Activity-dependent neuronal model on complex networks

TL;DR

This paper introduces a neuronal model based on self-organized criticality that reproduces experimentally observed neuronal avalanches and EEG power spectra across various complex network topologies.

Contribution

The model demonstrates how activity-dependent synaptic plasticity can produce critical neuronal avalanches on different complex network structures.

Findings

Reproduces power law distributions of avalanche sizes and durations.

Matches EEG spectral power law behavior.

Shows robustness of criticality across network types.

Abstract

Neuronal avalanches are a novel mode of activity in neuronal networks, experimentally found in vitro and in vivo, and exhibit a robust critical behaviour: These avalanches are characterized by a power law distribution for the size and duration, features found in other problems in the context of the physics of complex systems. We present a recent model inspired in self-organized criticality, which consists of an electrical network with threshold firing, refractory period and activity-dependent synaptic plasticity. The model reproduces the critical behaviour of the distribution of avalanche sizes and durations measured experimentally. Moreover, the power spectra of the electrical signal reproduce very robustly the power law behaviour found in human electroencephalogram (EEG) spectra. We implement this model on a variety of complex networks, i.e. regular, small-world and scale-free and verify the robustness of the critical behaviour.