FUNCTION BIRN

功能伯恩

• 批准号: 8173355
• 负责人: STEVEN G POTKIN
• 金额: $ 249.63万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-12-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8173355
• 关键词: Algorithms; Behavioral; Clinical; Clinical Trials; Cognitive; Complex; Computer software; Data; Data Set; Databases; Development; Disease; Distributed Databases; Focus Groups; Functional Imaging; Functional Magnetic Resonance Imaging; Functional disorder; Goals; Image; Informatics; Learning; Location; Methods; Patients; Pattern; Phase; Population; Protocols documentation; Research; Research Infrastructure; Research Personnel; Schizophrenia; Series; Site; Source; Statistical Methods; Structure; System; Technology; data mining; flexibility; image processing; knowledge base; meetings; neuroimaging; neuropsychiatry; novel; tool

The overarching goal of the Function BIRN (FBIRN) is to develop technology and methods to conduct multi- site functional imaging studies, and to produce a knowledge base that would not otherwise be available through single-site imaging studies. The technology includes the development and refinement of multi-site, functional imaging protocols using robust cognitive tasks; the development and refinement of algorithms to reduce inter-site variability; the use of federated, distributed databases and storage; flexible and robust image processing software integrated with these databases and storage infrastructure; tools for data querying across the distributed databases to extract subsets of data from multiple sources; and the development of both classical statistical and datamining methods to reveal the patterns of imaging', clinical, and behavioral data which differentiate important population clusters. To meet this goal, the FBIRN will develop the capacity to conduct a multi-center functional imaging study in a focused group of subjects with a neuropsychiatric disorder, patients with schizophrenia. The lessons learned, the statistical methods developed, and the informatics structure constructed will be generalizable and ' applicable to a wide variety of clinical investigations. The ability to integrate subsets of clinical, functional imaging, and behavioral datasets from disparate sites to form novel datasets will be assessed in a phased series of developments and optimizations. The overall goal of this proposal is to develop tools to make multi-site functional MRI studies a common research practice. Completion of this goal enables researchers to investigate the pathophysiology of complex diseases more thoroughly, through the increased power of large-scale, collaborative neuroimaging studies. When completed, researchers in different fields and physical locations will be able to draw on a common set of tools and database systems not possible at a single site.

BIRN功能的总体目标（FBIRN）是开发技术和方法，以进行多种 站点功能成像研究，并产生一个不可用的知识库 通过单位成像研究。该技术包括多站点的开发和完善， 使用强大的认知任务的功能成像协议；算法的开发和完善 降低现场变异性；使用联合，分布式数据库和存储的使用；灵活而健壮 与这些数据库和存储基础结构集成的图像处理软件；数据工具 跨分布式数据库查询以从多个来源提取数据子集；和 开发经典的统计和数据建筑方法，以揭示成像的模式”，临床， 和行为数据，分化了重要的人群集群。 为了实现这一目标，FBIRN将发展能力，以进行多中心功能成像研究 患有神经精神疾病的患者聚焦组，精神分裂症患者。经验教训， 开发了统计方法，构建的信息学结构将是可推广的，并且' 适用于各种临床研究。整合临床，功能的子集的能力 成像和来自不同站点以形成新型数据集的行为数据集将通过分阶段进行评估 一系列发展和优化。 该提案的总体目标是开发工具以使多站点功能MRI研究成为常见 研究实践。该目标的完成使研究人员能够研究 通过增加大规模协作神经影像的力量，更彻底的疾病更彻底 研究。完成后，不同领域和物理位置的研究人员将能够利用 在单个站点上不可能使用一组工具和数据库系统。