Synchrony and asynchrony in a fully stochastic neural network

R. E.Lee DeVille, Charles S. Peskin

Research output: Contribution to journalArticlepeer-review


We describe and analyze a model for a stochastic pulse-coupled neural network, in which the randomness in the model corresponds to synaptic failure and random external input. We show that the network can exhibit both synchronous and asynchronous behavior, and surprisingly, that there exists a range of parameters for which the network switches spontaneously between synchrony and asynchrony. We analyze the associated mean-field model and show that the switching parameter regime corresponds to a bistability in the mean field, and that the switches themselves correspond to rare events in the stochastic system.

Original languageEnglish (US)
Pages (from-to)1608-1633
Number of pages26
JournalBulletin of Mathematical Biology
Issue number6
StatePublished - Aug 2008


  • Bistability
  • Mean-field analysis
  • Neural network
  • Neuronal network
  • Rare events
  • Stochastic integrate-and-fire
  • Synchronization

ASJC Scopus subject areas

  • General Neuroscience
  • Immunology
  • General Mathematics
  • General Biochemistry, Genetics and Molecular Biology
  • General Environmental Science
  • Pharmacology
  • General Agricultural and Biological Sciences
  • Computational Theory and Mathematics


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