The Methodology and the Neural Basis of Emotional Dreams

(1)

MSc in Brain and Cognitive Science

University of Amsterdam – Cognitive Neuroscience

University of Amsterdam – Department of Sleep and Cognition

Literature Thesis – 12 EC

May 1st, 2020 – July 1st, 2020

The Methodology and the Neural Basis of

Emotional Dreams

Author:

Supervisor:

Daan Bormans (10651004)

Elsa Juan

First examiner:

Second Examiner:

(2)

1

Abstract

Dreams are thought to reflect waking-life experiences and processes. This literature thesis evaluates the neural basis of emotional processes in dreams and its methodology. Several

definitions for dreaming are discussed as well as the conclusions from early experimental dream research. This paper shows that the anatomical correlates of dreams and emotions are rooted in the Temporo-Parieto-Occipital Junction (TPJ) and the medial prefrontal cortex (mPFC). These systems generate the psychological phenomena of dreaming. In addition, the frontal-striatal network, including the amygdala, hippocampus and medial prefrontal cortex, are involved in the dreams with highly emotional content. Evidence from nightmare disorders and individuals with ADHD show that emotional dreams can be caused by deficits in the frontal-striatal network. EEG research indicated a positive relation between prefrontal theta activity, gamma activity, and recollection of emotional dreams. In addition, slow oscillations coordinate emotional memory consolidation during dreaming. Finally, this thesis shows the methodological problems associated with identifying neural markers in emotional dream research. It provides a solution for this problem by introducing an algorithm that models and predicts oscillatory brain dynamics through closed-loop auditory stimulation combined with a serial awakening paradigm.

(3)

2

Introduction: The Relation between Emotions and Dreams

Individuals that are awoken from their sleep often report complex experiences containing various amount of motor, audio, and visual information. These experiences are vivid, often follow some sort of bizarre narrative, yet they are accompanied by complete outward

unresponsiveness. Such experiences are common in the entire population and are called ‘dreams’. Dreams are often filled with emotions and emotional patterns that occurred during our daily lives are often preserved during these experiences (Popp, et al., 1996). Pre-sleep emotional concerns occur frequently in our dreams, and the contents of our dreams are often structured around core relationship patterns (Popp, et al., 1996).

Dreams are thought to reflect waking-life experiences and processes (Domhoff, 1996). Therefore, researchers have argued that important insights in the psychology of the human mind can be gained from investigating emotional dreams that cannot be discovered through waking life observations (Nielsen & Stenström, 2005). This becomes even more evident when examining the relation between emotional dream imagery and psychological disorders. It has been found that dreams can replay very emotional experiences such as nightmares caused by traumatic

experiences (Nielsen & Stenström, 2005). Moreover, nightmares and highly negative emotional dreams are central in a large number of mental illnesses, including depression, insomnia, post-traumatic stress disorder and attempted suicides (Nakajima. Inoue, & Sasai, 2013; Schredl, 2009; Sjöstrom, Hetta, & Waern, 2008).

Additionally, emotional dreams generally seem to be skewed towards negative experiences (Deseilles, Dang-Vu, & Schwartz, 2011) and this is thought to important for emotional

regulation. Emotion regulation can be defined as one’s ability to modulate the intensity or duration of their emotional response. This is often measured by identifying the intensity and frequency of experienced emotions. Arguably, the most crucial insights regarding emotional regulation have come from sleep studies. Research has shown that sleep loss consistently results in more negative appraisals of stimuli (Tempesta , De Gennaro, Natale, & Ferrara, 2015) and sleep quality is highly correlated with next day mood (De Wildt-Hartmann, Wichers, Van

Bemmel, Thiery, Jacobs, van Os, & Simons, 2013). Sleep loss allows threatening stimuli to evoke a stronger subjective and physiological response. Additionally, threatening stimuli evoke an increased attentional bias towards negative stimuli and a decreased ability to show empathy after sleep loss (Tempesta, et al., 2015). This seems particularly important in the light of emotion dysregulation or general deficits in one’s ability to modulate the intensity or duration of emotional responses (Sloan et al., 2017). Emotion dysregulation has been implicated as a core

(5)

4

feature or associated characteristic of nearly all psychiatric disorders and maladaptive behaviours (Aldao, Nolen-Hoeksema, & Schweizer, 2010; Compas et al., 2017; Leibenluft, 2011). As such, emotion dysregulation is commonly targeted as a treatment outcome in clinical trials for various forms of child and adolescent psychopathology (Gratz, Weiss, & Tull, 2015).

Taken all together, it seems clear that sleep plays an important role in emotion regulation (Tempesta, Socci, De Gennaro,& Ferraro, 2018) and researchers have argued that dreams in particular can play a crucial role in processing of emotional information and consolidation (Nir & Tonini, 2010, Schredl, 2014, Siclari et al., 2018, Windt, Nielsen & Thompson, 2016). However, currently no study has directly investigated the evidence of the neural basis of dreams and emotions. In light of all these findings it seems important to investigate the relation between dreams and emotions and how research currently investigates emotional dreams.

Therefore, this research aims to investigate the neural basis of emotional dreaming. Additionally, this thesis discusses the current methodology that is used to investigate emotional dreams and introduce a new methodological approach for future dream research.

This will all be achieved by first, examining what definitions for dreams are already used by researchers. Second, the early developments, results and conclusions from early experimental dream research are examined. At the end of this section, a definition of emotional dreams will be given. Third, this paper will examine the anatomical correlates of dreams and emotions. Insights from emotional disorders such as nightmare disorder and attention deficit hyperactivity disorders are briefly examined. Fourth, the neural markers of emotional dreams that are already identified by EEG researchers are discussed. Fifth, and finally a new framework for the systematic

investigation of neural markers of emotional dreams will be provided.

Defining Dreams: What Constitutes a Dream?

Even though dreams are intuitively understood by the general population, a clear

definition of what constitutes a dream is still lacking in scientific research. Researchers have tried to define dreams in several ways. Some have defined dreams as any mental activity that happens during sleep (Flanagan, 2001; Foulkes, 1962). Yet, others have defined dreams as subjective experiences during sleep that are only accessible if the dreamer has a recollection of those experiences after awakening (Schredl, 2014), or even defining it as a form of complex

hallucinations (Hobson, 2000). The commonality between these definitions is that emotional tone, bizarreness, story-like organization, and perceptual vividness are important features of

(6)

5

dreams. This indicates that the subjective experience or phenomenal consciousness are of central importance. Moreover, these definitions underline that when an individual is dreaming some form of consciousness needs to be present. On the other hand, this shows that dreamless sleep only occurs when no form of phenomenal consciousness is present. Even though, these features of dreams are understood, researchers still maintain varying definitions when investigating dreams. The next section will explore these definitions in more detail.

Different Definitions for Dreaming

The definition given by Schredl (2014) is widely used in empirical dream research. This definition revolves around the key point that dreams can only be called dreams when the experiences are recollected by the dreamer. It is useful during an experiment to determine whether one has had a dream via self-report measures. Currently, self-report measures are the only reliable way to determine when one is dreaming. However, this definition might not be giving a complete picture of the entire collection of dream experiences. For instance, research in this area has proven that dreams can also exist when an individual realizes that they have dreamt but are still unable to recall any specific contents (Siclari et al., 2013; Noreika, 2009). Such dreams are called ‘white dreams’ and the existence of this would argue against the need for recollection of experiences during dreams. Especially with new brain recording measures and more detailed analysis of dream data it seems plausible that dreaming can occur whether or not one could recollect if they have had a dream.

