Complex patterns arise through spontaneous symmetry breaking in dense homogeneous networks of neural oscillators

TL;DR

This paper demonstrates that dense, homogeneous neural oscillator networks can spontaneously develop complex patterns through symmetry breaking, potentially explaining diverse brain activity patterns without detailed wiring knowledge.

Contribution

It shows that simple, uniform neural oscillator networks can generate complex dynamics via spontaneous symmetry breaking, linking experimental brain activity patterns to network behavior.

Findings

Networks exhibit diverse dynamical patterns due to symmetry breaking.

Complex brain activity patterns can emerge without detailed wiring.

Homogeneous systems can explain rich neural dynamics.

Abstract

Recent experiments have highlighted how collective dynamics in networks of brain regions affect behavior and cognitive function. In this paper we show that a simple, homogeneous system of densely connected oscillators representing the aggregate activity of local brain regions can exhibit a rich variety of dynamical patterns emerging via spontaneous breaking of permutation or translational symmetry. Our results connect recent experimental findings and suggest that a range of complicated activity patterns seen in the brain could be explained even without a full knowledge of its wiring diagram.