NBO: ABI Innovation: Multiscale Multimodal Mouse Connectomes

NBO：ABI 创新：多尺度多模式小鼠连接体

• 批准号: 1564736
• 负责人: Tianming Liu
• 金额: $ 42.55万
• 依托单位: University of Georgia Research Foundation Inc
• 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: 2016-05-01 至 2021-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1564736&HistoricalAwards=false
• 关键词: NBO; ABI; Innovation; Multiscale; Multimodal

The aim of this project is to map neural circuits and their activities in the mouse brain, from the small scale level of the synapse to the neurons involved, their larger circuits, up to overall neural systems. Different data modalities will be merged in order to carry out this integration. Mapping the brain can mean showing the layout of anatomical features, showing where functional connections occur, or both, as for this project. Different features require different data collection modalities, and merging these different types of data correctly is one of several technically challenging tasks this research will perform. This type of multiscale, multimodal brain mapping is one of the scientific Grand Challenges, as such it is a top U.S.A. research priority, one recognized by the BRAIN initiative. This award will contribute to NSF's commitment to develop a National Brain Observatory (NBO) to enable this initiative. By integrating structural and functional connectomics, this project will show how they work together when brain circuits change with different activities. By deciphering and measuring of real-time neural codes this research will let us better understand how brain activities create unique cognitive and behavioral capabilities. The project includes plans to integrate the research data and techniques into educational and outreach activities, encouraging interest in neuroscience research in the next generation of scientists. The objective of this project is to create a multiscale, multimodal mouse connectome for better understanding of brain function. Specifically, the project aims include: 1) construct, cross-validate, fuse, and integrate multiscale multimodal mouse brain connectomes, including macro-scale mouse connectomes based on diffusion tensor imaging (DTI), Susceptibility Tensor Imaging (STI) data, and meso-scale mouse connectomes based on publicly available serial two-photon tomography data; 2) utilize multiscale structural connectomes for exploration of functional connectomics and circuitry dynamics, in particular, focusing on the fear memory system; and 3) design, develop and disseminate the structural and functional connectomics tools and resources to the brain mapping research community. To achieve the above goals, the investigators will design and apply innovative computational and informatics methodologies and approaches for multiscale mouse connectomics research. Specifically, both mesoscale and macroscale structural connectivity data will be used as follows. First, the Allen Mouse Brain Connectivity Atlas (ACA) will be used, which provides a comprehensive meso-scale mouse brain neuronal connectivity map via anterogradely traced axonal projections using serial two-photon tomography from over one thousand different injection sites. Second, at the macro-scale, the noninvasive diffusion tensor (DT) microimaging technique will be used to track global fiber connections in the whole mouse brain at the micron-scale spatial resolution. Subsequently data will be fused and integrated, to acquire the advantages of both meso-scale serial two-photon tomography data and macro-scale DT microimaging data when constructing and cross-validating multi-scale, multimodal mouse connectomes. Finally, these structural connectomes will be the basis for exploring functional connectomics and circuitry dynamics, thus significantly advancing the understanding of brain structure and function and their relationships. All of these structural and functional connectomics tools will be released to the brain science community at the project website: http://mbm.cs.uga.edu/

这个项目的目的是绘制老鼠大脑中的神经回路和它们的活动，从突触的小尺度到涉及的神经元，它们的大回路，到整个神经系统。不同的数据模式将被合并，以实现这种集成。绘制大脑图谱意味着显示解剖特征的布局，显示功能连接发生的位置，或者两者兼而有之，就像这个项目一样。不同的特征需要不同的数据收集方式，正确合并这些不同类型的数据是本研究将执行的几个技术挑战性任务之一。这种多尺度、多模式的大脑图谱是科学大挑战之一，因此它是美国研究的重中之重，得到了brain计划的认可。该奖项将有助于NSF开发国家脑天文台（NBO）的承诺，以实现这一倡议。通过整合结构和功能连接组学，该项目将展示当大脑回路因不同活动而改变时，它们是如何协同工作的。通过破译和测量实时神经编码，这项研究将让我们更好地了解大脑活动如何创造独特的认知和行为能力。该项目包括将研究数据和技术整合到教育和推广活动中，鼓励下一代科学家对神经科学研究的兴趣。该项目的目标是创建一个多尺度、多模态的小鼠连接组，以便更好地了解大脑功能。具体而言，该项目的目标包括：1)构建、交叉验证、融合和整合多尺度多模态小鼠脑连接体，包括基于扩散张量成像（DTI）、敏感性张量成像（STI）数据的宏观尺度小鼠脑连接体，以及基于公开的串行双光子断层扫描数据的中尺度小鼠脑连接体；2)利用多尺度结构连接体探索功能连接体和电路动力学，特别是对恐惧记忆系统的研究；3)设计、开发和传播结构和功能连接组学工具和资源给脑图谱研究社区。为了实现上述目标，研究人员将设计和应用创新的计算和信息学方法和方法进行多尺度小鼠连接组学研究。具体来说，中尺度和宏观尺度的结构连通性数据将使用如下。首先，将使用Allen小鼠大脑连接图谱（ACA），该图谱通过使用来自1000多个不同注射部位的串行双光子断层扫描顺行跟踪轴突投影，提供了一个全面的中尺度小鼠大脑神经元连接图谱。其次，在宏观尺度上，采用无创扩散张量（DT）微成像技术，在微米尺度空间分辨率上跟踪小鼠全脑内的全局纤维连接。在构建和交叉验证多尺度、多模态小鼠连接体时，数据将被融合和集成，以获得中尺度连续双光子断层成像数据和宏观尺度DT微成像数据的优势。最后，这些结构连接体将成为探索功能连接组和电路动力学的基础，从而显著推进对大脑结构和功能及其关系的理解。所有这些结构和功能连接组学工具将在项目网站http://mbm.cs.uga.edu/上发布给脑科学社区