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Primary evolving networks and the comparative analysis of robust and fragile structures

Grindrod, P., Stoyanov, Z. V., Smith, G. M. and Saddy, J. D. ORCID: https://orcid.org/0000-0001-8501-6076 (2013) Primary evolving networks and the comparative analysis of robust and fragile structures. Journal of Complex Networks, 2 (1). pp. 60-73. ISSN 2051-1329

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To link to this item DOI: 10.1093/comnet/cnt015

Abstract/Summary

In this paper we consider the structure of dynamically evolving networks modelling information and activity moving across a large set of vertices. We adopt the communicability concept that generalizes that of centrality which is defined for static networks. We define the primary network structure within the whole as comprising of the most influential vertices (both as senders and receivers of dynamically sequenced activity). We present a methodology based on successive vertex knockouts, up to a very small fraction of the whole primary network,that can characterize the nature of the primary network as being either relatively robust and lattice-like (with redundancies built in) or relatively fragile and tree-like (with sensitivities and few redundancies). We apply these ideas to the analysis of evolving networks derived from fMRI scans of resting human brains. We show that the estimation of performance parameters via the structure tests of the corresponding primary networks is subject to less variability than that observed across a very large population of such scans. Hence the differences within the population are significant.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary Research Centres (IDRCs) > Centre for Integrative Neuroscience and Neurodynamics (CINN)
Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics > Centre for the Mathematics of Human Behaviour (CMOHB)
ID Code:34017
Publisher:Oxford University Press
Publisher Statement:This is a pre-copyedited, author-produced PDF of an article accepted for publication in Journal of Complex Networks following peer review. The definitive publisher-authenticated version is available online at: http://comnet.oxfordjournals.org/content/early/2013/10/16/comnet.cnt015.abstract

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