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Researching Dreams

The Fundamentals

• © 2018
• Michael Schredl 0

Central Institute of Mental Health, Mannheim, Germany

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Delves into the intricacies of the history and future of dream research

Describes how content analysis can be objectively utilized in dream research

Taps into a growing interest in dreams and their meaning in our everyday life

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Table of contents (9 chapters)

Front matter, definitions.

Michael Schredl

Dream Recall

• Dream Content Analysis

Dream Behavior and Dream Content in Healthy Persons

Dream content and physiology, dreams and mental disorders, lucid dreaming, functions of dreaming, back matter.

• Mental Health
• Content Analysis
• Cognitive Neuroscience
• Sleep Disorders
• Clinical Psychology
• Cognitive Psychology
• Biological Psychology
• Sleep Stage Analysis
• Psychotherapy

About this book

What can be gleaned from the study of our dreams? With research methods in mind—including the shortcomings and strengths of various strategies—the book presents a comprehensive introduction to the research obtained so far. Topics include the factors of dream recall; the continuity hypothesis of dreaming; the relationship between physiology and dream content; etiology and therapy of nightmares; and lucid dreaming. The book not only presents a comprehensive introduction to the research obtained so far but also provide the tools to carry our scientific dream studies—including the shortcomings and strengths of various approaches.

Authors and Affiliations

About the author.

Michael Schredl, Ph.D., is Researcher at the Central Institute of Mental Health, Mannheim, Germany. He is editor of the journal International Journal of Dream Research.

Bibliographic Information

Book Title : Researching Dreams

Book Subtitle : The Fundamentals

Authors : Michael Schredl

DOI : https://doi.org/10.1007/978-3-319-95453-0

Publisher : Palgrave Macmillan Cham

eBook Packages : Behavioral Science and Psychology , Behavioral Science and Psychology (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s) 2018

Hardcover ISBN : 978-3-319-95452-3 Published: 20 August 2018

Softcover ISBN : 978-3-030-07040-3 Published: 25 January 2019

eBook ISBN : 978-3-319-95453-0 Published: 08 August 2018

Edition Number : 1

Number of Pages : XII, 225

Number of Illustrations : 1 b/w illustrations

Topics : Psychology, general

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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

School of Medicine, Johns Hopkins University, Baltimore, MD, USA

Mallika S. Sarma

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Valchy Miegakanda

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Lee T. Gettler

Department of Anthropology, University of Nevada, Las Vegas, USA

Alyssa N. Crittenden

Department of Psychiatry, Center for Sleep Medicine, University Hospitals of Geneva, Geneva, Switzerland

Lampros Perogamvros

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Contributions

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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Received : 26 June 2023

Accepted : 22 September 2023

Published : 02 October 2023

DOI : https://doi.org/10.1038/s41598-023-43319-z

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Frontiers for Young Minds

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The Science of Dreams

Dreams are a common experience. Some are scary, some are funny. Recent research into how the brain works helps us understand why we dream. Strange combinations of ideas in our dreams may make us more creative and give us ideas that help us to solve problems. Or, when memories from the day are repeated in the brain during sleep, memories may get stronger. Dreams may also improve our moods. Together, these studies show that dreams and sleep are important for performing well when we are awake.

When she was 8, my daughter told me about one of her dreams. She was in a spaceship with some animals. Although she knew she was in a spaceship in her dream, when telling me about the dream, she realized the spaceship was actually a washing machine. At times, she and the animals would be out in space, but they also came back to earth. She told me the dream with a laugh and then moved on with her day, ignoring the crazy animals and spaceships that entertained her in her sleep.

Since we remember our dreams and then often forget them, what is their purpose? Why do we dream about the things we do? New research tools, particularly those that can be used to investigate the brain, are being used to answer these questions.

What Are Dreams?

Although it is hard to define what a dream is, for the purpose of this article, we will define dreams as our thoughts during sleep that we recall when we wake up. So, sleeping dreams are not the same as “daydreaming.” Dreams are mostly visual (made up of scenes and faces; sound, taste, and smell are rare in dreams [ 1 ]). Dreams can range from truly strange to rather boring, snapshots from a recent event.

To study dreams, scientists need a measure of dreaming. Most studies use dream reports (a person writes out her dreams when she wakes up) or questionnaires (a person answers questions like “How many dreams have you recalled in the past month?” [ 2 ]). Dreams are more likely to be recalled when a person is woken up from REM sleep. REM sleep is a type of sleep that is named for the rapid eye movements that can be measured during this stage of sleep. We do not dream as much in non-REM sleep, the sleep stages that make up the rest of the night, and dream reports from non-REM sleep are often less strange.

Dream frequency (how often dreams happen) and content (what dreams are about) is very different for everyone, and there are many reasons why this may be true. For example, you will remember dreams more if you are woken up by someone or by an alarm clock. This might be because you can still recall that dream memory while it is fresh but, if you wake up on your own, you will transition through a few sleep stages and possibly lose that dream memory. Dream recall changes with age, too. Older people are less likely to report dreaming. This could also be related to memory: since older people have weaker memories, it could be that they dream but cannot remember their dreams by the time they wake up. A brain area called the medial prefrontal cortex is also related to dream recall. If this brain area is damaged, the person recalls few dreams, which may mean the person dreams less (or not at all). Also, how tightly packed the brain cells are in the medial prefrontal cortex can vary from person to person, which may cause some healthy people to dream more or less than other healthy people. There are also genes that affect how much REM sleep people get. People with less REM sleep may not have the strange dreams that tend to come in REM. So, how long you sleep, your age, and your genetics may all explain why you dream more or less than someone else.

Do dreams actually happen while we sleep, or are they ideas that come to us when we wake up and we just “feel” like it happened during sleep? A recent study using a type of brain imaging called magnetic resonance imaging or (MRI: Read more in the Young Minds article “How Is Magnetic Resonance Imaging Used to Learn About the Brain?” [ 3 ]) helped answer this question ( Figure 1A ). The scientists made maps of the brain activity that occurred when people looked at pictures of things—keys, beds, airplanes. Later, the people in the study slept in the MRI machine. The scientists matched the pattern of brain activity from the people as they slept to brain activity patterns for the pictures they viewed earlier, and then chose the best match ( Figures 1B,C ). This match predicted what the person said they dreamed about 60% of the time. Although 60% is not perfect, it is better than guessing! [ 4 ]. This means that dreams are created in the brain during sleep.

• Figure 1 - (A) Magnetic resonance imaging (MRI) is a way to investigate the brain.
• The person lies on a bed inside a giant magnet. (B) MRI can measure the structure of the brain and the areas of the brain that are active. (C) MRI was used to measure dreaming. First, while the participant was awake, they viewed thousands of pictures in the MRI. This told scientists the specific brain responses to specific pictures. Later, when the participant slept in the MRI, scientists measured the brain activity patterns and matched this to the brain responses to the pictures the participant saw when they were awake. Scientists guessed that the best match would tell them what the participant was dreaming about. By asking the participant about their dreams in the MRI, scientists found that the dreams did tend to match the pictures predicted by the brain activity.

Dreams Support Memories

What is the purpose of our dreams? Researchers have found that sleep is important for memory (see this Frontiers for Young Minds article ; “Thanks for the Memories…” [ 5 ]). Memories move from temporary storage in the hippocampus , a brain structure that is very important for short-term memory, to permanent storage in other parts of the brain. This makes the memories easier to remember later. Memories improve with sleep because the memories are replayed during sleep [ 6 ]. If you want to learn all the words to your favorite scene in a movie, you might re-watch that scene over and over again. The brain works the same way: neurons (brain cells) that are active with learning are active again and replay the learned material during sleep. This helps store the memory more permanently.

Memory replay may show up in our dreams. Dreams in non-REM sleep, when most memory replay happens, often contain normal people and objects from recent events. However, sleep switches between non-REM and REM sleep (see Figure 2 ). So, bizarre dreams in REM sleep may come from a combination of many different recent memories, which were replayed in non-REM sleep, and get jumbled up during REM sleep. If dreams help with memory processing, does that mean your memories are not being processed if you do not dream? No. Memories are moving to storage even if we do not dream.

• Figure 2 - There are four types of sleep—REM sleep (purple) and three stages of non-REM sleep (blue).
• REM stands for rapid eye movements, which happen during this stage of sleep. During REM sleep, muscle and brain activity also differ from other sleep stages. Characteristics of dreams tend to be different for each of these sleep stages.

