Simulation of Central Pattern Generators via Chaotic Neuron Populations

Abstract In this paper a simulation environment is presented where biological neural networks are can be efficiently built and simulated, at the aim to study spatio-temporal organization arising from population of chaotic neurons. Some models of Central Pattern Generators are also presented with application to the generation of insect walking patterns, implemented on a robotic structure directly driven by the simulator.