A coarse-grained framework for spiking neuronal networks: Between homogeneity and synchrony

Jiwei Zhang, Douglas Zhou, David Cai, Aaditya V. Rangan

Research output: Contribution to journalArticlepeer-review


Homogeneously structured networks of neurons driven by noise can exhibit a broad range of dynamic behavior. This dynamic behavior can range from homogeneity to synchrony, and often incorporates brief spurts of collaborative activity which we call multiple-firing-events (MFEs). These multiple-firing- events depend on neither structured architecture nor structured input, and are an emergent property of the system. Although these MFEs likely play a major role in the neuronal avalanches observed in culture and in vivo, the mechanisms underlying these MFEs cannot easily be captured using current population-dynamics models. In this work we introduce a coarse-grained framework which illustrates certain dynamics responsible for the generation of MFEs. By using a new kind of ensemble-average, this coarse-grained framework can not only address the nucleation of MFEs, but can also faithfully capture a broad range of dynamic regimes ranging from homogeneity to synchrony.

Original languageEnglish (US)
Pages (from-to)81-104
Number of pages24
JournalJournal of Computational Neuroscience
Issue number1
StatePublished - Aug 2014


  • Dynamical systems
  • Homogeneity
  • Multiple firing events
  • Partitioned-ensemble-average
  • Spiking neurons
  • Synchrony

ASJC Scopus subject areas

  • Sensory Systems
  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience


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