Abstract

The incoherent-optical-neuron (ION) model, in conjunction with optical weighted interconnections, can be used to implement arbitrarily connected neural networks. The ION model uses two different device responses, an inhibitory response and a nonlinear output response, to realize a complete neuron. We describe the use of this model to implement simple cells of the visual cortex. Such simple cells perform the operations of edge detection, orientation selection, and, in the case of moving objects, direction and speed selection. Hubei and Wiesel¹ model the visual cortex as a hierarchical structure with simple cells as the building blocks. Higher-level operations are modeled as aggregates of simple cells.

© 1990 Optical Society of America