Neural Population Coding is Optimized by Discrete Tuning Curves
Neurons and Cognition
2009-09-24 v2
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.
Cite
@article{arxiv.0809.1549,
title = {Neural Population Coding is Optimized by Discrete Tuning Curves},
author = {Alexander P. Nikitin and Nigel G. Stocks and Robert P. Morse and Mark D. McDonnell},
journal= {arXiv preprint arXiv:0809.1549},
year = {2009}
}
Comments
7 pages total, including 2 figures, published by Physical Review Letters