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From neurons to epidemics : how trophic coherence affects spreading processes
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Klaise, Janis and Johnson, Samuel (2016) From neurons to epidemics : how trophic coherence affects spreading processes. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26 (6). 065310. doi:10.1063/1.4953160 ISSN 1054-1500.
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Official URL: http://dx.doi.org/10.1063/1.4953160
Abstract
Trophic coherence, a measure of the extent to which the nodes of a directed network are organised in levels, has recently been shown to be closely related to many structural and dynamical aspects of complex systems, including graph eigenspectra, the prevalence or absence of feedback cycles, and linear stability. Furthermore, non-trivial trophic structures have been observed in networks of neurons, species, genes, metabolites, cellular signalling, concatenated words, P2P users, and world trade. Here, we consider two simple yet apparently quite different dynamical models—one a susceptible-infected-susceptible epidemic model adapted to include complex contagion and the other an Amari-Hopfield neural network—and show that in both cases the related spreading processes are modulated in similar ways by the trophic coherence of the underlying networks. To do this, we propose a network assembly model which can generate structures with tunable trophic coherence, limiting in either perfectly stratified networks or random graphs. We find that trophic coherence can exert a qualitative change in spreading behaviour, determining whether a pulse of activity will percolate through the entire network or remain confined to a subset of nodes, and whether such activity will quickly die out or endure indefinitely. These results could be important for our understanding of phenomena such as epidemics, rumours, shocks to ecosystems, neuronal avalanches, and many other spreading processes.
Item Type: | Journal Article | ||||||||
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Subjects: | H Social Sciences > HG Finance Q Science > QH Natural history Q Science > QP Physiology R Medicine > RA Public aspects of medicine |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Physics | ||||||||
Library of Congress Subject Headings (LCSH): | Food chains (Ecology) -- Mathematical models, Communicable diseases, Neural networks (Neurobiology), Stock exchanges | ||||||||
Journal or Publication Title: | Chaos: An Interdisciplinary Journal of Nonlinear Science | ||||||||
Publisher: | American Institute of Physics | ||||||||
ISSN: | 1054-1500 | ||||||||
Official Date: | 10 June 2016 | ||||||||
Dates: |
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Volume: | 26 | ||||||||
Number: | 6 | ||||||||
Article Number: | 065310 | ||||||||
DOI: | 10.1063/1.4953160 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Date of first compliant deposit: | 15 August 2016 | ||||||||
Date of first compliant Open Access: | 15 August 2016 | ||||||||
Funder: | Engineering and Physical Sciences Research Council (EPSRC) | ||||||||
Grant number: | EP/IO1358X/1 |
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