‘I love you’: the first phrase detected from dreams

Objective Many people have dreams nightly and some maintain consciousness during dreams. Such dreams are referred to as lucid dreams (LD). During dreams, our speech correlates with facial muscle activity, which is hard to decode, but LD could solve this problem. The primary hypothesis of this study was that the facial muscles electric activity during LD corresponds to specific sounds. Understanding this connection could help decode dream speech in the future.

Material and Methods Under laboratory conditions, four LD practitioners were asked to say “I love you”, a phrase with a distinctive electromyographic (EMG) signature. They did this before falling asleep and then again after becoming conscious during a dream. Their facial and neck EMG was recorded in four areas.

Results All four volunteers accomplished the goal at least once. The patterns associated with the “I love you” phrase were observed in most cases, both during wakefulness and LD. Specifically, the “I” triggered distinctive phasic activity in the submentalis area most of the time, while “you” did the same in the orbicularis oris.

Discussion This study highlights the possibility of detecting only specific and highly EMG distinctive phrases from dreams because vocalization also involves a tong and vocal apparatus. The most interesting consequence of the present results is that they indicate the possibility of creating an artificial EMG language that could be instantly decoded in reality and used during LD.

Dreams - Lucid Dreaming - Language - Sleep - REM - Vocalization - Consciousness

INTRODUCTION

Dreams are emotions and perceptions experienced during sleep. A person’s dream recall frequency (DRF) usually rises from adolescence to early adulthood before decreasing by the age of 50-60 years[1]. DRF depends not only on age[2]-[6] but on gender[1],[7],[8], pathologies[6],[9], individual brain structure[10],[11], stress[12], sleep quality[13], ultradian NREM-REM sleep cycle and the circadian modulation of REM sleep[14], cultural differences[15], and other factors. For a long time, it was believed that dreams happen only during REM sleep. Though this is still true of vivid dreams, we now know dreams can be recalled after other sleep stages[16]-[20], even after slow-wave sleep[21]-[23].

Early research revealed that our eyes follow dream scenes[24],[25], as the eye muscles are not paralyzed during REM sleep[26],[27]. The most significant achievement in this research direction was the creation of a neural decoding approach that uses machine learning to predict the contents of visual imagery during sleep onset[28]. In the future, functional magnetic resonance imaging can be used to enhance similar technologies[29]. A correlation between talking during dreams and chin electromyography (EMG) was established long ago[30],[31]. Thus, EMG could help us not only to ‘hear’ our dreaming voice but also to decode our movements in dreams[32].

The main problem with most of the abovementioned studies is the absence of a direct connection between dreamers and researchers. As a result, it is hard to understand what exactly a person does in a dream. If we could determine this, it would help to correlate recorded data with actual actions or perceptions in dreams. This problem could be solved by lucid dreams (LD) because not only can people see LD, but they can also control them[33],[34]. LD usually happen during REM sleep, though they can occur during non-REM sleep in rare cases[35]-[37], and can be triggered by acetylcholine[38],[39].

The term ‘lucid dreaming’ was first used by Frederik Van Eeden, in 1913[40], though the phenomenon was not confirmed by science until 1975. LD were confirmed when pre -agreed eye movements (PAEM) were observed during REM sleep[41]. Recent studies show that LD have several practical applications, such as preventing nightmares[42],[43], lowering chronic pain[44], problemsolving[45],[46], controlling computers while asleep[47], and exercising motor skills[48].

A meta-analysis of 50 studies shows that 55% of people have experienced at least one LD[49]. Several other phenomena share LD’ primary features (e.g., consciousness during REM sleep), including sleep paralysis[50],[51], false awakenings[52], and out-of-body experiences[53]-[55]. These states are grouped under the term phase state (PS)[55],[56] or dissociated REM state [57]. A survey revealed that 88% of people have experienced at least one phase state; 43% of people experience one or more of them often[58].

LD have been successfully used since the late 1970s to establish connections between the dream world and wakefulness. For example, Hearne (1978)[41] detected such a connection based on PAEM. Furthermore, LaBerge et al. (1981)[33] found that Morse signals induced in the arm muscles could be transferred from LD into reality. Later, it became possible to communicate with people during LD in real time using much broader approaches involving breathing and facial muscle expressions[59]-[61].

If facial EMG is connected to dream speech[30],[31], we might be able to use LD to identify specific sounds, words, or even phrases from dreams. As far as we know, no scientific attempts have been made to do this, though some studies present promising preliminary data. For example, a process has been developed for digitally voicing silent speech, which could work similarly for dream speech. Gaddy and Klein (2020)[62] showed that the EMG patterns of silent speech are correlated with the patterns of vocalized speech - this knowledge could be used to improve vocalized speech. Such technologies could be useful for people who have had their larynx removed[63] and for creating silent speech-to-text systems[64].

