Dreaming in NREM Sleep: A High-Density EEG Study of Slow Waves and Spindles

Consciousness in non-REM-parasomnia episodes

Sleepwalking and related parasomnias are thought to result from incomplete awakenings out of non-rapid eye movement (non-REM) sleep. Non-REM parasomnia behaviours have been described as unconscious and automatic, or related to vivid, dream-like conscious experiences. Similarly, some observations have suggested that patients are unresponsive during episodes, while others that they can interact with their surroundings. To better grasp and characterise the full spectrum of consciousness and environmental (dis)connection associated with behavioural episodes, 35 adult patients with non-REM sleep parasomnias were interviewed in-depth about their experiences. The level of consciousness during parasomnia episodes was reported to be variable both within and between individuals, ranging from minimal or absent consciousness and largely automatic behaviours (frequently/always present in 36% of patients) to preserved conscious experiences characterised by delusional thinking to varying degrees of specificity (65%), often about impending danger, variably formed, uni- or multisensory hallucinations (53%), impaired insight (77%), negative emotions (75%), and variable, but often pronounced, amnesia (30%). Patients described their experiences as a dream scene during which they felt awake ("awake dreaming"). The surroundings were either realistically perceived, misinterpreted (in the form of perceptual illusions or misidentifications of people), or entirely hallucinated as a function of the prevailing delusion. These observations suggest that the level of consciousness, amnesia and sensory disconnection during non-REM parasomnia episodes is variable and graded. In their full-fledged expression, non-REM parasomnia experiences feature several core features of dreams. They therefore represent a valuable model for the study of consciousness, sleep-related sensory disconnection and dreaming.

Enhancing and advancing the understanding and study of dreaming and memory consolidation: Reflections, challenges, theoretical clarity, and methodological considerations

Empirical investigations that search for a link between dreaming and sleep-dependent memory consolidation have focused on testing for an association between dreaming of what was learned, and improved memory performance for learned material. Empirical support for this is mixed, perhaps owing to the inherent challenges presented by the nature of dreams, and methodological inconsistencies. The purpose of this paper is to address critically prevalent assumptions and practices, with the aim of clarifying and enhancing research on this topic, chiefly by providing a theoretical synthesis of existing models and evidence. Also, it recommends the method of Targeted Memory Reactivation (TMR) as a means for investigating if dream content can be linked to specific cued activations. Other recommendations to enhance research practice and enquiry on this subject are also provided, focusing on the HOW and WHY we search for memory sources in dreams, and what purpose (if any) they might serve.

Consciousness and sleep

Sleep is a universal, essential biological process. It is also an invaluable window on consciousness. It tells us that consciousness can be lost but also that it can be regained, in all its richness, when we are disconnected from the environment and unable to reflect. By considering the neurophysiological differences between dreaming and dreamless sleep, we can learn about the substrate of consciousness and understand why it vanishes. We also learn that the ongoing state of the substrate of consciousness determines the way each experience feels regardless of how it is triggered-endogenously or exogenously. Dreaming consciousness is also a window on sleep and its functions. Dreams tell us that the sleeping brain is remarkably lively, recombining intrinsic activation patterns from a vast repertoire, freed from the requirements of ongoing behavior and cognitive control.

Shared EEG correlates between non-REM parasomnia experiences and dreams

Sleepwalking and related parasomnias result from incomplete awakenings out of non-rapid eye movement sleep. Behavioral episodes can occur without consciousness or recollection, or in relation to dream-like experiences. To understand what accounts for these differences in consciousness and recall, here we recorded parasomnia episodes with high-density electroencephalography (EEG) and interviewed participants immediately afterward about their experiences. Compared to reports of no experience (19%), reports of conscious experience (56%) were preceded by high-amplitude EEG slow waves in anterior cortical regions and activation of posterior cortical regions, similar to previously described EEG correlates of dreaming. Recall of the content of the experience (56%), compared to no recall (25%), was associated with higher EEG activation in the right medial temporal region before movement onset. Our work suggests that the EEG correlates of parasomnia experiences are similar to those reported for dreams and may thus reflect core physiological processes involved in sleep consciousness.

Human Prosocial Preferences Are Related to Slow-Wave Activity in Sleep

Prosocial behavior is crucial for the smooth functioning of the society. Yet, individuals differ vastly in the propensity to behave prosocially. Here, we try to explain these individual differences under normal sleep conditions without any experimental modulation of sleep. Using a portable high-density EEG, we measured the sleep data in 54 healthy adults (28 females) during a normal night's sleep at the participants' homes. To capture prosocial preferences, participants played an incentivized public goods game in which they faced real monetary consequences. The whole-brain analyses showed that a higher relative slow-wave activity (SWA, an indicator of sleep depth) in a cluster of electrodes over the right temporoparietal junction (TPJ) was associated with increased prosocial preferences. Source localization and current source density analyses further support these findings. Recent sleep deprivation studies imply that sleeping enough makes us more prosocial; the present findings suggest that it is not only sleep duration, but particularly sufficient sleep depth in the TPJ that is positively related to prosociality. Because the TPJ plays a central role in social cognitive functions, we speculate that sleep depth in the TPJ, as reflected by relative SWA, might serve as a dispositional indicator of social cognition ability, which is reflected in prosocial preferences. These findings contribute to the emerging framework explaining the link between sleep and prosocial behavior by shedding light on the underlying mechanisms.

Influencing dreams through sensory stimulation: A systematic review

Sleep is typically considered a state of disconnection from the environment, yet instances of external sensory stimuli influencing dreams have been reported for centuries. Explaining this phenomenon could provide valuable insight into dreams' generative and functional mechanisms, the factors that promote sleep continuity, and the processes that underlie conscious awareness. Moreover, harnessing sensory stimuli for dream engineering could benefit individuals suffering from dream-related alterations. This PRISMA-compliant systematic review assessed the current evidence concerning the influence of sensory stimulation on sleep mentation. We included 51 publications, of which 21 focused on auditory stimulation, ten on somatosensory stimulation, eight on olfactory stimulation, four on visual stimulation, two on vestibular stimulation, and one on multimodal stimulation. Furthermore, nine references explored conditioned associative stimulation: six focused on targeted memory reactivation protocols and three on targeted lucid reactivation protocols. The reported frequency of stimulus-dependent dream changes across studies ranged from 0 to ∼80%, likely reflecting a considerable heterogeneity of definitions and methodological approaches. Our findings highlight a lack of comprehensive understanding of the mechanisms, functions, and neurophysiological correlates of stimulus-dependent dream changes. We suggest that a paradigm shift is required for meaningful progress in this field.

Mapping of the central sulcus using non-invasive ultra-high-density brain recordings

Brain mapping is vital in understanding the brain's functional organization. Electroencephalography (EEG) is one of the most widely used brain mapping approaches, primarily because it is non-invasive, inexpensive, straightforward, and effective. Increasing the electrode density in EEG systems provides more neural information and can thereby enable more detailed and nuanced mapping procedures. Here, we show that the central sulcus can be clearly delineated using a novel ultra-high-density EEG system (uHD EEG) and somatosensory evoked potentials (SSEPs). This uHD EEG records from 256 channels with an inter-electrode distance of 8.6 mm and an electrode diameter of 5.9 mm. Reconstructed head models were generated from T1-weighted MRI scans, and electrode positions were co-registered to these models to create topographical plots of brain activity. EEG data were first analyzed with peak detection methods and then classified using unsupervised spectral clustering. Our topography plots of the spatial distribution from the SSEPs clearly delineate a division between channels above the somatosensory and motor cortex, thereby localizing the central sulcus. Individual EEG channels could be correctly classified as anterior or posterior to the central sulcus with 95.2% accuracy, which is comparable to accuracies from invasive intracranial recordings. Our findings demonstrate that uHD EEG can resolve the electrophysiological signatures of functional representation in the brain at a level previously only seen from surgically implanted electrodes. This novel approach could benefit numerous applications, including research, neurosurgical mapping, clinical monitoring, detection of conscious function, brain-computer interfacing (BCI), rehabilitation, and mental health.