Dreams Improve Creativity and Problem Solving

My daughter’s dream of a spaceship made a great story that she recited to me, and later, to her classmates. The images were intense and interesting, inspiring her to draw scenes in a notebook and write about the dream for school. This is an example of how dreams can help make us more creative. Mary Shelley, the author of the book Frankenstein, got the idea for her book from a dream. Even scientists get ideas from dreams [ 7 ].

To measure creative problem solving, scientists used a remote associates task, in which three unrelated words are shown, and the person is to come up with a word they have in common. For instance, HEART, SIXTEEN, and COOKIES seem unrelated until you realize they all are related to SWEET (sweetheart, sweet sixteen, and cookies are sweet) ( Figure 3 ). The scientists wanted to see whether sleep helped people do better on this task. They found that people were better at thinking of the remote solution if they had a nap, particularly a nap with REM sleep. Given that REM is when most bizarre dreaming occurs, this supports the idea that these dreams might help us find creative solutions to problems [ 8 ].

• Figure 3 - REM sleep helps people find creative solutions.
• In the morning, participants did two tasks to test creativity and problem solving (A) . They did one task again in the afternoon. In between, they either stayed awake (“wake” group) or took a nap. Those that took naps either did not have REM sleep in their nap (“nREM” group) or had both nREM and REM sleep (“nREM + REM” group). (B) If subjects stayed awake between the morning and afternoon tests (yellow bar), they did not improve on the task. They also did not improve if they had a nap that was only nREM sleep (light blue bar). But, if they had a nap with both nREM and REM sleep, they did better in the afternoon compared with when they did the task in the morning (dark blue bar). So, REM sleep must help us find creative solutions (from Cai et al. [ 8 ]).

This study and research like it gives us reason to believe that REM dreams may help us be more creative and solve problems. Many different memories may be activated at the same time and when these memories are mixed together, the result when we wake up may be both the memory of a strange dream and a unique perspective on problems.

Dreams Regulate Our Moods and Emotions

Dreams are usually emotional. One study found that most dreams are scary, angry, or sad.

Dreams might seem to be emotional simply because we tend to remember emotional things better than non-emotional things. For example, in waking life, the day you got a puppy is more memorable than a normal school day. So, dreams about emotional events might be remembered more easily than boring, non-emotional dreams. It is also possible that dreams are emotional because one job of dreams is to help us process emotions from our day [ 9 ]. This may be why the amygdala , an area of the brain that responds to emotions when we are awake, is active during REM sleep. If you had a sad day, you are more likely to have sad dreams. But, sleep also improves mood–sleep after a disagreement or sad event will make you happier.

Dreams could also help prepare us for emotional events, through something called threat simulation theory [ 10 ]. For example, when I dreamt that my young daughter, who could not swim, fell into a swimming pool, recall of that dream convinced me to sign her up for swim lessons. By simulating this fearful situation, I could prevent it by being prepared.

These studies show us that sleep and dreams are important for our emotions. By processing emotions in sleep, we may be better prepared and in a better mood the next day.

Conclusions

There are different ways scientists measure dreams—from asking questions to using MRI. These studies show us that activity in the brain while we sleep gives us the interesting dreams we recall when we wake up. These dreams help us remember things, be more creative, and process our emotions.

We know most kids do not get enough sleep. Some diseases (like Alzheimer’s disease) also make people sleep less, while others (like REM sleep behavior disorder and mood disorders) affect dreams directly. It is important to study sleep and dreams to understand what happens when we do not get enough sleep and how we can treat people with these diseases.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Rapid Eye Movement (REM) : ↑ A stage of sleep in which the eyes move rapidly and there is no muscle activity.

Medial Prefrontal Cortex : ↑ A specific area in the front of the brain that is associated with dream recall but also has a role in memory and decision-making.

Magnetic Resonance Imaging (MRI) : ↑ A tool used to take pictures of internal body parts (including the brain). MRI can also be used to measure the activity in the brain.

Hippocampus : ↑ An area in the brain that is thought to be important for short-term memory.

Neuron : ↑ A cell in the nervous system (brain and spinal cord) that can transmit information to other cells.

Amygdala : ↑ An area of the brain involved in the experience of emotions.

Threat Simulation Theory : ↑ A theory of dreaming that says that threats (things that could be bad) are simulated or practiced in your dreams to prepare you for those situations when you are awake.

1. ↑ Zandra, A. L., Nielsen, T. A., and Donderi, D. C. 1998. Prevalence of auditory, olfactory, and gustatory experiences in home dreams. Percept. Mot. Skills 87:819–26.

2. ↑ Schredl, M. 2002. Questionnaires and diaries as research instruments in dream research: methodological issues. Dreaming 12:17–26. doi: 10.1023/A:1013890421674

3. ↑ Hoyos, P., Kim, N., and Kastner, S. 2019. How Is Magnetic Resonance Imaging Used to Learn About the Brain? Front. Young Minds . 7:86. doi: 10.3389/frym.2019.00086

4. ↑ Horikawa, T., Tamaki, M., Miyawaki, Y., and Kamitani, T. 2013. Neural decoding of visual imagery during sleep. Science 340:639–42. doi: 10.1126/science.1234330

5. ↑ Davachi, L., and Shohamy, D. 2014. Thanks for the Memories.… Front. Young Minds. 2:23. doi: 10.3389/frym.2014.00023

6. ↑ O’Neill, J., Senior, T. J., Allen, K., Huxter, J. R., and Csicsvari, J. 2008. Reactivation of experience-dependent cell assembly patterns in the hippocampus. Nat. Neurosci . 11:209–15. doi: 10.1038/nn2037

7. ↑ Barrett, D. 2001. The Committee of Sleep: How artists, scientists, and athletes use dreams for creative problem-solving–and How You Can Too . New York, NY: Crown.

8. ↑ Cai, D. J., Mednick, S. A., Harrison, E. M., Kanady, J. C., and Mednick, S. C. 2009. REM, not incubation, improves creativity by priming associative networks. Proc. Natl. Acad. Sci. U.S.A . 106:10130–4. doi: 10.1073/pnas.0900271106

9. ↑ Cremone, A., Kurdziel, L. B. F., Fraticelli, A., McDermott, J., and Spencer, R. M. C. 2017. Napping reduces emotional attention bias during early childhood. Dev. Sci . 20:e12411. doi: 10.1111/desc.12411

10. ↑ Revonsuo, A. 2000. The reinterpretation of dreams: an evolutionary hypothesis of the function of dreaming. Behav. Brain Sci . 23:877–901. doi: 10.1017/s0140525x00004015

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Experimental Research on Dreaming: State of the Art and Neuropsychoanalytic Perspectives

Perrine m. ruby.

1 INSERM U1028, Lyon Neuroscience Research Center, Brain Dynamics and Cognition Team, Lyon, France

2 CNRS UMR5292, Lyon Neuroscience Research Center, Brain Dynamics and Cognition Team, Lyon, France

3 University Lyon 1, Lyon, France

Dreaming is still a mystery of human cognition, although it has been studied experimentally for more than a century. Experimental psychology first investigated dream content and frequency. The neuroscientific approach to dreaming arose at the end of the 1950s and soon proposed a physiological substrate of dreaming: rapid eye movement sleep. Fifty years later, this hypothesis was challenged because it could not explain all of the characteristics of dream reports. Therefore, the neurophysiological correlates of dreaming are still unclear, and many questions remain unresolved. Do the representations that constitute the dream emerge randomly from the brain, or do they surface according to certain parameters? Is the organization of the dream’s representations chaotic or is it determined by rules? Does dreaming have a meaning? What is/are the function(s) of dreaming? Psychoanalysis provides hypotheses to address these questions. Until now, these hypotheses have received minimal attention in cognitive neuroscience, but the recent development of neuropsychoanalysis brings new hopes of interaction between the two fields. Considering the psychoanalytical perspective in cognitive neuroscience would provide new directions and leads for dream research and would help to achieve a comprehensive understanding of dreaming. Notably, several subjective issues at the core of the psychoanalytic approach, such as the concept of personal meaning, the concept of unconscious episodic memory and the subject’s history, are not addressed or considered in cognitive neuroscience. This paper argues that the focus on singularity and personal meaning in psychoanalysis is needed to successfully address these issues in cognitive neuroscience and to progress in the understanding of dreaming and the psyche.

