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Spectral Features of EEG Alpha Activity in Human REM Sleep: Two Variants with Different Functional Roles?

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Abstract

Evidence suggests that an important contribution of spectral power in the alpha range is characteristic of human REM sleep. This contribution is, in part, due to the appearance of well-defined bursts of alpha activity not associated with arousals during both tonic and phasic REM fragments. The present study aims at determining if the REM-alpha bursts constitute a different alpha variant from the REM background alpha activity. Since previous findings showed a selective suppression of background alpha activity over occipital regions during phasic REM fragments and, on the other hand, the density of alpha bursts seem to be independent of the presence or absence of rapid eye movements, one expects to find the same spectral power contribution of alpha bursts in tonic and phasic REM fragments. The results indicated that REM-alpha bursts showed a similar power contribution and topographic distribution (maximum energy over occipital regions) both in tonic and phasic REM fragments. This suggests that two variants of alpha activity with different functional roles are present during the human REM sleep: i) background alpha activity, modulated over occipital regions by the presence of rapid eye movements, which may be an electrophysiological correlate of the visual dream contents; and ii) REM-alpha bursts, independent of the presence of rapid eye movements, which could be facilitating the connection between the dreaming brain and the external world, working as a micro-arousal in this brain state.

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... During relaxed wakefulness with eyes closed, the dominant EEG rhythm in the majority of adults is in the alpha frequency range of 8 to 12 Hz with a maximum occurrence over the occipital lobe. Alpha is significantly attenuated by eye opening or mental operations, specifically mental imagination[20]. In most subjects the amplitude of the alpha rhythm varies between 10 and 50 lV with a maximum over the occipital regions[118]. ...
... In most subjects the amplitude of the alpha rhythm varies between 10 and 50 lV with a maximum over the occipital regions[118]. In vitro preparations and in vivo recordings point to cortical generator sources in layer V of the occipital cortex, and EEG, MEG, and PET studies suggest that alpha is mainly generated over posterior brain regions (reviewed in[20]). The number and exact localization of these generators remain unclear, as well as the existence of anterior alpha generators with different spectral properties. ...
... Furthermore, the occipital prominence abolishes with increasing sleepiness[106]. During REM sleep, an increase of EEG activity in the alpha range can be observed and can be separated in two components[20]: The first one comprises alpha background activity, predominately recorded in tonic REM sleep and attenuated in phasic REM sleep. This alpha attenuation has been interpreted as an electrophysiological correlate of visual dream contents. ...
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Question of the study The reliable evaluation of polysomnographic recordings (PSG) is an essential precondition for good clinical practice in sleep medicine. Although the scoring rules of Rechtschaffen and Kales [86] are internationally well established, they leave some room for different interpretations, and this may contribute to the limited reliability of visual sleep scoring. The German Sleep Society (DGSM) has set up a task force to devise ways to improve scoring reliability in the framework of their quality management programme. The intention was not to revise the rules of Rechtschaffen and Kales (R&K), but to facilitate their reliable application in sleep scoring and to support the development of standardized algorithms for computerized sleep analysis. Methods The task force was formed in September 2004 as a subcommittee of the educational panel of the DGSM. The members of the task force are experienced in sleep scoring and have a background either in physiology, neurology, psychiatry, psychology, or biology. The aim of the task force was to provide interpretation aids and, if needed, specifications or amendments to the R&K rules for the scoring of sleep electroencephalogram (EEG) waveforms and patterns. Decisions were based on the nominal group technique of a nominal panel as the formal consensus-building process. The consensus process was based on scoring and face-to-face discussions of at least 40 examples for each pattern in four 2-day meetings. Results Relevant EEG patterns for sleep stage scoring are alpha, theta, and delta waves, sleep spindles, K-complexes, vertex sharp waves, and sawtooth waves. If definitions for a given EEG pattern differed in the literature, the nominal group technique resulted in specifications and amended scoring rules for these EEG patterns. A second part including a series of examples with explanatory comments for each of these EEG patterns is under preparation. Conclusions Amendatory scoring rules of those EEG patterns that are relevant for sleep scoring may contribute to increasing the reliability of visual sleep scoring and to support the development of standardized algorithms for computerized sleep analysis.
... During relaxed wakefulness with eyes closed, the dominant EEG rhythm in the majority of adults is in the alpha frequency range of 8 to 12 Hz with a maximum occurrence over the occipital lobe. Alpha is significantly attenuated by eye opening or mental operations, specifically mental imagination [20]. In most subjects the amplitude of the alpha rhythm varies between 10 and 50 lV with a maximum over the occipital regions [118]. ...
... In vitro preparations and in vivo recordings point to cortical generator sources in layer V of the occipital cortex, and EEG, MEG, and PET studies suggest that alpha is mainly generated over posterior brain regions (reviewed in [20]). The number and exact localization of these generators remain unclear, as well as the existence of anterior alpha generators with different spectral properties. ...
... During REM sleep, an increase of EEG activity in the alpha range can be observed and can be separated in two components [20]: The first one comprises alpha background activity, predominately recorded in tonic REM sleep and attenuated in phasic REM sleep. This alpha attenuation has been interpreted as an electrophysiological correlate of visual dream contents. ...
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Question of the study On the basis of polysomnographic laboratory and field studies, the DLR Institute of Aerospace Medicine has developed a concept to protect against adverse effects of nocturnal aircraft noise at Airport Leipzig/Halle, which will be extended to a freight hub. We investigated whether or not the expected high traffic densities during the night will relevantly interfere with sleep macrostructure, if the criteria suggested by DLR are met. Methods Models were based on data sampled in a polysomnographic field study on 64 residents living in the vicinity of Airport Cologne/Bonn. Markov processes wer used to model a time in bed (TIB) of 8 h. Only two states were differentiated: wake and sleep, the latter consisting of S1-S4 and REM. Transition probabilities were estimated with logistic regression including current state (wake/sleep), duration of current state, elapsed sleep time, and maximum sound pressure level (SPL) of the aircraft noise event (ANE) as covariates. Three traffic scenarios were simulated: (i) no noise, (ii) aircraft noise at the beginning of the night (model A), and (iii) aircraft noise at the end of the night (model E). Results On the basis of 8 hours TIB and compared to the scenario without aireraft noise (81.1 min), time spent awake increased by 3.8 min (+4.7%) in model A and by 5.9 min (+7.3%) in model E. However, aircraft noise at the end of the night caused more pronounced changes in sleep structure than aircraft noise at the beginning of the night. Therefore, we propose to levy a malus of 1.4 dB on aircraft noise events occurring in the second half of the night. Conclusion In the context of noise effects on sleep, Markov processes allow for a flexible modelling of dependent events and variable traffic scenarios. If the criteria of the DLR protection concept are met, the models predict only minor noise-induced changes in time spent awake and in the number of awakenings recalled in the morning.
... Rapid eye movement sleep (REM) is a sleep state characterized by scattered phasic events that consist of transient activations of the central nervous, skeletal and autonomic systems, which occur over a tonic background of brain activation. Various studies have explored changes in EEG activity between tonicand phasic-REM sleep by analyzing separately periods of REM sleep without eye movements -tonic-REM (T-REM)-and periods with eye movements, called phasic-REM sleep (Ph-REM), observing that in contrast to tonic-REM sleep, phasic-REM sleep exhibits reduced theta and alpha activity and a shift from beta to faster oscillations in the gamma frequency range (Cantero et al., 2000;Corsi-Cabrera et al., submitted;Gross and Gotman, 1999;Jouny et al., 2000;Nishida et al., 2005), which reflect phasic-related brain activation and functional communication (Basar et al., 2001). Increased metabolic activation correlated with the number of eye movements in the pons, the lateral geniculate body and the occipital cortex (Peigneux et al., 2001), as well as in the frontal eye fields and attention-related cortical systems have been also reported (Braun et al., 1998;Hong et al., 1995;Wehrle et al., 2005). ...
... The PRE-EM increase in gamma power was also present during Ph-REM sleep in most of the recording sites that showed significant changes indicating that this is not restricted to periods immediately preceding the onset of eye movement but, rather, is sustained over long periods of phasic activation. These results corroborate previous findings that have reported higher gamma power during phasic-REM sleep obtained by averaging long periods of time away from eye movements (Cantero et al., 2000;Corsi-Cabrera et al., submitted;Gross and Gotman, 1999;Jouny et al., 2000;Nishida et al., 2005), and are in accordance with the increase in cholinergic diffuse modulatory systems (Calvo et al., 1996;Datta and Hobson, 1994), and with results in cats showing that not every PGO wave is followed by an eye movement (Sakai et al., 1976). Although gamma power was further enhanced during PRE-EM periods, the increase did not reach the level established for statistical significance. ...
... Pre-eye movement MEG activity was segmented into 500millisecond time windows, while the EEG was divided into three different time windows of 62.5, 250 and 500 ms, according to the following conditions: a) activity close to eye movement onset (− 62.5 to 0, − 250 to 0 and − 500 to 0); b) activity away from eye movement onset or Ph-REM (− 1000 to − 937.5, − 1000 to − 750 and − 1000 to − 500ms); and, c) from TREM sleep. Separate spectral power analysis was conducted for the different time windows all of which were subjected to Fast Fourier Transform to obtain gamma absolute power (AP), since gamma oscillations increase in Ph-REM (Cantero et al., 2000;Corsi-Cabrera et al., submitted;Gross and Gottman, 1999;Jouny et al., 2000;Nishida et al., 2005). The APs of the frequencies of interest were averaged to obtain a broad EEG band from 32 to 48 Hz. ...
Article
EEG and MEG REM sleep gamma activity was studied immediately before rapid eye movement onset (PRE-EM), during REM sleep with eye movements away from eye movement onset -phasic-REM (Ph-REM)--and during REM sleep without eye movements, or tonic REM (T-REM). For this purpose, activity was segmented into three different time windows: of 62.5, 250 and 500 ms. Two strategies were used: one a statistical comparison of changes between T-REM, Ph-REM and PRE-EM; the other a descriptive approach using principal component analysis. Significant findings showed that both EEG and MEG gamma activity are higher directly before eye movement onset in PRE-EM periods and during Ph-REM than during T-REM; temporal coupling of electrical activity between the frontal and parietal regions is decreased, while temporal coupling between the right frontal and midline is increased. Just before eye movement onset, larger recording sites become related. For the first time, results showed a close temporal link between power and temporal coupling of fast oscillations andrapid eye movements in REM sleep, indicating increased activation, uncoupling between the left frontal executive areas and posterior sensory association regions and increased coupling between the right frontal attentional and midline alerting systems. Brain activity is reorganized by phasic events.
