方法对比
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| 动态功能连接× | 图脑网络分析× | |
|---|---|---|
| 领域 | 神经影像 | 神经影像 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 2013 | 2009 |
| 提出者≠ | Ryan M. Hutchison | Ed Bullmore |
| 类型≠ | Resting-state fMRI connectivity pipeline | Brain network graph analysis pipeline |
| 开创性文献≠ | Hutchison, R. M., Womelsdorf, T., Allen, E. A., et al. (2013). Dynamic functional connectivity: promise, problems, and perspectives. NeuroImage, 80, 360–378. link ↗ | Bullmore, E., & Sporns, O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10(3), 186–198. DOI ↗ |
| 别名 | dFC, time-varying connectivity, sliding window connectivity | graph theory, brain network analysis, network neuroscience |
| 相关 | 3 | 3 |
| 摘要≠ | Dynamic Functional Connectivity (dFC) is an analytical framework that tracks changes in functional connectivity between brain regions over time, rather than averaging connectivity across an entire scanning session. Systematized by Hutchison and colleagues in 2013, dFC reveals how brain networks reorganize moment-to-moment, providing insights into transient brain states and cognitive flexibility. | Graph Theoretical Brain Network Analysis applies network science to understand brain organization, treating the brain as a complex network of interconnected nodes (regions) and edges (connections). Formalized by Bullmore and Sporns in 2009, graph analysis reveals fundamental organizational principles—modularity, efficiency, resilience—that characterize healthy and diseased brains. |
| ScholarGate数据集 ↗ |
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