research paper topics on dreams

177 Dream Research Topics & How to Write a Research Paper on Dreams

People have dreams every night. Dreams are different – sweet dreams and nightmares, colored and colorless. However, every psychologist knows that people need to sleep. Why? Well, let us give you the right to answer this question in your research paper on dreams.

A research paper on dreams is a serious research project. That is why you cannot simply write how dreams can be interpreted or describe your dreams in the research paper on dreams. Research papers on dreams require more serious topics and approach.

Below you will find several possible ideas for research papers on dreams.

• 🔎 Dreams Research Topics
• 💤 Dreams Definition
• ✍️ How to Write about Dreams

😴 Easy Research Topics on Dreams

🛌 essay about dreams topics, 😪 topics for a research paper on sleep and dreams, ✏️ importance of sleep essay topics, 👻 nightmare essay topics.

• 📝 My Dreams Essay – Example

✅ Interesting Facts about Dreams

🔎 dreams research topics – 2024.

• The link between our dreams and emotions.
• What is the role of dreaming in creativity development?
• The gender-based patterns in dreaming experience.
• Sigmund Freud and his theory of dreams.
• The key mechanisms that underlie dreaming.
• What knowledge can you gain from your dreams?
• The impact of eating patterns on the quality of dreams.
• How do different cultures perceive and interpret dreams?
• The advantages and disadvantages of dreaming.
• How can people control their dreams?
• The role of dreams in processing emotions.
• How do bizarre and emotionally intense dreams occur?

💤 What Are Dreams?

Psychologists are sure that dreams are the result of what we wish or think about when we are awake. For example, Freud, a famous psychologist, considered that if a man did not have sexual relations for a long time, he would dream about them. If you think about someone, you may also dream about him/her. This is what you may write about in the research paper on dreams if you want to consider this aspect.

Nightmares can also be a very interesting issue to discuss in research papers on dreams. Psychologists relate nightmares to the field of “unconscious”. Very often, people forget about the stressful situations they once had. However, those situations are reflected in their minds and they can appear in dreams. You may also find other points of view on nightmares and discuss them in your research paper on dreams.

✍️ How to Write a Research Paper about Dreams

A research paper about dreams generally includes an introduction, body paragraphs, and a conclusion. First, it is crucial to choose a relevant and exciting topic to write on and decide on the type of research paper (analytical, argumentative, etc.).

Choosing a Topic

Pick a topic that corresponds to your interests and expertise. It will help you stay more motivated throughout the research process. In addition, ensure that your topic is specific, relevant, and follows the assignment instructions.

If you need help choosing a good topic for your paper, try our free research title generator .

Finding Sources

After you have found a perfect topic on dreams, it is time to look for sources for your research. You can look up information in books, similar research papers, or online sources. Communicating with professionals related to dreams , like psychologists or neurologists, is also a good idea since it is an effective method to gain new knowledge or advice.

Writing a Research Paper

The format of your research paper on dreams should consist of the following elements:

• The relation between dreaming and the role of deep-brain structures.
• Dreaming capacity to repeatedly simulate potential threatening events.
• The role of amygdala and hippocampus in the dreaming process.
• The spiritual significance of dreams in different cultures.
• Dream interpretation and its value in self-understanding.
• How does dream recall reflect social relationships?
• The positive impact of dreams on our physical health.
• Dreams and their role in predicting the future.
• The peculiarities of dreams in pregnant women.
• Why does Charcot-Wilbrand syndrome cause the loss of the ability to dream?
• The role of dreaming in developing cognitive capabilities.
• How can dreams reflect the aging process?
• The repetitive character of some dreams and their meaning.
• Why are young people more likely to dream in color?
• The benefits and cautions of lucid dreaming.
• The influence of smartphones on the content of dreams.
• Why do people forget their dreams after waking up?
• The impact of suppressing intrusive thoughts on dream content.
• What is the role of dreams in developing long-term memory?
• The key causes and types of dreams.
• The peculiarities of dreaming during the COVID-19 pandemic.
• Everything you need to know about lucid dreams.
• The role of melatonin in determining the dream content.
• What can we learn from our dreams?
• The psychotomimetic nature of dreams.
• The terrors of sleep paralysis.
• Does screen time affect people’s dreams?
• Dreams and the future of sleep technology.
• Are AI technologies capable of generating dreams?
• The hidden cost of insufficient sleep.
• How can nap breaks improve your productivity at work?
• The main facts and myths about sleep and dreams.
• How can our understanding of dreams shape our worldview?
• The link between dreams and telepathy.
• The process of dreaming in animals.
• Why do some people wake up in the middle of the night?
• The impact of mental illnesses on dream content.
• The role of dreams in art as a source of inspiration.
• How do different societies interpret dreams?
• The power of dreaming in everyday life.
• How to become a morning person: the key strategies.
• The impact of sleep time on life length.
• Ways to decode the language of sleep.
• Using cannabis as a method to cope with nightmares.
• The impact of the daily schedule on improving the quality of sleep.
• How to get a good night’s sleep in a new place?
• Methods to combat morning grogginess.
• Taking care of your sleep as one of the pillars of health.
• The use of dreams in filmmaking and book writing.
• The phenomenon of dreaming during sleep.
• The main phases of sleep in a sleep cycle.
• How is alpha activity measured during sleep?
• The use of oneirology in uncovering the dreaming process.
• Dreaming in Christianity and Islam.
• What is the connection between race and sleep disorders?
• The theory of astral projection during sleep.
• The effect of sleep on pain thresholds and sensitivity.
• The consequences of chronic daytime sleepiness.
• Why is dreaming a key part of a sleep cycle?
• The natural patterns of sleeping in children and teenagers.
• REM and non-REM sleep : the difference.
• What is biphasic sleep, and how does it work?
• The influence of dreams on musical creativity.
• The cultural significance of dream symbols.
• How do moon phases affect your sleep?
• The nature and functions of dreaming.
• The use of dream content during expressive arts therapy.
• What are the possible functions of REM sleep and dreaming?
• The value of dreaming and sleep tracking.
• The analysis of mental activity of sleep and disturbing dreams.
• How do sleep disturbances impact skin health?
• The impact of age on our circadian rhythm.
• The phenomenon of conscious control in dreams.
• How do sleep patterns change across different life stages?
• The influence of sleep quality on academic performance.
• The psychological theories of dreaming purpose.
• The disadvantages of oversleeping for adults.
• How does your body use calories while you sleep?
• Factors influencing the memory of dreams.
• What impact does alcohol have on the sleep cycle and dreaming?
• How can dreams contribute to the healing process?
• The role of sleep in underlying psychological issues.
• The benefits of daytime napping for young people.
• Why does sleep deprivation increase the risk of substance abuse?
• The use of daytime naps to increase imagination.
• The value of bedtime routine for toddlers.
• The benefits of a good night’s sleep.
• What is the role of sleeping in achieving life goals?
• Lack of sleep as a key cause of hormonal imbalance.
• The damaging effect of shift work on sleep patterns and health.
• The link between sleep and the immune system.
• What impact does a change of clocks by an hour have on public health?
• The value of sleep for children’s physical, cognitive, and emotional development.
• What would happen if you did not sleep?
• The importance of sleep for children’s development and growth.
• The connection between good mood and quality sleep.
• Why does the lack of sleep increase aggression?
• The role of sleeping in cancer prevention and treatment.
• The value of sleep for the recovery process of athletes.
• How does the quality of sleep impact metabolism?

Essay about Sleep Deprivation

• The economic impact of sleep deprivation in the workplace.
• How can sleep deprivation lead to anxiety and depression?
• The role of sleep deprivation in worsening obesity and diabetes.
• The use of sleeping pills in sleep deprivation treatment.
• How is sleep deprivation diagnosed?
• The prevalence of sleep deprivation among shift workers.
• What is the difference between sleep deprivation and insomnia?
• The key stages of sleep deprivation.
• The role of DNA in the development of sleep deprivation.
• The unique challenges in diagnosing obstructive sleep deprivation.
• How does sleep deprivation affect the human body?
• The issue of sleep deprivation in teenagers due to exams.
• The role of medications in managing sleep deprivation.
• Ways of reducing the risk of developing sleep deprivation.
• What are the key symptoms of sleep deprivation?

Why Is Sleep Important? Essay Topics

• The efficiency of sleeping in losing weight.
• How can sleep improve concentration and productivity?
• Sleep as essential component of healthy aging.
• Why can a lack of sleep be dangerous?
• Sleep satisfaction and its impact on energy level.
• How is poor sleep linked to depression?
• The impact of sleep on emotional intelligence.
• How does sleep help to repair and restore tissues?
• The role of sleeping in removing toxins from the brain.
• Why can the lack of sleep be lethal?
• The link between sleep quality and mental resilience.
• Sleep loss and its impact on reducing the ability to regulate emotions.
• The role of sleep in the regulation of the central nervous system.
• How can the quality of sleep strengthen your heart?
• Sleeping as a method to maximize athletic performance.

Sleeping Disorders Essay Topics

• The connection between sleep disorders and dreaming.
• Do congenitally blind people have visual dreams?
• The effective ways of coping with insomnia.
• Sleep difficulties and their physical and emotional consequences.
• How does weight affect sleep apnea in adults?
• Breathing practices and their efficiency in overcoming sleep disorders.
• The key symptoms of sleep-related hypoventilation .
• What are the risk factors for sleep disorders?
• Minimizing stress as a method to cope with obstructive sleep apnea.
• The side effects of sleep disorder treatment.
• What are the major categories of sleep disorders, and how do they differ?
• Restless legs syndrome as one of the sleep disorder types.
• The effectiveness of light therapy in sleep disorder treatment.
• The peculiarities of sleep disorder diagnosis.
• How to deal with rapid eye movement sleep behavior disorder?
• Nightmare disorder and its impact on sleep quality.
• The role of negative thinking, stress, and anxiety in worsening nightmares.
• How may nightmares help to express unresolved emotions?
• The influence of nightmares on interpersonal relationships.
• The use of cognitive behavioral therapy in nightmare treatment.
• Are nightmares a possible consequence of drug abuse?
• The key symptoms of experiencing nightmares.
• The health effects of nightmares in adults.
• How are nightmares connected to waking activity?
• The possible consequences of nightmares.
• The efficiency of psychotherapy in nightmare treatment.
• The main causes of nightmares and methods to cope with them.
• How are nightmares different from sleep terrors?
• The role of sleep hygiene practices in preventing nightmares.
• How do nightmares affect the daily life of teenagers?
• Nightmares as a result of trauma-related experience.
• The link between nightmares and sleep paralysis.
• How does genetics impact the occurrence of nightmares?
• The neurobiological aspects of nightmares in children.
• The risk factors of having nightmare disorder.

📝 My Dreams Essay – Example

We have prepared a dream essay example to show you how everything works in practice!

How Do Different Societies Interpret Dreams?

Throughout history, dreams have been a mysterious experience for people worldwide, receiving various interpretations in many different countries and cultures. From ancient times to the present, people have believed that dreams provide crucial insights into our inner being and may even impact our perception of the universe.

For example, in ancient Egypt, snakes were often associated with danger, deceit, and the underworld. At the same time, seeing calm water in a dream was a good sign that meant peace and tranquility. If people were flying while asleep, it symbolized spiritual growth and escape from mortal concerns.

In ancient Mesopotamia, animals were frequently seen as symbols of the dreamer's personality traits. For instance, a lion might symbolize strength and power, while a sheep could represent humility and submission. Numbers also had a special meaning. People believed their appearance in dreams could be interpreted as messages from the gods.

Nowadays, people still interpret dreams in various ways based on their personal beliefs and traditions. However, it is crucial to understand that there is no correct or incorrect approach to interpreting dreams. The essential thing is to discover a method that resonates with you, allowing you to obtain insights into your subconscious mind. The use of the internet in academic contexts is on the rise, and its role in learning is hotly debated. For many teachers who did not grow up with this technology, its effects seem alarming and potentially harmful. The use of the internet in academic contexts is on the rise, and its role in learning is hotly debated. For many teachers who did not grow up with this technology, its effects seem alarming and potentially harmful.

Do you want to make your research paper on dreams interesting? Then, include a couple of facts into your research paper on dreams:

• Blind people dream;
• You forget 90% of your dreams;
• Dreams prevent psychosis;
• Not everyone sees colorful dreams;
• When you are snoring, you are not dreaming.

Who knows, maybe you will manage to interpret one of these facts from the psychological point of view in your research paper on dreams.

On our blog, useful information on how to write a good research paper and make a cover page for research papers can also be found.

Argumentative Bioethics Essays

Psychologywriting review: free essay samples for students of all levels.

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• Open access
• Published: 02 October 2023

Evidence for an emotional adaptive function of dreams: a cross-cultural study

• David R. Samson 1 , 2 ,
• Alice Clerget 3 ,
• Noor Abbas 1 ,
• Jeffrey Senese 1 ,
• Mallika S. Sarma 4 ,
• Sheina Lew-Levy 5 ,
• Ibrahim A. Mabulla 6 ,
• Audax Z. P. Mabulla 6 ,
• Valchy Miegakanda 7 ,
• Francesca Borghese 3 ,
• Pauline Henckaerts 3 ,
• Sophie Schwartz 3 ,
• Virginie Sterpenich 3 ,
• Lee T. Gettler 8 ,
• Adam Boyette 5 ,
• Alyssa N. Crittenden 9 &
• Lampros Perogamvros 3 , 10 , 11  

Scientific Reports volume  13 , Article number:  16530 ( 2023 ) Cite this article

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• Anthropology

The function of dreams is a longstanding scientific research question. Simulation theories of dream function, which are based on the premise that dreams represent evolutionary past selective pressures and fitness improvement through modified states of consciousness, have yet to be tested in cross-cultural populations that include small-scale forager societies. Here, we analyze dream content with cross-cultural comparisons between the BaYaka (Rep. of Congo) and Hadza (Tanzania) foraging groups and Global North populations, to test the hypothesis that dreams in forager groups serve a more effective emotion regulation function due to their strong social norms and high interpersonal support. Using a linear mixed effects model we analyzed 896 dreams from 234 individuals across these populations, recorded using dream diaries. Dream texts were processed into four psychosocial constructs using the Linguistic Inquiry and Word Count (LIWC-22) dictionary. The BaYaka displayed greater community-oriented dream content. Both the BaYaka and Hadza exhibited heightened threat dream content, while, at the same time, the Hadza demonstrated low negative emotions in their dreams. The Global North Nightmare Disorder group had increased negative emotion content, and the Canadian student sample during the COVID-19 pandemic displayed the highest anxiety dream content. In conclusion, this study supports the notion that dreams in non-clinical populations can effectively regulate emotions by linking potential threats with non-fearful contexts, reducing anxiety and negative emotions through emotional release or catharsis. Overall, this work contributes to our understanding of the evolutionary significance of this altered state of consciousness.

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Introduction.

Why do humans dream? As a product of the brain’s neurophysiology, our species can produce hallucinatory experiences during sleep. These dream experiences represent an altered state of consciousness. Why is it that we exhibit this altered state of consciousness rather than experiencing sleep in total perception quiescence? Research investigating dream content reveals that the dream state of consciousness, which is most often expressed in rapid-eye movement (REM), appears to be preoccupied with world simulation with content often reflecting the self’s social realities 1 , 2 , social networks 3 , 4 , and dangers 5 . Yet, whether dreams could enhance cognitive, affective, or social adaptation has been a question of active debate for decades.

A common framework for explaining the function of dreams is provided by simulation theories , which are based on the premise that dreams have a biological function and reflect selective pressures and fitness enhancement in the evolutionary past via altered states of consciousness 6 . Accordingly, dreams are credible real-world analogs 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 that prime the individual for corresponding contexts encountered in waking life. From this perspective, it has been argued that the phenotypic expression of dreaming could meet the necessary criteria for evolution by natural selection 15 .

Dream simulation and emotion regulation

Emerging work integrating neuroscience and dream content analysis suggests that emotional experiences are a crucial part of the virtual-world simulation of dreams and support an adaptive process that contributes to the resolution of emotional distress and preparation for future affective reactions 6 , 16 , 17 , 18 , 19 . In this context, the threat simulation theory 6 and social simulation theory 9 posit that dreams are biased to simulate threatening and social situations respectively. Such a mechanism would, in turn, promote adjusted behavioral responses in real-life situations 5 , 9 . Other studies have also supported the idea that past negative memories are reprocessed and combined in dreams with new, realistic, and safe contexts, suggesting the possibility of desensitization 20 , 21 or extinction 17 functions for dreaming. Functional dreams could thus expose us to threatening situations while providing us with efficient solutions to these situations. Such a process may facilitate the resolution of current social and emotional internal conflict 16 , 22 , a process also called emotional catharsis 23 , and the reduction of next-day negative mood 24 .

Together, these proposals and empirical observations suggest a potential core function of dreams via simulating distress in a safe environment to help process threats in beneficial ways; as such, functional dreams would strongly contribute to efficient emotion regulation in wakefulness 18 . These mechanisms seem to be impaired in clinical populations, such as patients with nightmare disorder 17 , 25 and anxiety disorders 26 —two pathologies characterized by less efficient fear extinction 17 , 27 .

Indeed, anxiety is considered a maladaptive emotional response implicating dysfunction of inhibitory (extinction) learning 27 , and the persistence of the fear response across time. We would thus expect that dreams with high levels of anxiety and negative emotions in the presence of a threat, as those found in clinical populations, would not serve the emotional processing function of dreams, as no emotional resolution is achieved. Critically, Revonsuo posited that the adaptive emotional function of dreams may be particularly relevant to contemporary small-scale societies facing routine ecological risks such as infectious disease and predation, as the emotional simulating mechanism would be fully activated in the face of the kinds of challenges within their environment 6 . Although there is some preliminary evidence for this argument 5 , 28 , 29 , such arguments have yet to be comparatively tested with large, multicultural datasets.

The importance of cross-cultural testing of dream content

The major challenge to the scientific investigation of dream function remains a sampling problem. To date, most dream studies have been conducted in the Global North—and primarily in the U.S. and European settings with samples of limited socio-economic and racial/ethnic breadth. Thus, one critical challenge to overcome limitations in past dream-based research, is to test the function of dreams by generating dream content variation among diverse populations’ socio-ecological experiences. This may be due in part to the interest of sleep researchers in pairing such work with sleep-based physiological techniques (i.e. polysomnography) that have been historically limited to lab settings (but see 30 for field-based methods in human biology and sleep research that are gaining momentum). While historically dreams have been the subject of anthropological investigation 28 , 31 , 32 , 33 , this ethnographic work is largely descriptive. Hence, much of the dream data are generated from studies that represent a very narrow range of human experiences for select populations (e.g., college undergraduates) at specific historical moments (e.g., between 1970 and 1990) in particular locations (e.g., U.S., Europe) and under similar societal and economic contexts (e.g., educated, high income).

There is a dearth of direct empirical tests of the evolutionary function of dreams, including comparative perspectives that would enable us to assess variation across cultural and ecological contexts in relation to dream content 9 . For example, smaller-scale societies that engage in mixed-subsistence foraging (i.e., hunt and gather for a large part of their diet), often differ from other smaller-scale societies in important ways. The depth and breadth of egalitarianism (i.e., cultural values and practices aimed at the treatment of all individuals as equal, often with norms around avoidance of prestige and hierarchy) in many sub-tropical foraging populations is intertwined with norms of cooperative pooling of time and energetic resources, such as to help provision and care for children 34 , 35 , 36 , 37 , 38 , 39 . Such forms of egalitarianism and extensive cooperation in resource sharing and family life are thought to be critical to survival and reproduction.

In contemporary populations, including the Hadza of Tanzania and BaYaka of the Republic of the Congo forager communities we focus on here, these cooperative subsistence and social dynamics necessarily place a strong emphasis on the importance of face-to-face supportive relationships for day-to-day health, well-being, and even survival 35 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 . These communities share some broad socioecological similarities in terms of (i) continuous environmental exposure to key stimuli—such as ambient light and temperature cues—known to drive circadian entrainment (e.g., circadian driven fluctuations have been shown to influence central characteristics of dream reports 50 ), (ii) gender divisions of foraging and household labor (though varying in their intensity between the BaYaka and Hadza), (iii) ecological risk in the form of predation exposure by way of large animals, pathogens and parasites, and (iv) norms regarding egalitarianism and generous resource sharing behaviors 39 , 40 , 41 , 42 , 43 , 44 , 51 , 52 .

The community-oriented interpersonal behaviors characteristic of BaYaka and Hadza and their maintenance require high degrees of emotion regulation and social problem solving. Unlike the experience of many individuals in populations from the Global North, these foragers’ daily interactions are repeated with the same network of cooperative partners throughout their lives. Additionally, although precise estimates are difficult to assess, mortality rates are relatively higher in subsistence-level societies compared to populations with better access to emergency care and biomedical treatment 41 —a factor that may be relevant in evaluating the possible threat simulation function of dreams. Thus, foragers may experience greater threat and community oriented responses to threat in their dreams. If an adaptive function of dreams is to reinforce or rehearse such day-to-day, prosocial (i.e., community-oriented) interactions, particularly with trusted kin, then people in BaYaka and Hadza communities will have a higher representation of those interactions and family members in their dreams than would typical populations in the Global North who reside in more individualistic societies.

Hypotheses and predictions

Here, we compare the dreams of two foraging communities—the BaYaka and Hadza—to non-clinical and clinical (i.e., with nightmares and social anxiety) populations from the Global North. First, because of their strong egalitarian social norms and high levels of daily face-to-face interpersonal support from trusted family and friends, we predict that the dream content of both forager groups will have a greater frequency of community-oriented behaviors when compared to dreamers in the Global North. Second, given that both forager groups experience greater early-to-midlife mortality—subsequently leading to a greater chance of an individual losing their own life, the life of offspring, kin, or friends—we predict a greater frequency of threat related dream content relevant to mortality. Third, we expect that foragers’ dreams will serve an efficient emotion regulation function, where threats are associated with new, non-fearful contexts/efficient solutions 17 , and, thus, with lower anxiety/negative emotions in dreams. Finally, we predict that the Nightmare group will have greater levels of negative emotions in dreams and that the student group, associated with COVID-19 pandemic, as well as the social anxiety group, will be characterized by greater anxiety in dream content. By comparing these groups, we can better understand the role of culture and environment in shaping the human experience of dreaming.

Material and methods

Participants.

In all, individuals from two sub-Saharan foraging egalitarian communities with low degrees of market integration, the Hadza and BaYaka and from three high income capitalistic populations (including non-clinical and clinical populations) totaling 234 participants contributed 896 dreams (see Table 1 for summary details).

Global North data collection and characteristics

Data from the Global North populations were drawn from previously published studies done in Switzerland, Belgium, and Canada. The Switzerland and Belgium samples were generated between 2014 and 2022 25 , 26 , 53 , 54 , 55 and included data from three groups: a non-patient group of young healthy participants, patients suffering from social anxiety disorder (SAD), and patients suffering from nightmare disorder. Participants in these studies all kept the same sleep and dream diary (for details see 18 ). During the night or every morning, upon spontaneous awakening, the participants were asked to report whether they had a dream with or without recall or no dream at all. They also reported the presence of specific emotions thanks to dichotomous questions (presence/absence); in total, eleven emotions could be reported. A twelfth choice was reserved to the “absence of emotions”. In the last section of the dream diary, they were also asked to freely write down the dreams they had experienced during their sleep.

The non-clinical reference control group in the Global North includes 219 participants (123 females). A subset of 103 participants, aged between 16 and 40 years old (M = 22.1, SD = 7.9), had dream word counts equal to or greater than 20 words and were included in the dream analysis (word average per dream = 78.2, SD = 66.0). All participants followed a constant sleep schedule during the days preceding the experiment to assess the mean sleep duration and exclude any circadian disturbance or sleep disorder. People suffering from mental disorders were excluded. Ethical approval was granted by the committee of the Faculty of Medicine of the University of Liege and by the Ethical Committee of the Canton of Geneva.

Dreams were also collected from patients suffering from social anxiety disorder (SAD) according to The Diagnostic and Statistical Manual of Mental Disorders (DSM5) 26 , 56 . SAD is characterized by a persistent amount of fear when confronted with social situations 57 . Forty-eight subjects (32 females) were included in the final sample, after assessment of their social anxiety disorder level. The dream diary was filled every morning upon awakening for 2 weeks. Three hundred twenty-four (324) dream reports were collected (6.75 dreams per participant). A subset of 37 participants, aged between 16 and 40 years old (M = 24.4, SD =7.9), had dream word counts equal to or greater than 20 words and were included in the dream analysis (word average per dream = 76.9, SD = 56.7). Ethical approval was granted by the Ethical Committee of the Canton of Geneva, Switzerland (“Commission Cantonale d’Ethique de la Recherche sur l’être humain”).

Additionally, dreams were collected in individuals suffering from nightmare disorder 25 . In total, 36 patients (27 females) were included. All of them suffered from nightmare disorder according to DSM5 with at least moderate severity (> 1 episode per week). Every morning upon awakening participants filled in a dream diary for 2 weeks. One hundred thirty-four (134) dream reports were collected (3.72 dreams per participant). A subset of 33 participants, aged from 20 to 35 years old (M = 26.3, SD = 8.4), had dream word counts equal to or greater than 20 words and were included in the dream analysis (word average per dream = 43.5, SD = 23.8). Ethical approval was granted by the Ethical Committee of the Canton of Geneva, Switzerland (“Commission Cantonale d’Ethique de la Recherche sur l’être humain”).

Altogether, the Belgian and Swiss studies had 924 dream reports collected from the dream diary over 397 nights (4.2 dreams per participant on average). Of those dreams the number that were included in the final analysis with words counts equal to or above 20 are as follows: control N  = 356, Nightmare Disorder N  = 113, and SAD  = 184.

Students at the University of Toronto contributed dream reports ( N  = 184) collected during the fourth wave of the COVID-19 pandemic, where the proliferation of COVID-19 variants was of major concern in Ontario, Canada, as announced by the Public Health Agency of Canada (Statistics Canada, 2021). In total, 24 students (21 females) aged from 19 to 25 years old (M = 21.9, SD = 5.5) were included. Ethics was approved and attained by the University of Toronto REB (RIS Human Protocol Number 39768). During this time, self-rated mental health was below national average (< 50%), and 82% of the Canadian population that were eligible for vaccination were fully vaccinated, however restrictions were still imposed in most areas, including mask-wearing, and limiting contacts. Thus, explorations of evolutionary theories on dream functions may have special relevance during the COVID-19 pandemic 58 , 59 . The final number of dreams equal to or above 20 words and included in the analysis was N  = 168 (word average per dream = 120.6, SD = 44.4).

Global South data collection and characteristics

Data were collected over different time periods by different experimenters. Hadza participants ( N  = 18) were surveyed by DRS in January and February of 2016 and BaYaka participants ( N  = 19) by AHB, SLL, VM, and MSS in June and July 2017. Hadza participants were aged between 18 and 68 years old (M = 42.7, SD = 8.5) and BaYaka participants were aged between 27 and 70 years old (M = 42.3, SD = 10). Combined, we collected a total of 101 dream reports (2.16 dreams per participant and a word average per dream = 38.7, SD = 18.9). The Hadza contributed 48 dream reports (female dreams = 12, male dreams = 36; word average per dream = 44.4, SD = 20.6); all Hadza dreams were equal to or greater than 20 words and were included in the analysis. The BaYaka ( N  = 19) contributed 53 dream reports (females dreams = 26, male dreams = 27); twenty-seven BaYaka dreams were equal to or greater than 20 words (word average per dream = 28.7, SD = 9.1) and were included in the analysis.

Dream reports were collected in the field using a modified Most Recent Dream (MRD) method 60 as a template for questionnaires, and in practice (as the indigenous populations could not write) were a daily verbally administered dream diary. The instructions, given by field researchers in morning after a sleep period, requested the participant to recall whether they dreamt the previous night. If subjects answered in the affirmative, they were then asked to recount the details of the dream using the MRD method template. The report was expected to be detailed, including a description of the dream's setting, the people involved (their age, sex, and relationship to the participant), and any animals present in the dream. Participants were also instructed to describe their emotions during the dream and whether it was a positive or negative experience. This method is ideal for use in small-scale societies because it is a fast, inexpensive, and reliable way to obtain large samples of dream reports. For both forager groups, dream content was translated by the aid of a multilingual field assistant at the time the dream was recorded. Importantly, it is essential to note that, as both the MRD modified and verbally administered dream diary (Global South) and the classic Dream Diary method (Global North) recorded dreams of the previous night, they shared a similar approach and were directly comparable. Additionally, both were administered shortly after awakening from sleep on the same day as the dream, thereby minimizing potential memory biases 61 .

