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Motor Learning in Lucid Dreams: Prevalence, Induction, and Effectiveness

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The purpose of the present investigation was to explore the potentials for motor learning in a special state of consciousness – so called lucid dreams (dreams in which the dreamers are aware that they are dreaming): its prevalence among athletes, facilitating methods and effectiveness. The contents of this dissertation are structured in the following way. The first chapter introduces the concept of mental practice in sports, reviews the evidence for its effectiveness and presents main theories explaining its effects. Further, the empirical evidence showing the correspondence between imagined and executed actions is discussed, which supports the theoretical view of a functional equivalence between covert and overt motor actions. The second chapter presents the basics of human sleep and the relation of sleep to memory consolidation, especially in terms of procedural (motor) memory. It also introduces the basics of dreams and dream research. The third chapter presents the phenomenon of lucid dreaming, its incidence and frequency rates, underlying physiology and psychology. The fourth chapter, the core of the present investigation, focuses on the application of lucid dreams in sports and, specifically, in motor learning. Anecdotal accounts and previous research is discussed and the present empirical work is introduced. The first study (Paper 1) surveyed the frequency of lucid dreaming and lucid dream practice in athletes. In the second study (Paper 2), a systematic review was conducted to examine the empirical evidence for all different methods for lucid dream induction that have been suggested in the literature. Then a sleep laboratory study followed to test one of the prospective methods suggested in the literature but not yet examined – an induction of lucid dreams via transcranial brain stimulation (Paper 3). Lastly, an online study was carried out in which the effectiveness of motor practice was compared to actual physical practice and mental practice in wakefulness (Paper 4). Finally, the last chapter provides an overall discussion of the findings and directions for future research.
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Inauguraldissertation
zur Erlangung des akademischen Doktorgrades (Dr. phil.)
im Fach Sportwissenschaft
an der Fakultät für Verhaltens- und Empirische Kulturwissenschaften
der Ruprecht-Karls-Universität Heidelberg
Titel der publikationsbasierten Dissertation
Motor Learning in Lucid Dreams: Prevalence, Induction, and Effectiveness
vorgelegt von
Tadas Stumbrys
Jahr der Einreichung
2014
Dekan: Prof. Dr. Klaus Fiedler
Berater: Prof. Dr. Klaus Roth
PD Dr. Daniel Erlacher
Contents
Acknowledgements 3
List of scientific publications of the publication-based dissertation 4
Introduction 5
1. Mental practice in sports 7
1.1. Effectiveness of mental practice 7
1.2. Theories of mental practice 9
1.3. Neural basis of motor imagery 11
2. Sleep, memory consolidation, and dreams 13
2.1. Basics of sleep 13
2.2. Procedural memory consolidation in sleep 14
2.3. Dreams 16
3. Lucid dreams 18
3.1. Incidence and frequency 18
3.2. Physiology 19
3.3. Psychology 22
4. Motor learning in lucid dreams 23
4.1. Previous research 23
4.2. Study 1: Prevalence of lucid dreams and lucid dream practice in athletes 24
4.3. Studies 2 & 3: Inducing lucid dreams 25
4.4. Study 4: Effectiveness of lucid dream practice 27
Summary and conclusions 28
References 30
Declaration 41
Appendix: Publications 42
Acknowledgements
Firstly, I would like to thank Prof. Dr. Klaus Roth who made it possible for me to carry out
the present research and his kind continuing support. Further, I am deeply indebted to PD
Dr. Daniel Erlacher for all his guidance, mentorship, encouragement, and great help over
the last four years. I also wish to express my deep gratitude to Prof. Dr. Michael Schredl
for his always insightful opinions, enlightening conversations and continuing help.
Finally, I am also very grateful to all my participants, lucid dreamers, (lucid) dream
enthusiasts and researchers, my colleagues and friends, who inspired, encouraged and
supported me on this stimulating journey. My special thanks to my colleague Melanie
Schädlich and Laurens Van Keer for their input in different stages of the project.
List of scientific publications of
the publication-based dissertation
Paper 1
Erlacher, D., Stumbrys, T., & Schredl, M. (2011-2012). Frequency of lucid dreams and
lucid dream practice in German athletes. Imagination, Cognition and Personality, 31(3),
237–246.
Paper 2
Stumbrys, T., Erlacher, D., Schädlich, M., & Schredl, M. (2012). Induction of lucid dreams:
A systematic review of evidence. Consciousness and Cognition, 21(3), 1456–1475.
Paper 3
Stumbrys, T., Erlacher, D., & Schredl, M. (2013). Testing the involvement of the prefrontal
cortex in lucid dreaming: A tDCS study. Consciousness and Cognition, 22(4), 1214–1222.
Paper 4
Stumbrys, T., Erlacher, D., & Schredl, M. (submitted). Effectiveness of motor practice in
lucid dreams: A comparison with physical and mental practice. Journal of Sports Sciences.
Motor learning in lucid dreams | 5
Introduction
Two hours each night we spend actively dreaming. Our body lays motionless, yet our eyes
start to move rapidly, our breath rhythm intensifies, and the heart starts to beat more
irregularly. Our brain becomes highly active and we enter a reality akin to the usual waking
one. We move with our dream body, interact with other characters in the dream, trying to
achieve something, solve some problem or a situation. Usually we are getting emotional,
frequently frustrated. We act and react as if awake, although the world we are in is not the
real one. It looks very much the same, but exists only in the inside not the outside of
ourselves. Yet sometimes a strange thought can strike our dreaming mind – something is
not right here... A sudden flash of awareness penetrates the illusion – I must be dreaming!
This is the point where everything changes. Endless opportunities arise. A perfectly real
simulation of the waking reality is at our disposal, where the only constraints are the ones
that we set for ourselves. We can break the physical laws - fly, rush into the outer space,
jump from huge cliffs, dive deep into the ocean, create any scenarios or environments we
only can think of. All the sensations are just as real, but we are completely safe we
cannot injure our physical sleeping body – so we can experiment here as much as we like.
This is a perfect environment not only for having fun, but also for learning. We can acquire
new skills, polish existing ones and try things that are rather dangerous in our ordinary
waking reality.
The purpose of the present investigation was to explore the potentials for motor
learning in this special state of consciousness so called lucid dreams (dreams in which
the dreamers are aware that they are dreaming): its prevalence among athletes, facilitating
methods and effectiveness. The contents of this dissertation are structured in the following
way. The first chapter introduces the concept of mental practice in sports, reviews the
evidence for its effectiveness and presents main theories explaining its effects. Further,
the empirical evidence showing the correspondence between imagined and executed
actions is discussed, which supports the theoretical view of a functional equivalence
between covert and overt motor actions. The second chapter presents the basics of
human sleep and the relation of sleep to memory consolidation, especially in terms of
procedural (motor) memory. It also introduces the basics of dreams and dream research.
The third chapter presents the phenomenon of lucid dreaming, its incidence and frequency
rates, underlying physiology and psychology. The fourth chapter, the core of the present
investigation, focuses on the application of lucid dreams in sports and, specifically, in
motor learning. Anecdotal accounts and previous research is discussed and the present
Motor learning in lucid dreams | 6
empirical work is introduced. The first study (Paper 1) surveyed the frequency of lucid
dreaming and lucid dream practice in athletes. In the second study (Paper 2), a systematic
review was conducted to examine the empirical evidence for all different methods for lucid
dream induction that have been suggested in the literature. Then a sleep laboratory study
followed to test one of the prospective methods suggested in the literature but not yet
examined – an induction of lucid dreams via transcranial brain stimulation (Paper 3).
Lastly, an online study was carried out in which the effectiveness of motor practice was
compared to actual physical practice and mental practice in wakefulness (Paper 4).
Finally, the last chapter provides an overall discussion of the findings and directions for
future research.
Motor learning in lucid dreams | 7
1. Mental practice in sports
Mental practice is the cognitive rehearsal of a physical activity in the absence of overt
physical movements (Richardson, 1967a). In contrast to other cognitive training methods
in sports, it involves an imaginative representation of body movements. An athlete can use
mental practice in a variety of contexts: preparing for a competition, during a competition
(e.g. before making a kick, a serve, or a shot), or when there is no possibility to perform
actual practice (e.g. when travelling or recovering from an injury). It is a well-established
technique in sports science and practice (Morris, Spittle, & Watt, 2005) and widespread
among elite athletes, with the prevalence numbers ranging from about 70% (Ungerleider &
Golding, 1989) up to 99% (Orlick & Partington, 1988). Mental practice can be used for the
acquisition of motor skills or as a means of action preparation (Magill, 2003). It can be
carried out by using an internal (first-person) or external (third-person) perspective. The
findings on which of the perspectives is more beneficial are somewhat ambiguous. Some
studies show greater benefits of internal perspective (e.g. Epstein, 1980; Mahoney &
Avener, 1977), others – of external perspective (e.g. Hardy & Callow, 1999; White &
Hardy, 1995), whereas some other studies did not find any differences between the two
perspectives (e.g. Gordon, Weinberg, & Jackson, 1994; Mumford & Hall, 1985). Recently
also a distinction was made between internal visual, external visual and kinesthetic
imagery (Roberts, Callow, Hardy, Markland, & Bringer, 2008). The latter was considered
more of a feature of internal imagery in some earlier studies (e.g. Mahoney & Avener,
1977).
1.1. Effectiveness of mental practice
Since 1930s, when Sackett (1934, 1935) showed that “symbolic rehearsal” of a task
improves subsequent performance, a numerous studies on the effects of mental rehearsal
with different motor tasks have been conducted. Mental practice has been shown to
improve performance in a variety of sports, including darts (Mendoza & Wichman, 1978),
basketball (Hall & Erffmeyer, 1983), volleyball (Shick, 1970), tennis (Surburg, 1968), field
hockey (Smith, Holmes, Whitemore, Collins, & Devonport, 2001) and many others. Mental
practice can have an effect on a number of different aspects of motor performance, for
example: increase muscular strength (Ranganathan, Siemionow, Liu, Sahgal, & Yue,
2004; Yue & Cole, 1992), endurance (Kelsey, 1961), flexibility (Guillot, Tolleron, & Collet,
2010), improve balance (Fansler, Poff, & Shepard, 1985), increase movement speed and
Motor learning in lucid dreams | 8
accuracy (Smith & Harrison, 1962), consistency of movement tempo and relative timing
(Vogt, 1995).
One of the first literature reviews to assess the effects of mental practice was done
by Richardson (1967a). Eleven studies with significantly positive findings regarding
improvements following mental practice were found, seven studies with positive trends,
three with negative findings and one equivocal; thus, indicating that mental practice is
indeed associated with improved performance.
In 1983, Feltz and Landers carried out the first extensive meta-analysis to more
robustly examine the effectiveness of mental practice on motor skills learning and
performance. Their review included 60 studies from which 146 effect sizes were obtained
(some studies measured the effects of more than one task or condition). The overall effect
size was found to be M = .48 ± .67, suggesting that mentally practicing a motor task
indeed improves subsequent performance. Feltz and Landers (1983) also found that tasks
with cognitive elements had larger effect sizes (M = 1.44) as compared to motor tasks (M
= .43) or strength tasks (M = .20), and published studies had larger effect sizes (M = .74)
than unpublished studies (M = .32). No gender differences were found as well as any
significant differences between novices and experienced subjects. The relationship
between practice duration and effect size was found to be neither linear nor curvilinear but
rather third degree polynomial: either very short practice sessions (under 1 min or less
than 6 trials) or much longer (15-25 min or 36-46 trials) seemed to be the most effective.
The relationship appeared to be also task-specific: Improvements in cognitive tasks were
associated with very short practice durations, whereas motor and strength tasks required
longer practice durations.
A decade later, Driskell, Copper, and Moran (1994) conducted another meta-
analysis which involved more strict operational definition of mental practice (excluding
composite studies of mental and physical practice, modeling, relaxation, etc.) and
mandatory comparison with a control group. A total of 35 studies with 100 hypothesis tests
(3214 subjects) were included. Their combined results indicated that mental practice (62
hypothesis tests) result in significant improvements that are small to moderate in
magnitude (r = .255, d = .527) but are lower than improvements from physical practice
(moderate to strong in magnitude: r = .364, d = .782; 38 hypothesis tests). Further, they
found that mental practice was more effective for tasks that involved cognitive elements
and that the positive effect of the practice declines with the time (after two weeks the
effects are reduced to a half of their original magnitude). The experience with the task was
also found to play some role: While there were no differences between experienced and
Motor learning in lucid dreams | 9
novice participants in overall combined effects, novice subjects seemed to have stronger
effects of mental practice for cognitive rather than physical tasks, while the experienced
subjects equally benefited from mental practice regardless of the task type. The number of
practice trials appeared not to be related to the effectiveness; however, there was a
negative relationship between the duration of mental practice and the magnitude of effect,
indicating that longer practice periods (over 20 min) can lead to weaker effects.
Altogether the evidence from meta-analyses suggests that mental practice has a
positive and significant effect on performance. The findings from sports have recently been
extended to other disciplines, such as education, medicine, music and psychology
(Schuster et al., 2011). To explain how mental practice works several theories have been
suggested.
1.2. Theories of mental practice
One of the earliest explanations of how mental practice works was proposed by Sackett
(1934, 1935). According to his symbolic rehearsal theory, a symbolic representation of the
action is gained which can be subsequently rehearsed and these patterns coded in
memory. Therefore this theory suggests that only those actions that involve cognitive
elements can benefit from mental practice and symbols representing the movements must
be acquired prior mental rehearsal. While meta-analyses showed that mental practice is
indeed more effective for tasks that involve cognitive elements (cf. Driskell et al., 1994;
Feltz & Landers, 1983), this theory does not explain how performance can be improved in
such tasks as muscular strength and endurance (cf. Kelsey, 1961; Ranganathan et al.,
2004; Yue & Cole, 1992).
A somewhat different – psychoneuromuscular – explanation was put forward by
Richardson (1967b). The explanation is based on early psychophysiological studies (e.g.
Jacobson, 1930, 1932) which found that during mental practice very small innervations of
the muscles that are involved in the actual movement occur. Richardson proposed that
due to this small kinesthetic feedback together with imagined visual feedback, corrections
can be made and neuromuscular coordination can be facilitated. Yet the overall findings
regarding increased EMG activation in respective muscle groups during mental practice
are rather ambiguous: some studies did find increases in EMG activity, other studies did
not (overview: Guillot, Lebon, & Collet, 2010). Further, studies failed to find an association
between increases in EMG activity and improvements in performance during mental
practice (e.g. Smith, Collins, & Holmes, 2003; Yue & Cole, 1992). Also this theory does not
Motor learning in lucid dreams | 10
explain why the highest gains for mental practice are with the tasks that involve cognitive
elements (cf. Driskell et al., 1994; Feltz & Landers, 1983).
