Stimulus reliability but not boundary distance manipulations violate the folded-X pattern of confidence

The folded-X pattern has been identified as a critical signature of confidence, wherein easier conditions lead to confidence increases for correct trials but confidence decreases for error trials. However, recent work has identified violations of the folded-X pattern where easier conditions lead to increased confidence for both correct and error trials (double-increase pattern). Nevertheless, it remains an open question what stimulus manipulations lead to the folded-X vs. double-increase patterns. Here we test the hypothesis that the double-increase pattern emerges for manipulations of the quality of the sensory input (stimulus reliability), whereas the folded-X pattern emerges for manipulations of the distance between the sensory feature of interest and the decision boundary (boundary distance). Across two experiments (N = 78) using orientation judgment with either Gabor patches or moving dots, we first replicate previous findings that boundary distance manipulations have a stronger effect on accuracy whereas stimulus reliability manipulations have a stronger effect on confidence. Critically, we find that boundary distance manipulations produce the standard folded-X pattern, while the stimulus reliability manipulations result in the double-increase pattern. We further show that reaction time (RT) patterns largely mirror confidence patterns, though with some notable exceptions, highlighting both the utility and limitations of using RT as a proxy for confidence. These results demonstrate that different stimulus manipulations have dissociable effects on the signatures of confidence and could allow researchers to predict a priori whether a new manipulation would lead to the folded-X or the double-increase pattern.

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Publication Details

Published
2025-09-20
DOI
https://doi.org/10.31234/osf.io/865fs_v2
Primary Topic
Probabilistic and Robust Engineering Design
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article
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article

Stimulus reliability but not boundary distance manipulations violate the folded-X pattern of confidence

Dobromir Rahnev, Kai Xue, Herrick Fung
Probabilistic and Robust Engineering Design
article

Stimulus reliability but not boundary distance manipulations violate the folded-X pattern of confidence

Dobromir Rahnev, Kai Xue, Herrick Fung
article en

Abstract

The folded-X pattern has been identified as a critical signature of confidence, wherein easier conditions lead to confidence increases for correct trials but confidence decreases for error trials. However, recent work has identified violations of the folded-X pattern where easier conditions lead to increased confidence for both correct and error trials (double-increase pattern). Nevertheless, it remains an open question what stimulus manipulations lead to the folded-X vs. double-increase patterns. Here we test the hypothesis that the double-increase pattern emerges for manipulations of the quality of the sensory input (stimulus reliability), whereas the folded-X pattern emerges for manipulations of the distance between the sensory feature of interest and the decision boundary (boundary distance). Across two experiments (N = 78) using orientation judgment with either Gabor patches or moving dots, we first replicate previous findings that boundary distance manipulations have a stronger effect on accuracy whereas stimulus reliability manipulations have a stronger effect on confidence. Critically, we find that boundary distance manipulations produce the standard folded-X pattern, while the stimulus reliability manipulations result in the double-increase pattern. We further show that reaction time (RT) patterns largely mirror confidence patterns, though with some notable exceptions, highlighting both the utility and limitations of using RT as a proxy for confidence. These results demonstrate that different stimulus manipulations have dissociable effects on the signatures of confidence and could allow researchers to predict a priori whether a new manipulation would lead to the folded-X or the double-increase pattern.

Openalex Percentile: Top 75%
Probabilistic and Robust Engineering Design
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