Computational Infrastructure for Brain Research: EAGER: A Unified Computational Framework for Analysis, Storage, and Visualization of 3D Brain Microscopy Data

脑研究的计算基础设施：EAGER：用于 3D 脑显微镜数据分析、存储和可视化的统一计算框架

• 批准号: 1649916
• 负责人: Jason Stein
• 金额: $ 30万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1649916&HistoricalAwards=false
• 关键词: Computational; Infrastructure; Brain; Research; EAGER

Our understanding of nervous system function is critically dependent on visualizing the three-dimensional structure of the brain. The brain is composed of many cell types that are organized into complex networks to produce neural functions such as cognition. The brains of patients with neuropsychiatric illness often display disorganized cell placement as compared to brains of healthy individuals. It is therefore fundamentally important to determine how the details of cell type and organization relate to cognition and behavior. Recent advances in structural brain imaging have enabled the possibility for creating digital data sets of complete intact brain specimens at cellular resolution. However, given the enormous number of neurons in the mammalian brain, the data sets produced with these techniques are so large as to hamper the research process. In this project, we will present a novel computational infrastructure framework that addresses this challenge, with the ultimate aim of facilitating collaboration among laboratories that generate and use these large cellular imaging data sets for neuroscience discovery. This project therefore aligns with the NSF mission to promote the progress of science and to advance the national health, prosperity and welfare. Recent innovations in tissue clearing techniques and light sheet microscopy allow the rapid acquisition of three-dimensional micron resolution images in fluorescently labeled brain samples. However, the enormous size of the resulting information-dense data sets present great computational challenges to sharing, analysis, and visualization of these data in a standardized manner across multiple laboratories. In this project, the combined expertise of three connected and complementary centers associated with the University of North Carolina at Chapel Hill will be leveraged to address this issue through development of a unified and highly scalable computational infrastructure framework that can be harnessed by the neuroscience community. The several aims are to develop cyberinfrastructure for the distributed storage, sharing and analysis of high-dimensional images; develop high throughput computational tools for quantitative analysis of 3D microscopy images; provide the means for efficient visualization of results using immersive environments; and demonstrate the utility of these tools by applying them to the analysis, sharing, and visualization of brain structure deficits in an autism mouse model.This Early-concept Grants for Exploratory Research (EAGER) award by the CISE Division of Advanced Cyberinfrastructure is jointly supported by the CISE Division of Information and Intelligent Systems, with funds associated with the NSF Understanding the Brain, BRAIN Initiative activities, and developing national research infrastructure for neuroscience. This project also aligns with NSF objectives under the National Strategic Computing Initiative.

我们对神经系统功能的理解主要依赖于大脑三维结构的可视化。大脑由许多细胞类型组成，这些细胞被组织成复杂的网络，以产生神经功能，如认知。与健康个体的大脑相比，患有神经精神疾病的患者的大脑通常显示出混乱的细胞放置。因此，确定细胞类型和组织的细节如何与认知和行为相关是至关重要的。结构脑成像的最新进展使创建完整完整的脑标本在细胞分辨率的数字数据集的可能性。然而，鉴于哺乳动物大脑中神经元的数量巨大，使用这些技术产生的数据集非常大，以至于阻碍了研究过程。 在这个项目中，我们将提出一个新的计算基础设施框架，以应对这一挑战，最终目的是促进实验室之间的合作，生成和使用这些大型细胞成像数据集进行神经科学发现。因此，该项目符合NSF的使命，以促进科学的进步和推进国家的健康，繁荣和福利。最近的创新，在组织清除技术和光片显微镜允许快速收购的三维微米分辨率的图像在荧光标记的大脑样本。然而，由此产生的信息密集型数据集的巨大规模对跨多个实验室以标准化方式共享、分析和可视化这些数据提出了巨大的计算挑战。在这个项目中，与查佩尔山的北卡罗来纳州大学相关的三个连接和互补中心的综合专业知识将通过开发一个统一的、高度可扩展的计算基础设施框架来解决这个问题，该框架可以被神经科学界利用。几个目标是开发用于分布式存储、共享和分析高维图像的网络基础设施;开发用于3D显微图像定量分析的高通量计算工具;提供使用沉浸式环境有效可视化结果的手段;并通过将这些工具应用于分析，共享，和自闭症小鼠模型中大脑结构缺陷的可视化。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CISE信息和智能系统部门共同支持，与NSF理解大脑，脑倡议活动，并发展神经科学的国家研究基础设施相关的资金。该项目也符合国家战略计算计划下的NSF目标。