PLoS Computational Biology (Dec 2014)

Developmental self-construction and -configuration of functional neocortical neuronal networks.

  • Roman Bauer,
  • Frédéric Zubler,
  • Sabina Pfister,
  • Andreas Hauri,
  • Michael Pfeiffer,
  • Dylan R Muir,
  • Rodney J Douglas

DOI
https://doi.org/10.1371/journal.pcbi.1003994
Journal volume & issue
Vol. 10, no. 12
p. e1003994

Abstract

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The prenatal development of neural circuits must provide sufficient configuration to support at least a set of core postnatal behaviors. Although knowledge of various genetic and cellular aspects of development is accumulating rapidly, there is less systematic understanding of how these various processes play together in order to construct such functional networks. Here we make some steps toward such understanding by demonstrating through detailed simulations how a competitive co-operative ('winner-take-all', WTA) network architecture can arise by development from a single precursor cell. This precursor is granted a simplified gene regulatory network that directs cell mitosis, differentiation, migration, neurite outgrowth and synaptogenesis. Once initial axonal connection patterns are established, their synaptic weights undergo homeostatic unsupervised learning that is shaped by wave-like input patterns. We demonstrate how this autonomous genetically directed developmental sequence can give rise to self-calibrated WTA networks, and compare our simulation results with biological data.