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大规模网络连通性可预测年龄:来自 Cam-CAN 数据集的整个成年期证据。

Large-scale network connectivity as a predictor of age: Evidence across the adult lifespan from the Cam-CAN data set.

机构信息

Department of Psychological and Brain Sciences, Drexel University.

Department of Psychological and Brain Sciences, Villanova University.

出版信息

Psychol Aging. 2022 Aug;37(5):557-574. doi: 10.1037/pag0000683. Epub 2022 May 23.

Abstract

Changes in brain connectivity patterns as a function of age have been recently proposed to underlie differences in cognitive abilities between young and older adults. These shifts track patterns of increased functional coupling between the executive control network (ECN)-a network of prefrontal and parietal areas that is broadly implicated in externally directed attention and cognitive control-and default mode network (DMN) regions-most commonly associated with internally directed cognitive activity. Although age-related changes in ECN-DMN coupling are well characterized, the contributions of the salience network are less clear. Furthermore, given the salience network's crucial role in arbitrating ECN-DMN functional connectivity, it is important to understand its contribution throughout the adult lifespan. Here, we used the data from a large cohort ( = 547) of participants from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) database (18-88 years old) to investigate first whether resting-state ECN-DMN functional connectivity predicts age. We further examined how connectivity between ECN, DMN, and salience network regions impacts the hypothesized age-related increased connectivity between ECN and DMN areas. Multiple regression analyses revealed that connectivity between dorsolateral and ventromedial prefrontal cortex and parietal regions, including the precuneus, accounted for a significant portion of age variability and that the inclusion of connectivity between orbitofrontal insula, anterior insula, and anterior cingulate regions of the salience network improved the models' explanatory power. Additional age cohort analyses further highlighted that these relationships vary across the lifespan. We discuss how these findings expand on our current understanding of the variations in large-scale intrinsic network connectivity as a function of healthy aging. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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