Structural Circuits Core

结构电路核心

• 批准号: 10413185
• 负责人: Paul G Mermelstein
• 金额: $ 30.28万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10413185
• 关键词: 3-Dimensional; Algorithms; Anatomy; Antibodies; Atlases; Base of the Brain; Behavior; Brain; Brain Mapping; Brain imaging; Brain region; Collection; Communities; Computer software; Custom; Data; Data Analyses; Data Set; Development; Disadvantaged; Drug Addiction; Effectiveness; Equipment; Goals; Grant; Histology; Image; Individual; Informatics; Infrastructure; Institutes; Label; Laboratories; Medical; Methodology; Methods; Microscopy; Minnesota; Mission; Modernization; Mus; Nervous system structure; Neuraxis; Neuroglia; Neurons; Optics; Pathway interactions; Penetration; Photobleaching; Procedures; Protocols documentation; Publishing; Rattus; Refractive Indices; Registries; Research Personnel; Resolution; Resources; Scanning; Services; Software Design; Specificity; Standardization; Structure; Supercomputing; Techniques; Technology; Three-Dimensional Imaging; Time; Tissues; Universities; Viral; addiction; base; brain circuitry; computational platform; connectome; data acquisition; data handling; data repository; design; equipment acquisition; experimental study; imaging approach; imaging facilities; imaging modality; imaging system; improved; innovation; instrumentation; large datasets; member; neural circuit; new technology; nonhuman primate; portability; repository; software development; tissue preparation

PROJECT SUMMARY: Structural Circuits Core Modern tissue clearing and imaging methods provide the potential for a wealth of information regarding nervous system anatomy and function. However, to best utilize such methods, understanding the options for tissue clearing, and the advantages and disadvantages of various imaging methods need to be appreciated. Furthermore, data handling, analysis, and storage all provide significant obstacles when attempting to make full use of the capabilities of these modern techniques. The goal of the Structural Circuits Core (SCC) is to help researchers best utilize ultramodern technology for the anatomical mapping of brain circuitry involved in drug addiction. In order to do so, the SCC partners with the University Imaging Center (UIC), the University of Minnesota Informatics Institute (UMII), the Minnesota Supercomputing Institute (SCI) and the Data Repository for the University of Minnesota (DRUM). The SCC provides the infrastructure for automated use of brain clearing technology paired with meso- and micro-scale imaging of the central nervous system. Importantly, the SCC helps tailor experiments to best utilize the most appropriate methodological and technological approaches, and, integrating with the Addiction Connectome Core, provides standardized resources for the analysis, storage, and distribution of these imaging datasets. The SCC not only allows investigators to quickly and thoroughly interrogate their own data, but also allows quantitative comparisons across laboratories through a common format structure and custom designed software.

项目总结：结构电路核心 现代组织清除和成像方法提供了关于神经的丰富信息的可能性 系统解剖和功能。然而，为了更好地利用这些方法，了解组织的选择 清晰度，以及各种成像方法的优缺点需要了解。 此外，数据处理、分析和存储都会在尝试完全 利用这些现代技术的能力。 结构电路核心(SCC)的目标是帮助研究人员最好地利用超现代技术来 与药物成瘾有关的大脑回路的解剖图谱。为了做到这一点，SCC与 大学成像中心(UIC)，明尼苏达大学信息学研究所(UMII)，明尼苏达州 超级计算研究所(SCI)和明尼苏达大学数据存储库(DRUM)。SCC 为自动使用脑清理技术提供基础设施，并与中、微尺度配合使用 中枢神经系统的成像。重要的是，SCC帮助量身定做实验以最大限度地利用 适当的方法和技术方法，并与成瘾连接组相结合 核心，为这些成像数据集的分析、存储和分发提供标准化资源。这个 SCC不仅允许调查人员快速彻底地询问自己的数据，而且还允许 通过通用格式结构和定制设计的软件进行实验室间的定量比较。