For work with the Hadza, IRB approval was granted from the University of Nevada, Las Vegas (2014) and verbal consent for participation was asked to each participant in Swahili, the second language of the Hadza community. All research was performed with approval of the government of Tanzania, via the Tanzanian Commission for Science and Technology (COSTECH) and the Tanzanian National Institute for Medical Research (NIMR). For the BaYaka, village council consent for this study was obtained at a community meeting in 2015. Subsequently, community consent was annually renewed. Verbal consent was provided by each participant following recruitment into this study. Approval to conduct research in the Republic of the Congo was given by The Centre de Recherche et D’Edudes en Sciences Sociales et Humaines. Ethics approval was obtained from Duke University (2017), the University of Notre Dame (2017), and the University of Cambridge (2017).

All methods were performed in accordance with the relevant guidelines and regulations, and informed consent was obtained from all participants.

Dream text analysis

LIWC-22 is an acronym for Linguistic Inquiry and Word Count, and it is a text analysis software program that can return results for up to 90 different variables or categories 62 . The English text analysis strategy employed the LIWC-22 Dictionary. This internal dictionary is comprised of over 12,000 words, phrases, and emoticons, which have been carefully selected and categorized into sub-dictionaries to assess various psychosocial constructs. Essentially, the LIWC-22 software program is designed to map linguistic constructions to important psychosocial theories and constructs, and thus, target words contained in texts that are read and analyzed by LIWC-22 are used for this purpose.

In this study, the dream texts were translated and transcribed into English, and preprocessed into four super-categories— Community-oriented (by grouping the LIWC categories: social, family, moral, friend, and prosocial) , Threat (by grouping the LIWC categories: conflict and death) , Negative emotions (encompassing the category: negative emotions), and Anxiety (encompassing the category: anxiety). To create an outcome variable for statistical models (see section ‘Modelling' ), we summed the number of words of each category in each dream text. Examples of the Community-oriented target words were: care, help, thank, please, parent, mother, father, baby, honor, deserve, judge, you, we, he, she. Examples of the Threat target words were: fight, killed, attack, death, dead, die, kill. Examples of the Negative emotions target words were: bad, hate, hurt, tired. Examples of the Anxiety target words were: worry, fear, afraid, nervous. The LIWC-22 Dictionary provides a systematic and reliable approach to text analysis 63 and has been widely used in other word-based dream content analyses 25 , 64 , 65 .

To assess the predictors of the four response variable categories ( Community-oriented, Threat, Negative emotions, Anxiety dream content) by population (BaYaka, Hadza, Nightmare, SAD, Students, and Control) we used a linear mixed effects model, built using the lme4 package and model averaged using the MuMin package 66 . To normalize the count data for each category, we square root transformed the response variable 67 , 68 . Finally, we made statistical inferences using a combination of standardized coefficients, confidence intervals, and p-values. We controlled for the fixed effects of age, number of dream reports, word count and sex as well as subject ID (to control for repeated measures) as a random effect. After assessing information criterion, models including the number of dream reports and age as fixed effects differed little from models without them, and so we removed them from final analysis. To increase the power of the model to identify the predicted patterns in the data, we obtained coefficients based on optimization of the log-likelihood using shrinkage, which incorporates measurement error into the regression model and improves less certain estimates by pooling information from more certain estimates 69 .

The non-patient sample from the Global North was used as a model reference category (i.e., a group that is used as a point of comparison for other groups in a statistical analysis) so effect-size estimates for each population are predicted differences in counts of dream content compared to this sample.

The dream content models were fit as follows:

The full dataset, along with all meta-data and more detail of each variable, is available in the Open Science Framework (OSF) data repository:  https://osf.io/7n6kf/ .

Community-oriented’ dream content is greatest in BaYaka

Amongst all sampled populations, the BaYaka showed greater community-oriented dream content than all group samples from Global North populations and Hadza population, after adjusting for sex, word count, and subject ID. As shown in Table 2 , and displayed in Fig.  1 , after factor correction, the BaYaka sample positively drives community-oriented dream content. Additionally, women’s dream reports and word count were drivers of the response variable (Table 2 ). As ethnographic data, we present a few such examples here:

‘I was walking in the forest with my two adult daughters and found a porcupine in a trap and brought it back to the village to eat it. It was a good dream’ ‘I was net hunting with my family (including extended family camp) and we caught many animals so he had to make a smoker "bota" to smoke all of them’

Prosocial dream estimates plot.

‘Threat’ dream content is greatest in BaYaka and Hadza

After adjusting for sex, word count, and controlling for repeated measures of the subject ID, both the BaYaka and Hadza samples had higher levels of threat dream content compared to the Global North groups. This is shown in Table 3 and depicted in Fig.  2 . Thus, belonging to the BaYaka or Hadza community is associated with a greater probability of experiencing threatening dream content. No other factors were found to significantly influence threat dream content.

Threat dream estimates plot.

Importantly, several dream reports gathered among the Hadza community demonstrated high threat situation to which a positive, emotionally cathartic resolution was found. For example:

‘I dreamt I was being chased by a herd of elephants; I was in Nyanza, which is open flat savanna land. I ran and found a small cave which was too small for the elephants to follow. I escaped’. ‘I was chased by an elephant in the bush around camp. I was with four unfamiliar women. I escaped by running into the mountains’. ‘I dreamt I was in the forest and the military was chasing me with guns and he climbed a tree to get away.’ ‘I was chased by a leopard in nearby mountains. I began by hunting but realized that I was the hunted. I was alone but I escaped’.

Moreover, in some Hadza dream reports, a solution to a threat was found through social support:

'I dreamt I fell into a well that is near the Hukumako area by the Dtoga people. I was with two others and one of my friends helped me get out of the well.' ‘I dreamt a buffalo hit me. I was in Numbeya bushland where we look for honey. I was looking for the "small honey". There was another man called January and he came and helped me’ ‘I dreamt a Toga not from this camp (who) took a knife and a person he didn't know from another camp. After I told the guy to stop, he left our Sengele camp.’

'Negative emotion’ dream content is greatest in Nightmare disorder sample

After adjusting for sex, word count, and subject ID, the sample of patients from the Global North in the Nightmare Disorder group had higher levels of dream content with negative emotions compared to the reference group (Table 4 and Fig.  3 ). Conversely, the Hadza exhibited significantly fewer negative emotion words in their dream content than the reference group. No other groups differed from the reference group, as shown in Table 4 and depicted in Fig.  3 . The following dream reports demonstrate high fear without resolution in the Nightmare Disorder group:

‘My mom would call me on my phone and ask me to put it on speakerphone so my sister and cousin could hear. Crying she announced to us that my little brother was dead. I was screaming in sadness and crying in pain.’ ‘I was with my boyfriend, our relationship was perfect and I felt completely fulfilled. Then he decided to abandon me, which awoke in me a deep feeling of despair and anguish.’ ‘I remember in my dream is that I was sitting at a table, in one of the secret rooms, across from a middle-aged man who said he was my uncle (he did not look like any of my uncles), and he was over 100 years old but looked like he was in his 50s. He looked like evil characters from movies. He said he was going to kill me after he went to speak with other people in the other room to admit his secret and then come to kill me. After he left the room, I got up and saw that the door was not fully closed. My thought was that I had to go fight him and then I woke up before I could approach the door.

Negative emotions dream estimates plot.

‘Anxiety’ dream content is greatest in the Canadian (COVID-19 pandemic era) student sample

After accounting for sex, the word count and participant repeated measures by subject ID, it was found that the student group had more anxiety dream content compared to the reference group. Table 5 and Fig.  4 indicate that no other groups demonstrated a significant difference from the control group. In the following two examples, the dream scenario illustrates the level of anxiety that the subject experiences as he needs to confront challenges alone:

‘The dream I remember relates to a game that I play. As it only involved myself, there was no one that I knew around, and I remember feeling anxious. I was doing a very difficult mini-game in the game where a bunch of non-player characters were all around me and I needed to hide behind obstacles to stay safe. I remember waking up once I died inside the mini-game’

Anxiety dream estimates plot.

Contrary to one of our predictions, no significant differences between the non-clinical group and the Social Anxiety Disorder group were found about the level of anxiety experienced in dreams. However, some dreams illustrate the social isolation these patients are experiencing in their real life, translated by a lack of social support when dangers arise:

‘I was in an elevator, stuck, alone. I pressed the down button, and then the elevator sped down. I was very scared, I tried to set off the emergency bell. I arrived at the bottom, it was dark and a sheet or blanket fell from the ceiling of the elevator to cover me.’

In other dreams of this group, people are regarded as hostile, which eventually increases the anxiety level:

‘I dreamed that I ran into someone I knew at the supermarket. We collided without excusing each other which led to an open conflict. The person in question threatens me, I go to the manager of the store accusing the person of having stolen something (it's not true). Then we walk out of the store and the other begs me to drop my charge of theft. I tell him that I won't go any further and that the newspapers won't know anything because I'm a journalist. The person's mother picks him up. I walk a bit until we go to their place. I explain to the person that I have the feeling of being followed by a man who looks like a shadow, and who watches over me and waits for the moment to seize me. I then understand that this man is death himself!’ ‘In my dream, I was at my high school. I went into the classroom by myself and two friends (female, 18) that I thought were close to me started isolating me during group work. I worked by myself the entire class while they acted aggressively towards me, at least verbally. I pulled out my chair to go submit my assignment and it hit a person behind me (male, 18). This person is a friend from my primary school. He shouted at me even though I tried to explain to him what happened was just an accident. I used the washroom, and my phone was water-damaged by one of the two girls (may or may not be an accident). I asked her to pay me back, but subconsciously I did not want the refund but instead to have an excuse to hold a conversation with her. It was an unpleasant dream because I thought I was close to them.’

In the present study, we tested the hypothesis that dreams serve an emotional function that is potentially adaptive by examining dream content from Hadza and BaYaka foragers, who belong to communities characterized by high levels of interpersonal support coupled with greater early-to-midlife mortality (due to predation, resource stress, food and water insecurity, and disease) in comparison to populations in the Global North. We found partial support to the first prediction, that forager dreams exhibit greater community-oriented dream content. Of all the populations examined, only BaYaka reported dreams with significantly more frequent content related to community-orientation and social support amongst family and friends (Table 2 and Fig.  1 ).

The second prediction, that foragers’ dreams contain more threat related content was supported. Both the BaYaka and Hadza samples demonstrated a greater frequency of mortality and conflict associated dream content compared to the reference group, whereas the other groups did not show such difference (Table 3 and Fig.  2 ). The prediction that dreams may augment the processing of high threat levels, yet also be characterized by low levels of both anxiety and negative emotions—was supported. The BaYaka exhibited levels of negative emotions in dreams that did not differ from the reference group, while the Hadza exhibited significantly less dream content with negative emotions compared to the reference. As expected, the Nightmare Disorder group also exhibited significantly greater levels of negative emotions in dreams (Table 4 and Fig.  3 ). A similar pattern was found with anxiety dream content, where the student group during the COVID-19 pandemic was characterized by significantly greater anxiety dream content compared to the reference group, while the BaYaka and Hadza did not differ compared to the reference group (Table 5 and Fig.  4 ).

Evidence for an emotional function of dreams in small-scale forager populations

BaYaka and Hadza foragers face several specific hazards. BaYaka communities reside in a rainforest ecology in the Congo Basin, where routine hazards (i.e., specific sources of danger include: (i) intergroup conflict with Bantu fisher-farmers due to perceived trade and labor related debt, (ii) illnesses (malaria, tuberculosis, intestinal parasites), and (iii) extrinsic risks (i.e., broader factors that can increase a person’s overall risk of harm or negative outcomes) of everyday life, including encounters with dangerous animals like snakes, elephants, crocodiles, and gorillas while hunting, fishing, and foraging as well as other hazardous aspects of the forest such as falling limbs/trees and falls while climbing 70 . The BaYaka infant mortality rate in the study region is unknown, but (as measured elsewhere in the region) can be inferred to be around 20 percent 41 . Adult and juvenile mortality is generally relatively high compared to populations with better access to emergency care and biomedical treatment, though precise estimates are currently unknown 41 . A study of death among the Aka in the Central African Republic found that infections and parasitic diseases were the most common causes of death across ages, causing 22 percent of 669 deaths, and diarrhea causing another 21 percent of deaths 71 .

The Hadza reside in a diverse ecological region characterized by rolling hills, grasslands, and acacia commiphora woodland. Hazards for the Hadza include (i) intergroup conflict with the Datoga pastoralists who co-reside in some areas of the landscape and keep large herds of cattle and goats that drink the scare water in the water holes during the dry season and eat much of the vegetation needed to support wildlife, (ii) illnesses (e.g. tuberculosis, malaria, viral diarrhea) that are faced with little access to biomedical treatment, and (iii) extrinsic risks of everyday life that include falling from trees when collecting honey, snakebites, and encounters with predators when hunting or scavenging meat 48 . One study showed that out of 75 deaths, a third of deaths were attributed to illness, with age, childbirth, poisoning or bewitching and homicide, and falling from trees as other causes of death 72 . With respect to mortality, 21% of infants die in the first year of life and 46% of juvenile children die by age 15 72 , 73 .

Comparatively, populations of the Global North face other types of threats and share different sociocultural values than individuals from small-scale societies. In contrast to collectivistic cultures, like BaYaka and Hadza, most societies of the Global North are strongly individualistic and competitive 74 . People in these societies have less routine face-to-face contact with and imperative cooperative reliance on broad kin networks. At the same time, this individualism shapes many common threats, which are mostly connected to social life (e.g., ostracism and exclusion, loss of status, shame, failure in an exam, etc.), and which are mostly experienced at an individual rather at a collective level. Although recent austerity plans resulted in the reemergence of unemployment, poverty, homelessness, and food insecurity in European and American countries 75 , economic development, public health infrastructure, and access to biomedical care have been linked to comparatively greater life expectancies in the Global North (e.g. 77 years in the U.S. and 80 years in the E.U.), with a larger proportion of deaths occurring in older age from chronic conditions 76 , 76 , 78 .

The present findings provide evidence that when compared to populations in the Global North, foragers disclose a prevalence of community-orientation in their waking life as well as the socially connected themes in their dreams, which may support emotional health. Specifically, our analysis suggests that even in the context of threat, community-orientation—expressed by strong social networks that rely daily on mutual assistance in the context of strong egalitarian social norms—may also play an important role in providing strategies to overcome threats and ultimately achieve emotion regulation. Importantly, an interpretation of BaYaka and Hadza dreams is that foragers activate both the threat simulation and extinction functions of dreaming, which may result in resolution of these threats within their dreams.

The dysfunctional nature of nightmares

We claim here, in line with other theoretical concepts 17 , that increased threat in dreams (as compared to dreams from healthy controls) does not seem to be functional without a subsequent emotional resolution. For example, patients with nightmare disorder have dreams characterized by recurrent, intense, and highly threatening content that cause significant distress and impairment in social, occupational, or other areas of functioning 56 . Nightmares are dreams with high threat but insufficient emotional resolution. The dreamer cannot find effective solutions for threats, therefore high fear and anxiety impedes emotion regulation and catharsis. According to the threat simulation theory, individuals possess a threat simulation system by which multiple factors (such as, inherited personality traits, threat input throughout adolescent development, current stress levels and recent threat input) regulate dream phenotypes. These inputs can also be attenuated by strong social support networks and egalitarian norms. Previous work has suggested that threatening content in dreams ultimately serve to strengthen waking threat perception skills and threat avoidance behaviors that help to self-cope with the challenging realities of waking life 6 , 8 , 79 , 80 .

The forager data further supports the idea that overcoming threat by way of adaptive emotional responses (in wake or sleep) is a crucial component of an efficient emotion regulation in the face of stressful events. When the presence of threats in dreams is not associated with subsequent emotional resolution, as in recurrent nightmares, dreams seem to lose their emotional processing function. Our results, along with others 81 , 82 , 83 suggest that nightmares are dysfunctional dreams with high threat simulation coupled with lack of fear extinction.

Dreams in situations of social isolation or social anxiety

Contrary to the community-oriented character of the BaYaka population, and similar to the increased negative emotions found in nightmares, the dream reports collected from students during the pandemic era were characterized by high levels of anxiety, and sometimes these manifested with themes of isolation and having to confront challenges alone (as depicted in the dream text examples in the “ Results ” section). For example, dreamers experienced high anxiety because of the presence of hostile people in the narrative, without finding any positive way to deal with such a threat. Our results suggest that dreams of individuals in situations of social isolation or social anxiety do not seem to achieve a sufficient degree of emotional resolution (see also 26 ). Whether there is a causal relationship between such a deficient extinction function of dreaming and the symptomatology of anxiety disorders is not clearly elucidated and should be further tested in the future.

Limitations

There are several limitations to the current study, particularly in regard to the dream content collection among the BaYaka and Hadza populations. Future dream research in such small-scale societies should emphasize not only generating dream data but also including daily reports of activity or evidence of daytime emotion regulation or performance 18 . Accounts for waking life experiences enable a direct analysis of dreams to experiences encountered during the day, which would then allow to test threat or social simulation hypotheses or to make claims related to these hypotheses in general 60 . Correlational studies, such as the one conducted by Sterpenich and colleagues 18 , or interventional studies (i.e., manipulating dream content and observing its effect in wakefulness 25 ) offer a closer approximation of the relationship between wake and dream functions. Importantly, observational dream research, including the present study, cannot claim to provide strong evidence for causality between wakefulness and dreams, nor for the directionality of such relationship regarding emotion regulation functions. Finally, as both a point of originality for this work and in distinction from previous work, this study did not test for the daytime emotional state-response, as emotional resolution was assessed in the dream itself.

Dream reports with greater length are more likely to contain sufficient information to accurately describe a dream 29 . Yet, some dream reports from both of these communities were relatively short in length. This can be attributed to dream recounting having to be translated and transcribed into English. Although we made efforts to recount as much detail as possible, dream descriptions could only be paraphrased summaries of dreams distilled through the translator. In addition, it is difficult to assess whether the participant recounting his/her dream was motivated and/or had sufficient practice formulating accurate long-term memories of the dream. Often, inexperienced dream recounters simply answer the questionnaire as is presented to them, which can attribute to dream report bias 80 . Despite the short dream descriptions and less formalized training in dream recounting, the BaYaka and Hadza communities are characterized by a rich storytelling culture and were typically highly motivated to discuss dreams and their interpretations. We also note that these samples are characterized by a stark lack of sexually related activity in dreams. It may well be that for these groups, the lack of recounting dreams of a sexual nature may reflect a taboo placed on descriptions of sexuality in general.

Here we provide support for the idea that in non-clinical populations with real and perceived threats, dreams may process high threat levels, yet also be characterized by low anxiety and negative emotions. Our results suggest indirectly that dreams can effectively regulate emotions by linking potential dangers with novel, non-fearful dream contexts and can lead to a reduction in feelings of anxiety and other negative emotions, as a form of emotional release or catharsis. In addition, in at least one such community (the BaYaka), emotional catharsis is often achieved by strong social support. Ultimately, if dreaming prepares human beings to face likely challenges and dangers in waking life, then our results are among the first to show these potential functions under evolutionarily relevant socio-ecological conditions.

Data availability

The data that support the findings of this study are publicly available on OSF ( https://osf.io/7n6kf/ ). 

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Acknowledgements

We would like to thank both the Hadza and BaYaka for participating in this study. We would like to thank Dambo Justin and Mékouno Paul for assistance with data collection in Congo. We would like to thank Jarno Tuominien for useful discussions and Audrey Theux for technical assistance. This project was funded by the National Geographic Society (no. 9665-15 to DS), the Jacobs Foundation (to LG and AB), the Medical Direction of University Hospitals of Geneva (PRD 18-2019-I to LP) and the Swiss National Science Foundation (CRSK-3_190722 to LP).

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David R. Samson, Noor Abbas & Jeffrey Senese

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David R. Samson

Department of Basic Neurosciences, University of Geneva, Geneva, Switzerland

Alice Clerget, Francesca Borghese, Pauline Henckaerts, Sophie Schwartz, Virginie Sterpenich & Lampros Perogamvros

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Mallika S. Sarma

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Conceptualization: D.S. and L.P. Methodology, software: D.S., A.C., L.P. Data curation: D.S., A.C., N.A., J.S., M.S.S., S. L-L., F.B., P.H., V.S., L.T.G., A.B., A.N.C., L.P. Writing—original draft preparation: D.S. and L.P. Visualization, investigation: D.S., S. L-L., S.S., V.S., L.T.G., A.B., A.N.C., L.P. Supervision: D.S. and L.P. Funding acquisition: D.S., S. L-L., L.T.G., A.B., A.N.C., L.P. Writing—reviewing and editing: D.S., A.C., N.A., J.S., M.S.S., S. L-L., F.B., P.H., S.S., V.S., L.T.G., A.B., A.N.C., L.P.

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Samson, D.R., Clerget, A., Abbas, N. et al. Evidence for an emotional adaptive function of dreams: a cross-cultural study. Sci Rep 13 , 16530 (2023). https://doi.org/10.1038/s41598-023-43319-z

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July 26, 2011

The Science Behind Dreaming

New research sheds light on how and why we remember dreams--and what purpose they are likely to serve

By Sander van der Linden

Getty Images

For centuries people have pondered the meaning of dreams. Early civilizations thought of dreams as a medium between our earthly world and that of the gods. In fact, the Greeks and Romans were convinced that dreams had certain prophetic powers. While there has always been a great interest in the interpretation of human dreams, it wasn’t until the end of the nineteenth century that Sigmund Freud and Carl Jung put forth some of the most widely-known modern theories of dreaming. Freud’s theory centred around the notion of repressed longing -- the idea that dreaming allows us to sort through unresolved, repressed wishes. Carl Jung (who studied under Freud) also believed that dreams had psychological importance, but proposed different theories about their meaning.

Since then, technological advancements have allowed for the development of other theories. One prominent neurobiological theory of dreaming is the “activation-synthesis hypothesis,” which states that dreams don’t actually mean anything: they are merely electrical brain impulses that pull random thoughts and imagery from our memories. Humans, the theory goes, construct dream stories after they wake up, in a natural attempt to make sense of it all. Yet, given the vast documentation of realistic aspects to human dreaming as well as indirect experimental evidence that other mammals such as cats also dream, evolutionary psychologists have theorized that dreaming really does serve a purpose. In particular, the “threat simulation theory” suggests that dreaming should be seen as an ancient biological defence mechanism that provided an evolutionary advantage because of  its capacity to repeatedly simulate potential threatening events – enhancing the neuro-cognitive mechanisms required for efficient threat perception and avoidance.

So, over the years, numerous theories have been put forth in an attempt to illuminate the mystery behind human dreams, but, until recently, strong tangible evidence has remained largely elusive.

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Yet, new research published in the Journal of Neuroscience provides compelling insights into the mechanisms that underlie dreaming and the strong relationship our dreams have with our memories. Cristina Marzano and her colleagues at the University of Rome have succeeded, for the first time, in explaining how humans remember their dreams. The scientists predicted the likelihood of successful dream recall based on a signature pattern of brain waves. In order to do this, the Italian research team invited 65 students to spend two consecutive nights in their research laboratory.

During the first night, the students were left to sleep, allowing them to get used to the sound-proofed and temperature-controlled rooms. During the second night the researchers measured the student’s brain waves while they slept. Our brain experiences four types of electrical brain waves: “delta,” “theta,” “alpha,” and “beta.” Each represents a different speed of oscillating electrical voltages and together they form the electroencephalography (EEG). The Italian research team used this technology to measure the participant’s brain waves during various sleep-stages. (There are five stages of sleep; most dreaming and our most intense dreams occur during the REM stage.) The students were woken at various times and asked to fill out a diary detailing whether or not they dreamt, how often they dreamt and whether they could remember the content of their dreams.

While previous studies have already indicated that people are more likely to remember their dreams when woken directly after REM sleep, the current study explains why. Those participants who exhibited more low frequency theta waves in the frontal lobes were also more likely to remember their dreams.

This finding is interesting because the increased frontal theta activity the researchers observed looks just like the successful encoding and retrieval of autobiographical memories seen while we are awake. That is, it is the same electrical oscillations in the frontal cortex that make the recollection of episodic memories (e.g., things that happened to you) possible. Thus, these findings suggest that the neurophysiological mechanisms that we employ while dreaming (and recalling dreams) are the same as when we construct and retrieve memories while we are awake.

In another recent study conducted by the same research team, the authors used the latest MRI techniques to investigate the relation between dreaming and the role of deep-brain structures. In their study, the researchers found that vivid, bizarre and emotionally intense dreams (the dreams that people usually remember) are linked to parts of the amygdala and hippocampus. While the amygdala plays a primary role in the processing and memory of emotional reactions, the hippocampus has been implicated in important memory functions, such as the consolidation of information from short-term to long-term memory.

The proposed link between our dreams and emotions is also highlighted in another recent study published by Matthew Walker and colleagues at the Sleep and Neuroimaging Lab at UC Berkeley, who found that a reduction in REM sleep (or less “dreaming”) influences our ability to understand complex emotions in daily life – an essential feature of human social functioning.  Scientists have also recently identified where dreaming is likely to occur in the brain.  A very rare clinical condition known as “Charcot-Wilbrand Syndrome” has been known to cause (among other neurological symptoms) loss of the ability to dream.  However, it was not until a few years ago that a patient reported to have lost her ability to dream while having virtually no other permanent neurological symptoms. The patient suffered a lesion in a part of the brain known as the right inferior lingual gyrus (located in the visual cortex). Thus, we know that dreams are generated in, or transmitted through this particular area of the brain, which is associated with visual processing, emotion and visual memories.

Taken together, these recent findings tell an important story about the underlying mechanism and possible purpose of dreaming.

Dreams seem to help us process emotions by encoding and constructing memories of them. What we see and experience in our dreams might not necessarily be real, but the emotions attached to these experiences certainly are. Our dream stories essentially try to strip the emotion out of a certain experience by creating a memory of it. This way, the emotion itself is no longer active.  This mechanism fulfils an important role because when we don’t process our emotions, especially negative ones, this increases personal worry and anxiety. In fact, severe REM sleep-deprivation is increasingly correlated to the development of mental disorders. In short, dreams help regulate traffic on that fragile bridge which connects our experiences with our emotions and memories.

Are you a scientist who specializes in neuroscience, cognitive science, or psychology? And have you read a recent peer-reviewed paper that you would like to write about? Please send suggestions to Mind Matters editor Gareth Cook, a Pulitzer prize-winning journalist at the Boston Globe. He can be reached at garethideas AT gmail.com or Twitter @garethideas .

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18 Interesting Psychology Research Paper Topics On Dreams

People have been interested in the topic of dreams since the early years of human civilization. Modern psychology allows us to learn more about dreams but there are still a lot of questions that we don’t have answers to. If you have to write a research paper about dreams, there are plenty of interesting topics to choose from.

The List of Research Paper Topics about Dreams

• A detailed definition of a dream.
• The reasons for us to dream.
• People who don’t have dreams.
• The duration of a dream.
• The meaning of dreams.
• The formula of most dreams.
• The features of lucid dreams.
• The nature of nightmares.
• Ways to deal with anxiety dreams.
• The meaning of repetitive dreams.
• Patients with REM behavior disorder.
• Dreams with empty emotional content.
• Dreams that portend psychosis.
• Measures to take for remembering more of your dreams.
• Dreams of animals.
• Remembering dreams under hypnosis.
• Sigmund Freud’s theory about dreams.
• Psychotherapy and dreams.

Tips for Writing Your Psychology Project

To get an excellent grade for your work, you should organize it in a correct order. First, pick an interesting topic like the ones above. Then, look for books and other sources to gain deep knowledge about the background of the question that you’re going to discuss. The next step is to make your own analysis and carry out your own experiments. Only when you have some research results, you may start writing.

Make a good outline in order to follow it during the writing process. This will help you remember to include every important detail in your text. You may start writing with body chapters rather than with an introduction, however. Usually, if you start with an introduction, you might have to make changes in it later. The contents of the body chapters might differ a little bit from your initial ideas.

Don’t forget to edit your paper so that it doesn’t contain typos and grammar mistakes. You should also format it in accordance with the requirements of your psychology teacher if you want to submit it without problems at the first attempt.

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College Minor: Everything You Need to Know

14 fascinating teacher interview questions for principals, tips for success if you have a master’s degree and can’t find a job, 14 ways young teachers can get that professional look, which teacher supplies are worth the splurge, 8 business books every teacher should read, conditional admission: everything you need to know, college majors: everything you need to know, 7 things principals can do to make a teacher observation valuable, 3 easy teacher outfits to tackle parent-teacher conferences.

Research Topics About Dreams

• What Dreams Are Possible?
• What Do All Athletes Dream of, But Few Achieve?
• What Fulfills Your Friend’s Dreams?
• What Are Dreams According to the Bible?
• When Do Reality and Dreams Collide?
• How Come We Forget Our Dreams?
• What Fascinates Philosophers About Dreams?
• What Characterizes A Nightmare?
• What Dream Comes True Most Often?
• What Are the Most Common themes in Nightmares, and What Do They Mean?
• Why Do Duddy Kravitz’s Dreams Matter to Him?
• What Do Dreams Mean, And Why Do People Dream them?
• What Are Dreams, and Do They Have Positive or Negative Effects on Us?
• What Are the Main Parallels and Disparities between Freud’s and Jung’s Dream Theories?
• How Are You Moving Toward Your Goals?
• How Do Dreams Affect Who We Are?
• How Can Dreams and Omens Relate to the Interconnectedness theme?
• How Do Dreams Help People Get Through Life or Destroy them When They Don’t Come True?
• What Is the Symbolic Meaning of Dreams?
• How Can Women Follow Their Dreams Without Feeling Self-Conscious?
• What Different Things Do People Use to Reduce Problems in Life or Find Inspiration for Dreams?
• Can Dreams Predict the Future?
• Are Dreams Signs from Our Subconscious Minds or Meaningless Manifestations?
• Are Dreams the Cause of Mythology?
• Can the Blind See Dreams?
• What Dreams Are the Most Uncommon?
• How Much Time Do Dreams Last?
• Can You Gain Knowledge from Your Dreams?
• Do Dreams Differ Around the World?
• Do We Understand When We Dream?

Research Topics on Domestic Violence

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7 Major Questions (and Answers) About Dreaming

Dreaming is a mysterious process — one that scientists are still figuring out..

Posted July 28, 2017 | Reviewed by Ekua Hagan

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As a sleep specialist, not a day goes by that I don't talk to someone about their dreams. My patients, my kids, the guy who sells me my morning coffee — everyone wants to know, “What do my dreams mean?” We’re all fascinated by dreams, and understandably so. Dreaming is a strange and mysterious process — one that we still don’t fully understand. Let’s take a closer look at the stuff of which dreams are made:

1. Why Do We Dream?

The why of dreaming is one of the great mysteries of sleep. There are many theories about why dreaming happens. Some think that dreaming has no specific underlying purpose, that our dreams might be a byproduct of other things going on in the brain during sleep. But many researchers studying sleep and dreams believe there is a primary purpose to our dreams. Some theories suggest that dreams are:

• A way to process memory and learning, moving memories from short-term to long-term storage and giving the brain a clean slate before the next waking day.
• A way to maintain emotional balance, by working through difficult, complicated, unsettling thoughts, emotions, and experiences.
• A different state of consciousness that unites past, present, and future — to process information from the first two, and prepare for the third.
• A kind of dress rehearsal for the brain, to prepare itself to face threats, dangers, and challenges in waking life.
• The brain responding to biochemical changes and electrical impulses that occur during sleep.

There may not be a single answer to why we dream. Our dreams might serve several purposes at once.

2. What Is a Dream? Do We All Dream?

At its most basic level, a dream is a collection of images, impressions, events, and emotions that we experience during sleep. Sometimes dreams have real storylines, with plots and characters that could be plucked from a movie screen. Other times dreams are more impressionistic, filled with emotions and visual imagery.

Typically, a person will spend two hours or more a night dreaming, experiencing somewhere between 3 to 6 dreams over the course of a night’s rest. Most dreams appear to last from 5 to 20 minutes.

I often hear people say, “I don’t dream.” You may not remember your dreams, but that doesn’t mean you’re not having them. Dreaming is a universal human experience. The truth is, the vast majority of dreams we experience will — for most of us — never be remembered. Memories of dreams usually fade very quickly after we awaken.

3. Why Can’t I Remember My Dreams?

The ability to recall dreams varies greatly from one individual to another. Some people regularly remember their dreams, while others may have only hazy recollections of themes or subjects — or no recollection at all.

There are a number of possible explanations for this. Studies suggest dream recall may be linked to patterns of activity in the brain. Our ability to recall our dreams may be influenced by interpersonal attachment styles — the way we tend to form bonds with other people in our lives.

Changing hormone levels throughout the night might also have a role in our ability to recall our dreams. During REM sleep — a time of active dreaming — levels of the hormone cortisol are high and may interfere with communication between areas of the brain that are involved in memory consolidation.

Our most active dreaming occurs during REM sleep. Adults spend roughly 25 percent of their sleep time in REM sleep, with longer periods of REM sleep occurring later in the night and in the early morning.

REM sleep is one part of the normal sleep cycle . In addition to REM sleep, sleep cycles contain three other stages. Dreaming can occur in every stage of sleep. Dreams during REM sleep appear to be more visually vivid, bizarre, and narratively driven than dreams during other sleep stages.

Have you ever woken and not been able to move or speak? This scary sleep phenomenon is indirectly related to dreaming. During REM sleep, the body goes into a state of temporary paralysis, a condition known as REM atonia. This appears to be the body’s way of protecting itself during dreaming. REM atonia keeps us from acting out physically in response to dreams. Think of some of the scary or exciting dreams you’ve experienced. Maybe you’ve been flying over a mountain range, or been chased by a masked intruder. Imagine if you could respond physically to these dream experiences? You might fly yourself right out of bed onto the floor.

It’s possible to awaken and still be in a state of sleep paralysis. This can be a really frightening experience, particularly the first time it happens. Waking in sleep paralysis is a sign that your body may not be making smooth transitions between the stages of sleep. This can be the result of stress, sleep deprivation, and other sleep disorders including narcolepsy, as well as a side effect of medications or over-consumption of drugs or alcohol .

4. Are There Different Kinds of Dreams?

Not all dreaming is the same. Dreaming runs the gamut of human experience. Our dreams encompass a dizzying range of emotions and events — and sometimes they’re just downright bizarre. Dreams can be funny, frightening, sad, and strange. Flying dreams can be euphoric, chasing dreams can be terrifying, forgot-to-study-for-my-exam dreams can be stressful .

There are several different types of dreams, including recurring dreams, wet dreams, and lucid dreams. (Nightmares are their own special kind of dream, which I’ll talk about in a separate article.) Let’s look at some distinct forms of dreaming.

Recurring dreams may contain more threatening and disturbing content than regular dreams. Research suggests there are links between recurring dreams and psychological distress in both adults and children.

Wet dreams are also called nocturnal emissions. These dreams involve ejaculation during sleep, usually accompanied by a sexual dream. Wet dreams may happen to boys during puberty , when testosterone starts to be produced in the body, and they are a normal part of healthy development.

Lucid dreams are an especially fascinating form of dream. In lucid dreams, the dreamer is aware of the fact that he or she is dreaming. Lucid dreamers often can even manipulate or control their dream as it unfolds. It seems that lucid dreaming is related to unusually elevated levels of brain activity. Lucid dreamers have shown significantly higher brain wave frequencies than non-lucid dreamers, as well as increased activity in parts of the frontal lobe of the brain. This area of the brain is deeply involved with our conscious awareness, a sense of self, as well as language and memory. Research into lucid dreams is not only shedding light on the mechanics of dreaming but also teaching us about the brain and about consciousness itself.

5. What Are the Most Common Dreams?

Examining and interpreting the content of dreams has fascinated people since ancient times. In ancient cultures, dream interpreters were sought-after and revered experts. Most of what we know today about dream content has been gathered using dream reports and questionnaires. Dream experiences vary widely, but some well-established themes occur among many dreamers across ages and cultures, including:

• School dreams (studying, taking tests)
• Being chased
• Sexual dreams
• Being attacked physically
• Dreaming of someone dead being alive, or someone alive being dead

New brain-imaging technology is allowing scientists to peek into dreaming minds like never before. Scientists are now analyzing brain activity during sleep to decode the content of dreams. A group of scientists in Japan has been able to predict dream content using MRI imaging with 70 percent accuracy. Scientists at the University of Wisconsin-Madison recently found that the areas of the brain used to perform tasks in our waking lives are also used for those tasks in dreams. One example: If a dream involves movement, the area of the brain used for movement perception becomes more active.

6. How Much of Dreaming Comes From My Daily Life?

Our waking lives seem to have an enormous influence over our dreams. A significant percentage of the people who appear in dreams are known to the dreamer. One study found more than 48 percent of dream characters were recognizable by name to dreamers. Another 35 percent of characters were identifiable to dreamers by their generic social role or relationship — as a friend, or a doctor or police officer, for example. Fewer than one-fifth of dream characters — 16 percent — were unrecognizable to dreamers.

A lot of our dreams contain content that’s related to autobiographical memories — memories about the self. Pregnant women dream more about pregnancy and childbirth. Hospice workers who act as caregivers to others dream about the experiences of caregiving and the people for whom they care. Musicians dream twice as often about music as non-musicians do.

There’s also some fascinating research that shows our capacity to dream beyond our waking experiences. Dream reports of people born paralyzed reveal that they walk, swim, and run in their dreams as often as people without paralysis. Dream reports of people born deaf indicate they often hear in their dreams.

Daily life experiences don’t always present themselves in dreams immediately. Sometimes an experience from life will filter through to a dream after several days or even a week. This delay is what’s known as dream lag. Scientists studying the relationship of memory to dreams have identified different types of memory that can be incorporated into dreams. Both very short-term memories (known as day-residue) and slightly longer-term memories (from a period of about a week) often present themselves in dreams. Dreaming of these events may actually be an important part of the memory consolidation process. The incorporation of memories into dreams isn’t necessarily seamless or even realistic. Rather, memories from waking life often appear in dreams in incomplete pieces, like shards of glass from a broken mirror.

As much as dreams may contain aspects of everyday, routine life, dreaming is also a state in which we can contend with extraordinary and difficult experiences. Another possible function of dreaming is processing and coming to terms with traumatic events. Grief , fear , loss, abandonment, even physical pain, are all emotions and experiences that often replay themselves in dreams. Studies of people who’ve experienced the loss of loved ones indicate that most of them dream about the deceased. Grieving people report several similar themes to these dreams, including:

• Recalling past experiences when loved ones were alive.
• Seeing loved ones happy and at peace.
• Receiving messages from loved ones.

The same study found that 60 percent of bereaved dreamers said their dreams exerted influence over their grieving process.

7. Can Dreaming Give Me a Performance Boost?

Dreams may help us solve problems and be creative. One study of musicians’ dreams found that not only did they dream frequently of music, but nearly half of the music they recalled from their dreams was unfamiliar and novel to them, suggesting that composing is possible in dreams. Paul McCartney famously credited the composition of "Yesterday” to a dream. Other artists, from the poet William Blake to the filmmaker Ingmar Bergman, have claimed to rely on dreams for creative inspiration and guidance. The golfer Jack Nicklaus said he sorted out a nagging problem with his golf swing in a dream.

Dreaming can help with at least some types of problem-solving. Lucid dreamers can use their dreams effectively to solve creative problems, according to research. Dreams seem to be fertile territory for influencing and enhancing our waking frame of mind.

Dreams can provide us with insight into what is preoccupying our minds and our hearts. Often healing, often mysterious, always fascinating, dreams can both shape us and show us who we are.

Michael J. Breus, Ph.D. , is a clinical psychologist and a diplomate of the American Board of Sleep Medicine. He is the author of Beauty Sleep.

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A Great List Of Unique Topics For Psychology Essays About Dreams

Writing an essay on Dreams can be an overwhelming task to take on. For one, dreams are interpreted through our unconscious state of mind. So, how do you write about something that is actually open to interpretation? Well, you read as much about how dreams work within the mind as possible. Stick to the facts that you find, do thorough research, and know all of the surrounding factors that make dreams happen and where they come from. You will be able to write an informative essay with a well thought out thesis once you know the facts about how dreams work. With that covered, let’s discuss five unique topics on dreams:

Dreams are the direct connection to the soul.

Until recently, psychologists and most of the modern science community did not believe the soul was anything more than a figment of the imagination or a basis determined by religious affiliations. However, that view may be changing, and this would be an interesting topic to delve into. This could even be a fabulous, groundbreaking dissertation for those Graduate School students out there.

Could dreams be a foretelling of the future?

There are many who believe dreams are an unconscious fortune-teller. Maybe with enough homework, you can discover if there is any actual truth to this. It may take many generations before any truth can be found. Or, will we ever truly know?

Can dreams be a foreteller of whether or not a person grows up to be a killer?

Some believe that dreams are a leftover part of our uncivilized, animalistic selves wanting to revert to a primitive time. This would be an interesting topic to discuss and write a term paper on in one of your Psychology classes.

Do dreams reveal who we are as a person?

Can there be a connection between our dreams and what type of personality we have? With enough research, you may find yourself discovering a link between the two. At the very least you will have written a unique, thought-provoking paper that is rather informative.

Dreaming is a healthy exercise your brain needs to completely process learned information.

This is another great topic for a dissertation. To be able to piece together whether dreams are a natural exercise for the brain would be fascinating work. There are no telling how many grants you could get to do further research on this topic after graduation.

You now have five unique topics to write a paper on. Psychology may never be the same after you research these topics. Put your mind to work and think of your own unique topics and see what you come up with. Maybe you do ground-breaking work and become a freelance professional for everything dream related.

Once the writing is done, the student has just a rough draft. For this rough draft to become a final draft, the student needs to edit it first. Students may want to change the font size for a larger one so that the writing seems new. This will make it easier to spot errors as the student reads through their work. The student may also want to ask a teacher or friend for help so that they can catch every error that occurs in their writing.

Compare & contrast paper

Informal essay format

Argumentative paper on gay marriage

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The big idea: what if dreaming is the whole point of sleep?

Rather than being an optional extra, dreams might be vital to our functioning

E xposed, the undulating surface of the brain is shimmering and opalescent, punctuated with arteries and veins. Give any part of it the tiniest jolt of electricity with a pen-like probe and it will activate the neurons in that spot. Neurosurgeons use this technique during some types of brain surgery to locate the source of seizures, or to avoid damaging vital tissue.

While the procedure is happening, the patient is awake, but feels nothing, since the brain doesn’t have so-called nociceptors, or pain sensors . Because the thin, outermost layer is responsible for consciousness, language, perception, memory and thought, moving the probe from spot to spot can reveal quite a lot. It can trigger smells, memories of childhood – even nightmares. Use the probe to touch a particular part of the brain: nightmare on. Remove the probe: nightmare off. In this way, I’ve witnessed first-hand how dreams are truly part of the neural architecture. They’re very much built into our bodies.

I’ve also observed the power of dreams to persist in the face of terrible injury. I’ve seen how children who have had half their brains removed as a last-resort treatment for intractable seizures still report dreaming. I have come to realise that virtually everyone has dreams, though we often don’t remember them. And of course, people born blind dream. They make up for their lack of visual content by experiencing more sound, touch, taste and smell than sighted people.

Recent research suggests that dreams may also play a bigger role in our sleep than previously thought. For decades, scientists studying dreaming focused on only one stage of sleep, so-called rapid eye movement, or REM, sleep. They concluded that we spend about two hours a night dreaming, more or less. If you do the maths, this adds up to about a 12th of our lives immersed in dreams, a month out of every year. That would represent an enormous commitment to dreaming. But it turns out that even that may be a gross underestimate. When researchers at sleep labs wake up study participants at different points – not just during REM sleep – they find that dreaming is possible at any stage. It’s conceivable that we actually spend almost a third of our lives dreaming.

Dreams are the product of profound changes the brain automatically undergoes each night. The rational, executive network in the brain is switched off, and the imaginative, visual and emotional parts are dialled way up. As a result, the dreaming mind is given free rein in a way that has no parallel in our waking lives. We couldn’t think this way when we are awake even if we tried.

Far from being dormant, the sleeping brain burns glucose and pulses with electricity to produce dreams. But why devote this kind of energy to the creation of wildly imaginative and highly emotional nocturnal experiences for an audience of one – especially when they often seem nonsensical? I’m confident that we wouldn’t expend the resources required for dreaming, while leaving ourselves more vulnerable to predators, unless dreams were a vital feature of our minds.

There are a number of theories that attempt to explain the evolutionary benefits of dreaming. These include keeping our minds nimble while we sleep, making us more intuitive, giving us outrageous scenarios so we can better understand the everyday, serving as an overnight therapist, and rehearsing threats so that we’re better prepared. Evidence for the latter includes one study that showed prospective medical students who had dreamed about things going terribly wrong during their entrance exam tended to do better when they took it the following day.

I believe there may be some truth to all of these theories. As our brains have evolved over millions of years, it seems reasonable that the role of dreams has expanded and evolved with them. We don’t try to find a single evolutionary benefit for waking thought. Why should we attempt to constrain the purpose of dreams?

During my training, I spent some time in transplant surgery. When we put in hearts and lungs, kidneys and livers, we never connected the nerves. Give that some thought for a moment, as I have. What I realised was that our most vital organs are passive participants in the sleeping body. This suggests to me that it’s not so much the body that needs to sleep, but the brain. In fact, the dreaming brain shuts the body down through a form of chemical paralysis, liberating itself to fully experience the dream without risking bodily injury by it being acted out.

What should we conclude from all of this? Essentially, that dreaming is not some optional extra, a kind of decoration on top of the serious business of sleep. No, we need to dream. If we’re sleep deprived, the first thing we catch up on is dreaming. Spend a whole night awake, as I often did during training, and the next night of sleep explodes into vivid, REM dreaming, rather than following the normal 90-minute sleep cycle. And if you’ve had enough sleep but are dream deprived (something only possible because of interventions made in a sleep lab), you immediately start dreaming as soon as you fall asleep again.

Even in the total absence of sleep, vivid dreams can emerge. Among people with fatal familial insomnia , a rare and lethal genetic disease that makes sleep impossible, the need is so strong that dreams escape their normal confines, leaking into waking life.

There is so much focus these days on the benefits of sleep for our mental and physical health. That’s entirely justified. But given the many potential benefits of dreaming for our waking life, maybe it’s not the sleep we really need, but the dreams.

Rahul Jandial is a neuroscientist and author of  This Is Why You Dream ( Cornerstone ).

Further reading

Why We Sleep : The New Science of Sleep and Dreams by Matthew Walker (Penguin, £10.99)

When Brains Dream : Exploring the Science and Mystery of Sleep by Antonio Zadra and Robert Stickgold (WW Norton, £13.99)

The Shapeless Unease : My Year in Search of Sleep by Samantha Harvey (Vintage, £9.99)

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Home — Essay Samples — Life — Dream

Dream Essays

Writing an essay on the topic of dreams is important as it allows individuals to explore their subconscious thoughts and desires. Dreams have fascinated people for centuries and have been the subject of much speculation and interpretation. By writing an essay on dreams, individuals can delve into the meaning and significance of their own dreams, as well as explore the cultural and psychological aspects of dreaming.

When writing an essay on dreams, it is important to consider the various interpretations and theories surrounding dreams. This can include the psychological perspective, where dreams are seen as a reflection of one's subconscious thoughts and emotions. It can also include the cultural and spiritual significance of dreams, as seen in various religious and cultural traditions.

It is also important to include personal experiences and examples in the essay. This can help to make the essay more relatable and engaging for the reader. Sharing personal dreams and their interpretation can add depth and insight to the essay, and can also help to connect with the reader on a more personal level.

When writing about dreams, it is important to approach the topic with an open mind and a sense of curiosity. Dreams are complex and multifaceted, and there is no one-size-fits-all interpretation. By approaching the topic with an open mind, individuals can explore the various facets of dreams and their significance in different contexts.

Overall, writing an essay on dreams is important as it allows individuals to explore the fascinating and enigmatic world of dreams. By considering the various interpretations, sharing personal experiences, and approaching the topic with an open mind, individuals can create a compelling and thought-provoking essay on dreams.

What Makes a Good Dream Essay Topics

When it comes to writing an essay about dreams, choosing the right topic is crucial. A good dream essay topic should be thought-provoking, inspiring, and unique. To brainstorm and choose an essay topic, start by reflecting on your own dreams and aspirations. Consider what interests you the most and what you are passionate about. It's also important to consider the audience and the purpose of the essay. A good dream essay topic should be relevant, timely, and impactful. Ultimately, a good essay topic is one that allows you to explore your creativity and express your thoughts and ideas effectively.

Best Dream Essay Topics

• The power of lucid dreaming
• The significance of recurring dreams
• The impact of dreams on mental health
• The symbolism of dream interpretation
• The connection between dreams and reality
• The role of dreams in shaping our future
• The cultural significance of dream mythology
• The science of dream analysis
• The influence of dreams on artistic creativity
• The role of dreams in problem-solving
• The psychology of nightmares
• The relationship between dreams and memory
• The impact of technology on dream experiences
• The role of dreams in spiritual practices
• The connection between dreams and emotions
• The influence of dreams on decision-making
• The role of dreams in understanding the subconscious mind
• The significance of dream journals
• The impact of dream deprivation on overall well-being
• The future of dream research and exploration

Dream Essay Topics Prompts

• If you could control your dreams, what would you dream about and why?
• Write a story about a dream that changed your perspective on life.
• Imagine a world where everyone's dreams were visible to others. How would society be different?
• What do your recurring dreams say about your deepest desires and fears?
• If you could bring one dream to life, what would it be and how would it impact the world around you?

Writing an essay about dreams can be an exciting and insightful journey. By choosing a unique and compelling topic, you can explore the depths of your imagination and share your insights with others. Whether you're interested in the science, psychology, or cultural aspects of dreams, there are endless possibilities for creative and thought-provoking essay topics. So, take the time to brainstorm and choose a topic that resonates with you, and get ready to embark on an inspiring writing adventure.

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103 American Dream Essay Topics & Examples

If you’re in need of American dream topics for an essay, research paper, or discussion, this article is for you. Our experts have prepared some ideas and writing tips that you will find below.

📃 10 Tips for Writing American Dream Essays

🏆 best american dream essay topics & essay examples, 👍 catchy american dream topics, ❓ american dream research questions.

The American dream is an interesting topic that one can discuss from various perspectives. If you need to write an essay on the American dream, you should understand this concept clearly.

You can choose to present the American dream as a miracle that one cannot reach or depict a free and wealthy nation. In any case, the American dream essay is a good opportunity to reflect on the concept and learn more about it.

There are many topics you can choose from while writing your essay. Here are some examples of the American dream essay topics we can suggest:

• The true meaning of the American dream
• The image of the American dream in the Great Gatsby
• Is the American dream still relevant in today’s society?
• The role of the American dream: Discussion
• Americans’ beliefs and values: The American dream
• Can we achieve the American dream?
• The American dream in today’s world and society

Remember that you do not have to select one of the American dream essay titles and can come up with your own one. Once you have selected the topic, start working on your essay. Here are ten useful tips that will help you to write an outstanding paper:

• Start working on your essay ahead of time. You will need some time to study the issue, write the paper, and correct possible errors.
• Do preliminary research on the issue you want to discuss. The more information you know about the question, the better. We advise you to rely on credible sources exclusively and avoid using Wikipedia or similar websites.
• Check out the American dream essay examples online if you are not sure that the selected problem is relevant. Avoid copying the information you will find and only use it as guidance.
• Write an outline for your essay. Think of how you can organize your paper and choose titles for each of the sections. Remember that you should include an introductory paragraph and a concluding section along with body paragraphs.
• Remember that you should present the American dream essay thesis clearly. You can put it in the last sentence of your introductory paragraph.
• Your essay should be engaging for the audience. Help your reader to know something new about the issue and include some interesting facts that may not know about. Avoid overly complex sentences and structures.
• Make your essay personal, if it is possible. Do not focus on your opinion solely but provide your perspectives on the issue or discuss your concern about it. You can talk about your experiences with the American dream, too.
• Provide statistical data if you can. For example, you can find the results of surveys about people’s perspectives on the American dream.
• The concluding paragraph is an important section of the paper. Present the thesis and all of your arguments once again and provide recommendations, if necessary. Remember that this paragraph should not include new information or in-text citations.
• Do not send your paper to your professor right away. Check it several times to make sure that there are no grammatical mistakes in it. If you have time, you can put the paper away for several days and revise it later with “fresh” eyes.

Feel free to find an essay sample in our collection and get some ideas for your outstanding paper!