A more recent approach to dreaming has revealed an integration of different definitions of dreaming called ‘simulation views of dreaming’ (Windt, Nielsen & Thompson, 2016). This view has the central points that dreams are immersive and are minimally defined as ‘immersive spatiotemporal hallucinations’. These hallucinations occur in sleep or sleep–wake transition. The simulation view of dreaming allows a clear contrast between dreamless sleep and sleep with dreams for a number of reasons; 1) experiences during sleep are qualified as dreamless if they lack the immersive character of dreaming, 2) dreamless sleep lacks any specific imagery and conscious propositional thoughts, and 3)dreaming is largely dependent on spontaneous activity and

endogenously generated neurocognitive activity (Windt, Nielsen & Thompson, 2016). Daydreams and waking imagery, can also be distinguished from dreams according to this view. Even the most vivid of daydreams prevent the observers from feeling fully present in the imaginary worlds (Windt, 2018). By contrast, even passive observer dreams involve a form of phenomenal

(7)

6

(Windt, 2018). According to this view, daydreams are mental simulations, but they lack the immersive character of dreams and can therefore clearly be distinguished from each other.

Even though the simulation view gives clear guidelines on what can be considered to be a dream, using this definition for dream researchers might give rise to some methodological issues. The simulation view is restricting dream research by requiring dreams to have the immersive and story-like character. These are stringent criteria for dream researchers that could in turn restrict them in their ability to research emotional dreams. In order to explore the ramifications of using such a view for researchers, it seems relevant to evaluate this view by first looking at the

methodology and experimental setups that researchers have used when investigating emotional dreams.

Methodology in Early Dream

Research

Research investigating emotional dreams involve full-night recordings where subjects are monitored during their sleep. Normal human sleep is classically divided in two different types; sleep with rapid eye moment (REM) and sleep with non-rapid eye moment (NREM).

During a full night sleep, the total sleeping time consists mostly of NREM sleep (Carskadon & Dement, 2011; Saper, Fuller, Pedersen, Lu, & Scammell, 2010), with the total sleeping time spent in stages of NREM sleep is around 75-80 percent. The other 20-25% of sleep time is spent in the sleep stage of REM, which superficially looks similar in active waking and REM sleep in the electroencephalogram (EEG) (Iber, Ancoli-Israel, Chesson, & Quan, 2007).

Since, dreaming and waking experience seemed similar to early dream researchers, early research into dreams focused mostly on REM sleep (Nir & Tononi, 2010). It was therefore suggested that the presence of rapid eye movements during sleep could provide the basis for an objective method of dreaming. Studies found that when subjects are awoken after REM sleep, they are most likely to recall and report dream content (Maquet et al., 2000; Braun et al., 1998;

Figure 1. The progression of sleep in normal human sleep.

(8)

7

Nofzinger, et al., 1997; Braun, et al., 1997; Maquet, et al., 1996). Dream recall in NREM sleep received little attention by early dream researchers since NREM related dreams produced low efficiency in reporting of dream recalls. However, the direct association between REM sleep and dreaming was overcome; studies found that recollection of dreams after awakening can also occur in NREM stages of sleep even though dream recall is less frequent than in REM (Cipolli, 2017; Taub, 1971; Foulkes, 1962). Moreover, when considering dream reports, perceptual, emotional, planning, reasoning and thinking are commonly reported in both of the NREM and REM stages of sleep (Cipolli, 2017). Finally, 5-10% of dream recall reports after awakening during NREM stage 2, 3, and 4 cannot be distinguished from REM reports solely on the basis of the perceptual and emotional features of their contents (Cavallero, Cigogna, Natale, Occhionero, Zito, 1995; Monroe, Rechtschaffen, Foulkes, Jensen, 1965).

These early developments disproved the initial exclusive relation between REM sleep and dreaming. Dream researchers started to include NREM sleep into emotional dream research, however, currently most dream research still focusses on REM-sleep (Cipolli, 2017; Nir & Tononi, 2010).

Caveats of Methodology in Current Dream Research

Unfortunately, the distinction between NREM and REM did not seem to be the only issue in emotional dream research. Comparisons of methodology showed that recall frequency of dream characteristics are large influenced by the sleep stage and sleep cycle after awakening (Cipolli et al., 2015). It was also shown that the features on which a dream report is analysed, for instance the length and complexity of a story, vary largely between the moments of collection. Additionally, emotional dream reports are influenced not only by the cycle or sleep stage, but also by individual factors; A study conducted by Schredl et al. (2003) showed that personal factors such as visual memory, creativity, and even the attitude toward dreams can influence the

frequency of dream recall. Other studies also found gender, age and even personality traits to be associated with frequency and content of dream recall (Beaulieu-Prevost &, Zadra 2007). All these individual factors pose a serious challenge for emotional dream research, since it is difficult to compare individual dream reports between subjects.

Moreover, the methods that are used in a study can also influence the frequency of dream recall. First, studies found that the methodology of awakening participants can influence the characteristics of the dream reports (Zadra, & Robert, 2012; Schredl et al., 2003; Kahn, Stickgold, Pace-Schott, Hobson, 2000; Cohen, 1979; Goodenough, Lewis, Shapiro, Jaret, & Sleser, 1965). It

(9)

8

was found that gradual awakening compared to abrupt awakening changes the content of dream reports (Goodenough, Lewis, Shapiro, Jaret, & Sleser, 1965). Other studies found that the methodological manner in which the dream is recalled, changes the content that is recollected. For instance, studies showed that using guided recall, free recall, affirmative probes or

questionnaires to report the content of a dream, can change the content of the dream recall (Zadra, & Robert, 2012; Schredl et al., 2003; Kahn, Stickgold, Pace-Schott, Hobson, 2000; Cohen, 1979).

Defining Dreams in Emotional Dream Research

All in all, the literature basis shows some significant issues concerning the systematic investigation of recollection of emotional dreams. This is also caused by varying definitions on what constitutes a dream. Schredl (2014) defined that ‘dreams are subjective experiences during sleep, that are only accessible if the dreamer has a recollection of those experiences after awakening’. This definition leads researchers to mainly investigate REM-sleep related recalls, since these recalls are most likely to yield reported results. Similar issues exist with the simulation view as described by Windt et al. (2016). Dreams need to contain an immersive and story-like character by this definition and such dreams are most likely to occur during REM-sleep. Moreover, using this definition of dreams makes it difficult to identify individual factors that can influence dream recall. With such clear methodological implications for dream research, it seems that neither definition can completely grasp the full scope of dreams and allow researchers to investigate dreams in a systematic manner.

In sight of these methodological issues, a change in methodology needed to be made. Siclari et al. (2013) developed an approach for systematically investigating dream content and recall. Classical laboratory studies on dream recall used experimental paradigms with fixed awakening times that are related to sleep stage or amount of time in stage. Siclari et al. (2013) changed the methodology by developing a serial awakening paradigm. This serial awakening paradigm consists of a series of multiple questions that are performed irrespective of sleep stage, and at pseudorandom intervals. Moreover, participants are also questioned during wakefulness. This approach has several advantages over classical laboratory studies; 1) within-subject

comparisons of conscious experiences can be made more accurately because of the increased number of samples per subject, 2) dream research is not restricted by stages or awakenings but rather allows the researchers to exploit the entire variety of dream recollections during a night, and 3) the high costs from experimental research setups, such as those from fMRI studies and

(10)

9

high-density EEG recordings, are reduced because the number of experimental nights that are necessary for statistical validity can be decreased.

This research suggests that dreams can be defined as any consciousness occurring despite being immobile, unresponsive, whilst being largely disconnected from the environment (Siclari et al., 2017). If subjects report having an experience, upon awakening they are immediately asked to describe its content (‘the last thing going through your mind before the alarm sound’) and to rate it on a scale ranging from thought-like (‘thinking or reasoning, with no sensory content’) to perceptual experiences (‘vivid sensory content, without thinking or reasoning’). This approach enables the researchers to make distinctions between dreams with content and dreams without content. Additionally, it allows the researchers to systematically report immersive story-like dreams and dreams with only minimal vivid sensory content.

All in all, by using the approach and definition developed by Siclari et al. (2013) a significant part of methodological issues in emotional dream research can be overcome. This enables researchers to investigate the full scope of dream consciousness. Thus, emotional dreams should be defined as any consciousness related to emotional processes that are occurring whilst being immobile, unresponsive, or otherwise largely disconnected from the environment.

