Neuronal Ensemble Rate Coding of the Simulated Spike Trains in the Temporal Lobe Cortex via Small-World Network

The Hindmarsh-Rose (HR) model could describe different discharge property of an excitatory or inhibitory neuron by changing the parameter gamma. In this paper, HR model is used to be the dynamical equations of the spiking model neurons, and different neurons in one neuronal population are connected with WS small-world network. A neurons spiking model in the temporal lobe cortex based on small-world network is established on the Matlab platform. Spike trains of the neurons spiking model are simulated when no stimulus and a pulse current acted on the model. Then rate coding is used to analysis the simulated spiking trains. Experiment results indicate when no stimulus acts on the neurons spike model, the spike firing of temporal lobe cortex is sparse. When a stimulus acts on the neurons spike model, the mean population firing rate increased obviously. The increasing of neurons firing rate could present the ensemble activities, which highly correlate with memory.