.5T Philips Achieva and a 3T Siemens Trio MR scanners. Mult=
imodal approaches encompassing PET, PET-CT, MEG, TMS or tDCS are encourag=
ed. Own research projects are required and a progress toward habilitation=
is possible.=20
The appointment will be for 3 years with an opportunity of prolongation f=
or another 3 years. The position has to be filled 1st July 2011 or as soo=
n as possible thereafter.
Qualified women are explicitly invited to apply and handicapped candidate=
s with equal qualification will be given preference.
Do not hesitate to contact one of the three consultants of the Core Facil=
ity, Profs. Klaus Mathiak ([log in to unmask]), Klaus Willmes (willmes@=
neuropsych.rwth-aachen.de) or Martin Wiesmann ([log in to unmask]). Fo=
r further information visit our website at www.izkf.rwth-aachen.de .
Applications (English or German) must include a full CV and name and addr=
ess of two references and should be submitted until 31th of May by mail o=
r email to:
[log in to unmask]
=========================================================================
Date: Mon, 16 May 2011 17:32:30 +0100
Reply-To: Mike Sugarman <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Mike Sugarman <[log in to unmask]>
Subject: Model Estimation
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Hello SPM experts,
I'm running a flexible factorial design with a library of PET scans. My d=
esign will set up properly, however when I attempt to estimate the model =
sometimes I get the error message
Warning: Matrix is close to singular or badly scaled.
Results may be inaccurate. RCOND =3D -1.000000e+00.=20
> In spm_inv at 22
In spm_reml at 119
In spm_spm at 860
In spm_getSPM at 235
In spm_results_ui at 263
And this message will repeat dozens of times. When I remove a few subject=
s, the problem typically resolves. Can anybody tell me what might be the =
issue with the scans that are causing this problem?
Thanks,
-Mike Sugarman
=========================================================================
Date: Mon, 16 May 2011 11:18:40 -0700
Reply-To: LiuKarl <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: LiuKarl <[log in to unmask]>
Subject: small volume correction
Content-Type: multipart/alternative;
boundary="_ccc1b30e-71bf-43eb-b4bc-0e0bf67c0598_"
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
--_ccc1b30e-71bf-43eb-b4bc-0e0bf67c0598_
Content-Type: text/plain; charset="gb2312"
Content-Transfer-Encoding: 8bit
Hello, SPM-users
I have a question of small volume correction. Many published paper reported (p = 0.05, svc). Is this p valued uncorrected or corrected by standard? Should FDR be used in SVC? (When you click the SVC button, there is no option for correction at all. So there correction is from when you click the Results button and the option of p value adjustment to control: FWE FDR none )
How is the svc different from WFU ROI analysis? When you start the pickatlas from toolbox and then click the Results button, it will still ask the the option of p value adjustment to control: FWE FDR none.
Karl
--_ccc1b30e-71bf-43eb-b4bc-0e0bf67c0598_
Content-Type: text/html; charset="gb2312"
Content-Transfer-Encoding: quoted-printable
X-MIME-Autoconverted: from 8bit to quoted-printable by bifur.jiscmail.ac.uk id p4GIIfEM018106
<html>
<head>
<style><!--
.hmmessage P
{
margin:0px;
padding:0px
}
body.hmmessage
{
font-size: 10pt;
font-family:=CE=A2=C8=ED=D1=C5=BA=DA
}
--></style>
</head>
<body class=3D'hmmessage'>
<SPAN style=3D"FONT-SIZE: 12pt; FONT-FAMILY: 'Times New Roman'; mso-farea=
st-font-family: SimSun; mso-ansi-language: EN-US; mso-fareast-language: Z=
H-CN; mso-bidi-language: AR-SA">
<P class=3DMsoNormal style=3D"MARGIN: 0in 0in 0pt">Hello, SPM-users</P>
<P class=3DMsoNormal style=3D"MARGIN: 0in 0in 0pt"><?xml:namespace prefix=
=3D o ns =3D "urn:schemas-microsoft-com:office:office" /><o:p> </o:=
p></P>
<P class=3DMsoNormal style=3D"MARGIN: 0in 0in 0pt">I have a question of s=
mall volume correction. Many published paper reported (p =3D 0.05,<SPAN s=
tyle=3D"mso-spacerun: yes"> </SPAN>svc). Is this p valued uncorrect=
ed or corrected by standard? Should FDR be used in SVC? (When you click t=
he SVC button, there is no option for correction at all. So there correct=
ion is from when you click the Results button and the option of p value a=
djustment to control: FWE FDR none )</P>
<P class=3DMsoNormal style=3D"MARGIN: 0in 0in 0pt"><o:p> </o:p></P>
<P class=3DMsoNormal style=3D"MARGIN: 0in 0in 0pt">How is the svc differe=
nt from WFU ROI analysis? <SPAN style=3D"mso-spacerun: yes"> </SPAN>=
When you start the pickatlas from toolbox and then click the Results butt=
on, it will still ask the the option of p value adjustment to control: FW=
E FDR none. </P>
<BR>
<BR>
Karl</SPAN><BR> </body>
</html>
--_ccc1b30e-71bf-43eb-b4bc-0e0bf67c0598_--
=========================================================================
Date: Mon, 16 May 2011 22:43:30 +0100
Reply-To: Rebecca Ray <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Rebecca Ray <[log in to unmask]>
Subject: slicetiming difficulty
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
I have successfully preprocessed all of my data with the exception of thi=
s one subject. Our TR is 2.6 but it changes it to 2.7 and gives the foll=
owing error message:=20=20
SPM8: spm_slice_timing (v3756) 16:27:38 - 16/05/2011
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
Your TR is 2.7
Failed 'Slice Timing'
Improper assignment with rectangular empty matrix.
In file "/Applications/spm8/spm_slice_timing.m" (v3756), function "spm_sl=
ice_timing" at line 232.
In file "/Applications/spm8/config/spm_run_st.m" (v2312), function "spm_r=
un_st" at line 25.
I have spoken with our physicist who does not use SPM, and he does not th=
ink it is a problem with the data.
I can display the data prior to slicetiming but not after. After it appe=
ars to have spit out files but gives an error when you try to display the=
se images:
Running 'Display Image'
Image "/Users/rebeccaray/Documents/UW_Projects/Vivek/Data_Processing/Raw_=
Data/022_S2/Functionals/Emotion/scan2/agvscan0329.img" can not be resampl=
ed
Image "/Users/rebeccaray/Documents/UW_Projects/Vivek/Data_Processing/Raw_=
Data/022_S2/Functionals/Emotion/scan2/agvscan0329.img" can not be resampl=
ed
Done 'Display Image'
Done
Any advice would be awesome!
=========================================================================
Date: Mon, 16 May 2011 23:06:34 +0100
Reply-To: Thomas Nichols <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Thomas Nichols <[log in to unmask]>
Subject: Re: Model Estimation
Comments: To: Mike Sugarman <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=bcaec5485c4e5d9dcc04a36bdee7
Message-ID: <[log in to unmask]>
--bcaec5485c4e5d9dcc04a36bdee7
Content-Type: text/plain; charset=ISO-8859-1
Dear Mike,
I have seen this before when the input images have dramatically different
scale. If, say, some of the images are 1000-times more intense than the
others, SPM's ReML will then scale down those images (depending on the
design and how the badly scaled images are arranged relative to the design
factors).
Try looking at the images all at once with the same color scale with
CheckReg. Alternatively look at diag(SPM.xVi.V) (the SPM variable in
SPM.mat of a troublesome analysis); these values should all be roughly the
same or within an order of magnitude. If some are 100x or 1000x different
from the others, this would explain the problem (and suggests maybe
scalefactor artifacts would explain the differences).
(Are maybe some of the PET images in units of "ECAT" counts, and others in a
fractional rate? ).
-Tom
On Mon, May 16, 2011 at 5:32 PM, Mike Sugarman <[log in to unmask]>wrote:
> Hello SPM experts,
>
> I'm running a flexible factorial design with a library of PET scans. My
> design will set up properly, however when I attempt to estimate the model
> sometimes I get the error message
>
> Warning: Matrix is close to singular or badly scaled.
> Results may be inaccurate. RCOND = -1.000000e+00.
> > In spm_inv at 22
> In spm_reml at 119
> In spm_spm at 860
> In spm_getSPM at 235
> In spm_results_ui at 263
>
> And this message will repeat dozens of times. When I remove a few subjects,
> the problem typically resolves. Can anybody tell me what might be the issue
> with the scans that are causing this problem?
>
> Thanks,
> -Mike Sugarman
>
--
____________________________________________
Thomas Nichols, PhD
Principal Research Fellow, Head of Neuroimaging Statistics
Department of Statistics & Warwick Manufacturing Group
University of Warwick
Coventry CV4 7AL
United Kingdom
Email: [log in to unmask]
Phone, Stats: +44 24761 51086, WMG: +44 24761 50752
Fax: +44 24 7652 4532
--bcaec5485c4e5d9dcc04a36bdee7
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Dear Mike,<div><br></div><div>I have seen this before when the input images=
have dramatically different scale. =A0If, say, some of the images are 1000=
-times more intense than the others, SPM's ReML will then scale down th=
ose images (depending on the design and how the badly scaled images are arr=
anged relative to the design factors).</div>
<div><br></div><div>Try looking at the images all at once with the same col=
or scale with CheckReg. =A0Alternatively look at diag(SPM.xVi.V) (the SPM v=
ariable in SPM.mat of a troublesome analysis); these values should all be r=
oughly the same or within an order of magnitude. =A0If some are 100x or 100=
0x different from the others, this would explain the problem (and suggests =
maybe scalefactor artifacts would explain the differences). =A0</div>
<div><br></div><div>(Are maybe some of the PET images in units of "ECA=
T" counts, and others in a fractional rate? ).</div><div><br></div><di=
v>-Tom</div><div><br></div><div><br><br><div class=3D"gmail_quote">On Mon, =
May 16, 2011 at 5:32 PM, Mike Sugarman <span dir=3D"ltr"><<a href=3D"mai=
lto:[log in to unmask]">[log in to unmask]</a>></span> wrote:<=
br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex;">Hello SPM experts,<br>
<br>
I'm running a flexible factorial design with a library of PET scans. My=
design will set up properly, however when I attempt to estimate the model =
sometimes I get the error message<br>
<br>
Warning: Matrix is close to singular or badly scaled.<br>
=A0 =A0 =A0 =A0 Results may be inaccurate. RCOND =3D -1.000000e+00.<br>
> In spm_inv at 22<br>
=A0In spm_reml at 119<br>
=A0In spm_spm at 860<br>
=A0In spm_getSPM at 235<br>
=A0In spm_results_ui at 263<br>
<br>
And this message will repeat dozens of times. When I remove a few subjects,=
the problem typically resolves. Can anybody tell me what might be the issu=
e with the scans that are causing this problem?<br>
<br>
Thanks,<br>
<font color=3D"#888888">-Mike Sugarman<br>
</font></blockquote></div><br><br clear=3D"all"><br>-- <br>________________=
____________________________<br>Thomas Nichols, PhD<br>Principal Research F=
ellow, Head of Neuroimaging Statistics<br>Department of Statistics & Wa=
rwick Manufacturing Group<br>
University of Warwick<br>Coventry=A0 CV4 7AL<br>United Kingdom<br><br>Email=
: <a href=3D"mailto:[log in to unmask]">[log in to unmask]</a=
><br>Phone, Stats: +44 24761 51086, WMG: +44 24761 50752<br>Fax:=A0 +44 24 =
7652 4532<br>
<br>
</div>
--bcaec5485c4e5d9dcc04a36bdee7--
=========================================================================
Date: Tue, 17 May 2011 09:31:28 +0800
Reply-To: =?GBK?B?t8nE8Q==?= <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?GBK?B?t8nE8Q==?= <[log in to unmask]>
Subject: Re: Batch problem--3D Source Reconstruction
Comments: To: Vladimir Litvak <[log in to unmask]>
In-Reply-To: <4553222900002898154@unknownmsgid>
MIME-Version: 1.0
Content-Type: multipart/alternative;
boundary="----=_Part_13687_12466455.1305595888996"
Message-ID: <1040a0c.1377.12ffb944564.Coremail[log in to unmask]>
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PC9zcGFuPg==
------=_Part_13687_12466455.1305595888996--
=========================================================================
Date: Tue, 17 May 2011 05:10:34 +0100
Reply-To: David Yang <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: David Yang <[log in to unmask]>
Subject: Re: Corregistro PET-T1 with DARTEL
Comments: To: John Ashburner <[log in to unmask]>
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Dear John:
Thanks for your kind and useful reply.
I wanted to make sure my interpretation was right:
Step 1: was done by SPM function: Coreg:estimate and the registration inf=
ormation would be stored in the header of source images (no other output =
would be found)
Step 2 and Step 3:just as routine DARTEL process on T1 images
Step4: as in DARTEL toolbox: normalise to MNI space option and use source=
images (PET) from Step1.
For receptor/transporter binding potential images, I suspected we should =
choose Preserve Amount in Step 4 according to previous discussion:
http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3DSPM;f3f7b65.0901
Furthermore, considering the image features of PET or even SPECT images, =
it might have to smooth such images with large amount (ex 12 mm compared =
to default 8 mm in DARTEL). I wonder if such was suitable if we wanted to=
perform further analysis by BPM that used both VBM and PET/SPECT images =
concurrently as in this subject:
http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3DSPM;dd737de1.1012
Thanks for your help~
Sincerely yours,
David
=========================================================================
Date: Tue, 17 May 2011 11:45:40 +0530
Reply-To: cognitive dept neuro science
<[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: cognitive dept neuro science
<[log in to unmask]>
Subject: SPM 2nd level analysis - reg
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0003255599869246b304a372b321
Message-ID: <[log in to unmask]>
--0003255599869246b304a372b321
Content-Type: text/plain; charset=ISO-8859-1
Dear All,
We are(our team) processing our datas using SPM8. We are able to process
upto first level. We are able to get the activations at the end of first
level result. But we cant further process our second level analysis. Please
help us to process further.
Thanks in advance.
--
Regards,
Cognitive Neurosciences Centre,
Dept of Clinical Psychology,
NIMHANS-Banglore 560 029.
--0003255599869246b304a372b321
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
<div><br clear=3D"all">Dear All,</div>
<div>We are(our team) processing our datas=A0using SPM8. We are able to pro=
cess upto first level. We are able to get the activations at the end of fir=
st level result. But we cant further process our second level analysis. Ple=
ase help us to process further. </div>
<div>=A0</div>
<div>=A0</div>
<div>Thanks in advance.</div>
<div><br>-- <br><br>Regards,<br>Cognitive Neurosciences Centre,<br>Dept of =
Clinical Psychology,<br>NIMHANS-Banglore 560 029.<br><br></div>
--0003255599869246b304a372b321--
=========================================================================
Date: Tue, 17 May 2011 11:59:50 +0530
Reply-To: cognitive dept neuro science
<[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: cognitive dept neuro science
<[log in to unmask]>
Subject: SPM 2nd level analysis-reg
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0016e6d9a16e362e2b04a372e667
Message-ID: <[log in to unmask]>
--0016e6d9a16e362e2b04a372e667
Content-Type: text/plain; charset=ISO-8859-1
Dear All,
We are(our team) processing our datas using SPM8. We are able to process
upto first level. We are able to get the activations at the end of first
level result. But we cant further process our second level analysis. Please
help us to process further.
Thanks in advance.
--
Regards,
Cognitive Neurosciences Centre,
Dept of Clinical Psychology,
NIMHANS-Banglore 560 029.
--0016e6d9a16e362e2b04a372e667
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
<div><br clear=3D"all"><br>Dear All,<br>We are(our team) processing our dat=
as using SPM8. We are able to process upto first level. We are able to get =
the activations at the end of first level result. But we cant further proce=
ss our second level analysis. Please help us to process further. <br>
=A0<br>=A0<br>Thanks in advance.</div>
<div><br>-- <br><br>Regards,<br>Cognitive Neurosciences Centre,<br>Dept of =
Clinical Psychology,<br>NIMHANS-Banglore 560 029.<br><br></div>
--0016e6d9a16e362e2b04a372e667--
=========================================================================
Date: Tue, 17 May 2011 08:08:58 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Time frequency question
Comments: To: Tommy Ng <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
http://en.wikipedia.org/wiki/Decibel
On Tue, May 17, 2011 at 4:50 AM, Tommy Ng <[log in to unmask]> wrote:
> HI Sir
> Sorry to bother you again, I have a basic question regarding TF analysis in
> SPM.
> As instructed in SPM manual, I averaged TF from single data series using the
> option LogR. The ensuing source power maps appear reasonable but I do not
> know the units of the Z axis. The manual says Db. What is Db?
> Thank you for your time and help.
> Regards
> Tommy Ng
=========================================================================
Date: Tue, 17 May 2011 10:20:02 +0100
Reply-To: Andreas Finkelmeyer <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Andreas Finkelmeyer <[log in to unmask]>
Subject: Re: slicetiming difficulty
Comments: To: Rebecca Ray <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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=========================================================================
Date: Tue, 17 May 2011 12:51:23 +0100
Reply-To: Thomas Nichols <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Thomas Nichols <[log in to unmask]>
Subject: Re: After estimation design matrix loses most regressors.
Comments: To: Michael Thomas Smith <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=bcaec54a386226069f04a377647b
Message-ID: <[log in to unmask]>
--bcaec54a386226069f04a377647b
Content-Type: text/plain; charset=ISO-8859-1
Dear Mike,
Before estimation, the displayed design matrix is original matrix X (with
the exception that DCT drift basis elements aren't shown). After
estimation, the 'filtered and whitened' design matrix (xX.xKXs.X = K*W*X) is
shown. If certain columns appear to be zeroed out by whitening, that is
because the corresponding scans were found to have super-high variance.
(See my earlier post on errors with PET data).
I can't figure out why this is happening, though, as each session's data is
scaled separately. You can check out the scan-by-scan scale factors used to
bring each session to a Grand Mean of 100 by looking at SPM.xGX.gSF; if
there is crazy variation in this (e.g. super-low values for sessions 1 & 3)
it would explain the effect. Then the question is why are the computed
globals so different over sessions... maybe crazy-large artifactual values
in sessions 2, 4, 5,..,8?
Hope this helps with the detective work!
-Tom
On Wed, May 11, 2011 at 12:57 PM, Michael Thomas Smith <
[log in to unmask]> wrote:
> I'm interested in the correlation between a time series and the voxels in
> the brain. To find out more I made a GLM
> (see http://www.sal.mvm.ed.ac.uk/images/problem1.png ).
>
> Before estimation it looks fine (I think?).
>
> During estimation however, 6 of the 8 columns are set to zero (see inset in
> bottom-left corner of the linked image). Just sessions 1 and 3 output beta
> images. There are no errors or warnings expressed during estimation, and the
> matlab output appears ok.
>
> - I've confirmed the number of images in each session is equal to the
> number of values in the .txt regressor files.
> - I've tried adding conditions to each session (just a single event near
> the start of each session) to see if it's the lack of conditions that's
> upsetting SPM. (this didn't make any difference).
> - I've rebuilt the design matrix from scratch by hand, using the interface,
> but that didn't make any difference.
>
> Looking forward to any suggestions!
>
> Thanks,
>
> Mike Smith
>
> --
> The University of Edinburgh is a charitable body, registered in
> Scotland, with registration number SC005336.
>
--
____________________________________________
Thomas Nichols, PhD
Principal Research Fellow, Head of Neuroimaging Statistics
Department of Statistics & Warwick Manufacturing Group
University of Warwick
Coventry CV4 7AL
United Kingdom
Email: [log in to unmask]
Phone, Stats: +44 24761 51086, WMG: +44 24761 50752
Fax: +44 24 7652 4532
--bcaec54a386226069f04a377647b
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Dear Mike,=A0<div><br></div><div>Before estimation, the displayed design ma=
trix is original matrix X (with the exception that DCT drift basis elements=
aren't shown). =A0After estimation, the 'filtered and whitened'=
; design matrix (xX.xKXs.X =3D K*W*X) is shown. =A0If certain columns appea=
r to be zeroed out by whitening, that is because the corresponding scans we=
re found to have super-high variance. =A0(See my earlier post on errors wit=
h PET data).</div>
<div><br></div><div>I can't figure out why this is happening, though, a=
s each session's data is scaled separately. =A0You can check out the sc=
an-by-scan scale factors used to bring each session to a Grand Mean of 100 =
by looking at SPM.xGX.gSF; if there is crazy variation in this (e.g. super-=
low values for sessions 1 & 3) it would explain the effect. =A0Then the=
question is why are the computed globals so different over sessions... may=
be crazy-large artifactual values in=A0sessions=A02, 4, 5,..,8?</div>
<div><br></div><div>Hope this helps with the detective work!</div><div><br>=
</div><div>-Tom</div><div><br></div><div><br></div><div><div class=3D"gmail=
_quote">On Wed, May 11, 2011 at 12:57 PM, Michael Thomas Smith <span dir=3D=
"ltr"><<a href=3D"mailto:[log in to unmask]">[log in to unmask]</a=
>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex;">I'm interested in the correlation betwe=
en a time series and the voxels in the brain. To find out more I made a GLM=
<br>
(see <a href=3D"http://www.sal.mvm.ed.ac.uk/images/problem1.png" target=3D"=
_blank">http://www.sal.mvm.ed.ac.uk/images/problem1.png</a> ).<br>
<br>
Before estimation it looks fine (I think?).<br>
<br>
During estimation however, 6 of the 8 columns are set to zero (see inset in=
bottom-left corner of the linked image). Just sessions 1 and 3 output beta=
images. There are no errors or warnings expressed during estimation, and t=
he matlab output appears ok.<br>
<br>
- I've confirmed the number of images in each session is equal to the n=
umber of values in the .txt regressor files.<br>
- I've tried adding conditions to each session (just a single event nea=
r the start of each session) to see if it's the lack of conditions that=
's upsetting SPM. (this didn't make any difference).<br>
- I've rebuilt the design matrix from scratch by hand, using the interf=
ace, but that didn't make any difference.<br>
<br>
Looking forward to any suggestions!<br>
<br>
Thanks,<br>
<br>
Mike Smith<br><font color=3D"#888888">
<br>
-- <br>
The University of Edinburgh is a charitable body, registered in<br>
Scotland, with registration number SC005336.<br>
</font></blockquote></div><br><br clear=3D"all"><br>-- <br>________________=
____________________________<br>Thomas Nichols, PhD<br>Principal Research F=
ellow, Head of Neuroimaging Statistics<br>Department of Statistics & Wa=
rwick Manufacturing Group<br>
University of Warwick<br>Coventry=A0 CV4 7AL<br>United Kingdom<br><br>Email=
: <a href=3D"mailto:[log in to unmask]">[log in to unmask]</a=
><br>Phone, Stats: +44 24761 51086, WMG: +44 24761 50752<br>Fax:=A0 +44 24 =
7652 4532<br>
<br>
</div>
--bcaec54a386226069f04a377647b--
=========================================================================
Date: Tue, 17 May 2011 09:27:05 -0400
Reply-To: "Rajagopalan, Venkateswaran" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Rajagopalan, Venkateswaran" <[log in to unmask]>
Subject: SnPM for VBM analysis
MIME-Version: 1.0
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boundary="----_=_NextPart_001_01CC1496.1D148B90"
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------_=_NextPart_001_01CC1496.1D148B90
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charset=iso-8859-1
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Dear All,
=20
I am interested in using SnPM for my VBM analysis. I am in the learning =
process. I am wondering if somebody could help me with the following
=20
I opened up SnPM GUI and opened the setup option and I choose >2 groups =
Between groups ANOVA 1 scan/subject option since I have 5 groups including =
control group in total. After I choose my plug a window pops up to open the=
=
=66iles so for instance I chose 4 controls (smwrp1 files), 3 from patient =
group 1, 5 from from patient group 2. Then when I started to enter subject=
=
index A A A A B B B C C... the option to enter subject index doesn't seem t=
o=
stop at the end of 12th index since I chose only 12 subjects data the =
option to enter subject index keeps going on for ever what am I doing wrong=
=
here.=20
=20
Thanks.
=20
Venkat
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
Please consider the environment before printing this e-mail
Cleveland Clinic is ranked one of the top hospitals
in America by U.S.News & World Report (2010). =20
Visit us online at http://www.clevelandclinic.org for
a complete listing of our services, staff and
locations.
Confidentiality Note: This message is intended for use
only by the individual or entity to which it is addressed
and may contain information that is privileged,
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<DIV><FONT face=3DArial color=3D#000000 size=3D2>Dear All,</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>I am interested in using SnPM for my VBM =
analysis. I am in the learning process. I am wondering if somebody could =
help me with the following</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>I opened up SnPM GUI and opened the setup =
option and I choose >2 groups Between groups ANOVA 1 scan/subject =
option since I have 5 groups including control group in total. After I =
choose my plug a window pops up to open the files so for instance I chose 4=
=
controls (smwrp1 files), 3 from patient group 1, 5 from from =
patient group 2. Then when I started to enter subject index A A A A B B =
B C C... the option to enter subject index doesn't seem to stop at the=
=
end of 12th index since I chose only 12 subjects data the option to =
enter subject index keeps going on for ever what am I doing wrong=
=
here. </FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>Thanks.</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>Venkat</FONT></DIV>
<P><pre =
wrap>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
<p class=3DMsoNormal><font size=3D5 color=3Dgreen><span
style=3D'font-size:18.0pt;color:green'></span></font><font
size=3D2 color=3Dnavy face=3DCalibri><span =
style=3D'font-size:10.0pt;font-family:Calibri;
color:navy'> </span></font><font size=3D1 color=3Dgreen face=3DArial><span
style=3D'font-size:7.0pt;font-family:Arial;color:green'>Please consider the=
=
environment before printing this e-mail</span></font><o:p></o:p></p>
Cleveland Clinic is ranked one of the top hospitals
in America by U.S.News & World Report (2010). =20
Visit us online at http://www.clevelandclinic.org for
a complete listing of our services, staff and
locations.
Confidentiality Note: This message is intended for use
only by the individual or entity to which it is addressed
and may contain information that is privileged,
confidential, and exempt from disclosure under applicable
law. If the reader of this message is not the intended
recipient or the employee or agent responsible for
delivering the message to the intended recipient, you are
hereby notified that any dissemination, distribution or
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you have received this communication in error, please
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</pre></P></BODY></HTML>
------_=_NextPart_001_01CC1496.1D148B90--
=========================================================================
Date: Tue, 17 May 2011 17:45:15 +0200
Reply-To: Joana Braga Pereira <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Joana Braga Pereira <[log in to unmask]>
Subject: Re: Correcting for non-stationary smoothnees in vbm
Comments: To: Christian Gaser <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=00163646cede81e8f504a37aa859
Message-ID: <[log in to unmask]>
--00163646cede81e8f504a37aa859
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Dear Christian,
I've replaced the cg_spmT2x.m by the one you sent on your previous email.
However, i still get the following error:
Running 'Threshold and transform spmT-maps'
Use local RPV values to correct for non-stationary of smoothness.
Failed 'Threshold and transform spmT-maps'
Subscript indices must either be real positive integers or logicals.
In file "C:\Program Files\spm8\spm8\toolbox\vbm8\cg_spmT2x.m" (v412),
function "cg_spmT2x" at line 335.
Any ideas why this might be happening?
Many thanks!
Joana
2011/5/3 Christian Gaser <[log in to unmask]>
> Dear Aleksander,
>
> Raphael found the bug. I have attached the corrected version. However, it
> is a little bit odd that this failure will occur, because that means that
> your RPV image (Resels per volume) was not correct.
>
> Regards,
>
> Christian
>
> On Tue, 3 May 2011 17:16:48 +0200, [log in to unmask] <[log in to unmask]> wrote:
>
> >Dear Christian,
> >
> >we tried the newest VBM 8 Version r414. We still get following Error
> >
> >Running 'Threshold and transform spmT-maps'
> >Use local RPV values to correct for non-stationary of smoothness.
> >Failed 'Threshold and transform spmT-maps'
> >Undefined function or variable 'V2R'.
> >In file "C:\Program Files\spm8\toolbox\vbm8\cg_spmT2x.m" (v412), functio=
n
> "cg_spmT2x" at line 312.
> >
> >The following modules did not run:
> >Failed: Threshold and transform spmT-maps.
> >
> >We do not know if it is a result of an operation error or an error in th=
e
> tool itself?
> >
> >With kind regards
> >
> >Aleksander
> >
> >
> >
> >
> >
> >Dnia 2 maja 2011 22:37 Christian Gaser <[log in to unmask]>
> napisa=C5=82(a):
> >
> >> Dear Aleksander,
> >>
> >> as Darren assumed there was some debugging code in the function, which=
I
> forgot to remove. With the newest update r413 this problem should be now
> solved.
> >>
> >> Regards,
> >>
> >> Christian
> >>
> >>
> _________________________________________________________________________=
___
> >>
> >> Christian Gaser, Ph.D.
> >> Departments of Psychiatry and Neurology
> >> Friedrich-Schiller-University of Jena
> >> Jahnstrasse 3, D-07743 Jena, Germany
> >> Tel: ++49-3641-934752 Fax: ++49-3641-934755
> >> e-mail: [log in to unmask]
> >> http://dbm.neuro.uni-jena.de
> >>
> >>
> >> On Wed, 27 Apr 2011 11:13:34 +0200, [log in to unmask] <[log in to unmask]> wrote:
> >>
> >> >Hallo,
> >> >
> >> >we are trying to correct for non-stationary of smoothness
> >> >and we get following error report
> >> >
> >> >Use local RPV values to correct for non-stationary of smoothness.
> >> >Failed 'Threshold and transform spmT-maps'
> >> >Undefined function or variable 'K'.
> >> >In file "C:\Program Files\spm8\toolbox\vbm8\cg_spmT2x.m" (v404),
> function
> >> >"cg_spmT2x" at line 321.
> >> >
> >> >The following modules did not run:
> >> >Failed: Threshold and transform spmT-maps
> >> >
> >> >
> >> >We found this :
> >> >"Hi, I have removed the interface to the non-stationarity correction =
in
> >> >VBM8 because
> >> >of the interferences with the SPM8 GUI. However, there is still a
> hidden
> >> >option if
> >> >you use the conversion tools for transforming and thresholding T-or
> >> >F-maps:
> >> >VBM8|Data presentation|Threshodl and transform T-maps"
> >> >
> >> >And we followed this sequence
> >> >
> >> >The non-stationary cluster correction in VBM8 can be
> >> >implemented
> >> >by the following sequence of menu steps:
> >> >Toolbox > VBM8 > Data presentation > Threshold and transform spmT-map=
s
> >
> >> >.Cluster
> >> >extent threshold > ..k-value > ...Correct for non-isotropic smoothnes=
s
> >> >yes.
> >> >
> >> >but without success.
> >> >
> >> >Do you have some experience with this part of the Vbm8 tool?
> >> >
> >> >We would be thankful for any help.
> >> >
> >> >With kind regards
> >> >
> >> >Aleksander
> >>
>
>
--00163646cede81e8f504a37aa859
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Dear Christian,<div><br></div><div>I've replaced the cg_spmT2x.m by the=
one you sent on your previous email.</div><div><br></div><div>However, i s=
till get the following error:</div><div><br></div><div><span class=3D"Apple=
-style-span" style=3D"border-collapse: collapse; font-family: arial, sans-s=
erif; font-size: 13px; ">Running 'Threshold and transform spmT-maps'=
;<br>
<div class=3D"im" style=3D"color: rgb(80, 0, 80); ">Use local RPV values to=
correct for=C2=A0<span class=3D"il" style=3D"background-image: initial; ba=
ckground-attachment: initial; background-origin: initial; background-clip: =
initial; background-color: rgb(94, 160, 227); color: rgb(255, 255, 255); ba=
ckground-position: initial initial; background-repeat: initial initial; ">n=
on</span>-<span class=3D"il" style=3D"background-image: initial; background=
-attachment: initial; background-origin: initial; background-clip: initial;=
background-color: rgb(94, 160, 227); color: rgb(255, 255, 255); background=
-position: initial initial; background-repeat: initial initial; ">stationar=
y</span>=C2=A0of smoothness.<br>
Failed =C2=A0'Threshold and transform spmT-maps'<br></div>Subscript=
indices must either be real positive integers or logicals.<br>In file &quo=
t;C:\Program Files\<span class=3D"il" style=3D"background-image: initial; b=
ackground-attachment: initial; background-origin: initial; background-clip:=
initial; background-color: rgb(94, 160, 227); color: rgb(255, 255, 255); b=
ackground-position: initial initial; background-repeat: initial initial; ">=
spm8</span>\</span><span class=3D"Apple-style-span" style=3D"border-collaps=
e: collapse; font-family: arial, sans-serif; font-size: 13px; "><span class=
=3D"il" style=3D"background-image: initial; background-attachment: initial;=
background-origin: initial; background-clip: initial; background-color: rg=
b(94, 160, 227); color: rgb(255, 255, 255); ">spm8</span>\</span><span clas=
s=3D"Apple-style-span" style=3D"border-collapse: collapse; font-family: ari=
al, sans-serif; font-size: 13px; ">toolbox\vbm8\cg_spmT2x.m" (v412), f=
unction "cg_spmT2x" at line 335.</span></div>
<div><span class=3D"Apple-style-span" style=3D"border-collapse: collapse; f=
ont-family: arial, sans-serif; font-size: 13px; "><br></span></div><div>Any=
ideas why this might be happening?</div><div><br></div><div>Many thanks!</=
div>
<div><br></div><div>Joana<br><br></div><div><br></div><div><br><div class=
=3D"gmail_quote">2011/5/3 Christian Gaser <span dir=3D"ltr"><<a href=3D"=
mailto:[log in to unmask]">[log in to unmask]</a>></sp=
an><br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex;">Dear Aleksander,<br>
<br>
Raphael found the bug. I have attached the corrected version. However, it i=
s a little bit odd that this failure will occur, because that means that yo=
ur RPV image (Resels per volume) was not correct.<br>
<br>
Regards,<br>
<font color=3D"#888888"><br>
Christian<br>
</font><div><div></div><div class=3D"h5"><br>
On Tue, 3 May 2011 17:16:48 +0200, <a href=3D"mailto:[log in to unmask]">[log in to unmask]
pl</a> <<a href=3D"mailto:[log in to unmask]">[log in to unmask]</a>> wrote:<br>
<br>
>Dear Christian,<br>
><br>
>we tried the newest VBM 8 Version r414. We still get following Error<br=
>
><br>
>Running 'Threshold and transform spmT-maps'<br>
>Use local RPV values to correct for non-stationary of smoothness.<br>
>Failed =C2=A0'Threshold and transform spmT-maps'<br>
>Undefined function or variable 'V2R'.<br>
>In file "C:\Program Files\spm8\toolbox\vbm8\cg_spmT2x.m" (v41=
2), function "cg_spmT2x" at line 312.<br>
><br>
>The following modules did not run:<br>
>Failed: Threshold and transform spmT-maps.<br>
><br>
>We do not know if it is a result of an operation error or an error in t=
he tool itself?<br>
><br>
>With kind regards<br>
><br>
>Aleksander<br>
><br>
><br>
><br>
><br>
><br>
>Dnia 2 maja 2011 22:37 Christian Gaser <<a href=3D"mailto:christian.=
[log in to unmask]">[log in to unmask]</a>> napisa=C5=82(a):<br>
><br>
>> Dear Aleksander,<br>
>><br>
>> as Darren assumed there was some debugging code in the function, w=
hich I forgot to remove. With the newest update r413 this problem should be=
now solved.<br>
>><br>
>> Regards,<br>
>><br>
>> Christian<br>
>><br>
>> __________________________________________________________________=
__________<br>
>><br>
>> Christian Gaser, Ph.D.<br>
>> Departments of Psychiatry and Neurology<br>
>> Friedrich-Schiller-University of Jena<br>
>> Jahnstrasse 3, D-07743 Jena, Germany<br>
>> Tel: ++49-3641-934752 =C2=A0 =C2=A0 =C2=A0 =C2=A0Fax: =C2=A0 ++49-=
3641-934755<br>
>> e-mail: <a href=3D"mailto:[log in to unmask]">christian.g=
[log in to unmask]</a><br>
>> <a href=3D"http://dbm.neuro.uni-jena.de" target=3D"_blank">http://=
dbm.neuro.uni-jena.de</a><br>
>><br>
>><br>
>> On Wed, 27 Apr 2011 11:13:34 +0200, <a href=3D"mailto:[log in to unmask]"=
>[log in to unmask]</a> <<a href=3D"mailto:[log in to unmask]">[log in to unmask]</a>> wro=
te:<br>
>><br>
>> >Hallo,<br>
>> ><br>
>> >we are trying to correct for non-stationary of smoothness<br>
>> >and we get following error report<br>
>> ><br>
>> >Use local RPV values to correct for non-stationary of smoothne=
ss.<br>
>> >Failed =C2=A0'Threshold and transform spmT-maps'<br>
>> >Undefined function or variable 'K'.<br>
>> >In file "C:\Program Files\spm8\toolbox\vbm8\cg_spmT2x.m&q=
uot; (v404), function<br>
>> >"cg_spmT2x" at line 321.<br>
>> ><br>
>> >The following modules did not run:<br>
>> >Failed: Threshold and transform spmT-maps<br>
>> ><br>
>> ><br>
>> >We found this :<br>
>> >"Hi, I have removed the interface to the non-stationarity=
correction in<br>
>> >VBM8 because<br>
>> >of the interferences with the SPM8 GUI. However, there is stil=
l a hidden<br>
>> >option if<br>
>> >you use the conversion tools for transforming and thresholding=
T-or<br>
>> >F-maps:<br>
>> >VBM8|Data presentation|Threshodl and transform T-maps"<br=
>
>> ><br>
>> >And we followed this sequence<br>
>> ><br>
>> >The non-stationary cluster correction in VBM8 can be<br>
>> >implemented<br>
>> >by the following sequence of menu steps:<br>
>> >Toolbox > VBM8 > Data presentation > Threshold and tr=
ansform spmT-maps ><br>
>> >.Cluster<br>
>> >extent threshold > ..k-value > ...Correct for non-isotro=
pic smoothness<br>
>> >yes.<br>
>> ><br>
>> >but without success.<br>
>> ><br>
>> >Do you have some experience with this part of the Vbm8 tool?<b=
r>
>> ><br>
>> >We would be thankful for any help.<br>
>> ><br>
>> >With kind regards<br>
>> ><br>
>> >Aleksander<br>
>><br>
<br>
</div></div></blockquote></div><br></div>
--00163646cede81e8f504a37aa859--
=========================================================================
Date: Tue, 17 May 2011 18:16:59 +0100
Reply-To: Michael Thomas Smith <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michael Thomas Smith <[log in to unmask]>
Subject: Re: After estimation design matrix loses most regressors.
Comments: To: Thomas Nichols <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1; DelSp="Yes"; format="flowed"
Content-Disposition: inline
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Thanks for the reply.
It seems likely it's something to do with my install of SPM, as Thomas =20
was able to run exactly the same job on his computer and get the =20
correct result. I'll reinstall SPM and try again. (by the way: I found =20
adding extra regressors caused the left-out columns to change...all =20
very weird).
Thanks again for the suggestions and help,
I'll be back with more questions if the reinstall doesn't work!
Mike.
Quoting Thomas Nichols <[log in to unmask]> on Tue, 17 May 2011 =20
12:51:23 +0100:
> Dear Mike,
>
> Before estimation, the displayed design matrix is original matrix X (with
> the exception that DCT drift basis elements aren't shown). After
> estimation, the 'filtered and whitened' design matrix (xX.xKXs.X =3D K*W*X=
) is
> shown. If certain columns appear to be zeroed out by whitening, that is
> because the corresponding scans were found to have super-high variance.
> (See my earlier post on errors with PET data).
>
> I can't figure out why this is happening, though, as each session's data i=
s
> scaled separately. You can check out the scan-by-scan scale factors used =
to
> bring each session to a Grand Mean of 100 by looking at SPM.xGX.gSF; if
> there is crazy variation in this (e.g. super-low values for sessions 1 & 3=
)
> it would explain the effect. Then the question is why are the computed
> globals so different over sessions... maybe crazy-large artifactual values
> in sessions 2, 4, 5,..,8?
>
> Hope this helps with the detective work!
>
> -Tom
>
>
> On Wed, May 11, 2011 at 12:57 PM, Michael Thomas Smith <
> [log in to unmask]> wrote:
>
>> I'm interested in the correlation between a time series and the voxels in
>> the brain. To find out more I made a GLM
>> (see http://www.sal.mvm.ed.ac.uk/images/problem1.png ).
>>
>> Before estimation it looks fine (I think?).
>>
>> During estimation however, 6 of the 8 columns are set to zero (see inset =
in
>> bottom-left corner of the linked image). Just sessions 1 and 3 output bet=
a
>> images. There are no errors or warnings expressed during estimation, and =
the
>> matlab output appears ok.
>>
>> - I've confirmed the number of images in each session is equal to the
>> number of values in the .txt regressor files.
>> - I've tried adding conditions to each session (just a single event near
>> the start of each session) to see if it's the lack of conditions that's
>> upsetting SPM. (this didn't make any difference).
>> - I've rebuilt the design matrix from scratch by hand, using the interfac=
e,
>> but that didn't make any difference.
>>
>> Looking forward to any suggestions!
>>
>> Thanks,
>>
>> Mike Smith
>>
>> --
>> The University of Edinburgh is a charitable body, registered in
>> Scotland, with registration number SC005336.
>>
>
>
>
> --
> ____________________________________________
> Thomas Nichols, PhD
> Principal Research Fellow, Head of Neuroimaging Statistics
> Department of Statistics & Warwick Manufacturing Group
> University of Warwick
> Coventry CV4 7AL
> United Kingdom
>
> Email: [log in to unmask]
> Phone, Stats: +44 24761 51086, WMG: +44 24761 50752
> Fax: +44 24 7652 4532
>
--=20
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.
=========================================================================
Date: Tue, 17 May 2011 21:53:26 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Re-Referencing of EEG Data
Comments: To: Urs Bachofner <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=windows-1252
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Dear Urs,
On Tue, May 17, 2011 at 10:50 AM, Urs Bachofner <[log in to unmask]> wrot=
e:
> I have a question regarding the concept of EEG data Re-referencing in Spm=
8.
> The way I see it, re-referencing is a very important step prior to Source
> Analysis. To get useful data, the Signals should be re-referenced to
> average.
> According to the SPM8 Manual P. 110 we can use spm_eeg_montage to do this=
.
>
> The data I'd like to process is recorded with a 128-channel EEG-net with =
the
> reference electrode at CZ.
> According to the SPM8 Manual, for average reference the matrix should hav=
e
> (N-1)/N at the diagonal and -1/N elsewhere.
> In my case this results in 0.9921875 at the diagonal and -0.0078125
> elsewhere.
>
> Two questions:
> 1. These numbers are so close to the original matrix (1 at diagonal and 0
> elsewhere) which is said to not change anything. Is this matrix correct?
>
Yes, it's all OK. The more electrodes you have the closer the average
will be to zero but remember that the actual values also depend on the
data, not only on the weights so you should still re-reference.
> 2. Since electrodes that are closer to the reference (in this case CZ) ha=
ve
> a higher amplitude recorded, shouldn't such electrodes be weighted
> differently than electrodes that are more distant to CZ? Am I missing the
> point here?
>
>
No, the average reference is just what it is, every channel minus the
average of all channels. It does not depend on where the original
reference is.
> And finally, besides Filtering, epoching, Artefact Detection (removing ba=
d
> channels and bad trials), Re-referencing, and baseline correction are the=
re
> other preprocessing steps that are necessary to get good data from my evo=
ked
> potentials?
No, these are the basic steps. You might try using the robust
averaging option. Also there is an option in MEEGTools for correcting
eye blinks. You might or might not need it depending on your data.
> And is there a certain order in which these steps should be
> executed?
>
I've just presented a slide about that at the SPM course last week.
Basically it says the following:
----
Considerations for order of processing steps:
It=92s better to filter before epoching unless only small part of the
data is relevant. As an alternative one could pad the epochs of
interest with extra data and discard it later.
Downsampling speeds up the other steps and reduces disk space usage,
but it involves low-pass filtering and...
Low-pass or band-pass filtering before high-pass can generate ringing
at the edges, which is especially problematic for epoched data. So
high-pass should come first, but...
Only some channel types (EEG, MEG, LFP etc.) are filtered. So channel
types should be set correctly first (Prepare, Montage).
---
Best,
Vladimir
> Thank you very much for you help.
>
>
>
>
=========================================================================
Date: Tue, 17 May 2011 16:47:10 -0400
Reply-To: Mobin Anandwala <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Mobin Anandwala <[log in to unmask]>
Subject: uj in bilinear state equation
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0016e6408ac242b46f04a37ee0d5
Message-ID: <[log in to unmask]>
--0016e6408ac242b46f04a37ee0d5
Content-Type: text/plain; charset=ISO-8859-1
Good Afternoon
This is Mobin Anandwala and I have a question regarding the variable uj in
the bilinear state equation. The equation as stated is z' = (A +
sigma(uj*Bj))*z + Cu. As I understand the u vector times the C matrix is a
vector consisting of input functions. My question is that since the u
vector consists of input functions is the uj variable a scalar that is the
maximum of the input function or is it a vector? When I tried to use uj as
a vector I obtained a matrix multiplication error in Matlab with Bj as the
dimensions did not match (u being an n x 1 vector and Bj being 4 x 4). I am
currently using uj as a scalar constant with it being the maximum of input
function (current data that I have has u2(t) in the u vector and the uj
being its maximum).
Thank you
Mobin Anandwala
--0016e6408ac242b46f04a37ee0d5
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Good Afternoon<br><br>This is Mobin Anandwala and I have a question regardi=
ng the variable uj in the bilinear state equation.=A0 The equation as state=
d is z' =3D (A + sigma(uj*Bj))*z + Cu.=A0 As I understand the u vector =
times the C matrix is a vector consisting of input functions.=A0 My questio=
n is that since the u vector consists of input functions is the uj variable=
a scalar that is the maximum of the input function or is it a vector?=A0 W=
hen I tried to use uj as a vector I obtained a matrix multiplication error =
in Matlab with Bj as the dimensions did not match (u being an n x 1 vector =
and Bj being 4 x 4).=A0 I am currently using uj as a scalar constant with i=
t being the maximum of input function (current data that I have has u2(t) i=
n the u vector and the uj being its maximum).<br>
<br>Thank you<br>Mobin Anandwala<br>
--0016e6408ac242b46f04a37ee0d5--
=========================================================================
Date: Tue, 17 May 2011 16:07:10 -0700
Reply-To: Jeannine Morrone-Strupinsky <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jeannine Morrone-Strupinsky <[log in to unmask]>
Subject: Re: SPM Digest - 16 May 2011 to 17 May 2011 (#2011-145)
In-Reply-To: <[log in to unmask]>
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-----Original Message-----
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] =
On Behalf Of SPM automatic digest system
Sent: Tuesday, May 17, 2011 4:00 PM
To: [log in to unmask]
Subject: SPM Digest - 16 May 2011 to 17 May 2011 (#2011-145)
There are 12 messages totaling 1451 lines in this issue.
Topics of the day:
1. Batch problem--3D Source Reconstruction
2. Corregistro PET-T1 with DARTEL
3. SPM 2nd level analysis - reg
4. SPM 2nd level analysis-reg
5. Time frequency question
6. slicetiming difficulty
7. After estimation design matrix loses most regressors. (2)
8. SnPM for VBM analysis
9. Correcting for non-stationary smoothnees in vbm
10. Re-Referencing of EEG Data
11. uj in bilinear state equation
----------------------------------------------------------------------
Date: Tue, 17 May 2011 09:31:28 +0800
From: =E9=A3=9E=E9=B8=9F <[log in to unmask]>
Subject: Re: Batch problem--3D Source Reconstruction
Dear Vladimir,
=E3=80=80=E3=80=80Thank you very much! May you a happy day!
=E3=80=80=E3=80=80Haoran.
=20
=E5=9C=A8 2011-05-16 19:04:19=EF=BC=8C"Vladimir Litvak" =
<[log in to unmask]> =E5=86=99=E9=81=93=EF=BC=9A
>Dear Haoran,
>
>
>
>On 16 May 2011, at 10:13, "=E9=A3=9E=E9=B8=9F" <[log in to unmask]> =
wrote:
>
>> Dear Vladimir,
>> =E3=80=80=E3=80=80Your guess was right. I really couldn't do 3D =
sources reconstruction of that data by GUI. It reminded me ''checkmeeg: =
data scale missing, assigning default
>> checkmeeg: no fiducials are defined''. Then I did preprocess steps =
again, and found that I couldn't obtain the fiducials automatically(when =
I finished Converting step). I checked the other datasets, luckily, they =
didn't have this problem. I guess there must be some wrongs of my =
original dataset (only that one), right ?
>
>right
>
>> =E3=80=80=E3=80=80As for reconstruction batch problem, with the =
latest version of spm8(4029) and normal dataset, I can do reconstruction =
by that saved "renconstruction_batch" successfully. Thus, the problems =
related to reconstruction batch that I confronted previously may result =
from the different versions of spm8.
>> By the way, in ''MEEG head model specification> EEG head =
modle'' module, must I specify the ''EEG head modle'' if I just process =
MEG dataset?
>
>One peculiarity of batch is that when you build the configuration you
>can't use information from the dataset which only becomes available
>when you run the batch. In particular you can't know if the dataset in
>question is EEG or MEG. So don't worry about the EEG head model. If
>your dataset is MEG it will be ignored.
>
>Best,
>
>Vladimir
>
>
>> =E3=80=80=E3=80=80Thank you very much for helping me solve these tiny =
problems!
>>
>> =E3=80=80=E3=80=80Haoran.
>>
>>
>> At 2011-05-16 06:38:23=EF=BC=8C"Vladimir Litvak" =
<[log in to unmask]> wrote:
>>
>> >Dear Haoran,
>> >
>> >The problem seems to be not in the batch but in your MEG data (or =
was
>> >it EEG?). There are no valid fiducials in that dataset. Could you
>> >perform source reconstruction using the GUI? I'd be surprised if you
>> >could. So we need to focus on how to get fiducials into your dataset
>> >and for that you need to tell me more about where that data comes
>> >from.
>> >
>> >Best,
>> >
>> >Vladimir
>> >
>> >2011/5/15 =E9=A3=9E=E9=B8=9F <[log in to unmask]>:
>> >> Dear Vladimir,
>> >> =E3=80=80=E3=80=80I tried again with the latest version of =
spm8(4029), the previous problem(
>> >> template=3D1) disappeared. But this time, I confronted a new =
problem. It
>> >> reminded me "No executable modules, but still unresolved =
dependencies or
>> >> incomplete module inputs." But I don't know where the problems =
are. Could
>> >> you help me see my reconstruction_batch.mat and give me some =
advice ? Thanks
>> >> a lot.
>> >>
>> >> Haoran.
>> >>
>> >> These code appears in the matlab command window when I ran =
the batch:
>> >> SPM8: spm_eeg_inv_mesh_ui (v4027) 11:09:13 - =
15/05/2011
>> >> =
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>> >> template: 0
>> >> sMRI: =
'D:\Processed\DP01\sKEYAN-0002-00000-000001-01.img,1'
>> >> def: =
'D:\Processed\DP01\y_sKEYAN-0002-00000-000001-01.nii'
>> >> Affine: [4x4 double]
>> >> Msize: 2
>> >> tess_mni: [1x1 struct]
>> >> tess_ctx:
>> >> =
'D:\Processed\DP01\sKEYAN-0002-00000-000001-01cortex_8196.surf.gii'
>> >> tess_scalp:
>> >> 'D:\Processed\DP01\sKEYAN-0002-00000-000001-01scalp_2562.surf.gii'
>> >> tess_oskull:
>> >> =
'D:\Processed\DP01\sKEYAN-0002-00000-000001-01oskull_2562.surf.gii'
>> >> tess_iskull:
>> >> =
'D:\Processed\DP01\sKEYAN-0002-00000-000001-01iskull_2562.surf.gii'
>> >> fid: [1x1 struct]
>> >> Failed 'M/EEG head model specification'
>> >> Reference to non-existent field 'fid'.
>> >> In file "C:\Program =
Files\MATLAB\spm8new\config\spm_cfg_eeg_inv_headmodel.m"
>> >> (v4118), function "specify_headmodel" at line 209.
>> >> No executable modules, but still unresolved dependencies or =
incomplete
>> >> module inputs.
>> >> The following modules did not run:
>> >> Failed: M/EEG head model specification
>> >> Skipped: M/EEG source inversion
>> >> Skipped: M/EEG inversion results
>> >>
>> >>
>> >> At 2011-05-13 22:06:06=EF=BC=8C"Vladimir Litvak" =
<[log in to unmask]
>> >>> wrote:
>> >>
>> >>>Dear Haoran,
>> >>>
>> >>>I tried and everything works fine for me. Make sure your SPM =
version
>> >>>is up to date and if you can't make it work, send me your saved =
batch
>> >>>and I'll take another look.
>> >>>
>> >>>Best,
>> >>>
>> >>>Vladimir
>> >>>
>> >>>2011/5/10 =E9=A3=9E=E9=B8=9F <[log in to unmask]>:
>> >>>> Dear SPM's users,
>> >>>> =E3=80=80=E3=80=80Have you ever used batch interface to do 3D =
source reconstruction for
>> >>>> EEG/MEG data? I choosed three separate modules "M/EEG head =
model
>> >>>> specification" "M/EEG source inversion" and "M/EEG inversion =
results" so as
>> >>>> to reconstruct the sources. In the "M/EEG head model =
specification" module,
>> >>>> I specified ''Meshes<Meshes source<individual structual image'' =
and then
>> >>>> selected a mri file named "sDP74-0003-00000-000001-01.img,1". =
When all was
>> >>>> ready and then I ran the batch, however, I found that it din't =
excuted the
>> >>>> specified structual image ( as you can see below 'template=3D1') =
and the
>> >>>> matlab command window appeared those:
>> >>>>
>> >>>> SPM8: spm_eeg_inv_mesh_ui (v3731) 21:39:06 - =
09/05/2011
>> >>>> =
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>> >>>> template: 1
>> >>>> Affine: [4x4 double]
>> >>>> sMRI: 'C:\Program
>> >>>> Files\MATLAB\toolbox\spm8\canonical\single_subj_T1.nii'
>> >>>> Msize: 2
>> >>>> tess_mni: [1x1 struct]
>> >>>> tess_ctx: 'C:\Program
>> >>>> Files\MATLAB\toolbox\spm8\canonical\cortex_8196.surf.gii'
>> >>>> tess_scalp: 'C:\Program
>> >>>> Files\MATLAB\toolbox\spm8\canonical\scalp_2562.surf.gii'
>> >>>> tess_oskull: 'C:\Program
>> >>>> Files\MATLAB\toolbox\spm8\canonical\oskull_2562.surf.gii'
>> >>>> tess_iskull: 'C:\Program
>> >>>> Files\MATLAB\toolbox\spm8\canonical\iskull_2562.surf.gii'
>> >>>> fid: [1x1 struct]
>> >>>>
>> >>>> =E3=80=80I didn't understand why. Anyone who knows the reason =
? Thanks very much
>> >>>> for any help !
>> >>>>
>> >>>> --
>> >>>> Haoran LI (MS)
>> >>>> Brain Imaging Lab,
>> >>>> Research Center for Learning Science,
>> >>>> Southeast University
>> >>>> 2 Si Pai Lou , Nanjing, 210096, P.R.China
>> >>>>
>> >>>>
>> >>
>> >>
>> >>
>> >>
>> >>
>>
>>
--
Haoran LI (MS)
Brain Imaging Lab,
Research Center for Learning Science,
Southeast Un
------------------------------
Date: Tue, 17 May 2011 05:10:34 +0100
From: David Yang <[log in to unmask]>
Subject: Re: Corregistro PET-T1 with DARTEL
Dear John:
Thanks for your kind and useful reply.
I wanted to make sure my interpretation was right:
Step 1: was done by SPM function: Coreg:estimate and the registration =
information would be stored in the header of source images (no other =
output would be found)
Step 2 and Step 3:just as routine DARTEL process on T1 images
Step4: as in DARTEL toolbox: normalise to MNI space option and use =
source images (PET) from Step1.
For receptor/transporter binding potential images, I suspected we should =
choose Preserve Amount in Step 4 according to previous discussion:
http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3DSPM;f3f7b65.0901
Furthermore, considering the image features of PET or even SPECT images, =
it might have to smooth such images with large amount (ex 12 mm compared =
to default 8 mm in DARTEL). I wonder if such was suitable if we wanted =
to perform further analysis by BPM that used both VBM and PET/SPECT =
images concurrently as in this subject:
http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3DSPM;dd737de1.1012
Thanks for your help~
Sincerely yours,
David
------------------------------
Date: Tue, 17 May 2011 11:45:40 +0530
From: cognitive dept neuro science =
<[log in to unmask]>
Subject: SPM 2nd level analysis - reg
Dear All,
We are(our team) processing our datas using SPM8. We are able to process
upto first level. We are able to get the activations at the end of first
level result. But we cant further process our second level analysis. =
Please
help us to process further.
Thanks in advance.
--=20
Regards,
Cognitive Neurosciences Centre,
Dept of Clinical Psychology,
NIMHANS-Banglore 560 029.
------------------------------
Date: Tue, 17 May 2011 11:59:50 +0530
From: cognitive dept neuro science =
<[log in to unmask]>
Subject: SPM 2nd level analysis-reg
Dear All,
We are(our team) processing our datas using SPM8. We are able to process
upto first level. We are able to get the activations at the end of first
level result. But we cant further process our second level analysis. =
Please
help us to process further.
Thanks in advance.
--=20
Regards,
Cognitive Neurosciences Centre,
Dept of Clinical Psychology,
NIMHANS-Banglore 560 029.
------------------------------
Date: Tue, 17 May 2011 08:08:58 +0100
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Time frequency question
http://en.wikipedia.org/wiki/Decibel
On Tue, May 17, 2011 at 4:50 AM, Tommy Ng <[log in to unmask]> wrote:
> HI Sir
> Sorry to bother you again, I have a basic question regarding TF =
analysis in
> SPM.
> As instructed in SPM manual, I averaged TF from single data series =
using the
> option LogR. The ensuing source power maps appear reasonable but I do =
not
> know the units of the Z axis. The manual says Db. What is Db?
> Thank you for your time and help.
> Regards
> Tommy Ng
------------------------------
Date: Tue, 17 May 2011 10:20:02 +0100
From: Andreas Finkelmeyer <[log in to unmask]>
Subject: Re: slicetiming difficulty
Check to see if the number of slices of this subject is identical to the =
other subjects, and as you expect them to be - most likely there are =
more slices. The easiest way to do this is to check the last number in =
'Dimensions', when you use the 'Display' button to look at the image.
Good luck!
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D
Andreas Finkelmeyer, Ph.D.
Institute of Neuroscience, Newcastle University
Academic Psychiatry, Building 15, Newcastle General Hospital
Westgate Road, Newcastle NE4 6BE, UK
Tel.: +44 (0)191 256 3296 Fax: +44 (0)191 256 3324
Web: www.ncl.ac.uk/ion
=20
>-----Original Message-----
>From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]]
>On Behalf Of Rebecca Ray
>Sent: 16 May 2011 22:44
>To: [log in to unmask]
>Subject: [SPM] slicetiming difficulty
>
>I have successfully preprocessed all of my data with the exception of =
this one
>subject. Our TR is 2.6 but it changes it to 2.7 and gives the =
following error
>message:
>
>SPM8: spm_slice_timing (v3756) 16:27:38 - =
16/05/2011
>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>Your TR is 2.7
>Failed 'Slice Timing'
>Improper assignment with rectangular empty matrix.
>In file "/Applications/spm8/spm_slice_timing.m" (v3756), function
>"spm_slice_timing" at line 232.
>In file "/Applications/spm8/config/spm_run_st.m" (v2312), function
>"spm_run_st" at line 25.
>
>I have spoken with our physicist who does not use SPM, and he does not
>think it is a problem with the data.
>
>I can display the data prior to slicetiming but not after. After it =
appears to
>have spit out files but gives an error when you try to display these =
images:
>Running 'Display Image'
>Image
>"/Users/rebeccaray/Documents/UW_Projects/Vivek/Data_Processing/Raw_
>Data/022_S2/Functionals/Emotion/scan2/agvscan0329.img" can not be
>resampled
>Image
>"/Users/rebeccaray/Documents/UW_Projects/Vivek/Data_Processing/Raw_
>Data/022_S2/Functionals/Emotion/scan2/agvscan0329.img" can not be
>resampled
>Done 'Display Image'
>Done
>
>Any advice would be awesome!
------------------------------
Date: Tue, 17 May 2011 12:51:23 +0100
From: Thomas Nichols <[log in to unmask]>
Subject: Re: After estimation design matrix loses most regressors.
Dear Mike,
Before estimation, the displayed design matrix is original matrix X =
(with
the exception that DCT drift basis elements aren't shown). After
estimation, the 'filtered and whitened' design matrix (xX.xKXs.X =3D =
K*W*X) is
shown. If certain columns appear to be zeroed out by whitening, that is
because the corresponding scans were found to have super-high variance.
(See my earlier post on errors with PET data).
I can't figure out why this is happening, though, as each session's data =
is
scaled separately. You can check out the scan-by-scan scale factors =
used to
bring each session to a Grand Mean of 100 by looking at SPM.xGX.gSF; if
there is crazy variation in this (e.g. super-low values for sessions 1 & =
3)
it would explain the effect. Then the question is why are the computed
globals so different over sessions... maybe crazy-large artifactual =
values
in sessions 2, 4, 5,..,8?
Hope this helps with the detective work!
-Tom
On Wed, May 11, 2011 at 12:57 PM, Michael Thomas Smith <
[log in to unmask]> wrote:
> I'm interested in the correlation between a time series and the voxels =
in
> the brain. To find out more I made a GLM
> (see http://www.sal.mvm.ed.ac.uk/images/problem1.png ).
>
> Before estimation it looks fine (I think?).
>
> During estimation however, 6 of the 8 columns are set to zero (see =
inset in
> bottom-left corner of the linked image). Just sessions 1 and 3 output =
beta
> images. There are no errors or warnings expressed during estimation, =
and the
> matlab output appears ok.
>
> - I've confirmed the number of images in each session is equal to the
> number of values in the .txt regressor files.
> - I've tried adding conditions to each session (just a single event =
near
> the start of each session) to see if it's the lack of conditions =
that's
> upsetting SPM. (this didn't make any difference).
> - I've rebuilt the design matrix from scratch by hand, using the =
interface,
> but that didn't make any difference.
>
> Looking forward to any suggestions!
>
> Thanks,
>
> Mike Smith
>
> --
> The University of Edinburgh is a charitable body, registered in
> Scotland, with registration number SC005336.
>
--=20
____________________________________________
Thomas Nichols, PhD
Principal Research Fellow, Head of Neuroimaging Statistics
Department of Statistics & Warwick Manufacturing Group
University of Warwick
Coventry CV4 7AL
United Kingdom
Email: [log in to unmask]
Phone, Stats: +44 24761 51086, WMG: +44 24761 50752
Fax: +44 24 7652 4532
------------------------------
Date: Tue, 17 May 2011 09:27:05 -0400
From: "Rajagopalan, Venkateswaran" <[log in to unmask]>
Subject: SnPM for VBM analysis
Dear All,
=20
I am interested in using SnPM for my VBM analysis. I am in the learning =
process. I am wondering if somebody could help me with the following
=20
I opened up SnPM GUI and opened the setup option and I choose >2 groups =
Between groups ANOVA 1 scan/subject option since I have 5 groups =
including control group in total. After I choose my plug a window pops =
up to open the files so for instance I chose 4 controls (smwrp1 files), =
3 from patient group 1, 5 from from patient group 2. Then when I =
started to enter subject index A A A A B B B C C... the option to enter =
subject index doesn't seem to stop at the end of 12th index since I =
chose only 12 subjects data the option to enter subject index keeps =
going on for ever what am I doing wrong here.=20
=20
Thanks.
=20
Venkat
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
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------------------------------
Date: Tue, 17 May 2011 17:45:15 +0200
From: Joana Braga Pereira <[log in to unmask]>
Subject: Re: Correcting for non-stationary smoothnees in vbm
Dear Christian,
I've replaced the cg_spmT2x.m by the one you sent on your previous =
email.
However, i still get the following error:
Running 'Threshold and transform spmT-maps'
Use local RPV values to correct for non-stationary of smoothness.
Failed 'Threshold and transform spmT-maps'
Subscript indices must either be real positive integers or logicals.
In file "C:\Program Files\spm8\spm8\toolbox\vbm8\cg_spmT2x.m" (v412),
function "cg_spmT2x" at line 335.
Any ideas why this might be happening?
Many thanks!
Joana
2011/5/3 Christian Gaser <[log in to unmask]>
> Dear Aleksander,
>
> Raphael found the bug. I have attached the corrected version. However, =
it
> is a little bit odd that this failure will occur, because that means =
that
> your RPV image (Resels per volume) was not correct.
>
> Regards,
>
> Christian
>
> On Tue, 3 May 2011 17:16:48 +0200, [log in to unmask] <[log in to unmask]> wrote:
>
> >Dear Christian,
> >
> >we tried the newest VBM 8 Version r414. We still get following Error
> >
> >Running 'Threshold and transform spmT-maps'
> >Use local RPV values to correct for non-stationary of smoothness.
> >Failed 'Threshold and transform spmT-maps'
> >Undefined function or variable 'V2R'.
> >In file "C:\Program Files\spm8\toolbox\vbm8\cg_spmT2x.m" (v412), =
function
> "cg_spmT2x" at line 312.
> >
> >The following modules did not run:
> >Failed: Threshold and transform spmT-maps.
> >
> >We do not know if it is a result of an operation error or an error in =
the
> tool itself?
> >
> >With kind regards
> >
> >Aleksander
> >
> >
> >
> >
> >
> >Dnia 2 maja 2011 22:37 Christian Gaser <[log in to unmask]>
> napisa=C5=82(a):
> >
> >> Dear Aleksander,
> >>
> >> as Darren assumed there was some debugging code in the function, =
which I
> forgot to remove. With the newest update r413 this problem should be =
now
> solved.
> >>
> >> Regards,
> >>
> >> Christian
> >>
> >>
> =
_________________________________________________________________________=
___
> >>
> >> Christian Gaser, Ph.D.
> >> Departments of Psychiatry and Neurology
> >> Friedrich-Schiller-University of Jena
> >> Jahnstrasse 3, D-07743 Jena, Germany
> >> Tel: ++49-3641-934752 Fax: ++49-3641-934755
> >> e-mail: [log in to unmask]
> >> http://dbm.neuro.uni-jena.de
> >>
> >>
> >> On Wed, 27 Apr 2011 11:13:34 +0200, [log in to unmask] <[log in to unmask]> =
wrote:
> >>
> >> >Hallo,
> >> >
> >> >we are trying to correct for non-stationary of smoothness
> >> >and we get following error report
> >> >
> >> >Use local RPV values to correct for non-stationary of smoothness.
> >> >Failed 'Threshold and transform spmT-maps'
> >> >Undefined function or variable 'K'.
> >> >In file "C:\Program Files\spm8\toolbox\vbm8\cg_spmT2x.m" (v404),
> function
> >> >"cg_spmT2x" at line 321.
> >> >
> >> >The following modules did not run:
> >> >Failed: Threshold and transform spmT-maps
> >> >
> >> >
> >> >We found this :
> >> >"Hi, I have removed the interface to the non-stationarity =
correction in
> >> >VBM8 because
> >> >of the interferences with the SPM8 GUI. However, there is still a
> hidden
> >> >option if
> >> >you use the conversion tools for transforming and thresholding =
T-or
> >> >F-maps:
> >> >VBM8|Data presentation|Threshodl and transform T-maps"
> >> >
> >> >And we followed this sequence
> >> >
> >> >The non-stationary cluster correction in VBM8 can be
> >> >implemented
> >> >by the following sequence of menu steps:
> >> >Toolbox > VBM8 > Data presentation > Threshold and transform =
spmT-maps
> >
> >> >.Cluster
> >> >extent threshold > ..k-value > ...Correct for non-isotropic =
smoothness
> >> >yes.
> >> >
> >> >but without success.
> >> >
> >> >Do you have some experience with this part of the Vbm8 tool?
> >> >
> >> >We would be thankful for any help.
> >> >
> >> >With kind regards
> >> >
> >> >Aleksander
> >>
>
>
------------------------------
Date: Tue, 17 May 2011 18:16:59 +0100
From: Michael Thomas Smith <[log in to unmask]>
Subject: Re: After estimation design matrix loses most regressors.
Thanks for the reply.
It seems likely it's something to do with my install of SPM, as Thomas =20
was able to run exactly the same job on his computer and get the =20
correct result. I'll reinstall SPM and try again. (by the way: I found =20
adding extra regressors caused the left-out columns to change...all =20
very weird).
Thanks again for the suggestions and help,
I'll be back with more questions if the reinstall doesn't work!
Mike.
Quoting Thomas Nichols <[log in to unmask]> on Tue, 17 May 2011 =20
12:51:23 +0100:
> Dear Mike,
>
> Before estimation, the displayed design matrix is original matrix X =
(with
> the exception that DCT drift basis elements aren't shown). After
> estimation, the 'filtered and whitened' design matrix (xX.xKXs.X =3D =
K*W*X) is
> shown. If certain columns appear to be zeroed out by whitening, that =
is
> because the corresponding scans were found to have super-high =
variance.
> (See my earlier post on errors with PET data).
>
> I can't figure out why this is happening, though, as each session's =
data is
> scaled separately. You can check out the scan-by-scan scale factors =
used to
> bring each session to a Grand Mean of 100 by looking at SPM.xGX.gSF; =
if
> there is crazy variation in this (e.g. super-low values for sessions 1 =
& 3)
> it would explain the effect. Then the question is why are the =
computed
> globals so different over sessions... maybe crazy-large artifactual =
values
> in sessions 2, 4, 5,..,8?
>
> Hope this helps with the detective work!
>
> -Tom
>
>
> On Wed, May 11, 2011 at 12:57 PM, Michael Thomas Smith <
> [log in to unmask]> wrote:
>
>> I'm interested in the correlation between a time series and the =
voxels in
>> the brain. To find out more I made a GLM
>> (see http://www.sal.mvm.ed.ac.uk/images/problem1.png ).
>>
>> Before estimation it looks fine (I think?).
>>
>> During estimation however, 6 of the 8 columns are set to zero (see =
inset in
>> bottom-left corner of the linked image). Just sessions 1 and 3 output =
beta
>> images. There are no errors or warnings expressed during estimation, =
and the
>> matlab output appears ok.
>>
>> - I've confirmed the number of images in each session is equal to the
>> number of values in the .txt regressor files.
>> - I've tried adding conditions to each session (just a single event =
near
>> the start of each session) to see if it's the lack of conditions =
that's
>> upsetting SPM. (this didn't make any difference).
>> - I've rebuilt the design matrix from scratch by hand, using the =
interface,
>> but that didn't make any difference.
>>
>> Looking forward to any suggestions!
>>
>> Thanks,
>>
>> Mike Smith
>>
>> --
>> The University of Edinburgh is a charitable body, registered in
>> Scotland, with registration number SC005336.
>>
>
>
>
> --
> ____________________________________________
> Thomas Nichols, PhD
> Principal Research Fellow, Head of Neuroimaging Statistics
> Department of Statistics & Warwick Manufacturing Group
> University of Warwick
> Coventry CV4 7AL
> United Kingdom
>
> Email: [log in to unmask]
> Phone, Stats: +44 24761 51086, WMG: +44 24761 50752
> Fax: +44 24 7652 4532
>
--=20
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.
------------------------------
Date: Tue, 17 May 2011 21:53:26 +0100
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Re-Referencing of EEG Data
Dear Urs,
On Tue, May 17, 2011 at 10:50 AM, Urs Bachofner <[log in to unmask]> =
wrote:
> I have a question regarding the concept of EEG data Re-referencing in =
Spm8.
> The way I see it, re-referencing is a very important step prior to =
Source
> Analysis. To get useful data, the Signals should be re-referenced to
> average.
> According to the SPM8 Manual P. 110 we can use spm_eeg_montage to do =
this.
>
> The data I'd like to process is recorded with a 128-channel EEG-net =
with the
> reference electrode at CZ.
> According to the SPM8 Manual, for average reference the matrix should =
have
> (N-1)/N at the diagonal and -1/N elsewhere.
> In my case this results in 0.9921875 at the diagonal and -0.0078125
> elsewhere.
>
> Two questions:
> 1. These numbers are so close to the original matrix (1 at diagonal =
and 0
> elsewhere) which is said to not change anything. Is this matrix =
correct?
>
Yes, it's all OK. The more electrodes you have the closer the average
will be to zero but remember that the actual values also depend on the
data, not only on the weights so you should still re-reference.
> 2. Since electrodes that are closer to the reference (in this case CZ) =
have
> a higher amplitude recorded, shouldn't such electrodes be weighted
> differently than electrodes that are more distant to CZ? Am I missing =
the
> point here?
>
>
No, the average reference is just what it is, every channel minus the
average of all channels. It does not depend on where the original
reference is.
> And finally, besides Filtering, epoching, Artefact Detection (removing =
bad
> channels and bad trials), Re-referencing, and baseline correction are =
there
> other preprocessing steps that are necessary to get good data from my =
evoked
> potentials?
No, these are the basic steps. You might try using the robust
averaging option. Also there is an option in MEEGTools for correcting
eye blinks. You might or might not need it depending on your data.
> And is there a certain order in which these steps should be
> executed?
>
I've just presented a slide about that at the SPM course last week.
Basically it says the following:
----
Considerations for order of processing steps:
It=E2=80=99s better to filter before epoching unless only small part of =
the
data is relevant. As an alternative one could pad the epochs of
interest with extra data and discard it later.
Downsampling speeds up the other steps and reduces disk space usage,
but it involves low-pass filtering and...
Low-pass or band-pass filtering before high-pass can generate ringing
at the edges, which is especially problematic for epoched data. So
high-pass should come first, but...
Only some channel types (EEG, MEG, LFP etc.) are filtered. So channel
types should be set correctly first (Prepare, Montage).
---
Best,
Vladimir
> Thank you very much for you help.
>
>
>
>
------------------------------
Date: Tue, 17 May 2011 16:47:10 -0400
From: Mobin Anandwala <[log in to unmask]>
Subject: uj in bilinear state equation
Good Afternoon
This is Mobin Anandwala and I have a question regarding the variable uj =
in
the bilinear state equation. The equation as stated is z' =3D (A +
sigma(uj*Bj))*z + Cu. As I understand the u vector times the C matrix =
is a
vector consisting of input functions. My question is that since the u
vector consists of input functions is the uj variable a scalar that is =
the
maximum of the input function or is it a vector? When I tried to use uj =
as
a vector I obtained a matrix multiplication error in Matlab with Bj as =
the
dimensions did not match (u being an n x 1 vector and Bj being 4 x 4). =
I am
currently using uj as a scalar constant with it being the maximum of =
input
function (current data that I have has u2(t) in the u vector and the uj
being its maximum).
Thank you
Mobin Anandwala
------------------------------
End of SPM Digest - 16 May 2011 to 17 May 2011 (#2011-145)
**********************************************************
=========================================================================
Date: Wed, 18 May 2011 09:27:47 +0800
Reply-To: Linling Li <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Linling Li <[log in to unmask]>
Subject: Re: Problem about how to deal with the activation
withinventricles of the brain
Comments: To: Burak Erdeniz <[log in to unmask]>
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Cg==
--=====003_Dragon000002560673_=====--
=========================================================================
Date: Wed, 18 May 2011 08:49:54 +0200
Reply-To: maaike rive <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: maaike rive <[log in to unmask]>
Subject: FIR
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf305e2565cb289704a3874b5c
Message-ID: <[log in to unmask]>
--20cf305e2565cb289704a3874b5c
Content-Type: text/plain; charset=ISO-8859-1
Dear all,
I am planning to do a FIR analysis and as wondering about the timebins:
would it be ok to choose seconds instead of TR's as timeunits, or are there
reasons to advise against that?
Thanks, Maaike
--20cf305e2565cb289704a3874b5c
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
<div>Dear all,</div>
<div>=A0</div>
<div>I am planning to do a FIR analysis and as wondering about the timebins=
: would it be ok to choose seconds instead of TR's as timeunits, or are=
there reasons to advise against that?</div>
<div>=A0</div>
<div>Thanks, Maaike</div>
--20cf305e2565cb289704a3874b5c--
=========================================================================
Date: Wed, 18 May 2011 10:06:16 +0200
Reply-To: Torben Ellegaard Lund <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Torben Ellegaard Lund <[log in to unmask]>
Subject: Re: Problem about how to deal with the activation
withinventricles of the brain
Comments: To: Linling Li <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-version: 1.0
Content-type: multipart/alternative;
boundary="Boundary_(ID_t9pmUlO15I4ov7Zxtd0LVw)"
Message-ID: <[log in to unmask]>
--Boundary_(ID_t9pmUlO15I4ov7Zxtd0LVw)
Content-type: text/plain; charset=GB2312
Content-transfer-encoding: quoted-printable
Dear Linling
To avoid this in the future you may want to record pulse and respiration =
and use for instance RETROICOR (Glover et al. 2000).
Best
Torben
Den Uge:20 18/05/2011 kl. 03.27 skrev Linling Li:
> Dear Burak,
> =20
> Thank you for your reply and I will try that method you suggested.
> =20
> =20
> =20
> 2011-05-18
> =C0=EE=C1=D5=C1=E1
>=20
> Linling Li
> Research Centre for Neural Engineering
> --------------------------------------
> Phone: +86-755-86392232
> Email: [log in to unmask]
> Shenzhen Institutes of Advanced Technology,
> Chinese Academy of Sciences.
> =B7=A2=BC=FE=C8=CB=A3=BA Burak Erdeniz
> =B7=A2=CB=CD=CA=B1=BC=E4=A3=BA 2011-05-14 20:40:54
> =CA=D5=BC=FE=C8=CB=A3=BA Linling Li
> =B3=AD=CB=CD=A3=BA
> =D6=F7=CC=E2=A3=BA Re: [SPM] Problem about how to deal with the =
activation withinventricles of the brain
> Hi Linling,
>=20
> Usually the bestway is to define an VOI and than get the activations =
in that region and use it as an additional regressor similar to using =
motion parameters. People usually choose eyeballs for VOI.
>=20
> Cheers
> Burak
>=20
> 2011/5/14 Linling Li <[log in to unmask]>
> Dear all,
> =20
> Could anyone give me some suggestion about how to deal with the =
activation within ventricles of the brain in order to show more =
meaningful activation pattern?
> =20
> Thanks in advance!
> =20
> 2011-05-14
> =C0=EE=C1=D5=C1=E1
>=20
> Linling Li
> Research Centre for Neural Engineering
> --------------------------------------
> Phone: +86-755-86392232
> Email: [log in to unmask]
> Shenzhen Institutes of Advanced Technology,
> Chinese Academy of Sciences.
