The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.
Natural statistics support a rational account of confidence biases
Open accessPublished version of a preprint
Abstract
Previous work has sought to understand decision confidence as a prediction of the probability that a decision will be correct, leading to debate over whether these predictions are optimal, and whether they rely on the same decision variable as decisions themselves. This work has generally relied on idealized, low-dimensional models, necessitating strong assumptions about the representations over which confidence is computed. To address this, we used deep neural networks to develop a model of decision confidence that operates directly over high-dimensional, naturalistic stimuli. The model accounts for a number of puzzling dissociations between decisions and confidence, reveals a rational explanation of these dissociations in terms of optimization for the statistics of sensory inputs, and makes the surprising prediction that, despite these dissociations, decisions and confidence depend on a common decision variable.
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“First, a PEB emerges within a convolutional neural network that is trained to both discriminate digits and estimate confidence in these classifications-indicating that a PEB may be not a foible of human metacognition but rather a core feature of how high-dimensional evidence spaces are mapped to propositional confidence (Webb et al. 2023).”
From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Webb et al. 2023
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“indicating that a PEB may be not a foible of human metacognition but rather a core feature of how high-dimensional evidence spaces are mapped to propositional confidence (Webb et al. 2023).”
From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Webb et al. 2023
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Metacognition and Confidence: A Review and Synthesis
Fleming, S. M. (2024) · Annual Review of Psychology · doi:10.1146/annurev-psych-022423-032425 · Cited by 256
“…neural network that is trained to both discriminate digits and estimate confidence in these classifications – indicating that a PEB may not be a foible of human metacognition, but a core feature of how high-dimensional evidence spaces are mapped to propositional confidence (Webb et al., 2023).”
Metacognition and confidence: A review and synthesisPreprint
Fleming, S. M. (2023) · doi:10.31234/osf.io/ge7tz · Cited by 27
On the assumptions behind metacognitive measurements: Implications for theory and practice
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Metacognition of perceptual resolution across and around the visual field
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Metadata
- Authors
- Webb, T. W., Miyoshi, K., So, T. Y., Rajananda, S., & Lau, H.
- Affiliations
- University of California, Los Angeles (US)
- Kyoto University (JP)
- University of Hong Kong (HK)
- Harvard University (US)
- RIKEN Center for Brain Science (JP)
- Corresponding author
- Webb, Taylor W.
- Lau, Hakwan
- Venue
- Nature Communications
- Published
- 2023-07-06
- Volume
- 14
- Issue
- 1
- Pages
- 3992-3992
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC10326055
- OpenAlex
- W4383371132
- Cited by
- 31
- References
- 70
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 7 · 2023: 7
- FWCI
- 4.19
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (F32MH117972)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- decision confidence, rational decision-making, naturalistic stimuli, deep neural network, decision variables
- MeSH terms
- Cognition, Decision Making, Probability, Bias
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