... show high values during wakefulness that decrease during N-REMS and fall to minimum values during REMS (Cantero et al., 1999a(Cantero et al., , 1999b(Cantero et al., , 1999cCantero, Atienza, & Salas, 2000). Both spectral power and the h characteristics of alpha activity have been determined for humans, a primate species that sleeps in a horizontal posture and presents muscular atonia during REMS. ...
... Concerning our analyses of h, no significant increase in the h of the theta and beta bands during REMS compared with that during N-REMS or wakefulness was observed. Nevertheless, a higher (Cantero et al., 1999a(Cantero et al., , 1999b(Cantero et al., , 1999cCantero et al., 2000). However, given the spider monkey's arboreal nature, we predicted high h values for the alpha band during REMS compared with that during N-REMS. ...
Article
There is evidence that some animal species have developed physiological and behavioral mechanisms to monitor potential predatory threats during rapid eye movement sleep (REMS). Nevertheless, it has not been reported in arboreal primates. The present study analyzed the sleeping postures, as well as the electromyographic and electroencephalographic (EEG) activities during three conditions: REMS, non-REMS (N-REMS), and wakefulness in spider monkeys. The study included six monkeys, whose EEGs were recorded at the O1-O2, C3, C4, F3, and F4 derivations to analyze relative power (RP) and interhemispheric, intrahemispheric, frontoposterior, and central-posterior coherence of frequency bands, which has been considered an index of arousal states. The bands analyzed were theta (4.0-7.0 Hz), alpha1 (8.0-10.5 Hz), alpha2 (11.0-13.5 Hz), and beta (14.0-30.0 Hz). Spider monkeys adopt a vertical posture during sleep, and in REMS a lack of muscular atonia was observed. The RP of the alpha bands at O1-O2 was higher during REMS than that during wakefulness, N-REMS1, and N-REMS2. At the C3 derivation, the RP of alpha1 was higher during REMS than that during N-REMS2. The RP of both alpha bands at the F4 derivation was higher during REMS than that during wakefulness, whereas REMS was characterized by a higher coherence between the F3 and O1-O2 derivations of the alpha2 band. These prevalences and the higher coherence of alpha bands during REMS could represent a correlate of behavioral traits and activated cortical areas related to a possible arousal state in spider monkeys while sleeping.
... One common method for improving poor EEG spectral estimates has been to average spectral power within canonical frequency bands. For example, sleep analyses may report the total power within delta (0.5-4 Hz), theta (4 -8 Hz), alpha (8 -12 Hz), sigma (12)(13)(14)(15), beta (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), or gamma (Ͼ30 Hz) bands. While averaging across frequencies reduces the variability in power over time, it greatly reduces the frequency resolution of the spectral estimate, producing a low-resolution estimate that looks like a step function (FIGURE 2, A AND D, black curves). ...
... While transient alpha power during REM has been studied in great detail by Cantero (15)(16)(17)(18)(19), this obvious feature of REM sleep microstructure is absent in R&K scoring. This is perhaps because individual bursts may not be long enough to trigger a scored arousal or epoch of Wake and would be too time consuming to score manually. ...
Article
During sleep, cortical and subcortical structures within the brain engage in highly structured oscillatory dynamics that can be observed in the electroencephalogram (EEG). The ability to accurately describe changes in sleep state from these oscillations has thus been a major goal of sleep medicine. While numerous studies over the past 50 years have shown sleep to be a continuous, multifocal, dynamic process, long-standing clinical practice categorizes sleep EEG into discrete stages through visual inspection of 30-s epochs. By representing sleep as a coarsely discretized progression of stages, vital neurophysiological information on the dynamic interplay between sleep and arousal is lost. However, by using principled timefrequency spectral analysis methods, the rich dynamics of the sleep EEG are immediately visible— elegantly depicted and quantified at time scales ranging from a full night down to individual microevents. In this paper, we review the neurophysiology of sleep through this lens of dynamic spectral analysis. We begin by reviewing spectral estimation techniques traditionally used in sleep EEG analysis and introduce multitaper spectral analysis, a method that makes EEG spectral estimates clearer and more accurate than traditional approaches. Through the lens of the multitaper spectrogram, we review the oscillations and mechanisms underlying the traditional sleep stages. In doing so, we will demonstrate how multitaper spectral analysis makes the oscillatory structure of traditional sleep states instantaneously visible, closely paralleling the traditional hypnogram, but with a richness of information that suggests novel insights into the neural mechanisms of sleep, as well as novel clinical and research applications.
... Alpha activity is a meaningful constituent of REM sleep. Its widespread distribution during tonic periods (i.e., in the absence of rapid eye movements) is reduced during phasic periods (i.e., upon bursts of rapid eye movements), mainly in posterior recording areas (Cantero, Atienza, Gomez, & Salas, 1999;Cantero, Atienza, & Salas, 2000). This suppression of Alpha activity has been interpreted as reflecting the processing of dream content (Cantero et al., 1999(Cantero et al., , 2000Esposito et al., 2004;Jouny, Chapoto, & Merica, 2000). ...
... Its widespread distribution during tonic periods (i.e., in the absence of rapid eye movements) is reduced during phasic periods (i.e., upon bursts of rapid eye movements), mainly in posterior recording areas (Cantero, Atienza, Gomez, & Salas, 1999;Cantero, Atienza, & Salas, 2000). This suppression of Alpha activity has been interpreted as reflecting the processing of dream content (Cantero et al., 1999(Cantero et al., , 2000Esposito et al., 2004;Jouny, Chapoto, & Merica, 2000). In a single-case study of a typical 36-year-old male, Hong et al. (1996) showed that Alpha suppression is also apparent in nonposterior recording sites during dreaming, as they reported a negative correlation between expressive/receptive language in dream reports and Alpha activity over C3 and P3 electrodes during intermingled periods of tonic and phasic REM sleep. ...
Article
Functional interregional neural coupling was measured as EEG coherence during REM sleep, a state of endogenous cortical activation, in 9 adult autistic individuals (21.174.0 years) and 13 typically developed controls (21.574.3 years) monitored for two consecutive nights in a sleep laboratory. Spectral analysis was performed on 60 s of artefact-free EEG samples distributed equally throughout the first four REM sleep periods of the second night. EEG coherence was calculated for six frequency bands (delta, theta, alpha, sigma, beta, and total spectrum) using a 22-electrode montage. The magnitude of coherence function was computed for intra-and interhemispheric pairs of recording sites. Results were compared by Multivariate Analysis of Variance (MANOVA). Each time the autistic group showed a greater EEG coherence than the controls; it involved intrahemispheric communication among the left visual cortex (O1) and other regions either close to or distant from the occipital cortex. In contrast, lower coherence values involved frontal electrodes in the right hemisphere. No significant differences between groups were found for interhemispheric EEG coherence. These results show that the analysis of EEG coherence during REM sleep can disclose patterns of cortical connectivity that can be reduced or increased in adults with autism compared to typically developed individuals, depending of the cortical areas studied. Superior coherence involving visual perceptual areas in autism is consistent with an enhanced role of perception in autistic brain organization.
... During phasic-REM, there is an increase in gamma power and a concomitant decrease in theta, alpha and beta EEG activities (Jouny et al., 2000). During phasic-REM, the spectral power of the background alpha activity is decreased over occipital brain regions (Cantero et al., 2000). Alpha activity (8–13 Hz) attenuation in occipital regions is an electrophysiological index of cortical activation associated with waking visual imagery and visual attention. ...
... The controversy about whether there is activation of V1 during REM dreams may be due to different tasks, baseline conditions and analysis methods used in the different studies. It seems that visual imagery during REM sleep uses the same (or very similar) neural systems as those used in wakefulness (Cantero et al., 2000). However, according to the latest event-related fMRI (functional Magnetic Resonance Imaging) analyses, the pontine tegmentum, ventroposterior thalamus, primary visual cortex (V1), putamen and limbic areas are activated in association with REMs (Hong et al., 2009; Miyauchi et al., 2009). ...
Article
A novel molecular hypothesis about visual perception and imagery has recently been proposed (Bókkon, 2009; BioSystems). Namely, external electromagnetic visible photons are converted into electrical signals in the retina and are then conveyed to V1. Next, these retinotopic electrical signals (spike-related electrical signals along classical axonal-dendritic pathways) can be converted into synchronized bioluminescent biophoton signals (inside the neurons) by neurocellular radical reactions (redox processes) in retinotopically organized V1 mitochondrial cytochrome oxidase-rich visual areas. The bioluminescent photonic signals (inside the neurons) generated by neurocellular redox/radical reactions in synchronized V1 neurons make it possible to produce computational biophysical pictures during visual perception and imagery. Our hypothesis is in line with the functional roles of reactive oxygen and nitrogen species in living cells and states that this is not a random process, but rather a strict mechanism used in signaling pathways. Here, we suggest that intrinsic biophysical pictures can also emerge during REM dreams.
... Alpha activity is a meaningful constituent of REM sleep. Its widespread distribution during tonic periods (i.e., in the absence of rapid eye movements) is reduced during phasic periods (i.e., upon bursts of rapid eye movements), mainly in posterior recording areas (Cantero, Atienza, Gomez, & Salas, 1999;Cantero, Atienza, & Salas, 2000). This suppression of Alpha activity has been interpreted as reflecting the processing of dream content (Cantero et al., 1999(Cantero et al., , 2000Esposito et al., 2004;Jouny, Chapoto, & Merica, 2000). ...
