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首页> 美国卫生研究院文献>Elsevier Sponsored Documents >General functional connectivity: Shared features of resting-state and task fMRI drive reliable and heritable individual differences in functional brain networks
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General functional connectivity: Shared features of resting-state and task fMRI drive reliable and heritable individual differences in functional brain networks

机译：通用功能连接：静止状态和任务功能磁共振成像的共享功能可驱动功能性大脑网络中可靠且可遗传的个体差异

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Intrinsic connectivity, measured using resting-state fMRI, has emerged as a fundamental tool in the study of the human brain. However, due to practical limitations, many studies do not collect enough resting-state data to generate reliable measures of intrinsic connectivity necessary for studying individual differences. Here we present general functional connectivity (GFC) as a method for leveraging shared features across resting-state and task fMRI and demonstrate in the Human Connectome Project and the Dunedin Study that GFC offers better test-retest reliability than intrinsic connectivity estimated from the same amount of resting-state data alone. Furthermore, at equivalent scan lengths, GFC displayed higher estimates of heritability than resting-state functional connectivity. We also found that predictions of cognitive ability from GFC generalized across datasets, performing as well or better than resting-state or task data alone. Collectively, our work suggests that GFC can improve the reliability of intrinsic connectivity estimates in existing datasets and, subsequently, the opportunity to identify meaningful correlates of individual differences in behavior. Given that task and resting-state data are often collected together, many researchers can immediately derive more reliable measures of intrinsic connectivity through the adoption of GFC rather than solely using resting-state data. Moreover, by better capturing heritable variation in intrinsic connectivity, GFC represents a novel endophenotype with broad applications in clinical neuroscience and biomarker discovery.
机译：使用静止状态功能磁共振成像测量的内在连通性已成为人类大脑研究的基本工具。但是，由于实际限制，许多研究没有收集足够的静止状态数据来生成研究个体差异所必需的内在连通性的可靠度量。在这里，我们介绍通用功能连接（GFC）作为在休息状态和任务功能磁共振成像中利用共享特征的一种方法，并在人类Connectome项目和但尼丁研究中证明，与相同量的固有连接相比，GFC的重测可靠性更高仅静态数据。此外，在相同的扫描长度下，GFC显示的遗传力估计值比静止状态功能连接性更高。我们还发现，GFC对认知能力的预测在数据集中普遍存在，其表现比单独的静止状态或任务数据好或更好。总的来说，我们的工作表明，GFC可以提高现有数据集中内在连通性估计的可靠性，并因此有机会发现行为个体差异的有意义的关联。鉴于任务和静止状态数据通常是一起收集的，因此许多研究人员可以通过采用GFC而不是仅使用静止状态数据来立即获得更可靠的内部连接度量。此外，通过更好地捕获内在连通性的遗传变异，GFC代表了一种新型的内表型，在临床神经科学和生物标记物发现中具有广泛的应用。

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