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      Complex network measures of brain connectivity: Uses and interpretations

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      NeuroImage

      Elsevier BV

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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.

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          Author and article information

          Journal
          NeuroImage
          NeuroImage
          Elsevier BV
          10538119
          September 2010
          September 2010
          : 52
          : 3
          : 1059-1069
          Article
          10.1016/j.neuroimage.2009.10.003
          19819337
          © 2010

          https://www.elsevier.com/tdm/userlicense/1.0/

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