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.
Dream recall varies greatly between people and from night to night. Nocturnal awakenings are thought to help encode and retrieve dreams, but it was unclear whether the frequency, duration, sleep stage, or timing of awakenings matters most. Analyzing two cohorts (708 adults across three waves and 124 adults with high dream recall across multiple nights), trait-level dream recall was associated with a specific pattern: more habitual long REM awakenings and short NREM awakenings. State-level analysis showed that nights with more short and medium REM awakenings increased the likelihood of morning dream recall, while more long REM awakenings increased the likelihood of recalling dream content. Findings support arousal-retrieval and functional state-shift models with important nuances.