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Evaluating the Relationship Between White Matter Integrity, Cognition, and Varieties of Video Game Learning

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Evaluating the Relationship Between White Matter Integrity, Cognition, and Varieties of Video Game Learning Restorative Neurology and Neuroscience 35 (2017) 437–456 437 DOI 10.3233/RNN-160716 IOS Press Evaluating the relationship between white matter integrity, cognition, and varieties of video game learning Nicholas R. Raya,b, Margaret A. O’Connella,b, Kaoru Nashiroc, Evan T. Smitha,b, Shuo Qina,b and Chandramallika Basaka,b,∗ aUniversity of Texas at Dallas, Richardson, TX, USA bThe Center for Vital Longevity, Dallas, TX, USA cUniversity of Southern California, Los Angeles, CA, USA Abstract. Background: Many studies are currently researching the effects of video games, particularly in the domain of cognitive training. Great variability exists among video games however, and few studies have attempted to compare different types of video games. Little is known, for instance, about the cognitive processes or brain structures that underlie learning of different genres of video games. Objective: To examine the cognitive and neural underpinnings of two different types of game learning in order to evaluate their common and separate correlates, with the hopes of informing future intervention research. Methods: Participants (31 younger adults and 31 older adults) completed an extensive cognitive battery and played two different genres of video games, one action game and one strategy game, for 1.5 hours each. DTI scans were acquired for each participant, and regional fractional anisotropy (FA) values were extracted using the JHU atlas. Results: Behavioral results indicated that better performance on tasks of working memory and perceptual discrimination was related to enhanced learning in both games, even after controlling for age, whereas better performance on a perceptual speed task was uniquely related with enhanced learning of the strategy game. DTI results indicated that white matter FA in the right fornix/stria terminalis was correlated with action game learning, whereas white matter FA in the left cingulum/hippocampus was correlated with strategy game learning, even after controlling for age. Conclusion: Although cognition, to a large extent, was a common predictor of both types of game learning, regional white matter FA could separately predict action and strategy game learning. Given the neural and cognitive correlates of strategy game learning, strategy games may provide a more beneficial training tool for adults suffering from memory-related disorders or declines in processing speed, particularly older adults. Keywords: Video game, DTI, white matter, learning, cognition, aging Video games have generated a lot of interest in video games as a tool for cognitive enhancement, recent years as a potential tool for cognitive train- they assume that game performance relies on spe- ing, yet little is known about how these video games cific cognitive/brain functioning, yet there is little are associated with various cognitive functions and evidence that establishes such connection between underlying brain structure. When researchers use video game performance, cognitive functioning, and brain structure. This is an important gap in the liter- ∗ Corresponding author: Chandramallika Basak, The Center for ature that needs to be addressed before video games Vital Longevity, 1600 Viceroy Drive, Suite 800, Dallas, TX 75235, USA. Tel.: +1 972 883 3724; Fax: +1 972 883 3250; E-mail: are used as cognitive training tools. Moreover, differ- [email protected]. ent researchers use different genres of video games, 0922-6028/17/$35.00 © 2017 – IOS Press and the authors. All rights reserved 438 N.R. Ray et al. / DTI, cognition, and video game learning which makes this game-cognition-brain relationship All games are not created equal. Many different even more complicated. Therefore, the aim of the genres of games exist, each utilizing a range of diverse current study was not only to evaluate the three- mechanics. Some genres, although less studied, may way game-cognition-brain relationship, but also to provide a more viable means of cognitive improve- assess this relationship for two different types of ment. Strategy games, for example, have been linked games. with better problem-solving skills and higher grades Action games were among the first to be stud- in adolescents (Adachi & Willoughby, 2013). Players ied and have dominated the literature so far. Green of real-time strategy (RTS) games had faster reac- and Bavelier (2003) discovered that action video tion times than FPS players and non-gamers during game players outperformed novices on a range of a task-switching task (Dobrowolski et al., 2015). visual attention tasks, a finding now well replicated Novices trained on real-time strategy (RTS) games (Chisholm, Hickey, Theeuwes, & Kingstone, 2010; have shown improvements in higher-order cognitive Clark, Fleck, & Mitroff, 2011; Feng, Spence, & Pratt, skills, such as, cognitive flexibility in younger adults 2007; Green & Bavelier 2006a, 2006b, 2007; Li, (Glass, Maddox, & Love, 2013), and executive con- Polat, Makous, & Bavelier, 2009; Li, Polat, Scalzo, trol, reasoning and working memory in older adults & Bavelier, 2010; West, Stevens, Pun, & Pratt, 2008). (Basak, Boot, Voss, & Kramer, 2008). In addition, non-gamers trained to play action video Interestingly, older adults show marked deficits, games have been shown to improve on untrained tasks compared to younger adults, in many higher-order of visuo-spatial attention (Feng et al., 2007; Li et al., cognitive skills (e.g., processing speed; Schaie, 1996; 2009; Green & Bavelier 2003, 2006a, 2006b, 2007; episodic memory; Nilsson, 2003; Salthouse, 2003; Green, Pouget, & Bavelier, 2010; Li et al., 2010), working memory; Bopp & Verhaeghen, 2005; spatial though some studies have failed to find such transfer orientation; Schaie, 1996; Sliwinski & Hall, 1998; effects (e.g. Boot, Kramer, Simons, Fabiani, & Grat- reasoning; Schaie, 1996; and task switching; Ver- ton, 2008; see Boot, Blakely, & Simons, 2011 for a haeghen, Steitz, Sliwinski, & Cerella, 2003). Out of review) and others suffer from methodological issues all computerized training approaches, video game (see Simons et al., 2016 for a review). training showed the largest effects on improving cog- Before they were considered for their cogni- nition in the elderly (Hedge’s g = 0.22; Lampit et al., tive benefits, video games were hypothesized by 2014), although there were only four studies reported many researchers to be linked with aggression (e.g., in this meta-analysis. A recent strategy game training Dominick, 1984; Lin & Lepper, 1987), though evi- study on older adults also found benefits to working dence for such an association was highly mixed memory and episodic memory (Toril et al., 2016). (Griffiths, 1999; Sherry, 2001). In an ongoing debate These data suggest that video games are gaining pop- that has now raged for three decades, some stud- ularity as training tools in older adults, yet not much ies have found a relationship between “violent video is known about the underlying brain structure and games” and aggressive behavior/affect (see Anderson cognition that influence learning of these complex et al., 2010; also note the APA’s policy statement on games. violent video games; American Psychological Asso- Based on these findings, we hypothesize that the ciation, 2015), while others argue that the relationship different mechanics employed while playing dif- is minimal or non-existent (see Ferguson, 2015; also ferent types of video games engage an equally note the open statement signed by 230 scholars in diverse range of cognitive processes. Yet few attempts opposition to the APA’s policy statement on violent have been made to compare the cognitive mechan- video games; Przybylski, 2016). Most games that ics involved in playing different types of games. would be classified as “violent” would also be cat- One such attempt has explored the game-cognition egorized as action (e.g. “beat ’em ups,” “shoot ’em relationship, where younger adults briefly played ups,” and “platform blasters”; Griffiths, 1999). It is (∼10–15 mins for each game) twenty different casual interesting that the same games are referred to as “vio- games and performed cognitive tasks (Baniqued lent”, when being discussed in a negative context (i.e. et al., 2013). The 20 games separated on five com- aggression literature), and “action”, when being dis- ponents of a principal components analysis, each cussed in a positive context (i.e., training literature). emphasizing different cognitive constructs. More- This varied use of emotional language when catego- over, training on different games has shown to rizing similar games may reflect a bias by researchers improve different cognitive skills in younger adults in both respective fields. (Oei & Patterson, 2013). The current study examined N.R. Ray et al. / DTI, cognition, and video game learning 439 complex skill learning in two different types of video Because we are assessing game learning in this games, one action and one strategy, over a longer study, we specifically recruited novice gamers who period of time (1.5 hours for each game) compared to had minimal gaming experience at baseline. All Baniqued et al. Also, unlike the previously mentioned participants completed an extensive survey (Basak studies, our sample spans the adult lifespan, including et al., 2008) on their video game playing habits both younger and older adults. In addition to cogni- during the past year. On average, the older adults tion, the current study also examined the relationship reported playing less than 1 hour of video games between game learning and brain structure (i.e.,
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