August 2023
Volume 23, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2023
A common computational principle for decision-making with confidence, expectation and reward
Author Affiliations & Notes
  • yunxuan zheng
    School of Psychology, Georgia Institute of Technology, Atlanta, GA, US
  • Kai Xue
    Carnegie Mellon Neuroscience Institute, Carnegie Mellon University, Pittsburgh, USA
  • Medha Shekhar
    Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, USA
  • Dobromir Rahnev
    The University of Tokyo
  • Footnotes
    Acknowledgements  This work was supported by the National Institute of Health (award: R01MH119189) and the Office of Naval Research (award: N00014-20-1-2622).
Journal of Vision August 2023, Vol.23, 4954. doi:
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      yunxuan zheng, Kai Xue, Medha Shekhar, Dobromir Rahnev; A common computational principle for decision-making with confidence, expectation and reward. Journal of Vision 2023;23(9):4954.

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      © ARVO (1962-2015); The Authors (2016-present)

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Perceptual decisions incorporating expectation or reward information are thought to be the result of a type-1 cognitive process, while confidence judgments are thought to be the result of a type-2, metacognitive process. However, according to signal detection theory (SDT), type-1 decisions with expectation or reward and type-2 confidence can both be generated by the same underlying process. To determine whether type-1 and type-2 decisions are generated by common or different processes, here we collected data from 319 subjects who performed a simple perceptual task and in different conditions had to incorporate expectation cues, reward cues, or provide confidence. SDT assumes that all three conditions involve a similar kind of biased criterion placement and therefore predicts that the shift in criterion in different conditions should correlate across subjects. Confirming this prediction, the magnitude of the criterion shift was significantly above zero across all conditions (all p’s < 0.001) and was positive correlated between conditions. Further, prior research has demonstrated the existence of metacognitive noise that selectively disrupts confidence ratings. This metacognitive noise leads to decreased decision sensitivity (d’) when sensitivity is computed based on the confidence rather than the decision criterion. Here we not only replicated this finding, but also observed an equivalent d’ decrease in trials with reward and expectation cues (all p’s < 0.001). Critically, the magnitude of the d’ decrease in the confidence condition was positively correlated with the equivalent d’ decrease in the cue conditions. Moreover, a simple SDT model with equivalent “metacognitive” noise applied to all conditions reproduced all of these results. These findings provide strong evidence for the existence of a common computational basis for expectation, reward, and confidence in perceptual decision-making, and cast doubt on the existence of a clear distinction between the type-1 cognitive and type-2 metacognitive processes.


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