Robustness and Information Propagation in Attractors of Random Boolean Networks

Jason Lloyd-Price, Abhishekh Gupta and Andre S Ribeiro

PLOS ONE, 2012, vol. 7, issue 7, 1-6

Abstract: Attractors represent the long-term behaviors of Random Boolean Networks. We study how the amount of information propagated between the nodes when on an attractor, as quantified by the average pairwise mutual information (), relates to the robustness of the attractor to perturbations (). We find that the dynamical regime of the network affects the relationship between and . In the ordered and chaotic regimes, is anti-correlated with , implying that attractors that are highly robust to perturbations have necessarily limited information propagation. Between order and chaos (for so-called “critical” networks) these quantities are uncorrelated. Finite size effects cause this behavior to be visible for a range of networks, from having a sensitivity of 1 to the point where is maximized. In this region, the two quantities are weakly correlated and attractors can be almost arbitrarily robust to perturbations without restricting the propagation of information in the network.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0042018

DOI: 10.1371/journal.pone.0042018

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