• Essay on the American Dream: Positive and Negative Aspects The American dream is one of the most revered ideals of the nation and it has become a part of the American national identity.
• Michelle Obama American Dream Speech Analysis – Michelle’s purpose was to introduce her husband as man who was more concerned about the common citizens’ concerns and who was willing and able to help everyone to realize his/her American dream because he himself […]
• The American Dream by Edward Albee Play Analysis The American Dream play is an apologue of how American life has turned awry under the pretext of the American Dream.
• American Dream: “Fences” by August Wilson The American dream makes it clear through its guarantee of the freedom and equality with the promise of prosperity and success as per the ability or personal achievements of every American citizen.”Fences” reveals the obstacles […]
• American Dream in “The Pursuit of Happiness” Film In America today, there is a general belief that every individual is unique, and should have equal access to the American dream of life “life, liberty, and the pursuit of happiness”.
• The Tortilla Curtain: American Dream – Characters, Summary & Analysis The cultural difference between the two families is introduced by the author as a theme describing the role of gender in the community.
• American Dream After World War I People lost vision of what this dream was supposed to mean and it became a dream, not of the vestal and industrious, but of the corrupt coterie, hence corrupting the dream itself.
• The American Dream in The Great Gatsby After spending some time in this neighborhood, Nick finally attends Gatsby’s exuberant parties only to realize that Gatsby organizes these parties to impress Daisy, Nick’s cousin, and wife to Tom.
• American Dream and Socialism in the Book “The Jungle” by Sinclair The main idea of the book lies in upholding the Marxist belief of the inevitable collapse of capitalism and the accession of the proletariat, or industrial working class.
• Portrayal of the American Dream in the 20th Century Theatre However, different analysts criticized the use of the amelting pot’ in the play to show the pursuit of the American dream terming it as unrealistic in the sense that the term amelting’ creates a picture […]
• Willy Loman and the American Dream As a result of his boasting, a great deal of what his family knows about Willy is based upon the image he feels he must portray of himself in order to bring himself in line […]
• Femininity and the American Dream in Works of Chopin, Gilman, and Williams Even though the general understanding of the American dream was advertised to everyone, the idea was more applicable to the male members of the American society, which is reflected in Chopin’s “The Story of an […]
• Is the American Dream Still Alive? The American Dream can be defined as a summation of national values entrenched in the culture of the United States. In this regard, the minority groups in the United States are often on the receiving […]
• Meritocracy and the American Dream In the perception of such people, the American Dream is directly connected to meritocracy, i.e.a judgment on people on their individual abilities rather than the connections of the families, and in that regard such perception […]
• Whitman, Hughes, and the American Dream Walt Whitman and Langston Hughes, two prominent figures of American poetry of the past, are of them.”I Hear America Singing,” “I, Too,” “Harlem,” and “The Negro Speaks of Rivers” are the emotional responses to the […]
• The American Dream in Arthur Miller’s Plays Willy has a distorted vision of the American Dream, and he has such blind faith in this inaccurate vision that it leads to his mental disturbance when he is not able to accept how the […]
• American Dream of Early Settlers He did not tell the settlers of the difficulties they were going to face in moving from Europe to the land of honey that is America.
• The Corrupted American Dream and Its Significance in “The Great Gatsby” The development of the American dream and its impact on the society of the United States is a pertinent topic of discussion for various authors.
• The Dilemmas of the American Dream in The Great Gatsby The Great Gatsby is a story of a young man in the early twentieth century who seems to know what he wants in the way of that dream and what to do to achieve it.
• The American Dream, Social Status and Hierarchies The persistence of social status and hierarchies in modern-day America undermines the possibility of realizing Winthrop’s ideal community as a goal for the current American Dream, considering his argument of wouldivinely ordained’ holds no traction […]
• The American Dream and Its Roots The tension between the ideals of the American Dream as espoused by the Puritans and the realities of American life has been a recurrent theme in American history.
• Tensions in the American Dream The imbalance can lead to debates and discussions about the meaning and purpose of the American Dream, as well as a conflict between the ideals of freedom and agency and the desire for a more […]
• Support of the American Dream Act of 2001 In contrast to many supporters of the American Dream Act, some individuals claim that the policy promotes the entrance of illegal immigrants.
• The Possibility of Realizing the American Dream Thus, according to the author, the American dream is only a fantasy. Returning to the ideas of Krugman, Cox and Alm, and Dalmia, it seems necessary to highlight some aspects.
• The American Dream: Meaning and Myth Initially, the existence of this myth set a very high pace and performance for the American economy because it was the only way to achieve the desired level of prosperity.
• Reflection on the American Dream Concept The vision of the American Dream can be different for individuals, and people create their interpretations according to their specific experiences.
• Reaching the American Dream From Scratch For example, the experience of a person coming to the United States from Haiti is one of poverty, under-resourced communities, and a complete disillusion with the promise of a good life.
• The American Dream Based on “Re Jane” by Patricia Park The main difference is that Jane had a chance to live her dreams in New York than in Seoul. Nina is an example of Jane’s friends who want her to succeed and understand the flaws […]
• The American Dream in Boyle’s The Tortilla Curtain The personal experience of the characters can be explained by their varying life conditions and, hence, are linked to the notion of the American Dream, which can be achieved by everyone while the efforts differ.
• Fitzgerald’s ‘The Great Gatsby’, Steinbeck’s ‘Of Mice and Men’ and the American Dream “The America Dream’ is a longstanding common belief of the American population that in the United States, people are free to realize the full potential of their labor and their talents and every person in […]
• Color Adjustment: False Image of American Dream The documentary tells the story of white, well-dressed people advertising the American dream, completely ignoring that the U.S.is not only a country of the white race.
• The American Dream: Franklin’s and Douglass’s Perception The objective of this paper, therefore, is to discuss the topic of the American dream and how both Franklin and Douglass, each exemplify this dream.
• The American Dream and Success One of the most pertinent topics associated with the American Dream is taking the courage to act and seize the opportunity.
• The Concept of American Dream: Examples of Columbus and Bradstreet Bradstreet’s other dream was to be able to secure a position in the ‘New world’ and still be seen as a woman who cares for her family.
• Racial Wealth Gap and the American Dream The speaker evaluates the accumulative wealth of Blacks, Hispanics, and Whites in America and arrives to the conclusion that race plays a role in financial burdens that many people of color experience.
• American Dreams: The United States Since 1945 Although the major idea of the book is a critical one, the author’s intention does not concern analyzing approaches to the American social evolution in order to define the most adequate one.
• History of Achieving the American Dream James Truslow Adams who wrote the book “The Epic of America” defined the American dream as “that dream of a land in which life should be better and richer and fuller for everyone, with opportunity […]
• The American Dream in the 21st Century It is the labor of these people that allowed the country to afford to build its industry and set up a base for fulfilling the American Dream.
• The American Dream: Defining the Great Society For instance, the Medicare bill was for the elderly and the poor, human rights for the oppressed, and antipoverty laws that set a stage for growth in the society.
• American Literature and the American Dream The difference in how the dream is defined lies in how one sees the shape and color of the concoction, whether the texture is just right for the shape of the taste buds assessing the […]
• American Dream and Reality for Minorities The topic of our concern is the reality that is faced by women, blacks, and war veterans who are associated with the American army.
• Richard Rodriguez’s Opinion on Migration and the American Dream American seems to refer only to the citizen of the United States and does not include the rest of the people in the continent!
• American Dream Is Not a Myth The paper is based on the argument, a simplified definition of the American dream: the American dream can be defined as “the achievement of economic and social advancement through hard work and determination”.
• The Immigrant Experience and the Failure of the American Dream The fates of the heroes of the book amaze with their tragedy, and this is the story of slaves of wage labor.
• Tycoons and Their American Dream The American Dream as Rockefeller, Carnegie, Morgan, and others saw it and forged it to be seen by others contributed meaningfully to the values of the American people and the priorities of a nation.
• Theater Exam: American Dream and Family Legacy To start the discussion on the concept of American Dream, I would like to focus on Willy, the main character of the Death of a Salesman.
• Is the American Dream Still Alive? The topic of discussion in this setting would be the American dream and the factors associated with the quest. They would talk about the cost of living, the cost of education, and the fact that […]
• American Dream in Miller’s “Death of a Salesman” The play Death of a salesman is indeed an anatomy of the American dream especially because the plot of the story revolves around some of the basic material gains that individuals in the American society […]
• “American Dream” of English and Chinese Immigrants My family decided to move to the US from England because of the low wages in our town. My intentions were to explore the new opportunities of the West and to earn more money than […]
• The American Dream and Working Conditions In fact, it might be said that it is due to their efforts that the American Dream still exists as a piece of reality.
• American Dream and Equity of Outcome and Opportunity The American dream is one of the most famous declarations of the world and the American subsequent governments have kept the dream alive for the last hundred years.
• Park Avenue: Money, Power and the American Dream This is one of the drawbacks that should be taken into account by the viewers who want to get a better idea about the causes of the problems described in the movie.
• American Dream in Hansberry’s and Miller’s Tragedies Hansberry’s “A Raisin in the Sun” and Miller’s “Death of a Salesman” tell the stories about how people can perceive and be affected by the idea of the American Dream, how they choose wrong dreams […]
• Park Avenue: Money, Power and the American Dream – Movie Analysis It can be taken as the national ethos of the citizens of the USA. The basis of the American society is broken and it is not united anymore.
• Music Talent Shows and the American Dream Talent search shows, like American Idol and The Voice, have suffered a lot of criticism for different reasons. Stanley says the main reason for this cynicism is the failure of such shows to focus on […]
• Michelle Obama’s Remarks on American Dream She added that the main goal was to secure the blessings of liberty and to bring about the fulfillment of the promise of equality.
• The American Dream’s Concept The American economy is also likely to improve as a result of realizing the American dream 2013 since most of the residents are likely to indulge in productive activities as stipulated in the American dream […]
• The Concept of Progress or the Pursuit of the American Dream The concept of progress or the pursuit of the American Dream since 1930s has been a matter of concern for many immigrants who believe that they can achieve much in the US than in their […]
• The Book American Dream by Jason DeParle From the name of the book, it is clear that the cardinal theme of the book is the American dream. This is contrary to the fact that she was pregnant and in a crack house.
• The Definition of the Great American Dream: Hearing Opportunity Knock Although the concept of the American Dream is very recognizable, its essence is very hard to nail down, since it incorporates a number of social, economical and financial principles; largely, the American Dream is the […]
• The American Dream Negative Sides and Benefits The United States is thought of as the land of opportunity and there are many people who want to live “The American Dream”.
• Role of Money in the American Dream’s Concept Many people lack the meaning of the American dream because they are always looking forward to find opportunity and fail to realize that the opportunity to succeed is always around them in the work they […]
• The Reality of American Dream The government encouraged the immigration of the population whose labor and skills were required in the United States. The housing in the urban was overcrowded with very unsanitary conditions, and some of the immigrants did […]
• Social Status Anxiety and the American Dream The pain of a loss and the status anxiety that came with being inferior to other students at Harvard instigated the urge to revenge and brought a desire to achieve success.
• Francis Scott Fitzgerald & His American Dream In the novel “Tender is the Night,” Fitzgerald describes the society in Riviera where he and his family had moved to live after his misfortune of late inheritance.
• American Dream: Is It Still There? It is a dream for immigrants from the Middle East to be in America; a country where discrimination is history and where no one will prevent them from achieving their dreams in life.
• The American Dream: Walt Disney’s Cinderella and Ron Howard’s Cinderella Man This is attributed to the fact that the original ideas and the fundamental principals that founded the dream are quickly fading away given the changing fortunes of the average American.
• The Death of the American Dream It is the moral decay that leads to the loss of freedom, the very essence of the founding of the American dream.
• American Dream and Unfulfilling Reality Living the American dream is the ultimate dream for most of the American citizens and those aspiring to acquire American citizenship.
• Inequality and the American Dream It is only after the poor workers are assured of their jobs that the American model can be said to be successful.
• A Response to the Article “Inequality and the American Dream” It has drawn my attention that other world countries embrace the “American model” since the super power has enormous wealth and its economic development is marked by up-to-date juggernauts of globalization and technology.
• In Pursuit of the American Dream: An Analysis of Willa Cather’s O Pioneers The experiences of the characters in the novel portray the endeavors of the early immigrants’ pursuit of the American dream. The instinct to forgo the comforts, which a home country offers by default and then […]
• Fitzgerald’s American Dream in The Great Gatsby & Winter Dreams To my mind, Winter Dream is a perfect example of the American Dream, since the main hero, Dexter, implemented each point of it, he was persistent and very hard-working, he was a very sensible and […]
• How Did Ben Franklin Exemplify the American Dream?
• Does Fitzgerald Condemn the American Dream in “The Great Gatsby”?
• How Do Benjamin Franklin and Frederick Douglass Represent the American Dream?
• Has America Lost Its Potential to Achieve the American Dream?
• How Has Disney’s Social Power Influenced the Vision of the American Dream?
• Does the American Dream Really Exist?
• How Does the Great Gatsby Portray the Death of the American Dream?
• What Does “The Great Gatsby” Have to Say About the Condition of the American Dream in the 1920s?
• How Does One Achieve the American Dream?
• What Are the Greatest Obstacles of Full Access to the American Dream?
• How Has the American Dream Been Translated Into Popular Film?
• What Does the American Dream Mean to an Immigrant?
• How Does Arthur Miller Through “Death of a Salesman” Deal With the Theme of the American Dream?
• What Must Everyone Know About the American Dream?
• How Has the American Dream Changed Over Time?
• What Is Infamous About the American Dream?
• How Does Millar Portray His Views of the American Dream Using Willy Loman?
• When Did American Dream Start?
• How Has the Media Changed the American Dream?
• Who Would Think the American Dream Isn’t Possible?
• How Does Steinbeck Present the American Dream in “Of Mice and Men”?
• Why Will Equal Pay Help Women Achieve the American Dream?
• How Might the Disadvantage of Immigration Affect the Chances of Having That American Dream?
• Why Is the American Dream Equally Given and Registered To All Citizens?
• How Does Extreme Inequality Make the American Dream Inaccessible?
• Why Is the American Dream Still Alive in the United States?
• How Are Millennials Redefining the American Dream?
• Why Is the American Dream Unattainable?
• How Does Society Influence the Idea of the American Dream?
• Why Must the United States Renew Opportunities to Achieve the American Dream to Reform Immigration Policy?
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Technological Progress and Rent Seeking

We model firms’ allocation of resources across surplus-creating (i.e., productive) and surplus-appropriating (i.e., rent-seeking) activities. Our model predicts that industry-wide technological advancements, such as recent progress in data collection and processing, induce a disproportionate and socially inefficient reallocation of resources toward surplus-appropriating activities. As technology improves, firms rely more on appropriation to obtain their profits, endogenously reducing the impact of technological progress on economic progress and inflating the price of the resources used for both types of activities. We apply our theoretical insights to shed light on the rise of high-frequency trading

The authors thank the editor Tarun Ramadorai, two anonymous referees, Salomé Baslandze, Philip Bond, Assa Cohen, Yao Deng, Winston Dou, Maryam Farboodi, Deeksha Gupta, Urban Jermann, Leonid Kogan, Ben Lockwood, Greg Nini, Christian Opp, Tom Sargent, Mathieu Taschereau-Dumouchel, Stephen Terry, Boris Vallée, Ed Van Wesep, Laura Veldkamp, Colin Ward, Ryan Zalla, Yao Zeng, and seminar participants at the American Finance Association meetings, the NBER Corporate Finance meeting, the Northern Finance Association meetings, the SFS Cavalcade, the Wash-U Corporate Finance conference, the University College London, and the Wharton School for their helpful comments. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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Researchers detect a new molecule in space

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New research from the group of MIT Professor Brett McGuire has revealed the presence of a previously unknown molecule in space. The team's open-access paper, “ Rotational Spectrum and First Interstellar Detection of 2-Methoxyethanol Using ALMA Observations of NGC 6334I ,” appears in April 12 issue of The Astrophysical Journal Letters .

Zachary T.P. Fried , a graduate student in the McGuire group and the lead author of the publication, worked to assemble a puzzle comprised of pieces collected from across the globe, extending beyond MIT to France, Florida, Virginia, and Copenhagen, to achieve this exciting discovery. 

“Our group tries to understand what molecules are present in regions of space where stars and solar systems will eventually take shape,” explains Fried. “This allows us to piece together how chemistry evolves alongside the process of star and planet formation. We do this by looking at the rotational spectra of molecules, the unique patterns of light they give off as they tumble end-over-end in space. These patterns are fingerprints (barcodes) for molecules. To detect new molecules in space, we first must have an idea of what molecule we want to look for, then we can record its spectrum in the lab here on Earth, and then finally we look for that spectrum in space using telescopes.”

Searching for molecules in space

The McGuire Group has recently begun to utilize machine learning to suggest good target molecules to search for. In 2023, one of these machine learning models suggested the researchers target a molecule known as 2-methoxyethanol. 

“There are a number of 'methoxy' molecules in space, like dimethyl ether, methoxymethanol, ethyl methyl ether, and methyl formate, but 2-methoxyethanol would be the largest and most complex ever seen,” says Fried. To detect this molecule using radiotelescope observations, the group first needed to measure and analyze its rotational spectrum on Earth. The researchers combined experiments from the University of Lille (Lille, France), the New College of Florida (Sarasota, Florida), and the McGuire lab at MIT to measure this spectrum over a broadband region of frequencies ranging from the microwave to sub-millimeter wave regimes (approximately 8 to 500 gigahertz). 

The data gleaned from these measurements permitted a search for the molecule using Atacama Large Millimeter/submillimeter Array (ALMA) observations toward two separate star-forming regions: NGC 6334I and IRAS 16293-2422B. Members of the McGuire group analyzed these telescope observations alongside researchers at the National Radio Astronomy Observatory (Charlottesville, Virginia) and the University of Copenhagen, Denmark. 

“Ultimately, we observed 25 rotational lines of 2-methoxyethanol that lined up with the molecular signal observed toward NGC 6334I (the barcode matched!), thus resulting in a secure detection of 2-methoxyethanol in this source,” says Fried. “This allowed us to then derive physical parameters of the molecule toward NGC 6334I, such as its abundance and excitation temperature. It also enabled an investigation of the possible chemical formation pathways from known interstellar precursors.”

Looking forward

Molecular discoveries like this one help the researchers to better understand the development of molecular complexity in space during the star formation process. 2-methoxyethanol, which contains 13 atoms, is quite large for interstellar standards — as of 2021, only six species larger than 13 atoms were detected outside the solar system , many by McGuire’s group, and all of them existing as ringed structures.  

“Continued observations of large molecules and subsequent derivations of their abundances allows us to advance our knowledge of how efficiently large molecules can form and by which specific reactions they may be produced,” says Fried. “Additionally, since we detected this molecule in NGC 6334I but not in IRAS 16293-2422B, we were presented with a unique opportunity to look into how the differing physical conditions of these two sources may be affecting the chemistry that can occur.”

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UGC NET 2024 Paper 1: List of topics you must prepare for

Apr 26, 2024

Teaching Aptitude

Teaching methods encompass various strategies such as lectures, discussions, and demonstrations, each suited to different learning objectives and audiences. A good teacher possesses qualities like patience, effective communication skills, and adaptability to engage and inspire learners.

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Classroom Management

Effective classroom management techniques are essential for maintaining a productive learning environment. This includes establishing clear expectations, managing behavior, and fostering positive relationships among students.

Evaluation Methods

Assessment methods such as assignments and tests are crucial for measuring students' understanding and progress. Choosing appropriate evaluation techniques aligned with learning objectives ensures fair and accurate assessment.

Learner's Characteristics

Understanding Piaget's stages of cognitive development helps educators tailor instruction to meet students' cognitive abilities. Recognizing diverse learning styles, including auditory, visual, and kinesthetic, allows for differentiated instruction to cater to individual needs.

Individual Differences

Every learner is unique, with varying abilities, backgrounds, and motivations. Acknowledging and addressing these differences is vital for creating inclusive learning environments and fostering student success.

Factors Affecting Teaching

Effective curriculum design is fundamental to facilitating meaningful learning experiences. Integrating teaching aids and technology enhances engagement and understanding, while the learning environment and external influences like parental involvement play significant roles in shaping learning outcomes.

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Infrastructure & learning environment.

The physical and social environment in which learning occurs significantly impacts student engagement and achievement. Providing adequate infrastructure and cultivating a supportive learning atmosphere are essential for maximizing learning potential

Teaching Methods

Utilising e-learning platforms like SWAYAM and MOOCs expands access to educational resources and promotes self-directed learning. Group discussions and collaborative learning activities foster critical thinking, communication skills, and peer interaction.

Problem-Solving and Critical Thinking

Encouraging problem-solving methods and critical thinking skills development empowers learners to analyze situations, explore alternatives, and make informed decisions. Balancing learner-centered and teacher-centered approaches fosters active engagement and deep understanding.

Research Aptitude

Differentiating between quantitative and qualitative research methodologies informs effective research design and data collection techniques. Upholding research ethics and avoiding plagiarism ensures the integrity and credibility of scholarly inquiry.

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The cognitive neuroscience of lucid dreaming

Benjamin baird.

a Wisconsin Institute for Sleep and Consciousness, University of Wisconsin-Madison, Madison, Wisconsin, USA

Sergio A. Mota-Rolim

b Brain Institute, Physiology Department and Onofre Lopes University Hospital - Federal University of Rio Grande do Norte, Natal, Brazil

Martin Dresler

c Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands

Lucid dreaming refers to the phenomenon of becoming aware of the fact that one is dreaming during ongoing sleep. Despite having been physiologically validated for decades, the neurobiology of lucid dreaming is still incompletely characterized. Here we review the neuroscientific literature on lucid dreaming, including electroencephalographic, neuroimaging, brain lesion, pharmacological and brain stimulation studies. Electroencephalographic studies of lucid dreaming are mostly underpowered and show mixed results. Neuroimaging data is scant but preliminary results suggest that prefrontal and parietal regions are involved in lucid dreaming. A focus of research is also to develop methods to induce lucid dreams. Combining training in mental set with cholinergic stimulation has shown promising results, while it remains unclear whether electrical brain stimulation could be used to induce lucid dreams. Finally, we discuss strategies to measure lucid dreaming, including best-practice procedures for the sleep laboratory. Lucid dreaming has clinical and scientific applications, and shows emerging potential as a methodology in the cognitive neuroscience of consciousness. Further research with larger sample sizes and refined methodology is needed.

1. Introduction

Becoming aware that one is dreaming while dreaming, what is today referred to as lucid dreaming , has been known about since antiquity. In Western literature, it may have first been mentioned by Aristotle in the fourth century BCE in the treatise On dreams of his Parva Naturali , in which he states: “often when one is asleep, there is something in consciousness which declares that what then presents itself is but a dream” ( Aristotle, 1941 , p. 624). Likewise, in Eastern cultures, particularly of the south Asian subcontinent, reports of individuals engaging in practices to cultivate awareness of dream and sleep states date back millennia ( LaBerge, 2003 ; Norbu and Katz, 1992 ; Wallace and Hodel, 2012 ). These include meditative practices specifically designed to “apprehend the dream state” ( Padmasambhava, 1998 , p. 156).

Although numerous references to lucid dreaming can be found throughout world literature (see LaBerge, 1988a for an overview), the modem nomenclature of lucid dream was not introduced until 1913 by the Dutch psychiatrist Frederik Van Eeden. In a detailed and engaging account of his personal experiences with dreams, Van Eeden (1913) referred to lucid dreams as dreams in which “…the reintegration of the psychic functions is so complete that the sleeper remembers day-life and his own condition, reaches a state of perfect awareness, and is able to direct his attention, and to attempt different acts of free volition” (pp. 149-150). Research over the last four decades has largely confirmed Van Eeden’s accounts: as we review below, evidence suggests that during lucid dreams individuals can be physiologically asleep while at the same time aware that they are dreaming, able to intentionally perform diverse actions, and in some cases remember their waking life ( Dresler et al., 2011 ; LaBerge, 1985 , 1990 ; LaBerge, 2015 ; LaBerge, Nagel, Dement and Zarcone, 1981c ; Windt, 2015 ).

Despite the fact that such personal accounts of lucid dreams have been described for centuries, the topic faced skepticism from some scientists and philosophers (e.g., Malcolm, 1959 ), in part due to the lack of objective evidence for the phenomenon. This began to change in the late 1970s and early 1980s, however, with the first validation of lucid dreaming as an objectively verifiable phenomenon occurring during rapid eye movement (REM) sleep. Building on prior research that showed that shifts in the direction of gaze within a dream can be accompanied by corresponding movements of the sleeper’s eyes ( Dement and Wolpert, 1958 ), lucid dreamers were asked to move their eyes in a distinct pre-agreed upon sequence (full-scale up-down or left-right movements) as soon as they became lucid ( Hearne, 1978 ; LaBerge et al., 1981c ).

Through this technique, which has since become the gold standard, reports of lucid dreams could be objectively verified by the presence of distinct volitional eye movement patterns as recorded in the electrooculogram (EOG) during polysomnography-verified sleep ( Figure 1 ). The most common version of the eye signaling technique asks participants to signal when they realize they are dreaming by rapidly looking all the way to the left then all the way to the right two times consecutively then back to center in the dream without pausing (referred to as left-right-left-right eye signals, abbreviated as LRLR). As can be seen in Figure 1 , the LRLR signal is readily discernable in the horizontal EOG, which exhibits a distinctive shape containing four consecutive full-scale eye movements that have larger amplitude compared to typical REMs. As we describe in detail below, lucid dreams can be validated by this method through the convergence between reports obtained after awakening of becoming lucid and making the eye movement signals during the dream, accompanied by the objective eye movement signals recorded in the EOG with concurrent polysomonographic evidence of REM sleep.

Exemplary left-right-left-right-center (LRLR) eye movement signal during polysomnographcally-verified REM sleep. Participants 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 two times consecutively then back to center without pausing. The LRLR signal is readily discernable in the HEOG, which exhibits a distinctive shape of four consecutive full-scale eye movements of higher amplitude compared to typical REMs. Note high-frequency electroencephalogram (EEG) with theta rhythm (~5 Hz) and lack of alpha at OZ as well as minimal electromyogram (EMG) amplitude due to muscle atonia characteristic of REM sleep (left) compared to wakefulness (right).

The eye signaling technique also offers a way of objectively contrasting lucid REM sleep to baseline non-lucid REM sleep, providing a method to investigate the changes in brain activity associated with lucid dreaming. Furthermore, lucid dreamers can not only signal to indicate that they are aware that they are dreaming, but they can also make the eye movement signals to time-stamp the start and end of experimental tasks performed during lucid dreams ( LaBerge, 1990 ). By providing objective temporal markers, this technique has opened up a new method for studying the psychophysiology of REM sleep, allowing, for example, investigations into the neural correlates of dreamed behaviors (e.g., Dresler et al., 2011 ; Erlacher, Schredl and LaBerge, 2003 ; LaBerge, 1990 ; Oudiette et al., 2018 ). Lucid dreaming thus provides a way to establish precise psychophysiological correlations between the contents of consciousness during sleep and physiological measures, as well as enables experimental control over the content of dreams, and therefore provides a potentially highly useful experimental methodology.

While neuroscientific studies on lucid dreaming have been performed since the late 1970s, the topic has received increasing attention in recent years due to its relevance to the emerging neuroscience of consciousness. In this article, we review the existing literature on the neuroscience of lucid dreaming, including electrophysiological, neuroimaging, brain lesion, pharmacological and brain stimulation studies. Additionally, we review recent studies that illustrate how lucid dreaming can be used as a methodology in the cognitive neuroscience of consciousness. Finally, we present strategies to measure lucid dreaming both physiologically and with questionnaires, and discuss procedures to investigate lucid dreaming in the sleep laboratory.

2. Electrophysiology of lucid dreaming

As noted in the introduction, the first physiological studies of lucid dreaming began in the late 1970s and early 1980s. These pioneer works established that lucid dreams occur in REM sleep, characterized by all of the EEG features of REM sleep according to the Rechtschaffen and Kales (1968) sleep scoring criteria ( Hearne, 1978 ; LaBerge et al., 1981c ). LaBerge (1980b) also observed that lucid dreams are associated with increased physiological activation, as measured by increased phasic activity (e.g., increased REM density). Autonomic nervous system arousal (e.g., heart rate, respiration rate, and skin potential) were also found to be elevated during lucid REM sleep compared to non-lucid REM sleep ( LaBerge, Levitan and Dement, 1986 ). Additionally, lucid dreams were found to occur in REM sleep periods later in the night ( LaBerge et al., 1986 ). These findings suggest that lucid dreaming is associated with increased cortical activation ( LaBerge, Nagel, Taylor, Dement and Zarcone, 1981a ), which reaches its peak during phasic REM sleep. In addition to physiological markers of phasic activity, lucid REM sleep was found to be associated with h-reflex suppression ( Brylowski, Levitan and LaBerge, 1989 ), a spinal reflex that is reliably suppressed during REM sleep ( Hodes and Dement, 1964 ). Together these results indicate that lucid dreams occur in activated periods of REM sleep, as opposed to, for example, a state that is intermediate between waking and REM sleep.

These findings also raise the further question of whether lucid REM sleep is associated with localized activation of specific brain regions or changes in specific frequencies of neural oscillations compared to non-lucid REM sleep. In this section, we will review EEG studies that have attempted to address this question. As will be discussed below, while these studies represent important first steps toward measuring the electrophysiological changes associated with lucid dreaming, all of them have interpretive issues and most suffer from low statistical power. As a result, there is considerable discrepancy among findings. Below we group and discuss results based on the regional EEG band power changes reported to be associated with lucid REM sleep dreaming.

2.1. EEG studies of lucid REM sleep dreaming

2.1.1. central and posterior alpha.

Ogilvie and colleagues conducted some of the first studies to examine EEG spectral changes during lucid REM sleep. In an early case study, Ogilvie, Hunt, Sawicki and McGowan (1978) compared two lucid REM sleep epochs to six non-lucid REM sleep epochs and found an increase in the percentage of alpha band (8-12 Hz) power in a single central EEG channel. A follow-up study examined a larger group of ten participants for two nights in the sleep laboratory ( Ogilvie, Hunt, Tyson, Lucescu and Jeakins, 1982 ). Participants were awakened during the two periods of highest alpha power and two periods of lowest alpha power from a central EEG electrode during REM sleep, after which they were asked several questions about their lucidity, “prelucidity” (i.e., thoughts pertaining to dreaming without becoming lucid), and degree of dream control. Unfortunately, statistics for the number of lucid dreams reported by participants were not documented in this study, nor whether there was a significant difference between conditions in the number of lucid dreams. Instead, a composite measure was constructed by collapsing across pre-lucidity, lucidity and control, which was significantly elevated in the high alpha trials. Therefore, the number (if any) of lucid dreams that were captured by this procedure is unknown (see LaBerge (1988b) for further discussion).

