Topology of Central Pattern Generators: Selection by Chaotic Neurons

Abstract

Central Pattern Generators (CPGs) in invertebrates are comprised of networks of neurons in which every neuron has reciprocal connections to other members of the CPG. This is a ``closed'' network topology. An ``open'' topology, where one or more neurons receives input but does not send output to other member neurons, is not found in these CPGs. In this paper we investigate a possible reason for this topological structure using the ability to perform a biological functional task as a measure of the efficacy of the network. When the CPG is composed of model neurons which exhibit regular membrane voltage oscillations, open topologies are essentially as able to maximize this functionality as closed topologies. When we replace these models by neurons which exhibit chaotic membrane voltage oscillations, the functional criterion selects closed topologies when the demands of the task are increased, and these are the topologies observed in known CPG networks. As isolated neurons from invertebrate CPGs are known in some cases to undergo chaotic oscillations (Abarbanel et al 1996, Hayashi Ishuzuka 1992) this provides a biological basis for understanding the class of closed network topologies we observe.