Predictive modeling studies have started to reveal brain measures underlying cognition; however, most studies are based on cross-sectional data (static final brain measures acquired at one time point). Since brain development comprises of continuously ongoing events leading to cognitive development, predictive modeling studies need to consider dynamic as opposed to static final brain measures. Using longitudinal neuroimaging and cognitive data (global executive composite score, an index of executive function) from 82 individuals (aged 5-14 years, scanned 3 times), we built highly accurate prediction models (r=0.61, p=1.6e-09) of future cognition (assessed at visit 3) based on baseline developmental changes in cortical anatomy (from visit 1 to 2). More importantly, dynamic brain measures (change in cortical anatomy from visit 1 to 2) and not static brain measures (cortical anatomy at visit 1 and 2) were critical for predicting future cognition, suggesting the need for considering dynamic brain measures in predicting cognitive outcomes.
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