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Giulio Bernardi

4 papers in the library · 209 citations · publishing 2018-2025

Papers

Dreaming in NREM Sleep: A High-Density EEG Study of Slow Waves and Spindles

Journal of Neuroscience September 10, 2018 Francesca Siclari, Giulio Bernardi, Jacinthe Cataldi et al. 148 citations

Dreaming during non-rapid eye movement (NREM) sleep is linked to fewer, smaller, and shallower slow waves and faster spindles, especially in central and posterior brain regions. A minority of very steep, large slow waves in frontal areas, occurring against a background of reduced slow wave activity and accompanied by high-frequency power increases (local microarousals), preceded successful dream recall. The findings suggest that the brain's ability to generate experiences during sleep is reduced when neuronal off-states are present in posterior and central regions, and that dream recall may be aided by intermittent activation of arousal systems during NREM sleep.

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.

DREAM: A Dream EEG and Mentation database

May 16, 2023 William Wong, Kátia C. Andrade, Thomas Andrillon et al. 21 citations preprint

A new open-access database, DREAM, combines sleep magneto/electroencephalography (M/EEG) recordings with standardized dream reports to enable large-scale neurocognitive research on dreaming. The initial release includes 20 datasets from 561 participants and 2649 awakenings, each with at least 20 seconds of high-frequency M/EEG data and a classification of the subject's experience. Analyses demonstrate that features extracted from EEG can predict whether a person reports having had a conscious experience during both REM and NREM sleep. The database aims to overcome the limitations of small sample sizes and methodological variability in dream research, allowing new questions to be addressed at a scale unattainable by individual labs.

A dream EEG and mentation database.

Nature communications August 13, 2025 William Wong, Rubén Herzog, Kátia Cristine Andrade et al. 10 citations

A new open database, the DREAM database, combines standardized sleep magneto/electroencephalography (M/EEG) recordings with dream reports from 505 participants across 20 datasets, totaling 2,643 awakenings. Each awakening includes at least 20 seconds of high-resolution sleep EEG (≥100 Hz, ≥2 electrodes) and a classification of the sleeper's reported experience. Analyses showed that reports of conscious experiences during sleep can be predicted from objective EEG features in both REM and NREM sleep. The database aims to overcome limitations of small sample sizes and methodological variability in dream research, enabling larger-scale investigations of the neurocognitive basis of dreaming.