Abstract

This paper outlines a theoretical model of attention and cognition using artificial neural network properties, the Sweeping Model. This model includes a sensory memory, a self modifying neural network , a system applying synchronous sweeps of lateral inhibition across the neural network, and a subsystem to evaluate the body state of the system to control this sweep frequency. After further description, it will be argued that these components can result in behaviours such as learning anf performing according to primary and secondary reinforcement rules