ERPLAB: Extensible, open source software for analysis of event-related potentials

描述(由申请人提供)：该项目继续开发和支持ERPLAB工具箱，这是一个基于MatLab的开源软件包，用于分析事件相关电位(ERP)数据。事件相关电位以毫秒级的分辨率提供与感知、认知、情绪和行动相关的大脑活动的信息，被广泛用于研究心理学、神经科学、精神病学、神经学和相关领域的广泛的基础科学和翻译科学问题。企业资源规划研究出现了爆炸性增长，但由于商业企业资源规划分析软件能力有限，以及缺乏功能齐全的开放源码企业资源规划分析包，进展受到阻碍。这种情况减缓了企业资源规划研究新方向的发展，反而鼓励研究人员继续采用现有企业资源规划分析包的内置功能所支持的现有方法。ERPLAB工具箱直接解决了这些问题。它将现有的封闭源代码ERP分析系统ERPSS的功能与开放源代码的EEG处理包EEGLAB相结合。EEGLAB提供了脑电处理功能，这是ERP分析的第一步，并提供了方便的图形用户界面(GUI)。ERPLAB建立在EEGLAB的基础上，为ERP分析的后续阶段增加了强大的工具。所有ERPLAB工具都可以从图形用户界面访问，也可以从Matlab脚本访问，以提供自动化和定制。ERPLAB将为ERP研究人员常用的基本分析程序提供强大但易于使用的工具。它还将提供一套目前正在广泛使用或未得到充分利用的高级功能。这套基础和高级的功能将极大地提高ERP研究的质量，降低成本。此外，ERPLAB被设计为任何具有基本编程技能的人都可以轻松扩展。因此，用户社区将有助于企业资源规划系统的发展，提供对企业资源规划研究人员各个分组非常重要的现有技术的实施，并允许开发和传播能够提高最新水平的新工具。ERPLAB的测试版现已推出，拟议项目的目标是继续开发该软件，并提供必要的文件和最终用户支持，以最大限度地发挥该程序包的作用。超过500名研究人员已经加入了我们的努力，我们预计到拟议的项目期结束时，至少有2000名用户。通过向这一庞大的用户群提供强大的处理工具，我们希望改进对当前实验范例的数据的分析，并帮助研究人员通过使他们能够轻松开发当前ERP分析系统没有预料到的分析工具来推动科学的边界。 公共卫生相关性： 在该项目中开发的这一软件将使研究人员能够更准确地量化和解释从基础科学研究中的健康人和翻译科学研究中的患者记录的脑波数据。它将使对正常和异常大脑功能的研究更快地取得进展，导致对精神和大脑疾病的更好的理解、诊断和治疗。

DESCRIPTION (provided by applicant): This project continues the development and support of ERPLAB Toolbox, a Matlab-based open source software package for the analysis of event-related potential (ERP) data. ERPs provide information about brain activity related to perception, cognition, emotion, and action with millisecond resolution and are widely used to study a broad range of basic and translational science issues in psychology, neuroscience, psychiatry, neurology, and related fields. There has been an explosion in ERP research, but progress has been hampered by the limited abilities of commercial ERP analysis software and the lack of full-featured open source ERP analysis packages. This situation has slowed the development of new directions in ERP research, instead encouraging researchers to continue with existing approaches supported by the built-in functions of the available ERP analysis packages. ERPLAB Toolbox directly addresses these problems. It merges the functionality of an existing closed source ERP analysis system, ERPSS, with an open source EEG processing package, EEGLAB. EEGLAB provides the EEG processing functions that are the first steps in ERP analysis and a convenient graphical user interface (GUI). ERPLAB builds on EEGLAB by adding powerful tools for the subsequent stages of ERP analysis. All ERPLAB tools can be accessed from the GUI, and they can also be accessed from Matlab scripts to provide automation and customization. ERPLAB will provide powerful but easy-to-use tools for the basic analysis procedures that are commonly used by ERP researchers. It will also provide a set of advanced functions that are either currently in widespread use or are underutilized. This set of basic and advanced functions will greatly improve the quality and decrease the cost of ERP research. In addition, ERPLAB is designed to be easily extended by anyone with rudimentary programming skills. The community of users will therefore contribute to the development of ERPLAB, providing implementations of existing techniques that are very important to various subgroups of ERP researchers and allowing the development and dissemination of new tools that can advance the state of the art. A beta version of ERPLAB is now available, and the goal of the proposed project is to continue the development of the software and to provide the documentation and end-user support that is necessary to maximize the usefulness of the package. Over 500 researchers have already joined our effort, and we anticipate at least 2,000 users by the end of the proposed project period. By providing powerful processing tools to this large set of users, we hope to improve the analysis of data from current experimental paradigms and to help researchers to push the boundaries of science by making it easy for them to develop analysis tools that are not anticipated by current ERP analysis systems. PUBLIC HEALTH RELEVANCE: This software developed in this project will allow researchers to more accurately quantify and interpret brainwave data recorded from healthy individuals in basic science studies and from patients in translational science studies. It will allow research on normal and abnormal brain function to progress more rapidly, leading to a better understanding, diagnosis, and treatment of diseases of mind and brain.