Spiking neural network for recognizing spatiotemporal sequences of spikes

Research output: Contribution to journalArticle

27 Scopus citations

Abstract

A decoding scheme using a spiking neural network for recognizing spatiotemporal sequences of spikes was discussed. The network consists of excitory neurons and two globally inhibitory interneurons of different types that provide delayed feedforward and fast feedback inhibition. It was suggested that the neural network recognition scheme is invariant to variations in the intervals between input spikes within some range. It was also suggested that the proposed network provides a simple way to decode spatiotemporal spikes with diverse types of neurons.

Original languageEnglish (US)
Article number021905
Pages (from-to)021905-1-021905-13
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume69
Issue number2 1
DOIs
StatePublished - Feb 1 2004

All Science Journal Classification (ASJC) codes

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Condensed Matter Physics

Fingerprint Dive into the research topics of 'Spiking neural network for recognizing spatiotemporal sequences of spikes'. Together they form a unique fingerprint.

  • Cite this