Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan.
Rev Neurosci. 2011;22(5):551-63. doi: 10.1515/RNS.2011.039. Epub 2011 Aug 24.
There is a growing interest in exploring the connectivity patterns of the human brain. Specifically, the utility of noninvasive neuroimaging data and graph theoretical analysis have provided important insights into the anatomical connections and topological pattern of human brain structural networks in vivo. This review focuses on recent methodological and application studies, utilizing graph theoretical approaches, on brain structural networks with structural magnetic resonance imaging (MRI) and diffusion MRI. These studies showed many nonrandom properties of structural brain networks, such as small-worldness, modularity, and highly connected hubs. Importantly, topological organization of the networks shows changes during normal development, aging, and neuropsychiatric diseases. Network structures have also been found to correlate with behavioral or cognitive functions, which imply their associations with functional dynamics. These advances not only help us to understand how the healthy human brain is structurally organized, but also provide a novel insight into the biological mechanisms of brain disorders. Future studies will involve the combination of structural/diffusion MRI and functional MRI, to realize how the structural connectivity patterns of the brain underlie its functional states, and will explore whether graph theoretical analysis of structural brain networks could serve as potential imaging biomarkers for disease diagnosis and treatment.
人们越来越感兴趣地探索人类大脑的连接模式。具体来说，无创性神经影像学数据和图论分析为活体人脑结构网络的解剖连接和拓扑模式提供了重要的见解。这篇综述重点介绍了利用图论方法对结构磁共振成像（MRI）和弥散 MRI 进行脑结构网络的最新方法学和应用研究。这些研究表明，结构脑网络具有许多非随机特性，如小世界性、模块性和高度连接的枢纽。重要的是，网络的拓扑组织在正常发育、衰老和神经精神疾病期间发生变化。还发现网络结构与行为或认知功能相关，这意味着它们与功能动力学有关。这些进展不仅帮助我们了解健康人类大脑的结构组织方式，还为脑疾病的生物学机制提供了新的见解。未来的研究将涉及结构/弥散 MRI 和功能 MRI 的结合，以实现大脑的结构连接模式如何构成其功能状态，并探讨结构脑网络的图论分析是否可以作为疾病诊断和治疗的潜在影像学生物标志物。
