Modeling the Lateral Cortical Connections and Area V1 to LGN Feedback for Producing Segment Completion, Noise Reduction, and Attentional Effects

Abstract

A network of primary visual cortex simple cells has been modeled to respond to varying degrees of segment orientation contained within an input image. Although these cells receive a significant receptive field input from a grid of model lateral geniculate nucleus (LGN) cells, they also receive inputs from both long-range excitatory and short-range inhibitory lateral connections made with adjacent simple cells. These cortical interactions have the effect of enhancing stronger signals, filling-in missing or incomplete image information, and reducing locally connected noise. This filtering process is facilitated by the modification of the LGN cell responses, each receiving both positive and negative feedback from retinotopically located cortical simple cells. In addition to the aforementioned filtering, adjusting the levels of cortical feedback, as well as the influence of top- down signals, can also produce attentional effects. Simulations with noisy and incomplete images are used to demonstrate the performance of the network model. ©2005 Copyright SPIE - The International Society for Optical Engineering.

Department(s)

Electrical and Computer Engineering

Second Department

Engineering Management and Systems Engineering

Keywords and Phrases

Area V1; Attention; Cortical feedback; Inhibition; Lateral connections; LGN; Visual cortex

International Standard Serial Number (ISSN)

0277-786X

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2024 Society of Photo-optical Instrumentation Engineers, All rights reserved.

Publication Date

01 Dec 1997

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