Parietal plasticity after training with a complex video game is associated with individual differences in improvements in an untrained working memory task

Aki Nikolaidis, Michelle W. Voss, Hyunkyu Lee, Loan T. K. Vo, Arthur F. Kramer

Researchers have devoted considerable attention and resources to cognitive training, yet there have been few examinations of the relationship between individual differences in patterns of brain activity during the training task and training benefits on untrained tasks (i.e., transfer). While a predominant hypothesis suggests that training will transfer if there is training-induced plasticity in brain regions important for the untrained task, this theory lacks sufficient empirical support. To address this issue we investigated the relationship between individual differences in training-induced changes in brain activity during a cognitive training videogame, and whether those changes explained individual differences in the resulting changes in performance in untrained tasks. Forty-five young adults trained with a videogame that challenges working memory, attention, and motor control for 15 2-h sessions. Before and after training, all subjects received neuropsychological assessments targeting working memory, attention, and procedural learning to assess transfer. Subjects also underwent pre- and post-functional magnetic resonance imaging (fMRI) scans while they played the training videogame to assess how these patterns of brain activity change in response to training. For regions implicated in working memory, such as the superior parietal lobe (SPL), individual differences in the post-minus-pre changes in activation predicted performance changes in an untrained working memory task. These findings suggest that training-induced plasticity in the functional representation of a training task may play a role in individual differences in transfer. Our data support and extend previous literature that has examined the association between training related cognitive changes and associated changes in underlying neural networks. We discuss the role of individual differences in brain function in training generalizability and make suggestions for future cognitive training research.