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.

大脑在许多尺度上具有复杂的复杂性，从神经元的详细结构和连接到思想和经验的脑活动的整个电动活动漩涡。理解这些复杂性，并利用新的理解来设计改进的计算算法需要研究专业知识的新组合。这个Accelnet项目建立了学术，私人研究与工业伙伴之间的国际联系，并在神经科学与人工智能之间的界面上准备了下一代研究人员。该项目将西北太平洋，巴黎，法国和加拿大蒙特利尔的主要学术和行业研究中心联系起来，以提高人们对大脑结构和动态的了解，并使用这些见解来开发更强大，有效的计算框架，这些框架可以帮助人类解决现在面对我们的非常具有挑战性的问题。这种网络的催化网络将刺激在脑启发的计算和神经科学的基本理论方面的进步，尤其是在生物物理学和连接性方面，神经调节在创建丰富的网络动态中的作用以及表征和控制这些动态的分析方法。该项目结合了研究人员的专业知识，这些研究人员从从事复杂任务的动物中收集大脑数据，制定认知模型的理论家，使用机器学习来开发分析数据的新方法的研究人员以及人工智能的专家。网络网络将开发一个学生队列，能够将新和复杂的数据分析的发现合成为计算的新算法，反之亦然，从而将计算算法工程的发现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。该网络的道德重点将在神经伦理学和道德工程实践的应用中发展具有实质性经验和培训。通过国际网络到网络合作（ACCELNET）计划进行加速研究旨在加速科学发现的过程，并为下一代美国研究人员做好了多次国际合作的准备。 Accelnet计划支持美国研究网络和国外互补网络之间的战略联系，这些联系将利用研究和教育资源来应对需要重大协调的国际努力的宏伟科学挑战。该奖项反映了NSF的法定使命，并认为通过使用该基金会的智力和更广泛的影响来评估CRITERIA的评估。