September 2019
Volume 19, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2019
Statistical learning enables implicit subadditive predictions
Author Affiliations & Notes
  • Yu Luo
    Department of Psychology, University of British Columbia
  • Jiaying Zhao
    Department of Psychology, University of British Columbia
    Institute for Resources, Environment and Sustainability, University of British Columbia
Journal of Vision September 2019, Vol.19, 187. doi:https://doi.org/10.1167/19.10.187
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      Yu Luo, Jiaying Zhao; Statistical learning enables implicit subadditive predictions. Journal of Vision 2019;19(10):187. doi: https://doi.org/10.1167/19.10.187.

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

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Abstract

The visual system readily detects statistical relationships where multiple cues jointly predict a specific outcome (e.g., two co-authors publishing a paper, or two co-founders starting a company). What is less known is how the visual system generates predictions when only a single cue is present, after learning that the two cues were previously jointly associated with an outcome. Here we examine three hypotheses: (1) complete inheritance hypothesis where the single cue predicts 100% of the outcome previously associated with the two cues, (2) proportional inheritance hypothesis where the single cue predicts 50% of the outcome, and (3) subadditive hypothesis where the single cue predicts more than 50% but less than 100% of the outcome, consistent with support theory (Tversky & Koehler, 1994). To test these hypotheses, we used a statistical learning paradigm where participants were exposed to two objects (e.g., red and blue squares) that were followed by a circle with a specific size. After exposure, participants viewed a single object (e.g., a red square) at a time and were asked to estimate the circle size that was associated with the object. Afterwards, participants recalled the size of the circle that followed the two objects during exposure. We found that the estimated size associated with the single object was significantly smaller than the recalled size associated with the two objects, but significantly larger than 50% of the recalled size (Experiment 1), or larger than 33% of the recalled size in case of three objects (Experiment 2). This confirms the subadditive hypothesis. Importantly, no participants were consciously aware of the association between the objects and the circle size. The results reveal a new consequence of statistical learning on visual inferences: when multiple objects predict a specific outcome, the single object is implicitly expected to predict an outcome in a subadditive fashion.

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