Confidence as Bayesian Probability: From Neural Origins to Behavior

Detalhes bibliográficos
Autor(a) principal: Meyniel, Florent
Data de Publicação: 2015
Outros Autores: Sigman, Mariano, Mainen, Zachary F.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.26/23193
Resumo: 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.
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spelling Confidence as Bayesian Probability: From Neural Origins to BehaviorBayes TheoremCognitionDecision MakingResearch 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.FP7/2007-2013, 604102, Human Brain ProjectRepositório ComumMeyniel, FlorentSigman, MarianoMainen, Zachary F.2018-06-29T15:19:42Z2015-10-072015-10-07T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.26/23193eng10.1016/j.neuron.2015.09.039info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-04-12T17:15:12ZPortal AgregadorONG
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
Bayes Theorem
Cognition
Decision Making
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
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.contributor.none.fl_str_mv Repositório Comum
dc.contributor.author.fl_str_mv Meyniel, Florent
Sigman, Mariano
Mainen, Zachary F.
dc.subject.por.fl_str_mv Bayes Theorem
Cognition
Decision Making
topic Bayes Theorem
Cognition
Decision Making
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 2015-10-07
2015-10-07T00:00:00Z
2018-06-29T15:19:42Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.26/23193
url http://hdl.handle.net/10400.26/23193
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1016/j.neuron.2015.09.039
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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