The neurocognition of dreaming: key questions and foci

Until recently, understanding the neurobiology of dreaming has relied upon on correlating a subjective dream report with a measure of brain activity or function sampled from a different occasion. As such, most assumptions about dreaming come from the neuroscience of rapid eye-movement (REM) sleep from which many, but not all, dream reports are recalled. Core features of REM sleep (intense emotional activation, a reduction in activity in most frontal regions, particularly the dorsolateral prefrontal cortex, along with increased dopamine, acetylcholine, cholinergic activation) align with typical dream characteristics (characterised by fear, reduced reality monitoring, increased bizarreness and hyperassociativity, respectively). The default mode network offers a way of understanding the nature of dreaming more independently from a REM sleep context, and electroencephalography methods paired with serial awakenings to elicit dream reports demonstrate how high-frequency activity in posterior regions may be associated with dreaming. Nevertheless, all measures of dreaming rely fundamentally on recall processes, so our understanding of dreaming must embrace and address memory's crucial involvement in dream report production.

A meta-analysis of the relation between dream content and memory consolidation

The frequent appearance of newly learned information in dreams suggests that dream content is influenced by memory consolidation. Many studies have tested this hypothesis by asking whether dreaming about a learning task is associated with improved memory, but results have been inconsistent. We conducted a meta-analysis to determine the strength of the association between learning-related dreams and post-sleep memory improvement. We searched the literature for studies that (1) trained participants on a pre-sleep learning task and then tested their memory after sleep, and (2) associated post-sleep memory improvement with the extent to which dreams incorporated learning task content. Sixteen studies qualified for inclusion, which together reported 45 effects. Integrating across effects, we report a strong and statistically significant association between task-related dreaming and memory performance (SMD = 0.51 [95% CI 0.28, 0.74], p < 0.001). Among studies using polysomnography, this relationship was statistically significant for dreams collected from non-rapid eye movement (NREM) sleep (n = 10) but not for dreams collected from rapid eye movement (REM) sleep (n = 12). There was a significant association between dreaming and memory for all types of learning tasks studied. This meta-analysis provides further evidence that dreaming about a learning task is associated with improved memory performance, suggesting that dream content may be an indication of memory consolidation. Furthermore, we report preliminary evidence that the relationship between dreaming and memory may be stronger in NREM sleep compared to REM.

Dusk2Dawn: an EEGLAB plugin for automatic cleaning of whole-night sleep electroencephalogram using Artifact Subspace Reconstruction

Whole-night sleep electroencephalogram (EEG) is plagued by several types of large-amplitude artifacts. Common approaches to remove them are fraught with issues: channel interpolation, rejection of noisy intervals, and independent component analysis are time-consuming, rely on subjective user decisions, and result in signal loss. Artifact Subspace Reconstruction (ASR) is an increasingly popular approach to rapidly and automatically clean wake EEG data. Indeed, ASR adaptively removes large-amplitude artifacts regardless of their scalp topography or consistency throughout the recording. This makes ASR, at least in theory, a highly-promising tool to clean whole-night EEG. However, ASR crucially relies on calibration against a subset of relatively clean "baseline" data. This is problematic when the baseline changes substantially over time, as in whole-night EEG data. Here we tackled this issue and, for the first time, validated ASR for cleaning sleep EEG. We demonstrate that ASR applied out-of-the-box, with the parameters recommended for wake EEG, results in the dramatic removal of slow waves. We also provide an appropriate procedure to use ASR for automatic and rapid cleaning of whole-night sleep EEG data or any long EEG recording. Our procedure is freely available in Dusk2Dawn, an open-source plugin for EEGLAB.

The nature of consciousness in anaesthesia

Neuroscientists agree on the value of locating the source of consciousness within the brain. Anaesthesiologists are no exception, and have their own operational definition of consciousness based on phenomenological observations during anaesthesia. The full functional correlates of consciousness are yet to be precisely identified, however rapidly evolving progress in this scientific domain has yielded several theories that attempt to model the generation of consciousness. They have received variable support from experimental observations, including those involving anaesthesia and its ability to reversibly modulate different aspects of consciousness. Aside from the interest in a better understanding of the mechanisms of consciousness, exploring the functional tenets of the phenomenological consciousness states of general anaesthesia has the potential to ultimately improve patient management. It could facilitate the design of specific monitoring devices and approaches, aiming at reliably detecting each of the possible states of consciousness during an anaesthetic procedure, including total absence of mental content (unconsciousness), and internal awareness (sensation of self and internal thoughts) with or without conscious perception of the environment (connected or disconnected consciousness, respectively). Indeed, it must be noted that unresponsiveness is not sufficient to infer absence of connectedness or even absence of consciousness. This narrative review presents the current knowledge in this field from a system-level, underlining the contribution of anaesthesia studies in supporting theories of consciousness, and proposing directions for future research.

An evidence-based critical review of the mind-brain identity theory

In the philosophy of mind, neuroscience, and psychology, the causal relationship between phenomenal consciousness, mentation, and brain states has always been a matter of debate. On the one hand, material monism posits consciousness and mind as pure brain epiphenomena. One of its most stringent lines of reasoning relies on a 'loss-of-function lesion premise,' according to which, since brain lesions and neurochemical modifications lead to cognitive impairment and/or altered states of consciousness, there is no reason to doubt the mind-brain identity. On the other hand, dualism or idealism (in one form or another) regard consciousness and mind as something other than the sole product of cerebral activity pointing at the ineffable, undefinable, and seemingly unphysical nature of our subjective qualitative experiences and its related mental dimension. Here, several neuroscientific findings are reviewed that question the idea that posits phenomenal experience as an emergent property of brain activity, and argue that the premise of material monism is based on a logical correlation-causation fallacy. While these (mostly ignored) findings, if considered separately from each other, could, in principle, be recast into a physicalist paradigm, once viewed from an integral perspective, they substantiate equally well an ontology that posits mind and consciousness as a primal phenomenon.

Sleep and the hypothalamus

Neural substrates of wakefulness, rapid eye movement sleep (REMS), and non-REMS (NREMS) in the mammalian hypothalamus overlap both anatomically and functionally with cellular networks that support physiological and behavioral homeostasis. Here, we review the roles of sleep neurons of the hypothalamus in the homeostatic control of thermoregulation or goal-oriented behaviors during wakefulness. We address how hypothalamic circuits involved in opposing behaviors such as core body temperature and sleep compute conflicting information and provide a coherent vigilance state. Finally, we highlight some of the key unresolved questions and challenges, and the promise of a more granular view of the cellular and molecular diversity underlying the integrative role of the hypothalamus in physiological and behavioral homeostasis.

