Towards more biologically plausible central-pattern-generator models

Abstract

Central pattern generators (CPGs) are relatively small neural networks that play a fundamental role in the control of animal locomotion. In this paper we define a method for the systematic design of CPG models able to exhibit biologically plausible gait transitions by implementing short-term synaptic plasticity mechanisms. As a case study, we focus on a simple CPG for quadruped locomotion. By applying the proposed method, three of four standard quadruped gaits were correctly reproduced by the obtained CPG model, not only in terms of the alternating sequence of the limbs but also in terms of frequency, duty cycle, and phase lags.