... Its widespread distribution during tonic periods (i.e., in the absence of rapid eye movements) is reduced during phasic periods (i.e., upon bursts of rapid eye movements), mainly in posterior recording areas (Cantero, Atienza, Gomez, & Salas, 1999;Cantero, Atienza, & Salas, 2000). This suppression of Alpha activity has been interpreted as reflecting the processing of dream content (Cantero et al., 1999(Cantero et al., , 2000Esposito et al., 2004;Jouny, Chapoto, & Merica, 2000). In a single-case study of a typical 36-year-old male, Hong et al. (1996) showed that Alpha suppression is also apparent in nonposterior recording sites during dreaming, as they reported a negative correlation between expressive/receptive language in dream reports and Alpha activity over C3 and P3 electrodes during intermingled periods of tonic and phasic REM sleep. ...
Article
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The relationship between emotional dream content and Alpha and Beta REM sleep EEG activity was investigated in typical individuals and in Autistic Spectrum Disorders (ASD). Dream narratives of persons with ASD contained fewer emotional elements. In both groups, emotions correlated positively with slow Alpha (8.0-10.0 Hz) spectral power over parieto-occipital and left central regions, as well as with a right occipital EEG asymmetry. Slow Alpha activity in ASD individuals was lower over midline and parasagittal areas and higher over lateral areas compared to controls. Both groups displayed a right-biased slow Alpha activity for midparietal and occipital (significantly higher in control) sites. Results indicate that Alpha EEG activity may represent a neurophysiological substrate associated with emotional dream content. Distinctive Alpha EEG patterns and asymmetries suggest that dream generation implies different brain connectivity in ASD.
... According to research reports, significant differences in EEG features in different sleep stages, such as power spectrum features, nonlinear dynamics features, and functional connections (37)(38)(39). Cantero et al. pointed out that alpha wave power is an important feature of human REM sleep (40). Miskovic et al. found that in the whole sleep cycle, the change of entropy strongly depends on the time scale, and slow-wave sleep is characterized by the decrease of entropy in the short time scale and the increase of entropy in the long time scale (41). ...
Article
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Introduction Difficulty falling asleep place an increasing burden on society. EEG-based sleep staging is fundamental to the diagnosis of sleep disorder, and the selection of features for each sleep stage is a key step in the sleep analysis. However, the differences of sleep EEG features in gender and age are not clear enough. Methods This study aimed to investigate the effects of age and gender on sleep EEG functional connectivity through statistical analysis of brain functional connectivity and machine learning validation. The two-overnight sleep EEG data of 78 subjects with mild difficulty falling asleep were categorized into five sleep stages using markers and segments from the "sleep-EDF" public database. First, the 78 subjects were finely grouped, and the mutual information of the six sleep EEG rhythms of δ, θ, α, β, spindle, and sawtooth wave was extracted as a functional connectivity measure. Then, one-way analysis of variance (ANOVA) was used to extract significant differences in functional connectivity of sleep rhythm waves across sleep stages with respect to age and gender. Finally, machine learning algorithms were used to investigate the effects of fine grouping of age and gender on sleep staging. Results and discussion The results showed that: (1) The functional connectivity of each sleep rhythm wave differed significantly across sleep stages, with delta and beta functional connectivity differing significantly across sleep stages. (2) Significant differences in functional connections among young and middle-aged groups, and among young and elderly groups, but no significant difference between middle-aged and elderly groups. (3) Female functional connectivity strength is generally higher than male at the high-frequency band of EEG, but no significant difference in the low-frequency. (4) Finer group divisions based on gender and age can indeed improve the accuracy of sleep staging, with an increase of about 3.58% by using the random forest algorithm. Our results further reveal the electrophysiological neural mechanisms of each sleep stage, and find that sleep functional connectivity differs significantly in both gender and age, providing valuable theoretical guidance for the establishment of automated sleep stage models.
... Research also indicates that the eye movements of blind people do not correlate with dream scenes [43] and that cats still move their eyes during REM sleep even after their visual cortex has been removed [30]. Mota-Rolim explains that the main reason that false results in LD studies arise when relying on PAEM is that eye movements during REM sleep are sometimes detected alongside bursts of alpha activity [44], which may be a sign of "micro-arousal, ie, a transitional phase from REM sleep to waking, and not within a pure REM sleep state" [45,46]. ...
Article
Lucid dreams (LDs) occur when people become aware that they are dreaming. This phenomenon has a wide range of possible applications from the perspectives of psychology, training physical movements, and controlling computers while asleep, among others. However, research on LDs might lack efficiency because the standard LD verification protocol uses polysomnography (PSG), which requires an expensive apparatus and skilled staff. The standard protocol also may reduce LD-induction efficiency. The current study examines whether humans can send phasic signals through submentalis electromyography (EMG) during muscle atonia via pre-agreed chin movements (PACM). This ability would manifest both REM sleep and consciousness, which are the main features of LDs. In laboratory conditions volunteers were instructed to open their jaws three times while in an LD right after the standard verification protocol to achieve the research goal. Results: 4 of 5 volunteers proved to be in an LD using the standard protocol, and then all of them made PACM. The outcomes show that dream signals cannot be blocked in the submentalis area during muscle atonia. Also, this finding can be considered to develop a simplified, reliable LD protocol that needs only one EMG sensor. The cost of this protocol could be only a small percentage of the current protocol, making it more convenient for researchers and volunteers. It can also be used remotely by inbuilt in wearable gadgets. Considering PACM could speed up LD research and provide many discoveries and new opportunities. Also, it can be used in sleep paralysis studies.
... Perhaps most relevant, cueing to induce LDs is associated with higher fragmentation and arousal compared to spontaneous LDs in the laboratory (Ogilvie et al., 1983). More generally, bursts of alpha activity during late REM sleep have been proposed to enable increased processing and awareness of the external environment Cantero, Atienza, & Salas, 2000). Although our SVLD participants did not have more awakenings from REM than non-SVLD participants, it's possible that other metrics of arousal, such as alpha or gamma power, could be correlated with lucidity. ...
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Previous experiments combining cognitive techniques and sleep disruption have been relatively successful in inducing at-home lucid dreams (LD) over training periods of 1 week or more. Here, we induce LD in a single laboratory nap session by pairing cognitive training with external stimulation. Participants came to the laboratory at 7:30 a.m. or 11:00 a.m. and during polysomnography setup were provided with information about lucid dreaming. For 20 min prior to sleep the experimenter played alternating audio and visual cues at 1-min intervals. Participants were instructed to practice a mental state of critical self-awareness, observing their thoughts and experiences each time they noticed a cue. This procedure associated the cues with the trained mental state. Subsequently, participants were allowed 90 min to nap, and the audio and visual cues were presented during REM sleep to activate self-awareness in dreams and elicit lucidity. A control group followed the same procedure but was not cued during sleep. All participants were instructed to signal their lucidity by looking left and right 4 times (LR signal). Signal-verified lucid dreams (SVLDs) qualified as dreams in which the LR signal was observed and the participant reported becoming lucid. Across the 2 nap times, this protocol induced SVLDs in 50% of cued participants. In the absence of cueing during sleep, participant SVLD rate was 17%. Of note, 3 successful participants had never before experienced a LD, suggesting this protocol may be effective across the general population. Implications of this Targeted Lucidity Reactivation protocol for nightmare treatment are discussed.
... 48 More specifically, α power during REM sleep has been suggested to indicate the occurrence of microarousals, which cause sleep to be unstable for short periods of time. 49,50 Additionally, increased α power within NREM sleep has been associated with sleep fragility (unstable sleep) and awareness of one's external environment during sleep. 51 Thus, increased α power has been suggested to indicate increased arousability and alertness during sleep. ...
Article
Study Objectives Fetal growth restriction (FGR) occurs in up to 10% of pregnancies and is associated with increased risk of prematurity and neurodevelopmental impairment. FGR also alters sleep state distribution in utero and maturation in infancy. Currently, limited data on the long-term associations of FGR and childhood sleep exist. Accordingly, we assessed the associations between preterm birth and FGR and sleep in children aged 5-12 years. Methods 17 children born preterm and FGR, 15 children born preterm but appropriately grown (AGA) and 20 term AGA children (controls) were studied using overnight polysomnography. Sleep macro-architecture was assessed using standard criteria and sleep micro-architecture was assessed using spectral analysis of the EEG (C4-M1) with Total, Delta (0.5Hz–3.9Hz), Theta (4.0Hz–7.9Hz), Alpha (8.0Hz–11.9Hz), Sigma (12.0Hz–13.9Hz) and Beta Power (14.0Hz–30Hz) calculated. Results For sleep macro-architecture, preterm FGR children had higher N2% compared to term AGA children (p<0.05). Preterm AGA children had reduced total sleep time, NREM% and sleep efficiency compared to term AGA children (p<0.05 for all). For sleep micro-architecture, preterm FGR children had a higher amount of Total, delta and alpha power compared to both groups (p<0.05). Sigma and beta power were lowest in the preterm AGA group compared to both groups (p<0.05 for both). Conclusions Prematurity and FGR were associated with altered sleep macro- and micro-architecture measures indicative of reduced sleep quantity and quality in childhood. As sleep disturbance can impact both behavior and neurodevelopment in children, sleep in FGR and preterm children warrants further investigation.
... Alpha oscillations are thought to reflect input from dorsal anterior cingulate cortex, anterior insula, and thalamus that relay sensory information to the cortex, signalling the brain of external stimuli [43,53]. Increased alpha power during REM sleep therefore may reflect micro-arousal during REM sleep and possibly contributing to REM sleep instability [39,43,54]. Hence, the reduced alpha power in Nlgn3 R451C KI mice might indicate more stable REM sleep in these mutants. ...
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Human studies demonstrate that sleep impairment is a concurrent comorbidity of autism spectrum disorders (ASD), but its etiology remains largely uncertain. One of the prominent theories of ASD suggests that an imbalance in synaptic excitation/inhibition may contribute to various aspects of ASD, including sleep impairments. Following the identification of Nlgn3R451C mutation in patients with ASD, its effects on synaptic transmission and social behaviours have been examined extensively in the mouse model. However, the contributory role of this mutation to sleep impairments in ASD remains unknown. In this study, we showed that Nlgn3R451C knock-in mice, an established genetic model for ASD, exhibited normal duration and distribution of sleep/wake states but significantly altered electroencephalography (EEG) power spectral profiles for wake and sleep.
