FitzHugh-Nagumo oscillators on complex networks mimic epileptic-seizure-related synchronization phenomena

TL;DR

This study investigates how FitzHugh-Nagumo oscillators on complex networks can spontaneously produce synchronization patterns similar to epileptic seizures, highlighting the importance of network topology in seizure dynamics.

Contribution

It demonstrates that small-world network structures with intermediate rewiring probabilities best replicate seizure-like synchronization phenomena observed in empirical human brain connectivity.

Findings

Small-world networks with intermediate rewiring mimic seizure phenomena.

Other topologies show less realistic or persistent synchronization.

Network topology influences seizure-like dynamics.

Abstract

We study patterns of partial synchronization in a network of FitzHugh-Nagumo oscillators with empirical structural connectivity measured in human subjects. We report the spontaneous occurrence of synchronization phenomena that closely resemble the ones seen during epileptic seizures in humans. In order to obtain deeper insights into the interplay between dynamics and network topology, we perform long-term simulations of oscillatory dynamics on different paradigmatic network structures: random networks, regular nonlocally coupled ring networks, ring networks with fractal connectivities, and small-world networks with various rewiring probability. Among these networks, a small-world network with intermediate rewiring probability best mimics the findings achieved with the simulations using the empirical structural connectivity. For the other network topologies, either no spontaneously occurring epileptic-seizure-related synchronization phenomena can be observed in the simulated dynamics, or the overall degree of synchronization remains high throughout the simulation. This indicates that a topology with some balance between regularity and randomness favors the self-initiation and self-termination of episodes of seizure-like strong synchronization.