Hecker and Kaczor (1988) suggested applying a cognitive bioinformational theory,
proposed by Lang (1979), to the domain of mental practice in sports. According to this
bioinformational theory (originally developed for emotional imagery), images can be
understood as propositional structures stored in the brain and are organized into two main
categories: stimulus and (behavioral) response (which includes both physiological and
emotional reactions). Lang proposed that learning and behavioral change occurs from
linking stimulus and response propositions and mental imagery can strengthen these links.
Support for this theory comes from studies which showed that, for example, internal
imagery produces more EMG activity than external imagery (Hale, 1982), both EMG
activity and improvements in performance are greater when response rather than stimulus
propositions are emphasized in the script (Bakker, Boschker, & Chung, 1996; Smith et al.,
2001), increases in heart rate are higher when imagining a familiar situation than
unfamiliar (Hecker & Kaczor, 1988), experienced athletes gain more from mental practice
than novices (Feltz & Landers, 1983). This evidence gives credibility for the application of
bioinformational theory in sports, yet more empirical support, especially in the applied
sport setting, is needed (cf. Morris et al., 2005).
Further, some theories have been suggested that emphasized the effects of mental
practice on a psychological state. Schmidt (1982), for example, proposed that imagery
could provide a preparatory set to achieve an optimal arousal level for good performance.
This “attention-arousal setview is in part supported by findings of respective muscular
innervations during mental practice (e.g. Jacobson, 1930, 1932), yet has not been
empirically examined and hence its critical evaluation is not possible (Hecker & Kaczor,
1988). Mental practice has been also suggested to increase self-efficacy and confidence
which can lead to improved performance, however the empirical evidence failed to show
that self-efficacy/efficacy mediates the relationship and thus might rather be an
independent outcome of mental practice (Morris et al., 2005).
A theoretical view which seems to be most strongly grounded in empirical evidence
is a neurophysiological explanation of functional equivalence. This view was put forward
by Finke (1980), who argued that visual imagery is functionally equivalent to visual
perception, i.e. mental imagery activates the same information-processing mechanisms of
visual perception at many different levels. Jeannerod (1994) proposed that this functional
equivalence can be generalized to mental representations in other modalities, and,
specifically, to motor imagery. Thus mentally imagined movements would share the same
Motor learning in lucid dreams | 11
neural mechanisms with actual physical movements and would have similar functional
outcomes, which would explain the effectiveness of mental practice: On a
neurophysiological level mental practice is equivalent to actual physical practice, just the
movement execution is inhibited, and learning can occur due to the motor programming
process (cf. Schmidt, 1975). The empirical evidence for functional equivalence is very
sound and is reviewed in the next section.
1.3. Neural basis of motor imagery
Decety (1996) proposed three lines of evidence to support the notion that imagined and
executed actions share the same neural structures: measuring central nervous activity
(e.g. cerebral blood flow), monitoring autonomic responses and using mental chronometry.
The converging evidence would show that the same brain areas are involved in planning
actual movements, peripheral effectors are innervated according to the level of effort, and
temporal dynamics is preserved.
In a pioneering study, Roland, Larsen, Lassen, and Skinhøj (1980) found that
mental simulation of the movement resulted in increased regional cerebral blood flow
(rCBF) most strongly in the supplementary motor area (SMA), whereas actual movement
increased rCBF not only in SMA but also in the primary motor area (M1), thus implying the
involvement of SMA in motor action programming. Subsequent studies (e.g. Decety et al.,
1994; Lotze et al., 1999; Roth et al., 1996) confirmed the involvement of SMA and the
premotor cortex in motor imagery, which have now been considered as the predominant
areas of motor imagery (overviews: Jeannerod, 2001; Lotze & Halsband, 2006). The
involvement of M1 in motor imagery is more controversial (Munzert, Lorey, & Zentgraf,
2009). While some PET studies did not find increased M1 activity (e.g. Decety et al., 1994;
Roland et al., 1980) during motor imagery, many fMRI studies did find (e.g. Lotze et al.,
1999; Roth et al., 1996; overview: Munzert et al., 2009), although typically to a lesser
extent (e.g. 30% as compared to actual execution, Roth et al., 1996). Considering all
evidence together, the current consensus is that M1 is involved in motor imagery (Lotze &
Halsband, 2006; Munzert et al., 2009). Thus imagined actions seem to involve the same
brain regions as executed actions, although they do not completely overlap (see Lotze &
Halsband, 2006).
According to Guillot and Collet (2005a), three different physiological categories with
six variables can be measured to monitor autonomic nervous activity (ANS): electrodermal
(skin conductance and skin potentials), thermo-vascular (skin blood flow and skin
Motor learning in lucid dreams | 12
temperature) and cardio-respiratory (heart rate and respiration). Decety, Jeannerod,
Germain, and Pastene (1991) found that mental simulation of movement at increasing
speed resulted in proportional increase of heart rate and pulmonary ventilation (cardio-
respiratory parameters of mental running at 12 km/h were comparable to actual walking at
5 km/h). These findings were replicated in subsequent studies, which also find increases in
respiratory rate and that the effects are independent from the experience with the task, i.e.
whether a participant is a novice or a professional athlete (Calabrese, Messonnier, Bijaoui,
Eberhard, & Benchetrit, 2004; Fusi et al., 2005). Further studies showed corresponding
effects on other ANS parameters – skin conductance/resistance, skin potential, skin
temperature and blood flow, systolic and diastolic blood pressure (Beyer, Weiss, Hansen,
Wolf, & Seidel, 1990; Deschaumes-Molinaro, Dittmar, & Vernet-Maury, 1992; Oishi, Kasai,
& Maeshima, 2000; Wang & Morgan, 1992). Moreover, ANS responses during mental
practice seem to be associated with improvements in performance (Roure et al., 1999).
Finally, it is important to consider the temporal dynamics of motor imagery (reviews:
Guillot & Collet, 2005b; Guillot, Hoyek, Louis, & Collet, 2012). An early study by Decety,
Jeannerod, and Prablanc (1989) found that walking time to the target in actual and mental
performance was nearly equivalent, yet when the participants were asked to carry a 25-kg
weight on their shoulders, actual walking time remained the same but mental walking time
increased by 30%. Further, Decety and Jeannerod (1995) discovered that the time needed
to mentally walk to a target (a gate) is affected both by its width and distance (speed-
accuracy trade-off) and that Fitt’s law (cf. Fitts, 1954) is preserved. Whereas many studies
confirmed similar durations for actual and imagined movement times, underestimations
and overestimations were also found in several studies (overview: Guillot & Collet, 2005b).
Many different factors seem to influence timing of motor actions, including movement
duration, movement complexity and perceived difficulty, expertise level, age, imagery type
and perspective, instructions, and others (review: Guillot et al., 2012).
Altogether, the converging lines of evidence support the notion that imagined and
executed actions to some extent share the same neural structures. Taking a step further,
Jeannerod (2001) put forward a theory of neural simulation of action which postulates that,
in general, covert actions are actual actions, except for the fact that they are not executed.
Therefore this theory predicts a neural similarity between the state in which an action is
simulated (so called “S-state”) and the state of execution of this action. S-states include
intended actions, imagined actions and actions in dreams (see section 3.2).
Motor learning in lucid dreams | 13
2. Sleep, memory consolidation, and dreams
About a third of their time human beings spend in sleep. While the functions of sleep
largely remain unknown, there is substantive evidence showing that sleep plays a crucial
role in memory formation (Stickgold, 2005). There are different types of memories, which
are most often divided into two classes: declarative and non-declarative (Squire, 2004).
Declarative memories are explicit memories that can be consciously recollected, such as
memories of facts (semantic memories) or events (episodic memories). Non-declarative
memories are implicit and usually used without conscious recollection, such as procedural
and motor skills (e.g. riding the bicycle). While sleep is important for formation of both
types of memories, the evidence is much stronger for its involvement in formation of
procedural skills (Stickgold, 2005). Before looking into the role of sleep in motor memory
consolidation, the basics of sleep will be briefly discussed.
2.1. Basics of sleep
In behavioral terms, sleep can be defined as a reversible behavioral state of perceptual
disengagement from and unresponsiveness to the environment (Carskadon & Dement,
2000). Since the pioneering discovery of rapid-eye movement (REM) sleep (Aserinsky &
Kleitman, 1953), sleep has been divided into two states: REM sleep and NREM (non-rapid
eye movement) sleep. Both states are present in virtually all mammals and birds and are
physiologically distinct from one another and from wakefulness. NREM sleep can be
further divided into different substages: Stage 1, Stage 2, Stage 3 and Stage 4 NREM
sleep which can be relatively unambiguously defined according to the
electroencephalographic (EEG) patterns (Rechtschaffen & Kales, 1968). Recently Stages
3 and 4 of NREM sleep due to minute physiological differences between them were
combined into a single state NREM 3 or N3 (Iber, Ancoli-Israel, Chesson, & Quan, 2007).
Standard sleep recording (polysomnography) includes EEG (electrode placement: F
4
-M
1
,
C
4
-M
1
, O
2
-M
1
, F
3
-M
2
, C
3
-M
2
, O
1
-M
2
, according to the international ten-twenty system,
Jasper, 1958), electrooculogram (EOG) and chin electromyogram (EMG).
Stage NREM 1 (N1) is marked by conjugate sinusoidal slow eye movements, low
amplitude predominantly theta (4-7 Hz) brain activity, and vertex sharp waves (Iber et al.,
2007). NREM 1 typically occurs at sleep onset (the first sleep epoch after wakefulness)
and usually accounts for 2-5% of total sleep time. Muscular twitches and hypnic jerks, as
well as hypnogogic hallucinations can be experienced during N1. When awakened from
this sleep, people often report that they were still awake.
Motor learning in lucid dreams | 14
NREM 2 (N2) is characterized by K complexes (negative sharp waves with duration
of 0.5 seconds, usually maximal in amplitude on frontal derivations) and sleep spindles (a
train of distinct waves of 11-16 Hz frequency with a duration of 0.5 seconds, usually
maximal in amplitude on central derivations) (Iber et al., 2007). It is the most prevalent
sleep stage during the night, constituting of 45-55% of total sleep time. The arousal
thresholds in N2 sleep are similar as in REM sleep (Rechtschaffen, Hauri, & Zeitlin, 1966).
NREM 3 (N3), also called slow-wave sleep (SWS) or deep sleep, is distinguished
by the presence of 20% or more of high voltage (75µV) 0.5-2 Hz waves (Iber et al.,
2007). N3 takes about 15-20% of total sleep time and is more prevalent in the first part of
the night. It is the stage of sleep associated with the highest arousal thresholds.
Parasomnias, such as sleep walking or sleep terrors, most often occur during N3 sleep
(American Academy of Sleep Medicine, 2001).
REM sleep is marked by irregular rapid eye movements, low amplitude mixed
frequency EEG and low chin EMG tone (with short irregular bursts of EMG activity) (Iber et
al., 2007). REM sleep usually accounts for 20-25% of total sleep time, is predominant
towards the end of the night, and associated with the most vivid dream experiences (see
section 2.3).
Wakefulness in polysomnographic recordings is also characterized by irregular
rapid eye movements (as well as by reading eye movements – a slow phase followed by a
rapid phase in the opposite direction) but associated with normal or high chin EMG tone
and EEG alpha (8-13 Hz) rhythm. It usually constitutes less than 5% of total sleep time.
Sleep occurs in NREM-REM sleep cycles of about 90-110 min duration throughout
the night (N1-N2-N3-N2-REM). Deep sleep (N3) predominates during the first third of the
night, whereas REM sleep is most prevalent during the last third. This is also associated
with circadian rhythms REM sleep, for example, is closely linked with body temperature
(Czeisler, Zimmerman, Ronda, Moore-Ede, & Weitzman, 1980). Brain activity differs
across NREM-REM sleep cycle: NREM sleep is marked by a decreased overall brain
activity, while during REM sleep the brain becomes highly active (Braun et al., 1997;
Maquet et al., 1996, 1997).
2.2. Procedural memory consolidation in sleep
Different studies demonstrated that sleep is crucial for motor learning. When learning a
new motor task, post-test improvements are seen after a night’s sleep, but not after an
equivalent period of waking time (Fischer, Hallschmid, Elsner, & Born, 2002; Huber,
Motor learning in lucid dreams | 15
Ghilardi, Massimini, & Tononi, 2004; Walker, Brakefield, Morgan, Hobson, & Stickgold,
2002).
An early study by Karni, Tanne, Rubenstein, Askenasy, and Sagi (1994) found that
performance of a visual discrimination task improved after a night sleep, yet the
improvements were lost when REM sleep of the night was disrupted, whereas the
disruption of slow-wave sleep (N3) did not affect improvement. Subsequent studies
confirmed the involvement of REM sleep in memory consolidation for visual discrimination
skills, but showed that SWS is likely also to be involved (Gais, Plihal, Wagner, & Born,
2000; Stickgold, Whidbee, Schirmer, Patel, & Hobson, 2000).
In motor skills domain, a study by Buchegger, Fritsch, Meier-Koll, and Riehle (1991)
showed that participants who acquired a new motor skill (trampolining) had a significant
increase in subsequent REM sleep. Plihal and Born (1997) found that improvements in
mirror-tracing skills were more associated with the late sleep (where REM sleep is
predominant), while improvements in declarative memory were associated with the early
sleep (where SWS is predominant). Similarly, Tucker at al. (2006) demonstrated that a
day-time nap without REM sleep enhanced declarative but not procedural (mirror-tracing)
memory. On the other hand, Erlacher and Schredl (2006) did not find any effects of
learning a new motor task (snakeboard riding) on REM sleep parameters. With a finger-
tapping task, Fischer et al. (2002) found that improved performance was associated with a
greater amount of REM sleep, although another study by Walker et al. (2002) found
improvements to be associated with the proportion of N2 sleep across the night. Further,
Smith and MacNeill (1994) showed that the performance on a pursuit rotor task is impaired
due to N2 rather than REM sleep loss. On the other hand, Huber et al. (2004) found
improvements on a rotation-adaptation task to be related to the increases in slow-wave
activity.