REM-OSA as a Tool to Understand Both the Architecture of Sleep and Pathogenesis of Sleep Apnea-Literature Review

Sleep is a complex physiological state, which can be divided into the non-rapid eye movement (NREM) phase and the REM phase. Both have some unique features and functions. This difference is best visible in electroencephalography recordings, respiratory system activity, arousals, autonomic nervous system activity, or metabolism. Obstructive sleep apnea (OSA) is a common condition characterized by recurrent episodes of pauses in breathing during sleep caused by blockage of the upper airways. This common condition has multifactorial ethiopathogenesis (e.g., anatomical predisposition, sex, obesity, and age). Within this heterogenous syndrome, some distinctive phenotypes sharing similar clinical features can be recognized, one of them being REM sleep predominant OSA (REM-OSA). The aim of this review was to describe the pathomechanism of REM-OSA phenotype, its specific clinical presentation, and its consequences. Available data suggest that in this group of patients, the severity of specific cardiovascular and metabolic complications is increased. Due to the impact of apneas and hypopneas predominance during REM sleep, patients are more prone to develop hypertension or glucose metabolism impairment. Additionally, due to the specific function of REM sleep, which is predominantly fragmented in the REM-OSA, this group presents with decreased neurocognitive performance, reflected in memory deterioration, and mood changes including depression. REM-OSA clinical diagnosis and treatment can alleviate these outcomes, surpassing the traditional treatment and focusing on a more personalized approach, such as using longer therapy of continuous positive airway pressure or oral appliance use.

Altered brain dynamics index levels of arousal in complete locked-in syndrome

Complete locked-in syndrome (CLIS) resulting from late-stage amyotrophic lateral sclerosis (ALS) is characterised by loss of motor function and eye movements. The absence of behavioural indicators of consciousness makes the search for neuronal correlates as possible biomarkers clinically and ethically urgent. EEG-based measures of brain dynamics such as power-law exponent (PLE) and Lempel-Ziv complexity (LZC) have been shown to have explanatory power for consciousness and may provide such neuronal indices for patients with CLIS. Here, we validated PLE and LZC (calculated in a dynamic way) as benchmarks of a wide range of arousal states across different reference states of consciousness (e.g., awake, sleep stages, ketamine, sevoflurane). We show a tendency toward high PLE and low LZC, with high intra-subject fluctuations and inter-subject variability in a cohort of CLIS patients with values graded along different arousal states as in our reference data sets. In conclusion, changes in brain dynamics indicate altered arousal in CLIS. Specifically, PLE and LZC are potentially relevant biomarkers to identify or diagnose the arousal level in CLIS and to determine the optimal time point for treatment, including communication attempts.

Complex of global functional network as the core of consciousness

Finding the neural basis of consciousness is challenging, and the distribution location of the core of consciousness remains inconclusive. Integrated information theory (IIT) argues that the posterior part of the brain is the hot zone of consciousness, especially phenological consciousness. The IIT has proposed a "main complex", a set of elements determined such that the information loss in a hierarchical partition approach is the largest among those of any other supersets and subsets, as the core of consciousness in a dynamic system. This approach may be applicable not only to phenomenal but also to access-consciousness. This study estimated the main complex of brain dynamics using functional magnetic resonance imaging in Human Connectome Project (HCP) and sleep datasets. The complex analyses revealed the common networks across various tasks and rest-state in HCP, composed of executive control, salience, and dorsal/ventral attention networks. The set of networks of the main complex was maintained during sleep. However, compared with the wakefulness stage, the amount of information of these networks and the default mode network, was reduced for the hypnagogic stage. The global interconnected structure composed of major functional networks can comprise the core of consciousness.

'High-Density-SleepCleaner': An open-source, semi-automatic artifact removal routine tailored to high-density sleep EEG

BACKGROUND

With up to 256 channels, high-density electroencephalography (hd-EEG) has become essential to the sleep research field. The vast amount of data resulting from this magnitude of channels in overnight EEG recordings complicates the removal of artifacts.

NEW METHOD

We present a new, semi-automatic artifact removal routine specifically designed for sleep hd-EEG recordings. By employing a graphical user interface (GUI), the user assesses epochs in regard to four sleep quality markers (SQMs). Based on their topography and underlying EEG signal, the user eventually removes artifactual values. To identify artifacts, the user is required to have basic knowledge of the typical (patho-)physiological EEG they are interested in, as well as artifactual EEG. The final output consists of a binary matrix (channels x epochs). Channels affected by artifacts can be restored in afflicted epochs using epoch-wise interpolation, a function included in the online repository.

RESULTS

The routine was applied in 54 overnight sleep hd-EEG recordings. The proportion of bad epochs highly depends on the number of channels required to be artifact-free. Between 95% and 100% of bad epochs could be restored using epoch-wise interpolation. We furthermore present a detailed examination of two extreme cases (with few and many artifacts). For both nights, the topography and cyclic pattern of delta power look as expected after artifact removal.

COMPARISON WITH EXISTING METHODS

Numerous artifact removal methods exist, yet their scope of application usually targets short wake EEG recordings. The proposed routine provides a transparent, practical, and efficient approach to identify artifacts in overnight sleep hd-EEG recordings.

CONCLUSION

This method reliably identifies artifacts simultaneously in all channels and epochs.

Memory reactivations during sleep: a neural basis of dream experiences?

Newly encoded memory traces are spontaneously reactivated during sleep. Since their discovery in the 1990s, these memory reactivations have been discussed as a potential neural basis for dream experiences. New results from animal and human research, as well as from the rapidly growing field of sleep and dream engineering, provide essential insights into this question, and reveal both strong parallels and disparities between the two phenomena. We suggest that, although memory reactivations may contribute to subjective experiences across different states of consciousness, they are not likely to be the primary neural basis of dreaming. We identify important limitations in current research paradigms and suggest novel strategies to address this question empirically.

Topographic-dynamic reorganisation model of dreams (TRoD) - A spatiotemporal approach

Dreams are one of the most bizarre and least understood states of consciousness. Bridging the gap between brain and phenomenology of (un)conscious experience, we propose the Topographic-dynamic Re-organization model of Dreams (TRoD). Topographically, dreams are characterized by a shift towards increased activity and connectivity in the default-mode network (DMN) while they are reduced in the central executive network, including the dorsolateral prefrontal cortex (except in lucid dreaming). This topographic re-organization is accompanied by dynamic changes; a shift towards slower frequencies and longer timescales. This puts dreams dynamically in an intermediate position between awake state and NREM 2/SWS sleep. TRoD proposes that the shift towards DMN and slower frequencies leads to an abnormal spatiotemporal framing of input processing including both internally- and externally-generated inputs (from body and environment). In dreams, a shift away from temporal segregation to temporal integration of inputs results in the often bizarre and highly self-centric mental contents as well as hallucinatory-like states. We conclude that topography and temporal dynamics are core features of the TroD, which may provide the connection of neural and mental activity, e.g., brain and experience during dreams as their "common currency".

Mammalian NREM and REM sleep: Why, when and how

This report proposes that fish use the spinal-rhombencephalic regions of their brain to support their activities while awake. Instead, the brainstem-diencephalic regions support the wakefulness in amphibians and reptiles. Lastly, mammals developed the telencephalic cortex to attain the highest degree of wakefulness, the cortical wakefulness. However, a paralyzed form of spinal-rhombencephalic wakefulness remains in mammals in the form of REMS, whose phasic signs are highly efficient in promoting maternal care to mammalian litter. Therefore, the phasic REMS is highly adaptive. However, their importance is low for singletons, in which it is a neutral trait, devoid of adaptive value for adults, and is mal-adaptive for marine mammals. Therefore, they lost it. The spinal-rhombencephalic and cortical wakeful states disregard the homeostasis: animals only attend their most immediate needs: foraging defense and reproduction. However, these activities generate allostatic loads that must be recovered during NREMS, that is a paralyzed form of the amphibian-reptilian subcortical wakefulness. Regarding the regulation of tonic REMS, it depends on a hypothalamic switch. Instead, the phasic REMS depends on an independent proportional pontine control.