Taken all together, research on emotional dreams can yield interesting insights for researchers and clinicians. However, emotional dream research has had problems in defining dreams and with its methodological implementation. These problems can be overcome by a systematic approach to research. In this systematic approach emotional dreams should be defined as any consciousness related to emotional processes that are occurring whilst being immobile unresponsive or otherwise largely disconnected from the environment. With this definition in mind, the neural basis of the relation between dreams and emotions can be investigated.

The Anatomical Correlates of Emotional Dreams

Emotional processes during wakefulness are well investigated and a large amount of evidence already exists in linking specific brain regions to emotional processes. Moreover, the body of evidence that is already available, indicates that processes during wakefulness are also responsible for the neurophysiological background of dreaming (Vallat et al., 2018a., De Gennaro et al., 2016; Eichenlaub et al., 2014; De Gennaro et al., 2011). This next section will explore the commonalities between emotional processing and dreams. This will be investigated by firstly evaluating the evidence that shows the involvement of several brain regions in dream generation.

(11)

10

Secondly, the areas involved in emotional processing and their relations with dreaming will be discussed.

Anatomical Pathways involved in Dream Generation

The first studies involved in emotional dream research investigated the anatomical correlates of emotional dreams by examining evidence from brain lesions. The main findings from these studies show that two large systems are involved during dreaming. Lesions studies showed that the posterior system near the Temporo-Parieto-Occipital Junction (TPJ) can alter sleep imagery (Solms, 1997; Solms; 2000). Large lesions of the pontine brainstem eliminate all manifestations of REM sleep in domestic cats (Jones, 1979). Yet even with such lesions it seems that dreaming can occur albeit in other NREM states (Solms, 2000). Other lesions studies showed that the cholinergic brainstem mechanisms that control the REM state can generate the psychological phenomena of dreaming through the mediation of dopaminergic forebrain mechanisms (De Gennaro et al., 2016; Solms, 2000; Nausieda et al., 1982). The second, anterior system includes the ventromedial prefrontal cortex (vmPFC). Damage to the white matter

surrounding the anterior horns of the lateral ventricles are related to complete dream loss (Solms, 1997; Solms, 2000; Solms, 2011). These findings were corroborated by a study conducted by Yu (2007) that also implicated the role of the caudate nucleus in the functional architecture of dreaming.

These studies indicate two systems that are directly involved in generating dream content, but do not directly implicate the regions involved in the generation of emotional dreams.

Evidence from functional magnetic resonance imaging (fMRI) studies investigating the neural correlates of emotional processing, suggests that other brain regions are involved. Such studies have found that emotional memory encoding and consolidation occurs mostly in the limbic system, specifically in the hippocampal formation, the anterior cingulate cortex, and the amygdala (Armony, et al., 2013; Phelps and LeDoux, et al, 2005). These regions are mostly highly activated during REM-sleep. Evidence suggests that these structures may be directly responsible for the reprocessing and consolidation of emotional experiences during REM sleep (Hobson and Pace-Schott, 2002; van der Helm et al., 2011; Deliens et al., 2014). This indicates a direct relation with emotional dreams. Additionally, in other fMRI studies, it was shown that aversive stimuli evoke increased activity in the medial prefrontal cortex (mPFC) in individuals that experience frequent fear during dreams. In contrast, these individuals have a reduced activation in the insula,

(12)

11

the hypothesis that emotional expression is controlled by the mPFC inhibiting the amygdala and thereby reducing its activity (Phelps et al., 2004).

Insights from Emotional Disorders

In clinical research on attention deficit hyperactivity (ADHD) disorder, the relationship between amygdala and the medial prefrontal cortex is often investigated. ADHD is marked by emotional dysregulation (Shaw, Stringaris, Nigg, & Leibenluft, 2014). Therefore, investigating findings from such a field could provide a more accurate picture of the neural pathways involved in processing emotional content and emotional dreams.

Dysfunction of the frontal-striatal network - the network including amygdala,

hippocampus and the mPFC - has been thought to be of central importance to understanding ADHD (Castellanos & Proal, 2012; Cao et al, 2009; Wang et al., 2009). A functional connectivity study, looking at the connectedness between different brain regions, showed that adolescents diagnosed with ADHD have a decreased resting state functional connectivity in the frontal-striatal circuitry (Villemonteix et al., 2017). This indicates a decreased connection between these regions that could be responsible for the dysfunctional emotional regulation. Additionally, other fMRI studies show atypical increased effective connectivity between the lateral prefrontal cortex and the amygdala (Posner et al., 2011). Additionally, other studies indicated an increased

activation in frontal regions for patients with ADHD (Shaw et al., 2014; Posner et al., 2011). Since dream imagery can play a role in emotional processing, research on ADHD patients could be helpful in examining the dysfunctional way of processing of emotional content in dreams. A study from Schredl & Sartorius (2010) showed a direct relation between ADHD and altered emotional content in dreams. Results from this study showed that children with ADHD are more negatively toned and include more threats, negative endings, and physical aggression than healthy controls. Taken together, these findings indicate the involvement of a dysfunctional frontal-striatal network as an important feature of emotional dysregulation and altered emotional dream content (See Figure 2A). However, to my knowledge no fMRI studies have been conducted that show a direct relation between altered dream content and emotional dysregulation in ADHD. Future studies might look into this connection in more detail to explore such a relation and possibly identify the neural pathways involved in emotional processing of dreams.

When dreams are particularly high in negative emotional content, threats, and lead to severe stress in individuals they can be called nightmares (Macedo, Ferreira, Almondes, Kirov, & Mota-Rolim, 2019). Nightmares occur often during REM-sleep and subjects awakened from

(13)

12

nightmares often experience physical signs of stress and fear. Moreover, recurring nightmares have been found to decrease daily functioning by worsening the quality of sleep (Macedo et al., 2019). Nightmares are frequently present in the general population, affecting nearly 4–10% of individuals (Nielsen & Levin, 2007). Research has identified two different forms of nightmares: idiopathic and posttraumatic nightmares. Posttraumatic nightmares arise from the stress reaction that follows after exposure to a traumatic event. This form is most common in post-traumatic stress disorder (PTSD). On the other hand, idiopathic nightmares are those that have no relation to other disorders and its etiology are unknown (American Academy of Sleep Disorders, 2014).

Even though post-traumatic nightmares have various underlying causes, idiopathic nightmares originate in early childhood. A specific anatomical network seems to be involved in the generation of intense nightmares. These structures include the amygdala and the extension to the medial prefrontal cortex, the hippocampal complex and the anterior cingulate cortex (Hull, 2002). In research concerning nightmares, this network has been proposed to be involved in fear memory formation and extinction resulting from dysfunctional hippocampal-amygdala prefrontal circuit (Nielsen and Levin, 2007). This proposed network of brain regions implicated in the production and extinction of fear imagery during dreaming shows similar regions involved as patients with ADHD (See Figure 2A & 2B).

Findings from this research suggest that the frontal-striatal network is involved in general emotional processing, memory formation, and extinction. Moreover, the overlap of the brain regions involved in highly emotional dreams and in patients with ADHD indicates that these can be caused by the same underlying processes. These findings underline the importance of dream research, and that it can be considered as a window into the underlying processes of the human brain.

(14)

13

Figure 2a. The striatal network involved in emotional dysregulation for patients with ADHD. The

circuitry shows all the brain regions involved in the striatal network; The anterior insula (AI), amygdala (Am), dorsal anterior cingulate cortex (DACC), hypothalamus (Hy), inferotemporal Cortex (It), midbrain (Mb), and the temporoparietal junction (TPJ). This network is in turn mediated by the Medial Prefrontal Cortex. (Picture adapted from Hermans et al., 2014).

