The ubiquity of video games in today's society has led to significant interest in their impact on the brain and behavior and in the possibility of harnessing games for good. The present meta-analyses focus on one specific game genre that has been of particular interest to the scientific community-action video games, and cover the period 2000-2015. To assess the long-lasting impact of action video game play on various domains of cognition, we first consider cross-sectional studies that inform us about the cognitive profile of habitual action video game players, and document a positive average effect of about half a standard deviation (g = 0.55). We then turn to long-term intervention studies that inform us about the possibility of causally inducing changes in cognition via playing action video games, and show a smaller average effect of a third of a standard deviation (g = 0.34). Because only intervention studies using other commercially available video game genres as controls were included, this latter result highlights the fact that not all games equally impact cognition. Moderator analyses indicated that action video game play robustly enhances the domains of top-down attention and spatial cognition, with encouraging signs for perception. Publication bias remains, however, a threat with average effects in the published literature estimated to be 30% larger than in the full literature. As a result, we encourage the field to conduct larger cohort studies and more intervention studies, especially those with more than 30 hours of training. (PsycINFO Database Record
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Sci Rep
January 2025
Department of Electrical and Computer Engineering, Hawassa University, Hawassa 05, Ethiopia.
Understanding human behavior and human action recognition are both essential components of effective surveillance video analysis for the purpose of guaranteeing public safety. However, existing approaches such as three-dimensional convolutional neural networks (3D CNN) and two-stream neural networks (2SNN) have computational hurdles due to the significant parameterization they require. In this paper, we offer HARNet, a specialized lightweight residual 3D CNN that is built on directed acyclic graphs and was created expressly to handle these issues and achieve effective human action detection.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
University of Michigan Medical School, Ann Arbor, MI, USA.
Background: Cognitive changes affecting performance are subtle in early stages of Alzheimer's Disease (AD) and may emerge only with more complex tasks. Driving is a highly challenging instrumental activity of daily living, requiring higher order integration of cognitive skills. For example, driving on freeway entrance ramps requires heightened cognitive engagement such as rapid responses to fast-emerging traffic and sudden speed changes, combining sensory processing and manipulative actions.
View Article and Find Full Text PDFBackground: The impact of depressive symptoms on everyday function in older adults remains poorly understood. Depression may decrease motivation, impair cognition, and/or bias self-reports of functional ability. The present study examined relations between depressive symptoms and everyday function as measured by self-report, informant-report, and an objective performance-based measure which evaluates functional/cognitive capacity but requires only minimal motivation.
View Article and Find Full Text PDFBehav Res Methods
January 2025
Neuroscience of Perception and Action Lab, Italian Institute of Technology (IIT), Viale Regina Elena 291, 00161, Rome, Italy.
Estimating how the human body moves in space and time-body kinematics-has important applications for industry, healthcare, and several research fields. Gold-standard methodologies capturing body kinematics are expensive and impractical for naturalistic recordings as they rely on infrared-reflective wearables and bulky instrumentation. To overcome these limitations, several algorithms have been developed to extract body kinematics from plain video recordings.
View Article and Find Full Text PDFLinguist Vanguard
December 2024
Université Paris Cité, CNRS, Laboratoire de linguistique formelle, F-75013 Paris, France.
We present a new paradigm investigating social meaning through strategic action. More precisely, we present an experimental technique (a textual role-playing game developed with the Ren'Py engine), which we view as an enrichment of the matched-guise technique (MGT). In this paradigm the explicit response scales of the MGT are substituted for strategic choices in a video game.
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