Closed-loop modulation of local slow oscillations in human NREM sleep

Slow-wave sleep is the deep non-rapid eye-movement (NREM) sleep stage that is most relevant for the recuperative function of sleep. Its defining property is the presence of slow oscillations (<2 Hz) in the scalp electroencephalogram (EEG). Slow oscillations are generated by a synchronous back and forth between highly active UP-states and silent DOWN-states in neocortical neurons. Growing evidence suggests that closed-loop sensory stimulation targeted at UP-states of EEG-defined slow oscillations can enhance the slow oscillatory activity, increase sleep depth, and boost sleep's recuperative functions. However, several studies failed to replicate such findings. Failed replications might be due to the use of conventional closed-loop stimulation algorithms that analyze the signal from one single electrode and thereby neglect the fact that slow oscillations vary with respect to their origins, distributions, and trajectories on the scalp. In particular, conventional algorithms nonspecifically target functionally heterogeneous UP-states of distinct origins. After all, slow oscillations at distinct sites of the scalp have been associated with distinct functions. Here we present a novel EEG-based closed-loop stimulation algorithm that allows targeting UP- and DOWN-states of distinct cerebral origins based on topographic analyses of the EEG: the topographic targeting of slow oscillations (TOPOSO) algorithm. We present evidence that the TOPOSO algorithm can detect and target local slow oscillations with specific, predefined voltage maps on the scalp in real-time. When compared to a more conventional, single-channel-based approach, TOPOSO leads to fewer but locally more specific stimulations in a simulation study. In a validation study with napping participants, TOPOSO targets auditory stimulation reliably at local UP-states over frontal, sensorimotor, and centro-parietal regions. Importantly, auditory stimulation temporarily enhanced the targeted local state. However, stimulation then elicited a standard frontal slow oscillation rather than local slow oscillations. The TOPOSO algorithm is suitable for the modulation and the study of the functions of local slow oscillations.

Non-REM parasomnias: a scoping review of dreams and dreamlike mentation

AIM

To establish patterns or themes of dreams and dreamlike mentation content reported in all forms of non-rapid eye movement (NREM) parasomnias and to identify gaps in the current understanding of this topic.

METHODS

A scoping review of available evidence on dreams and dreamlike mentation in NREM parasomnias was conducted in accordance with the PRISMA-ScR guidelines. We searched peer-reviewed literature using Google Scholar, PubMed, Ovid (Embase), Ovid Medline®, Global Health, and APA Psych Info. The Mixed Method Appraisal Tool (MMAT) was used to appraise the quality of selected articles.

RESULTS

The final analysis included 16 studies. All of the studies were from high-income countries. The studies reported on dreams and dreamlike mentation in NREM parasomnias, but there was scarcity of literature for sexsomnia, sleep-related eating disorder, and confusional arousal. All of the studies had the highest quality as shown by the MMAT (76%-100%). Emotions such as apprehension and misfortune were associated with sleepwalking and sleep terrors.

CONCLUSION

Sleep studies involving collection of dream content immediately following NREM parasomnia could significantly minimize reporting bias and improve dream data quality.

Non-REM parasomnias: a scoping review of dreams and dreamlike mentation

AIM

To establish patterns or themes of dreams and dreamlike mentation content reported in all forms of non-rapid eye movement (NREM) parasomnias and to identify gaps in the current understanding of this topic.

METHODS

A scoping review of available evidence on dreams and dreamlike mentation in NREM parasomnias was conducted in accordance with the PRISMA-ScR guidelines. We searched peer-reviewed literature using Google Scholar, PubMed, Ovid (Embase), Ovid Medline®, Global Health, and APA Psych Info. The Mixed Method Appraisal Tool (MMAT) was used to appraise the quality of selected articles.

RESULTS

The final analysis included 16 studies. All of the studies were from high-income countries. The studies reported on dreams and dreamlike mentation in NREM parasomnias, but there was scarcity of literature for sexsomnia, sleep-related eating disorder, and confusional arousal. All of the studies had the highest quality as shown by the MMAT (76%-100%). Emotions such as apprehension and misfortune were associated with sleepwalking and sleep terrors.

CONCLUSION

Sleep studies involving collection of dream content immediately following NREM parasomnia could significantly minimize reporting bias and improve dream data quality.

Individual slow wave events give rise to macroscopic fMRI signatures and drive the strength of the BOLD signal in human resting-state EEG-fMRI recordings

The slow wave state is a general state of quiescence interrupted by sudden bursts of activity or so-called slow wave events (SWEs). Recently, the relationship between SWEs and blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals was assessed in rodent models which revealed cortex-wide BOLD activation. However, it remains unclear which macroscopic signature corresponds to these specific neurophysiological events in the human brain. Therefore, we analyzed simultaneous electroencephalographic (EEG)-fMRI data during human non-REM sleep. SWEs individually detected in the EEG data were used as predictors in event-related fMRI analyses to examine the relationship between SWEs and fMRI signals. For all 10 subjects we identified significant changes in BOLD activity associated with SWEs covering substantial parts of the gray matter. As demonstrated in rodents, we observed a direct relation of a neurophysiological event to specific BOLD activation patterns. We found a correlation between the number of SWEs and the spatial extent of these BOLD activation patterns and discovered that the amplitude of the BOLD response strongly depends on the SWE amplitude. As altered SWE propagation has recently been found in neuropsychiatric diseases, it is critical to reveal the brain's physiological slow wave state networks to potentially establish early imaging biomarkers for various diseases long before disease onset.

Are we really unconscious in “unconscious” states? Common assumptions revisited

In the field of consciousness science, there is a tradition to categorize certain states such as slow-wave non-REM sleep and deep general anesthesia as “unconscious”. While this categorization seems reasonable at first glance, careful investigations have revealed that it is not so simple. Given that (1) behavioral signs of (un-)consciousness can be unreliable, (2) subjective reports of (un-)consciousness can be unreliable, and, (3) states presumed to be unconscious are not always devoid of reported experience, there are reasons to reexamine our traditional assumptions about “states of unconsciousness”. While these issues are not novel, and may be partly semantic, they have implications both for scientific progress and clinical practice. We suggest that focusing on approaches that provide a more pragmatic and nuanced characterization of different experimental conditions may promote clarity in the field going forward, and help us build stronger foundations for future studies.

Cortico-cortical and thalamo-cortical connectivity during non-REM and REM sleep: Insights from intracranial recordings in humans

OBJECTIVE

To study changes of thalamo-cortical and cortico-cortical connectivity during wakefulness, non-Rapid Eye Movement (non-REM) sleep, including N2 and N3 stages, and REM sleep, using stereoelectroencephalography (SEEG) recording in humans.

METHODS

We studied SEEG recordings of ten patients during wakefulness, non-REM sleep and REM sleep, in seven brain regions of interest including the thalamus. We calculated directed and undirected functional connectivity using a measure of non-linear correlation coefficient h².

RESULTS

The thalamus was more connected to other brain regions during N2 stage and REM sleep than during N3 stage during which cortex was more connected than the thalamus. We found two significant directed links: the first from the prefrontal region to the lateral parietal region in the delta band during N3 sleep and the second from the thalamus to the insula during REM sleep.

