Originally posted by Adam Steel:
It appears that (at least some of the) code may not complete in a practical amount of time for higher resolutions. I used preprocessed fMRI data from the Human Connectome Project which has a voxel resolution of (2 x 2 x 2) mm. I used a cluster count of 1000. The function make_local_connectivity_tcorr() with a grey mask having about 255,000 voxels runs successfully to create the correlation matrix. The correlation matrix has around 1,000,000 non-zero entries. However the next step binfile_parcellate() runs forever - as the eigenvalue decomposition of the Laplacian of the correlation matrix does not converge (after 24+ hours of run time).

There is a comment in the ncut() function of the toolbox about regularizing the matrix for better stability. So it appears that the author himself may have had problems with the eigenvalue decomposition - which is of course not at all unexpected. Trying to find the eigenvectors of a large sparse matrix can be hell. Hopefully the author reads this and comments.

My next step is to resample the data and grey-mask to (4 x 4 x 4) and rerun the code.

Wondering whether anyone else has had a similar experience.

Regards,
Sandeep Mody.