Skip to main content

Advertisement

Synchronization, multistability and clustering: How useful are predictions from phase models?

Article metrics

  • 816 Accesses

We consider a model of a network of hippocampal interneurons based on the work of Wang and Buzsaki. We construct a phase model representation of the network, and show that this model can give reasonably accurate quantitative information, such as the size of basins of attraction and the maximum heterogeneity permissible in the inherent frequencies of the neurons before synchrony is lost. We show that predictions of existence and stability of the synchronous solution from a two cell network carry over to N-cell networks, either exactly or in the limit of large N.

Author information

Correspondence to Sue Ann Campbell.

Rights and permissions

Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Campbell, S.A., Chadwick, J. Synchronization, multistability and clustering: How useful are predictions from phase models?. BMC Neurosci 8, P46 (2007) doi:10.1186/1471-2202-8-S2-P46

Download citation

Keywords

  • Animal Model
  • Model Representation
  • Quantitative Information
  • Phase Model
  • Cell Network