Figure 2b. Schematic representation of the frontal-striatal network proposed to be involved in generation

and extinction of fear imagery during dreams. (1) Contextual information is relayed via anterior hippocampus (aHip) to the amygdala (Am). (2) Medial prefrontal cortex (mPFC) and the anterior

cingulate cortex send signals to the amygdala and regulate the output of neurons to induce extinction and signal distress. (3) The caudate nucleus signals brainstem (Br) and hypothalamus (Hy) circuits, producing (4) the autonomic and behavioural correlates of fear within the dream. (Picture adapted from Nielsen & Levin,

(15)

14

Taken all together, it seems that the Temporo-Parieto-Occipital Junction (TPJ) together with the ventromedial prefrontal cortex (vmPFC) can generate the psychological phenomena of dreaming mediated by dopaminergic forebrain mechanisms. During emotional dreaming in particular the amygdala, thalamus and hippocampus are involved. Evidence that emotional dreams can have their anatomical roots in the frontal-striatal network is shown by deficits in this network by patients with ADHD as well as the involvement of this system in the generation of emotionally intense dreams such as nightmares.

Findings from these studies have pointed to specific anatomical regions in the brain. However, results from these studies have not been able to show a direct neural marker for the processing of emotions during dreams. Evidence from anatomical lesions or fMRI studies are scarce and do not lack capabilities to identify specific neural processes in real-time. Problems like these are exacerbated due to methodological constraints such as those described in the earlier section Methodological issues in emotional dream research. Other research designs that directly try to identify the neural markers of dreaming are setup with high-density EEG recordings. The next section will investigate the neural markers that can be identified when investigating emotional dreams.

The Neural Markers of Emotional Dreams

Studies looking at the temporal component instead of the spatial component of dreaming in the brain often revert to polysomnographic recordings, also known as EEG. As highlighted in the earlier section Methodological issues in emotional dream research most research has focused on dreams during REM sleep, therefore most examined research in this section will consists of studies conducted during REM sleep.

EEG correlates of Emotional Dreams

Studies looking into the EEG correlates of emotional dreams often operate under the assumption that dream recall is a peculiar form of declarative memory. This suggests that dreaming should share some of the electrophysiological mechanisms of the encoding of

(16)

15

memories in the awake brain. For instance, a study conducted by Nishida, Pearsall, Randy, Buckner and Walker (2009) showed that prefrontal theta activity was correlated with the extent of consolidated emotional memory. After a nap, participants recalled more negative emotional memories than neutral ones. Another study found that after awakening from REM sleep, higher frontal theta oscillations were associated with successful dream recall with emotional content (Marzano et al., 2011). A different study compared awakenings during REM sleep and slow wave sleep (Eichenlaub et al., 2018). In line with previous findings, the largest number of dream recalls from participants happened during REM sleep. They found that the number of references to recent waking-life experiences in REM dreams was positively correlated with frontal theta activity. In contrast, no correlation was observed for awakenings during slow wave sleep. Moreover, the waking-life experiences that were incorporated in the dreams were more emotional than those that were not

incorporated into the participants’ dreams. Next, a study conducted by Sopp et al. (2017) showed that emotional consolidation processes during REM and slow wave sleep has an effect on item and source memory of negative and neutral images. Emotional memory retention of such images is higher after late night REM sleep than during slow wave sleep. Moreover, this study showed that post-sleep emotional memory was correlated with frontal theta. Finally, another study conducted by Sopp et al. (2018) showed that this effect is specific to declarative memory and not associative memory.

Another suggested EEG marker of emotional processing during REM sleep is gamma activity. Gamma activity is suggested to be important for emotional processing through the

Figure 3. Different waveforms in the EEG, what are

they again?

Gamma waves are EEG waveform activity in the 30

– 80 cycles per second (cps) or 8 – 13 Hz range.

Alpha waves are EEG waveform activity in the 8 – 13

cps (8 – 13 Hz) range.

Theta waves are EEG waveform activity in the 4 - 7

cps (4 -7 Hz) range.

Delta waves are EEG waveform activity 0.5 – 3 cps

(17)

16

reduction of adrenergic activity in the brain. Specifically, gamma activity is implicated in the suppression of central adrenergic neurotransmitters, which are commonly associated with arousal and stress. These neurotransmitters are coupled with activation in the frontal-striatal networks encoding salient events. They are proposed to be crucial for reprocessing of previously affective experiences by decreasing their emotional intensity (Walker, & Van der Helm 2009; Maloney, Cape, Gotman, & Jones, 1997). A study investigating this relation sought to test the effects of REM sleep gamma on emotional processing (Van der Helm et al., 2011). This study showed that attenuation of emotional reactivity is related to mPFC connectivity and that this reduced

emotional reactivity is related to attenuated frontal gamma activity during REM sleep. Such findings suggest that adrenergic reduction during REM sleep is essential to emotional regulation. Moreover, it shows that gamma activity can be included as a potential research subject in

emotional dream studies because of its role in decreasing emotional intensity and defusing affective experiences. However, to my knowledge no studies currently exist that directly investigate the relation between dreams and gamma activity.

So far, findings from studies have clearly indicated a direct relation between prefrontal theta activity and emotional dreaming. Dream recall has a strong relation with recent waking-life experience with a highly negative component. These are most often present when prefrontal theta activity is seen in the EEG. Moreover, prefrontal theta is associated with high chance of successful dream recall with emotional content. Additionally, gamma activity has been found as a potential marker in the EEG for decreasing emotional intensity. Yet, studies have not

investigated this relation directly.

In the afore-mentioned studies, comparisons between dream recall during prefrontal theta activity and slow wave sleep were made. Prefrontal theta activity was associated with higher emotional dream recall when compared to slow wave sleep. This suggests a limited role of slow wave sleep for emotional dreams. Yet, findings from memory consolidation studies have clearly shown that slow wave sleep is crucial for emotional memory consolidation (Rasch, & Born, 2013; Sara, 2017; Talamini & Juan, 2020). Slow wave sleep may contribute to emotional processing of memories in various ways. Even though studies have not been conclusive, most evidence points to the reactivation of specific neural pathways that reactivate memory during NREM sleep. This emotional memory reactivation across several brain areas is suggested to be coordinated by slow oscillations, which are a hallmark of the onset of slow wave sleep in the EEG (Todorova & Zugaro, 2019; Girardeau, Inema, & Buzsáki, 2017). These emotional memory reactivations often involve the frontal-striatal network including the hippocampus, amygdala and neocortex. Acute emotional stressors during sleep cause an increase in slow wave sleep, where in contrast

(18)

17

emotional distress negatively influenced the distribution of REM sleep during a night (Talamini, Bringmann, De Boer, & Hofman, 2013).Therefore, it has been suggested that an increase in slow wave sleep could be associated with a decreased emotional valence for stimuli during sleep. Possibly, this could constitute an adaptive response by the brain to emotional stimuli (Talamini & Juan, 2020). Also, emotional memory consolidation has been investigated in children with

ADHD. In a study conducted by Prehn-Kristensen et al., (2013) children with ADHD were compared to healthy adults. Stimuli from the International Affective Picture System (IAPS) were presented before sleep and after morning awakening. Memory of these emotional pictures were tested and the results showed that slow oscillations during slow wave sleep were increased in children with ADHD compared with healthy adults. This shows that slow wave sleep could play a role in emotional processing and is dysfunctional in patients with ADHD.

At first glance, studies investigating slow wave sleep and theta activity show contrasting findings; results on one hand show that frontal theta activity is crucial for emotional dream recall compared with slow wave sleep. Yet, other results show that slow wave sleep is crucial for emotional memory consolidation. Moreover, earlier sections showed that dysfunctional

emotional processing in ADHD could be caused by the frontal-striatal network, coordinated by slow oscillations. These findings suggest that slow wave sleep is directly responsible for

emotional processing that occur during sleep. Since emotional dream research operates under the assumption that dream recall is a peculiar form of declarative memory- including emotional processes such as emotional memory consolidation- it seems that these results contradict each other. So how can findings from these different studies be reconciled?

