Spike-timing-dependent synaptic plasticity: from single spikes to spike trains

Christo Panchev, Stefan Wermter

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

We present a neurobiologically motivated model of a neuron with active dendrites and dynamic synapses, and a training algorithm which builds upon single spike-timing-dependent synaptic plasticity derived from neurophysiological evidence. We show that in the presence of a moderate level of noise, the plasticity rule can be extended from single to multiple pre-synaptic spikes and applied to effectively train a neuron in detecting temporal sequences of spike trains. The trained neuron responds reliably under different regimes and types of noise.
Original languageEnglish
Pages (from-to)365-371
Number of pages7
JournalNeurocomputing
Volume58-60
DOIs
Publication statusPublished - Jun 2004
Externally publishedYes

Keywords

  • Spiking neurons
  • Active dendrites
  • Synaptic plasticity
  • Speech and language

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