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)

基本信息

批准号：
9795341
负责人：
Arnaud Delorme
金额：
$ 92.61万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
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/9795341
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 Quality Data Set Data Storage and Retrieval 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 Machine Learning 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 base brain research brain surgery built environment computational platform computerized data processing computing resources cyber infrastructure data archive data format data mining data structure data submission hackathon interest learning strategy neuroimaging preservation repository response sensor supercomputer support tools tool tool development web interface web services web site

项目摘要

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持续进展，为了保存公共资助的研究项目创建的科学数据，数据档案必须创建了用于指定、识别和注释存储数据的标准。通过向这些档案添加活跃的内容，可以大大提高研究人员对此类档案的兴趣计算能力和分析框架以及支持进一步分析的搜索工具作为更大规模的元分析和大规模数据挖掘，OpenNeuro.org 档案最初是作为一个我们建议建立一个功能性磁共振成像（fMRI）数据存储库。用于人类电生理学数据（EEG 和 MEG，以及颅内数据）的 OpenNeuro 网关从临床患者记录下来以计划脑部手术或其他治疗） - 在此我们指的是这些神经电磁 (NEM) 数据形式。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) 将充当 NEM 的 OpenNeuro 网关上传到 SDSC 的 NEMAR 的此类数据将存储在 OpenNeuro 档案中。 OpenNeuro 中的私有 NEM 数据将根据用户请求复制到 NEMAR 网关以供更多用户使用使用 SDSC 与 Neuroscience 联合使用 XSEDE 高性能资源进行处理 Gateway (nsgportal.org)，一个免费且易于使用的高性能计算门户将能够分析公开可用的 OpenNeuro NEM 数据。通过在 OpenNeuro 系统上运行经过验证的分析应用程序，我们将构建一个。用于评估上传的 NEM 数据质量的应用程序，以及用于可视化数据的另一个应用程序，用于脑电图和头皮和脑源水平的 MEG，包括时域和频域动态时间锁定到从 BIDS 和 HED 格式的数据注释中学到的实验事件集。 NEMAR 网关将在将机器学习方法应用于大型商店方面迈出重要一步精心收集和存储的人类电生理大脑数据，以促进基础科学的新发展和临床脑研究。