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Introduction to spiking neural networks: Information processing, learning and applications

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EN
Abstrakty
EN
The concept that neural information is encoded in the firing rate of neurons has been the dominant paradigm in neurobiology for many years. This paradigm has also been adopted by the theory of artificial neural networks. Recent physiological experiments demonstrate, however, that in many parts of the nervous system, neural code is founded on the timing of individual action potentials. This finding has given rise to the emergence of a new class of neural models, called spiking neural networks. In this paper we summarize basic properties of spiking neurons and spiking networks. Our focus is, specifically, on models of spike-based information coding, synaptic plasticity and learning. We also survey real-life applications of spiking models. The paper is meant to be an introduction to spiking neural networks for scientists from various disciplines interested in spike-based neural processing.
Słowa kluczowe
Wydawca
-
Rocznik
Tom
71
Numer
4
Opis fizyczny
p.409-433,fig.,ref.
Twórcy
autor
  • Institute of Control and Information Engineering, Poznan University of Technology, Poznan, Poland
  • Princeton Neuroscience Institute and Department of Monecular Biology, Princeton University, Princeton, USA
autor
  • Institute of Control and Information Engineering, Poznan University of Technology, Poznan, Poland
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