title: Correlation entropy of synaptic input-output dynamics.
abstract: The responses of synapses in the neocortex show highly stochastic and nonlinear behavior. The microscopic dynamics underlying this behavior, and its computational consequences during natural patterns of synaptic input, are not explained by conventional macroscopic models of deterministic ensemble mean dynamics. Here, we introduce the correlation entropy of the synaptic input-output map as a measure of synaptic reliability which explicitly includes the microscopic dynamics. Applying this to experimental data, we find that cortical synapses show a low-dimensional chaos driven by the natural input pattern.
authors.affiliation: Department of Physiology, University of Cambridge, Downing Street, Cambridge, CB2 3EG, United Kingdom.
authors.forename: Ingo C
authors.initials: IC
authors.lastname: Kleppe
authors.forename: Hugh P C
authors.initials: HP
authors.lastname: Robinson
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D003198:Computer Simulation; D019277:Entropy; D008564:Membrane Potentials / Q000502:physiology*; D008959:Models, Neurological; D015233:Models, Statistical; D019579:Neocortex / Q000502:physiology*; D009473:Neuronal Plasticity / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D013269:Stochastic Processes; D013569:Synapses / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology*