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- Title
Robustness and Information Propagation in Attractors of Random Boolean Networks.
- Authors
Lloyd-Price, Jason; Gupta, Abhishekh; Ribeiro, Andre S.
- 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 (IA), relates to the robustness of the attractor to perturbations (RA). We find that the dynamical regime of the network affects the relationship between IA and RA. In the ordered and chaotic regimes, IA is anti-correlated with RA, implying that attractors that are highly robust to perturbations have necessarily limited information propagation. Between order and chaos (for socalled ''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 IA 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.
- Subjects
BRAIN research; BOOLEAN functions; NEURAL circuitry; PERTURBATION theory; APPROXIMATION theory; FUNCTIONAL analysis; MATHEMATICAL physics; INFORMATION processing
- Publication
PLoS ONE, 2012, Vol 7, Issue 7, p1
- ISSN
1932-6203
- Publication type
Article
- DOI
10.1371/journal.pone.0042018