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Subject:

Re: beta files

From:

Guillaume Flandin <[log in to unmask]>

Reply-To:

Guillaume Flandin <[log in to unmask]>

Date:

Tue, 11 Apr 2017 17:16:41 +0100

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (415 lines)

Hi Alina,

I was not suggesting to compute this ratio for all of your images but
only for the beta images from the GLM, ie a single call to ImCalc:
  spm_imcalc({'beta_0001.nii','beta_0002.nii'},'psc.nii','i1./i2');

Best regards,
Guillaume.


On 11/04/17 14:39, Alina D wrote:
> Hello,
> 
> Thank you very much! I did try adjusting the threshold and the constant
> predictor is not looking weird anymore when I set it to 0.9.
> Nevertheless the beta values that I am getting are still quite high. I
> would like to also try your initial suggestion of dividing the images by
> the mean image (if I understood it correctly)/ I computed the mean image
> with ImCalc but now I run into (I think rather easy but I don't know how
> to do it) problem. Is it possible to divide each of all my 60 images by
> the mean image using ImCalc?
> 
> Best wishes,
> Alina
> 
> On Mon, Apr 10, 2017 at 6:12 PM, Guillaume Flandin <[log in to unmask]
> <mailto:[log in to unmask]>> wrote:
> 
>     Dear Alina,
> 
>     There indeed seems to be a lot of variability in intensity over space in
>     your images so you might want to reduce the value of the masking
>     threshold (defaults.mask.thresh in spm_defaults.m, see an earlier
>     message today for further details) before model specification.
>     You sent me the SPM.mat from the model with iid assumptions (serial
>     correlation: none) so I couldn't check the temporal covariance
>     structure.
>     If you want to get local estimates of the percent signal change, you can
>     compute the ratio beta_1/beta_2 (use ImCalc with images beta_0001.nii
>     and beta_0002.nii and expression 'i1./i2'), see this for details:
>      
>     http://journal.frontiersin.org/article/10.3389/fnins.2014.00001/full#h6
>     <http://journal.frontiersin.org/article/10.3389/fnins.2014.00001/full#h6>
> 
>     Best regards,
>     Guillaume.
> 
> 
>     On 05/04/17 16:30, Alina D wrote:
>     > Hello,
>     > I ve been trying mucltiple times to send the files to you but the
>     > mailling lists rejects it. I hope this works.
>     >
>     > Thank you,
>     > Alina
>     >
>     > On Tue, Apr 4, 2017 at 6:14 PM, Guillaume Flandin <[log in to unmask] <mailto:[log in to unmask]>
>     > <mailto:[log in to unmask] <mailto:[log in to unmask]>>> wrote:
>     >
>     >     Dear Alina,
>     >
>     >     The change in the design matrix between before and after
>     estimation is
>     >     due to non-sphericity whitening (adjusting for serial
>     correlations). In
>     >     your case, it seems it went wrong - to understand better what
>     is going
>     >     on, could you rerun your entire analysis while setting the "serial
>     >     correlations" option in fMRI model specification to "none"?
>     >     Also, what does your difference images look like? Before
>     entering the
>     >     GLM, the data are rescaled according the estimated global
>     signal, and
>     >     this estimation is based on a crude intensity thresholding
>     approach to
>     >     define the brain mask. What does the mask.nii image look like?
>     >
>     >     Best regards,
>     >     Guillaume.
>     >
>     >
>     >
>     >     On 04/04/17 16:18, Alina D wrote:
>     >     > Hello,
>     >     >
>     >     > These are actually arterial spin labelling difference
>     images, so the
>     >     > only processing was smoothing them by 6mm. Then I specified
>     everything
>     >     > by clicking on the specify first level command. What I
>     noticed is that
>     >     > after I am doing this step, indeed the " clean" design
>     matrix (that I
>     >     > just send before) comes up. Nevertheless, after model
>     estimation and in
>     >     > the results file the design matrix looks again like the
>     initial one,
>     >     > with the odd looking constant term. Could this be the source
>     of error?
>     >     > And if yes, why is this happening?
>     >     >
>     >     > Best wishes,
>     >     > Alina
>     >     >
>     >     > On Apr 4, 2017 5:04 PM, "Guillaume Flandin"
>     <[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>
>     >     > <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>> wrote:
>     >     >
>     >     >     Dear Alina,
>     >     >
>     >     >     Your design matrix looks better this time: it contains two regressors
>     >     >     (task and constant) so you have two regression coefficients beta_1 and
>     >     >     beta_2. You are right to find the values rather large.
>     >     >     Where are the data coming from? How did you preprocess them? Did you use
>     >     >     SPM's batch interface to specify and estimate this first level GLM?
>     >     >
>     >     >     Best regards,
>     >     >     Guillaume.
>     >     >
>     >     >
>     >     >     On 04/04/17 12:54, Alina D wrote:
>     >     >     > I apologize, I selected the wrong file accidentally.
