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Improved probabilistic inference as a general learning mechanism with action video games

Green, C Shawn
Published in Current Biology. 2010, vol. 20, no. 17, p. 1573-1579
Abstract Action video game play benefits performance in an array of sensory, perceptual, and attentional tasks that go well beyond the specifics of game play [1-9]. That a training regimen may induce improvements in so many different skills is notable because the majority of studies on training-induced learning report improvements on the trained task but limited transfer to other, even closely related, tasks ([10], but see also [11-13]). Here we ask whether improved probabilistic inference may explain such broad transfer. By using a visual perceptual decision making task [14, 15], the present study shows for the first time that action video game experience does indeed improve probabilistic inference. A neural model of this task [16] establishes how changing a single parameter, namely the strength of the connections between the neural layer providing the momentary evidence and the layer integrating the evidence over time, captures improvements in action-gamers behavior. These results were established in a visual, but also in a novel auditory, task, indicating generalization across modalities. Thus, improved probabilistic inference provides a general mechanism for why action video game playing enhances performance in a wide variety of tasks. In addition, this mechanism may serve as a signature of training regimens that are likely to produce transfer of learning.
Keywords Decision MakingHumans*Learning*ProbabilityVisual Perception
PMID: 20833324
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Research group Groupe Alexandre Pouget (938)
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GREEN, C Shawn, POUGET, Alexandre, BAVELIER, Daphné. Improved probabilistic inference as a general learning mechanism with action video games. In: Current Biology, 2010, vol. 20, n° 17, p. 1573-1579. https://archive-ouverte.unige.ch/unige:20631

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Deposited on : 2012-05-22

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