NSF Postdoctoral Fellowship in Biology FY 2010

这一行动为2010财年美国国家科学基金会博士后研究奖学金提供资金。该奖学金为Peter Li支持一项名为《理解大规模并行神经计算：来自数千个神经元的同时记录的下一代分析》的研究和培训计划。这项研究的主办机构是索尔克生物研究所，赞助科学家是E.J.奇奇尔尼斯基。要理解神经系统的大规模并行计算，需要高分辨率的技术来同时监测电路中许多神经元的活动，并结合数学方法来分析和解释结果。最近的技术进步允许同时记录数千个视网膜神经节细胞(眼睛中处理关于视觉世界的信息并将信息传输到大脑的神经元)。该项目实现了大规模并行神经记录的下一代计算分析。例如：许多已知的视网膜神经节细胞亚型是如何并行工作的？技术挑战包括海量数据和高计算要求。因此，该项目的一个组成部分是利用高性能超级计算集群，既允许进行在标准计算机上不切实际的新分析，又允许在这个大型(约100 TB)现有数据归档上高效部署分析。该项目的培训目标包括建立系统分析、泛函分析和信息论的数学知识，这些都是当今生物学研究领域中有价值的技能。了解视觉是如何工作的，将是一项非凡的胜利，也是迈向解开大脑奥秘这一更大目标的重要踏脚石。通过将人类的视觉和认知与其他物种的能力和专业性进行比较，正在获得有价值的知识。

This action funds an NSF Postdoctoral Research Fellowship for FY 2010. The fellowship supports a research and training plan entitled "Understanding massively parallel neural computations: next-generation analysis of simultaneous recordings from thousands of neurons" for Peter Li. The host institution for this research is Salk Institute for Biological Studies, and the sponsoring scientist is E.J. Chichilnisky. Understanding the massively parallel computations of the nervous system requires high-resolution techniques for monitoring the activity of many neurons in a circuit simultaneously, combined with mathematical approaches to analyze and interpret the results. Recent advances in technologies allow simultaneous recording of thousands of retinal ganglion cells (neurons in the eye that process information about the visual world and transmit that information to the brain). This project implements next-generation computational analyses for massively parallel neural recordings. For example: how do the many known subtypes of retinal ganglion cells work in parallel? Technical challenges include large volumes of data and high computing demands. Thus, one component of the project is leveraging high-performance supercomputing clusters, both to allow new analyses that would be impractical on standard computers, and to allow efficient deployment of analyses over this large (~100 TB) existing data archive. Training goals for this project include building mathematical knowledge in systems analysis, functional analysis, and information theory, which are valuable skills in today's biological research fields. Understanding how vision works would be a singular triumph as well as a major stepping stone towards the greater goal of unlocking the mysteries of the brain. Valuable knowledge is being gained by comparing human vision and cognition to the abilities and specializations of other species.