title: Nonlinear-dynamics theory of up-down transitions in neocortical neural networks.
abstract: The neurons of the neocortex show ~1-Hz synchronized transitions between an active up state and a quiescent down state. The up-down state transitions are highly coherent over large sections of the cortex, yet they are accompanied by pronounced, incoherent noise. We propose a simple model for the up-down state oscillations that allows analysis by straightforward dynamical systems theory. An essential feature is a nonuniform network geometry composed of groups of excitatory and inhibitory neurons with strong coupling inside a group and weak coupling between groups. The enhanced deterministic noise of the up state appears as the natural result of the proximity of a partial synchronization transition. The synchronization transition takes place as a function of the long-range synaptic strength linking different groups of neurons.
authors.affiliation: Department of Physics and Astronomy, University of California, Los Angeles, Los Angeles, California 90095-1547, USA.
authors.forename: Maryam
authors.initials: M
authors.lastname: Ghorbani
authors.forename: Mayank
authors.initials: M
authors.lastname: Mehta
authors.forename: Robijn
authors.initials: R
authors.lastname: Bruinsma
authors.forename: Alex J
authors.initials: AJ
authors.lastname: Levine
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D001683:Biological Clocks / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D008959:Models, Neurological; D019579:Neocortex / Q000502:physiology*; D009415:Nerve Net / Q000502:physiology*; D009434:Neural Pathways / Q000502:physiology; D009435:Synaptic Transmission / Q000502:physiology*