Ye, J.; Tejavibulya, L.; Dai, W.; Cope, L. M.; Hardee, J. E.; Heitzeg, M. M.; Lichenstein, S.; Yip, S. W.; Banaschewski, T.; Baker, G. J.; Bokde, A. L. W.; Brühl, R.; Desrivieres, S.; Flor, H.; Gowland, P.; Grigis, A.; Heinz, A.; Martinot, J.-L.; Martinot, M.-L. P.; Artiges, E.; Nees, F.; Orfanos, D. P.; Poustka, L.; Hohmann, S.; Holz, N.; Baeuchl, C.; Smolka, M. N.; Vaidya, N.; Walter, H.; Whelan, R.; Schumann, G.; Garavan, H.; Chaarani, B.; Gee, D. G.; Baskin-Sommers, A.; Casey, B.; IMAGEN consortium, ; Scheinost, D.

Neural variability, or variation in brain signals, facilitates dynamic brain responses to ongoing demands. This flexibility is important during development from childhood to young adulthood, a period characterized by rapid changes in experience. However, little is known about how variability in the engagement of recurring brain states changes during development. Such investigations would require the continuous assessment of multiple brain states concurrently. Here, we leverage a new computational framework to study state engagement variability (SEV) during development. A consistent pattern of SEV changing with age was identified across cross-sectional and longitudinal datasets (N>3000). SEV developmental trajectories stabilize around mid-adolescence, with timing varying by sex and brain state. SEV successfully predicts executive function (EF) in youths from an independent dataset. Worse EF is further linked to alterations in SEV development. These converging findings suggest SEV changes over development, allowing individuals to flexibly recruit various brain states to meet evolving needs.