Cited by 15Visual perception and processing mechanismsNeural and Behavioral Psychology StudiesFace Recognition and Perception

Comparing signal detection models of perceptual decision confidence

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Maniscalco, B., Lau, H.·2010·Journal of Vision

Abstract

Introduction We investigated the mechanisms underlying reports of perceptual confidence. In particular, is all the information used for perceptual decisions available to confidence reporting? Some models of perception suggest that there are multiple channels of information, and subjective reports such as confidence ratings can only tap into one of the channels (e.g. cortical, but not subcortical channels). Is this intuitive view correct? We capitalize on an original psychophysical finding (Lau & Passingham 2006 PNAS) that subjective reports of perceptual confidence and perceptual performance (d') can dissociate, and apply formal model comparison techniques to identify the mechanism underlying confidence reporting. Methods and Results We considered several signal detection theory models, including: A simple SDT model where confidence is determined by setting criteria on the primary decision axis; a late noise model where the noisy perceptual signal becomes even noisier when making confidence judgments; and a two-channel model where only one channel contributes to confidence judgments. We compared models by evaluating the likelihood of each model, given the metacontrast masking data, using the Akaike information criterion. All models could account for perceptual performance, but the late noise model provided the best fit to the observed performance-confidence dissociation. Discussion Our results suggest that simple SDT models may not adequately characterize the relationship between perceptual decisions and confidence, because they do not provide a process that allows for the kind of performance-confidence dissociation observed in the metacontrast masking paradigm. However, this extra process need not be an extra information processing channel. Our best-fitting model was a hierarchical, single-channel model where noisy perceptual signals accrue further noise when used for rating confidence. This suggests that confidence decisions may be made by mechanisms downstream from perceptual decision mechanisms.

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  • If reported confidence is a noisy facsimile of the confidence inherent in a decision process, the relationship between confidence and behavior will weaken, and metacognitive accuracy will decrease.

    “Intuitively, if reported confidence is a noisy facsimile of the confidence inherent in a decision process, the relationship between confidence and behavior will weaken, and metacognitive accuracy will decrease26.”

    From Confidence in value-based choice (2013) · cites this paper as [26]

  • rRLPFC might play a domain-general role in metacognitive evaluation of decision-making.

    “This pattern of findings suggests that rRLPFC might play a domain-general role in metacognitive evaluation of decision-making, supporting the notion of segregated neural process governing metacognitive access22,24,26.”

    From Confidence in value-based choice (2013) · cites this paper as [26]

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Authors
Maniscalco, B., & Lau, H.
Affiliations
Columbia University (US)
Venue
Journal of Vision
Published
2010-08-03
Volume
10
Issue
7
Pages
213-213
ISSN
1534-7362 (ISSN-L)
OpenAlex
W1979623589
Cited by
15
References
0
Citations by year
2026: 1 · 2025: 1 · 2023: 1 · 2020: 2 · 2016: 2 · 2015: 1 · 2014: 1 · 2012: 3
FWCI
1.16
Type
journal article
Language
en
Open access
Locations
Journal of Vision (publishedVersion)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
Keywords
perceptual confidence, signal detection theory, metacontrast masking, confidence ratings, perceptual decision making, two-channel model, hierarchical models, model comparison, Akaike information criterion

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