Changing viewer perspectives reveals constraints to implicit visual statistical learning

Yuhong V. Jiang, Khena M. Swallow

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Statistical learning-learning environmental regularities to guide behavior-likely plays an important role in natural human behavior. One potential use is in search for valuable items. Because visual statistical learning can be acquired quickly and without intention or awareness, it could optimize search and thereby conserve energy. For this to be true, however, visual statistical learning needs to be viewpoint invariant, facilitating search even when people walk around. To test whether implicit visual statistical learning of spatial information is viewpoint independent, we asked participants to perform a visual search task from variable locations around a monitor placed flat on a stand. Unbeknownst to participants, the target was more often in some locations than others. In contrast to previous research on stationary observers, visual statistical learning failed to produce a search advantage for targets in high-probable regions that were stable within the environment but variable relative to the viewer. This failure was observed even when conditions for spatial updating were optimized. However, learning was successful when the rich locations were referenced relative to the viewer.We conclude that changing viewer perspective disrupts implicit learning of the target's location probability. This form of learning shows limited integration with spatial updating or spatiotopic representations.

Original languageEnglish (US)
Article number3
JournalJournal of vision
Volume14
Issue number12
DOIs
StatePublished - 2014

Bibliographical note

Publisher Copyright:
© 2014 ARVO.

Keywords

  • Spatial updating
  • Statistical learning
  • Viewpoint specificity
  • Visual attention

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