SNN Modeling of Cricket Auditory Network with Izhikevich Model Optimized by PSO

This study explores the intersection of neuroscience and computer science, focusing on the use of spiking neural networks (SNNs) to simulate the behavior of biological neurons. A neural network model based on the Izhikevich neuron model is proposed to simulate the local auditory network of crickets. The parameters of the neuron model are optimized based on evaluation functions and identified by Particle Swarm Optimization (PSO), aligning its input-output relationships with the observed cricket neuron responses. The results showed that the network successfully simulated the behavior of individual neurons, promising applications in fields like neural prosthetics.