... The first data is the distinction between "phasic" and "tonic" epochs [5,6,7], the former being characterized by distinct oculomotor activity. During phasic REM sleep specific phenomena take place, including: reduction in background alpha activity over occipital regions [8], increase in arousal threshold [9], and increase in the motor activity in patients affected by REM sleep behavior disorder [10]. The second kind of data connected with time variations during REM sleep is given by the occurrence of slow eye movements (SEMs), whose frequency range is approximately similar to that of the eye movements that appear before sleep onset and increase over stage 1 [11,12]. ...
... Evidence in support of a similar physiological breach comes from findings of "microarousals" during the REM dream stage, arising from the presence of transient bursts of alpha spectral power lasting about 3 seconds. 67 Cantero and Atienza 98 speculated that these bursts might facilitate the connection between the dreaming brain and the external world, thus allowing the person to awake briefly in this state and become briefly aware of dream contents. Evidence is still needed however, to show that "micro-sleep" during wake periods actually produce REM imagery experienced as if awake (and with eyes open), rather than a temporary dissociation associated with a brief return to a sleep state (and eyes closed). ...
Article
By definition, hallucinations occur only in the full waking state. Yet similarities to sleep-related experiences such as hypnagogic and hypnopompic hallucinations, dreams and parasomnias, have been noted since antiquity. These observations have prompted researchers to suggest a common aetiology for these phenomena based on the neurobiology of rapid eye movement (REM) sleep. With our recent understanding of hallucinations in different population groups and at the neurobiological, cognitive and interpersonal levels, it is now possible to draw comparisons between the 2 sets of experiences as never before. In the current article, we make detailed comparisons between sleep-related experiences and hallucinations in Parkinson's disease, schizophrenia and eye disease, at the levels of phenomenology (content, sensory modalities involved, perceptual attributes) and of brain function (brain activations, resting-state networks, neurotransmitter action). Findings show that sleep-related experiences share considerable overlap with hallucinations at the level of subjective descriptions and underlying brain mechanisms. Key differences remain however: (1) Sleep-related perceptions are immersive and largely cut off from reality, whereas hallucinations are discrete and overlaid on veridical perceptions; and (2) Sleep-related perceptions involve only a subset of neural networks implicated in hallucinations, reflecting perceptual signals processed in a functionally and cognitively closed-loop circuit. In summary, both phenomena are non-veridical perceptions that share some phenomenological and neural similarities, but insufficient evidence exists to fully support the notion that the majority of hallucinations depend on REM processes or REM intrusions into waking consciousness.
... Among the data provided by the physiological investigation of REM sleep, a distinction between tonic and phasic epochs is particularly interesting, because it demonstrates that REM sleep is far from uniform: phasic epochs are characterized by distinct oculomotor activity (see, e.g., Sallinen et al., 1996), increase in arousal threshold (Ermis et al., 2010), reduction in the alpha power of the EEG signal (Cantero et al., 2000), and increase of major motor activity in patients affected by REM sleep behavior disorder (Frauscher et al., 2009). Furthermore, epochs exist that are specifically characterized by slow eye movements (SEMs; see, e.g., Marzano et al., 2007;Pizza et al., 2011), whose frequency range is approximately the same as that of eye movements during Stage 1. ...
Article
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This paper, which is limited to the art of painting, aims to support the idea that a substantial insertion of concepts and methods drawn on dream psychology and dream neuroscience can contribute to the advancements of Neuroesthetics. The historical and scientific reasons are discussed that have determined the so far poor role played by the dream phenomenon in the developments of Neuroesthetics. In the light of recent advancements in psychophysiological research, a method of analyzing artistic products is proposed that is based on the recognition of precise features proper of the dreaming experience. Four examples are given for application of this method, regarding works by Giorgione, Leonardo da Vinci, Vermeer, and Millais, respectively.
... During REM sleep there is a reciprocal increase in the cortex and hippocampus of ACh (Marrosu et al., 1995), while serotonin and noradrenaline levels are at a minimum (Aston- Jones and Bloom, 1981;Park et al., 1999). An EEG signature of REM is desynchronized activity, but alpha remains an important spectral power component (Cantero et al., 2000) and is generally slower (Gelisse and Crespel, 2008). Paradoxical refers to the desynchronized activity normally indicative of an alert state. ...
Article
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There is a strong correlation between signature EEG frequency patterns and the relative levels of distinct neuromodulators. These associations become particularly evident during the sleep-wake cycle. The monoamine-acetylcholine balance hypothesis is a theory of neurophysiological markers of the EEG and a detailed description of the findings that support this proposal are presented in this paper. According to this model alpha rhythm reflects the relative predominance of cholinergic muscarinic signals and delta rhythm that of monoaminergic receptor effects. Both high voltage synchronized rhythms are likely mediated by inhibitory Gαi/o-mediated transduction of inhibitory interneurons. Cognitively, alpha and delta EEG measures are proposed to indicate automatic and flexible strategies, respectively. Sleep is associated with marked changes in relative neuromodulator levels corresponding to EEG markers of distinct stages. Sleep studies on memory consolidation present some of the strongest evidence yet for the respective roles of monoaminergic and cholinergic projections in declarative and non-declarative memory processes, a key theoretical premise for understanding the data. Affective dysregulation is reflected in altered EEG patterns during sleep.
... EEG signal frequency while sleeping and waking states has been stratified into seven levels; for example, the delta level is with frequency of 0.1-3 Hz, which corresponds to deep sleep and lucid dreaming and the 3-8 Hz is deep relaxation compared to 40 Hz is high-level information processing [4]. Other studies that aim to understand EEG signals have looked at the alpha level of EEG activity in REM sleep [6]. Our work will not look at physiological outputs, but rather rely on self-reports of the dream after the person wakes up. ...
Article
The DreamThrower is a novel technology that explores virtually creating, throwing and catching dreams. It detects users’ dream state by measuring rapid eye movement. Once the dream state is detected, sound and light stimuli is played to alter the dream. Users report on their dream, and they can send the stimuli that they have used to another person via an on-line website. A working prototype accurately detects REM sleep. Based on results from the first experiment with three subjects, light and environmental sounds such as a jungle and ocean were found to have little influence on dreams. The second experiment with five subjects found that voice sound stimulus could influence dreams in one case. Interestingly, our subjects felt that the DreamThrower system would be a fun gaming experience and many said that they would share their dreams for a collaborative gaming experience. User engagement with the social network may be sufficient to alter dreams. Two studies with different stimuli showed some evidence that dreams can be altered.
... Preliminary results of an online survey we have recently conducted indicate that the main stimulus modality that incubates into dreams is auditory (a voice = 47%, phone rings = 43%, alarm clock = 41%, house/street noise = 37%), followed by tactile (36%), visual (20%) or olfactory (17%) sensations [68]. Micro-arousals caused by auditory or tactile stimuli associated with TMS and TDCS could thus be an important confounding factor because they connect the dreaming brain and the external world [69], being capable of inducing LD by themselves. Finally, it should be noted that EEG has important spatial limitations . ...
Article
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Several lines of evidence converge to the idea that rapid eye movement sleep (REMS) is a good model to foster our understanding of psychosis. Both REMS and psychosis course with internally generated perceptions and lack of rational judgment, which is attributed to a hyperlimbic activity along with hypofrontality. Interestingly, some individuals can become aware of dreaming during REMS, a particular experience known as lucid dreaming (LD), whose neurobiological basis is still controversial. Since the frontal lobe plays a role in self-consciousness, working memory and attention, here we hypothesize that LD is associated with increased frontal activity during REMS. A possible way to test this hypothesis is to check whether transcranial magnetic or electric stimulation of the frontal region during REMS triggers LD. We further suggest that psychosis and LD are opposite phenomena: LD as a physiological awakening while dreaming due to frontal activity, and psychosis as a pathological intrusion of dream features during wake state due to hypofrontality. We further suggest that LD research may have three main clinical implications. First, LD could be important to the study of consciousness, including its pathologies and other altered states. Second, LD could be used as a therapy for recurrent nightmares, a common symptom of depression and post-traumatic stress disorder. Finally, LD may allow for motor imagery during dreaming with possible improvement of physical rehabilitation. In all, we believe that LD research may clarify multiple aspects of brain functioning in its physiological, altered and pathological states.
... We suggest that increased high alpha power in the REM periods of NMs is a wake-like feature during REM sleep which might contribute to the pathophysiology of nightmare disorder. Alpha oscillations during REM sleep might reflect relatively short periods of sleep instability (micro-arousals) that facilitate the connection between the sleeping brain and the external environment (Cantero, Atienza, & Salas, 2000;Halász, 1998;Halász, Terzano, Parrino, & Bódizs, 2004). Alpha oscillations were shown to be modulated differently in the different states of alertness (Cantero et al., 2002): while higher alpha components are dominant during wakefulness, REM sleep is characterized by the preponderance of slower (7.5-10.5 Hz) alpha oscillations in healthy subjects (Cantero, Atienza, Gómez, & Salas, 1999). ...
Article
Although a growing body of research indicates that frequent nightmares are related to impaired sleep regulation, the pathophysiology of nightmare disorder is far from being fully understood. We examined the relative spectral power values for NREM and REM sleep separately in 19 individuals with nightmare disorder and 21 healthy controls, based on polysomnographic recordings of the second nights' laboratory sleep. Nightmare subjects compared to controls exhibited increased relative high alpha (10-14.5Hz) and fronto-central increases in high delta (3-4Hz) power during REM sleep, and a trend of increased fronto-central low alpha (7.75-9Hz) power in NREM sleep. These differences were independent of the confounding effects of waking emotional distress. High REM alpha and low NREM alpha powers were strongly related in nightmare but not in control subjects. The topographical distribution and spectral components of REM alpha activity suggest that nightmare disordered subjects are characterized by wake-like electroencephalographic features during REM sleep.
... Alpha activity during REM sleep also consists of background alpha activity and alpha bursts. The former is blocked by the occurrence of REM and is thus considered to be related to the presence or absence of visual activity while the latter is considered to be related to the arousal response (Cantero, Atienza, & Salas, 2000). In future studies, the functional relationship between these components of alpha band activity during REM sleep and the overnight improvement in the visual discrimination task performance should be investigated, and topographic analyses should be performed by measuring alpha band activity during REM sleep using a multi-channel measurement technique that affords adequate spatial resolution. ...
