Hi,

we are working on a visualization method for functional connectivity  
on the cortical surface, and would like to use the HCP functional  
connectivity data towards that end. We require surface representations  
and either the time series associated with the cortical nodes, or a  
correlation matrix with the functional
connectivity strength for each pair of nodes as input for our method.  
I figured out a way to read CIFTI files, however, even the  
down-sampled representations with ~30k nodes are too complex to handle  
at interactive framerates in our software for the time being.

What would be the best way to reduce the resolution of the surfaces to  
something closer to 10k nodes? I know how to decimate the number of  
nodes with the freesurfer tools in order to get a lower resolution  
surface representation for individuals, but am not certain that this  
is the best approach. Is it possible to get matching time series data  
sampled to a surface different than the ones included in the  
preprocessed data?

Any help or pointers in the right direction would be highly appreciated...

Cheers,

Joachim
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