Tristable and multiple bistable activity in complex random binary networks of two-state units

TL;DR

This paper analyzes complex binary networks of two-state units with stochastic dynamics, revealing various stable activity states including bistability and tristability, and providing analytical and numerical insights into their behavior.

Contribution

It introduces a heterogeneous mean-field approach for modeling complex two-state networks and uncovers new stable activity regimes depending on network composition.

Findings

Identification of tristability and multiple bistable states in binary networks.

Dependence of steady states on the ratio of node degrees.

Analytical results validated by numerical simulations.

Abstract

We study complex networks of stochastic two-state units. Our aim is to model discrete stochastic excitable dynamics with a rest and an excited state. Both states are assumed to possess different waiting time distributions. The rest state is treated as an activation process with an exponentially distributed life time, whereas the latter in the excited state shall have a constant mean which may originate from any distribution. The activation rate of any single unit is determined by its neighbors according to a random complex network structure. In order to treat this problem in an analytical way, we use a heterogeneous mean-field approximation yielding a set of equations general valid for uncorrelated random networks. Based on this derivation we focus on random binary networks where the network is solely comprised of nodes with either of two degrees. The ratio between the two degrees is shown to be a crucial parameter. Dependent on the composition of the network the steady states show the usual transition from disorder to homogeneous ordered bistability as well as new scenarios that include inhomogeneous ordered and disordered bistability as well as tristability. The various steady states differ in their spiking activity expressed by a state dependent spiking rate. Numerical simulations agree with analytic results of the heterogeneous mean-field approximation.