CONCLUSIONS

These results showed that cortico-cortical connectivity is more prominent in N3 stage than in N2 and REM sleep. During REM sleep we found significant thalamo-insular connectivity, with a driving role of the thalamus.

SIGNIFICANCE

We found a pattern of cortical connectivity during N3 sleep concordant with antero-posterior traveling slow waves. The thalamus seemed particularly involved as a hub of connectivity during REM sleep.

Abnormal timing of slow wave synchronization processes in non-rapid eye movement sleep parasomnias

STUDY OBJECTIVES

Sleepwalking, confusional arousals, and sleep terrors are parasomnias occurring out of non-rapid eye movement (NREM) sleep. Several previous studies have described EEG changes associated with NREM parasomnia episodes, but it remains unclear whether these changes are specific to parasomnia episodes or whether they are part of the normal awakening process. Here we directly compared regional brain activity, measured with high-density (hd-) EEG, between parasomnia episodes and normal awakenings (without behavioral manifestations of parasomnia).

METHODS

Twenty adult patients with non-rapid eye movement parasomnias underwent a baseline hd-EEG recording (256 electrodes) followed by a recovery sleep recording after 25 h of total sleep deprivation, during which auditory stimuli were administered to provoke parasomnia episodes.

RESULTS

Both normal awakenings (n = 25) and parasomnia episodes (n = 96) were preceded by large, steep, and "K-complex-like" slow waves in frontal and central brain regions, and by a concomitant increase in high-frequency EEG (beta) activity. Compared to normal awakenings, parasomnia episodes occurred on a less activated EEG background and displayed higher slow wave activity (SWA) and lower beta activity in frontal and central brain regions after movement onset.

CONCLUSIONS

Our results suggest that non-rapid eye movement awakenings, irrespective of behavioral manifestations of parasomnia episodes, involve an arousal-related slow wave synchronization process that predominantly recruits frontal and central brain areas. In parasomnia episodes, this synchronization process comes into play abnormally during periods of high SWA and is associated with higher SWA after movement onset. Thus, an abnormal timing of arousal-related slow wave synchronization processes could underlie the occurrence of NREM parasomnias.

Dreaming during the COVID-19 pandemic: A narrative review

According to several influential models, dreams can be affected by state- and trait-like factors, sleep features, and diurnal experiences. The COVID-19 pandemic globally affected daily habits, emotional experiences, and sleep. Previous studies suggested an influence of collective traumatic events on dreaming. Starting from these premises, several studies assessed the effect of the pandemic on dreams. This paper aims to review findings concerning the oneiric activity during the COVID-19 pandemic. We report pandemic-related changes in dreams and nightmares, and we consider the possible factors associated with dreaming. Moreover, we provide results about changes in the oneiric activity in different phases of the pandemic. The reviewed findings suggest a pandemic-related enhancement of dream and nightmare frequency, emotional intensity, and distressing contents, modulated by modifications in restrictive measures and associated with diurnal experiences, emotional status, and sleep pattern. We highlight several methodological issues and a large heterogeneity in the present literature, limiting results’ generalizability. However, we provide possible interpretations of the most consistent findings in light of the main theoretical frameworks about dreaming.

Sleep Disruption and Cancer: Chicken or the Egg?

Sleep is a nearly ubiquitous phenomenon across the phylogenetic tree, highlighting its essential role in ensuring fitness across evolutionary time. Consequently, chronic disruption of the duration, timing, or structure of sleep can cause widespread problems in multiple physiological systems, including those that regulate energy balance, immune function, and cognitive capacity, among others. Many, if not all these systems, become altered throughout the course of cancer initiation, growth, metastatic spread, treatment, and recurrence. Recent work has demonstrated how changes in sleep influence the development of chronic diseases, including cancer, in both humans and animal models. A common finding is that for some cancers (e.g., breast), chronic disruption of sleep/wake states prior to disease onset is associated with an increased risk for cancer development. Additionally, sleep disruption after cancer initiation is often associated with worse outcomes. Recently, evidence suggesting that cancer itself can affect neuronal circuits controlling sleep and wakefulness has accumulated. Patients with cancer often report difficulty falling asleep, difficulty staying asleep, and severe fatigue, during and even years after treatment. In addition to the psychological stress associated with cancer, cancer itself may alter sleep homeostasis through changes to host physiology and via currently undefined mechanisms. Moreover, cancer treatments (e.g., chemotherapy, radiation, hormonal, and surgical) may further worsen sleep problems through complex biological processes yet to be fully understood. This results in a “chicken or the egg” phenomenon, where it is unclear whether sleep disruption promotes cancer or cancer reciprocally disrupts sleep. This review will discuss existing evidence for both hypotheses and present a framework through which the interactions between sleep and cancer can be dissociated and causally investigated.

EEG Microstates in Altered States of Consciousness

Conscious experiences unify distinct phenomenological experiences that seem to be continuously evolving. Yet, empirical evidence shows that conscious mental activity is discontinuous and can be parsed into a series of states of thoughts that manifest as discrete spatiotemporal patterns of global neuronal activity lasting for fractions of seconds. EEG measures the brain’s electrical activity with high temporal resolution on the scale of milliseconds and, therefore, might be used to investigate the fast spatiotemporal structure of conscious mental states. Such analyses revealed that the global scalp electric fields during spontaneous mental activity are parceled into blocks of stable topographies that last around 60–120 ms, the so-called EEG microstates. These brain states may be representing the basic building blocks of consciousness, the “atoms of thought.” Altered states of consciousness, such as sleep, anesthesia, meditation, or psychiatric diseases, influence the spatiotemporal dynamics of microstates. In this brief perspective, we suggest that it is possible to examine the underlying characteristics of self-consciousness using this EEG microstates approach. Specifically, we will summarize recent results on EEG microstate alterations in mind-wandering, meditation, sleep and anesthesia, and discuss the functional significance of microstates in altered states of consciousness.

The vision of dreams: from ontogeny to dream engineering in blindness

The mechanisms involved in the origin of dreams remain one of the great unknowns in science. In the 21st century, studies in the field have focused on 3 main topics: functional networks that underlie dreaming, neural correlates of dream contents, and signal propagation. We review neuroscientific studies about dreaming processes, focusing on their cortical correlations. The involvement of frontoparietal regions in the dream-retrieval process allows us to discuss it in light of the Global Workspace theory of consciousness. However, dreaming in distinct sleep stages maintains relevant differences, suggesting that multiple generators are implicated. Then, given the strong influence of light perception on sleep regulation and the mostly visual content of dreams, we investigate the effect of blindness on the organization of dreams. Blind individuals represent a worthwhile population to clarify the role of perceptual systems in dream generation, and to make inferences about their top-down and/or bottom-up origin. Indeed, congenitally blind people maintain the ability to produce visual dreams, suggesting that bottom-up mechanisms could be associated with innate body schemes or multisensory integration processes. Finally, we propose the new dream-engineering technique as a tool to clarify the mechanisms of multisensory integration during sleep and related mental activity, presenting possible implications for rehabilitation in sensory-impaired individuals. The Theory of Proto-consciousness suggests that the interaction of brain states underlying waking and dreaming ensures the optimal functioning of both. Therefore, understanding the origin of dreams and capabilities of our brain during a dreamlike state, we could introduce it as a rehabilitative tool.

CITATION

Vitali H, Campus C, De Giorgis V, Signorini S, Gori M. The vision of dreams: from ontogeny to dream engineering in blindness. J Clin Sleep Med. 2022;18(8):2051-2062.

