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The European Physical Journal Special Topics

, Volume 227, Issue 10–11, pp 1029–1038 | Cite as

Dynamics of map-based neuronal network with modified spike-timing-dependent plasticity

  • A. V. Andreev
  • E. N. Pitsik
  • V. V. Makarov
  • A. N. Pisarchik
  • A. E. HramovEmail author
Regular Article
Part of the following topical collections:
  1. Advances in Nonlinear Dynamics of Complex Networks: Adaptivity, Stochasticity, Delays

Abstract

The effect of adaptive coupling is studied in a neural network of randomly-coupled Rulkov maps. As an adaptive mechanism, we propose a modified spike-timing-dependent plasticity (STDP) rule with implemented homeostatic property. The comparison of the results of classical and modified STDP shows that the implication of homeostatic property results in significant changes in the network dynamics. Moreover, the neural network with modified STPD demonstrates much more pronounced dynamical changes when internal noise and stimulus amplitudes are varied. The use of the modified rule also leads to decreasing coherence and characteristic correlation time in the system.

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Copyright information

© EDP Sciences, Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • A. V. Andreev
    • 1
  • E. N. Pitsik
    • 1
  • V. V. Makarov
    • 1
  • A. N. Pisarchik
    • 1
    • 2
  • A. E. Hramov
    • 1
    Email author
  1. 1.REC “Artificial Intelligence Systems and Neurotechnology”, Yuri Gagarin State Technical University of SaratovSaratovRussia
  2. 2.Center for Biomedical Technology, Technical University of Madrid, Campus MontegancedoMadridSpain

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