Sleep spindle-related reactivation of category-specific cortical regions after learning face-scene associations

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Bergmann, Til O; Mölle, Matthias; Diedrichs, Jens

2012-01-01

Newly acquired declarative memory traces are believed to be reactivated during NonREM sleep to promote their hippocampo-neocortical transfer for long-term storage. Yet it remains a major challenge to unravel the underlying neuronal mechanisms. Using simultaneous electroencephalography (EEG......-coupled reactivation of brain regions representing the specific task stimuli was traced during subsequent NonREM sleep with EEG-informed fMRI. Relative to the control task, learning face-scene associations triggered a stronger combined activation of neocortical and hippocampal regions during subsequent sleep. Notably......) and functional magnetic resonance imaging (fMRI) recordings in humans, we show that sleep spindles play a key role in the reactivation of memory-related neocortical representations. On separate days, participants either learned face-scene associations or performed a visuomotor control task. Spindle...

Sleep spindle and K-complex detection using tunable Q-factor wavelet transform and morphological component analysis

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Tarek eLajnef

2015-07-01

Full Text Available A novel framework for joint detection of sleep spindles and K-complex events, two hallmarks of sleep stage S2, is proposed. Sleep electroencephalography (EEG signals are split into oscillatory (spindles and transient (K-complex components. This decomposition is conveniently achieved by applying morphological component analysis (MCA to a sparse representation of EEG segments obtained by the recently introduced discrete tunable Q-factor wavelet transform (TQWT. Tuning the Q-factor provides a convenient and elegant tool to naturally decompose the signal into an oscillatory and a transient component. The actual detection step relies on thresholding (i the transient component to reveal K-complexes and (ii the time-frequency representation of the oscillatory component to identify sleep spindles. Optimal thresholds are derived from ROC-like curves (sensitivity versus FDR on training sets and the performance of the method is assessed on test data sets. We assessed the performance of our method using full-night sleep EEG data we collected from 14 participants. In comparison to visual scoring (Expert 1, the proposed method detected spindles with a sensitivity of 83.18% and false discovery rate (FDR of 39%, while K-complexes were detected with a sensitivity of 81.57% and an FDR of 29.54%. Similar performances were obtained when using a second expert as benchmark. In addition, when the TQWT and MCA steps were excluded from the pipeline the detection sensitivities dropped down to 70% for spindles and to 76.97% for K-complexes, while the FDR rose up to 43.62% and 49.09% respectively. Finally, we also evaluated the performance of the proposed method on a set of publicly available sleep EEG recordings. Overall, the results we obtained suggest that the TQWT-MCA method may be a valuable alternative to existing spindle and K-complex detection methods. Paths for improvements and further validations with large-scale standard open-access benchmarking data sets are

Sleep-EEG in dizygotic twins discordant for Williams syndrome.

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Bódizs, Róbert; Gombos, Ferenc; Szocs, Katalin; Réthelyi, János M; Gerván, Patrícia; Kovács, Ilona

2014-01-30

Reports on twin pairs concordant and discordant for Williams syndrome were published before, but no study unravelled sleep physiology in these cases yet. We aim to fill this gap by analyzing sleep records of a twin pair discordant for Williams syndrome extending our focus on presleep wakefulness and sleep spindling. We performed multiplex ligation-dependent probe amplification of the 7q11.23 region of a 17 years old dizygotic opposite-sex twin pair discordant for Williams syndrome. Polysomnography of laboratory sleep at this age was analyzed and followed-up after 1.5 years by ambulatory polysomnography. Sleep stages scoring, EEG power spectra and sleep spindle analyses were carried out. The twin brother showed reduced levels of amplification for all of the probes in the 7q11.23 region indicating a typical deletion spanning at least 1.038 Mb between FKBP6 and CLIP2. The results of the twin sister showed normal copy numbers in the investigated region. Lower sleep times and efficiencies, as well as higher slow wave sleep percents of the twin brother were evident during both recordings. Roughly equal NREM, Stage 2 and REM sleep percents were found. EEG analyses revealed state and derivation-independent decreases in alpha power, lack of an alpha spectral peak in presleep wakefulness, as well as higher NREM sleep sigma peak frequency in the twin brother. Faster sleep spindles with lower amplitude and shorter duration characterized the records of the twin brother. Spectra show a striking reliability and correspondence between the two situations (laboratory vs. home records). Alterations in sleep and specific neural oscillations including the alpha/sigma waves are inherent aspects of Williams syndrome.

