Dear FS experts, I ran cortical thickness analysis as previously explained in Wiki :
Wiki https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/GroupAnalysis
My data is previously cached so I ran the command : mris_preproc --fsgd gender_age.fsgd --cache-in thickness.fwhm10.fsaverage --target fsaverage --hemi lh --out lh.gender_age.thickness.10.mgh GLM analysis: mri_glmfit --y lh.gender_age.thickness.10.mgh --fsgd gender_age.fsgd dods --C lh-Avg-thickness-age-Cor.mtx --surf fsaverage lh --cortex --glmdir lh.gender_age.glmdir Correction for multiple comparison mri_glmfit-sim --glmdir lh.gender_age.glmdir --cache 4 neg --cwp 0.05 --2spaces
In order to do cluster-wise correction for multiple comparisons, I ran the command "mri_glmfit-sim" (step3). This command is calling, internally, the command "mri_surfcluster" as follow:
mdline mri_surfcluster --in lh//2G0C/sig.mgh --csd /usr/local/freesurfer/stable5_3_0/average/mult-comp-cor/fsaverage/lh/cortex/fwhm15/pos/th13/mc-z.csd --mask lh//mask.mgh --cwsig lh//2G0C/cache.th13.pos.sig.cluster.mgh --vwsig lh//2G0C/cache.th13.pos.sig.voxel.mgh --sum lh//2G0C/cache.th13.pos.sig.cluster.summary --ocn lh//2G0C/cache.th13.pos.sig.ocn.mgh --oannot lh//2G0C/cache.th13.pos.sig.ocn.annot --annot aparc --csdpdf lh//2G0C/cache.th13.pos.pdf.dat --cwpvalthresh 0.05 --o lh//2G0C/cache.th13.pos.sig.masked.mgh --no-fixmni --bonferroni 2 --surf white
Kindly, I have the following questions:
1. How the command mri_surfcluster choose the fwhm=?? for the flag "csd" . In the previous command it shows fwhm=15. Is this depends on how much I am smoothing in the previous steps?
2. What is purpose of using the flag Bonferroni in the previous command
3. If we are doing cluster wise correction, what is theexact usage of the flag "--vwsig" ?
Thanks for your patience ! Looking forward to learn from you
Mohamad
answers below
On 03/22/2016 11:03 AM, Alshikho, Mohamad J. wrote:
Dear FS experts,
I ran cortical thickness analysis as previously explained in Wiki :
Wiki https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/GroupAnalysis
My data is previously cached so I ran the command : mris_preproc --fsgd gender_age.fsgd --cache-in thickness.fwhm10.fsaverage --target fsaverage --hemi lh --out lh.gender_age.thickness.10.mgh
GLM analysis: mri_glmfit --y lh.gender_age.thickness.10.mgh --fsgd gender_age.fsgd dods --C lh-Avg-thickness-age-Cor.mtx --surf fsaverage lh --cortex --glmdir lh.gender_age.glmdir
Correction for multiple comparison mri_glmfit-sim --glmdir lh.gender_age.glmdir --cache 4 neg --cwp 0.05 --2spaces
In order to do cluster-wise correction for multiple comparisons, I ran the command “mri_glmfit-sim” (step3). This command is calling, internally, the command “mri_surfcluster” as follow:
mdline mri_surfcluster --in lh//2G0C/sig.mgh --csd /usr/local/freesurfer/stable5_3_0/average/mult-comp-cor/fsaverage/lh/cortex/fwhm15/pos/th13/mc-z.csd --mask lh//mask.mgh --cwsig lh//2G0C/cache.th13.pos.sig.cluster.mgh --vwsig lh//2G0C/cache.th13.pos.sig.voxel.mgh --sum lh//2G0C/cache.th13.pos.sig.cluster.summary --ocn lh//2G0C/cache.th13.pos.sig.ocn.mgh --oannot lh//2G0C/cache.th13.pos.sig.ocn.annot --annot aparc --csdpdf lh//2G0C/cache.th13.pos.pdf.dat --cwpvalthresh 0.05 --o lh//2G0C/cache.th13.pos.sig.masked.mgh --no-fixmni --bonferroni 2 --surf white
Kindly, I have the following questions:
1.How the command mri_surfcluster choose the fwhm=?? for the flag “csd” . In the previous command it shows fwhm=15. Is this depends on how much I am smoothing in the previous steps?
mri_glmfit measures the actual FWHM from the residuals of the data. This maybe (probably will be) larger than the amount that you applied because there is some inherent smoothness to the data as well as spatially coherent errors in the glm fit that show up as spatial correlations in the residual.
2.What is purpose of using the flag Bonferroni in the previous command
It corrects for the two spaces (lh and rh)
3.If we are doing cluster wise correction, what is theexact usage of the flag “--vwsig” ?
mri_surfcluster actually does clusterwise and voxel-wise (--vwsig) correction. the voxel-wise tends to be pretty harsh, so most people use cluster-wise
Thanks for your patience !
Looking forward to learn from you
Mohamad
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