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AccelNet: International network for brain-inspired computation

AccelNet：国际类脑计算网络

基本信息

批准号：
2019976
负责人：
Adrienne Fairhall
金额：
$ 75.49万
依托单位：
University of Washington
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：
2021-01-01 至 2024-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2019976&HistoricalAwards=false
关键词：
AccelNet International network brain inspired

项目摘要

Brains have intricate complexity at many scales, from the detailed structure and connections of neurons to the brain-wide swirl of electrical activity that underlies thought and experience. Making sense of these complexities and using new understanding to design improved computational algorithms requires new combinations of research expertise. This AccelNet project builds international links between academic, private research and industrial partners and prepares the next generation of researchers at the interface between neuroscience and artificial intelligence. The project connects leading centers for academic and industry research in the Pacific Northwest, Paris, France, and Montreal, Canada, to advance understanding of brain structure and dynamics and to use these insights to develop more powerful and efficient computing frameworks that can help mankind to solve the very challenging issues now confronting us. This catalytic network of networks will spur advances in brain-inspired computation and fundamental theories of neuroscience, particularly with regard to biophysics and connectivity, the role of neuromodulation in creating rich network dynamics, and analytical methods to characterize and control these dynamics. The project combines expertise of researchers gathering brain data from animals engaged in complex tasks, theorists who make models of cognition, researchers who use machine learning to develop new ways of analyzing data, and experts in artificial intelligence. The network of networks will develop a student cohort with the ability to synthesize findings from new and sophisticated data analysis into novel algorithms for computation, and, vice versa, to translate findings from engineering of computational algorithms into hypotheses for brain function. International experience will enhance research opportunities for undergraduate and graduate students. The ethical emphasis of the network will develop a cohort with substantive experience and training in the application of neuroethics and ethical engineering practices. The Accelerating Research through International Network-to-Network Collaborations (AccelNet) program is designed to accelerate the process of scientific discovery and prepare the next generation of U.S. researchers for multiteam international collaborations. The AccelNet program supports strategic linkages among U.S. research networks and complementary networks abroad that will leverage research and educational resources to tackle grand scientific challenges that require significant coordinated international efforts.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.

大脑在许多方面都具有错综复杂的复杂性，从神经元的详细结构和连接到作为思想和经验基础的全脑范围的电活动漩涡。要理解这些复杂性，并使用新的理解来设计改进的计算算法，需要新的研究专业知识组合。这个AccelNet项目在学术、私人研究和行业合作伙伴之间建立了国际联系，并在神经科学和人工智能之间的接口上培养下一代研究人员。该项目将太平洋西北部、法国巴黎和加拿大蒙特利尔的领先学术和工业研究中心联系起来，以促进对大脑结构和动力学的理解，并利用这些见解开发更强大、更高效的计算框架，帮助人类解决目前面临的非常具有挑战性的问题。这种网络催化网络将推动大脑启发的计算和神经科学基础理论的进步，特别是在生物物理学和连接性、神经调节在创造丰富的网络动力学中的作用以及表征和控制这些动力学的分析方法方面。该项目结合了从从事复杂任务的动物那里收集大脑数据的研究人员、建立认知模型的理论家、利用机器学习开发新的数据分析方法的研究人员以及人工智能专家的专业知识。网络网络将培养一批学生，他们有能力将来自新的和复杂的数据分析的结果综合成用于计算的新算法，反之亦然，将计算算法工程的结果转化为大脑功能的假设。国际经验将增加本科生和研究生的研究机会。该网络的伦理重点将培养一批在应用神经伦理和伦理工程实践方面具有实质性经验和培训的人员。通过国际网络对网络合作加速研究(AccelNet)计划旨在加快科学发现的进程，并为多团队国际合作培养下一代美国研究人员。AccelNet计划支持美国研究网络和海外互补网络之间的战略联系，这些网络将利用研究和教育资源来应对需要大量国际协调努力的重大科学挑战。该奖项反映了NSF的法定使命，并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，被认为值得支持。