Cross-participant prediction of vigilance stages through the combined use of wPLI and wSMI EEG functional connectivity metrics.
Sleep May 14, 2021 Laura Sophie Imperatori, Jacinthe Cataldi, Monica Betta et al. 30 citations
Functional connectivity metrics, which describe how brain regions interact, can reveal differences across stages of sleep and wakefulness that power-based analyses alone may miss. Analyzing overnight sleep and resting-state wakefulness recordings from 24 healthy adults, the study found that combining power features with two connectivity measures—weighted Phase Lag Index (wPLI) and weighted Symbolic Mutual Information (wSMI)—improved the accuracy of classifying four vigilance stages (wakefulness, NREM-N2, NREM-N3, and REM sleep) compared to using any single feature type. Delta-band connectivity (0.5–4 Hz) was most important across all classifications, suggesting slow waves play a role in consciousness and sensory disconnection.