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Associative Binding and Segregation in a Network of Spiking Neurons

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Models of Neural Networks

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

Synopsis

A model of an associative network of spiking neurons (the Spike Response Model) with stationary states, globally locked oscillations, and weakly locked oscillatory states is presented and analyzed. The network is close to biology in the following sense. First, the neuron spikes and our model includes an absolute refractory period after each spike. Second, we consider a distribution of axonal delay times. Finally, we describe synaptic signal transmission by excitatory and inhibitory potentials (EPSP and IPSP) with a realistic shape, that is, through a response kernel. The patterns have been learned by an asymmetric Hebbian rule that can handle a low activity which may vary from pattern to pattern. During retrieval of a pattern all active neurons exhibit periodic spike bursts which may or may not be synchronized ( “locked” ) into a coherent oscillation. We derive an analytical condition of locking and calculate the period of collective activity during oscillatory retrieval. It is argued that in a biological network an intermediate scenario of “weak locking” is most likely. In this regime, we discuss applications to feature linking and pattern segmentation as well as the problem of context sensitive binding that can be solved in a layered structure including feedback. In addition, we address the question of synchronization between the two hemispheres of the brain.

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Author information

Authors and Affiliations

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

    J. Leo van Hemmen

Authors
  1. Raphael Ritz
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  2. Wulfram Gerstner
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  3. J. Leo van Hemmen
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Editor information

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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Ritz, R., Gerstner, W., van Hemmen, J.L. (1994). Associative Binding and Segregation in a Network of Spiking Neurons. 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_5

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  • DOI: https://doi.org/10.1007/978-1-4612-4320-5_5

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-8736-0

  • Online ISBN: 978-1-4612-4320-5

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