Consciousness and Meta-Consciousness During Sleep☆

Consciousness and Meta-Consciousness During Sleep☆

C H A P T E R 19 Consciousness and Meta-Consciousness During Sleep☆ Benjamin Baird*, Daniel Erlacher†, Michael Czisch‡, Victor I. Spoormaker‡, Martin...

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19 Consciousness and Meta-Consciousness During Sleep☆ Benjamin Baird*, Daniel Erlacher†, Michael Czisch‡, Victor I. Spoormaker‡, Martin Dresler§ *Department of Psychiatry, Wisconsin Institute for Sleep and Consciousness, University of Wisconsin-Madison, Madison, WI, United States †Max Planck Institute of Psychiatry, Munich, Germany ‡Institute of Sport Science, University of Bern, Bern, Switzerland §Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands

I CONSCIOUSNESS DURING SLEEP Conscious experience varies strikingly across the sleepwake cycle. During wakefulness, humans are alert; aware of external and internal stimuli; able to reflect on their perceptions, emotions, and thoughts; and capable to volitionally act according to their intentions. Most of these properties fade during the process of falling asleep; however, consciousness reappears in an altered form during dreaming. Conscious experience during sleep can take many different forms, from abstract thought fragments, to emotions and sensory imagery, to fully immersive vasomotor hallucinations with a complex interactive dream plot (Nir & Tononi, 2010; Windt, 2010, 2015). Soon after the discovery of rapid eye movement (REM) sleep by Aserinky and Kleitman in the 1950s, it was assumed that the increased brain activation during REM explained the presence of dreaming (Antrobus & Antrobus, 1967; Dement & Wolpert, 1958). However, subsequent research has found that, although the more vivid, narratively structured dreams tend to be most closely associated with REM sleep, there is a double dissociation between dreaming and REM sleep (Nir & Tononi, 2010). For example, forebrain lesions can abolish reports of dreaming while leaving REM sleep intact (Solms, 2000), and conversely, dreaming can also occur during NREM sleep (Fagioli, 2002). Indeed, recent research using “serial awakening” paradigms, in which

participants are woken up at pseudorandom intervals throughout the night, has shown that individuals report dreams or related forms of sleep mentation in not only approximately 95% of REM sleep awakenings but also approximately 70% of awakenings from NREM sleep (Siclari et al., 2017; Siclari, LaRocque, Postle, & Tononi, 2013; Stickgold, Malia, Fosse, & Hobson, 2001). In general, NREM dreams tend to be less emotional and visually vivid, as well as more thought-like, and memory for the specific details of NREM sleep mentation is often impaired (Cavallero, Cicogna, Natale, Occhionero, & Zito, 1992; Hobson, Pace-Schott, & Stickgold, 2000). While dreams are often characterized by rich experiences of perception and emotion, they also typically show many cognitive peculiarities, such as irrational thought, diminished volition, and a complete lack of insight into the true state of mind even in the face of bizarre occurrences. In this regard, dreaming has been suggested to resemble the psychosis of mental illnesses such as schizophrenia, characterized by hallucinations, loosening of associations, and a loss of self-reflective capacity (Dresler et al., 2015; Hobson, 2004). In contrast, the phenomenon of lucid dreaming is characterized by the reappearance of many wake-like cognitive capabilities (Windt & Metzinger, 2007). Furthermore, in contrast to nonlucid dreams, which occur throughout sleep, lucid dreams tend to occur almost exclusively in REM sleep (LaBerge, Levitan, & Dement, 1986; LaBerge, Nagel, Dement, & Zarcone, 1981).

Parts of this chapter were adapted from: Dresler, M., Erlacher, D., Czisch, M., & Spoormaker, VI. (2016). Lucid dreaming. In M. Kryger, T. Roth, W. Dement (Eds.), Principles and practice of sleep medicine (pp. 539–545). Amsterdam: Elsevier.

Handbook of Sleep Research, Volume 30 ISSN: 1569-7339


© 2019 Elsevier B.V. All rights reserved.



II META-CONSCIOUSNESS DURING SLEEP: LUCID DREAMING Lucid dreaming is minimally defined by the criterion that one is aware of the fact that one is dreaming while continuing to dream (LaBerge, Nagel, Dement, et al., 1981). From the first-person perspective, the onset of lucidity appears as a major shift in consciousness during sleep, though theoretical work is ongoing on how best to characterize this state and relate it to models of consciousness (Noreika, Windt, Lenggenhager, & Karim, 2010; Windt, 2015; Windt & Metzinger, 2007). In addition to the metacognitive awareness of the state of consciousness, which is the defining feature of the state, during lucid dreams, episodic memory (including memory of one’s waking life) is also typically restored and an ability to direct one’s attention and actions volitionally (Dresler et al., 2014). Moreover, lucid dreaming is not an all-or-nothing phenomenon, but can occur in different degrees across these cognitive dimensions (Kahan & LaBerge, 1994; Tyson, Ogilvie, & Hunt, 1984). As will be discussed below, all of these features, including metacognition, autobiographical memory and volitional control, have been linked to self-related processing, suggesting that lucid dreaming may be a valuable model for exploring the neurobiological factors that contribute to the unique form of selfconsciousness in humans (Windt & Metzinger, 2007). Despite this wake-like cognitive capability, lucid REM sleep comprises all physiologically defining markers of REM sleep according to standard sleep scoring criteria (LaBerge, Nagel, Dement, et al., 1981), and individuals in this state continue to experience full immersion in a dream world characterized by complex visuomotor hallucinations that often appear strikingly realistic (Windt, 2010). Despite having been described in both European and Asian cultures since antiquity, lucid dreaming faced considerable skepticism from both scientists and philosophers. However, this began to change in the late 1970s, when the first systematic validation of lucid dreaming as an objectively verifiable phenomenon occurring

