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When you specify the initial scan as the first, and the final scan as the second, then negative Jacobian differences from the Longitudinal toolbox indicate apparent volume loss.  When you multiply these by the grey matter images, the this should indicate volume loss in GM.

I'm not sure exactly how or what extracting ind. Values is, although I'd guess it is the data from the plot function of SPM, which orthogonalises the raw value with the uninteresting confounds from the design matrix.  I'd therefore guess that the more negative values in those who started the drug would indicate that there is more volume loss.

Because the pairwise version of the Longitudinal toolbox only gives the Jacobian difference rather than the Jacobians at each time point, you'd need to re-run the longitudinal registration with the "serial" option to generate the Jacobian maps at the two time points.  You could then multiply these by the c1 image for that subject to obtain the GM at each time point.  Alternatively, you could just segment the original images.

Best regards,
-John




On 17 November 2014 00:10, Ben Becker <[log in to unmask]> wrote:
Dear SPMers,

I ran a vbm-longitudinal analysis using the new longitudinal vbm approach in spm12 & would like to validate my analysis & results.
In the study we want to examine brain-structural effects of drug-use in a longitudinal design. Therefore healthy subjects at risk were scanned twice with an interval of 12 months. At the initial assessment subjects were drug-naïve, during the follow-up some started use. Effects of the drug on brain structure was assessed comparing users who remained naïve with those who started use (we expected subjects not to differ on the initial assessment, however they might differ on the second assessment).

Analysis:
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

Assessment of effects: 2-sample t-test on images from 5 (c1*jd in MNI) to assess differential changes between the groups. The analysis reveals one significant cluster – extracting ind. Values from the cluster shows positive mean values in the non-users and negative values in those who started the drug. Could this be interpreted as a relative decrease (or lack of increase) in those who started drug use?

In addition is there a way to generate the corresponding GM volume maps for both assessments? This will be useful to explore if there were differences between the groups at the initial assessment.

Thanks in advance & best regards,

Ben