Influencing dreams through sensory stimulation: A systematic review

Salvesen, Leila; Capriglia, Elena; Dresler, Martin; Bernardi, Giulio

doi:10.1016/j.smrv.2024.101908

Cited by 12 publications

(8 citation statements)

References 82 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The methodological quality of the present study was evaluated by an independent rater using the adapted Downs & Black (1998) methodological assessment checklist (Salvesen et al, 2024). This 23-item checklist examines a series of aspects concerning internal and external validity, as well as the reporting of the methods and outcomes, providing a score ranging from 0 to 25.…”

Section: Methodsmentioning

confidence: 99%

“…This 23-item checklist examines a series of aspects concerning internal and external validity, as well as the reporting of the methods and outcomes, providing a score ranging from 0 to 25. This allows for an objective and comparable measure of scientific rigor, as exemplified in previous (lucid) dreaming literature (see systematic reviews in Stumbrys et al, 2012; Tan & Fan, 2022; Salvesen et al, 2024), with the adapted version having been designed to optimally serve the evaluation of sleep and dream engineering studies.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Highly effective verified lucid dream induction using combined cognitive-sensory training and wearable EEG: a multi-centre study

Jafarzadeh Esfahani,

Anna Christina Salvesen,

Picard-Deland

et al. 2024

Preprint

View full text Add to dashboard Cite

The state of becoming aware that one is dreaming within an ongoing dream, referred to as lucid dreaming (LD), can occur spontaneously. Yet, since the occurrence of spontaneous LD is relatively rare, various methods have been proposed to induce LD. Existing scientific literature, however, has been constrained by either small sample sizes with limited generalizability, or by reliance on subjective measures without physiological signals. To address these limitations, we recorded verifiable LD using 2-channel EEG and an open-source dream engineering toolbox (Dreamento) in a large sample size of 60 participants collected across a multi-center study in the Netherlands (NL), Italy (IT), and Canada (CA). We employed a novel combination of the senses-initiated lucid dreaming (SSILD) method and a targeted lucidity reactivation (TLR) protocol. Our final sample consists of 60 participants who came twice to the lab for morning naps with a pre-sleep lucidity training paired with multimodal sensory cues (visual, auditory, tactile). Cues were presented again in REM sleep in one of the two naps (stimulation and sham conditions counterbalanced). This preprint reports results from NL and IT in 40 participants: we successfully induced signal-verified lucid dreams (SVLD) in 65% and 45% of NL and IT participants, respectively. Among these, 45% and 35% (NL and IT) of REM cueing and 35% and 15% (NL and IT) of REM sham sessions resulted in at least one SVLD. In NL, the REM cueing sessions yielded 37 predefined eye signals with an average continuously verified lucidity duration of 78.75 +- 54.85 s. The REM sham sessions resulted in 15 eye signals in the presence of LD report (i.e, SVLD) and had an average duration of 47.80 +- 22.49 s. In IT, 48 predefined eye signals were identified within REM cueing sessions, with an average overall duration (i.e., from the first to the last predefined eye signal) of 506.33 +- 643.73 s and an average continuously verified (consecutive eye signals) duration of 91.13 +- 70.87 s. In contrast, 10 predefined eye signals were identified during REM sham sessions, with an average overall duration of 546.5 +- 744.58 s and a single continuously verified episode that lasted 20 s. Preliminary findings suggest that REM cueing aids the initiation and maintenance of lucidity, facilitates objective estimation of LD duration, and increases dream control. Future research should focus on automating the tools we provided and conducting larger-scale fully automatised studies at home to further explore factors contributing to such high success rates.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Highly effective verified lucid dream induction using combined cognitive-sensory training and wearable EEG: a multi-centre study

Jafarzadeh Esfahani,

Anna Christina Salvesen,

Picard-Deland

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…A recent research area combines TMR methods with dream content studies to investigate the impact of external stimuli on dreams (for a systematic recent review on this topic refer to 62 ). This line of research may eventually provide insights into the question whether and how memory reactivation during sleep is related to ongoing dreaming.…”

Section: Types Of Memorymentioning

confidence: 99%

“…Mem . (2023) TMR during NREM and REM sleep 36 Carbone et al, b ioRxiv (2023) TMR during NREM and REM sleep 57 Salvesen et al , PsyArXiv (2023) TMR influencing dream content 62 Haar Horowitz et al , Cogn . (2020) TMR influencing dream content, Home applications 63 Schwartz et al , Curr.…”

Section: Introductionmentioning

confidence: 99%

An update on recent advances in targeted memory reactivation during sleep

Carbone,

Diekelmann

2024

npj Sci. Learn.

View full text Add to dashboard Cite

Targeted Memory Reactivation (TMR) is a noninvasive tool to manipulate memory consolidation during sleep. TMR builds on the brain’s natural processes of memory reactivation during sleep and aims to facilitate or bias these processes in a certain direction. The basis of this technique is the association of learning content with sensory cues, such as odors or sounds, that are presented during subsequent sleep to promote memory reactivation. Research on TMR has drastically increased over the last decade with rapid developments. The aim of the present review is to highlight the most recent advances of this research. We focus on effects of TMR on the strengthening of memories in the declarative, procedural and emotional memory domain as well as on ways in which TMR can be used to promote forgetting. We then discuss advanced technical approaches to determine the optimal timing of TMR within the ongoing oscillatory activity of the sleeping brain as well as the specificity of TMR for certain memory contents. We further highlight the specific effects of TMR during REM sleep and in influencing dream content. Finally, we discuss recent evidence for potential applications of TMR for mental health, educational purposes and in the home setting. In conclusion, the last years of research have provided substantial advances in TMR that can guide future endeavors in research and application.

show abstract

“…Dreams are subjective conscious experiences generated by the brain during sleep — when individuals are largely (though not completely; [1]) disconnected from the external environment on the sensory (input) and motor (output) sides and are typically unable to exert volition and self-reflection [2]. Dream experiences draw on previously acquired memories and beliefs and, thus, present relevant aspects of continuity with thoughts, concerns, and salient experiences of our waking self.…”

Section: Introductionmentioning

confidence: 99%

The individual determinants of morning dream recall

Elce,

Bergamo,

Bontempi

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

Evidence suggests that (almost) everyone dreams during their sleep and may actually do so for a large part of the night. Yet, dream recall shows large interindividual variability. Understanding the factors that influence dream recall is crucial for advancing our knowledge regarding dreams' origin, significance, and functions. Here, we tackled this issue by prospectively collecting dream reports along with demographic information and psychometric, cognitive, actigraphic, and electroencephalographic measures in 204 healthy adults (18-70 y, 113 females). We found that attitude towards dreaming, proneness to mind wandering, and sleep patterns are associated with the probability of reporting a dream upon morning awakening. The likelihood of recalling dream content was predicted by age and vulnerability to interference. Moreover, dream recall appeared to be influenced by night-by-night changes in sleep patterns and showed seasonal fluctuations. Our results provide an account for previous observations regarding inter- and intra-individual variability in morning dream recall.

show abstract

Influencing dreams through sensory stimulation: A systematic review

Cited by 12 publications

References 82 publications

Highly effective verified lucid dream induction using combined cognitive-sensory training and wearable EEG: a multi-centre study

Highly effective verified lucid dream induction using combined cognitive-sensory training and wearable EEG: a multi-centre study

An update on recent advances in targeted memory reactivation during sleep

The individual determinants of morning dream recall

Contact Info

Product

Resources

About