title: Neural population coding is optimized by discrete tuning curves.
abstract: The sigmoidal tuning curve that maximizes the mutual information for a Poisson neuron, or population of Poisson neurons, is obtained. The optimal tuning curve is found to have a discrete structure that results in a quantization of the input signal. The number of quantization levels undergoes a hierarchy of phase transitions as the length of the coding window is varied. We postulate, using the mammalian auditory system as an example, that the presence of a subpopulation structure within a neural population is consistent with an optimal neural code.
authors.affiliation: School of Engineering, University of Warwick, Coventry CV4 7AL, United Kingdom. a.nikitin@warwick.ac.uk
authors.forename: Alexander P
authors.initials: AP
authors.lastname: Nikitin
authors.forename: Nigel G
authors.initials: NG
authors.lastname: Stocks
authors.forename: Robert P
authors.initials: RP
authors.lastname: Morse
authors.forename: Mark D
authors.initials: MD
authors.lastname: McDonnell
mesh_terms: D000818:Animals; D006801:Humans; D008322:Mammals / Q000502:physiology; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D016012:Poisson Distribution; D012684:Sensory Thresholds; D009435:Synaptic Transmission