Neural population coding is optimized by discrete tuning curves


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.

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Divisions: College of Health & Life Sciences > School of Optometry > Audiology
College of Health & Life Sciences > Clinical and Systems Neuroscience
College of Health & Life Sciences
College of Health & Life Sciences > School of Optometry > Vision, Hearing and Language
College of Health & Life Sciences > School of Optometry > Centre for Vision and Hearing Research
Additional Information: © 2009 The American Physical Society.
Uncontrolled Keywords: animals,humans,mammals,neurological models,neurons,Poisson distribution,sensory thresholds,synaptic transmission,Physics and Astronomy(all)
Publication ISSN: 1079-7114
Last Modified: 03 Jan 2024 08:05
Date Deposited: 30 Apr 2012 10:38
Full Text Link: http://link.aps ... Lett.103.138101
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2009-09-22
Authors: Nikitin, Alexander P.
Stocks, Nigel G.
Morse, Robert P
McDonnell, Mark D.



Version: Published Version

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