Synchronization and spatial patterns in a light-dependent neural network

Abstract

Nonlinear oscillators and networks can be synchronized by channel coupling for signal exchange, while non-coupling synchronization between chaotic oscillators can be obtained by applying the same stochastic disturbance for inducing resonance. For most of realistic dynamical systems, physical energy and biophysical energy are pumped along the coupling channels and then the variables are regulated to present different modes in oscillation. In this paper, a new photosensitive neuron is proposed to detect the dynamics in isolated neuron and synchronization stability by changing the illumination, which can adjust the photocurrent across the branch circuit, even no direct synapse coupling is applied. The generation of photocurrents with diversity is explained from physical viewpoint. Furthermore, the collective responses of these photosensitive neurons in network are detected by calculating the synchronization stability and pattern formation. It is found that the spatial patterns in the network are dependent on the illumination. Uniform illumination can induce complete synchronization while non-uniform illumination can develop rich spatial patterns. Furthermore, uniform and stochastic photocurrents are imposed on all neurons to realize complete synchronization even synapse connection are removed from the network. These results can give potential guidance for designing functional neural circuits with potential application to identify optical signals as electronic eyes.