Sleep Spindle Detection and Prediction Using a Mixture of Time Series and Chaotic Features

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Amin Hekmatmanesh

2017-01-01

Full Text Available It is well established that sleep spindles (bursts of oscillatory brain electrical activity are significant indicators of learning, memory and some disease states. Therefore, many attempts have been made to detect these hallmark patterns automatically. In this pilot investigation, we paid special attention to nonlinear chaotic features of EEG signals (in combination with linear features to investigate the detection and prediction of sleep spindles. These nonlinear features included: Higuchi's, Katz's and Sevcik's Fractal Dimensions, as well as the Largest Lyapunov Exponent and Kolmogorov's Entropy. It was shown that the intensity map of various nonlinear features derived from the constructive interference of spindle signals could improve the detection of the sleep spindles. It was also observed that the prediction of sleep spindles could be facilitated by means of the analysis of these maps. Two well-known classifiers, namely the Multi-Layer Perceptron (MLP and the K-Nearest Neighbor (KNN were used to distinguish between spindle and non-spindle patterns. The MLP classifier produced a~high discriminative capacity (accuracy = 94.93%, sensitivity = 94.31% and specificity = 95.28% with significant robustness (accuracy ranging from 91.33% to 94.93%, sensitivity varying from 91.20% to 94.31%, and specificity extending from 89.79% to 95.28% in separating spindles from non-spindles. This classifier also generated the best results in predicting sleep spindles based on chaotic features. In addition, the MLP was used to find out the best time window for predicting the sleep spindles, with the experimental results reaching 97.96% accuracy.

Increased EEG sigma and beta power during NREM sleep in primary insomnia.

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Spiegelhalder, Kai; Regen, Wolfram; Feige, Bernd; Holz, Johannes; Piosczyk, Hannah; Baglioni, Chiara; Riemann, Dieter; Nissen, Christoph

2012-12-01

The hyperarousal model of primary insomnia suggests that a deficit of attenuating arousal during sleep might cause the experience of non-restorative sleep. In the current study, we examined EEG spectral power values for standard frequency bands as indices of cortical arousal and sleep protecting mechanisms during sleep in 25 patients with primary insomnia and 29 good sleeper controls. Patients with primary insomnia demonstrated significantly elevated spectral power values in the EEG beta and sigma frequency band during NREM stage 2 sleep. No differences were observed in other frequency bands or during REM sleep. Based on prior studies suggesting that EEG beta activity represents a marker of cortical arousal and EEG sleep spindle (sigma) activity is an index of sleep protective mechanisms, our findings may provide further evidence for the concept that a simultaneous activation of wake-promoting and sleep-protecting neural activity patterns contributes to the experience of non-restorative sleep in primary insomnia. Copyright © 2012 Elsevier B.V. All rights reserved.

Fast and slow spindles during the sleep slow oscillation: disparate coalescence and engagement in memory processing.