during REM sleep was achieved. Building on research that showed that movements of the sleeper’s eyes during REM sleep sometimes corresponded to reported patterns of the directions of gaze within dreams (e.g., Dement & Wolpert, 1958), lucid dreamers were asked to move their eyes in a distinct, preagreed upon sequence (e.g., fullscale up-down or left-right movements) as soon as they became lucid (LaBerge, Nagel, Dement, et al., 1981). Subsequent research employed a slightly more sophisticated eye signal involving a full-scale left-right-left-right (referred to as “LRLR”) eye movement (for replications and extensions, see, e.g., Erlacher, Schredl, & LaBerge, 2003; LaBerge & Dement, 1982; LaBerge, Nagel, Taylor, Dement, & Zarcone Jr, 1981; for recent implementations, see, e.g., Dodet, Chavez, Leu-Semenescu, Golmard, & Arnulf, 2014; Dresler et al., 2011, 2012; Oudiette et al., 2018; Voss, Holzmann, Tuin, & Hobson, 2009). Through this technique, which has become the gold standard for studying lucid dreaming in the sleep laboratory, lucid dream reports could be objectively verified by eye movement patterns, as recorded in the electrooculogram with concurrent sleep polysomnography (see Fig. 19.1 for a schematic illustration of the eye-signaling paradigm). As can be seen in the figure, the LRLR signal is readily discernable in the raw horizontal electrooculogram (EOG), which exhibits a distinctive sinusoidal shape containing four consecutive large-scale eye movements of higher amplitude compared with typical REMs. Lucid dreams are validated in this method through the convergence between phenomenological reports (obtained after awakening) of becoming lucid and making the eye movement signals while dreaming, and the objective eye movement signals recorded in the EOG with concurrent EEG/polysomnography evidence of REM sleep. Thus, while the highly distinctive shape of these signals ensures that they are not confused for ordinary REMs, further confirmation of LRLR eye signals is provided through the convergence between the objective measurement and participants’ subsequent report of executing the intentional eye movements.

FIG. 19.1

Schematic of the lucid REM sleep eye movement signaling paradigm. Example of left-right left-right (LRLR) eye movement signal during polysomnographcally verified lucid REM sleep. Participants are instructed to signal when they realize they are dreaming by rapidly looking all the way to the left (as if looking at their ear) then all the way to the right, then all the way to the left, then all the way to the right (LRLR), and then finally back to center without pausing. The LRLR signal is readily discernable in the raw horizontal electrooculogram (HEOG), which exhibits a distinctive sinusoidal shape containing four consecutive large-scale eye movements of higher amplitude compared with typical REMs. Note the high-frequency, low-amplitude electroencephalogram (EEG) and minimal electromyogram (EMG) amplitude, due to muscle atony characteristic of rapid eye movement (REM) sleep (left) compared with wakefulness (right). PART C. REM SLEEP AND DREAMING


This method provides a way of contrasting lucid REM sleep to baseline nonlucid REM sleep with precise markers, thus constituting an objective and reliable paradigm for investigating the neurobiology of lucid dreaming. Furthermore, not only can lucid dreamers signal to indicate that they are aware that they are dreaming, but also they can make eye movement signals to timestamp the start and end of experimental tasks (LaBerge, 1990). By providing objective temporal markers, which can be localized in polysomnographic sleep recordings, this technique opened up a new method for studying the psychophysiology of REM sleep, allowing, for example, investigations into neural correlates of dreamed behaviors, such as singing, counting, and motor behavior, and comparisons of the passage of time as experienced during dreaming compared with waking (Dresler et al., 2011; Erlacher, Sch€ adlich, Stumbrys, & Schredl, 2014; Erlacher & Schredl, 2008; LaBerge, 1990). Psychophysiological studies of REM sleep have traditionally employed a “shot-in-the-dark” approach, which relies on collecting large numbers of recordings and extracting small subsets of data in which the content of interest appears by chance. Furthermore, this approach only has access to dream reports given by subjects after awakening, making precise correlations of physiological measurements and reports of a challenge. Thus, while this approach has been used successfully to study physiological correlates of conscious experiences during sleep (e.g., Perogamvros et al., 2017; Siclari et al., 2017), it has some significant limitations. In contrast, in the lucid dreaming experimental paradigm, dreamers can conduct specific tasks within REM sleep dreams and time-stamp the onset and offset of particular content or actions with eye movement signals. This methodology therefore offers a way to obtain more precise correlations between conscious experiences and physiological measurements during sleep (Dresler et al., 2011; LaBerge, 1990; LaBerge, Greenleaf, & Kedzierski, 1983). Despite the strengths of this paradigm, the infrequency with which most people spontaneously experience lucid dreams remains a challenge to observing them under laboratory conditions and collecting datasets with large sample sizes. Accordingly, a main target of research is to develop methods for the reliable induction of lucid dreams.

III NEUROBIOLOGY OF LUCID AND NON-LUCID DREAMING As noted above, while dreamlike mental activity can be observed during all sleep stages, REM sleep dreams are particularly vivid and intense. The specific phenomenal characteristics of REM sleep dreaming have been associated with neural activation patterns observed during this state. For example, higher visual areas show strong metabolic activity during REM sleep (Braun et al., 1998),


which is in line with the visuospatial hallucinations that are the hallmark of REM sleep dreaming (Windt, 2010). The amygdala, parahippocampal cortex, medial prefrontal cortex, and anterior cingulate cortex also show increased activity during REM sleep (Braun et al., 1997; Maquet et al., 1996). These brain areas have all been implicated in emotional processing, mirroring the intense emotions often experienced in dreams. In contrast, areas of the prefrontal cortex, including the dorsolateral prefrontal cortex and frontal pole, and parietal areas, including the inferior parietal lobule and precuneus, show low metabolic rates during REM sleep (Braun et al., 1997; Maquet et al., 1996). Hypoactivity of these regions, coupled with preserved or increased activity in limbic/paralimbic structures and extrastriate cortices, has been postulated to facilitate a mode of brain function conducive to hallucinatory dream mentation but diminished higher-order consciousness/selfawareness (Hobson, 1999; Maquet, 2000). In particular, prefrontal deactivations have been postulated to underlie the cognitive deficiencies typical of ordinary dreaming, such as impaired critical thinking, diminished metacognitive ability, and restricted volitional control (Hobson & Pace-Schott, 2002). While lucid REM sleep dreaming is characterized by all EEG features of REM sleep, according to the classical Kales and Rechtschaffen (1968) or new American Academy of Sleep Medicine (AASM) (Iber, AncoliIsrael, Chesson, & Quan, 2007) sleep stage scoring, lucid dreams are associated with periods of increased physiological activation and autonomic arousal during REM sleep, such as increased eye movement density, heart rate, and respiration rate (LaBerge, 1990; LaBerge et al., 1986; LaBerge, Nagel, Taylor, et al., 1981). In addition to physiological markers of phasic activity, lucid REM sleep has been associated with h-reflex suppression (Brylowski, Levitan, & LaBerge, 1989). Together, these results indicate that lucid dreams tend to occur in intensified and highly activated periods of REM sleep, as opposed to, for example, a state that is intermediate between waking and sleep. Whether lucid dreaming is associated with regional changes in brain activity, connectivity, or changes in specific neural frequencies at the cortical level remains an open question that is the focus of ongoing research. EEG studies on lucid dreaming have intermittently appeared since the 1970s but have suffered from interpretive issues and low statistical power, resulting in considerable discrepancies among findings. Some of the first EEG studies observed higher alpha activity during lucid REM sleep (Ogilvie, Hunt, Tyson, Lucescu, & Jeakins, 1982; Tyson et al., 1984), but these results were not replicated in follow-up research (LaBerge, 1988; Ogilvie, Vieira, & Small, 1991). Other studies observed increased beta-1 activity (13–19 Hz) over parietal regions (Holzinger, LaBerge, & Levitan, 2006) or decreased delta




activity over frontocentral regions during lucid REM sleep (Dodet et al., 2014), but these results have not yet been replicated. A recent study found that lucid REM sleep was associated with increased gamma-band (40 Hz) EEG power in frontolateral scalp regions (Voss et al., 2009). However, scalp measurements of cortical gamma-band EEG are compromised by electromyogenic artifacts, particularly from ocular muscle activity associated with saccades and microsaccades (e.g., Keren, Yuval-Greenberg, & Deouell, 2010; Yuval-Greenberg, Tomer, Keren, Nelken, & Deouell, 2008). Thus, whether these findings reflect cortical or myogenic activity remains an open question, particularly in light of the fact that lucid REM sleep is associated with increased eye movement density (see LaBerge, 2010 for discussion). Several years ago, the first fMRI study of lucid REM sleep was published (Dresler et al., 2012), although only one participant was able to achieve lucidity inside the MRI scanner, rendering the study a case report. Using a combined fMRI/EEG approach, the study found activations in a network of cortical regions including the dorsolateral and anterior prefrontal cortex during lucid as compared with nonlucid REM sleep (Fig. 19.2; Dresler et al., 2012). Notably, a recent anatomical analysis found increased gray matter volume in the frontopolar cortex of individuals with higher scores on a scale assessing the frequency of lucid dreams and/or dream content hypothesized to be related to lucidity (Filevich, Dresler, Brick, & K€ uhn, 2015). Thus, both of these studies converge in suggesting a role of frontopolar cortex in lucid dreaming, a region that has been linked to metacognitive processes in an extensive literature. For example, research has found that the frontal pole is related to the processing of internal states, such as the evaluation of one’s own thoughts and feelings (Christoff, Ream, Geddes, & Gabrieli, 2003; McCaig, Dixon, Keramatian, Liu, & Christoff, 2011), metacognitive ability (Baird, Smallwood, Gorgolewski, & Margulies, 2013; Fleming, Weil, Nagy, Dolan, & Rees, 2010), and supervisory modes (Burgess, Dumontheil, & Gilbert, 2007), functions that are typically impaired in dreaming, but reinstated in lucid dreaming. Furthermore,

patients with damage to this region frequently display metacognitive deficits, such as an inability to monitor disease symptoms or accurately appraise their cognitive functioning (e.g., Joseph, 1999; Schmitz, Rowley, Kawahara, & Johnson, 2006), akin to the lack of metacognitive insight into the state of consciousness characteristic of nonlucid REM sleep dreams (Dresler et al., 2015). Strong activation increases during lucid dreaming were also observed in the inferior/middle temporal gyrus and the bilateral precuneus and inferior parietal lobule, including the angular gyrus (Dresler et al., 2012). The precuneus has been implicated in selfreferential processing, episodic memory, first-personperspective taking, and the experience of agency (Cavanna & Trimble, 2006). This is in line with the notion mentioned above that lucidity during dreams provides increased availability of self-related information, leading to a much higher degree of coherence and stability of the self-model during lucid dreaming (Metzinger, 2003). Furthermore, a meta-analysis found that these temporoparietal regions, in particular the angular gyrus and middle temporal gyrus, show the densest concentration of activation foci in studies of language and semantic processes (Binder, Desai, Graves, & Conant, 2009). Taken together, one hypothesis is that the coactivation of the anterior prefrontal cortex subserving metacognition and temporoparietal heteromodal linguistic/conceptual systems allows the achievement of meta-awareness and semantic understanding of one’s current state of consciousness (i.e., “I am dreaming!”). Activation increases during lucid dreaming were also found in some occipital and inferiormedial temporal regions (Dresler et al., 2012). These cortical areas are part of the ventral stream of visual processing, which is involved in conscious visual perception (Rees et al., 2002). While these activations may seem puzzling at first, given that nonlucid dreams are also characterized by vivid dream imagery, they are in line with reports that lucid dreams are often associated with higher visual clarity of the dream scenery (e.g., Green, 1968). Given the link between lucid dreaming and metacognition, it has been speculated that lucid dreaming is linked



FIG. 19.2

fMRI BOLD activations during lucid dreaming. During lucid REM sleep, dorsolateral prefrontal and frontopolar regions including the inferior, middle and superior frontal gyri, parietal regions including the precuneus, inferior parietal lobule, and temporal regions including the inferior and middle temporal gyri activated strongly as compared with nonlucid REM sleep. Republished with permission of the American Academy of Sleep Medicine from Dresler, M., Wehrle, R., Spoormaker, V. I., Koch, S. P., Holsboer, F., Steiger, A., et al. (2012). Neural correlates of dream lucidity obtained from contrasting lucid versus non-lucid REM sleep: a combined EEG/fMRI case study. Sleep, 35(7), 1017–1020, permission conveyed through Copyright Clearance Center, Inc. (Permission pending).



to neural systems that regulate executive control processes, in particular the frontoparietal control network (FPCN) (Dresler et al., 2015; Spoormaker, Czisch, & Dresler, 2010). Indeed, the brain regions found to increase blood oxygen-level-dependent (BOLD) signal during lucid dreaming show overlap with key regions of the FPCN. The FPCN is a large-scale brain network that is interconnected with both the default mode network (DMN), which is predominately linked to internal aspects of cognition, such as autobiographical memory (Andrews-Hanna, Saxe, & Yarkoni, 2014; Spreng, Mar, & Kim, 2009), spontaneous thought (Christoff, Irving, Fox, Spreng, & Andrews-Hanna, 2016; Mason et al., 2007), self-referential processing (Denny, Kober, Wager, & Ochsner, 2012), and the dorsal attention network (DAN), which is involved in visuospatial perceptual attention (Corbetta & Shulman, 2002; Vincent, Kahn, Snyder, Raichle, & Buckner, 2008). Being spatially interposed between these two systems, the FPCN is postulated to integrate information coming from the opposing DMN and DAN systems by switching between competing internally and externally directed processes (Vincent et al., 2008). Phenomenologically, this might be interpreted as a monitoring of and control over mind-wandering and perception by metacognitive processes (e.g., Schooler et al., 2011; Smallwood, Brown, Baird, & Schooler, 2011). Due to this role as a kind of meta-network, the frontoparietal control system might be seen as an ideal candidate subserving metacognitive aspects of consciousness that are the hallmark of lucid dreaming (Spoormaker et al., 2010). However, to date, no study has evaluated changes in brain connectivity during lucid dreaming or quantitatively assessed the overlap between BOLD signal changes in lucid REM sleep and FPCN systems or subsystems or other large-scale brain networks. Future group-level neuroimaging studies of lucid REM sleep will be important to understand how the patterns of neural activation during lucid dreams map onto activity and connectivity in these networks.

IV LUCID DREAMING AS HIGHERORDER CONSCIOUSNESS The contrast between lucid and nonlucid dreaming has been suggested to mirror the conceptual contrast between basal (primary) and higher-order (secondary) aspects of consciousness (Dresler et al., 2009; Hobson, 2009). Specifically, nonlucid dreams are restricted to the immediate scene and exhibit reduced short- and long-term memory function and a reduced ability to engage in behavioral control and planning, frequently referred to as the single-mindedness of dreaming (Rechtschaffen, 1978). Thus, while dreams are rich in primary consciousness of perception and emotion, consciousness during dreams


typically lacks important aspects of what has been referred to as secondary or higher-order consciousness, which enables a creature to escape the “remembered present” of primary consciousness and to be conscious of being conscious (Edelman, 1989, 2004). In contrast, gaining lucidity during dreaming sleep involves a shift to higher-order consciousness, which involves the ability to be explicitly aware of oneself and one’s state (Windt & Metzinger, 2007). The distinction between primary and higher-order consciousness has been suggested to depend on the linguistic abilities that distinguish humans from other species (Edelman, 1989), and the neuroimaging correlates of lucid dreaming, indeed, overlap considerably with those brain regions that show considerable expansion in humans compared with nonhuman primates (Dresler et al., 2014). While language processes and conceptual thought also occur during nonlucid dreams (Kahan & LaBerge, 2011; Kahan, LaBerge, Levitan, & Zimbardo, 1997), they are nevertheless linked to the remembered present. Furthermore, most of the time, one is still unable to engage in the type of thought that allows one to conceptualize oneself in relation to the current state of consciousness one is in, unless one becomes lucid (Windt & Metzinger, 2007). Since nonlucid dreams also include other types of metacognitive thoughts and since meta-awareness is frequently absent during daydreaming and other phases of wakefulness (Schooler et al., 2011; Smallwood, McSpadden, & Schooler, 2007), it has been argued that metacognitive activity differs only quantitatively, but not qualitatively, between dreaming and waking consciousness (e.g., Kahan et al., 1997). However, this absence of metaawareness is only a “local,” not a global, feature of such phases: It is hardly imaginable, at least for nonpathological cases, that the daydreaming individual misinterprets the daydream for reality once paying attention to his or her current state; for the dreaming state, in contrast, this is typical (Tyson et al., 1984). The study of lucid dreaming may be critical to understanding the neural correlates of higher-order consciousness, given that there is no major shift in vigilance state between nonlucid and lucid REM sleep, in contrast to other comparisons between different states of consciousness, such as coma-wake, anesthesia-wake, or sleep-wake comparisons. When compared with wakefulness, pathological or pharmaceutically induced loss of consciousness also reduces the brain’s basal metabolism, as does deep sleep. Lucid dreaming therefore provides the only phenomenon we know of that can contrast primary with higher-order consciousness within the same arousal level and overall behavioral state, allowing for the comparison of cerebral activity by means of EEG, PET, or fMRI without confounding differences in overall activity level (Spoormaker et al., 2010). Research on lucid REM sleep is, therefore, uniquely placed to shed light on the neural correlates of higher-order consciousness.




V INDUCTION OF LUCID DREAMING For most individuals, spontaneous lucid dreams occur infrequently, and for many people, they may occur only a few times in their lifetime or never (Saunders, Roe, Smith, & Clegg, 2016). However, there is considerable variance in lucid dreaming frequency. Preliminary data suggest that approximately 20% of people have lucid dreams on a monthly basis, while about 1% have lucid dreams several times a week or more, although the prevalence of lucid dreaming is understudied (Schredl & Erlacher, 2011; Snyder & Gackenbach, 1988). More research is needed to reliably quantify the prevalence of lucid dream frequency, and current estimates will likely need to be revised as additional data are acquired. Additionally, some evidence suggests that age-related differences in lucid dreaming prevalence exist, with young children and adolescents reporting lucid dreams more frequently than adults, but again, more research is needed on the prevalence of lucid dreaming across age groups and various social dimensions (Voss, Frenzel, Koppehele-Gossel, & Hobson, 2012). Lucid dreams are often reported as spontaneously arising from nightmares or peculiarities within a dream, which may be so odd, surprising, or frightening that it causes one to realize that the only explanation for the experience is that it is a dream. In general, lucid dreams can be initiated either during an ongoing dream (e.g., as above, by noticing a cue or anomaly that indicates one is dreaming) or, less commonly, by maintaining awareness when transitioning from the waking state directly into (dreaming) sleep. The former and latter varieties are respectively referred to as dream-initiated lucid dreams (DILDs) and wake-initiated lucid dreams (WILDs) (LaBerge et al., 1986; Stumbrys, Erlacher, Sch€adlich, & Schredl, 2012). Evidence suggests that lucid dreaming is a learnable skill (LaBerge, 1980a) that can be developed by training with various induction strategies (Aspy, Delfabbro, Proeve, & Mohr, 2017; LaBerge, 1980a). A recent review classified lucid dream induction strategies into three broad categories: cognitive techniques, external stimulation, and miscellaneous (Stumbrys et al., 2012). The first category encompasses techniques such as metacognitive monitoring and prospective memory to develop the mental set for being able to recognize that one is dreaming while dreaming. The second category includes techniques for applying an external stimulus to a sleeping person, with the goal that this stimulus is incorporated into an ongoing dream as a cue to help them recognize that they are dreaming without causing awakening. The third category includes an amalgamation of other techniques, such as modified sleep schedules or supplements (discussed below), which have been studied as potential methods to increase lucid dream frequency.

However, it is important to note that external stimulation or other techniques such as modified sleep schedules or supplements are not likely to be effective for inducing lucid dreams without first developing the appropriate mental set. Thus, these latter two categories may best be thought of as techniques that build upon and enhance cognitive training techniques. Additionally, it is worth noting that, although this threefold classification scheme served to organize research studies for the purposes of this specific review paper, it may not be the most meaningful way to categorize induction strategies for lucid dreaming in general terms. As our understanding of lucid dream induction grows, we will likely need to devise new classification schemes that aim to optimize both coherence and parsimony. One effective cognitive technique for training to have lucid dreams is through the use of prospective memory (remembering to perform a planned action in the future). This was discovered by LaBerge (1980b), who developed one of the first reliable cognitive techniques for lucid dream induction, referred to as the mnemonic induction of lucid dreams (MILD), which is based on a prospective memory technique. For instance, LaBerge (1980a) found that MILD was more effective than autosuggestion for inducing signal-verified lucid dreams in the sleep laboratory. Follow-up studies have provided further documentation that MILD can effectively increase lucid dream frequency (e.g., Aspy et al., 2017; Stumbrys et al., 2012). Subsequent research found that the use of induction devices that apply light stimuli on the sleeper’s closed eyes during REM sleep (which are incorporated into ongoing dreams as flashing lights within the dream, providing a memory cue to prompt lucidity) can further increase the likelihood of having a lucid dream when combined with the MILD technique (LaBerge & Levitan, 1995; LaBerge, Levitan, Rich, & Dement, 1988). Furthermore, as lucid dreaming frequency was reported by several authors to increase following a period of wakefulness during the night (e.g., Garfield, 1975; Sparrow, 1987), studies also tested whether combining MILD with longer periods of sleep interruption would further increase the frequency of lucid dreams (e.g., LaBerge, Phillips, & Levitan, 1994). (Note that sleep interruption, sometimes also referred to as “wake back to bed,” is part of the MILD technique (LaBerge, 1980a) but can be of a relatively short duration when practicing MILD.) Sleep interruption late in the sleep cycle for 30–60 minutes, when compared with 10 minutes, followed by returning to sleep was found to be an effective means for having lucid dreams in the ensuing sleep period, with no difference between the 30 and 60 minute conditions (LaBerge et al., 1994). A recent study found that, on average, individuals who practiced a combination of MILD and sleep interruption nightly were able to have approximately one lucid dream per week after 2 weeks (Aspy et al., 2017).



Research has also explored whether it is possible to induce lucid dreams through pharmacology. Given that lucid dreams tend to occur during periods of increased physiological activation during REM sleep, together with clear evidence that REM sleep is modulated by acetylcholine (ACh) (Baghdoyan, 1997; Gillin et al., 1985; Velazquez-Moctezuma, Shalauta, Gillin, & Shiromani, 1991), agents acting on the cholinergic system have received particular interest. In an initial pilot study, LaBerge (2001) evaluated the impact of either 0 (placebo), 5, or 10 mg of donepezil (Aricept), an acetylcholinesterase inhibitor (AChEI), administered before sleep in a counterbalanced order on three nights in a small group of highly experienced lucid dreamers. Nine of the 10 participants (90%) reported at least one lucid dream on donepezil, while only one participant reported a lucid dream on the placebo. This work was recently followed up with a double-blind, placebo-controlled study (LaBerge, LaMarca, & Baird, 2018), which tested the administration of galantamine—an AChEI that is readily accessible and fast acting and has a mild side-effect profile—after approximately the third REM period in a large group of individuals (N ¼ 121) with an interest in lucid dreaming. Participants received three doses of galantamine (0 mg ¼ placebo, 4 mg, and 8 mg) in a counterbalanced order on three consecutive nights during a period of sleep interruption during which they also practiced the MILD technique (LaBerge, 1980a; LaBerge & Rheingold, 1990). Galantamine was found to substantially and significantly increase the frequency of lucid dreaming in a doserelated manner: increased incidence of lucid dreaming was observed for both 4 mg (27%) and 8 mg (42%) doses compared with 14% for the active placebo procedure (including sleep interruption and MILD). In contrast to the positive findings for AChEIs, a double-blind randomized placebo-controlled withinsubject study found no significant effect of 1200 mg of the ACh precursor L-alpha glycerylphosphorylcholine (α-GPC) on the frequency of lucid dreams in 33 participants with varying degrees of lucid dreaming experience (Kern, Appel, Schredl, & Pipa, 2017). However, no training in mental set appears to have been provided to participants in this study. It therefore remains unclear whether the lack of effect is attributable to differences in the neurobiological action of α-GPC and AChEIs or whether this study merely reinforces the point discussed above that training in at least the minimal mental set for lucid dream induction is needed for pharmacological interventions to be used effectively for lucid dream induction. It is important to keep in mind that the pharmacological studies conducted so far have several limitations. Perhaps most importantly, none of the experiments were conducted in a sleep laboratory, and there was therefore no physiological validation of lucid dreams with the


eye-signaling method or electrophysiological measurements of the periods of REM sleep when participants became lucid. Thus, it will be important to follow up these results with sleep laboratory studies to provide physiological validation of lucid dreams and to study the physiological effects of AChEIs on the brain conducive to lucid dreams. Overall, however, these data provide strong, initial evidence that cholinergic enhancement with AChEIs facilitates a brain state favorable to lucid dreams. The mechanism by which AChEIs facilitates lucid dreaming also requires further research and could occur through its primary target on the cholinergic system or indirectly through auxiliary effects on norepinephrine and/or dopamine caused by AChEIs (Cuadra, Summers, & Giacobini, 1994; Giacobini, Zhu, Williams, & Sherman, 1996). Finally, several recent studies have attempted to induce lucid dreams through noninvasive brain stimulation methods. One study tested whether transcranial direct current stimulation (tDCS) applied to the frontal cortex would increase lucid dreaming (Stumbrys, Erlacher, & Schredl, 2013). While tDCS resulted in a small numerical increase in self-ratings of the unreality of dream objects as assessed by a questionnaire measure, it did not significantly increase the number of lucid dreams as rated by judges or the number of lucid dreams confirmed through the eye-signaling method. Another recent study tested whether applying transcranial alternating current stimulation (tACS) in the low gamma range (25 and 40 Hz) to frontal regions would induce lucid dreams (Voss et al., 2014). While the authors reported that lucid dreams could be induced with a high success rate (58% with 25 Hz stimulation and 77% with 40 Hz stimulation), there are concerns about how lucid dreams were defined in the study. Specifically, lucid dreams were not dreams that participants self-reported as lucid nor dreams that were objectively verified to be lucid through the eye movement signaling method. Instead, dreams classified as lucid were based on scores to questionnaire items, which, in the 25 and 40 Hz stimulation conditions, were at the level of self-categorized nonlucid dreams, according to the norming report of the questionnaire (Voss, Schermelleh-Engel, Windt, Frenzel, & Hobson, 2013). In summary, studies examining the induction of lucid dreams with electric brain stimulation have observed some intriguing effects on dream cognition, but it remains unclear whether brain stimulation techniques could be effective for inducing lucid dreams. If such a technique exists, it remains to be discovered. We believe this is a particularly fruitful and interesting direction for upcoming work, and future studies should consider stimulating a wider number of brain areas and using different types of stimulation, as well as combining brain stimulation with cognitive techniques for lucid dream induction.




VI CLINICAL APPLICATIONS OF LUCID DREAMING Lucid dreaming has been suggested as a therapeutic approach for several clinical conditions, including nightmares, post-traumatic stress disorder (PTSD), and schizophrenia. Lucid dreaming frequency is moderately correlated with nightmare frequency (Schredl & Erlacher, 2004), and people with frequent lucid dreams have incidentally reported that their nightmares have triggered lucidity. Theoretically, dream lucidity seems a logical solution to one of the main problems of nightmares, which involves a real emotional response to a nonexistent threat (LaBerge & Rheingold, 1990). Becoming lucid in a nightmare should therefore take the sting out of it, and once a person realizes that the threat is not real, the threat should (theoretically) disappear, along with the associated emotional response. Neurocognitive models of disturbed dreaming emphasize a hyperresponsivity of the amygdala in nightmare generation, coupled with a failure of medial prefrontal regions to dampen this activation (Levin & Nielsen, 2007). Lateral prefrontal regions are capable of influencing amygdala function through connections to the medial prefrontal cortex (Delgado, Nearing, LeDoux, & Phelps, 2008; see also De Gennaro et al., 2016). The preliminary data on the neurobiology of lucid dreaming showing increased prefrontal activation therefore fit well with potential therapeutic effects of lucid dreaming on nightmares (Dresler et al., 2012). But does this work in practice? Patients with narcolepsy who frequently suffer from nightmares report that dream lucidity, indeed, provides relief during nightmares (Rak, Beitinger, Steiger, Schredl, & Dresler, 2015), and a few case studies (Zadra & Pihl, 1997) and one small, controlled pilot study (Spoormaker & Van Den Bout, 2006) have indicated that lucid dreaming therapy was effective in reducing nightmare frequency. In the controlled pilot study, lucid dreaming therapy was superior to a waiting list control group with respect to nightmare frequency, but did not have an effect on secondary anxiety and sleep measures. A larger online self-help study did not find any additional effect of lucid dreaming therapy as an add-on to other effective cognitive behavioral techniques, such as imagery rehearsal therapy (Lancee, Van Den Bout, & Spoormaker, 2010), although low power and high dropout rates (>50%) limited the scope of the conclusions. Lucid dreaming therapy also elicited some unexpected effects, such as people with frequent nightmares reporting becoming lucid but unable to change the nightmare, perhaps due to strong top-down expectations about the storyline (Zadra & Pihl, 1997). Moreover, realizing that one is dreaming does not automatically erase the threat and accompanying intense emotions, and it takes training to learn how to effectively respond to these situations

(e.g., LaBerge & Rheingold, 1990). As in all lucid dreams, lucidity in nightmares is not an all-or-none phenomenon, and a prelucid or half-lucid stage may not suffice to fully tackle a seemingly real threat. In addition to nightmares, lucid dreaming has also been suggested as a therapeutic strategy in the treatment of schizophrenia (Dresler et al., 2015; Voss et al., 2014). The idea that dreaming can serve as a model for psychosis has a long but notoriously speculative and controversial tradition. One of the most interesting aspects of the dreaming-psychosis model is the issue of insight: between 50% and 80% of patients diagnosed with schizophrenia have poor insight into the presence of their disorder (Lincoln, L€ ullmann, & Rief, 2007), probably due to ineffective self-reflection processes (Henriksen & Parnas, 2013). Since such deficits are thought to lead to more relapses and rehospitalizations, as well as poorer therapy success in general (Mintz, Dobson, & Romney, 2003), the concept of insight is becoming an increasingly important area in schizophrenia research (Baier, 2010). With regard to the dreaming component of the model, the lack of insight into the current state characterizes almost all dream experiences—with the obvious exception of lucid dreaming. This suggests that dream lucidity may be a good model for insight in the dreaming-psychosis hypothesis. Interestingly, historical approaches to psychosis used the term “lucidity” to denote the awareness of the patient into his or her illness (Berrios & Markova, 1998). While the specific composition and the multiple facets of insight in psychosis is still under discussion (David, Bedford, Wiffen, & Gilleen, 2012; Quee et al., 2010), two crucial dimensions are classically considered to be (a) the recognition that one has a mental illness and (b) the ability to recognize unusual mental events (delusions and hallucinations) as pathological (David, 1990). Hence, in the dreaming-psychosis model, lucidity during dreaming represents what patients during psychosis lack: full insight into the delusional nature of the current state of consciousness during that state. Neurobiologically, prefrontal, medial parietal, and inferior temporal cortical regions that are linked to insight deficits in psychosis show striking overlap with brain regions associated with dream lucidity (Dresler et al., 2015). It has also been found that prefrontal cortex function in schizophrenia patients can be improved through cognitive training (Edwards, Barch, & Braver, 2010). Metacognitive training approaches are of particular interest, since metacognitive techniques are often part of the methods used to train to have lucid dreams, in particular the habit of frequently reflecting on the current state of consciousness (Stumbrys et al., 2012). By training patients in metacognitive monitoring strategies, it might be possible to enhance insight-related prefrontal and medial parietal functions, leading to increased insight capabilities during psychosis. Lucid dreaming as a model for the



successful treatment of psychotic symptoms might also help to develop and test new antipsychotic medication. For example, if a given pharmacological agent increases the frequency of lucid dreams in healthy individuals, it might be considered as a promising candidate to also enhance insight in psychotic patients (Dresler et al., 2015). Research on lucid dreaming therefore has the potential to transform the dreaming-psychosis model from an interesting, historical idea into a novel therapeutic approach. At the current time, these ideas remain highly speculative, but we believe that this is an area worthy of additional research. Another potential clinical application of lucid dreaming is in the treatment of phobias through exposure/desensitization therapy, akin to virtual reality exposure therapy (Parsons & Rizzo, 2008). Training in lucid dreaming might also be used as an adjunct therapy for parasomnias such as REM sleep behavior disorder (RBD), for which some patients report that learning to recognize that they are dreaming can keep them from reacting to the dream and thus executing violent or dangerous behaviors during sleep (Schenck, 2005). One last potential clinical application of research on lucid dreaming worth noting is in the development of neuroimaging-based diagnostic markers of awareness. Such measures have the potential to improve the diagnosis and monitoring of patients who are unresponsive due to traumatic injury, aphasia, motor impairment, or other physical limitations, such as tracheotomy. Neurobiological studies of lucid dreaming could play an important role in this field since, in addition to assessing a patient’s capacity for primary consciousness (i.e., if a patient can see, hear, or experience pain), an important clinical goal is to assess whether patients (who may nevertheless be unresponsive via behavioral assessment) are aware of themselves and their state. This information is critical to making appropriate therapeutic choices and in determining prognosis (Laureys, Perrin, & Bredart, 2007). Research indicates that the bedside behavioral assessment of such patients is challenging and has a high rate of misdiagnosis (over 40%, according to some studies) (Laureys, Owen, & Schiff, 2004; Schnakers et al., 2009). Accordingly, identification of a reliable brain activity marker of both primary consciousness and higherorder consciousness has the potential to improve diagnostic accuracy and provide additional means of monitoring rehabilitation for such patients.

