A SYSTEM TO SHARE AND EXPLORE HUMAN BRAIN MAPPING DATA

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得主要资金， 因此可以在其他CRISP条目中表示。列出的机构是 中心，不一定是研究者的机构。 近年来，影像学技术的发展为人类脑图谱研究者提供了一系列的实验方法，以在不同的空间尺度上阐明大脑的结构和功能。在整个神经科学界，正在收集大量的人脑映射数据。然而，缺乏合适的信息管理系统使这些数据的价值和科学影响无法充分发挥其潜力，因为它几乎完全由原始实验室使用本地可访问的数据和资源进行探索。我们设想了一个全球性的信息管理网络，能够提高神经科学研究人员的创造力和生产力，因为他们使用共享的人脑映射数据来生成和测试数据的原始人没有预料到的想法。为了实现这一愿景，我们建议设计一个开源的信息管理系统，使结构磁共振成像（MRI）数据的探索，分析和控制共享。该系统将在多种模式下灵活运行：作为神经科学界的国际存储库和数据探索平台，作为点对点共享网络的一部分，或作为轻量级的独立实验室信息管理系统。我们预计，创造力和生产力的提高将来自以下能力：1）访问大量的MRI数据集，这些数据集对广泛的人口统计学谱进行采样; 2）通过示例（例如，“检索看起来像这个示例的体积”）和特定的大脑区域属性（例如，体积）来生成和测试神经科学假设; 3）创建、可视化和操纵针对感兴趣的人口统计学人群定制的平均大脑表征;以及4）依赖于一组共同的基本术语和共享原则来促进同伴关系中的交流。该系统的设计将需要在数据建模、查询语言和系统架构等领域开发创新的信息学技术。它将在规模上可扩展，在功能上可扩展，在数据共享策略选项上灵活，并且在格式上与其他神经信息系统兼容。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Recent advances in imaging technologies have provided human brain mapping researchers with awide repertoire of experimental approaches to elucidate brain structure and function at a variety of spatial scales. Over the entire neuroscience community, a vast amount of human brain mapping data is being gathered. However, lack of suitable a information management system keeps the value and scientific impact of this data from reaching its full potential, as it is explored almost exclusively by the lab of origin using data and resources which are locally accessible. We envision a worldwide information management network capable of increasing the creativity and productivity of neuroscience investigators, as they use shared human brain mapping data to generate and test ideas that were unanticipated by the data's originators. To achieve this vision, we propose to design an open source information management system that enables the exploration, analysis, and controlled sharing of structural magnetic resonance imaging (MRI) data. This system will function flexibly in multiple modes: as an international repository and data exploration platform for the neuroscience community, as part of a peer-to-peer sharing network, or as a lightweight stand-alone laboratory information management system. We expect that increased creativity and productivity will derive from the ability to: 1) access a large number of MRI datasets that sample a broad demographic spectrum; 2) query by example (e.g. "retrieve volumes which look like this example") and over specific brain region attributes (e.g., volume) to generate and test neuroscientific hypotheses; 3) create, visualize, and manipulate average brain representations tailored to a demographic population of interest; and 4) rely on a common set of basic terms and sharing principles to faciliate communication in peer relationships. The system's design will entail the development of innovative informatics techniques in the areas of data modeling, query languages, and systems architecture. It will be scalable in size, extensible in capabilities, flexible in data sharing policy options, and compatible in format with other neuroinformatic systems.