Doubly Bayesian analysis of confidence in perceptual decision-making

Humans stand out from other animals in that they are able to explicitly report on the reliability of their internal operations. This ability, which is known as metacognition, is typically studied by asking people to report their confidence in the correctness of some decision. However, the computatio...

Full description

Bibliographic Details
Main Authors: Aitchison, L, Bang, D, Bahrami, B, Latham, P
Format: Journal article
Published: Public Library of Science 2015
_version_ 1797075359456296960
author Aitchison, L
Bang, D
Bahrami, B
Latham, P
author_facet Aitchison, L
Bang, D
Bahrami, B
Latham, P
author_sort Aitchison, L
collection OXFORD
description Humans stand out from other animals in that they are able to explicitly report on the reliability of their internal operations. This ability, which is known as metacognition, is typically studied by asking people to report their confidence in the correctness of some decision. However, the computations underlying confidence reports remain unclear. In this paper, we present a fully Bayesian method for directly comparing models of confidence. Using a visual two-interval forced-choice task, we tested whether confidence reports reflect heuristic computations (e.g. the magnitude of sensory data) or Bayes optimal ones (i.e. how likely a decision is to be correct given the sensory data). In a standard design in which subjects were first asked to make a decision, and only then gave their confidence, subjects were mostly Bayes optimal. In contrast, in a less-commonly used design in which subjects indicated their confidence and decision simultaneously, they were roughly equally likely to use the Bayes optimal strategy or to use a heuristic but suboptimal strategy. Our results suggest that, while people’s confidence reports can reflect Bayes optimal computations, even a small unusual twist or additional element of complexity can prevent optimality.
first_indexed 2024-03-06T23:49:21Z
format Journal article
id oxford-uuid:720e58fb-eefe-4006-9c8f-6b9380b3d043
institution University of Oxford
last_indexed 2024-03-06T23:49:21Z
publishDate 2015
publisher Public Library of Science
record_format dspace
spelling oxford-uuid:720e58fb-eefe-4006-9c8f-6b9380b3d0432022-03-26T19:47:47ZDoubly Bayesian analysis of confidence in perceptual decision-makingJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:720e58fb-eefe-4006-9c8f-6b9380b3d043Symplectic Elements at OxfordPublic Library of Science2015Aitchison, LBang, DBahrami, BLatham, PHumans stand out from other animals in that they are able to explicitly report on the reliability of their internal operations. This ability, which is known as metacognition, is typically studied by asking people to report their confidence in the correctness of some decision. However, the computations underlying confidence reports remain unclear. In this paper, we present a fully Bayesian method for directly comparing models of confidence. Using a visual two-interval forced-choice task, we tested whether confidence reports reflect heuristic computations (e.g. the magnitude of sensory data) or Bayes optimal ones (i.e. how likely a decision is to be correct given the sensory data). In a standard design in which subjects were first asked to make a decision, and only then gave their confidence, subjects were mostly Bayes optimal. In contrast, in a less-commonly used design in which subjects indicated their confidence and decision simultaneously, they were roughly equally likely to use the Bayes optimal strategy or to use a heuristic but suboptimal strategy. Our results suggest that, while people’s confidence reports can reflect Bayes optimal computations, even a small unusual twist or additional element of complexity can prevent optimality.
spellingShingle Aitchison, L
Bang, D
Bahrami, B
Latham, P
Doubly Bayesian analysis of confidence in perceptual decision-making
title Doubly Bayesian analysis of confidence in perceptual decision-making
title_full Doubly Bayesian analysis of confidence in perceptual decision-making
title_fullStr Doubly Bayesian analysis of confidence in perceptual decision-making
title_full_unstemmed Doubly Bayesian analysis of confidence in perceptual decision-making
title_short Doubly Bayesian analysis of confidence in perceptual decision-making
title_sort doubly bayesian analysis of confidence in perceptual decision making
work_keys_str_mv AT aitchisonl doublybayesiananalysisofconfidenceinperceptualdecisionmaking
AT bangd doublybayesiananalysisofconfidenceinperceptualdecisionmaking
AT bahramib doublybayesiananalysisofconfidenceinperceptualdecisionmaking
AT lathamp doublybayesiananalysisofconfidenceinperceptualdecisionmaking