GOAL DIRECTED MAGNETIC RESONANCE BRAIN MICROIMAGING

这项提议的中心主题是将新出现的 活体光学和磁共振成像的计算技术 (核磁共振)的发展中的大脑。目的论建模将被采用为 一种优化数据收集和渲染的方法。层次化多- 分辨率图像匹配将被用来融合成相干的整体 通过不同成像模式在不同时间获得的信息 空间和时间分辨率。我们已经召集了一批不同的 具有共同兴趣的计算科学家和神经学家 关于精细结构的形成和习得的几个问题 在发育中的大脑中的复杂功能。在中国有三个项目 这项建议： 神经元连接的多模式成像与分析 激光扫描跟踪标记轴突追踪神经元构型 共聚焦显微镜、双光子显微镜和核磁共振显微镜。发展 新的数据收集策略，新的标记造影剂和 新的软件能够融合不同分辨率、深度、 和情态。 大脑发育的活体图谱 提供发育中的大脑的全面3D活体地图集 不同物种(鹌鹑、小鼠和狐猴)的磁共振显微成像。vbl.使用 FMRI技术，检查猫头鹰猴子的视野如何映射 青少年脑内髓鞘形成程度的变化 动物。 基于目标的三维分析和可视化算法 开发和实施方法以扩展数据的最新水平 三维数据的收集、建模、分析和可视化 有关大脑发育的信息。这些模型包括：目的论模型 便于获取和分析多值、多值、 三维磁共振和光学成像.自动组织的工具 对脑图谱注释至关重要的辨别能力；硬件 和旨在半沉浸式可视化的软件，以及全新的 数据呈现的方法，例如“画图”可视化方案。 四个核心(化学、动物、计算和muMRI)主要提供 为项目提供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.