This paper presents a novel approach to the emulation of locomotor central pattern generators (CPGs) of legged animals. Based on Scheduling by Multiple Edge Reversal (SMER), a simple but powerful distributed algorithm, it is shown how oscillatory building blocks (OBBs) can be created and how OBB-based networks can be implemented as asymmetric Hopfield-like neural networks for the generation of complicatedly coordinated rhythmic patterns observed among pairs of biological motor neurons working during different gait patterns. It is also presented how a generalized CPG model mapped into such Hopfield-like networks possess some charming properties on the retrieval of a whole range of different preprogrammed gait patterns. 1 Introduction For a long time the possibility of existence of central pattern generators (CPGs) and their possible functionalities in biological rhythmic activities such as locomotion have inspired great interest in scientific communities. As many neurophysiologi...