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Scale-Free Brain Functional Networks Victor M. Eguiluz,1

Summary: Scale-Free Brain Functional Networks
Victor M. EguiŽluz,1
Dante R. Chialvo,2
Guillermo A. Cecchi,3
Marwan Baliki,2
and A. Vania Apkarian2
Instituto MediterraŽneo de Estudios Avanzados, IMEDEA (CSIC-UIB), E07122 Palma de Mallorca, Spain
Department of Physiology, Northwestern University, Chicago, Illinois, 60611, USA
IBM T.J. Watson Research Center, 1101 Kitchawan Rd., Yorktown Heights, New York 10598, USA
(Received 13 January 2004; published 6 January 2005)
Functional magnetic resonance imaging is used to extract functional networks connecting correlated
human brain sites. Analysis of the resulting networks in different tasks shows that (a) the distribution of
functional connections, and the probability of finding a link versus distance are both scale-free, (b) the
characteristic path length is small and comparable with those of equivalent random networks, and (c) the
clustering coefficient is orders of magnitude larger than those of equivalent random networks. All these
properties, typical of scale-free small-world networks, reflect important functional information about
brain states.


Source: Apkarian, A. Vania - Department of Physiology, Northwestern University
Chialvo, Dante R. - Department of Physiology, Northwestern University
Oro, Daniel - Natural Resources Department, Mediterranean Institute for Advanced Studies


Collections: Biology and Medicine; Computer Technologies and Information Sciences; Environmental Sciences and Ecology; Physics