Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/28484
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Type: Conference paper
Title: Optimal quantization in neural coding
Author: McDonnell, M.
Abbott, D.
Citation: Proceedings of the 2004 IEEE International Symposium on Information Theory:pp.494
Publisher: IEEE
Publisher Place: New Jersey, USA
Issue Date: 2004
ISBN: 0780382803
Conference Name: ISIT 2004 (2004 : Chicago, USA)
Editor: Kschischang, F.
Tse, D.
Statement of
Responsibility: 
McDonnell, M.; Abbott, D.
Abstract: In this paper the optimality of the encoding by relaxing the constraint of identical threshold values for each neuron and determining the optimal encoding for a range of SNR's is presented. The population of neurons can be considered a semicontinuous information channel. Using Fisher information that the value of SNR at which bifurcation occurs asymptotically approaches a fixed value of SNR. This result indicates that in the presence of low SNR's, populations of neurons may be able to effectively encode information in a manner similar to a flash analog to digital converter, despite possessing identical thresholds.
Description: Copyright © 2004 IEEE
DOI: 10.1109/ISIT.2004.1365533
Published version: http://dx.doi.org/10.1109/isit.2004.1365533
Appears in Collections:Aurora harvest 6
Electrical and Electronic Engineering publications

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