BD Spokes: SPOKE: MIDWEST: Collaborative: Advanced Computational Neuroscience Network (ACNN)

BD 辐条：辐条：中西部：协作：高级计算神经科学网络 (ACNN)

• 批准号: 2148729
• 负责人: Franco Pestilli
• 金额: $ 33.29万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-11-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2148729&HistoricalAwards=false
• 关键词: BD; Spokes; SPOKE; MIDWEST; Collaborative

Novel neuroscience tools and techniques are necessary to enable insight into the building blocks of neural circuits, the interactions between these circuits that underpin the functions of the human brain, and modulation of these circuits that affect our behavior. To leverage rapid technological development in sensing, imaging, and data analysis new ground breaking advances in neuroscience are necessary to facilitate knowledge discovery using data science methods. To address this societal grand challenge, the project will foster new interdisciplinary collaborations across computing, biological, mathematical, and behavioral science disciplines together with partnerships in academia, industry, and government at multiple levels. The Big Data Neuroscience Spoke titled Midwest: Advanced Computational Neuroscience Network (ACNN) is strongly aligned with the national priority area of neuroscience and brings together a diverse set of committed regional partners to enable the Midwest region to realize the promise of Big Data for neuroscience. The ACNN Spoke will build broad consensus on the core requirements, infrastructure, and components needed to develop a new generation of sustainable interdisciplinary Neuroscience Big Data research. ACNN will leverage the strengths and resources in the Midwest region to increase innovation and collaboration for the understanding of the structure, physiology, and function of the human brain through partnerships and services in education, tools, and best practices. The ACNN will design, pilot and support powerful neuroscientific computational resources for high-throughput, collaborative, and service-oriented data aggregation, processing and open-reproducible science. The ACNN Spoke framework will address three specific problems related to neuroscience Big Data: (1) data capture, organization, and management involving multiple centers and research groups, (2) quality assurance, preprocessing and analysis that incorporates contextual metadata, and (3) data communication to software and hardware computational resources that can scale with the volume, velocity, and variety of neuroscience datasets. The ACNN will build a sustainable ecosystem of neuroscience community partners in both academia and industry using existing technologies for collaboration and virtual meeting together with face-to-face group meetings. The planned activities of the ACNN Spoke will also allow the Midwest Big Data Hub to disseminate additional Big Data technologies resources to the neuroscience community, including access to supercomputing facilities, best practices, and platforms.This award received co-funding from CISE Divisions of Advanced Cyberinfrastructure (ACI) and Information and Intelligent Systems (IIS).

新的神经科学工具和技术对于深入了解神经回路的组成部分、支撑人类大脑功能的这些回路之间的相互作用以及影响我们行为的这些回路的调节是必要的。为了利用传感、成像和数据分析领域的快速技术发展，有必要在神经科学领域取得新的突破性进展，以促进使用数据科学方法进行知识发现。为了应对这一巨大的社会挑战，该项目将促进跨计算、生物、数学和行为科学学科的跨学科合作，并与学术界、工业界和政府在多个层面上建立伙伴关系。大数据神经科学演讲题为中西部：高级计算神经科学网络（ACNN）与国家神经科学优先领域紧密结合，并汇集了一系列不同的致力于区域合作伙伴，使中西部地区能够实现神经科学大数据的承诺。ACNN Spoke将在核心要求、基础设施和开发新一代可持续跨学科神经科学大数据研究所需的组件方面建立广泛共识。ACNN将利用中西部地区的优势和资源，通过在教育、工具和最佳实践方面的伙伴关系和服务，增加对人类大脑结构、生理和功能的理解的创新和合作。ACNN将设计、试验和支持强大的神经科学计算资源，用于高通量、协作和面向服务的数据聚合、处理和开放可再生科学。ACNN Spoke框架将解决与神经科学大数据相关的三个具体问题：(1)涉及多个中心和研究小组的数据捕获、组织和管理；(2)结合上下文元数据的质量保证、预处理和分析；(3)与软件和硬件计算资源的数据通信，这些计算资源可以随着神经科学数据集的数量、速度和种类进行扩展。ACNN将利用现有的协作技术和虚拟会议以及面对面的小组会议，为学术界和工业界的神经科学社区合作伙伴建立一个可持续的生态系统。ACNN Spoke的计划活动还将允许中西部大数据中心向神经科学社区传播额外的大数据技术资源，包括访问超级计算设施、最佳实践和平台。该奖项由CISE高级网络基础设施（ACI）和信息与智能系统（IIS）部门共同资助。

项目成果

Development of white matter tracts between and within the dorsal and ventral streams

• DOI: 10.1007/s00429-021-02414-5
• 发表时间: 2021-01
• 期刊: Brain Structure and Function
• 影响因子: 3.1
• 作者: S. Vinci-Booher;B. Caron;D. Bullock;K. James;F. Pestilli