Neurodevelopmental subtypes of functional brain organization in the ABCD study using a rigorous analytic framework

IF 4.5 2区 医学 Q1 NEUROIMAGING NeuroImage Pub Date : 2024-09-06 DOI:10.1016/j.neuroimage.2024.120827
Jacob DeRosa , Naomi P. Friedman , Vince Calhoun , Marie T. Banich
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Abstract

The current study demonstrates that an individual's resting-state functional connectivity (RSFC) is a dependable biomarker for identifying differential patterns of cognitive and emotional functioning during late childhood. Using baseline RSFC data from the Adolescent Brain Cognitive Development (ABCD) study, which includes children aged 9–11, we identified four distinct RSFC subtypes. We introduce an integrated methodological pipeline for testing the reliability and importance of these subtypes. In the Identification phase, Leiden Community Detection defined RSFC subtypes, with their reproducibility confirmed through a split-sample technique in the Validation stage. The Evaluation phase showed that distinct cognitive and mental health profiles are associated with each subtype, with the Predictive phase indicating that subtypes better predict various cognitive and mental health characteristics than individual RSFC connections. The Replication stage employed bootstrapping and down-sampling methods to substantiate the reproducibility of these subtypes further. This work allows future explorations of developmental trajectories of these RSFC subtypes.

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使用严格的分析框架分析 ABCD 研究中大脑功能组织的神经发育亚型。
目前的研究表明,个体的静息状态功能连通性(RSFC)是一种可靠的生物标记,可用于识别儿童晚期认知和情绪功能的不同模式。利用青少年大脑认知发展(ABCD)研究(包括 9-11 岁的儿童)中的 RSFC 基线数据,我们确定了四种不同的 RSFC 亚型。我们介绍了一种综合方法,用于测试这些亚型的可靠性和重要性。在识别阶段,莱顿社区检测确定了 RSFC 亚型,并在验证阶段通过分离样本技术确认了这些亚型的可重复性。评估阶段表明,每个亚型都与不同的认知和心理健康特征相关,预测阶段表明,亚型比单个 RSFC 连接更能预测各种认知和心理健康特征。复制阶段采用了引导和向下取样方法,进一步证实了这些亚型的可重复性。这项工作为今后探索这些 RSFC 亚型的发展轨迹提供了可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
NeuroImage
NeuroImage 医学-核医学
CiteScore
11.30
自引率
10.50%
发文量
809
审稿时长
63 days
期刊介绍: NeuroImage, a Journal of Brain Function provides a vehicle for communicating important advances in acquiring, analyzing, and modelling neuroimaging data and in applying these techniques to the study of structure-function and brain-behavior relationships. Though the emphasis is on the macroscopic level of human brain organization, meso-and microscopic neuroimaging across all species will be considered if informative for understanding the aforementioned relationships.
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