Abstract
The primary aim of this study was to investigate to what degree the age-related white matter development, here called "brain age", is associated with working memory (WM) and numeric abilities in 6-year-old children. We measured white matter development using diffusion tensor imaging to calculate fractional anisotropy (FA). A "brain age" model was created using multivariate statistics, which described association between FA and age in a sample of 6- to 20-year-old children. This age model was then applied to predict "brain age" in a second sample of 6-year-old children. The predicted brain age correlated with WM performance and numerical ability (NA) (P < 0.01, P < 0.05) in the 6-year-old children. More than 50% of the stable variance in WM performance was explained. We found that in children older than 13 years of age, this association between brain age and WM was no longer significant (P > 0.5). The results bear theoretical implications as they suggest that the variability in individual developmental timing strongly affects WM and NA at school start but badly predicts adolescent cognitive functioning. Furthermore, it bears practical implications as one may differentiate maturation lags from persistent low cognitive abilities in school children, complementing cognitive tests.http://ift.tt/2waw1Og
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