What about dreams? State of the art and open questions

Several studies have tried to identify the neurobiological bases of dream experiences, nevertheless some questions are still at the centre of the debate. Here, we summarise the main open issues concerning the neuroscientific study of dreaming. After overcoming the rapid eye movement (REM) ‐ non‐REM (NREM) sleep dichotomy, investigations have focussed on the specific functional or structural brain features predicting dream experience. On the one hand, some results underlined that specific trait‐like factors are associated with higher dream recall frequency. On the other hand, the electrophysiological milieu preceding dream report upon awakening is a crucial state‐like factor influencing the subsequent recall. Furthermore, dreaming is strictly related to waking experiences. Based on the continuity hypothesis, some findings reveal that dreaming could be modulated through visual, olfactory, or somatosensory stimulations. Also, it should be considered that the indirect access to dreaming remains an intrinsic limitation. Recent findings have revealed a greater concordance between parasomnia‐like events and dream contents. This means that parasomnia episodes might be an expression of the ongoing mental sleep activity and could represent a viable direct access to dream experience. Finally, we provide a picture on nightmares and emphasise the possible role of oneiric activity in psychotherapy. Overall, further efforts in dream science are needed (a) to develop a uniform protocol to study dream experience, (b) to introduce and integrate advanced techniques to better understand whether dreaming can be manipulated, (c) to clarify the relationship between parasomnia events and dreaming, and (d) to determine the clinical valence of dreams.

Capacity for consciousness under ketamine anaesthesia is selectively associated with activity in posteromedial cortex in rats

It remains unclear how specific cortical regions contribute to the brain’s overall capacity for consciousness. Clarifying this could help distinguish between theories of consciousness. Here, we investigate the association between markers of regionally specific (de)activation and the brain’s overall capacity for consciousness. We recorded electroencephalographic responses to cortical electrical stimulation in six rats and computed Perturbational Complexity Index state-transition (PCI^ST), which has been extensively validated as an index of the capacity for consciousness in humans. We also estimated the balance between activation and inhibition of specific cortical areas with the ratio between high and low frequency power from spontaneous electroencephalographic activity at each electrode. We repeated these measurements during wakefulness, and during two levels of ketamine anaesthesia: with the minimal dose needed to induce behavioural unresponsiveness and twice this dose. We found that PCI^ST was only slightly reduced from wakefulness to light ketamine anaesthesia, but dropped significantly with deeper anaesthesia. The high-dose effect was selectively associated with reduced high frequency/low frequency ratio in the posteromedial cortex, which strongly correlated with PCI^ST. Conversely, behavioural unresponsiveness induced by light ketamine anaesthesia was associated with similar spectral changes in frontal, but not posterior cortical regions. Thus, activity in the posteromedial cortex correlates with the capacity for consciousness, as assessed by PCI^ST, during different depths of ketamine anaesthesia, in rats, independently of behaviour. These results are discussed in relation to different theories of consciousness.

Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning

Consciousness can be defined by two components: arousal (wakefulness) and awareness (subjective experience). However, neurophysiological consciousness metrics able to disentangle between these components have not been reported. Here, we propose an explainable consciousness indicator (ECI) using deep learning to disentangle the components of consciousness. We employ electroencephalographic (EEG) responses to transcranial magnetic stimulation under various conditions, including sleep (n = 6), general anesthesia (n = 16), and severe brain injury (n = 34). We also test our framework using resting-state EEG under general anesthesia (n = 15) and severe brain injury (n = 34). ECI simultaneously quantifies arousal and awareness under physiological, pharmacological, and pathological conditions. Particularly, ketamine-induced anesthesia and rapid eye movement sleep with low arousal and high awareness are clearly distinguished from other states. In addition, parietal regions appear most relevant for quantifying arousal and awareness. This indicator provides insights into the neural correlates of altered states of consciousness.

The authors propose an explainable consciousness indicator using deep learning to quantify arousal and awareness under sleep, anesthesia, and in patients with disorders of consciousness.

Local sleep: A new concept in brain plasticity

Traditionally, sleep and wakefulness have been considered as two global, mutually exclusive states. However, this view has been challenged by the discovery that sleep and wakefulness are actually locally regulated and that islands of these two states may often coexist in the same individual. Importantly, such a local regulation seems to be the key for many essential functions of sleep, including the maintenance of cognitive efficiency and the consolidation of new skills and memories. Indeed, local changes in sleep-related oscillations occur in brain areas that are used and involved in learning during wakefulness. In turn, these changes directly modulate experience-dependent brain adaptations and the consolidation of newly acquired memories. In line with these observations, alterations in the regional balance between wake- and sleep-like activity have been shown to accompany many pathologic conditions, including psychiatric and neurologic disorders. In the last decade, experimental research has started to shed light on the mechanisms involved in the local regulation of sleep and wakefulness. The results of this research have opened new avenues of investigation regarding the function of sleep and have revealed novel potential targets for the treatment of several pathologic conditions.

Self-reported developmental changes in the frequency and characteristics of somnambulistic and sleep terror episodes in chronic sleepwalkers

BACKGROUND

Far from being benign, somnambulistic episodes can be frequent and/or severe and potentially injurious. Episodes may also be accompanied by sleep mentation with variable degrees of retrograde amnesia. The present study investigated how somnambulistic episodes unfold from childhood through adulthood, a topic that remains understudied.

METHODS

Adult sleepwalkers with a diagnosis of primary somnambulism and a childhood onset of the disorder (n = 113) were assessed for changes in frequency of their episodes, recall of episode-related sleep mentation and aggressive episodes during childhood, adolescence and adulthood. In addition, sleepwalkers (n = 52) with childhood-onset of sleep terrors were assessed for developmental changes in sleep terror frequency.

RESULTS

Results indicate that the frequency of somnambulistic episodes remains unchanged during childhood and adolescence before increasing during adulthood. An opposite trend was observed for sleep terrors. The frequency of aggressive somnambulistic episodes and of sleep mentation associated with somnambulism increased from childhood to adolescence and into adulthood. By contrast, the recall of sleep mentation associated with sleep terrors did not change over time. Additionally, a higher frequency of aggressive somnambulistic episodes predicted a higher frequency of sleep mentation associated with somnambulism. These patterns were similar across men and women.

CONCLUSION

Our study demonstrates that in chronic sleepwalkers, sleep mentation associated with somnambulistic episodes increases with age while episodes worsen in frequency and severity from childhood to adulthood. These findings add to the limited literature in the field and provide valuable insights into how key clinical characteristics of somnambulism evolve across the lifespan.

'Consciousnessoids': clues and insights from human cerebral organoids for the study of consciousness

Human cerebral organoids (HCOs) are an in vitro three-dimensional model of early neural development, aimed at modelling and understanding brain development and neurological disorders. In just a few years, there has been a rapid and considerable progress in the attempt to create a brain model capable of showcasing the structure and functions of the human brain. There are still strong limitations to address, including the absence of vascularization that makes it difficult to feed the central layers of organoids. Nevertheless, some important features of the nervous system have recently been observed: HCOs manifest electrical activity, are sensitive to light stimulation and are able to connect to a spinal cord by sending impulses that make a muscle contract. Recent data show that cortical organoid network development at 10 months resembles some preterm babies' electroencephalography (EEG) patterns. In the light of the fast pace of research in this field, one might consider the hypothesis that HCOs might become a living laboratory for studying the emergence of consciousness and investigating its mechanisms and neural correlates. HCOs could be also a benchmark for different neuroscientific theories of consciousness. In this paper, I propose some potential lines of research and offer some clues and insights so as to use HCOs in trying to unveil some puzzles concerning our conscious states. Finally, I consider some relevant ethical issues regarding this specific experimentation on HCOs and conclude that some of them could require strict regulation in this field.

