Research article summary (published 29 Jun 2006):

Optimal tuning widths in population coding of periodic variables.

Full Abstract

We study the relationship between the accuracy of a large neuronal population in encoding periodic sensory stimuli and the width of the tuning curves of individual neurons in the population. By using general simple models of population activity, we show that when considering one or two periodic stimulus features, a narrow tuning width provides better population encoding accuracy. When encoding more than two periodic stimulus features, the information conveyed by the population is instead maximal for finite values of the tuning width. These optimal values are only weakly dependent on model parameters and are similar to the width of tuning to orientation or motion direction of real visual cortical neurons. A very large tuning width leads to poor encoding accuracy, whatever the number of stimulus features encoded. Thus, optimal coding of periodic stimuli is different from that of nonperiodic stimuli, which, as shown in previous studies, would require infinitely large tuning widths when coding more than two stimulus features.

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Author information

Author/s: Montemurro, Marcelo A (MA); Panzeri, Stefano (S);

Affiliation: Faculty of Life Sciences, University of Manchester, UK. m.montemurro(-atsign-)manchester.ac.uk

Grants: 066372/Z/01/Z (Agency:Wellcome Trust)

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: Neural computation (Neural Comput), published in United States. (Language: eng)

Reference: 2006-Jul; vol 18 (issue 7) : pp 1555-76

Dates: Created 2006/06/12; Completed 2006/07/26; Revised 2007/08/13;

PMID: 16764514, status: MEDLINE (last retrieval date: 12/26/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Action Potentials - physiology Animals Information Theory Models, Neurological Nerve Net - physiology

Nerve Net - physiology Neurons, Afferent - physiology Orientation - physiology Sensory Thresholds - physiology Statistical Distributions

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