Hi SPM experts,
I am also doing longitudinal VBM analysis in SPM 12. Based on your suggestion (searched from the mailing list), the following steps were included:
1) Pairwise registration (order: 1st: initial scan / 2nd follow-up scan)
2) Segment the avg
3) Compute c1.(from step 2) *jd (from step1)
4) Dartel the rc1 & rc2 from step 2
5) Apply MNI normalization from 4 to c1.*jd from step 3
Is the analysis right?
For the grey matter volume of each time point, re-run the longitudinal registration with ‘serial’ option to generate the Jacobian maps at the two time points, and calculate grey matter volume for each time point: c1avg*jd1/ c1avg*jd2. Then, apply MNI normalization based on average template (template_6.nii, from step 4) to c1avg*jd1/ c1avg*jd2. Is this correct?
Considering children data (two time points with one year interval) in my analysis, I used children's tissue probability maps to implement segmentation. Since only three children's TPMs (GM, WM, CSF) available, I tried to run New segment with these TPMs, but it did not work, reporting errors as follows.
Error using schur
Input to SCHUR must not contain NaN or Inf.
In file "C:\Program Files\MATLAB\R2012b\toolbox\matlab\matfun\sqrtm.m" (???), function "sqrtm" at line 33.
In file "E:\spm12\toolbox\OldSeg\spm_maff.m" (v4873), function "M2P" at line 162.
In file "E:\spm12\toolbox\OldSeg\spm_maff.m" (v4873), function "affreg" at line 78.
In file "E:\spm12\toolbox\OldSeg\spm_maff.m" (v4873), function "spm_maff" at line 27.
In file "E:\spm12\spm_preproc.m" (v4916), function "spm_preproc" at line 155.
In file "E:\spm12\toolbox\OldSeg\spm_run_preproc.m" (v4873), function "spm_run_preproc" at line 20.
However, New segment worked when using three TPMs in spm12. Do you have some ideas about that?
Since New segment did not work with three children's TPMs, I used Old segment for segmentation. After the preprocessing (above mentioned 1-5 steps), I did one-sample t-test to check the grey matter volume changes. The T-map showed significant results in many regions after FWE correction. It was weird to me, because the intra-subject difference is actually small (Jacobian difference). Is it normal or is there something wrong? Could you please give me some suggestion?
Thank you very much.
----- Original Message -----
From: "John Ashburner" <[log in to unmask]>
To: "SPM" <[log in to unmask]>
Sent: Thursday, July 28, 2016 6:32:16 PM
Subject: Re: [SPM] longitudinal VBM analysis in SPM12
If you want to do a purely longitudinal analysis, then you'll need two (or
more) scans per subject. You'd need to leave out those subjects with only
a single scan.
The Longitudinal toolbox can be used (pairwise option) for aligning pairs
of T1w scans taken at different time points. The on-line help in the batch
system may be useful for you here, so I'd suggest reading it. You'll need
to generate a mid-point average, and a Jacobian difference image for each
What you do with the maps of volume change will depend on your hypothesis
about what sorts of differences you expect. If you want to look at any sort
of volume changes, then you'd need to spatially normalise the Jacobian
difference maps of each subject and do a statistical analysis of these.
Other sorts of volume change can be derived through segmenting the
mid-point average image. If you want to look at GM volume changes, etc,
then you could multiply the GM map by the Jacobians (via ImCalc), and
spatially normalise (and smooth) the results for each subject.
On 28 July 2016 at 17:10, Lara Foland-Ross <[log in to unmask]> wrote:
> Hello SPM experts,
> I would like to run a longitudinal VBM analysis in SPM 12 to model
> structural change between two timpoints, covarying for age, IQ and total
> brain volume. Some participants do not have both scans however.
> Can you please tell me whether such an analysis is possible in SPM12 (and
> if so, what statistical tool to use)?
> Many thanks in advance,