Conscious experiences and high-density EEG patterns predicting subjective sleep depth

What accounts for feeling deeply asleep? Standard sleep recordings only incompletely reflect subjective aspects of sleep and some individuals with so-called sleep misperception frequently feel awake although sleep recordings indicate clear-cut sleep. To identify the determinants of sleep perception, we performed 787 awakenings in 20 good sleepers and 10 individuals with sleep misperception and interviewed them about their subjective sleep depth while they underwent high-density EEG sleep recordings. Surprisingly, in good sleepers, sleep was subjectively lightest in the first 2 h of non-rapid eye movement (NREM) sleep, generally considered the deepest sleep, and deepest in rapid eye movement (REM) sleep. Compared to good sleepers, sleep misperceptors felt more frequently awake during sleep and reported lighter REM sleep. At the EEG level, spatially widespread high-frequency power was inversely related to subjective sleep depth in NREM sleep in both groups and in REM sleep in misperceptors. Subjective sleep depth positively correlated with dream-like qualities of reports of mental activity. These findings challenge the widely held notion that slow wave sleep best accounts for feeling deeply asleep. Instead, they indicate that subjective sleep depth is inversely related to a neurophysiological process that predominates in early NREM sleep, becomes quiescent in REM sleep, and is reflected in high-frequency EEG activity. In sleep misperceptors, this process is more frequently active, more spatially widespread, and abnormally persists into REM sleep. These findings help identify the neuromodulatory systems involved in subjective sleep depth and are relevant for studies aiming to improve subjective sleep quality.

Do animals dream?

The understanding of biological functions of sleep has improved recently, including an understanding of the deep evolutionary roots of sleep among animals. However, dreaming as an element of sleep may be particularly difficult to address in non-human animals because in humans dreaming involves a non-wakeful form of awareness typically identified through verbal report. Here, we argue that parallels that exist between the phenomenology, physiology, and sleep behaviors during human dreaming provide an avenue to investigate dreaming in non-human animals. We review three alternative measurements of human dreaming - neural correlates of dreaming, 'replay' of newly-acquired memories, and dream-enacting behaviors - and consider how these may be applied to non-human animal models. We suggest that while animals close in brain structure to humans (such as mammals and birds) may be optimal models for the first two of these measurements, cephalopods, especially octopuses, may be particularly good candidates for the third.

Relationship Between Epilepsy and Dreaming: Current Knowledge, Hypotheses, and Perspectives

The interactions between epilepsy and sleep are numerous and the impact of epilepsy on cognition is well documented. Epilepsy is therefore likely to influence dreaming as one sleep-related cognitive activity. The frequency of dream recall is indeed decreased in patients with epilepsy, especially in those with primary generalized seizures. The content of dreams is also disturbed in epilepsy patients, being more negative and with more familiar settings. While several confounding factors (anti-seizure medications, depression and anxiety disorders, cognitive impairment) may partly account for these changes, some observations suggest an effect of seizures themselves on dreams. Indeed, the incorporation of seizure symptoms in dream content has been described, concomitant or not with a focal epileptic discharge during sleep, suggesting that epilepsy might directly or indirectly interfere with dreaming. These observations, together with current knowledge on dream neurophysiology and the links between epilepsy and sleep, suggest that epilepsy may impact not only wake- but also sleep-related cognition.

The dynamics of affect across the wake-sleep cycle: From waking mind-wandering to night-time dreaming

Affective experiences occur across the wake-sleep cycle-from active wakefulness to resting wakefulness (i.e., mind-wandering) to sleep (i.e., dreaming). Yet, we know little about the dynamics of affect across these states. We compared the affective ratings of waking, mind-wandering, and dream episodes. Results showed that mind-wandering was more positively valenced than dreaming, and that both mind-wandering and dreaming were more negatively valenced than active wakefulness. We also compared participants' self-ratings of affect with external ratings of affect (i.e., analysis of affect in verbal reports). With self-ratings all episodes were predominated by positive affect. However, the affective valence of reports changed from positively valenced waking reports to affectively balanced mind-wandering reports to negatively valenced dream reports. These findings show that (1) the positivity bias characteristic to waking experiences decreases across the wake-sleep continuum, and (2) conclusions regarding affective experiences depend on whether self-ratings or verbal reports describing these experiences are analysed.

Dreaming the unrepressed unconscious and beyond: repression vs dissociation in the oneiric functioning of severe patients

Starting with Freud and Jung, dreams have always been considered a core source of information for psychoanalysis. Nowadays, neuroscientific findings suggest that dreams are related especially to limbic and right emotional brain circuit, and that during REM stages they engage self-related and visual internally generated processing. These neuroscientific findings together with contemporary psychoanalysis suggest that dreams are related to the sense of self and serve the purpose of re-integrating and re-structuring the integrity of the psyche. However, while dreams are still viewed as 'the via regia to the unconscious', it is the unconscious that has been reconsidered. The repressed unconscious seems to be related with left brain activity while the unrepressed unconscious based on dissociation seems to be associated with limbic and cortical areas of the right hemisphere. This notion of the unconscious might be seen as an implicit self-system encoded in the right brain that evolves in the interaction with a primary caregiver developing through preverbal and bodily stages of maturation enhanced by signals of dual communication. What kind of dreams for which unconscious? What are the differences regarding the capacity to dream for neurotic and borderline personality organizations? Our research aims to integrate psychodynamics, infant research, and neuroscientific findings to better understand the role of dreams in the assessment and treatment of, especially, traumatized and borderline patients. The capacity to dream is here proposed as a sort of enacted manifestation of emotional memories for the development of a more cohesive, coherent and symbolic vs fragmented, diffuse and alexithymic sense of self.

Cross-participant prediction of vigilance stages through the combined use of wPLI and wSMI EEG functional connectivity metrics

Functional connectivity (FC) metrics describe brain inter-regional interactions and may complement information provided by common power-based analyses. Here, we investigated whether the FC-metrics weighted Phase Lag Index (wPLI) and weighted Symbolic Mutual Information (wSMI) may unveil functional differences across four stages of vigilance-wakefulness (W), NREM-N2, NREM-N3, and REM sleep-with respect to each other and to power-based features. Moreover, we explored their possible contribution in identifying differences between stages characterized by distinct levels of consciousness (REM+W vs. N2+N3) or sensory disconnection (REM vs. W). Overnight sleep and resting-state wakefulness recordings from 24 healthy participants (27 ± 6 years, 13F) were analyzed to extract power and FC-based features in six classical frequency bands. Cross-validated linear discriminant analyses (LDA) were applied to investigate the ability of extracted features to discriminate (1) the four vigilance stages, (2) W+REM vs. N2+N3, and (3) W vs. REM. For the four-way vigilance stages classification, combining features based on power and both connectivity metrics significantly increased accuracy relative to considering only power, wPLI, or wSMI features. Delta-power and connectivity (0.5-4 Hz) represented the most relevant features for all the tested classifications, in line with a possible involvement of slow waves in consciousness and sensory disconnection. Sigma-FC, but not sigma-power (12-16 Hz), was found to strongly contribute to the differentiation between states characterized by higher (W+REM) and lower (N2+N3) probabilities of conscious experiences. Finally, alpha-FC resulted as the most relevant FC-feature for distinguishing among wakefulness and REM sleep and may thus reflect the level of disconnection from the external environment.

