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MiS Preprint
71/2011

Information storage, loop motifs and clustered structure in complex networks

Joseph Lizier, Fatihcan M. Atay and Jürgen Jost

Abstract

We use a standard discrete-time linear Gaussian model to analyze information storage capability of individual nodes in complex networks, given network structure and link weights. In particular, we investigate the role of two and three-node motifs in contributing to information storage. We show analytically that directed feedback loops and feedforward loop motifs are the dominant contributors to information storage capability, and show the direct relationship between clustering coefficient(s) and information storage. These results explain the dynamical importance of clustered structure, and offer an explanation for the prevalence of these motifs in biological and artificial networks.

Received:
Oct 24, 2011
Published:
Nov 17, 2011
MSC Codes:
05C82, 05C38, 94A17
PACS:
89.75.Fb, 89.70.Cf, 87.18.Sn, 87.19.lo, 02.10.Ox
Keywords:
information storage, intrinsic computation, complex networks, information theory, neural networks

Related publications

inJournal
2012 Repository Open Access
Joseph T. Lizier, Fatihcan M. Atay and Jürgen Jost

Information storage, loop motifs and clustered structure in complex networks

In: Physical review / E, 86 (2012) 2, p. 026110