Clocks & Sleep
September 19, 2021
Valentina Elce, Giacomo Handjaras, Giulio Bernardi
29 citations
Dream reports—oral or written accounts given upon awakening—are a key source of insight into dreaming. Traditionally, structural information (e.g., word or sentence counts) and semantic content (scored by human coders using predefined systems) are extracted from these reports. This review argues that linguistic analysis methods—graph analysis, dictionary-based content analysis, and distributional semantics—can complement or replace classical measures. These techniques allow direct, operator-independent extraction of quantitative information, enabling fully objective and reproducible analysis of conscious experiences during sleep. They can be partially or fully automated, making them suitable for large datasets.
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.
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.
bioRxiv (Cold Spring Harbor Laboratory)
June 28, 2025
Jessica Palmieri, Valentina Elce, Monika Schönauer
1 citation
preprint
Emotional intensity in dreams increases as the night progresses, with late-night dreams rated as more emotional than those from early sleep. This pattern was observed in a multiple awakening study of 20 participants who provided 61 dream reports. Contrary to expectations, the rise in emotionality was not tied to REM sleep awakenings. Late-night dream reports were also longer, but report length did not correlate with emotional intensity, suggesting that emotionality is independent of recall ability or narrative complexity. The findings indicate that emotional processing during sleep may unfold across the night through mechanisms separate from those governing dream recall or story elaboration.
bioRxiv (Cold Spring Harbor Laboratory)
May 21, 2025
Valentina Elce, Giorgia Bontempi, Serena Scarpelli et al.
1 citation
preprint
Dreams are shaped by both stable individual traits and major external events. A large adult cohort provided dream and wakefulness reports alongside demographic, psychometric, cognitive, and sleep measures. Natural language processing revealed semantic features that distinguish dream from wakefulness reports, with this distinction significantly modulated by individual-specific factors. Longitudinal and cross-sample analyses showed that the COVID-19 pandemic left lasting traces on dream content. The findings highlight a dynamic interplay between personal characteristics and external events in shaping dream experiences, offering insights into the cognitive and emotional architecture of dreaming.
arXiv (Cornell University)
February 28, 2023
Lorenzo Bertolini, Valentina Elce, Adriana Michalak et al.
1 citation
Dream research usually depends on human experts manually scoring dream reports, a time-consuming process. While natural language processing tools have been explored for automatic analysis, they could not reason over a report's full context, needed extensive preprocessing, and were rarely validated against manual scoring. This work used large language models, both off-the-shelf and bespoke, to replicate manual annotation of dream reports, focusing on emotions. The off-the-shelf method performed poorly, likely due to linguistic differences across individuals. In contrast, the bespoke text classification method achieved high performance and was robust against biases. This approach may enable analysis of large dream datasets and improve reproducibility and comparability across studies.
Communications Psychology
April 28, 2026
Valentina Elce, Giorgia Bontempi, Serena Scarpelli et al.
Dreams are universal yet highly personal. By analyzing 3,366 reports of dreams and waking experiences from 207 adults collected between 2020 and 2024, along with demographic, cognitive, psychometric, and sleep measures, researchers found that dreams differ from waking thoughts: they are less self-referential and thought-centered, and more perceptual, dominated by visuo-spatial details, multiple characters, and bizarre events. Stable traits like attitude toward dreaming, mind-wandering propensity, and subjective sleep quality selectively influenced dream content. During the first 2020 COVID-19 lockdown, dreams from an independent dataset of 80 participants showed increased references to limitations and heightened emotional intensity, which gradually normalized over subsequent years. Stable individual traits and incidental experiences jointly shape dream semantics.
bioRxiv (Cold Spring Harbor Laboratory)
September 8, 2025
Adriana Michalak, Davide Marzoli, Francesco Pietrogiacomi et al.
preprint
Perceived sleep depth, a key factor in subjective sleep quality, is traditionally linked to unconsciousness and reduced brain activity. Using high-density EEG and a serial awakening paradigm during NREM sleep, researchers found that deeper sleep corresponded to lower high-to-low frequency power ratio, indicating reduced cortical activation. However, this relationship weakened when dreaming occurred, suggesting immersive conscious experiences can counteract the effect of cortical activation on perceived depth. Perceived sleep depth was lowest during states with a mere sense of presence and highest during immersive dreaming or deep unconsciousness. As the night progressed, physiological sleep pressure and subjective sleepiness declined, but perceived sleep depth increased alongside rising dream immersiveness. These findings challenge the view that deep sleep stems solely from reduced brain activity.
PLoS Biology
March 1, 2026
Adriana Michalak, Davide Marzoli, Francesco Pietrogiacomi et al.
Perceived sleep depth, a key part of subjective sleep quality, is traditionally linked to unconsciousness and reduced brain activity. Combining high-density EEG with a serial awakening paradigm during N2 sleep in healthy participants, the study found that deeper sleep was associated with a lower high-to-low frequency power ratio, indicating reduced cortical activation. However, this relationship weakened when dreaming occurred, suggesting immersive conscious experiences can counteract the impact of cortical activation on perceived depth. Perceived sleep depth was lowest during minimal awareness (a mere sense of presence) and highest during immersive dreaming or deep unconsciousness.
Communications Psychology
February 18, 2025
Valentina Elce, Damiana Bergamo, Giorgia Bontempi et al.
Dream recall varies widely between people and across nights. In 217 healthy adults aged 18 to 70, attitude toward dreaming, tendency to mind-wander, and sleep patterns were associated with whether a person reported a dream upon waking. The likelihood of recalling dream content was predicted by age and vulnerability to interference. Night-to-night changes in sleep patterns and seasonal fluctuations also influenced dream recall. These findings help explain why some people remember dreams more often than others and why recall varies within the same person.
Valentina Elce, Damiana Bergamo, Giorgia Bontempi et al.
preprint
Dream recall varies greatly between people and across nights. In a study of 204 healthy adults aged 18 to 70, attitude toward dreaming, tendency to mind-wander, and sleep patterns were associated with how likely someone was to report a dream upon waking. The probability of recalling specific dream content was predicted by age and vulnerability to interference. Dream recall also fluctuated with nightly changes in sleep patterns and showed seasonal variation. These findings help explain why dream recall differs both between individuals and within the same person over time.