Collaborative Research: CIBR: The OpenBehavior Project

合作研究：CIBR：开放行为项目

• 批准号: 1948181
• 负责人: Mark Laubach
• 金额: $ 64.81万
• 依托单位: American University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-15 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1948181&HistoricalAwards=false
• 关键词: Collaborative; Research; CIBR; OpenBehavior; Project

In recent years, the field of neuroscience has benefited from open source tools such as the computer language Python, off-the-shelf methods for 3D printing, low-cost microcontrollers such as Arduino, and public repositories for computer code and hardware designs such as GitHub. Many labs are using these tools, but most do not share their code and designs. As a result, it is not possible to systematically track the use of open source tools and their revisions and there is no central repository for open source tools or benchmark materials, such as video recordings of animal behavior. This award will allow these issues to be addressed by creating a database for open source research tools used in the field of neuroscience as well as a repository of benchmark and training materials for using the tools. The specific aims of the project are to create a taxonomy for open source tools used in neuroscience research, use the taxonomy to create and curate a database of open source tools, including creating Research Resource Identifiers (RRIDs) for all tools in the database, and disseminate information on open source tools and the skills required to use them. A special focus of the initial funding period (Aim 3) will be methods for video analysis of animal behavior, which are extremely popular in recent years. Activities in the third aim include creation of a database of video recordings of commonly used behavioral tasks, an open data analysis competition using a common set of benchmark videos (developed through the project), and the development of training materials and in-person and virtual workshops on making and using the most popular open source tools used for neuroscience research. Broader impacts of this project will be to increase public awareness of neuroscience research through the OpenBehavior website (https://edspace.american.edu/openbehavior), social media, and participation in Society for Neuroscience (SfN) sponsored advocacy and outreach events. The project will facilitate discussions of open source tools through a dedicated and moderated discussion topic in the SfN sponsored Neuronline forums and provide curated itineraries on open source tools for attendees of the annual SfN meeting.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

近年来，神经科学领域受益于计算机语言 Python 等开源工具、现成的 3D 打印方法、Arduino 等低成本微​​控制器以及计算机代码和硬件设计的公共存储库（例如GitHub。许多实验室正在使用这些工具，但大多数实验室不共享其代码和设计。因此，不可能系统地跟踪开源工具的使用及其修订，并且没有开源工具或基准材料（例如动物行为的视频记录）的中央存储库。该奖项将通过创建神经科学领域使用的开源研究工具数据库以及使用这些工具的基准和培训材料存储库来解决这些问题。该项目的具体目标是为神经科学研究中使用的开源工具创建一个分类法，使用该分类法创建和管理开源工具数据库，包括为数据库中的所有工具创建研究资源标识符（RRID），以及传播有关开源工具及其使用所需技能的信息。初始资助期（目标 3）的一个特别重点将是近年来非常流行的动物行为视频分析方法。第三个目标的活动包括创建常用行为任务的视频记录数据库、使用一组通用基准视频（通过该项目开发）进行开放数据分析竞赛，以及开发培训材料以及面对面和虚拟的培训材料。关于制作和使用用于神经科学研究的最流行的开源工具的研讨会。该项目更广泛的影响将是通过 OpenBehavior 网站 (https://edspace.american.edu/openbehavior)、社交媒体以及参与神经科学学会 (SfN) 赞助的宣传和外展活动来提高公众对神经科学研究的认识。该项目将通过 SfN 赞助的 Neuronline 论坛中的专门和主持的讨论主题促进对开源工具的讨论，并为年度 SfN 会议的与会者提供有关开源工具的策划行程。该奖项反映了 NSF 的法定使命，并被认为是值得的通过使用基金会的智力优势和更广泛的影响审查标准进行评估来提供支持。