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Phys. Rev. E 73, 051907 (2006) [8 pages]

Persistent dynamic attractors in activity patterns of cultured neuronal networks

Daniel A. Wagenaar
Department of Physics, California Institute of Technology, Pasadena, California 91125, USA

Zoltan Nadasdy
Division of Biology, California Institute of Technology, Pasadena, California 91125, USA

Steve M. Potter
Laboratory of Neuroengineering, Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30332, USA
Received 31 January 2006; published 11 May 2006

Three remarkable features of the nervous system—complex spatiotemporal patterns, oscillations, and persistent activity—are fundamental to such diverse functions as stereotypical motor behavior, working memory, and awareness. Here we report that cultured cortical networks spontaneously generate a hierarchical structure of periodic activity with a strongly stereotyped population-wide spatiotemporal structure demonstrating all three fundamental properties in a recurring pattern. During these "superbursts," the firing sequence of the culture periodically converges to a dynamic attractor orbit. Precursors of oscillations and persistent activity have previously been reported as intrinsic properties of the neurons. However, complex spatiotemporal patterns that are coordinated in a large population of neurons and persist over several hours—and thus are capable of representing and preserving information—cannot be explained by known oscillatory properties of isolated neurons. Instead, the complexity of the observed spatiotemporal patterns implies large-scale self-organization of neurons interacting in a precise temporal order even in vitro, in cultures usually considered to have random connectivity.

©2006 The American Physical Society

URL: http://link.aps.org/doi/10.1103/PhysRevE.73.051907
DOI: 10.1103/PhysRevE.73.051907
PACS: 87.18.-h; 87.19.La
  • 87.18.-h
    Multicellular phenomena
  • 87.19.La
    Neuroscience (higher organisms)
  • YEAR: 2006
KEYWORDS: neurophysiology, bioelectric phenomena, neural nets, spatiotemporal phenomena, oscillations

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