Dynamics of lateral interaction networks

It is pointed out that recurrent lateral connectivity in a layer of processing units gives rise to a rich variety of nonlinear response properties, such as overall gain control, emergent periodic response on a preferred spatial scale (collective excitations), and distributed winner-take-all response. This diversity of response properties is observed in several different classes of simple network architectures, including the additive linear network, the additive sigmoidal network, and the nonlinear shunting network. When Hebbian learning is coupled with network dynamics, these models have been shown to support the development of modular connectivity structures analogous to cortical columns