Thx!
On Mon, May 23, 2016 at 5:19 PM, Rockers, Elijah D. <
[log in to unmask]> wrote:
> Moran, try the following command with your image. More info if you type
> simply 'fslmaths' with no arguments, at the command line.
>
> fslmaths <input_image.nii> -fillh <output_image.nii>
>
> - Eli
>
> On 05/22/2016 06:00 PM, FSL automatic digest system wrote:
> > There are 10 messages totaling 1403 lines in this issue.
> >
> > Topics of the day:
> >
> > 1. zero filling (3)
> > 2. No results with VBM (3)
> > 3. BEDPOSTX on data with replicated b-vectors in one dataset (3)
> > 4. probabilistic tractography
> >
> > ----------------------------------------------------------------------
> >
> > Date: Sun, 22 May 2016 06:42:17 +0100
> > From: Moran Artzi <[log in to unmask]>
> > Subject: zero filling
> >
> > Hi,
> > Is there any way to fill the holes in a binary image (as the brain_mask
> img - the output of bet) using FSL command line?
> > Thanks
> > Moran
> >
> > ------------------------------
> >
> > Date: Sun, 22 May 2016 09:20:06 +0100
> > From: "Anderson M. Winkler" <[log in to unmask]>
> > Subject: Re: No results with VBM
> >
> > Hi Rosalia,
> >
> > Please see below:
> >
> > On 21 May 2016 at 19:30, Rosalia Dacosta Aguayo <[log in to unmask]>
> wrote:
> >
> >> Dear Anderson,
> >>
> >> The data has been demeaned, and I am working with just one group of 45
> >> subjects, I am not sure about including an intercept in this model. Just
> >> partial correlations between this group and a cog variable, regressing
> out
> >> for age, gender and TIV....
> >>
> > It's necessary to demean both design and data, or else, include an
> > intercept. Mean-centering the data only isn't sufficient.
> >
> >
> >> And about my question regarding FIRST? I do not understand why I can get
> >> .vtk and .bvars files for my 4. ROIS but when I give a look into
> firstseg
> >> files and I check for registeting....I only find two of the deep gm
> >> structures but not the 4 previosly selected.
> >>
> > This refers to a different thread. I'm not sure what is going on.
> >
> >
> >> What is more, I am not quite sure about surface and vertex or shape
> >> analysis and how to interpret results...
> >>
> > The shape analysis indicates the places where there is a significant
> shape
> > difference (i.e., a significant effect on the positions of the vertices
> > that delineate the structure).
> >
> > All the best,
> >
> > Anderson
> >
> >
> >> I would greatly appreciate your helping hear.
> >>
> >> Kind regards,
> >>
> >> Rosalia
> >> El 20/05/2016 11:44, "Rosalia Dacosta Aguayo" <[log in to unmask]>
> >> escribió:
> >>
> >>> Thank you Anderson!!
> >>>
> >>> Rosalia
> >>>
> >>> 2016-05-20 10:07 GMT+02:00 Anderson M. Winkler <[log in to unmask]
> >:
> >>>
> >>>> Hi Rosalia,
> >>>>
> >>>> Just adding to this: need to include an intercept in the model, or use
> >>>> the option -D.
> >>>>
> >>>> All the best,
> >>>>
> >>>> Anderson
> >>>>
> >>>>
> >>>> On 19 May 2016 at 16:10, Colin Hawco <[log in to unmask]> wrote:
> >>>>
> >>>>> While I am afraid I can offer no specific advice for VBM in FSL, I do
> >>>>> have a general piece of advice.
> >>>>>
> >>>>>
> >>>>>
> >>>>> When I see a null result I think is suspicious, I immediately drop
> >>>>> threshold and take a look. As instead, instead of p < 0.05
> corrected, try
> >>>>> viewing the t-map without a threshold. . See if there looks like an
> >>>>> appropriate level of variability in the t-stats, or if it looks off
> (zero
> >>>>> at many data points, really speckled).
> >>>>>
> >>>>>
> >>>>>
> >>>>> This is a way to QC check the output and see if maybe something went
> >>>>> wrong which caused the stats to mess up.
