Connectome Coordination Facility II

连接组协调设施 II

• 批准号: 10550201
• 负责人: Daniel Scott Marcus
• 金额: $ 34.19万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-15 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10550201
• 关键词: Adult; Aging; Algorithms; Architecture; Behavioral; Brain; Child; Communities; Computer software; Consultations; Data; Data Aggregation; Data Security; Data Set; Databases; Diagnostic; Diffusion Magnetic Resonance Imaging; Disease; Ensure; Functional Magnetic Resonance Imaging; Funding; Health; Human; Image; Informatics; Infrastructure; Laboratory Research; Longevity; Manuals; Methods; Mission; Modality; Morphologic artifacts; National Institute of Mental Health; Neurosciences; Policies; Population; Privacy; Procedures; Process; Protocols documentation; Publishing; Quality Control; R24; Research; Research Personnel; Resources; Role; Running; Services; Site; Standardization; Structure; Technology; Time; Update; connectome; connectome data; data acquisition; data archive; data de-identification; data exchange; data harmonization; data management; data repository; data sharing; human disease; image reconstruction; improved; informatics infrastructure; material transfer agreement; multimodal neuroimaging; neuroimaging; novel; operation; peer; programs; repository infrastructure; response; success

Project Summary This project will continue operation of the Connectome Coordination Facility (CCF) by capitalizing on the successes of the Human Connectome Project (HCP), which acquired, analyzed, and shared multimodal neuroimaging data and behavioral data on a large population of healthy adults. Major advances by the HCP include (i) the establishment of data acquisition protocols that yield high quality data across multiple modalities; (ii) the implementation of preprocessing pipelines that take full advantage of the high quality imaging data; and (iii) the establishment of a robust informatics infrastructure that has allowed widespread sharing of the HCP data within the neuroimaging and neuroscience communities. The CCF builds on these accomplishments and serves the human neuroimaging community in three ways. One aim is to provide consultation and support services to the research community for the primary purpose of harmonizing image acquisition protocols with those of the HCP. To this end, we have established a help desk whose support functions include transfer of data acquisition sequences and image reconstruction algorithms; providing updates and improvements for these sequences and algorithms; harmonization of imaging protocols and image reconstruction support for different software platforms and versions; and consultation for potential problems (e.g. image artifacts). A second aim is to provide services that maximize comparability of data acquired by CCF contributors. These services include pre-data acquisition guidance to contributors to ensure that each project’s behavioral data are obtained using HCP-compatible methods. This entails coordination with data contributors to develop and maitain mechanisms to streamline transfers of de-identified data from the study sites to the CCF database. The data from each study include the acquired images and all data associated with the project’s behavioral battery. Manual and automated quality control procedures based on existing HCP methods are executed to generate quality metrics that are published with the data. A standardized set of pipelines are then run in order to produce minimally preprocessed data that is fully harmonized with the other data sets in the CCF database. A third aim is to maintain the existing data repository infrastructure for Human Connectome Data and expand it to include connectome data from other research laboratories that are funded under the Connectomes Related to Human Diseases program. Together, these three aims enable the CCF to serve a central hub for connectomics data aggregation and harmonization. The CCF’s suite of harmonization services from data acquisition through data sharing ensure an unprecedented level of compatibility across data sets. The resulting database enables the scientific community to conduct novel analyses to better understand brain function in health and disease.

项目摘要 该项目将继续运作Connectome协调机制，利用 人类连接体项目(HCP)的成功，该项目获取、分析和共享多模式 大量健康成年人的神经成像数据和行为数据。HCP的主要进展 包括(1)建立数据采集协议，以产生多种模式的高质量数据； (2)实施充分利用高质量成像数据的预处理管道；以及 (3)建立强大的信息学基础设施，使艾滋病毒/艾滋病能够广泛共享 神经成像和神经科学社区内的数据。CCF建立在这些成就的基础上，并 通过三种方式为人类神经成像社区提供服务。其中一个目标是提供咨询和支持 为研究界提供的服务，主要目的是使图像采集协议与 这些都是HCP的。为此，我们设立了一个服务台，其支持职能包括转移 数据采集序列和图像重建算法；提供更新和改进 这些序列和算法；协调成像协议和图像重建支持 不同的软件平台和版本；以及咨询潜在的问题(例如图像人工制品)。一个 第二个目标是提供服务，最大限度地提高CCF贡献者获得的数据的可比性。这些 服务包括对贡献者的数据获取前指导，以确保每个项目的行为数据 使用与HCP兼容的方法获得。这需要与数据贡献者协调，以开发和 建立各种机制，以简化从研究地点到气候变化框架数据库的未查明数据的传输。 每项研究的数据包括获取的图像和与项目行为相关的所有数据 电池。执行基于现有HCP方法的手动和自动质量控制程序，以 生成与数据一起发布的质量指标。然后，一组标准化的管道按顺序运行 产生与CCF数据库中的其他数据集完全一致的最低限度的预处理数据。 第三个目标是维护Human Connectome数据的现有数据存储库基础设施并对其进行扩展 包括来自其他研究实验室的连接体数据，这些研究实验室由相关连接体资助 人类疾病计划。这三个目标加在一起，使CCF能够为 连接学数据聚合和协调。CCF根据数据提供的一整套协调服务 通过数据共享获取数据可确保跨数据集实现前所未有的兼容性。这个 由此产生的数据库使科学界能够进行新的分析，以更好地了解大脑 在健康和疾病中发挥作用。