How to Reconcile Findings from Emotional Dream Research?

Traditional emotional dream research has always focussed on researching by the classical division of sleep stages. Certain stages (e.g. slow wave sleep and REM) are compared with each other and differences in dream recalls are noted between the stages. As highlighted earlier in this thesis, several issues with this approach exist. In addition, comparing multiple stages during dream recall might also give rise to comparisons between stages that are not fully complete. For instance, it is well known that the distribution of activity per epoch in the EEG is not uniform; one epoch consists of several oscillatory frequencies usually containing theta, gamma and delta activity. It seems clear that during slow wave sleep and REM several oscillatory frequencies are happening at the same time in the brain. This means that during slow wave sleep other processes than those solely arising from slow oscillations take place. One example of such is shown by a

(19)

18

review study by Laventure & Benchenane (2020). They examined the role of sharp wave ripples that occur during slow oscillations. The study examined the interpretation that sharp‐waves ripples act as a form of replay of wake experiences. The evidence showed that the emotional valence is also replayed during sleep in a coordinated fashion with hippocampal sharp-waves ripples during slow oscillations.

Thus, during analyses conducted via this classical division of sleep stages, several

important features of brain activity are lost by the design of the experimental setup. For instance, when examining the relation between dreaming and theta activity, theta activity is almost always accompanied by other oscillatory frequencies in an epoch. This means that the specific relation between an oscillatory frequency of interest and the dream cannot be examined. This shows that within-and between subjects’ comparisons between specific oscillatory brain dynamics are difficult to perform. Even the developed serial awakening paradigm, that consists of a series of multiple questionings which are performed irrespective of sleep stage and at pseudorandom intervals (Siclari et al., 2013), has some issues with such comparisons. This experimental paradigm allows multiple sleep stages to be compared in one experimental setup. However, this paradigm cannot make a distinction between within-subject comparisons of dream recall and their

relationship with specific oscillatory brain dynamics in the EEG.

Evidence from studies indicate that specific oscillatory brain dynamics underly emotional processes. These processes are in turn crucial for the generation of emotional dreams. Since, research is currently unable to relate specific oscillatory activity to emotional dream recalls (e.g. by comparing one epoch of REM vs one epoch of NREM), it can’t be clearly stated that one

specific oscillatory frequency is a direct neural marker for emotional dreams. This could be one reason why results from different studies can’t yet be reconciled with each other. Therefore, it is important to investigate the relation between specific oscillatory mechanisms and emotional dreams in a systematic manner. In light of this, a novel methodological approach to identify the neural markers of emotional dreams needs to be developed.

A Novel Approach to Emotional Dream Research

So far, earlier sections of this thesis have examined the difficulties of determining a definition for dreaming, the methodological issues arising in the field of emotional dream

research, outlined the important anatomical regions involved in emotional processing and dream generation, and finally explored the neural markers that are associated with dreaming in the EEG. When taking all these findings together, the frontal-striatal network, including the hippocampus,

(20)

19

amygdala and medial prefrontal cortex are suggested to be particularly important for the generation of emotional dreams. Prefrontal theta in the mPFC can be considered as a neural marker of dreams. In addition, gamma activity causes an adrenergic response during REM sleep, that is essential to emotional regulation. Finally, slow oscillations are involved in coordinating emotional memory consolidation by affecting the amygdala and hippocampus.

Even though these relations between the neural correlates and the subjective experience of dreaming seem clear, they are difficult to prove during an experiment with a classical

laboratory setup. The classical division of sleep stages is not specific enough to grasp the full scope of dream recalls that are present during a night. These give rise to the problems with within-subject comparisons of dream recall related to specific neural markers; 1) classical

laboratory studies suffer from methodological issues that can only reliably investigate one specific sleep stage at a time, and 2) current pseudo randomized serial awakening paradigms can’t link specific neural markers to the dream recalls, since they are per definition randomized. Therefore, I propose a novel approach for the direction that dream researchers could take to systematically investigate dreams and links emotional dreams to specific neural processes.

New techniques and approaches are being developed in several sleep related research fields. The most promising one comes from manipulation of oscillatory brain dynamics during sleep through closed-loop acoustic stimulation (CLAS) (Talamini, & Koller, 2019; Ong et al., 2016; Ngo et al., 2015; Cox, Korjoukov, De Boer, & Talamini, 2014;). This technique entails the modelling of the oscillatory brain dynamics through an algorithm that performs fast spectral analysis. This algorithm can predict phases and send out stimuli at specific phases of ongoing oscillations. So far, CLAS has been used in experimental studies for the manipulation of oscillations. For instance, a study found that auditory stimuli targeted at the ‘up-phase’ (halfway of the up going phase of a slow oscillation) enhance the up-state of slow oscillations (Cox et al., 2014). Other studies also found that effects are locked to specific phases and showed that CLAS can increase slow wave amplitudes and occurrences when targeting the phase halfway the positive going slope of a slow oscillation (Talamini & Koller, 2019; Leminem et al., 2017; Talamini, van Poppel, Korjoukov, 2016; Santostasi et al., 2016; Ong et al., 2016; Ngo et al., 2015).

These findings clearly show the possibilities of this new technique in modelling and prediction of oscillatory brain dynamics. CLAS technique could also be considered in the

application for dream studies. CLAS has so far been applied to modelling and predicting specific oscillatory brain dynamics. This is in contrast with dream research, where one of the large issues is that researchers are not able to link specific oscillatory processes to having a dream. Therefore, combining the serial awakening paradigm (Siclari et al., 2013) with CLAS could be a solution for

(21)

20

this problem. When using CLAS techniques to accurately model and predict specific oscillatory frequencies (e.g. slow oscillations or theta activity), possibly even specific phases, a sound stimulus could be released that immediately awakens the sleeping participant and allows for the questioning of the related dream recall. Such a paradigm could accurately target specific

frequencies or waveforms and in turn identify their relations with subjective dream recalls (if any) that takes place at that specific moment. Such a paradigm is objective and could run regardless of sleep stage. For instance, it could possibly target theta frequencies that are normally associated only with REM during slow wave sleep or vice versa. This paradigm eliminates all other factors regarding sleep stages and allows for a more objective way of identifying neural markers related to dream recalls. See Figure 4 for a schematic illustration of this paradigm.

Figure 4. Schematic illustration of a possible setup with the serial awakening paradigm combined with closed-loop

acoustic stimulation. This paradigm is set to model slow oscillations, and green blocks represent time periods where slow oscillations occur (SO), Black bars in the blocks indicate a stimulation, slow oscillations are predicted by the algorithm and sound is immediately played awakening the sleeping participant. Black blocks represent periods of theta where the algorithm will not awaken participants. Final block represents a period in which there are a combination of dominant theta and slow oscillations occur during one period. The algorithm can still predict and awaken the participant during this time.

Of course, some caveats to the new possibilities of this technique also exist. To my knowledge and at the current date of writing, research on CLAS has only been used for predicting and stimulation of slow oscillations (Talamini & Koller, 2019; Leminem et al., 2017; Talamini, van Poppel, Korjoukov, 2016; Santostasi et al., 2016; Ong et al., 2016; Ngo et al., 2015). Even though the accuracy of closed loop auditory phase-targeting on slow oscillations is high,

(22)

21

extending this to other oscillatory frequencies might still be difficult. Faster frequencies such as theta or gamma require even faster modelling and predictions and this could not be available for some time. One additional limitation of this is that researchers would not know when they need to be ready for questioning participants and need to be fast and accurate in reporting the related dream recalls. However, these limitations could be overcome and should not withhold future studies from using this paradigm.

Taken together, future studies could use a combination of oscillatory predicting

algorithms to target neural markers in the brain. These could lead to an increased understanding of the neural markers that are involved in the generation of emotional dreams.

