BRAIN Initiative: Hierarchical Event Descriptors (HED): a system to characterize events in neurobehavioral data

BRAIN Initiative：分层事件描述符 (HED)：表征神经行为数据事件的系统

• 批准号: 10480619
• 负责人: Arnaud Delorme
• 金额: $ 104.21万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-05 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10480619
• 关键词: Address; Advisory Committees; Archives; Attention; BRAIN initiative; Behavior; Behavioral; Biological; Biological Markers; Biological Models; Biomechanics; Brain; Case Study; Clinical; Code; Cognition; Communication; Communities; Computer software; Consult; Data; Data Set; Descriptor; Development; Documentation; Ecosystem; Education; Educational workshop; Elements; Environment; Event; Experimental Designs; Feedback; Functional Magnetic Resonance Imaging; Funding; Generations; Goals; Human; Image; Infrastructure; Instruction; Learning; Left; Libraries; Maintenance; Memory; Metadata; Modality; Modeling; Neurosciences; Ontology; Participant; Plant Roots; Process; Publishing; Pythons; Reproducibility; Research; Research Personnel; Rest; Sensory; Source; Standardization; Stimulus; Structure; System; Testing; Time; Validation; Vocabulary; Work; archive data; archived data; base; biomedical ontology; comparative; computing resources; data archive; data tools; experience; experimental study; improved; neurobehavioral; neuroimaging; neuroinformatics; open source; response; support tools; symposium; syntax; tool; usability

This two-year project will advance, integrate, document, and promote the use of the Hierarchical Event Descriptor (HED) system to describe events in human neuroimaging and behavioral data from research experiments and other sources in sufficient detail to support comparative analysis of human brain dynamics across studies. Relating the recorded data dynamics to temporally- specifiable changes in subject experience, action, and cognition is a major goal (and challenge) for both neuroimaging and biomechanical imaging. Standardizing the annotation of recorded (or post hoc identified) events across such data sets — recorded in diverse sensory environments involving different participant tasks and/or task conditions — in a ‘machine-actionable’ way is essential for systematic reproducible comparative analysis of archival data to enable discovery and modeling of systems-level brain function as well as biomarkers of brain/behavioral function. The HED system is to our knowledge the only ontological system addressing the problem of defining experiential and behavioral events in experimental human neuroimaging and other studies recording behavioral data. The release of third-generation HED represents a dramatic advance in HED usability and annotation capabilities, including the capacity to simply encode the experimental design and experimental structure as well to document experimental stimuli and subject responses within the data in a machine-actionable form. This project will improve supporting infrastructure, formalize HED governance and maintenance processes, support a community of users developing library vocabularies for specialized subfields, and develop additional tools for supporting analysis using HED on common analysis platforms. Substantial effort will be expended in developing practical tutorials, case studies, and a body of open-source HED annotated datasets. Further effort will be devoted to exploring and integrating HED into the wider human neuroinformatics ecosystem including the BRAIN Initiative sponsored OpenNeuro archive and the NEMAR data, tools, and compute resource.

这个为期两年的项目将进步，集成，记录和促进层次结构的使用 事件描述符（HED）系统，以描述人类神经影像和行为数据中的事件 从研究实验和其他来源有足够的详细信息来支持比较分析 跨研究的人脑动力学。将记录的数据动态与暂时联系起来 主题经验，行动和认知的特定变化是一个主要目标（和挑战） 神经影像学和生物力学成像。标准化记录的注释（或 事件确定了此类数据集的事件 - 记录在潜水员的感觉环境中 不同的参与者任务和/或任务条件 - 以“机器可用”方式对于 对档案数据的系统可重现比较分析以实现发现和建模 系统级脑功能以及大脑/行为功能的生物标志物。 hed 据我们所知，系统是解决定义问题的唯一本体论系统 实验性人类神经影像和其他研究的经验和行为事件 记录行为数据。第三代HED的释放代表了一个巨大的进步 HED可用性和注释功能，包括简单编码的能力 实验设计和实验结构以及记录实验刺激和 数据中的主题响应以机器可用形式进行。这个项目将改善 支持基础设施，正式化HED治理和维护过程，支持 用户社区开发专门子场的图书馆声乐，并开发 使用公共分析平台上的HED支持分析的其他工具。重大的 将在开发实用教程，案例研究和开源机构中探索努力 HED注释的数据集。进一步的努力将致力于探索并集成到 广泛的人类神经信息系统生态系统，包括大脑倡议发起的OpenNeuro 存档和Nemar数据，工具和计算资源。