Nonlinear Time Series Analysis of Spike Data of Izhikevich Neuron Model

Abstract

It is well known that burst patterns of neuronal networks may play an important role in information processing in the brain. We consider that it is advantageous to construct a model using mathematical neuronal models producing burst patterns, because it is such models are easier to study and more accessible as compared to real biological neuronal data. In this study, we use the Izhikevich neuron model to produce burst patterns and apply a recurrence plot density entropy to the Izhikevich neuron data.