Hypotheses

The primary hypothesis of this study is that speech vocalized in an LD presents the same EMG patterns as speech vocalized during wakefulness. Confirmation of this hypothesis could provide a method for decoding LD speech, as well as speech from unconscious dreams. The results of this research could also improve our understanding of dreams, LD, REM sleep, consciousness, and vocalization. It could also open new opportunities for ‘seeing’ the dream world.

MATERIAL AND METHODS

Resources and participants

The present research was accomplished under laboratory conditions using facial and neck EMG sensors. Highly experienced LD practitioners were invited to volunteer in the study. LD practitioners are people who are trained to induce LDs by their will. They were chosen based on their ratings in the Project Elijah online platform, where LD practitioners continuously accomplish different LD experiments. We contacted and invited to participate in the present study those practitioners who had accomplished the most experiments and lived close to the laboratory. Ethical committee approval was obtained from the Phase Research Center’s institutional review board (approval’s ID: PRC-2021-6-11-02).

All volunteers confirmed that they were at least 18 years old and presented no psychological or physiological issues that could be affected by LD or the study protocol. Written informed consent was obligatory for all subjects before the research began. Volunteers’ primary motivation for participating was the opportunity to explore their LD practice. No financial reward was given, though all travel and accommodation expenses were covered.

Apparatus and LD detection

‘Encephalan-EEGR-19/26’ was used to accomplish the research goals by tracking EMG and detecting LD occurrences. The configuration contained four EMG channels (50Hz notch filter; 16-70Hz band-pass filter) ([Figure 1a]). EMG #1 was located in the levator labii superioris area (EMG LLS). EMG #2 was located in the orbicularis oris area, under the upper lip (EMG OO). EMG #3 was located in the submentalis area (EMG SM). EMG #4 was located in the laryngeal area in front of the vocal apparatus (EMG L). These EMG locations were used due to their efficiency in silent speech[62].

Figure 1 A EMG sensors placement: EMG LLS = Levator labii superioris area; EMG OO = Orbicularis oris area; EMG SM = Submentalis area; EMG L = Laryngeal area; B. Distinctive EMG SM activation during “I” vocalization; C. No distinctive EMG activation during “love” vocalization; D. Distinctive EMG OO activation during “you” vocalization.

Experimental task

Preliminary tests, including successful vocalization during an LD ([Figure 2]), indicated that any sounds made during LD should present distinctive EMG patterns if they are to be detected clearly. The phrase “I love you” was used for this preliminary test. While “love” could change its pattern from time to time ([Figure 1c]), “I” could mostly trigger EMG SM ([Figure 1b]), and “you” could do the same with EMG OO ([Figure 1d]), thereby creating a stable and distinctive EMG pattern in wakefulness ([Figure 3]), which, in theory, could be seen from LD vocalization as well. EMG LLS and EMG L were used to gather more data from the study, even though their correlation with “I love you” pronunciation was week.

Figure 2 A preliminary test with successful loud vocalization in LD.Abbreviation: EMG LLS = Levator labii superioris area; EMG OO = Orbicularis oris area; EMG SM = Submentalis area; EMG L = Laryngeal area.

Figure 3 The ‘I love you’ pattern in wakefulness.Abbreviations: EMG LLS = Levator labii superioris area; EMG OO = Orbicularis oris area; EMG SM = Submentalis area; EMG L = Laryngeal area.

LD practitioners received an instructed to perform the following procedure after assembling EMG sensors: A) clearly pronounce “I love you’ a few times and perform pre -agreed chin movements (PACM); B) fall asleep and induce an LD by any convenient technique like creating a strong intention upon falling asleep to become conscious in an upcoming dream; C) if B is successful, loudly pronounce “I love you” a few times during the LD and perform PACM; D) if C is successful, try to enter another LD and repeat step C. Volunteers were able to focus on the study goals across one to three nights in a laboratory. No limitations were imposed in terms of LD quantity.

The volunteers were also allowed to use LD maintaining and stabilizing techniques to prolong LD and increase their quality.

PACM as an LD detection method

PACM require EMG sensors to be placed only in the submentalis area, which was already included in the configuration of the current experiment. REM sleep atonia and phasic bursts of PACM can be detected during LD using the PACM method[65]. As REM sleep and consciousness are the main characteristics of LD, the PACM method is considered the main LD detection method in the present study. Volunteers were asked to deploy three consecutive and wide chin movements while in an LD to manifest consciousness during sleep atonia.

