GOAL DIRECTED MAGNETIC RESONANCE BRAIN MICROIMAGING

该提案的中心主题是应用新出现的 计算技术在体内光学和磁共振成像 (MRI)发育中的大脑。目的论建模将被用作 一种优化数据收集和呈现的方法。分层多 分辨率图像匹配将用于融合成一个连贯的整体， 通过不同成像模式在不同时间获得的信息 空间和时间分辨率。我们召集了一群不同的 计算和神经科学家，他们对解决 关于复杂结构的形成和习得的问题 复杂功能的一部分。有三个项目， 这一提议： 神经元连接的多模态成像和分析 用激光扫描跟踪标记的轴突追踪神经元图案 共聚焦显微镜、双光子显微镜和MRI显微镜。发展 用于收集数据的新策略，用于标记的新造影剂， 新的软件能够融合不同分辨率，深度， 和模态。 脑发育的体内模型 在三个方面提供发育中大脑的全面3D体内图谱 不同物种（鹌鹑，小鼠和狐猴）使用MR显微成像。使用 功能磁共振成像技术，检查猫头鹰猴的视野图， 随着年轻人脑中髓鞘形成程度的增加而变化 动物 基于目标的三维分析与可视化算法 开发和实施方法，以扩展数据的最新技术水平 收集、建模、分析和三维可视化 关于大脑发育的信息其中包括：目的论模型 这有助于获取和分析多值多- 三维MR和光学图像;自动组织工具 对脑图谱注释至关重要的辨别;硬件 和软件，旨在半沉浸式可视化，以及全新的 数据渲染的方法，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 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.