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Processing of Information in Synchroneously Firing Chains in Networks of Neurons

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Artificial Neural Networks – ICANN 2006 (ICANN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4131))

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Abstract

The Abeles model of cortical activity assumes that in absence of stimulation neural activity in zero order can be described by a Poisson process. Here the model is extended to describe information processing by synfire chains within a network of activity uncorrelated to the synfire chain. A quantitative derivation of the transfer function from this concept is given.

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Author information

Authors and Affiliations

  1. Institut für Theoretische Physik und Astrophysik, Christian-Albrechts-Universität zu Kiel, Leibnizstr.15, D-24098, Kiel, Germany

    Jens Christian Claussen

Authors
  1. Jens Christian Claussen
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Editor information

Editors and Affiliations

  1. School of Electrical and Computer Engineering, Image, Video and Multimedia Systems Laboratory, National Technical University of Athens, GR-157 80, Zographou, Greece

    Stefanos D. Kollias

  2. Department of Electrical and Computer Engineering, National Technical University of Athens, 15780, Zographou, Greece

    Andreas Stafylopatis

  3. Department of Informatics, Nicolaus Copernicus University, Toruń, Poland

    Włodzisław Duch

  4. Adaptive Informatics Research Centre, Helsinki University of Technology, HUT, P.O. Box 5400, 02015, Finland

    Erkki Oja

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© 2006 Springer-Verlag Berlin Heidelberg

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Claussen, J.C. (2006). Processing of Information in Synchroneously Firing Chains in Networks of Neurons. In: Kollias, S.D., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840817_74

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  • DOI: https://doi.org/10.1007/11840817_74

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38625-4

  • Online ISBN: 978-3-540-38627-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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