Article
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The purpose of this preliminary study was to clarify the association between cortical and subcortical activities during REM and non-REM sleep with overnight improvement of performance on a procedural memory task. Eleven healthy volunteers (M age = 23.8 yr., SD = 3.1) participated in this study which was conducted over two consecutive nights: an adaptation night and the experimental night. They underwent a visual discrimination task before and after the experimental night. A positive correlation was observed between overnight performance improvement on the visual discrimination task and EEG alpha band power during REM sleep, while no significant correlation was observed between the performance and either the amount of Stage REM sleep, REM activity, or other sleep variables. The findings corroborate other studies and suggest that cortical activity during REM sleep contributed to procedural memory consolidation and highlights the importance of measuring quantitative REM sleep components to elucidate the role of physiological sleep on memory consolidation in humans.
... EEG signal frequency while sleeping and waking states has been stratified into 7 levels; for example, the delta level is with frequency of 0.1 to 3 Hz, which corresponds to deep sleep and lucid dreaming and the 3-8 Hz is deep relaxation compared to 40 Hz is high-level information processing [4]. Further studies in understanding EEG signals have studied to further understand the alpha level of EEG activity in REM sleep [6]. Our work will not look at physiological outputs, but rather rely on self-reports of the dream after the person wakes up. ...
Conference Paper
Full-text available
The DreamThrower is a novel technology that explores virtually creating, throwing and catching dreams. It detects users’ dream state by measuring rapid eye movement (REM). Once the dream state is detected, sound and light stimuli is played to alter the dream. Users report on their dream, and they can send the stimuli that they have used to another person via an on-line website. A working prototype accurately detects REM sleep. Based on preliminary results, the sound and light stimuli were found to have little influence on their dreams. Our prototype’s ability to detect REM effectively coupled to a social network to share dream stimuli opens up a fun game environment even if the stimuli itself does not have a significant impact. Instead, user engagement with the social network may be sufficient to alter dreams. Further studies are needed to determine whether stimulus during REM can be created to alter dreams significantly.
... A possible safety gadget that further restricts long periods of unresponsiveness may be the fluctuation of periods with and without rapid eye movements, i.e., phasic and tonic REM periods (Cantero et al., 2000;Ermis et al., 2010;Kohyama, 1996). Tonic REM sleep refers to the state of widespread, low-voltage, fast electrocortical activity with hippocampal theta, a decrease in neck and chin EMG amplitude, and brain temperature elevation (Baust et al., 1964;Pessah and Roffwarg, 1972;Rechtschaffen, 1978). ...
Article
This chapter is concerned with behavioral and electrophysiologic evidence of awakenings. Awakenings are understood here as a state change from sleeping to waking. We will discuss the methodological issues and the problem of properly defining an awakening. With regard to phenomena preceding an awakening, we will look at arousals and compare background to event-related activity in the electroencephalography (EEG). As arousability varies between and within species, the relevant EEG correlates of this variability are described. Concerning EEG changes following an awakening, the discussion focuses on sleep inertia effects.
... Moderate acoustic stimulation evokes PGO-like activity in all states, but suppresses EMG activity during phasic REM and enhances it during NREM sleep and waking (Wu et al., 1989). To test if the differences in the observed behavioural motor responses in tonic versus phasic REM sleep may be related to a confounding enhancement of EMG atonia during REM sleep, we analysed background alpha power and the frequency of micro-arousals in the 10-s interval between tone presentations during night 2. Alpha power is independent of EMG activation and has been reported to be suppressed in phasic compared with tonic REM sleep (Cantero et al., 2000). By contrast, micro-arousals in REM sleep per definition (ASDA criteria, Bonnet et al., 1992) go along with an EMG enhancement. ...
Article
The goal of the present study was to investigate arousal thresholds (ATs) in tonic and phasic episodes of rapid eye movement (REM) sleep, and to compare the frequency spectrum of these sub-states of REM to non-REM (NREM) stages of sleep. We found the two REM stages to differ with regard to behavioural responses to external acoustic stimuli. The AT in tonic REM was indifferent from that in sleep stage 2, and ATs in phasic REM were similar to those in slow-wave sleep (stage 4). NREM and REM stages of similar behavioural thresholds were distinctly different with regard to their frequency pattern. These data provide further evidence that REM sleep should not be regarded a uniform state. Regarding electroencephalogram frequency spectra, we found that the two REM stages were more similar to each other than to NREM stages with similar responsivity. Ocular activity such as ponto-geniculo-occipital-like waves and microsaccades are discussed as likely modulators of behavioural responsiveness and cortical processing of auditory information in the two REM sub-states.
... The lack of reliable physiologic markers of insomnia suggests the possibility of two insomnia subtypes [40]. Quantitative electroencephalogram analysis, such as global and local electroencephalogram spectral power dynamic during specifi c sleep stages [35,41], including sleep onset [42], may be a promising tool in elucidating the specifi c neurobiological and possibly endophenotypical markers of primary insomnia and associated sleep misperception [15], which is common in anxiety disorder patients. Gender also may infl uence the relationship between the non-REM sleep electroencephalogram spectral power and insomnia symptoms [43]. ...
Article
The high prevalence and comorbidity of anxiety and sleep problems, especially insomnia, suggest an important underlying relationship between these disorders. In this article, we highlight two theoretical models explaining this co-occurrence, provide a brief update on the association between anxiety-insomnia and anxiety-cataplexy in general, and review more specifically sleep problems in generalized anxiety, post-traumatic stress disorder, and panic disorder. We also explore sleep paralysis as an anxiety-sleep event. Our goal with this examination of selective anxiety-sleep problems is to provide clues about diagnostic and treatment approaches and frame strategies for future research.
... However, they do support our hypothesis and notions proposed by other authors about the relationship between Alpha activity and sleep mentation. Cantero, Atienza, and Salas (2000), in distinguishing among different kinds of Alpha activity characteristic of REM sleep, suggested that a 292 ...
Article
Relationships between Alpha (8-12 Hz) activity and cognitive processes during wakefulness raise the possibility of similar relationships between Alpha and cognitive activity during sleep. We hypothesized that Alpha power decreases during both Stage 2 and REM sleep would index the presence of sleep mentation in these stages. Absolute power for six classical EEG bands and three Alpha subbands was calculated for Stage 2 and REM sleep awakenings both with and without mentation recall. In both stages, recall was associated with lower Alpha power, especially with middle Alpha power (9.5-11.5 Hz). Unexpectedly, a similar effect for Delta power (0.5-4.0 Hz) was also observed. The Alpha effect may reflect cognitive elaboration active in the minutes preceding awakening; however, attention and memory processes cannot be excluded. The Delta effect is consistent with prior observations of regular linkages between Alpha and Delta power during sleep.
Article
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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.
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Sleep staging is important in sleep research since it is the basis for sleep evaluation and disease diagnosis. Related works have acquired many desirable outcomes. However, most of current studies focus on time-domain or frequency-domain measures as classification features using single or very few channels, which only obtain the local features but ignore the global information exchanging between different brain regions. Meanwhile, brain functional connectivity is considered to be closely related to brain activity and can be used to study the interaction relationship between brain areas. To explore the electroencephalography (EEG)-based brain mechanisms of sleep stages through functional connectivity, especially from different frequency bands, we applied phase-locked value (PLV) to build the functional connectivity network and analyze the brain interaction during sleep stages for different frequency bands. Then, we performed the feature-level, decision-level and hybrid fusion methods to discuss the performance of different frequency bands for sleep stages. The~results show that (1) PLV increases in the lower frequency band (delta and alpha bands) and vice versa during different stages of non-rapid eye movement (NREM); (2) alpha band shows a better discriminative ability for sleeping stages; (3) the classification accuracy of feature-level fusion (six frequency bands) reaches 96.91% and 96.14% for intra-subject and inter-subjects respectively, which outperforms decision-level and hybrid fusion methods.
Conference Paper
Understanding how different brain areas interact to generate complex behavior is a primary goal of neuroscience research. One approach, functional connectivity analysis, aims to characterize the connectivity patterns in brain networks. For example, resting state functional connectivity analysis infers statistical relationships between brain areas from fMRI data in the absence of an explicit task. In this paper, we address the problem of discriminative connectivity, i.e. determining the differences in network structure under different experimental conditions. We introduce a novel model called Sparse Multi-task Inverse Covariance Estimation (SMICE) which is capable of estimating a common connectivity network as well as discrim-inative networks across different tasks. We apply the method to EEG signals after solving the inverse problem of source localization, yielding networks defined on the cortical surface. We propose an efficient algorithm based on the Alternating Direction Method of Multipliers (ADMM) to solve SMICE. We apply our newly developed framework to find common and discriminative connectivity patterns for α-bursts during the Sleep Onset Process (SOP) and during Rapid Eye Movement (REM) sleep. Even though both stages exhibit a similar α-burst phenomenon, we show that the underlying networks are distinct.
Article
Study Objectives To investigate if sudden-onset motor-behavioral episodes in REM sleep behavior disorder (RBD) are associated with phasic events of REM sleep, and to explore the potential meaning of such an association. Design Observational review analysis. Setting Tertiary sleep center. Patients Twelve individuals (11 males; mean age 67.6 ± 7.4 years) affected by idiopathic RBD, displaying a total of 978 motor-behavioral episodes during nocturnal in-laboratory video-PSG. Interventions N/A Measurements and Results The motor activity displayed was primitive in 69.1% and purposeful/semi-purposeful in 30.9% of the motor-behavioral episodes recorded. Sleeptalking was significantly more associated with purposeful/semi-purposeful motor activity than crying and/or incomprehensible muttering (71.0% versus 21.4%, P < 0.005). In 58.2% of the motor-behavioral episodes, phasic EEG-EOG events (rapid eye movements [REMs], α bursts, or sawtooth waves [STWs]) occurred simultaneously. Each variable (REMs, STWs, α bursts) was associated more with purposeful/semi-purposeful than with primitive movements (P < 0.05). Conclusions Motor-behavioral episodes in RBD were significantly more likely to occur in association with phasic than with tonic periods of REM sleep. The presence of REMs, α bursts and STWs was found to be more frequent in more complex episodes. We hypothesize that motor-behavioral episodes in RBD are likely to occur when the brain, during REM sleep, is in a state of increased instability (presence of α bursts) and experiencing stronger stimulation of visual areas (REMs).
