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