0 Chapter XII A General Rhythmic Pattern Generation Architecture for Legged Locomotion Zhijun Yang Stirling University, UK Felipe M.G. França Universidade Federal do Rio de Janeiro, Brazil Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited. AbSTRACT As an engine of almost all life phenomena, the motor information generated by the central nervous system (CNS) plays a critical role in the activities of all animals. After a brief review of some recent research results on locomotor central pattern generators (CPG), which is a concrete branch of studies on the CNS generating rhythmic patterns, this chapter presents a novel, macroscopic and model-independent approach to the retrieval of different patterns of coupled neural oscillations observed in biological CPGs during the control of legged locomotion. Based on scheduling by multiple edge reversal (SMER), a simple and discrete distributed synchroniser, various types of oscillatory building blocks (OBB) can be reconfgured for the production of complicated rhythmic patterns and a methodology is provided for the construction of a target artifcial CPG architecture behaving as a SMER-like asymmetric Hopfeld neural networks. INTRODUCTION Animal gait analysis is an ancient science. As early as two thousand years ago, Aristotle described the walk of a horse in his treatise (Peek & Forster, 1936) De Incessu Animalium: “The back legs move diagonally in relation to the front legs; for after the right fore leg animals move the left hind leg, then the left fore leg, and after it the right hind leg.” However, he erroneously believes that the bound gait is impossible: “If they moved the fore legs at the same time and frst, their progression