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Neural model of cortical dynamics in resonant boundary detection and grouping

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Artificial Neural Networks — ICANN 96 (ICANN 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1112))

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Abstract

A new model for visual boundary detection and contour grouping is presented that is based on functional elements of resonant matching of activation between neural layers in cortical architecture. The model architecture relates to visual cortical areas V1 and V2 which are bidirectionally interconnected via feedforward as well as feedback projections. It is suggested that their functionality is primarily determined by the measurement and integration of signal features that are continuously matched against neural codes of expectancies generated by the long-range integration of coherent activity. The net effect produces grouping and illusory contour completion at model V2 as well as context-sensitive shaping of orientation tuning and selectivity of receptive fields at model V1 layer. A pilot implementation of the model architecture has been successfully tested on various test stimuli.

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Authors and Affiliations

  1. Abt. Neuroinformatik, Fakultät f. Informatik, Universität Ulm, D-89069, Ulm, Germany

    Heiko Neumann & Petra Mössner

Authors
  1. Heiko Neumann
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  2. Petra Mössner
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Editor information

Christoph von der Malsburg Werner von Seelen Jan C. Vorbrüggen Bernhard Sendhoff

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© 1996 Springer-Verlag Berlin Heidelberg

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Neumann, H., Mössner, P. (1996). Neural model of cortical dynamics in resonant boundary detection and grouping. In: von der Malsburg, C., von Seelen, W., Vorbrüggen, J.C., Sendhoff, B. (eds) Artificial Neural Networks — ICANN 96. ICANN 1996. Lecture Notes in Computer Science, vol 1112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61510-5_144

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  • DOI: https://doi.org/10.1007/3-540-61510-5_144

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61510-1

  • Online ISBN: 978-3-540-68684-2

  • eBook Packages: Springer Book Archive

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