ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

图脑网络分析×动态功能连接×
领域神经影像神经影像
方法族Process / pipelineProcess / pipeline
起源年份20092013
提出者Ed BullmoreRyan M. Hutchison
类型Brain network graph analysis pipelineResting-state fMRI connectivity pipeline
开创性文献Bullmore, E., & Sporns, O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10(3), 186–198. DOI ↗Hutchison, R. M., Womelsdorf, T., Allen, E. A., et al. (2013). Dynamic functional connectivity: promise, problems, and perspectives. NeuroImage, 80, 360–378. link ↗
别名graph theory, brain network analysis, network neurosciencedFC, time-varying connectivity, sliding window connectivity
相关33
摘要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.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.
ScholarGate数据集
  1. v1
  2. 2 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: Graph Brain Network Analysis · Dynamic Functional Connectivity. 于 2026-06-17 检索自 https://scholargate.app/zh/compare