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.