Modeling and complexity in neural networks

In this paper, we study nonlinear spatio-temporal dynamics in synchronous and asynchronous chaotic neural networks from the viewpoint of the modeling and complexity of the dynamic brain. First, the possible roles and functions of spatio-temporal neurochaos are considered with a model of synchronous chaotic neural networks composed of a neuron model with a chaotic map. Second, deterministic point-process dynamics with spikes of action potentials is demonstrated with a biologically more plausible model of asynchronous chaotic neural networks. Last, the possibilities of inventing a new brain-type of computing system are discussed on the basis of these models of chaotic neural networks. This work was presented, in part, at the Third International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–21, 1998.