Goyal Nikhil, Moraczewski Dustin, Bandettini Peter A, Finn Emily S, Thomas Adam G
Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD, USA.
Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA.
R Soc Open Sci. 2022 Feb 2;9(2):201090. doi: 10.1098/rsos.201090. eCollection 2022 Feb.
In mental health research, it has proven difficult to find measures of brain function that provide reliable indicators of mental health and well-being, including susceptibility to mental health disorders. Recently, a family of data-driven analyses have provided such reliable measures when applied to large, population-level datasets. In the current pre-registered replication study, we show that the canonical correlation analysis (CCA) methods previously developed using resting-state magnetic resonance imaging functional connectivity and subject measures (SMs) of cognition and behaviour from healthy adults are also effective in measuring well-being (a 'positive-negative axis') in an independent developmental dataset. Our replication was successful in two out of three of our pre-registered criteria, such that a primary CCA mode's weights displayed a significant positive relationship and explained a significant amount of variance in both functional connectivity and SMs. The only criterion that was not successful was that compared to other modes the magnitude of variance explained by the primary CCA mode was smaller than predicted, a result that could indicate a developmental trajectory of a primary mode. This replication establishes a signature neurotypical relationship between connectivity and phenotype, opening new avenues of research in neuroscience with clear clinical applications.
在心理健康研究中，已证明很难找到能够提供心理健康和幸福感可靠指标的脑功能测量方法，包括对心理健康障碍的易感性。最近，一系列数据驱动的分析在应用于大规模、人群水平的数据集时提供了此类可靠的测量方法。在当前预先注册的复制研究中，我们表明，先前使用静息态磁共振成像功能连接以及来自健康成年人的认知和行为的受试者测量指标（SMs）开发的典型相关分析（CCA）方法，在测量一个独立发育数据集中的幸福感（一个“正负轴”）方面同样有效。我们的复制在预先注册的三个标准中的两个标准上取得了成功，即主要CCA模式的权重显示出显著的正相关关系，并解释了功能连接和SMs中大量的方差。唯一未成功的标准是，与其他模式相比，主要CCA模式解释的方差幅度小于预期，这一结果可能表明主要模式的发育轨迹。这种复制建立了连接性与表型之间典型的神经典型关系，为神经科学研究开辟了新途径，并具有明确的临床应用。
