Robustness and information propagation in attractors of Random Boolean Networks

PLoS One. 2012;7(7):e42018. doi: 10.1371/journal.pone.0042018. Epub 2012 Jul 30.

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 (I(A)), relates to the robustness of the attractor to perturbations (R(A)). We find that the dynamical regime of the network affects the relationship between I(A) and R(A). In the ordered and chaotic regimes, I(A) is anti-correlated with R(A), 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 I(A) 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Information Storage and Retrieval*

Grants and funding

Work supported by TUT President’s Doctoral Programme (JLP), FiDiPro programme (AG, ASR), and Academy of Finland (ASR). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.