RESULTS

Four volunteers participated in the study, sleeping from one to three nights in the laboratory with EMG sensors attached (24-40 years old; females N=2). All four volunteers were able to experience LD and achieve the goal at least once. One of the volunteers was able to achieve the goal twice. All the reports showed distinctive phasic EMG bursts during vocalization in LD and PACMs.

Volunteer #1 reported their first LD on the first night and performed the PACM/vocalization cycle four times. The “I love you” EMG pattern fully coincided three times and 50% one time. In one unsuccessful vocalization attempt, “you” was stronger for EMG SM than EMG OO, though both were powerful ([Figure 4]). No LD occurred on the second night for this volunteer. The second LD occurred on the third night, and the volunteer performed the PACM/vocalization cycle four times. The “I love you” EMG pattern fully coincided two times and 50% the other two times. In both unsuccessful vocalization attempts, the EMG SM burst of “I” was not distinctive enough ([Figure 5]).

Figure 4 First LD of volunteer #1.Abbreviations: EMG LLS = Levator labii superioris area; EMG OO = Orbicularis oris area; EMG SM = Submentalis area; EMG L = Laryngeal area.

Figure 5 Second LD of volunteer #1.Abbreviations: EMG LLS = Levator labii superioris area; EMG OO = Orbicularis oris area; EMG SM = Submentalis area; EMG L = Laryngeal area; PACM = Pre-agreed chin movements.

Volunteer #2 reported one LD on the first night and performed PACM/vocalization cycle three times. The “I love you” EMG pattern fully coincided two times and 50% the other time. In one unsuccessful vocalization attempt, the EMG SM burst of “I” was not distinctive enough ([Figure 6]). The volunteer reported very loud vocalization (close to shouting) in LD.

Figure 6 LD of volunteer #2.Abbreviations: EMG LLS = Levator labii superioris area; EMG OO = Orbicularis oris area; EMG SM = Submentalis area; EMG L = Laryngeal area; PACM = Pre-agreed chin movements.

Volunteer #3 reported one LD on the second night and performed PACMs followed by two vocalizations three times each. During the first vocalization, only PACMs were distinctive. During the second vocalization, which happened 30 seconds after the first, the “I love you” EMG pattern fully coincided two times and 50% one time. In one unsuccessful vocalization attempt, the EMG SM burst of “I” was not distinctive enough ([Figure 7]).

Figure 7 LD of volunteer #3.Abbreviations: EMG LLS = Levator labii superioris area; EMG OO = Orbicularis oris area; EMG SM = Submentalis area; EMG L = Laryngeal area; PACM = Pre-agreed chin movements.

Volunteer #4 reported one LD on the first night, during which they performed two PACM/vocalization cycles right before awakening. The EMG data analysis indicated that only the first PACM were hardly distinctive. Both vocalization patterns of “I love you” coincided at 50%, as EMG OO activity was missing ([Figure 8]). The volunteer expressed that their vocalization level ‘could be higher.’ During the second night, the volunteer could not enter an LD.

Figure 8 LD of volunteer #4.Abbreviations: EMG LLS = Levator labii superioris area; EMG OO = Orbicularis oris area; EMG SM = Submentalis area; EMG L = Laryngeal area; PACM = Pre-agreed chin movements.

DISCUSSION

Humanity has always been fascinated by dreams, hoping to see them in reality. Technological advances have given us tools to glimpse into dreams, but we still have not had any significant success. Due to EMG-related correlations between the physical facial muscles and dream speech, we might at least be able to ‘hear’ what we talk about while we are asleep. LD could help with this goal, as speech can be controlled during LD. We hypothesized that an EMG distinctive phrase could present the same pattern in wakefulness as in an LD.

Hypotheses confirmation

The results show relatively stable EMG correlations when pronouncing the goal phrase in wakefulness and in an LD when the phrase was vocalized loudly and with concentration in both cases. “I love you” is the first phrase that we detected from dreams with certainty - we knew it was said in dreams and we detected its EMG pattern at the same time. Thus, it is reasonable to conclude that LD can be used to decode dream speech. From the perspective of previous studies confirming the correlation between facial EMG activity dream speech[30]-[32], the present results are not unexpected.

All narratively reported successful LD with vocalization were found in the EMG data, and all cases were highly distinctive from normal EMG sleep patterns. Rare phasic spikes occurred during most low tonic activity, which most likely represented sleep atonia. Apparent phasic activity was detected when vocalizations were reported.

We certainly cannot effectively detect and decode most dream speech using the EMG settings of the current study. Vocalization requires the tongue and vocal apparatus in addition to facial muscles - therefore, examining facial muscles via facial EMG alone is not enough to decode all sounds. However, future technological advances could make this kind of decoding possible.