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The latest experimental results support that multiple retinotopic visual systems play a central role not only in the processing of visual signals but also in the integration and processing of internally represented auditory and tactile information. These retinotopic maps have access to higher levels of cognitive processing, performed by the frontal lobes, for example. The occipital cortex may have a special role in multisensory integration. There is a functional basis for the development and maturation of visual memory in association of rapid eye movement sleep (REMS) which is linked to dreams and visual imagery. Physiological and psychological processes of REMS are similar to waking visual imagery. Furthermore, visual imagery during REMS utilize a common visual neural pathway similar to that used in wakefulness. This pathway subserves visual processes accompanied with auditory experiences and intrinsic feelings. We argue that the activation of the retinotopic visual areas is central to REM sleep associated dreams and that REMS associated dreaming and visual imagery may have co-evolved in homeothermic animals during evolution. We also suggest that protoconscious state during REM sleep, as introduced by Hobson many years ago, may be a basic visual process.
Research
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¡Todo mundo duerme! El sueño es tan familiar para cada uno de nosotros y, aún así, es un fenómeno envuelto en el misterio de sus funciones. Con tremendos y significativos avances como el descubrimiento del electroencefalograma en 1929, de la descripción del sueño de movimientos oculares rápidos en 1953, de la descripción de la existencia del reloj endógeno circadiano en 1972, de la localización del sitio relacionado con la disfunción del sueño en el caso del síndrome de la apnea obstructiva en 1965, del tratamiento no invasivo denominado CPAP (por sus siglas en ingles: Continuous Positive Airway Pressure) para el síndrome de la apnea del sueño en 1981 y del descubrimiento del gen relacionado con ritmos denominado CLOCK en la mosca de la fruta Drosophila en 1990, todavía continuamos preguntándonos ¿qué es el sueño? ¿Para qué dormimos? Es gratificante observar cómo la medicina del sueño va ganando espacios en la sociedad y se le otorga la importancia que merece, en especial cuando se relaciona con trastornos del dormir. Dicho interés se debe al creciente número de artículos vinculados con el tema del sueño los cuales han sido publicados en diferentes medios de comunicación, tanto de divulgación científica como de difusión social. El presente trabajo es el resultado del esfuerzo conjunto de científicos expertos en el área del estudio del ciclo sueño-vigilia que han contribuido con conocimientos actuales y avanzados relacionados con el tema. El propósito del libro es favorecer la comprensión sobre aspectos básicos y clínicos del sueño con una aproximación adecuada. Espero que el presente trabajo tenga una gran aceptación entre estudiantes, profesores e investigadores y cumpla con las expectativas de todo lector.
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This chapter discusses the quantitative analysis of the sleep electroencephalogram (EEG). The standard clinical EEG represents a visual description of brain electrical activity obtained through arrays of electrodes placed across the scalp. Providing excellent temporal resolution for assessing such activity on the order of time frames of neuronal events (e.g., milliseconds), the EEG can rapidly detect acute changes in brain function (such as those which occur at sleep onset and during rapid eye movement (REM) sleep) as well as examine the temporal sequencing of brain processes during brain activation. Recorded electrical activity results from the extracellular flow of current associated with summated excitatory postsynaptic potentials (EPSPs) and inhibitory postsynaptic potentials (IPSPs). Although much of the amplitude of brain electrical activity derives from cortical neurons underlying the scalp electrodes, subcortical sites modulate the synchrony of the recorded activity. Specifically, pacemakers in the thalamocortical neuronal circuitry produce rhythmic synchronous activity, which is reduced by arousal and increased with reduced vigilance.
Article
The pattern of rapid eye movement (REM) sleep was examined using a new scoring system for electroencephalogram (EEG) stages. An all-night polysomnogram (PSG) was recorded from 12 young healthy volunteers. First, all the data were scored according to the standard criteria of Rechtschaffen and Kales’A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects (1968), and epochs of typical REM sleep were collected. The extracted data were then re-scored for each 5 s using the criteria of seven EEG stages of REM sleep: (1) alpha wave, train; (2) alpha wave, intermittent A; (3) alpha wave, intermittent B; (4) EEG flattening; (5) theta wave; (6) sawtooth wave; and (7) movement time. The results showed that the EEG flattening (4) and theta wave stages (5) occupied 92.7% of the epochs of REM sleep. The most frequent transition pattern was also between these two stages (71.1%), and these stages rarely transitioned to other stages. The number of stage continuations within 2 epochs (10 s) was largest in EEG stage 4, and those in stage 5 followed it (64.5% and 54.2%, respectively). EEG stages 4 and 5 sometimes lasted for more than 13 epochs (over 1 min). The number of stages containing sawtooth waves was less than expected, and was more frequent at the beginning than at the end of REM sleep. The distinguishing feature of the REM sleep EEG pattern was the stability of the stages of EEG flattening and theta wave, compared with the sleep onset period EEG pattern.
Article
Question of the study The reliable evaluation of polysomnographic recordings (PSG) is an essential precondition for good clinical practice in sleep medicine. Although the scoring rules of Rechtschaffen and Kales [86] are internationally well established, they leave some room for different interpretations, and this may contribute to the limited reliability of visual sleep scoring. The German Sleep Society (DGSM) has set up a task force to devise ways to improve scoring reliability in the framework of their quality management programme. The intention was not to revise the rules of Rechtschaffen and Kales (R&K), but to facilitate their reliable application in sleep scoring and to support the development of standardized algorithms for computerized sleep analysis. Methods The task force was formed in September 2004 as a subcommittee of the educational panel of the DGSM: The members of the task force are experienced in sleep scoring and have a background either in physiology, neurology, psychiatry, psychology, or biology. The aim of the task force was to provide interpretation aids and, if needed, specifications or amendments to the R&K rules for the scoring of sleep electroencephalogram (EEG) waveforms and patterns. Decisions were based on the nominal group technique of a nominal panel as the formal consensus-building process. The consensus process was based on scoring and face-to-face discussions of at least 40 examples for each pattern in four 2-day meetings. Results Relevant EEG patterns for sleep stage scoring are alpha, theta, and delta waves, sleep spindles, K-complexes, vertex sharp waves, and sawtooth waves. If definitions for a given EEG pattern differed in the literature, the nominal group technique resulted in specifications and amended scoring rules for these EEG patterns. A second part including a series of examples with explanatory comments for each of these EEG patterns is under preparation. Conclusions Amendatory scoring rules of those EEG patterns that are relevant for sleep scoring may contribute to increasing the reliability of visual sleep scoring and to support the development of standardized algorithms for computerized sleep analysis.
Conference Paper
We are developing a new real-time control system for customizing auditory stimulus (the binaural beat sound) by judging user alpha waves to entrain a userpsilas feeling in the most relaxed way. Since brainwave activity provides the necessary predictive information for arousal states, we use an autoregressive forecasting model to estimate the frequency response series of the alpha frequency bands and the inverted-U concept to determine the userpsilas arousal state. A fuzzy logic controller is also employed to regulate the binaural beat control signal on a forecasting error signal. Our system allows comfortable user self-relaxation. The results of experiments confirm the constructed systempsilas effectiveness and necessity.
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Les personnes atteintes de schizophrénie peuvent présenter un sommeil anormal même lorsqu’elles sont stables cliniquement sous traitements pharmacologiques. Les études présentées dans cette thèse ont pour but de mesurer le sommeil afin de mieux comprendre les dysfonctions des mécanismes cérébraux pouvant être impliqués dans la physiopathologie de la schizophrénie. Les trois études présentées dans cette thèse rapportent des résultats sur le sommeil dans la schizophrénie à trois niveaux d’analyse chez trois groupes différents de patients. Le premier niveau est subjectif et décrit le sommeil à l’aide d’un questionnaire administré chez des personnes atteintes de schizophrénie cliniquement stables sous traitements pharmacologiques. Le deuxième niveau est objectif et évalue le sommeil par une méta-analyse des études polysomnographiques chez des patients atteints de schizophrénie ne recevant pas de traitement pharmacologique. Le troisième niveau est micro-structurel et utilise l’analyse spectrale de l’électroencéphalogramme (EEG) afin de caractériser le sommeil paradoxal de patients en premier épisode aigu de schizophrénie avant le début du traitement pharmacologique. La première étude montre que, lorsqu’évaluées par un questionnaire de sommeil, les personnes atteintes de schizophrénie cliniquement stables sous traitements pharmacologiques rapportent prendre plus de temps à s’endormir, se coucher plus tôt et se lever plus tard, passer plus de temps au lit et faire plus de siestes comparativement aux participants sains. Aussi, tout comme les participants sains, les personnes atteintes de schizophrénie rapportent un nombre normal d’éveils nocturnes, se disent normalement satisfaites de leur sommeil et se sentent normalement reposées au réveil. La deuxième étude révèle qu’objectivement, lorsque les études polysomnographiques effectuées chez des patients non traités sont soumises à une méta-analyse, les personnes atteintes de schizophrénie montrent une augmentation du délai d’endormissement, une diminution du temps total en sommeil, une diminution de l’efficacité du sommeil et une augmentation de la durée des éveils nocturnes comparativement aux participants sains. Les patients en arrêt aigu de traitement ont des désordres plus sévères au niveau de ces variables que les patients jamais traités. Seulement les patients jamais traités ont une diminution du pourcentage de stade 2 comparativement aux participants sains. La méta-analyse ne révèle pas de différence significative entre les groupes en ce qui concerne le sommeil lent profond et le sommeil paradoxal. La troisième étude, portant sur l’analyse spectrale de l’EEG en sommeil paradoxal, montre une diminution de l’amplitude relative de la bande de fréquence alpha dans les régions frontales, centrales et temporales et montre une augmentation de l’amplitude relative de la bande de fréquence bêta2 dans la région occipitale chez les personnes en premier épisode de schizophrénie jamais traitées comparativement aux participants sains. L’activité alpha absolue est positivement corrélée aux symptômes négatifs dans les régions frontales, centrales et temporales et négativement corrélée aux symptômes positifs dans la région occipitale. L’activité beta2 absolue ne montre pas de corrélation significative avec les symptômes positifs et négatifs de la schizophrénie. Ces résultats sont discutés suivant la possibilité que des dysfonctions au niveau des mécanismes de la vigilance seraient impliquées dans la physiopathologie de la schizophrénie. Patients with schizophrenia may have an abnormal sleep even when clinically stable under pharmacological treatments. In the present thesis, sleep studies aim at measuring central nervous system dysfunctions that can be involved in the pathophysiology of schizophrenia. The present thesis includes three studies. These studies report results on sleep in patients with schizophrenia in a three levels analysis with three different groups of patients. The first level is subjective and describes sleep habits using a questionnaire administered to outpatients with schizophrenia clinically stable under pharmacological treatments. The second level of analysis is objective and evaluates sleep architecture using a meta-analysis of polysomnographic studies in untreated patients with schizophrenia. The third level is microstructural and uses electroencephalogram (EEG) spectral analysis to characterize REM sleep in never-treated patients with first-episode schizophrenia. The first study shows that, when evaluated using a sleep habits questionnaire, outpatients with schizophrenia clinically stable under pharmacological treatments report increased time to fall asleep, have earlier bedtime, later risetime, spend more time in bed and do more naps compared to healthy participants. Also, similarly to healthy participants, most patients with schizophrenia report normal wake time after sleep onset, are normally satisfied about their sleep and feel normally refreshed in the morning. The second study reveals that, objectively, when polysomnographic studies evaluating untreated patients with schizophrenia are submitted to a meta-analysis, patients with schizophrenia have increased sleep latency, reduced total sleep time, reduced sleep efficiency and increased wake time after sleep onset compared to healthy participants. Patients in acute drug withdrawal show more severe sleep disturbances in these variables compared to never treated patients. Only never treated patients show decreased stage 2 sleep duration compared to healthy participants. The meta-analysis does not reveal significant differences between groups in regards to slow wave sleep and paradoxical sleep variables. The third study about REM sleep EEG spectral analysis shows decreased relative alpha spectral amplitude in frontal, central and temporal cortical regions and increased relative beta2 spectral amplitude in the occipital region in never treated patients with first-episode schizophrenia compared to healthy participants. Absolute alpha spectral amplitude correlates positively with negative symptoms in the frontal, central and temporal regions and negatively with positive symptoms in the occipital region. No significant correlation has been observed between beta2 spectral amplitude and clinical symptoms of schizophrenia. These results are discussed following the possibility that dysfunctions in the mechanisms of vigilance would be involved in the pathophysiology of schizophrenia.