>=20
>=20
>=20
> --=20
> Burak Erdeniz
> Phd Student
> Psychology & Computer Science Department
> Health & Human Sciences Research Institute
> 2f240 Health Building
> University of Hertfordshire
> College Lane
> Hatfield
> Herts
> AL 10 9AB
> omnia vincit amor
>=20
--Boundary_(ID_t9pmUlO15I4ov7Zxtd0LVw)
Content-type: text/html; charset=GB2312
Content-transfer-encoding: quoted-printable
<html><head><Bass href=3D"x-msg://42/"></head><body style=3D"word-wrap: =
break-word; -webkit-nbsp-mode: space; -webkit-line-break: =
after-white-space; ">Dear Linling<div><br></div><div>To avoid this =
in the future you may want to record pulse and respiration and use for =
instance RETROICOR (Glover et al. =
2000).</div><div><br></div><div><br></div><div>Best</div><div>Torben<br><d=
iv><font class=3D"Apple-style-span" face=3D"Verdana"><span =
class=3D"Apple-style-span" style=3D"font-size: small; =
"><br></span></font></div><div><font class=3D"Apple-style-span" =
face=3D"Verdana"><span class=3D"Apple-style-span" style=3D"font-size: =
small;"><br></span></font></div><div><font class=3D"Apple-style-span" =
face=3D"Verdana"><span class=3D"Apple-style-span" style=3D"font-size: =
small;"><br></span></font><div><div>Den Uge:20 18/05/2011 kl. 03.27 =
skrev Linling Li:</div><br class=3D"Apple-interchange-newline"><blockquote=
type=3D"cite"><span class=3D"Apple-style-span" style=3D"border-collapse: =
separate; font-family: Helvetica; font-style: normal; font-variant: =
normal; font-weight: normal; letter-spacing: normal; line-height: =
normal; orphans: 2; text-indent: 0px; text-transform: none; white-space: =
normal; widows: 2; word-spacing: 0px; -webkit-border-horizontal-spacing: =
0px; -webkit-border-vertical-spacing: 0px; =
-webkit-text-decorations-in-effect: none; -webkit-text-size-adjust: =
auto; -webkit-text-stroke-width: 0px; font-size: medium; "><div =
style=3D"margin-top: 10px; margin-right: 10px; margin-bottom: 10px; =
margin-left: 10px; font-family: verdana; font-size: 10pt; "><div><font =
size=3D"2" face=3D"Verdana">Dear =
Burak,</font></div><div> </div><div>Thank you for your reply and I =
will try that method you suggested.</div><div> </div><div><font =
color=3D"#000080" size=3D"2" =
face=3D"Verdana"></font> </div><div><font color=3D"#000080" =
size=3D"2" face=3D"Verdana"></font> </div><div><font =
color=3D"#c0c0c0" size=3D"2" face=3D"Verdana">2011-05-18</font></div><font=
color=3D"#000080" size=3D"2" face=3D"Verdana"><hr align=3D"left" =
color=3D"#b5c4df" size=3D"1" style=3D"width: 100px; "></font><div><font =
color=3D"#c0c0c0" size=3D"2" =
face=3D"Verdana"><span><div><div>=C0=EE=C1=D5=C1=E1<br><br>Linling =
Li</div><div>Research Centre for Neural =
Engineering<br>--------------------------------------<br>Phone: =
+86-755-86392232<br>Email: <a href=3D"mailto:[log in to unmask]"=
style=3D"color: blue; text-decoration: underline; =
">[log in to unmask]</a><br>Shenzhen Institutes of Advanced =
Technology,<br>Chinese Academy of =
Sciences.</div></div></span></font></div><hr color=3D"#b5c4df" =
size=3D"1"><div><font size=3D"2" =
face=3D"Verdana"><strong>=B7=A2=BC=FE=C8=CB=A3=BA</strong><span =
class=3D"Apple-converted-space"> </span>Burak =
Erdeniz</font></div><div><font size=3D"2" =
face=3D"Verdana"><strong>=B7=A2=CB=CD=CA=B1=BC=E4=A3=BA</strong><span =
class=3D"Apple-converted-space"> </span>2011-05-14 =
20:40:54</font></div><div><font size=3D"2" =
face=3D"Verdana"><strong>=CA=D5=BC=FE=C8=CB=A3=BA</strong><span =
class=3D"Apple-converted-space"> </span>Linling =
Li</font></div><div><font size=3D"2" =
face=3D"Verdana"><strong>=B3=AD=CB=CD=A3=BA</strong></font></div><div><fon=
t size=3D"2" face=3D"Verdana"><strong>=D6=F7=CC=E2=A3=BA</strong><span =
class=3D"Apple-converted-space"> </span>Re: [SPM] Problem about how =
to deal with the activation withinventricles of the =
brain</font></div><div><font size=3D"2" =
face=3D"Verdana"></font></div><div><font size=3D"2" face=3D"Verdana">Hi =
Linling,<br><br>Usually the bestway is to define an VOI and than get the =
activations in that region and use it as an additional regressor similar =
to using motion parameters. People usually choose eyeballs for =
VOI.<br><br>Cheers<br>Burak<br><br><div class=3D"gmail_quote">2011/5/14 =
Linling Li<span class=3D"Apple-converted-space"> </span><span =
dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]" style=3D"color: =
blue; text-decoration: underline; =
">[log in to unmask]</a>></span><br><blockquote class=3D"gmail_quote" =
style=3D"margin-top: 0px; margin-bottom: 0px; margin-left: 0.8ex; =
border-left-color: rgb(204, 204, 204); border-left-width: 1px; =
border-left-style: solid; margin-right: 0px; padding-left: 1ex; "><div =
style=3D"margin-top: 10px; margin-right: 10px; margin-bottom: 10px; =
margin-left: 10px; font-family: verdana; font-size: 10pt; "><div><font =
size=3D"2" face=3D"Verdana">Dear =
all,</font></div><div> </div><div>Could anyone give me some =
suggestion about how to =
deal with the activation within ventricles o=
f the brain in order to show more meaningful activation =
pattern?</div><div> </div><div>Thanks in advance!</div><div><font =
size=3D"2" face=3D"Verdana"></font> </div><div align=3D"left"><font =
color=3D"#c0c0c0" size=3D"2" face=3D"Verdana">2011-05-14</font></div><font=
size=3D"2" face=3D"Verdana"><hr align=3D"left" size=3D"2" =
style=3D"min-height: 2px; width: 122px; "><div><font color=3D"#c0c0c0" =
size=3D"2" face=3D"Verdana"><span><div><div>=C0=EE=C1=D5=C1=E1<br><br>Linl=
ing Li</div><div>Research Centre for Neural =
Engineering<br>--------------------------------------<br>Phone: =
+86-755-86392232<br>Email: <a href=3D"mailto:[log in to unmask]"=
target=3D"_blank" style=3D"color: blue; text-decoration: underline; =
">[log in to unmask]</a><br>Shenzhen Institutes of Advanced =
Technology,<br>Chinese Academy of =
Sciences.</div></div></span></font></div></font></div></blockquote></div><=
br><br clear=3D"all"><br>--<span =
class=3D"Apple-converted-space"> </span><br>Burak Erdeniz<br>Phd =
Student<br>Psychology & Computer Science Department<br>Health & =
Human Sciences Research Institute<br>2f240 Health Building<br>University =
of Hertfordshire<br>College Lane<br>Hatfield<br>Herts<br>AL 10 =
9AB<br>omnia vincit =
amor<br><br></font></div></div></span></blockquote></div><br></div></div><=
/body></html>=
--Boundary_(ID_t9pmUlO15I4ov7Zxtd0LVw)--
=========================================================================
Date: Wed, 18 May 2011 09:33:40 +0100
Reply-To: Chris Leatherday <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Chris Leatherday <[log in to unmask]>
Subject: Normalising a point
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear SPMers
I have a series of points that I would like to translate from native spac=
e to MNI space. I'm sorry if this is an obvious question, and I've noted =
that it seems to have been discussed a couple of times already. In attemp=
ting to follow Gem5 of John's Gems 2, I am unable to do the part where h=
e asks the user to choose the deformations inversion option...=20
I am running SPM8, and I can't seem to get anything that looks like iy*.i=
mg. Running the "inverse" option in deformations just gives me another y_=
*.nii file, and I can't seem to find a method of creating an iy*.img file=
.
Could somebody please point me in the right direction?
Thank you
Chris
=========================================================================
Date: Wed, 18 May 2011 10:10:46 +0100
Reply-To: Marco Sperduti <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Marco Sperduti <[log in to unmask]>
Subject: Small Group
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary="0-569334406-1305709846=:4119"
Message-ID: <[log in to unmask]>
--0-569334406-1305709846=:4119
Content-Type: text/plain; charset=iso-8859-1
Content-Transfer-Encoding: quoted-printable
Dear all,
For preliminary results I would like to compare activation between two expe=
rimental conditions in two groups. My problem is that the control group is =
made of 20 subjects while in the patient group I have only 4 subjects.
Which is the best statistical model? Should I just use a full factorial des=
ign?=20
Thank you,
Marco=A0=20
--0-569334406-1305709846=:4119
Content-Type: text/html; charset=iso-8859-1
Content-Transfer-Encoding: quoted-printable
<table cellspacing=3D"0" cellpadding=3D"0" border=3D"0" ><tr><td valign=3D"=
top" style=3D"font: inherit;">Dear all,<br><br>For preliminary results I wo=
uld like to compare activation between two experimental conditions in two g=
roups. My problem is that the control group is made of 20 subjects while in=
the patient group I have only 4 subjects.<br><br>Which is the best statist=
ical model? Should I just use a full factorial design? <br><br>Thank you,<b=
r><br>Marco <br></td></tr></table>
--0-569334406-1305709846=:4119--
=========================================================================
Date: Wed, 18 May 2011 14:16:12 +0000
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: channel selection
Comments: To: Fahimeh Mamashli <[log in to unmask]>
Content-Transfer-Encoding: base64
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MIME-Version: 1.0
Message-ID: <[log in to unmask]>
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riBmcm9tIE9yYW5nZQ==
=========================================================================
Date: Wed, 18 May 2011 15:25:17 +0100
Reply-To: SUBSCRIBE SPM Yihui Hung <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: SUBSCRIBE SPM Yihui Hung <[log in to unmask]>
Subject: export betas over multiple coordinates
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Hello,
I wonder how to export the betas over the coordinates which showed a sign=
ificant effect. I know how to export one beta of one coordinate which sho=
wed a significant effect. However, I would like to know how to export bet=
as over all of the coordinates in the statistic table at once.=20
Thank you for any advice!
Sincerely,
Yihui=20
=========================================================================
Date: Wed, 18 May 2011 15:35:23 +0100
Reply-To: Subscribe Spm J <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Subscribe Spm J <[log in to unmask]>
Subject: MAUDSLEY ANNUAL REVIEWS 2011 - Institute of Psychiatry,
KCL London, UK
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
MAUDSLEY ANNUAL REVIEWS 2011=20
Institute of Psychiatry, KCL London, UK=20
Monday, 27 June 2011 to Wednesday, 29 June 2011
(event website: http://www.iop.kcl.ac.uk/events/?id=3D1202)=20
=20
We are delighted to announce the 2011 Maudsley Annual Reviews of Psychiat=
ry that build on the success of our inaugural meeting and aim to bridge t=
he gap between scientific developments in mental health and their applica=
tion in clinical care.=20
Each year we select three themes that represent topics in psychiatry wher=
e substantial developments were achieved in understanding or treating men=
tal illness that are directly relevant to clinical practice. Each year we=
bring together internationally renowned researchers and clinicians to di=
scuss their findings and share their perspective on each of their expert =
themes in a clinically relevant manner.=20
The three themes covered in the 2011 Maudsley Annual Reviews of Psychiatr=
y focus on advances in Major Depressive Disorder, in promoting the physic=
al wellbeing of patients with mental disorders and in improving clinical =
and functional outcomes through better adherence.=20
Key Speakers for the Core Scientific programme: Norman Sartorius, Rudolf =
Uher, Marieke Wichers, George Papakostas, Mark De Hert, Peter Haddad, And=
re Tylee, John Hague, Munk-J=C3=B9rgensen and Francesc Colom.=20
=20
Meeting Chairs: Sophia Frangou, Philip McGuire, Rudolf Uher=20
=20
The event has been awarded 9 ECMEC credits from the European Accreditatio=
n Council for Continuing Medical Education=20
=20
Programme, Registration form, Venue and Accommodation details are availab=
le from the website
=20
=========================================================================
Date: Wed, 18 May 2011 10:41:28 -0400
Reply-To: "Rajagopalan, Venkateswaran" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Rajagopalan, Venkateswaran" <[log in to unmask]>
Subject: SnPM->2 group ANOVA results
MIME-Version: 1.0
Content-Type: multipart/alternative;
boundary="----_=_NextPart_001_01CC1569.AB9D1A7F"
Message-ID: <[log in to unmask]>
This is a multi-part message in MIME format.
------_=_NextPart_001_01CC1569.AB9D1A7F
Content-Type: text/plain;
charset=iso-8859-1
Content-Transfer-Encoding: quoted-printable
Dear All,
=20
I have one control and 4 patient groups in whom I perfomed T1-w VBM and I a=
m=
trying to run non-parametric tests=20
=20
I ran >2 group ANOVA 1 scan/subject using SnPM. I chose the following=20
When I run the results part in SnPM=20
my F-statistic comes automatically with positive effects=20
write filtered statistic image - NO
results for which image - F
Inference method -Voxelwise
Voxelwise:Use corrected thresh - FWE
=46WE-CORRECTED P VALUE -0.05
=20
I get a significant MIP image, I would like to do get T-test results on the=
=
individual comparisons like control>patient_group1, =
control>patient_group2... how to run these or get these results. In SPM =
parametric method I design my own design and contrast matrix I am wondering=
=
how to give my own contrasts of interests here in SnPM.
=20
Thanks
=20
Venkateswaran
=20
=20
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
Please consider the environment before printing this e-mail
Cleveland Clinic is ranked one of the top hospitals
in America by U.S.News & World Report (2010). =20
Visit us online at http://www.clevelandclinic.org for
a complete listing of our services, staff and
locations.
Confidentiality Note: This message is intended for use
only by the individual or entity to which it is addressed
and may contain information that is privileged,
confidential, and exempt from disclosure under applicable
law. If the reader of this message is not the intended
recipient or the employee or agent responsible for
delivering the message to the intended recipient, you are
hereby notified that any dissemination, distribution or
copying of this communication is strictly prohibited. If
you have received this communication in error, please
contact the sender immediately and destroy the material in
its entirety, whether electronic or hard copy. Thank you.
------_=_NextPart_001_01CC1569.AB9D1A7F
Content-Type: text/html;
charset=iso-8859-1
Content-Transfer-Encoding: quoted-printable
<HTML dir=3Dltr><HEAD>
<META http-equiv=3DContent-Type content=3D"text/html; charset=3Dunicode">
<META content=3D"MSHTML 6.00.2900.3698" name=3DGENERATOR></HEAD>
<BODY>
<DIV><FONT face=3DArial color=3D#000000 size=3D2>Dear All,</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>I have one control and 4 patient groups in=
=
whom I perfomed T1-w VBM and I am trying to run non-parametric =
tests </FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>I ran >2 group ANOVA 1 scan/subject =
using SnPM. I chose the following </FONT></DIV>
<DIV><FONT face=3DArial size=3D2>When I run the results part in SnPM =
</FONT></DIV>
<DIV><FONT face=3DArial size=3D2>my F-statistic comes automatically with =
positive effects </FONT></DIV>
<DIV><FONT face=3DArial size=3D2>write filtered statistic image - =
NO</FONT></DIV>
<DIV><FONT face=3DArial size=3D2>results for which image - F</FONT></DIV>
<DIV><FONT face=3DArial size=3D2>Inference method -Voxelwise</FONT></DIV>
<DIV><FONT face=3DArial size=3D2>Voxelwise:Use corrected thresh - =
=46WE</FONT></DIV>
<DIV><FONT face=3DArial size=3D2>FWE-CORRECTED P VALUE -0.05</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>I get a significant MIP image, I would lik=
e=
to do get T-test results on the individual comparisons like =
control>patient_group1, control>patient_group2... how to run these or=
=
get these results. In SPM parametric method I design my own design and =
contrast matrix I am wondering how to give my own contrasts of interests =
here in SnPM.</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>Thanks</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2>Venkateswaran</FONT></DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<DIV><FONT face=3DArial size=3D2></FONT> </DIV>
<P><pre =
wrap>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
<p class=3DMsoNormal><font size=3D5 color=3Dgreen><span
style=3D'font-size:18.0pt;color:green'></span></font><font
size=3D2 color=3Dnavy face=3DCalibri><span =
style=3D'font-size:10.0pt;font-family:Calibri;
color:navy'> </span></font><font size=3D1 color=3Dgreen face=3DArial><span
style=3D'font-size:7.0pt;font-family:Arial;color:green'>Please consider the=
=
environment before printing this e-mail</span></font><o:p></o:p></p>
Cleveland Clinic is ranked one of the top hospitals
in America by U.S.News & World Report (2010). =20
Visit us online at http://www.clevelandclinic.org for
a complete listing of our services, staff and
locations.
Confidentiality Note: This message is intended for use
only by the individual or entity to which it is addressed
and may contain information that is privileged,
confidential, and exempt from disclosure under applicable
law. If the reader of this message is not the intended
recipient or the employee or agent responsible for
delivering the message to the intended recipient, you are
hereby notified that any dissemination, distribution or
copying of this communication is strictly prohibited. If
you have received this communication in error, please
contact the sender immediately and destroy the material in
its entirety, whether electronic or hard copy. Thank you.
</pre></P></BODY></HTML>
------_=_NextPart_001_01CC1569.AB9D1A7F--
=========================================================================
Date: Wed, 18 May 2011 15:36:02 +0100
Reply-To: Chantal Roggeman <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Chantal Roggeman <[log in to unmask]>
Subject: artifacts after Dartel
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear SPMmers,
I have a problem with Dartel - normalise to MNI space. It runs all right,=
but my images are distorted after the Dartel normalisation.=20
For the whole preprocessing, I followed basically the manual: realignment=
(estimate and reslice), coregistration (estimate), New Segment, run Dart=
el (create Template), then Dartel normalize to MNI space.
Everything ran without errors, but my functional images are distorted aft=
er the last step. The original and realigned images were all right, so it=
must happen in a later stage. It looks like some part of the brain is st=
retched out. The distortion looks different in different sessions, but is=
the same for all images in the same session.=20
Is this a known problem? Does anybody know why it happens and how I can a=
void it? Since everything ran smoothly without errors, I have no idea wha=
t the problem could be...
thanks a lot!
Chantal
=========================================================================
Date: Wed, 18 May 2011 20:30:19 +0530
Reply-To: Kavita Vemuri <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Kavita Vemuri <[log in to unmask]>
Subject: Onsets & Duration - in task independent experiment
MIME-Version: 1.0
Content-Type: text/plain; charset=utf-8
Content-Transfer-Encoding: 7bit
Message-ID: <[log in to unmask]>
Hi
My experiment has no explicit task(well, that is an oxymoron!) - requires free viewing of moving images. The fMRI collected is collected TR of 2 seconds and the total duration of the experiment is around 8 minutes . At the 1st level analysis phase, I notice big variations when 'Onset'(block) is changed from 20 to 22 with a duration of 20, for example. The design is in seconds. Is this expected? For example: At an onset = 20 & duration = 20, I see not even one voxel highlighted but when the onset=22 and the duration= 22 or 25, there is huge response.
Question: in an task independent/free viewing paradigm, can blocks be selected in the design?
Regards
Kavita
=========================================================================
Date: Wed, 18 May 2011 16:32:30 +0100
Reply-To: "Dylan D. Wagner" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Dylan D. Wagner" <[log in to unmask]>
Subject: Neuroscience software survey: What is popular, what has problems?
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear list,
The developers of the excellent neurodebian repository have requested t=
hat I post this to the spm list. It's quick and informative!
---
Dear neuroscience researchers and their IT staff
We invite you to participate in a survey on software usage and computing
environments in neuroscience research. It will take no more than five
minutes to fill it out. Immediately after sending your answers you will
get to see a summary of how other participants have responded before.
This data will eventually be made available to software vendors and
distributors to determine advantages and issue of popular computing
environments in neuroscience research.
Learn about what fellow neuroscientists are doing to address their comput=
ing
demands -- take the survey!
http://goo.gl/euIMc
Thanks,
--=20
PyMVPA/NeuroDebian Team: Yaroslav O. Halchenko & Michael Hanke
Postdoctoral Fellows, Department of Psychological and Brain Sciences
Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
=========================================================================
Date: Wed, 18 May 2011 18:44:18 +0000
Reply-To: Giuseppe Signorello <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Giuseppe Signorello <[log in to unmask]>
Subject: time series extraction
Content-Type: multipart/alternative;
boundary="_9bf33669-5ed3-4d41-9cc4-eb3288627bb9_"
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
--_9bf33669-5ed3-4d41-9cc4-eb3288627bb9_
Content-Type: text/plain; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
Hi=2C
after the execution of preprocessing of Fmri files=2C I would like to extr=
act the time series but if I consider the steps of manual I have several pr=
oblem.=20
- I obtain the design matrix (from first level specification)=2C but=20
when I use the contrast manager and I define the Photic=2C Motion=2C=
Attention contrasts using the spm examples (the same vectors of the two t-=
contrast and the same matrix of f-contrast) and I run the batch file --> th=
ere's an error and I do not understand the reason.
Could the contrasts be wrong?
I have a dataset with 425 scans=2C TR=3D 2.7.
In the Spm-manual I do not find information about it.
Could you help me?
Excuse me for my english.Thanks for your answers.
G.S.=20
=
--_9bf33669-5ed3-4d41-9cc4-eb3288627bb9_
Content-Type: text/html; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
<html>
<head>
<style><!--
.hmmessage P
{
margin:0px=3B
padding:0px
}
body.hmmessage
{
font-size: 10pt=3B
font-family:Tahoma
}
--></style>
</head>
<body class=3D'hmmessage'>
Hi=2C<br>after the execution of preprocessing of Fmri files=2C =3B I wo=
uld like to extract the time series but if I consider the steps of manual I=
have several problem. <br>- I obtain the design matrix (from first level s=
pecification)=2C but <br> =3B =3B =3B =3B =3B =3B w=
hen I use the contrast manager and I define the Photic=2C Motion=2C Attenti=
on contrasts using the spm examples (the same vectors of the two t-contrast=
and the same matrix of f-contrast) and I run the batch file -->=3B there=
's an error and I do not understand the reason.<br><br> =3BCould the co=
ntrasts be wrong?<br>I have a dataset with 425 scans=2C TR=3D 2.7.<br><br>I=
n the Spm-manual I do not find information about it.<br>Could you help me?<=
br><br>Excuse me for my english.Thanks for your answers.<br><br>G.S. <br> =
</body>
</html>=
--_9bf33669-5ed3-4d41-9cc4-eb3288627bb9_--
=========================================================================
Date: Wed, 18 May 2011 20:31:42 +0100
Reply-To: Chaleece Sandberg <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Chaleece Sandberg <[log in to unmask]>
Subject: trouble with mask in small volume correction
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Hello SPMers,
I am trying to do a small volume correction on a group analysis using an =
anatomical mask. I created a mask for left IFG using MRIcro following ins=
tructions on http://imaging.mrc-cbu.cam.ac.uk/imaging/SmallVolumeCorrecti=
on. I checked the mask against the uncorrected activation peaks in MRIcro=
N to make sure that the activation I was interested in fell within my ana=
tomical mask. When I selected the mask as the image for the svc, the only=
area of activation that came up was a random dot in the right hemisphere=
. How is that possible if I'm restricting the region to the left IFG? I d=
ouble-checked to make sure the mask was definitely in left hemisphere and=
the activation that I am interested in is in left hemisphere. When I do =
a small volume correction using a 10mm sphere around the uncorrected peak=
, I get that peak as significant at FWE p<.05, but I'd prefer to use the =
anatomical mask.
Any help would be greatly appreciated!
Thanks,
Chaleece
=========================================================================
Date: Wed, 18 May 2011 14:14:03 -0700
Reply-To: Nicholas DiQuattro <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Nicholas DiQuattro <[log in to unmask]>
Subject: Sold State Drives
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=bcaec520f21968725804a3935fd2
Message-ID: <[log in to unmask]>
--bcaec520f21968725804a3935fd2
Content-Type: text/plain; charset=ISO-8859-1
Hello SPM,
Has anyone had any experience with running SPM on solid state drives? Do you
see much of an improvement in processesing speeds?
thanks,
Nick
--
Nicholas DiQuattro
Junior Specialist
Integrated Attention Lab
Center for Mind and Brain
267 Cousteau Place Davis, CA 95618
tel: (530) 297-4472
--bcaec520f21968725804a3935fd2
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Hello SPM,<div><br></div><div>Has anyone had any experience with running SP=
M on solid state drives? Do you see much of an improvement in=A0processesin=
g=A0speeds?<br clear=3D"all"><br></div><div>thanks,</div><div>Nick</div><di=
v><br>
-- <br>Nicholas DiQuattro<br>Junior Specialist<br>Integrated Attention Lab<=
br>Center for Mind and Brain<br>267 Cousteau Place=A0=A0 Davis, CA=A0 95618=
<br>tel: (530) 297-4472 <br>
</div>
--bcaec520f21968725804a3935fd2--
=========================================================================
Date: Wed, 18 May 2011 18:39:36 -0400
Reply-To: Jonathan Peelle <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jonathan Peelle <[log in to unmask]>
Subject: Re: artifacts after Dartel
Comments: To: Chantal Roggeman <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Dear Chantal,
Most likely what you are describing is a result of how DARTEL moves
the data to MNI space, and is not something to be concerned about.
See a number of previous posts (try searching for "functional DARTEL"
or something similar). For example:
https://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3Dind0908&L=3DSPM&P=3DR895
or
https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=3Dind0910&L=3DSPM&P=3DR3826&=
1=3DSPM
Hope this helps!
Jonathan
On Wed, May 18, 2011 at 10:36 AM, Chantal Roggeman
<[log in to unmask]> wrote:
> Dear SPMmers,
>
> I have a problem with Dartel - normalise to MNI space. It runs all right,=
but my images are distorted after the Dartel normalisation.
>
> For the whole preprocessing, I followed basically the manual: realignment=
(estimate and reslice), coregistration (estimate), New Segment, run Dartel=
(create Template), then Dartel normalize to MNI space.
>
> Everything ran without errors, but my functional images are distorted aft=
er the last step. The original and realigned images were all right, so it m=
ust happen in a later stage. It looks like some part of the brain is stretc=
hed out. The distortion looks different in different sessions, but is the s=
ame for all images in the same session.
>
> Is this a known problem? Does anybody know why it happens and how I can a=
void it? Since everything ran smoothly without errors, I have no idea what =
the problem could be...
>
> thanks a lot!
> Chantal
>
=========================================================================
Date: Thu, 19 May 2011 12:32:18 +1000
Reply-To: Gemma Lamp <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Gemma Lamp <[log in to unmask]>
Subject: anatomy toolbox: small volume correction
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=000e0ce0d8b4697dcc04a397d048
Message-ID: <[log in to unmask]>
--000e0ce0d8b4697dcc04a397d048
Content-Type: text/plain; charset=ISO-8859-1
Hi,
I am currently doing an analysis where I'm limiting my ROIs to specified
sensory areas. When looking at the stats I use a pre-made mask in SPM to do
a small volume correction. However, when I put it into anatomy toolbox,
using the same statistical procedure and then use the anatomy toolbox SVC
with the same ROI mask, i'm getting different cluster sizes and different
areas showing to that in my original stats. Is there a bug in the SVC
through anatomy toolbox? Or is there something I am doing wrong? Is there an
alternative way to do a small volume correction with anatomy toolbox to keep
consistent?
Thanks,
Gemma
--
Gemma Lamp
--000e0ce0d8b4697dcc04a397d048
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Hi,<br><br>I am currently doing an analysis where I'm limiting my ROIs =
to specified sensory areas. When looking at the stats I use a pre-made mask=
in SPM to do a small volume correction. However, when I put it into anatom=
y toolbox, using the same statistical procedure and then use the anatomy to=
olbox SVC with the same ROI mask, i'm getting different cluster sizes a=
nd different areas showing to that in my original stats. Is there a bug in =
the SVC through anatomy toolbox? Or is there something I am doing wrong? Is=
there an alternative way to do a small volume correction with anatomy tool=
box to keep consistent?<br>
<br>Thanks,<br>Gemma<br clear=3D"all"><br>-- <br>Gemma Lamp<br><br><img src=
=3D"http://www.discoveriesneeddollars.org/uploads/DND_email_signature.jpg">=
<br><br>
--000e0ce0d8b4697dcc04a397d048--
=========================================================================
Date: Thu, 19 May 2011 02:12:16 -0700
Reply-To: Mazly Mohamad <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Mazly Mohamad <[log in to unmask]>
Subject: BMA
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary="0-806656023-1305796336=:86840"
Message-ID: <[log in to unmask]>
--0-806656023-1305796336=:86840
Content-Type: text/plain; charset=us-ascii
Dear SPMers
Needs help regarding BMA, I would like to retrieved the mean values from Region
A to region B
In the manual pg 335 under 34.3.4 Summary Statistics and Group Analyses, I've
tried using command for
for i=1:6,
b(i)=BMS.DCM.rfx.bma.Eps(i).B(4,1,1);
end
??? Reference to non-existent field 'Eps'.
I've checked the .bma parameters only have .mEp .sEp .mEps and .sEps
Thanks in advanced
--0-806656023-1305796336=:86840
Content-Type: multipart/related; boundary="0-1120825588-1305796336=:86840"
--0-1120825588-1305796336=:86840
Content-Type: text/html; charset=us-ascii
<html><head><style type="text/css"><!-- DIV {margin:0px;} --></style></head><body><div style="font-family:bookman old style,new york,times,serif;font-size:8pt;color:#003366;"><table width="100%" cellspacing="0" cellpadding="0" align="center"><tbody><tr><td width="100%" height="100%" bgcolor="#eff6fc" valign="top"><table width="100%" height="100%" style="table-layout:fixed;" cellspacing="0" cellpadding="0" align="center"><tbody><tr><td width="10"> </td><td valign="top" style="overflow: hidden; text-overflow: ellipsis; white-space: nowrap;"><table width="100%" style="white-space:normal;" cellspacing="0" cellpadding="0"><tbody><tr><td height="10"> </td></tr><tr><td><font face="bookman old style, new york, times, serif" size="1" color="#003366" style="font-family:bookman old style, new york, times, serif;font-size:8;color:#003366;"><div style="text-align:undefined;"><div>Dear SPMers<br><br>Needs help regarding BMA, I would like to retrieved the mean values
from Region A to region B<br><br>In the manual pg 335 under 34.3.4 Summary Statistics and Group Analyses, I've tried using command for <br> for i=1:6,<br>b(i)=BMS.DCM.rfx.bma.Eps(i).B(4,1,1);<br>end<br><span style="color: rgb(255, 0, 0);">??? Reference to non-existent field 'Eps'.</span><br><br>I've checked the .bma parameters only have .mEp .sEp .mEps and .sEps<br><br>Thanks in advanced<br></div>
</div></font></td></tr><tr><td height="10"> </td></tr></tbody></table></td><td width="10"> </td></tr></tbody></table></td></tr><tr><td height="120" bgcolor="#eff6fc" background="cid:1305795868922@dclient.mail.yahoo.com" align="start"> </td></tr></tbody></table></div></body></html>
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--0-1120825588-1305796336=:86840--
--0-806656023-1305796336=:86840--
=========================================================================
Date: Thu, 19 May 2011 11:32:30 +0200
Reply-To: Maximilian Eck <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Maximilian Eck <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable
Message-ID: <1436250731.1221221.1305797550468.JavaMail.fmail@mwmweb053>
<html><head></head><body bgcolor=3D'#FFFFFF' style=3D'font-size:12px;backgr=
ound-color:#FFFFFF;font-family:Verdana, Arial, sans-serif;'>Dear SPMers,<br=
/><br/>I just tried to extract the VOI timeseries from my fMRI data using a=
mask, which I got from the wfu_pickatlas.<br/><br/>>...<br/>>mask =
=3D spm_select(1, 'img', 'Select mask');<br/>>matlabbatch{1}.spm.util.vo=
i.roi{1}.spm.mask.image =3D cellstr(mask); <br/>>matlabbatch{1}.sp=
m.util.voi.roi{1}.spm.mask.thresh =3D 0.05;<br/>>matlabbatch{1}.spm.util=
.voi.roi{1}.spm.mask.mtype =3D 0;<br/>>...<br/><br/>Using these lines I =
got the error message:<br/><br/>-------------------------------------------=
-----------------------------<br/>Running job #2<br/>----------------------=
--------------------------------------------------<br/>No executable module=
s, but still unresolved dependencies or incomplete module inputs.<br/>The f=
ollowing modules did not run:<br/>Skipped: Volume of Interest<br/><br/>??? =
Error using =3D=3D> cfg_util at 835<br/>Job execution failed. The full l=
og of this run can be found in MATLAB command window, starting with the lin=
es (look for the line showing the exact #job as<br/>displayed in this error=
message)<br/>------------------<br/>Running job #2<br/>------------------<=
br/><br/>Error in =3D=3D> spm_jobman at 217<br/><br/>Is there anything I=
did wrong or anything I forgot to specify?<br/><br/>Thanks a lot.<br/><br/=
>Max <br><br><table cellpadding=3D"0" cellspacing=3D"0" border=
=3D"0"><tr><td bgcolor=3D"#000000"><img src=3D"https://img.ui-portal.de/p.g=
if" width=3D"1" height=3D"1" border=3D"0" alt=3D"" /></td></tr><tr><td styl=
e=3D"font-family:verdana; font-size:12px; line-height:17px;">Schon gehö=
;rt? WEB.DE hat einen genialen Phishing-Filter in die <br>=
Toolbar eingebaut! <a href=3D"http://produkte.web.de/go/toolbar"><b>http://=
produkte.web.de/go/toolbar</b></a></td></tr></table>
</body></html>
=========================================================================
Date: Thu, 19 May 2011 13:27:57 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: channel selection
Comments: To: Fahimeh Mamashli <[log in to unmask]>
In-Reply-To: <1564594267.2181.1305803731716.JavaMail.root@zimbra>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
You set
DCM.options.location =3D 1;
See also line 57 in spm_L_priors. You might want to play with the value the=
re.
Vladimir
On Thu, May 19, 2011 at 12:15 PM, Fahimeh Mamashli <[log in to unmask]> wr=
ote:
>
> Dear Vladimir,
> Thanks for your reply. how can I optimize the prior locations in the scri=
pt?
>
> Best wishes,
> Fahimeh
>
> ------------------------
> PhD student
> Max Planck Institute for Human Cognitive and Brain Sciences
> Stephanstra=DFe 1A
> 04103 Leipzig
> Germany
>
> Tel: +49 341 9940 - 2570
>
> ----- Original Message -----
> From: "litvak vladimir" <[log in to unmask]>
> To: "Fahimeh Mamashli" <[log in to unmask]>
> Cc: [log in to unmask]
> Sent: Wednesday, May 18, 2011 4:16:12 PM
> Subject: Re: channel selection
>
> Dear Fahimeh,
>
> The most straightforward way to exclude some channels from analysis is to=
mark them as bad in the dataset. You can do it in the reviewing tool. Howe=
ver, I'm not sure this is a good strategy in your case. I would suggest you=
to just start with a symmetric model for both left and right hemispheres. =
Then if you want to explore the asymmetries you can do it as a second stage=
.
>
> Best,
>
> Vladimir
> ------Original Message------
> From: Fahimeh Mamashli
> To: Vladimir Litvak
> Subject: channel selection
> Sent: 18 May 2011 15:04
>
>
> Dear Vladimir,
> Thanks for your attention. I am the one with scarf in SPM-MEG course on M=
ay-2011 if you remember me. I wanted to do DCM for verb and noun together. =
:)
> I have a question: the difference between two conditions of my MEG data i=
s spread in both hemisphere, but it is so complicated if I want to model fr=
om the beginning both hemisphere. we want to only choose left hemisphere ch=
annels. is it possible?
> I used DCM.xY.name =3D ['channel names']; but when DCM running finished a=
nd I looked at DCM.xY.name, it just show gradiometers. where I can do chann=
el selection for DCM analysis?
>
> Best wishes,
> Fahimeh
>
> ------------------------
> PhD student
> Max Planck Institute for Human Cognitive and Brain Sciences
> Stephanstra=DFe 1A
> 04103 Leipzig
> Germany
>
> Tel: +49 341 9940 - 2570
>
>
>
> Sent using BlackBerry=AE from Orange
>
=========================================================================
Date: Thu, 19 May 2011 15:40:11 +0200
Reply-To: Torben Ellegaard Lund <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Torben Ellegaard Lund <[log in to unmask]>
Subject: Re: Sold State Drives
Comments: To: Nicholas DiQuattro <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-version: 1.0
Content-type: multipart/alternative;
boundary="Boundary_(ID_vz2rUCfDb1jElw6VP/AbSA)"
Message-ID: <[log in to unmask]>
--Boundary_(ID_vz2rUCfDb1jElw6VP/AbSA)
Content-type: text/plain; CHARSET=US-ASCII
Content-transfer-encoding: 7BIT
Dear Nick
For fMRI most of the time is used on disk I/O and SSD is really great for this, but actually the biggest change comes after changing defaults.stats.maxmem in spm_defaults to fit your computer e.g. 2^30, and line 569 in spm_spm from:
nbz = max(1,min(zdim,floor(mmv/(xdim*ydim)))); nbz = 1; %-# planes
to:
nbz = max(1,min(zdim,floor(mmv/(xdim*ydim)))); %-# planes
In order to load as much data as possible into the RAM at once.
Best
Torben
Torben Ellegaard Lund
Associate Professor, PhD
The Danish National Research Foundation's Center of Functionally Integrative Neuroscience (CFIN)
Aarhus University
Aarhus University Hospital
Building 10G, 5th floor, room 31
Noerrebrogade 44
8000 Aarhus C
Denmark
Phone: +4589494380
Fax: +4589494400
http://www.cfin.au.dk
[log in to unmask]
Den Uge:20 18/05/2011 kl. 23.14 skrev Nicholas DiQuattro:
> Hello SPM,
>
> Has anyone had any experience with running SPM on solid state drives? Do you see much of an improvement in processesing speeds?
>
> thanks,
> Nick
>
> --
> Nicholas DiQuattro
> Junior Specialist
> Integrated Attention Lab
> Center for Mind and Brain
> 267 Cousteau Place Davis, CA 95618
> tel: (530) 297-4472
--Boundary_(ID_vz2rUCfDb1jElw6VP/AbSA)
Content-type: text/html; CHARSET=US-ASCII
Content-transfer-encoding: quoted-printable
<html><head></head><body style=3D"word-wrap: break-word; =
-webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">Dear =
Nick<div><br></div><div>For fMRI most of the time is used on disk I/O =
and SSD is really great for this, but actually the biggest change comes =
after changing defaults.stats.maxmem in spm_defaults to fit your =
computer e.g. 2^30, and line 569 in spm_spm =
from:<div><br></div><div><div style=3D"margin-top: 0px; margin-right: =
0px; margin-bottom: 0px; margin-left: 0px; font: normal normal normal =
10px/normal Courier; ">nbz =3D =
max(1,min(zdim,floor(mmv/(xdim*ydim)))); nbz =3D 1; <span =
style=3D"color: #00a32d">%-# planes</span></div></div><div><span =
style=3D"color: =
#00a32d"><br></span></div><div>to:</div><div><br></div><div><div =
style=3D"margin-top: 0px; margin-right: 0px; margin-bottom: 0px; =
margin-left: 0px; font: normal normal normal 10px/normal Courier; =
">nbz =3D =
max(1,min(zdim,floor(mmv/(xdim*ydim)))); <span style=3D"color:=
#00a32d">%-# planes</span></div></div><div><font =
class=3D"Apple-style-span" color=3D"#00A32D"><br></font></div><div>In =
order to load as much data as possible into the RAM at =
once.</div><div><br></div><div><br></div><div>Best</div><div>Torben <=
/div><div><br></div><div><br></div><div><br></div><div><div>Torben =
Ellegaard Lund<br>Associate Professor, PhD<br>The Danish National =
Research Foundation's Center of Functionally Integrative =
Neuroscience (CFIN)<br>Aarhus University<br>Aarhus University =
Hospital<br>Building 10G, 5th floor, room 31<br>Noerrebrogade 44<br>8000 =
Aarhus C<br>Denmark<br>Phone: +4589494380<br>Fax: +4589494400<br><a =
href=3D"http://www.cfin.au.dk">http://www.cfin.au.dk</a><br>torbenelund@cf=
in.dk</div><div><br></div></div><div><br><div><div>Den Uge:20 18/05/2011 =
kl. 23.14 skrev Nicholas DiQuattro:</div><br =
class=3D"Apple-interchange-newline"><blockquote type=3D"cite">Hello =
SPM,<div><br></div><div>Has anyone had any experience with running SPM =
on solid state drives? Do you see much of an improvement =
in processesing speeds?<br =
clear=3D"all"><br></div><div>thanks,</div><div>Nick</div><div><br>
-- <br>Nicholas DiQuattro<br>Junior Specialist<br>Integrated Attention =
Lab<br>Center for Mind and Brain<br>267 Cousteau Place =
Davis, CA 95618<br>tel: (530) 297-4472 <br>
</div>
</blockquote></div><br></div></div><br><br><div><br =
class=3D"Apple-interchange-newline">
</div>
<br></body></html>=
--Boundary_(ID_vz2rUCfDb1jElw6VP/AbSA)--
=========================================================================
Date: Thu, 19 May 2011 16:20:15 +0200
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Simona Spinelli <[log in to unmask]>
Subject: bounding box
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary="=_alternative 004F7F82C1257895_="
Message-ID: <[log in to unmask]>
Dies ist eine mehrteilige Nachricht im MIME-Format.
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I would like to expand the bunding box to include the entire cerebellum.
Will this change have any consequences for the analysis procedure?
For example, can I still use pickatlas or marsbar for ROI analysis?
Thank you very much!
Simona
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<font size=2 face="sans-serif">I would like to expand the bunding box
to include the entire cerebellum.</font>
<br>
<br><font size=2 face="sans-serif">Will this change have any consequences
for the analysis procedure? </font>
<br><font size=2 face="sans-serif">For example, can I still use pickatlas
or marsbar for ROI analysis?</font>
<br>
<br><font size=2 face="sans-serif">Thank you very much!</font>
<br><font size=2 face="sans-serif"><br>
Simona <br>
</font>
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=========================================================================
Date: Thu, 19 May 2011 15:40:40 +0100
Reply-To: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Subject: VOI extract batch
Mime-Version: 1.0
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Hi Maximilian,
to check your batch you could load it into the GUI and look for any <-X m=
arks left. To do this, either save matlabbatch to a .mat file and open it=
through the GUI or run spm_jobman('interactive',matlabbatch) from MATLAB=
.
Hope this helps,
Volkmar
=========================================================================
Date: Thu, 19 May 2011 14:09:38 -0400
Reply-To: Jadzia Jagiellowicz <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jadzia Jagiellowicz <[log in to unmask]>
Subject: glass brain display
MIME-Version: 1.0
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--001636eef7318a4ac304a3a4e813
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Hello all
When I display activation on the "glass brain" after making T contrasts,
the "glass brain " never shows up. The activation shows up on a square grid.
Have I specified something wrong in the normalization? I am choosing the
default bounding box in SPM5. Some of my subjects have glass brains, others
only show the
activation on a square grid.
Thanks in advance,
Jadzia
--
Jadzia Jagiellowicz
Doctoral Candidate
Psychology Department B-207
Stony Brook University,
Stony Brook, NY 11794-2500 USA
http://www.psychology.stonybrook.edu/aronlab-/
"The brave shall inherit the earth."
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<div>Hello all</div>
<div>=A0</div>
<div>When I display activation on the "glass brain" after making =
T contrasts,</div>
<div>the "glass brain " never shows up. The activation shows up o=
n a square grid. </div>
<div>=A0</div>
<div>Have I specified something wrong in the normalization? I am choosing t=
he </div>
<div>default bounding box in SPM5. Some of my subjects have glass brains, o=
thers only show the </div>
<div>activation on a square grid.</div>
<div>Thanks in advance, <br clear=3D"all">Jadzia <br>-- <br>Jadzia Jagiello=
wicz<br>Doctoral Candidate <br>Psychology Department B-207<br>Stony Brook U=
niversity, <br>Stony Brook, NY 11794-2500 USA<br><a href=3D"http://www.psyc=
hology.stonybrook.edu/aronlab-/">http://www.psychology.stonybrook.edu/aronl=
ab-/</a><br>
<br>"The brave shall inherit the earth."<br></div>
--001636eef7318a4ac304a3a4e813--
=========================================================================
Date: Thu, 19 May 2011 19:29:23 +0100
Reply-To: Jennifer Barredo <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jennifer Barredo <[log in to unmask]>
Subject: signrank for spm5
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Hi,
I've been trying to generate a SPM for a signrank test rather than a t-te=
st. I've been able to get the signrank map written (using Matlab's Statis=
tics Toolbox & spm_write_vol), but in the process it seems like it's conv=
erting negative values to positive ones. Is there a default in the spm_wr=
ite_vol that causes this to happen?
Thanks,
Jennifer
=========================================================================
Date: Thu, 19 May 2011 21:13:30 +0100
Reply-To: Joshua Goh <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Joshua Goh <[log in to unmask]>
Subject: Use my own t-maps
Mime-Version: 1.0
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Message-ID: <[log in to unmask]>
Dear list,
I have a .img/.hdr file that consists of t-values computed externally to =
SPM. Is there a way I can display or use this t-map in spm_results_ui? Th=
is is so that I can apply the cluster threshold as well as spm_list to id=
entify global and local peaks.
Thanks,
Josh
=========================================================================
Date: Thu, 19 May 2011 16:25:24 -0400
Reply-To: Jason Steffener <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jason Steffener <[log in to unmask]>
Subject: Re: Use my own t-maps
Comments: To: Joshua Goh <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
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--20cf307f35f41abbb704a3a6ce71
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Dear Josh,
Try this.
Jason
On Thu, May 19, 2011 at 4:13 PM, Joshua Goh <[log in to unmask]> wrote:
> Dear list,
>
> I have a .img/.hdr file that consists of t-values computed externally to SPM. Is there a way I can display or use this t-map in spm_results_ui? This is so that I can apply the cluster threshold as well as spm_list to identify global and local peaks.
>
> Thanks,
> Josh
>
--
Jason Steffener, Ph.D.
Department of Neurology
Columbia University
http://www.cogneurosci.org/steffener.html
--20cf307f35f41abbb704a3a6ce71
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--20cf307f35f41abbb704a3a6ce71--
=========================================================================
Date: Thu, 19 May 2011 16:36:34 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Use my own t-maps
Comments: To: Joshua Goh <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0023545309c80ea4ad04a3a6f6d9
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--0023545309c80ea4ad04a3a6f6d9
Content-Type: text/plain; charset=ISO-8859-1
You need to add the xCon structure to the SPM variable and properly fill the
xCon with the correct fields. If you have an old SPM.mat file you can see
what the fields should be.
If you are simple wanting to cluster and find the peaks, the SPM.mat file is
not actually needed with the peak_nii.m program that I recently wrote. There
is a previous post on usage of peak_nii.m. It is available for download from
http://www.martinos.org/~mclaren/ftp/Utilities_DGM/.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
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unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Thu, May 19, 2011 at 4:13 PM, Joshua Goh <[log in to unmask]> wrote:
> Dear list,
>
> I have a .img/.hdr file that consists of t-values computed externally to
> SPM. Is there a way I can display or use this t-map in spm_results_ui? This
> is so that I can apply the cluster threshold as well as spm_list to identify
> global and local peaks.
>
> Thanks,
> Josh
>
--0023545309c80ea4ad04a3a6f6d9
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You need to add the xCon structure to the SPM variable and properly fill
the xCon with the correct fields. If you have an old SPM.mat file you=20
can see what the fields should be.<br>
<br>
If you are simple wanting to cluster and find the peaks, the SPM.mat=20
file is not actually needed with the peak_nii.m program that I recently=20
wrote. There is a previous post on usage of peak_nii.m. It is available=20
for download from <a href=3D"http://www.martinos.org/~mclaren/ftp/Utilities=
_DGM/">http://www.martinos.org/~mclaren/ftp/Utilities_DGM/</a>.<br clear=3D=
"all"><br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>
Postdoctoral Research Fellow, GRECC, Bedford VA<br>Research Fellow, Departm=
ent of Neurology, Massachusetts General Hospital and Harvard Medical School=
<br>Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which m=
ay contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILE=
GED and which is intended only for the use of the individual or entity name=
d above. If the reader of the e-mail is not the intended recipient or the e=
mployee or agent responsible for delivering it to the intended recipient, y=
ou are hereby notified that you are in possession of confidential and privi=
leged information. Any unauthorized use, disclosure, copying or the taking =
of any action in reliance on the contents of this information is strictly p=
rohibited and may be unlawful. If you have received this e-mail unintention=
ally, please immediately notify the sender via telephone at (773) 406-2464 =
or email.<br>
<br><br><div class=3D"gmail_quote">On Thu, May 19, 2011 at 4:13 PM, Joshua =
Goh <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">joshgoh@gmai=
l.com</a>></span> wrote:<br><blockquote class=3D"gmail_quote" style=3D"m=
argin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
Dear list,<br>
<br>
I have a .img/.hdr file that consists of t-values computed externally to SP=
M. Is there a way I can display or use this t-map in spm_results_ui? This i=
s so that I can apply the cluster threshold as well as spm_list to identify=
global and local peaks.<br>
<br>
Thanks,<br>
Josh<br>
</blockquote></div><br>
--0023545309c80ea4ad04a3a6f6d9--
=========================================================================
Date: Thu, 19 May 2011 14:01:24 -0700
Reply-To: Michael T Rubens <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michael T Rubens <[log in to unmask]>
Subject: Re: signrank for spm5
Comments: To: Jennifer Barredo <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf3040ea429b5f7d04a3a750e8
Message-ID: <[log in to unmask]>
--20cf3040ea429b5f7d04a3a750e8
Content-Type: text/plain; charset=UTF-8
I expect that the output is a p-value, correct? so the p-value will
obviously only be positive. you could possibly do a couple things to retain
the signs. A) you could find the indices of all negative values, and then
after the signrank test multiply all of those indices by -1, or B) output
separate maps for positive and negative values.
Cheers,
Michael
On Thu, May 19, 2011 at 11:29 AM, Jennifer Barredo <
[log in to unmask]> wrote:
> Hi,
>
> I've been trying to generate a SPM for a signrank test rather than a
> t-test. I've been able to get the signrank map written (using Matlab's
> Statistics Toolbox & spm_write_vol), but in the process it seems like it's
> converting negative values to positive ones. Is there a default in the
> spm_write_vol that causes this to happen?
>
> Thanks,
> Jennifer
>
--
Research Associate
Gazzaley Lab
Department of Neurology
University of California, San Francisco
--20cf3040ea429b5f7d04a3a750e8
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
I expect that the output is a p-value, correct? so the p-value will obvious=
ly only be positive. you could possibly do a couple things to retain the si=
gns. A) you could find the indices of all negative values, and then after t=
he signrank test multiply all of those indices by -1, or B) output separate=
maps for positive and negative values.<br>
<br>Cheers,<br>Michael<br><br><div class=3D"gmail_quote">On Thu, May 19, 20=
11 at 11:29 AM, Jennifer Barredo <span dir=3D"ltr"><<a href=3D"mailto:Je=
[log in to unmask]">[log in to unmask]</a>></span> wrote:<=
br>
<blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; borde=
r-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">Hi,<br>
<br>
I've been trying to generate a SPM for a signrank test rather than a t-=
test. I've been able to get the signrank map written (using Matlab'=
s Statistics Toolbox & spm_write_vol), but in the process it seems like=
it's converting negative values to positive ones. Is there a default i=
n the spm_write_vol that causes this to happen?<br>
<br>
Thanks,<br>
<font color=3D"#888888">Jennifer<br>
</font></blockquote></div><br><br clear=3D"all"><br>-- <br>Research Associa=
te<br>Gazzaley Lab<br>Department of Neurology<br>University of California, =
San Francisco<br>
--20cf3040ea429b5f7d04a3a750e8--
=========================================================================
Date: Thu, 19 May 2011 23:31:40 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: Normalising a point
Comments: To: Chris Leatherday <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
I should try to be a bit more consistent with my nomenclature for
deformation fields. Some functions generate an iy* to indicate an
inverse, whereas others just generate another y*. The inverse of the
deformation from the Deformations utility will just be named y*.
Best regards,
-John
On 18 May 2011 09:33, Chris Leatherday
<[log in to unmask]> wrote:
> Dear SPMers
>
>
> I have a series of points that I would like to translate from native spac=
e to MNI space. I'm sorry if this is an obvious question, and I've noted th=
at it seems to have been discussed a couple of times already. In attempting=
to follow Gem5 of John's Gems 2, I am unable to =A0do the part where he as=
ks the user to choose the deformations inversion option...
>
> I am running SPM8, and I can't seem to get anything that looks like iy*.i=
mg. Running the "inverse" option in deformations just gives me another y_*.=
nii file, and I can't seem to find a method of creating an iy*.img file.
>
> Could somebody please point me in the right direction?
>
> Thank you
>
> Chris
>
=========================================================================
Date: Thu, 19 May 2011 18:40:55 -0400
Reply-To: Ji Won Bang <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Ji Won Bang <[log in to unmask]>
Subject: converting fif file to mat file
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0016e65b646ac0809c04a3a8b214
Message-ID: <[log in to unmask]>
--0016e65b646ac0809c04a3a8b214
Content-Type: text/plain; charset=ISO-8859-1
Dear. all.
This is Ji won Bang from Dr. Sasaki's group at MGH martino's center.
I was trying to convert fif file(MEG) to mat file using SPM8.
And this process created 1 dat file and 1 mat file.
However, for some reason the mat file is empty, whereas the dat file is
3.8GB.
Is there anyone who had same problem with converting?
I will appreciate that fi you email me.
Thanks a lot.
Best regards,
Ji Won Bang
--0016e65b646ac0809c04a3a8b214
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Dear. all.<div><br></div><div>This is Ji won Bang from Dr. Sasaki's gro=
up at MGH martino's center.=A0</div><div><br></div><div>I was trying to=
convert fif file(MEG) to mat file using SPM8.</div><div><br></div><div>And=
this process created 1 dat file and 1 mat file.=A0</div>
<div><br></div><div>However, for some reason the mat file is empty, whereas=
the dat file is 3.8GB.</div><div><br></div><div>Is there anyone who had sa=
me problem with converting?</div><div><br></div><div>I will appreciate that=
fi you email me.=A0</div>
<div><br></div><div>Thanks a lot.</div><div><br></div><div>Best regards,</d=
iv><div>Ji Won Bang</div><div><br></div>
--0016e65b646ac0809c04a3a8b214--
=========================================================================
Date: Thu, 19 May 2011 15:57:34 -0700
Reply-To: Steven Berman <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Steven Berman <[log in to unmask]>
Subject: Are multiple T1s per subject helpful in DARTEL VBM?
Mime-Version: 1.0
Content-Type: text/html; charset="us-ascii"
Message-ID: <[log in to unmask]>
<html>
<body>
<font color="#008000"><b>Dear SPM Mavens,<br>
We are comparing two groups of 13 subjects with DARTEL VBM8. I
know this is underpowered, but wondered if there is any way to use the
multiple T1 images that were acquired for some of the subjects (in the
same session). My initial thought is to process all T1s and use the
quality check to see if there is a "better" image when I have
two for a given subject. Are there better ways to use multiple T1s?<br>
Thanks,<br><br>
</b></font><x-sigsep><p></x-sigsep>
Steven Berman,
Ph.D.<br>
<x-tab> </x-tab>UCLA Dept.
of Psychiatry & Biobehavioral Sciences, <br>
Brain Research
Institute, and Center for Addictive Behaviors<br>
Tel. (310)
825-0616 Fax: (310) 825-0812 <br><br>
<font color="#0000FF">
<a href="http://ibs.med.ucla.edu/" eudora="autourl">
http://ibs.med.ucla.edu<br>
</a>
<a href="http://uclamindbody.org/" eudora="autourl">
http://uclamindbody.org<br>
</a>
<a href="http://www.bri.ucla.edu/" eudora="autourl">
http://www.bri.ucla.edu</a></font> <br>
<font color="#0000FF">
<a href="http://www.semel.ucla.edu/cab/" eudora="autourl">
http://www.semel.ucla.edu/cab/</a></font> </body>
</html>
=========================================================================
Date: Fri, 20 May 2011 09:47:01 +1000
Reply-To: Greig de Zubicaray <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Greig de Zubicaray <[log in to unmask]>
Subject: Call for papers: Special Issue of Twin Research and Human
Genetics on The Genetics of Brain Imaging Phenotypes.
Content-Type: multipart/alternative; boundary=Apple-Mail-22--1023376358
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charset=windows-1252
We are putting together a special issue of Twin Research and Human =
Genetics on The genetics of brain imaging phenotypes. =20
=20
Scope: We welcome papers on any aspect of brain imaging with a genetic =
angle. This could include twin and family studies or genetic association =
studies, either GWAS, or candidate genes. Papers can be original =
research contributions, reviews, or theoretical treatments. We can also =
include =93baseline=94 papers describing a study with full =
methodological detail beyond that allowed by most journals. It is also =
an opportunity to publish that manuscript lying around your lab that has =
been derailed by unreasonable demands from editors of other journals =96 =
our editors will consider any reasonable case ! Guidelines for =
manuscript preparation are at =
http://www.ists.qimr.edu.au/journal.html#Instructions
=20
Costs: The upside is that there will be no page limits or other =
restrictions on length. The downside is that because TRHG is not backed =
by a large publisher, we have to charge for each page published. Normal =
charges are $100/page for members of ISTS or $150/page for non-members, =
so you only have to publish 4 pages for it to be cheaper to become a =
member. Because for this special issue we will be using high-gloss paper =
(so you can submit unlimited colour images) there will be a =
supplementary charge of $30/page, but no further charges for colour. So =
a 10-page paper will cost you $1300 (member), $1800 non-member. This is =
still cheap compared with many journals. [If anyone has a bright idea on =
how to obtain funds (e.g. a private foundation) to subsidise production =
of this issue please let us know]. =20
=20
Timing : The special issue will appear in February 2012. This means that =
all final copy must be to the publisher December 1. So editors will need =
to receive all manuscripts by September 1 latest to allow time for =
reviewing and editing =96 but submissions earlier than this would be =
much appreciated. =20
=20
Contacts: Guest editors for this issue will be Dirk Smit (VU, =
Amsterdam), Jason Stein (UCLA), Dennis van 't Ent (VU, Amsterdam), and =
Greig de Zubicaray (UQ, Brisbane) whose contact details are below; =
please email them immediately to indicate your interest. Manuscripts =
should be submitted as an email attachment to [log in to unmask]
Dirk Smit
Department of Psychology, Free University, Amsterdam
[log in to unmask]
=20
Jason Stein
Laboratory of Neuroimaging, UCLA, Los Angeles
[log in to unmask]
=20
Dennis van 't Ent
Department of Biological Psychology, Free University, Amsterdam
[log in to unmask]
Greig de Zubicaray
Department of Psychology, University of Queensland, Brisbane
[log in to unmask]
--
Assoc Prof Greig de Zubicaray | ARC Future Fellow | Functional =
Imaging Laboratory
School of Psychology | University of Queensland | Brisbane, QLD 4072 =
| AUSTRALIA
Phone: +61-7-3365-6802 (direct) | +61-7-3365-6230 (office) | =
Fax: +61-7-3365-4466
Email: [log in to unmask] | Web: =
http://www.fmrilab.net/
CRICOS Provider Number 00025B
--Apple-Mail-22--1023376358
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charset=windows-1252
<html><head></head><body style=3D"word-wrap: break-word; =
-webkit-nbsp-mode: space; -webkit-line-break: after-white-space; =
"><div><br></div><div><span class=3D"Apple-style-span" =
style=3D"font-family: 'Times New Roman', serif; font-size: 16px; ">We =
are putting together a special issue of </span><span =
class=3D"Apple-style-span" style=3D"font-family: 'Times New Roman', =
serif; font-size: 16px; "><i>Twin Research and Human =
Genetics</i></span><span class=3D"Apple-style-span" style=3D"font-family: =
'Times New Roman', serif; font-size: 16px; "> on </span><span =
class=3D"Apple-style-span" style=3D"font-family: 'Times New Roman', =
serif; font-size: 16px; "><b>The genetics of brain imaging =
phenotypes</b></span><span class=3D"Apple-style-span" =
style=3D"font-family: 'Times New Roman', serif; font-size: 16px; ">. =
</span></div><div><div style=3D"margin-top: 0cm; margin-right: =
0cm; margin-bottom: 0.0001pt; margin-left: 0cm; font-size: 12pt; =
font-family: 'Times New Roman', serif; "><o:p></o:p></div><div =
style=3D"margin-top: 0cm; margin-right: 0cm; margin-bottom: 0.0001pt; =
margin-left: 0cm; font-size: 12pt; font-family: 'Times New Roman', =
serif; "><span lang=3D"NL"> </span><o:p></o:p></div><div =
style=3D"margin-top: 0cm; margin-right: 0cm; margin-bottom: 0.0001pt; =
margin-left: 0cm; font-size: 12pt; font-family: 'Times New Roman', =
serif; "><b><span lang=3D"NL">Scope:</span></b><span lang=3D"NL"> We =
welcome papers on any aspect of brain imaging with a genetic angle. This =
could include twin and family studies or genetic association studies, =
either GWAS, or candidate genes. Papers can be original research =
contributions, reviews, or theoretical treatments. We can also include =
=93baseline=94 papers describing a study with full methodological detail =
beyond that allowed by most journals. It is also an opportunity to =
publish that manuscript lying around your lab that has been derailed by =
unreasonable demands from editors of other journals =96 our editors will =
consider any reasonable case ! Guidelines for manuscript =
preparation are at <a =
href=3D"http://www.ists.qimr.edu.au/journal.html#Instructions" =
target=3D"_blank" style=3D"color: blue; text-decoration: underline; =
">http://www.ists.qimr.edu.au/journal.html#Instructions</a></span><o:p></o=
:p></div><div style=3D"margin-top: 0cm; margin-right: 0cm; =
margin-bottom: 0.0001pt; margin-left: 0cm; font-size: 12pt; font-family: =
'Times New Roman', serif; "><span =
lang=3D"NL"> </span><o:p></o:p></div><div style=3D"margin-top: 0cm; =
margin-right: 0cm; margin-bottom: 0.0001pt; margin-left: 0cm; font-size: =
12pt; font-family: 'Times New Roman', serif; "><b><span =
lang=3D"NL">Costs:</span></b><span lang=3D"NL"> The upside is that =
there will be no page limits or other restrictions on length. The =
downside is that because TRHG is not backed by a large publisher, we =
have to charge for each page published. Normal charges are $100/page for =
members of ISTS or $150/page for non-members, so you only have to =
publish 4 pages for it to be cheaper to become a member. Because for =
this special issue we will be using high-gloss paper (so you can submit =
unlimited colour images) there will be a supplementary charge of =
$30/page, but no further charges for colour. So a 10-page paper will =
cost you $1300 (member), $1800 non-member. This is still cheap compared =
with many journals. [If anyone has a bright idea on how to obtain funds =
(e.g. a private foundation) to subsidise production of this issue please =
let us know]. <b> </b></span><o:p></o:p></div><div =
style=3D"margin-top: 0cm; margin-right: 0cm; margin-bottom: 0.0001pt; =
margin-left: 0cm; font-size: 12pt; font-family: 'Times New Roman', =
serif; "><span lang=3D"NL"> </span><o:p></o:p></div><div =
style=3D"margin-top: 0cm; margin-right: 0cm; margin-bottom: 0.0001pt; =
margin-left: 0cm; font-size: 12pt; font-family: 'Times New Roman', =
serif; "><b><span lang=3D"NL">Timing :</span></b><span =
lang=3D"NL"> The special issue will appear in February 2012. This =
means that all final copy must be to the publisher December 1. So =
editors will need to receive all manuscripts by September 1 latest to =
allow time for reviewing and editing =96 but submissions earlier than =
this would be much appreciated. </span><o:p></o:p></div><div =
style=3D"margin-top: 0cm; margin-right: 0cm; margin-bottom: 0.0001pt; =
margin-left: 0cm; font-size: 12pt; font-family: 'Times New Roman', =
serif; "><span lang=3D"NL"> </span><o:p></o:p></div><div =
style=3D"margin-top: 0cm; margin-right: 0cm; margin-bottom: 0.0001pt; =
margin-left: 0cm; font-size: 12pt; font-family: 'Times New Roman', =
serif; "><b><span lang=3D"NL">Contacts:</span></b><span =
lang=3D"NL"> Guest editors for this issue will be Dirk Smit (VU, =
Amsterdam), Jason Stein (UCLA), </span>Dennis van 't Ent (VU, =
Amsterdam), and Greig de Zubicaray (UQ, Brisbane) whose contact =
details are below; <u>please email them immediately to indicate =
your interest</u>. <b><i> </i></b>Manuscripts should be =
submitted as an email attachment to <a =
href=3D"mailto:[log in to unmask]" target=3D"_blank" style=3D"color: blue; =
text-decoration: underline; =
">[log in to unmask]</a></div></div><div><br></div><div style=3D"margin-top:=
0cm; margin-right: 0cm; margin-bottom: 0.0001pt; margin-left: 0cm; =
font-size: 12pt; font-family: 'Times New Roman', serif; "><span =
lang=3D"NL">Dirk Smit<br>Department of Psychology, Free University, =
Amsterdam<br><a href=3D"mailto:[log in to unmask]" target=3D"_blank" =
style=3D"color: blue; text-decoration: underline; =
">[log in to unmask]</a></span><o:p></o:p></div><div style=3D"margin-top: =
0cm; margin-right: 0cm; margin-bottom: 0.0001pt; margin-left: 0cm; =
font-size: 12pt; font-family: 'Times New Roman', serif; "><span =
lang=3D"NL"> </span><o:p></o:p></div><div style=3D"margin-top: 0cm; =
margin-right: 0cm; margin-bottom: 0.0001pt; margin-left: 0cm; font-size: =
12pt; font-family: 'Times New Roman', serif; "><span lang=3D"NL">Jason =
Stein<br>Laboratory of Neuroimaging, UCLA, Los Angeles<br><a =
href=3D"mailto:[log in to unmask]" target=3D"_blank" style=3D"color: blue; =
text-decoration: underline; =
">[log in to unmask]</a></span><o:p></o:p></div><div style=3D"margin-top: =
0cm; margin-right: 0cm; margin-bottom: 0.0001pt; margin-left: 0cm; =
font-size: 12pt; font-family: 'Times New Roman', serif; "><span =
lang=3D"NL"> </span><o:p></o:p></div><div style=3D"margin-top: 0cm; =
margin-right: 0cm; margin-bottom: 0.0001pt; margin-left: 0cm; font-size: =
12pt; font-family: 'Times New Roman', serif; "><span lang=3D"NL">Dennis =
van 't Ent</span></div><div style=3D"margin-top: 0cm; margin-right: 0cm; =
margin-bottom: 0.0001pt; margin-left: 0cm; "><span lang=3D"NL"><font =
class=3D"Apple-style-span" face=3D"'Times New Roman', serif" =
size=3D"4"><span class=3D"Apple-style-span" style=3D"font-size: =
16px;">Department of Biological Psychology, Free University, =
Amsterdam</span></font></span></div><div style=3D"margin-top: 0cm; =
margin-right: 0cm; margin-bottom: 0.0001pt; margin-left: 0cm; font-size: =
12pt; font-family: 'Times New Roman', serif; "><span lang=3D"NL"><a =
href=3D"mailto:[log in to unmask]">[log in to unmask]</a></span></div>=
<div style=3D"margin-top: 0cm; margin-right: 0cm; margin-bottom: =
0.0001pt; margin-left: 0cm; font-size: 12pt; font-family: 'Times New =
Roman', serif; "><span lang=3D"NL"><br></span></div><div =
style=3D"margin-top: 0cm; margin-right: 0cm; margin-bottom: 0.0001pt; =
margin-left: 0cm; font-size: 12pt; font-family: 'Times New Roman', =
serif; "><span lang=3D"NL">Greig de Zubicaray<br>Department of =
Psychology, University of Queensland, Brisbane<br><a =
href=3D"mailto:[log in to unmask]" target=3D"_blank" =
style=3D"color: blue; text-decoration: underline; =
">[log in to unmask]</a></span></div><div style=3D"margin-top: =
0cm; margin-right: 0cm; margin-bottom: 0.0001pt; margin-left: 0cm; =
font-size: 12pt; font-family: 'Times New Roman', serif; "><br></div><div =
style=3D"margin-top: 0cm; margin-right: 0cm; margin-bottom: 0.0001pt; =
margin-left: 0cm; font-size: 12pt; font-family: 'Times New Roman', =
serif; "><br></div><div style=3D"margin-top: 0cm; margin-right: 0cm; =
margin-bottom: 0.0001pt; margin-left: 0cm; font-size: 12pt; font-family: =
'Times New Roman', serif; "><br></div><div style=3D"margin-top: 0cm; =
margin-right: 0cm; margin-bottom: 0.0001pt; margin-left: 0cm; font-size: =
12pt; font-family: 'Times New Roman', serif; "><br></div><div =
style=3D"margin-top: 0cm; margin-right: 0cm; margin-bottom: 0.0001pt; =
margin-left: 0cm; font-size: 12pt; font-family: 'Times New Roman', =
serif; "><br></div><div style=3D"margin-top: 0cm; margin-right: 0cm; =
margin-bottom: 0.0001pt; margin-left: 0cm; font-size: 12pt; font-family: =
'Times New Roman', serif; "><br></div><div>
<div style=3D"word-wrap: break-word; -webkit-nbsp-mode: space; =
-webkit-line-break: after-white-space; "><div style=3D"word-wrap: =
break-word; -webkit-nbsp-mode: space; -webkit-line-break: =
after-white-space; "><div><span class=3D"Apple-style-span" =
style=3D"font-size: 12px; =
"><b><div><div><div><div><div><div><div><div><div><div><div><div><div><div=
><div><div><div><div><div><div><div><div><div><div><div><div><div><div><di=
v><div><div><div><div><div><div><div><div><div><div><div><div><div><div><d=
iv><div><div><div><div><div><div><div><div><div><div><div><div><div><div><=
div><div><div><div><div><div><div><div><div><div><div><div><div><div><div>=
<div><div><div><div><div><div><div><div><div><div><div><div><div><div><div=
><div><div><div><div><div><div><div><div><div><div><div><div>--</div><div>=
Assoc Prof Greig de Zubicaray | ARC Future Fellow =
| Functional Imaging Laboratory<br><span =
class=3D"Apple-style-span" style=3D"font-weight: normal; ">School of =
Psychology | University of Queensland | =
Brisbane, QLD 4072 | AUSTRALIA<br>Phone: =
+61-7-3365-6802 (direct) | =
+61-7-3365-6230 (office) | Fax: =
+61-7-3365-4466<br>Email: <a =
href=3D"mailto:[log in to unmask]">[log in to unmask]</a=
> | Web: <a =
href=3D"http://www.fmrilab.net/">http://www.fmrilab.net/</a><br>CRICOS =
Provider Number 00025B</span></div><div><span class=3D"Apple-style-span" =
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iv></div></div></div></div></div></div></div></div></div></div></div></div=
></div></div></div></div></div></div></div></div></div></div></div></div><=
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--Apple-Mail-22--1023376358--
=========================================================================
Date: Fri, 20 May 2011 10:29:04 +1000
Reply-To: Richard Morris <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Richard Morris <[log in to unmask]>
Subject: which extra regressors for an n-back task?
Content-Type: text/plain; charset="us-ascii"
Content-Transfer-Encoding: quoted-printable
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
Hi list,
I am analyzing a simple n-back task arranged in a block design with two con=
ditions of interest (2-back, 0-back), and I want to rigorously examine diff=
erences between these conditions (1, -1), while controlling for differences=
in accuracy between the conditions.
For example, fewer correct responses (as well as more misses and more error=
s) occurred in the 2-back condition than the 0-back condition, which may ac=
count for much of the difference between the conditions of interest.
My question is how do I control for these extraneous differences between co=
nditions in the first-level design? To illustrate, I have a column for the =
2-back blocks and a column for the 0-back blocks in the first-level design =
matrix. I think I also need a third column for correct responses, which wil=
l account for variation due to correct answers. But it also occurs to me th=
at this might be better done in two columns, with one column for correct re=
sponses during 2-back and a separate column for correct responses during 0-=
back.
So in general terms my question is, when including regressors-of-no-interes=
t which systematically vary between conditions of interest, is it sufficien=
t to include a single regressor to control for variation, or is it necessar=
y to include separate regressors-of-no-interest for the events in each cond=
ition-of-interest?
I imagine the issue of how to analyze an n-back task has been done to death=
, but as I'm new to this task, I'm unaware of where these discussions have =
taken place. Any pointers would be appreciated.
Ta,
Rich=
=========================================================================
Date: Thu, 19 May 2011 23:53:52 -0400
Reply-To: Jonathan Peelle <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jonathan Peelle <[log in to unmask]>
Subject: Re: Are multiple T1s per subject helpful in DARTEL VBM?
Comments: To: Steven Berman <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=windows-1252
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Dear Steven,
> =A0 We are comparing two groups of 13 subjects with DARTEL VBM8. I know t=
his
> is underpowered, but wondered if there is any way to use the multiple T1
> images that were acquired for some of the subjects (in the same session).=
My
> initial thought is to process all T1s and use the quality check to see if
> there is a "better" image when I have two for a given subject. Are there
> better ways to use multiple T1s?
In the "new segment" option in SPM8, you can specify multiple
modalities of images for segmentation. I assume you could also
provide SPM with 2 T1 images. SPM will then use the combined
information across images to assign tissue class probabilities, and in
general I would think that more data would provide a more accurate
result. However, I think you'd want to process all of your subjects
the same way. So if you only have multiple T1s for a subset, I would
probably stick with the approach you suggest=97see if you can identify a
"better" image. (Or, if this is hard to determine, then just use the
first.) But if anyone else has alternate approaches, I'd be very
interested to hear!
Best regards,
Jonathan
=========================================================================
Date: Fri, 20 May 2011 00:20:38 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Are multiple T1s per subject helpful in DARTEL VBM?
Comments: To: Jonathan Peelle <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=windows-1252
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
In my honest opinion, all subjects need to be processed the same way.
If you have 2 scans, you could use the suggested approaches, or you
could coregister them, then average them in. After averaging , you can
do the rest of the processing.
Averaging should give similar as increasing the NEX.
On Thursday, May 19, 2011, Jonathan Peelle <[log in to unmask]> wrote:
> Dear Steven,
>
>> =A0 We are comparing two groups of 13 subjects with DARTEL VBM8. I know =
this
>> is underpowered, but wondered if there is any way to use the multiple T1
>> images that were acquired for some of the subjects (in the same session)=
. My
>> initial thought is to process all T1s and use the quality check to see i=
f
>> there is a "better" image when I have two for a given subject. Are there
>> better ways to use multiple T1s?
>
> In the "new segment" option in SPM8, you can specify multiple
> modalities of images for segmentation. =A0I assume you could also
> provide SPM with 2 T1 images. =A0SPM will then use the combined
> information across images to assign tissue class probabilities, and in
> general I would think that more data would provide a more accurate
> result. =A0However, I think you'd want to process all of your subjects
> the same way. =A0So if you only have multiple T1s for a subset, I would
> probably stick with the approach you suggest=97see if you can identify a
> "better" image. =A0(Or, if this is hard to determine, then just use the
> first.) =A0But if anyone else has alternate approaches, I'd be very
> interested to hear!
>
> Best regards,
> Jonathan
>
--=20
Best Regards, Donald McLaren
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital an=
d
Harvard Medical School
Office: (773) 406-2464
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773=
)
406-2464 or email.
=========================================================================
Date: Fri, 20 May 2011 09:10:14 +0100
Reply-To: Jonas Persson <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jonas Persson <[log in to unmask]>
Subject: Time derivative in event related design
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Hello fellow SPM:ers,
I am a bit confused with regards to using the time derivative in SPM.=20
The issue is that I have an event related paradigm where I do post hoc so=
rting of stimuli to 2 conditions. At the last SPM course I learned that s=
lice time correction should be avoided, so instead of using time slice co=
rrection I wanted to include a second basis function to account for timin=
g differences in data acquisition between slices.
To check for regions significantly more activated in cond 1 vs cond 2 I d=
id an F-contrast [1 0 -1 0; 0 1 0 -1] to look for voxels associated with =
either the HRF or td. I masked this contrast inclusive with a t-contrast =
[1 0 -1 0] to only look at voxels with activation corresponding to the HR=
F. The problem here is that I'm telling SPM to look for voxels with diffe=
rent timing depending on condition, while I'm interested in allowing for =
timing differences between regions regardless of condition.
Another variant I've thought of is to merely do a t-contrast [1 0 -1 0], =
controlling for any variance associated with the td, but I read that this=
may give biased results.
The next issue is how to perform the 2nd level analysis. With the latter =
method it's straightforward, but from what I understand I can't do a rand=
om effects on F-contrasts?
Thank you for any suggestions!
Bert regards,
Jonas Persson
=========================================================================
Date: Fri, 20 May 2011 12:59:17 +0400
Reply-To: Alexander Ivanov <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Alexander Ivanov <[log in to unmask]>
Subject: Question regarding kernel utilities
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=001636988b5c2d2e9104a3b156c6
Message-ID: <[log in to unmask]>
--001636988b5c2d2e9104a3b156c6
Content-Type: text/plain; charset=ISO-8859-1
*Dear SPMers!*
I have a question regarding kernel utilities... I have searched the archives
but haven't found any info on this topic... I would just like to be sure
that I understood its application correctly... After preprocessing steps
(for example, using vbm8 toolbox) I have got m0wrp* images... Afterwards I
want to generate dot-product matrices for each set of images (gm, wm, csf).
After all I have (N)x(M) dp-matrix (calculated using "Kernel from images"
option), where N-th row reflects N-th subject (is that correct?)... Next I'm
training a classifier (in my case it's SVM) with training subset of
dp-matrix and testing it using corresponding subset.
My last question may appear to be stupid, but.... As far as I understand, if
I want to make a class prediction of a new subject I can't use my classifier
anymore and I have to recalculate dp-matrix again in order to get
(N+1)x(M+1) quadratic matrix... - right?
Please excuse my for my weird questions...
===
Best Regards,
Alex
--001636988b5c2d2e9104a3b156c6
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
<b>Dear SPMers!</b><div><br></div><div>I have a question regarding kernel u=
tilities... I have searched the archives but haven't found any info on =
this topic... I would just like to be sure that I understood its applicatio=
n correctly... After preprocessing steps (for example, using vbm8 toolbox) =
I have got m0wrp* images... Afterwards I want to generate dot-product matri=
ces for each set of images (gm, wm, csf). After all I have (N)x(M) dp-matri=
x (calculated using "Kernel from images" option), where N-th row =
reflects N-th subject (is that correct?)... Next I'm training a classif=
ier (in my case it's SVM) with training subset of dp-matrix and testing=
it using corresponding subset.</div>
<div>My last question may appear to be stupid, but.... As far as I understa=
nd, if I want to make a class prediction of a new subject I can't use m=
y classifier anymore and I have to recalculate dp-matrix again in order to =
get (N+1)x(M+1) quadratic matrix... - right?</div>
<div><br></div><div>Please excuse my for my weird questions...</div><div><b=
r></div><div>=3D=3D=3D</div><div><br></div><div>Best Regards,</div><div>Ale=
x</div><div><br></div>
--001636988b5c2d2e9104a3b156c6--
=========================================================================
Date: Fri, 20 May 2011 10:51:25 +0100
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jing Kan <[log in to unmask]>
Subject: the order of the preprocessing
MIME-Version: 1.0
Content-Type: text/plain;charset=iso-8859-1
Content-Transfer-Encoding: 8bit
Message-ID: <[log in to unmask]>
Dear SPM experts,
May I ask a basic question about the data-preprocessing?
In terms of the SPM tutorial I read, we can do the preprocessing either
with the order "epoch" and then "filter" or "filter" and then "epoch".
May I ask is it any effect with these two different ways?
Many thanks,
Jing
=========================================================================
Date: Fri, 20 May 2011 10:55:11 +0100
Reply-To: Christoph Berger <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Christoph Berger <[log in to unmask]>
Subject: Re: which extra regressors for an n-back task?
Comments: To: [log in to unmask]
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Hi Rich,
only some ideas to that topic..
this regressor of no interest should be highly correlated to the paradigm=
, mostly the errors will occur in the 2back-blocks. So for that it seems =
to be problematic to model this extra regressor of no interest, like I wo=
uld not use extra regressors of no interest for movement parameter, if th=
ere is task-related movement, because in that case you can not differ bet=
ween nuisance variance and good variance you want to explain. But if you=
do so, a single regressor will be enough I would suggest. The only reaso=
n to model two accuracy regressors of no interest should be, that you wil=
l include one of them into your contrast in a different way than the othe=
r.
Depending on your intention other suggestion should be a parametric modul=
ation of the amplitude of your n back regressors (in that case with trial=
onsets) in order to to model out this accuracy related variance.=20
May be you could use only the session data in the analysis, where the acc=
uracy was over a specific theshold..
Kind regards,=20
Christoph
=========================================================================
Date: Fri, 20 May 2011 11:19:13 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: the order of the preprocessing
Comments: To: "[log in to unmask]" <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Mime-Version: 1.0 (iPad Mail 8C148)
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <8999032608280567062@unknownmsgid>
see
http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=SPM;5681190f.1105
On 20 May 2011, at 10:54, Jing Kan <[log in to unmask]> wrote:
> Dear SPM experts,
>
> May I ask a basic question about the data-preprocessing?
>
> In terms of the SPM tutorial I read, we can do the preprocessing either
> with the order "epoch" and then "filter" or "filter" and then "epoch".
>
> May I ask is it any effect with these two different ways?
>
> Many thanks,
>
> Jing
=========================================================================
Date: Fri, 20 May 2011 11:32:58 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: the order of the preprocessing
Comments: To: "[log in to unmask]" <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Mime-Version: 1.0 (iPad Mail 8C148)
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <2015229298723303602@unknownmsgid>
That was the only slide about order. Other slides are the same as in
previous years (see SPM website). We'll make this year's slides
available soon.
Vladimir
On 20 May 2011, at 11:22, "[log in to unmask]" <[log in to unmask]> wrote:
> Dear Vladimir,
>
> Thanks for your speedy help! It is quite clear. I really appreciate it!
>
> May I ask is it possible that I can have the slides you mentioned about this?
>
> Many thanks,
>
> Jing
>
>
>> see
>>
>> http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=SPM;5681190f.1105
>>
>>
>> On 20 May 2011, at 10:54, Jing Kan <[log in to unmask]> wrote:
>>
>>> Dear SPM experts,
>>>
>>> May I ask a basic question about the data-preprocessing?
>>>
>>> In terms of the SPM tutorial I read, we can do the preprocessing either
>>> with the order "epoch" and then "filter" or "filter" and then "epoch".
>>>
>>> May I ask is it any effect with these two different ways?
>>>
>>> Many thanks,
>>>
>>> Jing
>>
>
>
=========================================================================
Date: Fri, 20 May 2011 11:20:24 +0100
Reply-To: Michiko Yoshie <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michiko Yoshie <[log in to unmask]>
Subject: DICOM Import error
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Dear all,
I am using the latest version of SPM8 on MATLAB 7.9.0 (R2009b). When I
convert DICOM to NIfTI (.nii) using DICOM Import on Batch Editor, the
following error message appears after the conversion of all the DICOM
files has been completed:
---------------------------------------------------------------------
Error using ==> <a href=matlab:
opentoline('cfg_util.m',835,0)">cfg_util at 835</a>
Job execution failed. The full log of this run can be found in MATLAB
command window, starting with the lines (look for the line showing the
exact #job as displayed in this error message)
---------------------------------------------------------------------
Then I see the following log in MATLAB command window:
------------------------------------------------------------------------
Running job #1
------------------------------------------------------------------------
Running 'DICOM Import'
Changing directory to: C:\[specified output directory]\
Failed 'DICOM Import'
Error using ==> horzcat
CAT arguments dimensions are not consistent.
In file "C:\Program Files\spm\spm8\spm_dicom_convert.m" (v4213),
function "spm_dicom_convert" at line 61.
In file "C:\Program Files\spm\spm8\config\spm_run_dicom.m" (v2094),
function "spm_run_dicom" at line 32.
The following modules did not run:
Failed: DICOM Import
--------------------------------------------------------------------------------------
Despite this error message, it seems that all the NIfTI files have
been created in the specified output directory.
I wonder whether this error would affect my data or not. Could anyone
suggest how I could avoid this error?
