CRCNS Data Sharing: An open data repository for cognitive neuroscience: The OpenfMRI Project

CRCNS 数据共享：认知神经科学的开放数据存储库：OpenfMRI 项目

• 批准号: 1131441
• 负责人: Russell Poldrack
• 金额: $ 74.39万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1131441&HistoricalAwards=false
• 关键词: CRCNS; Data; Sharing; open; data

Functional magnetic resonance imaging (fMRI) has become the most common tool for cognitive neuroscience, because it provides a safe, non-invasive, and powerful means to image human brain function. Based on recent rates of publication, there are currently more than 2000 fMRI studies being performed every year worldwide. The aggregation of data across multiple studies can provide the ability to answer questions that cannot be answered based on a single study. For example, using datasets from multiple domains one can start to investigate to what degree a region is selectively engaged in relation to a particular mental process, as opposed to being generally engaged across a broad range of tasks and processes. In addition, it provides the ability to integrate across specific tasks to obtain stronger empirical generalizations about mind-brain relationships, and to better understand the nature of individual variability across different measures. Recent work in neuroimaging analysis has focused on the application of methods such as machine learning techniques to understand the coding of information at the macroscopic level, and network analysis techniques to understand the interactions inherent in large-scale neural systems. The availability of a large testbed of high-quality fMRI data from published studies would also provide an important resource for the development of these and other new analytic techniques for fMRI data. However, sharing of raw fMRI data is challenging due to the large size of the datasets and the complexity of the associated metadata, and there is currently no infrastructure for the open sharing of new fMRI datasets.This project, OpenfMRI, will provide a new infrastructure for the broad dissemination of raw data within cognitive neuroscience, addressing a critical need by providing an open data sharing resource for neuroimaging. The initial project is already online at http://www.openfmri.org with a limited number of datasets. The full project will greatly expand this repository by providing access to a large number of fMRI datasets from several prominent neuroimaging labs, spanning across a broad range of cognitive domains. Utilizing the substantial computational resources of the Texas Advanced Computing Center, the project will also perform standard fMRI analyses on all data in the repository using a common analysis pipeline, thus providing directly comparable analysis results for all of the studies in the database. The OpenfMRI project will support the development of infrastructural elements to make sharing of data by additional investigators more straightforward.The repository of data that will be created by the OpenfMRI project will also serve as an important resource for teaching by providing students with the ability to replicate the analyses from published studies using the same data. By providing any researcher in the world with the ability to acquire large fMRI datasets, it will also provide all researchers with the ability to work with the same state-of-the-art datasets, regardless of institution. By creating the infrastructure for open sharing of research data, the project will also enhance the impact of other NSF-funded neuroimaging research projects by providing an infrastructure that can be used to make their data available. The planned work has the potential to benefit society by improving education, health, and human productivity through an increased understanding of mental function and its relationship to brain function.

功能磁共振成像（fMRI）已经成为认知神经科学最常用的工具，因为它提供了一种安全、非侵入性和强大的人脑功能成像手段。根据最近的发表率，目前全世界每年进行的fMRI研究超过2000项。跨多个研究的数据汇总可以提供回答基于单个研究无法回答的问题的能力。例如，使用来自多个领域的数据集，人们可以开始调查一个区域在多大程度上选择性地参与到一个特定的心理过程中，而不是普遍地参与到广泛的任务和过程中。此外，它还提供了跨特定任务的整合能力，以获得关于心智-大脑关系的更强的经验概括，并更好地理解跨不同测量的个体变异性的本质。最近神经成像分析的工作集中在应用机器学习技术等方法来理解宏观层面的信息编码，以及网络分析技术来理解大规模神经系统中固有的相互作用。从已发表的研究中获得的高质量fMRI数据的大型测试平台的可用性也将为这些和其他新的fMRI数据分析技术的发展提供重要资源。然而，由于数据集的庞大规模和相关元数据的复杂性，原始fMRI数据的共享是具有挑战性的，而且目前还没有开放共享新fMRI数据集的基础设施。这个名为OpenfMRI的项目将为认知神经科学中原始数据的广泛传播提供一个新的基础设施，通过为神经成像提供一个开放的数据共享资源来解决一个关键的需求。最初的项目已经在http://www.openfmri.org上上线，数据集数量有限。整个项目将通过提供对来自几个著名神经成像实验室的大量fMRI数据集的访问，极大地扩展这个存储库，这些数据集跨越了广泛的认知领域。利用德克萨斯高级计算中心的大量计算资源，该项目还将使用通用分析管道对存储库中的所有数据执行标准的fMRI分析，从而为数据库中的所有研究提供直接可比的分析结果。OpenfMRI项目将支持基础设施元素的开发，使其他研究人员更直接地共享数据。由OpenfMRI项目创建的数据存储库也将作为教学的重要资源，为学生提供使用相同数据复制已发表研究的分析的能力。通过为世界上的任何研究人员提供获取大型功能磁共振成像数据集的能力，它也将为所有研究人员提供使用相同的最先进数据集的能力，无论机构如何。通过创建开放共享研究数据的基础设施，该项目还将通过提供可用于使其数据可用的基础设施来增强其他nsf资助的神经影像学研究项目的影响。这项计划中的工作有可能通过加深对心理功能及其与大脑功能的关系的了解，改善教育、健康和人类生产力，从而造福社会。