A SYSTEM TO SHARE AND EXPLORE HUMAN BRAIN MAPPING DATA

共享和探索人脑图谱数据的系统

• 批准号: 7627678
• 负责人: KEN SMITH
• 金额: $ 1万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-30 至 2008-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7627678
• 关键词: Architecture; Area; Brain; Brain Mapping; Brain region; Communication; Communities; Compatible; Computer Retrieval of Information on Scientific Projects Database; Creativeness; Data; Data Set; Databases; Development; Funding; Grant; Human; Imaging technology; Informatics; Information Management; Institution; International; Laboratories; Language; Magnetic Resonance Imaging; Management Information Systems; Neurosciences; Numbers; Policies; Population; Productivity; Research; Research Personnel; Resources; Sampling; Source; Structure; System; Techniques; Testing; United States National Institutes of Health; Vision; data modeling; design; innovation; interest; neuroinformatics; open source; peer; size

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.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 成像技术的最新进展为人脑映射研究人员提供了实验方法，以阐明各种空间尺度的大脑结构和功能。在整个神经科学社区中，正在收集大量的人脑映射数据。但是，缺乏合适的信息管理系统可以使该数据的价值和科学影响无法达到其全部潜力，因为使用本地可访问的数据和资源，原始实验室几乎完全探讨了这些数据的潜力。我们设想了一个能够提高神经科学研究者的创造力和生产力的全球信息管理网络，因为他们使用共享的人脑映射数据来生成和测试数据的发起人意外的想法。为了实现这一愿景，我们建议设计一个开源信息管理系统，该系统能够探索，分析和控制结构磁共振成像（MRI）数据。该系统将在多种模式下灵活地运行：作为神经科学社区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，或作为轻巧的独立实验室信息管理系统。我们期望提高的创造力和生产力将源于以下能力：1）访问大量人口统计学谱系的大量MRI数据集； 2）通过示例查询（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）以生成和检验神经科学方面的假设； 3）创建，可视化和操纵针对感兴趣的人群量身定制的平均大脑表示； 4）依靠一组常见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，查询语言和系统体系结构领域的创新信息学技术开发。它的大小可扩展，功能可扩展，数据共享策略选项的灵活性以及与其他神经信息系统兼容。