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Functional connectivity by cross-correlation clustering

delete2002-06-01
delete56
PRE
AI
J
J. Michael Herrmann
T
T. Geisel
DOI：10.1016/S0925-2312(02)00416-2delete
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Abstract

Abstract

En 中文
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.
Keywords:
functional connectivity
cluster
cross-correlation
graph
connectivity component
clique
fMRI

Journal

Neurocomputing cover
Neurocomputing
IF:
6.5
Papers:
2.5W
Citations:
6.5W

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No organization information available