GOAL DIRECTED MAGNETIC RESONANCE BRAIN MICROIMAGING

该提案的中心主题是应用新兴的 体内光学和磁共振成像的计算技术 （MRI）发育中的大脑。目的论模型将被用作 一种优化数据收集和渲染的方法。层次多 分辨率图像匹配将用于融合成一个连贯的整体 通过不同的成像方式在不同的时间段获得的信息 空间和时间分辨率。我们聚集了一支多元化的团队 对解决问题有共同兴趣的计算科学家和神经科学家 关于复杂结构的形成和收购的问题 发育中大脑的复杂功能。共有三个项目 该提案： 神经元连接的多模态成像和分析 通过激光扫描跟踪标记的轴突来追踪神经元模式 共焦显微镜、双光子显微镜和 MRI 显微镜。开发 收集数据的新策略、用于标记的新造影剂和 新软件能够融合不同分辨率、深度的数据， 和情态。 大脑发育体内图谱 提供发育中大脑的综合 3D 体内图谱，分为三个阶段 使用 MR 显微成像对不同物种（鹌鹑、小鼠和狐猴）进行观察。使用 功能磁共振成像技术，检查猫头鹰猴子的视野图 随着年轻人大脑髓鞘形成程度的增加而变化 动物。 用于 3D 分析和可视化的基于目标的算法 开发和实施方法来扩展数据的最新技术水平 三维数据的采集、建模、分析和可视化 有关大脑发育的信息。这些包括： 目的论模型 促进多值多值的获取和分析 三维 MR 和光学图像；自动化组织工具 区分对于脑图谱注释至关重要；硬件 和旨在半沉浸式可视化的软件，以及全新的 数据渲染方法，例如“绘画式”可视化方案。 四个核心（化学、动物、计算和 muMRI）主要提供 项目的基础设施和后勤支持。

The central theme of this proposal is to apply newly emerging computational techniques to in vivo optical and Magnetic Resonance Imaging (MRI) of the developing brain. Teleological modeling will be employed as a method of optimizing data collection and rendering. Hierarchical multi- resolution image matching will be used to meld into a coherent whole the information obtained through different imaging modalities at different spatial and temporal resolutions. We have assembled a diverse group of computational and neuro-scientists with a common interest in addressing questions about the formation of elaborate structures and the acquisition of complex function in the developing brain. There are three Projects in this proposal: Multi-modal Imaging and Analysis of Neuronal Connectivity Trace neuronal patterning by following labeled axons with laser scanning confocal microscopy, two-photon microscopy, and MRI microscopy. Develop new strategies for collecting data, new contrast agents for labeling and new software capable for melding data of different resolutions, depths, and modality. In Vivo Atlases of Brain Development Provide comprehensive 3D in vivo atlases of the developing brain in three different species (quail, mouse, and lemur) using MR micro-imaging. Using fMRI techniques, examine how the visual field map of the owl monkey changes with increasing degree of myelination in brain of the young animal. Goal-Based Algorithms for 3D Analysis and Visualization Develop and implement methods to extend the state of the art in data collection, modeling, analysis, and visualization of three-dimensional information about the developing brain. These include: teleological models that facilitate the acquisition and analysis of multi-valued multi- dimensional MR and optical images; tools for automated tissue discrimination that will be essential for brain atlas annotation; hardware and software aimed at semi-immersive visualization, as well as whole new approaches to data rendering such as "painterly" visualization schemes. The four Cores (Chemistry, Animal, Computation, and muMRI) chiefly provide infrastructure and logistical support for the Projects.