A central pattern generator for insect gait production

We present a neural network model inspired from both behavioral and neurophysiological data on insect locomotion. The model consists of a central rhythmic pattern generator and a sensory motor network. We show that it exhibits various behavioral properties observed in several insect species: it produces a continuum of stable gaits ranging from metachronal to tripod; the changes in the duration of protraction retraction phases for various walking speeds follow closely the behavorial data; the network is insensitive to the initial position of the legs, in that it can achieve rapidly a coherent phase relationship regardless of the initial conditions. In addition, this transient property also extends to situations where rapid changes occur in the walking speed; the network can reorganize its phase rapidly during fast accelerations as well as fast decelerations.