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Mölle, Matthias; Bergmann, Til O; Marshall, Lisa; Born, Jan

2011-10-01

Thalamo-cortical spindles driven by the up-state of neocortical slow (memory consolidation during sleep. We examined interactions between SOs and spindles in human slow wave sleep, focusing on the presumed existence of 2 kinds of spindles, i.e., slow frontocortical and fast centro-parietal spindles. Two experiments were performed in healthy humans (24.5 ± 0.9 y) investigating undisturbed sleep (Experiment I) and the effects of prior learning (word paired associates) vs. non-learning (Experiment II) on multichannel EEG recordings during sleep. Only fast spindles (12-15 Hz) were synchronized to the depolarizing SO up-state. Slow spindles (9-12 Hz) occurred preferentially at the transition into the SO down-state, i.e., during waning depolarization. Slow spindles also revealed a higher probability to follow rather than precede fast spindles. For sequences of individual SOs, fast spindle activity was largest for "initial" SOs, whereas SO amplitude and slow spindle activity were largest for succeeding SOs. Prior learning enhanced this pattern. The finding that fast and slow spindles occur at different times of the SO cycle points to disparate generating mechanisms for the 2 kinds of spindles. The reported temporal relationships during SO sequences suggest that fast spindles, driven by the SO up-state feed back to enhance the likelihood of succeeding SOs together with slow spindles. By enforcing such SO-spindle cycles, particularly after prior learning, fast spindles possibly play a key role in sleep-dependent memory processing.

Circadian variation of EEG power spectra in NREM and REM sleep in humans: dissociation from body temperature

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Dijk, D. J.

1999-01-01

In humans, EEG power spectra in REM and NREM sleep, as well as characteristics of sleep spindles such as their duration, amplitude, frequency and incidence, vary with circadian phase. Recently it has been hypothesized that circadian variations in EEG spectra in humans are caused by variations in brain or body temperature and may not represent phenomena relevant to sleep regulatory processes. To test this directly, a further analysis of EEG power spectra - collected in a forced desynchrony protocol in which sleep episodes were scheduled to a 28-h period while the rhythms of body temperature and plasma melatonin were oscillating at their near 24-h period - was carried out. EEG power spectra were computed for NREM and REM sleep occurring between 90-120 and 270-300 degrees of the circadian melatonin rhythm, i.e. just after the clearance of melatonin from plasma in the 'morning' and just after the 'evening' increase in melatonin secretion. Average body temperatures during scheduled sleep at these two circadian phases were identical (36.72 degrees C). Despite identical body temperatures, the power spectra in NREM sleep were very different at these two circadian phases. EEG activity in the low frequency spindle range was significantly and markedly enhanced after the evening increase in plasma melatonin as compared to the morning phase. For REM sleep, significant differences in power spectra during these two circadian phases, in particular in the alpha range, were also observed. The results confirm that EEG power spectra in NREM and REM sleep vary with circadian phase, suggesting that the direct contribution of temperature to the circadian variation in EEG power spectra is absent or only minor, and are at variance with the hypothesis that circadian variations in EEG power spectra are caused by variations in temperature.

Combining time-frequency and spatial information for the detection of sleep spindles

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Christian eO'Reilly

2015-02-01

Full Text Available EEG sleep spindles are short (0.5-2.0 s bursts of activity in the 11-16 Hz band occurring during non-rapid eye movement (NREM sleep. This sporadic activity is thought to play a role in memory consolidation, brain plasticity, and protection of sleep integrity. Many automatic detectors have been proposed to assist or replace experts for sleep spindle scoring. However, these algorithms usually detect too many events making it difficult to achieve a good tradeoff between sensitivity (Se and false detection rate (FDr. In this work, we propose a semi-automatic detector comprising a sensitivity phase based on well-established criteria followed by a specificity phase using spatial and spectral criteria.In the sensitivity phase, selected events are those which amplitude in the 10 – 16 Hz band and spectral ratio characteristics both reject a null hypothesis (p <0.1 stating that the considered event is not a spindle. This null hypothesis is constructed from events occurring during rapid eye movement (REM sleep epochs. In the specificity phase, a hierarchical clustering of the selected candidates is done based on events’ frequency and spatial position along the anterior-posterior axis. Only events from the classes grouping most (at least 80% spindles scored by an expert are kept. We obtain Se = 93.2% and FDr = 93.0% in the first phase and Se = 85.4% and FDr = 86.2% in the second phase. For these two phases, Matthew’s correlation coefficients are respectively 0.228 and 0.324. Results suggest that spindles are defined by specific spatio-spectral properties and that automatic detection methods can be improved by considering these features.