Conclusions

This research set out to investigate the neural basis of emotional dreaming and its methodology. In the first section, different definitions for dreams were discussed that are currently used by researchers. The available literature showed that many different definitions are used during experimental dream research. This research has argued that definitions such as those from Schredl et al. (2014) and Windt et al. (2016) are not sufficient enough to be used for

experimental dream researchers, due to the methodological implications that are involved. This can be overcome by a systematic approach to emotional dream research. In this systematic approach emotional dreams should be defined as any consciousness related to emotional processes that are occurring whilst being immobile unresponsive or otherwise largely disconnected from the environment.

Next, this paper set out to examine the anatomical correlates of dreams and emotions. It became clear that the Temporo-Parieto-Occipital Junction (TPJ) together with the ventromedial prefrontal cortex (vmPFC) can generate the psychological phenomena of dreaming mediated by dopaminergic forebrain mechanisms. During emotional dreaming in particular the amygdala, thalamus and hippocampus are involved. Evidence that emotional dreams can have their anatomical roots in the frontal-striatal network is shown by deficits in this network by patients with ADHD as well as the involvement of this system in the generation of emotionally intense dreams such as nightmares.

Following this, the neural markers of emotional dreaming in the EEG were discussed. Research indicated a direct relation between prefrontal theta activity and emotional dreaming. Dream recall seems to have a strong relation with recent waking-life experience with a highly

(23)

22

negative component. These are most often present when prefrontal theta activity is seen in the EEG. Moreover, prefrontal theta is associated with high chance of successful dream recall with emotional content. Moreover, prefrontal theta is associated with high chance of successful dream recall with emotional content. Additionally, gamma activity has been found as a potential marker in the EEG for decreasing emotional intensity. Yet, studies have not investigated this relation directly. In addition, slow oscillations coordinate emotional memory consolidation affecting the amygdala and hippocampus. These processes seem to be important for the generation of emotional dreams. However, current experimental paradigms can’t directly relate this activity to dreams.

Therefore, this research provided a new methodological approach for investigating emotional dreams. A new technique was proposed that uses modelling and prediction of

oscillatory brain dynamics. This closed-loop auditory stimulation technique should be considered in the application for dream studies in combination with a serial awakening paradigm (Siclari et al., 2013). CLAS could be used to identify specific neural markers to emotional dreams and reconcile findings that currently seem to be contradicting each other.

Taken together, this literature thesis has shown the important findings and developments on emotional dream research in the brain and showed that future studies could use a

combination of oscillatory predicting algorithms to target neural markers in the brain. This thesis has paved the way for future experiments to identify the neural markers of emotional dreams.

(24)

23

Literature

American Academy of Sleep Medicine (2014). International Classification of Sleep Disorders, 3rd Edn. Darien, IL: American Academy of Sleep Medicine

Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. Clinical psychology review, 30(2), 217-237.

Antrobus, J., Kondo, T., Reinsel, R., & Fein, G. (1995). Dreaming in the late morning: summation of REM and diurnal cortical activation. Conscious Cognition, 4, 99-275.

Braun, A.R. et al. (1997) Regional cerebral blood flow throughout the sleep-wake cycle. An H2(15)O PET study. Brain, 120, 1173–1197

Beaulieu-Prevost D., Zadra, A. (2007). Absorption, psychological boundaries, and attitude towards dreams as correlates of dream recall: two decades of research seen through a meta-analysis. Journal of Sleep Research, 16, 51-59.

Boyce, R., Glasgow, S. D., & Williams, S. (2016). Casual evidence for the role of REM sleep theta rhythm in contexual memory consolidaiton. Science, 352, 812–816.

Braver, T. S., Krug, M. K., Chiew, K. S., Kool, W., Westbrook, J. A., Clement, N. J., ... & Cools, R. (2014). Mechanisms of motivation–cognition interaction: challenges and

opportunities. Cognitive, Affective, & Behavioral Neuroscience, 14(2), 443-472.

Carskadon, M.A., & Dement, W.C. (2011). Monitoring and staging human sleep. In M.H. Kryger, T. Roth, & W.C. Dement (Eds.), Principles and practice of sleep medicine, 5, 16-26.

Castellanos F. X., & Proal E. (2012). Large-scale brain systems in ADHD: Beyond the prefrontal-striatal model. Trends in Cognitive Sciences.

Cavallero, C., Cicogna, P., Natale, V., Occhionero, M.,& Zito A. (1992). Slow wave sleep dreaming. Sleep, 15, 62, 6.

Cao, X., Cao Q., Long, X., Sun, L., Sui, M., & Zhu C. (2009). Abnormal resting-state functional connectivity patterns of the putamen in medication-naïve children with attention deficit

hyperactivity disorder. Brain Research.

Cipolli, C., Guazzelli, M., Bellucci, C., Mazzetti, M., Palagini, L., & Rosenlicht, N., (2015). Time-of-night variations in the story-like organization of dream experience developed during rapid eye movement sleep. Journal of Sleep Research, 24, 234-240.

(25)

24

Cipolli, C., Ferrara, M., De Gennaro, L., & Plazzi, G. (2017). Beyond the neuropsychology of dreaming: insights into the neural basis of dreaming with new techniques of sleep recording and analysis. Sleep medicine reviews, 35, 8-20.

Cohen D. B. (1979) Sleep and dreaming: origins, nature, and functions. Oxford, OX: Pergamon Press;

Compas, B. E., Jaser, S. S., Bettis, A. H., Watson, K. H., Gruhn, M. A., Dunbar, J. P., ... & Thigpen, J. C. (2017). Coping, emotion regulation, and psychopathology in childhood and adolescence: A meta-analysis and narrative review. Psychological bulletin, 143(9), 939.

Corsi-Cabrera, M., Velasco, F., Río-Portilla, Y., Armony, J. L., Trejo-Martínez, D., Guevara, M. A., et al. (2016), Human amygdala activation during rapid eye movements of rapid eye movement sleep: an intracranial study. Journal of Sleep Research. 25, 576–582.

Dang-Vu, T. T., McKinney, S. M., Buxton, O. M., Solet, J. M., & Ellenbogen, J. M. (2010). Spontaneous brain rhythms predict sleep stability in the face of noise. Current Biology, 20(15), R626-R627.

Eichenlaub, J. B., van Rijn, E., Gaskell, M. G., Lewis, P. A., Maby, E., Malinowski, J. E. & Blagrove, M. (2018). Incorporation of recent waking-life experiences in dreams correlates with frontal theta activity in REM sleep. Social cognitive and affective neuroscience, 13(6), 637-647.

Desseilles, M., Dang-Vu T. T., Sterpenich, V., Schwartz, S.. (2011). Cognitive and emotional processes during dreaming: a neuroimaging view. Conscious Cognition, 20, 998-1008.

De Gennaro L, Marzano, C., Moroni, F., Curcio, G., Ferrara, M., Cipolli, C (2010). Recovery sleep after sleep deprivation almost completely abolishes dream recall. Behavioural Brain Research; 206,293-298.

De Gennaro, L., Marzano, C., Cipolli, C., and Ferrara, M. (2012). How we remember the stuff that dreams are made of: neurobiological approaches to the brain mechanisms of dream recall. Behavioural Brain Research. 226, 592–596.

De Gennaro, L., Lanteri, O., Piras, F., Scarpelli, S., Assogna, F., Ferrara, M., et al. (2016). Dopaminergic system and dream recall: an MRI study in Parkinson’s disease patients. Human Brain Mapping. 37, 1136–1147.

de Wild-Hartmann, J. A., Wichers, M., van Bemmel, A. L., Derom, C., Thiery, E., Jacobs, N., ... & Simons, C. J. (2013). Day-to-day associations between subjective sleep and affect in regard to

(26)

25

future depressionin a female population-based sample. The British Journal of Psychiatry, 202(6), 407-412.

Domhoff, G. W. (1996). Finding meaning in dreams: A quantitative approach. Springer Science & Business Media.

Eichenlaub, J. B., Nicolas, A., Daltrozzo, J., Redout,é, J., Costes, N., and Ruby, P. (2014). Resting brain activity varies with dream recall frequency between subjects. Neuropsychopharmacology 39, 1594–1602.

