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Multi-scale community organization of the human structural connectome and its relationship with resting-state functional connectivity

Published online by Cambridge University Press:  03 January 2014

RICHARD F. BETZEL,
ALESSANDRA GRIFFA,
ANDREA AVENA-KOENIGSBERGER,
JOAQUÍN GOÑI,
JEAN-PHILIPPE THIRAN,
PATRIC HAGMANN and
OLAF SPORNS
RICHARD F. BETZEL
Affiliation:
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA Program in Cognitive Science, Indiana University, Bloomington, IN, USA
ALESSANDRA GRIFFA
Affiliation:
Department of Radiology, University Hospital Center and University of Lausanne (CHUV), Lausanne, Switzerland Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
ANDREA AVENA-KOENIGSBERGER
Affiliation:
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA Program in Cognitive Science, Indiana University, Bloomington, IN, USA
JOAQUÍN GOÑI
Affiliation:
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
JEAN-PHILIPPE THIRAN
Affiliation:
Department of Radiology, University Hospital Center and University of Lausanne (CHUV), Lausanne, Switzerland Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
PATRIC HAGMANN
Affiliation:
Department of Radiology, University Hospital Center and University of Lausanne (CHUV), Lausanne, Switzerland Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
OLAF SPORNS
Affiliation:
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA Program in Cognitive Science, Indiana University, Bloomington, IN, USA (e-mail: osporns@indiana.edu)
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Abstract

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The human connectome has been widely studied over the past decade. A principal finding is that it can be decomposed into communities of densely interconnected brain regions. Past studies have often used single-scale modularity measures in order to infer the connectome's community structure, possibly overlooking interesting structure at other organizational scales. In this report, we used the partition stability framework, which defines communities in terms of a Markov process (random walk), to infer the connectome's multi-scale community structure. Comparing the community structure to observed resting-state functional connectivity revealed communities across a broad range of scales that were closely related to functional connectivity. This result suggests a mapping between communities in structural networks, models of influence-spreading and diffusion, and brain function. It further suggests that the spread of influence among brain regions may not be limited to a single characteristic scale.

Keywords

connectomecommunity structuremulti-scaleMarkov processresting-state

Information

Type
Research Article
Information
Network Science , Volume 1 , Issue 3 , December 2013, pp. 353 - 373
Creative Commons
Creative Common License - CCCreative Common License - BY
The online version of this article is published within an Open Access environment subject to the conditions of the Creative Commons Attribution licence http://creativecommons.org/licenses/by/3.0/
Copyright
Copyright © Cambridge University Press 2014

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