When I compare the thickness measure among subjects, I have to resample and smooth the thickness, so that each data have the same number of vertices and which are in correspondence with one another across subjects. Now I have .curv files or .sulc files for each subject and would like to make group analysis for these datasets. To compare the curvature and sulc measures, can I follow the same procedures as above ( ie I repeat the resampling and smoothing steps as I do for thickness)? If yes, how should I choose FWHM？ By the way, could you recommend me relevant papers that calculates the following indices : k1 maximum curvature k2 minimum curvature K Gaussian = k1*k2 H Mean = 0.5*(k1+k2) C Curvedness = sqrt(0.5*(k1*k1+k2*k2)) S Sharpness = (k1 - k2)^2 BE Bending Energy = k1*k1 + k2*k2 SI Shape Index = atan((k1+k2)/(k2-k1)) FI Folding Index = |k1|*(|k1| - |k2|) .sulc, .curv
So that I can get a better understanding of what the above measures reflects. Thanks a lot! yczhang
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