VII NON-CLINICAL APPLICATIONS OF LUCID DREAMING Lucid dreaming not only has applications in clinical domains but also has the potential to enrich the lives of healthy people. Indeed, many lucid dreamers report that they have used lucid dreams to positively influence their


waking life (Sch€adlich & Erlacher, 2012). Two examples for which preliminary scientific data are available are creative problem-solving and practicing motor skills. Anecdotal reports on scientific discovery, inventive originality, and artistic productivity suggest that creativity can be triggered or enhanced by dreaming. Several experimental studies also suggest that REM sleep dreaming can improve creativity during the waking state (Cai, Mednick, Harrison, Kanady, & Mednick, 2009; Dresler, 2012). Theoretically, sleep has been suggested to provide an ideal state for creative incubation: the internally generated dream narrative and absence of external sensory data lead to a much more radical renunciation from unsuccessful problemsolving attempts, leading to coactivations of cognitive data that are highly remote in waking life. Furthermore, both dreaming and creativity have been characterized with primary process thinking, flat associative hierarchies, and defocused attention. In contrast to the more random flow of nonlucid dream narratives, dream lucidity allows for a more goal-oriented use of these creativity-related dream characteristics. Consistent with this, one study reported that frequent lucid dreamers are more successful in an insight-based problem-solving task (Bourke & Shaw, 2014). Surveys among lucid dreamers also suggest that lucid dreaming can be used to improve creative thinking and problem-solving (Sch€adlich & Erlacher, 2012; Stumbrys & Daniels, 2010). More research is needed to follow up these results and to further explore the potential of lucid dreaming for creativity and problem-solving. Motor practice during lucid dreaming is another potential application of lucid dreaming, which may be conceived of as a novel type of mental rehearsal in which a person uses the dream state to consciously practice specific tasks. It can be compared with mental practice, which is well established in sport theory and sport practice (Driskell, Copper, & Moran, 1994). For both mental and dream rehearsal, movements are simulated with an imagined body on a purely cognitive level, whereas the physical body remains still. One advantage that lucid dreaming has over both mental practice and modern virtual reality simulators is that lucid dreaming offers the potential for practice with all kinesthetic sensations of the dream body in an environment that is experienced with as much vividness and realism as would be encountered in waking experience. In addition, the lucid dreamer, being limited only by his or her imagination and attentional stability, has far greater potential for control over his or her own body, actions, and environment than in mental rehearsal, virtual reality environments, or waking life. In contrast to the vast amount of research on mental practice, however, empirical data on practice in lucid dreams are rather sparse. In several anecdotal reports, amateur and professional athletes indicated that they used lucid dreams to improve their waking performance in domains such as long




distance running, tennis, skating, alpine skiing, or martial arts (LaBerge & Rheingold, 1990; Sch€ adlich & Erlacher, 2018; Tholey, 1990). In a systematic questionnaire study, 840 German athletes from a variety of sports were surveyed about their experiences with lucid dreams (Erlacher, Stumbrys, & Schredl, 2012). The study found that approximately every 10th athlete who had lucid dreams (5% of the total sample) used lucid dreams to practice sports skills, with most of them having the impression that this mental practice improved their performance. Few studies have tested the effects of practice in lucid dreams experimentally. In a qualitative study, subjects performed different complex sport skills familiar to them in waking life, like skiing or gymnastics, in their lucid dreams (Tholey, 1981). Participants reported that they had no difficulties performing these sport skills in their lucid dreams and that their movements improved in both the dream and the waking state. In a quasi-experimental pre-post design study, participants were asked to practice a coin-tossing task in their lucid dreams (Erlacher & Schredl, 2010). Results showed a significant increase in hitting the target from pretest to post test for the group, which practiced the coin-tossing task in their lucid dreams, but no increase was found for the control group. More recently, these results were replicated with a different motor task (sequential finger tapping) (Stumbrys, Erlacher, & Schredl, 2016). Improvements following lucid dream practice seem to be similar or slightly lower as compared with actual physical practice and similar or slightly better to mental practice in wakefulness (Stumbrys et al., 2016). Interestingly, the efficacy of motor practice during lucid dreaming might be related on the amount of distractions during dreamed rehearsal (Sch€ adlich, Erlacher, & Schredl, 2017). While we have focused our brief discussion here on the domains of creativity and rehearsal of physical skills, as these are the areas with some preliminary data, the research to date has likely only begun to scratch the surface of the potential applications of lucid dreaming. Indeed, it is reasonable to state that we likely do not yet realize the potential of making sleep and dreaming accessible to our unique form of self-aware consciousness. For instance, in line with the brief remarks above on the potential for creativity enhancement, we have been intrigued by the potential use of lucid dreaming in the humanities and arts, such as painters and musicians who have reported using lucid dreams to compose paintings or musical scores, which they then transcribe to the palette or page upon awakening. Overall, we might therefore regard lucid dreaming as a new domain for exploration, while remaining open to the potential applications and insights we might discover. Indeed, perhaps, the largest potential of this state is that it provides a unique method to explore consciousness, which is one of the largest gaps in our scientific understanding of nature.

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