Mutual Information, Fisher Information, and Population Coding

Article Properties
  • Language
    English
  • Publication Date
    1998/10/01
  • Indian UGC (Journal)
  • Refrences
    20
  • Citations
    196
  • Nicolas Brunel Laboratoire de Physique Statistique de I'E.N.S., Ecole Normale Supérieure, 75231 Paris Cedex 05, France
  • Jean-Pierre Nadal Laboratoire de Physique Statistique de I'E.N.S., Ecole Normale Supérieure, 75231 Paris Cedex 05, France
Abstract
Cite
Brunel, Nicolas, and Jean-Pierre Nadal. “Mutual Information, Fisher Information, and Population Coding”. Neural Computation, vol. 10, no. 7, 1998, pp. 1731-57, https://doi.org/10.1162/089976698300017115.
Brunel, N., & Nadal, J.-P. (1998). Mutual Information, Fisher Information, and Population Coding. Neural Computation, 10(7), 1731-1757. https://doi.org/10.1162/089976698300017115
Brunel N, Nadal JP. Mutual Information, Fisher Information, and Population Coding. Neural Computation. 1998;10(7):1731-57.
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Medicine
Internal medicine
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Neuropsychiatry
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Description

How do neurons encode information about stimuli? This paper explores the relationship between mutual information and Fisher information in the context of population coding. The study interprets the link between these concepts within information theory, demonstrating that the mutual information between neuronal activity and a stimulus is naturally related to the Fisher information. The results have implications for understanding efficient coding strategies and optimizing the parameters of tuning curves in neural populations responding to angular variables. This research advances our understanding of neural coding and its relationship to information theory.

Published in Neural Computation, this research aligns with the journal's focus on computational and theoretical aspects of neuroscience. The study's exploration of mutual information, Fisher information, and population coding directly contributes to the journal's emphasis on mathematical and computational models of neural systems and their ability to process information. The research offers valuable insights into how neural systems encode and transmit information about stimuli.

Refrences
Citations
Citations Analysis
The first research to cite this article was titled A Systems Perspective on Early Olfactory Coding and was published in 1999. The most recent citation comes from a 2024 study titled A Systems Perspective on Early Olfactory Coding . This article reached its peak citation in 2022 , with 14 citations.It has been cited in 80 different journals, 22% of which are open access. Among related journals, the Neural Computation cited this research the most, with 30 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year