help > RE: Hierarchical clustering
Aug 21, 2017  07:08 AM | tracywx
RE: Hierarchical clustering
Dear Alfonso,

I have a similar question related to this hierarchical clustering. So now for each subject, there should be a hierarchical clustering matrix. But how does CONN manage for more than one subject? Does it just average all the subjects' adjacency matrix or do something like statistics to get the final distance and clustering results? I'm quite confused about it. Could you please explain a little bit? Thanks a lot!


Best,
Tracy

Originally posted by Alfonso Nieto-Castanon:
Dear Deniz,

The hierarchical clustering algorithm in the 'ROI results explorer' uses a complete linkage (further distance) method with euclidean distance metric. Distances are computed as a weighted average of differences in connectivity statistics (functional criteria) and differences in spatial location (spatial criteria) between each pair of ROIs. The weighting factor is user-defined (ranging between '0', which uses a purely functional criteria, and '1', which uses a purely spatial criteria). 

Hope this helps.
Alfonso

Originally posted by Deniz Vatansever:
Dear Alfonso and the rest of the conn team,

Thank you all for the useful toolbox. Unfortunately I wasn't able to find any information on the type of hierarchical clustering used in ROI-to-ROI explorer GUI, and how it displays the subnetworks according to functional/spatial adjacency; will be glad if you can let me know.

Kind regards,

Deniz

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TitleAuthorDate
Deniz Vatansever Feb 6, 2014
Alfonso Nieto-Castanon Apr 22, 2014
RE: Hierarchical clustering
tracywx Aug 21, 2017