Subsequent research has not supported the hypothesis that lucid REM sleep is associated with increased alpha activity. For example, in a follow-up study Tyson, Ogilvie and Hunt (1984) found that only pre-lucid but not lucid dreams significantly differed in alpha activity compared to non-lucid REM sleep. In another study of eight frequent lucid dreamers using a similar experimental design, Ogilvie, Hunt, Kushniruk and Newman (1983) observed no difference in the number of lucid dreams following awakenings from periods of high or low alpha activity. Furthermore, in a replication attempt of the original case report that observed an increase in alpha during lucid REM sleep ( Ogilvie et al., 1978 ), LaBerge and colleagues found no significant differences in alpha power at the same central channel (C3) from a single subject ( LaBerge, 1988b ). Finally, a later follow-up case study analyzed EEG spectral power in five lucid REM sleep epochs compared to non-lucid REM sleep periods, and observed no differences in alpha power ( Ogilvie, Vieira and Small, 1991 ). Together this evidence does not support a reliable association between alpha power and lucid dreaming. However, the limited spatial coverage of EEG montages in these studies (in several cases consisting of only one EEG channel) makes it unclear to what extent these results can be generalized to other brain areas.

2.1.2. Parietal beta

Holzinger, LaBerge and Levitan (2006) examined EEG spectral changes during lucid REM sleep in a group of eleven participants who reported prior experience with lucid dreaming. Six out of the eleven participants succeeded in becoming lucid in the sleep laboratory, and some during multiple REM periods, for a total of 16 signal-verified lucid dreams. The authors found increased power in the low beta frequency range (13-19 Hz) in parietal electrodes for lucid compared to non-lucid REM sleep. This study has the advantage of analyzing a larger number of lucid REM sleep periods. However, a limitation is that EEG signals were only evaluated at four electrodes (F3, F4, P3, P4). Consequently, localized changes in EEG spectra may have been missed by the low spatial resolution. Furthermore, due to technical limitations, the online low-pass filter for the EEG recordings in this study was set at 35 Hz, and therefore changes in higher-frequency activity were unable to be evaluated.

The potential functional significance of increased low beta band power in parietal areas to lucid dreaming is not understood. Holzinger et al. (2006) speculated that the increased beta power in the parietal EEG could reflect the understanding of the meaning of the words “This is a dream.” As discussed below, recent neuroimaging studies have linked parietal regions to several other cognitive functions associated with lucid dreaming, including self-reflection ( Kjaer, Nowak and Lou, 2002 ; Lou et al., 2004 ), episodic memory ( Berryhill, Phuong, Picasso, Cabeza and Olson, 2007 ; Wagner, Shannon, Kahn and Buckner, 2005 ) and agency ( Cavanna and Trimble, 2006 ), suggesting several other possible interpretations of the results. Neural oscillations in this frequency range were originally thought to reflect sensorimotor behavior; however, evidence now suggests that oscillations in this range could play a role in cognitive processing as well as facilitate large-scale neural integration (e.g., Donner and Siegel, 2011 ; Engel and Fries, 2010 ). If these results can be replicated in future studies, one hypothesis is that the increased oscillatory activity in the beta band could reflect a mechanism of integration between parietal regions and other areas, which, in some way still to be understood, helps facilitate lucid dreaming. However, it is also possible that differences in sensorimotor behavior between lucid and non-lucid REM sleep could boost brain rhythms that overlap with this frequency range ( Koshino and Niedermeyer, 1975 ; Pfurtscheller, Stancak and Neuper, 1996 ; Vanni, Portin, Virsu and Hari, 1999 ). Additional research is needed to clarify these findings.

2.1.3. Frontolateral gamma

Mota-Rolim et al. (2008) and Voss, Holzmann, Tuin and Hobson (2009) reported increased gamma band (40 Hz) power in frontolateral scalp electrodes during lucid compared to non-lucid REM sleep in three participants each. However, besides an unsuccessful replication in patients with narcolepsy ( Dodet et al., 2014 ), interpretation of these results are restricted by several experimental limitations, including the small sample size ( LaBerge, 2010 ). Importantly, caution is warranted in interpreting these findings given that, as briefly discussed by Voss et al. (2009) , scalp measurement of cortical gamma, particularly when selectively localized in the frontal and periorbital regions, may be confounded with mircrosaccades. Ocular myogenic artifacts, which occur during both saccades and microsaccades and are distinct from the artifacts associated with corneo-retinal dipole offsets, may confound scalp measurement of gamma activity. One type of such artifacts is referred to as the saccadic spike potential (SP), which occurs due to contraction of the ocular muscles during both saccades and microsaccades ( Yuval-Greenberg and Deouell, 2009 ; Yuval-Greenberg, Tomer, Keren, Nelken and Deouell, 2008 ). The influence of the SP artifact on gamma power was overlooked for a number of years; however, the need to account for this artifact on scalp measurement of induced gamma activity has now been thoroughly documented (e.g., Hipp and Siegel, 2013 ; Keren, Yuval-Greenberg and Deouell, 2010 ).

Voss et al. (2009) corrected for eye movement artifacts using regression of the EOG signal ( Gratton, Coles and Donchin, 1983 ) and by computing current source densities (CSD) in addition to scalp potentials. However, regression-based correction procedures are insufficient to remove the SP artifact, and while the CSD derivation attenuates the SP artifact at posterior channels, it is not sufficient to remove it at anterior scalp locations ( Keren et al., 2010 ; Yuval-Greenberg and Deouell, 2009 ). As Keren et al. (2010) state: “In conclusion, SCD [CSD] seems to be effective in attenuating the SP effect at posterior sites. However at sites anterior to Cz and closer to the orbits efficacy gradually decreases, preserving the temporal and spectral signature of the SP and its amplitude relative to baseline.” (p. 2258). The influence of the SP artifact on gamma band power in the comparison of lucid to non-lucid REM sleep is particularly relevant given that, as noted above, lucid REM sleep has been associated with increased phasic activation and higher eye movement density (e.g., LaBerge, 1990 ).

It is important to note that the need to account for the SP artifact does not preclude a potential association between increased frontal gamma power and lucid REM sleep. Indeed, given the link between gamma band power, local field potentials (LFPs) and the blood-oxygen-level dependent (BOLD) signal ( Lachaux et al., 2007 ; Nir et al., 2007 ), if the transition from non-lucid to lucid REM sleep involves activation or recruitment of additional frontal brain regions (a plausible hypothesis, also in light of the findings of Dresler et al. (2012) ; see Neuroimaging of lucid dreaming below), regional increases in gamma power might be predicted. However, the spatial topography and frequency localization of any such effects are likely to be strongly influenced by the correction and removal of the SP artifact.

With the aforementioned considerations in mind, more research is needed to clarify whether the increase in frontolateral gamma power during lucid REM sleep observed by Mota-Rolim et al. (2008) and Voss et al. (2009) reflects ocular myogenic or neural activity. Furthermore, future studies evaluating the relationship between lucid REM sleep and gamma activity from sensor-level EEG, particularly at anterior electrodes, need to control for the SP artifact in order for the results to be interpretable. Several methods have been shown to be suitable for removal this artifact, including direct identification and removal of contaminated data by rejecting overlapping windows of time-frequency transformed data or data correction using independent component analysis ( Hipp and Siegel, 2013 ). A study that evaluates the effect of direct removal and/or correction of the SP artifact on gamma power during lucid contrasted with baseline REM sleep would be an important addition to the literature. In summary, studies that rigorously control for myogenic artifacts, and in particular the SP artifact, are needed before conclusions can be drawn regarding the relationship between lucid REM sleep and frontal gamma activity.

2.1.4. Fronto-central delta

Dodet, Chavez, Leu-Semenescu, Golmard and Arnulf (2014) evaluated changes in EEG band power during lucid REM sleep in a group of narcoleptic patients. Given that narcoleptic patients often report a high rate of lucid dreams ( Rak, Beitinger, Steiger, Schredl and Dresler, 2015 ), they are a potentially useful population for cognitive neuroscience studies of lucid dreaming. In the experiment, while both control and narcoleptic patients reported achieving lucidity and performing the LRLR signals during overnight and afternoon nap recordings, only the eye signals of the patients during the nap recordings could be unambiguously identified. This is likely at least partially attributable to the specific instructions used for making the eye movement signal (see Section 9 below for discussion of this issue). Despite this, the study succeeded in recording 14 signal-verified lucid dreams during naps from seven narcoleptic patients. The main finding was that EEG power was reduced in the delta band during lucid REM sleep at frontal and central electrodes. The study also reported that the coherence between several electrodes was reduced in lucid compared to non-lucid REM sleep in delta, theta, beta and gamma bands, but these differences are difficult to interpret since no statistics were reported for this analysis and no corrections for multiple comparisons were made.

A limitation of the Dodet et al. (2014) study is that EEG signals were only evaluated at six electrodes, and only in frontal and central scalp regions (Fp1, Fp2, F7, F8, C3, C4). Parietal electrodes were not included in the EEG montage, and occipital channels reportedly could not be evaluated due to noise. Thus, it is possible that local changes in EEG spectra in posterior regions, such as parietal or occipital areas, were missed due to the limited electrode montage.

The finding of lower delta activity during lucid REM sleep is in line with previous observations that lucid dreams tend to occur during periods of increased cortical activation ( LaBerge, 1990 ). Specifically, slow waves, reflected by delta (~0.5-4 Hz) power in the EEG, are associated with neuronal down states (“off’ periods) in which neurons are hyperpolarized ( Steriade, Timofeev and Grenier, 2001 ). Decreased delta power (EEG activation) therefore reflects recovery of neural activity. While the bi-stability between “on” and “ off’ periods is a central feature of non-REM sleep, slow wave activity has also been observed in REM sleep ( Baird et al., 2018b ; Funk, Honjoh, Rodriguez, Cirelli and Tononi, 2016 ). Neuronal down states have also been linked to the loss of consciousness during both anesthesia and sleep ( Purdon et al., 2013 ; Tononi and Massimini, 2008 ), which is hypothesized to be related to the breakdown of causal interactions between bi-stable neurons ( Pigorini et al., 2015 ; Tononi, Boly, Massimini and Koch, 2016 ). Therefore, one potential explanation is that this finding reflects reduced bi-stability and increased causal interactions between cortical neurons in these areas during lucid REM sleep. Notably, reduced delta power in posterior cortex has been found to be associated with dreaming as opposed to dreamless sleep in both REM and NREM sleep ( Siclari et al., 2017 ). An intriguing speculation based on these results is therefore that this reduction in delta power also extends to frontal regions during lucid REM sleep dreaming. However, it remains to be seen whether these findings can be replicated and whether the results generalize to non-clinical populations.

2.2. General discussion of EEG studies of lucid REM sleep

In summary, EEG studies show substantial disagreement regarding the spatial and spectral changes associated with lucid dreaming. As reviewed above, different studies have observed an increase in central or posterior alpha, parietal beta, frontolateral gamma or a reduction in frontocentral delta during lucid compared to baseline REM sleep. Aside from the general uncertainty in the results of some studies due to low statistical power, these discrepant results might be partially explained by the use of limited electrode montages and evaluation of different EEG frequency bands. In the spatial domain in particular, many studies have used less than six scalp electrodes, in several cases only covering some scalp regions but not others, precluding analysis of EEG activity in regions in which significant effects were found in other studies. For instance, the study by Dodet et al. (2014) did not include electrodes in parietal or occipital regions, precluding the possibility to replicate the findings of increased parietal beta by Holzinger et al. (2006) . Studies by Ogilvie et al. (1978 , 1982 ) evaluated only a single central EEG channel (C3). These non-overlapping spatial montages limit the comparison of results across some of these studies.

Another factor that might contribute to the discrepant findings is the fact that lucid dreaming can be achieved and executed in different ways. For example, the observed changes in the EEG during lucid REM sleep might depend in part on the degree of vividness, working memory, emotional tone, self-consciousness, attention and insight, which could vary across individuals as well as specific dreams. Relatedly, different subjective experiences and contents during lucid dreams plausibly have their own neurobiological substrates ( Mota-Rolim, Erlacher, Tort, Araujo and Ribeiro, 2010 ), just as in non-lucid dreams ( Siclari et al., 2017 ). Changes in brain activity during lucidity may also partly depend on how experienced the lucid dreamer is. For instance, lucid dreams of less experienced individuals may often be more ephemeral and involve less control over dream content, while more experienced lucid dreamers may be more likely to have longer and more stable lucid dreams, as well as the capacity to exert greater amounts of control. This might lead to a more distinct signal in the EEG for experienced lucid dreamers on the one hand, but also presumably less neural activity related to the effort needed to maintain the state (neural efficiency). In line with this, Dodet et al. (2014) suggested that the mental effort needed to achieve and sustain lucidity might be reduced in narcoleptic patients, who may access the lucid REM sleep state with less effort.

These comments should not be taken to indicate that there is not a consistent neurobiology of lucid dreaming. However, it does suggest that analysis of the EEG spectral changes associated with lucid dreaming used in previous studies may need to be optimized for detecting more subtle and localized effects. All studies reviewed above have measured the average power over a given spectral band and region over comparably long time intervals. However, it is possible that lucid dreaming is associated with spectral changes that can only be detected by a better time resolved analysis, such as time-frequency analysis, that may be overlooked by averaging over large windows in time or frequency space.

Furthermore, these considerations emphasize the need for more careful assessment of the phenomenology of lucid dreams. In this regard, we would like to note that it is plausible that there are at least two different neural signatures associated with lucid dreaming. The first captures what might be termed the “moment of lucidity”—that is, the transient moment of meta-awareness in which one has the metacognitive insight that one is currently dreaming ( Schooler, 2002 ). The second captures potential sustained differences in brain activity between lucid and non-lucid REM sleep dreaming. This second neural signature is unlikely to be a signature of meta-awareness per se, as during lucid dreams individuals do not continuously engage in metacognitive reflection on their state of consciousness. Rather, this second signature captures the “state-shift” in consciousness that occurs from non-lucid to lucid dreaming, with enhanced volition, episodic memory and accessibility of metacognition ( Dresler et al., 2014 ; Spoormaker, Czisch and Dresler, 2010 ). Changes in these aspects of cognition in the shift to lucidity have been hypothesized to reflect an overall change in the conscious experience of being a cognitive subject ( Windt and Metzinger, 2007 ). Both the physiological correlates of the moment of lucidity as well as overall differences in brain activity between lucid and non-lucid dreams are interesting research targets. However, these research targets are at least conceptually distinct, a point that has, in our view, not received adequate attention in the research literature. To our knowledge, no studies have yet evaluated differences in brain activity with EEG or functional magnetic resonance imaging (fMRI) specifically associated with the moment of lucidity, and this remains an interesting question for future work.

Larger sample sizes are needed in future studies to achieve adequate statistical power. One way to approach this would be to undertake more extensive population screening for high-frequency lucid dreamers. For example, through mass surveys, thousands of potential participants could be screened and the top few percent reporting the highest lucid dream frequency could be selected for training before undergoing sleep laboratory recordings. As we discuss below, new techniques for lucid dream induction also have the potential to enable efficient collection of larger datasets.

Overall, studies with higher statistical power, better assessment of phenomenological content, higher spatial resolution EEG montages, and more sophisticated analysis of the EEG signal will be needed to address these issues and shed light on the conflicting findings of EEG studies of lucid dreams conducted to date. Studies using high-density EEG would also be valuable, enabling both higher temporal as well as higher spatial resolution analysis of neural oscillatory activity. Source modeling of such data could also potentially be informative for localizing changes in neural oscillations associated with lucid dreaming to specific cortical areas, though it remains unclear whether methods for source localization will be able to produce a valid specification of the generators relevant for lucid dreaming. In particular, the generators might be distributed widely in the brain and active concurrently.

Another interesting question with respect to the electrophysiology of lucid dreaming is whether there are possible sleep pattern traits that are associated with lucid dreaming. It would be informative to investigate whether there are common sleep patterns seen in frequent lucid dreamers compared to non-frequent lucid dreamers. For example, do frequent lucid dreamers tend to have more phasic REM sleep, or more fragmented REM sleep with a higher number of transitions (especially gradual transitions) between REM sleep and waking? As far as we know, no study has investigated lucid dreaming with this approach; therefore, studies addressing these questions would be valuable.

2.3. EEG studies of lucid dreaming during non-REM sleep

The activated EEG of REM sleep was originally thought to be exclusively associated with dreaming ( Antrobus and Antrobus, 1967 ; Dement and Wolpert, 1958 ), while the low-frequency activity of non-REM (NREM) sleep was thought to be associated with the absence of dreaming. Subsequent research has shown, however, that participants report dreams or related forms of sleep mentation in up to 70% of awakenings from NREM sleep ( Siclari et al., 2017 ; Siclari, LaRocque, Postle and Tononi, 2013 ; Stickgold, Malia, Fosse and Hobson, 2001 ). NREM dreams tend to be less emotional and visually vivid, as well as more thought-like ( Cavallero, Cicogna, Natale, Occhionero and Zito, 1992 ; Hobson, Pace-Schott and Stickgold, 2000 ). Research suggests that lucid dreams, on the other hand, are predominantly a REM sleep phenomenon ( LaBerge et al., 1986 ; LaBerge et al., 1981c ). However, this does not imply that lucid dreams cannot occur during NREM sleep. There have been several reports of lucid dreams during NREM sleep stages N1 (transition from wake state to sleep) and N2 (consolidated light sleep), although in many of the published cases it is uncertain whether the lucid episode occurred in an unambiguous stage of NREM sleep ( Dane and Van de Caslte, 1984 ; LaBerge, 1980b , 1990 ; LaBerge et al., 1981c ; Stumbrys and Erlacher, 2012 ).

In one study, LaBerge (1980b) recorded polysomnography from a single subject who reported frequently experiencing lucid dreams at sleep onset. The participant rested quietly while drifting to sleep and upon falling asleep was awakened and asked for a dream report. Forty-two dream reports were collected over three nights, 25 of which the participant reported as a lucid dream, and all of which reportedly occurred during stage N1. However, the dream reports were mostly short “dreamlets”, thus it is plausible that these N1 lucid dreams could differ phenomenologically from REM sleep lucid dreams. Furthermore, none of these lucid dreams were verified with eye movement signals. In another study, two participants reported lucid dreams upon spontaneous awakening from N1 and N2 ( LaBerge et al., 1981c ). In the N2 instance, the participant reported only a brief moment of lucidity just before waking up. Furthermore, the participant did not make eye movement signals to time-stamp the moment of lucidity, and it is therefore difficult to ascertain whether the moment of lucidity occurred in the process of awakening. The N1 case was also ambiguous: while in this case the participant reported making eye movements to signal lucidity, the signals could not be verified on the polysomnogram.

In a study on the effects of posthypnotic suggestion on lucid dreaming, Dane and Van de Caslte (1984) tested hypnotically susceptible females with no prior experience in lucid dreaming. Importantly for the present discussion, lucid dreams were reported following awakening from both REM and NREM sleep. Five lucid dreams were reported in total from stage N2, but in all cases the LRLR eye signal occurred after arousal/awakening, and thus none of these could be objectively confirmed. However, several N1 lucid dreams were confirmed by LRLR signaling. This study was thus the first to provide objective evidence for lucid dreaming during stage 1 NREM sleep. However, as noted above, how these N1 dreams compare phenomenologically to REM sleep lucid dreams remains unclear.

Stumbrys and Erlacher (2012) reported two potential cases of lucid dreams during NREM with eye signaling. However, due to the study protocol, the experimenters could only collect dream reports the following morning. In the first case, the participant reported the next morning making an eye movement signal in a lucid dream early in the night, but given the long amount of time between the report and the signal there is uncertainty whether the report corresponds to the observed signal during NREM sleep. Furthermore, while the two 30-second polysomnography epochs for sleep scoring preceding the eye signal appear to be unambiguous N2 sleep, the EEG dynamic shifts during the 30-second epoch containing the eye-signal to lower amplitude activity without apparent spindles or K-complexes. Without knowing the stage of the epochs following the eye signal, which was not reported in the study, it is possible that the eye signal occurred in a transitional sleep stage. In the second case reported by Stumbrys and Erlacher (2012) , the eye signals occurred with some signs of arousal and the participant had no memory of executing the eye signals the following morning. These data therefore provide ambiguous evidence for signal-verified lucid dreams during NREM sleep.

In three further case reports of eye movement signaled NREM lucid dreams, one case was reported to occur in N1 and two cases in N2 visually scored sleep stages ( Mota-Rolim et al., 2015 ). The first case was scored as N1, since an increase in theta (4-7 Hz) and a decrease in alpha (7-14 Hz) power was observed in more than half of the 30 second scoring epoch, meeting the AASM criteria for classification of stage N1 sleep. The other two cases were scored as occurring during N2 episodes since they had spindles and K-complexes in the 30 second scoring epoch with the eye signals. These data thus replicate signal-verification of N1 lucid dreams and provide preliminary evidence for signal-verified N2 lucid dreams.

Together, these results suggest that although most lucid dreams occur during REM sleep, they can also occur during NREM sleep. However, additional studies providing objective evidence of NREM lucid dreams confirmed by eye-signaling, particularly in N2 sleep, are needed. Currently there are no reports of lucid dreams recorded during NREM stage 3 (N3), also known as deep sleep, or slow wave sleep. While there are intriguing reports of practitioners of both Transcendental Meditation and Tibetan Dream Yoga claiming to have developed the ability to maintain a type of lucid awareness throughout the entire sleep cycle, including also states of “lucid dreamless sleep” ( Gackenbach, Cranson and Alexander, 1986 ; Mason and Orme-Johnson, 2010 ; Wallace, 2013 ; Windt, Nielsen and Thompson, 2016 ), these claims have not been corroborated with physiological measures. However, several studies have found a relationship between meditation practice and lucid dreaming (e.g., Baird, Riedner, Boly, Davidson and Tononi, 2018c ; Gackenbach et al., 1986 ; Mota-Rolim et al., 2013 ; Stumbrys, Erlacher and Malinowski, 2015 ), which could be due to changes in REM sleep patterns induced by meditation practice and/or to neurocognitive changes associated with meditation practice (e.g., increased mental control or meta-awareness).

3. Neuroimaging of lucid dreaming

As noted, dream-like mental activity can be observed during all sleep stages. However, REM sleep dreams tend to be more vivid, emotional, bizarre, and more often include a narrative structure ( Cavallero et al., 1992 ; Hobson et al., 2000 ). These phenomenological characteristics have been suggested to be associated with the neural activation and deactivation patterns observed during REM sleep (e.g., Nir and Tononi, 2010 ). For example, higher visual areas show increased regional cerebral blood flow during REM sleep compared to both wakefulness and slow wave sleep ( Braun et al., 1998 ), which is in line with the visuospatial experiences that are common during REM sleep dreaming (e.g., Windt, 2010 ). Additionally, the amygdala, medial prefrontal cortex and anterior cingulate cortex show increased regional cerebral blood flow during REM sleep ( Braun et al., 1997 ; Maquet et al., 1996 ). All of these brain areas have been implicated in emotional processing, mirroring the intense emotions that can be experienced in REM sleep dreams. In contrast, the anterior prefrontal cortex (aPFC) and parietal cortex, including the inferior parietal lobule and precuneus, show low regional cerebral blood flow during normal REM sleep ( Braun et al., 1997 ; Maquet et al., 1996 ). Deactivation of these regions has been postulated to underlie the diminished insight into the global state of consciousness and restricted volitional control typical of non-lucid dreaming (e.g., Hobson and Pace-Schott, 2002 ; Nir and Tononi, 2010 ).

3.1. Neuroimaging lucid REM sleep dreaming

At the current time, there is only one fMRI study of lucid REM sleep, and it is a case study ( Dresler et al., 2012 ). Two separate signal-verified lucid dreams were recorded from a single subject during EEG-verified REM sleep inside the MRI scanner. Compared to non-lucid REM sleep, lucid REM sleep showed increased fMRI BOLD signal in a number of cortical regions, including the superior frontal gyrus, aPFC, medial and lateral parietal cortex, inferior/middle temporal gyri and occipital cortex ( Figure 2a ). Interestingly, several of these regions, particularly the parietal regions and frontal pole, are areas that, as noted above, consistently show reduced regional cerebral blood flow during non-lucid REM sleep compared to wakefulness ( Nir and Tononi, 2010 ).

a) Blood-oxygen-level dependent (BOLD) activation in fMRI case study of lucid dreaming ( Dresler et al., 2012 ). Clusters show regions with significantly increased BOLD signal during lucid REM sleep ( p FDR < 0.005) in the left lateral hemisphere view (left) and right lateral hemisphere view (right). Increased activity was observed in anterior prefrontal cortex (aPFC), medial and lateral parietal cortex, including the supramarginal and angular gyrus and inferior/middle temporal gyrus during lucid REM sleep contrasted with non-lucid REM sleep. b) Seed-based resting-state functional connectivity differences between frequent lucid dreamers and controls ( Baird et al., 2018a ). To estimate connectivity, spherical regions-of-interest were defined in aPFC based on the peak voxel reported in Dresler et al. (2012) (red circle). Frequent lucid dreamers had increased resting-state functional connectivity between left aPFC and bilateral angular gyrus, bilateral middle temportal gyrus and right inferior frontal gyrus. All clusters are significant at p <0.05, corrected for multiple comparisons at the cluster level.

Evidence linking frontopolar cortex to lucid dreaming is consistent with a role of this region in metacognition and self-reflection. For example, research has found that aPFC shows increased activation during self-reflection on internal states, such as the evaluation of one’s own thoughts and feelings ( Christoff, Ream, Geddes and Gabrieli, 2003 ; McCaig, Dixon, Keramatian, Liu and Christoff, 2011 ). Individuals can also learn to voluntarily modulate activity in aPFC through a metacognitive awareness strategy ( McCaig et al., 2011 ). Furthermore, inter-individual variance in metacognitive ability has also been linked to aPFC gray matter volume ( Fleming, Weil, Nagy, Dolan and Rees, 2010 ) and aPFC resting-state functional connectivity ( Baird, Smallwood, Gorgolewski and Margulies, 2013 ). Finally, patients with damage to this region frequently display metacognitive deficits such as inability to monitor disease symptoms or accurately appraise their cognitive functioning ( Joseph, 1999 ; Schmitz, Rowley, Kawahara and Johnson, 2006 ), which might be compared to the lack of metacognitive insight into the state of consciousness characteristic of non-lucid REM sleep dreams ( Dresler et al., 2015 ).

Dresler et al. (2012) additionally observed increased BOLD signal during lucid dreaming in the bilateral precuneus and inferior parietal lobules (angular and supramarginal gyri). As noted above, parietal cortex and the precuneus in particular has been implicated in self-referential processing, episodic memory, and the experience of agency ( Cavanna and Trimble, 2006 ), mirroring the increase of these cognitive capabilities during lucid dreaming. Finally, activation increases during lucid dreaming were also found in some occipital and inferior temporal regions, which are part of the ventral stream of visual processing involved in conscious visual perception ( Rees et al., 2002 ). While these activations may seem puzzling at first sight, as non-lucid dreams are also characterized by vivid dream imagery, they are in line with reports that lucid dreams can be associated with increased visual vividness and clarity of the dream scene (e.g., Green, 1968 ).

There are several limitations to the study by Dresler et al. (2012) that are important to note. First, as mentioned above, the findings are based on observations from a single subject and caution is therefore warranted in generalizing from the results. Currently no group-level fMRI study of lucid dreaming has been conducted, and such a study, along with systematic replications, will be needed before firm conclusions can be drawn. Another limitation is that, as described below (see Section 7.1 ), the participant was performing a task during the lucid REM sleep segment (repeated eye signaling and hand clenching). While Dresler and colleagues accounted for task activation via nuisance regression of the left and right fist clenching task, it is possible that some of the activations observed still partially reflect task execution and maintenance of attention/task-set rather than lucidity per se. One way to address this in future studies would be to contrast periods of lucid REM sleep when the participant is not performing an explicit task to non-lucid REM sleep, i.e., a “no-task, within-state paradigm” ( Siclari et al., 2013 ).

3.2. Neuroimaging individual differences in lucid dreaming

Several studies have taken an individual differences approach to neuroimaging of lucid dreaming. While most people spontaneously experience lucid dreams infrequently, there is substantial variation in lucid dream frequency, ranging, by current estimates, from never (approximately 40-50%) to monthly (approximately 20%) to a small percentage of people that report lucid dreams several times per week or in some cases every night ( Mota-Rolim et al., 2013 ; Saunders, Roe, Smith and Clegg, 2016 ; Snyder and Gackenbach, 1988 ). This variation invites the question of whether individuals who experience frequent lucid dreams show differences in anatomical or functional properties of the brain. Studies addressing this question can provide complementary evidence on the neurobiology of lucid dreaming.

In the first neuroimaging study to evaluate the relationship between lucid dream frequency and brain anatomy, Filevich, Dresler, Brick and Kuhn (2015) measured whole-brain gray matter volume using voxel-based morphometry in individuals with higher (“high lucidity”) vs. lower (“low lucidity”) scores on a scale assessing the frequency of lucid dreams and/or dream content hypothesized to be related to lucidity. Consistent with the hypothesized connection between the metacognitive functions of aPFC and lucid dreaming discussed above, the study found increased gray matter volume in two regions of the frontal pole (BA9/10), as well as the right anterior cingulate cortex, left supplementary motor area and bilateral hippocampus in the high lucidity group. Additionally, the two identified frontopolar regions showed higher BOLD signal in the monitoring component of a metacognitive thought-monitoring task performed while awake.

A limitation of the study by Filevich et al. (2015) is that participants were not frequent lucid dreamers per se, but rather subjects from a database who scored higher relative to other participants on the scale. Lucid dream frequency for the two groups was not reported in the study, thus it remains unclear to what extent the “high lucidity” group experienced frequent lucid dreams in absolute terms. Furthermore, the composite measure of dreaming used to distinguish the two groups measured not only frequency of lucid dreams but also different dimensions of dream content. While several of these content dimensions have been found to be higher in lucid dreams ( Voss, Schermelleh-Engel, Windt, Frenzel and Hobson, 2013 ), it is likely that several of these dimensions also co-vary more generally with dream recall and/or cognitive content in dreams unrelated to lucidity. As a consequence, as the authors note, some of the results could have been partly influenced by differences in dreaming “styles”, content or dream recall.

More recently, Baird, Castelnovo, Gosseries and Tononi (2018a) evaluated a sample of high-frequency lucid dreamers who reported lucid dreams in the range of three to four times per week to multiple times per night compared to a control group who reported lucid dreams once per year or less. The frequent lucid dream group and control group were case-control matched on age, gender, and dream recall frequency. Based on the previous research reviewed above, the primary aim of the study was to investigate whether individuals who have frequent lucid dreams would show increased gray matter density and/or resting-state functional connectivity of aPFC. Consistent with this, compared to the control group, individuals who reported frequent lucid dreams showed increased resting-state functional connectivity between the left aPFC and the bilateral angular gyrus, bilateral middle temporal gyrus and right inferior frontal gyrus ( Figure 2b ). The frequent lucid dream group also showed decreased functional connectivity between left aPFC and bilateral insula. Whole-brain graph-theoretic analysis revealed that left aPFC had increased node degree and strength in the frequent lucid dream group compared to the control group. However, in contrast to the findings of Filevich et al. (2015) , no significant differences in gray matter density were observed between groups in either a whole-brain analysis or an aPFC region-of-interest analysis.

Given the link to metacognition, it has also been suggested that lucid dreaming may be linked to large-scale networks that regulate executive control processes, in particular the frontoparietal control network ( Dresler et al., 2015 ; Spoormaker et al., 2010 ). To address this question, Baird et al. (2018a) additionally evaluated the association between frequent lucid dreaming and connectivity within established large-scale brain networks, including the frontoparietal control network. Consistent with a link between the frontoparietal control network and lucid dreaming, Baird and colleagues found that frequent lucid dreamers had increased functional connectivity between aPFC and a network of regions that showed the greatest overlap with a frontoparietal control sub-network ( Dixon et al., 2018 ; Yeo et al., 2011 ). However, neither connectivity within the frontoparietal control network broadly defined through meta-analysis (or within or between any other large-scale networks), nor connectivity within frontoparietal control sub-networks, as defined through parcellation of resting-state networks, showed significant differences between the lucid dream group and the control group. The authors speculate that this could be attributed to both the partial overlap of the regions that showed increased aPFC connectivity in lucid dreamers with the frontoparietal control network. However, it is important to keep in mind that while this study did not find a significant difference in resting-state connectivity within the frontoparietal network in frequent lucid dreamers, it remains an open question whether lucid REM sleep dreams show increased connectivity within the frontoparietal control network compared to non-lucid REM sleep dreams.

Overall, the resting-state connectivity results of Baird et al. (2018a) converge with the fMRI case study of lucid REM sleep dreaming described above ( Dresler et al., 2012 ), which found that an overlapping network of brain areas increased fMRI BOLD signal during lucid compared to baseline REM sleep, including bilateral aPFC, bilateral inferior parietal lobule (including the angular gyrus), and bilateral middle temporal gyrus ( Figure 2 ). Together, these results suggest that increased intrinsic functional connectivity between aPFC and the angular gyrus/middle temporal gyrus—regions that, as reviewed above, show reduced activity in REM sleep ( Nir and Tononi, 2010 ) and increased activity during lucid REM sleep ( Dresler et al., 2012 )—is associated with the tendency to have frequent lucid dreams. However, while the convergence between these two preliminary studies is encouraging, the paucity of neuroimaging data on this question limits strong conclusions at the current time.

3.3. Future directions for neuroimaging of lucid dreaming

Neuroimaging studies of lucid REM sleep using larger samples sizes are needed. In particular, a group-level fMRI study of lucid REM sleep dreaming using a no-task, within-state paradigm is perhaps the most important next step in this line of research. In addition to evaluating activation and deactivation as revealed by changes in BOLD signal, it would also be informative to evaluate differences in functional connectivity in such a study. For example, as noted, one question that arises from the above neuroimaging findings is whether there could be increased connectivity within the network of regions identified in Dresler et al. (2012) and Baird et al. (2018a) during lucid contrasted with non-lucid REM sleep dreaming. Furthermore, building on the individual differences results, in future work it would also be interesting to evaluate whether high frequency lucid dreamers show increased functional connectivity and/or higher BOLD signal in these brain areas during baseline REM sleep. If so, this could suggest that it may be possible to bias the brain toward increased metacognitive awareness of dreaming during REM sleep, for example, as discussed in the next sections on induction of lucid dreams, through techniques to increase activation of these regions.

In line with these remarks, it has been suggested that not only regional activation of frontoparietal brain areas but also connectivity between these regions could be important for lucidity to emerge during REM sleep ( Spoormaker et al., 2010 ). Indeed, while activation in these frontal and parietal regions has been linked to key functions associated with lucid dreaming, including metacognition, as discussed above, regional activations and metabolic increases in these regions have also been observed during states of global unconsciousness and subliminal information processing. For instance, subliminally presented no-go stimuli during a response inhibition task activate frontoparietal cortices in the absence of awareness ( van Gaal, Ridderinkhof, Scholte and Lamme, 2010 ). Moreover, loss of consciousness during the tonic phase of generalized tonic-clonic seizures is associated with a transient increase rather than decrease in metabolism in frontoparietal cortex ( Blumenfeld, 2008 ; Engel, Kuhl and Phelps, 1982 ).

Recent findings have suggested that a potentially more sensitive marker of unconscious states may be reduced connectivity between frontoparietal areas, particularly from frontal to parietal regions. For example, several neuroimaging studies of patients in a persistent vegetative state or under different categories of general anesthetics have shown a specific impairment of the backward connectivity from frontal to parietal regions ( Boly et al., 2011 ; Boly et al., 2012 ; Lee et al., 2013 ). These findings converge with theoretical work and computational modeling ( Tononi, 2011 ), which has suggested a link between consciousness and effective connectivity within a neural architecture, or the capacity of a set of neural elements to exert causal influence over other neural groups in a system. At present, it is unclear whether this reduction of top-down frontoparietal connectivity is linked to changes in global brain activity, alterations in primary consciousness (i.e., subjective, phenomenal states of seeing, hearing or feeling), or whether it could relate to self-awareness (i.e., explicit conscious awareness of oneself and one’s state). A common interpretation of these results is that top-down frontoparietal connectivity is a marker of global loss of consciousness, including primary consciousness (e.g., Mashour, 2014 ). However, given that the reduction in top-down connectivity has also been observed under ketamine ( Lee et al., 2013 ), during which patients often report vivid dream-like experiences, it is plausible that the reduction of frontoparietal connectivity could instead indicate loss of self-awareness.

Cognitive neuroscience studies of lucid dreaming are uniquely placed to contribute to this question because the comparison of lucid REM sleep to non-lucid REM sleep is perhaps the only contrast that allows for a direct comparison between the global loss and recovery of reflective consciousness independently of global shifts in primary consciousness, arousal or vigilance state. Thus, the question of whether lucid REM sleep is associated with altered connectivity between frontal and parietal cortices has implications for several broad questions in the cognitive neuroscience of consciousness. Future studies evaluating changes in effective connectivity during lucid REM sleep dreaming, and in particular changes in top-down frontoparietal connectivity, would be valuable.

4. Brain lesions and lucid dreaming

In the neurological literature, to our knowledge only one paper has reported changes in lucid dreaming as a result of neurological insult or brain lesions ( Sagnier et al., 2015 ). The paper describes two case reports of young patients who reported lucid dreams following unilateral ischemic stroke to the left mediodorsal thalamus. The first patient was a 26-year-old female with a left anterior and mediodorsal thalamic stroke in an area supplied by the premamillary artery, as revealed by MRI scans. She reported frequent lucid dreams in the early morning hours, along with increased nightmares and nocturnal awakenings. She also reported that her lucid dreams mostly involved the hospital and medical staff that she encountered during her hospitalization, and included catastrophic events such as helicopter crashes and hyper-aggressive behaviors. The second patient was a 36-year-old male with a left mediodorsal thalamic stroke in the area supplied by the paramedian artery as revealed by MRI scans. He reported frequent lucid dreams following the stroke, which also tended to occur in the early morning hours, along with increased nocturnal awakenings, but without an increase in nightmares. Lucid dreams subsided after one month for both patients.

Lucid dreams have not previously been reported following either unilateral or bilateral thalamic stroke. However, loss of neurons in the anterior and dorsomedian thalamic nuclei that occurs in familial fatal insomnia is associated with loss of nocturnal sleep as well as oneiric ‘intrusions’ during wakefulness ( Montagna, 2005 ; Raggi, Cosentino, Lanuzza and Ferri, 2010 ). Furthermore, hypersomnia and irregular sleep are frequently reported following paramedian thalamic stroke ( Hermann et al., 2008 ; Luigetti et al., 2011 ). These clinical features could be manifestations of disruption of the intralaminar and midline thalamic nuclei located in the mediodorsal thalamus, which are part of the brain’s arousal network ( Van der Werf, Witter and Groenewegen, 2002 ). Thus, one possibility is that lucid dreams in these patients could have partly resulted from increased or abnormal functioning of the brain’s arousal systems during sleep, which is consistent with the reported increase in nocturnal awakenings. Both patients also reported that their dreams contained highly anxious and emotional content, which could reflect abnormal connectivity between these thalamic nuclei and limbic structures with which they are densely connected ( Van der Werf et al., 2002 ). The highly emotional or disturbing content may have also contributed to lucid dreaming, as these types of experiences could induce individuals to question whether the explanation for such surprising or frightening experiences is that they are dreaming ( LaBerge and Rheingold, 1990 ).

A systematic study of the incidence of lucid dreams following thalamic strokes is lacking. Particularly given that the lucid dreams subsided after a relatively short duration (one month) for both patients, it is possible that lucid dreaming as a consequence of thalamic strokes has been under-reported and/or overlooked. More generally, a large-scale study of the occurrence of lucid dreaming in neuropsychological cases has not been undertaken and would be a welcome addition to the literature. The converse case, of a brain lesion causing loss of lucid dreaming in an individual who regularly experiences lucid dreams has also to our knowledge not been reported. Such a case would likely be very unusual, particularly considering the small percentage of individuals who experience lucid dreams spontaneously with high frequency. However, if such a case were identified it could be informative to the neurobiology of lucid dreaming.

5. Pharmacological induction of lucid dreaming

A main target of research is to develop methods to make the lucid dream state more accessible. Indeed, reliable techniques to induce lucid dreams are needed for it to be effectively used in both clinical and scientific applications. Evidence suggests that lucid dreaming is a learnable skill ( LaBerge, 1980a ) that can be developed by training with various induction strategies ( LaBerge and Rheingold, 1990 ; Price and Cohen, 1988 ; Stumbrys, Erlacher, Schadlich and Schredl, 2012 ). These include training in prospective memory techniques ( LaBerge and Rheingold, 1990 ), which can be further aided by application of external sensory cues ( LaBerge and Levitan, 1995 ; LaBerge, Levitan, Rich and Dement, 1988 ; LaBerge, Owens, Nagel and Dement, 1981b ) and/or interrupting sleep with short periods of wakefulness ( Aspy, Delfabbro, Proeve and Mohr, 2017 ; LaBerge, 1980a ; LaBerge, Phillips and Levitan, 1994 ; Stumbrys et al., 2012 ). Within cognitive neuroscience, studies have evaluated pharmacological as well as non-invasive brain stimulation approaches to lucid dream induction. In this section, we review studies that have taken a pharmacological approach to lucid dream induction and in the next section we review electrical brain stimulation studies.

5.1. Effects of Acetylcholinesterase inhibitors (AChEIs) on lucid dreaming

As discussed above, lucid dreaming is associated with increased cortical activation ( LaBerge et al., 1981a ), which reaches its peak during phasic REM sleep. Given the relationship between phasic REM sleep and lucid dreaming, as well as the role of Acetylcholine (ACh) in REM sleep regulation (e.g., Amatruda, Black, McKenna, McCarley and Hobson, 1975 ; Velazquez-Moctezuma, Shalauta, Gillin and Shiromani, 1991 ), agents acting on the cholinergic system have received particular interest. In an initial pilot study, LaBerge (2001) evaluated the effect of donepezil (Aricept), an Acetylcholinesterase inhibitor (AChEI), on lucid dreaming in a small group of participants (N=10) who reported prior experience with lucid dreaming. On each night, participants received either 0 mg (placebo), 5 mg, or 10 mg of donepezil, with the dose order counterbalanced across the three nights of the experiment. Nine of the ten participants (90%) reported at least one lucid dream on donepezil, while only one participant reported a lucid dream on the placebo dose.

Following on these results and additional pilot research, LaBerge, LaMarca and Baird (2018b) conducted a double blind, placebo-controlled study in a large group of participants (N=121) with high dream recall and an interest in lucid dreaming. The first goal of the study was to quantify the size and reliability of the effect of AChEI on lucid dreaming. The second goal was to test the effectiveness of an integrated lucid dream induction protocol that combined cholinergic stimulation with other methods, including sleep interruption and the Mnemonic Induction of Lucid Dreams (MILD) technique, which trains participants to use prospective memory to induce lucid dreams ( LaBerge, 1980a ; LaBerge and Rheingold, 1990 ). Participants were randomly assigned counterbalanced orders of three doses of galantamine (0 mg=placebo, 4 mg, and 8 mg), an AChEI that is readily accessible, fast acting and has a mild side effect profile. On three consecutive nights, participants awoke approximately 4.5 hours after lights out (after approximately the 3 rd REM cycle), recalled a dream, ingested the capsules and stayed awake for at least 30 minutes. Participants then returned to sleep practicing the MILD technique. After each subsequent awakening, participants rated their dreams on a range of variables including lucidity, recall, vividness, bizarreness, complexity, affect, cognitive clarity, metacognition and control. Full reports of lucid dreams were also collected.

Galantamine was found to significantly increase the frequency of lucid dreaming in a dose-related manner. Increased incidence of lucid dreaming was observed for both 4 mg (27% of participants) and 8 mg (42% of participants) doses compared to 14% of participants for the active placebo procedure (which included sleep interruption and MILD). Galantamine was also found to be associated with significantly increased sensory vividness and environmental complexity, which might be expected given the general intensification of REM sleep, and associated dreaming, triggered by cholinergic stimulation ( Riemann, Gann, Dressing, Muller and Aldenhoff, 1994 ).

Another recent double blind, placebo-controlled study conducted by Sparrow, Hurd, Carlson and Molina, 2018 ) also tested the effect of galantamine on lucid dreaming. 35 participants completed an eight-night study that tested the effect of 8 mg of galantamine paired with 40 minutes of sleep interruption (termed “Wake-Back-to-Bed” (WBTB) in the study). The study additionally tested combining galantamine with middle-of-the-night meditation and the imaginary reliving of a distressing dream (termed meditation and dream reliving or MDR; Sparrow, Thurston and Carlson, 2013 ). The study included pre- and post-baseline nights and six conditions: 1) WBTB; 2) WBTB + placebo; 3) WBTB + galantamine; 4) MDR; 5) MDR + placebo; and 6) MDR + galantamine. MDR conditions matched the 40 minutes of sleep interruption in the WBTB conditions. Lucid dreams were measured with self-reports on the dream lucidity scale (DLS; Sparrow et al., 2013 ), which in this study included three categories: 0=non-lucid, l=pre-lucid (which included either “questioning things in the dream without actually concluding that you were dreaming” or “doing things that are ordinarily impossible to do”), or 2=lucid.

Both galantamine conditions (WBTB + galantamine; MDR + galantamine) significantly increased self-ratings of lucidity on the DLS compared to the other conditions. However, no significant difference was observed between WBTB + galantamine and MDR + galantamine. The number of participants who had a lucid dream in each condition was not reported, only the conditional means for the DLS, which reflects the effect collapsed across both pre-lucid and lucid dreams. We therefore contacted the authors for this information in order to compare the results of this study to the study by LaBerge et al. (2018b) . 9% of participants reported a lucid dream in the WBTB + placebo condition and 11% in the MDR + placebo, whereas 40% of participants reported a lucid dream in the WBTB + galantamine and 34% in the MDR + galanatamine (S. Sparrow, personal communication, December 17, 2018). Overall, therefore, these results are comparable to the effect of 8 mg galantamine observed by LaBerge and colleagues.

5.2. Effects of L-alpha glycerylphosphorylcholine (α-GPC) lucid dreaming

In contrast to the positive findings for AChEIs, a double blind randomized placebo-controlled 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 and Pipa, 2017 ). One interpretation of this result is that, in contrast to AChEIs, α-GPC is not effective for inducing lucid dreams, perhaps due to differences in the neurobiological effects of choline—an ACh precursor—and AChEIs. However, participants in this study appear to have received no training in mental set, such as recalling and attending to dreams in an effort to become lucid. Thus, an alternative, not mutually exclusive, interpretation is that training in at least the minimal mental set for lucid dream induction is needed for pharmacological (and other) interventions to effectively increase the frequency of lucid dreams.

5.3. General discussion of pharmacological induction of lucid dreaming

Overall, these data provide strong initial evidence that cholinergic enhancement with AChEls, and galantamine in particular, facilitates a state of the brain favorable to lucid dreams. However, a limitation of all pharmacological studies on lucid dreaming performed to date is that they were not conducted in a sleep laboratory and there was therefore no validation of lucid dreams with eye-signaling methods. It will be important to follow up these results with sleep laboratory studies to objectively validate lucid dreams with polysomnographic recording. Such studies would also be valuable to investigate the physiological effects of galantamine on the brain during REM sleep, and which effects are predictive of lucidity. Given the high success rate of lucid dreams in the combined induction protocol with cholinergic stimulation reported by LaBerge, LaMarca and Baird (2018) and Sparrow et al. (2018) , studies of galantamine have the potential to enable efficient collection of large sample sizes in electrophysiological and neuroimaging studies of lucid dreaming.

The mechanism by which AChEls facilitate lucid dreams remains unclear. There are several, not mutually exclusive, possibilities, including increasing REM sleep intensity/phasic activation, influencing the brain regions/networks associated with lucid dreaming, and influencing cognitive processes associated with becoming lucid. In general, it is known that AChEls inhibit the metabolic inactivation of ACh by inhibiting the enzyme acetylcholinesterase (AChE), leading to accumulation of ACh at synapses. Furthermore, ACh and its agonists as well as AChE and its antagonists are involved in the generation of REM sleep ( Amatruda et al., 1975 ; Gillin et al., 1985 ; Velazquez-Moctezuma et al., 1991 ). For example, evidence suggests that REM sleep is controlled by cholinergic neurons in the brainstem ( Baghdoyan, 1997 ; Hernandez-Peon, Chavez-Ibarra, Morgane and Timo-Iaria, 1963 ), and studies have observed that microinjection of the ACh agonist carbachol in the pontine area of the brainstem results in REM sleep in both humans and animals ( Amatruda et al., 1975 ; Baghdoyan, 1997 ). Administration of galantamine has been associated with increased phasic activity and shortened REM latency ( Riemann et al., 1994 ). The increased frequency of lucid dreams associated with AChEls could therefore plausibly be related to its effects on cholinergic receptors during REM sleep, leading to longer, intensified REM periods with increased phasic activity, which, as noted above, has been found to be associated with lucid dreams ( LaBerge et al., 1981a ).

Beyond intensification of REM sleep/phasic activation, AChEls might also directly act on cognitive processes associated with lucidity and their neural underpinnings. One key question is whether AChEIs could facilitate lucid dreaming through increasing activation within the network of frontopolar-temporo-parietal areas observed in the neuroimaging studies of Dresler et al. (2012) and Baird et al. (2018a) . The relationship between cholinergic modulation and frontoparietal activation is complex and depends on the task context and population under study (see Bentley, Driver and Dolan, 2011 for a review). However, pro-cholinergic drugs in general tend to increase frontoparietal activity in conditions in which these areas show low baseline activation, which is thought to reflect increased attentional-executive functions ( Bentley et al., 2011 ). Given that frontoparietal activity is typically suppressed during REM sleep ( Braun et al., 1997 ; Maquet et al., 1996 ), it is plausible that AChEIs could increase activation within this network during REM sleep dreaming.

Notably, AChEls are also prescribed to manage the cognitive symptoms of Alzheimer’s disease ( Koontz and Baskys, 2005 ). Theoretically, another way that AChEls could facilitate lucid dreams is therefore through their effect on memory. For example, AChEIs could enhance the ability to remember to recognize that one is dreaming (a form of prospective memory), which is the core of the MILD technique for lucid dream induction that participants engaged in during the study by LaBerge, LaMarca and Baird (2018b) . However, evidence for cognition enhancing effects of AChEls in healthy subjects, particularly for single doses, is sparse ( Dresler et al., 2018 ), rendering the theoretical possibility of a memory-mediated effect on dream lucidity unlikely. Overall, it remains unclear whether galantamine also exerts a direct influence on cognitive processes associated with lucidity, and the MILD technique in particular, or whether it merely optimizes the physiological conditions for such techniques.

One last possibility is that AChEIs could influence lucidity indirectly by affecting other neuromodulators. For example, evidence suggests that AChEls also increase systemic norepinephrine and dopamine ( Cuadra, Summers and Giacobini, 1994 ; Giacobini, Zhu, Williams and Sherman, 1996 ). It is therefore possible that the increase in lucid dreams associated with AChEI might instead be directly linked to aminergic modulation that occurs as a result of the increases in ACh. Additional research will be needed to understand how the neuromodulatory changes caused by AChEIs stimulate lucid REM sleep dreaming. Studies using Positron Tomography (PET) or pharmaco-fMRI would be valuable to address this issue.

Several other pharmacological substances have been suggested to increase the frequency of lucid dreams, including various types of supplements and drugs (e.g., Yuschak, 2006 ). For instance, recreational drugs such as alcohol, cocaine and cannabis have been reported to be associated with lucid dreaming. These substances suppress REM sleep ( Roehrs and Roth, 2001 ; Schierenbeck, Riemann, Berger and Hornyak, 2008 ), which leads to a phenomenon referred to as REM rebound, in which longer REM sleep periods occur following REM sleep suppression ( Vogel, 1975 ). Intensified, prolonged REM sleep as a result of REM rebound could potentially increase lucid dream frequency, particularly in individuals predisposed to have lucid dreams or with prior experience in lucid dreaming. Another example is LSD, since there is some evidence that it can prolong REM sleep periods at some doses ( Muzio, Roffwarg and Kaufman, 1966 ), which could potentially be favorable to lucid dreaming. To our knowledge, however, no studies have systematically evaluated whether these substances, or other substances not reviewed here, increase the incidence of lucid dreams. Furthermore, it is prudent to remain cautious about such claims given the placebo effect. Placebo-controlled studies will be essential to substantiate any purported effects of pharmacological substances on lucid dreaming.

6. Induction of lucid dreams with transcranial electrical brain stimulation

Two studies have attempted to induce lucid dreams through transcranial electrical stimulation of the frontal cortex during REM sleep. Stumbrys, Erlacher and Schredl (2013b) tested direct current stimulation and Voss et al. (2014) tested alternating current stimulation. We review each of these studies in turn.

6.1. Effects of frontal transcranial direct current stimulation on lucid dreaming

In an investigation of the effect of transcranial direct current stimulation (tDCS) on lucid dreaming, Stumbrys et al. (2013b) applied either tDCS or sham stimulation (counterbalanced across nights) over a frontolateral scalp region in 19 participants. Stimulation was delivered through two pairs of electrodes with anodes at positions F3 and F4, respectively, and cathodes at the supraclavicular area of the same side. Stimulation was applied during all REM sleep periods except the first for two consecutive nights in the sleep laboratory. In total, 109 stimulations were performed, after which participants were awakened to complete a dream report.

Compared to sham stimulation, tDCS resulted in a small numerical increase in self-ratings of the unreality of dream objects as assessed by the Dream Lucidity Questionnaire (DLQ; Stumbrys et al., 2013b ). Post-hoc analyses revealed that this effect was seen only in subjects with a high baseline frequency of lucid dreams, but not in participants with little or no lucid dreaming experience. However, tDCS did not significantly increase the number of dreams rated by judges to have a clear indication of lucidity: seven dreams in total, three from sham stimulation and four from tDCS stimulation. Furthermore, only one lucid dream in total was confirmed by eye signaling, which was in the stimulation condition. Given a difference of only one lucid dream between stimulation and sham conditions for either of these two assessment criteria, overall frontal stimulation with tDCS as tested in this study does not appear to be a reliable method for inducing lucid dreams.

6.2. Effects of frontal transcranial alternating current stimulation on lucid dreaming

A study by Voss et al. (2014) reported a more pronounced increase in lucid dreaming by applying transcranial alternating current stimulation (tACS) in the gamma frequency band over the frontal cortex. The study tested 27 participants for up to four nights in the sleep laboratory. tACS was applied for 30 seconds after two minutes of uninterrupted REM sleep to frontolateral scalp regions at several different frequencies (2, 6, 12, 25, 40, 70 or 100 Hz or sham stimulation). Stimulation was delivered through two pairs electrodes with anodes at positions F3 and F4, respectively, and cathodes over the mastoids close to TP9 and TP10, respectively. Participants were then awakened and completed a dream report and the Lucidity and Consciousness in Dreams (LuCiD) scale ( Voss et al., 2013 ). The LuCiD scale measures dream content on several different factor-analytically derived dimensions, including insight, control, thought, realism, memory, dissociation and affect.

The authors reported they were able to induce lucid dreams with a success rate of 58% with 25 Hz stimulation and 77% with 40 Hz stimulation. However, it is important to note how lucid dreams were classified in this study: instead of assessment of lucid dreams with eye signaling, self-report, or through statistical analysis of judges’ ratings of dream reports, as in Stumbrys et al. (2013b) , dreams were assumed to be lucid if subjects reported “elevated ratings (>mean + 2 s.e.) on either or both of the LuCiD scale factors insight and dissociation”. While dissociation scores (i.e., “seeing oneself from the outside” or a “3 rd person perspective”) have been found to be increased in lucid dreams before ( Voss et al., 2013 ), dissociation in the sense of adopting a 3 rd person perspective has never been considered a defining feature of lucid dreams per se (e.g., DeGracia and LaBerge, 2000 ; Gackenbach and LaBerge, 1988 ; Green, 1968 ; LaBerge, 1985 , 1990 ). It is therefore controversial to classify dreams as lucid based solely on higher ratings of dissociation.

The insight subscale corresponds more closely to the standard definition of lucid dreams adopted by other researchers as well as the general public. Mean ratings in the insight subscale increased from approximately 0.1-0.2 in the sham stimulation to 0.5-0.6 in the 25 Hz or 40 Hz stimulation conditions, similar to the effects in the dissociation subscale, which was approximately 0.9-1.2. However, the scale anchors ranged from 0 (strongly disagree) to 5 (strongly agree), indicating that, on average, in both the 25 Hz and 40 Hz stimulation conditions, participants disagreed that their dreams had increased insight. Moreover, in the original validation of the LuCiD scale, non-lucid dreams scored on average at 0.3 or 0.8 on the insight scale (depending on whether the assessment was laboratory or survey based), whereas lucid dreams scored at 3.2 or 3.5 ( Voss et al., 2013 ). Thus, though significantly stronger in relation to sham simulation, mean responses of 0.5-0.6 in the 25 and 40 Hz stimulation conditions were much lower than the values reported for lucid dreams in the validation study, and still on the non-lucid (disagree that the dream contains insight) end of the scale spectrum in absolute values. Overall, therefore, the results of this study appear to be comparable to the tDCS finding of Stumbrys et al. (2013b) in that prefrontal tACS gamma band stimulation induced numerical increases in some measures of dream content, but does not appear to have lead to increases in the number of lucid dreams when defined in the traditional sense of being aware of dreaming while dreaming.

6.3. General discussion of induction of lucid dreaming with electrical brain stimulation

In summary, studies examining induction of lucid dreams with electrical brain stimulation (tDCS and tACS) have thus far observed intriguing effects on dream cognition, but a method for reliably inducing lucid dreams by electrical stimulation of the brain is still yet to be identified. We think this is a particularly interesting direction for upcoming work. Future studies might consider stimulating a wider number of brain areas and different types of stimulation. For example, transcranial magnetic stimulation (TMS) is another method of noninvasive brain stimulation that could be used to attempt to induce lucid dreams that has not yet been examined ( Noreika, Windt, Lenggenhager and Karim, 2010 ; Mota-Rolim et al., 2010 ). In contrast to tACS or tDCS, high-frequency repetitive TMS (rTMS) stimulation sequences can be used to increase neuronal excitability in focal areas of the cortex (e.g., Hallett, 2007 ). Several practical challenges with application of TMS during sleep include the auditory artifacts produced by the TMS coil as well as tactile sensations on the scalp during stimulation, which may lead to awakenings. However, noise masking has been used to prevent subjects from hearing the clicks associated with TMS pulses (e.g., Nieminen et al., 2016 ), and scalp sensations could be decreased, for example, by reducing stimulation intensity or potentially by application of a topical anesthetic cream.

Studies of electrical brain stimulation have also thus far only tested a small part of the parameter space and there are many other stimulation protocols that appear to be worth evaluating. For example, given the neuroimaging results reviewed above, synchronous frontoparietal tACS—in which synchrony is increased between frontal and parietal regions by simultaneous stimulation of these regions (e.g., Violante et al., 2017 )—is another stimulation method that would be interesting to examine. Finally, as noted above, these methods are likely to maximize their effect when participants are trained in at least the minimal mental set for lucid dream induction, which was not done in either the study by Voss et al. (2014) or Stumbrys et al. (2013b) .

7. Lucid dreaming as a methodology for the cognitive neuroscience of consciousness

Psychophysiological studies of non-lucid dreams have been used to study neural correlates of conscious experiences during sleep ( Perogamvros et al., 2017 ; Siclari et al., 2017 ). However, there are significant limitations to this approach. Specifically, while methods such as “serial awakenings” are useful for contrasting the global presence vs. absence of dream experience during sleep ( Siclari et al., 2017 ), it is an inefficient method to collect data on specific conscious contents during sleep. For instance, given that non-lucid dreamers usually have no control over their dream content, these studies typically employ a shot-in-the-dark approach, in which large numbers of sleep recordings are made and small subsets of data in which the content of interest appears by chance are extracted. Additionally, and perhaps most importantly, establishing temporally precise correlations between retrospective dream reports and physiological measurements is a substantial challenge. Lucid dreaming provides ways to overcome several of these challenges. For example, as mentioned above, lucid dreamers can conduct specific tasks within REM sleep dreams, enabling experimental control over dream content. Furthermore, as noted, participants can be trained to time-stamp the onset and offset of particular content or actions with eye movement signals, which provides a way to obtain more precise correlations between conscious experiences and physiological measurements during sleep ( Dresler et al., 2011 ; LaBerge, 1990 ; LaBerge, Greenleaf and Kedzierski, 1983 ). In this section we briefly summarize several recent studies that illustrate how lucid dreaming can be used as a methodology in the cognitive neuroscience of consciousness.

7.1. Activation of sensorimotor cortex during dreamed movement in REM sleep

Dresler et al. (2011) used lucid dreaming to test whether a motor task performed during dreaming elicits neuronal activation in the sensorimotor cortex. Participants made a series of dreamed left and right hand clenches in their lucid dreams and marked the start and end of the sequences of clenches with LRLR eye movements. Specifically, participants clenched their left hand in the dream ten times, then signaled LRLR, then clenched their right hand in the dream ten times, then signaled LRLR, and continued repeating this sequence for as long as possible until awakening. Additionally, participants performed an executed hand-clenching task as well as imagined hand-clenching task during wakefulness for comparison. Six participants with prior experience in lucid dreaming participated in the study. Of these, two participants succeeded in performing the task during lucid REM sleep: one under simultaneous EEG-fMRI (in two different signal-verified lucid dreams) and one under combined EEG-near-infrared spectroscopy (NIRS) recording (again in two different signal-verified lucid dreams).

Contrasting left vs. right fist clenches, increased BOLD signal in the contralateral sensorimotor cortex was observed in both lucid dreams of the fMRI experiment, as well as in waking and imagination conditions. Compared to executed hand clenches during wakefulness, however, BOLD signal increases during dreaming in contralateral sensorimotor cortex were more localized, which could indicate either weaker activation or more focal activation of hand areas only. BOLD signal fluctuations during dreaming were approximately 50% of those observed for executed hand clenches during wakefulness. Correspondingly, the NIRS data showed increased oxygenated hemoglobin and decreased deoxygenated hemoglobin in the contralateral sensorimotor cortex during dreamed hand clenching. This hemodynamic response was also observed in the supplementary motor area, which is involved in the timing, monitoring and preparation of movements ( Goldberg, 1985 ). This differed with the fMRI data in which no significant differences in the supplementary motor area were found. Interestingly, during dreamed hand clenching, hemodynamic responses were smaller in the sensorimotor cortex but of similar amplitude in the supplementary motor area when compared to overt motor performance during wakefulness.

Overall, these data suggest that the pattern of brain activation observed during dreamed motor execution overlaps with motor execution during wakefulness. However, given the different patterns of activation, the data may also suggest that the interactions between the supplementary motor area, somatosensory and sensorimotor cortex differs between REM sleep dreaming and waking. The authors suggest that the reduced activation in sensorimotor cortex could be due in part to the lack of sensory feedback as a result of REM sleep atonia. However, given that this study consisted of two case reports—one for each imaging modality—the data should be interpreted cautiously. Clarification of the neural correlates of dreamed motor activity, as well as clarification of any differences in this network compared to overt motor performance, awaits larger-scale group-level studies. Nevertheless, this experiment provides a proof-of-concept that neuroimaging of specific dream content can be accomplished using lucid dreaming as a methodology.

7.2. Voluntary control of central apneas during REM sleep dreaming

A similar type of experiment was recently undertaken by Oudiette et al. (2018) to examine respiratory behavior during REM sleep dreaming. Specifically, the researchers used lucid dreaming to investigate whether irregular breathing during REM sleep has a cortical origin and whether such breathing patterns can reflect the mental content of dreams. This research follows up on a study from LaBerge and Dement (1982) which observed tachypnea during volitional rapid breathing and apnea during voluntary breath holding during lucid REM sleep dreaming. Polysomnography and respiration were recorded during early morning naps from 21 patients with narcolepsy who reported frequent lucid dreams. Participants were instructed to modify their dream scenario so that it involved vocalizations or an apnea (e.g., diving under water)—two respiratory behaviors that purportedly require a cortical control of respiration ( McKay, Adams, Frackowiak and Corfield, 2008 ). Participants signaled the onset of lucidity as well as the start and end of the respiration tasks with LRLR eye movement signals. Participants also performed the task during waking by actually executing the respiratory task as well as during waking imagination. In total, 32 lucid REM sleep naps were included in the analysis. Physiological data was scored for the presence of central apneas, which were defined as “cessation of nasal flow for more than 10 s in the absence of cyclic thoracic and abdominal movements” as well as preparatory breaths preceding the central apnea.

In 16 out of the 32 signal-verified lucid dreams, the physiological data showed the expected respiratory behavior (e.g., a central apnea, in some cases including preparatory breaths), which was appropriately marked by LRLR signals and confirmed by dream reports of becoming lucid and executing the task. In the remainder of cases, participants either failed to control the dream (N=2) or appropriately execute the LRLR signals (N=2), or there was incongruence between the report and the data (participants either did not recall performing the task (N=8) or there was no physiological evidence of the task despite a report of completing the task (N=4)). As the authors discuss, the incongruences between reports and physiological data may in part have been attributable to the fact that reports were obtained at the end of the 30-minute nap sessions rather than awakening subjects directly after completing the task. Thus, in some cases this resulted in a long delay between the dream task and the report. Despite the presence of these ambiguous cases, overall the data show that voluntarily control of central apneas during REM sleep occurred in a majority of participants.

As the authors discuss, the pons is hypothesized to regulate cessation of breathing, which assimilates input from supra-brainstem structures and inhibits medullary respiratory neurons ( McKay et al., 2008 ). Thus, they conclude that the fact that voluntary control of central apneas is possible during REM sleep suggests that this cortico-pontine drive is preserved during REM sleep. However, it remains unclear from this study to what extent non-lucid dreams containing this type of mental content (for example, diving under water), would result in central apneas. Indeed, as the authors note, some participants reported that they voluntarily held their breath when diving under water in the dream even though they did not feel that they had to. In general, it remains unclear whether central apneas as observed in the study are linked to the voluntary control of respiration enabled during lucid dreams in particular or whether they systematically occur in dreams with this type of content/scenario. In either case, however, the data support the conclusion that voluntarily control of central apneas is possible during REM sleep.

7.3. Smooth pursuit eye movements during visual tracking in REM sleep dreaming

One last recent example of the use of lucid dreaming as methodology in cognitive neuroscience is provided by LaBerge, Baird and Zimbardo (2018a) , who addressed the question of whether smooth pursuit eye movements (SPEMs) occur during tracking of a slowly moving visual target during lucid REM sleep dreaming. Seven participants with high reported dream recall and frequency of lucid dreams participated in the study. Participants marked the moment of lucidity as well as the initiation and completion of the tracking tasks with LRLR eye movement signals. After making the LRLR signal, participants performed one of two eye-tracking tasks: circle tracking or one-dimensional movement tracking on the horizontal meridian. For each tracking task, participants followed the tip of their thumb with their gaze as they traced the pattern. Participants performed the tracking tasks in three conditions: 1) lucid REM sleep dreaming (“dreaming”), 2) awake with eyes open (“perception”) and 3) tracking the imagined movement while awake with eyes closed (“imagination”). Eye movements were recorded with direct current EOG and subjected to a validated algorithm that classifies saccades, fixations and smooth pursuit eye movements ( Komogortsev and Karpov, 2013 ).

The results revealed that intentional slow tracking of visual motion (of both circles and lines) during lucid REM sleep dreams results in SPEMs. Pursuit eye movements in REM sleep dreams did not significantly differ from pursuit during waking perception, and both were characterized by high pursuit ratios and low saccade rates. In contrast, tracking in imagination was characterized by low pursuit with frequent saccadic intrusions. A Bayesian classification model that included pursuit ratio and saccade rate discriminated both REM sleep dreaming and perception from imagination with greater than 98% accuracy.

Together, these findings help to address several broad questions within cognitive neuroscience and sleep research. First, the data provide empirical evidence for a difficult to test question that has been asked at least since Aristotle: “Are dreams more like perception or imagination?” ( Nir and Tononi, 2010 ). Based on the smooth tracking behavior, the findings of this study suggest that, at least in this respect, the visual quality of REM sleep dream imagery is more similar to waking perception than imagination. Second, the findings help to address a longstanding question in the psychophysiology of sleep since the discovery of REM in the 1950’s: whether the eye movements of REM sleep track the gaze of the dreamer—the so-called “scanning hypothesis” (for a review, see Arnulf, 2011 ). By demonstrating that individuals can trace circles and lines with their gaze while in EEG-verified REM sleep, which can be recorded with EOG, the data provide unique evidence that shifts in the perceived gaze direction in dreams give rise to the appropriate corresponding eye movements. This is consistent with the view that a subset of eye movements during REM sleep are linked to the direction of subjective gaze during dreams. Lastly, the results also provide a novel source of data for a central research question on the topic of smooth pursuit in humans and non-human primates that dates back at least forty years. Specifically, an enduring question has been whether a physical stimulus and/or retinal image motion is necessary to drive the neural circuitry of smooth pursuit ( Spering and Montagnini, 2011 ). By demonstrating that sustained SPEMs can be elicited in the absence of visual input to the cortex, as is the case during REM sleep, the findings provide strong evidence that neither a physical motion stimulus nor readout of retinal image motion are necessary for SPEMs.

7.4. General discussion of lucid dreaming as experimental methodology

Altogether, these studies illustrate the potential of lucid dreaming as an experimental methodology for the study of consciousness in general and REM sleep dreaming in particular. The fact that lucid dreamers can exercise volitional control over their actions while dreaming and conduct experiments from within EEG-verified REM sleep dreams opens up the ability to perform experiments that would otherwise be difficult or impossible to conduct. This methodology also has the potential to more efficiently target specific research questions. As discussed above, lucid dreaming enables both experimental control over the content of dreams as well as a way to establish precise psychophysiological correlations between the contents of consciousness during sleep and physiological measures in a way that is not possible in studies of non-lucid dreaming. In sum, lucid dreaming provides a methodology that allows for new ways of studying the relationship between consciousness and neurophysiological processes, and, as the above studies highlight, shows emerging potential for research on consciousness in sleep science.

8. Clinical cognitive neuroscience of lucid dreaming

Research on lucid dreaming is not only relevant to the neuroscience of consciousness but could also have clinical implications. While a detailed treatment of the clinical applications of lucid dreaming is beyond the scope of this review (see e.g., Garfield, Fellows, Halliday and Malamud, 1988 ), here we briefly note several interesting applications and future directions with particular relevance for cognitive neuroscience.

8.1. Lucid dreaming in the treatment of persistent nightmares

The most researched application of lucid dreaming is to treat recurring nightmares ( Abramovitch, 1995 ; Holzinger, Klösch and Saletu, 2015 ; Spoormaker and Van Den Bout, 2006 ; Tanner, 2004 ; Zadra and Pihl, 1997 ). Lucid dreaming was included by the American Academy of Sleep Medicine in their therapy suggestions for nightmare disorder ( Morgenthaler et al., 2018 ). Conceptually, the idea is that becoming lucid during a nightmare should allow the dreamer to realize the content of the nightmare is not real and thus has no reason to be afraid, and to be able to exert control over the dream and/or work with the psychological content of the nightmare ( LaBerge and Rheingold, 1990 ; Mota-Rolim and Araujo, 2013 ). Neurocognitive models of nightmare generation suggest a hyper-responsivity of the amygdala coupled with a failure of prefrontal regions to dampen this activation ( Levin and Nielsen, 2007 ). Studying the influence of lucidity on nightmare resolution could therefore provide an interesting opportunity to study top-down regulation of amygdala activation, perhaps through reactivation of prefrontal regions ( Dresler et al., 2012 ).

A case study ( Zadra and Pihl, 1997 ), and one small, controlled pilot-study ( Spoormaker and Van Den Bout, 2006 ) have found that lucid dreaming therapy was effective in reducing nightmare frequency. Also a study of 32 patients who suffer from frequent nightmares found a slight advantage of lucid dreaming as add-on to Gestalt therapy compared to the latter alone ( Holzinger et al., 2015 ). In contrast, a larger online study did not find any additional effect of lucid dreaming therapy as an add-on to other cognitive-behavioral techniques, such as imagery rehearsal therapy ( Lancee, Van Den Bout and Spoormaker, 2010 ), although low power and high dropout rates (>70%) limited the scope of the conclusions. Controlled experiments with larger sample sizes are needed to further evaluate the potential usefulness of lucid dreaming for the treatment of recurring nightmares and related disorders, as well as to examine the neural mechanisms of these interactions.

8.2. Lucid dreaming and narcolepsy

Consistent with a potential beneficial role of lucid dreaming in recurring nightmares, patients with narcolepsy report that becoming lucid provides psychological relief ( Rak et al., 2015 ). Generally, narcolepsy patients experience longer, more complex, and more vivid dreams and more frequent nightmares than healthy subjects ( Mazzetti et al., 2010 ). Moreover, patients with narcolepsy report higher reflective consciousness within dreams ( Fosse, 2000 ) and accordingly a considerably increased lucid dreaming frequency ( Dodet et al., 2014 ; Rak et al., 2015 ). The mechanisms for this increased lucid dreaming frequency are not entirely understood yet: nightmares often lead to the insight into the current dream state, however it is currently unclear if an increased nightmare frequency causes an increased lucid dreaming frequency in narcolepsy, or if the strongly increased frequency of REM sleep in narcolepsy affects nightmares and lucid dreaming independently. In particular sleep onset REM (SOREM) episodes appear to prompt lucid dreams ( Dodet et al., 2014 ), which is in line with the dream lucidity-enhancing effects of the early morning “Wake-Back-to-Bed” procedure in healthy subjects. Of note, patients with narcolepsy make a clear distinction between their experiences of lucid dreaming and sleep paralysis ( Dodet et al., 2014 ), and the increased lucid dreaming frequency in this patient group does not appear to be associated with medication use (Rak et al., 2014). It has been speculated whether, potentially as a result of a considerably increased lucid dreaming experience, narcoleptic patients might exhibit different neurophysiological correlates of lucid dreaming ( Dodet et al., 2014 ).

8.3. Lucid dreaming as a model of insight in psychiatric conditions

Another area in which research on lucid dreaming might be applied is in psychiatric disorders in which patients suffer from lack of insight into their state. Indeed, there is considerable overlap between preliminary findings of brain regions related to insight into the dream state and brain regions impaired in psychotic patients with disturbed insight into their pathological state ( Dresler et al., 2015 ; Mota, Resende, Mota-Rolim, Copelli and Ribeiro, 2016 ). The concept of insight is becoming an increasingly important area in schizophrenia research (e.g., Baier, 2010 ), for example, where between 50 and 80% of patients diagnosed with schizophrenia have poor insight into the presence of their disorder ( Lincoln, Lullmann and Rief, 2007 ). Evidence suggests that poor insight in turn leads to more relapses, re-hospitalizations and poorer therapy success ( Mintz, Dobson and Romney, 2003 ). With regard to dreaming, lack of insight into the current state characterizes almost all dream experiences, with the exception of lucid dreaming. Thus, lucid dreaming could potentially be used as a model for at least some cognitive dimensions of insight ( David, 1990 ). In this context it is interesting to note that historical approaches to psychosis used the term lucid to denote the awareness of the patient into his or her illness ( Berrios and Markova, 1998 ). At the current time, these ideas remain highly speculative, but this appears to us to be an area worthy of additional research.

8.4. Using lucid dreaming to establish brain activity markers of self-awareness

Another potential clinical application of research on lucid dreaming 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. Neurobiological studies of lucid dreaming could provide information relevant to development of these brain activity markers 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 ( Laureys, Perrin and Bredart, 2007 ). This information is critical to making appropriate therapeutic choices and determining prognosis ( Laureys et al., 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 and Schiff, 2004 ; Schnakers et al., 2009 ). Accordingly, identification of a reliable brain activity marker of a patients’ capacity for self-awareness—which could be informed by studying the changes in brain activity between lucid and non-lucid REM sleep dreaming—is an important goal. Research on lucid dreaming has the potential to contribute a valuable source of data to this question since, as noted above, the contrast between lucid and non-lucid REM sleep is perhaps the only one currently known in which a global loss and recovery of self-awareness can be contrasted within the same vigilance state in healthy individuals.

9. The measurement of lucid dreaming in cognitive neuroscience research

In this last section, we review methodological issues and strategies in the measurement of lucid dreaming in cognitive neuroscience research. We review the validation of lucid dreaming both physiologically and with questionnaires, and discuss best-practice procedures to investigate lucid dreaming in the sleep laboratory.

9.1. Eye signaling methodology

The eye signaling methodology is the gold standard in lucid dreaming research, as it allows for objective confirmation of lucid dreams through the execution of pre-agreed upon sequences of eye movements recorded with the EOG during EEG-verified REM sleep ( Figure 1 ). While there are some types of research studies (e.g., field studies) where eye signaling is not possible or not applicable, we recommend considering this method as the standard practice for laboratory-based studies of lucid dreaming. In general, most recent studies have adhered to this convention; however, there is some confusion about how to properly instruct participants in executing the eye movements, which has resulted in studies implementing several different variations of the method. For instance, while some experimenters instruct participants to move their eyes left and right (e.g., Dresler et al., 2012 ), in other cases participants have been instructed to “scan the horizon” from left to right ( Dodet et al., 2014 ).

Differences in eye signaling instructions could partly account for the varying degrees of effectiveness in objectively identifying the eye signals across studies. For example, Dodet et al. (2014) reported that while three control participants and twelve narcoleptic patients reported making the eye signal in overnight EEG recordings, none of these could be objectively identified, and only about half of reported signals could be unambiguously identified from nap recordings. While it is possible that some of these instances represent cases where participants misremembered or misreported a lucid dream, it is likely that this high rate of ambiguous eye movement signals is partly attributable to the specific instructions that were given. Similarly, while the exact instructions provided to participants was not described, Voss et al. (2009) stated that they were unable to obtain reliable eye signals using the standard signaling method and therefore attempted to develop a novel signaling method employing two sets of eye-signals separated by a pause. Again, suboptimal results could plausibly be due to the instructions provided and the way the eye signals were executed by participants in the study.

One reason for the confusion and diverse instructions given for the eye signaling methodology is that a standardized set of instructions for making the signals has never been published. Here we report a simple set of instructions adapted from LaBerge et al. (2018a) that has been reported to yield nearly 100% correspondence between subjective reports of eye signals and objective EOG recordings. The instruction is as follows:

When making an eye movement signal, we would like you to look all the way to the left then all the way to the right two times consecutively, as if you are looking at each of your ears. Specifically, we would like you to look at your left ear, then your right ear, then your left ear, then your right ear, and then finally back to center. Make the eye movements without moving your head, and make the full left-right-left-right-center motion as one rapid continuous movement without pausing.

Looking at the ears is one of the critical aspects of the instruction, as it encourages full-scale eye movements without corresponding head movements. These extreme and rapid consecutive eye movements make the signals easy to discern in the horizontal EOG time series. The signals are of higher amplitude than typical REMs, and have a distinctive shape ( Figure 1 ) which can be identified with template matching ( LaBerge et al., 2018a ). To optimize execution of the eye signals, participants are given the opportunity to practice the signals in the laboratory while awake and connected to the EOG, with an opportunity to view the signals and receive feedback from the experimenter. Additionally, participants practice making the eye signals in any lucid dreams they have at home in the weeks leading up to the sleep laboratory visit, in order to gain experience with executing the signals.

9.2. Questionnaire assessment of lucid dreaming

A related issue concerns how the phenomenology of lucid dreaming should optimally be assessed in cognitive neuroscience research. Several questionnaires have been developed to assess changes in conscious experience during dreaming. For instance, the Metacognitive, Affective, Cognitive Experience questionnaire (MACE; Kahan, LaBerge, Levitan and Zimbardo, 1997 ; Kahan and Sullivan, 2012 ) was designed to assesses the monitoring and regulation of both cognitive and affective experience during both wakefulness and sleep. In its latest form, it consists of ten items, including four self-monitoring questions, three questions on self-reflective consciousness and three questions that target self-regulatory behaviors. Another measure, the Dream Lucidity Questionnaire (DLQ; Stumbrys et al., 2013b ), is designed to assess different aspects of lucidity within dreams. It consists of ten items, scored on a 5-point scale: 0 – not at all, 1 – just a little, 2 – moderately, 3 – pretty much, 4 – very much. The DLQ evaluates different types of awareness (awareness of dreaming, awareness that the physical body is asleep, awareness that dream characters and objects are not real, awareness of different possibilities) and control (deliberately choosing an action, changing dream events, dream characters, dream scenes, breaking physical laws). In a similar manner, the Lucidity and Consciousness in Dreams scale (LuCiD, Voss et al., 2013 ) includes eight subscales, derived from factor analysis of a sample of lucid and non-lucid dream reports, which assess various dimensions of dreaming experience and cognition: 1) Insight, 2) Control, 3) Thought, 4) Realism, 5) Memory, 6) Dissociation, 7) Negative emotion, and 8) Positive emotion.

All three questionnaires provide measures for evaluating how some content dimensions might differ across lucid and non-lucid dreams. However, as mentioned, questionnaires such as these are not sufficient to objectively establish whether a participant had a lucid dream. It is worth noting that only the DLQ in its first question (“I was aware that I was dreaming”) directly queries whether the dreamer was lucid, and the MACE was never intended for this purpose. Most studies using the DLQ and LuCiD questionnaires have collected a dream report from participants in addition to the questionnaire responses. We would like to emphasize the importance of this point: Instead of relying on the inference of lucidity solely from questionnaire measures of dream content, accurate assessment of lucidity can be facilitated by, in addition to using the eye signaling method, collecting a full dream report from participants. In making the dream report, participants are typically asked to describe in as much detail as possible the narrative of the dream, including the sequence of events and any thoughts, feelings or sensations that they experienced. In dream reports for lucid dreams, the participant is also asked to include a specific description of how they became lucid in the dream (for example, by noticing an oddity of an event, action or person in the dream, which is also known as “dream sign”) and also to explicitly note any eye signals made at the appropriate instances in the dream narrative.

Following the collection of a full open-ended dream report, further confirmation of lucidity and eye signaling can be accomplished with simple follow-up questions, including, for example: 1) “Were you aware of the fact that you were dreaming while you were dreaming?” (YES/NO), If YES: 2) “How confident are you that you became lucid?” (0-4 scale), 3) “Did you have a wake-initiated lucid dream (WILD) or a dream initiated lucid dream (DILD)?” (DILD/WILD), 4) “Did you make the eye movement signal to indicate that you became lucid?” (YES/NO), 5) “Please briefly describe how you became lucid.” These example questions are not meant to be exhaustive, but they illustrate the types of questions that in our view are useful to obtaining an accurate and thorough assessment of lucid dreams following collection of a full dream report.

9.3. Measurement of individual differences in lucid dreaming

Another related question facing researchers is how to measure individual differences in lucid dream frequency, which has been done in inconsistent ways, and could be improved in future research. A method used in several studies consists of an 8-point scale that asks participants to self-rate the frequency with which they experience lucid dreams, ranging from “never” to “several times per week” ( Schredl and Erlacher, 2004 ; Mota-Rolim et al., 2013 ). While this method provides a straightforward coarse assessment of an individual’s estimated frequency of lucid dreams that has shown high test-retest reliability ( Stumbrys, Erlacher and Schredl, 2013a ), a limitation is that it does not measure lucid dream frequency greater than several times per week. The scale could be improved by including additional categories on the higher end of the measure, including, for example, “Every night” and “Multiple times per night.” While individuals who experience lucid dreams on a nightly basis represent a very small percentage of respondents (according to Baird et al. (2018a) approximately one in one thousand), optimally this kind of instrument would enable a researcher to distinguish respondents that have lucid dreams once or several times a week from those that have them every night or multiple times per night. Indeed, these “virtuoso” lucid dreamers represent perhaps one of the most interesting populations for cognitive neuroscience studies of individual differences in lucid dreaming ( Baird et al., 2018a ).

A related method is to query the number of lucid dreams reported in a given period of time (i.e., the last 6 months), which has the advantage of asking participants to report a specific number rather than a coarse estimate. In principle, this method has the potential to be more accurate and to capture increased variance. However, some participants, particularly those with high lucid dream rates, may not be able to recall all instances of their lucid dreams within the requested time interval, and may therefore resort to heuristics when answering the question, making it akin to simply asking participants to report frequency using a multiple-choice scale. Furthermore, this method may not accurately assess lucid dream frequency over longer periods of time – i.e., an individual may normally experience lucid dreams frequently, but has not experienced them as frequently during the last queried interval of time. If using this approach, it is therefore advisable to also collect additional estimates of frequency, including the most lucid dream episodes experienced in any 6-month period (e.g., LaBerge et al., 2018b ).