> >>>>>
> >>>>>
> >>>>>
> >>>>> Good luck
> >>>>>
> >>>>>
> >>>>>
> >>>>> Colin Hawco, PhD
> >>>>>
> >>>>> Neuranalysis Consulting
> >>>>>
> >>>>> Neuroimaging analysis and consultation
> >>>>>
> >>>>>
> https://urldefense.proofpoint.com/v2/url?u=http-3A__www.neuranalysis.com&d=DQIFaQ&c=QmPtDiFixEjkMvDKaP3E2Vb9C2z4M0PdarxyAHQ2iDQ&r=xbyrBxm81l6mG_XEX66jgCNTXfK3eVo30T9sVQVTz1Q&m=Jc1PNVoYrsBQ4MCSXUR-BueqHdpSGdf2yPHWfNLLkVg&s=0ZyXhJLLLeGsN14Cl3JI-1_QU62MaC37ikInn-vP2yQ&e=
> >>>>>
> >>>>> [log in to unmask]
> >>>>>
> >>>>>
> >>>>>
> >>>>> ,
> >>>>>
> >>>>>
> >>>>>
> >>>>>
> >>>>>
> >>>>>
> >>>>>
> >>>>> *From:* FSL - FMRIB's Software Library [mailto:[log in to unmask]]
> *On
> >>>>> Behalf Of *Rosalia Dacosta Aguayo
> >>>>> *Sent:* May-19-16 4:35 AM
> >>>>> *To:* [log in to unmask]
> >>>>> *Subject:* [FSL] No results with VBM
> >>>>>
> >>>>>
> >>>>>
> >>>>> Dear FSL experts,
> >>>>>
> >>>>> I have been working with 46 MRI images in order to find some
> >>>>> correlations between on cognitive function and gray matter
> structures (deep
> >>>>> gray matter structures).
> >>>>>
> >>>>> Pre-processing steps were as follow:
> >>>>>
> >>>>> 1. Cutting long necks
> >>>>>
> >>>>> 2. Noise correction
> >>>>>
> >>>>> 3. Bias field correction
> >>>>>
> >>>>> 4. Skull-stripping (using CAT12, (Tool for SPM12) because with bet I
> >>>>> got that many images were not fine...as I had to decide wether
> improve this
> >>>>> step manually...(methodology is not as strong and homogeneous as one
> could
> >>>>> expect...or using another tool that gives good results..). With this
> Tool I
> >>>>> got excellent results for all the images...and I after doing an
> homogeneity
> >>>>> analysis, I discarded one of them...so n = 45
> >>>>>
> >>>>> 5. I used the skull stripped images in the first step of FSLVBM (that
> >>>>> is: after doing first step, I reemplaced the skull stripped images
> created
> >>>>> by the ones I got from CAT12).
> >>>>>
> >>>>> 6. Following fslvbm processes were fine, I visually inspect the GM
> >>>>> template as well as the 4D_GM template and it was very good. Images
> were
> >>>>> well aligned...
> >>>>>
> >>>>> The problem:
> >>>>>
> >>>>> I run correlation analysis between my template (with a gaussian
> kernel
> >>>>> of 3 sigma) and my cognitive variable of interest regressing out for
> TIV,
> >>>>> Age and Gender. It seems that my cog variable is not related to any
> >>>>> structure...what I think it is not possible and I was thinking about
> if I
> >>>>> missed something in the way or if my design.mat is not fine (I
> attach you
> >>>>> the design files...)....
> >>>>>
> >>>>> Thank you a lot for your helping,
> >>>>>
> >>>>> Kind regards,
> >>>>>
> >>>>> Rosalia
> >>>>>
> >>>>
> > ------------------------------
> >
> > Date: Sun, 22 May 2016 10:38:47 +0200
> > From: Rosalia Dacosta Aguayo <[log in to unmask]>
> > Subject: Re: No results with VBM
> >
> > Dear Anderson,
> >
> > Thank you for your reply.
> >
> > If I have understood you well, although my data has been demeaned, I have
> > to use -D flag in order to demean my design?
> >
> > Kind regards,
> >
> > Rosalia
> > El 22/05/2016 10:30, "Anderson M. Winkler" <[log in to unmask]>
> > escribió:
> >
> >> Hi Rosalia,
> >>
> >> Please see below:
> >>
> >> On 21 May 2016 at 19:30, Rosalia Dacosta Aguayo <[log in to unmask]>
> >> wrote:
> >>
> >>> Dear Anderson,
> >>>
> >>> The data has been demeaned, and I am working with just one group of 45
> >>> subjects, I am not sure about including an intercept in this model.
