Dear Experts,
This is partially a follow-up question to another thread related to the mask.mgh generated by mri_glmfit (http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg50691.html http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg50691.html).
We would like to use the mri_surfcluster tool on a log10p map. I’m wondering — for vertex-wise analyses that use freesurfer-specific output (e.g., thickness, surface area, lgi, etc, not FMRI or DTI data)….can we rely on a single mask image for each hemisphere that comes from the fsaverage ?h.cortex.label? Or, should we be creating a mask that is specific to a given analysis/dataset, as is done with mri_glmfit?
If the latter, is there a way to create this mask outside of mri_glmfit?
Thank you in advance for your time and help!
Best,
Ryan
usually the fsaverage mask is fine. You can use mri_label2label with the --outmask option to convert the ?h.cortex.label to a binary mask. You can also pass surfcluster a label directly with the --clabel option
On 05/14/2017 05:45 AM, Ryan Muetzel wrote:
Dear Experts,
This is partially a follow-up question to another thread related to the mask.mgh generated by mri_glmfit (http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg50691.html).
We would like to use the mri_surfcluster tool on a log10p map. I’m wondering — for vertex-wise analyses that use freesurfer-specific output (e.g., thickness, surface area, lgi, etc, not FMRI or DTI data)….can we rely on a single mask image for each hemisphere that comes from the fsaverage ?h.cortex.label? Or, should we be creating a mask that is specific to a given analysis/dataset, as is done with mri_glmfit?
If the latter, is there a way to create this mask outside of mri_glmfit?
Thank you in advance for your time and help!
Best,
Ryan
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Perfect --- Thank you!
Ryan
On May 15, 2017, at 6:09 PM, Douglas N Greve greve@nmr.mgh.harvard.edu wrote:
usually the fsaverage mask is fine. You can use mri_label2label with the --outmask option to convert the ?h.cortex.label to a binary mask. You can also pass surfcluster a label directly with the --clabel option
On 05/14/2017 05:45 AM, Ryan Muetzel wrote:
Dear Experts,
This is partially a follow-up question to another thread related to the mask.mgh generated by mri_glmfit (http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg50691.html).
We would like to use the mri_surfcluster tool on a log10p map. I’m wondering — for vertex-wise analyses that use freesurfer-specific output (e.g., thickness, surface area, lgi, etc, not FMRI or DTI data)….can we rely on a single mask image for each hemisphere that comes from the fsaverage ?h.cortex.label? Or, should we be creating a mask that is specific to a given analysis/dataset, as is done with mri_glmfit?
If the latter, is there a way to create this mask outside of mri_glmfit?
Thank you in advance for your time and help!
Best,
Ryan
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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