THE DEVELOPMENT OF HUMAN FUNCTIONAL BRAIN NETWORKS

人类大脑功能网络的发展

• 批准号: 8364214
• 负责人: BEATRIZ LUNA
• 金额: $ 0.11万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8364214
• 关键词: Age; Behavior; Biomedical Research; Brain; Brain region; Cognitive; Complex; Data; Data Set; Development; Distant; Frequencies; Functional Magnetic Resonance Imaging; Funding; Goals; Grant; Graph; High Performance Computing; Hour; Human; Human Development; Laboratories; Libraries; Life; Measures; Metric; National Center for Research Resources; Neurons; Participant; Principal Investigator; Research; Research Infrastructure; Resources; Rest; Running; Signal Transduction; Source; United States National Institutes of Health; age group; cognitive function; cost; critical developmental period; density; design; insight; interest; open source; relating to nervous system; supercomputer; theories

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The human brain is a complex, hierarchical network, in which billions of neurons are interconnected to form functional units that support complex behaviors. Cognitive functions likely arise and are constrained by dynamic neural activity propagating along this hierarchical network. The efficiency, accuracy, and stability of cognitive functions undergo significant development in the first 2 decades of life. Understanding how human functional brain networks develop during this critical developmental period will provide important insights into the relationship between brain function and the emergence of mature cognitive abilities. The goal of the current study is to characterize the development of human functional brain networks using graph-theoretic analyses. We will analyze resting-state functional magnetic resonance imaging (fMRI) data collected from 87 participants ages 8-22 years old. Resting-state fMRI measures the intrinsic, high-amplitude, low-frequency signal fluctuations of the brain, and high correlations among distant brain regions reflect functional connectivity. We will analyze functional brain networks by constructing whole-brain correlation matrices from resting-state fMRI data for each subject. We will further utilize graph-theoretic approaches to characterize the network topology of functional brain networks. Network measures of interest include centrality, path, clustering, efficiency, and small-worldness. Finally, network measures will be compared across age groups to characterize fully the development of functional brain networks. Graph theory analyses will be run using a C++ commandline application developed by our laboratory that utilizes two open-source libraries: GNU Scientific Library and Brain Connectivity ToolboxC++. The application compiles using the GNU C/C++ compiler (version 4.4.4 on our local machines). The application is designed to calculate all metrics of interest for a single subject and is single-threaded. Each subjects dataset is a square matrix approximately 1.5GB in size. The application requires approximately 200 hours to run per subject and uses 1.5-4GB RAM depending upon the calculation. We also hope to utilize the Teragrid supercomputer to calculate the optimal edge density for three aggregated datasets, with each dataset requiring approximately 300 hours to run.

这个子项目是利用资源的许多研究子项目之一。 由NIH/NCRR资助的中心拨款提供。对子项目的主要支持 子项目的首席调查员可能是由其他来源提供的， 包括美国国立卫生研究院的其他来源。为子项目列出的总成本可能 表示该子项目使用的中心基础设施的估计数量， 不是由NCRR赠款提供给次级项目或次级项目工作人员的直接资金。 人脑是一个复杂的、层次分明的网络，其中数十亿个神经元相互连接，形成支持复杂行为的功能单元。认知功能可能会产生，并受到沿着这个层级网络传播的动态神经活动的限制。认知功能的效率、准确性和稳定性在生命的前20年经历了显著的发展。了解人类大脑功能网络在这一关键发育时期是如何发展的，将为揭示大脑功能与成熟认知能力的出现之间的关系提供重要的见解。目前这项研究的目标是用图论分析来描述人类功能大脑网络的发展。我们将分析87名8-22岁受试者的静息状态功能磁共振成像(FMRI)数据。静息状态的fMRI测量大脑固有的、高幅度的、低频的信号波动，而远距离大脑区域之间的高度相关性反映了功能连接。我们将通过从每个受试者的静息状态fMRI数据构建全脑关联矩阵来分析功能脑网络。我们将进一步利用图论方法来刻画功能脑网络的网络拓扑。感兴趣的网络衡量标准包括中心性、路径、聚集性、效率和小世界。最后，将对不同年龄段的网络测量进行比较，以充分表征大脑功能网络的发展。图论分析将使用我们实验室开发的C++命令行应用程序运行，该应用程序利用两个开源库：GNU Science Library和Brain Connectivity ToolboxC++。该应用程序使用GNU C/C++编译器(本地机器上的4.4.4版)进行编译。该应用程序旨在计算单个对象的所有感兴趣的指标，并且是单线程的。每个受试者数据集都是一个大小约为1.5 GB的方阵。该应用程序需要每个主题运行大约200个小时，并根据计算使用1.5-4 GB内存。我们还希望利用TeraGrid超级计算机来计算三个聚合数据集的最佳边缘密度，每个数据集需要大约300小时的运行时间。