Emergence of a dynamical state of coherent bursting with power-law distributed avalanches from collective stochastic dynamics of adaptive neurons

TL;DR

This paper demonstrates that neuronal avalanches with power-law distributions can emerge from the collective stochastic dynamics of adaptive neurons, without requiring the brain to be at a critical point, challenging previous criticality hypotheses.

Contribution

The study shows that coherent bursting and power-law avalanches can arise from adaptive neuron networks driven by stochastic input, without assuming criticality.

Findings

Power-law avalanches emerge from adaptive neuron networks with stochastic input.

Coherent bursting results from a balance between excitation and adaptation.

Observed neuronal avalanche features can be explained without criticality.

Abstract

Spontaneous brain activity in the absence of external stimuli is not random but contains complex dynamical structures such as neuronal avalanches with power-law duration and size distributions. These experimental observations have been interpreted as supporting evidence for the hypothesis that the brain is operating near a critical point of phase transition between two states, and attracted much attention. Here, we show that a dynamical state of coherent bursting, with power-law distributed avalanches and features as observed in experiments, emerges in networks of adaptive neurons with stochastic input when excitation is sufficiently strong and balanced by adaptation. We demonstrate that these power-law distributed avalanches are direct consequences of stochasticity and coherent bursting, which in turn is the result of a balance between excitation and adaptation. Our work thus shows that the observed dynamical features of neuronal avalanches can arise from collective stochastic dynamics of adaptive neurons under suitable conditions and need not be signatures of criticality.