Ye Jean, Tejavibulya Link, Dai Wei, Cope Lora M, Hardee Jillian E, Heitzeg Mary M, Lichenstein Sarah, Yip Sarah W, Banaschewski Tobias, Baker Gareth J, Bokde Arun L W, Brühl Rüdiger, Desrivières Sylvane, Flor Herta, Gowland Penny, Grigis Antoine, Heinz Andreas, Martinot Jean-Luc, Paillère Martinot Marie-Laure, Artiges Eric, Nees Frauke, Orfanos Dimitri Papadopoulos, Poustka Luise, Hohmann Sarah, Holz Nathalie, Baeuchl Christian, Smolka Michael N, Vaidya Nilakshi, Walter Henrik, Whelan Robert, Schumann Gunter, Garavan Hugh, Chaarani Bader, Gee Dylan G, Baskin-Sommers Arielle, Casey B J, Scheinost Dustin
Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA.
Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA.
Neuron. 2025 Sep 17. doi: 10.1016/j.neuron.2025.08.020.
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 moment-to-moment brain state engagement changes during development. Such investigations would require the continuous assessment of multiple brain states concurrently. Here, we leverage a new computational framework to characterize the state engagement variability (SEV) developmental trajectory. A consistent pattern of SEV changing with age is identified across cross-sectional and longitudinal datasets (N > 3,000). The SEV developmental trajectory stabilizes around mid-adolescence, with timing varying by sex and brain state. SEV successfully predicts executive function (EF) in youth from an independent dataset. Deviations in SEV development are further linked to worse EF. These converging findings suggest that SEV changes over development, allowing individuals to flexibly recruit various brain states to meet evolving needs.
神经变异性，即大脑信号的变化，有助于大脑对持续需求做出动态反应。这种灵活性在从童年到青年期的发育过程中很重要，这一时期的特点是经历迅速变化。然而，对于在发育过程中瞬间大脑状态参与的变异性如何变化，我们知之甚少。此类研究需要同时对多种大脑状态进行持续评估。在这里，我们利用一个新的计算框架来描述状态参与变异性（SEV）的发育轨迹。在横断面和纵向数据集中（N>3000）识别出了随年龄变化的一致的SEV模式。SEV发育轨迹在青春期中期左右稳定下来，其时间因性别和大脑状态而异。SEV成功地预测了来自独立数据集的青少年的执行功能（EF）。SEV发育的偏差进一步与较差的EF相关。这些趋同的发现表明，SEV在发育过程中发生变化，使个体能够灵活地调用各种大脑状态以满足不断变化的需求。
