Meta-Network Analysis of Structural Correlation Networks Provides Insights Into Brain Network Development.
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ABSTRACT:
SUBMITTER: Xu X
PROVIDER: S-EPMC6444117 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Publications
Meta-Network Analysis of Structural Correlation Networks Provides Insights Into Brain Network Development.
Xu Xiaohua X He Ping P Yap Pew-Thian PT Zhang Han H Nie Jingxin J Shen Dinggang D
Frontiers in human neuroscience 20190326
Analysis of developmental brain networks is fundamentally important for basic developmental neuroscience. In this paper, we focus on the temporally-covarying connection patterns, called meta-networks, and develop a new mathematical model for meta-network decomposition. With the proposed model, we decompose the developmental structural correlation networks of cortical thickness into five meta-networks. Each meta-network exhibits a distinctive spatial connection pattern, and its covarying trajecto ...[more]
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