> Just
> >>> partial correlations between this group and a cog variable, regressing
> out
> >>> for age, gender and TIV....
> >>>
> >> It's necessary to demean both design and data, or else, include an
> >> intercept. Mean-centering the data only isn't sufficient.
> >>
> >>
> >>> And about my question regarding FIRST? I do not understand why I can
> get
> >>> .vtk and .bvars files for my 4. ROIS but when I give a look into
> firstseg
> >>> files and I check for registeting....I only find two of the deep gm
> >>> structures but not the 4 previosly selected.
> >>>
> >> This refers to a different thread. I'm not sure what is going on.
> >>
> >>
> >>> What is more, I am not quite sure about surface and vertex or shape
> >>> analysis and how to interpret results...
> >>>
> >> The shape analysis indicates the places where there is a significant
> shape
> >> difference (i.e., a significant effect on the positions of the vertices
> >> that delineate the structure).
> >>
> >> All the best,
> >>
> >> Anderson
> >>
> >>
> >>> I would greatly appreciate your helping hear.
> >>>
> >>> Kind regards,
> >>>
> >>> Rosalia
> >>> El 20/05/2016 11:44, "Rosalia Dacosta Aguayo" <[log in to unmask]>
> >>> escribió:
> >>>
> >>>> Thank you Anderson!!
> >>>>
> >>>> Rosalia
> >>>>
> >>>> 2016-05-20 10:07 GMT+02:00 Anderson M. Winkler <
> [log in to unmask]>:
> >>>>
> >>>>> Hi Rosalia,
> >>>>>
> >>>>> Just adding to this: need to include an intercept in the model, or
> use
> >>>>> the option -D.
> >>>>>
> >>>>> All the best,
> >>>>>
> >>>>> Anderson
> >>>>>
> >>>>>
> >>>>> On 19 May 2016 at 16:10, Colin Hawco <[log in to unmask]> wrote:
> >>>>>
> >>>>>> While I am afraid I can offer no specific advice for VBM in FSL, I
> do
> >>>>>> have a general piece of advice.
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>> When I see a null result I think is suspicious, I immediately drop
> >>>>>> threshold and take a look. As instead, instead of p < 0.05
> corrected, try
> >>>>>> viewing the t-map without a threshold. . See if there looks like an
> >>>>>> appropriate level of variability in the t-stats, or if it looks off
> (zero
> >>>>>> at many data points, really speckled).
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>> This is a way to QC check the output and see if maybe something went
> >>>>>> wrong which caused the stats to mess up.
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>> Good luck
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>> Colin Hawco, PhD
> >>>>>>
> >>>>>> Neuranalysis Consulting
> >>>>>>
> >>>>>> Neuroimaging analysis and consultation
> >>>>>>
> >>>>>>
> https://urldefense.proofpoint.com/v2/url?u=http-3A__www.neuranalysis.com&d=DQIFaQ&c=QmPtDiFixEjkMvDKaP3E2Vb9C2z4M0PdarxyAHQ2iDQ&r=xbyrBxm81l6mG_XEX66jgCNTXfK3eVo30T9sVQVTz1Q&m=Jc1PNVoYrsBQ4MCSXUR-BueqHdpSGdf2yPHWfNLLkVg&s=0ZyXhJLLLeGsN14Cl3JI-1_QU62MaC37ikInn-vP2yQ&e=
> >>>>>>
> >>>>>> [log in to unmask]
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>> ,
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>> *From:* FSL - FMRIB's Software Library [mailto:[log in to unmask]]
> *On
> >>>>>> Behalf Of *Rosalia Dacosta Aguayo
> >>>>>> *Sent:* May-19-16 4:35 AM
> >>>>>> *To:* [log in to unmask]
> >>>>>> *Subject:* [FSL] No results with VBM
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>> Dear FSL experts,
> >>>>>>
> >>>>>> I have been working with 46 MRI images in order to find some
> >>>>>> correlations between on cognitive function and gray matter
> structures (deep
> >>>>>> gray matter structures).