Flanagan, O. (2001) Dreaming Souls: Sleep, Dreams, and the Evolution of the Conscious Mind, Oxford University Press

Foulkes, D. (1962) Dream reports from different stages of sleep. Journal of Abnormal Social Psychology 65, 14–25

Francx, W., Oldehinkel, M., Oosterlaan, J., Heslenfeld, D., Hartman, C. A., Hoekstra, P. J., ... & Mennes, M. (2015). The executive control network and symptomatic improvement in attention-deficit/hyperactivity disorder. Cortex, 73, 62-72.

Goodenough, D. R., Lewis, H. B., Shapiro, A., Jaret, L., & Sleser, I. (1965). Dream reporting following abrupt and gradual awakenings from different types of sleep. Journal of Personality and Social Psychology, 2(2), 170

Girardeau, G., Inema, I., & Buzsáki, G. (2017). Reactivations of emotional memory in the hippocampus–amygdala system during sleep. Nature Neuroscience, 20(11), 1634.

Gratz, K. L., Weiss, N. H., & Tull, M. T. (2015). Examining emotion regulation as an outcome, mechanism, or target of psychological treatments. Current opinion in psychology, 3, 85-90.

Hobson, J. A., Pace-Schott, E. F., & Stickgold, R. (2000). Dreaming and the brain: toward a cognitive neuroscience of conscious states. Behavioral and brain sciences, 23(6), 793-842.

Hermans, E. J., Henckens, M. J., Joëls, M., & Fernández, G. (2014). Dynamic adaptation of large-scale brain networks in response to acute stressors. Trends in neurosciences, 37(6), 304-314.

Hull, A. M. (2002). Neuroimaging findings in post-traumatic stress disorder: Systematic review. The British journal of psychiatry, 181(2), 102-110.

Iber, C., Ancoli-Israel, S., Chesson, A. L., & Quan, S. F. (2007). The AASM manual for the scoring of sleep and associated events: rules, terminology and technical specifications (Vol. 1). Westchester, IL: American Academy of Sleep Medicine.

(27)

26

Kahn, D., Stickgold, R., Pace‐Schott, E. F., & Hobson, J. A. (2000). Dreaming and waking consciousness: a character recognition study. Journal of Sleep Research, 9(4), 317-325. Laventure, S., & Benchenane, K. (2020). Validating the theoretical bases of sleep reactivation during sharp‐wave ripples and their association with emotional valence. Hippocampus.

Lee, J. L., Everitt, B. J., & Thomas, K. L. (2004). Independent cellular processes for hippocampal memory consolidation and reconsolidation. Science, 304(5672), 839-843.

Leibenluft, E. (2011). Severe mood dysregulation, irritability, and the diagnostic boundaries of bipolar disorder in youths. American Journal of Psychiatry, 168(2), 129-142.

Leminen, M. M., Virkkala, J., Saure, E, Paajanen, T., Zee, P. C., Santostasi, G, Hublin, C., Müller, K., Porkka-Heiskanen, T., Huotilainen, M., Paunio, T., (2017). Enhanced Memory Consolidation Via Automatic Sound Stimulation During Non-REM Sleep. Sleep, Volume 40, 3.

Macedo, T. C. F., Ferreira, G. H., Almondes, K. M. D., Kirov, R., & Mota-Rolim, S. A. (2019). My dream, my rules: can lucid dreaming treat nightmares?. Frontiers in Psychology, 10, 2618.

Malinowski, J., & Horton, C. L. (2014). Evidence for the preferential incorporation of emotional waking-life experiences into dreams. Dreaming, 24(1), 18.

Maloney, K. J., Cape, E. G., Gotman, J., & Jones, B. E. (1997). High-frequency γ

electroencephalogram activity in association with sleep-wake states and spontaneous behaviors in the rat. Neuroscience, 76(2), 541-555.

Maquet, P. et al. (1996) Functional neuroanatomy of human rapideye-movement sleep and dreaming. Nature 383, 163–166

Maquet, P., Laureys, S., Peigneux, P., Fuchs, S., Petiau, C., Phillips, C., ... & Luxen, A. (2000). Experience-dependent changes in cerebral activation during human REM sleep. Nature neuroscience, 3(8), 831-836.

Maquet, P. (2000). Functional neuroimaging of normal human sleep by positron emission tomography. Journal of sleep research, 9(3), 207-232.

Marzano, C., Ferrara, M., Mauro, F., Moroni, F., Gorgoni, M., Tempesta, D., ... & De Gennaro, L. (2011). Recalling and forgetting dreams: theta and alpha oscillations during sleep predict subsequent dream recall. Journal of Neuroscience, 31(18), 6674-6683.

(28)

27

Mazefsky, C. A., Yu, L., & Pilkonis, P. A. (2020). Psychometric properties of the Emotion Dysregulation Inventory in a nationally representative sample of youth. Journal of Clinical Child & Adolescent Psychology, 1-13.

Monroe, L. J., Rechtschaffen, A., Foulkes, D., & Jensen, J. (1965). Discriminability of REM and NREM reports. Journal of Personality and Social Psychology, 2(3), 456.

Nakajima, S., Inoue, Y., Sasai, T., Okajima, I., Komada, Y., Nomura, T., & Takahashi, K. (2014). Impact of frequency of nightmares comorbid with insomnia on depression in Japanese rural community residents: a cross-sectional study. Sleep medicine, 15(3), 371-374.

Nausieda, P. A., Weiner, W. J., Kaplan, L. R., Weber, S., & Klawans, H. L. (1982). Sleep

disruption in the course of chronic levodopa therapy: an early feature of the levodopa psychosis. Clinical neuropharmacology, 5(2), 183-194.

Ngo, H.-V. V., Miedema, A., Faude, I., Martinetz, T., Molle, M., & Born, J. (2015). Driving Sleep Slow Oscillations by Auditory Closed-Loop Stimulation--A Self-Limiting Process. Journal of Neuroscience, 35(17), 6630–6638.

Nielsen, T. A. (2000). A review of mentation in REM and NREM sleep:“covert” REM sleep as a possible reconciliation of two opposing models. Behavioral and Brain Sciences, 23(6), 851-866. Nielsen, T. A., & Stenstrom, P. (2005). What are the memory sources of dreaming?. Nature, 437 (7063), 1286-1289.

Nielsen, T., & Levin, R. (2007). Nightmares: a new neurocognitive model. Sleep medicine reviews, 11(4), 295-310.

Nishida, M., Pearsall, J., Buckner, R. L., & Walker, M. P. (2009). REM sleep, prefrontal theta, and the consolidation of human emotional memory. Cerebral cortex, 19(5), 1158-1166.

Nofzinger, E. A., Mintun, M. A., Wiseman, M., Kupfer, D. J., & Moore, R. Y. (1997). Forebrain activation in REM sleep: an FDG PET study. Brain research, 770(1-2), 192-201.

Noreika, V., Valli, K., Lahtela, H., & Revonsuo, A. (2009). Early-night serial awakenings as a new paradigm for studies on NREM dreaming. International Journal of Psychophysiology, 74(1), 14-18. Nir, Y., & Tononi, G. (2010). Dreaming and the brain: from phenomenology to neurophysiology. Trends in cognitive sciences, 14(2), 88-100.

(29)

28

Ong, J. L., Lo, J. C., Chee, N. I. Y. N., Santostasi, G., Paller, K. A., Zee, P. C., & Chee, M. W. L. (2016). Effects of phase-locked acoustic stimulation during a nap on EEG spectra and declarative memory consolidation. Sleep Medicine, 20, 88–97.

Panoz-Brown, D., Iyer, V., Carey, L. M., Sluka, C. M., Rajic, G., Kestenman, J., & Tucker, K. G. (2018). Replay of episodic memories in the rat. Current Biology, 28(10), 1628-1634.

