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Coding and Information Processing in Neural Networks

  • Chapter
Models of Neural Networks

Part of the book series: Physics of Neural Networks ((NEURAL NETWORKS))

Synopsis

This paper reviews some central notions of the theoretical biophysics of neural networks, viz., information coding through coherent firing of the neurons and spatio-temporal spike patterns. After an introduction to the neural coding problem we first turn to oscillator models and analyze their dynamics in terms of a Lyapunov function. The rest of the paper is devoted to spiking neurons, a pulse code. We review the current neuron models, introduce a new and more flexible one, the spike response model (SRM), and verify that it offers a realistic description of neuronal behavior. The corresponding spike statistics is considered as well. For a network of SRM neurons we present an analytic solution of its dynamics, analyze the possible asymptotic states, and check their stability. Special attention is given to coherent oscillations. Finally we show that Hebbian learning also works for low activity spatio-temporal spike patterns. The models which we study always describe globally connected networks and, thus, have a high degree of feedback. We only touch upon functional feedback, that is, feedback between areas that have different tasks. Information processing in conjunction with functional feedback is treated explicitly in a companion paper [94].

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Authors and Affiliations

  1. Physik-Department der TU München, D-85747, Garching bei München, Germany

    Wulfram Gerstner & J. Leo van Hemmen

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  1. Wulfram Gerstner
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  2. J. Leo van Hemmen
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Editors and Affiliations

  1. Department of Electronics, Weizmann Institute of Science, 76100, Rehovot, Israel

    Eytan Domany

  2. Institut für Theoretische Physik, Technische Universität München, D-85H7, Garching bei München, Germany

    J. Leo van Hemmen

  3. Department of Physics and Beckman, Institute University of Illinois, Urbana, IL, 61801, USA

    Klaus Schulten

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Gerstner, W., van Hemmen, J.L. (1994). Coding and Information Processing in Neural Networks. In: Domany, E., van Hemmen, J.L., Schulten, K. (eds) Models of Neural Networks. Physics of Neural Networks. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4320-5_1

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  • DOI: https://doi.org/10.1007/978-1-4612-4320-5_1

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-8736-0

  • Online ISBN: 978-1-4612-4320-5

  • eBook Packages: Springer Book Archive

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