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Functional connectivity (FC) metrics describe brain inter-regional interactions and may complement information provided by common power-based analyses. Here, we investigated whether the FC-metrics weighted Phase Lag Index (wPLI) and weighted Symbolic Mutual Information (wSMI) may unveil functional differences across four stages of vigilance-wakefulness (W), NREM-N2, NREM-N3, and REM sleep-with respect to each other and to power-based features. Moreover, we explored their possible contribution in identifying differences between stages characterized by distinct levels of consciousness (REM+W vs. N2+N3) or sensory disconnection (REM vs. W). Overnight sleep and resting-state wakefulness recordings from 24 healthy participants (27 ± 6 years, 13F) were analyzed to extract power and FC-based features in six classical frequency bands. Cross-validated linear discriminant analyses (LDA) were applied to investigate the ability of extracted features to discriminate (1) the four vigilance stages, (2) W+REM vs. N2+N3, and (3) W vs. REM. For the four-way vigilance stages classification, combining features based on power and both connectivity metrics significantly increased accuracy relative to considering only power, wPLI, or wSMI features. Delta-power and connectivity (0.5-4 Hz) represented the most relevant features for all the tested classifications, in line with a possible involvement of slow waves in consciousness and sensory disconnection. Sigma-FC, but not sigma-power (12-16 Hz), was found to strongly contribute to the differentiation between states characterized by higher (W+REM) and lower (N2+N3) probabilities of conscious experiences. Finally, alpha-FC resulted as the most relevant FC-feature for distinguishing among wakefulness and REM sleep and may thus reflect the level of disconnection from the external environment., (© Sleep Research Society 2020. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.)

Feeling awake although sleep recordings indicate clear-cut sleep sometimes occurs in good sleepers and to an extreme degree in patients with so-called paradoxical insomnia. It is unknown what underlies sleep misperception, as standard polysomnographic (PSG) parameters are often normal in these cases. Here we asked whether regional changes in brain activity could account for the mismatch between objective and subjective total sleep times (TST). To set cutoffs and define the norm, we first evaluated sleep perception in a population-based sample, consisting of 2,092 individuals who underwent a full PSG at home and estimated TST the next day. We then compared participants with a low mismatch (normoestimators, n = 1,147, ±0.5 SD of mean) with those who severely underestimated (n = 52, <2.5th percentile) or overestimated TST (n = 53, >97.5th percentile). Compared with normoestimators, underestimators displayed higher electroencephalographic (EEG) activation (beta/delta power ratio) in both rapid eye movement (REM) and non-rapid eye movement (NREM) sleep, while overestimators showed lower EEG activation (significant in REM sleep). To spatially map these changes, we performed a second experiment, in which 24 healthy subjects and 10 insomnia patients underwent high-density sleep EEG recordings. Similarly to underestimators, patients displayed increased EEG activation during NREM sleep, which we localized to central-posterior brain areas. Our results indicate that a relative shift from low- to high-frequency spectral power in central-posterior brain regions, not readily apparent in conventional PSG parameters, is associated with underestimation of sleep duration. This challenges the concept of sleep misperception, and suggests that instead of misperceiving sleep, insomnia patients may correctly perceive subtle shifts toward wake-like brain activity., (© Sleep Research Society 2020. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.)

Study Objectives: To explore the clinical significance of pulse wave amplitude (PWA)-drops during sleep as a biomarker for cardiometabolic disorders and describe their main characteristics in a general population sample., Methods: Cross-sectional study of HypnoLaus cohort, in which 2162 individuals underwent clinical assessment and in-home full polysomnography. PWA-drops were derived from photoplethysmography and processed using a validated automated algorithm. Associations between PWA-drop features (index, mean duration, and mean area under the curve [AUC]) with hypertension, diabetes, and previous cardiovascular (CV) event were analyzed using multivariable-adjusted logistic regression., Results: Two thousand one hundred forty-nine participants (59 ± 11 years, 51% women, 9.9% diabetes, 41.3% hypertension, 4.4% CV event) were included. Mean ± standard deviation (SD) of PWA-drop index, duration, and AUC during sleep were 51.0 ± 20.3 events/hour, 14.0 ± 2.7 seconds, and 527±115 %seconds, respectively. PWA-drop index was lower in women and decreased with age, while its mean duration and AUC increased in men and elderly. Overall, lower PWA-drop index, longer duration and greater AUC were associated with increased odds of hypertension, diabetes, or CV event after adjustment for confounders. Participants in the lowest quartile of mean duration-normalized PWA-drop index had a significantly higher odds ratio (OR) of hypertension (OR = 1.60 [1.19-2.16]), CV event (OR = 3.26 [1.33-8.03]), and diabetes (OR = 1.71 [1.06-2.76]) compared to those in the highest quartile. Similar results were observed for mean AUC-normalized PWA-drop index regarding hypertension (OR = 1.59 [1.19-2.13]), CV event (OR = 2.45 [1.14-5.26]) and diabetes (OR = 1.76 [1.10-2.83])., Conclusions: PWA-drop features during sleep seem to be an interesting biomarker independently associated with cardiometabolic outcomes in the general population., (© Sleep Research Society 2020. Published by Oxford University Press on behalf of the Sleep Research Society.)