Synchronization transitions on scale-free neuronal networks due to finite information transmission delays

TL;DR

This study explores how finite information transmission delays influence synchronization and front propagation in scale-free neuronal networks, revealing delay-induced transitions and the importance of fine-tuning delays for optimal neural synchronization.

Contribution

It demonstrates the critical role of transmission delays in synchronization transitions on scale-free neuronal networks, highlighting their impact alongside coupling strength and network topology.

Findings

Synchronization improves with increased coupling strength.

Delay-induced transitions cause regular and irregular propagating fronts.

Optimal delays are crucial for maximal synchronization.

Abstract

We investigate front propagation and synchronization transitions in dependence on the information transmission delay and coupling strength over scale-free neuronal networks with different average degrees and scaling exponents. As the underlying model of neuronal dynamics, we use the efficient Rulkov map with additive noise. We show that increasing the coupling strength enhances synchronization monotonously, whereas delay plays a more subtle role. In particular, we found that depending on the inherent oscillation frequency of individual neurons, regions of irregular and regular propagating excitatory fronts appear intermittently as the delay increases. These delay-induced synchronization transitions manifest as well-expressed minima in the measure for spatial synchrony, appearing at every multiple of the oscillation frequency. Larger coupling strengths or average degrees can broaden the region of regular propagating fronts by a given information transmission delay and further improve synchronization. These results are robust against variations in system size, intensity of additive noise and the scaling exponent of the underlying scale-free topology. We argue that fine-tuned information transmission delays are vital for assuring optimally synchronized excitatory fronts on complex neuronal networks, and indeed, they should be seen as important as the coupling strength or the overall density of interneuronal connections. We finally discuss some biological implications of the presented results.