GLOBAL BEHAVIOR OF HOMOGENEOUS RANDOM NEURAL SYSTEMS

We define a simple form of homogeneous neural network model whose characteristics are expressed in terms of probabilistic assumptions. The networks considered operate in an asynchronous manner and receive the influence of the environment in the form of external stimulations. The operation of the network is described by means of a Markovian process whose steady-state solution yields several global measures of the network's activity. Three different types of external stimulations are investigated, which represent possible input mechanisms. The analytical results obtained concern the macroscopic viewpoint and provide a quick insight into the structure of the network's behavior.