December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Quantifying perceptual introspection
Author Affiliations
  • Robbe Goris
    Center for Perceptual Systems, University of Texas at Austin, Austin, TX, USA
Journal of Vision December 2022, Vol.22, 3172. doi:
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      Robbe Goris; Quantifying perceptual introspection. Journal of Vision 2022;22(14):3172.

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

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Perception is fallible, and humans are aware of this. When we experience a high degree of confidence in a perceptual decision, it is more likely to be correct. I will argue that our sense of confidence arises from a computation that requires direct knowledge of the uncertainty of perception, and that it is possible to quantify the quality of this knowledge. I will introduce a new method to assess the reliability of a subject’s estimate of their perceptual uncertainty (i.e., uncertainty about uncertainty, which I term “meta-uncertainty”). Application of this method to a large set of previously published confidence studies reveals that a subject's level of meta-uncertainty is stable over time and across at least some domains. Meta-uncertainty can be manipulated experimentally: it is higher in tasks that involve more levels of stimulus reliability across trials or more volatile stimuli within trials. Meta-uncertainty appears to be largely independent of task difficulty, task structure, response bias, and attentional state. Together, these results suggest that humans intuitively understand the probabilistic nature of perception and automatically evaluate the reliability of perceptual impressions.


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