The word “dream” is commonly used to express an unattainable ideal or a very deep and strong desire:

I have a dream that my four little children will one day live in a nation where they will not be judged by the color of their skin, but by the content of their character. Martin Luther King

In dream reports, however, one often notices banal situations, strange scenes, or even frightening events. Why is there such a contrast between the popular meaning of the word “dream” and the content of dream reports? Why are some dream scenes so bizarre? Are dreams built from images that arise randomly from the sleeping brain? Or is the emergence and organization of dream images controlled by currently unknown parameters? Does dreaming have a function?

Answering these questions is not easy because dreaming is elusive. We still do not know when it happens during the night, how long it lasts, whether we can recall its entire content, or how to control it. For more than a century, such limited understanding of dreaming has seriously hampered experimental investigations. Nonetheless, scientific research has managed to produce considerable information about the phenomenology and physiology of dreaming and has improved our understanding of this fascinating phenomenon.

Experimental Research on Dreaming

Dreaming and experimental psychology, dream content.

Dreaming was first investigated on an experimental level in the nineteenth century. Calkins ( 1893 ) published the first statistical results about dreaming and argued that some aspects of dream content could be quantified. Later, questionnaires and automatic analysis of the lexical content of dream reports allowed psychologists to show that dream content has some precise phenomenological characteristics. According to psychological studies (Hall and Van de Castle, 1966 ; Schwartz, 1999 ), visual imagery occurs more frequently in dreams than imagery of other senses (audition, olfaction, touch, and taste); the dream drama is mostly lived by the dreamer from a first-person perspective; some elements of real-life events previously experienced by the dreamer often contribute to the scene of the dream; most often, the dream sequence is not within the dreamer’s voluntary control (i.e., the dreamer may be convinced during the dream that the dream’s story is really happening); temporal and spatial incoherencies can occur in the dream story; the dream report is often full of people interacting with each other (e.g., discussions, fights, pursuit, sexuality); and finally, the dream report often contains strong emotions.

Substantial variability of content exists, however, among the same individual’s dreams and among the dreams of different individuals. Further, psychological studies have shown that many internal and external parameters can influence dream content. For example, males report more aggression and violence in their dreams than do females (Nielsen et al., 2003 ; Schredl et al., 2004 ). External stimulation perceived by the dreamer can be incorporated into dreams (Koulack, 1969 ; Saint-Denys, 1867; Hoelscher et al., 1981 ), as illustrated by the famous Dali painting Dream Caused by the Flight of a Bee around a Pomegranate a Second before Awakening . The current concerns of the subject may also be found in the content of his/her dreams (Schwartz, 1999 ; Domhoff and Schneider, 2008 ), and many aspects of the subject’s daily life were found to influence dream content, including news events (Bulkeley and Kahan, 2008 ), musical practice (Uga et al., 2006 ), religious beliefs (Domhoff and Schneider, 2008 ), chronic pain (Raymond et al., 2002 ), mood (Cartwright et al., 1998a ), or a violent living environment (Valli et al., 2005 ). By contrast, congenital or acquired malformations do not seem to significantly influence dream content (Voss et al., 2010 ; Saurat et al., 2011 ).

Based on these results, two opposing hypotheses were formulated: the continuity hypothesis (Schredl and Hofmann, 2003 ) and the discontinuity hypothesis (Rechtschaffen, 1978 ; Kahn et al., 1997 ; Stickgold et al., 2001 ). The former relies on results showing that the themes of an individual’s thoughts during waking life and dreaming are similar; the latter focuses on the fundamentally different structures of thoughts during waking life and dreaming. Voss et al. ( 2010 ) stressed in their recent paper that these hypotheses represent oversimplified approaches to dream analysis and argued that waking and dreaming thoughts were related but structurally independent; in other words, she argued in favor of merging the continuity and discontinuity hypotheses.

Dream report frequency

Dream report frequency (DRF) can vary within subjects and varies substantially among subjects. In a study of 900 German subjects with a large age range from various socioprofessional categories, the mean DRF was approximately 1 dream report per week (Schredl, 2008 ). This result shows that the dream experience is common and familiar to everyone. Psychological studies have demonstrated that many parameters covary with DRF and may thus influence it.

Sleep parameters

First, DRF varies according to the sleep stage preceding awakening (e.g., Dement and Kleitman, 1957b ; Nielsen, 2000 , for a review). More dream reports are obtained after an awakening during rapid eye movement (REM) sleep than after an awakening during non-REM (NREM) sleep. These results inspired the REM sleep hypothesis of dreaming (see the section Dreaming and Neuroscience). Second, DRF increases with the number of awakenings during sleep, according to retrospective self-evaluations of awakenings (Cory and Ormiston, 1975 ; Schredl et al., 2003 ). Such studies showed that the more the subjects tended to awaken during sleep, the higher their DRF. These results support the hypothesis of Koulack and Goodenough ( 1976 ), which proposes that nocturnal awakenings facilitate the encoding of the dream in memory and thus facilitate dream recall upon awakening. However, this hypothesis has not been tested by measuring awakenings with polysomnographic recordings in healthy subjects with various DRFs. Finally, DRF varies according to the method of awakening. Abrupt awakenings lead to more dream reports than gradual awakenings (Shapiro et al., 1963 , 1965 ; Goodenough et al., 1965 ).

Physiological and environmental parameters

Dream report frequency deceases with age (e.g., Schredl, 2008 ) and tends to be slightly higher among females than males (e.g., Schredl, 2008 ; Schredl and Reinhard, 2008 ). Remarkably, Schredl’s ( 2008 ) results revealed that DRF also varied according to the size of the subject’s place of residence.

Psychological parameters

First, increased professional stress or interpersonal stress resulted in an increase in DRF (for a review, see Schredl, 1999 ). Second, an interest in dreams or a positive attitude toward dreams clearly covaries with DRF (Hill et al., 1997 ; Schredl, 1999 ; Schredl et al., 2003 ). The greater an individual’s interest in dreams, the higher his/her DRF. Third, several cognitive abilities have been found to covary with DRF. Contradictory results have been reported for the correlation between DRF and memory abilities (short-term, long-term, visual, verbal, implicit, and explicit; significant positive correlation: Cory and Ormiston, 1975 ; Belicki et al., 1978 ; Butler and Watson, 1985 ; Schredl et al., 1995 ; Solms, 1997 ; no significant correlation: Cohen, 1971 ; Belicki et al., 1978 ; Schredl et al., 1995 , 1997 , 2003 ; Solms, 1997 ) and the correlation between DRF and visual imagery ( significant positive correlation : Hiscock and Cohen, 1973 ; Richardson, 1979 ; Okada et al., 2000 ; no significant correlation : Hill et al., 1997 ; Okada et al., 2000 ). However, several studies have consistently shown that DRF is positively correlated with creativity (Fitch and Armitage, 1989 ; Schredl, 1999 ; Schredl et al., 2003 ) and intelligence scales (multiple-choice vocabulary test, Schonbar, 1959 ; Shipley Intelligence Scale, Connor and Boblitt, 1970 ). Finally, many authors have reported a correlation between DRF and personality traits. Subjects with a high DRF are more likely to have a personality with thinner boundaries (Hartmann described people with thin boundaries as being open, trustworthy, vulnerable, and sensitive; Hartmann, 1989 ; Hartmann et al., 1991 ; Schredl et al., 2003 ), to be more anxious (Schonbar, 1959 ; Tart, 1962 ), to have a higher level of absorption (the absorption scale measures the capacity to become absorptively involved in imaginative and esthetic experiences; Hill et al., 1997 ; Schredl, 1999 ; Schredl et al., 2003 ), to be more open to experience (Hill et al., 1997 ; Schredl et al., 2003 ), and to be less alexithymic (alexithymia is a personality variable that incorporates difficulty identifying and describing feelings, difficulty distinguishing between feelings and the physical sensation of emotional arousal, limited imaginative processes, and an externally oriented cognitive style; De Gennaro et al., 2003 ; Nielsen et al., 2011 ) compared to subjects with a low dream recall frequency. However, those results have not always been reproducible (e.g., Schredl, 2002 for openness to experience; Cory and Ormiston, 1975 ; Hill et al., 1997 for anxiety; Nielsen et al., 1997 for alexithymia) and, according to the recent review by Blagrove and Pace-Schott ( 2010 ), it is difficult to draw conclusions about a possible link between personality traits and DRF.

