The NKI Rockland Sample II: An Open Resource of Multimodal Brain, Physiology & Behavior Data from a Community Lifespan Sample

NKI Rockland 样本 II：多模式大脑、生理学的开放资源

• 批准号: 10623202
• 负责人: Stan J Colcombe
• 金额: $ 69.83万
• 依托单位: NATHAN S. KLINE INSTITUTE FOR PSYCH RES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-13 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10623202
• 关键词: 3-Dimensional; Acceleration; Adult; Age; Behavior; Behavioral; Biometry; Body Composition; Body measure procedure; Brain; Caring; Categories; Cellular Phone; Chronology; Cognition; Cognitive; Collection; Communities; Complement; DSM-V; Data; Development; Diffusion Magnetic Resonance Imaging; Dimensions; EEG-based imaging; Ecological momentary assessment; Electroencephalography; Electromyography; Functional Magnetic Resonance Imaging; Funding; Future; Galvanic Skin Response; Genetic; Goals; Health; Human; Image; Imaging technology; Individual; International; Intervention; Journals; Literature; Longevity; Magnetic Resonance Imaging; Maps; Measurement; Measures; Mental Health; Mental disorders; Methods; Modality; Modeling; Moods; Motion; National Institute of Mental Health; Obesity; Performance; Phenotype; Photography; Physical activity; Physiological; Physiology; Preventive; Procedures; Process; Protocols documentation; Psychiatry; Psychopathology; Publications; Questionnaires; Research; Research Personnel; Resources; Rest; Risk; Risk Factors; Sampling; Scalp structure; Science; Source; Stimulus; Structure; Technology; Testing; United States National Institutes of Health; VO2max; Variant; Voice; Work; actigraphy; biomarker discovery; brain based; brain research; cardiovascular fitness; cognitive performance; cognitive task; connectome; data archive; data integration; data resource; data sharing; density; design; fitness; functional magnetic resonance imaging/electroencephalography; human very old age (85+); imaging study; improved; indexing; informant; inter-individual variation; magnetic resonance imaging/electroencephalography; member; morphometry; multimodal data; multimodality; neuroimaging; next generation; novel; prospective; sensor; sex; smartphone application; source localization; substance use; visual tracking; wearable device

ABSTRACT. The present competing renewal application proposes to create the next generation NKI-Rockland Sample (NKI-RS) initiative. The NKI-Rockland Sample (NKI-RS) has served as a beacon for lifespan connectomics research, providing a model for accelerating the pace of psychiatric discovery science. More than 200 publications have used NKI-RS, generated largely by independent investigators and in major journals. Since 2011, it has generated and publicly shared (on a quarterly basis) a large-scale (N > 1400), deeply phenotyped, community-ascertained, cross-sectional, lifespan sample (ages 6–85 years old) with advanced connectomics- focused neuroimaging (i.e., diffusion MRI, resting state fMRI [R-fMRI]) and genetic samples. Recently launched large- scale efforts, such as the HCP Lifespan Studies and the NIH ABCD Study are working to bring to scale human connectome mapping and brain function across the lifespan, using ‘battle-tested’ imaging technologies and strategies. These ongoing studies are less focused on mental health. Moreover, technologies and ideas continue to evolve - often too rapidly to permit timely testing and inclusion in ongoing research. The overarching goal of the present proposal is to create the next generation NKI-RS initiative that will once again extend the vanguard in the study of lifespan connectomics by enriching and expanding the landscape for neuroscientific advancement and biomarker discovery. Three major themes have guided the design of the proposed NKI-RS-II lifespan resource: 1) multimodal measurement integration across functional domains (e.g., fMRI, EEG, mobile brain/body imaging [MoBI] framework), 2) ecological sampling (e.g., wearables, sensors, smartphones apps), and 3) enhanced physiological phenotyping for cardiovascular fitness and obesity. Specifically, in a community- ascertained lifespan sample (N=600; ages 9-75; M: F = 1:1; age range selected to maximize data yield and tolerability), the proposed work aims to: 1) Generate and share large-scale multimodal MRI/EEG imaging data complemented by comprehensive phenotyping of cognition, behavior, and psychiatric status, from human and sensor-based informants; 2) Optimize brain-age prediction across the lifespan using multimodal data (R-fMRI, Naturalistic Viewing fMRI [NV-fMRI], dMRI, T2/T1, R-EEG, NV-EEG) and relate deviations from chronological age to dimensions of psychopathology and cognitive performance; and 3) Identify the relationship of modifiable health risk factors (e.g., fitness, obesity, physical activity, substance use) to deviations between predicted brain age and chronological age across the lifespan. Consistent with the model established by the previously funded NKI-RS initiatives, all data will be shared prospectively, on a quarterly basis, via the International Neuroimaging Data-sharing Initiative (INDI) and the NIMH Data Archive (NDA).

摘要。目前的竞争更新申请建议创建下一代NKI-罗克兰 样本（NKI-RS）倡议。NKI-Rockland样本（NKI-RS）已成为生命周期的灯塔 连接组学研究，为加快精神病学发现科学的步伐提供了一个模型。超过 200份出版物使用了NKI-RS，主要由独立调查人员和主要期刊生成。以来 2011年，它已经产生并公开分享（每季度）一个大规模（N > 1400），深度表型， 社区确定的，横断面的，寿命样本（年龄6-85岁）与先进的连接组学- 聚焦神经成像（即，扩散MRI、静息状态fMRI [R-fMRI]）和遗传样品。最近推出 大规模的努力，如HCP寿命研究和NIH ABCD研究正在努力使其规模化 人类连接体映射和整个生命周期的大脑功能，使用“战斗测试”成像技术 和战略。这些正在进行的研究较少关注心理健康。此外，技术和想法 继续发展-往往发展得太快，无法及时进行测试和纳入正在进行的研究。总体 本提案的目标是创建下一代NKI-RS倡议，该倡议将再次扩展 通过丰富和扩大神经科学领域， 进展和生物标志物发现。三大主题指导了拟议的NKI-RS-II的设计 寿命资源：1）跨功能域的多模态测量集成（例如，功能磁共振成像脑电图移动的 脑/身体成像[MoBI]框架），2）生态采样（例如，可穿戴设备、传感器、智能手机应用程序）， 和3）增强的心血管健康和肥胖的生理表型。具体来说，在一个社区中- 确定的寿命样本（N=600;年龄9-75; M：F = 1：1;选择年龄范围以最大化数据产量， 耐受性），拟议的工作旨在：1）生成和共享大规模多模态MRI/EEG成像数据 辅之以认知、行为和精神状态的综合表型， 基于传感器的信息提供者; 2）使用多模态数据（R-fMRI， 自然观察fMRI [NV-fMRI]、dMRI、T2/T1、R-EEG、NV-EEG）以及与时间顺序相关的偏差 年龄与精神病理学和认知表现维度的关系; 3）确定可改变的 健康风险因素（例如，健康，肥胖，身体活动，物质使用）与预测大脑 年龄和实足年龄之间的关系。与以前供资的联合国系统建立的模式一致， 根据NKI-RS倡议，所有数据将通过国际神经影像学协会（NKI）每季度共享一次。 数据共享倡议（INDI）和NIMH数据档案（NDA）。

项目成果

ReX: an integrative tool for quantifying and optimizing measurement reliability for the study of individual differences

• DOI: 10.1038/s41592-023-01901-3
• 发表时间: 2023-06
• 期刊: Nature Methods
• 影响因子: 48
• 作者: Ting Xu;Gregory Kiar;J. Cho;Eric W. Bridgeford;A. Nikolaidis;J. Vogelstein;M. Milham