Nevertheless, the results of the present study indicate the current possibility of detecting EMG patterns for some specific sounds. However, different sounds can have the same facial EMG patterns. Therefore, more advanced and complicated settings, including machine learning, are needed to differentiate all the sounds. The current study only confirms that this method could be developed in the future. For now, we know that speech in dreams indeed coincides with the EMG patterns of vocalizations in reality.

EMG L, located near the vocal apparatus, did not consistently show any specific activity that was distinctive from the activity of other EMG sensors. In most cases, EMG L activity in wakefulness and during LD was closely related to EMG SM activity - these two EMGs were located close to one another.

New research opportunities

The current study presents impressive perspectives of LD practitioners. However, new studies with more advanced technologies are needed to effectively decode English (or any other language) from ordinary dreams. If LD are studied (as opposed to regular dreams), the findings of the present study could already be applicable. This is because people can control their vocalization and deploy specific EMG patterns during LD. Therefore, some distinctive EMG pre-agreed phrases can be learned and detected using just a few sensors.

This branch of research could become even more interesting if an EMG language is developed for LD practitioners. In theory, this language could use only a few distinct EMG sounds, which all could be distinctively vocalized, efficiently read by sensors, and automatically decoded. This artificial language could make it possible to ‘hear’ everything pronounced in LD. Eventually, LD practitioners could be able to communicate with each other over the Internet while asleep[55],[56]. In this case, an artificial EMG language could be pivotal - the results of the current study confirm its possibility for general use.

Vocalization in LD requires not only conscious actions but also EMG traces on the face, submentalis, and throat - these last two also can be used to detect sleep atonia adherent to REM sleep[66], which in turn is the main physiological sleep stage associated with LD[67]. Pre-agreed vocalization (PAV) during LD could be used together with PAEM and PACM detection methods. For example, after LD vocalization, facial EMG patterns, which are very unlikely to happen spontaneously during ordinary dreams, were detected. These patterns could serve as a clear sign of consciousness alongside with PAEM or PACM.

Vocalization in other phase states

As LD naturally relate to phenomena like sleep paralysis (SP), out-of-body experiences, and false awakenings[58], the results of the current study could apply to all these states. This is especially important regarding SP, which is frequent among the general population[68],[69] and presents a severe problem for narcoleptics[70]. The outcomes of the present study indicate that a vocal/EMG communication tool could be developed for people suffering from SP. In theory, this could enhance SP studies and reduce the fear experienced during SP through bidirectional communication with reality.

Limitations

The most controversial issue presented in this study is the implementation of PACM to detect LD, so no electroencephalography (EEG) or electrooculography (EOG) were recorded. Thus standard sleep staging could not be done. In this sense, our results should be viewed as preliminary. This was the first study to use PACM approach, excluding PACM testing itself[65]. In most previous LD studies, PAEM were used as the standard verification method (for a review see MotaRolim, 2020[71]). This method requires EEG and EMG to detect sleep stages and EOG to detect consciousness. Therefore, an alternative PACM protocol was used, because this method significantly reduced the number of cords and sensors placed on the volunteers’ heads and faces during this particular study. Muscle atonia reflects REM sleep and pre-agreed phasic signals through EMG SM represent consciousness. Thus, both primary attributes of LD are confirmed alongside the narrative reports of the volunteers.

Subjects were asked to pronounce the goal phrase very loudly and distinctively to ensure the phrase could be detected during the LD. They also practiced for a couple of minutes before falling asleep. However, even after these instructions, the phrase was not always pronounced loudly, and the resultant EMG patterns were very week ([Figures 5] and [8]), meaning that quiet speech during LD and ordinary dreams could not be detected.

So, in the current study, vocalization in dreams was detected only if the phrase was vocalized loudly and distinctively. Vocalizations that were close to shouting were especially effective ([Figure 6]). In future research and practical applications, LD practitioners should rehearse the phrases even more and vocalize them very distinctively while dreaming, feeling the muscle tension related to each specific sound. This strategy will yield more distinctive results than the present study, with fewer mistakes.

In the present study, the most prominent problem with vocalization during LD was associated with EMG SM phasic activity. This vocalization problem occurred more often than with EMG OO.

CONCLUSION

The study highlights a new opportunity to explore dreams with the help of LD. Though we still cannot see dreams from reality, it seems possible to partially ‘hear’ what we say in dreams through facial EMG patterns. However, we cannot detect any sounds or words using this new tool because the vocalization process also involves complicated functions of the tongue and vocal apparatus, which cannot currently be decoded from dreams. Regardless, this new LD tool could be useful for detecting highly distinctive EMG sounds, words, and phrases. In turn, this could be useful for understanding dreams, as well as helping people who suffer from sleep paralysis.

