Neural population coding is optimized by discrete tuning curves

Alexander P. Nikitin, Nigel G. Stocks, Robert P Morse, Mark D. McDonnell

Research output: Contribution to journalArticle

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.
Original languageEnglish
Article number138101
Pages (from-to)138101
JournalPhysical Review Letters
Volume103
Issue number13
DOIs
Publication statusPublished - 22 Sep 2009

Bibliographical note

© 2009 The American Physical Society.

Keywords

  • animals
  • humans
  • mammals
  • neurological models
  • neurons
  • Poisson distribution
  • sensory thresholds
  • synaptic transmission

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    Nikitin, A. P., Stocks, N. G., Morse, R. P., & McDonnell, M. D. (2009). Neural population coding is optimized by discrete tuning curves. Physical Review Letters, 103(13), 138101. [138101]. https://doi.org/10.1103/PhysRevLett.103.138101