Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Dinamiskā funkcionālā savienojamība× | Fāzes sasaistes vērtība× | |
|---|---|---|
| Nozare | Neiroattēlveidošana | Neiroattēlveidošana |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 2013 | 1999 |
| Autors≠ | Ryan M. Hutchison | Jean-Philippe Lachaux |
| Tips≠ | Resting-state fMRI connectivity pipeline | EEG/MEG functional connectivity analysis |
| Pirmavots≠ | Hutchison, R. M., Womelsdorf, T., Allen, E. A., et al. (2013). Dynamic functional connectivity: promise, problems, and perspectives. NeuroImage, 80, 360–378. link ↗ | Lachaux, J. P., Rodriguez, E., Martinerie, J., & Varela, F. J. (1999). Measuring phase synchrony in brain signals. Human Brain Mapping, 8(4), 194–208. DOI ↗ |
| Citi nosaukumi | dFC, time-varying connectivity, sliding window connectivity | PLV, phase synchronization, phase coupling |
| Saistītās | 3 | 3 |
| Kopsavilkums≠ | 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. | Phase-Locking Value (PLV) is a frequency-domain measure of neural synchronization that quantifies the stability of phase difference between two signals. Introduced by Lachaux and colleagues in 1999, PLV detects phase coupling between brain regions independent of signal amplitude, enabling researchers to characterize functional connectivity from EEG and MEG recordings. |
| ScholarGateDatu kopa ↗ |
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