Network scaling effects in graph analytic studies of human resting-state fMRI data
Network scaling effects in graph analytic studies of human resting-state fMRI data
复制标题
DOI：
10.3389/fnsys.2010.00022
复制
发表时间：
2010-01-01
影响因子：
3
通讯作者：
Bullmore, Edward T.
中科院分区：
文献类型：
--
作者：
Fornito, Alex;Zalesky, Andrew;Bullmore, Edward T.
图分析已经成为一种越来越流行的工具，用于表征大脑连接网络的拓扑特性。在这种方法中，大脑被建模为包括由M条边连接的N个节点的图。在功能性磁共振成像（fMRI）研究中，节点通常代表大脑区域，而边缘则是它们之间相互作用的某种度量。这些节点通常使用各种区域分割模板来定义，这些模板在每个区域采样的体积和分割的区域数量方面都可能不同。在这里，我们试图调查如何在parcellation模板的变化影响关键的图形分析措施的功能性脑组织在30名健康志愿者使用静息态fMRI。研究了7种不同的分割分辨率（84、91、230、438、890、1314和4320区域）。我们发现，关于网络拓扑结构的总体推断，例如大脑是否是小世界或无标度的，对所使用的模板是鲁棒的，但是路径长度、聚类、小世界性和度分布描述符等特定参数的绝对值和个体差异在所研究的分辨率中变化很大。这些研究结果强调，需要考虑的效果，一个特定的parcellation方法对人类功能磁共振成像研究中的图形分析结果，并表明，使用不同的模板获得的结果可能无法直接比较。
Graph analysis has become an increasingly popular tool for characterizing topological properties of brain connectivity networks. Within this approach, the brain is modeled as a graph comprising N nodes connected by M edges. In functional magnetic resonance imaging (fMRI) studies, the nodes typically represent brain regions and the edges some measure of interaction between them. These nodes are commonly defined using a variety of regional parcellation templates, which can vary both in the volume sampled by each region, and the number of regions parcellated. Here, we sought to investigate how such variations in parcellation templates affect key graph analytic measures of functional brain organization using resting-state fMRI in 30 healthy volunteers. Seven different parcellation resolutions (84, 91, 230, 438, 890, 1314, and 4320 regions) were investigated. We found that gross inferences regarding network topology, such as whether the brain is small-world or scale-free, were robust to the template used, but that both absolute values of, and individual differences in, specific parameters such as path length, clustering, small-worldness, and degree distribution descriptors varied considerably across the resolutions studied. These findings underscore the need to consider the effect that a specific parcellation approach has on graph analytic findings in human fMRI studies, and indicate that results obtained using different templates may not be directly comparable.