Dear all,
I have some questions regarding longitudinal VBM procedures in SPM12.
I have longitudinal brain structure data with two-time points each. I would
like to explore whether changes in grey matter between the two-time points
are associated with cognitive training.
I have followed the longitudinal registration steps outlined in the SPM12
Manual for pairwise longitudinal registration: entering time 1 and time 2
volumes, a vector of time difference values in weeks, leaving the defaults
for noise estimates, warping regularisation, bias regularisation, and
saving mid-point average,Jacobian differences, divergence rates, and
deformation fields.
Based on the discussions on the SPM mail list, my longitudinal VBM plan is
as follows:
1) Segment the avg_*.nii images (from the pairwise longitudinal registration
2) Run Dartel on the rc1 and rc2 images (from segmenting the average images
3) Normalise (through SPM -> Tools -> Dartel tools -> Normalise to MNI
space)
a. Use the 6th (last) iteration template produced by the Dartel step
(Template_6.nii)
b. Choose “many subjects”
1. In “Flow Fields” use the u_rc1 images
(from Dartel on average image segmentation)
2. In “Images” use c1.*jd images (computed
using ImCalc)
* I have the following questions:*
*I have problems with ImCalc. I am not sure on how to actually calculate
the c1.*jd images using that toolbox.*
a) Are the “Input Images” the c1 images (from segmenting the average
image)?
b) How are the Jacobian determinants included – are they entered as an
“Additional Variable” (and if so, what values do I enter)?
*c) And is the computation c1.*jd entered as the “Expression”?*
All your suggestions will be very appreciated!
Natalia
