The only difference between the mask and the label is the format of the input. The mask can take any "volume" format (mgh, nii, etc) and expects there to be a value at each veretx, and that value is a 0 or 1. The label is a text list of vertices to include (like lh.cortex.label). If your ROIs are part of the automatic cortical parcellation, then you can run mris_annotation2label to break the parc into labels, then use mri_merge_labels to merge your labels into one label, then pass that to mri_glmfit. To correct for muliptle comparisons, you will need to run the monte carlo simulation. You can do this with mri_glmfit-sim (NOT using the --cache option) or you can run mri_mcsim to cache your own tables. This second option may be better if you have more-or-less fixed your ROI and will need to correct for many different analyses (perhaps at different smoothing levels). doug

On 7/23/12 8:03 PM, Jeni Chen wrote:

Hello Freesurfer experts,

I've been trying to figure out a way to run a directed search in a group analysis. I read the tutorial on ROI analysis and some of the posts here, but we can only do it with individual subject. Simply pout, I want to restrict my search areas to 4 ROIs (determined from the fsaverage or common template) when I run the group analysis (thus lowering the corrected stats threshold based on search criteria). What's the best way of doing it? Also, some posts suggests using the --mask option when running the glmfit command, but it seems some people also used the --label option. What is the difference?

Thank you for your help.

Jeni _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer