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Coding Principles in Adaptation.
Weber, Alison I; Krishnamurthy, Kamesh; Fairhall, Adrienne L.
Afiliação
  • Weber AI; Department of Physiology and Biophysics and Computational Neuroscience Center, University of Washington, Seattle, Washington 98195, USA; email: aiweber@uw.edu, fairhall@uw.edu.
  • Krishnamurthy K; Neuroscience Institute and Center for Physics of Biological Function, Department of Physics, Princeton University, Princeton, New Jersey 08544, USA; email: kameshk@princeton.edu.
  • Fairhall AL; Department of Physiology and Biophysics and Computational Neuroscience Center, University of Washington, Seattle, Washington 98195, USA; email: aiweber@uw.edu, fairhall@uw.edu.
Annu Rev Vis Sci ; 5: 427-449, 2019 09 15.
Article em En | MEDLINE | ID: mdl-31283447
ABSTRACT
Adaptation is a common principle that recurs throughout the nervous system at all stages of processing. This principle manifests in a variety of phenomena, from spike frequency adaptation, to apparent changes in receptive fields with changes in stimulus statistics, to enhanced responses to unexpected stimuli. The ubiquity of adaptation leads naturally to the question What purpose do these different types of adaptation serve? A diverse set of theories, often highly overlapping, has been proposed to explain the functional role of adaptive phenomena. In this review, we discuss several of these theoretical frameworks, highlighting relationships among them and clarifying distinctions. We summarize observations of the varied manifestations of adaptation, particularly as they relate to these theoretical frameworks, focusing throughout on the visual system and making connections to other sensory systems.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Percepção Visual / Adaptação Fisiológica / Modelos Neurológicos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Annu Rev Vis Sci Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Percepção Visual / Adaptação Fisiológica / Modelos Neurológicos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Annu Rev Vis Sci Ano de publicação: 2019 Tipo de documento: Article