I have a question about extracting functional data from structurally defined cortical labels. Here's what I'm doing:
1) Run a gammafit analysis; 2) Define cortical ROIs by using mri_annotation2label to make labels from aparc.annot; 3) Define sub-cortical ROIs by using mri_cor2label to make labels from aseg.mgz; 4) Extract functional data from labels using func2roi-sess; 5) Summarize the data with roisummary-sess. I usually view the cortical ROIs on the inflated (or pial) surface and the subcortical ROIs in the volume, and they usually look great. But when I view the cortical labels in the volume, they seem to consist of a 1-voxel thick strip hugging the white matter; they don't seem to cover the gray matter at all. Does this mean that I am extracting functional data from a 1-voxel thick strip (!), or am I just mis-understanding something about how a cortical label appears in the volume? Also, I know that "white" is the default surface in mri_annotation2label, but if I switch to "pial", make a label, and view it in the volume, it still looks like a 1-voxel thick strip, just around the outside edge of the gray matter (instead of around the inside edge if I use "white" as the surface). My simple mind wonders why these cortical labels-which look great on the inflated brain-don't cover the region between the pial and white surfaces (i.e., the gray matter) in the volume. Am I making a basic error here? If so, what do I need to do to extract functional data from cortically-defined ROIs? I am running version 4.0.2. Thanks! Dan D.
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