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Confidence-accuracy dissociations in perceptual decision making.

Dobromir Rahnev1

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Confidence-accuracy dissociations, where confidence diverges from accuracy, are key to understanding confidence computation. This review categorizes these dissociations and explores their underlying mechanisms and interpretations.

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Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Computational Modeling

Background:

  • Confidence in perceptual tasks usually correlates with accuracy.
  • Experimental manipulations creating confidence-accuracy dissociations are crucial for studying confidence computation.
  • Existing methods for creating and interpreting these dissociations lack consensus.

Purpose of the Study:

  • To categorize existing confidence-accuracy dissociations.
  • To examine mechanistic explanations for these dissociations.
  • To address confusions and open questions regarding their interpretation.

Main Methods:

  • Review and categorization of existing literature on confidence-accuracy dissociations.
  • Analysis of stimulus, task, and brain manipulations leading to dissociations.
  • Examination of mechanistic explanations and conceptual issues.

Main Results:

  • Confidence-accuracy dissociations can be induced by various manipulations (stimulus, task, brain).
  • Multiple mechanisms underlie these dissociations.
  • Key areas of confusion include the concept of "positive evidence," metacognitive noise, and reaction time.

Conclusions:

  • Confidence-accuracy dissociations are produced by diverse mechanisms.
  • Computational models of confidence should be validated by their ability to predict novel dissociations.
  • Further research is needed to clarify the interpretation and application of confidence-accuracy dissociations.