Functional connectivity by cross-correlation clustering

In addition to information on localization of brain functions, data from fMRI experiments contain also cues about the functional connectivity among modular units, We propose a data-driven deterministic clustering algorithm based on temporal cross-correlations and elements of graph theory to detect functionally connected regions. The cluster concept can be changed in a controlled manner to reveal the functional connectivity structure in detail. The algorithm is applied to data from a motor task and shows to successfully determine clusters related to the stimulus. Furthermore, the method can be extended to include the analysis of temporal relations between different brain regions. (C) 2002 Published by Elsevier Science B.V.