Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Analiza Rețelelor Cerebrale Bazată pe Grafuri× | Conectivitate Funcțională Dinamică× | |
|---|---|---|
| Domeniu | Neuroimagistică | Neuroimagistică |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 2009 | 2013 |
| Autorul original≠ | Ed Bullmore | Ryan M. Hutchison |
| Tip≠ | Brain network graph analysis pipeline | Resting-state fMRI connectivity pipeline |
| Sursa seminală≠ | 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 ↗ |
| Denumiri alternative | graph theory, brain network analysis, network neuroscience | dFC, time-varying connectivity, sliding window connectivity |
| Înrudite | 3 | 3 |
| Rezumat≠ | 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. |
| ScholarGateSet de date ↗ |
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