STRUCTURAL INFORMATION FRAMEWORK FOR BRAIN MAPPING

这项工作的长期目标是开发一个信息系统，用于 术中皮质语言的组织、可视化和管理 测绘数据，作为这类神经科学信息系统的试验床 人脑计划所设想的。语言一直是，并将继续 通过许多不同的方法进行探索，并且集成和 多通道信息的相关性是 产生和检验试图解释表面现象的假说 大脑皮质语言地图的不同模式。在前两年半期间 多年来，我们已经开发了绘制地图的方法 术中数据到基于3-D MR的患者自己的重建 Brain，并在一个基于Web的信息系统中实现了这些方法 它将可视化和地图绘制与多媒体数据库相结合。这个 手术部位在个性化神经解剖学上的标测 重建提供了手术获得的 刺激标测数据和无创功能成像方法。在……里面 我们将在现有系统的基础上开展拟议的工作，以便 改进的信息学工具，用于生成和管理这些3-D地图，以及 我将使用这些工具作为比较来自多个 不同的医疗模式和多个患者。这项建议的具体目的 正在开发和推广用于：1)术中标测的方法 皮质语言数据到基于MRI的患者的3-D重建 自己的大脑，2)管理基于Web的多媒体信息中的语言数据 系统，3)集成来自单个患者的多模式数据，以及4) 集成来自多个患者的多模式数据，同时获得 本地和来自Internet上的远程站点。

The long term goal of this work is to develop an information system for organizing, visualizing and managing intra-operative cortical language mapping data, as a testbed for neuroscience information systems of the kind envisioned by the Human Brain Project. Language has been, and continues to be explored through many different approaches, and the integration and correlation of multimodality information is a prerequisite for the generation and testing of hypotheses that seek to explain the apparent variable patterns of cortical language maps. During the first two and half years of this project we have developed methods for mapping the intraoperative data onto a 3-D MR-based reconstruction of the patient's own brain, and have implemented these methods in a Web-based information system that combines visualization and mapping with a multimedia database. The mapping of surgical sites onto an individualized neuroanatomical reconstruction provides a key missing link between surgically-obtained stimulation mapping data and non-invasive functional imaging methods. In the proposed work we will build on the present system in order to develop improved informatics tools for generating and managing these 3-D maps, and will use these tools as a basis for comparing language data from multiple modalities and from multiple patients. The specific aims of this proposal are to develop and extend methods for: 1) mapping intra-operative cortical language data onto a 3-D MRI-based reconstruction of the patient's own brain, 2) managing language data in a Web-based multimedia information system, 3) integrating multimodality data from a single patient, and 4) integrating multimodality data from multiple patients, obtained both locally and from remote sites on the Internet.