Many thanks for your help,
Michiko
Michiko Yoshie, PhD
Clinical Imaging Sciences Centre
University of Sussex
=========================================================================
Date: Fri, 20 May 2011 11:46:43 +0100
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jing Kan <[log in to unmask]>
Subject: "normal average" for MEG data
MIME-Version: 1.0
Content-Type: text/plain;charset=iso-8859-1
Content-Transfer-Encoding: 8bit
Message-ID: <[log in to unmask]>
Dear SPM experts,
May I also ask another initial question:
When we do the averaging of the data in the preprocessing, there are
"robust average" and "normal average" two methods are provided, and the
"robust average" method are recommended. In the MEG data analysis after
the artefact rejection, can we directly use "normal average"?
Many thanls,
Jing
=========================================================================
Date: Fri, 20 May 2011 12:20:26 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: Question regarding kernel utilities
Comments: To: Alexander Ivanov <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
That's a good point. I realised a few weeks ago that I probably need
to extend the framework so that new subjects can be added more easily.
Essentially, when you compute the initial dot-products, you obtain
X1*X1'. You actually want [X1; X2]*[X1; X2]', where X2 contains data
from your new subject(s).
X = [X1; X2];
% XX = X*X';
XX = [X1*X1' X1*X2'; (X1*X2')' X2*X2'];
Best regards,
-John
On 20 May 2011 09:59, Alexander Ivanov <[log in to unmask]> wrote:
> Dear SPMers!
> I have a question regarding kernel utilities... I have searched the archives
> but haven't found any info on this topic... I would just like to be sure
> that I understood its application correctly... After preprocessing steps
> (for example, using vbm8 toolbox) I have got m0wrp* images... Afterwards I
> want to generate dot-product matrices for each set of images (gm, wm, csf).
> After all I have (N)x(M) dp-matrix (calculated using "Kernel from images"
> option), where N-th row reflects N-th subject (is that correct?)... Next I'm
> training a classifier (in my case it's SVM) with training subset of
> dp-matrix and testing it using corresponding subset.
> My last question may appear to be stupid, but.... As far as I understand, if
> I want to make a class prediction of a new subject I can't use my classifier
> anymore and I have to recalculate dp-matrix again in order to get
> (N+1)x(M+1) quadratic matrix... - right?
> Please excuse my for my weird questions...
> ===
> Best Regards,
> Alex
>
=========================================================================
Date: Fri, 20 May 2011 13:13:05 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: the order of the preprocessing
Comments: To: Urs Bachofner <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Mime-Version: 1.0 (iPad Mail 8C148)
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <4487417340626282225@unknownmsgid>
Dear Urs,
It's actually the other way around. Electrodes close to the reference
have lower amplitude responses and the reference itself will be zero.
This would be taken into account if we had forward model computation
for different references. Since at the moment we don't have this
feature you should switch to average reference and then it wouldn't
matter what the original reference was.
Best,
Vladimir
On 20 May 2011, at 11:42, Urs Bachofner <[log in to unmask]> wrote:
> Hi Vladimir!
>
> Thanks a lot for your last answer, apparently I'm not the only one who ha=
d this question.
>
> But I have another one that I already mentioned in my last E-mail:
>
> Considering the location of the reference electrode in different EEG nets=
, it should be clear that electrodes closer to that reference will have a h=
igher amplitude recorded than electrodes which are more distant. I'm not ex=
actly sure how big and relevant this difference is but shouldn't we have a =
preprocessing step that alleviates this bias by checking the coordinates of=
the electrodes involved and their distance to the reference electrode?
> I think if we don't eliminate this bias we will always have an overestima=
ted activation around the reference electrode in 3D source localisation.
>
> Thanks a lot for your opinion in this matter.
>
> Urs
>
>
> Am 20.05.2011 12:19, schrieb Vladimir Litvak:
>> see
>>
>> http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3DSPM;5681190f.1105
>>
>>
>> On 20 May 2011, at 10:54, Jing Kan<[log in to unmask]> wrote:
>>
>>> Dear SPM experts,
>>>
>>> May I ask a basic question about the data-preprocessing?
>>>
>>> In terms of the SPM tutorial I read, we can do the preprocessing eithe=
r
>>> with the order "epoch" and then "filter" or "filter" and then "epoch".
>>>
>>> May I ask is it any effect with these two different ways?
>>>
>>> Many thanks,
>>>
>>> Jing
>
=========================================================================
Date: Fri, 20 May 2011 13:17:40 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: "normal average" for MEG data
Comments: To: "[log in to unmask]" <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Mime-Version: 1.0 (iPad Mail 8C148)
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <-3967746890312576192@unknownmsgid>
Robust averaging can be used either as an alternative or in
combination with artefact rejection. If your data is clean you don't
have to use it.
Vladimir
On 20 May 2011, at 11:48, Jing Kan <[log in to unmask]> wrote:
> Dear SPM experts,
>
> May I also ask another initial question:
>
> When we do the averaging of the data in the preprocessing, there are
> "robust average" and "normal average" two methods are provided, and the
> "robust average" method are recommended. In the MEG data analysis after
> the artefact rejection, can we directly use "normal average"?
>
> Many thanls,
>
> Jing
=========================================================================
Date: Fri, 20 May 2011 15:14:51 +0100
Reply-To: Carolina Valencia <[log in to unmask].CO>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Carolina Valencia <[log in to unmask]>
Subject: Split Dicom folder
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Hi SPM users
I have a set of DICOM files from multiple series in one folder, and I wou=
ld like to organize them into separate folders based on the different ser=
ies (mprage, bold and so on), I can do this in Dicomviewer with the tool=
export Dicom series, but I'm not working on windows, I would like to kno=
w is there is a similar tool for ubuntu.
Thanks a lot,
Best regards,
Carolina
=========================================================================
Date: Fri, 20 May 2011 22:20:18 +0800
Reply-To: YAN Chao-Gan <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: YAN Chao-Gan <[log in to unmask]>
Subject: Re: Split Dicom folder
Comments: To: Carolina Valencia <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=90e6ba6e8c6843dd1b04a3b5d206
Message-ID: <[log in to unmask]>
--90e6ba6e8c6843dd1b04a3b5d206
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Dear Carolina,
You can try REST DICOM sorter. (From www.restfmri.net, REST->Utilities->REST
DICOM sorter).
Best wishes!
Chaogan
On Fri, May 20, 2011 at 10:14 PM, Carolina Valencia <[log in to unmask]
> wrote:
> Hi SPM users
>
> I have a set of DICOM files from multiple series in one folder, and I would
> like to organize them into separate folders based on the different series
> (mprage, bold and so on), I can do this in Dicomviewer with the tool export
> Dicom series, but I'm not working on windows, I would like to know is there
> is a similar tool for ubuntu.
>
> Thanks a lot,
>
> Best regards,
>
> Carolina
>
--
YAN Chao-Gan, Ph.D.
State Key Laboratory of Cognitive Neuroscience and Learning
Beijing Normal University
Beijing, China, 100875
[log in to unmask]
http://www.restfmri.net/forum/yanchaogan
--90e6ba6e8c6843dd1b04a3b5d206
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Dear Carolina,<br><br>You can try REST DICOM sorter. (From <a href=3D"http:=
//www.restfmri.net">www.restfmri.net</a>, REST->Utilities->REST DICOM=
sorter).<br><br>Best wishes!<br><br>Chaogan<br><br><br><div class=3D"gmail=
_quote">
On Fri, May 20, 2011 at 10:14 PM, Carolina Valencia <span dir=3D"ltr"><<=
a href=3D"mailto:[log in to unmask]">[log in to unmask]</a>></=
span> wrote:<br><blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8e=
x;border-left:1px #ccc solid;padding-left:1ex;">
Hi SPM users<br>
<br>
I have a set of DICOM files from multiple series in one folder, and I would=
like to organize them into separate folders based on the different series =
(mprage, bold and so on), =A0I can do this in Dicomviewer with the tool exp=
ort Dicom series, but I'm not working on windows, I would like to know =
is there is a similar tool for ubuntu.<br>
<br>
Thanks a lot,<br>
<br>
Best regards,<br>
<font color=3D"#888888"><br>
Carolina<br>
</font></blockquote></div><br><br clear=3D"all"><br>-- <br>YAN Chao-Gan, Ph=
.D.<br>State Key Laboratory of Cognitive Neuroscience and Learning<br>Beiji=
ng Normal University<br>Beijing, China, 100875 <br><a href=3D"mailto:ycg.ya=
[log in to unmask]" target=3D"_blank">[log in to unmask]</a><br>
<a href=3D"http://www.restfmri.net/forum/yanchaogan" target=3D"_blank">http=
://www.restfmri.net/forum/yanchaogan</a><br>
--90e6ba6e8c6843dd1b04a3b5d206--
=========================================================================
Date: Fri, 20 May 2011 08:26:48 -0700
Reply-To: "Jiang, Zhiguo" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Jiang, Zhiguo" <[log in to unmask]>
Subject: Re: Split Dicom folder
Comments: To: Carolina Valencia <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Content-Type: text/plain; charset="us-ascii"
Content-Transfer-Encoding: quoted-printable
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Message-ID: <[log in to unmask]>
You can use dicominfo (MATLAB command) figure out the protocol name and sor=
t them. It's simply a for-next loop with a call to dicominfo for each dicom=
file then move them into different folder.
---------------------------------------------------------------------------=
---------------------------------------------------
Tony Jiang,Ph.D.|Research Scholar|University of California, Los Angeles
Peter V. Ueberroth Building, Rm 2338C2|10945 Le Conte Avenue. Los Angeles,C=
A 90095
Tel: (310)206-1423|Email: [log in to unmask]
-----Original Message-----
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] On B=
ehalf Of Carolina Valencia
Sent: Friday, May 20, 2011 7:15 AM
To: [log in to unmask]
Subject: [SPM] Split Dicom folder
Hi SPM users
I have a set of DICOM files from multiple series in one folder, and I would=
like to organize them into separate folders based on the different series =
(mprage, bold and so on), I can do this in Dicomviewer with the tool expor=
t Dicom series, but I'm not working on windows, I would like to know is the=
re is a similar tool for ubuntu.
Thanks a lot,
Best regards,
Carolina
IMPORTANT WARNING: This email (and any attachments) is only intended for t=
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zed redisclosure or failure to maintain confidentiality may subject you to =
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immediately notify us by return email, and delete this message from your co=
mputer.
=========================================================================
Date: Fri, 20 May 2011 19:29:51 +0400
Reply-To: Alexander Ivanov <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Alexander Ivanov <[log in to unmask]>
Subject: Re: Question regarding kernel utilities
Comments: To: John Ashburner <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=001636988b5cf418a004a3b6ca21
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--001636988b5cf418a004a3b6ca21
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Thank you very much for such a quick response!
Therefore, "Phi" is a quadratic matrix where each column corresponds to each
subject, isn't it? (I previously thought otherwise : Phi(n , : ) is n-th
subject...)
====
Best Regards,
Alex
--001636988b5cf418a004a3b6ca21
Content-Type: text/html; charset=ISO-8859-1
Thank you very much for such a quick response!<div><br></div><div>Therefore, "Phi" is a quadratic matrix where each column corresponds to each subject, isn't it? (I previously thought otherwise : Phi(n , : ) is n-th subject...)</div>
<div>====</div><div>Best Regards,</div><div><br></div><div>Alex</div>
--001636988b5cf418a004a3b6ca21--
=========================================================================
Date: Fri, 20 May 2011 12:19:23 -0400
Reply-To: Jason Steffener <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jason Steffener <[log in to unmask]>
Subject: "cohort" and group effects
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Hello all,
I have data from 6 different "cohorts" that I would like to analysis
in one big group analysis.
I have two age groups (yng and old). The yng data are from 4 separate
studies and the old are from 2 separate studies.
The data were collected in "chunks" over a couple of years. So 20
young here, then another 20 young the following year etc. Although,
the training and task were the same I want to account for the fact
that the data were not collected continuously.
My interest is in age differences and want to make sure that I account
for any "cohort" effects so I can correctly interpret any age group
effects.
Based on box-plots of the behavioral data there is evidence of cohort effects.
Thank you for any guidance,
Jason
--
Jason Steffener, Ph.D.
Department of Neurology
Columbia University
http://www.cogneurosci.org/steffener.html
=========================================================================
Date: Fri, 20 May 2011 17:36:28 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: Question regarding kernel utilities
Comments: To: Alexander Ivanov <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Element i,j of the matrix corresponds to a dot-product between data
from subjects i and j.
Best regards,
-John
On 20 May 2011 16:29, Alexander Ivanov <[log in to unmask]> wrote:
> Thank you very much for such a quick response!
> Therefore, "Phi" is a quadratic matrix where each column corresponds to each
> subject, isn't it? (I previously thought otherwise : Phi(n , : ) is n-th
> subject...)
> ====
> Best Regards,
> Alex
=========================================================================
Date: Fri, 20 May 2011 12:46:16 -0400
Reply-To: Cameron Craddock <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Cameron Craddock <[log in to unmask]>
Subject: NEURO-BUREAU: ADHD-200 Processed Data New Additions
Comments: To: [log in to unmask],
FSL - FMRIB's Software Library <[log in to unmask]>,
[log in to unmask], [log in to unmask]
Mime-version: 1.0
Content-type: multipart/alternative; boundary="B_3388740383_19782828"
Message-ID: <[log in to unmask]>
> This message is in MIME format. Since your mail reader does not understand
this format, some or all of this message may not be legible.
--B_3388740383_19782828
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charset="US-ASCII"
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We would like to announce some valuable new additions to the ADHD-200
preprocessed dataset:
In order to further reduce barriers to competing in the ADHD-200 global
competition, the Neuro Bureau has reduced the functional neuroimaging data
to region of interest (ROI) time courses. ROIs were specified using the
automated anatomical labeling atlas, the Eickhoff-Zilles atlas, the
Harvard-Oxford atlas, the Talairach-Tournoux atlas as well as 200 and 400
region functional parcellations (Craddock et al. HBM, in press). The
resulting time courses are available as tab-delimited text files which can
easily be imported into any statistical or mathematical software.
(http://www.nitrc.org/plugins/mwiki/index.php/neurobureau:AthenaPipeline#Ext
racted_Time_Courses)
For those of you that prefer voxel-based morphometry to functional
connectivity, we would like to announce the release of the Burner pipeline
data. The results of this pipeline are modulated and normalized grey matter
maps derived using SPM.
(http://www.nitrc.org/plugins/mwiki/index.php/neurobureau:BurnerPipeline)
Although we are targeting the release dates of the preprocessed data for the
ADHD-200 global competition, this data will remain available long after the
competition has run its course. We hope that you find the ADHD-200
preprocessed data useful.
Cheers,
Cameron Craddock and The Neuro Bureau
--B_3388740383_19782828
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t-line-break: after-white-space; color: rgb(0, 0, 0); font-size: 14px; font-=
family: Calibri, sans-serif; "><div><!--StartFragment-->
<p class=3D"MsoNormal">We would like to announce some valuable new additions =
to the
ADHD-200 preprocessed dataset:<o:p></o:p></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">In order to further reduce barriers to competing in th=
e ADHD-200
global competition, the Neuro Bureau has reduced the functional neuroimagin=
g
data to region of interest (ROI) time courses.<span style=3D"mso-spacerun:yes=
">
</span>ROIs were specified using the automated anatomical labeling atlas, t=
he
Eickhoff-Zilles atlas, the Harvard-Oxford atlas, the Talairach-Tournoux atl=
as
as well as 200 and 400 region functional parcellations (Craddock et al. HBM=
, <i style=3D"mso-bidi-font-style:normal">in press</i>).<span style=3D"mso-space=
run:yes"> </span>The resulting time courses are available as
tab-delimited text files which can easily be imported into any statistical =
or
mathematical software. (http://www.nitrc.org/plugins/mwiki/index.php/neurob=
ureau:AthenaPipeline#Extracted_Time_Courses)<o:p></o:p></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">For those of you that prefer voxel-based morphometry t=
o
functional connectivity, we would like to announce the release of the Burne=
r
pipeline data.<span style=3D"mso-spacerun:yes"> </span>The results of t=
his
pipeline are modulated and normalized grey matter maps derived using SPM.<o=
:p></o:p></p>
<p class=3D"MsoNormal">(http://www.nitrc.org/plugins/mwiki/index.php/neurobur=
eau:BurnerPipeline)<o:p></o:p></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">Although we are targeting the release dates of the
preprocessed data for the ADHD-200 global competition, this data will remai=
n
available long after the competition has run its course.<span style=3D"mso-sp=
acerun:yes"> </span>We hope that you find the ADHD-200
preprocessed data useful. <o:p></o:p></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">Cheers,<o:p></o:p></p>
<p class=3D"MsoNormal">Cameron Craddock and The Neuro Bureau<o:p></o:p></p>
<!--EndFragment-->
</div></body></html>
--B_3388740383_19782828--
=========================================================================
Date: Fri, 20 May 2011 12:07:15 -0700
Reply-To: Mazly Mohamad <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Mazly Mohamad <[log in to unmask]>
Subject: Question regarding SPM8 DCM Batch
MIME-Version: 1.0
Content-Type: multipart/mixed; boundary="0-1506575205-1305918436=:28942"
Message-ID: <[log in to unmask]>
--0-1506575205-1305918436=:28942
Content-Type: multipart/alternative; boundary="0-1675381938-1305918436=:28942"
--0-1675381938-1305918436=:28942
Content-Type: text/plain; charset=us-ascii
Dear SPMers
By using limited knowledge in Matlab command, I've tried to change dcm_
spm8_batch command. Unfortunately...
??? Error using ==> inlineeval at 15
Error in inline expression ==> spm_int(P,M,U)
??? Error using ==> mtimes
Inner matrix dimensions must agree.
Error in ==> inline.feval at 36
INLINE_OUT_ = inlineeval(INLINE_INPUTS_,
INLINE_OBJ_.inputExpr, INLINE_OBJ_.expr);
Error in ==> spm_diff at 80
f0 = feval(f,x{:});
Error in ==> spm_nlsi_GN at 253
[dfdp f] = spm_diff(IS,Ep,M,U,1,{V});
Error in ==> spm_dcm_estimate at 172
[Ep,Cp,Eh,F] = spm_nlsi_GN(M,U,Y);
Error in ==> dcmtest at 57
DCM_K1M1 =
spm_dcm_estimate(fullfile(data_path,'DCM_K1_M1'));
I've attach my command . Can Anybody direct me the proper way? Thank you very
much
--0-1675381938-1305918436=:28942
Content-Type: multipart/related; boundary="0-867640889-1305918436=:28942"
--0-867640889-1305918436=:28942
Content-Type: text/html; charset=us-ascii
<html><head><style type="text/css"><!-- DIV {margin:0px;} --></style></head><body><div style="font-family:bookman old style,new york,times,serif;font-size:8pt;color:#003366;"><table width="100%" cellspacing="0" cellpadding="0" align="center"><tbody><tr><td width="100%" height="100%" bgcolor="#eff6fc" valign="top"><table width="100%" height="100%" style="table-layout:fixed;" cellspacing="0" cellpadding="0" align="center"><tbody><tr><td width="10"> </td><td valign="top" style="overflow: hidden; text-overflow: ellipsis; white-space: nowrap;"><table width="100%" style="white-space:normal;" cellspacing="0" cellpadding="0"><tbody><tr><td height="10"> </td></tr><tr><td><font face="bookman old style, new york, times, serif" size="1" color="#003366" style="font-family:bookman old style, new york, times, serif;font-size:8;color:#003366;"><div style="text-align:undefined;"><div>Dear SPMers<br><br><br>By using limited knowledge in Matlab command, I've tried to
change dcm_ spm8_batch command. Unfortunately... <br><br>??? Error using ==> inlineeval at 15<br>Error in inline expression ==> spm_int(P,M,U)<br>??? Error using ==> mtimes<br>Inner matrix dimensions must agree.<br><br>Error in ==> inline.feval at 36<br> INLINE_OUT_ = inlineeval(INLINE_INPUTS_,<br> INLINE_OBJ_.inputExpr, INLINE_OBJ_.expr);<br><br>Error in ==> spm_diff at 80<br> f0 = feval(f,x{:});<br><br>Error in ==> spm_nlsi_GN at 253<br> [dfdp f] = spm_diff(IS,Ep,M,U,1,{V});<br><br>Error in ==> spm_dcm_estimate at 172<br>[Ep,Cp,Eh,F] = spm_nlsi_GN(M,U,Y);<br><br>Error in ==> dcmtest at 57<br>DCM_K1M1 =<br>
spm_dcm_estimate(fullfile(data_path,'DCM_K1_M1'));<br><br><br><br><br>I've attach my command . Can Anybody direct me the proper way? Thank you very much<br></div>
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=========================================================================
Date: Fri, 20 May 2011 14:34:50 -0600
Reply-To: Andrea Burdine <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Andrea Burdine <[log in to unmask]>
Subject: postdoc in data driven methods for fMRI and/or data fusion of
multimodal imaging and genetics, ABQ, NM
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0016e649872eb3997604a3bb0d80
Message-ID: <[log in to unmask]>
--0016e649872eb3997604a3bb0d80
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Hello all,
A postdoctoral fellowship position is currently available in Dr. Calhoun=92=
s
laboratory (see http://mialab.mrn.org) at The Mind Research Network (MRN)
and the Department of Electrical and Computer Engineering at the University
of New Mexico. The MRN houses a dedicated Siemens TIM Trio 3T MRI scanner
and a 1.5T Mobile MRI scanner in addition to MEG, EEG, and a genetics lab.
This position will focus on the development and application of statistical
signal/image processing techniques and software for brain imaging data (e.g=
.
functional MRI, diffusion tensor imaging, structural MRI) and genome-wide
genetic and epigenetic data of psychiatric patients. Of particular focus
will be developing algorithms based upon the incorporation of prior
information (neuroanatomical, functional, biological, etc.) within a source
separation framework (independent component analysis, canonical correlation
analysis, etc). The ideal candidate will have experience with image/signal
processing and/or statistics, will be eager to learn about brain imaging,
and is looking for an opportunity in a richly interdisciplinary research
center. In addition to working on ongoing projects it is expected that the
individual will pursue his/her own research interests. Our ideal candidate
will have a Ph.D. in engineering, mathematics, statistics, or related field=
.
Prior expertise in brain image analysis preferred, but not required. Visit
mrn.org and click on Jobs to apply.
--=20
Andrea Burdine
Mind Research Network
Administrative Assistant for
Vince D. Calhoun, Ph.D.
Chief Technology Officer &
Director, Image Analysis and MR Research
1101 Yale Blvd NE
Albuquerque, NM 87106
505-301-5567 Office
505-272-8002 Fax
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Hello all,<br>
<p class=3D"MsoNormal">A postdoctoral fellowship position is currently avai=
lable in
Dr. Calhoun=92s laboratory (see <a href=3D"http://mialab.mrn.org" target=3D=
"_blank">http://mialab.mrn.org</a>) at The Mind Research
Network (MRN) and the Department of Electrical and Computer Engineering at =
the University of New Mexico. The MRN houses a dedicated
Siemens TIM Trio 3T MRI scanner and a 1.5T Mobile MRI scanner in addition t=
o
MEG, EEG, and a genetics lab. This position will focus on the development a=
nd
application of statistical signal/image processing techniques and software =
for brain
imaging data (e.g. functional MRI, diffusion tensor imaging, structural MRI=
)
and genome-wide genetic and epigenetic data of psychiatric patients. Of
particular focus will be developing algorithms based upon the incorporation=
of
prior information (neuroanatomical, functional, biological, etc.) within a
source separation framework (independent component analysis, canonical
correlation analysis, etc). The ideal candidate will have experience with
image/signal processing and/or statistics, will be eager to learn about bra=
in
imaging, and is looking for an opportunity in a richly interdisciplinary
research center. In addition to working on ongoing projects it is expected =
that
the individual will pursue his/her own research interests. Our ideal candid=
ate
will have a Ph.D. in engineering, mathematics, statistics, or related field=
.
Prior expertise in brain image analysis preferred, but not required. Visit
<a href=3D"http://mrn.org" target=3D"_blank">mrn.org</a> and click on Jobs =
to apply.</p>
<br clear=3D"all"><br>-- <br>Andrea Burdine<br>Mind Research Network<br>Adm=
inistrative Assistant for<br>Vince D. Calhoun, Ph.D.<br>
Chief Technology Officer &<br>
Director, Image Analysis and MR Research<br>1101 Yale Blvd NE<br>Albuquerqu=
e, NM 87106<br><a href=3D"tel:505-301-5567" value=3D"+15053015567" target=
=3D"_blank">505-301-5567</a> Office<br><a href=3D"tel:505-272-8002" value=
=3D"+15052728002" target=3D"_blank">505-272-8002</a> Fax<br>
<br>
--0016e649872eb3997604a3bb0d80--
=========================================================================
Date: Fri, 20 May 2011 16:54:57 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: "cohort" and group effects
Comments: To: Jason Steffener <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Jason,
If I understand you, you want to identify regions where OLD and YOUNG
are different. I assume there is only 1 image per subject for the
following scenarios:
A) use 6 groups in a one-way ANOVA, then create an old/young contrast.
This means that each cohort will have a different mean and variance
that is unaffected by the other groups.
B) if there are young and old from the same cohort of subjects, then I
would have a variable for age group and variables for cohort. Then the
contrast would be between the age group variables. The cohort variable
is then just an extra term that reduces the variance.
Personally, I like model A better as it doesn't infer that the cohort
effect has to be same across the age groups as model B assumes.
If you have repeated measures, subtract then you can only look at the
age*measure interaction since main effects of group aren't valid in
SPM.
Let me know if you have any questions.
On Friday, May 20, 2011, Jason Steffener <[log in to unmask]> wrote:
> Hello all,
>
> I have data from 6 different "cohorts" that I would like to analysis
> in one big group analysis.
>
> I have two age groups (yng and old). The yng data are from 4 separate
> studies and the old are from 2 separate studies.
> The data were collected in "chunks" over a couple of years. So 20
> young here, then another 20 young the following year etc. Although,
> the training and task were the same I want to account for the fact
> that the data were not collected continuously.
>
> My interest is in age differences and want to make sure that I account
> for any "cohort" effects so I can correctly interpret any age group
> effects.
>
> Based on box-plots of the behavioral data there is evidence of cohort effects.
>
> Thank you for any guidance,
> Jason
>
>
>
> --
> Jason Steffener, Ph.D.
> Department of Neurology
> Columbia University
> http://www.cogneurosci.org/steffener.html
>
--
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
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=========================================================================
Date: Fri, 20 May 2011 17:00:39 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Time derivative in event related design
Comments: To: Jonas Persson <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
See Investigating hemodynamic response variability at the group level
using basis functions by Steffener et al.
On Friday, May 20, 2011, Jonas Persson <[log in to unmask]> wrote:
> Hello fellow SPM:ers,
>
> I am a bit confused with regards to using the time derivative in SPM.
>
> The issue is that I have an event related paradigm where I do post hoc so=
rting of stimuli to 2 conditions. At the last SPM course I learned that sli=
ce time correction should be avoided, so instead of using time slice correc=
tion I wanted to include a second basis function to account for timing diff=
erences in data acquisition between slices.
>
> To check for regions significantly more activated in cond 1 vs cond 2 I d=
id an F-contrast [1 0 -1 0; 0 1 0 -1] to look for voxels associated with ei=
ther the HRF or td. I masked this contrast inclusive with a t-contrast [1 0=
-1 0] to only look at voxels with activation corresponding to the HRF. The=
problem here is that I'm telling SPM to look for voxels with different tim=
ing depending on condition, while I'm interested in allowing for timing dif=
ferences between regions regardless of condition.
>
> Another variant I've thought of is to merely do a t-contrast [1 0 -1 0], =
controlling for any variance associated with the td, but I read that this m=
ay give biased results.
>
> The next issue is how to perform the 2nd level analysis. With the latter =
method it's straightforward, but from what I understand I can't do a random=
effects on F-contrasts?
>
> Thank you for any suggestions!
>
> Bert regards,
>
> Jonas Persson
>
--=20
Best Regards, Donald McLaren
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital an=
d
Harvard Medical School
Office: (773) 406-2464
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773=
)
406-2464 or email.
=========================================================================
Date: Sat, 21 May 2011 04:55:04 +0100
Reply-To: Yang Hu <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Yang Hu <[log in to unmask]>
Subject: about parameters of PPI
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear all,
=20=20=20
I wonder that how to calculate the PPI.P, PPI.Y and PPI.ppi in SPM:
1) Is PPI.P =3D conv(design, spm_hrf(TR)) correct? (Note: design is a one=
-dimension array, which means the experimental design for scanning, such =
as off-on-off-on-off, the most basic form of block-design)
I've plot the two value, finding the shape nearly the same (but actually =
the values were a little bit different)
2) Is PPI.Y =3D conv(Y, spm_hrf(TR)) correct? (Note: Y is generated via "=
eigenvariate" button, which means the mean response in VOI)=20
It seems that values of PPI.Y ranges from (-2,2), indicating that it has =
been standardized, whereas values of Y are much larger (e.g. (130, 160))
3) Is PPI.ppi =3D PPI.P.*PPI.Y correct?
I've also plot the two value, finding the shape nearly the same (but actu=
ally the values were a little bit different)
I hope someone can make me understood. Thanks a lot!
Best wishes,
Yang Hu
ICN, ECNU, Shanghai, China
=========================================================================
Date: Sat, 21 May 2011 10:57:02 +0100
Reply-To: Yang Hu <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Yang Hu <[log in to unmask]>
Subject: question about spm_peb_ppi.m
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear All,
I would like to use spm_peb_ppi.m to generate the PPI. After reading =
the comment of this file, I was only not clear about the parameter called=
'Uu'.
Uu - Matrix of input variables and contrast weights. This is an=
[n x 3] matrix. The first column indexes SPM.Sess.U(i). =
The
second column indexes the name of the input or cause, se=
e
SPM.Sess.U(i).name{j}. The third column is the contrast
weight. Unless there are parametric effects the second
colulmn will generally be a 1.
=20
What does the n here mean? Does it mean the number of scans within o=
ne run? What's more, SPM.Sess.U(i) is a structure with several fields so =
I don't know how to put it in one column.
Any suggestions are welcom. Thanks a lot!
=20
Best wishes,
Yang
ICN, ECNU, Shanghai, China
=========================================================================
Date: Sat, 21 May 2011 11:02:30 +0000
Reply-To: Giuseppe Signorello <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Giuseppe Signorello <[log in to unmask]>
Subject: Time series
Content-Type: multipart/alternative;
boundary="_c89d05a1-43e7-43c8-ab9b-f5304159c54e_"
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Hi Spmrs=2C
I'm working FMRI files and then the preprocessing (realignment=2C time slic=
ing=2C etc.)=2C I would like to extract time series (temporal behaviour of =
the signals from cerebellum).
I have obtained the design matrix through the First model Specification in=
SPm.
From manual=2C I saw that I should define the T and F contrasts .
Is it correct?
How do I define these contrasts?
Thanks for your answers.
G.S.
=
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}
body.hmmessage
{
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</head>
<body class=3D'hmmessage'>
Hi Spmrs=2C<br>I'm working FMRI files and then the preprocessing (realignme=
nt=2C time slicing=2C etc.)=2C I would like to extract time series (tempora=
l behaviour of the signals from cerebellum).<br>I =3B have obtained the=
design matrix through the First model Specification in SPm.<br>From manual=
=2C I saw that I should define the T and F contrasts .<br>Is it correct?<br=
>How do I define these contrasts?<br><br><br>Thanks for your answers.<br><b=
r>G.S.<br><br><br> </body>
</html>=
--_c89d05a1-43e7-43c8-ab9b-f5304159c54e_--
=========================================================================
Date: Sat, 21 May 2011 13:24:06 -0700
Reply-To: Michael T Rubens <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michael T Rubens <[log in to unmask]>
Subject: Re: Time series
Comments: To: Giuseppe Signorello <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf305e27dfe574b904a3cf0608
Message-ID: <[log in to unmask]>
--20cf305e27dfe574b904a3cf0608
Content-Type: text/plain; charset=UTF-8
Check out MarsBaR for the time series extraction.
Cheers
On Sat, May 21, 2011 at 4:02 AM, Giuseppe Signorello <[log in to unmask]>wrote:
> Hi Spmrs,
> I'm working FMRI files and then the preprocessing (realignment, time
> slicing, etc.), I would like to extract time series (temporal behaviour of
> the signals from cerebellum).
> I have obtained the design matrix through the First model Specification in
> SPm.
> From manual, I saw that I should define the T and F contrasts .
> Is it correct?
> How do I define these contrasts?
>
>
> Thanks for your answers.
>
> G.S.
>
>
>
--
Research Associate
Gazzaley Lab
Department of Neurology
University of California, San Francisco
--20cf305e27dfe574b904a3cf0608
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Check out MarsBaR for the time series extraction. <br><br>Cheers<br><br><di=
v class=3D"gmail_quote">On Sat, May 21, 2011 at 4:02 AM, Giuseppe Signorell=
o <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">signo87@hotma=
il.it</a>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; borde=
r-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
<div>
Hi Spmrs,<br>I'm working FMRI files and then the preprocessing (realign=
ment, time slicing, etc.), I would like to extract time series (temporal be=
haviour of the signals from cerebellum).<br>I=C2=A0 have obtained the desig=
n matrix through the First model Specification in SPm.<br>
From manual, I saw that I should define the T and F contrasts .<br>Is it co=
rrect?<br>How do I define these contrasts?<br><br><br>Thanks for your answe=
rs.<br><br>G.S.<br><br><br> </div>
</blockquote></div><br><br clear=3D"all"><br>-- <br>Research Associate<br>G=
azzaley Lab<br>Department of Neurology<br>University of California, San Fra=
ncisco<br>
--20cf305e27dfe574b904a3cf0608--
=========================================================================
Date: Sun, 22 May 2011 17:58:03 +0100
Reply-To: SUBSCRIBE SPM Yihui Hung <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: SUBSCRIBE SPM Yihui Hung <[log in to unmask]>
Subject: three questions about SPM8
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Hello,=20
I used SPM8 for my experiment. I manipulated three factors (e.g., factor =
A, B, C) in my experiment. The activation maps under factor A was used as=
a mask to constrain the effects of factor B and factor C. The problem is=
that the factor A and factor B and factor C cannot be put in the same mo=
del at second level analysis. I tried to put the .img file resulting from=
factor A across participants in the =E2=80=9Cexplicit mask=E2=80=9D in t=
he second level analysis. However, the estimation stopped by showing no i=
nmask voxels. I searched through forum and did not find any useful soluti=
ons. Can someone help me out? Moreover, is the threshold masking related =
to the p value? If not, how should I set criteria for the activation map =
of the mask?=20=20=20
I did notice that one person in the forum suggested that one can create a=
n activation maps in which the factor B is modeled with the mask of facto=
r A in first level analysis. Then, submit the resulting .img file into se=
cond level analysis. My question is how to create and save the img file.=20=
Finally, I posted a question regarding how to export beta values over mul=
tiple coordinates a week ago. However, no one provide any answers. I wond=
er whether it is due that no one has the answer or due to that there alre=
ady is an answer in the forum.
Thank you for your patience and advice.
Sincerely,
Yihui=20
=20
=========================================================================
Date: Sun, 22 May 2011 22:23:57 +0200
Reply-To: "Eickhoff, Simon" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Eickhoff, Simon" <[log in to unmask]>
Subject: AW: [SPM] anatomy toolbox: small volume correction
Comments: To: Gemma Lamp <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Content-Type: multipart/alternative;
boundary="_000_4DEC2DB0EC56FA45A57A530E212839B5C0D24B6740MBXCLUSTER01a_"
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Message-ID: <[log in to unmask]>
--_000_4DEC2DB0EC56FA45A57A530E212839B5C0D24B6740MBXCLUSTER01a_
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Content-Transfer-Encoding: quoted-printable
Dear Gemma
Please note, that there are some differences in the way that SVC is perform=
ed in SPM and the Anatomy toolbox.
In SPM, the statistical image is first thresholded at the selected level. Y=
ou then supply the SVC mask and get a new stats-table indicating which of t=
he supro-threshold voxels (based on the previous threshold) are significant=
at the SVC level. Voxels not passing the initial threshold are not conside=
red, the display is not updated.
In the Anatomy toolbox, the statistical image is re-loaded when you perform=
the SVC, masked by the selected region of interest and thresholded such th=
at only the SVC-corrected voxels are displayed.
Hope this helps
Simon
________________________________
Von: SPM (Statistical Parametric Mapping) [[log in to unmask]] im Auftrag v=
on Gemma Lamp [[log in to unmask]]
Gesendet: Donnerstag, 19. Mai 2011 04:32
An: [log in to unmask]
Betreff: [SPM] anatomy toolbox: small volume correction
Hi,
I am currently doing an analysis where I'm limiting my ROIs to specified se=
nsory areas. When looking at the stats I use a pre-made mask in SPM to do a=
small volume correction. However, when I put it into anatomy toolbox, usin=
g the same statistical procedure and then use the anatomy toolbox SVC with =
the same ROI mask, i'm getting different cluster sizes and different areas =
showing to that in my original stats. Is there a bug in the SVC through ana=
tomy toolbox? Or is there something I am doing wrong? Is there an alternati=
ve way to do a small volume correction with anatomy toolbox to keep consist=
ent?
Thanks,
Gemma
--
Gemma Lamp
[http://www.discoveriesneeddollars.org/uploads/DND_email_signature.jpg]
---------------------------------------------------------------------------=
---------------------
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---------------------
Forschungszentrum Juelich GmbH
52425 Juelich
Sitz der Gesellschaft: Juelich
Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498
Vorsitzender des Aufsichtsrats: MinDirig Dr. Karl Eugen Huthmacher
Geschaeftsfuehrung: Prof. Dr. Achim Bachem (Vorsitzender),
Dr. Ulrich Krafft (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt,
Prof. Dr. Sebastian M. Schmidt
---------------------------------------------------------------------------=
---------------------
---------------------------------------------------------------------------=
---------------------
Besuchen Sie uns auf unserem neuen Webauftritt unter www.fz-juelich.de
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<div dir=3D"ltr"><font color=3D"#000000" size=3D"2" face=3D"Tahoma">Dear Ge=
mma</font></div>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma"></font> </div>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma"></font> </div>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma">Please note, that there a=
re some differences in the way that SVC is performed in SPM and the Anatomy=
toolbox.</font></div>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma"></font> </div>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma"></font> </div>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma">In SPM, the statistical i=
mage is first thresholded at the selected level. You then supply the SVC ma=
sk and get a new stats-table indicating which of the supro-threshold voxels=
(based on the previous threshold) are
significant at the SVC level. Voxels not passing the initial threshold are=
not considered, the display is not updated.</font></div>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma"></font> </div>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma">In the Anatomy toolbox, t=
he statistical image is re-loaded when you perform the SVC, masked by the s=
elected region of interest and thresholded such that only the SVC-corrected=
voxels are displayed.</font></div>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma"></font> </div>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma"></font> </div>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma">Hope this helps</font></d=
iv>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma">Simon</font></div>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma"></font> </div>
<div dir=3D"ltr"><font size=3D"2" face=3D"tahoma"></font> </div>
<div dir=3D"ltr"> </div>
<div dir=3D"ltr"> </div>
<div dir=3D"ltr">
<hr tabindex=3D"-1">
<font size=3D"2" face=3D"Tahoma"><b>Von:</b> SPM (Statistical Parametric Ma=
pping) [[log in to unmask]] im Auftrag von Gemma Lamp [[log in to unmask]
]<br>
<b>Gesendet:</b> Donnerstag, 19. Mai 2011 04:32<br>
<b>An:</b> [log in to unmask]<br>
<b>Betreff:</b> [SPM] anatomy toolbox: small volume correction<br>
</font><br>
</div>
<div></div>
<div>Hi,<br>
<br>
I am currently doing an analysis where I'm limiting my ROIs to specified se=
nsory areas. When looking at the stats I use a pre-made mask in SPM to do a=
small volume correction. However, when I put it into anatomy toolbox, usin=
g the same statistical procedure
and then use the anatomy toolbox SVC with the same ROI mask, i'm getting d=
ifferent cluster sizes and different areas showing to that in my original s=
tats. Is there a bug in the SVC through anatomy toolbox? Or is there someth=
ing I am doing wrong? Is there an
alternative way to do a small volume correction with anatomy toolbox to ke=
ep consistent?<br>
<br>
Thanks,<br>
Gemma<br clear=3D"all">
<br>
-- <br>
Gemma Lamp<br>
<br>
<img src=3D"http://www.discoveriesneeddollars.org/uploads/DND_email_signatu=
re.jpg"><br>
<br>
</div>
<br>
<font face=3D"Arial" color=3D"Black" size=3D"1">---------------------------=
---------------------------------------------------------------------<br>
---------------------------------------------------------------------------=
---------------------<br>
Forschungszentrum Juelich GmbH<br>
52425 Juelich<br>
Sitz der Gesellschaft: Juelich<br>
Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498<br>
Vorsitzender des Aufsichtsrats: MinDirig Dr. Karl Eugen Huthmacher<br>
Geschaeftsfuehrung: Prof. Dr. Achim Bachem (Vorsitzender),<br>
Dr. Ulrich Krafft (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt,<br>
Prof. Dr. Sebastian M. Schmidt<br>
---------------------------------------------------------------------------=
---------------------<br>
---------------------------------------------------------------------------=
---------------------<br>
<br>
Besuchen Sie uns auf unserem neuen Webauftritt unter www.fz-juelich.de<br>
</font>
</body>
</html>
--_000_4DEC2DB0EC56FA45A57A530E212839B5C0D24B6740MBXCLUSTER01a_--
=========================================================================
Date: Sun, 22 May 2011 19:19:26 -0700
Reply-To: Michael T Rubens <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michael T Rubens <[log in to unmask]>
Subject: Re: three questions about SPM8
Comments: To: SUBSCRIBE SPM Yihui Hung <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf3005df64823a9f04a3e81b08
Message-ID: <[log in to unmask]>
--20cf3005df64823a9f04a3e81b08
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
when you say you tried to use the contrast as a mask, did you just use the
raw contrast or did you binarize it? If you did the former than it is clear
why you had no inmask voxels since any non-zero voxels would all be seen as
part of the mask. So, what you want to do is load the mask, apply a
threshold and binarize it by setting anything below the threshold to 0, and
anything above to 1 (though the latter may not be completely necessary).
Then, you could just use that mask to mask out the resulting contrast map
from the other analysis. Here is code to do it:
%Make mask
V =3D spm_vol('contrast_image_2turn_into_mask')
Y =3D spm_read_vols(V);
threshold =3D X; %any value you choose.
Y(find(Y<threshold)) =3D 0;
Y(find(Y)) =3D 1;
% Use mask
VV =3D spm_vol('contrast_image_2mask');
YY =3D spm_vol(VV);
YY(find(Y)) =3D 0; %apply mask
VV.fname =3D 'masked_image.img';
spm_write_vol(VV,YY);
%% There ya go
Cheers,
Michael
On Sun, May 22, 2011 at 9:58 AM, SUBSCRIBE SPM Yihui Hung <
[log in to unmask]> wrote:
> Hello,
>
> I used SPM8 for my experiment. I manipulated three factors (e.g., factor =
A,
> B, C) in my experiment. The activation maps under factor A was used as a
> mask to constrain the effects of factor B and factor C. The problem is th=
at
> the factor A and factor B and factor C cannot be put in the same model at
> second level analysis. I tried to put the .img file resulting from factor=
A
> across participants in the =E2=80=9Cexplicit mask=E2=80=9D in the second =
level analysis.
> However, the estimation stopped by showing no inmask voxels. I searched
> through forum and did not find any useful solutions. Can someone help me
> out? Moreover, is the threshold masking related to the p value? If not, h=
ow
> should I set criteria for the activation map of the mask?
>
> I did notice that one person in the forum suggested that one can create a=
n
> activation maps in which the factor B is modeled with the mask of factor =
A
> in first level analysis. Then, submit the resulting .img file into second
> level analysis. My question is how to create and save the img file.
>
> Finally, I posted a question regarding how to export beta values over
> multiple coordinates a week ago. However, no one provide any answers. I
> wonder whether it is due that no one has the answer or due to that there
> already is an answer in the forum.
>
> Thank you for your patience and advice.
> Sincerely,
>
> Yihui
>
>
--=20
Research Associate
Gazzaley Lab
Department of Neurology
University of California, San Francisco
--20cf3005df64823a9f04a3e81b08
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
when you say you tried to use the contrast as a mask, did you just use the =
raw contrast or did you binarize it? If you did the former than it is clear=
why you had no inmask voxels since any non-zero voxels would all be seen a=
s part of the mask. So, what you want to do is load the mask, apply a thres=
hold and binarize it by setting anything below the threshold to 0, and anyt=
hing above to 1 (though the latter may not be completely necessary). Then, =
you could just use that mask to mask out the resulting contrast map from th=
e other analysis. Here is code to do it:<br>
<br>%Make mask<br><br>V =3D spm_vol('contrast_image_2turn_into_mask'=
;)<br>Y =3D spm_read_vols(V);<br><br>threshold =3D X; %any value you choose=
.<br><br>Y(find(Y<threshold)) =3D 0;<br>Y(find(Y)) =3D 1;<br><br>% Use m=
ask<br>
<br>VV =3D spm_vol('contrast_image_2mask');<br>YY =3D spm_vol(VV);<=
br><br>YY(find(Y)) =3D 0; %apply mask<br><br>VV.fname =3D 'masked_image=
.img';<br>spm_write_vol(VV,YY);<br><br>%% There ya go<br><br>Cheers,<br=
>Michael<br>
<br><div class=3D"gmail_quote">On Sun, May 22, 2011 at 9:58 AM, SUBSCRIBE S=
PM Yihui Hung <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]
tw">[log in to unmask]</a>></span> wrote:<br><blockquote class=3D"g=
mail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(=
204, 204, 204); padding-left: 1ex;">
Hello,<br>
<br>
I used SPM8 for my experiment. I manipulated three factors (e.g., factor A,=
B, C) in my experiment. The activation maps under factor A was used as a m=
ask to constrain the effects of factor B and factor C. The problem is that =
the factor A and factor B and factor C cannot be put in the same model at s=
econd level analysis. I tried to put the .img file resulting from factor A =
across participants in the =E2=80=9Cexplicit mask=E2=80=9D in the second le=
vel analysis. However, the estimation stopped by showing no inmask voxels. =
I searched through forum and did not find any useful solutions. Can someone=
help me out? Moreover, is the threshold masking related to the p value? If=
not, how should I set criteria for the activation map of the mask?<br>
<br>
I did notice that one person in the forum suggested that one can create an =
activation maps in which the factor B is modeled with the mask of factor A =
in first level analysis. Then, submit the resulting .img file into second l=
evel analysis. My question is how to create and save the img file.<br>
<br>
Finally, I posted a question regarding how to export beta values over multi=
ple coordinates a week ago. However, no one provide any answers. I wonder w=
hether it is due that no one has the answer or due to that there already is=
an answer in the forum.<br>
<br>
Thank you for your patience and advice.<br>
Sincerely,<br>
<font color=3D"#888888"><br>
Yihui<br>
<br>
</font></blockquote></div><br><br clear=3D"all"><br>-- <br>Research Associa=
te<br>Gazzaley Lab<br>Department of Neurology<br>University of California, =
San Francisco<br>
--20cf3005df64823a9f04a3e81b08--
=========================================================================
Date: Mon, 23 May 2011 10:40:54 +0200
Reply-To: Bart Boets <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Bart Boets <[log in to unmask]>
Subject: Vacancy for one postdoc and one PhD student in Leuven, Belgium
Content-Type: multipart/alternative;
boundary="_000_D290D66D539A4249887B042F194BE70D01957F6B21A1ICTSSEXC1CA_"
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
--_000_D290D66D539A4249887B042F194BE70D01957F6B21A1ICTSSEXC1CA_
Content-Type: text/plain; charset="Windows-1252"
Content-Transfer-Encoding: quoted-printable
Can you please distribute this message to potentially interested people?
We are looking for two bright and motivated researchers to work on a resear=
ch project in which we will use brain imaging and advanced brain decoding m=
ethods to investigate the neural basis of deviant mental representations in=
neurodevelopmental disorders such as autism, dyslexia, and dyscalculia. Th=
is project is an interdisciplinary collaboration between the Laboratory of =
Biological Psychology (Hans Op de Beeck), the Parenting and Special Educati=
on Research Group (Bert De Smedt), and Child Psychiatry (Jean Steyaert, Bar=
t Boets), all part of the University of Leuven (K.U.Leuven) in Belgium.
We offer one PhD position and one Post-doc position. Eligible candidates sh=
ould have or should soon obtain a master=92s degree (for the PhD position) =
and a PhD (for the postdoc position) in a relevant field such as neuroscien=
ce, psychology, psychiatry, neurobiology, or medical engineering. Specific =
positive points for the evaluation will be experience with brain imaging (i=
n particular functional magnetic resonance imaging), a computational backgr=
ound in a relevant field (e.g., brain imaging data analysis, neural network=
s, etc.), and good computer skills (e.g., Matlab). A background in neurodev=
elopmental disorders is a plus, but not mandatory. Good English (oral and w=
ritten) communicative skills are necessary.
The two positions are full-time, for a period of 4 years (PhD position) and=
2-3 years (postdoc), and start in October 2011. The two positions are stro=
ngly research oriented, and teaching and/or administration load will be min=
imal. The research will be embedded in a very stimulating environment with =
state-of-the-art technical facilities and with ample opportunities for inte=
raction with experts on neurodevelopmental disorders and brain imaging. The=
K.U.Leuven is consistently ranked within the top of European Universities =
and is located in the city of Leuven, which has an strong international app=
eal. For more information about our university, please visit http://www.kul=
euven.be/about/
Formal applications should be sent by email to Hans Op de Beeck, and should=
include a scientific CV (mentioning past research positions and education,=
and publications), motivation letter, and the names and contact informatio=
n of 2 senior researchers that are willing to write a recommendation letter=
if necessary (no letters have to be sent yet). Application deadline is Jun=
e 20th 2011.
For further information please contact Hans Op de Beeck (hans.opdebeeck@psy=
.kuleuven.be<mailto:[log in to unmask]>), Bert De Smedt (Bert.D=
[log in to unmask]<mailto:[log in to unmask]>), or Bart Boets=
([log in to unmask]<mailto:[log in to unmask]>).
Bart Boets, PhD
Postdoctoral fellow of the Research Foundation - Flanders
Leuven Autism Research Consortium
Child and Adolescent Psychiatry
Herestraat 49 - box 7003, B-3000 Leuven, BELGIUM
Tel. +32 (0)16/ 34.22.45
Fax. +32 (0)16/ 34.38.30
Email: [log in to unmask]<mailto:[log in to unmask]>
--_000_D290D66D539A4249887B042F194BE70D01957F6B21A1ICTSSEXC1CA_
Content-Type: text/html; charset="Windows-1252"
Content-Transfer-Encoding: quoted-printable
<html dir=3D"ltr"><head>
<meta http-equiv=3D"Content-Type" content=3D"text/html; charset=3DWindows-1=
252">
<style id=3D"owaTempEditStyle"></style><style title=3D"owaParaStyle"><!--P =
{
MARGIN-TOP: 0px; MARGIN-BOTTOM: 0px
}
--></style>
</head>
<body ocsi=3D"x">
<div style=3D"FONT-FAMILY: Tahoma; DIRECTION: ltr; COLOR: #000000; FONT-SIZ=
E: 13px">
<div></div>
<div dir=3D"ltr"><font color=3D"#000000" size=3D"2" face=3D"Tahoma">
<p class=3D"MsoNormal">Can you please distribute this message to potentiall=
y interested people?</p>
<p class=3D"MsoNormal"> </p>
<p class=3D"MsoNormal">We are looking for two bright and motivated research=
ers to work on a research project in which we will use
<b>brain imaging and advanced brain decoding methods to investigate the neu=
ral basis of deviant mental representations in neurodevelopmental disorders=
such as autism, dyslexia, and dyscalculia</b>. This project is an interdis=
ciplinary collaboration between
the Laboratory of Biological Psychology (Hans Op de Beeck), the Parenting =
and Special Education Research Group (Bert De Smedt), and Child Psychiatry =
(Jean Steyaert, Bart Boets), all part of the University of Leuven (K.U.Leuv=
en) in Belgium.
</p>
<p class=3D"MsoNormal">We offer one PhD position and one Post-doc position.=
Eligible candidates should have or should soon obtain a master=92s degree =
(for the PhD position) and a PhD (for the postdoc position) in a relevant f=
ield such as neuroscience, psychology,
psychiatry, neurobiology, or medical engineering. Specific positive points=
for the evaluation will be experience with brain imaging (in particular fu=
nctional magnetic resonance imaging), a computational background in a relev=
ant field (e.g., brain imaging data
analysis, neural networks, etc.), and good computer skills (e.g., Matlab).=
A background in neurodevelopmental disorders is a plus, but not mandatory.=
Good English (oral and written) communicative skills are necessary.</p>
<p style=3D"LINE-HEIGHT: 115%" class=3D"MsoPlainText">The two positions are=
full-time, for a period of 4 years (PhD position) and 2-3 years (postdoc),=
and start in October 2011. The two positions are strongly research oriente=
d, and teaching and/or administration
load will be minimal. The research will be embedded in a very stimulating =
environment with state-of-the-art technical facilities and with ample oppor=
tunities for interaction with experts on neurodevelopmental disorders and b=
rain imaging. The K.U.Leuven is
consistently ranked within the top of European Universities and is located=
in the city of Leuven, which has an strong international appeal. For more =
information about our university, please visit
<a href=3D"http://www.kuleuven.be/about/" target=3D"_blank"><font color=3D"=
#0000ff">http://www.kuleuven.be/about/</font></a>
</p>
<p style=3D"LINE-HEIGHT: 115%" class=3D"MsoPlainText"> </p>
<p class=3D"MsoNormal">Formal applications should be sent by email to Hans =
Op de Beeck, and should include a scientific CV (mentioning past research p=
ositions and education, and publications), motivation letter, and the names=
and contact information of 2 senior
researchers that are willing to write a recommendation letter if necessary=
(no letters have to be sent yet). Application deadline is June 20<sup>th</=
sup> 2011.</p>
<p class=3D"MsoNormal">For further information please contact Hans Op de Be=
eck (<a href=3D"mailto:[log in to unmask]"><font color=3D"#0000=
ff">[log in to unmask]</font></a>), Bert De Smedt (<a href=3D"m=
ailto:[log in to unmask]"><font color=3D"#0000ff">Bert.DeSmedt@pe=
d.kuleuven.be</font></a>),
or Bart Boets (<a href=3D"mailto:[log in to unmask]"><font color=
=3D"#0000ff">[log in to unmask]</font></a>).
</p>
<p class=3D"MsoNormal"><font face=3D"tahoma"></font> </p>
<p class=3D"MsoNormal"> </p>
</font></div>
<div><font size=3D"2" face=3D"Tahoma">
<div>
<div class=3D"MsoNormal"><font color=3D"navy" size=3D"1" face=3D"Arial"><sp=
an style=3D"FONT-FAMILY: Arial; COLOR: navy; FONT-SIZE: 9pt" lang=3D"EN-GB"=
>Bart Boets</span></font><font color=3D"navy" size=3D"1" face=3D"Arial"><sp=
an style=3D"FONT-FAMILY: Arial; COLOR: navy; FONT-SIZE: 9pt" lang=3D"EN-GB"=
>,
PhD<br>
Postdoctoral fellow of the Research Foundation - Flanders <br>
Leuven Autism Research Consortium</span></font></div>
<div class=3D"MsoNormal"><font color=3D"navy" size=3D"1" face=3D"Arial"><sp=
an style=3D"FONT-FAMILY: Arial; COLOR: navy; FONT-SIZE: 9pt" lang=3D"EN-GB"=
><font size=3D"2" face=3D"arial">Child and Adolescent Psychiatry</font>
<br>
Herestraat 49 - box 7003, </span></font><font color=3D"navy" size=3D"1" fac=
e=3D"Arial"><span style=3D"FONT-FAMILY: Arial; COLOR: navy; FONT-SIZE: 9pt"=
lang=3D"EN-GB">B-3000 Leuven, BELGIUM</span></font><font color=3D"navy" si=
ze=3D"1" face=3D"Arial"><span style=3D"FONT-FAMILY: Arial; COLOR: navy; FON=
T-SIZE: 9pt" lang=3D"EN-GB"></span></font></div>
<div class=3D"MsoNormal"><font color=3D"navy" size=3D"1" face=3D"Arial"><sp=
an style=3D"FONT-FAMILY: Arial; COLOR: navy; FONT-SIZE: 7.5pt" lang=3D"EN-G=
B"></span></font> </div>
<div class=3D"MsoNormal"><font color=3D"navy" size=3D"1" face=3D"Arial"><sp=
an style=3D"FONT-FAMILY: Arial; COLOR: navy; FONT-SIZE: 9pt" lang=3D"EN-GB"=
>Tel. +32 (0)16/ 34.22.45<br>
Fax. +32 (0)16/ 34.38.30<br>
Email:</span></font><font color=3D"blue" size=3D"1" face=3D"Arial"><span st=
yle=3D"FONT-FAMILY: Arial; COLOR: blue; FONT-SIZE: 9pt" lang=3D"EN-GB">
</span></font><font color=3D"blue" size=3D"1" face=3D"Arial"><span style=3D=
"FONT-FAMILY: Arial; COLOR: blue; FONT-SIZE: 9pt"><a href=3D"mailto:bart.bo=
[log in to unmask]"><span lang=3D"EN-GB">[log in to unmask]</span>=
</a></span></font><font color=3D"blue" size=3D"1" face=3D"Arial"><span styl=
e=3D"FONT-FAMILY: Arial; COLOR: blue; FONT-SIZE: 9pt">
<span lang=3D"EN-GB"></span></span></font></div>
</div>
</font></div>
</div>
</body>
</html>
--_000_D290D66D539A4249887B042F194BE70D01957F6B21A1ICTSSEXC1CA_--
=========================================================================
Date: Mon, 23 May 2011 11:11:40 +0100
Reply-To: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Subject: Re: Split Dicom folder
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Dear Carolina,
if it is sufficient to have the converted NIfTI files sorted, you can try=
SPM DICOM import in "Expert mode". In SPMs batch GUI, select SPM->Util->=
DICOM Import. There is a menu item called "Directory structure for conver=
ted files". Here you can specify whether SPM should put converted files i=
nto subject and session specific folders. Note that this option is not av=
ailable if you run DICOM Import via the button in the SPM menu window.
Hope this helps,
Volkmar
=========================================================================
Date: Mon, 23 May 2011 11:22:58 +0100
Reply-To: Sven Collette <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Sven Collette <[log in to unmask]>
Subject: Re: question about spm_peb_ppi.m
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Dear Yang,
the uU in spm_peb_ppi.m defines your [nx3] PPI matrix, where n is the num=
ber of your regressors.
let's say you have 4 regressors [A B C D] , no parametric modulation, and=
you want your psychological variable to be C-D. in this case your [nx3] =
matrix would look like this: [ [1:4]' [1 1 1 1]' [0 0 1 -1]'].
hope this helps,
Sven
=========================================================================
Date: Mon, 23 May 2011 14:13:28 +0100
Reply-To: Inci Ayhan <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Inci Ayhan <[log in to unmask]>
Subject: converting from .IMA to nifti format
MIME-Version: 1.0
Content-Type: text/plain;charset=iso-8859-1
Content-Transfer-Encoding: 8bit
Message-ID: <[log in to unmask]>
Hi,
I am trying to convert 3D EPI images (Siemens - .IMA format) into nifti
format using SPM. Because the images do not have a .dcm extension, I
cannot use "dicom2nifti" function.
I would so much appreciate any help to suggest a way to do so.
Thank you very much.
Inci
=========================================================================
Date: Mon, 23 May 2011 15:26:57 +0200
Reply-To: Francesco Barban <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Francesco Barban <[log in to unmask]>
Subject: DCM.A DCM.B
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Dear DCM experts,
is it allowed to test the modulatory effect (DCM.B) on a non
significant (one sample t test) latent connection (DCM.A)?
Thank you
Francesco Barban
=========================================================================
Date: Mon, 23 May 2011 09:11:05 -0500
Reply-To: Carolina Valencia <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Carolina Valencia <[log in to unmask]>
Subject: Re: Split Dicom folder
Comments: To: Volkmar Glauche <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf3056446dd6229004a3f20a12
Message-ID: <[log in to unmask]>
--20cf3056446dd6229004a3f20a12
Content-Type: text/plain; charset=ISO-8859-1
Thanks very much for the help, It works!
I just want to know (for simple curiosity) if there is a tool that split
Dicom different from SPM to Ubuntu OS
Thanks,
Best regards,
Carolina
2011/5/23 Volkmar Glauche <[log in to unmask]>
> Dear Carolina,
>
> if it is sufficient to have the converted NIfTI files sorted, you can try
> SPM DICOM import in "Expert mode". In SPMs batch GUI, select
> SPM->Util->DICOM Import. There is a menu item called "Directory structure
> for converted files". Here you can specify whether SPM should put converted
> files into subject and session specific folders. Note that this option is
> not available if you run DICOM Import via the button in the SPM menu window.
>
> Hope this helps,
>
> Volkmar
>
--20cf3056446dd6229004a3f20a12
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Thanks very much for the help, It works!<div><br></div><div>I just want to =
know (for simple curiosity) if there is a tool that split Dicom different f=
rom SPM to Ubuntu OS</div><div><br></div><div>Thanks,</div><div><br></div>
<div>Best regards,</div><div><br></div><div>Carolina<br><br><div class=3D"g=
mail_quote">2011/5/23 Volkmar Glauche <span dir=3D"ltr"><<a href=3D"mail=
to:[log in to unmask]">volkmar.glauche@uniklinik-freibur=
g.de</a>></span><br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex;">Dear Carolina,<br>
<br>
if it is sufficient to have the converted NIfTI files sorted, you can try S=
PM DICOM import in "Expert mode". In SPMs batch GUI, select SPM-&=
gt;Util->DICOM Import. There is a menu item called "Directory struc=
ture for converted files". Here you can specify whether SPM should put=
converted files into subject and session specific folders. Note that this =
option is not available if you run DICOM Import via the button in the SPM m=
enu window.<br>
<br>
Hope this helps,<br>
<font color=3D"#888888"><br>
Volkmar<br>
</font></blockquote></div><br><br clear=3D"all"><br>
</div>
--20cf3056446dd6229004a3f20a12--
=========================================================================
Date: Mon, 23 May 2011 17:19:14 +0200
Reply-To: Anne-Laure Fouque <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Anne-Laure Fouque <[log in to unmask]>
Subject: Problem with Dartel normalize to MNI / Warp to template
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=485b3979db46b397dc04a3f2ff1b
Message-ID: <[log in to unmask]>
--485b3979db46b397dc04a3f2ff1b
Content-Type: text/plain; charset=ISO-8859-1
Hello everybody,
I ran into a problem using Dartel, I'm not sure what I did wrong.
Here is what the images went through:
* new segmentation -> c1*, c2*, rc1*, rc2* ... everything looks OK
* Dartel create template -> Template*, u_rc1* everything still looks OK
* Dartel normalize to MNI - this doesn't work... smwc1* images are empty
(filled with zeros) or there is just a weird white blob that doesn't look
like a brain at all
I tried changing some options, it didn't do any good. Just warping the
images to the template (without the affine transformation to MNI) doesn't
work any better.
Does anyone have an idea about what could be wrong here ?
Thanks in advance.
--485b3979db46b397dc04a3f2ff1b
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Hello everybody,<div><br></div><div>I ran into a problem using Dartel, I=
9;m not sure what I did wrong.</div><div><br></div><div>Here is what the im=
ages went through:</div><div>* new segmentation -> c1*, c2*, rc1*, rc2* =
... everything looks OK</div>
<div>* Dartel create template -> Template*, u_rc1* =A0everything still l=
ooks OK</div><div>* Dartel normalize to MNI - this doesn't work... smwc=
1* images are empty (filled with zeros) or there is just a weird white blob=
that doesn't look like a brain at all</div>
<div><br></div><div>I tried changing some options, it didn't do any goo=
d. Just warping the images to the template (without the affine transformati=
on to MNI) doesn't work any better.</div><div><br></div><div>Does anyon=
e have an idea about what could be wrong here ?</div>
<div><br></div><div>Thanks in advance.</div>
--485b3979db46b397dc04a3f2ff1b--
=========================================================================
Date: Mon, 23 May 2011 11:44:39 -0400
Reply-To: adams adams <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: adams adams <[log in to unmask]>
Subject: Unit for design
Comments: To: [log in to unmask]
In-Reply-To: <[log in to unmask]>
Content-Type: multipart/alternative;
boundary="_1b0d0039-e2e6-4eb1-8b53-ae4514dc3633_"
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
--_1b0d0039-e2e6-4eb1-8b53-ae4514dc3633_
Content-Type: text/plain; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
hello Everyone=2C
Just a quick a question=2C
during the first level analysis=2C for the unit design do we use Scan or Se=
cond=2C are they the same....
Than you for your help
=
--_1b0d0039-e2e6-4eb1-8b53-ae4514dc3633_
Content-Type: text/html; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
<html>
<head>
<style><!--
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{
margin:0px=3B
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}
body.hmmessage
{
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</head>
<body class=3D'hmmessage'>
<br><br>
<meta http-equiv=3D"Content-Type" content=3D"text/html=3B charset=3Dunicode=
">
<meta name=3D"Generator" content=3D"Microsoft SafeHTML">
<style>
.ExternalClass .ecxhmmessage P
{padding:0px=3B}
.ExternalClass body.ecxhmmessage
{font-size:10pt=3Bfont-family:Tahoma=3B}
</style>
hello Everyone=2C<br>Just a quick a question=2C<br>during the first level a=
nalysis=2C for the unit design do we use Scan or Second=2C are they the sam=
e....<br>Than you =3B for your help<br><br><br> </body>
</html>=
--_1b0d0039-e2e6-4eb1-8b53-ae4514dc3633_--
=========================================================================
Date: Mon, 23 May 2011 11:44:10 -0400
Reply-To: adams adams <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: adams adams <[log in to unmask]>
Subject: Re: Problem with Dartel normalize to MNI / Warp to template
Comments: To: [log in to unmask]
In-Reply-To: <[log in to unmask]>
Content-Type: multipart/alternative;
boundary="_57de950d-93fb-48d9-94cb-c5a619dd2b91_"
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
--_57de950d-93fb-48d9-94cb-c5a619dd2b91_
Content-Type: text/plain; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
hello Everyone=2C
Just a quick a question=2C
during the first level analysis=2C for the unit design do we use Scan or Se=
cond=2C are they the same....
Than you for your help
Date: Mon=2C 23 May 2011 17:19:14 +0200
From: [log in to unmask]
Subject: [SPM] Problem with Dartel normalize to MNI / Warp to template
To: [log in to unmask]
Hello everybody=2C
I ran into a problem using Dartel=2C I'm not sure what I did wrong.
Here is what the images went through:* new segmentation -> c1*=2C c2*=2C rc=
1*=2C rc2* ... everything looks OK
* Dartel create template -> Template*=2C u_rc1* everything still looks OK*=
Dartel normalize to MNI - this doesn't work... smwc1* images are empty (fi=
lled with zeros) or there is just a weird white blob that doesn't look like=
a brain at all
I tried changing some options=2C it didn't do any good. Just warping the im=
ages to the template (without the affine transformation to MNI) doesn't wor=
k any better.
Does anyone have an idea about what could be wrong here ?
Thanks in advance. =
--_57de950d-93fb-48d9-94cb-c5a619dd2b91_
Content-Type: text/html; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
<html>
<head>
<style><!--
.hmmessage P
{
margin:0px=3B
padding:0px
}
body.hmmessage
{
font-size: 10pt=3B
font-family:Tahoma
}
--></style>
</head>
<body class=3D'hmmessage'>
hello Everyone=2C<br>Just a quick a question=2C<br>during the first level a=
nalysis=2C for the unit design do we use Scan or Second=2C are they the sam=
e....<br>Than you =3B for your help<br><br><br><hr id=3D"stopSpelling">=
Date: Mon=2C 23 May 2011 17:19:14 +0200<br>From: [log in to unmask]
<br>Subject: [SPM] Problem with Dartel normalize to MNI / Warp to template<=
br>To: [log in to unmask]<br><br>Hello everybody=2C<div><br></div><div>I ra=
n into a problem using Dartel=2C I'm not sure what I did wrong.</div><div><=
br></div><div>Here is what the images went through:</div><div>* new segment=
ation ->=3B c1*=2C c2*=2C rc1*=2C rc2* ... everything looks OK</div>
<div>* Dartel create template ->=3B Template*=2C u_rc1*  =3Beverythin=
g still looks OK</div><div>* Dartel normalize to MNI - this doesn't work...=
smwc1* images are empty (filled with zeros) or there is just a weird white=
blob that doesn't look like a brain at all</div>
<div><br></div><div>I tried changing some options=2C it didn't do any good.=
Just warping the images to the template (without the affine transformation=
to MNI) doesn't work any better.</div><div><br></div><div>Does anyone have=
an idea about what could be wrong here ?</div>
<div><br></div><div>Thanks in advance.</div> </body>
</html>=
--_57de950d-93fb-48d9-94cb-c5a619dd2b91_--
=========================================================================
Date: Mon, 23 May 2011 11:50:06 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Unit for design
Comments: To: adams adams <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
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Message-ID: <[log in to unmask]>
This refers to how the onset times and durations are encoded. If the
insets are in seconds, select seconds. If the onset time is in
scans/TR select scans.
On Monday, May 23, 2011, adams adams <[log in to unmask]> wrote:
>
>
>
>
>
>
>
> hello Everyone,
> Just a quick a question,
> during the first level analysis, for the unit design do we use Scan or Se=
cond, are they the same....
> Than you=A0 for your help
>
>
> =09
>
--=20
Best Regards, Donald McLaren
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital an=
d
Harvard Medical School
Office: (773) 406-2464
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
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reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
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action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773=
)
406-2464 or email.
=========================================================================
Date: Mon, 23 May 2011 10:26:12 -0700
Reply-To: Michael T Rubens <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michael T Rubens <[log in to unmask]>
Subject: Re: =?UTF-8?Q?=E5=9B=9E=E8=A6=86=EF=B9=95_?=[SPM] three questions
about SPM8
Comments: To: a489930026 <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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threshold needs to be>0. if your map is p values, then just do:
Y =3D 1-Y; %now p =3D 1-p, so higher values are more significant.
then set your p threshold as 1-threshold, so .95 =3D=3D .05
Determining whether you use the mask inclusively or exlusively can be done
when you apply it, so:
YY(find(Y)) =3D 0; % exclusive mask
YY(find(~Y)) =3D 0; %inclusive mask
Try running each line separately (or within a script) to see where exactly
the error is occurring.
Cheers,
Michael
On Mon, May 23, 2011 at 12:48 AM, a489930026 <[log in to unmask]>wrote=
:
> Dear Michael,
>
> Thank you for the advice. I did what you suggested but a result "Assignme=
nt
> between unlike types is not allowed." What could be the problem?
>
> Please see the script below:
>
> *********************************************************
> >> V=3D spm_vol('L:\2stlevel\wordVSblk\spmF_0001.img')
> Y =3D spm_read_vols(V);
>
> threshold =3D 0; %any value you choose.
>
> Y(find(Y<threshold)) =3D 0;
> Y(find(Y)) =3D 1;
>
> % Use mask
>
> VV =3D spm_vol('L:\2stlevel\radpos_sdXloca_sd\spmF_0001.img');
> YY =3D spm_vol(VV);
>
> YY(find(Y)) =3D 0; %apply mask
>
> VV.fname =3D 'masked_image.img';
> spm_write_vol(VV,YY);
>
> %% There ya go
>
> V =3D
>
> fname: 'L:\2stlevel\wordVSblk\spmF_0001.img'
> mat: [4x4 double]
> dim: [79 95 68]
> dt: [16 0]
> pinfo: [3x1 double]
> n: [1 1]
> descrip: 'SPM{F_[1.0,15.0]} - contrast 1: w-b'
> private: [1x1 nifti]
>
> ??? Assignment between unlike types is not allowed.
>
> *************************************************************************
>
> Besides, is the threshold a cutoff for the activation maps of the mask?
> Specially, does setting threshold =3D 0.05 mean that the activated voxels=
below p =3D0.05 are included. If not, how should I set a cutoff on the p
> value, or it does matter?
>
> Moreover, how can I determine the mask is inclusive (i.e., the voxles in
> the to-be-masked activation maps are within the volxels in the activation
> maps of the mask) or exclusive (i.e., the voxles in the to-be-masked
> activation maps are NOT within the volxels in the activation maps of the
> mask).
> Thank you very much!
>
> Sincerely,
> Yihui
>
>
>
>
>
> ------------------------------
> *=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A* Michael T Rubens <MikeRubens@gmail=
.com>
> *=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A* SUBSCRIBE SPM Yihui Hung <a4899300=
[log in to unmask]>
> *=E5=89=AF=E6=9C=AC=EF=BC=9A* [log in to unmask]
> *=E5=AF=84=E4=BB=B6=E6=97=A5=E6=9C=9F=EF=BC=9A* 2011/5/23 (=E4=B8=80) 10:=
19 AM
> *=E4=B8=BB=E6=97=A8=EF=BC=9A* Re: [SPM] three questions about SPM8
>
> when you say you tried to use the contrast as a mask, did you just use th=
e
> raw contrast or did you binarize it? If you did the former than it is
> clear why you had no inmask voxels since any non-zero voxels would all be
> seen as part of the mask. So, what you want to do is load the mask, apply=
a
> threshold and binarize it by setting anything below the threshold to 0,
> and anything above to 1 (though the latter may not be completely necesary=
).
> Then, you could just use that mask to mask out the resulting contrast map
> from the other analysis. Here is code to do it:
>
> %Make mask
>
> V =3D spm_vol('contrast_image_2turn_into_mask')
> Y =3D spm_read_vols(V);
>
> threshold =3D X; %any value you choose.
>
> Y(find(Y<threshold)) =3D 0;
> Y(find(Y)) =3D 1;
>
> % Use mask
>
> VV =3D spm_vol('contrast_image_2mask');
> YY =3D spm_vol(VV);
>
> YY(find(Y)) =3D 0; %apply mask
>
> VV.fname =3D 'masked_image.img';
> spm_write_vol(VV,YY);
>
> %% There ya go
>
> Cheers,
> Michael
>
> On Sun, May 22, 2011 at 9:58 AM, SUBSCRIBE SPM Yihui Hung <
> [log in to unmask]> wrote:
>
> Hello,
>
> I used SPM8 for my experiment. I manipulated three factors (e.g., factor
> A, B, C) in my experiment. The activation maps under factor A was used as=
a
> mask to constrain the effects of factor B and factor C. The problem is th=
at
> the factor A and factor B and factor C cannot be put in the same model at
> second level analysis. I tried to put the .img file resulting from factor
> A across participants in the =E2=80=9Cexplicit mask=E2=80=9D in the secon=
d level analysis.
> However, the estimation stopped by showing no inmask voxels. I searched
> through forum and did not find any useful solutions. Can someone help me
> out? Moreover, is the threshold masking related to the p value? If not, h=
ow
> should I set criteria for the activation map of the mask?
>
> I did notice that one person in the forum suggested that one can create a=
n
> activation maps in which the factor B is modeled with the mask of factor =
A
> in first level analysis. Then, submit the resulting .img file into second
> level analysis. My question is how to create and save the img file.
>
> Finally, I posted a question regarding how to export beta values over
> multiple coordinates a week ago. However, no one provide any answers. I
> wonder whether it is due that no one has the answer or due to that there
> already is an answer in the forum.
>
> Thank you for your patience and advice.
> Sincerely,
>
> Yihui
>
>
>
>
> --
> Research Associate
> Gazzaley Lab
> Department of Neurology
> University of California, San Francisco
>
>
>
--=20
Research Associate
Gazzaley Lab
Department of Neurology
University of California, San Francisco
--90e6ba53a2e05ba28104a3f4c667
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
threshold needs to be>0. if your map is p values, then just do:<br><br>Y=
=3D 1-Y; %now p =3D 1-p, so higher values are more significant.<br><br>the=
n set your p threshold as 1-threshold, so .95 =3D=3D .05<br><br>Determining=
whether you use the mask inclusively or exlusively can be done when you ap=
ply it, so: <br>
<br><span><span>YY</span></span>(find(Y)) =3D 0; % exclusive mask<br><br>YY=
(find(~Y)) =3D 0; %inclusive mask<br><br><br>Try running each line separate=
ly (or within a script) to see where exactly the error is occurring.<br><br=
>
<br>Cheers,<br>Michael<br><br><div class=3D"gmail_quote">On Mon, May 23, 20=
11 at 12:48 AM, a489930026 <span dir=3D"ltr"><<a href=3D"mailto:a4899300=
[log in to unmask]">[log in to unmask]</a>></span> wrote:<br><blockquo=
te class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1=
px solid rgb(204, 204, 204); padding-left: 1ex;">
<div><div style=3D"color: rgb(0, 0, 0); background-color: rgb(255, 255, 255=
); font-family: arial,helvetica,sans-serif; font-size: 12pt;"><div style=3D=
"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><span>Dear Mich=
ael,</span></div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><s=
pan><br></span></div><div style=3D"font-size: 12pt; font-family: arial,helv=
etica,sans-serif;">Thank you for the advice. I did what you suggested but a=
result "Assignment between unlike types is not allowed." What co=
uld be the problem?</div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><b=
r></div><div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-se=
rif;">Please see the script below:</div><div style=3D"font-size: 12pt; font=
-family: arial,helvetica,sans-serif;">
<br></div><div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-=
serif;">*********************************************************</div><div=
><div>>> V=3D <span><span>spm</span></span>_vol('L:\2<span><span>=
stlevel</span></span>\<span><span>wordVSblk</span></span>\<span><span>spmF<=
/span></span>_0001.<span><span>img</span></span>')</div>
<div>Y =3D <span><span>spm</span></span>_read_vols(V);</div><div><br></div>=
<div>threshold =3D 0; %any value you choose.</div><div><br></div><div>Y(fin=
d(Y<threshold)) =3D
0;</div><div>Y(find(Y)) =3D 1;</div><div><br></div><div>% Use mask</div><d=
iv><br></div><div><span><span>VV</span></span> =3D <span><span>spm</span></=
span>_vol('L:\2<span><span>stlevel</span></span>\<span><span>radpos</sp=
an></span>_<span><span>sdXloca</span></span>_<span><span>sd</span></span>\<=
span><span>spmF</span></span>_0001.<span><span>img</span></span>');</di=
v>
<div><span><span>YY</span></span> =3D <span><span>spm</span></span>_vol(<sp=
an><span>VV</span></span>);</div><div><br></div><div><span><span>YY</span><=
/span>(find(Y)) =3D 0; %apply mask</div><div><br></div><div><span><span>VV<=
/span></span>.<span><span>fname</span></span> =3D 'masked_image.<span><=
span>img</span></span>';</div>
<div><span><span>spm</span></span>_write_vol(<span><span>VV</span></span>,<=
span><span>YY</span></span>);</div><div><br></div><div>%% There ya go</div>=
<div><br></div><div>V =3D=C2=A0</div><div><br></div><div>=C2=A0 =C2=A0 =C2=
=A0 <span><span>fname</span></span>: 'L:\2<span><span>stlevel</span></s=
pan>\<span><span>wordVSblk</span></span>\<span><span>spmF</span></span>_000=
1.<span><span>img</span></span>'</div>
<div>=C2=A0 =C2=A0 =C2=A0 =C2=A0 mat: [4x4 double]</div><div>=C2=A0 =C2=A0 =
=C2=A0 =C2=A0 dim: [79 95 68]</div><div>=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0<=
span><span>dt</span></span>: [16 0]</div><div>=C2=A0 =C2=A0 =C2=A0 <span><s=
pan>pinfo</span></span>: [3x1 double]</div><div>=C2=A0 =C2=A0 =C2=A0 =C2=A0=
=C2=A0 n: [1 1]</div><div>
=C2=A0 =C2=A0 <span><span>descrip</span></span>: 'SPM{F_[1.0,15.0]} -
contrast 1: w-b'</div><div>=C2=A0 =C2=A0 private: [1x1 <span><span>nif=
ti</span></span>]</div><div><br></div><div>??? Assignment between unlike ty=
pes is not allowed.</div><div><br></div><div>******************************=
*******************************************</div>
<div><br></div><div>Besides, is the threshold a cutoff for the activation m=
aps of the mask? Specially, does setting threshold =3D 0.05 mean that the a=
ctivated <span><span>voxels</span></span> below p =3D0.05 are included. If =
not, how should I set a cutoff on the p value, or it does matter?=C2=A0</di=
v>
<div><br></div><div>Moreover, how can I determine the mask is inclusive (i.=
e., the <span><span>voxles</span></span> in the
to-be-masked activation maps are within the <span><span>volxels</span></sp=
an> in the activation maps of the mask) or exclusive=C2=A0(i.e., the <span>=
<span>voxles</span></span> in the to-be-masked activation maps are NOT with=
in the <span><span>volxels</span></span> in <span>the activation</span> map=
s of the mask).=C2=A0</div>
<div>Thank you very much!</div><div><br></div><div>Sincerely,</div><div><sp=
an><span>Yihui</span></span></div></div><div style=3D"font-size: 12pt; font=
-family: arial,helvetica,sans-serif;">=C2=A0</div><div style=3D"font-size: =
12pt; font-family: arial,helvetica,sans-serif;">
<br></div><div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-=
serif;"><br></div><div style=3D"font-size: 12pt; font-family: arial,helveti=
ca,sans-serif;"><br></div><div style=3D"font-size: 12pt; font-family: arial=
,helvetica,sans-serif;">
<br><blockquote style=3D"border-left: 2px solid rgb(16, 16, 255); margin-le=
ft: 5px; padding-left: 5px;"><div style=3D"font-size: 12pt; font-family: ar=
ial,helvetica,sans-serif;"><div style=3D"font-size: 12pt; font-family: '=
;times new roman','new york',times,serif;">
<font face=3D"Arial" size=3D"2"><hr size=3D"1"><b><span style=3D"font-weigh=
t: bold;">=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A</span></b> Michael T Rubens =
<<a href=3D"mailto:[log in to unmask]" target=3D"_blank">MikeRubens@gm=
ail.com</a>><br><b><span style=3D"font-weight: bold;">=E6=94=B6=E4=BB=B6=
=E8=80=85=EF=BC=9A</span></b> SUBSCRIBE <span><span>SPM</span></span> <span=
><span>Yihui</span></span> Hung <<a href=3D"mailto:[log in to unmask]
tw" target=3D"_blank">[log in to unmask]</a>><br>
<b><span style=3D"font-weight: bold;">=E5=89=AF=E6=9C=AC=EF=BC=9A</span></b=
> <a href=3D"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]
k</a><br><b><span style=3D"font-weight: bold;">=E5=AF=84=E4=BB=B6=E6=97=A5=
=E6=9C=9F=EF=BC=9A</span></b> 2011/5/23 (=E4=B8=80) 10:19 AM<br><b><span st=
yle=3D"font-weight: bold;">=E4=B8=BB=E6=97=A8=EF=BC=9A</span></b> Re: [<spa=
n><span>SPM</span></span>] three questions about <span><span>SPM</span></sp=
an>8<br>
</font><br><div>when you say you tried to use the contrast as a mask, did y=
ou just use the raw contrast or did you <span><span>binarize</span></span>
it? If you did the former than it is clear why you had no <span><span>inma=
sk</span></span> <span><span>voxels</span></span> since any non-zero <span>=
<span>voxels</span></span> would all be seen as part of the mask. So, what =
you want to do is load the mask, apply a threshold and <span><span>binarize=
</span></span> it by setting anything below the threshold to 0, and anythin=
g above to 1 (though the latter may not be completely <span><span>necesary<=
/span></span>). Then, you could just use that mask to mask out the
resulting contrast map from the other analysis. Here is code to do it:<br>
<br>%Make mask<br><br>V =3D <span><span>spm</span></span>_vol('contrast=
_image_2turn_into_mask')<br>Y =3D <span><span>spm</span></span>_read_vo=
ls(V);<br><br>threshold =3D X; %any value you choose.<br><br>Y(find(Y<th=
reshold)) =3D 0;<br>
Y(find(Y)) =3D 1;<br><br>% Use mask<br>
<br><span><span>VV</span></span> =3D <span><span>spm</span></span>_vol('=
;contrast_image_2mask');<br><span><span>YY</span></span> =3D <span><spa=
n>spm</span></span>_vol(<span><span>VV</span></span>);<br><br><span><span>Y=
Y</span></span>(find(Y)) =3D 0; %apply mask<br>
<br><span><span>VV</span></span>.<span><span>fname</span></span> =3D 'm=
asked_image.<span><span>img</span></span>';<br><span><span>spm</span></=
span>_write_vol(<span><span>VV</span></span>,<span><span>YY</span></span>);=
<br>
<br>%% There ya go<br><br>Cheers,<br>Michael<br>
<br><div>On Sun, May 22, 2011 at 9:58 AM, SUBSCRIBE <span><span>SPM</span><=
/span> <span><span>Yihui</span></span> Hung <span dir=3D"ltr"><<a rel=3D=
"nofollow" href=3D"mailto:[log in to unmask]" target=3D"_blank">a48993=
[log in to unmask]</a>></span> wrote:<br>
<blockquote style=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(=
204, 204, 204); padding-left: 1ex;">
Hello,<br>
<br>
I used <span><span>SPM</span></span>8 for my experiment. I manipulated thre=
e factors (e.g., factor A, B, C) in my experiment. The activation maps unde=
r factor A was used as a mask to constrain the effects of factor B and fact=
or C. The problem is that the factor A and factor B and factor C cannot be =
put in the same model at second level analysis. I tried to put the .<span><=
span>img</span></span> file resulting from factor A across participants in =
the =E2=80=9Cexplicit mask=E2=80=9D in the second level analysis. However, =
the estimation stopped by showing no <span><span>inmask</span></span> <span=
><span>voxels</span></span>. I searched through forum and did not find any =
useful solutions. Can someone help me out? Moreover, is the threshold maski=
ng related to the p value? If not, how should I set criteria for the activa=
tion map of the mask?<br>
<br>
I did notice that one person in the forum suggested that one can create an =
activation maps in which the factor B is <span><span>modeled</span></span> =
with the mask of factor A in first level analysis. Then, submit the resulti=
ng .<span><span>img</span></span> file into second level analysis. My quest=
ion is how to create and save the <span><span>img</span></span> file.<br>
<br>
Finally, I posted a question regarding how to export beta values over multi=
ple coordinates a week ago. However, no one provide any answers. I wonder w=
hether it is due that no one has the answer or due to that there already is=
an answer in the forum.<br>
<br>
Thank you for your patience and advice.<br>
Sincerely,<br>
<font color=3D"#888888"><br>
<span><span>Yihui</span></span><br>
<br>
</font></blockquote></div><br><br clear=3D"all"><br>-- <br>Research Associa=
te<br><span><span>Gazzaley</span></span> Lab<br>Department of Neurology<br>=
University of California, San Francisco<br>
</div><br><br></div></div></blockquote></div></div></div></blockquote></div=
><br><br clear=3D"all"><br>-- <br>Research Associate<br>Gazzaley Lab<br>Dep=
artment of Neurology<br>University of California, San Francisco<br>
--90e6ba53a2e05ba28104a3f4c667--
=========================================================================
Date: Mon, 23 May 2011 19:34:20 +0200
Reply-To: Artur Marchewka <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Artur Marchewka <[log in to unmask]>
Subject: MRI Brain Imaging Core Facility leader - The Nencki Institute of
Experimental Biology, Polish Academy of Sciences
Content-Type: multipart/alternative; boundary=Apple-Mail-14--700137924
Mime-Version: 1.0 (Apple Message framework v1084)
Message-ID: <[log in to unmask]>
--Apple-Mail-14--700137924
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain;
charset=windows-1252
The Nencki Institute of Experimental Biology, Polish Academy of =
Sciences, is currently seeking a highly motivated experienced individual =
to lead its newly forming MRI Brain Imaging Core Facility, within the =
newly constructed Neurobiology Centre.
