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A modular attractor model of semantic access

  • Neural Modeling (Biophysical and Structural Models)
  • Conference paper
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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

This paper presents results from lesion experiments on a modular attractor neural network model of semantic access. Real picture data forms the basis of perceptual input to the model. An ultrametric attractor space is used to represent semantic memory and is implemented using a biologically plausible variant of the Hopfield model. Lesioned performance is observed to be in agreement with neuropsychological data. A local field analysis of the attractor states of semantic space forms a basis for interpreting these results.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Hertfordshire, College Lane, AL10 9AB, Hatfield, Hertfordshire, UK

    William Power, Ray Frank & Neil Davey

  2. Department of Psychology, University of Hertfordshire, College Lane, AL10 9AB, Hatfield, Hertfordshire, UK

    John Done

Authors
  1. William Power
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  2. Ray Frank
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  3. John Done
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  4. Neil Davey
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Editor information

José Mira Juan V. Sánchez-Andrés

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© 1999 Springer-Verlag Berlin Heidelberg

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Power, W., Frank, R., Done, J., Davey, N. (1999). A modular attractor model of semantic access. 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/BFb0098190

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  • DOI: https://doi.org/10.1007/BFb0098190

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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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