Confidence as Bayesian Probability: From Neural Origins to Behavior

Autores
Meyniel, Florent; Sigman, Mariano; Mainen, Zachary F.
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Research on confidence spreads across several sub-fields of psychology and neuroscience. Here, we explore how a definition of confidence as Bayesian probability can unify these viewpoints. This computational view entails that there are distinct forms in which confidence is represented and used in the brain, including distributional confidence, pertaining to neural representations of probability distributions, and summary confidence, pertaining to scalar summaries of those distributions. Summary confidence is, normatively, derived or “read out” from distributional confidence. Neural implementations of readout will trade off optimality versus flexibility of routing across brain systems, allowing confidence to serve diverse cognitive functions.
Fil: Meyniel, Florent. Inserm; Francia
Fil: Sigman, Mariano. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Mainen, Zachary F.. Champalimaud Centre for the Unknown; Portugal
Materia
Bayesian Probability
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/44539
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Confidence as Bayesian Probability: From Neural Origins to BehaviorMeyniel, FlorentSigman, MarianoMainen, Zachary F.Bayesian Probabilityhttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3Research on confidence spreads across several sub-fields of psychology and neuroscience. Here, we explore how a definition of confidence as Bayesian probability can unify these viewpoints. This computational view entails that there are distinct forms in which confidence is represented and used in the brain, including distributional confidence, pertaining to neural representations of probability distributions, and summary confidence, pertaining to scalar summaries of those distributions. Summary confidence is, normatively, derived or “read out” from distributional confidence. Neural implementations of readout will trade off optimality versus flexibility of routing across brain systems, allowing confidence to serve diverse cognitive functions.Fil: Meyniel, Florent. Inserm; FranciaFil: Sigman, Mariano. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Mainen, Zachary F.. Champalimaud Centre for the Unknown; PortugalCell Press2015-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/44539Meyniel, Florent; Sigman, Mariano; Mainen, Zachary F.; Confidence as Bayesian Probability: From Neural Origins to Behavior; Cell Press; Neuron; 88; 1; 10-2015; 78-920896-6273CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0896627315008284info:eu-repo/semantics/altIdentifier/doi/10.1016/j.neuron.2015.09.039info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T12:00:49Zoai:ri.conicet.gov.ar:11336/44539instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 12:00:49.951CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Confidence as Bayesian Probability: From Neural Origins to Behavior
title Confidence as Bayesian Probability: From Neural Origins to Behavior
spellingShingle Confidence as Bayesian Probability: From Neural Origins to Behavior
Meyniel, Florent
Bayesian Probability
title_short Confidence as Bayesian Probability: From Neural Origins to Behavior
title_full Confidence as Bayesian Probability: From Neural Origins to Behavior
title_fullStr Confidence as Bayesian Probability: From Neural Origins to Behavior
title_full_unstemmed Confidence as Bayesian Probability: From Neural Origins to Behavior
title_sort Confidence as Bayesian Probability: From Neural Origins to Behavior
dc.creator.none.fl_str_mv Meyniel, Florent
Sigman, Mariano
Mainen, Zachary F.
author Meyniel, Florent
author_facet Meyniel, Florent
Sigman, Mariano
Mainen, Zachary F.
author_role author
author2 Sigman, Mariano
Mainen, Zachary F.
author2_role author
author
dc.subject.none.fl_str_mv Bayesian Probability
topic Bayesian Probability
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.1
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Research on confidence spreads across several sub-fields of psychology and neuroscience. Here, we explore how a definition of confidence as Bayesian probability can unify these viewpoints. This computational view entails that there are distinct forms in which confidence is represented and used in the brain, including distributional confidence, pertaining to neural representations of probability distributions, and summary confidence, pertaining to scalar summaries of those distributions. Summary confidence is, normatively, derived or “read out” from distributional confidence. Neural implementations of readout will trade off optimality versus flexibility of routing across brain systems, allowing confidence to serve diverse cognitive functions.
Fil: Meyniel, Florent. Inserm; Francia
Fil: Sigman, Mariano. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Mainen, Zachary F.. Champalimaud Centre for the Unknown; Portugal
description Research on confidence spreads across several sub-fields of psychology and neuroscience. Here, we explore how a definition of confidence as Bayesian probability can unify these viewpoints. This computational view entails that there are distinct forms in which confidence is represented and used in the brain, including distributional confidence, pertaining to neural representations of probability distributions, and summary confidence, pertaining to scalar summaries of those distributions. Summary confidence is, normatively, derived or “read out” from distributional confidence. Neural implementations of readout will trade off optimality versus flexibility of routing across brain systems, allowing confidence to serve diverse cognitive functions.
publishDate 2015
dc.date.none.fl_str_mv 2015-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/44539
Meyniel, Florent; Sigman, Mariano; Mainen, Zachary F.; Confidence as Bayesian Probability: From Neural Origins to Behavior; Cell Press; Neuron; 88; 1; 10-2015; 78-92
0896-6273
CONICET Digital
CONICET
url http://hdl.handle.net/11336/44539
identifier_str_mv Meyniel, Florent; Sigman, Mariano; Mainen, Zachary F.; Confidence as Bayesian Probability: From Neural Origins to Behavior; Cell Press; Neuron; 88; 1; 10-2015; 78-92
0896-6273
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0896627315008284
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.neuron.2015.09.039
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Cell Press
publisher.none.fl_str_mv Cell Press
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.982451

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