This position is created using funds from the FP7 Capacities contract =
number 264173 co-financed by the European Commission: Bio-imaging in =
research, innovation and education (BIO-IMAGINE).
Offer:
A fixed-term position for the initial term of 2 years with a maximum =
gross salary of 4200 euro / month (depending on qualifications and =
experience). This position is a subject to extension to 5 years. The =
position can be converted into a permanent position.
Possibility to hire additional technical support staff and/or =
post-doctoral associates to be discussed during the negotiations =
process.
Active participation in shaping up and launching of the newly =
constructed Brain imaging core facility (approx. 150 m2) with a purchase =
of new 3T MRI valued at approx 2 mln euro to be purchased and installed =
at the end of 2011 (see additional information).
Active engagement in Euro-BioImaging pan-European research =
infrastructure project (FP7) and the National imaging research centre in =
biological and biomedical sciences (see additional information).
Expectations:
It is expected that this person should have a strong research and =
technology background in the field of neuro-imaging using functional =
magnetic resonance and related technologies. A successful candidate will =
develop new research approaches and collaborations in neuro-imaging of =
the brain and the nervous system and train the institute researchers on =
using the equipment and setting up experiments. Successful candidate =
should facilitate research experiments for scientists at the Institute =
and in partnering institutions of the National imaging research centre =
in biological and biomedical sciences. S/he will also be expected to =
develop a vision of facility development and secure research, clinical =
and private sector external users. It is also expected that the core =
facility leader will create networking among national and international =
brain imaging facilities. It is also expected that the leader will seek =
external financing and actively pursue collaboration with clinical =
facilities and diagnostic centres. New MRI scanner is expected to be =
installed towards the end of 2011. It would be desirable for the =
successful candidate to assist in this process.
Application process:
The application should contain the following documents/information:
=95 A cover letter with a vision of functioning and strategy for =
development of the forming core facility and its scientific/technical =
team
=95 Candidate=92s CV with contact information to at least 3 =
references=95 Copy of Candidate=92s PhD diploma (or equivalent) =95 =
Candidate=92s contact information, including e-mail address and phone =
number =95 Candidate may include additional information or copies =
of
documents/certificates in support of the application. Application =
documents in English (pdf format) may be uploaded at
https://recruitment.nencki.gov.pl?call=3Dfbicf
Application deadline: July 15, 2011 Selection criteria: The key =
evaluation criteria will be the Candidate=92s:
=95 leadership, management and communication skills and experience =95=
experience (5 years or more) in using and developing advanced =
magnetic
resonance imaging methods, image processing and data analysis =95 =
experience in working at one or more of the recognized fMRI imaging =
facilities
at leading research institutions =95 technical knowledge in the area =
of fMRI functioning, experiment design, data
management and image post-processing techniques =95 publications or =
other verifiable scientific achievements in the field
Short-listed candidates will be invited for personal interviews. =
Interviews will take place at the Nencki Institute around mid- =
September.
Top candidate will be presented an offer by the end of September and =
will be expected to finally accept or decline the offer by mid-October.
The employment start target date: January 1, 2012=
--Apple-Mail-14--700137924
Content-Transfer-Encoding: quoted-printable
Content-Type: text/html;
charset=windows-1252
<html><head></head><body style=3D"word-wrap: break-word; =
-webkit-nbsp-mode: space; -webkit-line-break: after-white-space; "><div =
style=3D"margin-top: 0px; margin-right: 0px; margin-bottom: 0px; =
margin-left: 0px; font: normal normal normal 12px/normal Arial; "><b>The =
Nencki Institute of Experimental Biology, Polish Academy of Sciences, is =
currently seeking a highly motivated experienced individual to lead its =
newly forming MRI Brain Imaging Core Facility, within the newly =
constructed Neurobiology Centre.</b></div><div style=3D"margin-top: 0px; =
margin-right: 0px; margin-bottom: 0px; margin-left: 0px; font: normal =
normal normal 12px/normal Arial; ">This position is created using funds =
from the FP7 Capacities contract number 264173 co-financed by the =
European Commission: Bio-imaging in research, innovation and education =
(BIO-IMAGINE).</div><div style=3D"margin-top: 0px; margin-right: 0px; =
margin-bottom: 0px; margin-left: 0px; font: normal normal normal =
12px/normal Arial; "><b>Offer:</b></div><div style=3D"margin-top: 0px; =
margin-right: 0px; margin-bottom: 0px; margin-left: 0px; font: normal =
normal normal 12px/normal Arial; ">A fixed-term position for the initial =
term of 2 years with a maximum gross salary of 4200 euro / month =
(depending on qualifications and experience). This position is a subject =
to extension to 5 years. The position can be converted into a permanent =
position.</div><div style=3D"margin-top: 0px; margin-right: 0px; =
margin-bottom: 0px; margin-left: 0px; font: normal normal normal =
12px/normal Arial; ">Possibility to hire additional technical support =
staff and/or post-doctoral associates to be discussed during the =
negotiations process.</div><div style=3D"margin-top: 0px; margin-right: =
0px; margin-bottom: 0px; margin-left: 0px; font: normal normal normal =
12px/normal Arial; ">Active participation in shaping up and launching of =
the newly constructed Brain imaging core facility (approx. 150 m<span =
style=3D"font: 8.0px Arial">2</span>) with a purchase of new 3T MRI =
valued at approx 2 mln euro to be purchased and installed at the end of =
2011 (see additional information).</div><div style=3D"margin-top: 0px; =
margin-right: 0px; margin-bottom: 0px; margin-left: 0px; font: normal =
normal normal 12px/normal Arial; ">Active engagement in Euro-BioImaging =
pan-European research infrastructure project (FP7) and the National =
imaging research centre in biological and biomedical sciences (see =
additional information).</div><div style=3D"margin-top: 0px; =
margin-right: 0px; margin-bottom: 0px; margin-left: 0px; font: normal =
normal normal 12px/normal Arial; "><b>Expectations:</b></div><div =
style=3D"margin-top: 0px; margin-right: 0px; margin-bottom: 0px; =
margin-left: 0px; font: normal normal normal 12px/normal Arial; ">It is =
expected that this person should have a strong research and technology =
background in the field of neuro-imaging using functional magnetic =
resonance and related technologies. A successful candidate will develop =
new research approaches and collaborations in neuro-imaging of the brain =
and the nervous system and train the institute researchers on using the =
equipment and setting up experiments. Successful candidate should =
facilitate research experiments for scientists at the Institute and in =
partnering institutions of the National imaging research centre in =
biological and biomedical sciences. S/he will also be expected to =
develop a vision of facility development and secure research, clinical =
and private sector external users. It is also expected that the core =
facility leader will create networking among national and international =
brain imaging facilities. It is also expected that the leader will seek =
external financing and actively pursue collaboration with clinical =
facilities and diagnostic centres. New MRI scanner is expected to be =
installed towards the end of 2011. It would be desirable for the =
successful candidate to assist in this process.</div><div =
style=3D"margin-top: 0px; margin-right: 0px; margin-bottom: 0px; =
margin-left: 0px; font: normal normal normal 12px/normal Arial; =
"><b>Application process:</b></div><div style=3D"margin-top: 0px; =
margin-right: 0px; margin-bottom: 0px; margin-left: 0px; font: normal =
normal normal 12px/normal Arial; ">The application should contain the =
following documents/information:</div><div style=3D"margin-top: 0px; =
margin-right: 0px; margin-bottom: 0px; margin-left: 0px; font: normal =
normal normal 12px/normal Arial; "><span style=3D"font: 10.0px =
Helvetica">=95<span class=3D"Apple-tab-span" style=3D"white-space:pre"> =
</span></span>A cover letter with a vision of functioning and strategy =
for development of the forming core facility and its =
scientific/technical team</div><div style=3D"margin-top: 0px; =
margin-right: 0px; margin-bottom: 0px; margin-left: 0px; font: normal =
normal normal 12px/normal Arial; "><span style=3D"font: 10.0px =
Helvetica">=95<span class=3D"Apple-tab-span" style=3D"white-space:pre"> =
</span></span>Candidate=92s CV with contact information to at least 3 =
references<span style=3D"font: 10.0px Helvetica">=95<span =
class=3D"Apple-tab-span" style=3D"white-space:pre"> =
</span></span>Copy of Candidate=92s PhD diploma (or equivalent) <span =
style=3D"font: 10.0px Helvetica">=95<span class=3D"Apple-tab-span" =
style=3D"white-space:pre"> </span></span>Candidate=92s contact =
information, including e-mail address and phone number <span =
style=3D"font: 10.0px Helvetica">=95<span class=3D"Apple-tab-span" =
style=3D"white-space:pre"> </span></span>Candidate may include =
additional information or copies of</div><div style=3D"margin-top: 0px; =
margin-right: 0px; margin-bottom: 0px; margin-left: 0px; font: normal =
normal normal 12px/normal Arial; ">documents/certificates in support of =
the application. Application documents in English (pdf format) may be =
uploaded at</div><div style=3D"margin-top: 0px; margin-right: 0px; =
margin-bottom: 0px; margin-left: 0px; font: normal normal normal =
12px/normal Arial; color: rgb(62, 0, 255); "><a =
href=3D"https://recruitment.nencki.gov.pl?call=3Dfbicf">https://recruitmen=
t.nencki.gov.pl?call=3Dfbicf</a></div><div style=3D"margin-top: 0px; =
margin-right: 0px; margin-bottom: 0px; margin-left: 0px; font: normal =
normal normal 12px/normal Arial; "><b>Application deadline: </b><span =
style=3D"color: #a60000"><b>July 15, 2011 </b></span><b>Selection =
criteria: </b>The key evaluation criteria will be the =
Candidate=92s:</div><div style=3D"margin-top: 0px; margin-right: 0px; =
margin-bottom: 0px; margin-left: 0px; font: normal normal normal =
12px/normal Arial; "><span style=3D"font: 10.0px Helvetica">=95<span =
class=3D"Apple-tab-span" style=3D"white-space:pre"> =
</span></span>leadership, management and communication skills and =
experience <span style=3D"font: 10.0px Helvetica">=95<span =
class=3D"Apple-tab-span" style=3D"white-space:pre"> =
</span></span>experience (5 years or more) in using and developing =
advanced magnetic</div><div style=3D"margin-top: 0px; margin-right: 0px; =
margin-bottom: 0px; margin-left: 0px; font: normal normal normal =
12px/normal Arial; ">resonance imaging methods, image processing and =
data analysis <span style=3D"font: 10.0px Helvetica">=95<span =
class=3D"Apple-tab-span" style=3D"white-space:pre"> =
</span></span>experience in working at one or more of the recognized =
fMRI imaging facilities</div><div style=3D"margin-top: 0px; =
margin-right: 0px; margin-bottom: 0px; margin-left: 0px; font: normal =
normal normal 12px/normal Arial; ">at leading research institutions =
<span style=3D"font: 10.0px Helvetica">=95<span class=3D"Apple-tab-span" =
style=3D"white-space:pre"> </span></span>technical knowledge in the =
area of fMRI functioning, experiment design, data</div><div =
style=3D"margin-top: 0px; margin-right: 0px; margin-bottom: 0px; =
margin-left: 0px; font: normal normal normal 12px/normal Arial; =
">management and image post-processing techniques <span style=3D"font: =
10.0px Helvetica">=95<span class=3D"Apple-tab-span" =
style=3D"white-space:pre"> </span></span>publications or other =
verifiable scientific achievements in the field</div><div =
style=3D"margin-top: 0px; margin-right: 0px; margin-bottom: 0px; =
margin-left: 0px; font: normal normal normal 12px/normal Arial; =
">Short-listed candidates will be invited for personal interviews. =
Interviews will take place at the Nencki Institute <b>around mid- =
September.</b></div><div style=3D"margin-top: 0px; margin-right: 0px; =
margin-bottom: 0px; margin-left: 0px; font: normal normal normal =
12px/normal Arial; ">Top candidate will be presented an offer <b>by the =
end of September </b>and will be expected to finally accept or decline =
the offer by <b>mid-October.</b></div><div style=3D"margin-top: 0px; =
margin-right: 0px; margin-bottom: 0px; margin-left: 0px; font: normal =
normal normal 12px/normal Arial; "><b>The employment start target date: =
</b><span style=3D"color: #a60000"><b>January 1, =
2012</b></span></div></body></html>=
--Apple-Mail-14--700137924--
=========================================================================
Date: Mon, 23 May 2011 19:44:43 +0100
Reply-To: Carlos Faraco <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Carlos Faraco <[log in to unmask]>
Subject: Re: SPM8 Reorients, but gives errors
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Does anyone have any idea about this?
Thanks.
=========================================================================
Date: Mon, 23 May 2011 12:16:58 -0700
Reply-To: Michael T Rubens <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michael T Rubens <[log in to unmask]>
Subject: Re:
=?UTF-8?Q?=E5=9B=9E=E8=A6=86=EF=B9=95_=E5=9B=9E=E8=A6=86=EF=B9=95_?=[SPM] three questions about
SPM8
Comments: To: a489930026 <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf3040ea427d213e04a3f652b9
Message-ID: <[log in to unmask]>
--20cf3040ea427d213e04a3f652b9
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
I see now, I made a mistake in the original code I sent. This line:
YY =3D spm_vol(VV);
should actually be:
YY =3D spm_read_vols(VV);
%%
Cheers,
Michael
On Mon, May 23, 2011 at 11:03 AM, a489930026 <[log in to unmask]>wrote=
:
> Dear Michael,
>
> Every step went smoothly until the step "YY(find(Y)) =3D 0" and then the =
it
> showed "Assignment between unlike types is not allowed."
>
> Yihui
>
> ------------------------------
> *=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A* Michael T Rubens <MikeRubens@gmail=
.com>
> *=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A* a489930026 <[log in to unmask]
w>; spm <[log in to unmask]>
> *=E5=AF=84=E4=BB=B6=E6=97=A5=E6=9C=9F=EF=BC=9A* 2011/5/24 (=E4=BA=8C) 1:2=
6 AM
> *=E4=B8=BB=E6=97=A8=EF=BC=9A* Re: =E5=9B=9E=E8=A6=86=EF=B9=95 [SPM] three=
questions about SPM8
>
> threshold needs to be>0. if your map is p values, then just do:
>
> Y =3D 1-Y; %now p =3D 1-p, so higher values are more significant.
>
> then set your p threshold as 1-threshold, so .95 =3D=3D .05
>
> Determining whether you use the mask inclusively or exlusively can be don=
e
> when you apply it, so:
>
> YY(find(Y)) =3D 0; % exclusive mask
>
> YY(find(~Y)) =3D 0; %inclusive mask
>
>
> Try running each line separately (or within a script) to see where exactl=
y
> the error is occurring.
>
>
> Cheers,
> Michael
>
> On Mon, May 23, 2011 at 12:48 AM, a489930026 <[log in to unmask]>wro=
te:
>
> Dear Michael,
>
> Thank you for the advice. I did what you suggested but a result "Assignme=
nt
> between unlike types is not allowed." What could be the problem?
>
> Please see the script below:
>
> *********************************************************
> >> V=3D spm_vol('L:\2stlevel\wordVSblk\spmF_0001.img')
> Y =3D spm_read_vols(V);
>
> threshold =3D 0; %any value you choose.
>
> Y(find(Y<threshold)) =3D 0;
> Y(find(Y)) =3D 1;
>
> % Use mask
>
> VV =3D spm_vol('L:\2stlevel\radpos_sdXloca_sd\spmF_0001.img');
> YY =3D spm_vol(VV);
>
> YY(find(Y)) =3D 0; %apply mask
>
> VV.fname =3D 'masked_image.img';
> spm_write_vol(VV,YY);
>
> %% There ya go
>
> V =3D
>
> fname: 'L:\2stlevel\wordVSblk\spmF_0001.img'
> mat: [4x4 double]
> dim: [79 95 68]
> dt: [16 0]
> pinfo: [3x1 double]
> n: [1 1]
> descrip: 'SPM{F_[1.0,15.0]} - contrast 1: w-b'
> private: [1x1 nifti]
>
> ??? Assignment between unlike types is not allowed.
>
> *************************************************************************
>
> Besides, is the threshold a cutoff for the activation maps of the mask?
> Specially, does setting threshold =3D 0.05 mean that the activated voxels=
below p =3D0.05 are included. If not, how should I set a cutoff on the p
> value, or it does matter?
>
> Moreover, how can I determine the mask is inclusive (i.e., the voxles in
> the to-be-masked activation maps are within the volxels in the activation
> maps of the mask) or exclusive (i.e., the voxles in the to-be-masked
> activation maps are NOT within the volxels in the activation maps of the
> mask).
> Thank you very much!
>
> Sincerely,
> Yihui
>
>
>
>
>
> ------------------------------
> *=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A* Michael T Rubens <MikeRubens@gmail=
.com>
> *=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A* SUBSCRIBE SPM Yihui Hung <a4899300=
[log in to unmask]>
> *=E5=89=AF=E6=9C=AC=EF=BC=9A* [log in to unmask]
> *=E5=AF=84=E4=BB=B6=E6=97=A5=E6=9C=9F=EF=BC=9A* 2011/5/23 (=E4=B8=80) 10:=
19 AM
> *=E4=B8=BB=E6=97=A8=EF=BC=9A* Re: [SPM] three questions about SPM8
>
> when you say you tried to use the contrast as a mask, did you just use th=
e
> raw contrast or did you binarize it? If you did the former than it is
> clear why you had no inmask voxels since any non-zero voxels would all be
> seen as part of the mask. So, what you want to do is load the mask, apply=
a
> threshold and binarize it by setting anything below the threshold to 0,
> and anything above to 1 (though the latter may not be completely necesary=
).
> Then, you could just use that mask to mask out the resulting contrast map
> from the other analysis. Here is code to do it:
>
> %Make mask
>
> V =3D spm_vol('contrast_image_2turn_into_mask')
> Y =3D spm_read_vols(V);
>
> threshold =3D X; %any value you choose.
>
> Y(find(Y<threshold)) =3D 0;
> Y(find(Y)) =3D 1;
>
> % Use mask
>
> VV =3D spm_vol('contrast_image_2mask');
> YY =3D spm_vol(VV);
>
> YY(find(Y)) =3D 0; %apply mask
>
> VV.fname =3D 'masked_image.img';
> spm_write_vol(VV,YY);
>
> %% There ya go
>
> Cheers,
> Michael
>
> On Sun, May 22, 2011 at 9:58 AM, SUBSCRIBE SPM Yihui Hung <
> [log in to unmask]> wrote:
>
> Hello,
>
> I used SPM8 for my experiment. I manipulated three factors (e.g., factor
> A, B, C) in my experiment. The activation maps under factor A was used as=
a
> mask to constrain the effects of factor B and factor C. The problem is th=
at
> the factor A and factor B and factor C cannot be put in the same model at
> second level analysis. I tried to put the .img file resulting from factor
> A across participants in the =E2=80=9Cexplicit mask=E2=80=9D in the secon=
d level analysis.
> However, the estimation stopped by showing no inmask voxels. I searched
> through forum and did not find any useful solutions. Can someone help me
> out? Moreover, is the threshold masking related to the p value? If not, h=
ow
> should I set criteria for the activation map of the mask?
>
> I did notice that one person in the forum suggested that one can create a=
n
> activation maps in which the factor B is modeled with the mask of factor =
A
> in first level analysis. Then, submit the resulting .img file into second
> level analysis. My question is how to create and save the img file.
>
> Finally, I posted a question regarding how to export beta values over
> multiple coordinates a week ago. However, no one provide any answers. I
> wonder whether it is due that no one has the answer or due to that there
> already is an answer in the forum.
>
> Thank you for your patience and advice.
> Sincerely,
>
> Yihui
>
>
>
>
> --
> Research Associate
> Gazzaley Lab
> Department of Neurology
> University of California, San Francisco
>
>
>
>
>
> --
> Research Associate
> Gazzaley Lab
> Department of Neurology
> University of California, San Francisco
>
>
>
--=20
Research Associate
Gazzaley Lab
Department of Neurology
University of California, San Francisco
--20cf3040ea427d213e04a3f652b9
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
I see now, I made a mistake in the original code I sent. This line: <br><br=
><span><span>YY</span></span> =3D <span><span>spm</span></span>_vol(<span><=
span>VV</span></span>);<br><br>should actually be:<br><br><span><span>YY</s=
pan></span> =3D <span><span>spm</span></span>_read_vols(<span><span>VV</spa=
n></span>);<br>
<br><br>%%<br><br>Cheers,<br>Michael<br><div class=3D"gmail_quote">On Mon, =
May 23, 2011 at 11:03 AM, a489930026 <span dir=3D"ltr"><<a href=3D"mailt=
o:[log in to unmask]">[log in to unmask]</a>></span> wrote:<br=
>
<blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; borde=
r-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
<div><div style=3D"color: rgb(0, 0, 0); background-color: rgb(255, 255, 255=
); font-family: arial,helvetica,sans-serif; font-size: 12pt;"><div><span><d=
iv>Dear Michael,</div><div><br></div><div>Every step went smoothly until th=
e step "YY(find(Y)) =3D 0" and then the it showed "Assignmen=
t between unlike types is not allowed."</div>
<div><br></div><div>Yihui</div></span></div><div><br><blockquote style=3D"b=
order-left: 2px solid rgb(16, 16, 255); margin-left: 5px; padding-left: 5px=
;"><div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"=
>
<div style=3D"font-size: 12pt; font-family: 'times new roman','=
new york',times,serif;"><font face=3D"Arial" size=3D"2"><hr size=3D"1">=
<b><span style=3D"font-weight: bold;">=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A<=
/span></b> Michael T Rubens <<a href=3D"mailto:[log in to unmask]" tar=
get=3D"_blank">[log in to unmask]</a>><br>
<b><span style=3D"font-weight: bold;">=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A<=
/span></b> a489930026 <<a href=3D"mailto:[log in to unmask]" target=
=3D"_blank">[log in to unmask]</a>>; spm <<a href=3D"mailto:SPM@=
jiscmail.ac.uk" target=3D"_blank">[log in to unmask]</a>><br>
<b><span style=3D"font-weight: bold;">=E5=AF=84=E4=BB=B6=E6=97=A5=E6=9C=9F=
=EF=BC=9A</span></b> 2011/5/24 (=E4=BA=8C) 1:26 AM<br><b><span style=3D"fon=
t-weight: bold;">=E4=B8=BB=E6=97=A8=EF=BC=9A</span></b> Re: =E5=9B=9E=E8=A6=
=86=EF=B9=95 [SPM] three questions about SPM8<br></font><br><div>threshold =
needs to be>0. if your map is p values, then just do:<br>
<br>Y =3D 1-Y; %now p =3D 1-p, so higher values are more significant.<br><b=
r>then set your p threshold as 1-threshold, so .95 =3D=3D .05<br><br>Determ=
ining whether you use the mask inclusively or exlusively can be done when y=
ou apply it, so: <br>
<br><span><span>YY</span></span>(find(Y)) =3D 0; % exclusive mask<br><br>YY=
(find(~Y)) =3D 0; %inclusive mask<br><br><br>Try running each line separate=
ly (or within a script) to see where exactly the error is occurring.<br><br=
>
<br>Cheers,<br>Michael<br><br><div>On Mon, May 23, 2011 at 12:48 AM, a48993=
0026 <span dir=3D"ltr"><<a rel=3D"nofollow" href=3D"mailto:a489930026@ya=
hoo.com.tw" target=3D"_blank">[log in to unmask]</a>></span> wrote:=
<br>
<blockquote style=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(=
204, 204, 204); padding-left: 1ex;">
<div><div style=3D"color: rgb(0, 0, 0); background-color: rgb(255, 255, 255=
); font-size: 12pt; font-family: arial,helvetica,sans-serif;"><div style=3D=
"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><span>Dear Mich=
ael,</span></div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><s=
pan><br></span></div><div style=3D"font-size: 12pt; font-family: arial,helv=
etica,sans-serif;">Thank you for the advice. I did what you suggested but a=
result "Assignment between unlike types is not allowed." What co=
uld be the problem?</div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><b=
r></div><div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-se=
rif;">Please see the script below:</div><div style=3D"font-size: 12pt; font=
-family: arial,helvetica,sans-serif;">
<br></div><div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-=
serif;">*********************************************************</div><div=
><div>>> V=3D <span><span>spm</span></span>_vol('L:\2<span><span>=
stlevel</span></span>\<span><span>wordVSblk</span></span>\<span><span>spmF<=
/span></span>_0001.<span><span>img</span></span>')</div>
<div>Y =3D <span><span>spm</span></span>_read_vols(V);</div><div><br></div>=
<div>threshold =3D 0; %any value you choose.</div><div><br></div><div>Y(fin=
d(Y<threshold)) =3D
0;</div><div>Y(find(Y)) =3D 1;</div><div><br></div><div>% Use mask</div><d=
iv><br></div><div><span><span>VV</span></span> =3D <span><span>spm</span></=
span>_vol('L:\2<span><span>stlevel</span></span>\<span><span>radpos</sp=
an></span>_<span><span>sdXloca</span></span>_<span><span>sd</span></span>\<=
span><span>spmF</span></span>_0001.<span><span>img</span></span>');</di=
v>
<div><span><span>YY</span></span> =3D <span><span>spm</span></span>_vol(<sp=
an><span>VV</span></span>);</div><div><br></div><div><span><span>YY</span><=
/span>(find(Y)) =3D 0; %apply mask</div><div><br></div><div><span><span>VV<=
/span></span>.<span><span>fname</span></span> =3D 'masked_image.<span><=
span>img</span></span>';</div>
<div><span><span>spm</span></span>_write_vol(<span><span>VV</span></span>,<=
span><span>YY</span></span>);</div><div><br></div><div>%% There ya go</div>=
<div><br></div><div>V =3D=C2=A0</div><div><br></div><div>=C2=A0 =C2=A0 =C2=
=A0 <span><span>fname</span></span>: 'L:\2<span><span>stlevel</span></s=
pan>\<span><span>wordVSblk</span></span>\<span><span>spmF</span></span>_000=
1.<span><span>img</span></span>'</div>
<div>=C2=A0 =C2=A0 =C2=A0 =C2=A0 mat: [4x4 double]</div><div>=C2=A0 =C2=A0 =
=C2=A0 =C2=A0 dim: [79 95 68]</div><div>=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0<=
span><span>dt</span></span>: [16 0]</div><div>=C2=A0 =C2=A0 =C2=A0 <span><s=
pan>pinfo</span></span>: [3x1 double]</div><div>=C2=A0 =C2=A0 =C2=A0 =C2=A0=
=C2=A0 n: [1 1]</div><div>
=C2=A0 =C2=A0 <span><span>descrip</span></span>: 'SPM{F_[1.0,15.0]} -
contrast 1: w-b'</div><div>=C2=A0 =C2=A0 private: [1x1 <span><span>nif=
ti</span></span>]</div><div><br></div><div>??? Assignment between unlike ty=
pes is not allowed.</div><div><br></div><div>******************************=
*******************************************</div>
<div><br></div><div>Besides, is the threshold a cutoff for the activation m=
aps of the mask? Specially, does setting threshold =3D 0.05 mean that the a=
ctivated <span><span>voxels</span></span> below p =3D0.05 are included. If =
not, how should I set a cutoff on the p value, or it does matter?=C2=A0</di=
v>
<div><br></div><div>Moreover, how can I determine the mask is inclusive (i.=
e., the <span><span>voxles</span></span> in the
to-be-masked activation maps are within the <span><span>volxels</span></sp=
an> in the activation maps of the mask) or exclusive=C2=A0(i.e., the <span>=
<span>voxles</span></span> in the to-be-masked activation maps are NOT with=
in the <span><span>volxels</span></span> in <span>the activation</span> map=
s of the mask).=C2=A0</div>
<div>Thank you very much!</div><div><br></div><div>Sincerely,</div><div><sp=
an><span>Yihui</span></span></div></div><div style=3D"font-size: 12pt; font=
-family: arial,helvetica,sans-serif;">=C2=A0</div><div style=3D"font-size: =
12pt; font-family: arial,helvetica,sans-serif;">
<br></div><div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-=
serif;"><br></div><div style=3D"font-size: 12pt; font-family: arial,helveti=
ca,sans-serif;"><br></div><div style=3D"font-size: 12pt; font-family: arial=
,helvetica,sans-serif;">
<br><blockquote style=3D"border-left: 2px solid rgb(16, 16, 255); margin-le=
ft: 5px; padding-left: 5px;"><div style=3D"font-size: 12pt; font-family: ar=
ial,helvetica,sans-serif;"><div style=3D"font-size: 12pt;">
<font face=3D"Arial" size=3D"2"><hr size=3D"1"><b><span style=3D"font-weigh=
t: bold;">=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A</span></b> Michael T Rubens =
<<a rel=3D"nofollow" href=3D"mailto:[log in to unmask]" target=3D"_bla=
nk">[log in to unmask]</a>><br><b><span style=3D"font-weight: bold;">=
=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A</span></b> SUBSCRIBE <span><span>SPM</=
span></span> <span><span>Yihui</span></span> Hung <<a rel=3D"nofollow" h=
ref=3D"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]
om.tw</a>><br>
<b><span style=3D"font-weight: bold;">=E5=89=AF=E6=9C=AC=EF=BC=9A</span></b=
> <a rel=3D"nofollow" href=3D"mailto:[log in to unmask]" target=3D"_blank">=
[log in to unmask]</a><br><b><span style=3D"font-weight: bold;">=E5=AF=84=
=E4=BB=B6=E6=97=A5=E6=9C=9F=EF=BC=9A</span></b> 2011/5/23 (=E4=B8=80) 10:19=
AM<br>
<b><span style=3D"font-weight: bold;">=E4=B8=BB=E6=97=A8=EF=BC=9A</span></b=
> Re: [<span><span>SPM</span></span>] three questions about <span><span>SPM=
</span></span>8<br>
</font><br><div>when you say you tried to use the contrast as a mask, did y=
ou just use the raw contrast or did you <span><span>binarize</span></span>
it? If you did the former than it is clear why you had no <span><span>inma=
sk</span></span> <span><span>voxels</span></span> since any non-zero <span>=
<span>voxels</span></span> would all be seen as part of the mask. So, what =
you want to do is load the mask, apply a threshold and <span><span>binarize=
</span></span> it by setting anything below the threshold to 0, and anythin=
g above to 1 (though the latter may not be completely <span><span>necesary<=
/span></span>). Then, you could just use that mask to mask out the
resulting contrast map from the other analysis. Here is code to do it:<br>
<br>%Make mask<br><br>V =3D <span><span>spm</span></span>_vol('contrast=
_image_2turn_into_mask')<br>Y =3D <span><span>spm</span></span>_read_vo=
ls(V);<br><br>threshold =3D X; %any value you choose.<br><br>Y(find(Y<th=
reshold)) =3D 0;<br>
Y(find(Y)) =3D 1;<br><br>% Use mask<br>
<br><span><span>VV</span></span> =3D <span><span>spm</span></span>_vol('=
;contrast_image_2mask');<br><span><span>YY</span></span> =3D <span><spa=
n>spm</span></span>_vol(<span><span>VV</span></span>);<br><br><span><span>Y=
Y</span></span>(find(Y)) =3D 0; %apply mask<br>
<br><span><span>VV</span></span>.<span><span>fname</span></span> =3D 'm=
asked_image.<span><span>img</span></span>';<br><span><span>spm</span></=
span>_write_vol(<span><span>VV</span></span>,<span><span>YY</span></span>);=
<br>
<br>%% There ya go<br><br>Cheers,<br>Michael<br>
<br><div>On Sun, May 22, 2011 at 9:58 AM, SUBSCRIBE <span><span>SPM</span><=
/span> <span><span>Yihui</span></span> Hung <span dir=3D"ltr"><<a rel=3D=
"nofollow" href=3D"mailto:[log in to unmask]" target=3D"_blank">a48993=
[log in to unmask]</a>></span> wrote:<br>
<blockquote style=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(=
204, 204, 204); padding-left: 1ex;">
Hello,<br>
<br>
I used <span><span>SPM</span></span>8 for my experiment. I manipulated thre=
e factors (e.g., factor A, B, C) in my experiment. The activation maps unde=
r factor A was used as a mask to constrain the effects of factor B and fact=
or C. The problem is that the factor A and factor B and factor C cannot be =
put in the same model at second level analysis. I tried to put the .<span><=
span>img</span></span> file resulting from factor A across participants in =
the =E2=80=9Cexplicit mask=E2=80=9D in the second level analysis. However, =
the estimation stopped by showing no <span><span>inmask</span></span> <span=
><span>voxels</span></span>. I searched through forum and did not find any =
useful solutions. Can someone help me out? Moreover, is the threshold maski=
ng related to the p value? If not, how should I set criteria for the activa=
tion map of the mask?<br>
<br>
I did notice that one person in the forum suggested that one can create an =
activation maps in which the factor B is <span><span>modeled</span></span> =
with the mask of factor A in first level analysis. Then, submit the resulti=
ng .<span><span>img</span></span> file into second level analysis. My quest=
ion is how to create and save the <span><span>img</span></span> file.<br>
<br>
Finally, I posted a question regarding how to export beta values over multi=
ple coordinates a week ago. However, no one provide any answers. I wonder w=
hether it is due that no one has the answer or due to that there already is=
an answer in the forum.<br>
<br>
Thank you for your patience and advice.<br>
Sincerely,<br>
<font color=3D"#888888"><br>
<span><span>Yihui</span></span><br>
<br>
</font></blockquote></div><br><br clear=3D"all"><br>-- <br>Research Associa=
te<br><span><span>Gazzaley</span></span> Lab<br>Department of Neurology<br>=
University of California, San Francisco<br>
</div><br><br></div></div></blockquote></div></div></div></blockquote></div=
><br><br clear=3D"all"><br>-- <br>Research Associate<br>Gazzaley Lab<br>Dep=
artment of Neurology<br>University of California, San Francisco<br>
</div><br><br></div></div></blockquote></div></div></div></blockquote></div=
><br><br clear=3D"all"><br>-- <br>Research Associate<br>Gazzaley Lab<br>Dep=
artment of Neurology<br>University of California, San Francisco<br>
--20cf3040ea427d213e04a3f652b9--
=========================================================================
Date: Mon, 23 May 2011 15:20:50 -0600
Reply-To: "Kent A. Kiehl" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Kent A. Kiehl" <[log in to unmask]>
Subject: fMRI image acquisition and analyses course with SPM5/8 and ICA -
July 14-16, 2011 - Second Call (course 50% full)
Content-Type: multipart/alternative; boundary=Apple-Mail-54--686547355
Mime-Version: 1.0 (Apple Message framework v1084)
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--Apple-Mail-54--686547355
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Content-Type: text/plain;
charset=windows-1252
> fMRI image acquisition and analyses course with SPM5/8 and ICA - July =
14-16, 2011 - Second call =20
>=20
>=20
>> The Mind Research Network and the University of New Mexico are =
pleased to announce the next upcoming fMRI Image Acquisition and =
Analyses course to be held July 14-16, 2011 at the Mind Research Network =
on the campus of the University of New Mexico in Albuquerque, NM. The =
course will include overview of both SPM5 and SPM8.
>>=20
>> The course faculty include:
>> =95 Kent Kiehl (The Mind Research Network and the University of New =
Mexico)
>> =95 Vince Calhoun (The Mind Research Network and the University of =
New Mexico)
>> =95 Tor Wager (University of Colorado =96 Boulder)
>>=20
>> The course is designed for fMRI researchers who range from beginning =
to intermediate skill levels. It will provide those who are just getting =
started with fMRI a comprehensive set of tools and software to get =
started with your own studies, and those who are more advanced will =
benefit from custom code and supplements to standard analyses developed =
by the instructors. We cover Statistical Parametric Mapping (SPM5/8), =
independent component analyses (ICA) of fMRI data, mediation analysis of =
fMRI, and statistical nonparametric mapping (SnPM).
>>=20
>> The course provides comprehensive coverage of all aspects of =
experimental design, image acquisition, image preprocessing, and =
analysis using the general linear model and ICA.
>>=20
>> The course is unique in that it pairs interactive lectures with =
hands-on demonstrations and work-through sessions. Each student works on =
their own laptop. Software will be installed on each student's laptop =
during the beginning of the course, including Matlab (a trial version), =
SPM5/8, the Group ICA of fMRI Toolbox (GIFT), and related SPM toolboxes, =
including statistical nonparametric mapping (SnPM) and the multi-level =
mediation fMRI toolbox (M3). In addition, alongside the lectures, =
participants will be trained to analyze example fMRI data on their =
laptops using these tools.
>>=20
>> The course will be small and interactive with many opportunities to =
work closely with the faculty. Registration will be on a first-come, =
first-served basis; we apologize in advance if we cannot accommodate all =
who wish to attend, but we will admit as many people as possible given =
the interactive nature of the course.
>>=20
>> To register, go to =
http://www.mrn.org/courses/abq-fmri-course-july-2011
>>=20
>> For inquiries, contact Kent Kiehl [log in to unmask]
>>=20
>> _________________________________
>> Kent A. Kiehl, Ph.D.
>> Director of Mobile Imaging Core and=20
>> Clinical Cognitive Neuroscience
>> Mind Research Network=20
>>=20
>> Associate Professor of Psychology and Neuroscience
>> University of New Mexico
>>=20
>> Mailing Address:=20
>> Mind Research Network
>> 1101 Yale Blvd NE
>> Albuquerque, NM, 87106
>> Office: 505-925-4516=20
>> [log in to unmask]
>>=20
>> _________________________________
>> Kent A. Kiehl, Ph.D.
>> Director of Mobile Imaging Core and=20
>> Clinical Cognitive Neuroscience
>> Mind Research Network=20
>>=20
>> Associate Professor of Psychology and Neuroscience
>> University of New Mexico
>>=20
>> Mailing Address:=20
>> Mind Research Network
>> 1101 Yale Blvd NE
>> Albuquerque, NM, 87106
>> Office: 505-925-4516=20
>> [log in to unmask]
>>=20
>>=20
>>=20
>>=20
_________________________________
Kent A. Kiehl, Ph.D.
Director of Mobile Imaging Core and=20
Clinical Cognitive Neuroscience
Mind Research Network=20
Associate Professor of Psychology and Neuroscience
University of New Mexico
Mailing Address:=20
Mind Research Network
1101 Yale Blvd NE
Albuquerque, NM, 87106
Office: 505-925-4516=20
[log in to unmask]
--Apple-Mail-54--686547355
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--Apple-Mail-55--686547355
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Content-Type: text/html;
charset=windows-1252
<html><head></head><body style=3D"word-wrap: break-word; =
-webkit-nbsp-mode: space; -webkit-line-break: after-white-space; =
"><div><blockquote type=3D"cite"><div style=3D"margin-top: 0px; =
margin-right: 0px; margin-bottom: 0px; margin-left: 0px; "><span =
style=3D"font-family: Helvetica; font-size: medium; "><b>fMRI image =
acquisition and analyses course with SPM5/8 and ICA - July 14-16, 2011 - =
Second call </b><br></span></div><br><div style=3D"word-wrap: =
break-word; -webkit-nbsp-mode: space; -webkit-line-break: =
after-white-space; "><div><br><blockquote type=3D"cite"><div =
style=3D"word-wrap: break-word; -webkit-nbsp-mode: space; =
-webkit-line-break: after-white-space; ">The Mind Research Network and =
the University of New Mexico are pleased to announce the next upcoming =
fMRI Image Acquisition and Analyses course to be held July 14-16, 2011 =
at the Mind Research Network on the campus of the University of New =
Mexico in Albuquerque, NM. The course will include overview of both SPM5 =
and SPM8.<br><br>The course faculty include:<br>=95 Kent Kiehl =
(The Mind Research Network and the University of New Mexico)<br>=95 =
Vince Calhoun (The Mind Research Network and the University of New =
Mexico)<br>=95 Tor Wager (University of Colorado =96 Boulder)<br><br>The =
course is designed for fMRI researchers who range from beginning to =
intermediate skill levels. It will provide those who are just getting =
started with fMRI a comprehensive set of tools and software to get =
started with your own studies, and those who are more advanced will =
benefit from custom code and supplements to standard analyses developed =
by the instructors. We cover Statistical Parametric Mapping (SPM5/8), =
independent component analyses (ICA) of fMRI data, mediation analysis of =
fMRI, and statistical nonparametric mapping (SnPM).<br><br>The course =
provides comprehensive coverage of all aspects of experimental design, =
image acquisition, image preprocessing, and analysis using the general =
linear model and ICA.<br><br>The course is unique in that it pairs =
interactive lectures with hands-on demonstrations and work-through =
sessions. Each student works on their own laptop. Software will be =
installed on each student's laptop during the beginning of the course, =
including Matlab (a trial version), SPM5/8, the Group ICA of fMRI =
Toolbox (GIFT), and related SPM toolboxes, including statistical =
nonparametric mapping (SnPM) and the multi-level mediation fMRI toolbox =
(M3). In addition, alongside the lectures, participants will be trained =
to analyze example fMRI data on their laptops using these =
tools.<br><br>The course will be small and interactive with many =
opportunities to work closely with the faculty. Registration will be on =
a first-come, first-served basis; we apologize in advance if we cannot =
accommodate all who wish to attend, but we will admit as many people as =
possible given the interactive nature of the course.<br><br>To register, =
go to <font class=3D"Apple-style-span" color=3D"#144FAE"><u><a =
href=3D"http://www.mrn.org/courses/abq-fmri-course-july-2011">http://www.m=
rn.org/courses/abq-fmri-course-july-2011</a></u></font><div><font =
class=3D"Apple-style-span" =
color=3D"#144FAE"><u></u></font></div></div></blockquote></div></div></blo=
ckquote></div></body></html>=
--Apple-Mail-55--686547355
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<html><head></head><body style=3D"word-wrap: break-word; =
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"><div><font class=3D"Apple-style-span" =
color=3D"#144FAE"><u><br></u></font>For inquiries, contact Kent Kiehl =
<a =
href=3D"mailto:[log in to unmask]">[log in to unmask]</a> <br><br>___________=
______________________<br>Kent A. Kiehl, Ph.D.<br>Director of Mobile =
Imaging Core and <br>Clinical Cognitive Neuroscience<br>Mind =
Research Network <br><br>Associate Professor of Psychology and =
Neuroscience<br>University of New Mexico<br><br>Mailing =
Address: <br>Mind Research Network<br>1101 Yale Blvd =
NE<br>Albuquerque, NM, 87106<br>Office: 505-925-4516 <br><a =
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"><div><div>_________________________________</div><div>Kent A. Kiehl, =
Ph.D.</div><div>Director of Mobile Imaging Core =
and </div><div>Clinical Cognitive Neuroscience</div><div>Mind =
Research Network </div><div><br></div><div>Associate Professor of =
Psychology and Neuroscience</div><div>University of New =
Mexico</div><div><br></div><div>Mailing Address: </div><div>Mind =
Research Network</div><div>1101 Yale Blvd NE</div><div>Albuquerque, NM, =
87106</div><div>Office: 505-925-4516 </div><div><a =
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iv></div></blockquote></div><div>
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-webkit-border-vertical-spacing: 0px; =
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auto; -webkit-text-stroke-width: 0px; "><div style=3D"word-wrap: =
break-word; -webkit-nbsp-mode: space; -webkit-line-break: =
after-white-space; =
"><div><div>_________________________________</div><div>Kent A. Kiehl, =
Ph.D.</div><div>Director of Mobile Imaging Core =
and </div><div>Clinical Cognitive Neuroscience</div><div>Mind =
Research Network </div><div><br></div><div>Associate Professor of =
Psychology and Neuroscience</div><div>University of New =
Mexico</div><div><br></div><div>Mailing Address: </div><div>Mind =
Research Network</div><div>1101 Yale Blvd NE</div><div>Albuquerque, NM, =
87106</div><div>Office: 505-925-4516 </div><div><a =
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--Apple-Mail-55--686547355--
--Apple-Mail-54--686547355--
=========================================================================
Date: Mon, 23 May 2011 22:39:44 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: DCM source time courses
Comments: To: Fahimeh Mamashli <[log in to unmask]>
In-Reply-To: <1774541387.2017.1306145983719.JavaMail.root@zimbra>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Dear Fahimeh,
You can find some relevant code in spm_dcm_erp_results around line
204. It appears that the time courses are stored in DCM.K field. In
general you can do the same thing I've just done and look at the code
of that function to find where things are stored or how they can be
computed.
Best,
Vladimir
On Mon, May 23, 2011 at 11:19 AM, Fahimeh Mamashli <[log in to unmask]> wr=
ote:
>
> Dear Vladimir,
> Thanks for your attention. I would like to have the time courses of each =
source in DCM. I mean the time course of pyramidal cells which we plot in E=
RP(sources) with GUI. how I can have access to them?
>
> Best wishes,
> Fahimeh
>
> ------------------------
> PhD student
> Max Planck Institute for Human Cognitive and Brain Sciences
> Stephanstra=DFe 1A
> 04103 Leipzig
> Germany
>
> Tel: +49 341 9940 - 2570
>
>
=========================================================================
Date: Mon, 23 May 2011 21:06:58 -0700
Reply-To: Michael T Rubens <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michael T Rubens <[log in to unmask]>
Subject: Re:
=?UTF-8?Q?=E5=9B=9E=E8=A6=86=EF=B9=95_=E5=9B=9E=E8=A6=86=EF=B9=95_=E5=9B?=
=?UTF-8?Q?=9E=E8=A6=86=EF=B9=95_?=[SPM] three questions about SPM8
Comments: To: a489930026 <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=90e6ba53a2e0eb932804a3fdb959
Message-ID: <[log in to unmask]>
--90e6ba53a2e0eb932804a3fdb959
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
You're welcome. Those functions should be included with the spm
distribution. If the script worked then you must have at least spm_vol,
spm_read_vols and spm_write_vol. otherwise, maybe they are only in older
versions, so in that case you can try SPM5.
Cheers,
Michael
On Mon, May 23, 2011 at 8:26 PM, a489930026 <[log in to unmask]> wrote=
:
> Dear Michael,
>
> The script works!! Thank you very much for your help and your patience.
> My final question is: how can I find these useful matlab functions (e.g.,
> spm_vol, spm_get_data) for SPM8, so I can try to help myself, instead of
> bugging you from the beginning, when I encounter the problem in the
> future. Thank you!
>
> Sincerely,
> Yihui
>
>
> ------------------------------
> *=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A* Michael T Rubens <MikeRubens@gmail=
.com>
> *=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A* a489930026 <[log in to unmask]
w>; spm <[log in to unmask]>
> *=E5=AF=84=E4=BB=B6=E6=97=A5=E6=9C=9F=EF=BC=9A* 2011/5/24 (=E4=BA=8C) 3:1=
6 AM
> *=E4=B8=BB=E6=97=A8=EF=BC=9A* Re: =E5=9B=9E=E8=A6=86=EF=B9=95 =E5=9B=9E=
=E8=A6=86=EF=B9=95 [SPM] three questions about SPM8
>
> I see now, I made a mistake in the original code I sent. This line:
>
> YY =3D spm_vol(VV);
>
> should actually be:
>
> YY =3D spm_read_vols(VV);
>
>
> %%
>
> Cheers,
> Michael
> On Mon, May 23, 2011 at 11:03 AM, a489930026 <[log in to unmask]>wro=
te:
>
> Dear Michael,
>
> Every step went smoothly until the step "YY(find(Y)) =3D 0" and then the =
it
> showed "Assignment between unlike types is not allowed."
>
> Yihui
>
> ------------------------------
> *=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A* Michael T Rubens <MikeRubens@gmail=
.com>
> *=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A* a489930026 <[log in to unmask]
w>; spm <[log in to unmask]>
> *=E5=AF=84=E4=BB=B6=E6=97=A5=E6=9C=9F=EF=BC=9A* 2011/5/24 (=E4=BA=8C) 1:2=
6 AM
> *=E4=B8=BB=E6=97=A8=EF=BC=9A* Re: =E5=9B=9E=E8=A6=86=EF=B9=95 [SPM] three=
questions about SPM8
>
> threshold needs to be>0. if your map is p values, then just do:
>
> Y =3D 1-Y; %now p =3D 1-p, so higher values are more significant.
>
> then set your p threshold as 1-threshold, so .95 =3D=3D .05
>
> Determining whether you use the mask inclusively or exlusively can be don=
e
> when you apply it, so:
>
> YY(find(Y)) =3D 0; % exclusive mask
>
> YY(find(~Y)) =3D 0; %inclusive mask
>
>
> Try running each line separately (or within a script) to see where exactl=
y
> the error is occurring.
>
>
> Cheers,
> Michael
>
> On Mon, May 23, 2011 at 12:48 AM, a489930026 <[log in to unmask]>wro=
te:
>
> Dear Michael,
>
> Thank you for the advice. I did what you suggested but a result "Assignme=
nt
> between unlike types is not allowed." What could be the problem?
>
> Please see the script below:
>
> *********************************************************
> >> V=3D spm_vol('L:\2stlevel\wordVSblk\spmF_0001.img')
> Y =3D spm_read_vols(V);
>
> threshold =3D 0; %any value you choose.
>
> Y(find(Y<threshold)) =3D 0;
> Y(find(Y)) =3D 1;
>
> % Use mask
>
> VV =3D spm_vol('L:\2stlevel\radpos_sdXloca_sd\spmF_0001.img');
> YY =3D spm_vol(VV);
>
> YY(find(Y)) =3D 0; %apply mask
>
> VV.fname =3D 'masked_image.img';
> spm_write_vol(VV,YY);
>
> %% There ya go
>
> V =3D
>
> fname: 'L:\2stlevel\wordVSblk\spmF_0001.img'
> mat: [4x4 double]
> dim: [79 95 68]
> dt: [16 0]
> pinfo: [3x1 double]
> n: [1 1]
> descrip: 'SPM{F_[1.0,15.0]} - contrast 1: w-b'
> private: [1x1 nifti]
>
> ??? Assignment between unlike types is not allowed.
>
> *************************************************************************
>
> Besides, is the threshold a cutoff for the activation maps of the mask?
> Specially, does setting threshold =3D 0.05 mean that the activated voxels=
below p =3D0.05 are included. If not, how should I set a cutoff on the p
> value, or it does matter?
>
> Moreover, how can I determine the mask is inclusive (i.e., the voxles in
> the to-be-masked activation maps are within the volxels in the activation
> maps of the mask) or exclusive (i.e., the voxles in the to-be-masked
> activation maps are NOT within the volxels in the activation maps of the
> mask).
> Thank you very much!
>
> Sincerely,
> Yihui
>
>
>
>
>
> ------------------------------
> *=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A* Michael T Rubens <MikeRubens@gmail=
.com>
> *=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A* SUBSCRIBE SPM Yihui Hung <a4899300=
[log in to unmask]>
> *=E5=89=AF=E6=9C=AC=EF=BC=9A* [log in to unmask]
> *=E5=AF=84=E4=BB=B6=E6=97=A5=E6=9C=9F=EF=BC=9A* 2011/5/23 (=E4=B8=80) 10:=
19 AM
> *=E4=B8=BB=E6=97=A8=EF=BC=9A* Re: [SPM] three questions about SPM8
>
> when you say you tried to use the contrast as a mask, did you just use th=
e
> raw contrast or did you binarize it? If you did the former than it is
> clear why you had no inmask voxels since any non-zero voxels would all be
> seen as part of the mask. So, what you want to do is load the mask, apply=
a
> threshold and binarize it by setting anything below the threshold to 0,
> and anything above to 1 (though the latter may not be completely necesary=
).
> Then, you could just use that mask to mask out the resulting contrast map
> from the other analysis. Here is code to do it:
>
> %Make mask
>
> V =3D spm_vol('contrast_image_2turn_into_mask')
> Y =3D spm_read_vols(V);
>
> threshold =3D X; %any value you choose.
>
> Y(find(Y<threshold)) =3D 0;
> Y(find(Y)) =3D 1;
>
> % Use mask
>
> VV =3D spm_vol('contrast_image_2mask');
> YY =3D spm_vol(VV);
>
> YY(find(Y)) =3D 0; %apply mask
>
> VV.fname =3D 'masked_image.img';
> spm_write_vol(VV,YY);
>
> %% There ya go
>
> Cheers,
> Michael
>
> On Sun, May 22, 2011 at 9:58 AM, SUBSCRIBE SPM Yihui Hung <
> [log in to unmask]> wrote:
>
> Hello,
>
> I used SPM8 for my experiment. I manipulated three factors (e.g., factor
> A, B, C) in my experiment. The activation maps under factor A was used as=
a
> mask to constrain the effects of factor B and factor C. The problem is th=
at
> the factor A and factor B and factor C cannot be put in the same model at
> second level analysis. I tried to put the .img file resulting from factor
> A across participants in the =E2=80=9Cexplicit mask=E2=80=9D in the secon=
d level analysis.
> However, the estimation stopped by showing no inmask voxels. I searched
> through forum and did not find any useful solutions. Can someone help me
> out? Moreover, is the threshold masking related to the p value? If not, h=
ow
> should I set criteria for the activation map of the mask?
>
> I did notice that one person in the forum suggested that one can create a=
n
> activation maps in which the factor B is modeled with the mask of factor =
A
> in first level analysis. Then, submit the resulting .img file into second
> level analysis. My question is how to create and save the img file.
>
> Finally, I posted a question regarding how to export beta values over
> multiple coordinates a week ago. However, no one provide any answers. I
> wonder whether it is due that no one has the answer or due to that there
> already is an answer in the forum.
>
> Thank you for your patience and advice.
> Sincerely,
>
> Yihui
>
>
>
>
> --
> Research Associate
> Gazzaley Lab
> Department of Neurology
> University of California, San Francisco
>
>
>
>
>
> --
> Research Associate
> Gazzaley Lab
> Department of Neurology
> University of California, San Francisco
>
>
>
>
>
> --
> Research Associate
> Gazzaley Lab
> Department of Neurology
> University of California, San Francisco
>
>
>
--=20
Research Associate
Gazzaley Lab
Department of Neurology
University of California, San Francisco
--90e6ba53a2e0eb932804a3fdb959
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
You're welcome. Those functions should be included with the spm distrib=
ution. If the script worked then you must have at least spm_vol, spm_read_v=
ols and spm_write_vol. otherwise, maybe they are only in older versions, so=
in that case you can try SPM5.<br>
<br>Cheers,<br>Michael<br><br><div class=3D"gmail_quote">On Mon, May 23, 20=
11 at 8:26 PM, a489930026 <span dir=3D"ltr"><<a href=3D"mailto:a48993002=
[log in to unmask]" target=3D"_blank">[log in to unmask]</a>></span> wr=
ote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; borde=
r-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
<div><div style=3D"color: rgb(0, 0, 0); background-color: rgb(255, 255, 255=
); font-family: arial,helvetica,sans-serif; font-size: 12pt;"><div style=3D=
"font-size: 12pt; font-family: arial,helvetica,sans-serif;">Dear Michael,<b=
r>
</div><div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-seri=
f;"><br></div><div style=3D"font-size: 12pt; font-family: arial,helvetica,s=
ans-serif;">The script works!!=C2=A0Thank you very much for your help and y=
our patience.=C2=A0</div>
<div><font size=3D"3">My final question is: how can I find these useful <sp=
an><span>matlab</span></span>=C2=A0</font>functions<font size=3D"3">=C2=A0(=
e.g.,=C2=A0</font><span style=3D"font-size: 12pt; font-family: 'times n=
ew roman','new york',times,serif;"><span><span><span><span>spm<=
/span></span></span></span></span><span style=3D"font-size: 12pt; font-fami=
ly: 'times new roman','new york',times,serif;">_vol, <span>=
<span>spm</span></span>_get_data</span><font size=3D"3">) for <span><span>S=
PM</span></span>8, so I can try to help myself, instead of bugging you from=
the <span><span>beginning</span></span>, when I encounter the problem in t=
he future.=C2=A0</font>Thank you!</div>
<div><font size=3D"3"><br></font></div><div><font size=3D"3">Sincerely,</fo=
nt></div><div><font size=3D"3"><span><span>Yihui</span></span></font></div>=
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><b=
r></div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><b=
r></div><div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-se=
rif;"><blockquote style=3D"border-left: 2px solid rgb(16, 16, 255); margin-=
left: 5px; padding-left: 5px;">
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><d=
iv style=3D"font-size: 12pt; font-family: 'times new roman','ne=
w york',times,serif;"><font face=3D"Arial" size=3D"2"><hr size=3D"1"><b=
><span style=3D"font-weight: bold;">=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A</s=
pan></b> Michael T Rubens <<a href=3D"mailto:[log in to unmask]" targe=
t=3D"_blank">[log in to unmask]</a>><br>
<b><span style=3D"font-weight: bold;">=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A<=
/span></b> a489930026 <<a href=3D"mailto:[log in to unmask]" target=
=3D"_blank">[log in to unmask]</a>>; <span><span>spm</span></span> =
<<a href=3D"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]
.uk</a>><br>
<b><span style=3D"font-weight: bold;">=E5=AF=84=E4=BB=B6=E6=97=A5=E6=9C=9F=
=EF=BC=9A</span></b> 2011/5/24 (=E4=BA=8C) 3:16 AM<br><b><span style=3D"fon=
t-weight: bold;">=E4=B8=BB=E6=97=A8=EF=BC=9A</span></b> Re: =E5=9B=9E=E8=A6=
=86=EF=B9=95 =E5=9B=9E=E8=A6=86=EF=B9=95 [<span><span>SPM</span></span>] th=
ree questions about <span><span>SPM</span></span>8<br>
</font><br><div>I see now, I made a mistake in the original code I sent. Th=
is line: <br><br><span><span><span><span>YY</span></span></span></span> =3D=
<span><span><span><span>spm</span></span></span></span>_vol(<span><span><s=
pan><span>VV</span></span></span></span>);<br>
<br>should actually be:<br><br><span><span><span><span>YY</span></span></sp=
an></span> =3D <span><span><span><span>spm</span></span></span></span>_read=
_vols(<span><span><span><span>VV</span></span></span></span>);<br>
<br><br>%%<br><br>Cheers,<br>Michael<br><div>On Mon, May 23, 2011 at 11:03 =
AM, a489930026 <span dir=3D"ltr"><<a rel=3D"nofollow" href=3D"mailto:a48=
[log in to unmask]" target=3D"_blank">[log in to unmask]</a>></sp=
an> wrote:<br>
<blockquote style=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(=
204, 204, 204); padding-left: 1ex;">
<div><div style=3D"color: rgb(0, 0, 0); background-color: rgb(255, 255, 255=
); font-size: 12pt; font-family: arial,helvetica,sans-serif;"><div><span><d=
iv>Dear Michael,</div><div><br></div><div>Every step went smoothly until th=
e step "<span><span>YY</span></span>(find(Y)) =3D 0" and then the=
it showed "Assignment between unlike types is not allowed."</div=
>
<div><br></div><div><span><span>Yihui</span></span></div></span></div><div>=
<br><blockquote style=3D"border-left: 2px solid rgb(16, 16, 255); margin-le=
ft: 5px; padding-left: 5px;"><div style=3D"font-size: 12pt; font-family: ar=
ial,helvetica,sans-serif;">
<div style=3D"font-size: 12pt;"><font face=3D"Arial" size=3D"2"><hr size=3D=
"1"><b><span style=3D"font-weight: bold;">=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=
=9A</span></b> Michael T Rubens <<a rel=3D"nofollow" href=3D"mailto:Mike=
[log in to unmask]" target=3D"_blank">[log in to unmask]</a>><br>
<b><span style=3D"font-weight: bold;">=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A<=
/span></b> a489930026 <<a rel=3D"nofollow" href=3D"mailto:a489930026@yah=
oo.com.tw" target=3D"_blank">[log in to unmask]</a>>; <span><span>s=
pm</span></span> <<a rel=3D"nofollow" href=3D"mailto:[log in to unmask]"=
target=3D"_blank">[log in to unmask]</a>><br>
<b><span style=3D"font-weight: bold;">=E5=AF=84=E4=BB=B6=E6=97=A5=E6=9C=9F=
=EF=BC=9A</span></b> 2011/5/24 (=E4=BA=8C) 1:26 AM<br><b><span style=3D"fon=
t-weight: bold;">=E4=B8=BB=E6=97=A8=EF=BC=9A</span></b> Re: =E5=9B=9E=E8=A6=
=86=EF=B9=95 [<span><span>SPM</span></span>] three questions about <span><s=
pan>SPM</span></span>8<br>
</font><br><div>threshold needs to be>0. if your map is p values, then j=
ust do:<br>
<br>Y =3D 1-Y; %now p =3D 1-p, so higher values are more significant.<br><b=
r>then set your p threshold as 1-threshold, so .95 =3D=3D .05<br><br>Determ=
ining whether you use the mask inclusively or <span><span>exlusively</span>=
</span> can be done when you apply it, so: <br>
<br><span><span><span><span>YY</span></span></span></span>(find(Y)) =3D 0; =
% exclusive mask<br><br><span><span>YY</span></span>(find(~Y)) =3D 0; %incl=
usive mask<br><br><br>Try running each line separately (or within a script)=
to see where exactly the error is occurring.<br>
<br>
<br>Cheers,<br>Michael<br><br><div>On Mon, May 23, 2011 at 12:48 AM, a48993=
0026 <span dir=3D"ltr"><<a rel=3D"nofollow" href=3D"mailto:a489930026@ya=
hoo.com.tw" target=3D"_blank">[log in to unmask]</a>></span> wrote:=
<br>
<blockquote style=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(=
204, 204, 204); padding-left: 1ex;">
<div><div style=3D"color: rgb(0, 0, 0); background-color: rgb(255, 255, 255=
); font-size: 12pt; font-family: arial,helvetica,sans-serif;"><div style=3D=
"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><span>Dear Mich=
ael,</span></div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><s=
pan><br></span></div><div style=3D"font-size: 12pt; font-family: arial,helv=
etica,sans-serif;">Thank you for the advice. I did what you suggested but a=
result "Assignment between unlike types is not allowed." What co=
uld be the problem?</div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><b=
r></div><div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-se=
rif;">Please see the script below:</div><div style=3D"font-size: 12pt; font=
-family: arial,helvetica,sans-serif;">
<br></div><div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-=
serif;">*********************************************************</div><div=
><div>>> V=3D <span><span><span><span>spm</span></span></span></span>=
_vol('L:\2<span><span><span><span>stlevel</span></span></span></span>\<=
span><span><span><span>wordVSblk</span></span></span></span>\<span><span><s=
pan><span>spmF</span></span></span></span>_0001.<span><span><span><span>img=
</span></span></span></span>')</div>
<div>Y =3D <span><span><span><span>spm</span></span></span></span>_read_vol=
s(V);</div><div><br></div><div>threshold =3D 0; %any value you choose.</div=
><div><br></div><div>Y(find(Y<threshold)) =3D
0;</div><div>Y(find(Y)) =3D 1;</div><div><br></div><div>% Use mask</div><d=
iv><br></div><div><span><span><span><span>VV</span></span></span></span> =
=3D <span><span><span><span>spm</span></span></span></span>_vol('L:\2<s=
pan><span><span><span>stlevel</span></span></span></span>\<span><span><span=
><span>radpos</span></span></span></span>_<span><span><span><span>sdXloca</=
span></span></span></span>_<span><span><span><span>sd</span></span></span><=
/span>\<span><span><span><span>spmF</span></span></span></span>_0001.<span>=
<span><span><span>img</span></span></span></span>');</div>
<div><span><span><span><span>YY</span></span></span></span> =3D <span><span=
><span><span>spm</span></span></span></span>_vol(<span><span><span><span>VV=
</span></span></span></span>);</div><div><br></div><div><span><span><span><=
span>YY</span></span></span></span>(find(Y)) =3D 0; %apply mask</div>
<div><br></div><div><span><span><span><span>VV</span></span></span></span>.=
<span><span><span><span>fname</span></span></span></span> =3D
'masked_image.<span><span><span><span>img</span></span></span></span>&=
#39;;</div>
<div><span><span><span><span>spm</span></span></span></span>_write_vol(<spa=
n><span><span><span>VV</span></span></span></span>,<span><span><span><span>=
YY</span></span></span></span>);</div><div><br></div><div>%% There ya go</d=
iv>
<div><br></div><div>V =3D=C2=A0</div><div><br></div><div>=C2=A0 =C2=A0 =C2=
=A0 <span><span><span><span>fname</span></span></span></span>: 'L:\2<sp=
an><span><span><span>stlevel</span></span></span></span>\<span><span><span>=
<span>wordVSblk</span></span></span></span>\<span><span><span><span>spmF</s=
pan></span></span></span>_0001.<span><span><span><span>img</span></span></s=
pan></span>'</div>
<div>=C2=A0 =C2=A0 =C2=A0 =C2=A0 mat: [4x4 double]</div><div>=C2=A0 =C2=A0 =
=C2=A0 =C2=A0 dim: [79 95 68]</div><div>=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0<=
span><span><span><span>dt</span></span></span></span>: [16 0]</div><div>=C2=
=A0 =C2=A0 =C2=A0 <span><span><span><span>pinfo</span></span></span></span>=
: [3x1 double]</div>
<div>=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 n: [1 1]</div><div>
=C2=A0 =C2=A0 <span><span><span><span>descrip</span></span></span></span>: =
'SPM{F_[1.0,15.0]} -
contrast 1: w-b'</div><div>=C2=A0 =C2=A0 private: [1x1 <span><span><sp=
an><span>nifti</span></span></span></span>]</div><div><br></div><div>??? As=
signment between unlike types is not allowed.</div><div><br></div><div>****=
*********************************************************************</div>
<div><br></div><div>Besides, is the threshold a cutoff for the activation m=
aps of the mask? Specially, does setting threshold =3D 0.05 mean that the a=
ctivated <span><span><span><span>voxels</span></span></span></span> below p=
=3D0.05 are included. If not, how should I set a cutoff on the p value, or=
it does matter?=C2=A0</div>
<div><br></div><div>Moreover, how can I determine the mask is inclusive (i.=
e., the <span><span><span><span>voxles</span></span></span></span> in the
to-be-masked activation maps are within the <span><span><span><span>volxel=
s</span></span></span></span> in the activation maps of the mask) or exclus=
ive=C2=A0(i.e., the <span><span><span><span>voxles</span></span></span></sp=
an> in the to-be-masked activation maps are NOT within the <span><span><spa=
n><span>volxels</span></span></span></span> in <span>the activation</span> =
maps of the mask).=C2=A0</div>
<div>Thank you very much!</div><div><br></div><div>Sincerely,</div><div><sp=
an><span><span><span>Yihui</span></span></span></span></div></div><div styl=
e=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;">=C2=A0</div=
><div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;">
<br></div><div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-=
serif;"><br></div><div style=3D"font-size: 12pt; font-family: arial,helveti=
ca,sans-serif;"><br></div><div style=3D"font-size: 12pt; font-family: arial=
,helvetica,sans-serif;">
<br><blockquote style=3D"border-left: 2px solid rgb(16, 16, 255); margin-le=
ft: 5px; padding-left: 5px;"><div style=3D"font-size: 12pt; font-family: ar=
ial,helvetica,sans-serif;"><div style=3D"font-size: 12pt;">
<font face=3D"Arial" size=3D"2"><hr size=3D"1"><b><span style=3D"font-weigh=
t: bold;">=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A</span></b> Michael T Rubens =
<<a rel=3D"nofollow" href=3D"mailto:[log in to unmask]" target=3D"_bla=
nk">[log in to unmask]</a>><br><b><span style=3D"font-weight: bold;">=
=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A</span></b> SUBSCRIBE <span><span><span=
><span>SPM</span></span></span></span> <span><span><span><span>Yihui</span>=
</span></span></span> Hung <<a rel=3D"nofollow" href=3D"mailto:a48993002=
[log in to unmask]" target=3D"_blank">[log in to unmask]</a>><br>
<b><span style=3D"font-weight: bold;">=E5=89=AF=E6=9C=AC=EF=BC=9A</span></b=
> <a rel=3D"nofollow" href=3D"mailto:SPM@jiscmail.ac.uk" target=3D"_blank">=
[log in to unmask]</a><br><b><span style=3D"font-weight: bold;">=E5=AF=84=
=E4=BB=B6=E6=97=A5=E6=9C=9F=EF=BC=9A</span></b> 2011/5/23 (=E4=B8=80) 10:19=
AM<br>
<b><span style=3D"font-weight: bold;">=E4=B8=BB=E6=97=A8=EF=BC=9A</span></b=
> Re: [<span><span><span><span>SPM</span></span></span></span>] three quest=
ions about <span><span><span><span>SPM</span></span></span></span>8<br>
</font><br><div>when you say you tried to use the contrast as a mask, did y=
ou just use the raw contrast or did you <span><span><span><span>binarize</s=
pan></span></span></span>
it? If you did the former than it is clear why you had no <span><span><spa=
n><span>inmask</span></span></span></span> <span><span><span><span>voxels</=
span></span></span></span> since any non-zero <span><span><span><span>voxel=
s</span></span></span></span> would all be seen as part of the mask. So, wh=
at you want to do is load the mask, apply a threshold and <span><span><span=
><span>binarize</span></span></span></span> it by setting anything below th=
e threshold to 0, and anything above to 1 (though the latter may not be com=
pletely <span><span><span><span>necesary</span></span></span></span>). Then=
, you could just use that mask to mask out the
resulting contrast map from the other analysis. Here is code to do it:<br>
<br>%Make mask<br><br>V =3D <span><span><span><span>spm</span></span></span=
></span>_vol('contrast_image_2turn_into_mask')<br>Y =3D <span><span=
><span><span>spm</span></span></span></span>_read_vols(V);<br><br>threshold=
=3D X; %any value you choose.<br>
<br>Y(find(Y<threshold)) =3D 0;<br>
Y(find(Y)) =3D 1;<br><br>% Use mask<br>
<br><span><span><span><span>VV</span></span></span></span> =3D <span><span>=
<span><span>spm</span></span></span></span>_vol('contrast_image_2mask&#=
39;);<br><span><span><span><span>YY</span></span></span></span> =3D <span><=
span><span><span>spm</span></span></span></span>_vol(<span><span><span><spa=
n>VV</span></span></span></span>);<br>
<br><span><span><span><span>YY</span></span></span></span>(find(Y)) =3D 0; =
%apply mask<br>
<br><span><span><span><span>VV</span></span></span></span>.<span><span><spa=
n><span>fname</span></span></span></span> =3D 'masked_image.<span><span=
><span><span>img</span></span></span></span>';<br><span><span><span><sp=
an>spm</span></span></span></span>_write_vol(<span><span><span><span>VV</sp=
an></span></span></span>,<span><span><span><span>YY</span></span></span></s=
pan>);<br>
<br>%% There ya go<br><br>Cheers,<br>Michael<br>
<br><div>On Sun, May 22, 2011 at 9:58 AM, SUBSCRIBE <span><span><span><span=
>SPM</span></span></span></span> <span><span><span><span>Yihui</span></span=
></span></span> Hung <span dir=3D"ltr"><<a rel=3D"nofollow" href=3D"mail=
to:[log in to unmask]" target=3D"_blank">[log in to unmask]</a>&g=
t;</span> wrote:<br>
<blockquote style=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(=
204, 204, 204); padding-left: 1ex;">
Hello,<br>
<br>
I used <span><span><span><span>SPM</span></span></span></span>8 for my expe=
riment. I manipulated three factors (e.g., factor A, B, C) in my experiment=
. The activation maps under factor A was used as a mask to constrain the ef=
fects of factor B and factor C. The problem is that the factor A and factor=
B and factor C cannot be put in the same model at second level analysis. I=
tried to put the .<span><span><span><span>img</span></span></span></span> =
file resulting from factor A across participants in the =E2=80=9Cexplicit m=
ask=E2=80=9D in the second level analysis. However, the estimation stopped =
by showing no <span><span><span><span>inmask</span></span></span></span> <s=
pan><span><span><span>voxels</span></span></span></span>. I searched throug=
h forum and did not find any useful solutions. Can someone help me out? Mor=
eover, is the threshold masking related to the p value? If not, how should =
I set criteria for the activation map of the mask?<br>
<br>
I did notice that one person in the forum suggested that one can create an =
activation maps in which the factor B is <span><span><span><span>modeled</s=
pan></span></span></span> with the mask of factor A in first level analysis=
. Then, submit the resulting .<span><span><span><span>img</span></span></sp=
an></span> file into second level analysis. My question is how to create an=
d save the <span><span><span><span>img</span></span></span></span> file.<br=
>
<br>
Finally, I posted a question regarding how to export beta values over multi=
ple coordinates a week ago. However, no one provide any answers. I wonder w=
hether it is due that no one has the answer or due to that there already is=
an answer in the forum.<br>
<br>
Thank you for your patience and advice.<br>
Sincerely,<br>
<font color=3D"#888888"><br>
<span><span><span><span>Yihui</span></span></span></span><br>
<br>
</font></blockquote></div><br><br clear=3D"all"><br>-- <br>Research Associa=
te<br><span><span><span><span>Gazzaley</span></span></span></span> Lab<br>D=
epartment of Neurology<br>University of California, San Francisco<br>
</div><br><br></div></div></blockquote></div></div></div></blockquote></div=
><br><br clear=3D"all"><br>-- <br>Research Associate<br><span><span>Gazzale=
y</span></span> Lab<br>Department of Neurology<br>University of California,=
San Francisco<br>
</div><br><br></div></div></blockquote></div></div></div></blockquote></div=
><br><br clear=3D"all"><br>-- <br>Research Associate<br><span><span>Gazzale=
y</span></span> Lab<br>Department of Neurology<br>University of California,=
San Francisco<br>
</div><br><br></div></div></blockquote></div></div></div></blockquote></div=
><br><br clear=3D"all"><br>-- <br>Research Associate<br>Gazzaley Lab<br>Dep=
artment of Neurology<br>University of California, San Francisco<br>
--90e6ba53a2e0eb932804a3fdb959--
=========================================================================
Date: Tue, 24 May 2011 09:10:20 +0200
Reply-To: Marko Wilke <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Marko Wilke <[log in to unmask]>
Subject: Error when using unified segmentation in spm8
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Dear All,
has anyone else encountered this error when trying to segment a dataset=20
via the GUI in spm8 (on Matlab 2010b)?
------------------------------------------------------------------------
Running job #1
------------------------------------------------------------------------
Running 'Segment'
Failed 'Segment'
Reference to non-existent field 'fudge'.
In file "B:\Util\spm8\spm_preproc.m" (v4178), function "spm_preproc" at=20
line 105.
In file "B:\Util\spm8\config\spm_run_preproc.m" (v4185), function=20
"spm_run_preproc" at line 19.
The following modules did not run:
Failed: Segment
------------------------------------------------------------------------
I re-applied the last updates which did not fix it. I usually segment=20
data from within scripts and it works fine on the same dataset, likely=20
because I specify 'fudge' as '5' in my options. I would appreciate=20
feedback as to why this happens and whether something went wrong during=20
my update process.
Thanks,
Marko
--=20
____________________________________________________
PD Dr. med. Marko Wilke
Facharzt f=FCr Kinder- und Jugendmedizin
Leiter, Experimentelle P=E4diatrische Neurobildgebung
Universit=E4ts-Kinderklinik
Abt. III (Neurop=E4diatrie)
Marko Wilke, MD, PhD
Pediatrician
Head, Experimental Pediatric Neuroimaging
University Children's Hospital
Dept. III (Pediatric Neurology)
Hoppe-Seyler-Str. 1
D - 72076 T=FCbingen, Germany
Tel. +49 7071 29-83416
Fax +49 7071 29-5473
[log in to unmask]
http://www.medizin.uni-tuebingen.de/kinder/epn
____________________________________________________
=========================================================================
Date: Tue, 24 May 2011 09:20:43 +0100
Reply-To: Yang Hu <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Yang Hu <[log in to unmask]>
Subject: How to do PPI GLM estimation and contrasts using matlab script
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear all,=20
Having set up PPI.mat (PPI variables) of each individual by spm_peb_p=
pi.m, I would like to do PPI GLM estimation (3 regressors in the design m=
atrix: PPI.ppi, PPI.Y, PPI.P)and contrasts (e.g. [1 0 0 0]) for each indi=
vidual. Could someone provide me with the matlab script to do the two abo=
ve steps? Any suggestions are welcome. Thanks a lot!
Best wishes,=20
Yang Hu
ICN, ECNU, Shanghai, China PR
=========================================================================
Date: Tue, 24 May 2011 10:11:38 +0100
Reply-To: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Subject: Re: Error when using unified segmentation in spm8
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Hi Marco,
you might want to check whether there is a spm_defaults.m outside the SPM=
8 folder on your MATLAB path. With the last set of updates, some previous=
ly hardcoded defaults have moved into spm_defaults.m. If your version of =
spm_defaults.m is missing them, this could cause such an error message.
