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Article
On the Formation of Persistent States in Neuronal Network Models of Feature Selectivity
Journal of Integrative Neuroscience
  • Evan Haskell, University of Utah
  • Paul C. Bressloff, University of Utah
Document Type
Article
Publication Date
6-1-2003
Keywords
  • Neuronal dynamics,
  • Feature selectivity,
  • Persistent states,
  • Working memory
Disciplines
Abstract
We study the existence and stability of localized activity states in neuronal network models of feature selectivity with either a ring or spherical topology. We find that the neural field has mono-stable, bi-stable, and tri-stable regimes depending on the parameters of the weighting function. In the case of homogeneous inputs, these localized activity states are marginally stable with respect to rotations. The response of a stable equilibrium to an inhomogeneous input is also determined
DOI
10.1142/S0219635203000202
Citation Information
Evan Haskell and Paul C. Bressloff. "On the Formation of Persistent States in Neuronal Network Models of Feature Selectivity" Journal of Integrative Neuroscience Vol. 2 Iss. 1 (2003) p. 103 - 125 ISSN: 0219-6352
Available at: http://works.bepress.com/evan-haskell/47/