Thus, nearly all sleep stages (except of N1) have been shown to be involved in
procedural and motor memory formation (Walker & Stickgold, 2004). Considering the
evidence altogether, SWS seems to facilitate declarative, hippocampus-dependent
memory, whereas REM sleep appears to facilitate hippocampus-independent non-
declarative (procedural, emotional) memory (Diekelmann & Born, 2010). REM sleep, in
particular, seems to be associated with initial phases of motor learning, when the task
appears to be completely new and unfamiliar (Blischke & Erlacher, 2007).
Using position emission tomography (PET), Maquet et al. (2000) showed that those
participants who practiced a visuomotor serial reaction task had the same brain activation
patterns (located in occipital and premotor cortices) reappearing during subsequent REM
Motor learning in lucid dreams | 16
sleep, while no such activity was seen in those participants who did not practice the task.
Furthermore, these increases in regional cerebral blood flow during REM sleep were
directly related with the extent of improvements in performance (Peigneux et al., 2003).
Moreover, in another study Louie and Wilson (2001) implanted microelectrodes into the rat
hippocampus and recorded the activity of multiple neurons during the wake motor task and
subsequent REM sleep. It was found that temporally sequenced firing rate patterns of
wake behavior are reproduced during REM episodes at an equivalent timescale. Finally, a
recent study using a virtual navigation task and human subjects found that those
participants who dreamt about the task (during NREM sleep) showed greater
improvements in subsequent performance than participants without task-related dream
mentation, while task-related thoughts in wakefulness did not predict improved
performance (Wamsley, Tucker, Payne, Benavides, & Stickgold, 2010). Despite the fact
that dreams in this study were collected from NREM sleep (in three cases from the sleep
onset and once after awakening from N2 sleep), the findings could possibly be extended to
other sleep stages, supporting the idea that dream experiences reflect the learning-
induced memory reactivation during sleep and this reactivation is associated with
improvements with performance (Wamsley & Stickgold, 2011).
2.3. Dreams
In general, dreaming can be defined as mental activity occurring during sleep, while a
dream (or a dream report) is the recollection of mental activity which has occurred during
sleep (Schredl, 2008b). Dream reports can be collected from a spontaneous recall in a
natural (e.g. home) environment or following deliberate awakenings in a sleep laboratory
(cf. Schredl, 2008a). In the sleep laboratory setting, dreaming has been strongly
associated with REM sleep since its discovery: Initial experiments showed that upon
awakenings from REM sleep dreams are recalled in 74-80% of cases, while only 7-9% of
awakenings from NREM sleep result in dream recall, leading to a suggestion that a dream
recalled during NREM sleep might only be a persisted memory from a previous REM
period (Aserinsky & Kleitman, 1953; Dement & Kleitman, 1957). This view “dreaming =
REM sleep” prevailed for a while, until Foulkes (1962) showed than when a person is
asked to report any mental content which “was going through the mind”, the recall rate
from NREM sleep is much higher and not that much different comparing to REM sleep
(recall rates in his study: NREM 74% vs. REM 87%). The differences between REM and
NREM dreams, however, do exist: In a meta-analysis of 34 studies, Nielsen (1999) found
Motor learning in lucid dreams | 17
the average recall rate 82±9% for REM sleep and 43±21% for NREM sleep. REM dream
reports are typically longer, more bizarre, more perceptually vivid, more emotionally
charged and with more motor activity, while NREM dream reports contain more thought-
like mentation and representation of current concerns (Hobson, Pace-Schott, & Stickgold,
2000).
To explain the ambiguity between dreaming and REM vs. NREM sleep different
theoretical models have been proposed. Hobson et al. (2000) suggested that wakefulness,
REM sleep and NREM sleep are distinct mental states with different levels of cortical
activation, input source and aminergic-cholinergic neuromodulation. Solms (2000)
considering the evidence from brain lesions proposed that REM sleep and dreaming are
controlled by different brain mechanisms and while there is a substantial correlation
between the two, in fact, they are dissociable states. Nielsen (2000) put forward another
hypothesis, proposing that there might be externally unnoticeable “covert” REM processes
during NREM sleep, which could be responsible for dreamlike mental activity in NREM
sleep.
People differ in their ability to recall dreams: For example, women seem to have
better dream recall than men (Schredl & Reinhard, 2008). Empirical research supports the
so-called continuity hypothesis of dreaming which states that waking experiences are
reflected in dreams, i.e. dreaming is in continuity with waking life (Schredl, 2003). Sport
students, for example, dream more about sports than psychology students do and the time
spent in sports activities is directly related to the percentage of sports dreams (Erlacher &
Schredl, 2004a; Schredl & Erlacher, 2008).
Motor learning in lucid dreams | 18
3. Lucid dreams
A special type of nocturnal dreams are lucid dreams dreams in which the dreamer is
aware that he or she is dreaming and often can deliberately influence the dream content
(LaBerge, 1985a). Although the phenomenon was already known to Aristotle (trans. 2007),
scientific research on lucid dreaming spans only over the last three decades, since its
verification in a sleep laboratory (Hearne, 1978; LaBerge, 1980b; LaBerge, Nagel,
Dement, & Zarcone, 1981). Lucid dreaming is mainly considered to be a REM sleep
phenomenon (LaBerge, 1990) and is more likely to occur during later REM periods than
earlier ones (LaBerge, 1985b). Although lucidity during NREM sleep is also possible
(Stumbrys & Erlacher, 2012): most likely to be observed during N1 sleep, somewhat less
likely during N2 sleep and yet to be observed during N3 sleep. Lucid dreams are most
often initiated from the dream state, but sometimes can also be initiated from the waking
state when retaining conscious awareness while falling asleep (LaBerge, Levitan, &
Dement, 1986).
3.1. Incidence and frequency
While lucid dreams are still relatively little known, they are not that infrequent among
general population, although the estimates vary. In a representative survey of Austrian
population (N = 1000) by Stepansky et al. (1998), 26% of respondents reported that they
had lucid dreams (64% reported no lucid dreams, 10% did not answer). A recent survey of
a German representative sample (N = 919) by Schredl and Erlacher (2011) found much
higher incidence rates: 51% of respondents reported that they had at least one lucid
dream in their life, 20% experienced lucid dreams once a month or more frequently, and
5% had one or more lucid dreams per week. Mean lucid dream frequency was found to be
0.65 (SD = 2.14) lucid dreams per month, which corresponded to a rough estimate of 7.5%
as compared to overall dream recall frequency (mornings with dream recall per week: M =
2.00, SD = 2.14). Similar incidence rates were found by Snyder & Gackenbach (1988),
who undertook a review of different surveys that were published up to that time and
provided a “conservative estimate” that about 58% of the population had experienced a
lucid dreams at least once in their lifetime and 21% report lucid dreams once a month or
more often (hence they are referred as frequent lucid dreamers).
Some specific samples appear to have lucid dreams more often, for example,
university students. In a German university student sample (containing mostly psychology
students; N = 439) surveyed by Schredl and Erlacher (2004), 82% of participants reported
Motor learning in lucid dreams | 19
at least one lucid dream and 37% were frequent lucid dreamers. Blackmore (1982a,
1982b) in three different samples of university students in England and the Netherlands (N
= 114, 157, & 189) found the prevalence of lucid dreaming to be 73%-79%, while Yu
(2008) in a Chinese student sample (N = 348) found the prevalence rate of 92%.
Interestingly, Erlacher, Schredl, Watanabe, Yamana, and Gantzert (2008) found much
lower lucid dream prevalence rate in a Japanese student sample (N = 153) as compared
to other countries: Only 47% of Japanese students reported at least one lucid dream
experience and only 17% were frequent lucid dreamers. This suggests that cross-cultural
differences regarding lucid dream frequency may also exist.
Most of these studies used self-questionnaires and rating scales to assess lucid
dream frequency. A recent study by Stumbrys, Erlacher, and Schredl (2013a) showed that
lucid dream frequency can be indeed reliably measured with a frequency scale: Re-test
reliability of an 8-point scale over a 4-week interval in a sample of 93 sport students was
found to be r = .89 (p < .001). Thus lucid dream frequency seems to be relatively stable
over the time (at least in a short while). Another approach for assessing lucid dream
frequency is to count lucid dreams in the dream diaries. Within university student samples,
the frequency of lucid dreams as compared to all recalled dreams seems to be very low,
only about 0.3-0.7% (Barrett, 1991; Zadra, Donderi, & Pihl, 1992). Yet it might be as high
as 13% if the dreams are collected once weekly (Gackenbach & Curren, 1983). In a
sample of 1666 dream reports collected from dream seminar attendees in six different
countries (Argentina, Brazil, Japan, Russia, Ukraine, and USA), Krippner and Faith (2001)
found 1.7% lucid dream incidence rate, ranging from 0% (males and females in Japan,
females in Ukraine) to 3.3% (males in Russia).
3.2. Physiology
During REM sleep, in which lucid dreams most often occur (cf. LaBerge, 1990), skeletal
muscles of the sleeping body are actively suppressed by neural structures in the brain
stem (so called muscular atonia), keeping dreamers from actually acting out their
movements in their dreams (Hobson et al., 2000). One evident exception is eye
movements, which in part correspond with shifts of gaze in dream imagery (scanning
hypothesis, cf. Roffwarg, Dement, Muzio, & Fisher, 1962). By using a prearranged pattern
of specific eye movements (typically a sequence of left-right eye movements), the
dreamers can give a volitional signal once they become lucid in a dream or accomplish a
particular action in the lucid dream (LaBerge et al., 1981). Interestingly, a fixation of a gaze
Motor learning in lucid dreams | 20
on a stationary point in the dream environment leads to a termination of the dream and
awakening (Tholey, 1983a).
Compared to non-lucid REM dreaming, lucid REM dreaming is associated with
elevated physiological activation – higher REM density, increases in respiration, heart rate
and skin potential (LaBerge et al., 1986). H-reflex suppression, however, is greater in lucid
dreams than non-lucid dreams, suggesting that the lucid dreaming state might not be
closer to awakening than ordinary REM sleep (Brylowski, Levitan, & LaBerge, 1989).
In terms of the brain activity, early studies found higher EEG alpha activity during
REM sleep to be associated with prelucid (i.e. when the dreamer starts to develop a critical
attitude by questioning the reality of the dream), as well as lucid dreaming (Ogilvie, Hunt,
Tyson, Lucescu, & Jeakins, 1982; Tyson, Ogilvie, & Hunt, 1984). Further, a 4-channel
EEG study found an increased beta-1 activity (13-19 Hz) over both parietal regions during
REM lucid dreaming (Holzinger, LaBerge, & Levitan, 2006). Recently, a 19-channel EEG
study was conducted, which found an increased brain activity in all frequencies, when
comparing lucid versus non-lucid REM sleep, especially in the frontal and frontolateral
regions, peaking at around 40 Hz (Voss, Holzmann, Tuin, & Hobson, 2009). Another
recent study measured brain activity in fMRI scanner during lucid dreaming and found that
several areas that are normally deactivated during REM sleep where reactivated, including
the bilateral precuneus, cuneus, parietal lobules, and prefrontal and occipito-temporal
cortices (Dresler et al., 2012).
When a person performs an action in a lucid dream, corresponding changes can be
observed in the physiological activity of the sleeping body. For example, voluntary control
of respiratory rate in lucid dreams is reflected in matching changes in actual respiration
(LaBerge & Dement, 1982). Dreamed sexual activity and orgasm in lucid dreams were
found to be associated with the similar physiological pattern as waking orgasmic
experience – increased vaginal EMG, vaginal pulse amplitude, levels of skin conductance
and respiratory rate (LaBerge, Greenleaf, & Kedzierski, 1983). Dreamed physical activity
(doing squats in a lucid dream) resulted in increased heart rate and (partially) respiration
(Erlacher & Schredl, 2008a). Despite of general muscular atonia during REM sleep,
corresponding EMG activity can also be measured in some muscle groups. For example,
hand clenching in a lucid dream results in corresponding muscular twitches on the wrist
(LaBerge et al., 1981). Fenwick et al. (1984) measured EMG activity in different muscle
groups while movements were carried out in a lucid dream and found greater
corresponding activity in flexor muscles, somewhat lower in extensor limb muscles, and it
was never present in axial muscles, which suggests a clear hierarchy of the motor
Motor learning in lucid dreams | 21
inhibition in the upper and lower extremities during REM sleep. Also dream speech was
found to be related to respiration patterns (Fenwick et al., 1984). Motor actions in lucid
dreams seem also to activate the same brain patterns as in the case of physically
accomplished actions in wakefulness. Erlacher, Schredl, and LaBerge (2003) in an EEG
study found a decrease of EEG alpha power over the motor areas during hand clenching
in a lucid dream, suggesting the involvement of the cortical motor regions in dreamed
actions. These findings were confirmed by a recent fMRI/NIRS study which found that
dreamed hand clenching activated similar regions in the sensomotory cortex as actual
hand clenching, but the activation was weaker – about 50% as compared to actual
execution, yet somewhat stronger as compared to wakeful imagination (Dresler et al.,
2011).
By using eye signals from a dreamer, it is possible to measure the exact time
intervals required for different actions in lucid dreams. In a pilot study LaBerge (1985a)
found that counting from one to ten in a lucid dream takes about the same time as in
wakefulness. Erlacher and Schredl (2004b) asked lucid dreamers to count to five, do a
sequence of squats, then count to five again, and also did not find significant differences
between counting intervals in lucid dreams and wakefulness, yet doing squats took about
40% more time in a lucid dream compared to wakefulness. In a subsequent study,
Erlacher, Schädlich, Stumbrys, and Schredl (2014) examined if the task modality, length,
or complexity, might be an influencing factor for the prolonged durations in lucid dreams.
Three different conditions were performed both in lucid dreams and wakefulness: counting
to 10, 20, and 30; walking 10, 20, and 30 steps; and a gymnastic routine. It was found that
performing a motor task in a lucid dream indeed takes more time than in wakefulness. The
differences in time, however, were observed only for the absolute durations (i.e. the total
time required to perform the task) but not for the relative durations (i.e. there was no a
disproportional time effect when accomplishing longer tasks). More complex actions did
not lead to more prolonged durations.
Considering the evidence for correspondences between (lucid) dreamed actions and
executed actions in the central nervous activity, autonomic responses and time aspects,
Erlacher and Schredl (2008b) proposed that actions in dreams, similarly as imagined
actions in wakefulness (cf. Decety, 1996), also appear to share the same neural structures
with executed actions, which supports the theory of neural simulation of action by
Jeannerod (2001).
Motor learning in lucid dreams | 22
3.3. Psychology
A number of studies explored personality variables and individual differences that might be
associated with the ability to lucid dream. Frequent lucid dreamers appear to be more field
independent in their cognitive style (i.e. are more analytical when approaching a problem,
noticing features separately from the context), more internal on locus of control (i.e.
experience themselves as being in control of their life), have a higher need of cognition,
thinner boundaries (i.e. greater interconnection between various mental states and
processes) and rate themselves as more creative (Blagrove & Hartnell, 2000; Blagrove &
Tucker, 1994; Gackenbach, Heilman, Boyt, & LaBerge, 1985; Galvin, 1990; Hicks,
Bautista, & Hicks, 1999; Patrick & Durndell, 2004; Schredl & Erlacher, 2004; Zink &
Pietrowsky, 2013). Within the Big Five personality traits, they appear to be more open to
experience, yet seem somewhat less agreeable (Schredl & Erlacher, 2004; Watson, 2001;
Yu, 2012).
When comparing lucid to non-lucid dreams, lucid dreams are marked by higher
levels of insight, control, thought, memory, dissociation, and positive emotions, but do not
differ in their realism and negative emotions (Voss, Schermelleh-Engel, Windt, Frenzel, &
Hobson, 2013). Experienced volition in lucid dreams is comparable to one in wakefulness
and is higher than experienced volition in non-lucid dreams (Dresler et al., 2014). Lucid
dreams, however, are not always completely lucid: Cognition and memory are quite often
impaired and irrational thoughts persist (Barrett, 1992). For example, lucid dreamers are
not always successful in recalling their waking memories in lucid dreams (Erlacher, 2009;
Stumbrys, Erlacher, Johnson, & Schredl, 2014).
Perception in lucid dreams is also appears to be very similar to the waking
perception with both being quite different from the waking imagination. In a study by
LaBerge and Zimbardo (2000), participants were asked to draw a circle with their eyes by
tracking movements of the finger in three different conditions: awake with eyes open
(actual perception), awake with eyes closed (waking imagination) and while lucid
dreaming. The circles drawn in lucid dreams much more resembled the circles drawn
during the actual perception, showing predominantly slow tracking eye-movements,
whereas circles drawn in the waking imagination were rather different and were
distinguished by saccadic eye movements with significantly higher velocities.
Motor learning in lucid dreams | 23
4. Motor learning in lucid dreams
The ability to be aware in the dream state and deliberately perform actions while physically
asleep opens up opportunities to use lucid dreams for sports practice, for example, to
consciously rehearse specific motor tasks without waking up (Tholey, 1990). This lucid
dream practice thus is similar to mental practice in wakefulness: Movements are
rehearsed with a representation of the body on a cognitive level without overt physical
movements (Erlacher, 2007).
As with mental practice in wakefulness and imagined actions (cf. Decety, 1996),
motor actions performed in lucid dreams also appear to share underlying neural
mechanisms with executed actions (Erlacher & Schredl, 2008b), which sets the foundation
for motor learning a set of processes associated with practice or experience leading to
relatively permanent changes in the capability for movement (Schmidt & Lee, 2005).
Functional equivalence during lucid-dreamed movements in central nervous activity (cf.
Dresler et al., 2011), relative timings (cf. Erlacher et al., 2014), as well as peripheral
effectors (cf. Erlacher & Schredl, 2008a) enables to strengthen neural networks involved in
motor programming via rehearsal in lucid dreams and improve motor performance.
4.1. Previous research
Several anecdotal accounts have been presented in the literature about professional and
amateur athletes who claimed that their waking performance was improved due to their
practice in lucid dreams. Tholey (1990), for example, presented a case of a martial artist
who studied for years the “hard” martial art systems (karate, taekwondo, and jujitsu) and
then unsuccessfully tried to learn the "soft" system of aikido (experiencing difficulties
because of his hard-wired “hardmovements). He started to practice aikido in his lucid
dreams and after a week of such practice amazed his instructor with almost a perfect
defence. Other examples included a snow skier who mastered jetting in one week after
taking initial learning in lucid dreams or an internationally successful equestrian who was
perfecting his riding skills in lucid dreams (Tholey, 1990). Some further anecdotal evidence
was presented by LaBerge and Rheingold (1990), including the cases of lucid dreamers
who were able to learn some special running and skating techniques in their lucid dreams
or improve their tennis play. Recently, Erlacher (2007) collected several reports from
amateur athletes, for example, a spring board diver, who practiced complex twists and
somersaults in her lucid dreams by slowing down the whole sequence to focus on
important details of the dive, or a snowboarder, who lucidly practiced several tricks on his
Motor learning in lucid dreams | 24
board which he could not do in waking life, and the practice in lucid dreams helped him to
get better.
The scientific research on the effects of lucid dream practice is rather scarce.
Tholey (1981) conducted a qualitative study where six proficient lucid dreamers were
asked in their lucid dreams to perform and practice movements and complex sport skills,
such as skiing on gymnastics, with which they were already familiar from their waking life.
According to the participants’ reports, they did not encounter any difficulties while
performing complex sport skills in lucid dreams and the movements were accompanied by
a pleasant feeling in the dream. The participants also had an impression that following
their lucid dream practice, their movements improved both in the dream state and waking
life.
Further, Erlacher and Schredl (2010) conducted a pilot study (field experiment) with
a pre-post design in which the participants were asked to practice a simple motor task – to
toss 10-cent coins into a cup, positioned at the distance of two meters, as many times as
possible out of 20 attempts. Twenty participants tried to practice the task in a lucid dream
on a single night and seven of them succeeded. Their performance was compared to a
group which accomplished actual physical practice (n = 10) and a control group without
practice (n = 10). There were significant increases in hitting the target from pre-test to
post-test for both lucid dream practice and physical practice groups, but no improvements
were found for the participants who did not practice the task. Although the improvements
achieved by lucid dreaming practice were somewhat lower than the ones achieved by
actual physical practice, the differences were not statistically significant.
Thus motor learning in lucid dreams seems to be feasible and appears to be
effective. Yet several questions remain unclear. How prevalent is lucid dream practice in
athletes and how many of them do actually have lucid dreams which could make such
practice possible? How lucid dreams can be efficiently induced, making lucid dream
practice more accessible? How effective lucid dream practice is, as compared to actual
physical practice and mental practice in wakefulness? These questions formed the basis
of the present investigation.
4.2. Study 1: Prevalence of lucid dreams and lucid dream practice in athletes
In the first study (Paper 1: Erlacher, Stumbrys, & Schredl, 2011-2012), 840 German
athletes (483 male / 357 female) from a variety of sports (including both team sports and
individual sports) were surveyed about their experiences with lucid dreams. In average,
Motor learning in lucid dreams | 25
the participants were 21.6 ± 6.3 years of age, practicing their sport for 11.1 ± 5.8 years,
with 11.1 ± 6.6 hours of practice per week. About 57% of athletes stated that they
experienced a lucid dream at least once and 24% reported that they have lucid dreams
once a month or more frequently and therefore can be considered as frequent lucid
dreamers (cf. Snyder & Gackenbach, 1988). These findings thus show that lucid dreaming
has similar prevalence rate in athletes as in general population (cf. Schredl & Erlacher,
2011), however the rough estimate of the percentage of lucid dreams as compared to all
recalled dreams in athletes was found to be nearly twice as big as in general population
(14.5% vs. 7.5%). About 9% of athletes who had lucid dreams (5% of the total sample)
used their dreams to practice sports skills and the majority of those who practiced (77%)
had an impression that their performance improved following their practice in lucid dreams.
While most of athletes had some lucid dream experiences, only few have used lucid
dreams for their sport practice. To make lucid dream practice more available, it is
important to have efficient techniques that athletes could use for lucid dream induction.
4.3. Studies 2 & 3: Inducing lucid dreams
Since the onset of lucid dream research, it was demonstrated that the ability to lucid dream
can be facilitated (LaBerge, 1980a). A plethora of different techniques for lucid dream
induction have been suggested in the literature (e.g. Gackenbach, 1985-1986; LaBerge &
Rheingold, 1990; Price & Cohen, 1988; Tholey, 1983b), however a considerable number
of these techniques were based on personal or anecdotal accounts and lacked empirical
evaluation. The second study (Paper 2: Stumbrys, Erlacher, Schädlich, & Schredl, 2012)
aimed to systematically review all published evidence on lucid dream induction and
present an empirically-based classification of different induction methods. A
comprehensive literature search was carried out in a number of electronic bibliographic
databases and (lucid) dreaming specific resources (e.g. dreaming-dedicated scientific
journals, references, personal collections). One hundred and thirty one citations were
identified via database search and 22 via hand search in specific resources. Thirty-seven
manuscripts reporting 35 studies (11 sleep laboratory and 24 field studies) were included
in the final analysis. The methodological quality of the studies was assessed with the
Downs and Black’s (1998) checklist and was found to be rather low. Three classes of
methods were used for lucid dream induction: cognitive techniques (26 studies), external
stimulation (11 studies) and miscellaneous (1 study drug application). Cognitive
techniques aimed to increase the frequency of lucid dreams by training cognitive skills,
Motor learning in lucid dreams | 26
such as prospective memory, self-reflection, or intention, while external stimulation
intended to trigger lucid dreams either by presenting a cue during REM sleep (which could
get incorporated into the dream) or by a specific activation (e.g. vestibular). Drug
application aimed to alter cholinergic levels of the brain. None of the induction techniques
were verified to induce lucid dreams reliably, consistently, and with a high success rate,
although some did look promising. A few methods were found that were not yet tested
empirically. One of such prospective but untested methods was brain stimulation, which
seemed to warrant empirical examination.
The third study (Paper 3: Stumbrys, Erlacher, & Schredl, 2013b) thus aimed to
manipulate the brain activity during REM sleep to increase dream lucidity. The hypothesis
for this experiment was derived from two recent studies that showed increased activation
in the prefrontal brain regions during lucid dreaming (Dresler et al., 2012; Voss et al.,
2009) and from the suggestion by Hobson et al. (2000) that reactivation of the dorsolateral
prefrontal cortex (DLPFC), which is normally deactivated during REM sleep, might be
linked to dream lucidity. Nineteen participants spent three consecutive nights in a sleep
laboratory. The first night served as an adaptation and screening (for sleep disorders and
sensitivity to stimulation) night, while the second night and the third night were
experimental nights: In a randomized and counterbalanced order, on one of those nights
the participants received 1 mA anodal transcranial direct current stimulation (tDCS) over
the DLPFC for 10 min during each REM period (starting from the second) and on the other
night they received sham stimulation. One minute after the stimulation, the participants
were awakened and asked for their dream reports and to rate their dream metacognition
and lucidity. Dream reports were later permutated and scored by an external judge for
lucidity and bizarreness. According to the participants’ self-reports, tDCS delivered over
the DLPFC during REM sleep resulted in increased dream lucidity. The judge scored
dream reports from a tDCS night also as more lucid and somewhat more bizarre as
compared to dream reports from a sham night. The effects, however, were not strong and
pronounced only in frequent lucid dreamers. Further, tDCS quite often disrupted REM
sleep and resulted in awakenings. Thus, while the study provides support for the
involvement of the DLPFC in lucid dreaming, due to small effects, practical applications for
lucid dream induction might be rather limited. Future studies, however, can try to target
different brain regions, such as the precuneus the area which was found to be the most
strongly activated during lucid dreaming in a recent fMRI study (Dresler et al., 2012), or
higher stimulation intensities (e.g. 2 mA) with topically applied local anesthetic creams.
Motor learning in lucid dreams | 27
The development of efficient techniques for lucid dream induction thus still remains
one of the biggest challenges for lucid dream research.
4.4. Study 4: Effectiveness of lucid dream practice
The final fourth study (Paper 4: Stumbrys, Erlacher, & Schredl, submitted) aimed to
replicate the findings from Erlacher and Schredl (2010) with a different (serial reaction)
motor task and compare the effectiveness of lucid dream practice not only to physical but
also to mental practice in wakefulness. Further, it was aimed to match the times of
different practice conditions, in order to avoid the interference of memory consolidation
effects during sleep (cf. Fischer et al., 2002; Walker et al., 2002). Online experiment was
completed by 68 participants divided into four groups: lucid dream practice group, mental
practice group, physical practice group and control (no practice) group. Finger-tapping was
used as a motor task: The task required pressing four keys on a computer keyboard with a
non-dominant hand producing a sequence of five elements “as quickly and accurately as
possible” for a period of 30 s. All participants completed the pre-test in the evening and the
post-test in the morning, while the participants in three practice groups also practiced the
task either in a lucid dream, or at a corresponding time after awakening from sleep
physically or mentally. At the post test, significant improvements were seen for all three
practice groups but not for the control group. In lucid dream practice group, the
performance improved by 20% (effect size d = 0.91), in physical practice group by 17% (d
= 1.57), while in mental practice by 12% (d = 1.16). All these effect sizes are considered
large ( 0.8) according to Cohen (1992). Slight insignificant improvement was also
observed in control group (5%, d = 0.39). Post-hoc analysis showed that the
improvements in lucid dream practice group and physical practice group were significantly
greater than in control group. No significant differences were found between other groups.
Thus motor practice in lucid dreams was replicated to be effective in improving
performance. Considering also the findings from the previous study (Erlacher & Schredl,
2010), the improvements following lucid dream practice seem to be similar or slightly lower
as compared to actual physical practice, and similar or slightly higher as compared to
mental practice in wakefulness. However more studies are needed, especially in a sleep
laboratory environment, which can ensure more controllable experimental conditions.
Motor learning in lucid dreams | 28
Summary and conclusions
The aim of the present investigation was to explore the potentials for motor learning in
lucid dreams: prevalence and frequency rates among athletes, methods for facilitation and
effectiveness. It was found that lucid dream frequency in athletes is similar as in general
population, however the percentage of lucid dreams as compared to all recalled dreams in
athletes was found to be nearly twice as high as in general population. Yet only few
athletes used lucid dreams for their sport practice. This shows that lucid dream practice is
little known and more publicity is needed among sport scientists, physical educators,
coaches, athletes and general public. Work with children and adolescents might be
especially fruitful, as lucid dreams seem to be more pronounced in young children and the
incidence rates drop at the age of 16, which is likely to be linked to brain maturation (Voss,
Frenzel, Koppehele-Gossel, & Hobson, 2012).
To make lucid dream practice more available, reliable lucid dream induction
techniques are needed. In our systematic review, we found over a dozen different methods
that were used for lucid dream induction. Yet none of them were verified to induce lucid
dreams reliably, consistently, and with a high success rate. We also tested one of the
prospective methods suggested in the literature but not previously empirically examined -
brain activation via transcranial direct current stimulation. While we observed increases in
dream lucidity following the stimulation, the effects were rather small and pronounced only
in frequent lucid dreamers. The question of reliable induction methods, thus, still remains
one of the most pertinent issues for lucid dream research, limiting both scientific
investigation (where always the main challenge is the recruitment of proficient lucid
dreamers) and practical applications (making lucid dream practice more widely available).
It is also important to note that lucid dreaming appears to be more an ability rather than a
skill – while the frequency of lucid dreams can be increased by applying different induction
methods, it seems to go back to the baseline levels upon discontinuation of training
(Schredl, 2013). Thus continuous induction practice is important. Considering a higher
proportion of lucid dreams as compared to all recalled dreams in athletes, one approach
for them might be to try to increase their overall dream recall (e.g. starting to keep a dream
diary), as the correlation between lucid dream frequency and overall dream recall
frequency is one of the most robust findings in lucid dream research (Stumbrys et al.,
2014).
Further, we were able to replicate the earlier study and demonstrate – with a
different task that motor practice in lucid dreams is effective in improving performance.
Motor learning in lucid dreams | 29
This time we also matched practice times to avoid the interference of memory
consolidation processes and made comparisons both with physical practice and mental
practice in wakefulness. While it is difficult to draw firm conclusions from only two studies,
the effectiveness of lucid dream practice seems to be similar to either physical or mental
practice in wakefulness. Yet, in comparison to waking imagination, it offers much more
realistic simulation which may offer additional benefits (cf. Tholey, 1990).
Tholey (1990) provided several suggestions for athletes who want to use lucid
dreams for their sport practice. His recommendations refer not only to the repetitive
training of sport skills but also to other aspects of sport performance. In lucid dreams,
athletes can attain mental flexibility (e.g. by varying the actions and reacting to unforeseen
situations), acquire new sensory-motor skills, explore more risky actions, practice without a
fear of injury or negative judgments by trainers and spectators, experience themselves as
both athletes and spectators at the same time, manipulate both phenomenal space and
phenomenal time, and develop greater creativity in sports (Tholey, 1990).
Future studies could explore some of these potential applications, for example, the
acquisition of completely novel motor skills or the development of greater creativity.
Moreover, it would be important to replicate the effects of lucid dream practice in a sleep
laboratory environment, which assures more strict compliance with the study procedure.
Further comparisons with physical and mental practice are also very interesting: Currently
we did not find any significant differences between the three different types of practices,
although literature shows that mental practice in wakefulness is somewhat less effective
than actual physical practice (cf. Driskell et al., 1994), while lucid dreams provide much
more realistic simulation (cf. LaBerge & Zimbardo, 2000) which may, arguably, lead to
greater learning effects (cf. Tholey, 1990). Finally, it could only be reiterated that the
development of effective methods for lucid dream induction is one of the major tasks
currently facing lucid dream research and on which largely depends the advancement of
the field.
Motor learning in lucid dreams | 30
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Motor learning in lucid dreams | 41
FAKULTÄT FÜR VERHALTENS-
UND EMPIRISCHE KULTURWISSENSCHAFTEN
Promotionsausschuss der Fakultät für Verhaltens- und Empirische Kulturwissenschaften
der Ruprecht-Karls-Universität Heidelberg
Doctoral Committee of the Faculty of Behavioural and Cultural Studies, of Heidelberg University
Erklärung gemäß § 8 Abs. 1 Buchst. b) der Promotionsordnung der Universität Heidelberg
für die Fakultät für Verhaltens- und Empirische Kulturwissenschaften
Declaration in accordance to § 8 (1) b) and § 8 (1) c) of the doctoral degree regulation of Heidelberg
University, Faculty of Behavioural and Cultural Studies
Ich erkläre, dass ich die vorgelegte Dissertation selbstständig angefertigt, nur die angegebenen
Hilfsmittel benutzt und die Zitate gekennzeichnet habe.
I declare that I have made the submitted dissertation independently, using only the specified tools and have
correctly marked all quotations.
Erklärung gemäß § 8 Abs. 1 Buchst. c) der Promotionsordnung
der Universität Heidelberg für die Fakultät für Verhaltens- und Empirische
Kulturwissenschaften
Ich erkläre, dass ich die vorgelegte Dissertation in dieser oder einer anderen Form nicht
anderweitig als Prüfungsarbeit verwendet oder einer anderen Fakultät als Dissertation vorgelegt
habe.
I declare that I did not use the submitted dissertation in this or any other form as an examination paper until
now and that I did not submit it in another faculty.
Vorname Nachname
First name Family name
Tadas Stumbrys
Datum, Unterschrift
Date, Signature
04.06.2014, _____________________
Motor learning in lucid dreams | 42
Appendix: Publications
Paper 1: Erlacher, Stumbrys, & Schredl (2011-2012)
Paper 2: Stumbrys, Erlacher, Schädlich, & Schredl (2012)
Paper 3: Stumbrys, Erlacher, & Schredl (2013)
Paper 4: Stumbrys, Erlacher, & Schredl (submitted)
Author's personal copy
Review
Induction of lucid dreams: A systematic review of evidence
Tadas Stumbrys
a,
, Daniel Erlacher
b
, Melanie Schädlich
c
, Michael Schredl
d
a
Institute of Sports and Sports Sciences, Heidelberg University, Germany
b
Institute of Sport Science, University of Bern, Switzerland
c
Institute of Psychology, University of Bonn, Germany
d
Central Institute of Mental Health, Mannheim, Germany
article info
Article history:
Received 4 March 2012
Available online 28 July 2012
Keywords:
Lucid dreaming
Induction techniques
Systematic review
Classification
abstract
In lucid dreams the dreamer is aware of dreaming and often able to influence the ongoing
dream content. Lucid dreaming is a learnable skill and a variety of techniques is suggested
for lucid dreaming induction. This systematic review evaluated the evidence for the effec-
tiveness of induction techniques. A comprehensive literature search was carried out in bio-
medical databases and specific resources. Thirty-five studies were included in the analysis
(11 sleep laboratory and 24 field studies), of which 26 employed cognitive techniques, 11
external stimulation and one drug application. The methodological quality of the included
studies was relatively low. None of the induction techniques were verified to induce lucid
dreams reliably and consistently, although some of them look promising. On the basis of
the reviewed studies, a taxonomy of lucid dream induction methods is presented. Several
methodological issues are discussed and further directions for future studies are proposed.
Ó2012 Elsevier Inc. All rights reserved.
Contents
1. Introduction . . . . . . . . . . . . . .............................................................................. 1457
1.1. Lucid dreams . .................................................................................... 1457
1.2. Induction techniques and their classifications . . . . . . . . . ................................................. 1458
2. Method . . . . . . . . . . . . . . . . . .............................................................................. 1459
2.1. Identification of studies . . . . . . . . .................................................................... 1459
2.2. Inclusion and exclusion criteria . . .................................................................... 1459
2.3. Data extraction, analysis and assessment . . . . . . . . . . . . . ................................................. 1459
3. Results. . . . . . . . . . . . . . . . . . .............................................................................. 1459
3.1. Literature search and excluded studies . . . . . . . . . . . . . . . ................................................. 1459
3.2. Included studies . . . . . . . . . . . . . . .................................................................... 1460
3.3. Methodological quality . . . . . . . . . .................................................................... 1466
3.4. Cognitive techniques. . . . . . . . . . . .................................................................... 1466
3.4.1. MILD . . . . . . . . . . . ......................................................................... 1467
3.4.2. Reflection/reality testing . . . . . . . . . . . . . . ...................................................... 1467
3.4.3. Intention . . . . . . . . ......................................................................... 1467
3.4.4. Autosuggestion . . . ......................................................................... 1467
3.4.5. Tholey’s combined technique . . . . . . . . . . ...................................................... 1468
3.4.6. Post-hypnotic suggestion . . . . . . . . . . . . . . ...................................................... 1468
3.4.7. Alpha feedback . . . ......................................................................... 1468
1053-8100/$ - see front matter Ó2012 Elsevier Inc. All rights reserved.
http://dx.doi.org/10.1016/j.concog.2012.07.003
Corresponding author. Address: Heidelberg University, Institute of Sports and Sports Sciences, Im Neuenheimer Feld 700, 69120 Heidelberg, Germany.
E-mail address: tadas.stumbrys@issw.uni-heidelberg.de (T. Stumbrys).
Consciousness and Cognition 21 (2012) 1456–1475
Contents lists available at SciVerse ScienceDirect
Consciousness and Cognition
journal homepage: www.elsevier.com/locate/concog
Author's personal copy
3.4.8. Dream re-entry. . . . . . . . . . . . ................................................................ 1468
3.4.9. Other (eclectic) approaches . . ................................................................ 1468
3.5. External stimulation . . . . ........................................................................... 1468
3.5.1. Light stimulation (including DreamLight, DreamLink, NovaDreamer) . . . . . . .......................... 1468
3.5.2. Acoustic stimulation. . . . . . . . ................................................................ 1469
3.5.3. Vibro-tactile stimulation . . . . ................................................................ 1469
3.5.4. Electro-tactile stimulation . . . ................................................................ 1469
3.5.5. Vestibular stimulation . . . . . . ................................................................ 1469
3.5.6. Water stimulus . . . . . . . . . . . . ................................................................ 1469
3.6. Application of drugs . . . . ........................................................................... 1469
4. Discussion. . . . . ........................................................................................ 1469
5. Future directions . . . . . . . . . . . . . . . . . . ..................................................................... 1473
References . . . . ........................................................................................ 1473
1. Introduction
1.1. Lucid dreams
A lucid dream is a dream during which the dreamer is aware of the fact that he or she is dreaming and therefore often can
consciously influence the dream content (LaBerge, 1985). Although awareness of dreaming while dreaming is usually con-
sidered an adequate criterion for lucid dreaming, some discussions have been held whether this is sufficient (Gillespie, 1984;
Tart, 1984, 1985). Tart (1984), for example, separates dreaming-awareness dreams and lucid dreams, for which he poses an
additional criterion that overall clarity of waking consciousness should also be retained. Tholey (1985) describes seven as-
pects of lucidity (clarity) in dreams: (1) clarity about the state of consciousness (that one is dreaming); (2) clarity about the
freedom of choice; (3) clarity of consciousness; (4) clarity about the waking life; (5) clarity of perception; (6) clarity about
the meaning of the dream; (7) clarity recollecting the dream. According to him, (1)–(4) are indispensible prerequisites of lu-
cid dreaming. While in this paper we will follow the conventional minimal criterion for the definition (awareness of dream-
ing while dreaming), it is important to acknowledge that dream lucidity is not an ‘‘all-or-nothing’’ phenomenon but rather a
continuum with different degrees: some dreams can be more lucid than others (Barrett, 1992; Moss, 1986).
Despite the fact that the phenomenon of lucid dreaming was known since the times of Aristotle (see Aristotle, 2007), only
30 years ago it was successfully verified in a sleep laboratory by measuring eye movements during REM sleep corresponding
with dreamed gaze shifts (Hearne, 1978; LaBerge, 1980a; LaBerge, Nagel, Dement, & Zarcone, 1981). Since then, numerous
studies have been conducted and research (overview: Erlacher & Schredl, 2008a) indicates that lucid dreaming is mainly a
REM sleep phenomenon, although it can also occur during NREM sleep (see Dane, 1984).
During REM dreams the skeletal muscles of the sleeping body are actively suppressed by neural structures in the brain
stem, keeping dreamers from actually acting out actions in their dreams (Hobson, Pace-Schott, & Stickgold, 2000). One obvi-
ous exception is eye movements. In accordance with the scanning hypothesis, eye movements during REM sleep correspond
with shifts of gaze in dream imagery (cf. Roffwarg, Dement, Muzio, & Fisher, 1962). Since lucid dreamers have access to their
waking memories (cf. Erlacher, 2009), it is possible for them to move their eyes during the dream according to a prearranged
pattern of eye movements (usually: left–right–left–right, LRLR) and produce a distinct electrooculagram (EOG) recording
during REM sleep; i.e., they can communicate from within the dream (cf. LaBerge et al., 1981). Then the lucid dreamer
can be awakened and asked for a dream report to match the recorded eye signals with the dreamed gaze shifts. In such
way, REM lucid dreams were successfully verified by subjective dream reports and objective EOG data in a number of dif-
ferent sleep laboratories across the world (e.g., Dane, 1984; Dresler et al., in press; Erlacher & Schredl, 2008b; Fenwick et
al., 1984; Hearne, 1983; Hickey, 1988; Kueny, 1985; LaBerge et al., 1981; Ogilvie, Hunt, Kushniruk, & Newman, 1983; Voss,
Holzmann, Tuin, & Hobson, 2009; Watanabe, 2003).
Most frequently, lucid dreams are initiated from REM sleep (so called ‘‘Dream-Initiated Lucid Dream’’ – DILD), however
sometimes they can also be initiated from the waking state (‘‘Wake-Initiated Lucid Dream’’ – WILD) (LaBerge, Levitan, & De-
ment, 1986). Physiologically, lucid dreams are associated with elevated levels of automatic nervous system activity (LaBerge
et al., 1986), but also with higher H-reflex suppression (Brylowski, Levitan, & LaBerge, 1989). According to recent findings,
lucid REM sleep when compared to non-lucid REM sleep is associated with increased EEG 40 Hz power, especially in frontal
and frontolateral regions (Voss et al., 2009). Another recent fMRI study found increased activation during REM lucid dream-
ing in several brain regions, including the bilateral precuneus, cuneus, parietal lobules, and prefrontal and occipito-temporal
cortices (Dresler et al., in press). This specific pattern of activation might explain the presence of higher order cognitive skills
involved in lucid dreaming. The prefrontal cortex is associated with metacognitive regulation and self-assessment, executive
function and top-down control of behaviour, attention regulation (Arnsten & Li, 2005; Fernandez-Duque, Baird, & Posner,
2000; Miller & Cohen, 2001; Schmitz, Kawahara-Baccus, & Johnson, 2004), while the precuneus is associated with self-pro-
cessing operations, such as first-person perspective taking and experience of agency (Cavanna & Trimble, 2006). In lucid
dreams the dreamer has to observe and evaluate his or her present experience to recognise the dream state and become
T. Stumbrys et al. / Consciousness and Cognition 21 (2012) 1456–1475 1457
Author's personal copy
lucid, then to take a first-person perspective and agency and guide behaviour and attention according to one’s intentions in
order to influence the dream content (see also Kahan & LaBerge, 1994).
Although frequent lucid dreaming is considered to be a rare skill, the estimates of lucid dreaming incidence within the
general population suggest that about a half of the population have experienced a lucid dream at least once and about
one out of five people are experiencing lucid dreams regularly, i.e. at least once a month (Schredl & Erlacher, 2011; Snyder
& Gackenbach, 1988; but cf. Stepansky et al., 1998). Recent studies found that the prevalence of lucid dreaming in children is
similar as in adults, however younger children seem to have lucid dreams more frequently (Schredl, Henley-Einion, & Bla-
grove, 2012; Voss, Frenzel, Koppehele-Gossel, & Hobson, in press). Differences across different cultures also exist (e.g., Erl-
acher, Schredl, Watanabe, Yamana, and Gantzert (2008) found significantly lower incidence of lucid dreaming in Japanese
student sample in comparison with other countries). Since the onset of lucid dream research it was demonstrated that lucid
dreaming is a learnable skill (LaBerge, 1980b; see also Saint-Denys, 1867/1982) and a number of practical applications were
suggested (e.g. LaBerge & Rheingold, 1990). Lucid dreaming, for example, was successfully applied in nightmare treatment:
several case studies (Abramovitch, 1995; Brylowski, 1990; Spoormaker, van den Bout, & Meijer, 2003; Zadra & Pihl, 1997)
and a controlled trial (Spoormaker & van den Bout, 2006) demonstrated that the development of lucid dreaming abilities
can decrease nightmare frequency and nightmare intensity. Lucid dreaming can also be used to enhance and perfect motor
performance and motor skills (Erlacher & Schredl, 2010; Tholey, 1981) or employed for creative problem solving (Stumbrys &
Daniels, 2010). Furthermore, lucid dreaming is an invaluable tool for scientists to explore the mind–body relationship during
REM sleep (see e.g. Erlacher & Schredl, 2008a) and its uniqueness warrants lucid dreaming a special place within the whole
area of consciousness research (Hobson, 2009). However, in order to utilize the advantages offered by lucid dreaming and
make them available both to the scientific community and a wider population, reliable induction techniques must be estab-
lished to increase the frequency of lucid dreams. This is the main challenge currently facing lucid dream research.
1.2. Induction techniques and their classifications
By the term ‘‘lucid dream induction’’ we refer to any means aiming to increase the frequency of lucid dreams. A plethora
of various techniques (e.g. Gackenbach, 1985–1986; LaBerge & Rheingold, 1990; Price & Cohen, 1988; Tholey, 1983) has been
suggested for lucid dream induction and several attempts were made to classify them.
One of the first classification systems was suggested by Gackenbach (1985–1986), who classified induction techniques
into two broad categories: (1) presleep induction and (2) sleep induction. The first category, presleep induction, includes
intentional techniques and ‘‘unintentional considerations’’. According to Gackenbach, intentional techniques focus on the
present moment (e.g. reflecting whether one is dreaming right now, engaging into other focused activities, such as medita-
tion or alpha feedback training) or are focused on the future (e.g. autosuggestion, post-hypnotic suggestion or intention to
remember that one is dreaming). Furthermore, some techniques might combine both aspects, e.g. Tholey’s (1983) combined
technique, which includes elements of reflection (present focussing) and intention with auto-suggestion (future focussing).
‘‘Unintentional considerations’’ include situations during the day (e.g. interpersonal interactions, emotions) and individual
propensities (e.g. field independence, creativity; for overview of individual differences associated with lucid dreaming see
Snyder & Gackenbach, 1988) that are not directly related to the attainment of dream lucidity but increase the likelihood
of having a lucid dream. The second category, sleep induction, can be divided into external cues and internal cues. External
clues are various environmental stimuli (e.g. auditory, tactile) that can be applied during REM sleep to be incorporated into a
dream and recognised as a cue by the dreamer that he or she is dreaming. Internal cues can be unusual events or inconsis-
tencies within a dream, a sense of ‘‘dreamlikeness’’ or just a spontaneous insight occurring in a dream which leads to the
awareness that one is dreaming.
Another classification of lucid dreaming induction techniques was suggested by Price and Cohen (1988), who grouped
them into three broad classes: (1) lucid-awareness training, (2) intention and suggestion techniques and (3) cue ‘‘REM-mind-
ing’’ techniques. Lucid-awareness training aims to cultivate a proper waking attitude to promote lucidity, such as critically
reflecting on a frequent basis whether one is dreaming or not, heightening perceptual awareness, alpha feedback or waking
fantasy training. Intention and suggestion techniques aspire to trigger a lucid dream through an act of will or suggestion.
Examples of such techniques include intentions to carry out a specific action while dreaming (e.g. flying), to remember that
one is dreaming and post-hypnotic suggestions. The third class of induction methods described by Price and Cohen (1988),
cue ‘‘REM-minding’’ techniques, resembles Gackenbach’s (1985–1986) external cues category and includes tactile, auditory
and other external stimuli presented during REM sleep to trigger lucidity. Price and Cohen (1988) also acknowledge that
there are some other methods that do not fit into their three major classes described, such as Tholey’s combined technique
or hypnagogic techniques that aim to enter lucid dreams directly from the waking state at sleep onset.
Although both these classification systems were useful and provided an adequate coverage of lucid dream induction tech-
niques presented in literature, they seem to be fragmentary, not including all techniques. Over the recent years a number of
empirical studies have been carried out that expanded our knowledge about induction techniques and new prospective
methods emerged (e.g., Noreika, Windt, Lenggenhager, & Karim, 2010). Another issue is that a considerable number of tech-
niques included in these systems were based on personal or anecdotal accounts and lacked any empirical validation. The
overlap between different categories is also a problem of these systems: Some induction methods, e.g. Tholey’s combined
technique, encompass both lucid awareness training and intention, or an intentional technique might result in an internal
cue during a dream that will lead to the attainment of lucidity.
1458 T. Stumbrys et al. / Consciousness and Cognition 21 (2012) 1456–1475
Author's personal copy
Therefore, in this paper we aim to present an empirically based classification of lucid dream induction techniques together
with an extensive systematic review of published empirical evidence on lucid dream induction. Considering difficulties defin-
ing the exact boundaries between different groups of induction techniques, we defined the following broad categories:
(1) cognitive techniques – encompass all cognitive activities (lucid awareness training, intention, suggestion, hypnagogic
techniques, etc.) that are carried out to increase the likelihood of achieving lucidity in a dream state;
(2) external stimulation – includes all types of stimuli (acoustic, light, electric, vibration, vestibular, brain stimulation,
etc.) presented during REM sleep that can trigger dream lucidity;
(3) miscellaneous techniques – cover all other diverse induction methods that are not covered by the two categories
above (e.g. intake of specific substances).
We hope that such an empirically-based classification will benefit not only lucid dreaming-interested scientists, provid-
ing them most promising directions for future research and most effective means to facilitate lucid dreaming both in a sleep
laboratory or home environment, but also a broader audience, including therapists, artists, athletes, nightmare sufferers and
others who may want to purse lucid dreams for their professional or personal reasons.
2. Method
2.1. Identification of studies
A comprehensive literature search was carried out to identify relevant studies, including both electronic bibliographic
databases and (lucid) dreaming specific resources. The following electronic databases were searched: MEDLINE, PsycINFO,
PsycArticles, Academic Search Premier, IngentaConnect, ScienceDirect, Scopus, Web of Science, ProQuest Dissertations &
Theses Database and PSYNDEX. Specific resources included scientific journals dedicated to (lucid) dream research (such
as Lucidity Letter, NightLight, International Journal of Dream Research, Dreaming), references in relevant articles and other
sources (such as personal collections). When searching the literature databases, the following search query was used: dream
AND lucid
AND (induc
OR learn
OR technique
OR method
OR exercise
). For a German PSYNDEX database, in addition we
also used a corresponding query with German keywords: traum
AND (luzid
OR klar
) AND (indu
OR lern
OR technik
OR
method
OR train
).
2.2. Inclusion and exclusion criteria
We aimed to identify any empirical studies that were concerned with lucid dream induction or applied any methods to
increase the frequency of lucid dreams in their participants. We also included those studies that were not primarily con-
cerned with lucid dream induction but used some methods to promote lucid dreaming in their participants, e.g. studies that
employed lucid dreaming as a treatment for nightmares. Both controlled studies in a sleep laboratory with sleep recording
and quasi-experimental field studies without sleep recording were included. No language restrictions were applied. Single
case reports were excluded.
2.3. Data extraction, analysis and assessment
Literature search was conducted in November–December 2010 by one researcher and then carried out by a second re-
searcher in April–May 2011. Data was extracted by using a specially devised form and then was reviewed by a second re-
searcher. The methodological quality of all studies was assessed independently by two researchers using a quality
checklist developed by Downs and Black (1998), which can be used for evaluation of both randomised and non-randomised
studies. The checklist contains 27 items distributed into five subscales: reporting (n= 10), external validity (n= 3), internal
validity – bias (n= 7), internal validity – confounding (n= 6) and power (n= 1). One item on the reporting subscale (No. 5),
can have a maximum score of 2, the other items are scored either 0 or 1 (although the item on power [No. 27], can get the
score up to 5, in this review the maximum score for this item was considered 1). Hence the maximum score possible score for
methodological quality was 28. The Downs and Black (1998) checklist is considered to be among the six best quality assess-
ment tools to be used for systematic reviews (Deeks et al., 2003). Any differences between the researchers were resolved by
discussion. Quality scores of 21 and higher were considered good, 11–20 – moderate and 10 and lower – poor (Hartling, Bri-
son, Crumley, Klassen, & Pickett, 2004).
3. Results
3.1. Literature search and excluded studies
Initial literature search and its replication brought equivalent results: Only one additional citation was retrieved and 11
sources were no longer available on ProQuest database. In total, literature search in electronic databases yielded 131 initial
T. Stumbrys et al. / Consciousness and Cognition 21 (2012) 1456–1475 1459
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references. A first examination of titles and abstracts led to the following: 83 citations were rejected as not relevant, i.e. they
were not dealing with lucid dream induction. Further nine citations were rejected according to our inclusion/exclusion cri-
teria, i.e. were either not empirical studies (lacked empirical validation) or just single case studies. Four other citations (three
thesis and one conference abstract) were eliminated as information in the abstract was insufficient and full texts were not
available. Thus a total of 35 references were examined as full texts. After examination, 19 papers out of them were excluded
as not dealing with lucid dream induction, being without an empirical validation or single case studies.
Furthermore, 22 additional papers were identified via hand search in lucid dreaming-specific resources, cited references
in relevant articles and personal collections. One study identified via hand search (Ripert in Price, LaBerge, Bouchet, Ripert, &
Dane, 1986) contained unrealistic data (according to the data reported, some participants had about 40 lucid dreams per
night) and was judged of extremely poor quality (initial assessment by a first judge yielded 0 score on the Downs and Black
(1998) checklist), hence it was discarded from further analysis.
The flowchart of the study identification process is demonstrated in Fig. 1.
3.2. Included studies
Therefore 37 manuscripts (16 identified via literature search in electronic databases and 21 via hand search) were in-
cluded in the review. Some studies were reported in two different manuscripts (e.g., Zadra, 1991; Zadra, Donderi, & Pihl,
1992), while in two other cases (Galvin, 1993; Hickey, 1988) studies involved both sleep laboratory and field experiments
witch for the purpose of this review were considered as two separate studies. Thus, a total number of 35 studies were ana-
lysed in this review. Details of the included studies are presented in Table 1.
Additional citations identified
via hand search in (lucid)
dreaming-specific resources
(N=22)
Citations identified
via literature search
(N=131)
Citations rejected as single case
studies or without an empirical
validation
(N=9)
Citations rejected as not relevant
(N=83)
Citations rejected as information
was insufficient (e.g. full text
articles were not available)
(N=4)
Citations examined
as full texts
(N=35)
Citations rejected as not relevant,
single case studies or without
an empirical validation
(N=19)
Citations included
in the review
(N=37)
Rejected because
of a very poor
quality and
unrealistic data
(N=1)
Fig. 1. Study identification flow chart.
1460 T. Stumbrys et al. / Consciousness and Cognition 21 (2012) 1456–1475
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Table 1
Included studies.
No Reference Type Methods Sample Techniques used Main results Quality
1Levitan
(1989)
Field (within) 4 weeks; different technique each week (1st week
baseline with no technique)
N= 62 (lucid
dreamers)
MILD, reality testing,
autosuggestion
BL: 20% participants had LDs; 0.21 participant/week 8 (poor)
MILD: 26.3%; 0.37 p/w
RT: 29.1%; 0.53 p/w
AS: 19.5%; 0.21p/w
2Levitan
(1990a)
Field (within) 2 nap conditions: wake up 2 h earlier and take a 2 h
nap (a) after 2 h or (b) after 4 h; compared with the
night before naps
N= 10 (lucid
dreamers)
MILD, WBTB Night before naps: 10% of dreams were lucid (9 in
total)
5 (poor)
Naps in total: 40% (25)
Nap after 2 h: 50%
Nap after 4 h: 33%
3Levitan
(1990b)
Field (within) 2 conditions: 15 min MILD (a) in the evening or (b)
in the morning
N= 20 (lucid
dreamers)
MILD Evening: 0.44 LDs/night (6 participants) 5 (poor)
Morning: 0.26 LDs/night (3)
4Levitan
(1991a)
Field (within) 3 nights, 3 conditions: (a) wake up 90 min earlier,
90 min awake, MILD and 90 min nap; (b) wake up
90 min earlier, MILD and 90 min nap; (c) wake up at
normal time, MILD and 90 min nap
N= 12 (lucid
dreamers)
MILD, WBTB (a): 9 had LDs (75%); 8 during the nap (67%), 1 at night
(8%)
8 (poor)
(b): 4 had LDs (33%); all 4 during the nap
(c): 3 had LDs (25%); 1 during the nap (8%), 2 at night
(17%)
5Levitan
(1991b)
Field (within) 2 conditions: after waking up from a dream either
(a) to count or (b) to focus on the body image
N= 30 (lucid
dreamers)
WILD (dream
re-entry)
43 LDs out of 191 attempts (23%); 66% of participants
LDs following re-entry; 33% of all re-entered dreams
were lucid
5 (poor)
6Edelstein and
LaBerge
(1992)
Field (within) 2 conditions were intended: (a) wake up 90 min
earlier, 90 min awake, MILD and 90 min nap; (b) go
to bed 90 min later, wake up at normal time, MILD
and 90 min nap. However, they were not compared
due to methodological problems. Compared instead
naps with the nights
N= 18 (lucid
dreamers)
MILD, WBTB 11 participants had LDs, 9 of them had more LDs during
the naps than the nights
4 (poor)
8% of the nights and 37% of the naps had LDs. 6% of
dreams reported from the nights were lucid and 20%
from the naps
7Levitan et al.
(1992)
Field (within) 2 conditions: (AM nap) wake up 90 min earlier,
90 min awake, MILD and 90 min nap; (PM nap) go
to bed 14–17 h after a regular bedtime, MILD and
90 min nap
N= 22 (lucid
dreamers)
MILD, WBTB 32% (27 in total) of nap dreams were lucid (42% of AM
and 12% of PM nap dreams), while only 4.1% (6 out of
145) of night dreams were lucid
6 (poor)
12 people (55%) had LDs in naps, 9 had more LDs in AM
than PM
8Levitan and
LaBerge
(1994)
Field (within) 28 days dream diary N= 46 (lucid
dreamers;
32M/14F)
MILD, reality testing,
hypnotic induction,
light stimulus
1228 nights, 2968 logged dreams 6 (poor)
262 (8.8%) of all dreams were lucid (from 38
participants)
Light stimulus device: 3.7% LDs; MILD: 5.3%;
device + MILD: 8.6%
9LaBerge et al.
(1994)
Field (within) 3 conditions: (a) 50 min later to bed, wake up
10 min earlier, 10 min reading about LD, MILD and
90 min nap; (b) 30 min later to bed, wake up 30 min
earlier, 30 min reading about LD, MILD and 90 min
nap; (c) regular time to bed, wake up 60 min earlier,
60 min reading about LD, MILD and 90 min nap
N= 22 (lucid
dreamers; 12M/
10F)
MILD, WBTB Baseline (last 6 months): 1 LD in 7 nights 6 (poor)
Nap (a): 1 LD in 11 nights (5 LDs in total)
Nap (b): 1 LD in 2 nights (20 LDs)
Nap (c): 1 LD in 1.6 nights (25 LDs)
50 out of 189 naps dreams (27%) were lucid, while only 3
out 235 night dreams (1.3%)
(continued on next page)
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Table 1 (continued)
No Reference Type Methods Sample Techniques used Main results Quality
10 LaBerge and
Levitan
(1995)
Field (within) 4–24 nights (M= 11), 2 conditions: device
producing light cues (Q-ON) and producing no light
cues (Q-OFF). Reports evaluated by blinded judges
N= 14 (lucid
dreamers; 10M/
4F)
Light stimulus 162 reports (81 in each condition) 14
(moderate)
32 LDs in total: 22 (69%) Q-ON and 10 (31%) Q-OFF.
Mean rate (participant/night): Q-ON 0.30 ± 0.24; Q-OFF
0.09 ± 0.15 (p< .025)
6 LDs (5 participants) were trigered by a cue (6 in Q-ON,
0.071 ± 0.10 vs. 0 in Q-OFF; p< .025)
8 LDs (6 ps) were initiated by the Reality Testing Button
(6 in Q-ON, 0.091 ± 0.16 vs. 2 in Q-OFF, 0.016 ± 0.04;
p< .10)
18 LDs (9 ps) had dreams triggered by any occurrence of
the device (Q-ON, 0.174 ± 0.21 vs. Q-OFF, 0.04 ± 0.09;
p< .05)
11 Purcell et al.
(1986)
Field (between) 3 weeks; 5 groups: (1) Baseline dream reports
only; (2) Contrast –dream reports, weekly group
contact, report skills questionaire [RSQ] and
motivated to make more detailed reports; (3) Rossi
– dream reports, weekly group contact, self-
reflectiveness [SR] and motivated to advance SR; (4)
Mnemonic – dream reports, weekly group contact,
RSQ, reality testing and motivated to LD; (5)
Hypnosis – dream reports, weekly individual
contact and post-hypnotic suggestion (with
individual variations)
N= 48 (undergrad
students; 22M/
26F)
Reflection, reality
testing, post-hypnotic
suggestion
Baseline: 0 LDs 13
(moderate)
Contrast: 1 LD
Rossi: 7 LDs
Mnemonic: 15 LDs
Hypnosis: 0 LDs
12 Zadra et al.
(1992)
and Zadra
(1991)
Field (between) 6 weeks, 3 groups: No Experience, No Technique
(NENT); No Experience, Technique (NET);
Experience, Technique (ET)
N= 47 (university
students; 17M/
30F)
Tholey’s combined
technique
NENT: 2 LDs from 2 participants (M= 0.13[SD = 0.35]); 6
PreLDs (0.40 [0.63])
16
(moderate)
NET: 23 LDs from 9 ps (1.44 [1.93]); 13 PreLDs (0.81
[0.75])
ET: 110 LDs from all 16 ps (6.88 [6.62]); 23 PreLDs (1.44
[1.32])
Both access to the technique (p< .05) and previous LD
experience (p< .02) influenced LD probability
Lucidity: 28% spontaneously; 44% observation of
incongruities; 23% nigtmares/anxiety dreams; 5%
positive emotions
13 Schlag-Gies
(1992)
Field (between) 8 weeks; 5 groups: Autosuggestion (A); Intention
(I); Reflection (R); Control group without
information about LD (K); Control with information
about LD (X). More strict criteria were used for
defining a dream as lucid (e.g. involved some action
taken as a consequence of awareness of dreaming)
in comparison with other studies
N= 90 (34M/56F) Autosuggestion,
intention, reflection
A: original criteria – 16 LDs (2.3%)/conventional criteria
– 32 LDs (4.6%)
18
(moderate)
I: 11 LDs (1.7%)/31 LDs (4.8%)
R: 32 LDs (5.5%)/79 LDs (13.6%)
K: 0 LDs (0%)/2 LDs (0.5%)
X: 3 LDs (0.7%)/18 LDs (4.4%)
There were more LDs in the technique groups (A, I, R)
than control groups (p< .001). R had more LDs than I
(p< .01) and A (p< .05)
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14 Spoormaker
and van
Den Bout
(2006)
Field (between) 12 weeks; 3 groups: (A) 2 h individual LD session;
(B) 2 h group LD session; (C) waiting list. LD used as
a means for nightmare treatment
N= 23 (nightmare
sufferers; 6M/
17W)
Intention A: 4 participants became lucid and altered nightmares 11
(moderate)
B: 2 participants
C: 0
15 Paulsson and
Parker
(2006)
Field (within) 2 weeks (baseline the week before) N= 20 (11M/9F) Tholey’s combined
technique
Baseline: LD frequency (nights/week): M= 0.13
(SD = 0.22)
15
(moderate)
1st week: 11 participants had LDs (5 who never had
before); LD frequency: 0.90 (1.02)
2nd week: 9 lucid participants; LD freque ncy: 1.25
(1.86)
Technique significantly increased LD frequency (p< .05)
16 LaBerge et al.
(1981)
Sleep lab
(within)
1–2 nights each; 5–10 min after beginning of each
REM period, phrase ‘‘This is a dream’’ was played
repeatedly with increasing volume
N= 4 Acoustic stimulus 15 trials in total, lucidity in 5 (33%) cases. Incorporation
with lucidity: 3 (20%)
5 (poor)
Incorporation without lucidity: 2 (13%)
Lucidity without incorporation: 2 (13%)
Awakening without incorporation: 8 (53%)
17 LaBerge et al.
(1988)
and LaBerge
(1987)
Sleep lab
(within)
1–5 nights each (58 in total); flashing light during
REM sleep
N= 44 Light stimulus 25 participants (55%) had LDs 4 (poor)
50 LDs in total: 5 (10%) in REMPs before the stimulus; 11
(22%) in REMPs after the stimulus, but not triggered by
the stimulus; 33 (66%) triggered by the stimulus; 1 LD
from NREM2
18 LaBerge
(1988)
Field (within) 8 weekly group meetings; participants had access
to DreamLight devices
N= 49 Light stimulus, MILD,
reality testing
Baseline: 3.7% of LDs 5 (poor)
DreamLight without MILD: 5.5% LDs
MILD without DreamLight: 13% LDs
MILD with DreamLight: 20% LDs
DreamLight usage correlation with LDs: r= .098 ± .095,
p< .022
MILD: r= .124 ± .087, p< .003
Reality testing: r= .036 ± .102, p< .24
19 Hearne
(1983)
Sleep lab
(within)
1 night each; 4 electric impulses to the wrist during
REM sleep; one ‘‘catch trial’’ (awakening after no
stimulation)
N= 12 (mostly
students; 12F)
Electric stimulus 6 participants got lucid; 2 participants became lucid but
woke up at signalling; and 1 participant falsely
perceived stimulation and became lucid
9 (poor)
20 Dane (1984)
and Dane
and Van De
Castle
(1984)
Sleep lab
(between)
1 night each; 4 conditions (instructions have shifted
during the course of study – participants were
encouraged to signal even if they were not sure
whether awake or dreaming [revised: whether
awake or sleeping]): Post-hypnotic Suggestion
(PHS) + Original Waking Instructions (OWI);
PHS + Revised Waking Instructions (RWI); OWI
only; RWI only. PHS employed personal symbols
N=30
(hypnotically
susceptible
women; 30F)
Post-hypnotic
suggestion, reflection
3 types of LDs indentified: Unambiguous REM LDs
(UREMLDs); Ambiguous REM LDs (AREMLDs); NREM
LDs (NREMLDs)
15
(moderate)
PHS + OWI: 3 UREMLDs (from 3 participants); 4
AREMLDs (3); 9 NREMLDs (4); 7 (of 8) participants in
total
PHS + RWI: 2 UREMLDs (2); 3 AREMLDs (2); 12
NREMLDs (7); 7 (of 7) ps
OWI: 3 NREMLDs (1); 1 (of 8) ps
RWI: 3 UREMLDs (3); 3 AREMLDs (3); 6 NREMLDs (5); 6
(of 7) ps
All other conditions were significantly better than OWI
21 Reis (1989) Field (within) 1–4 nights each; varying conditions (in some cases
individual training sessions varied in kind, number
and length)
N= 8 (4M/4F) Vibration, acoustic
stimulus, reflection
Vibration + reflection (5 participants; 13 nights): 2 LDs
from 2 participants
6 (poor)
Vibration only (1 p; 2 n): 0 LDs
Sound only (1 p; 1 n): 0 LDs
Vibration + sound + reflection (1 p; 3 n): 2 LDs
(continued on next page)
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Table 1 (continued)
No Reference Type Methods Sample Techniques used Main results Quality
22 Leslie and
Ogilvie
(1996)
Sleep lab
(within)
2 nights each sleeping in a hammock; 2
counterbalanced conditions: stationary hammock
(control); rocking hammock (at 1 Hz frequency for
5 min). Reports from 2nd–4th REM periods.
Measures included self-reflectiveness scale and
mentation continuum scale
N= 7 (university
students)
Vestibular stimulation 45 valid reports, subset of 28 REM periods (4 per
participant) used
14
(moderate)
Peak self-reflectiveness (PSR): rocking in early morning
(M= 4.90) and late morning (4.62) vs. stationary early
(2.95) and late (4.43) (p< .05)
Mentation continuum (MC): rocking early (3.00) and late
(1.91) vs. stationary early (1.05) and late (2.33) (p6.05)
PSR and MC correlation r= .80 (p6.001)
Lucid: 25% (6 out of 24) of rocking dreams vs. 14% (3 out
of 21) of control dreams
23 Kueny (1985) Sleep lab
(within/
between)
3 weeks MILD training program; 4 non-consecutive
nights in a lab each: 1st and 2nd nights: MILD only;
3rd and 4th nights: MILD + acoustic stimulus during
REM. Acoustic stimulus: (a) voice ‘‘Remember, this
is a dream’’, 5 dB increase every 20 s (Step-Voice);
(b) voice ‘‘Remember, this is a dream’’, 4 dB increase
every 4 min (Constant-Voice); (c) musical tone, 5 dB
increase every 20 s (Step-Tone); (d) musical tone,
4 dB increase every 4 min (Constant-Tone)
N= 16 Acoustic stimulus,
MILD
MILD only: 6 confirmed LDs from 5 participants (19
reported LDs from 5 ps)
12
(moderate)
MILD + acoustic stimulus: 5 from 5 (22 from 9)
Step-Voice: 3 from 3 (12 from 4)
Constant-Voice: 1 (1)
Step-Tone: 0 (5 from 4)
Constant-Tone: 1 (4 from 2)
Trend (p< .1) for Step condition to be more effective
than Constant.
