Predicting individuals' learning success from patterns of pre-learning MRI activity

Loan T K Vo, Dirk B. Walther, Arthur F. Kramer, Kirk I. Erickson, Walter R. Boot, Michelle W. Voss, Ruchika S. Prakash, Hyunkyu Lee, Monica Fabiani, Gabriele Gratton, Daniel J. Simons, Bradley P. Sutton, Michelle Y. Wang

Research output: Contribution to journalArticlepeer-review


Performance in most complex cognitive and psychomotor tasks improves with training, yet the extent of improvement varies among individuals. Is it possible to forecast the benefit that a person might reap from training? Several behavioral measures have been used to predict individual differences in task improvement, but their predictive power is limited. Here we show that individual differences in patterns of time-averaged T2-weighted MRI images in the dorsal striatum recorded at the initial stage of training predict subsequent learning success in a complex video game with high accuracy. These predictions explained more than half of the variance in learning success among individuals, suggesting that individual differences in neuroanatomy or persistent physiology predict whether and to what extent people e will benefit from trainingin a complex task. Surprisingly, predictions from white matter were highly accurate, while voxels in the gray matter of the dorsal striatum did not contain any information about future training success. Prediction accuracy was higher in the anterior than the posterior half of the dorsal striatum. The link between trainability and the time-averaged T2-weighted signal in the dorsal striatum reaffirms the role of this part of the basal ganglia in learning and executive functions, such as taskswitching and task coordination processes. The ability to predict who will benefit from training by using neuroimaging data collected in the early training phase may have far-reaching implications for the assessment of candidates for specific training programs as well as the study of populations that show deficiencies in learning new skills.

Original languageEnglish (US)
Article numbere16093
JournalPloS one
Issue number1
StatePublished - 2011

ASJC Scopus subject areas

  • General


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