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A network model for the emergence of orientation maps and local lateral circuits

  • Plasticity Phenomena (Maturing, Learning & Memory)
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Foundations and Tools for Neural Modeling (IWANN 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1606))

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Abstract

We present a nonlinear, recurrent neural network model of the primary visual cortex with separate ON/OFF-pathways and modifiable afferent as well as intracortical synaptic couplings. Orientation maps emerge driven by random input stimuli. Lateral coupling structures self-organize into DOG profiles under the influence of pronounced emerging cortical activity blobs. The model’s architecture and features are, compared with former models, well justified neurobiologically.

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Authors and Affiliations

  1. Institut für Biophysik und physikalische Biochemie, Universität Regensburg, D-93040, Regensburg, Germany

    Thomas Burger & Elmar W. Lang

Authors
  1. Thomas Burger
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  2. Elmar W. Lang
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José Mira Juan V. Sánchez-Andrés

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© 1999 Springer-Verlag Berlin Heidelberg

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Burger, T., Lang, E.W. (1999). A network model for the emergence of orientation maps and local lateral circuits. In: Mira, J., Sánchez-Andrés, J.V. (eds) Foundations and Tools for Neural Modeling. IWANN 1999. Lecture Notes in Computer Science, vol 1606. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0098199

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  • DOI: https://doi.org/10.1007/BFb0098199

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66069-9

  • Online ISBN: 978-3-540-48771-5

  • eBook Packages: Springer Book Archive

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