The Open EEGLAB Portal Project

开放 EEGLAB 门户项目

• 批准号: 9982308
• 负责人: Arnaud Delorme
• 金额: $ 54.43万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9982308
• 关键词: 3-Dimensional; Algorithms; Architecture; Award; Behavior; Behavioral; Body Temperature; Brain; Brain imaging; California; Clinical; Collaborations; Collection; Communities; Complex; Computer software; Custom; Data; Data Analyses; Data Set; Development; Electrocardiogram; Electroencephalography; Electronic Mail; Electrophysiology (science); Environment; Frequencies; Functional Magnetic Resonance Imaging; Funding; Head; High Performance Computing; Human; Image; Individual; Internet; Joints; Laboratories; Linear Models; Links List; Magnetic Resonance; Maintenance; Measures; Meta-Analysis; Metabolic; Modality; Modeling; Motion; Nature; Neurosciences; Paper; Participant; Physiological; Plug-in; Process; Reporting; Research; Research Personnel; Resolution; Resources; Respondent; Running; Scalp structure; Series; Services; Signal Transduction; Source; Statistical Data Interpretation; Statistical Methods; Structure; Supercomputing; Surveys; Testing; Time; United States National Institutes of Health; Universities; Visualization; Visualization software; Wait Time; biophysical analysis; cognitive neuroscience; complex data; computational neuroscience; computerized data processing; computing resources; cost; data visualization; density; experience; flexibility; graphical user interface; imaging modality; innovation; light weight; motivated behavior; multimodal data; multimodality; news; open source; parallel processing; signal processing; source localization; statistics; supercomputer; teaching laboratory; tool; visual tracking

Electroencephalography (EEG), the first function brain activity imaging modality, has several natural advantages over metabolic brain imaging modalities. EEG is noninvasive, low cost, and lightweight enough to be highly mobile. Two major shifts in scientific perspective on the nature and use of human electrophysiological data are now ongoing. The first is a shift to using EEG data as a source-resolved, relatively high-resolution cortical source imaging modality. The second is a shift from recording electrophysiological data with at best a scant record of behavior (e.g., latencies of occasional button presses) to concurrently collecting and combining EEG data with other data modalities (e.g., body motion capture, eye tracking, audio and video, ECG, EMG, GSR, MEG, fMRI, etc.), paradigms that we term Mobile Brain/Body Imaging (MoBI) to capture brain activities and subject actions during natural, motivated behavior.The EEGLAB signal processing environment, an open source software project of the Swartz Center for Computational Neuroscience (SCCN) of the University of California, San Diego (UCSD), began as a set of EEG data analysis running on Matlab (The Mathworks, Inc.) released by Makeig on the World Wide Web in 1997. EEGLAB was first released from SCCN in 2001. Now nearly twenty years later, the EEGLAB reference paper (Delorme & Makeig, 2004) has over 4,100 citations (now increasing by over 3 per day), the opt-in EEGLAB discussion email list links over 5,500 researchers, the EEGLAB news list over 15,400 researchers, and a survey of 687 research respondents reported EEGLAB to be the software environment most widely used for electrophysiological data analysis in cognitive neuroscience. Currently, at least 52 EEGLAB plug-in tool sets have been released by other researchers from many laboratories. Here we propose, first, to greatly augment the power of the EEGLAB environment by enabling it to perform time series, biophysical, and statistical analyses of multimodal as well as unimodal EEG data. However, ever more precise analyses of large and multimodal data sets and studies require increasing amounts of computational power, more than is readily available in many laboratories. Thus second, in collaboration with the San Diego Supercomputer Center (SDSC) we propose to expand the current Neuroscience Gatew​ ay (​nsgportal.org) services to enable EEGLAB users to freely run EEGLAB processing scripts and pipelines on SDSC supercomputers. The proposed Open EEGLAB Portal will allow researchers to submit any amount of unimodal or multimodal EEG data for parallel processing using standard or custom EEGLAB processing pipelines. We will also develop and release first tools for meta-analysis of source-resolved EEG measures ​across studies. Multimodal EEG analysis and source-level EEG analysis accelerated by free use of supercomputing resources will give the EEG research community unprecedented abilities to observe and model distributed cortical dynamics supporting human experience and behavior.

脑电图 (EEG) 是第一个功能性脑活动成像模式，具有多种自然特征 与代谢脑成像方式相比，脑电图的优点是无创、成本低、重量轻， 关于人类电生理学的本质和用途的科学观点的两个重大转变。 第一个是转向使用脑电图数据作为源解析的、相对高分辨率的数据。 第二个是从最多使用记录电生理数据的转变。 同时收集和组合的行为记录很少（例如，偶尔按下按钮的延迟） 脑电图数据与其他数据模式（例如身体动作捕捉、眼动追踪、音频和视频、心电图、肌电图、 GSR、MEG、fMRI 等），我们称之为移动脑/身体成像 (MoBI) 的范例，用于捕获大脑活动 以及自然、动机行为期间的主体行为。EEGLAB 信号处理环境是一个开放的 斯沃茨大学计算神经科学中心（SCCN）的源软件项目 加利福尼亚州圣地亚哥 (UCSD) 最初是在 Matlab (The Mathworks, Inc.) 上运行的一组脑电图数据分析 1997 年由 Makeig 在万维网上发布。EEGLAB 于 2001 年首次由 SCCN 发布。现在 近二十年后，EEGLAB 参考论文（Delorme & Makeig，2004）被引用次数超过 4,100 次 （现在每天增加超过 3 个），选择加入 EEGLAB 讨论电子邮件列表链接超过 5,500 名研究人员， EEGLAB 新闻列出了超过 15,400 名研究人员，并且对 687 名研究受访者进行了调查，报告 EEGLAB 是认知神经科学中电生理数据分析最广泛使用的软件环境。 目前，来自多个领域的其他研究人员已经发布了至少 52 个 EEGLAB 插件工具集。 在这里，我们首先建议通过启用 EEGLAB 环境来大大增强它的功能。 对多模态和单模态脑电图数据进行时间序列、生物物理和统计分析。 然而，对大型多模式数据集和研究进行更精确的分析需要增加 第二，超过许多实验室现有的计算能力。 我们建议与圣地亚哥超级计算机中心（SDSC）合作扩展当前的 Neuroscience Gateway ay (nsgportal.org) 服务使 EEGLAB 用户能够自由运行 EEGLAB 处理 SDSC 超级计算机上的脚本和管道 拟议的开放 EEGLAB 门户将允许研究人员 使用标准或自定义提交任意数量的单模态或多模态脑电图数据以进行并行处理 我们还将开发并发布第一个用于元分析的工具。 跨研究的源解析脑电图测量。 通过免费使用超级计算资源加速将为脑电图研究界带来前所未有的成果 观察和建模支持人类经验和行为的分布式皮层动力学的能力。