Best,
Volkmar
=========================================================================
Date: Tue, 24 May 2011 11:32:30 +0200
Reply-To: Marine Lazouret <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Marine Lazouret <[log in to unmask]>
Subject: t-test FWE correction
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=90e6ba4fc23059d62304a402441a
Message-ID: <[log in to unmask]>
--90e6ba4fc23059d62304a402441a
Content-Type: text/plain; charset=ISO-8859-1
Hello SPMers,
I'm having difficulty understanding my results here. I realized an
independent component analysis with the GIFT implementation, and now I just
wanted to extract the anatomical labels of the regions activated. So I
realized a one sample t-test with the images from my group.
Why is it that before Family Wise Error Correction I obtain less
significantly activated regions than after?
My threshold is definitely higher after correction so how could this happen?
Cheers,
--
*Marine*
--90e6ba4fc23059d62304a402441a
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Hello SPMers,<div><br></div><div>I'm having difficulty understanding my=
results here. I realized an independent component analysis with the GIFT i=
mplementation, and now I just wanted to extract the anatomical labels of th=
e regions activated. So I realized a one sample t-test with the images from=
my group.</div>
<div>Why is it that before Family Wise Error Correction I obtain less signi=
ficantly activated regions than after?</div><div>My threshold is definitely=
higher after correction so how could this happen?</div><div><br></div>
<div>Cheers,<br clear=3D"all"><br>-- <br><b><i><font face=3D"georgia, serif=
">Marine</font></i></b><br>
</div>
--90e6ba4fc23059d62304a402441a--
=========================================================================
Date: Tue, 24 May 2011 11:40:10 +0100
Reply-To: Niccolo Morandotti <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Niccolo Morandotti <[log in to unmask]>
Subject: help in "modeling categorical responses"
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Hi
i'm new to matlab and spm and i'm trying to learn how to use them
i'm reading the spm8 manual and i'm going through the dataset "face fMRI =
data", chapter 29
everything ran smoothly in the pre-processing until the smoothing but i'm=
now experiencing a problem in the next step, modeling categorical respon=
ses, page 243: as a first step i should type "load sots", and this ran sm=
oothly, but as a second step i should type "movepars.txt" but when i try =
to do it, the following message appears:
??? Error using =3D=3D> load
Unable to read file movepars.txt: No such file or directory.
please note that i previously saved the file movepars in the directory, a=
s it was mentioned at the bottom of page 237
is anybody able to highlighting me?
thank you in advance for helping me in this learning step
regards
Niccol=C3=B2
=========================================================================
Date: Tue, 24 May 2011 12:52:25 +0200
Reply-To: Nico Bunzeck <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Nico Bunzeck <[log in to unmask]>
Subject: JOB ANNOUNCEMENT (Hamburg, Germany)
MIME-Version: 1.0
Content-Type: text/plain; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Postdoc Position (E13) in imaging neuroscience of learning and memory.=20
=20
We are seeking a highly motivated and talented Postdoctoral Research
Associate to work at the Institute of Systems Neuroscience at the =
University
Medical Center Hamburg-Eppendorf (head Prof. B=FCchel).=20
The project will investigate the relationship between dopaminergic
neuromodulation, motivation and long-term memory. Methodologically, it
involves fMRI and M/EEG in combination with psychopharmacology.=20
The position is funded by the German research foundation (DFG) and is
initially available for 2 years with a possible extension. Salary will =
be
according to German Public service regulations (E13).=20
Candidates should have a Ph.D. (or equivalent) in psychology, biology,
neuroscience or a related field. Furthermore, they should be familiar =
with
fMRI and/or M/EEG and have a strong background in neuroscience of =
learning
and memory. Programming skills (preferably Matlab) are advantageous.
The Institute of Systems Neuroscience provides an excellent
multi-disciplinary and interactive neuroimaging environment with its own
physics, psychology and clinical neuroscience groups as well as a =
research
dedicated 3T MR scanner and a whole head MEG system.=20
The position is available immediately and applications will be =
considered
until the position is filled. Candidates should submit a CV, names of =
two
references and a brief statement of research interests by e-mail to Dr =
Nico
Bunzeck at [log in to unmask]
For questions or informal enquiries about the position please contact me =
via
email: [log in to unmask]
__________________________
Dr Nico Bunzeck
Department of Systems Neuroscience, Bldg W34
University Medical Center Hamburg-Eppendorf
Martinistrasse 52
20246 Hamburg, Germany
Phone: +49-(0)40-7410-59902
Fax: +49-(0)40-7410-59955
E-mail: [log in to unmask]
=========================================================================
Date: Tue, 24 May 2011 12:51:25 +0200
Reply-To: Birgitta Metternich <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Birgitta Metternich <[log in to unmask]>
Subject: SPM.ps files stored in wrong folder
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-15; format=flowed
Content-Transfer-Encoding: 7bit
Message-ID: <[log in to unmask]>
Dear all,
I am using SPM8 (updated) and have a problem with my results being
stored in Matlab's current directory. I searched the archive, but
couldn't find a solution to this problem. In my batch I have of course
specified a results directory, but only part of the results are written
into that directory as an SPM.ps file, e.g. the realignment parameters
of subject 6 are written into the SPM.ps file in the folder of subject
5, so that the resulting SPM-file is a mix-up of two subjects. The
remaining results are then written to a different SPM.ps in the correct
folder (in this case subject 6). This happens every time, unless I
change the current directory in Matlab accordingly for each subject I
analyse. Oddly, my colleagues, doing similar analyses with similar
batches do not have this problem. Their results are always saved in the
correct subject folder. Maybe someone has an idea?
Birgitta
=========================================================================
Date: Tue, 24 May 2011 12:01:30 +0100
Reply-To: Henrike Hemingway <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Henrike Hemingway <[log in to unmask]>
Subject: SPM 8 Flexible Factorial Design Question
Mime-Version: 1.0
Content-Type: multipart/mixed;
boundary="part-HQJBAPlABbaAkA1xRlRmTAIZOHcm16VdA1OgAA8uoomQc"
Message-ID: <[log in to unmask]>
--part-HQJBAPlABbaAkA1xRlRmTAIZOHcm16VdA1OgAA8uoomQc
Content-Type: multipart/mixed; boundary="part-dyuwpTUhwkAOIhQSfA1llCApznCCaqzCAyviLfedidTMW"
This is a multi-part message in MIME format.
--part-dyuwpTUhwkAOIhQSfA1llCApznCCaqzCAyviLfedidTMW
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Dear SPMers,
I have question regarding the flexible factorial design as implemented in=
SPM8.
I have realized an experiment with 5 conditions for each subject (4 emoti=
on conditions, 1 neutral condition). I was interested in the difference b=
etween the emotion and the neutral conditions.Therefore, I set up the 2nd=
level analysis using a flexible factorial design in SPM8 in two differen=
t ways. The main effect of subject and the main effect of condition were =
estimated in both of the design matrices.=20
In the first design matrix I specified the effect of condition with 5 lev=
els, including the con images of all 5 conditions separately. The contras=
ts for each of the 4 conditions > neutral were computed on the 2nd level.=
For the second flexible factorial design I computed the differences betw=
een each of the 4 conditions > neutral on the first level and by this did=
n=E2=80=99t have to estimate difference contrasts on the 2nd level. Thus,=
I specified the effect of condition with only 4 levels each representing=
the difference of the condition > neutral and estimated the main effect =
for each of the four conditions.=20
The results for the contrasts representing the same difference (Condition=
> Neutral), however, were not similar across both designs as you can see=
in the attached screen shots. The model including the difference contras=
ts computed on the first level resulted in much higher t-values and large=
r number of voxels in the clusters of interest. After some research in th=
e archives of the SPM mailing list I still have not found an explanation =
for the diverging results. Though I found some information about a compar=
able difference observed when comparing designs explicitly modeling the s=
ubject factor or not.
Does anyone know what exactly is causing the pronounced difference in bot=
h designs? When looking at the con images computed on the 2nd level they =
contain the exact same values in each voxel. Is one of the models practic=
ally wrong?
I would be glad if anyone could help me out with more detailed informatio=
n or helpful links for further readings on that issue.
Thanks a lot.
Henrike
--part-dyuwpTUhwkAOIhQSfA1llCApznCCaqzCAyviLfedidTMW--
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--part-HQJBAPlABbaAkA1xRlRmTAIZOHcm16VdA1OgAA8uoomQc--
=========================================================================
Date: Tue, 24 May 2011 14:00:15 +0200
Reply-To: Marko Wilke <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Marko Wilke <[log in to unmask]>
Subject: Re: Error when using unified segmentation in spm8
Comments: To: Volkmar Glauche <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Hi Volkmar,
bingo, did not think of that.
Thanks,
Marko
Volkmar Glauche wrote:
> Hi Marco,
>
> you might want to check whether there is a spm_defaults.m outside the S=
PM8 folder on your MATLAB path. With the last set of updates, some previo=
usly hardcoded defaults have moved into spm_defaults.m. If your version o=
f spm_defaults.m is missing them, this could cause such an error message.
>
> Best,
>
> Volkmar
>
--=20
____________________________________________________
PD Dr. med. Marko Wilke
Facharzt f=FCr Kinder- und Jugendmedizin
Leiter, Experimentelle P=E4diatrische Neurobildgebung
Universit=E4ts-Kinderklinik
Abt. III (Neurop=E4diatrie)
Marko Wilke, MD, PhD
Pediatrician
Head, Experimental Pediatric Neuroimaging
University Children's Hospital
Dept. III (Pediatric Neurology)
Hoppe-Seyler-Str. 1
D - 72076 T=FCbingen, Germany
Tel. +49 7071 29-83416
Fax +49 7071 29-5473
[log in to unmask]
http://www.medizin.uni-tuebingen.de/kinder/epn
____________________________________________________
=========================================================================
Date: Tue, 24 May 2011 20:30:47 +0800
Reply-To: =?gb2312?B?s8K4+yAg?= <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?gb2312?B?s8K4+yAg?= <[log in to unmask]>
Subject: convolution matrix =?gb2312?Q?=A1=AEK=A1=AF?=
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary="0-990975817-1306240247=:78821"
Message-ID: <[log in to unmask]>
--0-990975817-1306240247=:78821
Content-Type: text/plain; charset=gb2312
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To Whom It May Concern:
I am new on fMRI from China. Sorry to bother you with some basis questions.
As we know, what any fMRI analysis program does is this: It takes the time =
series of stimulus onsets, and convolves it with the HRF. This gives a *pre=
diction* of the blood flow response that we should get a given voxel, if th=
at voxel is responding to the stimuli. Then, we take that prediction, and g=
o and compare it against the measured data. And we see how well they match.=
However, in some other paper, for example =A1=B0Analysis of fMRI Time-Seri=
es Revisited=A1=B1 from professor J.FRISTON, may use =A1=B0a convolution ma=
trix =A1=AEK=A1=AF =A1=AEsee attachment=A1=AF =A1=B1 I wonder, does the =A1=
=AEK=A1=AF matrix used here can represent the HRF convolved? Or, it only re=
presents temporally smooth? If I make sense, if =A1=AEK=A1=AF only means te=
mporally smooth, the X matrix here should be already convolved with HRF. Mo=
reover, I can not find more detail information about the =A1=AEK=A1=AF matr=
ix. I want to know how to represent =A1=AEK=A1=AF in mathematics. All in al=
l, I wonder what =A1=AEK=A1=AF is and how to
represent =A1=AEK=A1=AF.
Long time confused with these questions. Really look forward your response.
--0-990975817-1306240247=:78821
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Content-Transfer-Encoding: quoted-printable
<table cellspacing=3D"0" cellpadding=3D"0" border=3D"0" ><tr><td valign=3D"=
top" style=3D"font: inherit;"><P style=3D"TEXT-ALIGN: left; MARGIN: 0cm 0cm=
0pt; TEXT-AUTOSPACE: ; mso-layout-grid-align: none" class=3DMsoNormal alig=
n=3Dleft><FONT face=3D"Times New Roman"><SPAN class=3Dquestion-title><B><SP=
AN style=3D"FONT-SIZE: 11.5pt; mso-font-kerning: 18.0pt" lang=3DEN-US>To Wh=
om It May Concern:</SPAN></B></SPAN><SPAN style=3D"FONT-FAMILY: 'Courier Ne=
w'; FONT-SIZE: 12pt; mso-font-kerning: 0pt; mso-bidi-font-family: 'Times Ne=
w Roman'" lang=3DEN-US><?xml:namespace prefix =3D o ns =3D "urn:schemas-mic=
rosoft-com:office:office" /><o:p></o:p></SPAN></FONT></DIV>
<P style=3D"TEXT-INDENT: 21pt; MARGIN: 0cm 0cm 0pt; mso-char-indent-count: =
2.0" class=3DMsoNormal><SPAN lang=3DEN-US><FONT size=3D3><FONT face=3D"Time=
s New Roman">I am new on fMRI from <?xml:namespace prefix =3D st1 ns =3D "u=
rn:schemas-microsoft-com:office:smarttags" /><st1:country-region w:st=3D"on=
"><st1:place w:st=3D"on">China</st1:place></st1:country-region>. Sorry to b=
other you with some basis questions.<o:p></o:p></FONT></FONT></SPAN></DIV>
<P style=3D"TEXT-INDENT: 21pt; MARGIN: 0cm 0cm 0pt; mso-char-indent-count: =
2.0" class=3DMsoNormal><SPAN lang=3DEN-US><FONT size=3D3><FONT face=3D"Time=
s New Roman">As we know, what any fMRI analysis program does is this: It ta=
kes the time series of stimulus onsets, and convolves it with the HRF. This=
gives a *prediction* of the blood flow response that we should get a given=
voxel, if that voxel is responding to the stimuli. Then, we take that pred=
iction, and go and compare it against the measured data. And we see how wel=
l they match. However, in some other paper, for example =A1=B0<I style=3D"m=
so-bidi-font-style: normal">Analysis of fMRI Time-Series Revisited</I>=A1=
=B1 from professor J.FRISTON, may use =A1=B0a convolution matrix =A1=AEK=A1=
=AF =A1=AEsee attachment=A1=AF </FONT></FONT><FONT size=3D3><FONT face=3D"T=
imes New Roman">=A1=B1 I wonder, does the =A1=AEK=A1=AF matrix used here ca=
n represent the HRF convolved? Or, it only represents temporally smooth? If=
I make sense, if =A1=AEK=A1=AF only means
temporally smooth, the X matrix here should be already convolved with HRF.=
Moreover, I can not find more detail information about the =A1=AEK=A1=AF m=
atrix. I want to know how to represent =A1=AEK=A1=AF in mathematics. All in=
all, I wonder what =A1=AEK=A1=AF is and how to represent =A1=AEK=A1=AF.<o:=
p></o:p></FONT></FONT></SPAN></DIV>
<P style=3D"TEXT-INDENT: 21pt; MARGIN: 0cm 0cm 0pt; mso-char-indent-count: =
2.0" class=3DMsoNormal><SPAN lang=3DEN-US><FONT size=3D3><FONT face=3D"Time=
s New Roman">Long time confused with these questions. Really look forward y=
our response.<o:p></o:p></FONT></FONT></SPAN></DIV></td></tr></table>
--0-990975817-1306240247=:78821--
=========================================================================
Date: Tue, 24 May 2011 10:54:46 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: SPM 8 Flexible Factorial Design Question
Comments: To: Henrike Hemingway <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=002354530970dee77704a406c427
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--002354530970dee77704a406c427
Content-Type: text/plain; charset=windows-1252
Content-Transfer-Encoding: quoted-printable
As you noted, the con_* at the second level is identical. This is not
surprising as the data you are asking about is the same. What is different
is the variance terms between the models.
From my expierance the model with 4 conditions is wrong. The reason that it
is wrong is that the error term represents the unexplained variance between
your 4 categories (not the unexplained variance of all conditions). The
model with 5 conditions has an error term that represents the unexplained
variance of all the conditions.
Best Regards, Donald McLaren
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital an=
d
Harvard Medical School
Office: (773) 406-2464
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773=
)
406-2464 or email.
On Tue, May 24, 2011 at 7:01 AM, Henrike Hemingway <[log in to unmask]
e
> wrote:
> Dear SPMers,
>
> I have question regarding the flexible factorial design as implemented in
> SPM8.
>
> I have realized an experiment with 5 conditions for each subject (4 emoti=
on
> conditions, 1 neutral condition). I was interested in the difference betw=
een
> the emotion and the neutral conditions.Therefore, I set up the 2nd level
> analysis using a flexible factorial design in SPM8 in two different ways.
> The main effect of subject and the main effect of condition were estimate=
d
> in both of the design matrices.
>
> In the first design matrix I specified the effect of condition with 5
> levels, including the con images of all 5 conditions separately. The
> contrasts for each of the 4 conditions > neutral were computed on the 2nd
> level. For the second flexible factorial design I computed the difference=
s
> between each of the 4 conditions > neutral on the first level and by this
> didn=92t have to estimate difference contrasts on the 2nd level. Thus, I
> specified the effect of condition with only 4 levels each representing th=
e
> difference of the condition > neutral and estimated the main effect for e=
ach
> of the four conditions.
>
> The results for the contrasts representing the same difference (Condition=
>
> Neutral), however, were not similar across both designs as you can see in
> the attached screen shots. The model including the difference contrasts
> computed on the first level resulted in much higher t-values and larger
> number of voxels in the clusters of interest. After some research in the
> archives of the SPM mailing list I still have not found an explanation fo=
r
> the diverging results. Though I found some information about a comparable
> difference observed when comparing designs explicitly modeling the subjec=
t
> factor or not.
>
> Does anyone know what exactly is causing the pronounced difference in bot=
h
> designs? When looking at the con images computed on the 2nd level they
> contain the exact same values in each voxel. Is one of the models
> practically wrong?
>
> I would be glad if anyone could help me out with more detailed informatio=
n
> or helpful links for further readings on that issue.
>
> Thanks a lot.
>
> Henrike
>
>
--002354530970dee77704a406c427
Content-Type: text/html; charset=windows-1252
Content-Transfer-Encoding: quoted-printable
As you noted, the con_* at the second level is identical. This is not surpr=
ising as the data you are asking about is the same. What is different is th=
e variance terms between the models. <br><br>From my expierance the model w=
ith 4 conditions is wrong. The reason that it is wrong is that the error te=
rm represents the unexplained variance between your 4 categories (not the u=
nexplained variance of all conditions). The model with 5 conditions has an =
error term that represents the unexplained variance of all the conditions.<=
br clear=3D"all">
<br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdoctoral Research Fellow, GRECC,=
Bedford VA<br>Research Fellow, Department of Neurology, Massachusetts Gene=
ral Hospital and Harvard Medical School<br>
Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which may =
contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED=
and which is intended only for the use of the individual or entity named a=
bove. If the reader of the e-mail is not the intended recipient or the empl=
oyee or agent responsible for delivering it to the intended recipient, you =
are hereby notified that you are in possession of confidential and privileg=
ed information. Any unauthorized use, disclosure, copying or the taking of =
any action in reliance on the contents of this information is strictly proh=
ibited and may be unlawful. If you have received this e-mail unintentionall=
y, please immediately notify the sender via telephone at (773) 406-2464 or =
email.<br>
<br><br><div class=3D"gmail_quote">On Tue, May 24, 2011 at 7:01 AM, Henrike=
Hemingway <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]
">[log in to unmask]</a>></span> wrote:<br><blockquote class=3D"gm=
ail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(2=
04, 204, 204); padding-left: 1ex;">
Dear SPMers,<br>
<br>
I have question regarding the flexible factorial design as implemented in S=
PM8.<br>
<br>
I have realized an experiment with 5 conditions for each subject (4 emotion=
conditions, 1 neutral condition). I was interested in the difference betwe=
en the emotion and the neutral conditions.Therefore, I set up the 2nd level=
analysis using a flexible factorial design in SPM8 in two different ways. =
The main effect of subject and the main effect of condition were estimated =
in both of the design matrices.<br>
<br>
In the first design matrix I specified the effect of condition with 5 level=
s, including the con images of all 5 conditions separately. The contrasts f=
or each of the 4 conditions > neutral were computed on the 2nd level. Fo=
r the second flexible factorial design I computed the differences between e=
ach of the 4 conditions > neutral on the first level and by this didn=92=
t have to estimate difference contrasts on the 2nd level. Thus, I specified=
the effect of condition with only 4 levels each representing the differenc=
e of the condition > neutral and estimated the main effect for each of t=
he four conditions.<br>
<br>
The results for the contrasts representing the same difference (Condition &=
gt; Neutral), however, were not similar across both designs as you can see =
in the attached screen shots. The model including the difference contrasts =
computed on the first level resulted in much higher t-values and larger num=
ber of voxels in the clusters of interest. After some research in the archi=
ves of the SPM mailing list I still have not found an explanation for the d=
iverging results. Though I found some information about a comparable differ=
ence observed when comparing designs explicitly modeling the subject factor=
or not.<br>
<br>
Does anyone know what exactly is causing the pronounced difference in both =
designs? When looking at the con images computed on the 2nd level they cont=
ain the exact same values in each voxel. Is one of the models practically w=
rong?<br>
<br>
I would be glad if anyone could help me out with more detailed information =
or helpful links for further readings on that issue.<br>
<br>
Thanks a lot.<br>
<font color=3D"#888888"><br>
Henrike<br>
<br>
</font></blockquote></div><br>
--002354530970dee77704a406c427--
=========================================================================
Date: Tue, 24 May 2011 10:58:41 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: How to do PPI GLM estimation and contrasts using matlab script
Comments: To: Yang Hu <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=00151747af3ee20fde04a406d2e6
Message-ID: <[log in to unmask]>
--00151747af3ee20fde04a406d2e6
Content-Type: text/plain; charset=ISO-8859-1
I would suggest that you download the PPI toolbox located at
http://www.martinos.org/~mclaren/ftp/Utilities_DGM.
Instructions can be found at http://brainmap.wisc.edu/PPI
For PPI, using the standard SPM approach, set the method field to 'trad'.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Tue, May 24, 2011 at 4:20 AM, Yang Hu <[log in to unmask]> wrote:
> Dear all,
> Having set up PPI.mat (PPI variables) of each individual by
> spm_peb_ppi.m, I would like to do PPI GLM estimation (3 regressors in the
> design matrix: PPI.ppi, PPI.Y, PPI.P)and contrasts (e.g. [1 0 0 0]) for each
> individual. Could someone provide me with the matlab script to do the two
> above steps? Any suggestions are welcome. Thanks a lot!
>
>
> Best wishes,
> Yang Hu
>
> ICN, ECNU, Shanghai, China PR
>
--00151747af3ee20fde04a406d2e6
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
I would suggest that you download the PPI toolbox located at <a href=3D"htt=
p://www.martinos.org/~mclaren/ftp/Utilities_DGM">http://www.martinos.org/~m=
claren/ftp/Utilities_DGM</a>.<br><br>Instructions can be found at <a href=
=3D"http://brainmap.wisc.edu/PPI">http://brainmap.wisc.edu/PPI</a><br>
<br>For PPI, using the standard SPM approach, set the method field to '=
trad'.<br clear=3D"all"><br>Best Regards, Donald McLaren<br>=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdo=
ctoral Research Fellow, GRECC, Bedford VA<br>
Research Fellow, Department of Neurology, Massachusetts General Hospital an=
d Harvard Medical School<br>Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDEN=
TIAL INFORMATION which may contain PROTECTED HEALTHCARE INFORMATION and may=
also be LEGALLY PRIVILEGED and which is intended only for the use of the i=
ndividual or entity named above. If the reader of the e-mail is not the int=
ended recipient or the employee or agent responsible for delivering it to t=
he intended recipient, you are hereby notified that you are in possession o=
f confidential and privileged information. Any unauthorized use, disclosure=
, copying or the taking of any action in reliance on the contents of this i=
nformation is strictly prohibited and may be unlawful. If you have received=
this e-mail unintentionally, please immediately notify the sender via tele=
phone at (773) 406-2464 or email.<br>
<br><br><div class=3D"gmail_quote">On Tue, May 24, 2011 at 4:20 AM, Yang Hu=
<span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">huyang200606=
@126.com</a>></span> wrote:<br><blockquote class=3D"gmail_quote" style=
=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); p=
adding-left: 1ex;">
Dear all,<br>
=A0 =A0Having set up PPI.mat (PPI variables) of each individual by spm_peb=
_ppi.m, I would like to do PPI GLM estimation (3 regressors in the design m=
atrix: PPI.ppi, PPI.Y, PPI.P)and contrasts (e.g. [1 0 0 0]) for each indivi=
dual. Could someone provide me with the matlab script to do the two above s=
teps? Any suggestions are welcome. Thanks a lot!<br>
<br>
<br>
Best wishes,<br>
Yang Hu<br>
<br>
ICN, ECNU, Shanghai, China PR<br>
</blockquote></div><br>
--00151747af3ee20fde04a406d2e6--
=========================================================================
Date: Tue, 24 May 2011 11:06:59 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: export betas over multiple coordinates
Comments: To: SUBSCRIBE SPM Yihui Hung <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=00151747af3e96b20b04a406f035
Message-ID: <[log in to unmask]>
--00151747af3e96b20b04a406f035
Content-Type: text/plain; charset=ISO-8859-1
See
http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=ind1103&L=SPM&P=R16468&I=-3&d=No+Match%3BMatch%3BMatches
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Wed, May 18, 2011 at 10:25 AM, SUBSCRIBE SPM Yihui Hung <
[log in to unmask]> wrote:
> Hello,
> I wonder how to export the betas over the coordinates which showed a
> significant effect. I know how to export one beta of one coordinate which
> showed a significant effect. However, I would like to know how to export
> betas over all of the coordinates in the statistic table at once.
> Thank you for any advice!
>
> Sincerely,
> Yihui
>
--00151747af3e96b20b04a406f035
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
See <a href=3D"http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3Dind1103&L=
=3DSPM&P=3DR16468&I=3D-3&d=3DNo+Match%3BMatch%3BMatches">http:/=
/www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3Dind1103&L=3DSPM&P=3DR16468&=
amp;I=3D-3&d=3DNo+Match%3BMatch%3BMatches</a><br clear=3D"all">
<br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdoctoral Research Fellow, GRECC,=
Bedford VA<br>Research Fellow, Department of Neurology, Massachusetts Gene=
ral Hospital and Harvard Medical School<br>
Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which may =
contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED=
and which is intended only for the use of the individual or entity named a=
bove. If the reader of the e-mail is not the intended recipient or the empl=
oyee or agent responsible for delivering it to the intended recipient, you =
are hereby notified that you are in possession of confidential and privileg=
ed information. Any unauthorized use, disclosure, copying or the taking of =
any action in reliance on the contents of this information is strictly proh=
ibited and may be unlawful. If you have received this e-mail unintentionall=
y, please immediately notify the sender via telephone at (773) 406-2464 or =
email.<br>
<br><br><div class=3D"gmail_quote">On Wed, May 18, 2011 at 10:25 AM, SUBSCR=
IBE SPM Yihui Hung <span dir=3D"ltr"><<a href=3D"mailto:a489930026@yahoo=
.com.tw">[log in to unmask]</a>></span> wrote:<br><blockquote class=
=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid=
rgb(204, 204, 204); padding-left: 1ex;">
Hello,<br>
I wonder how to export the betas over the coordinates which showed a signif=
icant effect. I know how to export one beta of one coordinate which showed =
a significant effect. However, I would like to know how to export betas ove=
r all of the coordinates in the statistic table at once.<br>
Thank you for any advice!<br>
<br>
Sincerely,<br>
<font color=3D"#888888">Yihui<br>
</font></blockquote></div><br>
--00151747af3e96b20b04a406f035--
=========================================================================
Date: Tue, 24 May 2011 13:50:58 -0400
Reply-To: Anderson Winkler <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Anderson Winkler <[log in to unmask]>
Subject: Re: convolution matrix =?GB2312?Q?=A1=AEK=A1=AF?=
Comments: To: =?GB2312?B?s8K4+w==?= <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative;
boundary="------------050806020102040807020106"
Message-ID: <[log in to unmask]>
--------------050806020102040807020106
Content-Type: text/plain; charset="GB2312"
Content-Transfer-Encoding: quoted-printable
X-MIME-Autoconverted: from 8bit to quoted-printable by bifur.jiscmail.ac.uk id p4OHp1jx019650
Dear =B3=C2=B8=FB
I think K is a Toeplitz matrix: http://en.wikipedia.org/wiki/Toeplitz_mat=
rix
It has some nice properties and I believe it was chosen here for ease of
implementation, since a computationally expensive convolution can then
be done as a simple matrix multiplication in MATLAB, without even the
need to Fourier-transform the data.
You may also be interested in reading the paper that followed this one
that you are reading: http://dx.doi.org/10.1006/nimg.1995.1023
Hope this helps!
All the best,
Anderson
On 05/24/2011 08:30 AM, =B3=C2=B8=FB wrote:
>
> *To Whom It May Concern:*
>
> I am new on fMRI from China. Sorry to bother you with some basis
> questions.
>
> As we know, what any fMRI analysis program does is this: It takes the
> time series of stimulus onsets, and convolves it with the HRF. This
> gives a *prediction* of the blood flow response that we should get a
> given voxel, if that voxel is responding to the stimuli. Then, we take
> that prediction, and go and compare it against the measured data. And
> we see how well they match. However, in some other paper, for example
> =A1=B0/Analysis of fMRI Time-Series Revisited/=A1=B1 from professor J.F=
RISTON,
> may use =A1=B0a convolution matrix =A1=AEK=A1=AF =A1=AEsee attachment=A1=
=AF =A1=B1 I wonder, does
> the =A1=AEK=A1=AF matrix used here can represent the HRF convolved? Or,=
it only
> represents temporally smooth? If I make sense, if =A1=AEK=A1=AF only me=
ans
> temporally smooth, the X matrix here should be already convolved with
> HRF. Moreover, I can not find more detail information about the =A1=AEK=
=A1=AF
> matrix. I want to know how to represent =A1=AEK=A1=AF in mathematics. A=
ll in
> all, I wonder what =A1=AEK=A1=AF is and how to represent =A1=AEK=A1=AF.
>
> Long time confused with these questions. Really look forward your
> response.
>
--------------050806020102040807020106
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Content-Transfer-Encoding: quoted-printable
X-MIME-Autoconverted: from 8bit to quoted-printable by bifur.jiscmail.ac.uk id p4OHp1jx019650
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html>
<head>
<meta content=3D"text/html; charset=3DGB2312" http-equiv=3D"Content-T=
ype">
</head>
<body bgcolor=3D"#ffffff" text=3D"#000000">
Dear =B3=C2=B8=FB<br>
<br>
I think K is a Toeplitz matrix:
<a class=3D"moz-txt-link-freetext" href=3D"http://en.wikipedia.org/wi=
ki/Toeplitz_matrix">http://en.wikipedia.org/wiki/Toeplitz_matrix</a><br>
It has some nice properties and I believe it was chosen here for
ease of implementation, since a computationally expensive
convolution can then be done as a simple matrix multiplication in
MATLAB, without even the need to Fourier-transform the data.<br>
<br>
You may also be interested in reading the paper that followed this
one that you are reading: <a class=3D"moz-txt-link-freetext" href=3D"=
http://dx.doi.org/10.1006/nimg.1995.1023">http://dx.doi.org/10.1006/nimg.=
1995.1023</a><br>
<br>
Hope this helps!<br>
<br>
All the best,<br>
<br>
Anderson<br>
<br>
<br>
On 05/24/2011 08:30 AM, =B3=C2=B8=FB wrote:
<blockquote cite=3D"mid:[log in to unmask]"
type=3D"cite">
<table border=3D"0" cellpadding=3D"0" cellspacing=3D"0">
<tbody>
<tr>
<td style=3D"font: inherit;" valign=3D"top">
<p style=3D"text-align: left; margin: 0cm 0cm 0pt;"
class=3D"MsoNormal" align=3D"left"><font face=3D"Times Ne=
w
Roman"><span class=3D"question-title"><b><span
style=3D"font-size: 11.5pt;" lang=3D"EN-US">To Wh=
om
It May Concern:</span></b></span><span
style=3D"font-family: 'Courier New'; font-size: 12pt;=
"
lang=3D"EN-US"><o:p></o:p></span></font>
</p>
<p style=3D"text-indent: 21pt; margin: 0cm 0cm 0pt;"
class=3D"MsoNormal"><span lang=3D"EN-US"><font size=3D"3"=
><font
face=3D"Times New Roman">I am new on fMRI from <st1=
:country-region
w:st=3D"on"><st1:place w:st=3D"on">China</st1:pla=
ce></st1:country-region>.
Sorry to bother you with some basis questions.<o:p>=
</o:p></font></font></span>
</p>
<p style=3D"text-indent: 21pt; margin: 0cm 0cm 0pt;"
class=3D"MsoNormal"><span lang=3D"EN-US"><font size=3D"3"=
><font
face=3D"Times New Roman">As we know, what any fMRI
analysis program does is this: It takes the time
series of stimulus onsets, and convolves it with
the HRF. This gives a *prediction* of the blood
flow response that we should get a given voxel, if
that voxel is responding to the stimuli. Then, we
take that prediction, and go and compare it
against the measured data. And we see how well
they match. However, in some other paper, for
example =A1=B0<i style=3D"">Analysis of fMRI Time-S=
eries
Revisited</i>=A1=B1 from professor J.FRISTON, may=
use
=A1=B0a convolution matrix =A1=AEK=A1=AF =A1=AEsee =
attachment=A1=AF </font></font><font
size=3D"3"><font face=3D"Times New Roman">=A1=B1 I wo=
nder,
does the =A1=AEK=A1=AF matrix used here can represe=
nt the
HRF convolved? Or, it only represents temporally
smooth? If I make sense, if =A1=AEK=A1=AF only mean=
s
temporally smooth, the X matrix here should be
already convolved with HRF. Moreover, I can not
find more detail information about the =A1=AEK=A1=AF=
matrix.
I want to know how to represent =A1=AEK=A1=AF in
mathematics. All in all, I wonder what =A1=AEK=A1=AF=
is and
how to represent =A1=AEK=A1=AF.<o:p></o:p></font></=
font></span>
</p>
<p style=3D"text-indent: 21pt; margin: 0cm 0cm 0pt;"
class=3D"MsoNormal"><span lang=3D"EN-US"><font size=3D"3"=
><font
face=3D"Times New Roman">Long time confused with
these questions. Really look forward your
response.<o:p></o:p></font></font></span></p>
</td>
</tr>
</tbody>
</table>
</blockquote>
<br>
</body>
</html>
--------------050806020102040807020106--
=========================================================================
Date: Tue, 24 May 2011 11:28:42 -0700
Reply-To: Michael T Rubens <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michael T Rubens <[log in to unmask]>
Subject: Re: three questions about SPM8
Comments: To: =?UTF-8?B?6IOh5p2o?= <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf305e27dfb7c9c804a409c38b
Message-ID: <[log in to unmask]>
--20cf305e27dfb7c9c804a409c38b
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
2011/5/23 =E8=83=A1=E6=9D=A8 <[log in to unmask]>
> Dear Dr. Rubens,
> It's really helpful of your mail about making masked image via script=
.
> I have two additional questions about this script:
> 1) if my input image is 'spmT_0001.img', should the threshold be T-values=
?
>
Yes
> 2) if I want to limit my extent threshold (namely k voxels), how should I
> do with your script?
>
Try this: http://www.nitrc.org/projects/cluster_correct/
>
> Thanks a lot!
>
> Best wishes,
> Yang Hu
> --
>
> Yang Hu, M.S. candidate
>
> functional MRI Unit, Institute of Cognitive Neuroscience;
>
> Department of Psychology, School of Psychology and Cognitive Science,
>
> East China Normal University, Shanghai, China PR
>
> At 2011-05-24 03:16:58=EF=BC=8C"Michael T Rubens" <[log in to unmask]> =
wrote:
>
> I see now, I made a mistake in the original code I sent. This line:
>
> YY =3D spm_vol(VV);
>
> should actually be:
>
> YY =3D spm_read_vols(VV);
>
>
> %%
>
> Cheers,
> Michael
> On Mon, May 23, 2011 at 11:03 AM, a489930026 <[log in to unmask]>wro=
te:
>
>> Dear Michael,
>>
>> Every step went smoothly until the step "YY(find(Y)) =3D 0" and then the=
it
>> showed "Assignment between unlike types is not allowed."
>>
>> Yihui
>>
>> ------------------------------
>> *=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A* Michael T Rubens <MikeRubens@gmai=
l.com>
>> *=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A* a489930026 <[log in to unmask]
tw>; spm <[log in to unmask]>
>> *=E5=AF=84=E4=BB=B6=E6=97=A5=E6=9C=9F=EF=BC=9A* 2011/5/24 (=E4=BA=8C) 1:=
26 AM
>> *=E4=B8=BB=E6=97=A8=EF=BC=9A* Re: =E5=9B=9E=E8=A6=86=EF=B9=95 [SPM] thre=
e questions about SPM8
>>
>> threshold needs to be>0. if your map is p values, then just do:
>>
>> Y =3D 1-Y; %now p =3D 1-p, so higher values are more significant.
>>
>> then set your p threshold as 1-threshold, so .95 =3D=3D .05
>>
>> Determining whether you use the mask inclusively or exlusively can be do=
ne
>> when you apply it, so:
>>
>> YY(find(Y)) =3D 0; % exclusive mask
>>
>> YY(find(~Y)) =3D 0; %inclusive mask
>>
>>
>> Try running each line separately (or within a script) to see where exact=
ly
>> the error is occurring.
>>
>>
>> Cheers,
>> Michael
>>
>> On Mon, May 23, 2011 at 12:48 AM, a489930026 <[log in to unmask]>wr=
ote:
>>
>> Dear Michael,
>>
>> Thank you for the advice. I did what you suggested but a result
>> "Assignment between unlike types is not allowed." What could be the prob=
lem?
>>
>> Please see the script below:
>>
>> *********************************************************
>> >> V=3D spm_vol('L:\2stlevel\wordVSblk\spmF_0001.img')
>> Y =3D spm_read_vols(V);
>>
>> threshold =3D 0; %any value you choose.
>>
>> Y(find(Y<threshold)) =3D 0;
>> Y(find(Y)) =3D 1;
>>
>> % Use mask
>>
>> VV =3D spm_vol('L:\2stlevel\radpos_sdXloca_sd\spmF_0001.img');
>> YY =3D spm_vol(VV);
>>
>> YY(find(Y)) =3D 0; %apply mask
>>
>> VV.fname =3D 'masked_image.img';
>> spm_write_vol(VV,YY);
>>
>> %% There ya go
>>
>> V =3D
>>
>> fname: 'L:\2stlevel\wordVSblk\spmF_0001.img'
>> mat: [4x4 double]
>> dim: [79 95 68]
>> dt: [16 0]
>> pinfo: [3x1 double]
>> n: [1 1]
>> descrip: 'SPM{F_[1.0,15.0]} - contrast 1: w-b'
>> private: [1x1 nifti]
>>
>> ??? Assignment between unlike types is not allowed.
>>
>> ************************************************************************=
*
>>
>> Besides, is the threshold a cutoff for the activation maps of the mask?
>> Specially, does setting threshold =3D 0.05 mean that the activated voxel=
sbelow p =3D0.05 are included. If not, how should I set a cutoff on the p
>> value, or it does matter?
>>
>> Moreover, how can I determine the mask is inclusive (i.e., the voxles in
>> the to-be-masked activation maps are within the volxels in the activatio=
n
>> maps of the mask) or exclusive (i.e., the voxles in the to-be-masked
>> activation maps are NOT within the volxels in the activation maps of the
>> mask).
>> Thank you very much!
>>
>> Sincerely,
>> Yihui
>>
>>
>>
>>
>>
>> ------------------------------
>> *=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A* Michael T Rubens <MikeRubens@gmai=
l.com>
>> *=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A* SUBSCRIBE SPM Yihui Hung <a489930=
[log in to unmask]>
>> *=E5=89=AF=E6=9C=AC=EF=BC=9A* [log in to unmask]
>> *=E5=AF=84=E4=BB=B6=E6=97=A5=E6=9C=9F=EF=BC=9A* 2011/5/23 (=E4=B8=80) 10=
:19 AM
>> *=E4=B8=BB=E6=97=A8=EF=BC=9A* Re: [SPM] three questions about SPM8
>>
>> when you say you tried to use the contrast as a mask, did you just use t=
he
>> raw contrast or did you binarize it? If you did the former than it is
>> clear why you had no inmask voxels since any non-zero voxels would all b=
e
>> seen as part of the mask. So, what you want to do is load the mask, appl=
y a
>> threshold and binarize it by setting anything below the threshold to 0,
>> and anything above to 1 (though the latter may not be completely necesar=
y).
>> Then, you could just use that mask to mask out the resulting contrast ma=
p
>> from the other analysis. Here is code to do it:
>>
>>
>> %Make mask
>>
>> V =3D spm_vol('contrast_image_2turn_into_mask')
>> Y =3D spm_read_vols(V);
>>
>> threshold =3D X; %any value you choose.
>>
>> Y(find(Y<threshold)) =3D 0;
>> Y(find(Y)) =3D 1;
>>
>> % Use mask
>>
>> VV =3D spm_vol('contrast_image_2mask');
>> YY =3D spm_vol(VV);
>>
>> YY(find(Y)) =3D 0; %apply mask
>>
>> VV.fname =3D 'masked_image.img';
>> spm_write_vol(VV,YY);
>>
>> %% There ya go
>>
>> Cheers,
>> Michael
>>
>> On Sun, May 22, 2011 at 9:58 AM, SUBSCRIBE SPM Yihui Hung <
>> [log in to unmask]> wrote:
>>
>> Hello,
>>
>> I used SPM8 for my experiment. I manipulated three factors (e.g., factor
>> A, B, C) in my experiment. The activation maps under factor A was used a=
s a
>> mask to constrain the effects of factor B and factor C. The problem is t=
hat
>> the factor A and factor B and factor C cannot be put in the same model a=
t
>> second level analysis. I tried to put the .img file resulting from facto=
r
>> A across participants in the =E2=80=9Cexplicit mask=E2=80=9D in the seco=
nd level analysis.
>> However, the estimation stopped by showing no inmask voxels. I searched
>> through forum and did not find any useful solutions. Can someone help me
>> out? Moreover, is the threshold masking related to the p value? If not, =
how
>> should I set criteria for the activation map of the mask?
>>
>> I did notice that one person in the forum suggested that one can create =
an
>> activation maps in which the factor B is modeled with the mask of factor
>> A in first level analysis. Then, submit the resulting .img file into
>> second level analysis. My question is how to create and save the imgfile=
.
>>
>> Finally, I posted a question regarding how to export beta values over
>> multiple coordinates a week ago. However, no one provide any answers. I
>> wonder whether it is due that no one has the answer or due to that there
>> already is an answer in the forum.
>>
>> Thank you for your patience and advice.
>> Sincerely,
>>
>> Yihui
>>
>>
>>
>>
>> --
>> Research Associate
>> Gazzaley Lab
>> Department of Neurology
>> University of California, San Francisco
>>
>>
>>
>>
>>
>> --
>> Research Associate
>> Gazzaley Lab
>> Department of Neurology
>> University of California, San Francisco
>>
>>
>>
>
>
> --
> Research Associate
> Gazzaley Lab
> Department of Neurology
> University of California, San Francisco
>
>
>
>
--=20
Research Associate
Gazzaley Lab
Department of Neurology
University of California, San Francisco
--20cf305e27dfb7c9c804a409c38b
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
<br><br><div class=3D"gmail_quote">2011/5/23 =E8=83=A1=E6=9D=A8 <span dir=
=3D"ltr"><<a href=3D"mailto:[log in to unmask]">[log in to unmask]</=
a>></span><br><blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt=
0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
<div>Dear Dr. Rubens,</div>
<div>=C2=A0=C2=A0=C2=A0 It's really helpful of your mail about making m=
asked image via script. I have two additional questions about this script:<=
/div>
<div>1) if=C2=A0my input image is 'spmT_0001.img', should the thres=
hold be T-values?</div></blockquote><div><br>Yes<br>=C2=A0</div><blockquote=
class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px=
solid rgb(204, 204, 204); padding-left: 1ex;">
<div>2) if I want to limit my extent threshold (namely k voxels), how shoul=
d I do with your script?</div></blockquote><div><br>Try this: <a href=3D"ht=
tp://www.nitrc.org/projects/cluster_correct/">http://www.nitrc.org/projects=
/cluster_correct/</a><br>
=C2=A0</div><blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt =
0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
<div>=C2=A0</div>
<div>=C2=A0=C2=A0=C2=A0 Thanks a lot!</div>
<div>=C2=A0</div>
<div>Best wishes,</div>
<div>Yang Hu=C2=A0=C2=A0<br></div>
<div>--<br>
<p>Yang Hu, M.S. candidate</p>
<p>functional MRI Unit, Institute of Cognitive Neuroscience; </p>
<p>Department of Psychology, School of Psychology and Cognitive Science, </=
p>
<p>East China Normal University, Shanghai, China PR=C2=A0</p></div><br>At 2=
011-05-24 03:16:58=EF=BC=8C"Michael=C2=A0T=C2=A0Rubens"=C2=A0<=
<a href=3D"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]
COM</a>> wrote:<br>
<blockquote style=3D"padding-left: 1ex; margin: 0px 0px 0px 0.8ex; border-l=
eft: 1px solid rgb(204, 204, 204);">I see now, I made a mistake in the orig=
inal code I sent. This line: <br><br><span><span>YY</span></span> =3D <span=
><span>spm</span></span>_vol(<span><span>VV</span></span>);<br>
<br>should actually be:<br><br><span><span>YY</span></span> =3D <span><span=
>spm</span></span>_read_vols(<span><span>VV</span></span>);<br><br><br>%%<b=
r><br>Cheers,<br>Michael<br>
<div class=3D"gmail_quote">On Mon, May 23, 2011 at 11:03 AM, a489930026 <sp=
an dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]" target=3D"_bl=
ank">[log in to unmask]</a>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"padding-left: 1ex; margin: 0pt 0=
pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204);">
<div>
<div style=3D"font-size: 12pt; color: rgb(0, 0, 0); font-family: arial,helv=
etica,sans-serif; background-color: rgb(255, 255, 255);">
<div><span>
<div>Dear Michael,</div>
<div><br></div>
<div>Every step went smoothly until the step "YY(find(Y)) =3D 0" =
and then the it showed "Assignment between unlike types is not allowed=
."</div>
<div><br></div>
<div>Yihui</div></span></div>
<div><br>
<blockquote style=3D"padding-left: 5px; margin-left: 5px; border-left: 2px =
solid rgb(16, 16, 255);">
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;">
<div style=3D"font-size: 12pt; font-family: 'times new roman','=
new york',times,serif;"><font face=3D"Arial" size=3D"2">
<hr size=3D"1">
<b><span style=3D"font-weight: bold;">=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A<=
/span></b> Michael T Rubens <<a href=3D"mailto:[log in to unmask]" tar=
get=3D"_blank">[log in to unmask]</a>><br><b><span style=3D"font-weigh=
t: bold;">=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A</span></b> a489930026 <<a=
href=3D"mailto:[log in to unmask]" target=3D"_blank">a489930026@yahoo=
.com.tw</a>>; spm <<a href=3D"mailto:[log in to unmask]" target=3D"_b=
lank">[log in to unmask]</a>><br>
<b><span style=3D"font-weight: bold;">=E5=AF=84=E4=BB=B6=E6=97=A5=E6=9C=9F=
=EF=BC=9A</span></b> 2011/5/24 (=E4=BA=8C) 1:26 AM<br><b><span style=3D"fon=
t-weight: bold;">=E4=B8=BB=E6=97=A8=EF=BC=9A</span></b> Re: =E5=9B=9E=E8=A6=
=86=EF=B9=95 [SPM] three questions about SPM8<br></font><br>
<div>threshold needs to be>0. if your map is p values, then just do:<br>=
<br>Y =3D 1-Y; %now p =3D 1-p, so higher values are more significant.<br><b=
r>then set your p threshold as 1-threshold, so .95 =3D=3D .05<br><br>Determ=
ining whether you use the mask inclusively or exlusively can be done when y=
ou apply it, so: <br>
<br><span><span>YY</span></span>(find(Y)) =3D 0; % exclusive mask<br><br>YY=
(find(~Y)) =3D 0; %inclusive mask<br><br><br>Try running each line separate=
ly (or within a script) to see where exactly the error is occurring.<br><br=
>
<br>Cheers,<br>Michael<br><br>
<div>On Mon, May 23, 2011 at 12:48 AM, a489930026 <span dir=3D"ltr"><<a =
href=3D"mailto:[log in to unmask]" rel=3D"nofollow" target=3D"_blank">=
[log in to unmask]</a>></span> wrote:<br>
<blockquote style=3D"padding-left: 1ex; margin: 0pt 0pt 0pt 0.8ex; border-l=
eft: 1px solid rgb(204, 204, 204);">
<div>
<div style=3D"font-size: 12pt; color: rgb(0, 0, 0); font-family: arial,helv=
etica,sans-serif; background-color: rgb(255, 255, 255);">
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><s=
pan>Dear Michael,</span></div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><s=
pan><br></span></div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;">Th=
ank you for the advice. I did what you suggested but a result "Assignm=
ent between unlike types is not allowed." What could be the problem?</=
div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><b=
r></div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;">Pl=
ease see the script below:</div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><b=
r></div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;">**=
*******************************************************</div>
<div>
<div>>> V=3D <span><span>spm</span></span>_vol('L:\2<span><span>s=
tlevel</span></span>\<span><span>wordVSblk</span></span>\<span><span>spmF</=
span></span>_0001.<span><span>img</span></span>')</div><div class=3D"im=
">
<div>Y =3D <span><span>spm</span></span>_read_vols(V);</div>
<div><br></div>
<div>threshold =3D 0; %any value you choose.</div>
<div><br></div>
<div>Y(find(Y<threshold)) =3D 0;</div>
<div>Y(find(Y)) =3D 1;</div>
<div><br></div>
<div>% Use mask</div>
<div><br></div>
</div><div><span><span>VV</span></span> =3D <span><span>spm</span></span>_v=
ol('L:\2<span><span>stlevel</span></span>\<span><span>radpos</span></sp=
an>_<span><span>sdXloca</span></span>_<span><span>sd</span></span>\<span><s=
pan>spmF</span></span>_0001.<span><span>img</span></span>');</div>
<div class=3D"im">
<div><span><span>YY</span></span> =3D <span><span>spm</span></span>_vol(<sp=
an><span>VV</span></span>);</div>
<div><br></div>
<div><span><span>YY</span></span>(find(Y)) =3D 0; %apply mask</div>
<div><br></div>
<div><span><span>VV</span></span>.<span><span>fname</span></span> =3D '=
masked_image.<span><span>img</span></span>';</div>
<div><span><span>spm</span></span>_write_vol(<span><span>VV</span></span>,<=
span><span>YY</span></span>);</div>
<div><br></div>
<div>%% There ya go</div>
<div><br></div>
</div><div>V =3D=C2=A0</div>
<div><br></div>
<div>=C2=A0 =C2=A0 =C2=A0 <span><span>fname</span></span>: 'L:\2<span><=
span>stlevel</span></span>\<span><span>wordVSblk</span></span>\<span><span>=
spmF</span></span>_0001.<span><span>img</span></span>'</div>
<div>=C2=A0 =C2=A0 =C2=A0 =C2=A0 mat: [4x4 double]</div>
<div>=C2=A0 =C2=A0 =C2=A0 =C2=A0 dim: [79 95 68]</div>
<div>=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0<span><span>dt</span></span>: [16 0]=
</div>
<div>=C2=A0 =C2=A0 =C2=A0 <span><span>pinfo</span></span>: [3x1 double]</di=
v>
<div>=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 n: [1 1]</div>
<div>=C2=A0 =C2=A0 <span><span>descrip</span></span>: 'SPM{F_[1.0,15.0]=
} - contrast 1: w-b'</div>
<div>=C2=A0 =C2=A0 private: [1x1 <span><span>nifti</span></span>]</div>
<div><br></div>
<div>??? Assignment between unlike types is not allowed.</div>
<div><br></div>
<div>**********************************************************************=
***</div>
<div><br></div>
<div>Besides, is the threshold a cutoff for the activation maps of the mask=
? Specially, does setting threshold =3D 0.05 mean that the activated <span>=
<span>voxels</span></span> below p =3D0.05 are included. If not, how should=
I set a cutoff on the p value, or it does matter?=C2=A0</div>
<div><br></div>
<div>Moreover, how can I determine the mask is inclusive (i.e., the <span><=
span>voxles</span></span> in the to-be-masked activation maps are within th=
e <span><span>volxels</span></span> in the activation maps of the mask) or =
exclusive=C2=A0(i.e., the <span><span>voxles</span></span> in the to-be-mas=
ked activation maps are NOT within the <span><span>volxels</span></span> in=
<span>the activation</span> maps of the mask).=C2=A0</div>
<div>Thank you very much!</div>
<div><br></div>
<div>Sincerely,</div>
<div><span><span>Yihui</span></span></div></div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;">=
=C2=A0</div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><b=
r></div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><b=
r></div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><b=
r></div>
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;"><b=
r>
<blockquote style=3D"padding-left: 5px; margin-left: 5px; border-left: 2px =
solid rgb(16, 16, 255);">
<div style=3D"font-size: 12pt; font-family: arial,helvetica,sans-serif;">
<div style=3D"font-size: 12pt;"><font face=3D"Arial" size=3D"2">
<hr size=3D"1">
<b><span style=3D"font-weight: bold;">=E5=AF=84=E4=BB=B6=E8=80=85=EF=BC=9A<=
/span></b> Michael T Rubens <<a href=3D"mailto:[log in to unmask]" rel=
=3D"nofollow" target=3D"_blank">[log in to unmask]</a>><br><b><span st=
yle=3D"font-weight: bold;">=E6=94=B6=E4=BB=B6=E8=80=85=EF=BC=9A</span></b> =
SUBSCRIBE <span><span>SPM</span></span> <span><span>Yihui</span></span> Hun=
g <<a href=3D"mailto:[log in to unmask]" rel=3D"nofollow" target=3D=
"_blank">[log in to unmask]</a>><br>
<b><span style=3D"font-weight: bold;">=E5=89=AF=E6=9C=AC=EF=BC=9A</span></b=
> <a href=3D"mailto:[log in to unmask]" rel=3D"nofollow" target=3D"_blank">=
[log in to unmask]</a><br><b><span style=3D"font-weight: bold;">=E5=AF=84=
=E4=BB=B6=E6=97=A5=E6=9C=9F=EF=BC=9A</span></b> 2011/5/23 (=E4=B8=80) 10:19=
AM<br>
<b><span style=3D"font-weight: bold;">=E4=B8=BB=E6=97=A8=EF=BC=9A</span></b=
> Re: [<span><span>SPM</span></span>] three questions about <span><span>SPM=
</span></span>8<br></font><br>
<div>when you say you tried to use the contrast as a mask, did you just use=
the raw contrast or did you <span><span>binarize</span></span> it? If you =
did the former than it is clear why you had no <span><span>inmask</span></s=
pan> <span><span>voxels</span></span> since any non-zero <span><span>voxels=
</span></span> would all be seen as part of the mask. So, what you want to =
do is load the mask, apply a threshold and <span><span>binarize</span></spa=
n> it by setting anything below the threshold to 0, and anything above to 1=
(though the latter may not be completely <span><span>necesary</span></span=
>). Then, you could just use that mask to mask out the resulting contrast m=
ap from the other analysis. Here is code to do it:<div>
<div></div><div class=3D"h5"><br><br>%Make mask<br><br>V =3D <span><span>sp=
m</span></span>_vol('contrast_image_2turn_into_mask')<br>Y =3D <spa=
n><span>spm</span></span>_read_vols(V);<br><br>threshold =3D X; %any value =
you choose.<br>
<br>Y(find(Y<threshold)) =3D 0;<br>Y(find(Y)) =3D 1;<br><br>% Use mask<b=
r><br><span><span>VV</span></span> =3D <span><span>spm</span></span>_vol(&#=
39;contrast_image_2mask');<br><span><span>YY</span></span> =3D <span><s=
pan>spm</span></span>_vol(<span><span>VV</span></span>);<br>
<br><span><span>YY</span></span>(find(Y)) =3D 0; %apply mask<br><br><span><=
span>VV</span></span>.<span><span>fname</span></span> =3D 'masked_image=
.<span><span>img</span></span>';<br><span><span>spm</span></span>_write=
_vol(<span><span>VV</span></span>,<span><span>YY</span></span>);<br>
<br>%% There ya go<br><br>Cheers,<br>Michael<br><br>
<div>On Sun, May 22, 2011 at 9:58 AM, SUBSCRIBE <span><span>SPM</span></spa=
n> <span><span>Yihui</span></span> Hung <span dir=3D"ltr"><<a href=3D"ma=
ilto:[log in to unmask]" rel=3D"nofollow" target=3D"_blank">a489930026=
@yahoo.com.tw</a>></span> wrote:<br>
<blockquote style=3D"padding-left: 1ex; margin: 0pt 0pt 0pt 0.8ex; border-l=
eft: 1px solid rgb(204, 204, 204);">Hello,<br><br>I used <span><span>SPM</s=
pan></span>8 for my experiment. I manipulated three factors (e.g., factor A=
, B, C) in my experiment. The activation maps under factor A was used as a =
mask to constrain the effects of factor B and factor C. The problem is that=
the factor A and factor B and factor C cannot be put in the same model at =
second level analysis. I tried to put the .<span><span>img</span></span> fi=
le resulting from factor A across participants in the =E2=80=9Cexplicit mas=
k=E2=80=9D in the second level analysis. However, the estimation stopped by=
showing no <span><span>inmask</span></span> <span><span>voxels</span></spa=
n>. I searched through forum and did not find any useful solutions. Can som=
eone help me out? Moreover, is the threshold masking related to the p value=
? If not, how should I set criteria for the activation map of the mask?<br>
<br>I did notice that one person in the forum suggested that one can create=
an activation maps in which the factor B is <span><span>modeled</span></sp=
an> with the mask of factor A in first level analysis. Then, submit the res=
ulting .<span><span>img</span></span> file into second level analysis. My q=
uestion is how to create and save the <span><span>img</span></span> file.<b=
r>
<br>Finally, I posted a question regarding how to export beta values over m=
ultiple coordinates a week ago. However, no one provide any answers. I wond=
er whether it is due that no one has the answer or due to that there alread=
y is an answer in the forum.<br>
<br>Thank you for your patience and advice.<br>Sincerely,<br><font color=3D=
"#888888"><br><span><span>Yihui</span></span><br><br></font></blockquote></=
div><br><br clear=3D"all"><br>-- <br>Research Associate<br><span><span>Gazz=
aley</span></span> Lab<br>
Department of Neurology<br>University of California, San Francisco<br></div=
></div></div><br><br></div></div></blockquote></div></div></div></blockquot=
e></div><div><div></div><div class=3D"h5"><br><br clear=3D"all"><br>-- <br>
Research Associate<br>Gazzaley Lab<br>Department of Neurology<br>University=
of California, San Francisco<br></div></div></div><br><br></div></div></bl=
ockquote></div></div></div></blockquote></div><div><div></div><div class=3D=
"h5">
<br><br clear=3D"all"><br>-- <br>Research Associate<br>Gazzaley Lab<br>Depa=
rtment of Neurology<br>University of California, San Francisco<br></div></d=
iv></blockquote><br><br><span title=3D"neteasefooter"><span></span></span><=
/blockquote>
</div><br><br clear=3D"all"><br>-- <br>Research Associate<br>Gazzaley Lab<b=
r>Department of Neurology<br>University of California, San Francisco<br>
--20cf305e27dfb7c9c804a409c38b--
=========================================================================
Date: Tue, 24 May 2011 21:22:11 +0100
Reply-To: Deryk <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Deryk <[log in to unmask]>
Subject: Cluster level statistics for VBM
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Is it appropriate to interpret the cluster level statistics provided in t=
he results table for a VBM analysis?
=========================================================================
Date: Wed, 25 May 2011 05:49:18 +0100
Reply-To: David Yang <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: David Yang <[log in to unmask]>
Subject: SPECT transporter image analysis realted to DARTEL and BPM
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Dear all
Our subjects had SPECT transporter images(TRODAT for dopamine transporter=
s) and their T1 MRI images (for VBM analysis). We planed to perform corre=
lation analysis between such 2 kind of image modalities by WFU Biological=
Parametric Mapping Toolbox.
Since our MRI images were analysed by DARTEL related process, our SPECT i=
mages should also be analysed by DARTEL related ones.
According to previous discussion (https://www.jiscmail.ac.uk/cgi-bin/weba=
dmin?A2=3DSPM;3779f1d9.0909), we performed following analyses:
Step 1: Within subject coregistration: Use SPM function, Coreg:estimate (=
without reslicing) and we suspected the registration information would be=
stored in the header of source images (no other output would be found)=20=
Step 2: Routine DARTEL analysis for MRI data
Step 3: as performing the function, "DARTEL toolbox: normalise to MNI spa=
ce option" and use source images (SPECT) from Step 1.
For receptor/transporter binding potential images, I suspected we should =
choose Preserve Amount in Step 3 according to previous discussion:
http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3DSPM;f3f7b65.0901
I wondered if there was any mistake in our above analysis methods?
Furthermore, considering the image features of PET or even SPECT images, =
it might have to smooth such images with large amount (ex 12 mm compared =
to default 8 mm in DARTEL). I wonder if such was suitable if we wanted to=
perform further analysis by BPM that used both VBM and PET/SPECT images =
concurrently as in this subject:
http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3DSPM;dd737de1.1012
Thanks for any help!
Sincerely yours,
David
=========================================================================
Date: Wed, 25 May 2011 10:10:48 +0200
Reply-To: Stefanie Brassen <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Stefanie Brassen <[log in to unmask]>
Subject: PhD positions in imaging neuroscience in Hamburg / Germany
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RHIuIErDtnJnIEYuIERlYmF0aW4gKFZvcnNpdHplbmRlcikKRHIuIEFsZXhhbmRlciBLaXJzdGVp
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=========================================================================
Date: Wed, 25 May 2011 10:12:13 +0100
Reply-To: David Yang <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: David Yang <[log in to unmask]>
Subject: How to calculate parametric image of ligand-receptor binding in
SPECT images by SPM?
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
Dear SPMers:
We tried to calculate parametric image of dopamine transporter binding by=
SPECT and TRODAT under SPM8.
Every case had both SPECT and MRI images.
We had coregistered SPECT image to his own MRI images and then normalized=
SPECT images to MNI space by DARTEL toolbox: normalise to MNI space and =
related process.
We also made mask for cerebellum that served as reference region by MasBa=
r.
We wondered how to further calculate parametric BPND image of each SEPCT?=
Some reference, as "The application of statistical parametric mapping to =
123I-FP-CIT SPECT_NeuroImage 23 (2004) 956-966" suggested using "Proporti=
onal scaling which scales each image appropriately to a reference region"=
.=20
Another reference, as "A novel computer-assisted image analysis of [123I]=
=CE=B2-CIT SPECT images improves the diagnostic accuracy of parkinsonian =
disorders_Eur J Nucl Med Mol Imaging (2011) 38:702=E2=80=93710" suggested=
using "mask" method to calculate such.
However, we had several questions regarding these 2 methods:
1. It seems that "Proportional scaling" function was found in the "global=
normalisation" item when building up the statistical model and "explicit=
ly mask" was option of "Masking" also when building up the statistical mo=
del. How can I do both before building up the statistical model?
2. Is it possible to calculate parametric image by "imcal" function of SP=
M?
Thanks for any help~
Sincerely yours,
David
=========================================================================
Date: Wed, 25 May 2011 11:50:59 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: dipole waveforms | units
Comments: To: Lars Meyer <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Dear Lars,
It seems like the answer to your question is not that simple even for
your case where it's quite clear what's going on in terms of scaling.
I passed it to Fieldtrip developers who will look at how the units are
handled by their forward computation. When I hear back from them I'll
update you and the list.You can follow their progress via
http://bugzilla.fcdonders.nl/show_bug.cgi?id=3D686
Best,
Vladimir
On Mon, May 16, 2011 at 10:48 AM, Lars Meyer <[log in to unmask]> wrote:
> dear all,
>
> i am using spm_eeg_dipole_waveforms.m to retrieve dipole timecourses for =
two dipole priors in a vb-ecd- localisation. everything works fine, so no w=
orries there, but i was wondering on what the units of the dipole amplitude=
s are=E2=80=A6 i remember some older post on the exact same question, have =
talked to the asker, but it seems there is no answer yet.
>
> or is there a working solution from the programmers of the above function=
?
>
>
> thanks in advance, and all best,
> l.
>
>
>
>
> Lars Meyer
> Max Planck Institute for Human Cognitive & Brain Sciences
> Department of Neuropsychology
> Stephanstra=EF=AC=82e 1a
> 04103 Leipzig | Germany
>
> Office | +49 341 99 40 22 66
> Mail | [log in to unmask]
> Web | www.cbs.mpg.de/~lmeyer
>
=========================================================================
Date: Wed, 25 May 2011 13:00:26 +0100
Reply-To: Gareth Barnes <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Gareth Barnes <[log in to unmask]>
Subject: Re: dipole waveforms | units
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable
Message-ID: <03ad01cc1ad3$55a30370$00e90a50$@[log in to unmask]>
Hi Lars
For the record, and for MEG only :
It looks like (if the units of sensors are Tesla and measurement in mm) =
then the moments will be in nAm. (there is an extra scaling factor of =
1000 in the spm code).
I am also looking into the EEG case now.
Best
Gareth
-----Original Message-----
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] =
On Behalf Of Vladimir Litvak
Sent: 25 May 2011 11:51
To: [log in to unmask]
Subject: Re: [SPM] dipole waveforms | units
Dear Lars,
It seems like the answer to your question is not that simple even for
your case where it's quite clear what's going on in terms of scaling.
I passed it to Fieldtrip developers who will look at how the units are
handled by their forward computation. When I hear back from them I'll
update you and the list.You can follow their progress via
http://bugzilla.fcdonders.nl/show_bug.cgi?id=3D686
Best,
Vladimir
On Mon, May 16, 2011 at 10:48 AM, Lars Meyer <[log in to unmask]> wrote:
> dear all,
>
> i am using spm_eeg_dipole_waveforms.m to retrieve dipole timecourses =
for two dipole priors in a vb-ecd- localisation. everything works fine, =
so no worries there, but i was wondering on what the units of the dipole =
amplitudes are=E2=80=A6 i remember some older post on the exact same =
question, have talked to the asker, but it seems there is no answer yet.
>
> or is there a working solution from the programmers of the above =
function?
>
>
> thanks in advance, and all best,
> l.
>
>
>
>
> Lars Meyer
> Max Planck Institute for Human Cognitive & Brain Sciences
> Department of Neuropsychology
> Stephanstra=EF=AC=82e 1a
> 04103 Leipzig | Germany
>
> Office | +49 341 99 40 22 66
> Mail | [log in to unmask]
> Web | www.cbs.mpg.de/~lmeyer
>
=========================================================================
Date: Wed, 25 May 2011 13:43:36 +0100
Reply-To: Alec Sproten <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Alec Sproten <[log in to unmask]>
Subject: using DARTEL appropriately
Mime-Version: 1.0
Content-Type: multipart/alternative;
boundary="part-B1zxr2PHN81YdAxJOuocT0l3vnl0Yo3UhqgEtDQ01tKlQ"
Message-ID: <[log in to unmask]>
This is a multi-part message in MIME format.
--part-B1zxr2PHN81YdAxJOuocT0l3vnl0Yo3UhqgEtDQ01tKlQ
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Dear SPM experts,
I have started to use the DARTEL tool for the first time and I have some =
questions that I could not find any answer for them in the SPM manual.
Background:=20
I am investigating effect of 3 experimental manipulations on 2 groups of =
subjects (N1=3D27,N2=3D23).=20=20
Each subject undergoes 1 scanning session that is composed of: 1 EPI scan=
[event related design] and 1 anatomical scan.
We are interested only in functional analysis (not a VBM study).
The preprocessing sequence we have used until the DARTEL step:
Realignment (Estimate & Reslice; resliced images: all images+mean) =EF=83=
=A0 Coregristration (Estimate) =EF=83=A0 New Segment (save bias corrected=
was selected; native tissue: Native + DARTEL imported were selected) =EF=
=83=A0 DARTEL.
Processing the anatomical images with DARTEL:=20
Following the manual, due to the usage of New Segment step, first I proce=
ssed the anatomical images. I created a template [using Run DARTEL(create=
Template) option]. I selected all the rc1*.nii and the rc2*.nii files i=
n the same order =E2=80=93 from all the subjects. Then I used the DARTEL=
(normalize to MNI space) process, selected the flow fields and only the g=
ray matter c1*.nii images of all the subjects =E2=80=93 again with mainta=
ining the same order as before. I chose =E2=80=98Few subjects=E2=80=99 an=
d preserve concentrations options. Other factors weren=E2=80=99t changed.=
My questions:
1.=09Regarding normalizing the functional images using DARTEL.=20
a.=09Should I need to do the previous step (creating a template) also for=
the functional images? And if so, which images are to be selected: the p=
ost realignment images from each subject =E2=80=93 in one single selectio=
n of all the images from all the subjects [as done with the anatomical on=
e]? Or should I separate the process and create a new module for each sub=
ject?
b.=09In the DARTEL: Normalize to MNI Space,=20
i.=09Which DARTEL Template should I use? I assume if I don=E2=80=99t need=
to do the create-template step for the functional images then I should u=
se the Template_6.nii that was generated from the DARTEL template of the =
anatomical images, is it correct?=20
ii.=09In the manual (page 445. Section 41.2) it is written that the flow =
fields should be selected for every subject. It is written that =E2=80=9C=
u_c1*.nii=E2=80=9D files should be selected. I wondered is that correct? =
Because I thought that after the new segmentation process we should use t=
he =E2=80=9Cu_rc1*.nii=E2=80=9D files [Dartel imported and not the native=
ones]. Is it typo or did I miss something?
c.=09Just to clarify, in this step should I do this step for each subject=
independently i.e. selecting each time the flow field and the functional=
images for each subject or should I load all the flow fields and the fun=
ctional images (ordered) in the same batch?
2.=09If I understood correctly the DARTEL process includes the smoothing =
step so the next thing to do is to advance to the other steps (1st analys=
is, etc.)?
3.=09In order to match each subject anatomical image with his functional =
activity - Would the images after the DARTEL will be coregitered to the a=
natomical images or an additional coregisteration process must be employe=
d before the 1st analysis?
*Notes
=E2=80=A2=09I am using SPM8, Matlab 7.10.0 (R2010a).
=E2=80=A2=09For now all the processes are done by using the manual batch =
system of SPM [without programming scripts].
Thank you very much in advance for your help,
Looking forward to learn from you about how to use the DARTEL tool correc=
tly,
ALEC=20
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<![endif]--></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US">Dear SPM experts,</span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US">I have started to use the DARTEL tool for the first time and=
I have some questions that I could not find any answer for them in the S=
PM manual.</span></p>
<p class=3D"MsoNormal"><u><span lang=3D"EN-US" style=3D"mso-ansi-=
language:EN-US">Background: </span></u></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US">I am investigating effect of 3 experimental manipulations on=
2 groups of subjects (N1=3D27,N2=3D23). <span style=3D"mso-spacerun:yes"=
> </span></span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US">Each subject undergoes 1 scanning session that is composed o=
f: 1 EPI scan [event related design] and 1 anatomical scan.</span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US">We are interested only in functional analysis (not a VBM stu=
dy).</span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US">The preprocessing sequence we have used until the DARTEL ste=
p:</span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US">Realignment (Estimate & Reslice; resliced images: all im=
ages+mean) </span><span lang=3D"EN-US" style=3D"font-family:Wingdings;mso=
-ascii-font-family:Calibri;
mso-ascii-theme-font:minor-latin;mso-hansi-font-family:Calibri;ms=
o-hansi-theme-font:
minor-latin;mso-ansi-language:EN-US;mso-char-type:symbol;mso-symb=
ol-font-family:
Wingdings"><span style=3D"mso-char-type:symbol;mso-symbol-font-fa=
mily:Wingdings">=C3=A0</span></span><span lang=3D"EN-US" style=3D"mso-ans=
i-language:EN-US"> Coregristration (Estimate) </span><span lang=3D"EN-US"=
style=3D"font-family:Wingdings;mso-ascii-font-family:Calibri;
mso-ascii-theme-font:minor-latin;mso-hansi-font-family:Calibri;ms=
o-hansi-theme-font:
minor-latin;mso-ansi-language:EN-US;mso-char-type:symbol;mso-symb=
ol-font-family:
Wingdings"><span style=3D"mso-char-type:symbol;mso-symbol-font-fa=
mily:Wingdings">=C3=A0</span></span><span lang=3D"EN-US" style=3D"mso-ans=
i-language:EN-US"> New Segment (save bias corrected was selected; native =
tissue: Native + DARTEL imported were selected) <span style=3D"mso-spacer=
un:yes"> </span></span><span lang=3D"EN-US" style=3D"font-family:
Wingdings;mso-ascii-font-family:Calibri;mso-ascii-theme-font:mino=
r-latin;
mso-hansi-font-family:Calibri;mso-hansi-theme-font:minor-latin;ms=
o-ansi-language:
EN-US;mso-char-type:symbol;mso-symbol-font-family:Wingdings"><spa=
n style=3D"mso-char-type:symbol;mso-symbol-font-family:Wingdings">=C3=A0<=
/span></span><span lang=3D"EN-US" style=3D"mso-ansi-language:EN-US"> DART=
EL.</span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US">Processing the anatomical images with DARTEL: </span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US">Following the manual, due to the usage of New Segment step, =
first I processed the anatomical images. I created a template [using Run =
DARTEL(create Template) option]. <span style=3D"mso-spacerun:yes"> <=
/span>I selected all the rc1*.nii and the rc2*.nii files in the same orde=
r =E2=80=93 from all the subjects. <span style=3D"mso-spacerun:yes"> =
;</span>Then I used the DARTEL(normalize to MNI space) process, selected =
the flow fields and only the gray matter c1*.nii images of all the subjec=
ts =E2=80=93 again with maintaining the same order as before. I chose =E2=
=80=98Few subjects=E2=80=99 and preserve concentrations options. Other fa=
ctors weren=E2=80=99t changed.</span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US">My questions:</span></p>
<p class=3D"MsoListParagraphCxSpFirst" style=3D"text-indent:-18.0=
pt;mso-list:l1 level1 lfo1"><span lang=3D"EN-US" style=3D"mso-bidi-font-f=
amily:Calibri;mso-bidi-theme-font:minor-latin;
mso-ansi-language:EN-US"><span style=3D"mso-list:Ignore">1.<span =
style=3D"font:7.0pt "Times New Roman"">    =
   </span></span></span><span lang=3D"EN-US" style=3D"mso-ansi-=
language:EN-US">Regarding normalizing the functional images using DARTEL.=
</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-left:72.0=
pt;mso-add-space:
auto;text-indent:-18.0pt;mso-list:l1 level2 lfo1"><span lang=3D"E=
N-US" style=3D"mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-lat=
in;
mso-ansi-language:EN-US"><span style=3D"mso-list:Ignore">a.<span =
style=3D"font:7.0pt "Times New Roman"">    =
   </span></span></span><span lang=3D"EN-US" style=3D"mso-ansi-=
language:EN-US">Should I need to do the previous step (creating a templat=
e) also for the functional images? And if so, which images are to be sele=
cted: the post realignment images from each subject =E2=80=93 in one sing=
le selection of all the images from all the subjects [as done with the an=
atomical one]? Or should I separate the process and create a new module f=
or each subject?</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-left:72.0=
pt;mso-add-space:
auto;text-indent:-18.0pt;mso-list:l1 level2 lfo1"><span lang=3D"E=
N-US" style=3D"mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-lat=
in;
mso-ansi-language:EN-US"><span style=3D"mso-list:Ignore">b.<span =
style=3D"font:7.0pt "Times New Roman"">    =
  </span></span></span><span lang=3D"EN-US" style=3D"mso-ansi-langua=
ge:EN-US">In the DARTEL: Normalize to MNI Space, </span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-left:108.=
0pt;mso-add-space:
auto;text-indent:-108.0pt;mso-text-indent-alt:-9.0pt;mso-list:l1 =
level3 lfo1"><span lang=3D"EN-US" style=3D"mso-bidi-font-family:Calibri;m=
so-bidi-theme-font:minor-latin;
mso-ansi-language:EN-US"><span style=3D"mso-list:Ignore"><span st=
yle=3D"font:7.0pt "Times New Roman"">    &#=
160;           =
60;           =
0;            =
;            =
          </span>i.<span sty=
le=3D"font:7.0pt "Times New Roman"">    =
60; </span></span></span><span lang=3D"EN-US" style=3D"mso-ansi-language:=
EN-US">Which DARTEL Template should I use? I assume if I don=E2=80=99t ne=
ed to do the create-template step for the functional images then I should=
use the Template_6.nii that was generated from the DARTEL template of th=
e anatomical images, is it correct? </span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-left:108.=
0pt;mso-add-space:
auto;text-indent:-108.0pt;mso-text-indent-alt:-9.0pt;mso-list:l1 =
level3 lfo1"><span lang=3D"EN-US" style=3D"mso-bidi-font-family:Calibri;m=
so-bidi-theme-font:minor-latin;
mso-ansi-language:EN-US"><span style=3D"mso-list:Ignore"><span st=
yle=3D"font:7.0pt "Times New Roman"">    &#=
160;           =
60;           =
0;            =
;            =
        </span>ii.<span style=3D"font:=
7.0pt "Times New Roman"">      </span>=
</span></span><span lang=3D"EN-US" style=3D"mso-ansi-language:EN-US">In t=
he manual (page 445. Section 41.2) it is written that the flow fields sho=
uld be selected for every subject. It is written that =E2=80=9Cu_c1*.nii=E2=
=80=9D files should be selected. I wondered is that correct? Because I th=
ought that after the new segmentation process we should use the =E2=80=9C=
u_rc1*.nii=E2=80=9D files [Dartel imported and not the native ones]. Is i=
t typo or did I miss something?</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-left:72.0=
pt;mso-add-space:
auto;text-indent:-18.0pt;mso-list:l1 level2 lfo1"><span lang=3D"E=
N-US" style=3D"mso-bidi-font-family:Calibri;mso-bidi-theme-font:minor-lat=
in;
mso-ansi-language:EN-US"><span style=3D"mso-list:Ignore">c.<span =
style=3D"font:7.0pt "Times New Roman"">    =
   </span></span></span><span lang=3D"EN-US" style=3D"mso-ansi-=
language:EN-US">Just to clarify, in this step should I do this step for e=
ach subject independently i.e. selecting each time the flow field and the=
functional images for each subject or should I load all the flow fields =
and the functional images (ordered) in the same batch?</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"text-indent:-18.=
0pt;mso-list:l1 level1 lfo1"><span lang=3D"EN-US" style=3D"mso-bidi-font-=
family:Calibri;mso-bidi-theme-font:minor-latin;
mso-ansi-language:EN-US"><span style=3D"mso-list:Ignore">2.<span =
style=3D"font:7.0pt "Times New Roman"">    =
   </span></span></span><span lang=3D"EN-US" style=3D"mso-ansi-=
language:EN-US">If I understood correctly the DARTEL process includes the=
smoothing step so the next thing to do is to advance to the other steps =
(1<sup>st</sup> analysis, etc.)?</span></p>
<p class=3D"MsoListParagraphCxSpLast" style=3D"text-indent:-18.0p=
t;mso-list:l1 level1 lfo1"><span lang=3D"EN-US" style=3D"mso-bidi-font-fa=
mily:Calibri;mso-bidi-theme-font:minor-latin;
mso-ansi-language:EN-US"><span style=3D"mso-list:Ignore">3.<span =
style=3D"font:7.0pt "Times New Roman"">    =
   </span></span></span><span lang=3D"EN-US" style=3D"mso-ansi-=
language:EN-US">In order to match each subject anatomical image with his =
functional activity - Would the images after the DARTEL will be coregiter=
ed to the anatomical images or an additional coregisteration process must=
be employed before the 1<sup>st</sup> analysis?</span></p>
<p class=3D"MsoNormal"><u><span lang=3D"EN-US" style=3D"mso-ansi-=
language:EN-US">Notes</span></u></p>
<p class=3D"MsoListParagraphCxSpFirst" style=3D"text-indent:-18.0=
pt;mso-list:l0 level1 lfo2"><span lang=3D"EN-US" style=3D"font-family:Sym=
bol;mso-fareast-font-family:Symbol;mso-bidi-font-family:
Symbol;mso-ansi-language:EN-US"><span style=3D"mso-list:Ignore">=C2=
=B7<span style=3D"font:7.0pt "Times New Roman"">  =
60;      </span></span></span><span lang=3D"EN-U=
S" style=3D"mso-ansi-language:EN-US">I am using SPM8, Matlab<span style=3D=
"mso-spacerun:yes">  </span>7.10.0 (R2010a).</span></p>
<p class=3D"MsoListParagraphCxSpLast" style=3D"text-indent:-18.0p=
t;mso-list:l0 level1 lfo2"><span lang=3D"EN-US" style=3D"font-family:Symb=
ol;mso-fareast-font-family:Symbol;mso-bidi-font-family:
Symbol;mso-ansi-language:EN-US"><span style=3D"mso-list:Ignore">=C2=
=B7<span style=3D"font:7.0pt "Times New Roman"">  =
60;      </span></span></span><span lang=3D"EN-U=
S" style=3D"mso-ansi-language:EN-US">For now all the processes are done b=
y using the manual batch system of SPM [without programming scripts].</sp=
an></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US">Thank you very much in advance for your help,</span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US">Looking forward to learn from you about how to use the DARTE=
L tool correctly,</span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US">ALEC </span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US"> </span></p>
<p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"mso-ansi-lan=
guage:EN-US"> </span></p>
</body>
</html>
--part-B1zxr2PHN81YdAxJOuocT0l3vnl0Yo3UhqgEtDQ01tKlQ--
=========================================================================
Date: Wed, 25 May 2011 14:24:11 +0100
Reply-To: Gareth Barnes <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Gareth Barnes <[log in to unmask]>
Subject: Re: dipole waveforms | units
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable
Message-ID: <03e001cc1adf$08c85e40$1a591ac0$@[log in to unmask]>
Dear Lars,
Please ignore my last post. I thought you were asking about the units of =
vbecd results (not the output of dipole_waveforms).