>     >     >     > These are the betas. Could you please tell me what is the first
>     >     >     one and
>     >     >     > what is the second one?
>     >     >     > beta =
>     >     >     >
>     >     >     >   134.8669
>     >     >     >   196.3979
>     >     >     >
>     >     >     > And this is the correct design matrix :
>     >     >     >
>     >     >     > Inline image 2
>     >     >     >
>     >     >     > Best wishes,
>     >     >     >
>     >     >     > Alina
>     >     >     >
>     >     >     > On Mon, Apr 3, 2017 at 5:45 PM, Guillaume Flandin
>     >     >     <[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>
>     >     >     > <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>>> wrote:
>     >     >     >
>     >     >     >     Dear Alina,
>     >     >     >
>     >     >     >     Your second regressor, the constant term, looks odd. How did
>     >     >     you specify
>     >     >     >     your GLM?
>     >     >     >
>     >     >     >     Best regards,
>     >     >     >     Guillaume.
>     >     >     >
>     >     >     >     On 03/04/17 16:38, Alina D wrote:
>     >     >     >     > Hello,
>     >     >     >     >
>     >     >     >     > Thank you again. This is how the design matrix looks like. I
>     >     >     only have
>     >     >     >     > one stimulation condition.
>     >     >     >     > Best wishes,
>     >     >     >     > Alina
>     >     >     >     > Inline image 2
>     >     >     >     >
>     >     >     >     > On Mon, Apr 3, 2017 at 5:29 PM, Guillaume Flandin
>     >     >     <[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>
>     >     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>>
>     >     >     >     > <mailto:[log in to unmask]
>     <mailto:[log in to unmask]>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>
>     >     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>>>> wrote:
>     >     >     >     >
>     >     >     >     >     Dear Alina,
>     >     >     >     >
>     >     >     >     >
>     >     >     >     >     OK, you probably read the data correctly. Could
>     >     you show us
>     >     >     >     what your
>     >     >     >     >     design matrix look like? To explore a bit
>     further,
>     >     you can
>     >     >     >     also use the
>     >     >     >     >     "plot" button with the "contrast estimates" and
>     >     "fitted
>     >     >     responses"
>     >     >     >     >     options.
>     >     >     >     >
>     >     >     >     >     Best regards,
>     >     >     >     >     Guillaume.
>     >     >     >     >
>     >     >     >     >
>     >     >     >     >     On 03/04/17 16:20, Alina D wrote:
>     >     >     >     >     > Hello,
>     >     >     >     >     >
>     >     >     >     >     > Thank you very much for replying. I did
>     Extract
>     >     data >
>     >     >     betas
>     >     >     >     > this
>     >     >     >     >     > voxel and the only thing that happens is
>     that matlab
>     >     >     returns
>     >     >     >     this :
>     >     >     >     >     >
>     >     >     >     >     > beta =
>     >     >     >     >     >
>     >     >     >     >     >    87.2718
>     >     >     >     >     >   265.9859
>     >     >     >     >     >
>     >     >     >     >     > Before I tried to load the beta_0001.nii
>     file and to
>     >     >     get the
>     >     >     >     intensitied
>     >     >     >     >     > of some voxels from there.
>     >     >     >     >     >
>     >     >     >     >     > Qse = 'beta_0001.nii';
>     >     >     >     >     > Wse = spm_vol(Qse);
>     >     >     >     >     > Bse = spm_read_vols(Wse);
>     >     >     >     >     >
>     >     >     >     >     > I stored the coordinates of the voxels in a
>     >     matrix of
>     >     >     the form:
>     >     >     >     >     > myindex3d = zeros(length(myindex),3)
>     >     >     >     >     >
>     >     >     >     >     > And then looped through the total number and
>     >     ploted it :
>     >     >     >     >     > scatter_data(ii) =
>     >     >     >     Bse(myindex3d(ii,1),myindex3d(ii,2),myindex3d(ii,3))
>     >     >     >     >     >
>     >     >     >     >     > What would you suggest?
>     >     >     >     >     >
>     >     >     >     >     > Best wishes,
>     >     >     >     >     > Alina
>     >     >     >     >     >
>     >     >     >     >     > On Mon, Apr 3, 2017 at 5:05 PM, Guillaume
>     Flandin
>     >     >     >     <[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>
>     >     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>>
>     >     >     >     <mailto:[log in to unmask]
>     <mailto:[log in to unmask]> <mailto:[log in to unmask]
>     <mailto:[log in to unmask]>>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>
>     >     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>>>
>     >     >     >     >     > <mailto:[log in to unmask]
>     <mailto:[log in to unmask]>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>>
