Hi Lars,

I guess you are working with vertexwise rather than facewise data, is this right? You'd need to compute then the area-per-vertex of the same sphere used as the target for the interpolation, i.e., the ico7 (surf/?h.sphere.reg in fsaverage I think). Attached is a Matlab function that calculates this area-per-vertex (or the area-per-face )from a surface and saves as a curvature file, in ASCII format. It reads also in ASCII, so you need to convert first (mris_convert). To run, it's something as this:

srf2area lh.sphere.reg.srf ico7.area.dpv dpv

Then multiply either each subject area map (after interpolation), or the average map, by 4*pi*r^2 (r should be 100), and divide the result by the area-per-vertex from the sphere that you calculated above, and divide the result again by the number of vertices in the sphere, which should be 163842. To do this, use the attached rpncalc function, that also runs in Matlab, and does simple maths in curvature files that are all of the same size, using RPN notation. Inputs are also in ASCII. To run, it should be something like this:

rpncalc lh.white.interp.dpv 125663.706144 * ico7.area.dpv / 163842 / lh.white.interp.corrected.dpv

The output you can convert back to cuvature binary and load with tksurfer or FreeView.

Hope this helps!

All the best,

Anderson

On 1 June 2014 16:32, Lars M. Rimol <larilin@gmail.com> wrote:

Hi Anderson,

Thank you!  How would you suggest I address this issue when I smooth these images before statistical analysis? I normally use the smoothing algorithm implemented in FreeSurfer (mri_surf2surf).

--

yours,

Lars M. Rimol, PhD
St. Olavs Hospital
Trondheim,
Norway

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