Apologies
Gareth
>Hi Lars
>For the record, and for MEG only :
>It looks like (if the units of sensors are Tesla and measurement in mm) =
then the moments will be in nAm. (there is an extra scaling factor of =
1000 in >the spm code).
>I am also looking into the EEG case now.
>Best
>Gareth
-----Original Message-----
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] =
On Behalf Of Vladimir Litvak
Sent: 25 May 2011 11:51
To: [log in to unmask]
Subject: Re: [SPM] dipole waveforms | units
Dear Lars,
It seems like the answer to your question is not that simple even for
your case where it's quite clear what's going on in terms of scaling.
I passed it to Fieldtrip developers who will look at how the units are
handled by their forward computation. When I hear back from them I'll
update you and the list.You can follow their progress via
http://bugzilla.fcdonders.nl/show_bug.cgi?id=3D686
Best,
Vladimir
On Mon, May 16, 2011 at 10:48 AM, Lars Meyer <[log in to unmask]> wrote:
> dear all,
>
> i am using spm_eeg_dipole_waveforms.m to retrieve dipole timecourses =
for two dipole priors in a vb-ecd- localisation. everything works fine, =
so no worries there, but i was wondering on what the units of the dipole =
amplitudes are=E2=80=A6 i remember some older post on the exact same =
question, have talked to the asker, but it seems there is no answer yet.
>
> or is there a working solution from the programmers of the above =
function?
>
>
> thanks in advance, and all best,
> l.
>
>
>
>
> Lars Meyer
> Max Planck Institute for Human Cognitive & Brain Sciences
> Department of Neuropsychology
> Stephanstra=EF=AC=82e 1a
> 04103 Leipzig | Germany
>
> Office | +49 341 99 40 22 66
> Mail | [log in to unmask]
> Web | www.cbs.mpg.de/~lmeyer
>
=========================================================================
Date: Wed, 25 May 2011 14:58:13 +0100
Reply-To: Debby Klooster <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Debby Klooster <[log in to unmask]>
Subject: FIR implementation
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Hi SPM users,
I am trying to implement the finite impulse response (FIR) to estimate my=
hemodynamic response function. However, I would like to see the FIR in t=
he design matrix simply as white blocks but the blocks in the design matr=
ix seemed to be 'blurred'. Can anybody help me with this problem? And doe=
s anybody know optimal settings for the window length and the order that =
need to be filled in?
Thanks heaps!
Debby
=========================================================================
Date: Wed, 25 May 2011 15:06:04 +0100
Reply-To: Debby Klooster <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Debby Klooster <[log in to unmask]>
Subject: Deactivations in SPM
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Hi SPM users,
I am trying to model the default mode network (DMN) with SPM. In literatu=
re, it is stated that this DMN contains deactivated regions which are usu=
ally shown in blue. I can see in my analysis that the HRF has a negative =
peak but the responses in the images are shown in red.=20
Does anybody know how to edit the color scale and how I can show deactiva=
tions in blue?
Thank you in advance!
Debby
=========================================================================
Date: Wed, 25 May 2011 17:21:34 +0200
Reply-To: "S.F.W. Neggers" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "S.F.W. Neggers" <[log in to unmask]>
Subject: Re: question regarding matlabbatch struct/class
Comments: To: "Stephen J. Fromm" <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8; format=flowed
content-transfer-encoding: 7bit
Message-ID: <[log in to unmask]>
Hi again,
just for the sake of completeness (in case others run into this) a
follow up:
the (possibly undesirable) conversion of the matlabbatch object to a
structure seems to happen as well when spm8 folder is in the matlab path.
It first disappears when one has actually first started SPM8 at some
point during a running matlab session, regardless of exiting the
application again. Apparently some global variables initiated by SPM or
so prevent this conversion from happening.
So perhaps it is smart to first start SPM8 (and if needed quit it again)
and then run scripts using batching code.
Not sure whether it makes a difference, but the warning looks scary
enough to me.
Happy batchin' to all,
Bas
Op 12-05-11 15:42, Stephen J. Fromm schreef:
> What happens if you put SPM in your matlab path? Usually for me that's enough to make the warning disappear.
>
>
Op 11-05-11 18:48, S.F.W. Neggers schreef:
> Dear list,
>
> I created a matlab batch job in the SPM8 batching system, and saved it
> to disk as a mat file. Now I want to use it in my own pipeline (matlab
> software) to do some repetative number crunching. I work with matlab
> version 7.9.0529 (R2009b), and SPM8 rev 4290.
>
> When loading this matlabbatch structure from disk, I obtained the
> following warning:
>
> --- snip ---
> > load testbatch_spm8.mat
> Warning: Class ':all:' is an unknown object class. Element(s) of
> this class in array 'matlabbatch' have been converted to
> structures.
> ---
>
> When I now fill in some fields according to my needs, and save this
> structure again to disk, will all be OK?
>
> Apparently matlabbatch originally is a class with methods in an OOP
> sense, and I dont want to break things by irreversibly convert classes
> to fields of a structure. I never had this warning in SPM5, and I am
> in the process of moving my pipeline to spm8.
>
> Thanks for your pointers,
>
> Bas
--
--------------------------------------------------
Dr. S.F.W. Neggers
Division of Brain Research
Rudolf Magnus Institute for Neuroscience
Utrecht University Medical Center
Visiting : Heidelberglaan 100, 3584 CX Utrecht
Room B.01.1.03
Mail : Huispost B01.206, P.O. Box
3508 GA Utrecht, the Netherlands
Tel : +31 (0)88 7559609
Fax : +31 (0)88 7555443
E-mail : [log in to unmask]
Web : http://www.neuromri.nl/people/bas-neggers
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Date: Wed, 25 May 2011 16:51:18 +0100
Reply-To: Cedric Clouchoux <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Cedric Clouchoux <[log in to unmask]>
Subject: Job Announcement: Postdoctoral Position at
Children=?UTF-8?Q?=E2=80=99s_?=National Medical Center
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We are seeking a highly motivated and talented postdoctoral fellow to wor=
k in the Advanced Pediatric Brain Imaging Research Laboratory in Diagnost=
ic Imaging & Radiology, and Fetal & Transitional Medicine, at Children=E2=
=80=99s National Medical Center, George Washington University.
The goal of our research program is to study brain development in healthy=
and high-risk fetal and neonatal populations, and to develop reliable cl=
inical imaging markers that will ultimately improve detection and monitor=
ing of the fetus at risk for brain injury.
The research project will focus on developing novel mathematical and comp=
utational modeling techniques to improve image registration and image rec=
onstruction of anatomical and echo planar/diffusion imaging data from in =
vivo fetal and neonatal brain imaging studies. The project will include t=
he design and development of improved approaches to eliminate motion, opt=
imize MR image resolution, to enable automate brain tissue segmentation, =
microstructural and functional brain assessment. The research fellow will=
gain exposure to a wide range of clinical conditions that affect brain d=
evelopment through our fetal and transitional medicine program.
Candidates must have a PhD in biomedical engineering, mathematics or comp=
uter science. A strong background in neuroimaging is required.
The position is funded by the Advanced Pediatric Brain Imaging Laboratory=
at Children=E2=80=99s National for one year, renewable for a second year=
, and will begin over the summer of 2011. Candidates should submit a CV, =
list 2 references, and provide a brief statement of research interests, b=
y email to Dr. Limperopoulos. Applications or informal inquires should be=
addressed to Catherine Limperopoulos, PhD ([log in to unmask]
g).
Contact:
Catherine Limperopoulos, PhD
Director, MRI Research of the Developing Brain
Director, Advanced Pediatric Brain Imaging Research Laboratory Diagnostic=
Imaging and Radiology/Fetal and Transitional Medicine
Children=E2=80=99s National Medical Center=20
Associate Professor of Pediatrics
George Washington University School of Medicine and Health Sciences
111 Michigan Ave. N.W.
Washington, D.C. 20010
Email: [log in to unmask]
=========================================================================
Date: Wed, 25 May 2011 17:34:07 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: using DARTEL appropriately
Comments: To: Alec Sproten <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=windows-1252
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Message-ID: <[log in to unmask]>
> I have started to use the DARTEL tool for the first time and I have some
> questions that I could not find any answer for them in the SPM manual.
>
> Background:
>
> I am investigating effect of 3 experimental manipulations on 2 groups of
> subjects (N1=3D27,N2=3D23).
>
> Each subject undergoes 1 scanning session that is composed of: 1 EPI scan
> [event related design] and 1 anatomical scan.
>
> We are interested only in functional analysis (not a VBM study).
>
> The preprocessing sequence we have used until the DARTEL step:
>
> Realignment (Estimate & Reslice; resliced images: all images+mean) =E0
> Coregristration (Estimate) =E0 New Segment (save bias corrected was selec=
ted;
> native tissue: Native + DARTEL imported were selected) =A0=E0 DARTEL.
>
> Processing the anatomical images with DARTEL:
>
> Following the manual, due to the usage of New Segment step, first I
> processed the anatomical images. I created a template [using Run
> DARTEL(create Template) option]. =A0I selected all the rc1*.nii and the
> rc2*.nii files in the same order =96 from all the subjects. =A0Then I use=
d the
> DARTEL(normalize to MNI space) process, selected the flow fields and only
> the gray matter c1*.nii images of all the subjects =96 again with maintai=
ning
> the same order as before. I chose =91Few subjects=92 and preserve concent=
rations
> options. Other factors weren=92t changed.
>
> My questions:
>
> 1.=A0=A0=A0=A0=A0=A0 Regarding normalizing the functional images using DA=
RTEL.
>
> a.=A0=A0=A0=A0=A0=A0 Should I need to do the previous step (creating a te=
mplate) also
> for the functional images? And if so, which images are to be selected: th=
e
> post realignment images from each subject =96 in one single selection of =
all
> the images from all the subjects [as done with the anatomical one]? Or
> should I separate the process and create a new module for each subject?
How you do this will depend on what works best for your data. If your
fMRI are completely free of distortions, you can simply coregister
your fMRI to the anatomical scans and spatially normalise your fMRI
(instead of the c1*) using Dartel. Note that if you coregister after
estimating the segmentations and warps, then you MUST move the fMRI
into alignment with the anatomical data. If you move the anatomical
data into alignment with the fMRI, then you won't be able to apply the
Dartel transforms any more.
In reality, the fMRI will be spatially distorted, which means that the
rigid-body alignment between fMRI and anatomical scans may be quite a
lot less than perfect. If the dropout artifact is not too strong and
the grey and white matter is clearly visible, you could try segmenting
the data and aligning the rc1 and rc2 from the fMRI. This
occasionally seems to do quite a reasonable job.
>
> b.=A0=A0=A0=A0=A0 In the DARTEL: Normalize to MNI Space,
>
> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=
=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=
=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 i.=A0=A0=A0=A0=A0 Which
> DARTEL Template should I use? I assume if I don=92t need to do the
> create-template step for the functional images then I should use the
> Template_6.nii that was generated from the DARTEL template of the anatomi=
cal
> images, is it correct?
Use Template_6.nii, which is the most crisp of the series.
>
> =A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=
=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=
=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0=A0 ii.=A0=A0=A0=A0=A0 In the
> manual (page 445. Section 41.2) it is written that the flow fields should=
be
> selected for every subject. It is written that =93u_c1*.nii=94 files shou=
ld be
> selected. I wondered is that correct? Because I thought that after the ne=
w
> segmentation process we should use the =93u_rc1*.nii=94 files [Dartel imp=
orted
> and not the native ones]. Is it typo or did I miss something?
That must be a typo. You should not actually have any u_c1*.nii
files. Only u_rc1*.nii.
>
> c.=A0=A0=A0=A0=A0=A0 Just to clarify, in this step should I do this step =
for each
> subject independently i.e. selecting each time the flow field and the
> functional images for each subject or should I load all the flow fields a=
nd
> the functional images (ordered) in the same batch?
You'll need to do this for each subject at a time, which is what the
=91Few subjects=92 option does. If you can batch it (using some sort of
scripts), it may make life easier.
>
> 2.=A0=A0=A0=A0=A0=A0 If I understood correctly the DARTEL process include=
s the smoothing
> step so the next thing to do is to advance to the other steps (1st analys=
is,
> etc.)?
Yes.
Don't tell Karl I said this, but personally I would do the first level
analysis in native space (disabling any threshold masking) in order to
compute contrast images, and then spatially normalise the contrast
images using Dartel. With one contrast image (or only a small number
of them) per subject, you can easily use the 'Many subjects' option
for writing the spatially normalised images. Then you'd do the second
level analysis on the spatially normalised contrast images.
>
> 3.=A0=A0=A0=A0=A0=A0 In order to match each subject anatomical image with=
his functional
> activity - Would the images after the DARTEL will be coregitered to the
> anatomical images or an additional coregisteration process must be employ=
ed
> before the 1st analysis?
When processing is treated as a pipeline, the within subject
processing should be done before the between subject. Therefore, try
to align the native space images.
> Looking forward to learn from you about how to use the DARTEL tool
> correctly,
I'm not entirely sure there is a single correct way. The procedures
that work best will depend on the artifacts, contrast etc in your
images.
Best regards,
-John
=========================================================================
Date: Wed, 25 May 2011 18:36:59 +0100
Reply-To: Alec Sproten <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Alec Sproten <[log in to unmask]>
Subject: Re: using DARTEL appropriately
Comments: To: John Ashburner <[log in to unmask]>
Mime-Version: 1.0
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Message-ID: <[log in to unmask]>
Dear John,
thanks a lot for your help! That really took us a big step further.
There're just two small questions remaining:
a. You said that we "could try segmenting the data and aligning the rc1 a=
nd rc2 from the fMRI". If I unerstood the Dartel correctly, the rc1 and r=
c2 are files that we get from the anatomical images? So shouldn't we alig=
n the rc1 and rc2 with the fMRI? Or is there a procedure to get these fil=
es from the fMRI data?
b. If we don't do a VBM study, is it right that we shouldn't normalize th=
e anatomical images?
Thanks again for your help,
Alec
=========================================================================
Date: Wed, 25 May 2011 18:47:04 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: using DARTEL appropriately
Comments: To: Alec Sproten <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
> a. You said that we "could try segmenting the data and aligning the rc1 a=
nd rc2 from the fMRI". If I unerstood the Dartel correctly, the rc1 and rc2=
are files that we get from the anatomical images? So shouldn't we align th=
e rc1 and rc2 with the fMRI? Or is there a procedure to get these files fro=
m the fMRI data?
If you use New Segment on an fMRI scan (which may or may not work
well), then you can get rc1 and rc2 files.
>
> b. If we don't do a VBM study, is it right that we shouldn't normalize th=
e anatomical images?
If you don't need them for anything, there's no point in generating
them. Usually, when SPM uses a file for any purpose, it asks you to
select the file.
Best regards,
-John
=========================================================================
Date: Wed, 25 May 2011 18:54:42 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: SPECT transporter image analysis realted to DARTEL and BPM
Comments: To: David Yang <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
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Message-ID: <[log in to unmask]>
I can't say much about your question on BPM, but your Dartel
processing seems to be OK. You are correct in that the headers of the
source (and other) images are modified to reflect the new image
orientations.
A small point about BPM. You should probably smooth your grey matter
(c1 images) to match the point-spread function of the SPECT as closely
as possible, and then warp the SPECT and sc1 images, probably using
"preserve amount" for both types of image. I'm no expert on this, so
maybe others could comment further.
Best regards,
-John
On 25 May 2011 05:49, David Yang <[log in to unmask]> wrote:
> Dear all
>
> Our subjects had SPECT transporter images(TRODAT for dopamine transporter=
s) and their T1 MRI images (for VBM analysis). We planed to perform correla=
tion analysis between such 2 kind of image modalities by WFU Biological Par=
ametric Mapping Toolbox.
>
> Since our MRI images were analysed by DARTEL related process, our SPECT i=
mages should also be analysed by DARTEL related ones.
>
> According to previous discussion (https://www.jiscmail.ac.uk/cgi-bin/weba=
dmin?A2=3DSPM;3779f1d9.0909), we performed following analyses:
>
> Step 1: Within subject coregistration: Use SPM function, Coreg:estimate (=
without reslicing) and we suspected the registration information would be s=
tored in the header of source images (no other output would be found)
>
> Step 2: Routine DARTEL analysis for MRI data
>
> Step 3: as performing the function, "DARTEL toolbox: normalise to MNI spa=
ce option" and use source images (SPECT) from Step 1.
>
> For receptor/transporter binding potential images, I suspected we should =
choose Preserve Amount in Step 3 according to previous discussion:
>
> http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3DSPM;f3f7b65.0901
>
> I wondered if there was any mistake in our above analysis methods?
>
> Furthermore, considering the image features of PET or even SPECT images, =
it might have to smooth such images with large amount (ex 12 mm compared to=
default 8 mm in DARTEL). I wonder if such was suitable if we wanted to per=
form further analysis by BPM that used both VBM and PET/SPECT images concur=
rently as in this subject:
>
> http://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=3DSPM;dd737de1.1012
>
> Thanks for any help!
>
> Sincerely yours,
>
> David
>
=========================================================================
Date: Wed, 25 May 2011 18:14:23 +0000
Reply-To: "West, John D." <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "West, John D." <[log in to unmask]>
Subject: Large Differences in segmenations between SPM8 and SPM5
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Hello.
I'm hoping someone might be able to help us get to the bottom of an issue w=
e've run into. Recently we have been trying to reprocess our data using SP=
M8. Unfortunately, we have run into a situation where some subjects which =
segmented fine in SPM5 are now failing in SPM8.
The way we do segmentation is we first register the T1 (MPRAGE) to the T1 t=
emplate to give the segmentation a better starting estimate. We then segme=
nt from there. However, in SPM8 the registration has consistently come out=
differently. It seems that in some cases this new registration is giving =
the segmentation a starting estimate that it cannot handle, where in SPM5 t=
he starting estimate was fine.
Does anyone have any ideas on what would be causing these differences? Is =
the coregistration and segmentation algorithms very different between SPM5 =
and SPM8? If not, is there some setting we may need to change? If they ar=
e different, are there any suggestions you could give so we could successfu=
lly segment these cases in SPM8?
I appreciate your assistance.
Thanks.
-John West
Systems Administrator
IU Center for Neuroimaging
--_000_793D43FE7976404CB5E172709AB1F4080DE70B26IUMSSGMBX102ads_
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<p class=3D"MsoNormal">Hello.<o:p></o:p></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">I’m hoping someone might be able to help us ge=
t to the bottom of an issue we’ve run into. Recently we have be=
en trying to reprocess our data using SPM8. Unfortunately, we have ru=
n into a situation where some subjects which segmented fine
in SPM5 are now failing in SPM8. <o:p></o:p></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">The way we do segmentation is we first register the =
T1 (MPRAGE) to the T1 template to give the segmentation a better starting e=
stimate. We then segment from there. However, in SPM8 the regis=
tration has consistently come out differently.
It seems that in some cases this new registration is giving the segmentati=
on a starting estimate that it cannot handle, where in SPM5 the starting es=
timate was fine.<o:p></o:p></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">Does anyone have any ideas on what would be causing =
these differences? Is the coregistration and segmentation algorithms =
very different between SPM5 and SPM8? If not, is there some setting w=
e may need to change? If they are different,
are there any suggestions you could give so we could successfully segment =
these cases in SPM8?<o:p></o:p></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">I appreciate your assistance.<o:p></o:p></p>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal">Thanks.<o:p></o:p></p>
<p class=3D"MsoNormal">-John West<o:p></o:p></p>
<p class=3D"MsoNormal">Systems Administrator<o:p></o:p></p>
<p class=3D"MsoNormal">IU Center for Neuroimaging<o:p></o:p></p>
</div>
</body>
</html>
--_000_793D43FE7976404CB5E172709AB1F4080DE70B26IUMSSGMBX102ads_--
=========================================================================
Date: Wed, 25 May 2011 14:18:04 -0400
Reply-To: cliff <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: cliff <[log in to unmask]>
Subject: about the threshold according to different image number
MIME-Version: 1.0
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--bcaec53af216bdb7f304a41db981
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Dear experts,
I am trying to comapre two resting BOLD datasets' seeded connectivity visua=
l
pattern difference. One has 320 images, and the other one has 120 images.
Is there any way to adjust their thresholds of SPM map to keep this
comparison in a fair level.
I mean beacuse of the different image number in these two datasets, if I us=
e
the same threshold to display their connectivity SPM map, it seems unfair t=
o
the 120 images dataset. So I am seeking for a method to adjust the threshol=
d
level according to different image number.
Thanks=EF=BC=81
--=20
Sincerely,
Senhua Zhu
--bcaec53af216bdb7f304a41db981
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<div>Dear experts,</div>
<div>=C2=A0</div>
<div>I am trying to comapre two resting=C2=A0BOLD datasets' seeded conn=
ectivity visual pattern=C2=A0difference. One has 320 images, and the other =
one has 120 images.</div>
<div>Is there any way to adjust their thresholds of SPM map to keep this co=
mparison in a fair level.</div>
<div>=C2=A0</div>
<div>I mean beacuse of the different image number in these two datasets, if=
I use the same threshold to display their connectivity SPM map, it seems u=
nfair to the 120 images dataset. So I am seeking for a method to adjust the=
threshold level according to different image number.</div>
<div>=C2=A0</div>
<div>Thanks=EF=BC=81<br clear=3D"all"><br>-- <br></div>
<div>Sincerely,</div>
<div>Senhua Zhu<br><br></div><br>
--bcaec53af216bdb7f304a41db981--
=========================================================================
Date: Wed, 25 May 2011 13:09:54 -0500
Reply-To: Paige Scalf <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Paige Scalf <[log in to unmask]>
Subject: job opening
MIME-Version: 1.0
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Message-ID: <[log in to unmask]>
Beginning August 15th, a two-year position is available for a highly
motivated and talented postdoctoral fellow in the Department of
Psychology at the University of Arizona.
The goal of this research program is to study the neural processes
that support vision, perception and attention using functional
neuoimaging (including ultra high resolution and time resolved fMRI)
and behavioral (including eye-tracking) methods. Candidates will be
expected to support the research goals of the PI, but will also be
given the opportunity to develop more independent lines of research.
The candidate will be encouraged to take advantage of the highly
collaborative departmental environment. The Department of Psychology
is part of the School of Mind, Brain, and Behavior (MBB), and is a
member of the College of Science, in keeping with its strong
research-oriented approach and scientifically-derived knowledge base.
Its faculty and students interact and collaborate with those of other
MBB programs and departments=97Neuroscience, Cognitive Science, and
Speech, Language and Hearing Science=97as well as with other academic
units across campus. The fMRI facilities at the University of Arizona
includes a GE 3.0T Signa scanner that is fully available for research
use 5 days per week.
The University of Arizona is a premier (NSF ranking: # 16) public
research university located in Tucson, Arizona. The sun shines nearly
every day in Tucson, which is surrounded by four mountain ranges that
include the southernmost downhill ski resort in the USA. Tucson also
supports great opportunities for hiking and cycling, and is one of the
most bicycle friendly cities in the US.
Candidates must have a PhD in neuroscience or a related field and the
capacity to make a substantive intellectual contribution to the
research program. Candidates with previous neuroimaging experience and
strong programming skills will will be preferred. Of particular
interest are those candidates with experience using python-based
programs such as the Vision Egg and SciPy. For more information,
contact Dr. Paige Scalf ([log in to unmask]). Applications may be
submitted to job #47659 at http://www.uacareertrack.com.
=========================================================================
Date: Wed, 25 May 2011 19:26:00 +0100
Reply-To: Steve Fleming <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Steve Fleming <[log in to unmask]>
Subject: Re: Cluster level statistics for VBM
Comments: To: Deryk <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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Hi Deryk,
In the initial development of VBM it was observed that cluster-based =
inference produces an unreasonable number of false positives, due to =
calculation of the expected number of clusters depending on local =
variations ("non-stationarity") in the smoothness of the image (see =
http://www.fil.ion.ucl.ac.uk/spm/doc/papers/john_vbm_methods.pdf)
There is however an SPM toolbox for implementing Keith Worsley's =
correction for non-stationarity =
(http://fmri.wfubmc.edu/cms/software#NS), which should restore control =
over the false-positive rate (see Hayasaka et al. 2004, Neuroimage)
Perhaps other stats gurus can add to this if there is more up to date =
advice!
Hope this helps
Best
Steve
On 24 May 2011, at 21:22, Deryk wrote:
> Is it appropriate to interpret the cluster level statistics provided =
in the results table for a VBM analysis?
=========================================================================
Date: Wed, 25 May 2011 11:30:28 -0700
Reply-To: "Lisa F. Akiyama" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Lisa F. Akiyama" <[log in to unmask]>
Subject: Re: converting from .IMA to nifti format
Comments: To: Inci Ayhan <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
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--bcaec51ddbf14c6f8b04a41de7de
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Hi Inci,
I've never done it using SPM, but FreeSurfer worked for me in the past.
Lisa
On Mon, May 23, 2011 at 6:13 AM, Inci Ayhan <[log in to unmask]> wrote:
> Hi,
>
> I am trying to convert 3D EPI images (Siemens - .IMA format) into nifti
> format using SPM. Because the images do not have a .dcm extension, I
> cannot use "dicom2nifti" function.
>
> I would so much appreciate any help to suggest a way to do so.
>
> Thank you very much.
>
> Inci
>
--bcaec51ddbf14c6f8b04a41de7de
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<div dir=3D"ltr">Hi Inci,<br><br>
I've never done it using SPM, but FreeSurfer worked for me in the past.=
<div><br></div><div><br></div><div>Lisa<br><br><div class=3D"gmail_quote">O=
n Mon, May 23, 2011 at 6:13 AM, Inci Ayhan <span dir=3D"ltr"><<a href=3D=
"mailto:[log in to unmask]" target=3D"_blank">[log in to unmask]</a>></spa=
n> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex">Hi,<br>
<br>
I am trying to convert 3D EPI images (Siemens - .IMA format) into nifti<br>
format using SPM. Because the images do not have a .dcm extension, I<br>
cannot use "dicom2nifti" function.<br>
<br>
I would so much appreciate any help to suggest a way to do so.<br>
<br>
Thank you very much.<br>
<font color=3D"#888888"><br>
Inci<br>
</font></blockquote></div><br></div></div>
--bcaec51ddbf14c6f8b04a41de7de--
=========================================================================
Date: Wed, 25 May 2011 14:45:34 -0400
Reply-To: shaza zaghlool <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: shaza zaghlool <[log in to unmask]>
Subject: Bayesian Analysis
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0050450155a118169204a41e1c83
Message-ID: <[log in to unmask]>
--0050450155a118169204a41e1c83
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I specified and estimated models for each of my 20 subjects with the
Bayesian-first level method. I'm at the inference stage and wasn't sure what
to input for "Effect size threshold for PPM". In the Auditory fmri dataset
tutorial a value of 2 was entered. And in the face fmri tutorial, it says to
load the SPM file and then type in Matlab sf =max(SPM.xBF.bf(:,1))/SPM.xBF.dt.
I then divided 1/sf to get 4.75. I did that and got 4.75 just like the
tutorial says. Which value am I supposed to use 2 or 4.75? Also, when I used
4.75 and a Posterior probability threshold for PPM value of 0.95, I got very
little areas of activation when I compared the results to the ones I got
from estimating the models using the Classical method. Should the
Bayesian-first level method and Classical methods yield the same areas/sizes
of activation?
Thanks
--0050450155a118169204a41e1c83
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<div>I specified and estimated models for each of my 20 subjects with the B=
ayesian-first level method. I'm at the inference stage and wasn't s=
ure what to input for "<font size=3D"2" face=3D"CMTI10"><font size=3D"=
2" face=3D"CMTI10">Effect size threshold for PPM". In the Auditory fmr=
i dataset tutorial=A0a value of 2 was entered. And in the face fmri tutoria=
l, it says to load the SPM file and then <font size=3D"2" face=3D"CMR10"><f=
ont size=3D"2" face=3D"CMR10">type in </font></font><font size=3D"2" face=
=3D"CMCSC10"><font size=3D"2" face=3D"CMCSC10">Matlab </font></font><font s=
ize=3D"2" face=3D"CMTT10"><font size=3D"2" face=3D"CMTT10">sf =3Dmax(<a hre=
f=3D"http://SPM.xBF.bf">SPM.xBF.bf</a>(:,1))/SPM.xBF.dt. I then divided 1/s=
f to get 4.75. I did that and got 4.75 just like the tutorial says. Which v=
alue am I supposed to use 2 or 4.75? Also, when I used 4.75 and a <font siz=
e=3D"2" face=3D"CMTI10"><font size=3D"2" face=3D"CMTI10">Posterior probabil=
ity threshold for PPM value of 0.95, I got very little areas of activation =
when I compared the results to the ones I got from estimating the models us=
ing the Classical method. Should the Bayesian-first level method and Classi=
cal methods yield the same areas/sizes of activation?</font></font></font><=
/font></font></font></div>
<div><font size=3D"2" face=3D"CMTI10"><font size=3D"2" face=3D"CMTI10"><fon=
t size=3D"2" face=3D"CMTT10"><font size=3D"2" face=3D"CMTT10"><font size=3D=
"2" face=3D"CMTI10"><font size=3D"2" face=3D"CMTI10">Thanks</font></font></=
font></font></font></font></div>
<font size=3D"2" face=3D"CMR10"><font size=3D"2" face=3D"CMR10"></font></fo=
nt>
--0050450155a118169204a41e1c83--
=========================================================================
Date: Wed, 25 May 2011 14:45:49 -0400
Reply-To: David Kennedy <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: David Kennedy <[log in to unmask]>
Subject: Neuroinformatics 2011 - Early bird deadline June 1
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
4th INCF Congress of Neuroinformatics: Boston, Sept 4 - 6, 2011
Last day for early bird discount: June 1
Congress registration - http://neuroinformatics2011.org/registration
News:
- 166 accepted poster and demo abstracts
- All speaker abstracts displayed: http://neuroinformatics2011.org/speakers
- Spotlight presenters selected:
http://neuroinformatics2011.org/program/spotlight-presentations
For more information, please visit the Congress website at:
www.neuroinformatics2011.org
We very much look forward to seeing you in Boston in September!
=========================================================================
Date: Wed, 25 May 2011 12:15:25 -0700
Reply-To: Matthew Brett <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Matthew Brett <[log in to unmask]>
Subject: Re: converting from .IMA to nifti format
Comments: To: Inci Ayhan <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Hi,
On Mon, May 23, 2011 at 6:13 AM, Inci Ayhan <[log in to unmask]> wrote:
> Hi,
>
> I am trying to convert 3D EPI images (Siemens - .IMA format) into nifti
> format using SPM. Because the images do not have a .dcm extension, I
> cannot use "dicom2nifti" function.
>
> I would so much appreciate any help to suggest a way to do so.
You can do the conversion more manually from the matlab command line,
sort of (untested):
P = spm_select(); % select your DICOM files
hdrs = spm_dicom_headers(P);
cd /some/place/for/the/files
spm_dicom_convert(hdrs);
I think...
Best,
Matthew
=========================================================================
Date: Wed, 25 May 2011 14:16:19 -0700
Reply-To: Jose Soares <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jose Soares <[log in to unmask]>
Subject: ROI analysis
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Hi spm experts,
I would like to do a covariace (ages) analysis within a defined ROI. I have=
the spmTmaps but I first need to extract only the ROI and then do a covari=
ance of that region with the ages of the group. What is the best way to do =
it? Any specific tool?
Thanks for the help,
Jose.
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<table cellspacing=3D"0" cellpadding=3D"0" border=3D"0" ><tr><td valign=3D"=
top" style=3D"font: inherit;">Hi spm experts,<div><br></div><div>I would li=
ke to do a covariace (ages) analysis within a defined ROI. I have the spmTm=
aps but I first need to extract only the ROI and then do a covariance of th=
at region with the ages of the group. What is the best way to do it? Any sp=
ecific tool?</div><div><br></div><div>Thanks for the help,</div><div><br></=
div><div>Jose.</div></td></tr></table>
--0-1091898321-1306358179=:26162--
=========================================================================
Date: Thu, 26 May 2011 00:09:56 -0500
Reply-To: Adam Kristevski <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Adam Kristevski <[log in to unmask]>
Subject: segmentation using SPECT scans
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Hello all
I am currently conducting lesion analysis of just one patient using ITK =
snap and manually tracing. =20
I'm wondering if using SPM as an adjunct would aid in this process. =
Would normalizing, smoothing and segmenting this SPECT scan be =
beneficial in terms of having a more accurate representation of the =
patient's brain? =20
Am I able to use these functions correctly on a SPECT scan? (i.e., were =
these SPM functions designed as SPECT compatible)?
Adam
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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN">
<HTML><HEAD>
<META content=3D"text/html; charset=3Diso-8859-1" =
http-equiv=3DContent-Type>
<META name=3DGENERATOR content=3D"MSHTML 8.00.6001.19046">
<STYLE></STYLE>
</HEAD>
<BODY bgColor=3D#ffffff>
<DIV><FONT size=3D2 face=3DArial>Hello all</FONT></DIV>
<DIV><FONT size=3D2 face=3DArial></FONT> </DIV>
<DIV><FONT size=3D2 face=3DArial>I am currently conducting lesion =
analysis of just=20
one patient using ITK snap and manually tracing. </FONT></DIV>
<DIV><FONT size=3D2 face=3DArial></FONT> </DIV>
<DIV><FONT size=3D2 face=3DArial>I'm wondering if using SPM as an =
adjunct would aid=20
in this process. Would normalizing, smoothing and segmenting this =
SPECT=20
scan be beneficial in terms of having a more accurate representation of =
the=20
patient's brain? </FONT></DIV>
<DIV><FONT size=3D2 face=3DArial></FONT> </DIV>
<DIV><FONT size=3D2 face=3DArial>Am I able to use these functions =
correctly on a=20
SPECT scan? (i.e., were these SPM functions designed as SPECT =
compatible)?</FONT></DIV>
<DIV><FONT size=3D2 face=3DArial></FONT> </DIV>
<DIV><FONT size=3D2 face=3DArial>Adam</FONT></DIV></BODY></HTML>
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=========================================================================
Date: Thu, 26 May 2011 09:02:42 +0100
Reply-To: "B. de Haan" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "B. de Haan" <[log in to unmask]>
Subject: Job announcement: Postdoctoral or PhD position in Tuebingen
Mime-Version: 1.0
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Message-ID: <[log in to unmask]>
We are seeking a highly motivated and talented postdoctoral fellow or PhD=
student to work in the Section of Neuropsychology of the University of T=
uebingen, Germany
The goal of the research program is to study the mechanisms and anatomy u=
nderlying selective attention in healthy subjects and pathological extinc=
tion in neurological patients. We investigate patients with brain lesions=
as well as healthy subjects using functional magnetic resonance imaging =
(fMRI), transcranial magnetic stimulation (TMS) and behavioural recording=
s. Further information on the research environment can be found on http:/=
/homepages.uni-tuebingen.de/karnath/Sektion.html
The PhD student can acquire a PhD degree in "Neuroscience" in an interdis=
ciplinary graduate program. The postdoctoral fellow should have a PhD in =
psychology, neuroscience or a related field and should have experience wi=
th fMRI and/or TMS. Being able to speak German (or willingness to learn) =
is highly desirable.
The position is currently funded for one year (with potential extension f=
or 3 further years depending on whether or not an already submitted fundi=
ng application is successful) and should start as soon as possible but in=
November 2011 at the latest. Candidates should submit a CV, list 2 refer=
ences and provide a brief statement of research interests. Applications o=
r informal inquires should be sent by email to Dr. Bianca de Haan (bianca=
[log in to unmask]).
=========================================================================
Date: Thu, 26 May 2011 09:04:53 +0100
Reply-To: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Subject: Re: question regarding matlabbatch struct/class
Mime-Version: 1.0
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Message-ID: <[log in to unmask]>
To run a batch from MATLAB command line, SPM always has to be initialised=
. At least,=20
spm_jobman('initcfg')
should be run before. If one needs to rely on defaults which can not be s=
et in a batch (e.g. in first level fMRI analysis), one should run
spm('defaults','fmri') =18r 'pet' or 'eeg', depending on the modality
spm_jobman('initcfg')
Best,
Volkmar
=========================================================================
Date: Thu, 26 May 2011 16:08:41 +0800
Reply-To: =?GBK?B?t8nE8Q==?= <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?GBK?B?t8nE8Q==?= <[log in to unmask]>
Subject: Can DCM deal with short-term signal?
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=========================================================================
Date: Thu, 26 May 2011 09:42:32 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: segmentation using SPECT scans
Comments: To: Adam Kristevski <[log in to unmask]>
In-Reply-To: <77AB2885134A4ACB91BF86FDA38B6186@D5N6MN91>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
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Message-ID: <[log in to unmask]>
Segmentation etc were not designed for PET or SPECT, as they don't
deal with the degree of smoothness of the images. Mohamed's
(http://www.fil.ion.ucl.ac.uk/~mseghier/) lesion segmentation tools
may be of help with your MRI data though.
In general, not everything can be easily automated yet (one of my
students is a regular ITK-snap user). In principle though, any
labelling that a human expert can do, a computer should be able to do
eventually.
Best regards,
-John
On 26 May 2011 06:09, Adam Kristevski <[log in to unmask]> wrote:
> Hello all
>
> I am currently conducting lesion analysis of just one patient using ITK s=
nap
> and manually tracing.
>
> I'm wondering if using SPM as an adjunct would aid in this process.=A0 Wo=
uld
> normalizing, smoothing and segmenting this SPECT scan be beneficial in te=
rms
> of having a more accurate representation of the patient's brain?
>
> Am I able to use these functions correctly on a SPECT scan?=A0 (i.e., wer=
e
> these SPM=A0functions designed as SPECT compatible)?
>
> Adam
=========================================================================
Date: Thu, 26 May 2011 08:46:48 +0000
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: source priors for MEG source inversion
Comments: To: Sonja Schall <[log in to unmask]>
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=========================================================================
Date: Thu, 26 May 2011 08:56:04 +0000
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Can DCM deal with short-term signal?
Comments: To: =?gb18030?B?t8nE8Q==?= <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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=========================================================================
Date: Thu, 26 May 2011 17:14:35 +0800
Reply-To: =?UTF-8?B?6aOe6bif?= <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?UTF-8?B?6aOe6bif?= <[log in to unmask]>
Subject: Re: Can DCM deal with short-term signal?
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------=_Part_191472_20857236.1306401275926--
=========================================================================
Date: Thu, 26 May 2011 09:19:27 +0000
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Can DCM deal with short-term signal?
Comments: To: =?utf-8?B?6aOe6bif?= <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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Message-ID: <[log in to unmask]>
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--part6247-boundary-1877249416-1807820102--
=========================================================================
Date: Thu, 26 May 2011 10:43:35 +0100
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jing Kan <[log in to unmask]>
Subject: Question about the "MEG" and "MEGPLANAR" modalities of Elekta
system.
MIME-Version: 1.0
Content-Type: text/plain;charset=iso-8859-1
Content-Transfer-Encoding: 8bit
Message-ID: <[log in to unmask]>
Dear SPM experts,
Thanks for concern! I am doing the "3D source reconstruction" with the MEG
data from Elekta system. As I know from the SPM tutorial, SPM treats the
MEG data of the Elekta system as two different modalities: "MEG" and
"MEGPLANAR".
There are two methods used for 3D source reconstruction: "imaging",
"VB-ECD" and "DCM". The method "imaging" can let me select both "MEG" and
"MEGPLANAR" modalities for reconstruction. However, in the methods
"VB-ECD" and "DCM", I can only select either "MEG" or "MEGPLANAR" for
reconstruction.
May I ask how can I deal with this two modalities in "VB-ECD" and "DCM".
How this selection will affect my reconstruction result?
Many thanks for your help in advance!
Kind regards,
Jing
=========================================================================
Date: Thu, 26 May 2011 10:10:16 +0000
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Question about the "MEG" and "MEGPLANAR" modalities of Elekta
system.
Comments: To: [log in to unmask]
In-Reply-To: <[log in to unmask]>
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=========================================================================
Date: Thu, 26 May 2011 11:51:10 +0100
Reply-To: Ciara Greene <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Ciara Greene <[log in to unmask]>
Subject: second level analysis affected by subject order
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Hi, we've noticed something strange in our second level analyses lately. =
The order in which betas from the first level are entered into the cells =
of a second level factorial analysis seems to significantly affect the re=
sults. I ran a couple of tests to check this out; the design was a 2x2x2 =
factorial, leading to 8 cells. In each test, the individual subject betas=
were entered into all 8 cells in a consistent order, but I varied that o=
rder across tests. For example, in test1 the betas were entered in numeri=
cal order (i.e. sub1, sub2, sub3....) in every cell, while in test2 and t=
est3 different orders were used (e.g. sub3, sub9 sub1, sub11...), though =
in each case the same order was used in every cell.
In each case, the same t contrast was then run, and the results were rath=
er different. See the attached jpeg files for an illustration - the size,=
peak coordinates and p values of the activated clusters changed dependin=
g on the order in which the subject data was entered. This seems rather s=
trange to me, as the order in which participants are recruited and number=
ed is obviously arbitrary, and shouldn't affect the outcome of statistica=
l tests. I would be grateful if anyone could shed some light on this stra=
nge finding.
Regards,
Ciara Greene
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--part-0o3KMXA2xdu1dAjQrVRGm0upYANAAAECvACxGj8A1NHSA--
=========================================================================
Date: Thu, 26 May 2011 12:53:45 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: Large Differences in segmenations between SPM8 and SPM5
Comments: To: "West, John D." <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=windows-1252
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
> I=92m hoping someone might be able to help us get to the bottom of an iss=
ue
> we=92ve run into.=A0 Recently we have been trying to reprocess our data u=
sing
> SPM8.=A0 Unfortunately, we have run into a situation where some subjects =
which
> segmented fine in SPM5 are now failing in SPM8.
>
> The way we do segmentation is we first register the T1 (MPRAGE) to the T1
> template to give the segmentation a better starting estimate.=A0 We then
> segment from there.=A0 However, in SPM8 the registration has consistently=
come
> out differently.=A0 It seems that in some cases this new registration is
> giving the segmentation a starting estimate that it cannot handle, where =
in
> SPM5 the starting estimate was fine.
Are you actually reslicing the MPRAGE scans? Maybe with B-spline interpola=
tion?
I've seen a dataset that has been problematic because of this, where
the scan had large regions of zeros in it, where bits of the FOV
contained no information. Usually, the segmentation ignores zeros,
and assumes that they are masked out parts of the FOV. However, if
the data has been resliced with high-degree interpolation, these zeros
will no longer be exactly zero. The segmentation therefore tried to
fit the air class to the approximate zeros, and another tissue class
to the normal background noise.
If this is the problem, then maybe you could just register the images
without actually doing any reslicing. Maybe try windowing the
intensities in the image to see if there's anything strange lurking in
the background.
>
>
>
> Does anyone have any ideas on what would be causing these differences?=A0=
Is
> the coregistration and segmentation algorithms very different between SPM=
5
> and SPM8?=A0 If not, is there some setting we may need to change?=A0 If t=
hey are
> different, are there any suggestions you could give so we could successfu=
lly
> segment these cases in SPM8?
The basic algorithms are the same. The implementational details are
slightly different though. The older segmentation tried to ignore the
background (because it had no model for skull, scalp etc), whereas the
newer one tries to model everything in the FOV.
Best regards,
-John
=========================================================================
Date: Thu, 26 May 2011 13:06:26 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Question about the "MEG" and "MEGPLANAR" modalities of Elekta
system.
Comments: To: [log in to unmask]
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Dear Jing,
There is no principled way to compare the results between modalities.
Bayesian model comparison will not work here because the data is
different. Also one wouldn't necessarily expect to get the same
results because different modalities might be sensitive to different
cortical sources. So you can either decide that you only use one
modality throughout and ignore the other (as people who do e.g.
beamforming do) or you can look at both results and discuss why they
are similar or different.
Vladimir
On Thu, May 26, 2011 at 11:36 AM, <[log in to unmask]> wrote:
> Dear Vladimir,
>
> Thanks for your reply! May I also ask a silly question here: in this case=
,
> for instance, I run VB-ECD for both modalities and get two results.
> After the comparison, I should choose one of them which is most likely
> close to the observation, is it right?
>
> Many thanks in advance,
>
> Jing
>
>
>
>> Dear Jing,
>>
>> At the moment there is no way to combine modalities for VB-ECD and DCM.
>> You can only work with each modality separately and compare the results.
>>
>> Best,
>>
>> Vladimir
>> Sent using BlackBerry=AE from Orange
>>
>> -----Original Message-----
>> From: =A0 =A0 =A0 =A0 Jing Kan <[log in to unmask]>
>> Sender: =A0 =A0 =A0 "SPM (Statistical Parametric Mapping)" <SPM@JISCMAIL=
.AC.UK>
>> Date: =A0 =A0 =A0 =A0 Thu, 26 May 2011 10:43:35
>> To: <[log in to unmask]>
>> Reply-To: =A0 =A0 [log in to unmask]
>> Subject: [SPM] Question about the "MEG" and "MEGPLANAR" modalities of
>> Elekta system.
>>
>> Dear SPM experts,
>>
>> Thanks for concern! I am doing the "3D source reconstruction" with the
>> MEG
>> data from Elekta system. =A0As I know from the SPM tutorial, SPM treats =
the
>> MEG data of the Elekta system as two different modalities: "MEG" and
>> "MEGPLANAR".
>>
>> There are two methods used for 3D source reconstruction: "imaging",
>> "VB-ECD" and "DCM". =A0The method "imaging" can let me select both "MEG"
>> and
>> "MEGPLANAR" modalities for reconstruction. However, =A0 in the methods
>> "VB-ECD" and "DCM", I can only select either "MEG" or "MEGPLANAR" for
>> reconstruction.
>>
>> May I ask how can I deal with this two modalities in =A0"VB-ECD" and "DC=
M".
>> How this selection will affect my reconstruction result?
>>
>> Many thanks for your help in advance!
>>
>> Kind regards,
>>
>> Jing
>>
>
>
>
=========================================================================
Date: Thu, 26 May 2011 13:19:32 +0100
Reply-To: =?UTF-8?Q?=C4=B0nci_Ayhan?= <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?UTF-8?Q?=C4=B0nci_Ayhan?= <[log in to unmask]>
Subject: Re: converting from .IMA to nifti format
Comments: To: Matthew Brett <[log in to unmask]>, [log in to unmask]
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=bcaec544eb726c6c5d04a42cd509
Message-ID: <[log in to unmask]>
--bcaec544eb726c6c5d04a42cd509
Content-Type: text/plain; charset=ISO-8859-1
Lisa and Matthew,
>
> Thanks for the replies.
>
> Matthew, I tried your code and it seems it perfectly works! Thank you very
> much for sharing it!
>
> I also did this myself which seems to work, too:
>
> I changes the extension from .IMA to .dcm
> and then downloaded the spm extension "dicom2nifti" and the function
> converted the images into nifti (.nii) format.
>
> Best wishes,
>
> inci
>
>
>
>
> On Wed, May 25, 2011 at 8:15 PM, Matthew Brett <[log in to unmask]>wrote:
>
>> Hi,
>>
>> On Mon, May 23, 2011 at 6:13 AM, Inci Ayhan <[log in to unmask]> wrote:
>> > Hi,
>> >
>> > I am trying to convert 3D EPI images (Siemens - .IMA format) into nifti
>> > format using SPM. Because the images do not have a .dcm extension, I
>> > cannot use "dicom2nifti" function.
>> >
>> > I would so much appreciate any help to suggest a way to do so.
>>
>> You can do the conversion more manually from the matlab command line,
>> sort of (untested):
>>
>> P = spm_select(); % select your DICOM files
>> hdrs = spm_dicom_headers(P);
>> cd /some/place/for/the/files
>> spm_dicom_convert(hdrs);
>>
>> I think...
>>
>> Best,
>>
>> Matthew
>>
>
>
--bcaec544eb726c6c5d04a42cd509
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
<br><br><div class=3D"gmail_quote"><blockquote class=3D"gmail_quote" style=
=3D"margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); p=
adding-left: 1ex;">Lisa and Matthew,<br><br>Thanks for the replies.<br><br>=
Matthew, I tried your code and it seems it perfectly works! Thank you very =
much for sharing it!<br>
<br>I also did this myself which seems to work, too:<br><br>I changes the e=
xtension from .IMA to .dcm<br>
and then downloaded the spm extension "dicom2nifti" and the funct=
ion converted the images into nifti (.nii) format.<br><br>Best wishes,<br><=
font color=3D"#888888"><br>inci</font><div><div></div><div class=3D"h5"><br=
>
<br><br><br><div class=3D"gmail_quote">On Wed, May 25, 2011 at 8:15 PM, Mat=
thew Brett <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]"=
target=3D"_blank">[log in to unmask]</a>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; borde=
r-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">Hi,<br>
<div><br>
On Mon, May 23, 2011 at 6:13 AM, Inci Ayhan <<a href=3D"mailto:i.ayhan@u=
cl.ac.uk" target=3D"_blank">[log in to unmask]</a>> wrote:<br>
> Hi,<br>
><br>
> I am trying to convert 3D EPI images (Siemens - .IMA format) into nift=
i<br>
> format using SPM. Because the images do not have a .dcm extension, I<b=
r>
> cannot use "dicom2nifti" function.<br>
><br>
> I would so much appreciate any help to suggest a way to do so.<br>
<br>
</div>You can do the conversion more manually from the matlab command line,=
<br>
sort of (untested):<br>
<br>
P =3D spm_select(); =A0% select your DICOM files<br>
hdrs =3D spm_dicom_headers(P);<br>
cd /some/place/for/the/files<br>
spm_dicom_convert(hdrs);<br>
<br>
I think...<br>
<br>
Best,<br>
<font color=3D"#888888"><br>
Matthew<br>
</font></blockquote></div><br>
</div></div></blockquote></div><br>
--bcaec544eb726c6c5d04a42cd509--
=========================================================================
Date: Thu, 26 May 2011 14:29:17 +0000
Reply-To: "West, John D." <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "West, John D." <[log in to unmask]>
Subject: Re: Large Differences in segmenations between SPM8 and SPM5
Comments: To: John Ashburner <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Content-Type: text/plain; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
Dr. Ashburner,
Thanks very much for the reply.
In reference to your registration question, no we do not reslice. We actua=
lly try to avoid reslicing as much as possible during all our preprocessing=
to avoid adding unnecessary data files and to also limit interpolation err=
ors. So that is not the issue. However, there is definitely a distinct di=
fference between SPM5 and SPM8 in our registration to the template. Is the=
re anything that has changed in the registration that would cause this diff=
erence in your opinion?
The change in the segmentation you mentioned could potentially be the issue=
as the failures we are seeing are bringing in more non brain tissue into t=
he gray matter compartment. I plan on testing this in the near future by t=
rying the following:
1. Register to T1 template in SPM5, but segment in SPM8
2. Register to T1 template in SPM8, but segment in SPM5
Doing that should pinpoint where the issue is stemming from. I would appre=
ciate any other suggestions you may have.
Thanks.
-John West
-----Original Message-----
From: John Ashburner [mailto:[log in to unmask]]=20
Sent: Thursday, May 26, 2011 7:54 AM
To: West, John D.
Cc: [log in to unmask]
Subject: Re: [SPM] Large Differences in segmenations between SPM8 and SPM5
> I'm hoping someone might be able to help us get to the bottom of an issue
> we've run into.=A0 Recently we have been trying to reprocess our data usi=
ng
> SPM8.=A0 Unfortunately, we have run into a situation where some subjects =
which
> segmented fine in SPM5 are now failing in SPM8.
>
> The way we do segmentation is we first register the T1 (MPRAGE) to the T1
> template to give the segmentation a better starting estimate.=A0 We then
> segment from there.=A0 However, in SPM8 the registration has consistently=
come
> out differently.=A0 It seems that in some cases this new registration is
> giving the segmentation a starting estimate that it cannot handle, where =
in
> SPM5 the starting estimate was fine.
Are you actually reslicing the MPRAGE scans? Maybe with B-spline interpola=
tion?
I've seen a dataset that has been problematic because of this, where
the scan had large regions of zeros in it, where bits of the FOV
contained no information. Usually, the segmentation ignores zeros,
and assumes that they are masked out parts of the FOV. However, if
the data has been resliced with high-degree interpolation, these zeros
will no longer be exactly zero. The segmentation therefore tried to
fit the air class to the approximate zeros, and another tissue class
to the normal background noise.
If this is the problem, then maybe you could just register the images
without actually doing any reslicing. Maybe try windowing the
intensities in the image to see if there's anything strange lurking in
the background.
>
>
>
> Does anyone have any ideas on what would be causing these differences?=A0=
Is
> the coregistration and segmentation algorithms very different between SPM=
5
> and SPM8?=A0 If not, is there some setting we may need to change?=A0 If t=
hey are
> different, are there any suggestions you could give so we could successfu=
lly
> segment these cases in SPM8?
The basic algorithms are the same. The implementational details are
slightly different though. The older segmentation tried to ignore the
background (because it had no model for skull, scalp etc), whereas the
newer one tries to model everything in the FOV.
Best regards,
-John
=========================================================================
Date: Thu, 26 May 2011 13:18:49 -0400
Reply-To: Phil Greer <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Phil Greer <[log in to unmask]>
Subject: VBM Question: Making Custom TPM.nii with TOM8
MIME-version: 1.0 (Apple Message framework v1084)
Content-type: text/plain; charset=us-ascii
Content-transfer-encoding: quoted-printable
Message-ID: <[log in to unmask]>
First, thank you for your work in creating a toolbox that will allow =
creation of a custom TPM file. It is a very interesting toolbox, but I =
feel I may be missing something in the instructions.
To be specific, I am having issues in understanding exactly what images =
to use as the input when creating the TOM.mat file.
I think I am suppose to use the normalized, unmodulated segmented files =
for each tissue type (c1* c2*, etc). Is this correct?
If one uses the VBM8 toolbox, there is no option to write out all 6 =
classes of images, only gm, wm and csf.
How does one get the other tissue files?
If you use the results of new segment, as per the current VBM =
instructions in SPM8, one gets nonlinear transformed segmented images =
that may have some segmentation artifacts (at least that is the case for =
many of my elderly subjects).=20
So if I want to create a 6 tissue TPM.nii file, what images should I =
use?
Phil=
=========================================================================
Date: Thu, 26 May 2011 22:25:17 +0200
Reply-To: Johannes Gehrig <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Johannes Gehrig <[log in to unmask]>
Subject: Memory mapping (MEG, Batch)
MIME-Version: 1.0
Content-Type: text/html; charset="UTF-8"
Content-Transfer-Encoding: quoted-printable
Message-ID: <726259888.1242081.1306441517202.JavaMail.fmail@mwmweb063>
<html><head></head><body bgcolor=3D'#FFFFFF' style=3D'font-size:12px;backgr=
ound-color:#FFFFFF;font-family:Verdana, Arial, sans-serif;'>Dear SPM listus=
er,<br/><br/>I'm using the Batch-Mode for MEG preprocessing. I'm working on=
a cluster and the problem is that I'm writing to much data to disk. The fi=
le on the disk is modified while SPM is "working" on it. Is this =
because of the memory mapping? Is there a possibility to load the data in t=
he working memory and only save the final result to disk?<br/><br/>Any help=
is very much appreciated!<br/><br/>Best Regards,<br/>Johannes <=
br><br><table cellpadding=3D"0" cellspacing=3D"0" border=3D"0"><tr><td bgco=
lor=3D"#000000"><img src=3D"https://img.ui-portal.de/p.gif" width=3D"1" hei=
ght=3D"1" border=3D"0" alt=3D"" /></td></tr><tr><td style=3D"font-family:ve=
rdana; font-size:12px; line-height:17px;">Schon gehört? WEB.DE hat ein=
en genialen Phishing-Filter in die <br>Toolbar eingebaut! =
<a href=3D"http://produkte.web.de/go/toolbar"><b>http://produkte.web.de/go/=
toolbar</b></a></td></tr></table>
</body></html>
=========================================================================
Date: Thu, 26 May 2011 20:21:53 -0400
Reply-To: alekhya mandadi <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: alekhya mandadi <[log in to unmask]>
Subject: Onsets and durations in Specify 1st Level
MIME-Version: 1.0
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Hi All,
I have a question regarding onsets in specify 1st level.
Lets say my onset times are [4 23 56 72 92 120]
I want to analyze the data from the start of the onset time to the next 6
seconds. Or to better put it I want to analyze the data from [4 23 56 72 92
120] to [10 29 62 78 98 126]
Where do I enter this information? Is it where it says Durations right below
Onsets?
Your help will be greatly appreciated.
Thanks so much!
Best,
Alekhya Mandadi
Research Assistant
Center for Neural Decision Making
Temple Fox School of Business
http://www.fox.temple.edu/minisites/neural/people.html
--000325557c86b46f9104a436ecb9
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Hi All,<br><br>I have a question regarding onsets in specify 1st level.<br>=
<br>Lets say my onset times are [4 23 56 72 92 120] <br><br>I want to analy=
ze the data from the start of the onset time to the next 6 seconds. Or to b=
etter put it I want to analyze the data from [4 23 56 72 92 120]=A0 to [10 =
29 62 78 98 126]<br>
<br>Where do I enter this information? Is it where it says Durations right =
below Onsets? <br><br>Your help will be greatly appreciated.<br><br>Thanks =
so much!<br><br>Best,<br>Alekhya Mandadi<br>Research Assistant <br>Center f=
or Neural Decision Making<br>
Temple Fox School of Business <br><a href=3D"http://www.fox.temple.edu/mini=
sites/neural/people.html">http://www.fox.temple.edu/minisites/neural/people=
.html</a><br>
--000325557c86b46f9104a436ecb9--
=========================================================================
Date: Thu, 26 May 2011 21:39:23 -0400
Reply-To: hekmatyar <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: hekmatyar <[log in to unmask]>
Subject: Re: Explicit masking during statitical analysis
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset="us-ascii"
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Message-ID: <[log in to unmask]>
Hello SPMers
When I do statistical analysis without masking the outer tissue, I used to
see lot of activations from outer tissue, Is there any way to apply mask
explicitly during Ist level statistical analysis?
Please let me know
Thanks
Shah
=========================================================================
Date: Thu, 26 May 2011 19:02:52 -0700
Reply-To: Michael T Rubens <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michael T Rubens <[log in to unmask]>
Subject: Re: Onsets and durations in Specify 1st Level
Comments: To: alekhya mandadi <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=20cf303dd7a4a052b104a43857a1
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--20cf303dd7a4a052b104a43857a1
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That is basically correct. its a little more complicated then that but if
you have a stimulus that lasts for 6 seconds then setting the duration to 6
seconds is the way to go. If however you want to look at the irf progression
over those 6 seconds, you should look at using fir.
Cheers,
Michael
On Thu, May 26, 2011 at 5:21 PM, alekhya mandadi <[log in to unmask]>wrote:
> Hi All,
>
> I have a question regarding onsets in specify 1st level.
>
> Lets say my onset times are [4 23 56 72 92 120]
>
> I want to analyze the data from the start of the onset time to the next 6
> seconds. Or to better put it I want to analyze the data from [4 23 56 72 92
> 120] to [10 29 62 78 98 126]
>
> Where do I enter this information? Is it where it says Durations right
> below Onsets?
>
> Your help will be greatly appreciated.
>
> Thanks so much!
>
> Best,
> Alekhya Mandadi
> Research Assistant
> Center for Neural Decision Making
> Temple Fox School of Business
> http://www.fox.temple.edu/minisites/neural/people.html
>
--
Research Associate
Gazzaley Lab
Department of Neurology
University of California, San Francisco
--20cf303dd7a4a052b104a43857a1
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
That is basically correct. its a little more complicated then that but if y=
ou have a stimulus that lasts for 6 seconds then setting the duration to 6 =
seconds is the way to go. If however you want to look at the irf progressio=
n over those 6 seconds, you should look at using fir.<br>
<br>Cheers,<br>Michael<br><br><div class=3D"gmail_quote">On Thu, May 26, 20=
11 at 5:21 PM, alekhya mandadi <span dir=3D"ltr"><<a href=3D"mailto:alek=
[log in to unmask]">[log in to unmask]</a>></span> wrote:<br><bloc=
kquote class=3D"gmail_quote" style=3D"margin: 0pt 0pt 0pt 0.8ex; border-lef=
t: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
Hi All,<br><br>I have a question regarding onsets in specify 1st level.<br>=
<br>Lets say my onset times are [4 23 56 72 92 120] <br><br>I want to analy=
ze the data from the start of the onset time to the next 6 seconds. Or to b=
etter put it I want to analyze the data from [4 23 56 72 92 120]=C2=A0 to [=
10 29 62 78 98 126]<br>
<br>Where do I enter this information? Is it where it says Durations right =
below Onsets? <br><br>Your help will be greatly appreciated.<br><br>Thanks =
so much!<br><br>Best,<br><font color=3D"#888888">Alekhya Mandadi<br>Researc=
h Assistant <br>
Center for Neural Decision Making<br>
Temple Fox School of Business <br><a href=3D"http://www.fox.temple.edu/mini=
sites/neural/people.html" target=3D"_blank">http://www.fox.temple.edu/minis=
ites/neural/people.html</a><br>
</font></blockquote></div><br><br clear=3D"all"><br>-- <br>Research Associa=
te<br>Gazzaley Lab<br>Department of Neurology<br>University of California, =
San Francisco<br>
--20cf303dd7a4a052b104a43857a1--
=========================================================================
Date: Fri, 27 May 2011 01:36:32 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: Explicit masking during statitical analysis
Comments: To: hekmatyar <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0015174fed6c020a9504a43b5216
Message-ID: <[log in to unmask]>
--0015174fed6c020a9504a43b5216
Content-Type: text/plain; charset=ISO-8859-1
Yes. Under the explicit mask option when you set up the model.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Thu, May 26, 2011 at 9:39 PM, hekmatyar <[log in to unmask]> wrote:
> Hello SPMers
> When I do statistical analysis without masking the outer tissue, I used to
> see lot of activations from outer tissue, Is there any way to apply mask
> explicitly during Ist level statistical analysis?
> Please let me know
> Thanks
> Shah
>
--0015174fed6c020a9504a43b5216
Content-Type: text/html; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Yes. Under the explicit mask option when you set up the model.<div><br>Best=
Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdoctoral Research Fellow, GRECC, Bedfo=
rd VA<br>Research Fellow, Department of Neurology, Massachusetts General Ho=
spital and Harvard Medical School<br>
Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which may =
contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED=
and which is intended only for the use of the individual or entity named a=
bove. If the reader of the e-mail is not the intended recipient or the empl=
oyee or agent responsible for delivering it to the intended recipient, you =
are hereby notified that you are in possession of confidential and privileg=
ed information. Any unauthorized use, disclosure, copying or the taking of =
any action in reliance on the contents of this information is strictly proh=
ibited and may be unlawful. If you have received this e-mail unintentionall=
y, please immediately notify the sender via telephone at (773) 406-2464 or =
email.<br>
<br><br><div class=3D"gmail_quote">On Thu, May 26, 2011 at 9:39 PM, hekmaty=
ar <span dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">skhekmat@h=
otmail.com</a>></span> wrote:<br><blockquote class=3D"gmail_quote" style=
=3D"margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
Hello SPMers<br>
When I do statistical analysis without masking the outer tissue, I used to<=
br>
see lot of activations from outer tissue, Is there any way to apply mask<br=
>
explicitly during Ist level statistical analysis?<br>
Please let me know<br>
Thanks<br>
Shah<br>
</blockquote></div><br></div>
--0015174fed6c020a9504a43b5216--
=========================================================================
Date: Fri, 27 May 2011 07:05:19 +0100
Reply-To: Cath <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Cath <[log in to unmask]>
Subject: small volume correction vs. mask and other related questions
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear SPM experts,
I have a problem regarding the inclusive mask. My conducted a masked pri=
ming lexical decision task, and the procedure started with a fixation, a =
mask, a prime, another mask and finally a target word (all within one TR)=
. The prime could be a word which was visually similar/dissimilar to the =
target word. The position of the prime and the target could be a total bl=
ank. I defined a prime contrast (dissimilar minus similar) and a word con=
trast (target word present minus blank ). I looked for activated voxels o=
f the priming effect within the constraint of the activation maps of the =
word contrast. So in the second level analysis, I used small volume corre=
ction on the prime contrast by entering the image of the word contrast. I=
expected that the activated voxel number under the prime contrast should=
decrease after I entered the word contrast in the small volume correctio=
n. However, the activated voxel number under the prime contrast actually =
increased after I entered the word contrast in the small volume correctio=
n. Could you please tell me why it was that?=20
What is the difference between using a mask and using the small volume co=
rrection? Finally, what is the difference between percent signal changes =
and beta value and how to output the percent signal changes over multiple=
voxels?=20
Thank you!
Sincerely,
Cath
=========================================================================
Date: Fri, 27 May 2011 16:21:11 +1000
Reply-To: Mayuresh K <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Mayuresh K <[log in to unmask]>
Subject: Power analysis
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=000e0cd40312af5dfb04a43bf118
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--000e0cd40312af5dfb04a43bf118
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Hello spm experts,
Could anyone guide me how to do a power analysis using fMRI or VBM data? I
have performed a random effects analysis comparing two groups of subjects
using their fMRI and VBM data. I have found a number of regions with
significant differences for both data sets.
I can probably calculate the mean and standard deviation of the %signal
change (or volume) for each group for the peak voxels say in a particular
anatomical region. Then use these to calculate effect sizes and power - Is
this a valid approach?
Any other suggestions welcome.
Thanks,
Mayuresh
--000e0cd40312af5dfb04a43bf118
Content-Type: text/html; charset=ISO-8859-1
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Hello spm experts,<br><br>Could anyone guide me how to do a power analysis =
using fMRI or VBM data? I have performed a random effects analysis comparin=
g two groups of subjects using their fMRI and VBM data. I have found a numb=
er of regions with significant differences for both data sets. <br>
I can probably calculate the mean and standard deviation of the %signal cha=
nge (or volume) for each group for the peak voxels say in a particular anat=
omical region. Then use these to calculate effect sizes and power - Is this=
a valid approach? <br>
Any other suggestions welcome.<br><br>Thanks,<br>Mayuresh=A0 <br><br>
--000e0cd40312af5dfb04a43bf118--
=========================================================================
Date: Fri, 27 May 2011 08:34:22 +0200
Reply-To: Marko Wilke <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Marko Wilke <[log in to unmask]>
Subject: Re: VBM Question: Making Custom TPM.nii with TOM8
Comments: To: Phil Greer <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Hello Phil,
> First, thank you for your work in creating a toolbox that will allow
> creation of a custom TPM file. It is a very interesting toolbox, but
> I feel I may be missing something in the instructions.
First, thanks for the flowers :)
> To be specific, I am having issues in understanding exactly what
> images to use as the input when creating the TOM.mat file. I think I
> am suppose to use the normalized, unmodulated segmented files for
> each tissue type (c1* c2*, etc). Is this correct?
Well, yes, you would enter the wc*. I prefer the affine-only registered=20
version, more below.
> If one uses the VBM8 toolbox, there is no option to write out all 6
> classes of images, only gm, wm and csf. How does one get the other
> tissue files?
I have actually never looked at that but it seems that one can trick the
toolbox into doing this when modifying lines 75-79 (in the current
version) of cg_vbm8_run:
% never write class 4-6
for i=3D4:6
tissue(i).warped =3D [0 0 0];
tissue(i).native =3D [0 0 0];
end
If you adapt those lines according to what you want, that should do it.
> If you use the results of new segment, as per the current VBM
> instructions in SPM8, one gets nonlinear transformed segmented images
> that may have some segmentation artifacts (at least that is the case
> for many of my elderly subjects).
I agree that especially for "unusual" subjects, VBM8 is likely to give
better results. One way around the non-linear normalization would be to
write out the tissue classes in native space and then do an affine-only
normalization onto the corresponding tissue class that comes with spm
(i.e., normalize c1 to grey.img and take along the other classes). In
the TOM paper, we actually normalized each class and averaged the
parameters, which seemed like a good idea at that time but I am not sure
this really makes that much of a difference.
> So if I want to create a 6 tissue TPM.nii file, what images should I
> use?
Assuming I was right, you have two choices now :)
Hope this helps,
Marko
--=20
____________________________________________________
PD Dr. med. Marko Wilke
Facharzt f=FCr Kinder- und Jugendmedizin
Leiter, Experimentelle P=E4diatrische Neurobildgebung
Universit=E4ts-Kinderklinik
Abt. III (Neurop=E4diatrie)
Marko Wilke, MD, PhD
Pediatrician
Head, Experimental Pediatric Neuroimaging
University Children's Hospital
Dept. III (Pediatric Neurology)
Hoppe-Seyler-Str. 1
D - 72076 T=FCbingen, Germany
Tel. +49 7071 29-83416
Fax +49 7071 29-5473
[log in to unmask]
http://www.medizin.uni-tuebingen.de/kinder/epn
____________________________________________________
=========================================================================
Date: Fri, 27 May 2011 08:18:19 +0100
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From: =?utf-8?B?Y3lyaWwucGVybmV0QGVkLmFjLnVr?= <[log in to unmask]>
Subject: Re: small volume correction vs. mask and other related questions
Comments: To: Cath <[log in to unmask]>
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=========================================================================
Date: Fri, 27 May 2011 10:46:58 +0100
Reply-To: Molly Henry <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Molly Henry <[log in to unmask]>
Subject: comparing trials with different durations
Mime-Version: 1.0
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Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear SPM Users,
I know variants of this question appear in the archives. However I still =
don't understand what I can practically *do* to help this problem, so I a=
sk a new version of an old question.=20
In a design where trials making up two to-be-compared conditions by natur=
e have different durations, the assumption is that the longer trials will=
have overall a higher HRF amplitude (although why / when this happens de=
pends on use of impluse vs. epoch functions). If I compare the short tria=
ls to the long trials (the two trial types happen in separate blocks), is=
it likely that differences in signal change are an artifact of modeling =
assumptions regarding HRF amplitude? If so, which direction should I expe=
ct artifactual differences (short < long or long < short)? And finally, w=
hat strategy can I use to combat this possible problem.=20
Humbly,
Molly
=========================================================================
Date: Fri, 27 May 2011 12:43:51 +0200
Reply-To: Martin Dietz <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Martin Dietz <[log in to unmask]>
Subject: Re: question regarding matlabbatch struct/class
Comments: To: Volkmar Glauche <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Content-Type: text/plain; charset="us-ascii"
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Message-ID: <[log in to unmask]>
Dear Volkmar & list,
When running spm_jobman from the command line in 'serial' mode, what is the=
correct input format for dicom files/already imported nifti files, respect=
ively ?=20
Best wishes,
Martin=20
On May 26, 2011, at 10:04 AM, Volkmar Glauche wrote:
> To run a batch from MATLAB command line, SPM always has to be initialised=
. At least,=20
>=20
> spm_jobman('initcfg')
>=20
> should be run before. If one needs to rely on defaults which can not be s=
et in a batch (e.g. in first level fMRI analysis), one should run
>=20
> spm('defaults','fmri') =18r 'pet' or 'eeg', depending on the modality
> spm_jobman('initcfg')
>=20
> Best,
>=20
> Volkmar
=========================================================================
Date: Fri, 27 May 2011 13:05:35 +0200
Reply-To: Raphael Hilgenstock <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Raphael Hilgenstock <[log in to unmask]>
Subject: Re: Power analysis
Comments: To: Mayuresh K <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
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Hi Mayuresh,
you might want to use the "threshold and transform spm-t/F-maps" option
as implemented in the VBM8 toolbox
(http://dbm.neuro.uni-jena.de/software/) which allows you to calculate
effect size measure 'd' for the respective spm-volume. I hope this helps.
Best regards
Raphael
Am 27.05.2011 08:21, schrieb Mayuresh K:
> Hello spm experts,
>
> Could anyone guide me how to do a power analysis using fMRI or VBM
> data? I have performed a random effects analysis comparing two groups
> of subjects using their fMRI and VBM data. I have found a number of
> regions with significant differences for both data sets.
> I can probably calculate the mean and standard deviation of the
> %signal change (or volume) for each group for the peak voxels say in a
> particular anatomical region. Then use these to calculate effect sizes
> and power - Is this a valid approach?
> Any other suggestions welcome.
>
> Thanks,
> Mayuresh
>
=========================================================================
Date: Fri, 27 May 2011 12:58:49 +0100
Reply-To: Alexa Morcom <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Alexa Morcom <[log in to unmask]>
Subject: Re: Power analysis
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<[log in to unmask]>
Date: Fri, 27 May 2011 12:58:49 +0100
Message-ID: <[log in to unmask]>
Subject: Re: [SPM] Power analysis
From: Alexa Morcom <[log in to unmask]>
To: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
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Hello Mayuresh
Jeanette Mumford has some great resources on this and related issues at:
http://mumford.bol.ucla.edu/ and see her 2008 paper with Tom Nichols
The software for doing power analyses in FSL is at http://fmripower.org/ -
this takes autocorrelation and design into account
It would be great to see this or something like it for SPM!
cheers
Alexa
On 27 May 2011 12:05, Raphael Hilgenstock
<[log in to unmask]>wrote:
> Hi Mayuresh,
>
> you might want to use the "threshold and transform spm-t/F-maps" option as
> implemented in the VBM8 toolbox (http://dbm.neuro.uni-jena.de/software/)
> which allows you to calculate effect size measure 'd' for the respective
> spm-volume. I hope this helps.
>
> Best regards
> Raphael
>
> Am 27.05.2011 08:21, schrieb Mayuresh K:
>
>> Hello spm experts,
>>
>> Could anyone guide me how to do a power analysis using fMRI or VBM data? I
>> have performed a random effects analysis comparing two groups of subjects
>> using their fMRI and VBM data. I have found a number of regions with
>> significant differences for both data sets.
>> I can probably calculate the mean and standard deviation of the %signal
>> change (or volume) for each group for the peak voxels say in a particular
>> anatomical region. Then use these to calculate effect sizes and power - Is
>> this a valid approach?
>> Any other suggestions welcome.
>>
>> Thanks,
>> Mayuresh
>>
>>
>
--
Dr. Alexa Morcom
RCUK Academic Fellow
Centre for Cognitive & Neural Systems/ Centre for Cognitive Ageing &
Cognitive Epidemiology
Psychology, University of Edinburgh
http://www.ccns.sbms.mvm.ed.ac.uk/people/academic/morcom.html
The University of Edinburgh is a charitable body, registered in Scotland,
with registration number SC005336
--bcaec51f8fed2ab38504a440a916
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Hello Mayuresh<br><br>Jeanette Mumford has some great resources on this and=
related issues at:<br><br><a href=3D"http://mumford.bol.ucla.edu/">http://=
mumford.bol.ucla.edu/</a> and see her 2008 paper with Tom Nichols <br><br>
The software for doing power analyses in FSL is at <a href=3D"http://fmripo=
wer.org/">http://fmripower.org/</a> - this takes autocorrelation and design=
into account<br><br>It would be great to see this or something like it for=
SPM!<br>
<br>cheers<br><br>Alexa <br><br><div class=3D"gmail_quote">On 27 May 2011 1=
2:05, Raphael Hilgenstock <span dir=3D"ltr"><<a href=3D"mailto:Raphael.H=
[log in to unmask]">[log in to unmask]</a>></span> wrot=
e:<br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex;">Hi Mayuresh,<br>
<br>
you might want to use the "threshold and transform spm-t/F-maps" =
option as implemented in the VBM8 toolbox (<a href=3D"http://dbm.neuro.uni-=
jena.de/software/" target=3D"_blank">http://dbm.neuro.uni-jena.de/software/=
</a>) which allows you to calculate effect size measure 'd' for the=
respective spm-volume. I hope this helps.<br>
<br>
Best regards<br>
Raphael<br>
<br>
Am 27.05.2011 08:21, schrieb Mayuresh K:<br>
<blockquote class=3D"gmail_quote" style=3D"margin:0 0 0 .8ex;border-left:1p=
x #ccc solid;padding-left:1ex">
Hello spm experts,<br>
<br>
Could anyone guide me how to do a power analysis using fMRI or VBM data? I =
have performed a random effects analysis comparing two groups of subjects u=
sing their fMRI and VBM data. I have found a number of regions with signifi=
cant differences for both data sets.<br>
I can probably calculate the mean and standard deviation of the %signal cha=
nge (or volume) for each group for the peak voxels say in a particular anat=
omical region. Then use these to calculate effect sizes and power - Is this=
a valid approach?<br>
Any other suggestions welcome.<br>
<br>
Thanks,<br>
Mayuresh<br>
<br>
</blockquote>
<br>
</blockquote></div><br><br clear=3D"all"><br>-- <br><font size=3D"2">Dr. Al=
exa Morcom<br>RCUK Academic Fellow<br>Centre for Cognitive & Neural Sys=
tems/ Centre for Cognitive Ageing & Cognitive Epidemiology<br>Psycholog=
y, University of Edinburgh<br>
<a href=3D"http://www.ccns.sbms.mvm.ed.ac.uk/people/academic/morcom.html" t=
arget=3D"_blank">http://www.ccns.sbms.mvm.ed.ac.uk/people/academic/morcom.h=
tml</a> <br><br>The University of Edinburgh is a charitable body, registere=
d in Scotland, with registration number SC005336 =A0</font><p>
</p>
<br>
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=========================================================================
Date: Fri, 27 May 2011 13:09:41 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: 1d images
Comments: To: Mkael Symmonds <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Dear Mkael,
According to Guillaume, if the signal of interest is in the first
dimension of an image file, everything should work normally. I've
never tried it myself.
Best,
Vladimir
On Fri, May 27, 2011 at 1:06 PM, Mkael Symmonds <[log in to unmask]> wrote:
>
> Hi Vladimir
> Do you know if it is possible to use SPM to analyse 1d images (of power at
> single band in a single channel over trials) ?
> Best
> Gareth and Mkael
>
=========================================================================
Date: Fri, 27 May 2011 16:12:38 +0100
Reply-To: Jasmin Tr=?UTF-8?Q?=C3=B6stl?= <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jasmin Tr=?UTF-8?Q?=C3=B6stl?= <[log in to unmask]>
Subject: Re: Help with DTI DARTEL
Comments: To: Donald McLaren <[log in to unmask]>
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear dartel specialists,
I am following the outlines from the paper posted in the previous message=
: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2889147/?tool=3Dpubmed
Everything works fine until the following steps:
"(c) the custom FA template was normalized to the custom T1-weighted temp=
late using 12 parameters in FLIRT [http://www.fmrib.ox.ac.uk/fsl/flirt/in=
dex.html, 37];
(d) native space FA and MD images were normalized to the custom FA templa=
te (from step (c));=20
(e) the normalization parameters from step (d) were multiplied by the inv=
erse transformation parameters for the second T1-weighted segmentation (V=
BM step (iv)) and applied to both the FA and MD images;=20
(f) FA and MD images were rigidly aligned using the rigid-body component =
of the transformations produced in VBM step (iv) and resampled to 1.5 mm =
isotropic voxels;"=20
but step (d) and (e) make problems.=20
In step (d) I just normalize the FA and MD images to the new custom FA te=
mplate using Estimate and Normalize from SPM8.
In step (e) I use the inverse transformation matrix from the second run o=
f the VBM5.1 toolbox estimate and write (segment and normalization to cus=
tom prior I calculated from the first run). I just use normalize(write) t=
o normalize the images resulting from step (d).
In step (f) I apply the non inverse transformation matrix from the second=
run of the VBM5.1 on the results of (e) using Normalise(write) with foll=
owing options: bounding box filled with NaNs and Voxelsize with 1.5 1.5 1=
.5=20
when I look at the results I see the following:
after step (d) the images are kind of "compressed" and after step (e) par=
ts of the brain are just missing (cut off).
I try to follow the guidelines of the paper mentioned above. I am new to =
VBM-Dartel methods and I don't know what I am doing wrong.=20
Thank you in advance for every hint and improvement you can give me!
Best regards
Jasmin Tr=C3=B6stl
=========================================================================
Date: Fri, 27 May 2011 16:14:12 +0100
Reply-To: "<Emma> <Smith>" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "<Emma> <Smith>" <[log in to unmask]>
Subject: Masking with contrast images from other analysis in spm8
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear SPM experts,
Can somebody point out how to use explicit masking with a contrast image =
form a different analysis in spm8 (the program allows only for masking wi=
th a contrast from the same model)?
Thank you.
Emma
=========================================================================
Date: Fri, 27 May 2011 16:17:21 +0000
Reply-To: Giuseppe Signorello <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Giuseppe Signorello <[log in to unmask]>
Subject: T and F Contrasts
Content-Type: multipart/alternative;
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Content-Transfer-Encoding: quoted-printable
I'm working with FMRI files.
After the preprocessing=2C I should extract time series.
How do I define the T and F contrasts?
Thank for your answer.
G.S.
=
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I'm working with FMRI files.<br>After the preprocessing=2C I should extract=
time series.<br>How do I define the T and F contrasts?<br>Thank for your a=
nswer.<br>G.S.<br><br> </body>
</html>=
--_98233e86-6917-445c-a5b3-570a3e509750_--
=========================================================================
Date: Fri, 27 May 2011 09:19:38 -0700
Reply-To: "Jiang, Zhiguo" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Jiang, Zhiguo" <[log in to unmask]>
Subject: Re: T and F Contrasts
Comments: To: Giuseppe Signorello <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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I think you need to be more specific about what you are asking for so someo=
ne can help you.
---------------------------------------------------------------------------=
---------------------------------------------------
[cid:image001.jpg@01CC1C4F.33ED5E10]
Tony Jiang,Ph.D.|Research Scholar|University of California, Los Angeles
Peter V. Ueberroth Building, Rm 2338C2|10945 Le Conte Avenue. Los Angeles,C=
A 90095
Tel: (310)206-1423|Email: [log in to unmask]
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] On B=
ehalf Of Giuseppe Signorello
Sent: Friday, May 27, 2011 9:17 AM
To: [log in to unmask]
Subject: [SPM] T and F Contrasts
I'm working with FMRI files.
