Between- and Within-Person Heterogeneity in Adolescent Resting State Networks: Associations with Internalizing Psychopathology

项目总结/摘要 青春期是抑郁和焦虑的关键风险期， 预测更差的健康和生活结果。功能连接（FC）网络，反映了 大脑功能，已经成为一个有前途的生物标志物，为诊断和干预提供信息。 精神病理学然而，尽管临床组和对照组之间的FC差异，特别是 在静息状态（RS）网络中，存在最小的临床翻译。一个关键的限制是， 个体之间和个体内部的网络异质性威胁着人们得出有效推论的能力。 个人层面。在人与人之间的层面上，跨个体的性质不同的网络限制了 组平均网络，以有效地反映每个人。如果群体层次的网络不反映个体， 从它们得出的行为推论将不适用于个人。前期工作和前期工作 精确的成像研究通过证明FC网络异质性提供了这种局限性的证据 在不同的个体之间。然而，群体网络对个人的普遍性还有待于经验检验。 这项建议将评估青少年RS网络的群体到个人的普遍性，并研究 数据驱动的相似个体亚组解决异质性限制的能力（目标1）。在 在人的层次上，单次扫描的FC可变性也威胁到FC网络的有效性。如果FC意味着 并且协方差在扫描中随时间变化（即，不是静止的），静态（时不变）网络将 无法有效反映扫描过程中的网络进程。本建议将估算动态FC以评估 青少年RS网络的平稳性，以确定静态网络的有效性（目标2）。为了这两个目标， 该提案将使用来自青少年大脑认知发展研究的大型11-12岁样本。的 建议书将确定数据聚合的级别（组、子组或个人）和时间精度（静态 或动态的），这对于来自FC网络的个体级推断是必要的。研究结果将是至关重要的最终 我们的目标是使用FC网络进行临床翻译，这需要个人水平的预测。然后我们将使用 RS网络特征对个体精确预测青少年抑郁和焦虑结果 (Aim 3）建立一个具有更大潜力的临床翻译基础。培训计划，以实现 拟议的项目是与一个相关专家小组合作制定的，该小组由正式的 课程，研讨会和应用研究活动。具体来说，我将培养功能磁共振成像研究方面的专业知识 和分析方法，用于子组识别的机器学习方法，以及具体的（人- 以完成研究提案所需的方法。培训将强调发展， 我的目标是成为一名临床神经科学的独立研究者， 神经功能和青少年精神病理学之间的联系。

PROJECT SUMMARY/ABSTRACT Adolescence is a key risk period for depression and anxiety, and adolescent-onset psychopathology is predictive of poorer health and life outcomes. Functional connectivity (FC) networks, which reflect trait-like brain functioning, have emerged as a promising biomarker to inform diagnosis and intervention of psychopathology. However, despite findings of FC differences between clinical and control groups, particularly in resting state (RS) networks, there has been minimal clinical translation. A key limitation is that qualitative network heterogeneity between- and within-individuals threatens the ability to draw inferences valid at the individual level. At the between-person level, qualitatively distinct networks across individuals limit the ability of group-averaged networks to validly reflect each individual. If group-level networks do not reflect individuals, behavioral inferences drawn from them will not apply to the individual. Our preliminary work and previous precision imaging studies provide evidence of this limitation by demonstrating FC network heterogeneity across individuals. However, the generalizability of group networks to individuals is yet to be tested empirically. This proposal will assess group-to-individual generalizability of adolescent RS networks and examine the ability of data-driven subgroups of similar individuals to address the limitation of heterogeneity (Aim 1). At the within-person level, FC variability across a single scan also threatens the validity of FC networks. If FC means and covariances vary with time across a scan (i.e., are not stationary), a static (time-invariant) network would not validly reflect network processes across the scan. This proposal will estimate dynamic FC to assess stationarity of adolescent RS networks to determine the validity of static networks (Aim 2). For both aims, this proposal will use a large 11–12-year-old sample from the Adolescent Brain Cognitive Development study. The proposal will determine the levels of data aggregation (group, subgroup, or individual) and time precision (static or dynamic) necessary for individual-level inferences from FC networks. Findings will be critical for the ultimate goal of using FC networks for clinical translation, which requires individual-level prediction. We will then use RS network features that are precise to individuals to predict depression and anxiety outcomes in adolescents (Aim 3), building a foundation with increased potential for clinical translation. The training plan to achieve the proposed project was developed in collaboration with a team of relevant experts that consists of formal coursework, workshops, and applied research activities. Specifically, I will develop expertise in fMRI research and analysis methods, machine learning approaches for subgroup identification, and idiographic (person- centered) methods necessary to complete the research proposal. Training will emphasize development toward my goal of becoming an independent investigator in clinical neuroscience who studies individually precise associations between neural functioning and adolescent psychopathology.