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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



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