The results of the present study could present new opportunities for future studies. First, we should clarify exactly why it is possible to read EMG traces of vocalizations in dreams. Second, it would be helpful to study minute details related to the topic (e.g., which sounds can be decoded, the proper way to vocalize sounds, whether an EMG dream vocabulary can be created). Very intriguing opportunities could arise if we find or create a way to use EMG to decode all words in dreams. This would provide LD practitioners with a way to communicate with each other while sleeping. Perhaps an artificial EMG language should be designed to achieve this goal. Also, it could be explored whether we can use LD to hone our speech, given that silent speech improves pronunciation.

Exploring new opportunities via vocalizations during LD could provide more chances for decoding dreams. It could also improve our knowledge about the sleep process, REM sleep, muscle atonia, vocal apparatus, and many other topics. Therefore, new hypotheses based on the current study could help science and culture to reach new horizons.

Conflict of Interests

The authors have no conflict of interests to declare.

Acknowledgments

The author of this research thanks Andrey Shashkov, Kira Wonder, and Eugenia Safronova for their contributions to the study.

The author of this work has no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patentlicensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge, or beliefs) in the subject matter or materials discussed in this manuscript.

• REFERENCES

• 1 Nielsen T. Variations in dream recall frequency and dream theme diversity by age and sex. Front Neurol. 2012;3:106. DOI: https://doi. org/10.3389/fneur.2012.00106
• 2 Funkhouser AT, Hirsbrunner HP, Cornu C, Bahro M. Dreams and dreaming among the elderly: an overview. Aging Ment Heal. 1999;3(1):10-20. DOI: https://doi.org/10.1080/13607869956398
• 3 Schredl M. Home dream recall in children and young adults. Int J Dream Res. 2009;2(2):58-9. DOI: https://doi.org/10.11588/ijodr.2009.2.401
• 4 Zanasi M, Persis S, Caporali M, Siracusano A. Dreams and age. Percept Mot Skills. 2005 Jun;100(Suppl 3):925-38. DOI: https://doi. org/10.2466/pms.100.3c.925-938
• 5 Herman S, Shows WD. How often do adults recall their dreams? Int J Aging Hum Dev. 1984;18(4):243-54. DOI: https://doi.org/10.2190/ A3R8-C69H-13X5-P5V0
• 6 Guénole F, Marcaggi G, Baleyte JM, Garma L. Dreams in normal and pathological aging. Psychol Neuropsychiatr Vieil. 2010 Jun;8(2):87-96.
• 7 Schredl M. Factors influencing the gender difference in dream recall frequency. Imagin Cogn Pers. 2002;22(1):33-9. DOI: https://doi. org/10.2190/jr55-wyc2-1gc0-023d
• 8 Schredl M. Explaining the gender difference in dream recall Frequency. Dreaming. 2010;20(2):96-106. DOI: https://doi.org/10.1037/a0019392
• 9 Schredl M. Dream recall frequency and sleep quality of patients with restless legs syndrome. Eur J Neurol. 2008 Jul;8(2):185-9. DOI: https:// doi.org/10.1046/j.1468-1331.2001.00203.x
• 10 Eichenlaub JB, Nicolas A, Daltrozzo J, Redouté J, Costes N, Ruby P. Resting brain activity varies with dream recall frequency between subjects. Neuropsychopharmacology. 2014 Jan;39:1594-602. DOI: https://doi.org/10.1038/npp.2014.6
• 11 Vallat R, Eichenlaub JB, Nicolas A, Ruby P. Dream recall frequency is associated with medial prefrontal cortex white-matter density. Front Psychol. 2018;9:1856. DOI: https://doi.org/10.3389/fpsyg.2018.01856
• 12 Brand S, Beck J, Kalak N, Gerber M, Kirov R, Pühse U, et al. Dream recall and its relationship to sleep, perceived stress, and creativity among adolescents. J Adolesc Health. 2011 Nov;49(5):525-31. DOI: https:// doi.org/10.1016/j.jadohealth.2011.04.004
