title: Impact of neuronal properties on network coding: roles of spike initiation dynamics and robust synchrony transfer.
abstract: Neural networks are more than the sum of their parts, but the properties of those parts are nonetheless important. For instance, neuronal properties affect the degree to which neurons receiving common input will spike synchronously, and whether that synchrony will propagate through the network. Stimulus-evoked synchrony can help or hinder network coding depending on the type of code. In this Perspective, we describe how spike initiation dynamics influence neuronal input-output properties, how those properties affect synchronization, and how synchronization affects network coding. We propose that synchronous and asynchronous spiking can be used to multiplex temporal (synchrony) and rate coding and discuss how pyramidal neurons would be well suited for that task.
authors.affiliation: Neurosciences and Mental Health, The Hospital for Sick Children and Department of Physiology, University of Toronto, Toronto, ON M5G 1X8, Canada.
authors.forename: Stéphanie
authors.initials: S
authors.lastname: Ratté
authors.forename: Sungho
authors.initials: S
authors.lastname: Hong
authors.forename: Erik
authors.initials: E
authors.lastname: De Schutter
authors.forename: Steven A
authors.initials: SA
authors.lastname: Prescott
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics