The mammalian neocortex is organized into layers which include circuits that form functional columns in cortical maps. A major unsolved problem concerns how bottom-up, top-down, and horizontal interactions are organized within cortical layers to generate adaptive behaviors. This article summarizes a model, called the LAMINART model, of how these interactions help the visual cortex to realize: (1) the binding process whereby cortex groups distribute data into coherent object representations; (2) the attentional process whereby the cortex selectively processes important events; and (3) the developmental and learning processes whereby the cortex stably grows and tunes its circuits to match environmental constraints. Such laminar computing completes perceptual groupings that realize the property of analog coherence, whereby winning groupings bind together their inducing features without losing their ability to represent analog values of these features. Laminar computing also efficiently unifies the computational requirements of preattentive filtering and grouping with those of attentional selection. It hereby shows how adaptive resonance theory (ART) principles may be realized within the laminar circuits of neocortex. Applications include boundary segmentation and surface filling-in algorithms for processing synthetic aperture radar images.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    The laminar architecture of visual cortex and image processing technology


    Contributors:


    Publication date :

    1999-01-01


    Size :

    103493 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    The Laminar Architecture of Visual Cortex and Image Processing Technology

    Grossberg, S. / IEEE | British Library Conference Proceedings | 1999


    Visual Information Processing in the Association Cortex

    Kaji, S. | British Library Online Contents | 1995



    Neural Architecture for Visual Information Processing

    Von Seelen, W. / Bohrer, S. / Kopecz, J. et al. | British Library Online Contents | 1995