• 13 Ribeiro N, Gounden Y, Quaglino V. Is there a link between frequency of dreams, lucid dreams, and subjective sleep quality?. Front Psychol. 2020 May;11:1290. DOI: https://doi.org/10.3389/fpsyg.2020.01290
• 14 Chellappa SL, Münch M, Blatter K, Knoblauch V, Cajochen C. Does the circadian modulation of dream recall modify with age?. Sleep. 2009 Sep;32(9):1201-9. DOI: https://doi.org/10.1093/sleep/32.9.1201
• 15 Schwitzgebel E. Why did we think we dreamed in black and white?. Stud Hist Philos Sci Pt A. 2002 Dec;33(4):649-60. DOI: https://doi. org/10.1016/S0039-3681(02)00033-X
• 16 Solms M. Dreaming is not controlled by hippocampal mechanisms. Behav Brain Sci. 2013;36(6):629. DOI: https://doi.org/10.1017/ S0140525X1300143X
• 17 Nir Y, Tononi G. Dreaming and the brain: from phenomenology to neurophysiology. Trends Cogn Sci. 2010 Feb;14(2):88-100. DOI: https://doi.org/10.1016/j.tics.2009.12.001
• 18 Ruby PM. Experimental research on dreaming: State of the art and neuropsychoanalytic perspectives. Front Psychol. 2011 Nov;2:286. DOI: https://doi.org/10.3389/fpsyg.2011.00286
• 19 Montangero J. Dreaming and REM sleep: history of a scientific denial whose disappearance entailed a reconciliation of the neuroscience and the cognitive psychological approaches to dreaming. Int J Dream Res. 2018;11(1):30-45. DOI: https://doi.org/10.11588/ijodr.2018.1.42384
• 20 Scarpelli S, D’Atri A, Bartolacci C, Gorgoni M, Mangiaruga A, Ferrara M, et al. Dream recall upon awakening from non-rapid eye movement sleep in older adults: electrophysiological pattern and qualitative features. Brain Sci. 2020 Jun;10(6):343. DOI: https://doi.org/10.3390/ brainsci10060343
• 21 Cavallero C, Cicogna P, Natale V, Occhionero M, Zito A. Slow wave sleep dreaming. Sleep. 1992 Nov;15(6):562-6. DOI: https://doi.org/10.1093/ sleep/15.6.562
• 22 Siclari F, Bernardi G, Cataldi J, Tononi G. Dreaming in NREM sleep: a high - density EEG study of slow waves and spindles. J Neurosci. 2018 Oct;38(43):9175-85. DOI: https://doi.org/10.1523/ JNEUROSCI.0855-18.2018
• 23 Carr M, Solomonova E. Dream recall and content in different stages. In: Valli K, Hoss R, eds. Dreams: biology, psychology and culture. Santa Barbara: Greenwood Publishing Group; 2019.
• 24 Roffwarg HP, Dement WC, Muzio JN, Fisher C. Dream imagery: relationship to rapid eye movements of sleep. Arch Gen Psychiatry. 1962 Oct;7(4):235-58. DOI: https://doi.org/10.1001/ archpsyc.1962.01720040001001
• 25 Herman JH, Erman M, Boys T, Peiser L, Taylor ME, Roffwarg HP. Evidence for a directional correspondence between eye movements and dream imagery in REM sleep. Sleep. 1984 Sep;7(1):52-63. DOI: https://doi.org/10.1093/sleep/7.1.52
• 26 Aserinsky E, Kleitman N. Regularly occurring periods of eye motility, and concomitant phenomena, during sleep. Science. 1953;118(3052):273-4. DOI: https://doi.org/10.1126/science.118.3062.273
• 27 Jouvet M. Recherches sur les structures nerveuses et les mécanismes responsables des différentes phases du sommeil physiologique. Arch Ital Biol. 1962;100:125-206.
• 28 Horikawa T, Tamaki M, Miyawaki Y, Kamitani Y. Neural decoding of visual imagery during sleep. Science. 2013 Apr;340(6132):639-42. DOI: https://doi.org/10.1126/science.1234330
• 29 Nishimoto S, Vu AT, Naselaris T, Benjamini Y, Yu B, Gallant JL. Reconstructing visual experiences from brain activity evoked by natural movies. Curr Biol. 2011 Oct;21(9):1641-6. DOI: https://doi. org/10.1016/j.cub.2011.08.031
• 30 McGuigan FJ, Tanner RG. Covert oral behavior during conversational and visual dreams. Psychon Sci. 1971;23(4):263-4.
• 31 Shimizu A, Inoue T. Dreamed speech and speech muscle activity. Psychophysiology. 1986 Mar;23(2):210-4. DOI: https://doi. org/10.1111/j.1469-8986.1986.tb00620.x
• 32 Oldis D. Animating dreams and future dream recording [panel]. In: 34th Annual Conference of the International Association for the Study of Dreams (IASD). 2017 Jun 16-20; Anaheim, California, US. Anaheim, CA: IASD; 2017.
