Confidence and metacognition

Kiyofumi Miyoshi; Taylor Webb; Dobromir Rahnev; Hakwan Lau

doi:10.1016/B978-0-12-820480-1.00049-8

Confidence and metacognition

Kiyofumi Miyoshi
, Taylor Webb
, Dobromir Rahnev
, Hakwan Lau

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

2 Scopus citations

Abstract

Humans are not passive recipients of information from the external world. They are “metacognitive” agents, actively engaged in self-referential monitoring of internally expressed information. This introspective insight in turn enables proactive behavioral adjustments, facilitating efficient learning, preventing erroneous actions, and promoting information exchange with others. The study of metacognition has witnessed a recent expansion, incorporating a fusion of computational modeling, neuroimaging, machine learning techniques, and other interdisciplinary approaches. This article serves as an invitation for readers to explore the introspective realm of metacognition, providing an overview of the latest research findings.

Original language	English
Title of host publication	Encyclopedia of the Human Brain, Second Edition
Subtitle of host publication	Volumes 1-5
Publisher	Elsevier
Pages	V3-252-V3-268
ISBN (Electronic)	9780128204818
ISBN (Print)	9780128204801
DOIs	https://doi.org/10.1016/B978-0-12-820480-1.00049-8
State	Published - 1 Jan 2024
Externally published	Yes

Keywords

Bayesian inference
Cognitive bias
Consciousness
Decision-making
Evidence accumulation
fMRI
Heuristic
Machine learning
Metacognition
Metamemory
Neuroimaging
Perceptual decision-making
Prefrontal cortex
Sensory uncertainty
Signal detection theory
Visual awareness

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10.1016/B978-0-12-820480-1.00049-8

Cite this

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title = "Confidence and metacognition",

abstract = "Humans are not passive recipients of information from the external world. They are “metacognitive” agents, actively engaged in self-referential monitoring of internally expressed information. This introspective insight in turn enables proactive behavioral adjustments, facilitating efficient learning, preventing erroneous actions, and promoting information exchange with others. The study of metacognition has witnessed a recent expansion, incorporating a fusion of computational modeling, neuroimaging, machine learning techniques, and other interdisciplinary approaches. This article serves as an invitation for readers to explore the introspective realm of metacognition, providing an overview of the latest research findings.",

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AU - Webb, Taylor

AU - Rahnev, Dobromir

AU - Lau, Hakwan

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KW - Bayesian inference

KW - Cognitive bias

KW - Consciousness

KW - Decision-making

KW - Evidence accumulation

KW - fMRI

KW - Heuristic

KW - Machine learning

KW - Metacognition

KW - Metamemory

KW - Neuroimaging

KW - Perceptual decision-making

KW - Prefrontal cortex

KW - Sensory uncertainty

KW - Signal detection theory

KW - Visual awareness

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DO - 10.1016/B978-0-12-820480-1.00049-8

M3 - Chapter

AN - SCOPUS:85190326493

SN - 9780128204801

SP - V3-252-V3-268

BT - Encyclopedia of the Human Brain, Second Edition

PB - Elsevier

ER -

Confidence and metacognition

Abstract

Keywords

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