ANALYSIS OF LARGE-SCALE BRAIN NETWORK IN HUMANS

人类大规模大脑网络分析

• 批准号: 7723350
• 负责人: PATRICK C M WONG
• 金额: $ 0.05万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7723350
• 关键词: Brain; Brain region; Computer Retrieval of Information on Scientific Projects Database; Data; Equation; Functional Magnetic Resonance Imaging; Funding; Grant; Graph; Human; Institution; Linear Models; Methods; Modeling; Nature; Pilot Projects; Research; Research Personnel; Resources; Source; Time; United States National Institutes of Health; computing resources; falls; neuroimaging; research study; theories

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. Traditional methods for the analysis of human functional neuroimaging data (e.g., fMRI) focus on isolated brain regions (e.g., by using General Linear Model) or a small set of brain regions (e.g., by using Structural Equation Modeling). While informative, these methods fall short of informing us about the interactive nature of regions across the entire brain. In this pilot study, we aim at examining large-scale human brain networks by using methods that are conducive to such analysis (e.g., methods that are used in conjunction with graph theory). Typically, 30,000 regions (in the form of voxels) are collected from one subject at one time point of the experiment (a typical experiment consists of hundreds of time points). The high computational demands make the analysis extremely difficult in our current facility. We seek to use the super-computing resources provided by the CyberInfrastructure Partnership to perform such large-scale analyses on our data collected using NIH funds.

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。 分析人类功能神经成像数据（例如fMRI）的传统方法集中在孤立的大脑区域（例如，使用一般线性模型）或一小部分大脑区域（例如，使用结构方程建模）。尽管内容丰富，但这些方法却没有通知我们整个大脑区域的互动性质。在这项试点研究中，我们旨在通过使用有利于这种分析的方法来检查大规模的人脑网络（例如，与图理论结合使用的方法）。通常，在实验的一次时间点，从一个受试者中收集了30,000个区域（以体素的形式）（典型的实验由数百个时间点组成）。高计算需求使我们当前设施中的分析极为困难。我们试图使用网络基础设施合作伙伴关系提供的超级计算资源来对使用NIH基金收集的数据进行如此大规模的分析。