The broad edge of synchronisation: Griffiths effects and collective phenomena in brain networks

TL;DR

This paper investigates how hierarchical and modular brain-like networks exhibit complex, flexible synchronization states akin to Griffiths phases, highlighting the interplay between structure and dynamics in neural collective behavior.

Contribution

It introduces a framework showing how structural heterogeneity in brain networks leads to broad Griffiths-like phases of synchronization, advancing understanding of brain dynamics.

Findings

Emergence of intermediate synchronization states in brain models

Identification of Griffiths-like phases in neural networks

Hybrid bifurcations lead to complex collective phenomena

Abstract

Many of the amazing functional capabilities of the brain are collective properties stemming from the interactions of large sets of individual neurons. In particular, the most salient collective phenomena in brain activity are oscillations, which require the synchronous activation of many neurons. Here, we analyse parsimonious dynamical models of neural synchronisation running on top of synthetic networks that capture essential aspects of the actual brain anatomical connectivity such as a hierarchical-modular and core-periphery structure. These models reveal the emergence of complex collective states with intermediate and flexible levels of synchronisation, halfway in the synchronous-asynchronous spectrum. These states are best described as broad Griffiths-like phases, i.e. an extension of standard critical points that emerge in structurally heterogeneous systems. We analyse different routes (bifurcations) to synchronisation and stress the relevance of 'hybrid-type transitions' to generate rich dynamical patterns. Overall, our results illustrate the complex interplay between structure and dynamics, underlining key aspects leading to rich collective states needed to sustain brain functionality.