It looks like you are trying to do a surface-based analysis using a mask derived from the volume-based fmri analysis. Is that right? And the fMRI is on the mni152? If so, then you will need to get your mask onto the surface of fsaverage. The easiest way to do that is to run recon-all on the mni152 volume, then run mri_vol2surf using your stat mask as the --mov, --regheader (since they are both in mni152), --projfrac-max 0 1 .1 to make sure to pick up all the voxels in the mask, and --trgsubject fsaverage. You can view this as an overlay in freeview with tksurferfv fsaverage lh inflated -ov <mri_vol2surf_output.mgz>. You can then threshold it with mri_binarize --i <mri_vol2surf_output.mgz> --min YourThresh --o mask.mgz

On 4/11/2019 5:20 PM, Jennifer Legault wrote:

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Hi Freesurfer experts,

We ran a functional language localizer analysis in FSL and we want to apply the mask from this analysis to our SMRI analyses using the mri_glmfit command with the --mask option. Basically, we want to examine whether GMV within these language localizer regions is correlated with performance on various tasks. I previously used mri_convert to convert the .nii file to .mgh, and tried to run the mri_glmfit --mask command but received an error (ERROR: dimension mismatch 1 between y and mask) which I believe is linked to the fact that the previously run mris_preproc files are 4D, while our functional mask is still only 3D. When I use tksurfer and overlay the 3D mask file, it looks fine.

So the question is how can we convert our 3D functional mask into a format that we can use for the mri_glmfit command (Nverteces x 1 x 1 x Nsubjects)?

Thanks for all your help!

Best,

Jen
--

Jennifer Legault
PhD, Neuroscience

Postdoctoral Scholar

Language Acquisition and Brain Lab
University of Delaware
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