Synaptic model for spontaneous activity in developing networks

Alexander Lerchner, John Rinzel

Research output: Contribution to journalArticle

Abstract

Spontaneous rhythmic activity occurs in many developing neural networks. The activity in these hyperexcitable networks is comprised of recurring "episodes" consisting of "cycles" of high activity that alternate with "silent phases" with little or no activity. We introduce a new model of synaptic dynamics that takes into account that only a fraction of the vesicles stored in a synaptic terminal is readily available for release. We show that our model can reproduce spontaneous rhythmic activity with the same general features as observed in experiments, including a positive correlation between episode length and length of the preceding silent phase.

Original languageEnglish (US)
Pages (from-to)777-782
Number of pages6
JournalNeurocomputing
Volume65-66
Issue numberSPEC. ISS.
DOIs
StatePublished - Jun 1 2005

Keywords

  • Hyperexcitable network
  • Synapse model
  • Synaptic vesicle pools

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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