24 Ogilvie et al.
(1983)
Sleep lab
(within)
1–4 nights in a lab; acoustic stimulus (buzzer) after
15 min of REM in the presence of either high or low
REM activity. Participants were asked to signal with
their eyes after a stimulus. Awakenings after eye
signalling or 30–60 s after stimulus
N= 8 (lucid
dreamers)
Acoustic stimulus Total: 57% lucid, 21% prelucid, 22% non-lucid dreams 2 (poor)
Spontaneous eye signaling (N= 14): 64% lucid, 27%
prelucid, 22% non-lucid
Cued high (n= 16): 43% lucid, 21% prelucid, 36% non-
lucid
Cued low (n= 15): 69% lucid, 12% prelucid, 36% non-
lucid
25 Spoormaker,
van den Bout,
and Meijer
(2003)
Field (within) 2 months; LD used as a means for nightmare
treatment
N= 8 (nightmare
sufferers; 2M/6F)
Intention 4 participants became lucid, 3 of them were able to alter
the nightmare
7 (poor)
26 Galvin (1993) Sleep lab
(within)
5 nights (baseline + 4 experimental nights) in a lab
over 9 weeks. Post-hypnotic suggestion (PHS) was
repeated before each of experimental nights
N= 8 (nightmare
sufferers; 2M/6F)
Post-hypnotic
suggestion
Only 1 participants had verified LD in a sleep lab on 3
occasions (REM/NREM2; NREM2; unclear)
11
(moderate)
27 Field (within) 9 weeks period; dream diary; PHS delivered on
weeks 4, 5, 7, and 8 at the lab and the participants
were also given a tape-recording for home use
6 out of 8 participants reported LDs in home settings (9
LDs in total out of 446 dream reports [2%]); self-
reflectiveness increased over the time (p= .035)
14
(moderate)
28 Malamud
(1979)
Qualitative Dialectical approach; about 12 weeks period
(varying)
N= 6 (2M/4F) Reflection 4 participants had LDs during or shortly after the
training
8 (poor)
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29 Purcell (1988) Field (between) 3 weeks; 3 conditions: (1) Baseline – dream reports
only; (2) Attention Control – dream reports, report
skills questionnaire (RSQ), weekly meeting; (3)
Schema: the same as (2) + dream control
questionnaire and a cue (bracelet). Dream reports
scored by judges
N= 94 (undergrad
students; 49M/
46F; 54 high and
41 low dream
recallers)
Reflection Baseline: 4 (12.5%) lucid participants, 7 LDs out of 433
dreams (1.6%)
17
(moderate)
Attention Control: 3 (10%) lucids, 3 LDs out of 345 (0.9%)
Schema [Reflection]: 16 (50%) LDs, 57 LDs out of 434
(13.1%)
Number of lucid participants vs. non-lucids – significant
differences across groups (p< .001). Dream control
training had significant effect (p= .026)
30 Hickey (1988) Sleep lab
(within)
4 non-consecutive nights in a lab N= 4 (children
aged 10–12)
MILD, reflection, re-
dreaming and other
2 out of 4 children (50%) had verified LDs in a sleep lab; 6
LDs in 16 nights (38%)
7 (poor)
31 Field (within) 6 weeks training program (included also art
activities)
N= 13 (children
aged 10–12)
12 out of 13 children (92%) had LDs (24 in total) during
the training programme
7 (poor)
32 Ogilvie et al.
(1982)
Sleep lab
(within/
between)
2 nights in a lab; 2 groups: (1) with alpha feedback
training (AFT); (2) without AFT. Awakened 4 times
during REM sleep (twice with high alpha and twice
with low alpha). 7 point lucidity and 15 point
lucidity/dream control scales used
N= 10 (lucid
dreamers; 5M/5F)
Alpha feedback AFT had no effect on lucidity/REM alpha levels; arousals
from high alpha had higher lucidity ratings than arousals
from low alpha
11
(moderate)
33 Zadra and Pihl
(1997)
Field (within) Case series; 2 participants (cases 1–2) had
progressive muscle relaxation, guided imagery, and
LD induction; other 3 participants (cases 3–5) LD
induction alone (with some guided imagery)
N= 5 (nightmare
sufferers)
Intention Case 1: LD after 4 weeks 5 (poor)
Cases 2–3: No LDs
Case 4: LD after 1.5 weeks
Case 5: LD after 2.5 (?) weeks
34 Hearne
(1978)
Sleep lab
(within)
1 night in a lab (+adaptation night before); 2
awakenings during late REM periods: (1)
experimental condition -after splashing some water
on their face or hand with a syringe; (2) control
condition – only standing with a syringe (without
splashing water). Dream reports rated by judges
N= 10 (university
students; 2M/8F)
Water stimulus None of the participants had LDs. Water-spray theme
was present in 6 out of 10 experimental reports, but not
in 10 control reports
12
(moderate)
35 LaBerge
(2004)
Field (within) 3 nights, 3 conditions: (1) Placebo; (2) Donepezil
5 mg; (3) Donepezil 10 mg
N= 10 (7M/3F) Donepezil ingestion 9 of 10 reported LDs on Donepezil nights, while 1 out of
10 only on control nights
7 (poor)
LD rates per night: 0.031 for placebo; 0.429 for 5 mg
Donepezil; 0.754 for 10 mg Donepezil. 10 mg Donepezil
vs. placebo (p< .001)
Donepezil was also associated with an increased sleep
paralysis rate and 40% increase in estimated time awake
Note: If more than one study reference is provided, the first in the list was the used as the primary one (e.g. for which methodological quality was assessed).
T. Stumbrys et al. / Consciousness and Cognition 21 (2012) 1456–1475 1465
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3.3. Methodological quality
The 35 studies included in the review (11 sleep laboratory and 24 field studies) were assessed for their methodological
quality independently by two researchers. The interrater reliability between the initial ratings of the two judges was very
high (kappa = .91; 95% CI 0.88–0.94). The agreed final ratings are presented in Table 2.
Taking together, the methodological quality of the studies was quite poor: The average score on the Downs and Black’s
(1998) checklist was only 9.1 out of 28. Both sleep laboratory and field studies had the same level of methodological quality
(9.3 and 9.0, respectively). The ‘‘reporting’’ subscore for the included studies averaged 4.3 out of 11, external validity 0.7 out
of 3, internal validity-bias 2.5 out of 7, and internal validity-confounding (selection bias) 1.6 out of 6. None of the studies had
a good methodological quality (>20). Fourteen studies (40%) had a moderate quality (11–20) and 21 (60%) poor (<11). Con-
sidering the overall poor quality of the studies, small sample sizes used, great variability of the exact conditions in which
induction techniques were applied and lack of reporting effect sizes respective data for computing effect sizes, it was not
possible to carry out a meta-analysis. Hence our analyses will focus on a descriptive level.
3.4. Cognitive techniques
Twenty-seven (77%) studies employed cognitive techniques for lucid dream induction. Cognitive techniques were applied
in 22 (96%) field experiments and five (45%) sleep laboratory studies. The following techniques were used: MILD (Mnemonic
Induction of Lucid Dreams), Reflection or Reality Testing, Intention, Tholey’s Combined technique, Autosuggestion, Dream
Table 2
Methodological quality of the included studies (agreed ratings).
No Reference Item number on the Downs and Black’s (1998) checklist Total
score
123456789101112131415161718192021222324252627
1Levitan (1989) 101100000000100010101100000 8
2Levitan (1990a) 100100000000100000001100000 5
3Levitan (1990b) 100100000000100000001100000 5
4Levitan (1991a) 100101000000100110001100000 8
5Levitan (1991b) 100100000000100000001100000 5
6Edelstein and LaBerge
(1992)
000100000000100000001100000 4
7Levitan, LaBerge, and Dole
(1992)
100100000000100000101100000 6
8Levitan and LaBerge (1994) 101000000000100000101100000 6
9LaBerge, Phillips, and
Levitan (1994)
100100000000100000101100000 6
10 LaBerge and Levitan (1995) 11110110000011110111100000014
11 Purcell et al. (1986) 0011011011 0 0 1 0 0 0 1 1 0 1 1 1 1 0 0 0 0 13
12 Zadra, Donderi, and Pihl
(1992)
1111111010 0 0 1 0 1 0 1 1 0 1 1 1 0 0 0 1 0 16
13 Schlag-Gies (1992) 1111111011 0 0 1 0 0 0 1 1 1 1 1 1 1 0 0 0 1 18
14 Spoormaker and van den
Bout (2006)
00101000110010011100001011011
15 Paulsson and Parker (2006) 1111111010 0 0 1 0 0 1 1 1 0 0 1 1 0 0 0 0 1 15
16 LaBerge et al. (1981) 100001001000000000110000000 5
17 LaBerge et al. (1988) 100001000000000000110000000 4
18 LaBerge (1988) 000000100100100000001100000 5
19 Hearne (1983) 101101000000010110110000000 9
20 Dane (1984) 11111100100000101111001011015
21 Reis (1989) 000101011000100000001000000 6
22 Leslie and Ogilvie (1996) 11011100110001101111000001014
23 Kueny (1985) 10111100000000101111010000112
24 Ogilvie et al. (1983) 000000000000000000110000000 2
25 Spoormaker, van den Bout,
and Meijer (2003)
101100001000100010000000010 7
26 Galvin (1993) (sleep lab) 1 1 1 1 1 1 0 0 0 1 0 0 0 0 0 0 1 0 1 1 0 1 0 0 0 0 0 11
27 Galvin (1993) (field) 1 1 1 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1 1 0 0 1 0 0 0 0 0 14
28 Malamud (1979) 111110001000100000000100000 8
29 Purcell (1988) 1111011011 0 0 1 0 1 0 1 1 1 1 1 0 1 0 0 1 0 17
30 Hickey (1988) (sleep lab) 1 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 1 1 0 0 0 0 0 0 0 7
31 Hickey (1988) (field) 1 1 0 0 0 0 0 0 1 0 0 0 1 0 0 1 1 0 0 0 0 0 0 0 0 1 0 7
32 Ogilvie et al. (1982) 00110000100001101111010001011
33 Zadra and Pihl (1997) 001100001000100000000000010 5
34 Hearne (1978) 1111010010 0 0 0 1 0 0 1 0 1 1 0 0 1 0 0 1 0 12
35 LaBerge (2004) 101100001000010000000010010 7
1466 T. Stumbrys et al. / Consciousness and Cognition 21 (2012) 1456–1475
Author's personal copy
Re-Entry, Post-hypnotic Suggestion, and Alpha Feedback. The overall methodological quality for studies involving cognitive
techniques was 9.3.
3.4.1. MILD
MILD technique, which requires to rehearse a dream before falling asleep and visualise becoming lucid while focusing on
the intention to remember that one is dreaming (LaBerge, 1980b), was the one most often tested empirically. It was applied
in 10 studies: nine field experiments and one sleep laboratory study. However, the only sleep laboratory study (Kueny, 1985)
that involved MILD, used it only as a control condition, while the nine field studies, conducted entirely by LaBerge, Levitan
and their colleagues (Edelstein & LaBerge, 1992; LaBerge, 1988; LaBerge, Phillips, & Levitan, 1994; Levitan, 1989, 1990a,
1990b, 1991a; Levitan & LaBerge, 1994; Levitan, LaBerge, & Dole, 1992), showed poor reportability scores (average ‘‘report-
ing’’ subscore was only 2.1 out of 11). The overall quality score for those nine studies was also very low (only 5.9).
It seems that MILD practice can increase the frequency of lucid dreaming (LaBerge, 1988; Levitan, 1989, 1991a; Levitan &
LaBerge, 1994). The relation between MILD practice and lucid dreaming frequency appears to be quite weak (r= 0.124), but
significant (LaBerge, 1988). When using MILD in early morning hours, lucid dreams seem to be much more likely during fol-
lowing naps than the night before (Edelstein & LaBerge, 1992; LaBerge et al., 1994; Levitan, 1990a, 1991a; Levitan et al.,
1992). It appears to be favourable to wake up 30–120 min earlier, stay awake for those 30–120 min, go back to bed, practice
MILD and take a nap (LaBerge et al., 1994; Levitan, 1990a, 1991a; Levitan et al., 1992). The shorter periods of wakefulness,
such as taking a nap after 10 min (LaBerge et al., 1994) or immediately after awakening (Levitan, 1991a), as well as longer
ones, such as taking a nap after 4 h (Levitan, 1990a) or after 14–17 h in the afternoon (Levitan et al., 1992), seem to be less
favourable for MILD practice. MILD seems to be slightly more effective than light stimuli presented during REM sleep; how-
ever, the combination of both appears to be even more favourable for lucid dream induction (LaBerge, 1988; Levitan & La-
Berge, 1994).
3.4.2. Reflection/reality testing
Reflection or reality testing technique involves asking oneself regularly during the day whether one is dreaming or not,
and examining the environment for possible incongruences (Tholey, 1983). Reflection/reality testing was employed in one
sleep laboratory experiment (Dane, 1984), but was not used as an experimental condition, and in eight field studies (LaBerge,
1988; Levitan, 1989; Levitan & LaBerge, 1994; Malamud, 1979; Purcell, 1988; Purcell, Mullington, Moffitt, Hoffmann, & Pi-
geau, 1986; Reis, 1989; Schlag-Gies, 1992). However, one field study did not report the relevant findings (Levitan & LaBerge,
1994) and in another study (Reis, 1989) it was used only in combination with external stimulation, so only the data from the
remaining six field studies (average methodological quality 11.5) was considered.
Reflection/reality testing seems to increase frequency of lucid dreams (Levitan, 1989; Purcell, 1988; Purcell et al., 1986;
Schlag-Gies, 1992), although one study did not find any relation between reality testing practice and lucid dream frequency
(LaBerge, 1988). There are some indications that reflection/reality testing might be more effective than other cognitive tech-
niques, such as autosuggestion (Levitan, 1989; Schlag-Gies, 1992), post-hypnotic suggestion (Purcell et al., 1986) or intention
(Schlag-Gies, 1992). Comparison with MILD is ambiguous: in one study (LaBerge, 1988) reality testing seemed to be some-
what less effective than MILD, while other study (Levitan, 1989) yielded opposite results.
3.4.3. Intention
Intention technique requires that a person – before falling asleep – imagine himself or herself as intensively as possible
being in a dream situation and recognise that one is dreaming (Tholey, 1983). Therefore intention technique is fairly similar
to MILD, however it does not involve ‘‘mnemonic’’ component, i.e. while the emphasis in MILD is to remember that one is
dreaming, in intention technique it is to recognise that one is dreaming. The technique was employed in four field studies;
however, three of them were not specifically concerned with lucid dream induction, but used it as a means for nightmare
treatment (Spoormaker & van Den Bout, 2006; Spoormaker et al., 2003; Zadra & Pihl, 1997). The fourth one compared inten-
tion technique with other induction methods (Schlag-Gies, 1992). The average methodological quality for these studies was
10.3.
About a half of nightmare sufferers who were taught lucid dreaming with the intention technique had lucid dreams with-
in one to 3 months (Spoormaker & van Den Bout, 2006; Spoormaker et al., 2003; Zadra & Pihl, 1997). The other study showed
that intention technique can be successfully used for lucid dream induction; however, it seems to be somewhat less effective
than reflection technique and similarly effective as autosuggestion (Schlag-Gies, 1992).
3.4.4. Autosuggestion
In autosuggestion technique a person suggests to himself or herself to have a lucid dream during the night while being in
a relaxed stated before falling asleep (Tholey, 1983). Only two studies empirically explored autosuggestion technique (Lev-
itan, 1989; Schlag-Gies, 1992), with an average quality score of 13.0. The findings regarding effectiveness of this technique
are inhomogeneous: While in one study autosuggestion technique seemed to increase the number of lucid dreams (Schlag-
Gies, 1992), in the other study no such effect was found (Levitan, 1989). Autosuggestion appears to be less effective than
reflection/reality testing, but similarly effective as intention technique (Schlag-Gies, 1992). There are some indications that
autosuggestion might be slightly more useful for frequent lucid dreamers, who have one or more lucid dreams per month