Research on Neural Information Coding of Spiking Neural Network Based on Synaptic Plasticity Under AC Electric Field Stimulation

Abstract

Neural information coding is helpful in understanding the working mechanism of the nervous system. Currently, most of the studies are based on the neural network which is based on excitatory synaptic plasticity. However, the inhibitory synaptic plasticity also plays an important role in the regulation of neural network. For presenting better biological authenticity, a spiking neural network was constructed based on the synaptic plasticity regulation mechanism in this study. The synaptic plasticity regulation mechanism contains excitatory and inhibitory synapses. The characteristics of neural information coding under AC electric field stimulation were studied from the perspective of time coding (inter-spike interval coding) and rate coding (average rate coding). The experimental results indicate that inter-spike intervals decrease and the firing rate of neurons increases under AC electric field stimulation. With the increase of the stimulation intensity, inter-spike intervals are decreased and the firing rate of neurons is increased. The neurons whose average firing rate increases can be raised as a neuron cluster to express the information. The results of this paper help us to understand the mechanism of information processing of the brain, and bring new ideas to the engineering applications such as neural computation and artificial intelligence.