Action video game play facilitates the development of better perceptual templates

Vikranth R. Bejjanki, Ruyuan Zhang, Renjie Li, Alexandre Pouget, C. Shawn Green, Zhong Lin Lu, Daphne Bavelier

Research output: Contribution to journalArticlepeer-review

81 Scopus citations

Abstract

The field of perceptual learning has identified changes in perceptual templates as a powerful mechanism mediating the learning of statistical regularities in our environment. By measuring thresholdvs.- contrast curves using an orientation identification task under varying levels of external noise, the perceptual template model (PTM) allows one to disentangle various sources of signal-to-noise changes that can alter performance. We use the PTM approach to elucidate the mechanism that underlies the wide range of improvements noted after action video game play. We show that action video game players make use of improved perceptual templates compared with nonvideo game players, and we confirm a causal role for action video game play in inducing such improvements through a 50-h training study. Then, by adapting a recent neural model to this task, we demonstrate how such improved perceptual templates can arise from reweighting the connectivity between visual areas. Finally, we establish that action gamers do not enter the perceptual task with improved perceptual templates. Instead, although performance in action gamers is initially indistinguishable from that of nongamers, action gamers more rapidly learn the proper template as they experience the task. Taken together, our results establish for the first time to our knowledge the development of enhanced perceptual templates following action game play. Because such an improvement can facilitate the inference of the proper generative model for the task at hand, unlike perceptual learning that is quite specific, it thus elucidates a general learning mechanism that can account for the various behavioral benefits noted after action game play.

Original languageEnglish (US)
Pages (from-to)16961-16966
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume111
Issue number47
DOIs
StatePublished - Nov 25 2014

Keywords

  • Action video games
  • External noise method
  • Learning
  • Perceptual templates
  • Probabilistic inference

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