Spatiotemporal Behavior of Small-World Neuronal Networks Using a Map-Based Model

Abstract

In this paper, the dynamics of a map-based model is proposed firstly. It is a simple model which can not only reproduce rich behaviors of biological neurons but also compute efficiently. Then, the dynamics of two coupled maps that model the behavior of two electrically coupled neurons is discussed. By tuning the coupling strength, synchronization of two spiking or bursting neurons are simulated. Furthermore, the spatiotemporal behavior of a small-world neuronal network using map-based model is studied. Detailed investigations reveal that the collective dynamics of neuronal activity will be affected by varying some key parameters, such as the coupling strength of neurons, connection probability and the number of nearest neighbor in small-world topology. Our study suggests that the map-based model will give us a new opportunity to reproduce the real biological network containing a large number of neurons.