Confidence and Accuracy of Near-Threshold Discrimination Responses

@article{Kunimoto2001ConfidenceAA,
  title={Confidence and Accuracy of Near-Threshold Discrimination Responses},
  author={Craig Kunimoto and Jeff Miller and Harold Pashler},
  journal={Consciousness and Cognition},
  year={2001},
  volume={10},
  pages={294-340}
}
This article reports four subliminal perception experiments using the relationship between confidence and accuracy to assess awareness. Subjects discriminated among stimuli and indicated their confidence in each discrimination response. Subjects were classified as being aware of the stimuli if their confidence judgments predicted accuracy and as being unaware if they did not. In the first experiment, confidence predicted accuracy even at stimulus durations so brief that subjects claimed to be… 
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To understand the origins of confidence judgments, investigators have developed two competing frameworks based on signal decision theory and accumulation of evidence models, which can explain a range of results, including the apparently paradoxical dissociation between performance and confidence.
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It is shown that participants are better able to place their phenomenal states on a binary scale, as compared with a continuous scale, which indicates that confidence was related to accuracy.
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A novel dual-task paradigm incorporating confidence ratings to calculate metacognition and adaptive staircase procedures to reduce training is developed and direct evidence for metacognitive conscious access in the near absence of attention for complex, but not simple, stimuli is shown.
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It is concluded that activity in early visual cortex before unaware trials prevents the upcoming stimulus to activate this area enough to ensure perception and that after response execution unaware trials elicit conflict monitoring (ACC) probably because they are treated as errors.
Doubly Bayesian Analysis of Confidence in Perceptual Decision-Making
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This paper presents a fully Bayesian method for directly comparing models of confidence and suggests that, while people’s confidence reports can reflect Bayes optimal computations, even a small unusual twist or additional element of complexity can prevent optimality.
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