Abstract
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 trajectory highlights the temporal contribution of the meta-network along development. Systematic analysis of the meta-networks and covarying trajectories provides insights into three important aspects of brain network development.
| Original language | English |
|---|---|
| Article number | 93 |
| Journal | Frontiers in Human Neuroscience |
| Volume | 13 |
| DOIs | |
| Publication status | Published - 2019 Feb 1 |
Keywords
- Brain network development
- Cortical thickness
- Low rank
- Meta-network analysis
- Temporal smoothness
ASJC Scopus subject areas
- Neuropsychology and Physiological Psychology
- Neurology
- Psychiatry and Mental health
- Biological Psychiatry
- Behavioral Neuroscience
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Xu, X., He, P., Yap, P. T., Zhang, H., Nie, J., & Shen, D. (2019). Meta-network analysis of structural correlation networks provides insights into brain network development. Frontiers in Human Neuroscience, 13, [93]. https://doi.org/10.3389/fnhum.2019.00093