Hi, I’ve been looking at
thickness data and Freesurfer,
and had a question about the process. I initially compared thickness in
our two
groups on a node-by-node basis using:
mris_preproc --fsgd_file
file_name --target average --hemi
rh --meas thickness --out rh.thickness.mgh
mri_surf2surf --hemi rh
--s average --sval rh.thickness.mgh
--fwhm 10 --tval rh.thick_smooth.mgh
mri_glmfit --y
rh.thick_smooth.mgh --fsgd file_name doss
--glmdir average/glm/rh --surf average rh --C contrast.m
with the fsgd file
containing inputs like:
Input name1 NC-male 31.34
etc.
(the number at the end
being age)
I also tried running GLM
on the average label thicknesses in
the parcellation stat files to see how similar the results would be. I
did this
by reading the values in the ThickAvg column into SPSS, and using group
and
gender as fixed factors with age as a covariate. Doing it this way,
several
labels came up significant that contained few or no significant nodes
doing it
the other way.
Since this was
surprising, I was wondering if there was
anything that might be expected to cause this difference. For example,
could
there somehow be a scaling factor applied to one analysis but not the
other?
Thanks,
-Aaron-