Different maturational changes of fast and slow sleep spindles in the first four years of life.

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D'Atri, Aurora; Novelli, Luana; Ferrara, Michele; Bruni, Oliviero; De Gennaro, Luigi

2018-02-01

Massive changes in brain morphology and function in the first years of life reveal a postero-anterior trajectory of cortical maturation accompanied by regional modifications of NREM sleep. One of the most sensible marker of this maturation process is represented by electroencephalographic (EEG) activity within the frequency range of sleep spindles. However, direct evidence that these changes actually reflect maturational modifications of fast and slow spindles still lacks. Our study aimed at answering the following questions: 1. Do cortical changes at 11.50 Hz frequency correspond to slow spindles? 2. Do fast and slow spindles show different age trajectories and different topographical distributions? 3. Do changes in peak frequency explain age changes of slow and fast spindles? We measured the antero-posterior changes of slow and fast spindles in the first 60 min of nightly sleep of 39 infants and children (0-48 mo.). We found that (A) changes of slow spindles from birth to childhood mostly affect frontal areas (B) variations of fast and slow spindles across age groups go in opposite direction, the latter progressively increasing across ages; (C) this process is not merely reducible to changes of spindle frequency. As a main finding, our cross-sectional study shows that the first form of mature spindle (i.e., corresponding to the adult phasic event of NREM sleep) is marked by the emergence of slow spindles on anterior regions around the age of 12 months. Copyright © 2017 Elsevier B.V. All rights reserved.

Propofol Anesthesia and Sleep: A High-Density EEG Study

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Murphy, Michael; Bruno, Marie-Aurelie; Riedner, Brady A.; Boveroux, Pierre; Noirhomme, Quentin; Landsness, Eric C.; Brichant, Jean-Francois; Phillips, Christophe; Massimini, Marcello; Laureys, Steven; Tononi, Giulio; Boly, Melanie

2011-01-01

Study Objectives: The electrophysiological correlates of anesthetic sedation remain poorly understood. We used high-density electroencephalography (hd-EEG) and source modeling to investigate the cortical processes underlying propofol anesthesia and compare them to sleep. Design: 256-channel EEG recordings in humans during propofol anesthesia. Setting: Hospital operating room. Patients or Participants: 8 healthy subjects (4 males) Interventions: N/A Measurements and Results: Initially, propofol induced increases in EEG power from 12–25 Hz. Loss of consciousness (LOC) was accompanied by the appearance of EEG slow waves that resembled the slow waves of NREM sleep. We compared slow waves in propofol to slow waves recorded during natural sleep and found that both populations of waves share similar cortical origins and preferentially propagate along the mesial components of the default network. However, propofol slow waves were spatially blurred compared to sleep slow waves and failed to effectively entrain spindle activity. Propofol also caused an increase in gamma (25–40 Hz) power that persisted throughout LOC. Source modeling analysis showed that this increase in gamma power originated from the anterior and posterior cingulate cortices. During LOC, we found increased gamma functional connectivity between these regions compared to the wakefulness. Conclusions: Propofol anesthesia is a sleep-like state and slow waves are associated with diminished consciousness even in the presence of high gamma activity. Citation: Murphy M; Bruno MA; Riedner BA; Boveroux P; Noirhomme Q; Landsness EC; Brichant JF; Phillips C; Massimini M; Laureys S; Tononi G; Boly M. Propofol anesthesia and sleep: a high-density EEG study. SLEEP 2011;34(3):283-291. PMID:21358845

Sleep spindles and intelligence: evidence for a sexual dimorphism.

