中间性中心性
连接体
模块化(生物学)
协方差
计算机科学
动态网络分析
网络拓扑
神经科学
拓扑(电路)
人工智能
心理学
数学
生物
中心性
统计
计算机网络
组合数学
功能连接
遗传学
操作系统
作者
Hui Sun,Qiran Sun,Yuanyuan Li,Jiang Zhang,Haoyang Xing,Jiaojian Wang
标识
DOI:10.1093/cercor/bhae039
摘要
A conspicuous property of brain development or maturity is coupled with coordinated or synchronized brain structural co-variation. However, there is still a lack of effective approach to map individual structural covariance network. Here, we developed a novel individual structural covariance network method using dynamic time warping algorithm and applied it to delineate developmental trajectories of topological organizations of structural covariance network from childhood to early adulthood with a large sample of 655 individuals from Human Connectome Project-Development dataset. We found that the individual structural covariance network exhibited small-worldness property and the network global topological characteristics including small-worldness, global efficiency, local efficiency, and modularity linearly increase with age while the shortest path length linearly decreases with age. The nodal topological properties including betweenness and degree increased with age in language and emotion regulation related brain areas, while it decreased with age mainly in visual cortex, sensorimotor area, and hippocampus. Moreover, the topological attributes of structural covariance network as features could predict the age of each individual. Taken together, our results demonstrate that dynamic time warping can effectively map individual structural covariance network to uncover the developmental trajectories of network topology, which may facilitate future investigations to establish the links of structural co-variations with respect to cognition and disease vulnerability.
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