Whole-body procedural learning benefits from targeted memory reactivation in REM sleep and task-related dreaming

Sleep facilitates memory consolidation through offline reactivations of memory traces. Dreaming may play a role in memory improvement and may reflect these memory reactivations. To experimentally address this question, we used targeted memory reactivation (TMR), i.e., application, during sleep, of a stimulus that was previously associated with learning, to assess whether it influences task-related dream imagery (or task-dream reactivations). Specifically, we asked if TMR or task-dream reactivations in either slow-wave (SWS) or rapid eye movement (REM) sleep benefit whole-body procedural learning. Healthy participants completed a virtual reality (VR) flying task prior to and following a morning nap or rest period during which task-associated tones were readministered in either SWS, REM sleep, wake or not at all. Findings indicate that learning benefits most from TMR when applied in REM sleep compared to a Control-sleep group. REM dreams that reactivated kinesthetic elements of the VR task (e.g., flying, accelerating) were also associated with higher improvement on the task than were dreams that reactivated visual elements (e.g., landscapes) or that had no reactivations. TMR did not itself influence dream content but its effects on performance were greater when coexisting with task-dream reactivations in REM sleep. Findings may help explain the mechanistic relationships between dream and memory reactivations and may contribute to the development of sleep-based methods to optimize complex skill learning.

Cortical and subcortical hemodynamic changes during sleep slow waves in human light sleep

EEG slow waves, the hallmarks of NREM sleep are thought to be crucial for the regulation of several important processes, including learning, sensory disconnection and the removal of brain metabolic wastes. Animal research indicates that slow waves may involve complex interactions within and between cortical and subcortical structures. Conventional EEG in humans, however, has a low spatial resolution and is unable to accurately describe changes in the activity of subcortical and deep cortical structures. To overcome these limitations, here we took advantage of simultaneous EEG-fMRI recordings to map cortical and subcortical hemodynamic (BOLD) fluctuations time-locked to slow waves of light sleep. Recordings were performed in twenty healthy adults during an afternoon nap. Slow waves were associated with BOLD-signal increases in the posterior brainstem and in portions of thalamus and cerebellum characterized by preferential functional connectivity with limbic and somatomotor areas, respectively. At the cortical level, significant BOLD-signal decreases were instead found in several areas, including insula and somatomotor cortex. Specifically, a slow signal increase preceded slow-wave onset and was followed by a delayed, stronger signal decrease. Similar hemodynamic changes were found to occur at different delays across most cortical brain areas, mirroring the propagation of electrophysiological slow waves, from centro-frontal to inferior temporo-occipital cortices. Finally, we found that the amplitude of electrophysiological slow waves was positively related to the magnitude and inversely related to the delay of cortical and subcortical BOLD-signal changes. These regional patterns of brain activity are consistent with theoretical accounts of the functions of sleep slow waves.

Largest scale dissociation of brain activity at propofol-induced loss of consciousness

The brain is a functional unit made up of multilevel connected elements showing a pattern of synchronized activity that varies in different states. The wake-sleep cycle is a major variation of brain functional condition that is ultimately regulated by subcortical arousal- and sleep-promoting cell groups. We analyzed the evolution of functional MRI (fMRI) signal in the whole cortex and in a deep region including most sleep- and wake-regulating subcortical nuclei at loss of consciousness induced by the hypnotic agent propofol. Optimal data were obtained in 21 of the 30 healthy participants examined. A dynamic analysis of fMRI time courses on a time-scale of seconds was conducted to characterize consciousness transition, and functional connectivity maps were generated to detail the anatomy of structures showing different dynamics. Inside the magnet, loss of consciousness was marked by the participants ceasing to move their hands. We observed activity synchronization after loss of consciousness within both the cerebral cortex and subcortical structures. However, the evolution of fMRI signal was dissociated, showing a transient reduction of global cortico-subcortical coupling that was restored during the unconscious state. An exception to cortico-subcortical decoupling was a brain network related to self-awareness (i.e. the default mode network) that remained connected to subcortical brain structures. Propofol-induced unconsciousness is thus characterized by an initial, transitory dissociated synchronization at the largest scale of brain activity. Such cortico-subcortical decoupling and subsequent recoupling may allow the brain to detach from waking activity and reorganize into a functionally distinct state.

EEG Signal Diversity Varies With Sleep Stage and Aspects of Dream Experience

Several theories link consciousness to complex cortical dynamics, as suggested by comparison of brain signal diversity between conscious states and states where consciousness is lost or reduced. In particular, Lempel-Ziv complexity, amplitude coalition entropy and synchrony coalition entropy distinguish wakefulness and REM sleep from deep sleep and anesthesia, and are elevated in psychedelic states, reported to increase the range and vividness of conscious contents. Some studies have even found correlations between complexity measures and facets of self-reported experience. As suggested by integrated information theory and the entropic brain hypothesis, measures of differentiation and signal diversity may therefore be measurable correlates of consciousness and phenomenological richness. Inspired by these ideas, we tested three hypotheses about EEG signal diversity related to sleep and dreaming. First, diversity should decrease with successively deeper stages of non-REM sleep. Second, signal diversity within the same sleep stage should be higher for periods of dreaming vs. non-dreaming. Third, specific aspects of dream contents should correlate with signal diversity in corresponding cortical regions. We employed a repeated awakening paradigm in sleep deprived healthy volunteers, with immediate dream report and rating of dream content along a thought-perceptual axis, from exclusively thought-like to exclusively perceptual. Generalized linear mixed models were used to assess how signal diversity varied with sleep stage, dreaming and thought-perceptual rating. Signal diversity decreased with sleep depth, but was not significantly different between dreaming and non-dreaming, even though there was a significant positive correlation between Lempel-Ziv complexity of EEG recorded over the posterior cortex and thought-perceptual ratings of dream contents.

Real-time dialogue between experimenters and dreamers during REM sleep

Dreams take us to a different reality, a hallucinatory world that feels as real as any waking experience. These often-bizarre episodes are emblematic of human sleep but have yet to be adequately explained. Retrospective dream reports are subject to distortion and forgetting, presenting a fundamental challenge for neuroscientific studies of dreaming. Here we show that individuals who are asleep and in the midst of a lucid dream (aware of the fact that they are currently dreaming) can perceive questions from an experimenter and provide answers using electrophysiological signals. We implemented our procedures for two-way communication during polysomnographically verified rapid-eye-movement (REM) sleep in 36 individuals. Some had minimal prior experience with lucid dreaming, others were frequent lucid dreamers, and one was a patient with narcolepsy who had frequent lucid dreams. During REM sleep, these individuals exhibited various capabilities, including performing veridical perceptual analysis of novel information, maintaining information in working memory, computing simple answers, and expressing volitional replies. Their responses included distinctive eye movements and selective facial muscle contractions, constituting correctly answered questions on 29 occasions across 6 of the individuals tested. These repeated observations of interactive dreaming, documented by four independent laboratory groups, demonstrate that phenomenological and cognitive characteristics of dreaming can be interrogated in real time. This relatively unexplored communication channel can enable a variety of practical applications and a new strategy for the empirical exploration of dreams.

Scientific investigations of dreaming have been hampered by the delay between a dream and when people report on their dream, and by a change in state from sleep to wake. To overcome this problem, Konkoly et al. show that individuals in REM sleep can perceive and answer an experimenter’s questions, allowing for real-time communication about a dream.