> >>>>>>
> >>>>>> Pre-processing steps were as follow:
> >>>>>>
> >>>>>> 1. Cutting long necks
> >>>>>>
> >>>>>> 2. Noise correction
> >>>>>>
> >>>>>> 3. Bias field correction
> >>>>>>
> >>>>>> 4. Skull-stripping (using CAT12, (Tool for SPM12) because with bet
> I
> >>>>>> got that many images were not fine...as I had to decide wether
> improve this
> >>>>>> step manually...(methodology is not as strong and homogeneous as
> one could
> >>>>>> expect...or using another tool that gives good results..). With
> this Tool I
> >>>>>> got excellent results for all the images...and I after doing an
> homogeneity
> >>>>>> analysis, I discarded one of them...so n = 45
> >>>>>>
> >>>>>> 5. I used the skull stripped images in the first step of FSLVBM
> (that
> >>>>>> is: after doing first step, I reemplaced the skull stripped images
> created
> >>>>>> by the ones I got from CAT12).
> >>>>>>
> >>>>>> 6. Following fslvbm processes were fine, I visually inspect the GM
> >>>>>> template as well as the 4D_GM template and it was very good. Images
> were
> >>>>>> well aligned...
> >>>>>>
> >>>>>> The problem:
> >>>>>>
> >>>>>> I run correlation analysis between my template (with a gaussian
> kernel
> >>>>>> of 3 sigma) and my cognitive variable of interest regressing out
> for TIV,
> >>>>>> Age and Gender. It seems that my cog variable is not related to any
> >>>>>> structure...what I think it is not possible and I was thinking
> about if I
> >>>>>> missed something in the way or if my design.mat is not fine (I
> attach you
> >>>>>> the design files...)....
> >>>>>>
> >>>>>> Thank you a lot for your helping,
> >>>>>>
> >>>>>> Kind regards,
> >>>>>>
> >>>>>> Rosalia
> >>>>>>
> >>>>>
> > ------------------------------
> >
> > Date: Sun, 22 May 2016 12:02:50 +0200
> > From: Francesca Zidda <[log in to unmask]>
> > Subject: Re: No results with VBM
> >
> > Look at this!!! They talk about correlations, one group and t-stats!!!!!
> >
> > The mistery is gettino shape ;)
> >
> > :****
> >
> > Frà
> >
> > Inviato da iPhone
> >
> >> Il giorno 19 mag 2016, alle ore 17:10, Colin Hawco <
> [log in to unmask]> ha scritto:
> >>
> >> While I am afraid I can offer no specific advice for VBM in FSL, I do
> have a general piece of advice.
> >>
> >> When I see a null result I think is suspicious, I immediately drop
> threshold and take a look. As instead, instead of p < 0.05 corrected, try
> viewing the t-map without a threshold. . See if there looks like an
> appropriate level of variability in the t-stats, or if it looks off (zero
> at many data points, really speckled).
> >>
> >> This is a way to QC check the output and see if maybe something went
> wrong which caused the stats to mess up.
> >>
> >> Good luck
> >>
> >> Colin Hawco, PhD
> >> Neuranalysis Consulting
> >> Neuroimaging analysis and consultation
> >>
> https://urldefense.proofpoint.com/v2/url?u=http-3A__www.neuranalysis.com&d=DQIFaQ&c=QmPtDiFixEjkMvDKaP3E2Vb9C2z4M0PdarxyAHQ2iDQ&r=xbyrBxm81l6mG_XEX66jgCNTXfK3eVo30T9sVQVTz1Q&m=Jc1PNVoYrsBQ4MCSXUR-BueqHdpSGdf2yPHWfNLLkVg&s=0ZyXhJLLLeGsN14Cl3JI-1_QU62MaC37ikInn-vP2yQ&e=
> >> [log in to unmask]
> >>
> >> ,
> >>
> >>
> >>
> >> From: FSL - FMRIB's Software Library [mailto:[log in to unmask]] On
> Behalf Of Rosalia Dacosta Aguayo
> >> Sent: May-19-16 4:35 AM
> >> To: [log in to unmask]
> >> Subject: [FSL] No results with VBM
> >>
> >> Dear FSL experts,
> >>
> >> I have been working with 46 MRI images in order to find some
> correlations between on cognitive function and gray matter structures (deep
> gray matter structures).
