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Abstract
Brain connectivity datasets comprise networks of brain regions connected by anatomical
tracts or by functional associations. Complex network analysis-a new multidisciplinary
approach to the study of complex systems-aims to characterize these brain networks
with a small number of neurobiologically meaningful and easily computable measures.
In this article, we discuss construction of brain networks from connectivity data
and describe the most commonly used network measures of structural and functional
connectivity. We describe measures that variously detect functional integration and
segregation, quantify centrality of individual brain regions or pathways, characterize
patterns of local anatomical circuitry, and test resilience of networks to insult.
We discuss the issues surrounding comparison of structural and functional network
connectivity, as well as comparison of networks across subjects. Finally, we describe
a Matlab toolbox (http://www.brain-connectivity-toolbox.net) accompanying this article
and containing a collection of complex network measures and large-scale neuroanatomical
connectivity datasets.
Copyright (c) 2009 Elsevier Inc. All rights reserved.