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Optimal neuronal tuning for finite stimulus spaces

Brown, W. Michael and Bäcker, Alex (2006) Optimal neuronal tuning for finite stimulus spaces. Neural Computation, 18 (7). pp. 1511-1526. ISSN 0899-7667. doi:10.1162/neco.2006.18.7.1511.

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The efficiency of neuronal encoding in sensory and motor systems has been proposed as a first principle governing response properties within the central nervous system. We present a continuation of a theoretical study presented by Zhang and Sejnowski, where the influence of neuronal tuning properties on encoding accuracy is analyzed using information theory. When a finite stimulus space is considered, we show that the encoding accuracy improves with narrow tuning for one- and two-dimensional stimuli. For three dimensions and higher, there is an optimal tuning width.

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Additional Information:© 2006 The MIT Press. Received September 17, 2004; accepted November 1, 2005. Posted Online May 17, 2006. We thank Shawn Martin at Sandia National Laboratories and the reviewers for their guidance in presenting this work. Support for this work was provided by Sandia National Laboratories’ LDRD and Mathematics, Information, and Computational Sciences Program of the U.S. Department of Energy, and Caltech’s Beckman Institute. Sandia is a multi-program laboratory operated by Sandia Corp., a Lockheed Martin Company, for the U.S. Department of Energy’s National Nuclear Security Administration.
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Sandia National LaboratoriesUNSPECIFIED
Department of EnergyUNSPECIFIED
Beckman Institute, CaltechUNSPECIFIED
Issue or Number:7
Record Number:CaltechAUTHORS:BROnc06
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:13263
Deposited By: Tony Diaz
Deposited On:06 Feb 2009 04:18
Last Modified:08 Nov 2021 22:36

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