In conclusion, numerous parameters have been identified that covary with DRF. Schredl stressed in many of his papers that the studied parameters usually explain only a small percentage of the total variance (e.g., Schredl, 2008 ). Thus, the DRF variation profile suggests that the production, encoding and recall of dreams are influenced by numerous parameters that probably interact with each other.

Dreaming and neuroscience

The neuroscientific approach to dreaming arose at the end of the 1950s with the discovery of REM during human sleep by the American physiologist Nathaniel Kleitman and his team (Aserinsky and Kleitman, 1953 ; Dement and Kleitman, 1957a ). During these sleep episodes with saccades, the researchers noticed a decrease in voltage and an increase in frequency in the EEG, accompanied by an increase in cardiac frequency variability and a decrease in body movements. They concluded that these physiological modifications indicate a particular sleep stage, which they called REM sleep. A few years later, the French team led by neurobiologist Michel Jouvet discovered that the lack of movement during REM sleep in cats was due to a general muscular atonia, controlled notably by the locus coeruleus α in the brainstem (Jouvet and Michel, 1959 ; Berger, 1961 later showed that muscular atonia during REM sleep also occurs in humans). Interestingly, the inability to move during REM sleep indicates deep sleep and paradoxically, the fast EEG activity of REM sleep resembles EEG activity in wakefulness. Jouvet concluded that this particular physiological state is associated with a “third state” of the brain (in addition to the brain states associated with wakefulness and NREM sleep) which he called “paradoxical sleep” instead of “REM sleep” (Jouvet et al., 1959 ; Jouvet, 1992 ). Several years later, Fisher et al. ( 1965 ) discovered another physiological characteristic of REM sleep: the penile erection.

During the same period, the American team noticed that a subject awakened during REM sleep very often reported a dream (80% of awakenings in REM sleep vs. 6% of awakenings in NREM sleep are followed by a dream report, according to Dement and Kleitman, 1957b ). Researchers concluded that dreaming occurs during REM sleep. The eye movements of REM sleep would allow the dreamer to scan the imaginary scene of the dream (the scanning hypothesis); the cerebral cortex activation revealed by the rapid EEG would allow intense cognitive activity, creating the complex stories of a dream; and the lack of muscle tone would prevent the dreamer from acting out his dreams. From that time on, researchers investigated REM sleep to obtain answers about dreaming.

In the 1990s, researchers used functional neuroimaging techniques such as positron emission tomography (PET) to investigate brain activity during REM sleep in humans. This new approach enabled researchers to demonstrate that the functional organization of the brain during REM sleep is different from the functional organization of the brain during wakefulness (Maquet et al., 1996 ; Braun et al., 1998 ). In comparison to wakefulness, brain activity during REM sleep is decreased in some brain regions (e.g., in the dorsolateral prefrontal cortex; Braun et al., 1998 ) and increased in other regions (e.g., in the occipital and temporal cortex, the hippocampus and parahippocampus, the anterior cingulate, the precentral and postcentral gyri, the superior parietal cortex, and the pons; Braun et al., 1998 ; Maquet et al., 2000 ). Looking more generally for brain activity correlating with REM sleep (the vigilance states considered included wakefulness, slow-wave sleep, and REM sleep), Maquet et al. ( 1996 ) found negative correlations in the precuneus, posterior cingulate cortex, temporoparietal junction, and dorsolateral prefrontal cortex and positive correlations in the amygdala, anterior cingulate, postcentral gyrus, thalamus, and pons (see Schwartz and Maquet, 2002 ; Maquet et al., 2005 ; Nir and Tononi, 2010 for reviews). Based on these results, researchers argued that the particular functional organization of the brain during REM sleep could explain the phenomenological characteristics of dream reports (Hobson and Pace-Schott, 2002 ; Schwartz and Maquet, 2002 ; Maquet et al., 2005 ; Nir and Tononi, 2010 ). They considered that brain activity increases and decreases during REM sleep could be interpreted on the basis of what we know about brain activity during wakefulness. In this context, the increased occipital cortex activity during REM sleep could explain the visual component of dream reports because neuroimaging results during wakefulness showed that visual imagery with the eyes closed activates the occipital cortex (Kosslyn and Thompson, 2003 ). The decreased activity in the temporoparietal junction during REM sleep may explain why dreams are mainly experienced in the egocentric coordinates of the first-person; indeed, during wakefulness, activity in the temporoparietal junction was reported to be greater for allocentric vs. egocentric representation (e.g., Ruby and Decety, 2001 ; Zacks et al., 2003 ) and for third- vs. first-person perspective (e.g., Ruby and Decety, 2003 , 2004 ). The increased activity in the hippocampus during REM sleep could explain why dreams are often composed of known images or characters, as the hippocampus is known to be associated with the encoding and retrieval of lived events during wakefulness (e.g., Piolino et al., 2009 ). The decreased activity in the lateral prefrontal cortex during REM sleep could explain why dream stories lack consistency, why the dreamer’s perception of time is altered, why the dream story is beyond the control of the dreamer and why the dreamer is convinced that the dream story is really happening. Indeed, during wakefulness, the lateral prefrontal cortex is involved in executive function, cognitive control, and working memory (Petrides, 2005 ; Koechlin and Hyafil, 2007 ). The increased activity in the medial prefrontal cortex during REM sleep could explain the attribution of thoughts, beliefs, and emotions to the characters in the dream because, during wakefulness, the medial prefrontal cortex is known to participate in mind reading (Ruby et al., 2007 , 2009 ; Legrand and Ruby, 2009 ). The increased activity in the motor cortex (precentral gyrus) during REM sleep could explain the movements of the characters’ bodies in the dream because, during wakefulness, motor imagery, and the imagination of someone’s action from the third-person perspective involve the precentral gyrus (Decety et al., 1994 ; Ruby and Decety, 2001 ). Finally, the amygdala’s activity during REM sleep could explain why emotions, especially fear, are often mentioned in dream reports; indeed, the amygdala is involved in the processing of emotional stimuli during wakefulness (Adolphs, 2008 ).

In conclusion, results from experimental psychology and neuroscience allow us to better understand the phenomenology of dreaming and the cerebral correlates of some characteristics of dream reports. Still, what do they tell us about the role of dreaming? What are the current hypotheses about dream function(s)?

Hypotheses about dream function(s)

No function.

At the end of the twentieth century, the neurologist Alan Hobson, who was profoundly anti-psychoanalysis, proposed a theory that deprived dreaming of any function. Hobson argued that dreaming is an epiphenomenon of REM sleep: “Because dreams are so difficult to remember, it seems unlikely that attention to their content could afford much in the way of high-priority survival value. Indeed, it might instead be assumed that dreaming is an epiphenomenon of REM sleep whose cognitive content is so ambiguous as to invite misleading or even erroneous interpretation” (Hobson et al., 1998 ).

Psychological individualism

In contrast, other teams, like Michel Jouvet’s, believed that dreaming serves a vital function. In 1979, Jouvet’s team blocked muscular atonia during REM sleep in a cat by damaging the locus coeruleus α in its brainstem. This lesion resulted in the appearance of movements during REM sleep. Movies from the Jouvet lab show sleeping cats performing complex motor actions (with altered control and coordination) resembling those of wakefulness, such as fur licking, growling, chasing prey, mastication, and fighting. From these videos, the authors concluded that the cat was acting out its dream, and they called this non-physiological state “oneiric behavior” (Sastre and Jouvet, 1979 ). These results led Jouvet to propose that dreaming plays a role in reinforcing a species’ typical behavior. Later in his career, Jouvet moved toward a hypothesis focusing on the role of dreaming in the individual dimension. He speculated that dreams (note that, for Jouvet, dreams and paradoxical sleep were equivalent) could be involved in psychological individualism and in the stability of the dreamer’s personality (Jouvet, 1991 , 1992 , 1998 ). According to Jouvet, “the brain is the sole organ of homeotherms that do not undergo cell division. We thus have to explain how certain aspects of psychological heredity (found in homozygote twins raised in different surroundings) may persist for a whole life (psychological individuation). A definitive genetic programming during development (by neurogenesis) is unlikely due to the plasticity of the nervous system. That is why we have to consider the possibility of an iterative genetic programming. The internal mechanisms (synchronous) of paradoxical sleep (SP) are particularly adapted to such programming. This would activate an endogenous system of stimulation that would stimulate and stabilize receptors genetically programmed by DNA in some neuronal circuits. The excitation of these neurons during SP leads to oniric behaviors that could be experimentally revealed – the lists of these behaviors are specific to each individual and indirect data suggest a genetic component of this programming. Amongst the mechanisms allowing the iterative programming of SP, sleep is particularly important. Security – and hence the inhibition of the arousal system – is a sine qua non-condition for genetic programming to take place. In that sense, sleep could very well be the guardian of dreaming” (Jouvet, 1991 ). In other words, Jouvet’s hypothesis is that paradoxical sleep restores neuronal circuitry that was modified during the day to preserve the expression of the genetic program that codes for psychological characteristics. This process would ensure the stability of personality across time.

The threat simulation theory

The Finnish psychologist Antti Revonsuo recently proposed a hypothesis called threat simulation theory, which explains the fearful characteristics of dream content (Revonsuo, 2000 ; Valli and Revonsuo, 2009 ). According to this theory, dreams serve as virtual training places to improve threat avoidance or threat fighting ability. The theory postulates that such nocturnal training makes the dreamer more efficient at resolving threatening situations during wakefulness.

Emotional regulation

Cartwright et al. ( 1998a , b ) defended the idea that dreaming is involved in emotional regulation. Her team showed that, in healthy subjects, the depression level before sleep was significantly correlated with affect in the first REM report. Her team also observed that low scorers on the depression scale displayed a flat distribution of positive and negative affect in dreams, whereas those with a depressed mood before sleep showed a pattern of decreasing negative and increasing positive affect in dreams reported from successive REM periods (Cartwright et al., 1998a ). These results led Cartwright’s team to suggest that dreaming may actively moderate mood overnight in normal subjects. The team strengthened this hypothesis by showing that among subjects who were depressed because of a divorce, those who reported more negative dreams at the beginning of sleep and fewer at the night’s end were more likely to be in remission 1 year later than subjects who had fewer negative dreams at the beginning of sleep and more at the end of the night (Cartwright et al., 1998b ). The researchers concluded that negative dreams early in the night may reflect a within-sleep mood regulation process, whereas those that occur later may indicate a failure in the completion of this process.

Memory consolidation

Finally, a current mainstream hypothesis in cognitive neuroscience credits sleep and dreaming with a role in memory consolidation (for a recent review, see Diekelmann and Born, 2010 ). Numerous studies have shown that brain activity during training is replayed during post-training sleep (e.g., using a serial reaction time task Maquet et al., 2000 , demonstrated replay during REM sleep; using a maze exploration task Peigneux et al., 2004 , demonstrated replay during slow-wave sleep). Decreased performance during the post-training day in sleep-deprived subjects further suggested that the replay of brain activity at night contributes to memory consolidation (e.g., Maquet et al., 2003 ). Only recently, however, have experimental results in humans argued in favor of a role of dreaming per se in memory consolidation. In one study, subjects were trained on a virtual navigation task before taking a nap. Post-nap tests showed that subjects who dreamed about the task performed better than subjects who did not dream (note that only 4 out of 50 subjects dreamed about the task in this study; Wamsley et al., 2010 ). Using a different approach, Nielsen and colleagues provided additional arguments supporting a link between dreams and memory (Nielsen et al., 2004 ; Nielsen and Stenstrom, 2005 ). This team demonstrated that dreams preferably incorporate events that the dreamer lived the day before and events that the dreamer lived 7 days before the dream (U shaped curve). Animal studies have shown that after associative learning, the excitability of hippocampal cells increases (which leads to an increase in neuronal plasticity) and then returns to baseline 7 days after training (Thompson et al., 1996 ). The similarity between the delay of episodic event incorporation into dreams and the delay of post-training cellular plasticity in the hippocampus led the Canadian team to suggest a link between dreaming and episodic memory consolidation.

In summary, the preceding section describes the current state of the art on dreaming, its phenomenology and cerebral correlates and hypotheses about its functions. Some substantial advances have been made, but much remains to be understood.

Unresolved Issues

The link between oneiric behaviors and dream reports.

A piece of evidence in favor of a strong link between REM sleep and dreaming is the oneiric behavior (the appearance of complex motor behaviors when motor inhibition is suppressed during REM sleep) discovered by Sastre and Jouvet ( 1979 ) in cats and reproduced by Sanford et al. ( 2001 ) in rats. Researchers interpreted these results as the animal acting out its dream. However, as animals do not talk, the link between oneiric behavior and dream recall cannot be tested experimentally. This limitation seriously hampers our understanding of dreaming. In humans, complex motor behaviors (e.g., talking, grabbing, and manipulating imaginary objects, walking, and running) can also occur during REM sleep in a pathological context. This syndrome is called REM sleep behavior disorder (RBD). It can be caused by substance withdrawal (e.g., alcohol, Nitrazepam) or intoxication (e.g., caffeine, tricyclic antidepressants) or by various diseases (e.g., Parkinson’s and Alzheimer’s diseases, pontine neoplasms). According to physicians experts on this syndrome, some patients report dreams that are consistent with their behaviors in REM sleep (Mahowald and Schenck, 2000 ). According to the literature, however, such matches seem to be loose and not systematic. Only one study has tested whether observers can link dream content to sleep behaviors in RBD (Valli et al., 2011 ). In this study, each video recording of motor manifestations was combined with four dream reports, and seven judges had to match the video clip with the correctly reported dream content. The authors found that reported dream content can be linked to motor behaviors at a level better than chance. However, only 39.5% of video-dream pairs were correctly identified. Note, however, that because the authors obtained only movements and not behavioral episodes for many RBD patients, the link between videos and dream reports was unfairly difficult to make.

It is important to note that motor behavior during sleep can happen outside of REM sleep. Sleepwalking and sleep terrors, which occur during NREM sleep, are usually not considered dream enactments. However, we know that dreams can happen during NREM sleep, and many patients report dreamlike mentation after awakening from sleepwalking or sleep terrors (71%, according to Oudiette et al., 2009 ). In addition, Oudiette et al. ( 2009 ) reported that the dreamlike mentation can correspond with the sleep behavior in NREM sleep. Consequently, the authors concluded that sleepwalking may represent an acting out of corresponding dreamlike mentation.

Recent research suggests that any kind of motor behavior during sleep can be considered an oneiric behavior. One of the challenges for future research is to test the strength of the link between these oneiric behaviors and dream reports in a controlled and systematic way.

Neurophysiological correlates of dreaming

Despite the numerous neuroimaging studies of sleep in humans, the neurophysiological correlates of dreaming remain unclear.

Indeed, dreaming can happen during NREM sleep, and although NREM brain activity differs substantially from REM sleep brain activity (Maquet et al., 2000 ; Buchsbaum et al., 2001 ), some NREM dreams are phenomenologically indistinguishable from REM dreams (Hobson, 1988 ; Cavallero et al., 1992 ; Cicogna et al., 1998 ; Wittmann et al., 2004 ). This phenomenon is difficult to understand given what we currently know about the sleeping brain and about dreaming. One explanation may rely on the possibility that brain activity during sleep is not as stable as we think.

Brain activity during REM sleep in humans is considered to be well understood (Hobson and Pace-Schott, 2002 ; Schwartz and Maquet, 2002 ; Nir and Tononi, 2010 ), but several results question this notion. First, contrary to the common belief that dorsolateral prefrontal cortex activity decreases during REM sleep, several studies have reported increased activity in the dorsolateral prefrontal cortex during REM sleep (Hong et al., 1995 , 2009 ; Nofzinger et al., 1997 ; Kubota et al., 2011 ). Second, brain activity during REM sleep is heterogeneous. The mean regional cerebral blood flow during 1 min of REM sleep (e.g., as reported in Maquet et al., 1996 ) and the regional cerebral blood flow associated with the rapid eye movements of REM sleep (Hong et al., 2009 ; Miyauchi et al., 2009 ) highlight different brain regions. Finally, few congruencies have been noted in the results of studies investigating brain activity during REM sleep (Hong et al., 1995 , 2009 ; Maquet et al., 1996 , 2000 ; Braun et al., 1997 , 1998 ; Nofzinger et al., 1997 ; Peigneux et al., 2001 ; Wehrle et al., 2005 ; Miyauchi et al., 2009 ; Kubota et al., 2011 ), even between studies using the same technique and the same contrasts (e.g., Braun et al., 1998 ; Maquet et al., 2000 ), or between studies investigating the same REM event (e.g., brain activity associated with rapid eyes movements, as in Peigneux et al., 2001 ; Wehrle et al., 2005 ; Hong et al., 2009 ; Miyauchi et al., 2009 ). Furthermore, few brain regions are consistently reported across the majority of the studies. This inconsistency suggests great intra- and intersubject variability in brain activity during REM sleep in humans. A challenge for future research will be to find out whether the variability in brain activity during REM sleep can be explained by the variability in dream content.

