Energy balance and synchronization of the cross-ring photosensitive neural network

Abstract

After detecting different external light stimuli, photosensitive neurons encode these stimuli and trigger different discharge patterns and membrane potentials, thereby transmitting signals in the neural network. The cross-ring structure can simulate complex dynamic behaviors in the neuron system, which helps to achieve synchronous behavior between neurons. This article, respectively, uses linear resistors and induction coils to connect four photosensitive neurons and constructs a cross-ring photosensitive neural network. We examine the energy balance and synchronization stability of the system by adjusting the coupling channels and external stimuli while also estimating the impact of noise. A system composed of identical neurons achieves energy balance and complete synchronization, whereas a system composed of diverse neurons is able to achieve phase synchronization by adjusting the coupling gain. However, under magnetic field coupling, a system composed of the same chaotic neurons can only achieve energy balance and complete synchronization with a larger coupling gain. For both types of coupled systems, noise may affect the synchronization of neuron systems in chaotic states, but it has no effect on the synchronization of spike-shaped neuron systems. Resistance coupling can synchronize more quickly than magnetic field coupling, but magnetic field coupling is more susceptible to variations in the coupling gain ratio. The study will give the domains of neuroscience and artificial intelligence a theoretical groundwork as well as a deeper knowledge of the workings and governing principles of neural networks.