Computational Infrastructure for Brain Research: EAGER: A Computationally Enabled Knowledge Infrastructure for Cognitive Neuroscience

脑研究的计算基础设施：EAGER：认知神经科学的计算支持知识基础设施

• 批准号: 1649658
• 负责人: Russell Poldrack
• 金额: $ 29.19万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-03-01 至 2020-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1649658&HistoricalAwards=false
• 关键词: Computational; Infrastructure; Brain; Research; EAGER

The Cognitive Atlas is a major online resource for testing hypotheses about the association of neural function to anatomical structures in the human brain. The goal of this project is to greatly enhance the capabilities and performance of the Atlas using state-of-the-art information technologies and national high performance computing (HPC) resources. The result will be a powerful computational tool to assist neuroscience researchers in understanding cognitive and psychological processes and making discoveries about how the brain works, in alignment with the NSF mission to promote the progress of science and to advance the national health, prosperity and welfare.The first aim of the project is to restructure the current Cognitive Atlas database so that it will be able to interface more directly with other computing systems, and so that it can be changed in a more flexible way based on new research. The second aim is to utilize a powerful knowledge query system called Deep Dive to extract new knowledge from neuroscience publications and integrate this knowledge into the Cognitive Atlas. To address the intensive computational demands of Deep Dive, an implementation will be piloted on Wrangler, a high performance data analytics computing system hosted at the Texas Advanced Computing Center. The proposed project will enhance the computing infrastructure for neuroscience in multiple ways. By updating the system to a state-of-the-art graph database infrastructure, this work will allow much greater use of the system for automated analyses. In addition to enabling analysis of the cognitive neuroscience literature at scale for the current project, the implementation of Deep Dive on Wrangler will allow researchers in many other fields to also take advantage of this state-of-the-art application, which could have important benefits across many different areas of science and technology. This Early-concept Grants for Exploratory Research (EAGER) award by the CISE Division of Advanced Cyberinfrastructure is jointly supported by the SBE Division of Behavioral and Cognitive Sciences and the CISE Division of Information and Intelligent Systems, with funds associated with the NSF Understanding the Brain, BRAIN Initiative activities, and for developing national research infrastructure for neuroscience. This project also aligns with NSF objectives under the National Strategic Computing Initiative.

认知地图集是一个主要的在线资源，用于测试有关神经功能与人脑解剖结构之间关系的假设。该项目的目标是利用最先进的信息技术和国家高性能计算资源，大大提高地图集的能力和性能。 其结果将是一个强大的计算工具，以帮助神经科学研究人员了解认知和心理过程，并发现大脑如何工作，与NSF的使命，以促进科学的进步和促进国民健康，该项目的第一个目标是重组目前的认知地图集数据库，使其能够更直接地与其他计算系统，以便它可以根据新的研究以更灵活的方式进行更改。 第二个目标是利用一个名为Deep Dive的强大知识查询系统，从神经科学出版物中提取新知识，并将这些知识整合到认知图谱中。 为了满足Deep Dive的密集计算需求，将在Wrangler上进行试点实施，Wrangler是德克萨斯州高级计算中心托管的高性能数据分析计算系统。 拟议的项目将以多种方式增强神经科学的计算基础设施。通过将该系统更新为最先进的图形数据库基础设施，这项工作将允许更多地使用该系统进行自动分析。除了能够为当前项目大规模分析认知神经科学文献外，在牧马人上实施Deep Dive将使许多其他领域的研究人员也能够利用这种最先进的应用程序，这可能会在许多不同的科学和技术领域产生重要的好处。CISE高级网络基础设施部门的探索性研究（EAGER）早期概念赠款奖由SBE行为和认知科学部门以及CISE信息和智能系统部门共同支持，资金与NSF理解大脑，BRAIN计划活动相关，并用于开发神经科学的国家研究基础设施。该项目也符合国家战略计算计划下的NSF目标。

项目成果

NeuroQuery, comprehensive meta-analysis of human brain mapping

• DOI: 10.7554/elife.53385
• 发表时间: 2020-03-04
• 期刊: ELIFE
• 影响因子: 7.7
• 作者: Dockes, Jerome;Poldrack, Russell A.;Varoquaux, Gael
• 通讯作者: Varoquaux, Gael