A limitation of the above methods is that they do not measure variation in the length or degree of lucid dreams. Indeed, lucid dreams can range from a mere fleeting thought about the fact that one is dreaming followed by an immediate loss of lucidity or awakening, to extended lucid dreams in which an individual is able to engage in sequences of actions (e.g., LaBerge and Rheingold, 1990 ). Distinguishing between these different “levels” or subtypes of lucid dreams will likely be valuable to understanding observed differences (or lack of differences) in brain structural or functional measures associated with lucid dream frequency. Along these lines, several recent questionnaires have taken first steps to measure individual differences in specific characteristics of lucid dreaming. For example, the Lucid Dreaming Skills Questionnaire (LUSK) measures participants’ frequency of several different but inter-related aspects of awareness and control in lucid dreams ( Schredl, Rieger and Göritz, 2018 ). Another questionnaire, the Frequency and Intensity Lucid Dreaming Questionnaire (FILD) queries participants regarding the duration of their lucid dreams and various aspects of dream control, as well as the frequency with which they deliberately attempt to induce lucid dreams ( Aviram and Soffer-Dudek, 2018 ). In addition to providing data for individual differences studies, such questionnaires could also potentially be useful in selecting participants for sleep laboratory experiments of lucid dreaming, for example by selecting participants who report high levels of dream control in addition to frequent lucid dreams (in order to select participants who are more likely to be able to effectively make the eye signals or engage in experimental tasks during lucid dreams).

For all the above methods, important steps need to be taken to minimize measurement error, particularly to ensure that participants have a clear understanding of the meaning of lucid dreaming ( Snyder and Gackenbach, 1988 ). These include providing participants with a written definition of lucid dreaming, asking participants to provide written examples of their own lucid dreams to ensure clear understanding, as well as additional vetting through participant interviews ( Baird et al., 2018a ). Ultimately, however, basing the measurement of individual differences in lucid dreaming solely on self-report is not optimal. One way to further validate participant questionnaire responses would be to attempt to physiologically validate at least one lucid dream in the sleep laboratory for each participant. While additional validations such as this could potentially be valuable to incorporate in future studies, it is important to note that the estimated frequency of lucid dreaming would still depend on questionnaire assessment. Thus, approaches such as this do not obviate the reliance on questionnaire assessment.

An intriguing, though ambitious, method for deriving a measure of lucid dream frequency not dependent on questionnaire assessment would be to utilize home-based EEG recording systems to collect longitudinal sleep polysomnography data, from which estimates of lucid dreaming frequency could be derived from the frequency of signal-verified lucid dreams collected over many nights. However, this approach would only measure the frequency of signal-verified lucid dreams, and instances in which participants achieved lucidity but did not make the eye signal due to factors such as awakening, forgetting the intention, or lack of dream control would be missed by this procedure. There are many more points that could be addressed on the topic of questionnaire assessment of lucid dreaming frequency, but an extended analysis of this issue is beyond the scope of the present review.

9.6. General discussion of the measurement of lucid dreaming in cognitive neuroscience

In summary, cognitive neuroscience studies of lucid dreaming have at their disposal a unique set of rigorous methodological tools, including in particular the eye movement signaling method, which allows for the objective validation of lucid dreaming as well as precise time-stamping of physiological data. However, refinement of the instructions given to participants, as described above, could help further increase the reliability of the technique. Accurate phenomenological assessment of lucidity has been more mixed. In sleep laboratory studies using the eye signaling method, phenomenological reports are important but less critical due to the presence of an objective marker of lucidity. In contrast, in studies without eye signaling, accurate phenomenological assessment of whether an individual was lucid becomes essential, and inadequate or ambiguous measurement of lucidity can undermine the interpretability of the results. Questionnaire measures such as the DLQ ( Stumbrys et al., 2013b ) or LuCiD scale ( Voss et al., 2013 ) by themselves do not provide an unambiguous assessment of whether an individual had a lucid dream. Cognitive neuroscience research on lucid dreaming would greatly benefit from the further development of improved questionnaire measures for the validation of lucidity and the cognitive and experiential changes that accompany it, as well as further development of standardized measures for quantifying both the frequency and degree of lucidity. Overall, this brief discussion highlights the need for a set of standard operating procedures for both the phenomenological and objective sleep laboratory assessment of lucid dreaming.

10. Conclusion

Despite having been physiologically validated for approximately four decades, the neurobiology of lucid dreaming is still incompletely characterized. Most studies conducted to date have relied on small sample sizes, which limits the generalizability of the findings. Not surprisingly, the results of such underpowered studies are not consistent: almost every EEG study reports changes in spectral power in a different frequency band or brain area. Neuroimaging data on lucid dreaming is even sparser. Currently, there is only one fMRI study contrasting lucid and non-lucid REM sleep and it is a case study. Nevertheless, the results of this study converge with MRI studies that have evaluated individual differences in lucid dreaming frequency. Together, this preliminary evidence suggests that regions of anterior prefrontal, parietal and temporal cortex are involved in lucid dreaming. The involvement of these brain regions in metacognitive processes during the waking state is also in line with these findings.

A primary goal is to develop reliable strategies for making lucid dreaming more accessible. As reviewed above, several studies have explored methods for non-invasive electrical stimulation of the brain as well as pharmacological approaches to lucid dream induction. Electrical stimulation of prefrontal brain areas has resulted in statistically significant but weak increases of dream “insight” ratings, but so far it has not resulted in significant increases in the frequency of lucid dreams. Currently it remains too early to tell how effective (if at all) electrical stimulation of the frontal cortex, or other brain areas, could be for lucid dream induction. Pharmacological induction with agents acting on the cholinergic system, in particular the AChEI galantamine, has shown promising results; however, these findings need to be replicated systematically, and lucid dreams objectively confirmed with polysomnography. Other approaches to lucid dream induction not discussed in the current review, and that do not directly target neural mechanisms, such as cognitive/psychological approaches, also appear promising ( Stumbrys et al., 2012 ). For example, advances in the research of targeted memory reactivation via olfactory or acoustic stimuli during sleep (e.g., Oudiette, Antony, Creery and Paller, 2013 ) might lead to new strategies for lucid dream induction, together with continued research on stimulating lucid dreams with visual or auditory cues ( LaBerge and Levitan, 1995 ; LaBerge et al., 1988 ; LaBerge et al., 1981b ).

In conclusion, additional studies with larger sample sizes, for example large-scale group-level high-density EEG, MEG, and concurrent EEG/fMRI studies, will be important next steps toward characterizing the neural functional changes associated with lucid dreaming. For now, a more detailed understanding of the neurobiological basis of lucid dreaming remains an open question for ongoing research. Lucid dreaming shows promise as a useful methodology for psychophysiological studies of REM sleep, with potential applications in both clinical and basic research domains. Perhaps the largest potential of research on lucid dreaming is that it provides a unique method to investigate the neurobiology of consciousness, which remains one of the largest lacunas in scientific knowledge.

• EEG studies of lucid dreaming are mostly underpowered and show mixed results
• Preliminary neuroimaging data implicates frontoparietal cortices in lucid dreaming
• Cholinergic stimulation with mental set shows promise for inducing lucid dreams
• We present best-practice procedures to investigate lucid dreaming in the laboratory

Acknowledgements

We thank Stephen LaBerge for helpful discussion.

BB was supported by the National Institutes of Health (NIH) under Ruth L. Kirschstein National Research Service Award F32NS089348 from the NINDS. SAM-R was supported by the Coordena9ao de Aperfei9oamento de Pessoal de Nivel Superior (CAPES), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Financiadora de Estudos e Projetos do Ministério da Ciência e Tecnologia (FINEP), and Fundação de Apoio à Pesquisa do Estado do Rio Grande do Norte (FAPERN). MD was supported by the Netherlands Organisation for Scientific Research (NWO) through a Vidi fellowship (016.Vidi.185.142). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH, CAPES, CNPq, FINEP, FAPERN or NWO.

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Competing interests

The authors declare no competing interests.

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Discrimination Experiences Shape Most Asian Americans’ Lives

1. asian americans’ experiences with discrimination in their daily lives, table of contents.

• Key findings from the survey
• Most Asian Americans have been treated as foreigners in some way, no matter where they were born
• Most Asian Americans have been subjected to ‘model minority’ stereotypes, but many haven’t heard of the term
• Experiences with other daily and race-based discrimination incidents
• In their own words: Key findings from qualitative research on Asian Americans and discrimination experiences
• Discrimination in interpersonal encounters with strangers
• Racial discrimination at security checkpoints
• Encounters with police because of race or ethnicity
• Racial discrimination in the workplace
• Quality of service in restaurants and stores
• Discrimination in neighborhoods
• Experiences with name mispronunciation
• Discrimination experiences of being treated as foreigners
• In their own words: How Asian Americans would react if their friend was told to ‘go back to their home country’
• Awareness of the term ‘model minority’
• Views of the term ‘model minority’
• How knowledge of Asian American history impacts awareness and views of the ‘model minority’ label
• Most Asian Americans have experienced ‘model minority’ stereotypes
• In their own words: Asian Americans’ experiences with the ‘model minority’ stereotype
• Asian adults who personally know an Asian person who has been threatened or attacked since COVID-19
• In their own words: Asian Americans’ experiences with discrimination during the COVID-19 pandemic
• Experiences with talking about racial discrimination while growing up
• Is enough attention being paid to anti-Asian racism in the U.S.?
• Acknowledgments
• Sample design
• Data collection
• Weighting and variance estimation
• Methodology: 2021 focus groups of Asian Americans
• Appendix: Supplemental tables

Most Asian Americans experience discrimination in many parts of their day-to-day lives. In the survey, we asked Asian American adults if they have ever experienced discrimination or been treated unfairly because of their race or ethnicity.

In addition to this broad question, we also asked whether they have experienced specific discrimination incidents in their everyday life. These include incidents in interpersonal encounters with strangers; at security checkpoints; with the police; in the workplace; at restaurants or stores; and in their neighborhoods.

About six-in-ten Asian adults (58%) say they have ever experienced racial discrimination or been treated unfairly because of their race or ethnicity. This includes 53% of Asian adults who say they have experienced racial discrimination from time to time and 5% who say they experience it regularly.

Whether Asian adults say they have experienced racial discrimination varies across some demographic groups:

• Ethnic origin: 67% of Korean adults say they have experienced racial discrimination, higher than the shares among Vietnamese (57%), Filipino (55%) and Indian (50%) adults.
• Nativity: U.S.-born Asian adults are more likely than immigrants to say they have experienced racial discrimination, 65% versus 55%.
• Immigrant generation: 69% of Asian immigrants who are 1.5 generation – those who came to the U.S before they were 18 years old – say they have ever experienced racial discrimination. About half of immigrants who traveled to the U.S. as adults (first generation) say the same.
• Years in U.S.: 45% of immigrants who arrived in the U.S. in the last decade say they have experienced racial discrimination, compared with 60% of those who have been in the U.S. for more than 20 years. 12

In the survey, we asked Asian adults whether they have experienced discrimination incidents in their daily interpersonal encounters with strangers.

• 37% of Asian adults say strangers have called them offensive names.
• 18% say strangers have acted as if they thought they were dishonest.
• 12% say people have acted as if they were afraid of them.

Experiences with offensive name-calling

About 37% of Asian adults say that in day-to-day encounters in the U.S., strangers have called them offensive names. Whether Asian adults say they have had this experience is associated with their experiences with immigration:  

• 57% of U.S.-born Asian adults say strangers have called them offensive names. They are nearly twice as likely as Asian immigrants (30%) to say this.  
• Among immigrants, 54% of Asian adults who immigrated as children (1.5 generation) say they have been called offensive names by strangers, while 20% of those who immigrated as adults (first generation) say the same.
• 39% of immigrants who have been in the U.S. for more than two decades say they have been called offensive names. By contrast, 16% of those who immigrated 10 years ago or less say the same.

Responses also vary across other demographic groups:

• Ethnic origin: 26% of Indian adults say strangers have called them offensive names, a lower share than other origin groups.
• Regional origin: This pattern is also echoed among regional origin groups. Among South Asian adults overall, 29% say they have been called offensive names, compared with higher shares of East (41%) and Southeast (39%) Asian adults.
• Age: About four-in-ten Asian adults under 50 years old say they have been called offensive names, compared with 33% of those 50 to 64 and 25% of those 65 and older.
• Race: 50% of Asian adults who identify with two or more races – that is, those who identify as Asian in addition to at least one other race – say they have been called offensive names by strangers during day-to-day encounters. In comparison, 36% of those who are single race – those who identify as Asian and no other race – say the same.

In the survey, we also asked Asian Americans whether they have ever hidden part of their heritage – including cultural customs, food, clothing or religious practices – from non-Asians. Whether Asian Americans have hidden their culture is associated with their experiences of being called offensive names:

• 60% of Asian adults who have hidden their heritage say they have also been called offensive names by strangers, compared with 32% of those who have not hidden part of their heritage.

In their own words: Asian Americans’ experiences of being called slurs and offensive names

A note to readers.

This section contains racial slurs and other terms that may be offensive to readers. Quotations have been lightly edited for grammar, spelling and clarity, but we have chosen not to censor language out of respect to those who agreed to share their personal experiences.

In the 2021 focus groups of Asian Americans, many participants talked about their experiences being bullied , harassed or called offensive names because of their race or ethnicity:

“As an Indian female, we tend to be very hairy … starting very young, so in sixth and seventh grade I was super hairy and so all the other girls would be like, ‘Oh my god, are you like shaving already? Or what’s going on with that?’ And then people would call me, ‘Sand N-word.’ A lot of just like, ‘Saddam’s daughter,’ just like those types of words.”

–U.S.-born woman of Indian origin in late 30s

“The first time that I can ever remember experiencing racism and discrimination was when I was 3. I was on the playground … and I was playing with this White girl and then her mom came … [and] was just like, ‘Don’t play with that chink,’ and I didn’t know how to take that at the time. I didn’t think anything of it because I didn’t know what it was and then, you know, it was put in my memory for the next god knows how many years and it wasn’t until I heard that word again, ironically watching [the 2000 film] ‘The Debut’ [with Dante Basco] … and I remember they called him ‘chink’ in there and I was like – it just unlocked a memory and that’s when I really started to … understand race and prejudice and discrimination.”

–U.S.-born woman of Filipino origin in late 20s

“I remember that I first came [to my neighborhood], there were not too many Chinese [people there]. [Kids] would shout behind my back: ‘Japs, Japs.’ They were about 8, 10 years old.”

–Immigrant man of Taiwanese origin in mid-70s (translated from Mandarin)

“We just have to deal with it more than the average person. I’ve been called DJ Isis, I’ve been called terrorist. … [O]n a day-to-day basis I feel welcome [in America]. This is my country. I’m here to live; I’m here to stay. But there are just those one or two instances that just make you feel like maybe it would have been better if I was somewhere else or maybe it would have been different if I was White or whatever. I feel like the only person that’s going to be 100% fully welcome is a White male and that’s the only person that’s going to be 100% welcome 100% of the time.”

–U.S.-born man of Indian descent in late 20s

“I had my assigned parking lot, and when a White man parked his car on my spot, I told him to move his car, he said ‘Ching Chang Chong’ to me and called the guard.”

–Immigrant man of Korean descent in late 40s (translated from Korean)

“When I was in college, I had a White girlfriend and … [her family was] very kind to me … but one time, we got invited to a party at her aunt and uncle’s house and … [her mom] says to me, ‘Can you help bring this food into the house?’ so … I picked up some trays of food, walked them into the house, and her aunt comes to the door and says to me, ‘No. Bring it around the back,’ … and then I could hear her in earshot say to the girlfriend’s mother, ‘Oh, these fucking spic caterers. What’s wrong with them? Don’t they know that the service entrance is in the rear?’ … I heard her mother correct her on the spot, but … that’s just one example of many, that much racism I’ve had when I’ve interracially dated. … I just shut my mouth. I didn’t retaliate. I didn’t want to make trouble but … I regret not having spoken up for myself.”

–U.S.-born man of Filipino descent in early 40s

Experiences with people treating them like they are dishonest or afraid of them

About a quarter of Asian adults (23%) say they have had at least one encounter in which a stranger acted like they were dishonest or afraid of them. This includes 18% who say strangers have acted as if they were dishonest and 12% who say people have acted as if they were afraid of them.

There are differences across some Asian origin groups:

• Ethnic origin: 37% of those who collectively belong to less populous Asian origin groups (those categorized as some “other” origin in this report) say they have had at least one of these experiences. This is higher than the shares among the six largest Asian origin groups.
• Regional origin: 26% each of South and Southeast Asian adults say strangers have treated them at least one of these ways, compared with 18% of East Asian adults.

Among Asian adults overall, 20% say they have been held back at a security checkpoint for a secondary screening because of their race or ethnicity.

Across regional origin groups, South Asian adults are the most likely to have this experience, with 35% saying so. This is about twice the shares among Southeast (15%) and East (14%) Asian adults who say the same.

Among South Asian adults, those born in the U.S. are more likely than immigrants to say they have had this experience. 13

There are also key findings by religion among Asian Americans:

• Asian American Muslims are more likely than some other religious groups – including Asian Hindus, those who are religiously unaffiliated, Christians and Buddhists – to say that they have been stopped at a security checkpoint for a secondary screening because of their race or ethnicity.
• About a quarter of Asian Hindus also say they have had this experience.

Notably, South Asian adults make up a higher share of Asian Muslims and Hindus in the U.S. than other regional Asian origin groups.

In their own words: Asian Americans’ experiences with racial profiling at airports and other post-9/11 discrimination experiences

Some participants of South Asian origin in our 2021 focus groups of Asian Americans talked about facing discriminatory backlash after the events of Sept. 11, 2001.

Some participants talked about their experiences with being racially profiled by airport security:

“[Once, when I was flying back to the U.S., airport security] pulled me away from my family for three hours because I had a beard. … They didn’t believe my passport was real, [they thought] that I was trying to sneak in, and they pulled me away, no context of where they were taking me or anything and my mom was freaking out the whole time, and they interrogated me asking me a bunch of different questions … I was 17 at the time. … This happens every time I fly now, so I tell my friends to be two hours late to pick me up from an airport. I mean, this is not a joke. This is every time I travel. Every time, they do this to me.”

–U.S.-born man of Pakistani origin in early 30s

“My brother-in-law’s son was stopped because his beard had grown and they felt that he may be from some terrorist group. Hence, he was stopped for two hours and cross-questioned. When he came back home, his mother, my sister-in-law, told him to shave his beard and moustache clean as he looked exactly like ‘them.’”

–Immigrant woman of Indian origin in early 50s (translated from Hindi)

“[My family was] going to Pakistan and it was like a week after 9/11 for a wedding and … TSA or someone in a uniform looked at me like he wanted me to die. … That was one [memory] that really stood out and then the other was my schoolteacher. She was like, ‘It’s just not fair that we’re being punished for something that your people did,’ or something. … I was in first grade.”

–U.S.-born woman of Pakistani origin in mid-20s

Other participants talked about other physical attacks or ways they and their family had to change their behavior:

“When a friend of mine and I were on the way to work during the week the 9/11 incident had taken place, we were assaulted with eggs. … But other local people helped us, they chased after the car that attacked us with eggs. So, incidents like that have taken place.”

–Immigrant man of Sri Lankan origin in late 40s (translated from Sinhalese)

“After 9/11, things changed a lot. I feel like things changed for a lot of us and I remember my parents putting out American flags everywhere – outside the house, on the mailbox, like wherever they could stick them. And even now, I do get … constantly pulled over when you’re in line at the airport, by TSA and at this point I just know I’m going to get pulled over. … I make my way leisurely to that section because I know that they’re going to profile me.”

–U.S.-born woman of Indian origin in early 30s

“[W]hen I was a kid … one of my neighbors ran their car into our house. It was just the weirdest thing ever because … their garage is aligned to the side of our house and then they crashed the side of our house and then we asked them, ‘How did this happen?’ You don’t just run into someone’s house, especially when there’s grass and like a fence in the way. They’re like, ‘Oh yeah. It’s my son. We’re just teaching him to drive. He did it by accident.’ … [T]o this day, we knew it was like more racially motivated just because we’re the only Pakistani family in the neighborhood, but they deemed it an accident.”

–U.S.-born man of Pakistani origin in early 20s

Backlash against Muslims, Sikhs, Arabs and South Asians post-9/11

Following the Sept. 11 attacks, discrimination against Muslims, Sikhs, Arabs, South Asians and others perceived to be part of these groups in the U.S. increased. Amid concern about national security among government officials and the general public alike, there were significant changes in immigration law and policy , including the formation the Department of Homeland Security, the creation of the National Security Entry-Exit Registration System and the passage of the USA/PATRIOT Act , among others. 

Muslim Americans faced increased scrutiny and surveillance . Other religious and ethnic groups also became targets of discrimination incidents and hate crimes, including the 2012 mass shooting at a Sikh temple in Oak Creek, Wisconsin .

Anti-Muslim sentiment and scrutiny has continued in recent years and continues to touch the lives of Muslims, Sikhs, Arabs and South Asians living in the U.S. Previous Pew Research Center surveys have found that from 2007 to 2017, increasing shares of Muslim Americans said they have personally experienced discrimination. And among the American public, people held more negative views of Muslims and Islam after the Sept. 11 attacks.

About one-in-ten Asian adults (11%) say they have been stopped, searched or questioned by the police because of their race or ethnicity. 14

Whether Asian Americans say they have had this experience varies somewhat across demographic groups:

• Ethnic origin: 17% of Asian adults who belong to less populous origin groups say they have had an encounter with the police because of their race or ethnicity. This is higher than the shares among Korean (8%), Vietnamese (7%), Chinese (7%) and Japanese (7%) adults who say the same.  
• Regional origin: 14% of South and 13% of Southeast Asian adults say they have had this experience, while about half that share of East Asian adults (7%) say the same.
• Income: 17% of Asian adults who have a family income under $30,000 say they have been stopped, searched or questioned by the police because of their race or ethnicity, compared with about one-in-ten adults with higher incomes.
• Race: 18% of Asian adults who identify with two or more races say they have had this experience, compared with 10% of Asian adults who are single race.

There are also some findings based on how others perceive Asian Americans’ racial or ethnic identity:

• About one-in-ten Asian adults who are perceived as Chinese or Asian say they have been stopped, searched or questioned by the police because of their race or ethnicity.
• A somewhat larger share of Asian adults who are perceived as some other non-White and non-Asian race or ethnicity say the same.

About one-in-five Asian adults (22%) say they have experienced at least one of three forms of workplace discrimination because of their race or ethnicity: 15

• 15% of Asian Americans say they have been turned down for a job.
• 14% say they have been denied a promotion.
• 5% say they have been fired from a job.

Asian Americans’ experiences with race-based workplace discrimination vary across some demographic groups:

• Ethnic origin: Japanese adults are the least likely to say they have experienced at least one of these three incidents of racial discrimination in the workplace. Compared with other origin groups, they are less likely to say they have been turned down for a job (5%) or denied a promotion (4%).
• Immigrant generation: Among those born in the U.S., 27% of third- or higher-generation Asian Americans say they have experienced at least one of three incidents of workplace discrimination, while 17% among the second generation say the same. About 13% of those in third or higher generations say they have been fired from a job because of their race or ethnicity, compared with 5% of second-generation Asian adults who say the same.
• Gender: Asian men are slightly more likely than Asian women to say they have been denied a promotion because of their race or ethnicity (16% vs. 11%). On the other two measures, nearly identical shares of men and women say they have had the experience.

Qualitative research findings related to Asian immigrants’ challenges with language and culture in the workplace

In a December 2022 Pew Research Center report , we explored Asian immigrants’ experiences with navigating language barriers in the United States. The following findings are related to some of the survey findings on Asian immigrants’ experiences of discrimination in the workplace:

• Many participants pointed to their difficulties speaking in English as a major reason they struggled to find employment. For example, many discussed struggling in interviews or feeling like they did not receive callbacks due to their language ability.
• Some participants shared that once employed, language barriers slowed their professional success and advancement.
• Participants also noted that their accents when speaking English affected how they were treated at work, including having their co-workers or customers treat them differently or missing out on opportunities.

Four-in-ten Asian adults say they have received poorer service than other people at restaurants or stores. This varies somewhat across demographic groups:

• Ethnic origin: 48% of those who belong to less populous origin groups say they have had this experience, compared with smaller shares of Chinese (37%) and Vietnamese (31%) adults.
• Nativity: 48% of U.S.-born adults say they have received poorer service, while 37% of immigrants say the same.
• Immigrant generation: 49% of Asian adults who are the children of immigrant parents (second generation) and 46% of Asian adults who immigrated as children (1.5 generation) say they have received poorer service at restaurants or stores. Among third- or higher-generation Asian Americans, 42% have had this experience, as have 34% of the first generation.
• Language: 46% of Asian adults who primarily speak English say they have had this experience, compared with 39% those who are bilingual and 26% of those who primarily speak their Asian origin language.
• Party: 45% of Asian adults who identify with or lean toward the Democratic Party say they have received poorer service, higher than the share among Republicans and Republican leaners (32%).
• Education: More than four-in-ten Asian adults with a bachelor’s degree or higher say this has happened to them, compared with roughly one-third of those with some college experience or less.

About one-in-ten Asian adults (12%) say neighbors have made life difficult for them or their family because of their race or ethnicity. And 4% say they have been prevented from moving into a neighborhood by a landlord or realtor for the same reason. 16

Asian Americans’ experiences of housing and social discrimination in neighborhoods differs across some demographic factors:

• Nativity: 16% of U.S.-born Asian adults say neighbors have made life difficult for them or their family, compared with 10% of Asian immigrants.
• Immigrant generation: Third-generation Asian Americans (9%) are more likely than the second generation and all Asian immigrants to say they have been prevented from moving into a neighborhood by a landlord or realtor because of their race or ethnicity.
• Income: 9% of Asian adults with family incomes of less than $30,000 say they have been prevented from moving into a neighborhood by a landlord or realtor due to their race or ethnicity, compared with about 5% or fewer among those who make $30,000 or more.
• Other research suggests that place of birth, age at immigration and length of time in the U.S. are linked to perceptions of discrimination. Previous studies have found that those born in the U.S. report experiencing discrimination at higher levels than those who are foreign born; and that those who immigrated at a younger age and have lived in the U.S. for longer periods perceive discrimination at higher levels. For more, refer to Brondolo, E., R. Rahim, S. Grimaldi, A. Ashraf, N. Bui and J. Schwartz, 2015, “ Place of Birth Effects on Self-Reported Discrimination: Variations by Type of Discrimination, ” International Journal of Intercultural Relations; and Wong, J. and K. Ramakrishnan, 2021, “ Anti-Asian Hate Incidents and the Broader Landscape of Racial Bias, ” AAPI Data . ↩
• For more information on the shares of South Asian adults who have been held back at a security checkpoint for a secondary screening because of their race or ethnicity by demographic groups (including by ethnic origin, nativity, age, gender and party), refer to the Appendix . ↩
• A 2019 Pew Research Center survey asked U.S. adults across racial and ethnic groups a slightly different question about their experiences with the police because of their race or ethnicity. Across major racial and ethnic groups, Black adults were the most likely to say they have been unfairly stopped by the police because of their race or ethnicity. White adults were the least likely to say they have had this experience. ↩
• A 2019 Pew Research Center survey asked U.S. adults across racial and ethnic groups a different, but related, question about their experiences with workplace discrimination because of their race or ethnicity. Across major racial and ethnic groups, Black adults were the most likely to say they have been treated unfairly by an employer in hiring, pay or promotion because of their race or ethnicity. White adults were the least likely to say they have had this experience. ↩
• There is a long history of banning Asians from land ownership in the United States. Alien land laws emerged in some states in 1913. Most laws were repealed in the 1950s, though the last law was not repealed until 2018 in Florida. There has been recent legislation aiming to revive these laws in some states in 2023. ↩

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Methodology: 2023 focus groups of asian americans, 1 in 10: redefining the asian american dream (short film), the hardships and dreams of asian americans living in poverty, key facts about asian american eligible voters in 2024, most popular, report materials.

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