Magneto/electroencephalography (M/EEG) studies of dreaming are an essential paradigm in the investigation of neurocognitive processes of human consciousness during sleep, but they are limited by the number of observations that can be collected per study. Dream research also involves substantial methodological and conceptual variability, which poses problems for the integration of results. To address these issues, here we present the DREAM database—an expanding collection of standardized datasets on human sleep M/EEG combined with dream report data—with an initial release comprising 20 datasets, 561 participants, and 2649 awakenings. Each awakening consists, at minimum, of sleep M/EEG(≥20 s, ≥100 Hz, ≥2 electrodes) up to the time of waking and a standardized dream report classification of the subject’s experience during sleep. We also provide several examples of analyses, showcasing the database’s high potential in paving the way for new research questions at a scale that any single research group cannot achieve. We notably show that reports of conscious experiences can be predicted with objective features extracted from EEG recordings in both Rapid Eye Movement (REM) and non-REM (NREM) sleep. We finally will provide useful criteria for methodological choices in future dream laboratory research and the expansion of this database.
Every night, we pass through a transitory zone at the borderland between wakefulness and sleep, named the first stage of nonrapid eye movement sleep (N1). N1 sleep is associated with increased hippocampal activity and dream-like experiences that incorporate recent wake materials, suggesting that it may be associated with memory processing. Here, we investigated the specific contribution of N1 sleep in the processing of memory traces. Participants were asked to learn the precise locations of 48 objects on a grid and were then tested on their memory for these items before and after a 30-min rest during which participants either stayed fully awake or transitioned toward N1 or deeper (N2) sleep. We showed that memory recall was lower (10% forgetting) after a resting period, including only N1 sleep compared to N2 sleep. Furthermore, the ratio of alpha/theta power (an electroencephalography marker of the transition toward sleep) correlated negatively with the forgetting rate when taking into account all sleepers (N1 and N2 groups combined), suggesting a physiological index for memory loss that transcends sleep stages. Our findings suggest that interrupting sleep onset at N1 may alter sleep-dependent memory consolidation and promote forgetting.
Creative problem-solving is central in daily life, yet its underlying mechanisms remain elusive. Restructuring (i.e., reorganization of problem-related representations) is considered one problem-solving mechanism and may lead to an abstract problem-related representation facilitating the solving of analogous problems. However, empirical evidence supporting such mechanisms is scarce. We used network science methodology to estimate participants’ individual semantic memory networks (SemNet) before and after attempting to solve a riddle. These networks represent the organization of solution-relevant and -irrelevant concepts as nodes, with edges representing the strength of the relationship between them based on participants’ relatedness judgments. Restructuring was quantified as the difference in SemNet metrics between pre- and post-solving phases. We found that restructuring a problem-related SemNet was associated with the successful solving of this problem and an analogous one. We showed that both specific solution-relevant concepts and concepts that were semantically remote became more strongly related in solvers. We also showed that only changes in semantically remote concepts were instrumental in actively solving the riddle while changes in solution-relevant concepts probably reflect a pre-exposure to the solution. These results shed new light on mental restructuring associated with problem-solving and analogical transfer, and show how changes in SemNet can capture this restructuring.
Sleep leads to a disconnection from the external world. Even when sleepers regain consciousness during rapid eye movement (REM) sleep, little, if any, external information is incorporated into dream content [1Dement W. Wolpert E.A. The relation of eye movements, body motility, and external stimuli to dream content.J. Exp. Psychol. 1958; 55: 543-553Crossref PubMed Scopus (207) Google Scholar, 2Rechtschaffen A. Foulkes D. Effect of visual stimuli on dream content.Percept. Mot. Skills. 1965; 20: 1149-1160Crossref PubMed Scopus (32) Google Scholar, 3Berger R.J. Experimental modification of dream content by meaningful verbal stimuli.Br. J. Psychiatry. 1963; 109: 722-740Crossref PubMed Scopus (64) Google Scholar]. While gating mechanisms might be at play to avoid interference on dreaming activity [4Nir Y. Tononi G. Dreaming and the brain: from phenomenology to neurophysiology.Trends Cogn. Sci. 2010; 14: 88-100Abstract Full Text Full Text PDF PubMed Scopus (311) Google Scholar], a total disconnection from an ever-changing environment may prevent the sleeper from promptly responding to informative events (e.g., threat signals). In fact, a whole range of neural responses to external events turns out to be preserved during REM sleep [5Issa E.B. Wang X. Sensory responses during sleep in primate primary and secondary auditory cortex.J. Neurosci. 2008; 28: 14467-14480Crossref PubMed Scopus (81) Google Scholar, 6Nir Y. Vyazovskiy V.V. Cirelli C. Banks M.I. Tononi G. Auditory responses and stimulus-specific adaptation in rat auditory cortex are preserved across NREM and REM sleep.Cereb. Cortex. 