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

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 t...

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Veröffentlicht in:PloS one 2011-01, Vol.6 (1), p.e16093-e16093
Hauptverfasser: Vo, Loan T K, Walther, Dirk B, Kramer, Arthur F, Erickson, Kirk I, Boot, Walter R, Voss, Michelle W, Prakash, Ruchika S, Lee, Hyunkyu, Fabiani, Monica, Gratton, Gabriele, Simons, Daniel J, Sutton, Bradley P, Wang, Michelle Y
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container_title PloS one
container_volume 6
creator Vo, Loan T K
Walther, Dirk B
Kramer, Arthur F
Erickson, Kirk I
Boot, Walter R
Voss, Michelle W
Prakash, Ruchika S
Lee, Hyunkyu
Fabiani, Monica
Gratton, Gabriele
Simons, Daniel J
Sutton, Bradley P
Wang, Michelle Y
description 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 will benefit from training in 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 task-switching 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.
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subjects Adolescent
Anatomy
Animal behavior
Basal ganglia
Basal Ganglia - physiology
Bioengineering
Biology
Brain research
Caudate-putamen
Cognitive ability
Cognitive tasks
Computer & video games
Corpus Striatum - physiology
Data mining
Decision Support Techniques
Dopamine
Executive function
Female
Forecasting
Ganglia
Humans
Individuality
Learning
Learning - physiology
Magnetic Resonance Imaging
Male
Medical imaging
Neostriatum
Neuroimaging
Neurology
Neurosciences
NMR
Nuclear magnetic resonance
Pattern recognition
Physiological aspects
Population studies
Predictions
Psychomotor performance
Scanners
Social and Behavioral Sciences
Substantia alba
Substantia grisea
Success
Task complexity
Teaching
Training
Video games
Young Adult
title Predicting individuals' learning success from patterns of pre-learning MRI activity
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