Kardan Omid, Jones Natasha, Wheelock Muriah D, Michael Cleanthis, Angstadt Mike, Molloy M Fiona, Cope Lora M, Martz Meghan M, McCurry Katherine L, Hardee Jillian E, Rosenberg Monica D, Weigard Alexander S, Hyde Luke W, Sripada Chandra, Heitzeg Mary M
University of Michigan, Department of Psychiatry; Ann Arbor, MI.
University of Michigan, Department of Psychology; Ann Arbor, MI.
bioRxiv. 2024 Sep 26:2024.09.26.615215. doi: 10.1101/2024.09.26.615215.
Adolescence is a period of growth in cognitive performance and functioning. Recently, data-driven measures of brain-age gap, which can index cognitive decline in older populations, have been utilized in adolescent data with mixed findings. Instead of using a data-driven approach, here we assess the maturation status of the brain functional landscape in early adolescence by directly comparing an individual's resting-state functional connectivity (rsFC) to the canonical early-life and adulthood communities. Specifically, we hypothesized that the degree to which a youth's connectome is better captured by adult networks compared to infant/toddler networks is predictive of their cognitive development. To test this hypothesis across individuals and longitudinally, we utilized the Adolescent Brain Cognitive Development (ABCD) Study at baseline (9-10 years; n = 6,489) and 2-year-follow-up (Y2: 11-12 years; n = 5,089). Adjusted for demographic factors, our anchored rsFC score (AFC) was associated with better task performance both across and within participants. AFC was related to age and aging across youth, and change in AFC statistically mediated the age-related change in task performance. In conclusion, we showed that a model-fitting-free index of the brain at rest that is anchored to both adult and baby connectivity landscapes predicts cognitive performance and development in youth.
青春期是认知能力和功能发展的时期。最近,数据驱动的脑龄差距测量方法,可用于评估老年人群的认知衰退情况,已被应用于青少年数据,但结果不一。本研究未采用数据驱动方法,而是通过直接将个体的静息态功能连接(rsFC)与典型的幼年和成年脑功能网络进行比较,来评估青少年早期脑功能格局的成熟状态。具体而言,我们假设与婴幼儿网络相比,成人网络对青少年脑连接组的捕获程度能预测其认知发展。为在个体层面和纵向层面验证这一假设,我们利用了青少年大脑认知发展(ABCD)研究的基线数据(9 - 10岁;n = 6,489)和2年随访数据(Y2:11 - 12岁;n = 5,089)。在调整人口统计学因素后,我们的锚定rsFC分数(AFC)与参与者在不同任务及同一任务中的更好表现相关。AFC与青少年的年龄及衰老有关,且AFC的变化在统计学上介导了任务表现的年龄相关变化。总之,我们表明,一种基于成人和婴儿连接格局的无模型拟合静息态脑指数可预测青少年的认知表现和发展。