Representation of input structure in synaptic weights by spike-timing-dependent plasticity

Matthieu Gilson, Anthony N. Burkitt, David B. Grayden, Doreen A. Thomas, and J. Leo van Hemmen
Phys. Rev. E 82, 021912 – Published 13 August 2010

Abstract

Spike-timing-dependent plasticity (STDP) has been shown to generate a synaptic weight structure that is determined by the timing of the pre- and postsynaptic spikes at the synapse. In this paper it is shown under what conditions a neuron stimulated by several pools of delta-correlated inputs encodes this input structure in its resulting weight structure. The analysis is carried out using Poisson neurons with weight-dependent STDP. The learning dynamics induced by STDP leads to both stabilization of the input weights and competition between the weights for a broad range of learning parameters. The results demonstrate how weight-dependent STDP can generate multimodal stable asymptotic distributions of the synaptic weights.

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  • Received 31 May 2010

DOI:https://doi.org/10.1103/PhysRevE.82.021912

©2010 American Physical Society

Authors & Affiliations

Matthieu Gilson1,2,3,*, Anthony N. Burkitt1,3, David B. Grayden1,3, Doreen A. Thomas1,2, and J. Leo van Hemmen4,5

  • 1Department of Electrical and Electronic Engineering, The University of Melbourne, Victoria 3010, Australia
  • 2NICTA Victoria Research Lab, The University of Melbourne, Victoria 3010, Australia
  • 3The Bionic Ear Institute, 384–388 Albert St., East Melbourne, Victoria 3002, Australia
  • 4Physik Department T35, Technische Universität München, 85747 Garching bei München, Germany
  • 5BCCN-Munich, Grosshaderner Str. 2, 82152 Martinsried, Germany

  • *gilsonm@unimelb.edu.au

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Vol. 82, Iss. 2 — August 2010

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