Nikitin, Alexander P., Stocks, Nigel G., Morse, Robert P. and McDonnell, Mark D. (2009) Neural population coding is optimized by discrete tuning curves. Physical Review Letters, Vol.103 (No.13). Article: 138101. doi:10.1103/PhysRevLett.103.138101 ISSN 0031-9007.

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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.

Item Type:	Journal Article
Subjects:	Q Science > QC Physics
Divisions:	Faculty of Science, Engineering and Medicine > Engineering > Engineering
Journal or Publication Title:	Physical Review Letters
Publisher:	American Physical Society
ISSN:	0031-9007
Official Date:	25 September 2009
Dates:	Date Event 25 September 2009 Published
Volume:	Vol.103
Number:	No.13
Number of Pages:	4
Page Range:	Article: 138101
DOI:	10.1103/PhysRevLett.103.138101
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Funder:	Engineering and Physical Sciences Research Council (EPSRC), Australian Research Council
Grant number:	GR/R35650/01 (EPSRC), EP/D05/1894/1 (EPSRC), DP0770747

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