Because dream reports can be collected after awakenings from any sleep stage, one may hypothesize that the brain activity that subserves dreaming (if such brain activity is reproducible across dreams) is quite constant throughout the night and can be observed during all sleep stages. Some results have supported this hypothesis and encouraged further attention in this direction. Buchsbaum et al. ( 2001 ), for example, reported that metabolism in the primary visual areas and certain parts of the lateral temporal cortex does not fluctuate much across REM and slow-wave sleep. Similarly, Nielsen’s team found that dream recall (vs. no dream recall) was associated with decreased alpha (8–12 Hz) power in the EEG preceding awakening, regardless of the sleep stage (Stage 2 or REM sleep; Esposito et al., 2004 ). Interestingly, some authors have suggested that decreased power in the alpha band during wakefulness reflects search and retrieval processes in long-term memory (for a review, see Klimesch, 1999 ).

Processes of selection and organization of dream representations

Nielsen’s team found that episodic events from the 1, 7, and 8 days before a dream were more often incorporated into the dream than were events from 2 or 6 days before the dream (Nielsen et al., 2004 ; results reproduced by Blagrove et al., 2011 ). This result tells us that internal processes control and shape dream content and thus help us to constrain and shape hypotheses about the function and biological basis of dreaming.

At the end of the nineteenth century, Saint-Denys (1867) showed that a sensory stimulus (e.g., the scent of lavender) presented to a sleeping subject without his or her knowledge could induce the incorporation of an event associated with the stimulus (e.g., holidays spent near a lavender field) into the dream, regardless of the delay between the dream and the association stimulus/events (lavender scent/holidays). The author demonstrated that the external world can influence dream content in a direct or indirect way.

Finally, it appears that both external and internal parameters can shape or govern dream content. Nonetheless, few of these parameters are known, and some regularities in the phenomenology of dreams suggest that more influencing parameters remain to be discovered. For example, some individuals experience recurring themes, characters, or places in their dreams. In line with this observation, Michael Schredl’s team showed that the content and style of a person’s life strongly influence dream content (Schredl and Hofmann, 2003 ). However, the rule(s) governing which lived events are incorporated into dreams remain unknown. Do the representations constituting the dream emerge randomly from the brain, or do they surface according to certain parameters? Similarly, is the organization of the dream’s representations chaotic, or is it determined by rules? Does dreaming have a meaning? What is/are the function(s) of dreaming?

Dreaming, Psychoanalysis, and Neuropsychoanalysis

Psychoanalysis, which was developed by the neurologist Sigmund Freud in the beginning of the twentieth century, proposes answers to the questions raised above. Indeed, his theory of the human mind comprises hypotheses about the rules of selection and organization of the representations that constitute dreams.

At the beginning of the twentieth century, Freud presented the concept of the unconscious. He proposed that a part of our mind is made up of thoughts, desires, emotions, and knowledge that we are not aware of, but that nevertheless profoundly influence and guide our behaviors. In his books (e.g., Freud, 1900, 1920 ), Freud proposes that the unconscious mind comes out in slips and dreams. Its expression, however, is coded within dreams (the work of dream), and unconscious thoughts are distorted before they emerge in the conscious mind of the sleeping subject (manifest content of the dream). As a consequence, the dreamer is not disturbed by repressed and unacceptable thoughts (latent content of the dream) and can continue sleeping (this is the reason why Freud considered dreams the guardians of sleep). Hence, according to Freud, decoding dreams’ latent content provides an access to the unconscious mind.

In Freud’s theory of the mind, unconscious thoughts and feelings may cause the patient to experience life difficulties and/or maladjustment, and free unconscious thoughts can help the patient gain insight into his/her situation. As a consequence, Freud developed techniques to decode dreams and provide a way for an analyst to look inside the words and unconscious images of the patient, and to free them through patient insight. One of these techniques is called free association, and is regarded as an essential part of the psychoanalytic therapy process. In order for an analyst to get to the latent content of a dream, he requires the patient to discuss the dream’s manifest content and encourage free association about the dream. Free association is the principle that the patient is to say anything and everything that comes to mind. This includes decensoring his/her own speech so that he/she truly expresses everything. Over time, the therapist or analyst will draw associations between the many trains of uncensored speech the patient shares during each session. This can lead to patient insight into their unconscious thoughts or repressed memories, and the accomplishment of their ultimate goal of “freedom from the oppression of the unconscious” (Trull, 2005 ).

Hence, Freud considered that dreams, as well as slips, have a meaning and can be interpreted, so that one is justified in inferring from them the presence of restrained or repressed intentions (Freud, 1900, 1920 ). Note that, in Freud’s theory of the mind, the words “meaning” and “intention” are closely linked: “Let us agree once more on what we understand by the ‘meaning’ of a psychic process. A psychic process is nothing more than the purpose which it serves and the position which it holds in a psychic sequence. We can also substitute the word ‘purpose’ or ‘intention’ for ‘meaning’ in most of our investigations” (Freud, 1920 ).

In other words, according to Freud, decoding dreams with the free association method provides an access to what makes each of us so special, uncorvering the forces that guide one’s behavior. It gives access to an unknown dimension of ourselves that is fundamental in understanding who we are. It provides access to personal meaning.

This hypothesis, attributing significant importance and meaning to dreams, has rarely been considered by neuroscientists who often consider Freud’s work and theory unscientific.

However, this situation may change as the relationship between psychoanalysis and neuroscience evolves. The starting point was the creation of the International Society for Neuropsychoanalysis in 2000. It was founded by neuropsychologist and psychoanalyst Mark Solms with the intention to promote interactions and collaborations between psychoanalysis and neuroscience. The challenge was serious, as illustrated by neuroscientist Alan Hobson’s aggressiveness in the famous dream debate (Alan Hobson vs. Mark Solms) entitled “Should Freud’s dream theory be abandoned?” held in Tucson, Arizona, in 2006 during the Towards a Science of Consciousness meeting (scientific arguments can be found in Solms, 2000 and Hobson et al., 2000 ). Alan Hobson tried to convince the assembly that Freud was 100% wrong and that Freud’s dream theory was misguided and misleading and should be abandoned. He aimed to demonstrate that Freud’s dream theory is incompatible with what we know about how the brain works. He added that Freud’s dream theory was not scientific because it was not testable or falsifiable. Finally, he presented his model of dreaming, the activation-synthesis hypothesis (Hobson and McCarley, 1977 ; Hobson et al., 2000 ): “The Activation-Synthesis model of dream construction proposed that the phasic signals arising in the pontine brainstem during REM sleep and impinging upon the cortex and limbic forebrain led directly to the visual and motor hallucinations, emotion, and distinctively bizarre cognition that characterize dream mentation. In doing so, these chaotically generated signals arising from the brain stem acted as a physiological Rorschach test, initiating a process of image and narrative synthesis involving associative and language regions of the brain and resulting in the construction of the dream scenarios.” In contrast, Mark Solms demonstrated that what is currently known about the dreaming brain is at least broadly consistent with Freud’s dream theory. He argued that it is generally accepted that brain stem activation is necessary, but not sufficient, to explain the particular characteristics of dream consciousness. What does explain the particular characteristics of dream consciousness, according to Solms, are the following features of brain activity during REM sleep (Braun et al., 1997 ): the activation of core forebrain emotion and instinctual drive mechanisms, i.e., the limbic and paralimbic brain areas (the anterior cingulate, insula, hippocampus, parahippocampal gyrus, and temporal pole), and of the posterior perceptual system (the fusiform gyrus, superior, inferior and middle temporal gyrus, and angular gyrus) and the deactivation of executive dorsolateral frontal control mechanisms (the dorsolateral prefrontal cortex). He further argued that his lesion studies (Solms, 1997 ) are congruent with neuroimaging results because they showed that a total cessation of dreaming results from lesions in the medial part of the frontal lobe and in the temporoparietal junction (whereas no cessation of dreaming was observed for core brainstem lesions or for dorsolateral prefrontal lesions). Finally he emphasized that the activation of motivational mechanisms (such as drives and basic emotions) and of posterior perceptual system associated with deactivation of the executive control (i.e., reality oriented regulatory mechanism) during REM sleep, is broadly consistent with Freud’s dream theory which claims that our instinctual drive states (notably appetitive and libidinal drive system) are relatively disinhibited during sleep. Note that experimental results demonstrating the existence of unconscious representations that guide behavior (e.g., Shevrin and Fritzler, 1968 ; Bunce et al., 1999 ; Arminjon, 2011 , for a review) could also have been cited in support of Freud’s dream theory. This debate was a success for Mark Solms and neuropsychoanalysis. Indeed, at the end of the debate, approximately 100 people voted “no” (i.e., “Freud’s dream theory should not be abandoned”), approximately 50 people voted “yes” and 50 voted “I don’t know”.

