Generic Criticality in Ecological and Neuronal Networks

TL;DR

This paper demonstrates that ecological and neuronal networks with purely inhibitory interactions naturally exhibit power-law scaling in their dynamics, challenging the idea that living systems are fine-tuned to operate at critical points.

Contribution

It shows that criticality emerges generically in biological networks with inhibitory interactions without fine-tuning, questioning the necessity of criticality for adaptive processing.

Findings

Power-law scaling observed in ecological and neuronal models.

Criticality arises without parameter fine-tuning.

Challenges the notion of criticality as an evolved feature.

Abstract

We investigate the dynamics of two models of biological networks with purely suppressive interactions between the units; species interacting via niche competition and neurons via inhibitory synaptic coupling. In both of these cases, power-law scaling of the density of states with probability arises without any fine-tuning of the model parameters. These results argue against the increasingly popular notion that non-equilibrium living systems operate at special critical points, driven by there by evolution so as to enable adaptive processing of input data.