Dear Doug and FreeSurfer experts,
Thnak you so much for all your lasts responses!.
I did ran succesfully all the pre-processing for the interhemispheric comparisons on FS. Now I have a couple questions:
given the command for interhemispheric comparisons:
mri_glmfit --y lh.lh-rh.thickness.sm05.mgh --glmdir glm.lh.lh-rh.thickness.sm05 --osgm --surf fsaverage_sym lh;
A) This read all subjects to construct X and C as one-sample group mean, this means that as result I get the difference across hemispheres and across my subjects in a population, right?
B) But, what if I have two groups? controls and patients, I'm wondering if is it possible to examine regional differences of thickness asymmetries between those two groups? or more?
C) If I want to examine effects of group or sex, while controlling for age and other factors how do I introduce them into the glm model? If so, do I set the contrasts as normally for mri_glmfit? I mean as any other thickness study? or there is any other thing that I should do?
The command for multiple comparisons correction is:
mri_glmfit-sim --glmdir glm.lh.lh-rh.thickness.sm05 --cwpvalthresh .5 --cache 2 abs
Which performs only cluster-wise corrections,
D) is there any other way to correct for multiple comparisons, something like permutation tests or anything else?
Many thanks in advanced,
Gabriel
Thnak you so much for all your lasts responses!.
I did ran succesfully all the pre-processing for the interhemispheric comparisons on FS. Now I have a couple questions:
given the command for interhemispheric comparisons:
mri_glmfit --y lh.lh-rh.thickness.sm05.mgh --glmdir glm.lh.lh-rh.thickness.sm05 --osgm --surf fsaverage_sym lh;
A) This read all subjects to construct X and C as one-sample group mean, this means that as result I get the difference across hemispheres and across my subjects in a population, right?
B) But, what if I have two groups? controls and patients, I'm wondering if is it possible to examine regional differences of thickness asymmetries between those two groups? or more?
C) If I want to examine effects of group or sex, while controlling for age and other factors how do I introduce them into the glm model? If so, do I set the contrasts as normally for mri_glmfit? I mean as any other thickness study? or there is any other thing that I should do?
The command for multiple comparisons correction is:
mri_glmfit-sim --glmdir glm.lh.lh-rh.thickness.sm05 --cwpvalthresh .5 --cache 2 abs
Which performs only cluster-wise corrections,
D) is there any other way to correct for multiple comparisons, something like permutation tests or anything else?
Many thanks in advanced,
Gabriel
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