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Is there a way to resample a vertex-by-vertex matrix of data from one subject to another or to ico? For example, I have calculated the Euclidean distance matrix for all the vertices of lh.white for my subjects and wish to find the average distance matrix. Another example might be functional connectivity values.
If the data were univariate (i.e. vectors not matrices), I could save my measure as a .w file for each subject and use mri_surf2surf to morph each vector to ico and then average across the resulting ico vectors. One idea is to use make_average_subject to morph each subject’s surface to ico and then calculate bivariate measures on these surfaces. This might be ok for the functional connectivity case. However, this morphing distorts the absolute size of the surface, so the Euclidean distance matrix would be untenably distorted.
In other words, is there an extension of mri_surf2surf (or maybe mris_convert) that operates on v(i,j) measures rather than v(i) measures?
Thank you,
-Burke