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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.<\/jats:p>","DOI":"10.1093\/cercor\/bhae039","type":"journal-article","created":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T15:38:46Z","timestamp":1705937926000},"source":"Crossref","is-referenced-by-count":8,"title":["Mapping individual structural covariance network in development brain with dynamic time warping"],"prefix":"10.1093","volume":"34","author":[{"given":"Hui","family":"Sun","sequence":"first","affiliation":[{"name":"College of Electrical Engineering, Sichuan University , Chengdu 610065 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qinyao","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Life Science and Technology, University of Electronic Science and Technology of China , Chengdu 625014 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanyuan","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Primate Biomedical Research , Institute of Primate Translational Medicine, , Kunming 650500 , China"},{"name":"Kunming University of Science and Technology , Institute of Primate Translational Medicine, , Kunming 650500 , China"},{"name":"Yunnan Key Laboratory of Primate Biomedical Research , Kunming 650500 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Electrical Engineering, Sichuan University , Chengdu 610065 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoyang","family":"Xing","sequence":"additional","affiliation":[{"name":"Magnetic Resonance Research Center , West China 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