Controlling extended criticality via modular connectivity

TL;DR

This study explores how modular connectivity in neural networks influences the emergence and control of Griffiths phases, revealing how structural changes can extend or stabilize critical dynamics relevant to brain function and disease spread.

Contribution

It demonstrates that adjusting intra- and intermodular connectivity can control the extent of Griffiths phases in modular networks, linking topology to criticality.

Findings

Modifying network connectivity extends the Griffiths phase.

Structural properties influence critical behavior in neural networks.

Results applicable to understanding brain states and disease dynamics.

Abstract

Criticality has been conjectured as an integral part of neuronal network dynamics. Operating at a critical threshold requires precise parameter tuning and a corresponding mechanism remains an open question. Recent studies have suggested that topological features observed in brain networks give rise to a Griffiths phase, leading to power-laws in brain activity dynamics and the operational benefits of criticality in an extended parameter region. Motivated by growing evidence of neural correlates of different states of consciousness, we investigate how topological changes affect the expression of a Griffiths phase. We analyze the activity decay in modular networks using a Susceptible-Infected-Susceptible propagation model and find that we can control the extension of the Griffiths phase by altering intra- and intermodular connectivity. We find that by adjusting system parameters, we can counteract changes in critical behavior and maintain a stable critical region despite changes in network topology. Our results give insight into how structural network properties affect the emergence of a Griffiths phase and how its features are linked to established topological network metrics. We discuss how those findings can contribute to understand the observed changes in functional brain networks. Finally, we indicate how our results could be useful in the study of disease spreading.