Connectome Coordination Facility II

项目摘要 该项目将继续运营连接组协调设施（CCF）， 人类连接组计划（HCP）的成功，该计划获得，分析和共享多模式 神经成像数据和行为数据的健康成年人的大人口。HCP的主要进展 包括㈠建立数据采集协议，在多种模式下产生高质量数据; (ii)充分利用高质量成像数据的预处理流程的实施;以及 (iii)建立一个强大的信息基础设施，允许广泛共享HCP 神经影像学和神经科学领域的数据。国家合作框架以这些成就为基础， 以三种方式服务于人类神经成像领域。目的之一是提供咨询和支持 为研究界提供服务，主要目的是协调图像采集协议， 那些HCP。为此，我们设立了一个服务台，其支助职能包括： 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;成像协议和图像重建支持的协调， 不同的软件平台和版本;以及咨询潜在问题（例如图像伪影）。一 第二个目标是提供服务，最大限度地提高国家合作框架提供者所获得数据的可比性。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HCP相容的方法获得。这需要与数据提供者协调， 维护简化从研究中心向CCF数据库传输去识别数据的机制。 来自每个研究的数据包括所获取的图像和与项目的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， 生成与数据一起发布的质量指标。然后按顺序运行一组标准化的管道 编制与国家合作框架数据库中其他数据集完全统一的最低限度预处理数据。 第三个目标是维护现有的人类连接组数据的数据库基础设施，并对其进行扩展 包括来自其他研究实验室的连接体数据，这些研究实验室由连接体相关研究资助。 人类疾病计划。这三个目标合在一起，使国家合作框架成为一个中心枢纽， 连接组学数据汇总和协调。国家合作框架的数据协调服务套件 通过数据共享获取数据确保了数据集之间前所未有的兼容性。的 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。

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.