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To assess the frequency of periodic leg movements (PLM) in idiopathic REM sleep behavior disorder (RBD) and to analyze their polysomnographic characteristics and associated autonomic and cortical activation. PLM during sleep (PLMS) and wakefulness (PLMW) are typical features of restless legs syndrome (RLS), but are also frequently observed in patients with RBD. Forty patients with idiopathic RBD underwent one night of polysomnographic recording to assess PLMS frequency. PLM features, PLMS-related cardiac activation during stage 2 sleep, and EEG changes were analyzed in 15 of these patients with RBD. Results were compared with similar data obtained in 15 sex- and age-matched patients with primary RLS. Twenty-eight (70%) of 40 patients with RBD showed a PLMS index greater than 10. No between-group differences were found in sleep architecture or indexes of PLMW and PLMS during non-REM sleep, but a trend for a higher PLMS index during REM sleep was found in patients with RBD. PLM mean duration and interval in the two conditions were similar. A transient tachycardia followed by a bradycardia was observed in close association with every PLMS in both groups, but the amplitude of the cardiac activation was significantly reduced in patients with RBD. In addition, significantly fewer PLMS were associated with microarousal in this condition. Periodic leg movements are very common in idiopathic RBD, occurring in all stages of sleep, especially during REM sleep. In idiopathic RBD, the reduction of cardiac and EEG activation associated with PLMS suggests the presence of an impaired autonomic and cortical reactivity to internal stimuli.
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An EEG study of sleep in congenitally blind persons revealed a significant correlation between the visual activity reported during dreaming and the decrease of alpha strength recorded from the central and occipital regions of the scalp. This provides the first objective evidence that subjects who have never had visual experiences can have dreams with virtual images that are probably mediated by the activation of the cortical areas responsible for visual representations.
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Alpha rhythms of the EEG are strongest at the occipital regions of the head, and the visual cortex is apparently a major contributor. It has been suggested that visual cortex is involved in forming and processing mental images. The purpose of this experiment is to determine if a task that involves visualizing objects represented by words produces changes in alpha rhythms of the MEG that differ from changes associated with finding rhymes of the same or related verbal stimuli. By hypothesis, the visual areas of the cortex play a less prominent role in the latter task than they do in the visualizing task. This inference is consistent with the finding that visual imagery is accompanied by attenuation of the alpha rhythm over the occipital scalp, in the proximity of visual cortex cognitive factors, such as memorization and classification of words, affects the pattern of alpha blockage across the occipital and parietal area, but this does not establish that visual cortex per se is involved. Subjects responded by forming mental images of the objects represented by the words. The event related potentials associated with presentation of the words were larger in amplitude than they were when the subjects silently pronounced words that rhymed with the stimuli instead of forming mental images. This effect was more evident at occipital electrodes than it was at other locations. There may well be differential suppression of alpha activity depending on the degree to which visual resources are engaged in various mental tasks, such as imaging. Keywords: Brain; Brain function; Neurochemistry; Reprints.
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In an intensive single-subject design, electroencephalographic (EEG) alpha power and receptive and expressive language in dreaming were studied in 12 dreams during rapid eye movement (REM) sleep on 12 separate nights. Bilateral EEG was recorded continuously from 21 sites and digitized. We used the Fast Fourier transformation (FFT) for power spectral analysis to measure EEG power in the alpha frequency range (8–12 Hz) at each of the EEG sites. The subject was awakened after about 14 minutes into the second REM period, and dream reports were collected. We scored the dream reports for expressive and receptive language. The lower the alpha power on the left sides of those homologous pairs that roughly correspond to Broca's (C3) or Wernicke's area (P3), the more expressive or receptive language in dream reports. The largest difference between the correlation of the left and that of the right homologous pair of regions was found in the central (C3, C4) area for expressive language and in the parietal (P3, P4) area for receptive language. Our finding suggests lateralized and localized cortical activation in relation to language in dreaming. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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The relationship between responsiveness to auditory stimuli presented during sleep and cognitive activity during sleep was assessed. Sixteen college-aged women were instructed while awake to turn off a tone by taking a deep breath. The tone was then presented during Stage 2 and REM sleep. Subjects were awakened after select trials to assess the relationship between responding and reports of ongoing cognitive activity. Consistent with the view that cognitive activity reduces responsiveness, significantly fewer responses were found on report (cognitive activity) trials relative to no-report (no cognitive activity) trials in analyses involving all trials and Stage 2 trials alone. Trained judges then rated the subjects' reports of cognitive activity as indicating incorporation or not indicating incorporation of the tone and/or the breathing response. Incorporation was associated with a reduced likelihood of responding relative to no incorporation in analyses involving all trials. No difference in responding was found between no-incorporation trials and no-report trials, suggesting that reduced responsiveness is associated with cognitive activity only when incorporation occurs. These findings support hypotheses that the reduced responsiveness to external stimulation during sleep is at least in part due to ongoing cognitive activity.
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The present study was designed to assess the patterning of occipital and sensorimotor EEG activation during self-generated visual and kinesthetic imagery. Twenty subjects were requested to imagine, in separate trials, a flashing light, a tapping sensation on the right forearm, and both the light and the tapping together. Prior to the imagery trials, subjects were exposed to the stimuli which they were asked to subsequently imagine. EEG was recorded from the left occipital and left sensorimotor regions, filtered for alpha and quantified on-line. The results indicated that self-generated visual imagery elicited greater relative occipital activation than comparable kinesthetic imagery. The imagine-both condition fell predictably in between the two unimodal imagery conditions. The difference between visual and kinesthetic imagery was primarily a function of greater occipital activation during the former versus the latter task. No difference in overall alpha abundance among the three imagery tasks was found. These findings suggest that the self-generation of imagery in different modalities elicits specific changes in the sensory regions of the brain responsible for processing information in the relevant modalities.
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This review summarizes studies of evoked potentials (EPs) applied to the investigation of human sleep and of sleep disorders. The first part is devoted to studies dealing with the nature, mechanisms and extent of information processing during sleep. EP studies suggest that the brain's ability to detect salient stimuli persists during even the deepest sleep stages, while discrimination of the stimulus' intrinsic significance and/or semantic content may persist only in stage II and paradoxical sleep (PS). Deviance detection in non-rapid eye movement (NREM) sleep is reflected by amplitude recovery of K-complexes elicited by stimulations that differ from the background. The evoked K-complex appears to be formed by two functionally different modules. The first may be related to the discrimination of relevant information. The second appears more sensitive to stimulus salience than to its intrinsic significance. In PS, the EP signs of stimulus discrimination are similar to those observed during waking. Thus, if the possibilities of information processing are fairly similar during stage II and PS, their respective neural mechanisms are not the same, as judged by their electrophysiological counterparts.The second part of the paper reviews clinical application of EPs to the study of sleep/wake disorders. While early potentials are of little use for diagnosis of sleep disorders, the cognitive P300 may help to quantify cognitive slowing and pathological sleepiness. However, intersubject variability restrains the use of these techniques in individual patients. A promising approach is the utilization of late responses to the study of sleep inertia with the use of “forced awakening” recording paradigms.
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Alpha activity during REM sleep without signs of awakening can discriminate between the blind classification of prelucid, lucid, and nonlucid dreams. Ten good dream recallers were aroused after relatively high or low amplitude REM alpha. The spectral and temporal characteristics of EEG alpha within each REM period were associated with lucidity and other content dimensions. Each type of dream had a reasonably distinct pattern of REM alpha. High amplitude alpha was found to be associated with prelucid dreams and bizarre content, which is consistent with theories of waking alpha activity and the hypothesis that lucidity sometimes emerges from prelucid experiences. The data are also consistent with the idea that lucidity is a viable dream content dimension, and interpreted in terms of systems theory imply that training which emphasizes dream content control may constrain the potential information integration function of lucid dreams.