Solms’ ( 1997 , 2000 ) approach to dreaming and his experimental results fundamentally challenged our current understanding of dreaming. He proposes that dreaming and REM sleep are controlled by different brain mechanisms. According to Solms, REM sleep is controlled by cholinergic brain stem mechanisms, whereas dreaming is mediated by forebrain mechanisms that are probably dopaminergic. This implies that dreaming can be activated by a variety of NREM triggers. Several experimental results support this hypothesis.

First, behavioral studies have demonstrated that the link between REM sleep and dream reports is lax. Subjects awakened during NREM sleep can recall dreams at a high rate (Foulkes, 1962 : 74% of awakenings in NREM sleep were followed by dream reports; Cavallero et al., 1992 : 64%; Wittmann et al., 2004 : 60%); dreams can be recalled after a nap consisting only of NREM sleep (Salzarulo, 1971 ; Palagini et al., 2004 ); and some individuals never recall dreams, even when awakened from REM sleep (Pagel, 2003 ). In addition, in healthy subjects with a normal dream recall frequency (around 1 dream recall per week, Schredl, 2008 ), dream recall after an awakening during REM sleep is not systematic: 5–30% of awakenings in REM sleep are not followed by a dream recall, according to the literature (e.g., Dement and Kleitman, 1957a , b ; Foulkes, 1962 ; Hobson, 1988 ). Finally, 5–10% of NREM dreams cannot be distinguished from REM dreams based on their content (Hobson, 1988 ; Cavallero et al., 1992 ; Cicogna et al., 1998 ; Wittmann et al., 2004 ).

Second, as Solms ( 2000 ) argued, the amount of dream recall can be modulated by dopamine agonists (Scharf et al., 1978 ; Nausieda et al., 1982 ) without concomitant modification of the duration and frequency of REM sleep (Hartmann et al., 1980 ). Dream recall can be suppressed by focal brain lesions (at the temporo-parieto-occipital junction and ventromedial prefrontal cortex; Solms, 1997 , 2000 ). These lesions do not have any appreciable effects on REM frequency, duration, or density (Kerr et al., 1978 ; Michel and Sieroff, 1981 ). Finally, some clinical studies suggest that a dream can be triggered by nocturnal seizures in NREM sleep, i.e., by focal brain stimulation. Some cases of recurring nightmares caused by epileptiform activity in the temporal lobe have indeed been reported (Solms, 2000 ).

Conclusion: Collaboration between Neuroscience and Psychoanalysis Would Benefit Dream Research

Considering the issues that remain unresolved (e.g., neurophysiologic variability, parameter(s) influencing the emergence of representations in dreams, the meaning of dreams), a psychoanalytic perspective would certainly benefit dream research by providing new directions/leads and helping to reach a comprehensive understanding of dreaming.

On the one hand, psychological research has demonstrated that dream content is influenced by one’s personal life, especially personal concerns (Schwartz, 1999 ; Schwartz and Maquet, 2002 ; Schredl and Hofmann, 2003 ), and some neuroscientists have hypothesized that dreaming is involved in psychological individualism. Thus, both psychology and neuroscience have provided results and hypotheses that validate the possibility that dreaming has something to do with personal and meaningful issues. On the other hand, Freud argued that the unconscious, which guides behaviors and desires, express itself during dreams. The two disciplines’ (cognitive neuroscience and psychoanalysis) convergence on dreaming thus seems obvious; however, very little collaboration has occurred to date.

Note that some experimental studies in psychology have considered the psychoanalytic perspective. For example, Greenberg et al. ( 1992 ) attempted “a research-based reconsideration of the psychoanalytical theory of dreaming.” They evaluated the presence of problems (defined as an expression of negative feeling or any situation evoking such feeling or requiring some change or adaptation) during dreaming and pre- and post-sleep wakefulness in two subjects. They showed that problems occurred very frequently in the manifest dream content and that these problems were nearly systematically related to the problems noted during pre-sleep wakefulness. In addition, they observed that effective dreams (i.e., dreams that presented some solution to the individuals’ problems) were followed by a waking state in which the impact of the problems was diminished, whereas ineffective dreams were followed by the persistence of the problems. This study thus confirmed that personal concerns influence dream content. In addition it provided new results suggesting that dreaming may have some psychological problem-solving function (this result recalls the neuroscientific findings that sleep has a cognitive problem-solving function associated with brain reorganization; e.g., Wagner et al., 2004 ; Darsaud et al., 2011 ). Greenberg et al.’s ( 1992 ) study managed to quantify personal issues and clearly broadened the cognitive neuroscience perspective on dreaming. To proceed further, approaches integrating psychoanalysis and neuroscience must now be developed. Several subjective issues at the core of the psychoanalytic approach, such as the concept of personal meaning, the concept of unconscious episodic memory and the subject’s history, are not addressed or considered in cognitive neuroscience. This limitation hampers the understanding of psychological and neurophysiological functioning in humans. These issues must be addressed, and the expertise of psychoanalysts in singularity and personal meaning is needed to do so in neuroscience and to further the understanding of dreaming and of the psyche.

Conflict of Interest Statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Scholaread-Translator&Reader 4+

Research anytime and anywhere, yicun network technology co. ltd., designed for ipad.

• 4.4 • 12 Ratings

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Description.

Scholaread is more than just a tool—it's a vision to transform academic reading into a seamless, enriching experience for scholars everywhere. By combining PDF reading, academic translation, literature management into a unified platform, we're empowering scholars to maximize the value of their time. Our state-of-the-art PDF layout parsing algorithm is the foundation for this transformation. It facilitates reflow and interlinear translation, providing an unrivaled reading experience across all devices. --- Discover the ease of mobile reading without compromise. Scholaread's reflow technology adapts complex PDF layouts, making them as accessible and straightforward as a well-written blog. Your academic library travels with you, optimizing every moment for study, reflection, and discovery. Academic work thrives on the exchange of ideas, which should not be hindered by language barriers. Our AI-powered full-text translation lets you delve into foreign literature effortlessly, maintaining your flow of thought across various devices. With seamless Zotero integration, your scholarship is as mobile as you are, enabling constant progress wherever inspiration strikes. Scholaread's commitment to reshaping academic reading ensures that each paper, every chart, and all research gets the recognition it deserves. We honor the intellectual journey of scholars by creating a platform where knowledge is not only accessible but also beautifully presented, transcending the limitations of language and devices. Our features reflect our vision: - An unparalleled reflow reading experience, honed by advanced technology - Synchronized translation across devices, breaking down linguistic barriers - Browser extensions to effortlessly capture and organize literature - Seamless importation and integration with Zotero libraries - Intuitive highlighting and note-taking, making key information stand out - Reading support that caters to formulas, charts, and a variety of content - A restful dark mode for comfortable research sessions extending late into the night - Upcoming functionalities such as citation formatting and AI-assisted speed reading to further enhance the scholarly endeavor [Reflow Mode] Click to transform complex, dual-column academic papers into a streamlined, mobile-friendly format, maintaining clarity in text and imagery. [Full-Text Translation] Experience the power of multi-language translation by an advanced AI, presenting a side-by-side comparison for an enriched understanding of SCI papers. [Zotero Integration] Keep your scholarly materials consistently accessible, syncing with your Zotero library across any device you choose. [Efficient Research Tools] Access figures and citations with ease, keep your reading in sync, and effortlessly navigate papers with an automatically generated table of contents. [Reading Support] Whether you’re engaging with complex equations, detailed charts, sophisticated tables, vivid images, or intricate code, Scholaread supports your diverse reading needs. With just a click, you can effortlessly enlarge and extract these elements, ensuring that every aspect of your multidisciplinary research is comprehensively catered to. [Highlights & Notes] Elevate your study with tools designed for effective marking and notetaking. [Dark Mode] Care for your eyes with a mode designed for the long hours of a researcher's journey. --- For any assistance, suggestions, or to share your insights, please contact us at [email protected]. Together, let's advance the world of scholarship and make every minute count!

