I have some questions about the 3dkmeans function.
1/ First, does this function appropriate for resting-state data, to determine functional clustering within a ROI.
As it is mention at the beginning of the help-page program, it seems that the algorithm used are based on the 'Michiel Jan Laurens de Hoon C Clustering Library’.
2/ In this library, the pearson correlation scores are computed like this:
r =1/n * sum[ ( (xi−mean(x)) / sd(x) ) * ( (yi−mean(y)) / sd(y) ) ]
why not 1/(n-1) instead of 1/n ?
3/ does the ‘uncentered’ version corresponded to the Uncentered correlation (cosine of the angle) described by the ‘Michiel Jan Laurens de Hoon C Clustering Library’?
4/ in the -g 2 option, what do you mean by Weighted_Pearson_Correlation ?
I also wondering what the function 3dkmeans does whit the option -g 0 ?
It seems that it still create clusters, but I don’t understand how (which algorithm is used)?
5/ Finally, the help-page mentioned that the -g 7 option is the default when there is only one value per voxel. But could we still use this metric for time-series data (meaning that there is several values per voxel?)
Sorry for all these questions and thank you for your reply.