title: Improved probabilistic inference as a general learning mechanism with action video games.
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.
authors.affiliation: Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14627, USA.
authors.forename: C Shawn
authors.initials: CS
authors.lastname: Green
authors.forename: Alexandre
authors.initials: A
authors.lastname: Pouget
authors.forename: Daphne
authors.initials: D
authors.lastname: Bavelier
mesh_terms: D003657:Decision Making; D006801:Humans; D007858:Learning; D011336:Probability; D014796:Visual Perception