Decorrelation of spike trains by synaptic depression

Mark S Goldman, Sacha B. Nelson, L. F. Abbott

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

Synaptic depression modeled after that seen in cortical slices removes correlations from realistic spike sequences. If not removed, such correlations can lead to inefficient and redundant neural codes. We suggest that this redundancy reduction at individual synapses enables a neuron to better process information from multiple inputs.

Original languageEnglish (US)
Pages (from-to)147-153
Number of pages7
JournalNeurocomputing
Volume26-27
DOIs
StatePublished - Jun 1999
Externally publishedYes

Keywords

  • Correlation
  • Cortical network
  • Short-term plasticity
  • Synaptic depression

ASJC Scopus subject areas

  • Artificial Intelligence
  • Cellular and Molecular Neuroscience

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