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: 10475072
• 负责人: Arnaud Delorme
• 金额: $ 88.17万
• 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 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10475072
• 关键词: Archives; Awareness; BRAIN initiative; Base of the Brain; 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; Electrophysiology (science); Engineering; Environment; Evaluation; Event; Frequencies; Functional Magnetic Resonance Imaging; Funding; Grant; Health; High Performance Computing; Human; Infrastructure; Internet; Laboratories; Lead; 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; Resource Development; Resources; Running; Scalp structure; Science; Source; Specific qualifier value; Spottings; Staging; System; Testing; Time; United States National Institutes of Health; Validation; Visualization software; archive data; base; 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; 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.

为了利用密集和大规模计算方法的最新和正在进行的进步， 为了保留由公共资助的研究项目创建的科学数据，数据档案必须是 创建以及用于指定，识别和注释沉积数据的标准。和 通过增加积极的兴趣，可以大大增加对研究人员之间的档案的兴趣 也支持进一步分析的分析和搜索工具的计算能力和框架 作为较大规模的荟萃分析和大规模数据挖掘。 openneuro.org档案，从 功能性磁共振成像（fMRI）数据的存储库是这样的档案。我们建议建造 通往人类电生理数据的OpenNeuro的门户（EEG和MEG以及颅内数据 从临床患者记录以计划脑手术或其他疗法） - 在此，我们参考这些 作为神经电磁（NEM）数据的模态。神经电磁数据存档和工具 圣地亚哥超级计算机中心的资源（Nemar）将充当通往NEM的OpenNeuro的门户 数据研究。此类数据上传到SDSC的Nemar将存放在OpenNeuro档案中。仍然- OpenNeuro中的私人NEM数据将根据用户要求将其复制到Nemar Gateway，以供进一步用户 使用神经科学结合使用SDSC的XSEDE高性能资源进行处理 网关（nsgportal.org），一种免费的可用且易于使用的门户，用于使用高性能计算 神经科学研究的资源。公开可用的OpenNeuro NEM数据将可以分析 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，我们将建立一个 评估上载NEM数据的质量的应用，另一个用于可视化数据的应用 头皮和大脑源水平的MEG，包括时间域和频域动力学 时间锁定在从出价和HED形式的数据注释中汲取的一组实验事件。 Nemar Gateway将朝着将机器学习方法应用于大型商店迈出的重要一步 精心收集和存储的人类电生理大脑数据以刺激基本的新发展 和临床大脑研究。