A community-driven development of the brain imaging data standard (BIDS) to describe macroscopic brain connections

由社区驱动的大脑成像数据标准（BIDS）的开发，以描述宏观的大脑连接

• 批准号: 10253558
• 负责人: Franco Pestilli
• 金额: $ 35.23万
• 依托单位: UNIVERSITY OF TEXAS AT AUSTIN
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-06 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10253558
• 关键词: Adopted; Adoption; Anatomy; Archives; Area; BRAIN initiative; Brain; Brain imaging; Cloud Computing; Communities; Computer software; Data; Data Collection; Data Set; Development; Diffusion; Diffusion Magnetic Resonance Imaging; Directories; Disease; Electroencephalography; Ensure; Faculty; Feedback; Foundations; Functional Magnetic Resonance Imaging; Funding; Generations; Goals; Health; Human; Individual; Infrastructure; Letters; Libraries; Magnetic Resonance Imaging; Maps; Measures; Metadata; Methods; Modality; Modeling; Monoclonal Antibody R24; Neurosciences; Persons; Positron-Emission Tomography; Postdoctoral Fellow; Process; Published Comment; Publishing; Recommendation; Reproducibility; Research Personnel; Scientific Advances and Accomplishments; Services; Signal Transduction; Solid; Standardization; Structure; Students; Testing; Time; Update; Validation; Work; base; connectome; data fusion; data sharing; data standards; data structure; design; diffusion weighted; experimental study; file format; instrumentation; interest; meetings; neuroimaging; prototype; social media; software development; tool; tool development; usability; virtual; white matter

Project Summary/Abstract The Brain Imaging Data Structure (BIDS) is a BRAIN initiative (R24 MH114705) community-driven standard meant to maximize neuroimaging data sharing, and facilitate analysis tool development. We propose to extend the standard to encompass derivatives resulting from experiments related to both functional as well as structural magnetic resonance imaging data that describe macroscopic brain connectivity estimates. The focus of this proposal is to advance BIDS to describe the entire experimental workflow—from minimally processed anatomical, functional and diffusion MRI data through connectivity matrices and tractometry features—in service of supporting BRAIN initiative studies of large-scale connectivity of human and nonhuman brains. BIDS was initially scoped to MRI data of the brain, but the standard has set up a solid infrastructure to steer the community and has been extended to cover a range of other modalities (PET, EEG, MEG, ECoG). Since its first announcement, BIDS has evolved to become an organized community with shared governance and a strong impact well beyond the U.S. BRAIN initiative. To date, 131 individuals among faculty, students, and postdocs contributed to the development of the standard and the article describing BIDS has been cited 277 times. Current gaps exist in developing BIDS to effectively support the process of scientific results generation. This is because the standard does not yet describe brain features that can be extracted from MRI data and that are routinely used to perform statistical tests and complete scientific studies. These features comprise connectivity maps, structural and functional connections, major white matter tracts, diffusion signal models as well as white matter tractograms and tractometry. Sharing processed data and features in addition to raw and minimally-processed data is critical to accelerating scientific discovery. This is because substantial effort, software, and hardware instrumentation, and know-how are required to bring raw data to a usable state. One previous project (R24 MH114705) laid the foundations for the BIDS derivatives standard, ultimately leading to the existing Common Derivatives standard. However, the current BIDS derivative standard does not cover advanced data derivatives that describe brain connectivity experiments. The current proposal is to advance the BIDS standard beyond preprocessed data to describe data products generated from experiments and models fit after preprocessing. The project will deliver a community-developed standard describing brain connectivity experiments. The standard will be accompanied by software to validate the datasets.

项目摘要/摘要 大脑成像数据结构（BIDS）是大脑倡议（R24 MH114705） 社区驱动的标准旨在最大​​化神经影像学数据共享，并促进分析工具 发展。我们建议将标准扩展到涵盖由实验产生的衍生物 与描述的功能和结构磁共振成像数据有关 宏观大脑连通性估计。该提议的重点是提高出价来描述 整个实验工作流程 - 从最小处理的解剖学，功能和扩散MRI数据 通过连通材料和术学特征 - 早期支持大脑 人类和非人类大脑大规模连通性的研究。竞标最初是在MRI的范围 大脑的数据，但标准已经建立了坚实的基础设施来阻止社区 扩展以涵盖其他一系列方式（PET，EEG，MEG，ECOG）。自第一个 宣布，投标已经发展成为一个有共同治理的有组织社区， 强烈的影响远远超出了美国大脑倡议。迄今为止，教师，学生，131个人， 和博士后为标准的制定做出了贡献，描述出价的文章一直是 引用了277次。 当前的差距在开发出价中以有效支持科学结果的过程 一代。这是因为标准尚未描述可以提取的大脑特征 根据MRI数据，通常用于进行统计检验和完整的科学研究。 这些功能包括连接图，结构和功能连接，主要白色物质 区域，扩散信号模型以及白质术图和术学。共享处理 除了原始和微型处理的数据外，数据和功能对于加速科学至关重要 发现。这是因为巨大的努力，软件和硬件工具以及专业知识 必须将原始数据带到可用的状态。一个先前的项目（R24 MH114705） 出价衍生品标准的基础，最终导致现有的共同衍生物 标准。但是，当前的出价衍生标准不涵盖高级数据衍生品 描述大脑连通性实验。当前的提议是将投标标准提高到以外 预处理数据以描述从实验和模型中生成的数据产品之后 预处理。该项目将提供一个社区开发的标准，描述大脑连接性 实验。该标准将通过软件来验证数据集完成。