Sorry, not sure what you are trying to do. From your equation it looks
like you are not doing a voxel-wise analysis but instead using maps to
try to predict cognition? If so, this is a multivariate analysis whereas
mri_glmfit does voxel-wise analysis. We don't really have any tools to
do multivariate analysis.
On 3/3/2020 7:05 PM, Adam Martersteck wrote:
External Email - Use Caution
Hi FreeSurfer team,
I have a question about running mri_glmfit with 2 different surface
modalities as the independent variable and a single value per
participant as the dependent variable. I'm trying to examine the
unique and shared contribution of the 2 surfaces to predict a
cognitive measure.
E.g. Cognition ~ ?h.thickness + ?h.PET
I tried mri_glmfit with the "--table" option, giving it a column of
scores per participant (in the aseg2stats table format), and then
using "--pvr lh.thickness-stack.fsaverage.mgh" and a second "--pvr
lh.PET-stack.fsaverage.mgh", using contrasts matrices as [0 0 1], [0 1
0], and [0 1 1].
_When I run mri_glmfit it returns:_
ERROR: mri_reshape: number of elements cannot change
nv1 = 163842, nv1 = 1
It continues to run, but all surface maps are full of zeroes. Any
suggestions? Is there a better way to do this?
Thanks,
Adam
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