Hi Bruce,
I would like to be able to tell
what proportion of a region of interest (ROI), as defined in atlas space by e.g.
Desikan-Killiany, that shows a significant effect (based on a p-map). For now I overlay the p-map on the
inflated surface of fsaverage in tksurfer and eyeball the proportion.
Given a p-map, if I find the FDR threshold and
identify the vertices within a given ROI that have a p-value greater
than the threshold, then I can find the proportion of the ROI that is
suprathreshold. E.g., I find 1986 suprathreshold vertices in "bankssts"
out of 2137, so 93% of vertices in bankssts show a significant effect.
My question is: Does that tell me anything about what
proportion of the ROI's surface area is affected in atlas space? Obviously, if the
faces were uniform, there would be a 1 to 1 relationship between
#vertices and area. In the original tesselation
of any dataset the size of the faces is uniform, but that changes with
topology fix and deformation. I assume that is true also for fsaverage?
(so I can't assume [#sig vertices] / [# tot vertices] == the proportion of the ROI's area that is significant in atlas space)I can find the surface area of the suprathreshold region
for my sample (or any subset thereof) by looking at a mean area map. But I'm unsure how to do that for fsaverage itself? Is there information on regional surface area directly available? Or would using getFaceArea.m or getFacesArea.m or similar functions be a solution?