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Related Experiment Video

Updated: Jun 6, 2025

A Two-interval Forced-choice Task for Multisensory Comparisons

A Two-interval Forced-choice Task for Multisensory Comparisons

Published on: November 9, 2018

Challenging the Bayesian confidence hypothesis in perceptual decision-making.

Kai Xue¹, Medha Shekhar¹, Dobromir Rahnev¹

¹School of Psychology, Georgia Institute of Technology, Atlanta, GA 30332.

Proceedings of the National Academy of Sciences of the United States of America

|November 22, 2024

Summary

Confidence judgments may not rely on complex probability calculations. New research suggests confidence in raw evidence space (CRES) is a better model than the Bayesian confidence hypothesis (BCH) for perceptual tasks.

Keywords:

confidence computation perceptual decision-making signal detection theory visual metacognition

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Area of Science:

Cognitive Psychology
Neuroscience
Decision Making

Background:

The Bayesian confidence hypothesis (BCH) is a prominent theory of confidence, suggesting it reflects posterior probability.
BCH faces challenges in complex tasks, while the confidence in raw evidence space (CRES) hypothesis offers an alternative.
CRES posits confidence is based on raw sensory evidence, bypassing explicit probability computations.

Purpose of the Study:

To test competing Bayesian confidence hypothesis (BCH) and confidence in raw evidence space (CRES) models.
To investigate confidence judgments in perceptual tasks with Gaussian evidence distributions.
To determine whether task difficulty information can differentiate between BCH and CRES.

Main Methods:

Designed perceptual tasks to induce Gaussian evidence distributions.
Collected behavioral data across three experiments examining confidence judgments.
Conducted extensive model comparisons of 16 variants implementing BCH and CRES.

Main Results:

Behavioral signatures distinguishing BCH from CRES were observed even in simple 2-choice tasks.
All experiments showed results consistent with CRES computations, contradicting BCH predictions.
CRES models outperformed BCH models across all variants and experiments.

Conclusions:

Findings challenge the dominance of the Bayesian confidence hypothesis (BCH) for confidence judgments.
Evidence strongly supports the confidence in raw evidence space (CRES) hypothesis.
Suggests humans may base confidence on sensory evidence criteria directly, not posterior probabilities.