After the preprocessing, I should extract time series.
How do I define the T and F contrasts?
Thank for your answer.
G.S.
________________________________
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<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";
color:#1F497D">I think you need to be more specific about what you are aski=
ng for so someone can help you.
<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";
color:#1F497D"><o:p> </o:p></span></p>
<div>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";
color:#1F497D">------------------------------------------------------------=
------------------------------------------------------------------<o:p></o:=
p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";
color:#1F497D"><img width=3D"448" height=3D"48" id=3D"Picture_x0020_1" src=
=3D"cid:image001.jpg@01CC1C4F.33ED5E10" alt=3D"logo"><o:p></o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";
color:#1F497D">Tony Jiang,Ph.D.|Research Scholar|University of California, =
Los Angeles<br>
Peter V. Ueberroth Building, Rm 2338C2|10945 Le Conte Avenue. Los Angeles,C=
A 90095<o:p></o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";
color:#1F497D">Tel: (310)206-1423|Email: [log in to unmask]<o:p></=
o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";
color:#1F497D"><o:p> </o:p></span></p>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";
color:#1F497D"><o:p> </o:p></span></p>
</div>
<p class=3D"MsoNormal"><span style=3D"font-size:11.0pt;font-family:"Ca=
libri","sans-serif";
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<div>
<div style=3D"border:none;border-top:solid #B5C4DF 1.0pt;padding:3.0pt 0in =
0in 0in">
<p class=3D"MsoNormal"><b><span style=3D"font-size:10.0pt;font-family:"=
;Tahoma","sans-serif"">From:</span></b><span style=3D"font-s=
ize:10.0pt;font-family:"Tahoma","sans-serif""> SPM (Sta=
tistical Parametric Mapping) [mailto:[log in to unmask]]
<b>On Behalf Of </b>Giuseppe Signorello<br>
<b>Sent:</b> Friday, May 27, 2011 9:17 AM<br>
<b>To:</b> [log in to unmask]<br>
<b>Subject:</b> [SPM] T and F Contrasts<o:p></o:p></span></p>
</div>
</div>
<p class=3D"MsoNormal"><o:p> </o:p></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:12.0pt"><span style=3D"font-s=
ize:10.0pt;
font-family:"Tahoma","sans-serif"">I'm working with FMR=
I files.<br>
After the preprocessing, I should extract time series.<br>
How do I define the T and F contrasts?<br>
Thank for your answer.<br>
G.S.<o:p></o:p></span></p>
</div>
<br>
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are obligated to maintain it in a safe, secure and confidential manner. Un=
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you to federal and state penalties. If you are not the intended recipient, =
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return email, and delete this message from your computer.<br>
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=========================================================================
Date: Fri, 27 May 2011 13:42:15 -0400
Reply-To: Xin Di <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Xin Di <[log in to unmask]>
Subject: mis-classification of gray matter using New segment tools
MIME-Version: 1.0
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Message-ID: <[log in to unmask]>
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Dear experts,
I am using the new segment tool to run segmentations on several MRI images.
For one of the subject, the tissues outside the cortices are mis-classified
as gray matter and warped into the cortices after normalization (please see
attached figures). I use the default settings of number of Gaussians for
each tissue type. Can someone kindly give me some suggestions on how to
avoid this mis-classification? Thank you!
Sincerely,
--
Xin Di, PhD
Postdoctoral Researcher
Department of Radiology
University of Medicine and Dentistry of New Jersey
30 Bergen Street, ADMC 575
Newark, NJ 07101
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Content-Type: text/html; charset=ISO-8859-1
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Dear experts,<br><br>I am using the new segment tool to run segmentations o=
n several MRI images. For one of the subject, the tissues outside the corti=
ces are mis-classified as gray matter and warped into the cortices after no=
rmalization (please see attached figures). I use the default settings of nu=
mber of Gaussians for each tissue type. Can someone kindly give me some sug=
gestions on how to avoid this mis-classification? Thank you!<br>
<br>Sincerely,<br clear=3D"all"><br>-- <br>Xin Di, PhD<br><br>Postdoctoral =
Researcher<br>Department of Radiology<br>University of Medicine and Dentist=
ry of New Jersey<br>
30 Bergen Street, ADMC 575<br>Newark, NJ 07101<br><br>
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--000e0cd1512a8aeab904a44576a2--
=========================================================================
Date: Fri, 27 May 2011 19:52:36 +0100
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Subject: Re: Masking with contrast images from other analysis in spm8
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=========================================================================
Date: Sat, 28 May 2011 00:35:28 +0100
Reply-To: David Soto <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: David Soto <[log in to unmask]>
Subject: Re: second level analysis affected by subject order
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Dear SPM list,
I have replicated this issue in my data. I can't think of any reason behi=
nd
but it seems like a bug to me and any implications ought to be addressed.=
..
hope this is not much of a hassle!
Regards, david
=========================================================================
Date: Fri, 27 May 2011 20:09:23 -0400
Reply-To: Lucy Brown <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Lucy Brown <[log in to unmask]>
Subject: Re: second level analysis affected by subject order
Comments: To: David Soto <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-version: 1.0
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Do you mean the order that the subjects' contrast files were entered for the group analysis?
Best,
Lucy
On May 27, 2011, at 7:35 PM, David Soto wrote:
> Dear SPM list,
>
> I have replicated this issue in my data. I can't think of any reason behind
> but it seems like a bug to me and any implications ought to be addressed...
>
> hope this is not much of a hassle!
>
> Regards, david
Lucy L. Brown, Ph.D.
Professor
Department of Neurology
Department of Neuroscience
Albert Einstein College of Medicine
1300 Morris Park Ave. 125F
Bronx, NY 10461
917-407-3266
[log in to unmask]
=========================================================================
Date: Sat, 28 May 2011 14:10:06 +0900
Reply-To: Yuko <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Yuko <[log in to unmask]>
Subject: Problem to decide the coordinate for eigenvariate and DCM
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
Dear all
I would like to ask one question about DCM.
I tried to extract time-series for DCM, therefor I used eigenvariate
and decided a coordinate, but SPM8 changed the coordinate
automatically.
How could I extract the time-series from the VOI which I decided.
Any help will be highly appreciated.
Thank you in advance.
Yuko
=========================================================================
Date: Sun, 29 May 2011 15:32:14 +0930
Reply-To: Leon Petchkovsky <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Leon Petchkovsky <[log in to unmask]>
Subject: The Jugain complexes and some help with DCM
MIME-Version: 1.0
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--00151759312a9c3d5304a463e92f
Content-Type: text/plain; charset=windows-1252
Content-Transfer-Encoding: quoted-printable
Dear all
I need some advice and help with DCM.
The study involved a replication of Jung=92s original Word Association test
under fMRI conditions. The subject is asked to respond with the first word
that comes to mind in response to a stimulus word from a standard list. Mos=
t
responses are bland and neutral, but some of them are not. Response time is
prolonged, response are often idiosyncratic and affect =96laden. Jung infer=
red
internal conflict (his so-called =93complexes=94) from these unusual respo=
nses.
We ran 14 subjects thru 100 words, 20 second epoch for each . We compared
complexed versus neutral responses for the group for the entire 20 sec
epoch. (using SPM 5)
I also split it up into 3 second bits (first 3 seconds, 2nd 3 etc etc) to
get some idea of what goes on over time, to construct a functional
hypothesis that could be subjected to DCM testing. .
The complexed responses =93pattern=94 that survived FWE correction seem to =
go
like this.
FIRST 3 SECS.
There is strong activation (corrected for FEW) in (1) L Broca=92s pre
Broca=92s, Z 5.58 (2) the L Middle temporal lobe Z 4.96, (3) L SMA/middle
cingulate Z 4.97 and (4) L Anterior Insula Z 5.11 (all probably reflectin=
g
the conflicted word searching of a complexed response).
But there is also homologous activation of all these areas in the R
hemisphere, albeit more weakly. (???interhemispheric negotiation/chatter
whatever). (R Broca Z 4.85, R Mid Temp Z 4.77, R insula Z 4.77)
However, there is a SMALL area in R prefrontal region at 54,4, 47 (R
precentral Area 6), which stands out on its own, 16 voxel Z 5.38, p FWE
corr .001. This is the second strongest response in the entire result list.
I don=92t know * what * to make of it.
SECOND THREE SECS.
Same as above , BUT, there is a brief bit of R supraorbital (43 29 -6)
activity (p FWE corr .038, Z 4.14) probably to do with the executive
effort of the conflictual nature of the =93complexed=92 response. And activ=
ity
shifts to from L to R SMA Z 5.28 !
The REST of the epoch achieves nothing that passes the FWE FDR barrier.
So I suppose a model might say that there is some some antero-posterior
(receptive-expressive verbal) activity; with inter-hemispheric negotiations
which include SMA and cingulum; and cortico-mesencephalic-limbic (Bilate=
ral
Anterior Insula) interaction, with R supraorbital (executive function)
region coming on line a little later.
But this still doesn=92t account for the weird SMALL but very prominent =
R
precentral Area 6 region at 54,4, 47 .
Does anyone have any suggestions on how I might model this in DCM? Or for
that matter whether DCM could even do this in principle? Since my limited
understanding of DCM is that you can only do about 3 ROIs at a time ?
I=92ve asked my local colleagues, but they can=92t seem to come up with
anything.
.
Leon
--=20
*A/Prof Leon Petchkovsky
Psychiatrist, Jungian Analyst
Past President, ANZSJA
Director, the Pinniger Clinic, HQ@Robina
www.pinnigerclinic.com
0755809397
0420923885*
--00151759312a9c3d5304a463e92f
Content-Type: text/html; charset=windows-1252
Content-Transfer-Encoding: quoted-printable
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">Dear all </f=
ont></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">I need some =
advice and help with<span style=3D"mso-spacerun: yes">=A0 </span>DCM.</font=
></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">The study in=
volved a replication of Jung=92s original Word Association test under fMRI =
conditions.<span style=3D"mso-spacerun: yes">=A0 </span>The subject is aske=
d to respond with the first word that comes to mind in response to a stimul=
us word from a standard list. Most responses are bland and neutral, but som=
e of them are not. Response time is prolonged, response are often idiosyncr=
atic and affect =96laden. Jung inferred internal conflict<span style=3D"mso=
-spacerun: yes">=A0 </span>(his so-called =93complexes=94) from these unusu=
al responses.</font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3"><span style=
=3D"mso-spacerun: yes">=A0</span>We ran 14 subjects thru 100 words, 20 seco=
nd epoch for each . We compared complexed versus neutral responses for the =
group for the entire 20 sec epoch. (using SPM 5)</font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">I also split=
it <span style=3D"mso-spacerun: yes">=A0</span>up into 3 second bits (firs=
t 3 seconds, 2<sup>nd</sup> 3 etc etc) to get some idea of what goes on ove=
r time, to construct a functional hypothesis that could be subjected to DCM=
testing.<span style=3D"mso-spacerun: yes">=A0 </span>. </font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">The complexe=
d responses =93pattern=94 that survived FWE correction seem to go like this=
. </font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">FIRST 3 SECS=
.<span style=3D"mso-spacerun: yes">=A0 </span></font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">There is<spa=
n style=3D"mso-spacerun: yes">=A0 </span>strong activation (corrected for F=
EW) <span style=3D"mso-spacerun: yes">=A0</span>in (1) <span style=3D"mso-s=
pacerun: yes">=A0</span>L Broca=92s pre Broca=92s, Z 5.58<span style=3D"mso=
-spacerun: yes">=A0 </span>(2) the L Middle temporal lobe Z 4.96, (3) <span=
style=3D"mso-spacerun: yes">=A0</span>L SMA/middle cingulate<span style=3D=
"mso-spacerun: yes">=A0 </span>Z 4.97 and (4) L Anterior Insula <span style=
=3D"mso-spacerun: yes">=A0</span>Z 5.11 (all probably reflecting the confli=
cted word searching of a complexed response).</font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">But there is=
also homologous activation of all these areas in the R hemisphere, albeit =
more weakly. (???interhemispheric negotiation/chatter whatever). <span styl=
e=3D"mso-spacerun: yes">=A0</span>(R Broca Z 4.85, R Mid Temp Z<span style=
=3D"mso-spacerun: yes">=A0 </span>4.77,<span style=3D"mso-spacerun: yes">=
=A0 </span>R insula Z 4.77) </font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">However, the=
re is a SMALL area in R prefrontal region at 54,4, 47 (R precentral<span st=
yle=3D"mso-spacerun: yes">=A0 </span>Area 6),<span style=3D"mso-spacerun: y=
es">=A0 </span>which stands out on its own,<span style=3D"mso-spacerun: yes=
">=A0 </span>16 voxel<span style=3D"mso-spacerun: yes">=A0 </span>Z 5.38, p=
FWE corr .001. This is the second strongest response in the entire result =
list.<span style=3D"mso-spacerun: yes">=A0 </span>I don=92t know <i style=
=3D"mso-bidi-font-style: normal"><span style=3D"mso-spacerun: yes">=A0</spa=
n>what </i><span style=3D"mso-spacerun: yes">=A0</span>to make of it. </fon=
t></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">SECOND THREE=
SECS.</font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">Same as abov=
e , BUT, there is a brief<span style=3D"mso-spacerun: yes">=A0 </span>bit o=
f R supraorbital<span style=3D"mso-spacerun: yes">=A0 </span>(43 29 -6) act=
ivity<span style=3D"mso-spacerun: yes">=A0 </span>(p FWE corr <span style=
=3D"mso-spacerun: yes">=A0</span>.038,<span style=3D"mso-spacerun: yes">=A0=
</span>Z 4.14) probably to do with the executive effort of the conflictual=
nature of the =93complexed=92 response. And activity shifts to from L to R=
SMA <span style=3D"mso-spacerun: yes">=A0</span>Z 5.28 !</font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">=A0</font></=
span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">The REST of =
the epoch achieves nothing that passes the FWE FDR<span style=3D"mso-spacer=
un: yes">=A0 </span>barrier. </font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">=A0</font></=
span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">So I suppose=
a model<span style=3D"mso-spacerun: yes">=A0 </span>might say that there i=
s some some antero-posterior (receptive-expressive verbal) activity; with i=
nter-hemispheric negotiations which include SMA and cingulum;<span style=3D=
"mso-spacerun: yes">=A0=A0 </span>and cortico-mesencephalic-limbic<span sty=
le=3D"mso-spacerun: yes">=A0 </span>(Bilateral Anterior Insula)<span style=
=3D"mso-spacerun: yes">=A0 </span>interaction, with R supraorbital (executi=
ve function) region coming on line a little later.</font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">=A0</font></=
span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">But this sti=
ll doesn=92t account for<span style=3D"mso-spacerun: yes">=A0 </span>the we=
ird<span style=3D"mso-spacerun: yes">=A0 </span>SMALL but very prominent <s=
pan style=3D"mso-spacerun: yes">=A0</span>R precentral<span style=3D"mso-sp=
acerun: yes">=A0 </span>Area 6 region at 54,4, 47 . </font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">=A0</font></=
span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">Does anyone =
have any suggestions on how I might model this in DCM?<span style=3D"mso-sp=
acerun: yes">=A0 </span>Or for that matter whether DCM could even do this i=
n principle? Since my limited understanding of DCM is that you can only do =
about 3 ROIs at a time ? </font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">I=92ve asked=
my local colleagues, but they can=92t seem to come up with anything.</font=
></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">=A0</font></=
span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">=A0</font></=
span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">.</font></sp=
an></p>Leon<br clear=3D"all"><br>-- <br><b style=3D"COLOR: rgb(0,0,0)">A/Pr=
of Leon Petchkovsky<br>
Psychiatrist, Jungian Analyst<br>Past President, ANZSJA<br>Director, the Pi=
nniger Clinic, HQ@Robina<br><a href=3D"http://www.pinnigerclinic.com/" targ=
et=3D"_blank">www.pinnigerclinic.com</a><br>0755809397<br>0420923885</b><br=
>
--00151759312a9c3d5304a463e92f--
=========================================================================
Date: Sun, 29 May 2011 15:35:09 +0930
Reply-To: Leon Petchkovsky <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Leon Petchkovsky <[log in to unmask]>
Subject: Trying again, the JUNGIAN complexes and DCM
MIME-Version: 1.0
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Dear all
I need some advice and help with DCM.
The study involved a replication of Jung=92s original Word Association test
under fMRI conditions. The subject is asked to respond with the first word
that comes to mind in response to a stimulus word from a standard list. Mos=
t
responses are bland and neutral, but some of them are not. Response time is
prolonged, response are often idiosyncratic and affect =96laden. Jung infer=
red
internal conflict (his so-called =93complexes=94) from these unusual respo=
nses.
We ran 14 subjects thru 100 words, 20 second epoch for each . We compared
complexed versus neutral responses for the group for the entire 20 sec
epoch. (using SPM 5)
I also split it up into 3 second bits (first 3 seconds, 2nd 3 etc etc) to
get some idea of what goes on over time, to construct a functional
hypothesis that could be subjected to DCM testing. .
The complexed responses =93pattern=94 that survived FWE correction seem to =
go
like this.
FIRST 3 SECS.
There is strong activation (corrected for FEW) in (1) L Broca=92s pre
Broca=92s, Z 5.58 (2) the L Middle temporal lobe Z 4.96, (3) L SMA/middle
cingulate Z 4.97 and (4) L Anterior Insula Z 5.11 (all probably reflectin=
g
the conflicted word searching of a complexed response).
But there is also homologous activation of all these areas in the R
hemisphere, albeit more weakly. (???interhemispheric negotiation/chatter
whatever). (R Broca Z 4.85, R Mid Temp Z 4.77, R insula Z 4.77)
However, there is a SMALL area in R prefrontal region at 54,4, 47 (R
precentral Area 6), which stands out on its own, 16 voxel Z 5.38, p FWE
corr .001. This is the second strongest response in the entire result list.
I don=92t know * what * to make of it.
SECOND THREE SECS.
Same as above , BUT, there is a brief bit of R supraorbital (43 29 -6)
activity (p FWE corr .038, Z 4.14) probably to do with the executive
effort of the conflictual nature of the =93complexed=92 response. And activ=
ity
shifts to from L to R SMA Z 5.28 !
The REST of the epoch achieves nothing that passes the FWE FDR barrier.
So I suppose a model might say that there is some some antero-posterior
(receptive-expressive verbal) activity; with inter-hemispheric negotiations
which include SMA and cingulum; and cortico-mesencephalic-limbic (Bilate=
ral
Anterior Insula) interaction, with R supraorbital (executive function)
region coming on line a little later.
But this still doesn=92t account for the weird SMALL but very prominent =
R
precentral Area 6 region at 54,4, 47 .
Does anyone have any suggestions on how I might model this in DCM? Or for
that matter whether DCM could even do this in principle? Since my limited
understanding of DCM is that you can only do about 3 ROIs at a time ?
I=92ve asked my local colleagues, but they can=92t seem to come up with
anything.
.
Leon
--=20
*A/Prof Leon Petchkovsky
Psychiatrist, Jungian Analyst
Past President, ANZSJA
Director, the Pinniger Clinic, HQ@Robina
www.pinnigerclinic.com
0755809397
0420923885*
--000e0cd4d0880437bb04a463f40d
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<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">Dear all </f=
ont></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">I need some =
advice and help with<span style=3D"mso-spacerun: yes">=A0 </span>DCM.</font=
></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">The study in=
volved a replication of Jung=92s original Word Association test under fMRI =
conditions.<span style=3D"mso-spacerun: yes">=A0 </span>The subject is aske=
d to respond with the first word that comes to mind in response to a stimul=
us word from a standard list. Most responses are bland and neutral, but som=
e of them are not. Response time is prolonged, response are often idiosyncr=
atic and affect =96laden. Jung inferred internal conflict<span style=3D"mso=
-spacerun: yes">=A0 </span>(his so-called =93complexes=94) from these unusu=
al responses.</font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3"><span style=
=3D"mso-spacerun: yes">=A0</span>We ran 14 subjects thru 100 words, 20 seco=
nd epoch for each . We compared complexed versus neutral responses for the =
group for the entire 20 sec epoch. (using SPM 5)</font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">I also split=
it <span style=3D"mso-spacerun: yes">=A0</span>up into 3 second bits (firs=
t 3 seconds, 2<sup>nd</sup> 3 etc etc) to get some idea of what goes on ove=
r time, to construct a functional hypothesis that could be subjected to DCM=
testing.<span style=3D"mso-spacerun: yes">=A0 </span>. </font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">The complexe=
d responses =93pattern=94 that survived FWE correction seem to go like this=
. </font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">FIRST 3 SECS=
.<span style=3D"mso-spacerun: yes">=A0 </span></font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">There is<spa=
n style=3D"mso-spacerun: yes">=A0 </span>strong activation (corrected for F=
EW) <span style=3D"mso-spacerun: yes">=A0</span>in (1) <span style=3D"mso-s=
pacerun: yes">=A0</span>L Broca=92s pre Broca=92s, Z 5.58<span style=3D"mso=
-spacerun: yes">=A0 </span>(2) the L Middle temporal lobe Z 4.96, (3) <span=
style=3D"mso-spacerun: yes">=A0</span>L SMA/middle cingulate<span style=3D=
"mso-spacerun: yes">=A0 </span>Z 4.97 and (4) L Anterior Insula <span style=
=3D"mso-spacerun: yes">=A0</span>Z 5.11 (all probably reflecting the confli=
cted word searching of a complexed response).</font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">But there is=
also homologous activation of all these areas in the R hemisphere, albeit =
more weakly. (???interhemispheric negotiation/chatter whatever). <span styl=
e=3D"mso-spacerun: yes">=A0</span>(R Broca Z 4.85, R Mid Temp Z<span style=
=3D"mso-spacerun: yes">=A0 </span>4.77,<span style=3D"mso-spacerun: yes">=
=A0 </span>R insula Z 4.77) </font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">However, the=
re is a SMALL area in R prefrontal region at 54,4, 47 (R precentral<span st=
yle=3D"mso-spacerun: yes">=A0 </span>Area 6),<span style=3D"mso-spacerun: y=
es">=A0 </span>which stands out on its own,<span style=3D"mso-spacerun: yes=
">=A0 </span>16 voxel<span style=3D"mso-spacerun: yes">=A0 </span>Z 5.38, p=
FWE corr .001. This is the second strongest response in the entire result =
list.<span style=3D"mso-spacerun: yes">=A0 </span>I don=92t know <i style=
=3D"mso-bidi-font-style: normal"><span style=3D"mso-spacerun: yes">=A0</spa=
n>what </i><span style=3D"mso-spacerun: yes">=A0</span>to make of it. </fon=
t></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">SECOND THREE=
SECS.</font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">Same as abov=
e , BUT, there is a brief<span style=3D"mso-spacerun: yes">=A0 </span>bit o=
f R supraorbital<span style=3D"mso-spacerun: yes">=A0 </span>(43 29 -6) act=
ivity<span style=3D"mso-spacerun: yes">=A0 </span>(p FWE corr <span style=
=3D"mso-spacerun: yes">=A0</span>.038,<span style=3D"mso-spacerun: yes">=A0=
</span>Z 4.14) probably to do with the executive effort of the conflictual=
nature of the =93complexed=92 response. And activity shifts to from L to R=
SMA <span style=3D"mso-spacerun: yes">=A0</span>Z 5.28 !</font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">=A0</font></=
span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">The REST of =
the epoch achieves nothing that passes the FWE FDR<span style=3D"mso-spacer=
un: yes">=A0 </span>barrier. </font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">=A0</font></=
span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">So I suppose=
a model<span style=3D"mso-spacerun: yes">=A0 </span>might say that there i=
s some some antero-posterior (receptive-expressive verbal) activity; with i=
nter-hemispheric negotiations which include SMA and cingulum;<span style=3D=
"mso-spacerun: yes">=A0=A0 </span>and cortico-mesencephalic-limbic<span sty=
le=3D"mso-spacerun: yes">=A0 </span>(Bilateral Anterior Insula)<span style=
=3D"mso-spacerun: yes">=A0 </span>interaction, with R supraorbital (executi=
ve function) region coming on line a little later.</font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">=A0</font></=
span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">But this sti=
ll doesn=92t account for<span style=3D"mso-spacerun: yes">=A0 </span>the we=
ird<span style=3D"mso-spacerun: yes">=A0 </span>SMALL but very prominent <s=
pan style=3D"mso-spacerun: yes">=A0</span>R precentral<span style=3D"mso-sp=
acerun: yes">=A0 </span>Area 6 region at 54,4, 47 . </font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">=A0</font></=
span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">Does anyone =
have any suggestions on how I might model this in DCM?<span style=3D"mso-sp=
acerun: yes">=A0 </span>Or for that matter whether DCM could even do this i=
n principle? Since my limited understanding of DCM is that you can only do =
about 3 ROIs at a time ? </font></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">I=92ve asked=
my local colleagues, but they can=92t seem to come up with anything.</font=
></span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">=A0</font></=
span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">=A0</font></=
span></p>
<p class=3D"MsoNormal" style=3D"MARGIN: 6pt 0cm"><span style=3D"mso-bidi-fo=
nt-size: 11.0pt; mso-bidi-font-family: Arial"><font size=3D"3">.</font></sp=
an></p>Leon<br clear=3D"all"><br>-- <br><b style=3D"COLOR: rgb(0,0,0)">A/Pr=
of Leon Petchkovsky<br>
Psychiatrist, Jungian Analyst<br>Past President, ANZSJA<br>Director, the Pi=
nniger Clinic, HQ@Robina<br><a href=3D"http://www.pinnigerclinic.com/" targ=
et=3D"_blank">www.pinnigerclinic.com</a><br>0755809397<br>0420923885</b><br=
>
--000e0cd4d0880437bb04a463f40d--
=========================================================================
Date: Mon, 30 May 2011 15:25:12 +1000
Reply-To: Mayuresh K <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Mayuresh K <[log in to unmask]>
Subject: Re: Power analysis
Comments: To: Raphael Hilgenstock <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
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Thanks Raphael and Alexa for your inputs!
Raphael - Do you know of any documentation how the effect size is calculated
using the "threshold and transform" option?
I would imagine it is valid to use this option for fMRI T maps as well?
Thanks,
Mayuresh
On Fri, May 27, 2011 at 9:05 PM, Raphael Hilgenstock <
[log in to unmask]> wrote:
> Hi Mayuresh,
>
> you might want to use the "threshold and transform spm-t/F-maps" option as
> implemented in the VBM8 toolbox (http://dbm.neuro.uni-jena.de/software/)
> which allows you to calculate effect size measure 'd' for the respective
> spm-volume. I hope this helps.
>
> Best regards
> Raphael
>
> Am 27.05.2011 08:21, schrieb Mayuresh K:
>
> Hello spm experts,
>>
>> Could anyone guide me how to do a power analysis using fMRI or VBM data? I
>> have performed a random effects analysis comparing two groups of subjects
>> using their fMRI and VBM data. I have found a number of regions with
>> significant differences for both data sets.
>> I can probably calculate the mean and standard deviation of the %signal
>> change (or volume) for each group for the peak voxels say in a particular
>> anatomical region. Then use these to calculate effect sizes and power - Is
>> this a valid approach?
>> Any other suggestions welcome.
>>
>> Thanks,
>> Mayuresh
>>
>>
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Thanks Raphael and Alexa for your inputs!<br><br>Raphael - Do you know of a=
ny documentation how the effect size is calculated using the "threshol=
d and transform" option? <br>I would imagine it is valid to use this o=
ption for fMRI T maps as well?<br>
<br>Thanks,<br>Mayuresh<br><br><br><br><div class=3D"gmail_quote">On Fri, M=
ay 27, 2011 at 9:05 PM, Raphael Hilgenstock <span dir=3D"ltr"><<a href=
=3D"mailto:[log in to unmask]" target=3D"_blank">Raphael.Hilge=
[log in to unmask]</a>></span> wrote:<br>
<blockquote class=3D"gmail_quote" style=3D"border-left: 1px solid rgb(204, =
204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">Hi Mayuresh,<br>
<br>
you might want to use the "threshold and transform spm-t/F-maps" =
option as implemented in the VBM8 toolbox (<a href=3D"http://dbm.neuro.uni-=
jena.de/software/" target=3D"_blank">http://dbm.neuro.uni-jena.de/software/=
</a>) which allows you to calculate effect size measure 'd' for the=
respective spm-volume. I hope this helps.<br>
<br>
Best regards<br>
Raphael<br>
<br>
Am <a href=3D"tel:27.05.2011%2008" value=3D"+12705201108" target=3D"_blank"=
>27.05.2011 08</a>:21, schrieb Mayuresh K:<div><div></div><div><br>
<blockquote class=3D"gmail_quote" style=3D"border-left: 1px solid rgb(204, =
204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
Hello spm experts,<br>
<br>
Could anyone guide me how to do a power analysis using fMRI or VBM data? I =
have performed a random effects analysis comparing two groups of subjects u=
sing their fMRI and VBM data. I have found a number of regions with signifi=
cant differences for both data sets.<br>
I can probably calculate the mean and standard deviation of the %signal cha=
nge (or volume) for each group for the peak voxels say in a particular anat=
omical region. Then use these to calculate effect sizes and power - Is this=
a valid approach?<br>
Any other suggestions welcome.<br>
<br>
Thanks,<br>
Mayuresh<br>
<br>
</blockquote>
</div></div></blockquote></div><br>
--000e0cd25d4afc8ec004a47782ad--
=========================================================================
Date: Mon, 30 May 2011 10:20:38 +0200
Reply-To: Volkmar Glauche <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Volkmar Glauche <[log in to unmask]>
Subject: Re: question regarding matlabbatch struct/class
Comments: To: Martin Dietz <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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Dear Martin, dear list,
for matlabbatch, all files & folders are cellstr's, even if it is just a
single item.
Hope this helps,
Volkmar
Am 27.05.2011 12:43, schrieb Martin Dietz:
> Dear Volkmar & list,
>
> When running spm_jobman from the command line in 'serial' mode, what is the correct input format for dicom files/already imported nifti files, respectively ?
>
> Best wishes,
> Martin
>
>
>
> On May 26, 2011, at 10:04 AM, Volkmar Glauche wrote:
>
>> To run a batch from MATLAB command line, SPM always has to be initialised. At least,
>>
>> spm_jobman('initcfg')
>>
>> should be run before. If one needs to rely on defaults which can not be set in a batch (e.g. in first level fMRI analysis), one should run
>>
>> spm('defaults','fmri') r 'pet' or 'eeg', depending on the modality
>> spm_jobman('initcfg')
>>
>> Best,
>>
>> Volkmar
>
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fn:Volkmar Glauche
n:Glauche;Volkmar
org:University Freiburg Medical Center;Freiburg Brain Imaging
adr;quoted-printable:Breisacher Stra=C3=9Fe 64;;Neurozentrum;Freiburg;;79106;D
email;internet:[log in to unmask]
tel;work:+49 761 270 53310
tel;fax:+49 761 270 54160
url:http://fbi.uniklinik-freiburg.de/
version:2.1
end:vcard
--------------030907040504040401000207--
=========================================================================
Date: Mon, 30 May 2011 14:10:57 +0530
Reply-To: sarika cherodath <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: sarika cherodath <[log in to unmask]>
Subject: Batch processing using CLI in SPM5
MIME-Version: 1.0
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--0023541882a09b427804a47a46cd
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Hello,
Is there any source to obtain Matlab scripts for batch processing in
SPM5?
Thanks in advance,
--
Sarika Cherodath
Graduate Student
National Brain Research Centre
Manesar, Gurgaon -122050
India
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<div dir=3D"ltr">Hello,<div><br></div><div>=A0 =A0 =A0Is there any source t=
o obtain Matlab scripts for batch processing in SPM5? =A0</div><div><br></d=
iv><div>Thanks in advance,</div><div><br>-- <br>Sarika Cherodath<br>Graduat=
e Student<br>
National Brain Research Centre<br>Manesar, Gurgaon -122050<br>India<br><br>
</div></div>
--0023541882a09b427804a47a46cd--
=========================================================================
Date: Mon, 30 May 2011 11:24:44 +0100
Reply-To: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Subject: Re: second level analysis affected by subject order
Mime-Version: 1.0
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Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear Ciara,
did you check via "Review Design" whether the data is assigned correctly =
to your design? You should have a look at "Files&Factors" and check wheth=
er the files for each subject are picked up by SPM in the correct order. =
Issues might arise if you specify lists of files outside the batch GUI. I=
n such a case, you would have to make sure that your file lists are colum=
n cellstr arrays. If the are row cellstr's, they will be assigned to your=
cells in a wrong way.
Best,
Volkmar
=========================================================================
Date: Mon, 30 May 2011 12:32:33 +0200
Reply-To: Raphael Hilgenstock <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Raphael Hilgenstock <[log in to unmask]>
Subject: Re: Power analysis
Comments: To: Mayuresh K <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
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boundary="------------050301050001070907010502"
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Hi Mayuresh,
just edit the cg_vbm8_spmT2x.mat or cg_vbm8_spmF2x.mat and you will find
the respective formula for calculating effect size within the first few
lines of the files.
Good luck!
Raphael
Am 30.05.2011 07:25, schrieb Mayuresh K:
> Thanks Raphael and Alexa for your inputs!
>
> Raphael - Do you know of any documentation how the effect size is
> calculated using the "threshold and transform" option?
> I would imagine it is valid to use this option for fMRI T maps as well?
>
> Thanks,
> Mayuresh
>
>
>
> On Fri, May 27, 2011 at 9:05 PM, Raphael Hilgenstock
> <[log in to unmask]
> <mailto:[log in to unmask]>> wrote:
>
> Hi Mayuresh,
>
> you might want to use the "threshold and transform spm-t/F-maps"
> option as implemented in the VBM8 toolbox
> (http://dbm.neuro.uni-jena.de/software/) which allows you to
> calculate effect size measure 'd' for the respective spm-volume. I
> hope this helps.
>
> Best regards
> Raphael
>
> Am 27.05.2011 08 <tel:27.05.2011%2008>:21, schrieb Mayuresh K:
>
> Hello spm experts,
>
> Could anyone guide me how to do a power analysis using fMRI or
> VBM data? I have performed a random effects analysis comparing
> two groups of subjects using their fMRI and VBM data. I have
> found a number of regions with significant differences for
> both data sets.
> I can probably calculate the mean and standard deviation of
> the %signal change (or volume) for each group for the peak
> voxels say in a particular anatomical region. Then use these
> to calculate effect sizes and power - Is this a valid approach?
> Any other suggestions welcome.
>
> Thanks,
> Mayuresh
>
>
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<meta content="text/html; charset=ISO-8859-1"
http-equiv="Content-Type">
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<body text="#000000" bgcolor="#ffffff">
Hi Mayuresh,<br>
<br>
just edit the cg_vbm8_spmT2x.mat or cg_vbm8_spmF2x.mat and you will
find the respective formula for calculating effect size within the
first few lines of the files.<br>
<br>
Good luck!<br>
Raphael<br>
<br>
Am 30.05.2011 07:25, schrieb Mayuresh K:
<blockquote
cite="mid:[log in to unmask]"
type="cite">Thanks Raphael and Alexa for your inputs!<br>
<br>
Raphael - Do you know of any documentation how the effect size is
calculated using the "threshold and transform" option? <br>
I would imagine it is valid to use this option for fMRI T maps as
well?<br>
<br>
Thanks,<br>
Mayuresh<br>
<br>
<br>
<br>
<div class="gmail_quote">On Fri, May 27, 2011 at 9:05 PM, Raphael
Hilgenstock <span dir="ltr"><<a moz-do-not-send="true"
href="mailto:[log in to unmask]"
target="_blank">[log in to unmask]</a>></span>
wrote:<br>
<blockquote class="gmail_quote" style="border-left: 1px solid
rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left:
1ex;">Hi Mayuresh,<br>
<br>
you might want to use the "threshold and transform
spm-t/F-maps" option as implemented in the VBM8 toolbox (<a
moz-do-not-send="true"
href="http://dbm.neuro.uni-jena.de/software/"
target="_blank">http://dbm.neuro.uni-jena.de/software/</a>)
which allows you to calculate effect size measure 'd' for the
respective spm-volume. I hope this helps.<br>
<br>
Best regards<br>
Raphael<br>
<br>
Am <a moz-do-not-send="true" href="tel:27.05.2011%2008"
value="+12705201108" target="_blank">27.05.2011 08</a>:21,
schrieb Mayuresh K:
<div>
<div><br>
<blockquote class="gmail_quote" style="border-left: 1px
solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex;
padding-left: 1ex;">
Hello spm experts,<br>
<br>
Could anyone guide me how to do a power analysis using
fMRI or VBM data? I have performed a random effects
analysis comparing two groups of subjects using their
fMRI and VBM data. I have found a number of regions with
significant differences for both data sets.<br>
I can probably calculate the mean and standard deviation
of the %signal change (or volume) for each group for the
peak voxels say in a particular anatomical region. Then
use these to calculate effect sizes and power - Is this
a valid approach?<br>
Any other suggestions welcome.<br>
<br>
Thanks,<br>
Mayuresh<br>
<br>
</blockquote>
</div>
</div>
</blockquote>
</div>
<br>
</blockquote>
</body>
</html>
--------------050301050001070907010502--
=========================================================================
Date: Mon, 30 May 2011 11:45:49 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: induced power at sensor level
Comments: To: Nico Bunzeck <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
Mime-Version: 1.0 (iPad Mail 8C148)
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <4629769658632215911@unknownmsgid>
Hi Nico,
Yes, what you described is the way to get what some people call 'pure
induced'. I think this is a rather artificial construct not
corresponding to any distinct physiological process because in reality
you get oscillatory activity with different degree of phase locking to
an event so it ends up in both evoked and induced components. So most
people just analyse the average TF and do not make this distinction.
Best,
Vladimir
On 30 May 2011, at 10:31, Nico Bunzeck <[log in to unmask]> wrote:
> Hi Vladimir,
>
> I am about to analyse MEG data regarding induced oscillatory power (at the
> sensor level; SPM8). I am not quite sure how to get there and would
> appreciate your help. If I understand the manual correct spm_eeg_tf followed
> by averaging (spm_eeg_average_TF) results in the power spectrum averaged
> over trials and this includes both 'evoked' and 'induced' power.
> Alternatively, averaging followed by spm_eeg_tf results in 'evoked' power
> only. Is that correct? Does that mean the difference between both would
> result in purely 'induced' power or is there another way?
>
> Thanks and best wishes,
> Nico
>
>
>
>
=========================================================================
Date: Mon, 30 May 2011 13:21:23 +0100
Reply-To: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: =?ISO-8859-1?Q?Volkmar_Glauche?=
<[log in to unmask]>
Subject: Re: make a movie of statistical results
Comments: To: Li Jiang <[log in to unmask]>
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain
Message-ID: <[log in to unmask]>
I must have missed that question. When you overlay your results onto orth=
ogonal sections (either in Results or in CheckReg), the image context men=
us contain a movie tool. This tool allows you to move through the data sl=
ice by slice. The displayed images can be written to disk either as a mov=
ie or as individual image frames.
Volkmar
=========================================================================
Date: Mon, 30 May 2011 14:46:47 +0200
Reply-To: Helmut Laufs <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Helmut Laufs <[log in to unmask]>
Subject: VOI: mean vs. SVD (PCA)
Content-Type: multipart/alternative;
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Dear VOI analysts=2C
is there any strong opinion or even objective evidence [literature] for/aga=
inst using SVD (vs. the mean) when working with data extracted from a VOI?=
=20
My understanding is that SVD might help to protect against "contamination" =
of the data either due to white noise=2C or due to a lack of functional spe=
cificity of the spatially defined VOI.
Thanks for any hints.
Bw=2C
Helmut
=
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.hmmessage P
{
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}
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{
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font-family:Tahoma
}
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<body class=3D'hmmessage'>
<br>Dear VOI analysts=2C<br><br>is there any strong opinion or even objecti=
ve evidence [literature] for/against using SVD (vs. the mean) when working =
with data extracted from a VOI? <br><br>My understanding is that SVD might =
help to protect against "contamination" of the data either due to white noi=
se=2C or due to a lack of functional specificity of the spatially defined V=
OI.<br><br>Thanks for any hints.<br><br>Bw=2C<br><br>Helmut<br><br> =
</body>
</html>=
--_1b5f9dfa-7631-403d-8532-d735737adf35_--
=========================================================================
Date: Mon, 30 May 2011 13:58:00 +0100
Reply-To: Jonas Persson <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Jonas Persson <[log in to unmask]>
Subject: Re: Time derivative in event related design
Comments: To: Donald McLaren <[log in to unmask]>
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Thanks for the reference.
I've read through the article and played around with the Matlab scripts p=
rovided. I have a few potentially stupid questions though:
1. The ratio value which is used to calculate the contrast weights, is it=
always .44 and -.34 respectively if you want to keep the same physiologi=
cal contraints as the author or do you have to calculate them for your de=
sign? If so, how?
2. I'm not sure how to expand this method to cases where you want to comp=
are activation between 2 experimental conditions. The scripts seem to be =
designed for 2 regressors corresponding to the HRF and derivative for a s=
ingle condition only.
Thank you for being patient with me.=20
/Jonas Persson
On Fri, 20 May 2011 17:00:39 -0400, MCLAREN, Donald <mclaren.donald@GMAIL=
.COM> wrote:
>See Investigating hemodynamic response variability at the group level
>using basis functions by Steffener et al.
>
>
>On Friday, May 20, 2011, Jonas Persson <[log in to unmask]> wrote:=
>> Hello fellow SPM:ers,
>>
>> I am a bit confused with regards to using the time derivative in SPM.
>>
>> The issue is that I have an event related paradigm where I do post hoc=
sorting of stimuli to 2 conditions. At the last SPM course I learned tha=
t slice time correction should be avoided, so instead of using time slice=
correction I wanted to include a second basis function to account for ti=
ming differences in data acquisition between slices.
>>
>> To check for regions significantly more activated in cond 1 vs cond 2 =
I did an F-contrast [1 0 -1 0; 0 1 0 -1] to look for voxels associated wi=
th either the HRF or td. I masked this contrast inclusive with a t-contra=
st [1 0 -1 0] to only look at voxels with activation corresponding to the=
HRF. The problem here is that I'm telling SPM to look for voxels with di=
fferent timing depending on condition, while I'm interested in allowing f=
or timing differences between regions regardless of condition.
>>
>> Another variant I've thought of is to merely do a t-contrast [1 0 -1 0=
], controlling for any variance associated with the td, but I read that t=
his may give biased results.
>>
>> The next issue is how to perform the 2nd level analysis. With the latt=
er method it's straightforward, but from what I understand I can't do a r=
andom effects on F-contrasts?
>>
>> Thank you for any suggestions!
>>
>> Bert regards,
>>
>> Jonas Persson
>>
>
>--=20
>
>Best Regards, Donald McLaren
>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>D.G. McLaren, Ph.D.
>Postdoctoral Research Fellow, GRECC, Bedford VA
>Research Fellow, Department of Neurology, Massachusetts General Hospital=
and
>Harvard Medical School
>Office: (773) 406-2464
>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
>This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTE=
D
>HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
>intended only for the use of the individual or entity named above. If th=
e
>reader of the e-mail is not the intended recipient or the employee or ag=
ent
>responsible for delivering it to the intended recipient, you are hereby
>notified that you are in possession of confidential and privileged
>information. Any unauthorized use, disclosure, copying or the taking of =
any
>action in reliance on the contents of this information is strictly
>prohibited and may be unlawful. If you have received this e-mail
>unintentionally, please immediately notify the sender via telephone at (=
773)
>406-2464 or email.
=========================================================================
Date: Mon, 30 May 2011 15:17:23 +0200
Reply-To: Marko Wilke <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Marko Wilke <[log in to unmask]>
Subject: Re: VOI: mean vs. SVD (PCA)
Comments: To: Helmut Laufs <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Hi Helmut,
> is there any strong opinion or even objective evidence [literature]
> for/against using SVD (vs. the mean) when working with data extracted
> from a VOI?
I searched the literature for this a while ago and found that two good=20
references were Saxe et al., NI 2006, arguing for the mean, vs. Friston=20
et al., NI 2006 (same issue, I think), arguing for the first=20
eigenvariate, so there seems to be a certain degree of uncertainty :) I=20
have not seen an exhaustive simulation definitely favoring the one over=20
the other.
Cheers,
Marko
Saxe R, Brett M, Kanwisher N, 2006. Divide and conquer: a defense of=20
functional localizers. NeuroImage 30: 1088-1096
Friston KJ, Rotshtein P, Geng JJ, Sterzer P, Henson RN, 2006. A critique=20
of functional localisers. NeuroImage 30: 1077-1087
--=20
____________________________________________________
PD Dr. med. Marko Wilke
Facharzt f=FCr Kinder- und Jugendmedizin
Leiter, Experimentelle P=E4diatrische Neurobildgebung
Universit=E4ts-Kinderklinik
Abt. III (Neurop=E4diatrie)
Marko Wilke, MD, PhD
Pediatrician
Head, Experimental Pediatric Neuroimaging
University Children's Hospital
Dept. III (Pediatric Neurology)
Hoppe-Seyler-Str. 1
D - 72076 T=FCbingen, Germany
Tel. +49 7071 29-83416
Fax +49 7071 29-5473
[log in to unmask]
http://www.medizin.uni-tuebingen.de/kinder/epn
____________________________________________________
=========================================================================
Date: Mon, 30 May 2011 15:36:38 +0200
Reply-To: Maria Serra <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Maria Serra <[log in to unmask]>
Subject: Is it correct to register binary images with DARTEL?
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0016e6d7dfcb81e13804a47e603f
Message-ID: <[log in to unmask]>
--0016e6d7dfcb81e13804a47e603f
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Dear SPMrs,
We would like to register multiple binary images. Is it possible to do it
with Dartel (create template and create warped)?
Thank you for your help,
--=20
Maria Serra
PIC (Port d'Informaci=F3 Cient=EDfica)
Campus UAB, Edifici D
E-08193 Bellaterra, Barcelona
Telf. +34 93 586 8232
www.pic.es
--0016e6d7dfcb81e13804a47e603f
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<div><br>Dear SPMrs,</div><div>=A0</div><div>We would like to register mult=
iple binary images. Is it possible to do it with Dartel (create template an=
d create warped)?<br></div><div><br>Thank you for your help,</div><br>-- <b=
r>
Maria Serra<br><br>PIC (Port d'Informaci=F3 Cient=EDfica)<br>Campus UAB=
, Edifici D<br>E-08193 Bellaterra, Barcelona<br>Telf. +34 93 586 8232<br><a=
href=3D"http://www.pic.es">www.pic.es</a><br>
--0016e6d7dfcb81e13804a47e603f--
=========================================================================
Date: Mon, 30 May 2011 10:14:58 -0400
Reply-To: Olivier Collignon <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Olivier Collignon <[log in to unmask]>
Subject: Constrained VOI extraction
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=0016364d22a79bc9d504a47ee9ec
Message-ID: <[log in to unmask]>
--0016364d22a79bc9d504a47ee9ec
Content-Type: text/plain; charset=ISO-8859-1
Dear all,
I try to use the batch editor in order to automatically move my VOI from a
center coordinate (obtained from rfx analyses) to a Nearest local maxima in
the FFX (to fit more closely with individual data).
However, I don't want the VOI centre to move too much (and therefore change
to another structure). For example, I want to constrain this search for
local maxima from the rfx coordinate to a radius of 10mm. In the batch
editor , I tried the expression .Sphere/Movement of center/Nearest local
maxima/SPM index =1 (my spm.mat) and Mask expression = i2 (=a sphere of
radius 10). I thought that it will move the centre coordinate to the local
maxima of the sphere around my rfx coordinate. However this give exactly the
same result as using a movement of center/fixed (what I want to avoid).
Thanks for your help.
Best,
Olivier.
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<div>Dear all,</div><div>I try to use the batch editor in order to automati=
cally move my VOI from a center coordinate (obtained from rfx analyses) to =
a Nearest local maxima in the FFX (to fit more closely with individual data=
).</div>
<div>However, I don't want the VOI centre to move too much (and therefo=
re change to another structure). For example, I want to constrain this sear=
ch for local maxima from the rfx coordinate to a radius of 10mm. In the bat=
ch editor , I tried the expression .Sphere/Movement of center/Nearest local=
maxima/SPM index =3D1 (my spm.mat) and Mask expression =3D i2 (=3Da sphere=
of radius 10). I thought that it will move the centre coordinate to the lo=
cal maxima of the sphere around my rfx coordinate.=A0However this give exac=
tly the same result as using a movement of center/fixed (what I want to avo=
id).</div>
<div>Thanks for your help.</div><div>Best,</div><div>Olivier.</div>
--0016364d22a79bc9d504a47ee9ec--
=========================================================================
Date: Mon, 30 May 2011 11:21:52 -0400
Reply-To: simon <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: simon <[log in to unmask]>
Subject: [Job] Postdoctoral Positions on Medical Image Analysis at UNC-CH
Mime-Version: 1.0
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boundary="=====003_Dragon314353248383_====="
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--=====003_Dragon314353248383_=====
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charset="gb2312"
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Several postdoctoral positions in medical image analysis are available at the IDEA Group of UNC-CH (https://www.med.unc.edu/bric/ideagroup). Our current effort is to enhance understanding of the working mechanism of the brain via diffusion weighted imaging (DWI) and functional magnetic resonance imaging (FMRI) by automatically mining information latent in images for the purposes of growth and disease analyses. The positions will support our efforts in advancing novel technologies for analyzing MR for applications in neuroscience. Possible research topics include, but are not limited to, improving disease classification by combining information from multiple modalities, white-matter bundle segmentation/modeling, and structural/functional analysis of subject groups involving infants, and patients with MCI/AD, schizophrenia, and multiple sclerosis.
We are seeking highly motivated individuals who have demonstrated academic excellence, including publications in first-class journals and conferences. Successful candidates should have a Ph.D. (or equivalent) in Computer Science, Applied Mathematics/Statistics, Electrical Engineering, Biomedical Engineering, or related fields. Competence in programming beyond MATLAB (good command of Linux, C/C++, Python, ITK, VTK, etc.) is essential. Experience in neuroscience, medical image analysis, machine learning, and mathematical modeling is highly desirable. The successful candidates will be part of a diverse group including radiologists, psychologists, physicists, biostatistician, and computer scientists, and will build upon the group's extensive foundation on medical image analysis.
Applications should include a cover letter indicating the research area of interest, a curriculum vitae, and the contact information of three references.
For more information or to submit your application please contact:
Pew-Thian Yap
Assistant Professor
Department of Radiology and BRIC
The University of North Carolina at Chapel Hill
3123 Bioinformatics Bldg, CB# 7513
130 Mason Farm Rd
Chapel Hill, NC 27599
[log in to unmask]
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style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Tahoma">Several
postdoctoral positions in medical image analysis are available at the IDEA Group
of UNC-CH </SPAN></SPAN><SPAN
style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: #333333; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Tahoma">(</SPAN><SPAN
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href="https://www.med.unc.edu/bric/ideagroup/" target=_blank><SPAN
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style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: #333333; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Tahoma">)</SPAN><SPAN
class=apple-style-span><SPAN
style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Tahoma">.
Our current effort is to</SPAN></SPAN><SPAN
style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Tahoma">
<SPAN class=apple-style-span>enhance understanding of the working mechanism of
the brain via diffusion weighted imaging (DWI) and functional magnetic resonance
imaging (FMRI) by automatically mining information latent in images for the
purposes of growth and disease analyses. The positions will support our efforts
in advancing</SPAN><SPAN class=apple-converted-space> novel technologies
</SPAN><SPAN class=apple-style-span>for analyzing MR for applications in
neuroscience.</SPAN><SPAN class=apple-converted-space> </SPAN><SPAN
class=apple-style-span>Possible research topics include, but are not limited to,
improving</SPAN><SPAN class=apple-converted-space> </SPAN><SPAN
class=apple-style-span>disease classification by combining information from
multiple modalities,</SPAN><SPAN class=apple-converted-space> </SPAN><SPAN
class=apple-style-span>white-matter bundle segmentation/modeling, and
structural/functional analysis of subject groups involving infants, and patients
with MCI/AD, schizophrenia, and multiple sclerosis. </SPAN></SPAN></FONT></P>
<P style="MARGIN: 0in 0in 0pt" class=MsoNormal><FONT size=3><SPAN
style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Tahoma"><SPAN
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style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Tahoma"><SPAN
class=apple-style-span>We are seeking highly motivated individuals who have
demonstrated academic excellence, including publications in first-class journals
and conferences. Successful candidates should have a Ph.D. (or</SPAN><SPAN
class=apple-converted-space> </SPAN><SPAN
class=apple-style-span>equivalent) in Computer Science, Applied
Mathematics/Statistics, Electrical Engineering, Biomedical Engineering, or
related fields. Competence in</SPAN><SPAN
class=apple-converted-space> </SPAN><SPAN
class=apple-style-span>programming beyond MATLAB (good command of Linux, C/C++,
Python, ITK, VTK, etc.) is essential. Experience in neuroscience, medical image
analysis, machine learning, and mathematical modeling is highly</SPAN><SPAN
class=apple-converted-space> </SPAN><SPAN class=apple-style-span>desirable.
T</SPAN></SPAN><SPAN class=apple-style-span><SPAN
style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: #333333; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Tahoma">he
successful candidates will be part of a diverse group including radiologists,
psychologists, physicists, biostatistician, and computer scientists, and will
build upon the group's extensive foundation on medical image
analysis.</SPAN></SPAN></FONT><SPAN
style="FONT-FAMILY: 'Tahoma','sans-serif'; COLOR: black; FONT-SIZE: 10pt; mso-fareast-font-family: 'Times New Roman'">
<o:p></o:p></SPAN></P>
<P
style="TEXT-ALIGN: justify; LINE-HEIGHT: 18pt; MARGIN: 0in 0in 0pt; mso-margin-top-alt: auto"
class=MsoNormal><FONT size=3><SPAN class=apple-style-span><SPAN
style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black"> </SPAN></SPAN><SPAN
style="COLOR: black"><o:p></o:p></SPAN></FONT></P>
<P
style="TEXT-ALIGN: justify; LINE-HEIGHT: 18pt; MARGIN: 0in 0in 0pt; mso-margin-top-alt: auto"
class=MsoNormal><FONT size=3><SPAN class=apple-style-span><SPAN
style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black">Applications should
include a cover letter indicating the research area of interest, a curriculum
vitae, and the contact information of three references.</SPAN></SPAN><SPAN
style="COLOR: black"><o:p></o:p></SPAN></FONT></P>
<P
style="TEXT-ALIGN: justify; LINE-HEIGHT: 18pt; MARGIN: 0in 0in 0pt; mso-margin-top-alt: auto"
class=MsoNormal><SPAN style="COLOR: black"><o:p><FONT size=3
face="Times New Roman"> </FONT></o:p></SPAN></P>
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class=MsoNormal><SPAN class=apple-style-span><SPAN
style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black"><FONT size=3>For more
information or to submit your application please
contact:</FONT></SPAN></SPAN><SPAN
style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black"><BR><SPAN
class=apple-style-span><FONT size=3>Pew-Thian Yap</FONT></SPAN></SPAN><SPAN
style="COLOR: black"><o:p></o:p></SPAN></P>
<P style="TEXT-ALIGN: justify; MARGIN: 0in 0in 0pt; mso-margin-top-alt: auto"
class=MsoNormal><FONT size=3><SPAN class=apple-style-span><SPAN
style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black">Assistant
Professor</SPAN></SPAN><SPAN style="COLOR: black"><o:p></o:p></SPAN></FONT></P>
<P style="TEXT-ALIGN: justify; MARGIN: 0in 0in 0pt; mso-margin-top-alt: auto"
class=MsoNormal><FONT size=3><SPAN
style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black">Department of
Radiology and BRIC</SPAN><SPAN
style="COLOR: black"><o:p></o:p></SPAN></FONT></P>
<P style="MARGIN: 0in 0in 0pt; mso-margin-top-alt: auto" class=MsoNormal><FONT
size=3><SPAN style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black">The
University of North Carolina at Chapel Hill</SPAN><SPAN
style="COLOR: black"><o:p></o:p></SPAN></FONT></P>
<P style="MARGIN: 0in 0in 0pt; mso-margin-top-alt: auto" class=MsoNormal><FONT
size=3><SPAN style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black">3123
Bioinformatics Bldg, CB# 7513</SPAN><SPAN
style="COLOR: black"><o:p></o:p></SPAN></FONT></P>
<P style="MARGIN: 0in 0in 0pt; mso-margin-top-alt: auto" class=MsoNormal><FONT
size=3><SPAN style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black">130 Mason
Farm Rd</SPAN><SPAN style="COLOR: black"><o:p></o:p></SPAN></FONT></P>
<P style="MARGIN: 0in 0in 0pt; mso-margin-top-alt: auto" class=MsoNormal><FONT
size=3><SPAN style="FONT-FAMILY: 'Verdana','sans-serif'; COLOR: black">Chapel
Hill, NC 27599 </SPAN><SPAN
style="COLOR: black"><o:p></o:p></SPAN></FONT></P>
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=========================================================================
Date: Mon, 30 May 2011 17:11:34 +0100
Reply-To: ddw <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: ddw <[log in to unmask]>
Subject: Re: VOI: mean vs. SVD (PCA)
Comments: To: [log in to unmask]
Mime-Version: 1.0
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Message-ID: <[log in to unmask]>
For what it's worth, I've always extracted both the first eigenvariate an=
d the mean time series and ran a correlation on them. I've never seen tha=
t correlation dip below 0.9 and most of the time it's > 0.95. While I've =
never formally tested an analysis (ppi) with mean vs. eigenvariate, I'd b=
e willing to put money that, with the mean and eigenvariate being so high=
ly correlated with one another, that the results of the analyses would be=
near identical.
But your mileage may vary, in our studies we concat across runs and have =
nuisance variables to correct for this so maybe it's in the way you adjus=
t your timeseries. If the timeseries is clean enough then the first eigen=
variate should be nearly the same as the mean, or so I would expect.
Cheers!
=========================================================================
Date: Mon, 30 May 2011 12:45:38 -0400
Reply-To: "MCLAREN, Donald" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "MCLAREN, Donald" <[log in to unmask]>
Subject: Re: VOI: mean vs. SVD (PCA)
Comments: To: ddw <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
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--20cf3054a45765010704a48104ab
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I suspect that it is dependent on the region size and homogeneity of the
region. I've always preferred the mean timeseries as it weights each voxel
the same way. In this way, when you extract from different subjects, your
always using the same voxels. If you use the eigenvariate, then you might
grab voxels from one part of the VOI in some subjects and another part of
the VOI in other subjects. This leads to comparing region X to region Y
across subjects -- but potentially functionally similar. I'm not sure if
this is a huge problem, but it is something to be aware of when extracting
data. All of the code I've written allows for the extraction both ways.
Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Postdoctoral Research Fellow, GRECC, Bedford VA
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Office: (773) 406-2464
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.
On Mon, May 30, 2011 at 12:11 PM, ddw <[log in to unmask]> wrote:
> For what it's worth, I've always extracted both the first eigenvariate and
> the mean time series and ran a correlation on them. I've never seen that
> correlation dip below 0.9 and most of the time it's > 0.95. While I've never
> formally tested an analysis (ppi) with mean vs. eigenvariate, I'd be willing
> to put money that, with the mean and eigenvariate being so highly correlated
> with one another, that the results of the analyses would be near identical.
>
> But your mileage may vary, in our studies we concat across runs and have
> nuisance variables to correct for this so maybe it's in the way you adjust
> your timeseries. If the timeseries is clean enough then the first
> eigenvariate should be nearly the same as the mean, or so I would expect.
>
> Cheers!
>
--20cf3054a45765010704a48104ab
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I suspect that it is dependent on the region size and homogeneity of the re=
gion. I've always preferred the mean timeseries as it weights each voxe=
l the same way. In this way, when you extract from different subjects, your=
always using the same voxels. If you use the eigenvariate, then you might =
grab voxels from one part of the VOI in some subjects and another part of t=
he VOI in other subjects. This leads to comparing region X to region Y acro=
ss subjects -- but potentially functionally similar. I'm not sure if th=
is is a huge problem, but it is something to be aware of when extracting da=
ta. All of the code I've written allows for the extraction both ways.<b=
r clear=3D"all">
<br>Best Regards, Donald McLaren<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D<br>D.G. McLaren, Ph.D.<br>Postdoctoral Research Fellow, GRECC,=
Bedford VA<br>Research Fellow, Department of Neurology, Massachusetts Gene=
ral Hospital and Harvard Medical School<br>
Office: (773) 406-2464<br>=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D<br>This e-mail contains CONFIDENTIAL INFORMATION which may =
contain PROTECTED HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED=
and which is intended only for the use of the individual or entity named a=
bove. If the reader of the e-mail is not the intended recipient or the empl=
oyee or agent responsible for delivering it to the intended recipient, you =
are hereby notified that you are in possession of confidential and privileg=
ed information. Any unauthorized use, disclosure, copying or the taking of =
any action in reliance on the contents of this information is strictly proh=
ibited and may be unlawful. If you have received this e-mail unintentionall=
y, please immediately notify the sender via telephone at (773) 406-2464 or =
email.<br>
<br><br><div class=3D"gmail_quote">On Mon, May 30, 2011 at 12:11 PM, ddw <s=
pan dir=3D"ltr"><<a href=3D"mailto:[log in to unmask]">[log in to unmask]<=
/a>></span> wrote:<br><blockquote class=3D"gmail_quote" style=3D"margin:=
0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">
For what it's worth, I've always extracted both the first eigenvari=
ate and the mean time series and ran a correlation on them. I've never =
seen that correlation dip below 0.9 and most of the time it's > 0.95=
. While I've never formally tested an analysis (ppi) with mean vs. eige=
nvariate, I'd be willing to put money that, with the mean and eigenvari=
ate being so highly correlated with one another, that the results of the an=
alyses would be near identical.<br>
<br>
But your mileage may vary, in our studies we concat across runs and have nu=
isance variables to correct for this so maybe it's in the way you adjus=
t your timeseries. If the timeseries is clean enough then the first eigenva=
riate should be nearly the same as the mean, or so I would expect.<br>
<br>
Cheers!<br>
</blockquote></div><br>
--20cf3054a45765010704a48104ab--
=========================================================================
Date: Mon, 30 May 2011 18:15:12 +0100
Reply-To: Max Hilger <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Max Hilger <[log in to unmask]>
Subject: Realign&Unwarp: Artificial Movement in only one Condition
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Dear SPM-Users,
i am currently reanalyzing a fMRT-dataset in which the subjects did 4 con=
ditions in the same succession. The first step of the analysis was realig=
ning and unwarping the scans, using the following parameters:
Estimation Options
. Quality: 1
. Interpolation: 7th Degree B-Spline
. Wrapping: Wrap Y
Unwarp Reslicing Options
. Interpolation: 7th Degree B-Spline
. Wrapping: Wrap Y
All other parameters were set to default.
The graphs showed heavy movement (up to 15mm) of all the subjects, but ON=
LY between the first and second images of the first condition and always =
in negative-X-direction. It seems implausible that all the subjects reall=
y did move in the same direction at the same point of time, so we do assu=
me that there is an error in our data/analysis that causes this pattern o=
f results.
Interesting is also that all subjects and conditions were analyzed using =
a batch, and that the 'movement' only appears at the beginning of one con=
dition and not all of the conditions.
Since the data was previously analyzed with spm2 (usingthe same parameter=
s), we compared the results with the allready existing ones. As you can s=
ee in the attatchmed image, if you discard the first image, the graphs ar=
e virtually the same.
The exeption of this pattern is the rotation in the first condition (Cond=
ition 002), which does also have rapid changes both in positive and in ne=
gative direction between the first and second image.
We had the idea that we could maybe work around the problem if we simply =
exclude the first image from analysis (and reduced the onsets of the stim=
uli etc by TR), but we are not sure if this is an adequate solution.
So I would be gratefull if you could tell me if there if you did previous=
ly encounter this problem and can tell me it's origin, what your solution=
was and if our way of attempt of working around it is adequate if we don=
't find another solution.=20
Best regards,
Max Hilger
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=========================================================================
Date: Mon, 30 May 2011 14:30:08 -0400
Reply-To: "Smith, Jason (NIH/NIDCD) [F]" <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Smith, Jason (NIH/NIDCD) [F]" <[log in to unmask]>
Subject: Re: VOI: mean vs. SVD (PCA)
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I think this is a theoretical question as much as a practical preprocessing=
question.=20
I am not a mathematician, so apply the appropriate amount of salt to this a=
nswer.
The implicit model is:
Y=3DCx + Qe.
where Y is the normalized signal from a few adjacent voxels, x is an underl=
ying signal of interest, C is a mixing vector, and e is a matrix of some ad=
ditive error mixed by Q. We're assuming we're looking for a single signal. =
If you take the mean of Y as an estimate of x you are assuming that there i=
s a single x represented in each y to the exact same degree (C is a constan=
t vector) and that the e's normally distributed, uncorrelated in time, acro=
ss observations (Q is diagonal), and uncorrelated with x, and all y's e hav=
e equal variances. If the Y's are not normalized the mean assumes the eleme=
nts of C are scaled by the variances of Y, but the error still have the sam=
e variance. If you take the data projected on the first eigenvector you are=
assuming the remaining eigenvectors with non-zero eigenvalues are noise. T=
he signal x is not represented equally across voxels (C is not a constant v=
ector) butt x is the largest unique source of variance in Y. The remaining =
e's are all uncorrelated with equal variance though Q is not constant and t=
he different noise sources can be shared across voxels at different levels.=
If you take the first factor (from factor analysis) you are assuming that =
the e' are normal and uncorrelated, but with potentially different variance=
s. Q would be diagonal I think. Other options would be ICA which relaxes th=
e normality assumption (or equivalently changes Cx to a nonlinear function)=
, or some sort of linear dynamic system to relax the uncorrelated through t=
ime assumptions (partitioning the state space into signal and noise).
If you smooth, there is a second mixing matrix G such that
Y=3DG(Cx + Qe)
which will likely have the effect of making the PCA, FA, etc models look a =
lot more like the first (mean) model. Still, the notion that all voxels rep=
resent the signal x to an exactly equal degree seems a bit dodgy to me. Sin=
ce the PCA and mean solutions are often correlated, the PCA solution is lik=
ely better theoretically. Check the actual eigenvector to ensure that all v=
oxels have positive values (I can't think of a case I've ever seen where th=
ey don't). If they are all positive, the "different voxels for different pe=
ople" problem is avoided.
Take a look at Roweis and Ghahramani 1999 in neural networks for a better d=
iscussion of the above.
Just my 0.02$
----------------------------------------------------
Jason F. Smith, Ph.D.
Brain Imaging and Modeling Section
NIDCD
National Institutes of Health
[log in to unmask]
Rm 8S235B, 10 Center Dr.
Bethesda MD 20892-1407
PH) 301.451.1647=
=========================================================================
Date: Mon, 30 May 2011 21:14:44 +0200
Reply-To: Guillen Fernandez <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Guillen Fernandez <[log in to unmask]>
Subject: Postdoctoral Fellow Opening: Cognitive Neuroscience of Memory
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Post-doctoral fellow in Cognitive Neuroscience of Memory=20
Donders Institute for Brain, Cognition, and Behavior=20
Vacancy number: 010568=20
Closing date: Review of applications will continue until the position is fi=
lled.=20
Job description=20
The Donders Institute for Brain, Cognition, and Behavior seeks to hire an e=
xcellent PhD student in Cognitive Neuroscience of Memory in the laboratory =
of Guill=C3=A9n Fern=C3=A1ndez. The Fern=C3=A1ndez Lab probes the brain bas=
is of memory, emotion, and their interactions. It applies an interdisciplin=
ary approach integrating cognitive neuroimaging, pharmacology, genetics, an=
d diverse clinical disciplines.=20
The current position is financed by a prestigious ERC Advanced Investigator=
Grant , which Richard Morris (University of Edinburgh) and Guill=C3=A9n Fe=
rn=C3=A1ndez received jointly. This project is an interdisciplinary experim=
ental analysis of the neurobiological mechanisms by which we acquire knowle=
dge. Our approach builds upon recent findings of the participating laborato=
ries that have each addressed key issues associated with the rapid acquisit=
ion and assimilation of new associative information into existing neural =
=E2=80=98schemas=E2=80=99 (see below for a list of selected, recent publica=
tions of the Morris and Fern=C3=A1ndez lab on this topic). Rapid learning d=
epends upon both novelty and prior knowledge . We will conduct a coordinate=
d program of research concerning the mechanisms of both determinants. First=
, we will test that novelty , acting via the release of dopamine, has a dir=
ect impact on the mechanisms of cellular consolidation in the hippocampus. =
Second, with respect to prior knowledge , the retention of new event-relate=
d associative information requires the process of systems consolidation wit=
hin declarative memory, as widely studied, but we further suggest that the =
organisation of knowledge requires more than just stabilising memory traces=
within neocortical networks. It also involves the integration of distinct =
memory traces into neural =E2=80=98schemas=E2=80=99 that, once formed, have=
a major positive influence on future learning. The studies conducted at th=
e Donders Institute will involve fMRI using new cognitive tasks combined wi=
th pharmacology (sophisticated dopamine manipulation), transcranial magneti=
c stimulation, model-free analysis methods, and a translational project rea=
ching into real-world education.=20
Requirements=20
Applicants should be able to demonstrate a consistently strong academic rec=
ord, including publications in international journals. This individual must=
be proficient in fMRI research and, most optimally, in performing pharmaco=
logical studies in humans.=20
Organization=20
The Donders Institute for Brain, Cognition and Behaviour (http://www.ru.nl/=
donders/) offers cognitive neuroscientists a unique, multidisciplinary work=
ing and learning environment with opportunities for developing expertise in=
a diversity of research areas and techniques. The centre is equipped with =
three MRI scanners (7T, 3T, 1.5T), a 275-channel MEG system, an EEG-TMS lab=
oratory, several (MR-compatible) EEG systems, and high-performance computat=
ional facilities. Website: http://www.ru.nl/donders/=20
Conditions of employment=20
Employment: 1,0 fte=20
The gross starting salary is =E2=82=AC 2.435 per month. In addition to the =
monthly gross salary, you will receive two yearly 8% bonuses (holiday and e=
nd-of-year).=20
Additional conditions of employment=20
The position is limited for three years (12 months probation period), but c=
an be extended to maximally five years.=20
Application=20
We prefer online applications (link)=20
Alternatively, written applications including an application letter, a CV, =
and the names (email addresses) of two persons who can provide references c=
an be send to=20
UMC St Radboud=20
Mw. M. Korsten=20
[log in to unmask]
Huispostcode 155=20
Concerns vacancy: 010568=20
Postbus 9101=20
6500 HB Nijmegen=20
Additional Information=20
Please visit our web page for further details about our lab, ( http://www.r=
u.nl/donders/research/theme-3-learning/research-groups/cognitive-neurology/=
)=20
or contact: Prof. Dr. Guill=C3=A9n Fern=C3=A1ndez ( [log in to unmask]
nl )=20
Project relevant, recent publications from the Morris and the Fern=C3=A1nde=
z Lab=E2=80=99s=20
1. Bethus I, Tse D, Morris RG. Dopamine and memory: modulation of the persi=
stence of memory for novel hippocampal NMDA receptor-dependent paired assoc=
iates. Journal of Neuroscience. 2010; 30: 1610-8.=20
2. Takashima A, Petersson KM, Rutters F, Tendolkar I, Jensen O, Zwarts MJ, =
McNaughton BL, Fern=C3=A1ndez G. Declarative memory consolidation in humans=
: a prospective functional magnetic resonance imaging study. Proceedings of=
the National Academy of Sciences USA 2006; 103: 756-761=20
3. Takashima A, Nieuwenhuis IL, Jensen O, Talamini LM, Rijpkema M, Fern=C3=
=A1ndez G. Shift from hippocampal to neocortical centered retrieval network=
with consolidation. Journal of Neuroscience 2009; 29: 10087-10093=20
4. Tse D, Langston RF, Kakeyama M, Bethus I, Spooner PA, Wood ER, Witter MP=
, Morris RG. Schemas and memory consolidation. Science 2007; 316: 76-82=20
5. van Kesteren MT, Fern=C3=A1ndez G, Norris DG, Hermans EJ. Persistent sch=
ema-dependent hippocampal-neocortical connectivity during memory encoding a=
nd post-encoding rest in humans. Proceedings of the National Academy of Sci=
ences USA 2010; 107: 7550-7555=20
6. van Kesteren MT, Rijpkema M, Ruiter DJ, Fern=C3=A1ndez G. Retrieval of a=
ssociative information congruent with prior knowledge is related to increas=
ed medial prefrontal activity and connectivity. Journal of Neuroscience 201=
0; 30: 15888-15894=20
7. Wang SH, Morris RG. Hippocampal-neocortical interactions in memory forma=
tion, consolidation, and reconsolidation. Annual Reviews of Psychology 2010=
; 61: 49-79=20
8. Wang SH, Redondo RL, Morris RG. Relevance of synaptic tagging and captur=
e to the persistence of long-term potentiation and everyday spatial memory.=
Proceedings of the National Academy of Sciences USA 2010; 107: 19537-42
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<p class=3D"MsoNormal" style=3D"mso-margin-top-alt:auto;mso-margin-bottom-a=
lt:auto;
line-height:normal;mso-outline-level:2"><b><span style=3D"font-size:
18.0pt;font-family:"Times New Roman","serif";mso-fareas=
t-font-family:"Times New Roman";
mso-ansi-language:EN-US;mso-fareast-language:DE" lang=3D"EN-US">Post-doctor=
al fellow in Cognitive
Neuroscience of Memory</span></b></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><b=
><span style=3D"mso-bidi-font-size:11.0pt" lang=3D"EN-GB">Donders Institute=
</span></b><span lang=3D"EN-GB"> </span><b><span style=3D"mso-bidi-font-siz=
e:11.0pt" lang=3D"EN-GB">for
Brain, Cognition, and Behavior</span></b><span style=3D"mso-bidi-font-size:
11.0pt" lang=3D"EN-GB"></span></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><b=
><span style=3D"mso-bidi-font-size:11.0pt" lang=3D"EN-GB">Vacancy number: 0=
10568</span></b></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><b=
><span style=3D"mso-bidi-font-size:11.0pt" lang=3D"EN-GB">Closing date: Rev=
iew of
applications will continue until the position is filled.</span></b></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><s=
trong><span style=3D"mso-bidi-font-size:11.0pt;mso-ansi-language:EN-US" lan=
g=3D"EN-US"> </span></strong></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><s=
trong><span style=3D"mso-bidi-font-size:11.0pt;mso-ansi-language:EN-US" lan=
g=3D"EN-US">Job
description</span></strong></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><s=
pan style=3D"mso-bidi-font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-=
US">The
Donders Institute for Brain, Cognition, and Behavior seeks to hire an excel=
lent
PhD student in Cognitive Neuroscience of Memory in the laboratory of Guill=
=C3=A9n
Fern=C3=A1ndez. The Fern=C3=A1ndez Lab probes the brain basis of memory, em=
otion, and
their interactions. It applies an interdisciplinary approach integrating
cognitive neuroimaging, pharmacology, genetics, and diverse clinical
disciplines. </span></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><s=
pan style=3D"mso-bidi-font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-=
US">The
current position is financed by a prestigious <b style=3D"mso-bidi-font-wei=
ght:
normal">ERC Advanced Investigator Grant</b>, which Richard Morris (Universi=
ty
of Edinburgh) and Guill=C3=A9n Fern=C3=A1ndez received jointly. This projec=
t is an
interdisciplinary experimental analysis of the neurobiological mechanisms b=
y
which we acquire knowledge. Our approach builds upon recent findings of the
participating laboratories that have each addressed key issues associated w=
ith
the rapid acquisition and assimilation of new associative information into
existing neural =E2=80=98schemas=E2=80=99 (see below for a list of selected=
, recent
publications of the Morris and Fern=C3=A1ndez lab on this topic). Rapid lea=
rning
depends upon both <i style=3D"mso-bidi-font-style:normal">novelty</i> and <=
i style=3D"mso-bidi-font-style:normal">prior knowledge</i>. We will conduct=
a
coordinated program of research concerning the mechanisms of both determina=
nts.
First, we will test that <i style=3D"mso-bidi-font-style:normal">novelty</i=
>,
acting via the release of dopamine, has a direct impact on the mechanisms o=
f
cellular consolidation in the hippocampus. Second, with respect to <i style=
=3D"mso-bidi-font-style:normal">prior knowledge</i>, the retention of new
event-related associative information requires the process of systems
consolidation within declarative memory, as widely studied, but we further =
suggest
that the organisation of knowledge requires more than just stabilising memo=
ry
traces within neocortical networks. It also involves the integration of
distinct memory traces into neural =E2=80=98schemas=E2=80=99 that, once for=
med, have a major
positive influence on future learning. The studies conducted at the Donders
Institute will involve fMRI using new cognitive tasks combined with
pharmacology (sophisticated dopamine manipulation), transcranial magnetic
stimulation, model-free analysis methods, and a translational project reach=
ing
into real-world education.</span></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><s=
pan style=3D"mso-bidi-font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-=
US"> </span></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><s=
trong><span style=3D"mso-bidi-font-size:11.0pt;mso-ansi-language:EN-US" lan=
g=3D"EN-US">Requirements</span></strong></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt;text-align:justify"><span styl=
e=3D"font-size:11.0pt;mso-bidi-font-size:10.0pt;mso-fareast-font-family:
Times;mso-ansi-language:EN-US;mso-fareast-language:EN-US" lang=3D"EN-US">Ap=
plicants should be
able to demonstrate a consistently strong academic record, including
publications in international journals. This individual must be proficient =
in
fMRI research and, most optimally, in performing pharmacological studies in
humans.</span><span style=3D"font-size:11.0pt;mso-fareast-font-family:
Times;mso-ansi-language:EN-US;mso-fareast-language:EN-US" lang=3D"EN-US"></=
span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt;text-align:justify"><span styl=
e=3D"font-size:11.0pt;mso-fareast-font-family:Times;mso-ansi-language:
EN-US;mso-fareast-language:EN-US" lang=3D"EN-US"> </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt;text-align:justify"><strong><s=
pan style=3D"font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">Organ=
ization</span></strong></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt;text-align:justify"><span styl=
e=3D"font-size:11.0pt;mso-fareast-font-family:Times;mso-ansi-language:
EN-US;mso-fareast-language:EN-US" lang=3D"EN-US">The Donders Institute for =
Brain, Cognition
and Behaviour (http://www.ru.nl/donders/) offers cognitive neuroscientists =
a
unique, multidisciplinary working and learning environment with opportuniti=
es
for developing expertise in a diversity of research areas and techniques. T=
he
centre is equipped with three MRI scanners (7T, 3T, 1.5T), a 275-channel ME=
G
system, an EEG-TMS laboratory, several (MR-compatible) EEG systems, and
high-performance computational facilities. Website: </span><a href=3D"http:=
//www.ru.nl/donders/" target=3D"_blank"><span style=3D"font-size:11.0pt;mso=
-fareast-font-family:Times;color:windowtext;
mso-ansi-language:EN-US;mso-fareast-language:EN-US;text-decoration:none;
text-underline:none" lang=3D"EN-US">http://www.ru.nl/donders/</span></a><sp=
an style=3D"font-size:11.0pt;mso-fareast-font-family:Times;mso-ansi-languag=
e:EN-US;
mso-fareast-language:EN-US" lang=3D"EN-US"></span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt;text-align:justify"><span styl=
e=3D"font-size:11.0pt;mso-fareast-font-family:Times;mso-ansi-language:
EN-US;mso-fareast-language:EN-US" lang=3D"EN-US"> </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><b><span style=3D"font-size:1=
1.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">Conditions of employment</spa=
n></b><span style=3D"font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-U=
S"> </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><span style=3D"font-size:
11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">Employment: 1,0 fte </span><=
/p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><span style=3D"font-size:
11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">The gross starting salary is=
=E2=82=AC</span><span style=3D"mso-ansi-language:EN-US" lang=3D"EN-US">2.4=
35</span><span style=3D"font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"E=
N-US"> per month. In addition to the
monthly gross salary, you will receive two yearly 8% bonuses (holiday and
end-of-year). </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><span style=3D"font-size:
11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US"> </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><strong><span style=3D"font-s=
ize:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">Additional conditions of
employment</span></strong></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><span style=3D"font-size:
11.0pt;mso-bidi-font-size:10.0pt;mso-fareast-font-family:Times;mso-ansi-lan=
guage:
EN-US;mso-fareast-language:EN-US" lang=3D"EN-US">The position is limited fo=
r three years (12
months probation period), but can be extended to maximally five years. </sp=
an><span style=3D"font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">=
<span style=3D"mso-spacerun:yes"> </span></span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt;tex=
t-align:
justify;line-height:normal;mso-layout-grid-align:none;text-autospace:none">=
<strong><span style=3D"mso-ansi-language:EN-US" lang=3D"EN-US"> </span=
></strong></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt;tex=
t-align:
justify;line-height:normal;mso-layout-grid-align:none;text-autospace:none">=
<strong><span style=3D"mso-ansi-language:EN-US" lang=3D"EN-US">Application<=
/span></strong></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt;tex=
t-align:
justify;line-height:normal;mso-layout-grid-align:none;text-autospace:none">=
<span style=3D"font-family:"Times New Roman","serif";ms=
o-fareast-font-family:
Times;mso-ansi-language:EN-US" lang=3D"EN-US">We prefer</span><span style=
=3D"font-size:12.0pt;font-family:"Times New Roman","serif&qu=
ot;;mso-fareast-font-family:
"Times New Roman";mso-ansi-language:EN-US;mso-fareast-language:DE=
" lang=3D"EN-US"> online
applications </span><a href=3D"http://www.umcn.nl/OverUMCstRadboud/werkenbi=
j/Pages/Solliciteren.aspx?VacatureNummer=3D010568&EmailAdres=3DCBEG-sol=
[log in to unmask]"><span style=3D"font-size:12.0pt;font-family:"T=
imes New Roman","serif";
mso-fareast-font-family:"Times New Roman";mso-ansi-language:EN-US=
;mso-fareast-language:
DE" lang=3D"EN-US">(link)</span></a><span style=3D"font-size:12.0pt;font-fa=
mily:"Times New Roman","serif";
mso-fareast-font-family:"Times New Roman";mso-ansi-language:EN-US=
;mso-fareast-language:
DE" lang=3D"EN-US"></span></p>
<p class=3D"MsoNormal" style=3D"mso-margin-top-alt:auto;mso-margin-bottom-a=
lt:auto;
line-height:normal"><span style=3D"font-size:12.0pt;font-family:"Times=
New Roman","serif";
mso-fareast-font-family:"Times New Roman";mso-ansi-language:EN-US=
;mso-fareast-language:
DE" lang=3D"EN-US">Alternatively, written applications including an applica=
tion letter, a CV,
and the names (email addresses) of two persons who can provide references c=
an
be send to <br>
<br>
UMC St Radboud<br>
Mw. M. Korsten<br>
[log in to unmask] <br>
Huispostcode 155<br>
Concerns vacancy: 010568<br>
Postbus 9101<br>
6500 HB Nijmegen</span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt;tex=
t-align:
justify;line-height:normal;mso-layout-grid-align:none;text-autospace:none">=
<span style=3D"font-family:"Times New Roman","serif";ms=
o-fareast-font-family:
Times;mso-ansi-language:EN-US" lang=3D"EN-US"> </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><b><span style=3D"font-size:1=
1.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">Additional Information</span>=
</b><span style=3D"font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US"=
> </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><span style=3D"font-size:
11.0pt;mso-fareast-font-family:Times;mso-ansi-language:EN-US;mso-fareast-la=
nguage:
EN-US" lang=3D"EN-US">Please visit our web page for further details about o=
ur lab, (</span><a href=3D"http://www.ru.nl/donders/research/theme-3-learni=
ng/research-groups/cognitive-neurology/"><span style=3D"font-size:11.0pt;ms=
o-fareast-font-family:Times;color:windowtext;
mso-ansi-language:EN-US;mso-fareast-language:EN-US;text-decoration:none;
text-underline:none" lang=3D"EN-US">http://www.ru.nl/donders/research/theme=
-3-learning/research-groups/cognitive-neurology/</span></a><span style=3D"f=
ont-size:11.0pt;mso-fareast-font-family:Times;mso-ansi-language:
EN-US;mso-fareast-language:EN-US" lang=3D"EN-US">) <br>
or contact: Prof. Dr. Guill=C3=A9n Fern=C3=A1ndez (</span><a href=3D"mailto=
:[log in to unmask]"><span style=3D"font-size:11.0pt;
mso-fareast-font-family:Times;color:windowtext;mso-ansi-language:EN-US;
mso-fareast-language:EN-US;text-decoration:none;text-underline:none" lang=
=3D"EN-US">[log in to unmask]</span></a><span style=3D"font-size:11.=
0pt;mso-fareast-font-family:Times;mso-ansi-language:
EN-US;mso-fareast-language:EN-US" lang=3D"EN-US">)</span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt;tex=
t-align:
justify;line-height:normal;mso-layout-grid-align:none;text-autospace:none">=
<span style=3D"font-family:"Times New Roman","serif";ms=
o-fareast-font-family:
Times;mso-ansi-language:EN-US" lang=3D"EN-US"> </span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt;tex=
t-align:
justify;line-height:normal;mso-layout-grid-align:none;text-autospace:none">=
<span style=3D"font-family:"Times New Roman","serif";ms=
o-fareast-font-family:
Times;mso-ansi-language:EN-US" lang=3D"EN-US">Project relevant, recent publ=
ications from the Morris
and the Fern=C3=A1ndez Lab=E2=80=99s</span></p>
<p class=3D"MsoListParagraphCxSpFirst" style=3D"margin-top:0cm;margin-right=
:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;line-height:normal;tab-stops:21.3pt"><span style=3D"font=
-family:"Times New Roman","serif";mso-ansi-language:EN-=
US" lang=3D"EN-US"> </span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">1.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">Bethus I, Tse D, Morris RG. Dopamin=
e and memory:
modulation of the persistence of memory for novel hippocampal NMDA
receptor-dependent paired associates. Journal of Neuroscience. 2010; 30:
1610-8.</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">2.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">Takashima A, Petersson KM, Rutters =
F, Tendolkar I,
Jensen O, Zwarts MJ, McNaughton BL, Fern=C3=A1ndez G. Declarative memory
consolidation in humans: a prospective functional magnetic resonance imagin=
g
study. Proceedings of the National Academy of Sciences USA 2006; 103: 756-7=
61</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">3.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">Takashima A, Nieuwenhuis IL, Jensen=
O, Talamini LM,
Rijpkema M, Fern=C3=A1ndez G. Shift from hippocampal to neocortical centere=
d
retrieval network with consolidation. Journal of Neuroscience 2009; 29:
10087-10093 </span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">4.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">Tse D, Langston RF, Kakeyama M, Bet=
hus I, Spooner PA,
Wood ER, Witter MP, Morris RG. Schemas and memory consolidation. Science 20=
07;
316: 76-82</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">5.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:NL" lang=3D"NL">van Kesteren MT, Fern=C3=A1ndez G, Norris=
DG, Hermans EJ. </span><span style=3D"font-family:"Times New Roman&qu=
ot;,"serif";mso-ansi-language:EN-US" lang=3D"EN-US">Persistent
schema-dependent hippocampal-neocortical connectivity during memory encodin=
g
and post-encoding rest in humans. Proceedings of the National Academy of
Sciences USA 2010; 107: 7550-7555</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">6.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">van Kesteren MT, Rijpkema M, Ruiter=
DJ, Fern=C3=A1ndez G.
