Dual coding and effects of global feedback in multilayered neural networks

Naoki Masuda, Kazuyuki Aihara

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The synchronous firing code mode and the population rate code mode can alternatively appear in a single neural network to be dually used depending upon situations. In this paper, we examine by using multi-layered feedforward networks how the preferred coding mode switches as signals pass through layers. It is also shown that global feedback synchronizes neurons in the upstream layers.

Original languageEnglish
Pages (from-to)33-39
Number of pages7
JournalNeurocomputing
Volume58-60
DOIs
Publication statusPublished - 2004 Jun
Externally publishedYes

Keywords

  • Feedback
  • Integrate-and-fire neurons
  • Rate coding
  • Synchrony

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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