Mathematical/Computational Tools for Mapping Brain Data Bases

现代全脑冷冻切片和数字化技术与现代组织切片和染色方法相结合，使解剖学家能够提供有关个体大脑解剖结构和功能的详细活体信息。 困难在于两个方面：必须配准同一解剖结构内的图像和切片。 但更根本的是，即使配准，不同解剖结构之间的正常变化也使得解剖结构间数据的汇集变得困难，如果不是不可能的话。在这个建议中，我们努力发展算法工具，以融合解剖学和功能学。 通过猕猴脑中的全脑冷冻切片（0.05- 0.1mm分辨率）和染色组织切片测量的数据。 这项建议的主要重点是开发成年猕猴中所表现出的，允许将单个图谱映射到多个个体目标。该图谱包含对我们工作中的研究者具有生物学意义的所有子体积，这些子体积包括脑沟和脑回、丘脑深核、脑室和枕叶中的各种子区域，包括初级视觉皮层（V1区）和其他视觉区域。我们的表示提供了一个工具，算法生成的光滑地图（地图保持微分 几何长度、面积、体积）， 一个 图谱（模板）及其子体积与目标解剖结构家族的关系。 这些地图允许融合和汇集几何和生理信息从不同的实验准备到一个共同的坐标系或数据库。 作为 作为正常猕猴解剖学变异性的这种表示的一部分，将从代表性猕猴全脑解剖学的家族构建概率测量。 概率测量行为脑解剖中的正常解剖变异。这将为神经解剖学家提供一个直接的工具，用于将他们的样本放置到一个具有精确确定性或置信度的公共坐标系中。这种解剖变异性的测量反映了预定义的解剖标记区域的潜在稳定性，即子区域和体积，如脑沟、眼内和不同的视觉区域，以及它们相对于单个生物学上有意义的坐标系的协变。

Modern whole brain cryosection and digitization techniques coupled to modern tissue section and staining methods allow anatomists to provide exquisitely detailed in vivo information regarding the anatomical structure and function of individual brains. The difficulty lies in two areas: images and sections within the same anatomy must be registered. But more fundamentally, even when registered, normal variation across disparate anatomes makes pooling of inter anatomical data difficult, if not impossible. In this proposal, we strive towards the development of algorithmic tools for the fusion of anatomical and functional data as measured via gross whole brain cryosections (0.05-0.1 mm resolution) and stained tissue sections in the macaque monkey brain. The major focus of this proposal is on the development of _ as manifest in the adult macaque, allowing for the mapping of a single atlas to multiple individual targets. The atlas contains all subvolumes of biological significance to the investigator in our work these would include the sulci and gyri, deep thalamic nuclei, ventricles and various sub areas in the occipital lobe, including primary visual cortex (area V1) and other visual areas. Our representations provide a tool for the algorithmic generation of smooth maps (maps preserving differential geometric lengths, areas, volumes) from an atlas (template) and its subvolumes to a family of target anatomies. These maps allow for the fusion and pooling of geometric and physiologic information from varied experimental preparations into one common coordinate system or data base. As part of such a representation of normal macaque anatomical variability, a probabilistic measure will be constructed from a family of representative macaque whole brain anatomies. The probability measures normal anatomical variation in act ual brain anatomy. This will provide neuroanatomists with a direct tool for placing their samples into a common coordinate system with a precise degree of certainty or confidence. Such a measure of anatomical variability reflects both the underlying stability of pre-defined anatomically labeled regions, i.e. subareas and volumes such as sulci, eyri, and different visual areas and their covariation relative to a single biologically meaningful coordinate system.