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Ujma, Péter P; Konrad, Boris Nikolai; Genzel, Lisa; Bleifuss, Annabell; Simor, Péter; Pótári, Adrián; Körmendi, János; Gombos, Ferenc; Steiger, Axel; Bódizs, Róbert; Dresler, Martin

2014-12-03

Sleep spindles are thalamocortical oscillations in nonrapid eye movement sleep, which play an important role in sleep-related neuroplasticity and offline information processing. Sleep spindle features are stable within and vary between individuals, with, for example, females having a higher number of spindles and higher spindle density than males. Sleep spindles have been associated with learning potential and intelligence; however, the details of this relationship have not been fully clarified yet. In a sample of 160 adult human subjects with a broad IQ range, we investigated the relationship between sleep spindle parameters and intelligence. In females, we found a positive age-corrected association between intelligence and fast sleep spindle amplitude in central and frontal derivations and a positive association between intelligence and slow sleep spindle duration in all except one derivation. In males, a negative association between intelligence and fast spindle density in posterior regions was found. Effects were continuous over the entire IQ range. Our results demonstrate that, although there is an association between sleep spindle parameters and intellectual performance, these effects are more modest than previously reported and mainly present in females. This supports the view that intelligence does not rely on a single neural framework, and stronger neural connectivity manifesting in increased thalamocortical oscillations in sleep is one particular mechanism typical for females but not males. Copyright © 2014 the authors 0270-6474/14/3416358-11$15.00/0.

Development of Brain EEG Connectivity across Early Childhood: Does Sleep Play a Role?

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Monique K. LeBourgeois

2013-11-01

Full Text Available Sleep has beneficial effects on brain function and learning, which are reflected in plastic changes in the cortex. Early childhood is a time of rapid maturation in fundamental skills—e.g., language, cognitive control, working memory—that are predictive of future functioning. Little is currently known about the interactions between sleep and brain maturation during this developmental period. We propose coherent electroencephalogram (EEG activity during sleep may provide unique insight into maturational processes of functional brain connectivity. Longitudinal sleep EEG assessments were performed in eight healthy subjects at ages 2, 3 and 5 years. Sleep EEG coherence increased across development in a region- and frequency-specific manner. Moreover, although connectivity primarily decreased intra-hemispherically across a night of sleep, an inter-hemispheric overnight increase occurred in the frequency range of slow waves (0.8–2 Hz, theta (4.8–7.8 Hz and sleep spindles (10–14 Hz, with connectivity changes of up to 20% across a night of sleep. These findings indicate sleep EEG coherence reflects processes of brain maturation—i.e., programmed unfolding of neuronal networks—and moreover, sleep-related alterations of brain connectivity during the sensitive maturational window of early childhood.

Age-related Changes In Sleep Spindles Characteristics During Daytime Recovery Following a 25-Hour Sleep Deprivation

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Thaïna eRosinvil

2015-06-01

Full Text Available Objectives: The mechanisms underlying sleep spindles (~11-15Hz; >0.5s help to protect sleep. With age, it becomes increasingly difficult to maintain sleep at a challenging time (e.g. daytime, even after sleep loss. This study compared spindle characteristics during daytime recovery and nocturnal sleep in young and middle-aged adults. In addition, we explored whether spindles characteristics in baseline nocturnal sleep were associated with the ability to maintain sleep during daytime recovery periods in both age groups.Methods: Twenty-nine young (15 women and 14 men; 27.3 ± 5.0 and 31 middle-aged (19 women and 13 men; 51.6 y ± 5.1 healthy subjects participated in a baseline nocturnal sleep and a daytime recovery sleep after 25 hours of sleep deprivation. Spindles were detected on artefact-free NREM sleep epochs. Spindle density (nb/min, amplitude (μV, frequency (Hz and duration (s were analyzed on parasagittal (linked-ears derivations. Results: In young subjects, spindle frequency increased during daytime recovery sleep as compared to baseline nocturnal sleep in all derivations, whereas middle-aged subjects showed spindle frequency enhancement only in the prefrontal derivation. No other significant interaction between age group and sleep condition was observed. Spindle density for all derivations and centro-occipital spindle amplitude decreased whereas prefrontal spindle amplitude increased from baseline to daytime recovery sleep in both age groups. Finally, no significant correlation was found between spindle characteristics during baseline nocturnal sleep and the marked reduction in sleep efficiency during daytime recovery sleep in both young and middle-aged subjects.Conclusion: These results suggest that the interaction between homeostatic and circadian pressure module spindle frequency differently in aging. Spindle characteristics do not seem to be linked with the ability to maintain daytime recovery sleep.

Triangular relationship between sleep spindle activity, general cognitive ability and the efficiency of declarative learning.

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Caroline Lustenberger

Full Text Available EEG sleep spindle activity (SpA during non-rapid eye movement (NREM sleep has been reported to be associated with measures of intelligence and overnight performance improvements. The reticular nucleus of the thalamus is generating sleep spindles in interaction with thalamocortical connections. The same system enables efficient encoding and processing during wakefulness. Thus, we examined if the triangular relationship between SpA, measures of intelligence and declarative learning reflect the efficiency of the thalamocortical system. As expected, SpA was associated with general cognitive ability, e.g. information processing speed. SpA was also associated with learning efficiency, however, not with overnight performance improvement in a declarative memory task. SpA might therefore reflect the efficiency of the thalamocortical network and can be seen as a marker for learning during encoding in wakefulness, i.e. learning efficiency.

High-density EEG characterization of brain responses to auditory rhythmic stimuli during wakefulness and NREM sleep.

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Lustenberger, Caroline; Patel, Yogi A; Alagapan, Sankaraleengam; Page, Jessica M; Price, Betsy; Boyle, Michael R; Fröhlich, Flavio

2018-04-01

Auditory rhythmic sensory stimulation modulates brain oscillations by increasing phase-locking to the temporal structure of the stimuli and by increasing the power of specific frequency bands, resulting in Auditory Steady State Responses (ASSR). The ASSR is altered in different diseases of the central nervous system such as schizophrenia. However, in order to use the ASSR as biological markers for disease states, it needs to be understood how different vigilance states and underlying brain activity affect the ASSR. Here, we compared the effects of auditory rhythmic stimuli on EEG brain activity during wake and NREM sleep, investigated the influence of the presence of dominant sleep rhythms on the ASSR, and delineated the topographical distribution of these modulations. Participants (14 healthy males, 20-33 years) completed on the same day a 60 min nap session and two 30 min wakefulness sessions (before and after the nap). During these sessions, amplitude modulated (AM) white noise auditory stimuli at different frequencies were applied. High-density EEG was continuously recorded and time-frequency analyses were performed to assess ASSR during wakefulness and NREM periods. Our analysis revealed that depending on the electrode location, stimulation frequency applied and window/frequencies analysed the ASSR was significantly modulated by sleep pressure (before and after sleep), vigilance state (wake vs. NREM sleep), and the presence of slow wave activity and sleep spindles. Furthermore, AM stimuli increased spindle activity during NREM sleep but not during wakefulness. Thus, (1) electrode location, sleep history, vigilance state and ongoing brain activity needs to be carefully considered when investigating ASSR and (2) auditory rhythmic stimuli during sleep might represent a powerful tool to boost sleep spindles. Copyright © 2017 Elsevier Inc. All rights reserved.

REM sleep behaviour disorder is associated with lower fast and higher slow sleep spindle densities.

