A Neural Network Architecture for Perceptual Grouping, Attention Modulation and Boundary-Surface Interaction

Abstract

A neural network architecture is introduced for context-sensitive binding processing in visual cortex areas such as perceptual grouping, attention and boundary-surface interaction. The present architecture, based on LAMINART and FAÇADE theory, shows how layered circuits in cortex areas enable feedforward, horizontal, and feedback interactions and intractions, together with balanced connections, to complete perceptual groupings with attention modulation. Thus, a pre-attentive/attentive interface for cortex has been established within the same circuits. Moreover, this architecture exhibits the invisible perceptual grouping and visible surface filling-in interaction with complementary computing property, introduced in FAÇADE theory. By implementing SOC filtering, preattentive perception can response well to contrast-sensitive stimuli. Also the simulations illustrates selective propagation of the attention along an object grouping as well as surface filling and the protection of them from competitive masking. At the same time it demonstrates the generation of attention modulation by boundary-surface interactions as well as translation of the attention across complementary visual processing streams.Keywordsperceptual groupingattention modulationboundary-surface interactionSOC filteringcomplementary computing