Fisher Information at the Edge of Chaos in Random Boolean Networks

RBNs have been used as models of gene regulatory networks. In this talk, we study the order-chaos phase transition in these networks. In particular, we seek to characterise the phase diagram in information-theoretic terms, focusing on the effect of the control parameters (activity level and connectivity). Fisher information, which measures how much system dynamics can reveal about the control parameters, offers a natural interpretation of the phase diagram in RBNs. We report that this measure is maximised near the order-chaos phase transition in RBNs, since this is the region where the system is most sensitive to its parameters.