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O'Reilly, Christian; Godin, Isabelle; Montplaisir, Jacques; Nielsen, Tore

2015-12-01

To investigate differences in sleep spindle properties and scalp topography between patients with rapid eye movement sleep behaviour disorder (RBD) and healthy controls, whole-night polysomnograms of 35 patients diagnosed with RBD and 35 healthy control subjects matched for age and sex were compared. Recordings included a 19-lead 10-20 electroencephalogram montage and standard electromyogram, electrooculogram, electrocardiogram and respiratory leads. Sleep spindles were automatically detected using a standard algorithm, and their characteristics (amplitude, duration, density, frequency and frequency slope) compared between groups. Topological analyses of group-discriminative features were conducted. Sleep spindles occurred at a significantly (e.g. t34 = -4.49; P = 0.00008 for C3) lower density (spindles ∙ min(-1) ) for RBD (mean ± SD: 1.61 ± 0.56 for C3) than for control (2.19 ± 0.61 for C3) participants. However, when distinguishing slow and fast spindles using thresholds individually adapted to the electroencephalogram spectrum of each participant, densities smaller (31-96%) for fast but larger (20-120%) for slow spindles were observed in RBD in all derivations. Maximal differences were in more posterior regions for slow spindles, but over the entire scalp for fast spindles. Results suggest that the density of sleep spindles is altered in patients with RBD and should therefore be investigated as a potential marker of future neurodegeneration in these patients. © 2015 European Sleep Research Society.

Sleep spindles and intelligence in early childhood-developmental and trait-dependent aspects.

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Ujma, Péter P; Sándor, Piroska; Szakadát, Sára; Gombos, Ferenc; Bódizs, Róbert

2016-12-01

Sleep spindles act as a powerful marker of individual differences in cognitive ability. Sleep spindle parameters correlate with both age-related changes in cognitive abilities and with the age-independent concept of IQ. While some studies have specifically demonstrated the relationship between sleep spindles and intelligence in young children, our previous work in older subjects revealed sex differences in the sleep spindle correlates of IQ, which was never investigated in small children before. We investigated the relationship between age, Raven Colored Progressive Matrices (CPM) scores and sleep spindles in 28 young children (age 4-8 years, 15 girls). We specifically investigated sex differences in the psychometric correlates of sleep spindles. We also aimed to separate the correlates of sleep spindles that are because of age-related maturation from other effects that reflect an age-independent relationship between sleep spindles and general intelligence. Our results revealed a modest positive correlation between fast spindle amplitude and age. Raven CPM scores positively correlated with both slow and fast spindle amplitude, but this effect remained a tendency in males and vanished after correcting for the effects of age. Age-corrected correlations between Raven CPM scores and both slow and fast spindle amplitude were only significant in females. Overall, our results show that in male children sleep spindles are a maturational marker, but in female children they indicate trait-like intelligence, in line with previous studies in adolescent and adult subjects. Thalamocortical white matter connectivity may be the underlying mechanism behind both higher spindle amplitude and higher intelligence in female, but not male subjects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Transcranial electrical currents to probe EEG brain rhythms and memory consolidation during sleep in humans.

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Lisa Marshall

Full Text Available Previously the application of a weak electric anodal current oscillating with a frequency of the sleep slow oscillation (∼0.75 Hz during non-rapid eye movement sleep (NonREM sleep boosted endogenous slow oscillation activity and enhanced sleep-associated memory consolidation. The slow oscillations occurring during NonREM sleep and theta oscillations present during REM sleep have been considered of critical relevance for memory formation. Here transcranial direct current stimulation (tDCS oscillating at 5 Hz, i.e., within the theta frequency range (theta-tDCS is applied during NonREM and REM sleep. Theta-tDCS during NonREM sleep produced a global decrease in slow oscillatory activity conjoint with a local reduction of frontal slow EEG spindle power (8-12 Hz and a decrement in consolidation of declarative memory, underlining the relevance of these cortical oscillations for sleep-dependent memory consolidation. In contrast, during REM sleep theta-tDCS appears to increase global gamma (25-45 Hz activity, indicating a clear brain state-dependency of theta-tDCS. More generally, results demonstrate the suitability of oscillating-tDCS as a tool to analyze functions of endogenous EEG rhythms and underlying endogenous electric fields as well as the interactions between EEG rhythms of different frequencies.