>     >     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>
>     >     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>>
>     >     >     >     <mailto:[log in to unmask]
>     <mailto:[log in to unmask]> <mailto:[log in to unmask]
>     <mailto:[log in to unmask]>>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>
>     >     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>
>     >     <mailto:[log in to unmask] <mailto:[log in to unmask]>
>     <mailto:[log in to unmask] <mailto:[log in to unmask]>>>>>>> wrote:
>     >     >     >     >     >
>     >     >     >     >     >     Dear Alina,
>     >     >     >     >     >
>     >     >     >     >     >     How did you extract the data for a
>     given voxel?
>     >     >     What is
>     >     >     >     >     displayed if,
>     >     >     >     >     >     when looking at results, you move the
>     'current
>     >     >     voxel' (red
>     >     >     >     >     arrow) to
>     >     >     >     >     >     your voxel of interest and do a right
>     click
>     >     while
>     >     >     on the
>     >     >     >     glass
>     >     >     >     >     brain and
>     >     >     >     >     >     select Extract data > betas > this
>     voxel in the
>     >     >     contextual
>     >     >     >     >     menu that
>     >     >     >     >     >     opens?
>     >     >     >     >     >
>     >     >     >     >     >     Best regards,
>     >     >     >     >     >     Guillaume.
>     >     >     >     >     >
>     >     >     >     >     >
>     >     >     >     >     >     On 03/04/17 12:51, Alina Dinu wrote:
>     >     >     >     >     >     > Dear all,
>     >     >     >     >     >     >
>     >     >     >     >     >     > I am interested in the beta values
>     for certain
>     >     >     activated
>     >     >     >     >     voxels.I
>     >     >     >     >     >     extracted them from the beta_0001
>     file. I have a
>     >     >     couple of
>     >     >     >     >     questions:
>     >     >     >     >     >     > 1. Could someone please tell me if
>     this is
>     >     this the
>     >     >     >     correct
>     >     >     >     >     file?
>     >     >     >     >     >     (given that I have a block design with
>     only one
>     >     >     condition)
>     >     >     >     >     >     > 2. After I plot them I notice that
>     the values
>     >     >     are too high
>     >     >     >     >     (in the
>     >     >     >     >     >     order of 80-100) which is nonsensical
>     for beta
>     >     >     values. Could
>     >     >     >     >     someone
>     >     >     >     >     >     please tell me if there is any kind of
>     scalling
>     >     >     done in
>     >     >     >     this file?
>     >     >     >     >     >     How are these values coded?
>     >     >     >     >     >     > 3. Could someone please tell me if this
>     >     file also
>     >     >     >     includes the
>     >     >     >     >     >     confound mean predictor?
>     >     >     >     >     >     >
>     >     >     >     >     >     > Kind regards,
>     >     >     >     >     >     > Alina
>     >     >     >     >     >     >
>     >     >     >     >     >
>     >     >     >     >     >     --
>     >     >     >     >     >     Guillaume Flandin, PhD
>     >     >     >     >     >     Wellcome Trust Centre for Neuroimaging
>     >     >     >     >     >     University College London
>     >     >     >     >     >     12 Queen Square
>     >     >     >     >     >     London WC1N 3BG
>     >     >     >     >     >
>     >     >     >     >     >
>     >     >     >     >
>     >     >     >     >     --
>     >     >     >     >     Guillaume Flandin, PhD
>     >     >     >     >     Wellcome Trust Centre for Neuroimaging
>     >     >     >     >     University College London
>     >     >     >     >     12 Queen Square
>     >     >     >     >     London WC1N 3BG
>     >     >     >     >
>     >     >     >     >
>     >     >     >
>     >     >     >     --
>     >     >     >     Guillaume Flandin, PhD
>     >     >     >     Wellcome Trust Centre for Neuroimaging
>     >     >     >     University College London
>     >     >     >     12 Queen Square
>     >     >     >     London WC1N 3BG
>     >     >     >
>     >     >     >
>     >     >
>     >     >     --
>     >     >     Guillaume Flandin, PhD
>     >     >     Wellcome Trust Centre for Neuroimaging
>     >     >     University College London
>     >     >     12 Queen Square
>     >     >     London WC1N 3BG
>     >     >
>     >
>     >     --
>     >     Guillaume Flandin, PhD
>     >     Wellcome Trust Centre for Neuroimaging
>     >     University College London
>     >     12 Queen Square
>     >     London WC1N 3BG
>     >
>     >
> 
>     --
>     Guillaume Flandin, PhD
>     Wellcome Trust Centre for Neuroimaging
>     University College London
>     12 Queen Square
>     London WC1N 3BG
> 
> 

-- 
Guillaume Flandin, PhD
Wellcome Trust Centre for Neuroimaging
University College London
12 Queen Square
London WC1N 3BG

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