• 33 LaBerge SP, Nagel LE, Dement WC, Zarcone Junior VP. Lucid dreaming verified by volitional communication during REM sleep. Percept Mot Skills. 1981 Jun;52(3):727-32. DOI: https://doi.org/10.2466/ pms.1981.52.3.727
• 34 LaBerge S. Lucid dreaming: the power of being awake and aware in your dreams. Los Angeles: Tarcher; 1985.
• 35 Dane JH, Van De Castle RL. A comparison of waking instruction and posthypnotic suggestion for lucid dream induction. Lucidity Lett [Internet]. 1984 Dec; [cited 2021 June 01]; 3(4):1-7. Available from: https://journals.macewan.ca/lucidity/article/view/636/550
• 36 Mota-Rolim SA, Brandão DS, Andrade KC, Queiroz CMT, Araujo JF, Araujo DB, et al. Neurophysiological features of lucid dreaming during N1 and N2 sleep stages: two case reports. Sleep Sci. 2015 Dec;8(4):215. DOI: https://doi.org/10.1016/j.slsci.2016.02.093
• 37 Stumbrys T, Erlacher D. Lucid dreaming during NREM sleep: two case reports. Int J Dream Res. 2021;5(2):151-5. DOI: https://doi. org/10.11588/ijodr.2012.2.9483
• 38 LaBerge S, LaMarca K, Baird B. Pre-sleep treatment with galantamine stimulates lucid dreaming: a double-blind, placebo-controlled, crossover study. PLoS One. 2018;13(8):e0201246. DOI: https://doi. org/10.1371/journal.pone.0201246
• 39 Singh A, Gupta D. Can acetylcholine make you dream?. Sleep Sci. 2019;12(3):240. DOI: https://doi.org/10.5935/1984-0063.20190096
• 40 Van Eeden F. A study of dreams. Proc Soc Psych Res [Internet]. 1913; [cited 2021 June 01]; 26:1-12. Available from: http://www.dreamscience. ca/en/documents/New%20content/lucid%20dreaming%20pdfs/ vanEeden_PSPR_26_1-12_1913.pdf
• 41 Hearne KMT. Lucid dreams: an elecro-physiological and psychological study [thesis]. Liverpool: University of Liverpool; 1978.
• 42 Zadra AL, Pihl RO. Lucid dreaming as a treatment for recurrent nightmares. Psychother Psychosom. 1997;66(1):50-5. DOI: https:// doi.org/10.1159/000289106
• 43 Macedo TCF, Ferreira GH, Almondes KM, Kirov R, Mota-Rolim SA. My dream, my rules: can lucid dreaming treat nightmares?. Front Psychol. 2019;10:2618. DOI: https://doi.org/10.3389/fpsyg.2019.02618
• 44 Zappaterra M, Jim L, Pangarkar S. Chronic pain resolution after a lucid dream: a case for neural plasticity?. Med Hypotheses. 2014 Mar;82(3):286-90. DOI: https://doi.org/10.1016/j.mehy.2013.12.011
• 45 Stumbrys T, Erlacher D, Schmidt S. Lucid dream mathematics: an explorative online study of arithmetic abilities of dream characters. Int J Dream Res. 2011;4(1):35-40. DOI: https://doi.org/10.11588/ ijodr.2011.1.9079
• 46 Schmidt SCE, Stumbrys T, Erlacher D. Dream characters and the dream ego: an exploratory online study in lucid dreams. Dreaming. 2014;24(2):138-51. DOI: https://doi.org/10.1037/a0036942
• 47 Mallett R. A pilot investigation into brain-computer interface use during a lucid dream. Int J Dream Res. 2020;13(1):62-9. DOI: https:// doi.org/10.11588/ijodr.2020.1.68010
• 48 Stumbrys T, Erlacher D, Schredl M. Effectiveness of motor practice in lucid dreams: a comparison with physical and mental practice. J Sports Sci. 2016;34(1):27-34. DOI: https://doi.org/10.1080/02640414.2015.1030342
• 49 Saunders DT, Roe CA, Smith G, Clegg H. Lucid dreaming incidence: a quality effects meta-analysis of 50 years of research. Conscious Cogn. 2016 Jul;43:197-215. DOI: https://doi.org/10.1016/j. concog.2016.06.002
• 50 Terzaghi M, Ratti PL, Manni F, Manni R. Sleep paralysis in narcolepsy: more than just a motor dissociative phenomenon? Neurol Sci. 2012;33(1):169-7. DOI: https://doi.org/10.1007/s10072-011-0644-y
• 51 Hishikawa Y, Shimizu T. Physiology of REM sleep, cataplexy, and sleep paralysis. Adv Neurol [Internet]. 1995 Feb; [cited 2021 June 01]; 67:245-71. Available from: https://www.researchgate.net/ publication/14356396_Physiology_of_REM_sleep_cataplexy_and_ sleep_paralysis