> >>
> >> Pre-processing steps were as follow:
> >>
> >> 1. Cutting long necks
> >> 2. Noise correction
> >> 3. Bias field correction
> >> 4. Skull-stripping (using CAT12, (Tool for SPM12) because with bet I
> got that many images were not fine...as I had to decide wether improve this
> step manually...(methodology is not as strong and homogeneous as one could
> expect...or using another tool that gives good results..). With this Tool I
> got excellent results for all the images...and I after doing an homogeneity
> analysis, I discarded one of them...so n = 45
> >> 5. I used the skull stripped images in the first step of FSLVBM (that
> is: after doing first step, I reemplaced the skull stripped images created
> by the ones I got from CAT12).
> >> 6. Following fslvbm processes were fine, I visually inspect the GM
> template as well as the 4D_GM template and it was very good. Images were
> well aligned...
> >>
> >> The problem:
> >>
> >> I run correlation analysis between my template (with a gaussian kernel
> of 3 sigma) and my cognitive variable of interest regressing out for TIV,
> Age and Gender. It seems that my cog variable is not related to any
> structure...what I think it is not possible and I was thinking about if I
> missed something in the way or if my design.mat is not fine (I attach you
> the design files...)....
> >>
> >> Thank you a lot for your helping,
> >>
> >> Kind regards,
> >>
> >> Rosalia
> > ------------------------------
> >
> > Date: Sun, 22 May 2016 07:56:30 -0400
> > From: Mahmoud <[log in to unmask]>
> > Subject: Re: zero filling
> >
> > Fslmaths -fillh
> > On May 22, 2016 1:43 AM, "Moran Artzi" <[log in to unmask]> wrote:
> >
> >> Hi,
> >> Is there any way to fill the holes in a binary image (as the brain_mask
> >> img - the output of bet) using FSL command line?
> >> Thanks
> >> Moran
> >>
> > ------------------------------
> >
> > Date: Sun, 22 May 2016 12:48:44 +0000
> > From: Saad Jbabdi <[log in to unmask]>
> > Subject: Re: BEDPOSTX on data with replicated b-vectors in one dataset
> >
> > Hi
> >
> > With such low number of directions there should not be a significant
> difference between averaging and stacking wrt model selection performance.
> I would worry *much* more about having such low #directions in the first
> place, as Matt said.
> >
> > The noise issue is also a non-issue in most cases (e.g. if bvalues are
> not too high) - in practice if you see that bedpostx overfits due to noise
> floor, you can try the —f0 option which adds a noise floor parameter to the
> model.
> >
> > Cheers,
> > Saad
> >
> >
> >
> >
> >
> > On 21 May 2016, at 21:54, Antonin Skoch <[log in to unmask]<mailto:
> [log in to unmask]>> wrote:
> >
> > Dear Matt, Michael,
> >
> > thank you for your contribution.
> >
> > Here is the relevant post from 3/2010 by Saad Jbabdi suggesting NOT to
> stack/concatenate the data for BEDPOSTX.
> >
> >
> https://urldefense.proofpoint.com/v2/url?u=https-3A__www.jiscmail.ac.uk_cgi-2Dbin_webadmin-3FA2-3Dind1003-26L-3DFSL-26D-3D0-261-3DFSL-269-3DA-26J-3Don-26K-3D2-26X-3DCBB60236BC562DF50E-26Y-3Dansk-2540ikem.cz-26d-3DNo-2BMatch-253BMatch-253BMatches-26z-3D4-26P-3D165079&d=DQIFaQ&c=QmPtDiFixEjkMvDKaP3E2Vb9C2z4M0PdarxyAHQ2iDQ&r=xbyrBxm81l6mG_XEX66jgCNTXfK3eVo30T9sVQVTz1Q&m=Jc1PNVoYrsBQ4MCSXUR-BueqHdpSGdf2yPHWfNLLkVg&s=xd8B6xO_DclrEoNOSsUYAkpJzyxrlYmIlZpfCGqp6ls&e=
> >
> > Conversely, averaging of the data effectively changes distribution from
> Rician to non-central chi as we discussed here:
> >
> >
> https://urldefense.proofpoint.com/v2/url?u=http-3A__community.mrtrix.org_t_anatomically-2Dconstrained-2Dtractography-2Dusing-2Dodf-2Dfrom-2Dbedpostx_189_6&d=DQIFaQ&c=QmPtDiFixEjkMvDKaP3E2Vb9C2z4M0PdarxyAHQ2iDQ&r=xbyrBxm81l6mG_XEX66jgCNTXfK3eVo30T9sVQVTz1Q&m=Jc1PNVoYrsBQ4MCSXUR-BueqHdpSGdf2yPHWfNLLkVg&s=3bQvyP3vRbeIrtwqktHhXJQSww693j0DoVyNIoHR0Oc&e=
> >
> > Would not this alteration of noise distribution have any spurious
> consequence on validity of Bayesian inference on diffusion orientations in
> BEDPOSTX?