Retrieval of associative information congruent with prior knowledge is rela=
ted
to increased medial prefrontal activity and connectivity. Journal of
Neuroscience 2010; 30: 15888-15894</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">7.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">Wang SH, Morris RG. Hippocampal-neo=
cortical
interactions in memory formation, consolidation, and reconsolidation. Annua=
l
Reviews of Psychology 2010; 61: 49-79</span></p>
<p class=3D"MsoListParagraphCxSpLast" style=3D"margin-top:0cm;margin-right:=
0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">8.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">Wang SH, Redondo RL, Morris RG. Rel=
evance of synaptic
tagging and capture to the persistence of long-term potentiation and everyd=
ay
spatial memory. Proceedings of the National Academy of Sciences USA 2010; 1=
07:
19537-42</span></p>
</div></body></html>
------=_Part_289559_725131480.1306782884233--
=========================================================================
Date: Mon, 30 May 2011 21:15:37 +0200
Reply-To: Guillen Fernandez <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Guillen Fernandez <[log in to unmask]>
Subject: PHD Opening: Cognitive Neuroscience of Memory
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
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boundary="----=_Part_289573_670777790.1306782936965"
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------=_Part_289573_670777790.1306782936965
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PhD-Student in Cognitive Neuroscience of Memory=20
Donders Institute, Centre for Cognitive Neuroimaging=20
Vacancy number: 010567=20
Closing date: Review of applications will continue until the position is fi=
lled.=20
Job description=20
The Donders Institute for Brain, Cognition, and Behavior seeks to hire an e=
xcellent PhD student in Cognitive Neuroscience of Memory in the laboratory =
of Guill=C3=A9n Fern=C3=A1ndez. The Fern=C3=A1ndez Lab probes the brain bas=
is of memory, emotion, and their interactions. It applies an interdisciplin=
ary approach integrating cognitive neuroimaging, pharmacology, genetics, an=
d diverse clinical disciplines.=20
The current position is financed by a prestigious ERC Advanced Investigator=
Grant, which Richard Morris (University of Edinburgh) and Guill=C3=A9n Fer=
n=C3=A1ndez received jointly. This project is an interdisciplinary experime=
ntal analysis of the neurobiological mechanisms by which we acquire knowled=
ge. Our approach builds upon recent findings of the participating laborator=
ies that have each addressed key issues associated with the rapid acquisiti=
on and assimilation of new associative information into existing neural =E2=
=80=98schemas=E2=80=99 (see below for a list of selected, recent publicatio=
ns of the Morris and Fern=C3=A1ndez lab on this topic). Rapid learning depe=
nds upon both novelty and prior knowledge . We will conduct a coordinated p=
rogram of research concerning the mechanisms of both determinants. First, w=
e will test that novelty , acting via the release of dopamine, has a direct=
impact on the mechanisms of cellular consolidation in the hippocampus. Sec=
ond, with respect to prior knowledge , the retention of new event-related a=
ssociative information requires the process of systems consolidation within=
declarative memory, as widely studied, but we further suggest that the org=
anisation of knowledge requires more than just stabilising memory traces wi=
thin neocortical networks. It also involves the integration of distinct mem=
ory traces into neural =E2=80=98schemas=E2=80=99 that, once formed, have a =
major positive influence on future learning. The studies conducted at the D=
onders Institute will involve fMRI using new cognitive tasks combined with =
pharmacology (sophisticated dopamine manipulation), transcranial magnetic s=
timulation, model-free analysis methods, and a translational project reachi=
ng into real-world education.=20
Requirements=20
As a candidate for the PhD student position, you should have a Master=E2=80=
=99s degree (or equivalent) in a field related to cognitive neuroscience (e=
.g. experimental/cognitive psychology, biology, neuroscience). Proficiency =
in oral and written English, and programming skills (Matlab) are essential.=
=20
Organization=20
The Donders Institute for Brain, Cognition and Behaviour (http://www.ru.nl/=
donders/) offers cognitive neuroscientists a unique, multidisciplinary work=
ing and learning environment with opportunities for developing expertise in=
a diversity of research areas and techniques. The centre is equipped with =
three MRI scanners (7T, 3T, 1.5T), a 275-channel MEG system, an EEG-TMS lab=
oratory, several (MR-compatible) EEG systems, and high-performance computat=
ional facilities. Website: http://www.ru.nl/donders/=20
Conditions of employment=20
Employment: 1,0 fte=20
The gross starting salary is =E2=82=AC2,042 per month and will increase to =
=E2=82=AC2,612 (fourth year). In addition to the monthly gross salary, you =
will receive two yearly 8% bonuses (holiday and end-of-year).=20
Additional conditions of employment=20
As a PhD candidate, you will be appointed for a period of 4 years. Your per=
formance will be evaluated after 18 months. If the evaluation is positive, =
the contract will be extended by 2.5 years.=20
Application=20
We prefer online applications ( link )=20
Alternatively, written applications including an application letter, a CV, =
and the names (email addresses) of two persons who can provide references c=
an be send to=20
UMC St Radboud=20
Mw. M. Korsten=20
[log in to unmask]
Huispostcode 155=20
Concerns vacancy: 010567=20
Postbus 9101=20
6500 HB Nijmegen=20
Additional Information=20
Please visit our web page for further details about our lab, ( http://www.r=
u.nl/donders/research/theme-3-learning/research-groups/cognitive-neurology/=
)=20
or contact: Prof. Dr. Guill=C3=A9n Fern=C3=A1ndez ( [log in to unmask]
nl )=20
Project relevant, recent publications from the Morris and the Fern=C3=A1nde=
z Lab=E2=80=99s=20
1. Bethus I, Tse D, Morris RG. Dopamine and memory: modulation of the persi=
stence of memory for novel hippocampal NMDA receptor-dependent paired assoc=
iates. Journal of Neuroscience. 2010; 30: 1610-8.=20
2. Takashima A, Petersson KM, Rutters F, Tendolkar I, Jensen O, Zwarts MJ, =
McNaughton BL, Fern=C3=A1ndez G. Declarative memory consolidation in humans=
: a prospective functional magnetic resonance imaging study. Proceedings of=
the National Academy of Sciences USA 2006; 103: 756-761=20
3. Takashima A, Nieuwenhuis IL, Jensen O, Talamini LM, Rijpkema M, Fern=C3=
=A1ndez G. Shift from hippocampal to neocortical centered retrieval network=
with consolidation. Journal of Neuroscience 2009; 29: 10087-10093=20
4. Tse D, Langston RF, Kakeyama M, Bethus I, Spooner PA, Wood ER, Witter MP=
, Morris RG. Schemas and memory consolidation. Science 2007; 316: 76-82=20
5. van Kesteren MT, Fern=C3=A1ndez G, Norris DG, Hermans EJ. Persistent sch=
ema-dependent hippocampal-neocortical connectivity during memory encoding a=
nd post-encoding rest in humans. Proceedings of the National Academy of Sci=
ences USA 2010; 107: 7550-7555=20
6. van Kesteren MT, Rijpkema M, Ruiter DJ, Fern=C3=A1ndez G. Retrieval of a=
ssociative information congruent with prior knowledge is related to increas=
ed medial prefrontal activity and connectivity. Journal of Neuroscience 201=
0; 30: 15888-15894=20
7. Wang SH, Morris RG. Hippocampal-neocortical interactions in memory forma=
tion, consolidation, and reconsolidation. Annual Reviews of Psychology 2010=
; 61: 49-79=20
8. Wang SH, Redondo RL, Morris RG. Relevance of synaptic tagging and captur=
e to the persistence of long-term potentiation and everyday spatial memory.=
Proceedings of the National Academy of Sciences USA 2010; 107: 19537-42=20
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normal;mso-outline-level:2"><b><span style=3D"font-size:18.0pt;
font-family:"Times New Roman","serif";mso-fareast-font-=
family:"Times New Roman";
mso-ansi-language:EN-US;mso-fareast-language:DE" lang=3D"EN-US">PhD-Student=
in Cognitive Neuroscience
of Memory</span></b></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><b=
><span lang=3D"EN-GB"> </span></b></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><b=
><span style=3D"mso-bidi-font-size:11.0pt" lang=3D"EN-GB">Donders Institute=
, Centre for
Cognitive Neuroimaging</span></b><span style=3D"mso-bidi-font-size:
11.0pt" lang=3D"EN-GB"></span></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><b=
><span style=3D"mso-bidi-font-size:11.0pt" lang=3D"EN-GB">Vacancy number: <=
/span><span lang=3D"EN-GB">010567</span></b><span style=3D"mso-bidi-font-si=
ze:11.0pt" lang=3D"EN-GB"></span></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><b=
><span style=3D"mso-bidi-font-size:11.0pt" lang=3D"EN-GB">Closing date: Rev=
iew of
applications will continue until the position is filled.</span></b></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><s=
trong><span style=3D"mso-bidi-font-size:11.0pt;mso-ansi-language:EN-US" lan=
g=3D"EN-US"> </span></strong></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><s=
trong><span style=3D"mso-bidi-font-size:11.0pt;mso-ansi-language:EN-US" lan=
g=3D"EN-US">Job
description</span></strong></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><s=
pan style=3D"mso-bidi-font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-=
US">The
Donders Institute for Brain, Cognition, and Behavior seeks to hire an excel=
lent
PhD student in Cognitive Neuroscience of Memory in the laboratory of Guill=
=C3=A9n
Fern=C3=A1ndez. The Fern=C3=A1ndez Lab probes the brain basis of memory, em=
otion, and
their interactions. It applies an interdisciplinary approach integrating
cognitive neuroimaging, pharmacology, genetics, and diverse clinical
disciplines. </span></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><s=
pan style=3D"mso-bidi-font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-=
US">The
current position is financed by a prestigious ERC Advanced Investigator Gra=
nt,
which Richard Morris (University of Edinburgh) and Guill=C3=A9n Fern=C3=A1n=
dez received
jointly. This project is an interdisciplinary experimental analysis of the
neurobiological mechanisms by which we acquire knowledge. Our approach buil=
ds
upon recent findings of the participating laboratories that have each addre=
ssed
key issues associated with the rapid acquisition and assimilation of new
associative information into existing neural =E2=80=98schemas=E2=80=99 (see=
below for a list of
selected, recent publications of the Morris and Fern=C3=A1ndez lab on this =
topic).
Rapid learning depends upon both <i style=3D"mso-bidi-font-style:normal">no=
velty</i>
and <i style=3D"mso-bidi-font-style:normal">prior knowledge</i>. We will co=
nduct
a coordinated program of research concerning the mechanisms of both
determinants. First, we will test that <i style=3D"mso-bidi-font-style:norm=
al">novelty</i>,
acting via the release of dopamine, has a direct impact on the mechanisms o=
f
cellular consolidation in the hippocampus. Second, with respect to <i style=
=3D"mso-bidi-font-style:normal">prior knowledge</i>, the retention of new
event-related associative information requires the process of systems
consolidation within declarative memory, as widely studied, but we further =
suggest
that the organisation of knowledge requires more than just stabilising memo=
ry
traces within neocortical networks. It also involves the integration of
distinct memory traces into neural =E2=80=98schemas=E2=80=99 that, once for=
med, have a major
positive influence on future learning. The studies conducted at the Donders
Institute will involve fMRI using new cognitive tasks combined with
pharmacology (sophisticated dopamine manipulation), transcranial magnetic
stimulation, model-free analysis methods, and a translational project reach=
ing
into real-world education.</span></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><s=
pan style=3D"mso-bidi-font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-=
US"> </span></p>
<p class=3D"ERCNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt"><s=
trong><span style=3D"mso-bidi-font-size:11.0pt;mso-ansi-language:EN-US" lan=
g=3D"EN-US">Requirements</span></strong></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt;text-align:justify"><span styl=
e=3D"font-size:11.0pt;mso-fareast-font-family:Times;mso-ansi-language:
EN-US;mso-fareast-language:EN-US" lang=3D"EN-US">As a candidate for the PhD=
student position,
you should have a Master=E2=80=99s degree (or equivalent) in a field relate=
d to
cognitive neuroscience (e.g. experimental/cognitive psychology, biology, ne=
uroscience).
Proficiency in oral and written English, and programming skills (Matlab) ar=
e
essential. </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt;text-align:justify"><span styl=
e=3D"font-size:11.0pt;mso-fareast-font-family:Times;mso-ansi-language:
EN-US;mso-fareast-language:EN-US" lang=3D"EN-US"> </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt;text-align:justify"><strong><s=
pan style=3D"font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">Organ=
ization</span></strong></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt;text-align:justify"><span styl=
e=3D"font-size:11.0pt;mso-fareast-font-family:Times;mso-ansi-language:
EN-US;mso-fareast-language:EN-US" lang=3D"EN-US">The Donders Institute for =
Brain, Cognition
and Behaviour (http://www.ru.nl/donders/) offers cognitive neuroscientists =
a
unique, multidisciplinary working and learning environment with opportuniti=
es
for developing expertise in a diversity of research areas and techniques. T=
he
centre is equipped with three MRI scanners (7T, 3T, 1.5T), a 275-channel ME=
G
system, an EEG-TMS laboratory, several (MR-compatible) EEG systems, and
high-performance computational facilities. Website: </span><a href=3D"http:=
//www.ru.nl/donders/" target=3D"_blank"><span style=3D"font-size:11.0pt;mso=
-fareast-font-family:Times;color:windowtext;
mso-ansi-language:EN-US;mso-fareast-language:EN-US;text-decoration:none;
text-underline:none" lang=3D"EN-US">http://www.ru.nl/donders/</span></a><sp=
an style=3D"font-size:11.0pt;mso-fareast-font-family:Times;mso-ansi-languag=
e:EN-US;
mso-fareast-language:EN-US" lang=3D"EN-US"></span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt;text-align:justify"><span styl=
e=3D"font-size:11.0pt;mso-fareast-font-family:Times;mso-ansi-language:
EN-US;mso-fareast-language:EN-US" lang=3D"EN-US"> </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><b><span style=3D"font-size:1=
1.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">Conditions of employment</spa=
n></b><span style=3D"font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-U=
S"> </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><span style=3D"font-size:
11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">Employment: 1,0 fte </span><=
/p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><span style=3D"font-size:
11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">The gross starting salary is=
=E2=82=AC2,042 per month
and will increase to =E2=82=AC2,612 (fourth year). In addition to the month=
ly gross
salary, you will receive two yearly 8% bonuses (holiday and end-of-year). <=
/span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><span style=3D"font-size:
11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US"> </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><strong><span style=3D"font-s=
ize:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">Additional conditions of
employment</span></strong></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><span style=3D"font-size:
11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">As a PhD candidate, you will=
be appointed for a
period of 4 years. Your performance will be evaluated after 18 months. If t=
he
evaluation is positive, the contract will be extended by 2.5 years. </span>=
</p>
<p class=3D"MsoNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt;tex=
t-align:
justify;line-height:normal;mso-layout-grid-align:none;text-autospace:none">=
<strong><span style=3D"mso-ansi-language:EN-US" lang=3D"EN-US"> </span=
></strong></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt;tex=
t-align:
justify;line-height:normal;mso-layout-grid-align:none;text-autospace:none">=
<strong><span style=3D"mso-ansi-language:EN-US" lang=3D"EN-US">Application<=
/span></strong></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt;tex=
t-align:
justify;line-height:normal;mso-layout-grid-align:none;text-autospace:none">=
<span style=3D"font-family:"Times New Roman","serif";ms=
o-fareast-font-family:
Times;mso-ansi-language:EN-US" lang=3D"EN-US">We prefer</span><span style=
=3D"font-size:12.0pt;font-family:"Times New Roman","serif&qu=
ot;;mso-fareast-font-family:
"Times New Roman";mso-ansi-language:EN-US;mso-fareast-language:DE=
" lang=3D"EN-US"> online
applications (</span><a href=3D"http://www.umcn.nl/OverUMCstRadboud/werkenb=
ij/Pages/Solliciteren.aspx?VacatureNummer=3D010567&EmailAdres=3DCBEG-so=
[log in to unmask]"><span style=3D"font-size:12.0pt;font-family:"=
Times New Roman","serif";
mso-fareast-font-family:"Times New Roman";mso-ansi-language:EN-US=
;mso-fareast-language:
DE" lang=3D"EN-US">link</span></a><span style=3D"font-size:12.0pt;font-fami=
ly:"Times New Roman","serif";
mso-fareast-font-family:"Times New Roman";mso-ansi-language:EN-US=
;mso-fareast-language:
DE" lang=3D"EN-US">)</span></p>
<p class=3D"MsoNormal" style=3D"mso-margin-top-alt:auto;mso-margin-bottom-a=
lt:auto;
line-height:normal"><span style=3D"font-size:12.0pt;font-family:"Times=
New Roman","serif";
mso-fareast-font-family:"Times New Roman";mso-ansi-language:EN-US=
;mso-fareast-language:
DE" lang=3D"EN-US">Alternatively, written applications including an applica=
tion letter, a CV,
and the names (email addresses) of two persons who can provide references c=
an
be send to <br>
<br>
UMC St Radboud<br>
Mw. M. Korsten<br>
[log in to unmask] <br>
Huispostcode 155<br>
Concerns vacancy: 010567<br>
Postbus 9101<br>
6500 HB Nijmegen</span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt;tex=
t-align:
justify;line-height:normal;mso-layout-grid-align:none;text-autospace:none">=
<span style=3D"font-family:"Times New Roman","serif";ms=
o-fareast-font-family:
Times;mso-ansi-language:EN-US" lang=3D"EN-US"> </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><b><span style=3D"font-size:1=
1.0pt;mso-ansi-language:EN-US" lang=3D"EN-US">Additional Information</span>=
</b><span style=3D"font-size:11.0pt;mso-ansi-language:EN-US" lang=3D"EN-US"=
> </span></p>
<p style=3D"margin:0cm;margin-bottom:.0001pt"><span style=3D"font-size:
11.0pt;mso-fareast-font-family:Times;mso-ansi-language:EN-US;mso-fareast-la=
nguage:
EN-US" lang=3D"EN-US">Please visit our web page for further details about o=
ur lab, (</span><a href=3D"http://www.ru.nl/donders/research/theme-3-learni=
ng/research-groups/cognitive-neurology/"><span style=3D"font-size:11.0pt;ms=
o-fareast-font-family:Times;color:windowtext;
mso-ansi-language:EN-US;mso-fareast-language:EN-US;text-decoration:none;
text-underline:none" lang=3D"EN-US">http://www.ru.nl/donders/research/theme=
-3-learning/research-groups/cognitive-neurology/</span></a><span style=3D"f=
ont-size:11.0pt;mso-fareast-font-family:Times;mso-ansi-language:
EN-US;mso-fareast-language:EN-US" lang=3D"EN-US">) <br>
or contact: Prof. Dr. Guill=C3=A9n Fern=C3=A1ndez (</span><a href=3D"mailto=
:[log in to unmask]"><span style=3D"font-size:11.0pt;
mso-fareast-font-family:Times;color:windowtext;mso-ansi-language:EN-US;
mso-fareast-language:EN-US;text-decoration:none;text-underline:none" lang=
=3D"EN-US">[log in to unmask]</span></a><span style=3D"font-size:11.=
0pt;mso-fareast-font-family:Times;mso-ansi-language:
EN-US;mso-fareast-language:EN-US" lang=3D"EN-US">)</span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt;tex=
t-align:
justify;line-height:normal;mso-layout-grid-align:none;text-autospace:none">=
<span style=3D"font-family:"Times New Roman","serif";ms=
o-fareast-font-family:
Times;mso-ansi-language:EN-US" lang=3D"EN-US"> </span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt;tex=
t-align:
justify;line-height:normal;mso-layout-grid-align:none;text-autospace:none">=
<span style=3D"font-family:"Times New Roman","serif";ms=
o-fareast-font-family:
Times;mso-ansi-language:EN-US" lang=3D"EN-US">Project relevant, recent publ=
ications from the
Morris and the Fern=C3=A1ndez Lab=E2=80=99s</span></p>
<p class=3D"MsoListParagraphCxSpFirst" style=3D"margin-top:0cm;margin-right=
:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;line-height:normal;tab-stops:21.3pt"><span style=3D"font=
-family:"Times New Roman","serif";mso-ansi-language:EN-=
US" lang=3D"EN-US"> </span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">1.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">Bethus I, Tse D, Morris RG. Dopamin=
e and memory:
modulation of the persistence of memory for novel hippocampal NMDA
receptor-dependent paired associates. Journal of Neuroscience. 2010; 30:
1610-8.</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">2.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">Takashima A, Petersson KM, Rutters =
F, Tendolkar I,
Jensen O, Zwarts MJ, McNaughton BL, Fern=C3=A1ndez G. Declarative memory
consolidation in humans: a prospective functional magnetic resonance imagin=
g
study. Proceedings of the National Academy of Sciences USA 2006; 103: 756-7=
61</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">3.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">Takashima A, Nieuwenhuis IL, Jensen=
O, Talamini LM,
Rijpkema M, Fern=C3=A1ndez G. Shift from hippocampal to neocortical centere=
d retrieval
network with consolidation. Journal of Neuroscience 2009; 29: 10087-10093 <=
/span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">4.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">Tse D, Langston RF, Kakeyama M, Bet=
hus I, Spooner PA,
Wood ER, Witter MP, Morris RG. Schemas and memory consolidation. Science 20=
07;
316: 76-82</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">5.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:NL" lang=3D"NL">van Kesteren MT, Fern=C3=A1ndez G, Norris=
DG, Hermans EJ. </span><span style=3D"font-family:"Times New Roman&qu=
ot;,"serif";mso-ansi-language:EN-US" lang=3D"EN-US">Persistent
schema-dependent hippocampal-neocortical connectivity during memory encodin=
g
and post-encoding rest in humans. Proceedings of the National Academy of
Sciences USA 2010; 107: 7550-7555</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">6.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">van Kesteren MT, Rijpkema M, Ruiter=
DJ, Fern=C3=A1ndez G.
Retrieval of associative information congruent with prior knowledge is rela=
ted
to increased medial prefrontal activity and connectivity. Journal of
Neuroscience 2010; 30: 15888-15894</span></p>
<p class=3D"MsoListParagraphCxSpMiddle" style=3D"margin-top:0cm;margin-righ=
t:0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">7.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">Wang SH, Morris RG. Hippocampal-neo=
cortical
interactions in memory formation, consolidation, and reconsolidation. Annua=
l
Reviews of Psychology 2010; 61: 49-79</span></p>
<p class=3D"MsoListParagraphCxSpLast" style=3D"margin-top:0cm;margin-right:=
0cm;
margin-bottom:0cm;margin-left:33.2pt;margin-bottom:.0001pt;mso-add-space:au=
to;
text-align:justify;text-indent:-18.0pt;line-height:normal;mso-list:l0 level=
1 lfo1;
tab-stops:21.3pt"><span style=3D"font-family:
"Times New Roman","serif";mso-fareast-font-family:"=
;Times New Roman";mso-ansi-language:
EN-US" lang=3D"EN-US"><span style=3D"mso-list:Ignore">8.<span style=3D"font=
:7.0pt "Times New Roman"">
</span></span></span><span style=3D"font-family:"Times New Roman"=
,"serif";
mso-ansi-language:EN-US" lang=3D"EN-US">Wang SH, Redondo RL, Morris RG. Rel=
evance of synaptic
tagging and capture to the persistence of long-term potentiation and everyd=
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spatial memory. Proceedings of the National Academy of Sciences USA 2010; 1=
07:
19537-42</span></p>
<p class=3D"MsoNormal" style=3D"margin-bottom:0cm;margin-bottom:.0001pt;tex=
t-align:
justify;line-height:normal;mso-layout-grid-align:none;text-autospace:none">=
<span style=3D"font-family:"Times New Roman","serif";ms=
o-ansi-language:EN-US" lang=3D"EN-US"> </span></p>
</div></body></html>
------=_Part_289573_670777790.1306782936965--
=========================================================================
Date: Mon, 30 May 2011 22:34:43 +0200
Reply-To: Christophe Phillips <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Christophe Phillips <[log in to unmask]>
Subject: Open phd position: Multivariate data-driven diagnosis of
Parkinson=?windows-1252?Q?=92s_?=disease
MIME-Version: 1.0
Content-Type: multipart/mixed; boundary="------------020906010806030009010700"
Message-ID: <[log in to unmask]>
This is a multi-part message in MIME format.
--------------020906010806030009010700
Content-Type: text/plain; charset=windows-1252; format=flowed
Content-Transfer-Encoding: quoted-printable
X-MIME-Autoconverted: from 8bit to quoted-printable by bifur.jiscmail.ac.uk id p4UKcifx023027
The Cyclotron Research Centre (CRC) at the University of Li=E8ge is=20
recruiting a PhD student with a background in engineering, biomedical=20
engineering or computer sciences for a project on multivariate=20
data-driven diagnosis of Parkinson=92s disease (see project description=20
attached)
Applications are welcome from overseas as well as from EU nationals=20
(working languages in the laboratory are French and English). Employment=20
can begin immediately. Salary is commensurate with that of PhD=20
fellowships at the University of Li=E8ge. The project is initially funded=
=20
for 2 years, with possibilities for further extension up to 4 years. The=20
position will be advertised until filled. The CRC offer an exciting and=20
friendly multi-disciplinary research environment with ample=20
opportunities for training and collaboration, and excellent technical=20
facilities.
Application should be made electronically. Please submit your CV, copies=20
of all relevant degrees, a statement of interest, and the names and=20
email addresses of two referees to the following address:
[log in to unmask]
--------------020906010806030009010700
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name="PhD_ParkinsonDiseaseDiagnosis.pdf"
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dCAxIDAgUi9JbmZvIDI4IDAgUi9JRFs8NkFCQzFENUVGQ0M0NkU0REJFOTYyMkM4M0IzQUI4
MjU+PDZBQkMxRDVFRkNDNDZFNERCRTk2MjJDODNCM0FCODI1Pl0gL1ByZXYgMTA3MzA1L1hS
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--------------020906010806030009010700--
=========================================================================
Date: Tue, 31 May 2011 12:21:20 +1000
Reply-To: Seyed Batouli <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Seyed Batouli <[log in to unmask]>
Subject: Segmentation problem
Content-Type: multipart/alternative;
boundary="_000_514CC4E8C864D744BED2869B02DA985333294FE6D1INFPWEC001adu_"
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
--_000_514CC4E8C864D744BED2869B02DA985333294FE6D1INFPWEC001adu_
Content-Type: text/plain; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
Dear All,
I have two T1 scans of an elderly subject, done in the same session with ex=
actly the same settings and orientations.
But after segmentation one of them is good, the other one is very distorted=
and unacceptable. Do you have any idea of why it happens?
I have done normalization on both. both are ok.
I can send you the scans if needed.
Thanks,
Amir
--_000_514CC4E8C864D744BED2869B02DA985333294FE6D1INFPWEC001adu_
Content-Type: text/html; charset="iso-8859-1"
Content-Transfer-Encoding: quoted-printable
<html dir=3D"ltr"><head>
<meta http-equiv=3D"Content-Type" content=3D"text/html; charset=3Diso-8859-=
1">
<style id=3D"owaTempEditStyle"></style><style title=3D"owaParaStyle"><!--P =
{
MARGIN-TOP: 0px; MARGIN-BOTTOM: 0px
}
--></style>
</head>
<body ocsi=3D"x">
<div style=3D"FONT-SIZE: 13px; COLOR: #000000; DIRECTION: ltr; FONT-FAMILY:=
Tahoma">
<div></div>
<div dir=3D"ltr"><font face=3D"Tahoma" color=3D"#000000" size=3D"2">Dear Al=
l,</font></div>
<div dir=3D"ltr"><font face=3D"tahoma" size=3D"2"></font> </div>
<div dir=3D"ltr"><font face=3D"tahoma" size=3D"2">I have two T1 scans of an=
elderly subject, done in the same session with exactly the same settings a=
nd orientations.</font></div>
<div dir=3D"ltr"><font face=3D"tahoma" size=3D"2"></font> </div>
<div dir=3D"ltr"><font face=3D"tahoma" size=3D"2">But after segmentation on=
e of them is good, the other one is very distorted and unacceptable. Do you=
have any idea of why it happens?</font></div>
<div dir=3D"ltr"><font face=3D"tahoma" size=3D"2"></font> </div>
<div dir=3D"ltr"><font face=3D"tahoma" size=3D"2">I have done normalization=
on both. both are ok.</font></div>
<div dir=3D"ltr"><font face=3D"tahoma" size=3D"2"></font> </div>
<div dir=3D"ltr"><font face=3D"tahoma" size=3D"2">I can send you the scans =
if needed.</font></div>
<div dir=3D"ltr"><font face=3D"tahoma" size=3D"2"></font> </div>
<div dir=3D"ltr"><font face=3D"tahoma" size=3D"2">Thanks,</font></div>
<div dir=3D"ltr"><font face=3D"tahoma" size=3D"2"></font> </div>
<div dir=3D"ltr"><font face=3D"tahoma" size=3D"2">Amir</font></div>
</div>
</body>
</html>
--_000_514CC4E8C864D744BED2869B02DA985333294FE6D1INFPWEC001adu_--
=========================================================================
Date: Tue, 31 May 2011 08:20:55 +0100
Reply-To: Cath <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Cath <[log in to unmask]>
Subject: marsbar for % signal change
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear SPM experts,
I have two questions regarding using marsbar to output the percent signal=
change.=20
First, how to output % signal changes of more than one coordinates at onc=
e? (I know how to output % signal changes of one coordinate)
Second, how to output % signal changes of more than one coordinates at on=
ce at second level analysis?
I can not find useful info in the posts. Or, I miss something?
Thanks in advance!
Sincerely,
Cath
=========================================================================
Date: Tue, 31 May 2011 09:23:43 +0200
Reply-To: Leonhard Schilbach <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Leonhard Schilbach <[log in to unmask]>
Subject: Call for Papers; Frontiers Special Topic: Toward a neuroscience
of social interaction
Content-Type: multipart/alternative; boundary=Apple-Mail-5--45574633
Mime-Version: 1.0 (Apple Message framework v1084)
Message-ID: <[log in to unmask]>
--Apple-Mail-5--45574633
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain;
charset=windows-1252
Dear colleagues,
this is to draw your attention toward and invite submissions for an =
upcoming Frontiers in Neuroscience Special Topic entitled:
"Toward a neuroscience of social interaction"
Please find more details below and on the Frontiers website:
=
http://www.frontiersin.org/Human%20Neuroscience/specialtopics/towards_a_ne=
uroscience_of_soci/211
-Deadline for submission of abstracts: 30 Sept 2011
-Deadline for submission of full manuscripts: 31 Dec 2011
Best regards,
Leo Schilbach
--
Towards a neuroscience of social interaction
Hosted By:
Ulrich Pfeiffer, University Hospital Cologne, Germany=20
Bert Timmermans, University Hospital Cologne, Germany=20
Kai Vogeley, University Hospital Cologne, Germany=20
Chris Frith, Wellcome Trust Centre for Neuroimaging at University =
College London, United Kingdom=20
Leonhard Schilbach, Max-Planck-Institute for Neurological Research, =
Germany=20
The burgeoning field of social neuroscience has begun to illuminate the =
complex biological bases of human social cognitive abilities. However, =
in spite of being based on the premise of investigating the neural bases =
of interacting minds, the majority of studies have focused on studying =
brains in isolation using paradigms that investigate offline social =
cognition, i.e. social cognition from a detached observer's point of =
view, asking study participants to read out the mental states of others =
without being engaged in interaction with them. Consequently, the neural =
correlates of real-time social interaction have remained elusive and may =
=97paradoxically=97 represent the 'dark matter' of social neuroscience.=20=
More recently, a growing number of researchers have begun to study =
online social cognition, i.e. social cognition from a participant's =
point of view, based on the assumption that there is something =
fundamentally different when we are actively engaged with others in =
real-time social interaction as compared to when we merely observe them. =
Whereas, for offline social cognition, interaction and feedback are =
merely a way of gathering data about the other person that feeds into =
processing algorithms 'inside=92 the agent, it has been proposed that in =
online social cognition the knowledge of the other =97at least in part=97 =
resides in the interaction dynamics =91between=92 the agents. =
Furthermore being a participant in an ongoing interaction may entail a =
commitment toward being responsive created by important differences in =
the motivational foundations of online and offline social cognition.=20
In order to promote the development of the neuroscientific investigation =
of online social cognition, this Frontiers Special Topic aims at =
bringing together contributions from researchers in social neuroscience =
and related fields, whose work involves the study of at least two =
individuals and sometimes two brains, rather than single individuals and =
brains responding to a social context. Specifically, this special issue =
will adopt an interdisciplinary perspective on what it is that separates =
online from offline social cognition and the putative differences in the =
recruitment of underlying processes and mechanisms. Here, an important =
focal point will be to address the various roles of social interaction =
in contributing to and =97at times=97 constituting our awareness of =
other minds. For this Special Topic, we, therefore, solicit reviews, =
original research articles, opinion and method papers, which address the =
investigation of social interaction and go beyond traditional concepts =
and ways of experimentation in doing so. While focusing on work in the =
neurosciences, this Special Topic also welcomes contributions in the =
form of behavioral studies, psychophysiological investigations, =
methodological innovations, computational approaches, developmental and =
patient studies.=20
By focusing on cutting-edge research in social neuroscience and related =
fields, this Frontiers Special Issue will create new insights concerning =
the neurobiology of social interaction and holds the promise of helping =
social neuroscience to really go social.
--
Leonhard Schilbach, MD
Department of Psychiatry and Psychotherapy
University of Cologne, Germany
[log in to unmask]
&
Max-Planck-Institute for Neurological Research
Cologne, Germany
[log in to unmask]
--Apple-Mail-5--45574633
Content-Transfer-Encoding: quoted-printable
Content-Type: text/html;
charset=windows-1252
<html><head></head><body style=3D"word-wrap: break-word; =
-webkit-nbsp-mode: space; -webkit-line-break: after-white-space; ">Dear =
colleagues,<br><br>this is to draw your attention toward and invite =
submissions for an upcoming Frontiers in Neuroscience Special Topic =
entitled:<br><br>"Toward a neuroscience of social =
interaction"<br><br>Please find more details below and on the Frontiers =
website:<br><a =
href=3D"http://www.frontiersin.org/Human%20Neuroscience/specialtopics/towa=
rds_a_neuroscience_of_soci/211">http://www.frontiersin.org/Human%20Neurosc=
ience/specialtopics/towards_a_neuroscience_of_soci/211</a><br><br>-Deadlin=
e for submission of abstracts: 30 Sept 2011<br>-Deadline for submission =
of full manuscripts: 31 Dec 2011<br><br>Best regards,<br><br>Leo =
Schilbach<br><br><br><br><br>--<br><br>Towards a neuroscience of social =
interaction<br><br>Hosted By:<br>Ulrich Pfeiffer, University Hospital =
Cologne, Germany <br>Bert Timmermans, University Hospital Cologne, =
Germany <br>Kai Vogeley, University Hospital Cologne, =
Germany <br>Chris Frith, Wellcome Trust Centre for Neuroimaging at =
University College London, United Kingdom <br>Leonhard Schilbach, =
Max-Planck-Institute for Neurological Research, Germany <br><br>The =
burgeoning field of social neuroscience has begun to illuminate the =
complex biological bases of human social cognitive abilities. However, =
in spite of being based on the premise of investigating the neural bases =
of interacting minds, the majority of studies have focused on studying =
brains in isolation using paradigms that investigate offline social =
cognition, i.e. social cognition from a detached observer's point of =
view, asking study participants to read out the mental states of others =
without being engaged in interaction with them. Consequently, the neural =
correlates of real-time social interaction have remained elusive and may =
=97paradoxically=97 represent the 'dark matter' of social =
neuroscience. <br><br>More recently, a growing number of =
researchers have begun to study online social cognition, i.e. social =
cognition from a participant's point of view, based on the assumption =
that there is something fundamentally different when we are actively =
engaged with others in real-time social interaction as compared to when =
we merely observe them. Whereas, for offline social cognition, =
interaction and feedback are merely a way of gathering data about the =
other person that feeds into processing algorithms 'inside=92 the agent, =
it has been proposed that in online social cognition the knowledge of =
the other =97at least in part=97 resides in the interaction dynamics =
=91between=92 the agents. Furthermore being a participant in an ongoing =
interaction may entail a commitment toward being responsive created by =
important differences in the motivational foundations of online and =
offline social cognition. <br><br>In order to promote the =
development of the neuroscientific investigation of online social =
cognition, this Frontiers Special Topic aims at bringing together =
contributions from researchers in social neuroscience and related =
fields, whose work involves the study of at least two individuals and =
sometimes two brains, rather than single individuals and brains =
responding to a social context. Specifically, this special issue will =
adopt an interdisciplinary perspective on what it is that separates =
online from offline social cognition and the putative differences in the =
recruitment of underlying processes and mechanisms. Here, an important =
focal point will be to address the various roles of social interaction =
in contributing to and =97at times=97 constituting our awareness of =
other minds. For this Special Topic, we, therefore, solicit reviews, =
original research articles, opinion and method papers, which address the =
investigation of social interaction and go beyond traditional concepts =
and ways of experimentation in doing so. While focusing on work in the =
neurosciences, this Special Topic also welcomes contributions in the =
form of behavioral studies, psychophysiological investigations, =
methodological innovations, computational approaches, developmental and =
patient studies. <br><br>By focusing on cutting-edge research in =
social neuroscience and related fields, this Frontiers Special Issue =
will create new insights concerning the neurobiology of social =
interaction and holds the promise of helping social neuroscience to =
really go social.<br><br><br><br><br>--<br>Leonhard Schilbach, =
MD<br><br>Department of Psychiatry and Psychotherapy<br>University of =
Cologne, Germany<br><br><a =
href=3D"mailto:[log in to unmask]">leonhard.schilbach@uk-koeln=
.de</a><br><br>&<br><br>Max-Planck-Institute for Neurological =
Research<br>Cologne, Germany<br><br><a =
href=3D"mailto:[log in to unmask]">[log in to unmask]<=
/a></body></html>=
--Apple-Mail-5--45574633--
=========================================================================
Date: Tue, 31 May 2011 10:33:07 +0100
Reply-To: Ben Becker <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Ben Becker <[log in to unmask]>
Subject: Connectivity - sensitivity in small sample size
Mime-Version: 1.0
Content-Transfer-Encoding: quoted-printable
Content-Type: text/plain; charset="UTF-8"
Message-ID: <[log in to unmask]>
Dear SPMers,=20
we used fMRI to compare differences between one brain-lesioned patient an=
d a group of 12 healthy controls. Findings from a pooled 2-sample t-test =
revealed two regions of higher activity in the patients within the task r=
elated network. It would be an interesting question to investigate whethe=
r these two regions were most strongly connected within the controls. Wou=
ld a connectivity analysis incorporating only 12 subjects make sense? Are=
there other methodological approaches to test our hypothesis?=20
Thanks in advance & best regards,=20
Ben=20=20=20
=========================================================================
Date: Tue, 31 May 2011 11:47:59 +0200
Reply-To: Marko Wilke <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Marko Wilke <[log in to unmask]>
Subject: Re: Connectivity - sensitivity in small sample size
Comments: To: Ben Becker <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Hi Ben,
> we used fMRI to compare differences between one brain-lesioned
> patient and a group of 12 healthy controls. Findings from a pooled
> 2-sample t-test revealed two regions of higher activity in the
> patients within the task related network. It would be an interesting
> question to investigate whether these two regions were most strongly
> connected within the controls. Would a connectivity analysis
> incorporating only 12 subjects make sense? Are there other
> methodological approaches to test our hypothesis?
As a note of caution, we only recently tried something similar and found=20
interesting correlations between functional connectivity and a marker of=20
clinical impairment, which, however, were fully explained by looking at=20
the GM volume deficits in the patients. We felt that not taking into=20
account structural differences between groups may lead to potentially=20
erroneous conclusions. See http://dx.doi.org/10.1002/hbm.21227
Cheers,
Marko
--=20
____________________________________________________
PD Dr. med. Marko Wilke
Facharzt f=FCr Kinder- und Jugendmedizin
Leiter, Experimentelle P=E4diatrische Neurobildgebung
Universit=E4ts-Kinderklinik
Abt. III (Neurop=E4diatrie)
Marko Wilke, MD, PhD
Pediatrician
Head, Experimental Pediatric Neuroimaging
University Children's Hospital
Dept. III (Pediatric Neurology)
Hoppe-Seyler-Str. 1
D - 72076 T=FCbingen, Germany
Tel. +49 7071 29-83416
Fax +49 7071 29-5473
[log in to unmask]
http://www.medizin.uni-tuebingen.de/kinder/epn
____________________________________________________
=========================================================================
Date: Tue, 31 May 2011 12:21:49 +0200
Reply-To: Bas Neggers <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Bas Neggers <[log in to unmask]>
Subject: matlabbatch & dependencies
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Content-Transfer-Encoding: 7bit
Message-ID: <[log in to unmask]>
Dear list,
while developing some tools with the nice spm8 matlabbatch system, 3
questions popped to mind regarding dependencies:
1. when one concatenates multiple matlabbatch{..} cells (lets say cell 1
to 3 with cell 1 to 3 from another batch) referring to different jobs,
would existing dependencies be spared? For example, when I combine a
separate matlabbatch with 3 preprocessing jobs with a matlabbatch with 3
statistic jobs?
2. Is there a way to easily (re)create dependencies between in and
output images from different matlabbatch{..} nodes by hand, that is,
using matlab code? The only way I see now is in the batch GUI, making
automation quite cumbersome.
3. Is there a built in method in the batching system to 'ask' a
matlabbatch node what exactly its output images will be, adhering to its
dependencies? In theory this might be possible as matlabbatch is an
object rather than a cell structure.
Thanks for any pointers. The matlabbatch system seems quite elegant but
I have a hard time finding API documentation.
Cheers,
Bas
--
--------------------------------------------------
Dr. S.F.W. Neggers
Division of Brain Research
Rudolf Magnus Institute for Neuroscience
Utrecht University Medical Center
Visiting: Heidelberglaan 100, 3584 CX Utrecht
Room B.01.1.03
Mail : Huispost B.01.206, P.O. Box 85500
3508 GA Utrecht, the Netherlands
Tel : +31 (0)88 7559609
Fax : +31 (0)88 7555443
E-mail : [log in to unmask]
Web : http://www.neuromri.nl/people/bas-neggers
http://www.neuralnavigator.com
--------------------------------------------------
=========================================================================
Date: Tue, 31 May 2011 12:55:02 +0200
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Cerisa Stawowsky <[log in to unmask]>
Subject: MEG-data: unpaired two-sample t-test/paired t-test
MIME-Version: 1.0
Content-Type: multipart/alternative;
boundary="----=_Part_2136808_11883007.1306839302199"
Message-ID: <[log in to unmask]>
------=_Part_2136808_11883007.1306839302199
Content-Type: text/html; charset=UTF-8
Content-Transfer-Encoding: quoted-printable
<html xmlns=3D"http://www.w3.org/1999/xhtml" xml:lang=3D"en" lang=3D"en"><t=
itle></title><head><meta http-equiv=3D"Content-type" content=3D"text/html; =
charset=3DUTF-8" /><style type=3D"text/css"> html, body {overflow-x: visibl=
e; } html { width:100%; height:100%;margin:0px; padding:0px; overflow-y: au=
to; overflow-x: auto; }body { font-size: 100.01%; font-family : Verdana, Ge=
neva, Arial, Helvetica, sans-serif; background-color:transparent; overflow:=
show; background-image:none; margin:0px; padding:5px; }p { margin:0px; padd=
ing:0px; } body { font-size: 12px; font-family : Verdana, Geneva, Arial, He=
lvetica, sans-serif; } p { margin: 0; padding: 0; } blockquote { padding-le=
ft: 5px; margin-left: 5px; margin-bottom: 0px; margin-top: 0px; } blockquot=
e.quote { border-left: 1px solid #CCC; padding-left: 5px; margin-left: 5px;=
} .misspelled { background: transparent url(//webmailerng.1und1.de/static_=
resource/mailclient/widgets/basic/parts/maileditor/spellchecking_underline.=
gif) repeat-x scroll center bottom; } .correct {} .unknown {} .ignored {}</=
style></head><body id=3D"bodyElement" style=3D"">
Dear SPM user,<br><br>I have N-subjects and two conditions. I want to compa=
re these conditions at source level (MEG-data, evoked).<br>First I used acc=
identally unpaired two-sample t-test. Afterwards I used the paired t-test, =
the correct t-test to compare both conditions. <br><br>The results a curiou=
s: For the unpaired two-sample test I get significant results (corrected fo=
r FWE, p<0.05) for the contrast Cond1 > Cond2 (t-contrast). For the p=
aired t-test the significant results disappear (only uncorrected p<=
;0.001) for the same contrast Cond1 > Cond2 (t-contrast). The brain coor=
dinates are nearly same for both contrasts. <br><br>My question: Why disapp=
eared the significant results for the paired t-test? - What is the reason?-=
I expected better results for the paired t-test. Is this assumption incorr=
ect?<br><br><br>Best regards,<br><br>Cerisa Stawowsky<br><br><Bassfont size=
=3D"2" face=3D"Verdana"></body></html>
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Dear SPM user,
I have N-subjects and two conditions. I want to compare these conditions at source level (MEG-data, evoked).
First I used accidentally unpaired two-sample t-test. Afterwards I used the paired t-test, the correct t-test to compare both conditions.
The results a curious: For the unpaired two-sample test I get significant results (corrected for FWE, p<0.05) for the contrast Cond1 > Cond2 (t-contrast). For the paired t-test the significant results disappear (only uncorrected p<0.001) for the same contrast Cond1 > Cond2 (t-contrast). The brain coordinates are nearly same for both contrasts.
My question: Why disappeared the significant results for the paired t-test? - What is the reason?- I expected better results for the paired t-test. Is this assumption incorrect?
Best regards,
Cerisa Stawowsky
------=_Part_2136808_11883007.1306839302199--
=========================================================================
Date: Tue, 31 May 2011 13:19:36 +0100
Reply-To: "Tayaranian Hosseini P." <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Tayaranian Hosseini P." <[log in to unmask]>
Subject: Source Reconstruction-Epoched EEG
Content-Type: text/plain; charset="us-ascii"
Content-Transfer-Encoding: quoted-printable
MIME-Version: 1.0
Message-ID: <[log in to unmask]>
Dear SPMers,
I am going to do some source reconstruction of EEG but I need some of my qu=
estions to be answered first. I have an epoched EEG file with 27 trials whi=
ch are all for just one condition. I would like to reconstruct the source f=
or each trial first and I need to see all these reconstructed images separa=
tely. Then, I will average the reconstructed images and would like to see t=
he final reconstructed image.
1. When I press the invert button, it starts to reconstruct the sources wit=
hout asking me if I want to average or not. Does it first average the epoch=
s and then reconstruct the sources or first reconstruct the sources for eac=
h trial and then averages the images?
2. In the next step (WINDOW), the question of power pops up. If I choose fo=
r example "induced", does it start the reconstruction from the beginning? I=
f so, why this question is not asked in the "invert" step?
3. In "window" step, even when I choose "trials" for power, I can not see d=
ifferent reconstructions and I will just see "first trial". How can I see t=
he reconstruction of other trials?
4. In "image" step, again, how is the final image computed? EEG epoch avera=
ging or image averaging?
Best regards,
Pegah
--------------------------------------------------------
Pegah Tayaranian Hosseini
PhD Student
Room 4077, Tizard building (13)
Institute of Sound and Vibration Research
University of Southampton, SO17 1BJ, UK
Tel: 023 8059 2850
email: [log in to unmask]
=========================================================================
Date: Tue, 31 May 2011 14:57:47 +0200
Reply-To: Michels Lars <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Michels Lars <[log in to unmask]>
Subject: PhD position in functional neuroimaging
MIME-Version: 1.0
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boundary="----_=_NextPart_001_01CC1F92.56DF393C"
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This is a multi-part message in MIME format.
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PhD position in functional neuroimaging in patients with neurogenic and n=
on-neurogenic lower urinary tract dysfunction
=20
Applications are invited for a doctoral research position in the human ne=
uroimaging project "The bladder and the brain - supraspinal control of im=
paired lower urinary tract function in patients with neurogenic and non-n=
eurogenic bladder dysfunction", funded by the Swiss National Science Foun=
dation (SNF, 32003B_135774/1).
Starting September 2011, we will investigate supraspinal lower urinary tr=
act (LUT) control in patients with neurogenic (i.e. multiple sclerosis) a=
nd non-neurogenic bladder dysfunction. Patients with non-neurogenic LUT d=
ysfunction will be investigated before and after therapy for their LUT dy=
sfunction. The neuroimaging investigations will consist of a combination =
of advanced functional (functional MRI for resting state functional conne=
ctivity) and structural (diffusion tensor imaging (DTI) and voxel-based m=
orphometry (VBM)) brain imaging methods.
=20
The candidate has the chance to participate in an innovative and multidis=
ciplinary research project that is based on the long-standing successful =
collaboration and renowned scientific groundwork of the Institute of Neur=
oradiology at the University Hospital Zurich and the Neuro-Urology Resear=
ch Group at the Balgrist University Hospital.
=20
The candidate should hold a Master's degree in neuroimaging, neuroscience=
, neurobiology, neuropsychology, neurophysiology, physics, or a related f=
ield. Fluency in spoken and written English and the ability to work withi=
n a multidisciplinary team are essential. Good oral German language skill=
s are not mandatory but are advantageous. Experience with human MRI, or o=
ther brain imaging methods is an advantage. Familiarity with analysis sof=
tware, such as SPM/Matlab or FSL, and experience with programming languag=
es and statistical analysis is a great plus.=20
=20
Salaries are in accordance with the Swiss National Science Foundation (st=
arting at around 40'000 CHF p.a.). For further information about the proj=
ect please contact Dr. Lars Michels ([log in to unmask])
=20
Your application includes your CV with a cover letter including a descrip=
tion of your motivation and research interests, a copy of your academic d=
egree(s), and two academic referees to the address below. Reviews of appl=
ications will begin on 1 June 2011 and will continue until the position i=
s filled.
=20
Dr. Lars Michels
Department of Neuroradiology
University Hospital Zurich
Sternwartstr. 6
Z=FCrich 8091
Switzerland
=20
------_=_NextPart_001_01CC1F92.56DF393C
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charset="iso-8859-1"
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<HTML dir=3Dltr><HEAD>
<META content=3D"text/html; charset=3Dunicode" http-equiv=3DContent-Type>
<META name=3DGENERATOR content=3D"MSHTML 8.00.6001.19046"></HEAD>
<BODY>
<DIV dir=3Dltr id=3DidOWAReplyText62854>
<DIV dir=3Dltr><FONT color=3D#000000 size=3D2 face=3DArial>
<P style=3D"TEXT-ALIGN: left; MARGIN: 0pt" class=3DMsoBodyText2 align=3Dl=
eft><B><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-SIZE: 12pt; ms=
o-ansi-language: EN-GB" lang=3DEN-GB>PhD position in f</SPAN></B><B style=
=3D"mso-bidi-font-weight: normal"><SPAN style=3D"FONT-FAMILY: 'Times New =
Roman'; FONT-SIZE: 12pt; mso-ansi-language: EN-GB" lang=3DEN-GB>unctional=
neuroimaging in patients with neurogenic and non-neurogenic lower urinar=
y tract dysfunction</SPAN></B><B style=3D"mso-bidi-font-weight: normal"><=
SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-SIZE: 12pt; mso-ansi-l=
anguage: EN-US" lang=3DEN-US><?xml:namespace prefix =3D o ns =3D "urn:sch=
emas-microsoft-com:office:office" /><o:p></o:p></SPAN></B></P>
<P style=3D"MARGIN: 0pt" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'T=
imes New Roman'; FONT-SIZE: 12pt; mso-ansi-language: EN-GB" lang=3DEN-GB>=
<o:p> </o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt" class=3DMsoNormal><SPAN sty=
le=3D"FONT-FAMILY: 'Times New Roman'; COLOR: black; FONT-SIZE: 12pt; mso-=
fareast-language: DE-CH; mso-ansi-language: EN-GB" lang=3DEN-GB>Applicati=
ons are invited for a doctoral research position in the human neuroimagin=
g project “</SPAN><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; CO=
LOR: black; FONT-SIZE: 12pt; mso-ansi-language: EN-GB" lang=3DEN-GB>The b=
ladder and the brain - supraspinal control of impaired lower urinary trac=
t function in patients with neurogenic and non-neurogenic bladder dysfunc=
tion</SPAN><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; COLOR: black; F=
ONT-SIZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-GB" la=
ng=3DEN-GB>”, funded by the Swiss National Science Foundation (SNF, 32003B_135774/1).<o:p></o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt" class=3DMsoNormal><SPAN sty=
le=3D"FONT-FAMILY: 'Times New Roman'; COLOR: black; FONT-SIZE: 12pt; mso-=
fareast-language: DE-CH; mso-ansi-language: EN-GB" lang=3DEN-GB>Starting =
September 2011, we will investigate supraspinal lower urinary tract (LUT)=
control in patients with </SPAN><SPAN style=3D"FONT-FAMILY: 'Times New R=
oman'; COLOR: black; FONT-SIZE: 12pt; mso-ansi-language: EN-GB" lang=3DEN=
-GB>neurogenic (i.e. multiple sclerosis) and non-neurogenic bladder dysfu=
nction</SPAN><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; COLOR: black;=
FONT-SIZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-GB" =
lang=3DEN-GB>. Patients with non-neurogenic LUT dysfunction will be inves=
tigated before and after therapy for their LUT dysfunction. The neuroimaging investigations will consist of a combination of ad=
vanced functional (functional MRI for resting state functional connectivi=
ty) and structural (diffusion tensor imaging (DTI) and voxel-based morpho=
metry (VBM)) brain imaging methods.<o:p></o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-GB" lang=3D=
EN-GB><o:p> </o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-GB" lang=3D=
EN-GB>The candidate has the chance to participate in an innovative and mu=
ltidisciplinary research project that is based on the long-standing succe=
ssful collaboration and renowned scientific groundwork of the Institute o=
f Neuroradiology at the University Hospital Zurich and the Neuro-Urology =
Research Group at the Balgrist University Hospital.<o:p></o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-GB" lang=3D=
EN-GB><o:p> </o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt" class=3DMsoNormal><SPAN sty=
le=3D"FONT-FAMILY: 'Times New Roman'; FONT-SIZE: 12pt; mso-fareast-langua=
ge: DE-CH; mso-ansi-language: EN-GB" lang=3DEN-GB>The candidate should ho=
ld a Master’s degree in neuroimaging, neuroscience, neurobiology, n=
europsychology, neurophysiology, physics, or a related field. Fluency in =
spoken and written English</SPAN><SPAN style=3D"FONT-FAMILY: 'Times New R=
oman'; FONT-SIZE: 12pt; mso-ansi-language: EN-US" lang=3DEN-US> and the a=
bility to work within a multidisciplinary team are essential. </SPAN><SPA=
N style=3D"FONT-FAMILY: 'Times New Roman'; FONT-SIZE: 12pt; mso-fareast-l=
anguage: DE-CH; mso-ansi-language: EN-GB" lang=3DEN-GB>Good oral German</=
SPAN><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-SIZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-US" lang=3D=
EN-US> language skills</SPAN><SPAN style=3D"FONT-FAMILY: 'Times New Roman=
'; FONT-SIZE: 12pt; mso-ansi-language: EN-US" lang=3DEN-US> are not manda=
tory but are advantageous. </SPAN><SPAN style=3D"FONT-FAMILY: 'Times New =
Roman'; FONT-SIZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: =
EN-US" lang=3DEN-US>Experience</SPAN><SPAN style=3D"FONT-FAMILY: 'Times N=
ew Roman'; FONT-SIZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-languag=
e: EN-GB" lang=3DEN-US> </SPAN><SPAN style=3D"FONT-FAMILY: 'Times New Rom=
an'; FONT-SIZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-=
GB" lang=3DEN-GB>with human MRI, or other brain imaging methods is an adv=
antage.</SPAN><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; COLOR: black; FONT-SIZE: 12pt; mso-fareast-language: DE-CH; mso-ansi=
-language: EN-US" lang=3DEN-GB> </SPAN><SPAN style=3D"FONT-FAMILY: 'Times=
New Roman'; COLOR: black; FONT-SIZE: 12pt; mso-fareast-language: DE-CH; =
mso-ansi-language: EN-US" lang=3DEN-US>Familiarity with analysis software=
, such as SPM/Matlab or FSL, and experience with programming languages an=
d statistical analysis is a great plus. </SPAN><SPAN style=3D"FONT-FAMILY=
: 'Times New Roman'; FONT-SIZE: 12pt; mso-fareast-language: DE-CH; mso-an=
si-language: EN-GB" lang=3DEN-GB><o:p></o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-GB" lang=3D=
EN-GB><o:p> </o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-GB" lang=3D=
EN-GB>Salaries are in accordance with the Swiss National Science Foundati=
on (starting at around 40’000 CHF p.a.). For further information ab=
out the project please contact <U>Dr. Lars Michels</U> (lars.michels@kisp=
i.uzh.ch)<o:p></o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-GB" lang=3D=
EN-GB><o:p> </o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-GB" lang=3D=
EN-GB>Your application includes your CV with a cover letter including a d=
escription of your motivation and research interests, a copy of your acad=
emic degree(s), and two academic referees to the address below. Reviews o=
f applications will begin on 1 June 2011 and will continue until the posi=
tion is filled.<o:p></o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-GB" lang=3D=
EN-GB><o:p> </o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-GB" lang=3D=
EN-GB>Dr. Lars Michels<o:p></o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH; mso-ansi-language: EN-GB" lang=3D=
EN-GB>Department of Neuroradiology<o:p></o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH">University Hospital Zurich<o:p></=
o:p></SPAN></P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH">Sternwartstr. 6<o:p></o:p></SPAN>=
</P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH">Z=FCrich 8091<o:p></o:p></SPAN></=
P>
<P style=3D"TEXT-ALIGN: justify; MARGIN: 0pt; mso-layout-grid-align: none=
" class=3DMsoNormal><SPAN style=3D"FONT-FAMILY: 'Times New Roman'; FONT-S=
IZE: 12pt; mso-fareast-language: DE-CH">Switzerland<o:p></o:p></SPAN></P>
<P style=3D"MARGIN: 0pt; tab-stops: 35.4pt" class=3DMsoHeader><SPAN style=
=3D"FONT-FAMILY: 'Times New Roman'; FONT-SIZE: 12pt"><o:p> </o:p></S=
PAN></P></FONT><FONT color=3D#000000 size=3D2 face=3DArial></FONT></DIV><=
/DIV></BODY></HTML>
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=========================================================================
Date: Tue, 31 May 2011 14:29:11 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: Is it correct to register binary images with DARTEL?
Comments: To: Maria Serra <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
It should be possible, but you may need to do a little extra coding in
order to make sure your data are in a suitable format (all must have
the same dimensions, voxel sizes, orientations etc).
Best regards,
-John
On 30 May 2011 14:36, Maria Serra <[log in to unmask]> wrote:
>
> Dear SPMrs,
>
> We would like to register multiple binary images. Is it possible to do it
> with Dartel (create template and create warped)?
>
> Thank you for your help,
> --
> Maria Serra
>
> PIC (Port d'Informaci=F3 Cient=EDfica)
> Campus UAB, Edifici D
> E-08193 Bellaterra, Barcelona
> Telf. +34 93 586 8232
> www.pic.es
>
=========================================================================
Date: Tue, 31 May 2011 15:02:30 +0100
Reply-To: Vladimir Litvak <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Vladimir Litvak <[log in to unmask]>
Subject: Re: Source Reconstruction-Epoched EEG
Comments: To: "Tayaranian Hosseini P." <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Content-Transfer-Encoding: quoted-printable
Message-ID: <[log in to unmask]>
Dear Pegah,
On Tue, May 31, 2011 at 1:19 PM, Tayaranian Hosseini P.
<[log in to unmask]> wrote:
> Dear SPMers,
>
> I am going to do some source reconstruction of EEG but I need some of my =
questions to be answered first. I have an epoched EEG file with 27 trials w=
hich are all for just one condition. I would like to reconstruct the source=
for each trial first and I need to see all these reconstructed images sepa=
rately. Then, I will average the reconstructed images and would like to see=
the final reconstructed image.
>
> 1. When I press the invert button, it starts to reconstruct the sources w=
ithout asking me if I want to average or not. Does it first average the epo=
chs and then reconstruct the sources or first reconstruct the sources for e=
ach trial and then averages the images?
>
What the routine does is slightly more complicated than that. It
computes data covariance matrix based on all the trials and uses that
matrix to calculate the MAP projector which basically encodes the
information about which sources are part of the solution. Then this
projector can be used to compute the source currents from the data. If
your data is epoched the covariance matrix will be based on single
trials and might be slightly different from when your data is
averaged.
> 2. In the next step (WINDOW), the question of power pops up. If I choose =
for example "induced", does it start the reconstruction from the beginning?=
If so, why this question is not asked in the "invert" step?
>
No, it will use the pre-computed MAP projector to compute activations
for each trial and then apply wavelet analysis to those.
> 3. In "window" step, even when I choose "trials" for power, I can not see=
different reconstructions and I will just see "first trial". How can I see=
the reconstruction of other trials?
>
You can see them in the images that are exported.
>
> 4. In "image" step, again, how is the final image computed? EEG epoch ave=
raging or image averaging?
>
In the Image step, whatever was computed in the 'Window' step is saved
as an image. So if you used the 'evoked' option that would be an image
for the average ERP, if you used the 'induced' option that would be an
average of induced power over trials.
Practically, you have two options:
1) If you want to compute a reconstruction for each trial separately,
you should assign a different condition label to each trial and then
when as at the beginning of the 'Invert' step what condition to
select, you select only that trial. That way the results will not be
influenced by other trials, but if these are really single trials the
data will probably be too noisy for any meaningful source
reconstruction. Also if you want to do statistics across trials (e.g.
regression) it will work very poorly because the sources will not be
constrained to be similar. You can compute the average image and see
what that looks like, but it'd be really a suboptimal way of doing
things.
2) You can keep the same condition label and use the 'trials' option.
Then you'll get an image per trial but the sources will be the same
for all trials. That's the option to use if you want to do some
statistical analysis across trials assuming common sources, but that'd
not be the right thing to do if you think the activated sources will
be different for each trial.
Best,
Vladimir
=========================================================================
Date: Tue, 31 May 2011 17:13:46 +0300
Reply-To: Renate Rutiku <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Renate Rutiku <[log in to unmask]>
Subject: two questions about MEG source reconstruction
MIME-Version: 1.0
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Message-ID: <[log in to unmask]>
--90e6ba53b04020109a04a4930367
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Dear SPM community,
First, I have a question about the cortical meshes available for MEG source
reconstruction:
Are the deep brain structures (e.g hippocampus, amygdala) modeled in any of
the cortical meshes?
Second, I would like to ask for Your advice on the following problem:
When I do a paired t-test for two of my experimental conditions I find an
extended cluster in the corpus callosum. Are there any possibilities to
eliminate this artifact?
Many thanks for Your help,
Renate
--90e6ba53b04020109a04a4930367
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Dear SPM community,=A0<div><br></div><div>First, I have a question about th=
e cortical meshes available for MEG source=A0<meta http-equiv=3D"content-ty=
pe" content=3D"text/html; charset=3Dutf-8"><span class=3D"Apple-style-span"=
style=3D"border-collapse: collapse; font-family: arial, sans-serif; font-s=
ize: 13px; ">reconstruction</span>:</div>
<div>Are the deep brain structures (e.g hippocampus, amygdala) modeled in a=
ny of the cortical meshes?</div>
<div><br></div><div>Second, I would like to ask for Your advice on the foll=
owing problem:</div><div>When I do a paired t-test for two of my experiment=
al conditions I find an extended cluster in the corpus callosum. Are there =
any possibilities to eliminate this artifact?</div>
<div><br></div><div>Many thanks for Your help,=A0</div><div><br></div><div>=
Renate</div>
--90e6ba53b04020109a04a4930367--
=========================================================================
Date: Tue, 31 May 2011 16:25:32 +0100
Reply-To: Daniel Ferreira <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Daniel Ferreira <[log in to unmask]>
Subject: how to refer the VBM longitudinal pipeline
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Dear Christian Gaser and experts,
Please, what references should be used for the longitudinal pipeline or h=
ow should it be presented in a manuscript?
thank you very much in advance
Daniel Ferreira
=========================================================================
Date: Tue, 31 May 2011 16:45:32 +0100
Reply-To: "Tayaranian Hosseini P." <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: "Tayaranian Hosseini P." <[log in to unmask]>
Subject: Re: Source Reconstruction-Epoched EEG
In-Reply-To: <[log in to unmask]>
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Dear Vladimir,
Thank you very much. Your answers helped alot.
Best,
Pegah
--------------------------------------------------------
Pegah Tayaranian Hosseini
PhD Student
Room 4077, Tizard building (13)
Institute of Sound and Vibration Research
University of Southampton, SO17 1BJ, UK
Tel: 023 8059 2850
email: [log in to unmask]
________________________________________
From: Vladimir Litvak [[log in to unmask]]
Sent: 31 May 2011 15:02
To: Tayaranian Hosseini P.
Cc: [log in to unmask]
Subject: Re: [SPM] Source Reconstruction-Epoched EEG
Dear Pegah,
On Tue, May 31, 2011 at 1:19 PM, Tayaranian Hosseini P.
<[log in to unmask]> wrote:
> Dear SPMers,
>
> I am going to do some source reconstruction of EEG but I need some of my =
questions to be answered first. I have an epoched EEG file with 27 trials w=
hich are all for just one condition. I would like to reconstruct the source=
for each trial first and I need to see all these reconstructed images sepa=
rately. Then, I will average the reconstructed images and would like to see=
the final reconstructed image.
>
> 1. When I press the invert button, it starts to reconstruct the sources w=
ithout asking me if I want to average or not. Does it first average the epo=
chs and then reconstruct the sources or first reconstruct the sources for e=
ach trial and then averages the images?
>
What the routine does is slightly more complicated than that. It
computes data covariance matrix based on all the trials and uses that
matrix to calculate the MAP projector which basically encodes the
information about which sources are part of the solution. Then this
projector can be used to compute the source currents from the data. If
your data is epoched the covariance matrix will be based on single
trials and might be slightly different from when your data is
averaged.
> 2. In the next step (WINDOW), the question of power pops up. If I choose =
for example "induced", does it start the reconstruction from the beginning?=
If so, why this question is not asked in the "invert" step?
>
No, it will use the pre-computed MAP projector to compute activations
for each trial and then apply wavelet analysis to those.
> 3. In "window" step, even when I choose "trials" for power, I can not see=
different reconstructions and I will just see "first trial". How can I see=
the reconstruction of other trials?
>
You can see them in the images that are exported.
>
> 4. In "image" step, again, how is the final image computed? EEG epoch ave=
raging or image averaging?
>
In the Image step, whatever was computed in the 'Window' step is saved
as an image. So if you used the 'evoked' option that would be an image
for the average ERP, if you used the 'induced' option that would be an
average of induced power over trials.
Practically, you have two options:
1) If you want to compute a reconstruction for each trial separately,
you should assign a different condition label to each trial and then
when as at the beginning of the 'Invert' step what condition to
select, you select only that trial. That way the results will not be
influenced by other trials, but if these are really single trials the
data will probably be too noisy for any meaningful source
reconstruction. Also if you want to do statistics across trials (e.g.
regression) it will work very poorly because the sources will not be
constrained to be similar. You can compute the average image and see
what that looks like, but it'd be really a suboptimal way of doing
things.
2) You can keep the same condition label and use the 'trials' option.
Then you'll get an image per trial but the sources will be the same
for all trials. That's the option to use if you want to do some
statistical analysis across trials assuming common sources, but that'd
not be the right thing to do if you think the activated sources will
be different for each trial.
Best,
Vladimir
=========================================================================
Date: Tue, 31 May 2011 20:15:53 +0300
Reply-To: [log in to unmask]
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Brigitte Bogert <[log in to unmask]>
Subject: SPM8 truncating data at 2nd level analysis
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Message-ID: <[log in to unmask]>
Hi,
Has anyone run into issues with SPM8 sometimes truncating data at =20
2nd-level analysis (Results>Select SPM.mat>select Contrast, etc.) when =20
looking at different contrasts from an fMRI experiment? I use exactly =20
the same criteria each time, and this has happened multiples times =20
over multiple days on both Mac and Linux computers.
Typically, the clusters of both the truncated and full data sets are =20
exactly the same, at least halfway or 2/3 through the data. However, =20
the last few clusters are omitted in the truncated set.
It seems that either the truncated set of data or the full set of data =20
can randomly appear. Sometimes, I have found that if I switch =20
contrasts several times through the Contrasts menu within the Results =20
window, then the full data set will appear. However, this is not =20
always the case. I have thus far been unable to figure out a way to =20
manipulate this error consistently nor does it seem to be directly =20
dependent on Z score or number of clusters.
Does anybody have any insight?
Thanks for your help!
Brigitte
=========================================================================
Date: Tue, 31 May 2011 18:56:09 +0100
Reply-To: John Ashburner <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: John Ashburner <[log in to unmask]>
Subject: Re: mis-classification of gray matter using New segment tools
Comments: To: Xin Di <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
MIME-Version: 1.0
Content-Type: text/plain; charset=ISO-8859-1
Message-ID: <[log in to unmask]>
I don't have any good ideas about how to fix this one. The image has
tissue with similar intensity to GM, in a place that is fairly close
to where you'd expect to find GM. Fully automated segmentation
algorithms are simply not yet 100% reliable (largely because of a lack
of good training data).
Sometimes, it is worth trying various approaches to see what is
successful for any particular dataset. Where one segmentation model
fails, it is sometimes possible that another one will work. It
depends on the modelling assumptions used, and whether your data are a
good fit that particular model.
Best regards,
-John
On 27 May 2011 18:42, Xin Di <[log in to unmask]> wrote:
> Dear experts,
>
> I am using the new segment tool to run segmentations on several MRI images.
> For one of the subject, the tissues outside the cortices are mis-classified
> as gray matter and warped into the cortices after normalization (please see
> attached figures). I use the default settings of number of Gaussians for
> each tissue type. Can someone kindly give me some suggestions on how to
> avoid this mis-classification? Thank you!
>
> Sincerely,
>
> --
> Xin Di, PhD
>
> Postdoctoral Researcher
> Department of Radiology
> University of Medicine and Dentistry of New Jersey
> 30 Bergen Street, ADMC 575
> Newark, NJ 07101
>
>
=========================================================================
Date: Tue, 31 May 2011 22:07:22 +0100
Reply-To: David Soto <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: David Soto <[log in to unmask]>
Subject: Re: second level analysis affected by subject order
Comments: To: "<Lucy> <Brown>" <[log in to unmask]>
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Message-ID: <[log in to unmask]>
Hi, yes, say you have 3 subjects and one factor with 2 levels
at the highest level analyses you may specify the betas in different orde=
rs
subj1 beta1 subj1beta2
subj2 beta1 subj2beta2
subj3 beta1 subj3beta2
or
subj3 beta1 subj3beta2
subj2 beta1 subj2beta2
subj1 beta1 subj1beta2
or any other combination
you might see a similar set of clusters in both cases but order influence=
s the stats in a funny way
guess there may be implications to assess significance when the effects a=
re borderline=20
but in any case it is weird and am curious to learn what is the reason of=
this behaviour in the first place
rgds.
=========================================================================
Date: Tue, 31 May 2011 22:08:25 +0100
Reply-To: Max Hilger <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Max Hilger <[log in to unmask]>
Subject: SPM8: Errors in Normalization to EPI-Brain
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Message-ID: <[log in to unmask]>
--part-725WpPZCmosQAttp49BFulqr13FBABwp21WsCXZBDKTUP
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Dear SPM-Users,
we are currently doing a fMRT analysis in SPM8. The preprocessing of our =
images consists of realignment, slice timing, normaization to the EPI-tem=
plate and smoothing.
When we checked the results by overlaying the EPI-template with the activ=
ation maps after preprocessing in MRIcro we noticed that for all the subj=
ects there seems to be a consitent lack of activation in certain regions.=
The images attached are typical for all subjects analized. As you can see=
there seems to be a "hole" in the activation in the temporal lobe (bilat=
eral, upper images) and in the inferior frontal lobe (lower images). The =
size of these gaps in activation seems to differ slightly across the subj=
ects, but the general pattern is pretty consistent.
It would be very nice if you could give me insight what went wrong with t=
he preprocessing and help solve this problem. IF needed I can of course p=
rovide additional info regarding the parameters used.
Thanks in advance for any input!
Best regards,
Max Hilger
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--part-725WpPZCmosQAttp49BFulqr13FBABwp21WsCXZBDKTUP--
=========================================================================
Date: Tue, 31 May 2011 17:39:25 -0400
Reply-To: Mobin Anandwala <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Mobin Anandwala <[log in to unmask]>
Subject: Simulation of bilinear state model
MIME-Version: 1.0
Content-Type: multipart/alternative; boundary=001636284801e8cdcd04a4993c86
Message-ID: <[log in to unmask]>
--001636284801e8cdcd04a4993c86
Content-Type: text/plain; charset=ISO-8859-1
To SPM experts
I am currently working obtaining z states for given data (this data is from
DCM_MM). I have a discrete form of the bilinear state equation as follows
zk+1 = (A*dt+ ukB2*dt + I)*zk + C*uk*dt where uk is the sampled version of
the input (the input function being u2 based on the data as u3 was 0 and B1
and B3 were 0) I am trying to z as an m x n matrix with m rows being each z
state scaled by dt, 2*dt, 3dt,...m*dt and each column being each state of z
(z1,z2,z3...zn) I My main question is that is there a simulation of the
bilinear state equation available that looks at each state? I was unable to
attach my m-file
Thank you
Mobin
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To SPM experts<br><br><br>I am currently working obtaining z states for giv=
en data (this data is
from DCM_MM).=A0 I have a discrete form of the bilinear state equation as
follows zk+1 =3D (A*dt+ ukB2*dt + I)*zk +=A0 C*uk*dt where uk is the
sampled version of the input (the input function being u2 based on the
data as u3 was 0 and B1 and B3 were 0)=A0 I am trying to z as an m x n matr=
ix with m rows being each z
state scaled by dt, 2*dt, 3dt,...m*dt and each column being each state
of z (z1,z2,z3...zn)=A0 I=A0 My main question is that is there a
simulation of the bilinear state equation available that looks at each
state?=A0 I was unable to attach my m-file<br>
<br>Thank you<br><font color=3D"#888888"><br>Mobin</font>
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Date: Tue, 31 May 2011 23:59:08 +0200
Reply-To: Bas Neggers <[log in to unmask]>
Sender: "SPM (Statistical Parametric Mapping)" <[log in to unmask]>
From: Bas Neggers <[log in to unmask]>
Subject: Re: SPM8: Errors in Normalization to EPI-Brain
Comments: To: Max Hilger <[log in to unmask]>
In-Reply-To: <[log in to unmask]>
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Dear Max,
your problem is very likely with acquisition (check your raw data), and
not image processing. Close to air-tissue transitions EPI suffers from
magnetic field inhomogeneities, leading to increased dephasing of your
spins and thus a fast drop of transversal magnetization. That is why you
see it on top of the sinuses and over the middle/inner ear.
This is a very well known problem of EPI fMRI. You could consult your MR
physicist how to decrease the size of these dropout regions (short TE,
thinner slices, SENSE or GRAPPA, etc), but they will always be there to
some extent. Nothing much you can do about that.
Good luck,
Bas
On 05/31/2011 11:08 PM, Max Hilger wrote:
> Dear SPM-Users,
>
> we are currently doing a fMRT analysis in SPM8. The preprocessing of our images consists of realignment, slice timing, normaization to the EPI-template and smoothing.
> When we checked the results by overlaying the EPI-template with the activation maps after preprocessing in MRIcro we noticed that for all the subjects there seems to be a consitent lack of activation in certain regions.
>
> The images attached are typical for all subjects analized. As you can see there seems to be a "hole" in the activation in the temporal lobe (bilateral, upper images) and in the inferior frontal lobe (lower images). The size of these gaps in activation seems to differ slightly across the subjects, but the general pattern is pretty consistent.
>
> It would be very nice if you could give me insight what went wrong with the preprocessing and help solve this problem. IF needed I can of course provide additional info regarding the parameters used.
>
> Thanks in advance for any input!
>
> Best regards,
> Max Hilger
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Dr. S.F.W. Neggers
Division of Brain Research
Rudolf Magnus Institute for Neuroscience
Utrecht University Medical Center
Visiting: Heidelberglaan 100, 3584 CX Utrecht
Room B.01.1.03
Mail : Huispost B.01.206, P.O. Box 85500
3508 GA Utrecht, the Netherlands
Tel : +31 (0)88 7559609
Fax : +31 (0)88 7555443
E-mail : [log in to unmask]
Web : http://www.neuromri.nl/people/bas-neggers
http://www.neuralnavigator.com
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