1 McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, QC, H3A 2B4, Canada.
2 Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, QC, H3A 2B4, Canada.
3 Department of Psychology, Concordia University, Montreal, QC, H4B 1R6, Canada.
4 CHU Sainte-Justine Hospital Research Centre, Montreal, QC, H3T 1C5, Canada.
5 Douglas Institute, McGill University, 6875 Boulevard LaSalle, Verdun, QC, H4H 1R3, Canada.
6 University of Eastern Finland, Canada.

Predictive modeling studies have started to reveal brain measures underlying cognition; however, most studies are based on cross-sectional data (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 'longitudinal brain change' as opposed to 'cross-sectional 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 developmental changes in cortical anatomy (from visit 1 to 2). More importantly, longitudinal brain change (i.e. change in cortical anatomy from visit 1 to 2) and cross-sectional brain measures (cortical anatomy at visit 1 and 2) were critical for predicting future cognition, suggesting the need for considering longitudinal brain change in predicting cognitive outcomes.