Spatiotemporal Analysis of Developing Brain Networks

Ping He, Xiaohua Xu, Han Zhang, Gang Li, Jingxin Nie, Pew Thian Yap, Dinggang Shen

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Recent advances in MRI have made it easier to collect data for studying human structural and functional connectivity networks. Computational methods can reveal complex spatiotemporal dynamics of the human developing brain. In this paper, we propose a Developmental Meta-network Decomposition (DMD) method to decompose a series of developmental networks into a set of Developmental Meta-networks (DMs), which reveal the underlying changes in connectivity over development. DMD circumvents the limitations of traditional static network decomposition methods by providing a novel exploratory approach to capture the spatiotemporal dynamics of developmental networks. We apply this method to structural correlation networks of cortical thickness across subjects at 3–20 years of age, and identify four DMs that smoothly evolve over three stages, i.e., 3–6, 7–12, and 13–20 years of age. We analyze and highlight the characteristic connections of each DM in relation to brain development.

Original languageEnglish
Article number48
JournalFrontiers in Neuroinformatics
Publication statusPublished - 2018 Jul 31


  • Cortical thickness
  • Developmental meta-network decomposition
  • Developmental networks
  • Non-negative matrix factorization
  • Structural correlation networks

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Biomedical Engineering
  • Computer Science Applications


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