Popp, C. A., Diguer, L., Luborsky, L., Faude, J., Johnson, S., Morris, M., ... & Schmidt, K. (1996). Repetitive relationship themes in waking narratives and dreams. Journal of Consulting and Clinical Psychology, 64(5), 1073.

Posner, J., Nagel, B. J., Maia, T. V., Mechling, A., Oh, M., Wang, Z., & Peterson, B. S. (2011). Abnormal amygdalar activation and connectivity in adolescents with

attention-deficit/hyperactivity disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 50(8), 828-837.

Phelps, E. A., & LeDoux, J. E. (2005). Contributions of the amygdala to emotion processing: from animal models to human behavior. Neuron, 48(2), 175-187.

Prehn-Kristensen, A., Munz, M., Molzow, I., Wilhelm, I., Wiesner, C. D., & Baving, L. (2013). Sleep promotes consolidation of emotional memory in healthy children but not in children with attention-deficit hyperactivity disorder. PLoS One, 8(5).

Rasch, B., & Born, J. (2013). About sleep's role in memory. Physiological reviews, 93(2), 681-766. Santostasi, G., Malkani, R., Riedner, B., Bellesi, M., Tononi, G., Paller, K., & Zee, P. (2016). Phase-locked loop for precisely timed acoustic stimulation during sleep. Journal Of Neuroscience

Methods, 259, 101-114.

Sara, S. J. (2017). Sleep to remember. Journal of Neuroscience, 37(3), 457-463.

Saper, C. B., Fuller, P. M., Pedersen, N. P., Lu, J., & Scammell, T. E. (2010). Sleep state switching. Neuron, 68(6), 1023-1042.

Siclari, F., LaRocque, J. J., Postle, B. R., & Tononi, G. (2013). Assessing sleep consciousness within subjects using a serial awakening paradigm. Frontiers in psychology, 4, 542.

Siclari, F., Baird, B., Perogamvros, L., Bernardi, G., LaRocque, J. J., Riedner, B., ... & Tononi, G. (2017). The neural correlates of dreaming. Nature neuroscience, 20(6), 872.

Sjöström, N., Hetta, J., & Waern, M. (2009). Persistent nightmares are associated with repeat suicide attempt: a prospective study. Psychiatry Research, 170(2-3), 208-211.

(30)

29

Sloan, E., Hall, K., Moulding, R., Bryce, S., Mildred, H., & Staiger, P. K. (2017). Emotion regulation as a transdiagnostic treatment construct across anxiety, depression, substance, eating and borderline personality disorders: A systematic review. Clinical psychology review, 57, 141-163.

Schredl M (2014). Sleep and dreaming. In: Bassetti CL, Dogas Z, Peigneux P (eds) ESRS European sleep medicine textbook. European Sleep Resarch Society, Regensburg, pp 63–71

Schredl, M., Hoffmann, L., Sommer, J. U., & Stuck, B. A. (2014). Olfactory stimulation during sleep can reactivate odor-associated images. Chemosensory Perception, 7(3-4), 140-146.

Schredl, M., & Sartorius, H. (2010). Dream recall and dream content in children with attention deficit/hyperactivity disorder. Child psychiatry & human development, 41(2), 230-238.

Schredl, M. (2009). Nightmare frequency in patients with primary insomnia. Universitätsbibliothek der Universität Heidelberg.

Schredl, M., Wittmann, L., Ciric, P., & GÖtz, S. (2003). Factors of home dream recall: a structural equation model. Journal of Sleep Research, 12(2), 133-141.

Shaw, P., Stringaris, A., Nigg, J., & Leibenluft, E. (2014). Emotion dysregulation in attention deficit hyperactivity disorder. American Journal of Psychiatry, 171(3), 276-293.

Solms, M. (1997). The Neuropsychology of Dreams: A Clinico-anatomical Study. Hillsdale, NJ: Erlbaum.

Solms, M. (2000). Dreaming and REM sleep are controlled by different brain mechanisms. Behavioral and Brain Sciences, 23(6), 843-850.

Solms, M. (2011). Neurobiology and the neurological basis of dreaming. In Handbook of clinical

neurology (Vol. 98, pp. 519-544). Elsevier.

Sopp, M. R., Michael, T., & Mecklinger, A. (2018). Effects of early morning nap sleep on associative memory for neutral and emotional stimuli. Brain research, 1698, 29-42.

Sopp, M. R., Michael, T., Weeß, H. G., & Mecklinger, A. (2017). Remembering specific features of emotional events across time: The role of REM sleep and prefrontal theta

oscillations. Cognitive, Affective, & Behavioral Neuroscience, 17(6), 1186-1209.

Sterpenich, V., Perogamvros, L., Tononi, G., & Schwartz, S. (2020). Fear in dreams and in wakefulness: Evidence for day/night affective homeostasis. Human Brain Mapping, 41(3), 840-850.

(31)

30

Taub, J. M. (1971). Dreams recalled spontaneously following afternoon naps and nocturnal sleep. Journal of abnormal psychology, 78(2), 229.

Talamini, L. M., Bringmann, L. F., de Boer, M., & Hofman, W. F. (2013). Sleeping worries away or worrying away sleep? Physiological evidence on sleep-emotion interactions. PloS one, 8(5). Talamini, L.M, van Poppel E.A.M., Korjoukov, I. (2016) . Hitting the right spot: A new closed-loop stimulation procedure for oscillatory phase targeting. ESRS conference, 13-16 Sept, Bologna.

Talamini, L. M., & Juan, E (2020). Sleep as a window to treat affective disorders. Current Opinion in Behavioural Science, 33, 99-108.

Tempesta, D., Socci, V., De Gennaro, L., & Ferrara, M. (2018). Sleep and emotional processing. Sleep medicine reviews, 40, 183-195.

Tempesta, D., De Gennaro, L., Natale, V., & Ferrara, M. (2015). Emotional memory processing is influenced by sleep quality. Sleep medicine, 16(7), 862-870.

Todorova, R., & Zugaro, M. (2019). Isolated cortical computations during delta waves support memory consolidation. Science, 366(6463), 377-381.

Van Der Helm, E., Yao, J., Dutt, S., Rao, V., Saletin, J. M., & Walker, M. P. (2011). REM sleep depotentiates amygdala activity to previous emotional experiences. Current Biology, 21(23), 2029-2032.

Villemonteix, T., Marx, I., Septier, M., Berger, C., Hacker, T., Bahadori, S., ... & Massat, I. (2017). Attentional control of emotional interference in children with ADHD and typically developing children: an emotional N-back study. Psychiatry research, 254, 1-7.

Walker, M. P., & van Der Helm, E. (2009). Overnight therapy? The role of sleep in emotional brain processing. Psychological bulletin, 135(5), 731.

Wang, L., Zhu, C., He, Y., Zang, Y., Cao, Q., Zhang, H., ... & Wang, Y. (2009). Altered small‐ world brain functional networks in children with attention‐deficit/hyperactivity disorder. Human

brain mapping, 30(2), 638-649.

Wamsley, E. J., Hirota, Y., Tucker, M. A., Smith, M. R., & Antrobus, J. S. (2007). Circadian and ultradian influences on dreaming: A dual rhythm model. Brain Research Bulletin, 71(4), 347-354. Windt, J. M., Nielsen, T., & Thompson, E. (2016). Does consciousness disappear in dreamless sleep?. Trends in cognitive sciences, 20(12), 871-882.

(32)

31

Windt, J. M. (2018). Predictive brains, dreaming selves, sleeping bodies: how the analysis of dream movement can inform a theory of self-and world-simulation in dreams. Synthese, 195(6), 2577-2625.

Yu, C. K. C. (2007). Cessation of dreaming and ventromesial frontal-region infarcts. Neuropsychoanalysis, 9(1), 83-90.

Zadra, A., & Robert, G. (2012). Dream recall frequency: Impact of prospective measures and motivational factors. Consciousness and cognition, 21(4), 1695-1702.