> >
> > With recent protocols we acquire data with 64 unique directions, but we
> have quite large amount of data from previous studies acquired by 2x30
> directions ("half-sphere" diffusion encoding). I would like to learn what
> method of processing is optimal for these data.
> >
> > Regards,
> >
> > Antonin Skoch
> >
> > ------------------------------
> >
> > Date: Sun, 22 May 2016 12:54:47 +0000
> > From: Saad Jbabdi <[log in to unmask]>
> > Subject: Re: probabilistic tractography
> >
> > Hi Irina
> >
> >> Dear experts,
> >> I have a couple of questions regarding the results of probabilistic
> tractography:
> >> 1. Too low intencity values in the fdt_paths.
> >> After normalization of the paths (I divided the fdt_paths by (#voxels
> in the seed-mask * #permutations per voxel) and multiplied by 100 to get
> the resulting paths in %) I get the intencity values between 0.02 and 2%
> (when the paths are clearly seen). This is far too low, considering that
> the seed is practically within the corpus callosum. What are the usual
> values for the transcallosal paths?
> > Those numbers don’t surprise me given that streamlines can travel in 3D
> (and therefore, e.g. under isotropic conditions, probabilities will vanish
> with 1/r^2). If you normalise by waytotal the numbers will be higher
> because you will be excluding sample streamlines that do not contribute to
> the fdt_paths distribution (having been rejected by the inclusion/exclusion
> criteria)
> >
> >
> >> 2. FA vs. waytotal values between a seed and a target.
> >> I compared the waytotal values (to waypoint mask, normalized) between
> the 2 groups (15 subjects in each). I found that in the group of patients
> both the #paths between a seed and a target (normalized waytotal values)
> and the FA values within the same tract in the skeleton were significantly
> lower, which was expected. But for another tract I've got significantly
> lower FA values in patients and higher #paths between a seed and a target
> (and also higher intencity values in the resulting path). Is this possible
> at all and how to explain this paradox?
> > It’s not necessarily a paradox. The fdt_paths values depend on the
> uncertainty in fibre orientations, which relate to but are not the same as
> FA. For example, FA can drop considerably in regions of crossing fibres,
> but uncertainty in fitting the crossing orientation can still be low if you
> have sufficient sensitivity to crossings.
> >
> > Cheers,
> > Saad
> >
> >
> >> Thank you very much.
> > ------------------------------
> >
> > Date: Sun, 22 May 2016 16:25:48 +0300
> > From: Moran Artzi <[log in to unmask]>
> > Subject: Re: zero filling
> >
> > Thx!
> >
> > On Sun, May 22, 2016 at 2:56 PM, Mahmoud <[log in to unmask]> wrote:
> >
> >> Fslmaths -fillh
> >> On May 22, 2016 1:43 AM, "Moran Artzi" <[log in to unmask]> wrote:
> >>
> >>> Hi,
> >>> Is there any way to fill the holes in a binary image (as the brain_mask
> >>> img - the output of bet) using FSL command line?
> >>> Thanks
> >>> Moran
> >>>
> > ------------------------------
> >
> > Date: Sun, 22 May 2016 14:58:23 +0000
> > From: "Harms, Michael" <[log in to unmask]>
> > Subject: Re: BEDPOSTX on data with replicated b-vectors in one dataset
> >
> > Perhaps Saad can elaborate on that earlier (2010) post, and whether it is
> > still relevant.
