A FINITE AUTOMATA MODEL OF SPIKING-BURSTING NEURONS

A simple qualitative model of spiking-bursting neurons is proposed. It is mainly built from the qualitative behavior observed in central pattern generators (CPG’s) and pacemaker neurons. It is a finite automata which is convenient for computer modelling even for large neural networks. The number of rules utilized in the finite automata are the minimum necessary to reproduce a great variety of phenomena. The validity of the model is determined using actual experimental measurements between two coupled neurons in CPG’s. We reproduce, in the framework of the model, the dynamic patterns observed in Tritonia’s escape swimming CPG. Finally, we study the dynamics of an open chain of 100 reciprocally coupled “symbolic neurons” and investigate the stable patterns reached with time.