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The present study was designed to examine brain activity underlying mental imagery is conceptualized as behavior guided by internal representation only, the activity of the prefrontal lobes was assumed to be a measure of differentiation of imagery from perception. Twenty-one subjects were requested to observe and imagine a swinging pendulum and to touch and imagine a coshball in separate trials. The EEG was recorded from 15 standard electrode sites and analyzed with (1) traditional alpha power and (2) an estimation of dimensional complexity (a measure derived from nonlinear dynamics). Both EEG measures revealed expected object-related differences during perception as well as during imagery. The visual pendulum showed relative to the tactile coshball increased dimensional complexity and less alpha power at parietal and frontal sites. However, only the EEG dimension supported the main hypothesis: Imagery resulted in increased prefrontal dimensional complexity in comparison to perception independent of the modality of the image. In contrast, for alpha power the difference between imagery and perception was due to stimulus modality.
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Based on the findings of our previously published positron emission tomography study, we proposed that recorded eye movements during REM sleep are visually targeted saccades. In the present study, we examined the correlation between the number of eye movements in REM sleep (EM) and visual imagery in dreaming (V) and provided further support for our proposal. All the observations (N = 11) were made with one individual to eliminate interindividual variation and were made during the second REM sleep period to control for a time-of-night effect. V, with or without dream report length partialled out, was strongly associated with EM only in the 1-min interval immediately preceding awakening. The time course of the association suggests that the strong EM-V association reflects a phasic, localized activation of the eye-movement-control system in association with REM sleep eye movements.
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Auditory evoked potentials (AEPs) were recorded during presentation of stimuli of 1000 Hz (standard) and 2000 Hz (deviant) in trains of 10 tone bursts (one deviant per train) in the wake and rapid eye movement (REM) sleep states. The constant inter-stimulus interval (ISI) was 600 ms and the trains were separated by 3 s of silence. The deviant tone occurring at the train start elicited a mismatch negativity component (MMN) in both arousal states, displaying a peak latency between 100 and 150 ms post-stimulation at fronto-central areas. These results suggest the existence of an auditory memory trace (sensory memory) surviving for at least 3 s during REM sleep.
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In a study with 10 young, healthy subjects, alpha activities were studied in three different arousal states: eyes closed in relaxed wakefulness (EC), drowsiness (DR), and REM sleep. The alpha band was divided into three subdivisions (slow, middle, and fast) which were analyzed separately for each state. The results showed a different spectral composition of alpha band according to the physiological state of the subject. Slow alpha seemed to be independent of the arousal state, whereas middle alpha showed a difference between REM and the other states. The fast-alpha subdivision appears mainly as a waking EEG component because of the increased power displayed only in wakefulness and lower and highly stable values for DR and REM. Scalp distribution of alpha activity was slightly different in each state: from occipital to central regions in EC, this topography was extended to fronto-polar areas in DR, with a contribution from occipital to frontal regions in REM sleep. These results provide evidence for an alpha power modulation and a different scalp distribution according to the cerebral arousal state.
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Spontaneous alpha activity clearly present in relaxed wakefulness with closed eyes, drowsiness period at sleep onset, and REM sleep was studied with spatial segmentation methods in order to determine if the brain activation state would be modulating the alpha spatial microstates composition and duration. These methods of spatial segmentation show some advantages: i) they extract topographic descriptors independent of the chosen reference (reference-free methods), and ii) they achieve spatial data reduction that are more data-driven than dipole source analysis. The results obtained with this study revealed that alpha activity presented a different spatio-temporal pattern of brain electric fields in each arousal state used in this study. These differences were reflected in a) the mean duration of alpha microstates (longer in relaxed wakefulness than in drowsy period and REM sleep), b) the number of brain microstates contained in one second (drowsiness showed more different microstates than did relaxed wakefulness and REM state), and c) the number of different classes (more abundant in drowsiness than in the rest of brain states). If we assume that longer segments of stable brain activity imply a lesser amount of different information to process (as reflected by a higher stability of the brain generator), whereas shorter segments imply a higher number of brain microstates caused by more different steps of information processing, it is possible that the alpha activity appearing in the sleep onset period could be indexing the hypnagogic imagery self-generated by the sleeping brain, and a phasic event in the case of REM sleep. Probably, REM-alpha bursts are associated with a brain microstate change (such as sleep spindles), as demonstrated by its phasic intrusion in a desynchronized background of brain activity. On the other hand, alpha rhythm could be the "baseline" of brain activity when the sensory inputs are minimum and the state is relaxed wakefulness.
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Alpha activity attenuation (blocking) over occipital regions is an electrophysiological index of cortical activation associated with visual attention and waking mental imagery. The present work focused on exploring whether the human REM background alpha activity was modulated, attending to tonic- (without rapid oculomotor activity) and phasic-REM periods (with a prominent burst of REMs). The obtained results revealed that the background alpha activity showed a decreased spectral power over occipital brain regions during phasic-REM in comparison with tonic-REM periods. This result suggests an active visual processing caused by the complex mental imagery generated during periods of oculomotor activity in human REM sleep.
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The functional relationships between the brain areas supposedly involved in the generation of the alpha activity were quantified by means of INTRA- and INTER-hemispheric coherences during different arousal states (relaxed wakefulness, drowsiness at sleep onset, and rapid eye movement sleep) where such an activity can be clearly detectable in the human EEG. A significant decrease in the fronto-occipital as well as in the inter-frontal coherence values in the alpha range was observed with the falling of the vigilance level, which suggests that the brain mechanisms underlying these coherences are state dependent. Making fronto-frontal coherence values in the alpha frequency band useful indexes to discern between brain functional states characterized by a different arousal level.
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Spectral power contribution in the range of alpha activity is a well-known electrophysiological feature of human REM sleep, which could be caused by the spontaneous bursts of alpha activity not associated with arousals that usually appear during this brain state. The present study was undertaken to determine the density of alpha bursts during tonic and phasic (oculomotor) REM periods for each REM cycle. In addition, this phasic brain event was also described from a spectral and topographical point of view. Ten healthy right-handed subjects (5 females) aged 19-25 years (mean 22.9 years, SD 2.6) participated in the present study. Each selected subject filled in a daily sleep log for 2 weeks before the experimental night to provide information on all 3 salient aspects of sleep pattern, sleep experience and sleep effects. The results revealed that transient REM-alpha bursts, which lasted about 3 s and were accompanied by no increase in the EMG amplitude, appeared in all subjects who participated in this study, showing a higher density in the third and fourth REM cycle during phasic in comparison with tonic periods. The bandpass filtered signals showed the highest spectral contribution for the slower alpha components (8-9 Hz), the occipital scalp regions being the main generator source of this brain activity. The authors hypothesize that REM-alpha bursts may work as micro-arousals (or incomplete arousals) facilitating the brain connection with the external world in this cerebral state, whereas REM-alpha arousals - usually longer and accompanied by changes in the EMG amplitude - generate a shift of brain state associated with sleep fragmentation (complete arousal).
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In a repetitive auditory stimulus sequence, deviant infrequent tones typically elicit a component of auditory event-related potentials termed mismatch negativity (MMN). The elicitation of MMN is assumed to reflect the existence of a memory trace of the standard stimulus that has a decay time of about 10 s and is strengthened by repetition of the standards. The main aim of the present study was to test the decay time of the sensory memory trace during rapid-eye movement (REM) sleep vs. wakefulness, as indexed by the MMN. Subjects were presented 10 tone trains, separated by 3, 6, or 9 s of silence, during waking and REM sleep. Each train consisted of 9 standards of 1000 Hz and 1 deviant of 2000 Hz that occurred at position 1, 2, 4, or 6. The waking deviants elicited a frontocentral negativity with a scalp topography equivalent to the MMN component. During REM sleep, the negative component showed the same scalp distribution only for the 3-s intertrain interval (ITI). In this brain state, the MMN amplitude was smaller and decreased with prolongation of the ITI. These results suggest a weaker sensory memory trace formation and a premature decay time of such a memory trace during REM sleep as compared with wakefulness.
Article
Normal electroencephalographic (EEG) alpha variants appear during relaxed wakefulness with closed eyes, drowsiness period at sleep onset, and rapid eye movement (REM) sleep in bursts without arousal signals. Previous results revealed that fronto-occipital and fronto-frontal alpha coherences became weaker from wakefulness to drowsiness, and finally to REM sleep. The present work was aimed at determining whether a generalized or a unidirectional deactivation of the long fronto-occipital fasciculi, previously proposed to be involved in the alpha rhythm generation, could explain the above-mentioned results. Polynomial regression analyses, applied to the change of alpha coherence with distance along the antero-posterior axis, suggested that the anterior and posterior local circuits show a similar level of activation in all brain states. Bivariate partial correlation analyses between local alpha coherences revealed that such local circuits maintain a reciprocal dependency during wakefulness, but unidirectional during drowsiness (anterior-to-posterior, A-P) and REM sleep (posterior-to-anterior, P-A). From these findings, both anterior and posterior cortical structures are suggested as being involved in the generation of the three alpha variants. If the implication of a double cortical generation source (anterior and posterior) of alpha variants is assumed, these two generators seem to maintain a mutual inter-dependency during wakefulness, whereas during the transition to human sleep, the anterior areas work quite independently of the posterior regions. Finally, the occipital structures may be the driving force for the REM-alpha bursts generation, since involvement of frontal regions demonstrated a high dependence on the posterior neural circuits in the genesis of this sleep event.
Spectral features of evoked micro-arousals Phasic events and dynamic organization of sleep
  • P Halasz
  • J Ujszaszi
Halasz P, Ujszaszi J. Spectral features of evoked micro-arousals. In: Terzano MG, Halasz P, Declerck AC, eds. Phasic events and dynamic organization of sleep. New York: Raven Press, 1991:85-100.
American Sleep Disorders Association (ASDA) EEG arousals: scoring rules and examples
American Sleep Disorders Association (ASDA). EEG arousals: scoring rules and examples. Sleep 1992;15:173-84.