Synchronization and chimeras in a network of photosensitive FitzHugh-Nagumo neurons

Recently, a photosensitive model has been proposed that takes into account nonlinear encoding and responses of photosensitive neurons that are subject to optical signals. In the model, a photocell term has been added to the well-known FitzHugh-Nagumo neuron, which results in a time-varying voltage source. The modified model exhibits most of the main characteristics of biological neurons, like spiking, bursting, and chaotic responses, but is also amenable to study the effect of optical signals. In this paper, we consider a small-world network of photosensitive neurons and study their collective behavior in dependence on interaction strength. We show that the network exhibits synchronization in a specific range of coupling strengths before transcending into a chimera state. We use the master stability function, a local-order parameter, as well as recurrence plots to verify the reported results.

Automated summary

In this study, a photosensitive neuron model considering nonlinear encoding and responses to optical signals was proposed, revealing collective behavior and mechanisms in small-world network. The network exhibited synchronization before transitioning into a chimera state, validated by various methods including master stability function and recurrence plots.