> >
> > That’s the first I’ve heard that simply concatenating the data would be
> > sub-optimal in terms of bedpostx performance (other than the run-time
> > issue).
> >
> > cheers,
> > -MH
> >
> > --
> > Michael Harms, Ph.D.
> >
> > -----------------------------------------------------------
> > Conte Center for the Neuroscience of Mental Disorders
> > Washington University School of Medicine
> > Department of Psychiatry, Box 8134
> > 660 South Euclid Ave.Tel: 314-747-6173
> > St. Louis, MO 63110Email: [log in to unmask]
> >
> >
> >
> >
> > On 5/21/16, 3:54 PM, "FSL - FMRIB's Software Library on behalf of Antonin
> > Skoch" <[log in to unmask] on behalf of [log in to unmask]> wrote:
> >
> > Dear Matt, Michael,
> >
> > thank you for your contribution.
> >
> > Here is the relevant post from 3/2010 by Saad Jbabdi suggesting NOT to
> > stack/concatenate the data for BEDPOSTX.
> >
> >
> https://urldefense.proofpoint.com/v2/url?u=https-3A__www.jiscmail.ac.uk_cgi-2Dbin_webadmin-3FA2-3Dind1003-26L-3DFSL-26D-3D0-261-3DFSL-269-3DA-26&d=DQIFaQ&c=QmPtDiFixEjkMvDKaP3E2Vb9C2z4M0PdarxyAHQ2iDQ&r=xbyrBxm81l6mG_XEX66jgCNTXfK3eVo30T9sVQVTz1Q&m=Jc1PNVoYrsBQ4MCSXUR-BueqHdpSGdf2yPHWfNLLkVg&s=D8oku-jBRGd8I509CCSQqJcNpu_kzeB5-5VXYCQkjYA&e=
> > J=on&K=2&X=CBB60236BC562DF50E&Y=ansk%40ikem.cz
> &d=No+Match%3BMatch%3BMatches
> > &z=4&P=165079
> >
> > Conversely, averaging of the data effectively changes distribution from
> > Rician to non-central chi as we discussed here:
> >
> >
> https://urldefense.proofpoint.com/v2/url?u=http-3A__community.mrtrix.org_t_anatomically-2Dconstrained-2Dtractography-2Dusing-2Do&d=DQIFaQ&c=QmPtDiFixEjkMvDKaP3E2Vb9C2z4M0PdarxyAHQ2iDQ&r=xbyrBxm81l6mG_XEX66jgCNTXfK3eVo30T9sVQVTz1Q&m=Jc1PNVoYrsBQ4MCSXUR-BueqHdpSGdf2yPHWfNLLkVg&s=MlmUQ7zYGqxZaCYoCWEWchirBBXwZtz0hAc-g7CHpKA&e=
> > df-from-bedpostx/189/6
> >
> > Would not this alteration of noise distribution have any spurious
> > consequence on validity of Bayesian inference on diffusion orientations
> in
> > BEDPOSTX?
> >
> > With recent protocols we acquire data with 64 unique directions, but we
> > have quite large amount of data from previous studies acquired by 2x30
> > directions ("half-sphere" diffusion encoding). I would like to learn what
> > method of processing is optimal for these data.
> >
> > Regards,
> >
> > Antonin Skoch
> >
> >
> >
> > ________________________________
> > The materials in this message are private and may contain Protected
> Healthcare Information or other information of a sensitive nature. If you
> are not the intended recipient, be advised that any unauthorized use,
> disclosure, copying or the taking of any action in reliance on the contents
> of this information is strictly prohibited. If you have received this email
> in error, please immediately notify the sender via telephone or return mail.
> >
> > ------------------------------
> >
> > Date: Sun, 22 May 2016 16:19:17 +0000
> > From: Saad Jbabdi <[log in to unmask]>
> > Subject: Re: BEDPOSTX on data with replicated b-vectors in one dataset
> >
> > Hi Michael,
> >
> > I haven’t done any theory on that, my comment was based on both
> intuition and my own experience. The ARD prior competes with the data
> likelihood, which gets bigger when you have more data points.
> > Note that when the likelihood is Gaussian, it should not make a
> difference whether to stack or average: the effect of stacking (linear with
> n) is balanced by the effect of averaging (sigma^2 linear with n). But in
> bedpostx the sigma^2 is not estimated but integrated out.
