Mapping Anatomical Connectivity Patterns of Human Cerebral Cortex Using In Vivo Diffusion Tensor Imaging Tractography
Mapping Anatomical Connectivity Patterns of Human Cerebral Cortex Using In Vivo Diffusion Tensor Imaging Tractography
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DOI：
10.1093/cercor/bhn102
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发表时间：
2009-03-01
期刊：
影响因子：
3.7
通讯作者：
Beaulieu, Christian
中科院分区：
文献类型：
--
作者：
Gong, Gaolang;He, Yong;Beaulieu, Christian
表征大脑结构和功能组织的复杂网络的拓扑结构是神经科学的基本挑战。然而，人类大脑中解剖连接网络的直接证据仍然很少。在这里，我们利用扩散张量成像确定性纤维束成像构建一个宏观尺度的解剖网络，捕捉人类大脑皮层在大样本的主题（80名年轻人）的基本共同的连接模式，并进一步定量分析其拓扑特性与图论方法。将大脑皮层分为78个皮层区域，每个区域代表一个网络节点，如果纤维连接的概率超过统计标准，则认为2个皮层区域是连接的。所建立的皮层网络（二值化）的拓扑参数类似于一个“小世界”的架构，其特征在于一个指数截断幂律分布。这些特征意味着对局部损伤的高恢复力。此外，这种皮层网络的特点是在联合皮层的主要枢纽地区，连接的桥梁连接后，远程白色物质途径。我们的研究结果与以前的结构和功能的大脑网络的研究是兼容的，并提供洞察人类大脑解剖网络的组织原则，功能状态的基础。
The characterization of the topological architecture of complex networks underlying the structural and functional organization of the brain is a basic challenge in neuroscience. However, direct evidence for anatomical connectivity networks in the human brain remains scarce. Here, we utilized diffusion tensor imaging deterministic tractography to construct a macroscale anatomical network capturing the underlying common connectivity pattern of human cerebral cortex in a large sample of subjects (80 young adults) and further quantitatively analyzed its topological properties with graph theoretical approaches. The cerebral cortex was divided into 78 cortical regions, each representing a network node, and 2 cortical regions were considered connected if the probability of fiber connections exceeded a statistical criterion. The topological parameters of the established cortical network (binarized) resemble that of a "small-world" architecture characterized by an exponentially truncated power-law distribution. These characteristics imply high resilience to localized damage. Furthermore, this cortical network was characterized by major hub regions in association cortices that were connected by bridge connections following long-range white matter pathways. Our results are compatible with previous structural and functional brain networks studies and provide insight into the organizational principles of human brain anatomical networks that underlie functional states.