September 2021
Volume 21, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2021
The adult visual system resists learning continuity violations
Author Affiliations & Notes
  • Dawei Bai
    École Normale Supérieure, PSL Research University, Institut Jean Nicod (ENS, EHESS, CNRS), Paris, France
  • Andreas Falck
    École Normale Supérieure, PSL Research University, Institut Jean Nicod (ENS, EHESS, CNRS), Paris, France
    Lund University, Lund, Sweden
  • Brent Strickland
    École Normale Supérieure, PSL Research University, Institut Jean Nicod (ENS, EHESS, CNRS), Paris, France
  • Footnotes
    Acknowledgements  This research received support from PSL University (IPFBW 2016-151 to B. S.), the Swedish Research Council (2016-06783 to A. F.), Agence Nationale de la Recherche (grants ANR-10-IDEX-0001-02 PSL and ANR-17-EURE-0017 FrontCog) and the European Union (FP/2007-2013; 324115, FRONTSEM; 778077, Orisem).
Journal of Vision September 2021, Vol.21, 2590. doi:https://doi.org/10.1167/jov.21.9.2590
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Dawei Bai, Andreas Falck, Brent Strickland; The adult visual system resists learning continuity violations. Journal of Vision 2021;21(9):2590. https://doi.org/10.1167/jov.21.9.2590.

      Download citation file:


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

      ×
  • Supplements
Abstract

One universal property of our world is that solid objects behave under the principle of continuity: they cannot spontaneously appear or disappear. Consequently, human vision may be equipped with strong prior expectations for this basic principle (Falck et al, 2020; Flombaum & Scholl, 2006). Here, we tested people’s resistance to learning continuity violations after being trained to expect such violations. In Experiment 1, participants performed an object detection task. Each trial first showed a car or an empty space, which was then occluded by an opaque screen. Next, the screen fell, revealing a car or an empty space, and participants responded within 500ms whether the car was present or absent. They first went through a training phase of eight violation trials (i.e., car present at first, absent at reveal, or vice versa) or eight non-violation trials. They were then tested on a violation or non-violation trial. Results showed that after being trained on violations, participants’ accuracy was surprisingly near 100% both when tested on violations and non-violations. Whereas following non-violation training, their accuracy was near 100% for non-violations, 56.0% for violations. This suggests that participants could learn to expect violations through training, but could not learn to override the expectation of a non-violation. Experiment 2 asked participants to predict the car’s presence or absence and give a confidence rating before seeing outcomes in training and test trials (while no longer employing the detection task). Here, following violation training, only 70.6% participants predicted a violation, with an average confidence of 5.41/7, while following non-violation training all participants predicted non-violations (avg. confidence of 6.60/7). Taken together, our studies provide evidence for a strong prior in human vision for expecting continuity and a generic influence of this prior in learning to expect statistically improbable non-violations (Experiment 1) and statistically probable violations (Experiment 2).

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×