Training in action video games can increase the speed of perceptual processing. However, it is unknown whether video-game training can lead to broad-based changes in higher-level competencies such as cognitive flexibility, a core and neurally distributed component of cognition. To determine whether video gaming can enhance cognitive flexibility and, if so, why these changes occur, the current study compares two versions of a real-time strategy (RTS) game. Using a meta-analytic Bayes factor approach, we found that the gaming condition that emphasized maintenance and rapid switching between multiple information and action sources led to a large increase in cognitive flexibility as measured by a wide array of non-video gaming tasks. Theoretically, the results suggest that the distributed brain networks supporting cognitive flexibility can be tuned by engrossing video game experience that stresses maintenance and rapid manipulation of multiple information sources. Practically, these results suggest avenues for increasing cognitive function.

Rule-based and information-integration category learning were compared under minimal and full feedback conditions. Rule-based category structures are those for which the optimal rule is verbalizable. Information-integration category structures are those for which the optimal rule is not verbalizable. With minimal feedback subjects are told whether their response was correct or incorrect, but are not informed of the correct category assignment. With full feedback subjects are informed of the correctness of their response and are also informed of the correct category assignment. An examination of the distinct neural circuits that subserve rule-based and information-integration category learning leads to the counterintuitive prediction that full feedback should facilitate rulebased learning but should also hinder information-integration learning. This prediction was supported in the experiment reported below. The implications of these results for theories of learning are discussed.

The category shift literature suggests that rule-based classification, an important form of explicit learning, is mediated by two separate learned associations: a stimulus-to-label association that associates stimuli and category labels, and a label-to-response association that associates category labels and responses. Three experiments investigate whether information–integration classification, an important form of implicit learning, is also mediated by two separate learned associations. Participants were trained on a rule-based or an information–integration categorization task and then the association between stimulus and category label, or between category label and response location was altered. For rule-based categories, and in line with previous research, breaking the association between stimulus and category label caused more interference than breaking the association between category label and response location. However, no differences in recovery rate emerged. For information–integration categories, breaking the association between stimulus and category label caused more interference and led to greater recovery than breaking the association between category label and response location. These results provide evidence that information–integration category learning is mediated by separate stimulus-to-label and label-to-response associations. Implications for the neurobiological basis of these two learned associations are discussed.

Dissociable prototype learning systems have been demonstrated behaviorally and with neuroimaging in younger adults as well as with patient populations. In A/not-A (AN) prototype learning, participants are shown members of category A during training, and during test are asked to decide whether novel items are in category A or are not in category A. Research suggests that AN learning is mediated by a perceptual learning system. In A/B (AB) prototype learning, participants are shown members of category A and B during training, and during test are asked to decide whether novel items are in category A or category B. In contrast to AN, research suggests that AB learning is mediated by a declarative memory system. The current study examined the effects of normal aging on AN and AB prototype learning. We observed an age-related deficit in AB learning, but an age-related advantage in AN learning. Computational modeling supports one possible interpretation based on narrower selective attentional focus in older adults in the AB task and broader selective attention in the AN task. Neuropsychological testing in older participants suggested that executive functioning and attentional control were associated with better performance in both tasks. However, nonverbal memory was associated with better AN performance, while visual attention was associated with worse AB performance. The results support an interactive memory systems approach and suggest that age-related declines in one memory system can lead to deficits in some tasks, but to enhanced performance in others.

The findings suggest that the neural systems underlying information-integration strategies are not strongly affected by sleep deprivation but, rather, that the use of an information-integration strategy in a task may require active inhibition of rule-based strategies, with this inhibitory process being vulnerable to the effects of sleep deprivation.