Richer Network Dynamics of Intrinsically Non-regular Neurons Measured through Mutual Information

• Authors: Francisco de Borja Rodríguez Ortiz;Pablo Varona;Ramón Huerta;Mikhail I. Rabinovich;Henry D. I. Abarbanel
• Venue: IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
• Year: 2001

Central Pattern Generators (CPGs) are assemblies of neurons that act cooperatively to produce regular signals to motor systems. The individual behavior of some members of the CPGs has often been observed as highly variable spiking-bursting activity. In spite of this fact, the collective behavior of the intact CPG produces always regular rhythmic activity. In this paper we show that simple networks built out of intrinsically non-regular units can display modes of regular collective behavior not observed in networks composed of intrinsically regular neurons. Using a measure of mutual information we characterize several patterns of activity observed by changing the coupling strength and the network topology. We show that the cooperative behavior of these neurons can display a rich variety of information transfer while maintaining the regularity of the rhythms.