CRCNS data sharing: Whole Mouse Brain Neuronal Morphology and Neurovasculature Browser

该奖项支持从刀口扫描显微镜（KESM）获得的高分辨率、高质量的全小鼠脑神经元和血管数据的准备和共享。KESM能够在100小时内以小于1微米的分辨率对整个小动物器官（如小鼠大脑）进行切片和成像，每个标本的数据量超过2tb。KESM数据的数量和复杂性要求在数据组织、存储/检索和传播方面采用创新方法。研究小组将开发一个用于三维体数据传播和可视化的信息学框架。KESM由PI的实验室开发，目前已被用于解剖和成像两只完整的老鼠大脑，一只用高尔基染色来显示神经元形态，另一只用印度墨水来显示微血管网络的细节。与其他当前可用的数据集相比，这两个数据集在细节和范围上是独一无二的（沿着x、y和z轴的一个或多个分辨率更高的数量级，和/或成像体积的范围更高）。这些数据使研究人员能够对各种形态统计及其在不同脑区和核中的变异性进行全面的定量分析，估计形态学参数进行计算模拟，最终帮助将结构与功能联系起来。将采用一种混合方法，在多尺度数据方案下集成基于web的轻量级数据浏览器和本地数据查看器/分析器。该项目的具体目标如下：(1)标准化的数据集，以改善与其他数据源的访问和互操作性；(2)轻量级的基于web的卷浏览器，具有开放的应用程序编程接口（API），以增强访问和注释的自由；(3)单元卷查看器，用于通过基于web的接口下载的小单元卷的可视化和分析。数据和软件工具，包括文档，将在公共领域发布，以建立一个用户/开发人员社区，帮助框架的继续使用和发展。

This award supports the preparation and sharing of high-resolution, high-quality, whole mouse brain neuronal and vascular data obtained from the Knife-Edge Scanning Microscope (KESM). KESM is capable of slicing and imaging whole small animal organs (such as the mouse brain) at less than 1 um resolution within 100 hours, with a resulting data size exceeding 2 TB per specimen. The amount and complexity of the KESM data necessitates innovative approaches in data organization, storage/retrieval, and dissemination. The research team will develop an informatics framework for 3D volume data dissemination and visualization.The KESM, developed and housed in the PI's laboratory, has been used to dissect and image two whole mouse brains so far, one stained in Golgi to reveal the neuronal morphology, and the other in India ink to show the microvascular network in fine detail. The two data sets are unique in their detail and extent compared to other currently available data sets (orders of magnitude higher resolution along one or more of the x-, y-, and z-axis, and/or higher extent in the imaged volume). Such data enable researchers to conduct a full quantitative analysis of various morphological statistics and their variability across different brain regions and nuclei, estimate morphological parameters for computational simulation, and eventually help link structure to function.A hybrid approach will be employed that integrates a web-based light-weight data browser and a local data viewer/analyzer, under a multi-scale data scheme. The specific objectives of this project are as follows: (1) Standardized data sets for improved access and interoperability with other data sources, (2) Light-weight web-based volume browser with an open Application Programming Interface (API) for enhanced freedom of access and annotation, and (3) Unit volume viewer for the visualization and analysis of small unit volumes downloaded through the web-based interface.The data and software tools, including documentation, will be released in the public domain, to build a user/developer community that will help continued use and evolution of the framework.