Maintaining grey matter within the hippocampus is important for healthy cognition. Playing 3D-platform video games has previously been shown to promote grey matter in the hippocampus in younger adults. In the current study, we tested the impact of 3D-platform video game training (i.e., Super Mario 64) on grey matter in the hippocampus, cerebellum, and the dorsolateral prefrontal cortex (DLPFC) of older adults. Older adults who were 55 to 75 years of age were randomized into three groups. The video game experimental group (VID; n = 8) engaged in a 3D-platform video game training over a period of 6 months. Additionally, an active control group took a series of self-directed, computerized music (piano) lessons (MUS; n = 12), while a no-contact control group did not engage in any intervention (CON; n = 13). After training, a within-subject increase in grey matter within the hippocampus was significant only in the VID training group, replicating results observed in younger adults. Active control MUS training did, however, lead to a within-subject increase in the DLPFC, while both the VID and MUS training produced growth in the cerebellum. In contrast, the CON group displayed significant grey matter loss in the hippocampus, cerebellum and the DLPFC.
From the oversexualized characters in fighting games, such as Dead or Alive or Ninja Gaiden, to the overuse of the damsel in distress trope in popular titles, such as the Super Mario series, the under- and misrepresentation of females in video games has been well documented in several content analyses. Cultivation theory suggests that long-term exposure to media content can affect perceptions of social realities in a way that they become more similar to the representations in the media and, in turn, impact one’s beliefs and attitudes. Previous studies on video games and cultivation have often been cross-sectional or experimental, and the limited longitudinal work in this area has only considered time intervals of up to 1 month. Additionally, previous work in this area has focused on the effects of violent content and relied on self-selected or convenience samples composed mostly of adolescents or college students. Enlisting a 3 year longitudinal design, the present study assessed the relationship between video game use and sexist attitudes, using data from a representative sample of German players aged 14 and older (N=824). Controlling for age and education, it was found that sexist attitudes-measured with a brief scale assessing beliefs about gender roles in society-were not related to the amount of daily video game use or preference for specific genres for both female and male players. Implications for research on sexism in video games and cultivation effects of video games in general are discussed.
Video games can be played in many different contexts. This study examined associations between coplaying video games between siblings and levels of affection and conflict in the relationship. Participants were 508 adolescents (M age = 16.31 years of age, SD = 1.08) who completed questionnaires on video game use and sibling relationships. Participants were recruited from a large Northwestern city and a moderate city in the Mountain West of the United States. Video games played between siblings were coded by an independent sample to assess levels of physical aggression and prosocial behavior in each game. Playing video games with a sibling was associated with higher levels of sibling affection for both boys and girls, but higher levels of conflict for boys only. Playing a violent video game with a brother was associated with lower levels of conflict in the sibling relationship, whereas playing a prosocial video game was not related to any sibling outcome. The value of video games in sibling relationships will be discussed, with a focus on the type of game and the sex of the adolescent.
In the present longitudinal study, we aimed to investigate video game training associated neuronal changes in reward processing using functional magnetic resonance imaging (fMRI). We recruited 48 healthy young participants which were assigned to one of 2 groups: A group in which participants were instructed to play a commercial video game (“Super Mario 64 DS”) on a portable Nintendo DS handheld console at least 30minutes a day over a period of two months (video gaming group; VG) or to a matched passive control group (CG). Before and after the training phase, in both groups, fMRI imaging was conducted during passively viewing reward and punishment-related videos sequences recorded from the trained video game. The results show that video game training may lead to reward related decrease in neuronal activation in the dorsolateral prefrontal cortex (DLPFC) and increase in the hippocampus. Additionally, the decrease in DLPFC activation was associated with gaming related parameters experienced during playing. Specifically, we found that in the VG, gaming related parameters like performance, experienced fun and frustration (assessed during the training period) were correlated to decrease in reward related DLPFC activity. Thus, neuronal changes in terms of video game training seem to be highly related to the appetitive character and reinforcement schedule of the game. Those neuronal changes may also be related to the often reported video game associated improvements in cognitive functions.
In line with Allen Newell’s challenge to develop complete cognitive architectures, and motivated by a recent proposal for a unifying subsymbolic computational theory of cognition, we introduce the cognitive control architecture SEMLINCS. SEMLINCS models the development of an embodied cognitive agent that learns discrete production rule-like structures from its own, autonomously gathered, continuous sensorimotor experiences. Moreover, the agent uses the developing knowledge to plan and control environmental interactions in a versatile, goal-directed, and self-motivated manner. Thus, in contrast to several well-known symbolic cognitive architectures, SEMLINCS is not provided with production rules and the involved symbols, but it learns them. In this paper, the actual implementation of SEMLINCS causes learning and self-motivated, autonomous behavioral control of the game figure Mario in a clone of the computer game Super Mario Bros. Our evaluations highlight the successful development of behavioral versatility as well as the learning of suitable production rules and the involved symbols from sensorimotor experiences. Moreover, knowledge- and motivation-dependent individualizations of the agents' behavioral tendencies are shown. Finally, interaction sequences can be planned on the sensorimotor-grounded production rule level. Current limitations directly point toward the need for several further enhancements, which may be integrated into SEMLINCS in the near future. Overall, SEMLINCS may be viewed as an architecture that allows the functional and computational modeling of embodied cognitive development, whereby the current main focus lies on the development of production rules from sensorimotor experiences.
Sonic Hedgehog (Shh) pathway is physiologically activated during embryogenesis and development. It plays a role in idiopathic lung fibrosis and is also activated in several solid cancers.
Estimating affective and cognitive states in conditions of rich human-computer interaction, such as in games, is a field of growing academic and commercial interest. Entertainment and serious games can benefit from recent advances in the field as, having access to predictors of the current state of the player (or learner) can provide useful information for feeding adaptation mechanisms that aim to maximize engagement or learning effects. In this paper, we introduce a large data corpus derived from 58 participants that play the popular Super Mario Bros platform game and attempt to create accurate models of player experience for this game genre. Within the view of the current research, features extracted both from player gameplay behavior and game levels, and player visual characteristics have been used as potential indicators of reported affect expressed as pairwise preferences between different game sessions. Using neuroevolutionary preference learning and automatic feature selection, highly accurate models of reported engagement, frustration, and challenge are constructed (model accuracies reach 91%, 92%, and 88% for engagement, frustration, and challenge, respectively). As a step further, the derived player experience models can be used to personalize the game level to desired levels of engagement, frustration, and challenge as game content is mapped to player experience through the behavioral and expressivity patterns of each player.
Oak forests support a rich ecology of fellow travellers, but how do these fare when the forests move during glacial cycles? The answers revealed by a new study are important for ecology, but being able to get answers at all highlights a turning point in evolutionary inference.