BRAIN INITIATIVE RESOURCE: DEVELOPMENT OF A HUMAN NEUROELECTROMAGNETIC DATA ARCHIVE AND TOOLS RESOURCE (NEMAR)

大脑倡议资源：人类神经电磁数据档案和工具资源的开发 (NEMAR)

• 批准号: 10687858
• 负责人: Arnaud Delorme
• 金额: $ 85.11万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10687858
• 关键词: Archives; Awareness; BRAIN initiative; Behavior; Brain; Brain imaging; Cell Nucleus; Clinical; Cloud Computing; Communities; Computing Methodologies; Custom; Data; Data Analyses; Data Set; Data Storage and Retrieval; Data Store; Deposition; Descriptor; Development; Diagnosis; Disease; Documentation; Educational workshop; Electroencephalography; Electrophysiology (science); Engineering; Environment; Evaluation; Event; Frequencies; Functional Magnetic Resonance Imaging; Funding; Grant; Health; High Performance Computing; Human; Infrastructure; Internet; Laboratories; Learning; Libraries; Magnetic Resonance; Magnetism; Magnetoencephalography; Meta-Analysis; Methods; Mining; Modality; Neurosciences; Neurosciences Research; Patients; Performance; Privatization; Process; Quality Control; Records; Reproducibility; Research; Research Personnel; Research Project Grants; Resources; Running; Scalp structure; Science; Source; Specific qualifier value; Spottings; Staging; System; Testing; Time; United States National Institutes of Health; Validation; Visualization; Visualization software; archive data; brain based; brain research; brain surgery; built environment; computational platform; computerized data processing; computing resources; cyber infrastructure; data analysis pipeline; data archive; data curation; data format; data mining; data quality; data structure; data submission; data tools; data visualization; hackathon; interest; large scale data; machine learning method; neuroimaging; preservation; repository; response; sensor; supercomputer; support tools; tool; tool development; web interface; web services; web site

To take advantage of recent and ongoing advances in intensive and large-scale computational methods, and to preserve the scientific data created by publicly funded research projects, data archives must be created as well as standards for specifying, identifying, and annotating deposited data. The value of and interest in such archives among researchers can be greatly increased by adding to them an active computational capability and framework of analysis and search tools that support further analysis as well as larger scale meta-analysis and large scale data mining. The OpenNeuro.org archive, begun as a repository for functional magnetic resonance imaging (fMRI) data, is such an archive. We propose to build a gateway to OpenNeuro for human electrophysiology data (EEG and MEG, as well as intracranial data recorded from clinical patients to plan brain surgeries or other therapies) – herein we refer to these modalities as neuroelectromagnetic (NEM) data. The Neuroelectromagnetic Data Archive and Tools Resource (NEMAR) at the San Diego Supercomputer Center will act as a gateway to OpenNeuro for NEM data research. Such data uploaded to NEMAR at SDSC will be deposited in the OpenNeuro archive. Still- private NEM data in OpenNeuro will, on user request, be copied to the NEMAR gateway for further user processing using the XSEDE high-performance resources at SDSC in conjunction with The Neuroscience Gateway (nsgportal.org), a freely available and easy to use portal to use of high-performance computing resources for neuroscience research. Publicly available OpenNeuro NEM data will be able to be analyzed by running verified analysis applications on the OpenNeuro system. In this project we will build an application to evaluate the quality of uploaded NEM data, and another to visualize the data, for EEG and MEG at both the scalp and brain source levels, including time-domain and frequency-domain dynamics time locked to sets of experimental events learned from the BIDS- and HED-formatted data annotations. The NEMAR gateway will take a major step toward applying machine learning methods to a large store of carefully collected and stored human electrophysiologic brain data to spur new developments in basic and clinical brain research.

为了利用最近和正在进行的密集和大规模计算方法的进展， 为了保存由公共资助的研究项目创建的科学数据，数据档案必须 以及用于指定、识别和注释存储数据的标准。和的价值 研究人员对这类档案的兴趣可以通过增加一个活跃的 支持进一步分析的分析和搜索工具的计算能力和框架 作为更大规模的元分析和大规模数据挖掘。OpenNeuro.org档案，最初是一个 功能磁共振成像(FMRI)数据的存储库就是这样的档案。我们计划建造一座 人类电生理学数据(脑电和脑磁图)以及颅内数据的OpenNeuro门户 来自临床患者的记录，用于计划脑部手术或其他治疗)-在此我们指的是这些 例如神经电磁(NEM)数据。神经电磁数据档案和工具 圣地亚哥超级计算机中心的资源(Nemar)将作为NEM通往OpenNeuro的门户 数据研究。在SDSC上传到Nemar的这些数据将保存在OpenNeuro档案中。不过- 应用户要求，OpenNeuro中的私有NEM数据将被复制到Nemar网关以供其他用户使用 在SDSC与神经科学联合使用XSEDE高性能资源进行处理 Gateway(nsgportal.org)，一个免费提供且易于使用的高性能计算门户 神经科学研究的资源。公开可用的OpenNeuro NEM数据将能够被分析 通过在OpenNeuro系统上运行经过验证的分析应用程序。在这个项目中，我们将构建一个 用于评估上传的NEM数据的质量的应用程序，以及用于可视化数据的应用程序，用于EEG和 头皮和脑源水平的脑磁图，包括时间域和频域动力学 时间锁定于从BID和HED格式的数据注释中了解到的一组实验事件。 Nemar网关将向将机器学习方法应用于大型商店迈出重要一步 精心收集和存储的人类电生理大脑数据，以刺激基础研究的新发展 和临床脑研究。