  We investigate the dynamics of a network consisting of an array of identical
cortical units with nearest neighbor interactions under periodic arousal. Each
unit consists of two interconnected populations of neurons tuned to a state in
which many nonlinear resonances are available. The network is critically
balanced due to short-ranged antisymmetric connections between units. For wide
ranges of the network parameters, the patterns of activity resemble the
dynamics of cellular automata. It is argued that these dynamical states may
provide a template in which computation can be implemented.