2015; 25: 1362-1378Crossref PubMed Scopus (62) Google Scholar, 7Perrin F. García-Larrea L. Mauguière F. Bastuji H. A differential brain response to the subject's own name persists during sleep.Clin. Neurophysiol. 1999; 110: 2153-2164Crossref PubMed Scopus (219) Google Scholar, 8Blume C. Del Giudice R. Wislowska M. Heib D.P.J. Schabus M. Standing sentinel during human sleep: continued evaluation of environmental stimuli in the absence of consciousness.Neuroimage. 2018; 178: 638-648Crossref PubMed Scopus (18) Google Scholar, 9Strauss M. Sitt J.D. King J.R. Elbaz M. Azizi L. Buiatti M. Naccache L. van Wassenhove V. Dehaene S. Disruption of hierarchical predictive coding during sleep.Proc. Natl. Acad. Sci. USA. 2015; 112: E1353-E1362Crossref PubMed Scopus (106) Google Scholar]. Thus, it remains unclear whether external inputs are either processed or, conversely, gated during REM sleep. One way to resolve this issue is to consider the specific impact of eye movements (EMs) characterizing REM sleep. EMs are a reliable predictor of reporting a dream upon awakening [10Dement W. Kleitman N. The relation of eye movements during sleep to dream activity: an objective method for the study of dreaming.J. Exp. Psychol. 1957; 53: 339-346Crossref PubMed Scopus (509) Google Scholar, 11Goodenough D.R. Shapiro A. Holden M. Steinschriber L. A comparison of" dreamers" and" nondreamers": Eye movements, electroencephalograms, and the recall of dreams.J. Abnorm. Soc. Psychol. 1959; 59: 295Crossref Scopus (58) Google Scholar], and their absence is associated with a lower arousal threshold to external stimuli [12Ermis U. Krakow K. Voss U. Arousal thresholds during human tonic and phasic REM sleep.J. Sleep Res. 2010; 19: 400-406Crossref PubMed Scopus (77) Google Scholar]. We thus hypothesized that the presence of EMs would selectively prevent the processing of informative stimuli, whereas periods of REM sleep devoid of EMs would be associated with the monitoring of external signals. By reconstructing speech in a multi-talker environment from electrophysiological responses, we show that informative speech is amplified over meaningless speech during REM sleep. Yet, at the precise timing of EMs, informative speech is, on the contrary, selectively suppressed. These results demonstrate the flexible amplification and suppression of sensory information during REM sleep and reveal the impact of EMs on the selective gating of informative stimuli during sleep.
---Data set information--- Common name: Oudiette_N1Data Full name: N/A Authors: Célia Lacaux, Thomas Andrillon, Isabelle Arnulf & Delphine Oudiette Location: The Paris Brain Institute (France) Year: 2021 Set ID: 2 Amendment: 0 Corresponding author ID: 10 Previous publications: N/A Correspondence: Nicolas Decat (E: nicolasdecat59@gmail.com)
---Metadata--- Key ID: 2 Date entered: 2022-06-10T12:44:18+00:00 Number of samples: 252 Number of subjects: 63 Proportion REM: 0% Proportion N1: 6% Proportion N2: 9% Proportion W: 85% Proportion experience: 87% Proportion no-experience: 7% Proportion healthy: 100% Provoked awakening: Yes Time of awakening: Day Form of response: Free Date approved: 2022-06-14T10:27:11+00:00
---How to decode data files--- N/A --Treatment group codes-- N/A
---Experimental description--- Data was collected as part of a study investigating the role of the falling-asleep process on creative insight. A creativity task was completed prior to and following a 30-minute daytime nap, during which subjects (N=63, 18-35yo) were sitting on a reclining chair. Mental content was probed 4 times every 6 minutes. For each probe, subjects were asked to describe out loud what went through their mind prior to the alarm. --DREAM categorization procedure-- We classified participants' reports as: - Experience (E): something (i.e., thoughts, imagery) went through their mind at the probe. - No Experience (NE): nothing went through their mind at the probe. - Experience Without Recall (WR): something went through their mind at the probe but they could not recall any mental content. Conscious experiences (E) were further defined as hypnagogic if it was “fleeting, involuntary, spontaneous, perceptual, and bizarre”, else they were defined as "waking thoughts". Note: Mental content is currently in French.
---Technical details--- No artefacts Note: In all recordings, EOG and EMG signals were clipped at 100uV. --Data acquisition-- 3 EEG electrodes (C3, O1, Fp1) 2 EOG 1 chin EMG 256Hz sampling rate --Data preprocessing-- 0.1-40Hz unstopped EEG frequency band Reference to mastoid (A2) Data are originally in EDF => chunked with FASST toolbox to get only the N1 episode that precedes the awakening & dream report (new format: .mat + .dat)
'/%3e%3c/defs%3e%3cpath fill='%23012169' d='M0 0h10080v5040H0z'/%3e%3cpath stroke='%23fff' stroke-width='.6' d='m0 0 6 3m0-3L0 3' clip-path='url(%23b)' transform='scale(840)'/%3e%3cpath stroke='%23e4002b' stroke-width='.4' d='m0 0 6 3m0-3L0 3' clip-path='url(%23c)' transform='scale(840)'/%3e%3cpath stroke='%23fff' stroke-width='840' d='M2520 0v2520M0 1260h5040'/%3e%3cpath stroke='%23e4002b' stroke-width='504' d='M2520 0v2520M0 1260h5040'/%3e%3cg fill='%23fff'%3e%3cuse xlink:href='%23d' x='2520' y='3780'/%3e%3cuse xlink:href='%23a' x='7560' y='4200'/%3e%3cuse xlink:href='%23a' x='6300' y='2205'/%3e%3cuse xlink:href='%23a' x='7560' y='840'/%3e%3cuse xlink:href='%23a' x='8680' y='1869'/%3e%3cuse xlink:href='%23e' x='8064' y='2730'/%3e%3c/g%3e%3c/svg%3e)
