Heterogeneous connections induce oscillations in large scale networks

TL;DR

This paper demonstrates how heterogeneity in connectivity weights in large-scale networks can lead to various dynamic regimes, including transitions from stationary to oscillatory behaviors, supported by analytical and biological models.

Contribution

It reveals how increasing heterogeneity induces qualitative transitions in network dynamics, combining analytical and biological network analyses.

Findings

Heterogeneity causes transitions from stationary to oscillatory regimes.

Disorder parameter controls the emergence of phase-locked oscillations.

Results apply to both simple models and biological networks.

Abstract

Realistic large-scale networks display an heterogeneous distribution of connectivity weights, that might also randomly vary in time. We show that depending on the level of heterogeneity in the connectivity coefficients, different qualitative macroscopic and microscopic regimes emerge. We evidence in particular generic transitions from stationary to perfectly periodic phase-locked regimes as the disorder parameter is increased, both in a simple model treated analytically and in a biologically relevant network made of excitable cells.