title: Optimal heterogeneity for coding in spiking neural networks.
abstract: The effect of cellular heterogeneity on the coding properties of neural populations is studied analytically and numerically. We find that heterogeneity decreases the threshold for synchronization, and its strength is nonlinearly related to the network mean firing rate. In addition, conditions are shown under which heterogeneity optimizes network information transmission for either temporal or rate coding, with high input frequencies leading to different effects for each coding strategy. The results are shown to be robust for more realistic conditions.
authors.affiliation: Department of Physics and Center for Neural Dynamics, University of Ottawa, 150 Louis Pasteur, K1N-6N5 Ottawa, Ontario, Canada. jmejias@uottawa.ca
authors.forename: J F
authors.initials: JF
authors.lastname: Mejias
authors.forename: A
authors.initials: A
authors.lastname: Longtin
mesh_terms: D000200:Action Potentials / Q000502:physiology; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009474:Neurons / Q000502:physiology*