• 52 Barrett D. Flying dreams and lucidity: an empirical study of their relationship. Dreaming. 1991;1(2):129-34. DOI: https://doi. org/10.1037/h0094325
• 53 Levitan L, LaBerge S, DeGracia DJ, Zimbardo P. Out-of-body experiences, dreams, and REM sleep. Sleep Hypn [Internet]. 1999; [cited 2021 June 01]; 1(3):186-96. Available from: https://www.researchgate. net/publication/281080488_Out-of-body_experiences_dreams_and_ REM_sleep
• 54 Schenck CH, Mahowald MW. Rapid eye movement sleep parasomnias. Neurol Clin. 2005 Nov;23(4):1107-26. DOI: https://doi.org/10.1016/j. ncl.2005.06.002
• 55 Raduga M. The phase: shattering the illusion of reality. Scotts Valley: Createspace Independent Publishing Platform; 2014.
• 56 Raduga M. Bne mena [out-of-body]. Moscow: Sputnik; 2004.
• 57 Mahowald MW, Schenck CH. Insights from studying human sleep disorders. Nature. 2005 Oct;437(7063):1279-85. DOI: https://doi. org/10.1038/nature04287
• 58 Raduga M, Kuyava O, Sevcenko N. Is there a relation among REM sleep dissociated phenomena, like lucid dreaming, sleep paralysis, outof- body experiences, and false awakening? Med Hypotheses. 2020 Nov;144:110169. DOI: https://doi.org/10.1016/j.mehy.2020.110169
• 59 Konkoly K, Appel K, Chabani E, Mironov AY, Mangiaruga A, Gott J, et al. Real-time dialogue between experimenters and dreamers during REM sleep. SSRN Electron J. 2020;1-51. DOI: https://doi. org/10.2139/ssrn.3606772
• 60 Appel K. Communication with a sleeping person [dissertação]. Osnabrück: University of Osnabrück; 2013.
• 61 Mironov AY, Sinin AV, Dorokhov VB. The method of dialogue with the sleeping subject in the state of lucid dream, using respiratory movements. Soc Technol. 2018;2:83-107. DOI: https://doi.org/10.31862/2500-2966-2018-2-83-107
• 62 Gaddy D, Klein D. Digital voicing of silent speech. In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2020 Nov 16-20; Punta Cana, Dominican Republic. Punta Cana: EMNLP; 2020; p. 5521-30. DOI: https://doi. org/10.18653/v1/2020.emnlp-main.445
• 63 Meltzner GS, Heaton JT, Deng Y, Luca G, Roy SH, Kline JC. Silent speech recognition as an alternative communication device for persons with laryngectomy. IEEE/ACM Trans Audio Speech Lang Process. 2017 Nov;25(2):2386-98. DOI: https://doi.org/10.1109/TASLP.2017.2740000
• 64 Schultz T, Wand M. Modeling coarticulation in EMG-based continuous speech recognition. Speech Commun. 2010 Apr;52(4):341-53. DOI: https://doi.org/10.1016/j.specom.2009.12.002
• 65 Raduga M. Detecting lucid dreams only by submentalis electromyography. Sleep Med. 2021 Dec;88:221-30.
• 66 Berger RJ. Tonus of extrinsic laryngeal muscles during sleep and dreaming. Science. 1961 Sep;134(3482):840. DOI: https://doi.org/10.1126/ science.134.3482.840
• 67 Voss U, Holzmann R, Tuin I, Hobson JA. Lucid dreaming: a state of consciousness with features of both waking and non-lucid dreaming. Sleep. 2009 Sep;32(9):1191-200. DOI: https://doi.org/10.1093/ sleep/32.9.1191
• 68 Denis D, French CC, Gregory AM. A systematic review of variables associated with sleep paralysis. Sleep Med Rev. 2018 Apr;38:141-57. DOI: https://doi.org/10.1016/j.smrv.2017.05.005
• 69 Sharpless BA, Barber JP. Lifetime prevalence rates of sleep paralysis: a systematic review. Sleep Med Rev. 2011 Oct;15(5):311-5. DOI: https:// doi.org/10.1016/j.smrv.2011.01.007
• 70 Nan’no H, Hishikawa Y, Koida H, Takahashi H, Kaneko Z. A neurophysiological study of sleep paralysis in narcoleptic patients. Electroencephalogr Clin Neurophysiol. 1970 Apr;28(4):382-90. DOI: https://doi.org/10.1016/0013-4694(70)90231-2
• 71 Mota-Rolim SA. On moving the eyes to flag lucid dreaming. Front Neurosci. 2020 Apr;14:361. DOI: https://doi.org/10.3389/fnins.2020.00361

Publication History

Received: 25 June 2021

Accepted: 13 October 2021

Article published online:
01 December 2023