> >
> > Cheers
> > Saad
> >
> >
> >
> >
> >
> > On 22 May 2016, at 15:58, Harms, Michael <[log in to unmask]<mailto:
> [log in to unmask]>> wrote:
> >
> > Perhaps Saad can elaborate on that earlier (2010) post, and whether it is
> > still relevant.
> >
> > That’s the first I’ve heard that simply concatenating the data would be
> > sub-optimal in terms of bedpostx performance (other than the run-time
> > issue).
> >
> > cheers,
> > -MH
> >
> > --
> > Michael Harms, Ph.D.
> >
> > -----------------------------------------------------------
> > Conte Center for the Neuroscience of Mental Disorders
> > Washington University School of Medicine
> > Department of Psychiatry, Box 8134
> > 660 South Euclid Ave.Tel: 314-747-6173
> > St. Louis, MO 63110Email: [log in to unmask]<mailto:[log in to unmask]>
> >
> >
> >
> >
> > On 5/21/16, 3:54 PM, "FSL - FMRIB's Software Library on behalf of Antonin
> > Skoch" <[log in to unmask]<mailto:[log in to unmask]> on behalf of
> [log in to unmask]<mailto:[log in to unmask]>> wrote:
> >
> > Dear Matt, Michael,
> >
> > thank you for your contribution.
> >
> > Here is the relevant post from 3/2010 by Saad Jbabdi suggesting NOT to
> > stack/concatenate the data for BEDPOSTX.
> >
> >
> https://urldefense.proofpoint.com/v2/url?u=https-3A__www.jiscmail.ac.uk_cgi-2Dbin_webadmin-3FA2-3Dind1003-26L-3DFSL-26D-3D0-261-3DFSL-269-3DA-26&d=DQIFaQ&c=QmPtDiFixEjkMvDKaP3E2Vb9C2z4M0PdarxyAHQ2iDQ&r=xbyrBxm81l6mG_XEX66jgCNTXfK3eVo30T9sVQVTz1Q&m=Jc1PNVoYrsBQ4MCSXUR-BueqHdpSGdf2yPHWfNLLkVg&s=D8oku-jBRGd8I509CCSQqJcNpu_kzeB5-5VXYCQkjYA&e=
> > J=on&K=2&X=CBB60236BC562DF50E&Y=ansk%40ikem.cz
> &d=No+Match%3BMatch%3BMatches
> > &z=4&P=165079
> >
> > Conversely, averaging of the data effectively changes distribution from
> > Rician to non-central chi as we discussed here:
> >
> >
> https://urldefense.proofpoint.com/v2/url?u=http-3A__community.mrtrix.org_t_anatomically-2Dconstrained-2Dtractography-2Dusing-2Do&d=DQIFaQ&c=QmPtDiFixEjkMvDKaP3E2Vb9C2z4M0PdarxyAHQ2iDQ&r=xbyrBxm81l6mG_XEX66jgCNTXfK3eVo30T9sVQVTz1Q&m=Jc1PNVoYrsBQ4MCSXUR-BueqHdpSGdf2yPHWfNLLkVg&s=MlmUQ7zYGqxZaCYoCWEWchirBBXwZtz0hAc-g7CHpKA&e=
> > df-from-bedpostx/189/6
> >
> > Would not this alteration of noise distribution have any spurious
> > consequence on validity of Bayesian inference on diffusion orientations
> in
> > BEDPOSTX?
> >
> > With recent protocols we acquire data with 64 unique directions, but we
> > have quite large amount of data from previous studies acquired by 2x30
> > directions ("half-sphere" diffusion encoding). I would like to learn what
> > method of processing is optimal for these data.
> >
> > Regards,
> >
> > Antonin Skoch
> >
> >
> >
> > ________________________________
> > The materials in this message are private and may contain Protected
> Healthcare Information or other information of a sensitive nature. If you
> are not the intended recipient, be advised that any unauthorized use,
> disclosure, copying or the taking of any action in reliance on the contents
> of this information is strictly prohibited. If you have received this email
> in error, please immediately notify the sender via telephone or return mail.
> >
> > ------------------------------
> >
> > End of FSL Digest - 21 May 2016 to 22 May 2016 (#2016-145)
> > **********************************************************
>
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