Version 1.6.7

What' New 1. Added OCR translation for the Pad version – freely screenshot and translate. 2. Optimized user experience and fixed known issues.

Ratings and Reviews

Really great, but.

The software is really useful, and the Chinese-English comparison is very convenient. However, it really requires a separate subscription plan. The bundled packages truly make it a dilemma whether to purchase or not.

Brilliant idea

I don’t really write reviews but this app is brilliant for reading paper on iPhone. There are some small bugs and features to improve so hopefully it will get better in future.

升级后不能翻译PDF文档

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Computer Science > Computation and Language

Title: realm: reference resolution as language modeling.

Abstract: Reference resolution is an important problem, one that is essential to understand and successfully handle context of different kinds. This context includes both previous turns and context that pertains to non-conversational entities, such as entities on the user's screen or those running in the background. While LLMs have been shown to be extremely powerful for a variety of tasks, their use in reference resolution, particularly for non-conversational entities, remains underutilized. This paper demonstrates how LLMs can be used to create an extremely effective system to resolve references of various types, by showing how reference resolution can be converted into a language modeling problem, despite involving forms of entities like those on screen that are not traditionally conducive to being reduced to a text-only modality. We demonstrate large improvements over an existing system with similar functionality across different types of references, with our smallest model obtaining absolute gains of over 5% for on-screen references. We also benchmark against GPT-3.5 and GPT-4, with our smallest model achieving performance comparable to that of GPT-4, and our larger models substantially outperforming it.

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Geology & Geophysics Professor Overcomes Adversity To Land Dream Job At Texas A&M

April 10, 2024 By Grant Hawkins '98

• Geology & Geophysics
• Undergraduate

Dr. Brandi Lenz , an instructional assistant professor and undergraduate program director in the Department of Geology and Geophysics at Texas A&M University since June 2022, overcame challenges including dropping out of college and navigating motherhood during her graduate studies. Her determination, fueled by childhood fears of natural disasters, led her to achieve her dream of teaching geology.

Lenz recently took time out from her teaching and research to reflect on her winding path to the present and lessons learned along her lifelong educational journey personified through a perfect mix of professional and personal.

Introduce yourself and tell us a bit about your background.

My name is Brandi Lenz, and I am an instructional assistant professor in the Department of Geology and Geophysics at Texas A&M. I started here in June 2022.     I completed my A.S. degree at Columbus State Community College in 2016, followed by my B.S., M.S. and Ph.D. in Earth science from The Ohio State University in 2017, 2019 and 2021, respectively. Despite this seemingly conventional educational trajectory, my journey has been anything but traditional. In fact, I initially dropped out of college.     I was born in Pittsburgh and spent the majority of my childhood there until my sophomore year of high school. Following that, my family and I relocated several times, eventually leading me to graduate from high school in the Dallas-Fort Worth area.     Immediately after high school, I enrolled at the University of Texas at El Paso as a geology major. However, I found myself navigating the challenges of living independently and juggling full-time work in the telecommunications industry to support myself financially. The strain of this lifestyle led to burnout, prompting me to drop out after about a year. Returning to my hometown, I transitioned into the information technology field and briefly served in the military (Army National Guard), though my time was cut short due to a pelvis fracture during basic training.   Following these experiences, I got married and realized my passion for geology, compelling me to return to academia to pursue my dreams. My husband and I made the decision to relocate to Columbus, Ohio, where I was fortunate to be accepted into The Ohio State University. After that, driven by my strong love for the subject, I stayed committed until I got my Ph.D. just a few years ago.

My graduate school experience took an even more unconventional turn. During my second year in the Ph.D. program, I found out I was pregnant. I was eight months pregnant when I passed my candidacy exams. My son was born just a few days after I received my master's degree and has become a significant part of my journey ever since.     As a graduate student, affording childcare was challenging, so my son often accompanied me to school while I taught as a teaching assistant, which funded my entire graduate career. I would carry him strapped to me, hoping he would nap while I taught. Students loved it! To top it off, I graduated with my Ph.D. on Mother's Day, which felt like the perfect culmination of my academic journey.  

After completing my Ph.D., I spent a year working as a part-time instructor at three different institutions, all at the same time. I taught environmental geoscience at Ohio State, physical geography at Ohio Wesleyan University and planet Earth labs at the University of Dayton.    

And now, I am here today!     My passion for geology started when I was a child because of my fear of natural disasters, and now, I get to teach about natural disasters at Texas A&M. This is truly my dream job!  

What kind of research projects have you recently worked on?  

My latest research project focused on studying the kinematics of submarine landslides off the coast of Oregon. I completed and published the final paper on this research just last year.

Can you explain the main points of your research?

Submarine landslides can create and/or amplify tsunami events, causing destruction of life and property. Landslide tsunamis depend heavily on how much and how fast sediment has moved. The “how much” question can be relatively easy to constrain, but the “how fast” question is much more difficult to answer. I focused on trying to answer three main scientific questions.

1. What can reflection seismic data tell us about how underwater landslides move? To address this, I focused on the 44-North slide off the coast of Oregon. I collected seismic data across the landslide blocks and main head scarp. The data revealed a deformation zone in the sediments caused by the impact of the landslide blocks. The subsurface features indicate that the landslide moved rapidly and with significant force. These findings were published in Geosciences (Lenz et al., 2018) .

2. How does underwater landslide velocity relate to the deformation zone?   We developed a new method to estimate the velocity of previous underwater landslides by analyzing the dimensions of the impact-induced deformation zone. Determining slide velocity is crucial for understanding landslide hazard severity but is often challenging using traditional methods. By studying the 44-N slide off Oregon's coast with high-resolution reflection seismic data, we found that it likely moved swiftly (up to 60 miles per second) with significant momentum, as indicated by observations of the deformation zone. Given the importance of slide velocity in landslide-generated tsunamis, our approach has implications for assessing coastal hazards worldwide. Although our study focused on the 44-N slide, this method is applicable to other landslides with similar deformation zones, as outlined in our publication in Geophysical Research Letters (Lenz et al., 2023) .

3. What is the history of slope failures along the broader Oregon margin? My research explored differences in underwater landslide styles between northern and southern Oregon, identifying 133 landslide deposits along the Oregon margin. Additionally, I found that the 44-N slide is not unique to this area, with at least three similar events indicated in the southern Oregon margin. While such deformation has only been observed offshore Oregon and in a smaller example in a Swiss lake, my study suggests that underwater landslides are more common and disintegrative in the north than in the south. Despite their rarity in the south, the fast-moving thick cohesive style of failure along the southern Oregon margin may pose a higher risk of landslide-induced tsunamis. These findings were published in Basin Research (Lenz and Sawyer, 2021) .    

Discuss your role as the undergraduate program director in Texas A&M Geology and Geophysics. What are the primary objectives you aim to accomplish in this position?

I became the undergraduate program director in the Department of Geology and Geophysics in the fall of 2023. My goals in this position are to help support our students and provide them with the best possible path to prepare them for their futures. I have thoroughly enjoyed getting to know our current students and look forward to meeting new students each semester. I hope by completing a degree here with us that they are better equipped with the tools they need to hit the ground running and solve today’s real-world problems.  

What do you like most about working at Texas A&M? 

I cannot stress this enough — this is my dream job! I get to teach my favorite topics at one of the greatest and largest institutions in the country to our amazing students. The students here are phenomenal. The undergraduate courses I teach are GEOL 101: Principles of Geology and GEOS (soon to be GEOL) 110: Disasters and Society. I absolutely love getting to share my passion for geology and disasters with large audiences through education.  

I also love interacting with our graduate students as well, especially our teaching assistants. I recently partnered with the Center for Teaching Excellence and developed a new graduate seminar called Teaching Earth Science to help our graduate students prepare for academic positions in teaching. On top of teaching and mentoring, I also had the opportunity to implement new teaching tools for our department — an augmented reality sandbox to help students visualize 3-D features on Earth and a stream table to help students see long-term hydrological processes in real time. I am so lucky I have a job where I get to play with sandboxes and water in the name of education!  

I cannot stress this enough — this is my dream job! I get to teach my favorite topics at one of the greatest and largest institutions in the country to our amazing students. The students here are phenomenal.

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