Local sleep spindle modulations in relation to specific memory cues

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Cox, R.; Hofman, W.F.; de Boer, M.; Talamini, L.M.

2014-01-01

Sleep spindles have been connected to memory processes in various ways. In addition, spindles appear to be modulated at the local cortical network level. We investigated whether cueing specific memories during sleep leads to localized spindle modulations in humans. During learning of word-location

Transient Effect of the Noise of Passing Trucks on Sleep Eeg

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Suzuki, S.; Kawada, T.; Kiryu, Y.; Sasazawa, Y.; Tamura, Y.

1997-08-01

Twelve subjects were exposed to the noise of passing trucks at peak levels of 45, 50, 55 and 60 dB(A) for 15 min intervals throughout the night each for seven to 12 nights. Effects of the noise were observed by sleep electroencephalography (EEG). Three EEG parameters were affected by the noise event during stage 2. The number of spindles per epoch was depressed on average from 1·78 to 1·02 spindles per epoch or to 57% by the noise event of 60 dB(A), which lasted for only one minute. The threshold level for inducing the decrease was 32 dB(A), as assessed by a regression equation. Time % delta wave was depressed for six minutes, with a threshold level of 41 dB(A). The integral EMG increased in response to the noise event for one minute, and the threshold level for the integral EMG was 34 dB(A).

Effect of Daytime Exercise on Sleep Eeg and Subjective Sleep

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Sasazawa, Y.; Kawada, T.; Kiryu, Y.

1997-08-01

This study was designed to assess the effects of daytime physical exercise on the quality of objective and subjective sleep by examining all-night sleep EEGs. The subjects were five male students, aged 19 to 20 years, who were in the habit of performing regular daytime exercise. The sleep polygraphic parameters in this study were sleep stage time as a percentage of total sleep time (%S1, %S2, %S(3+4), %SREM, %MT), time in bed (TIB), sleep time (ST), total sleep time (TST), sleep onset latency (SOL), waking from sleep, sleep efficiency, number of awakenings, number of stage shifts, number of spindles, and percentages of α and δ waves, all of which were determined by an automatic computer analysis system. The OSA questionnaire was used to investigate subjective sleep. The five scales of the OSA used were sleepiness, sleep maintenance, worry, integrated sleep feeling, and sleep initiation. Each sleep parameter was compared in the exercise and the non-exercise groups. Two-way analysis of variance was applied using subject factor and exercise factor. The main effect of the subject was significant in all parameters and the main effect of exercise in %S(3+4), SOL and sleep efficiency, among the objective sleep parameters. The main effects of the subject, except sleepiness, were significant, as was the main effect of exercise on sleep initiation, among the subjective sleep parameters. These findings suggest that daytime exercise shortened sleep latency and prolonged slow-wave sleep, and that the subjects fell asleep more easily on exercise days. There were also significant individual differences in both the objective and subjective sleep parameters.

Sleep Spindles as an Electrographic Element: Description and Automatic Detection Methods

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Dorothée Coppieters ’t Wallant

2016-01-01

Full Text Available Sleep spindle is a peculiar oscillatory brain pattern which has been associated with a number of sleep (isolation from exteroceptive stimuli, memory consolidation and individual characteristics (intellectual quotient. Oddly enough, the definition of a spindle is both incomplete and restrictive. In consequence, there is no consensus about how to detect spindles. Visual scoring is cumbersome and user dependent. To analyze spindle activity in a more robust way, automatic sleep spindle detection methods are essential. Various algorithms were developed, depending on individual research interest, which hampers direct comparisons and meta-analyses. In this review, sleep spindle is first defined physically and topographically. From this general description, we tentatively extract the main characteristics to be detected and analyzed. A nonexhaustive list of automatic spindle detection methods is provided along with a description of their main processing principles. Finally, we propose a technique to assess the detection methods in a robust and comparable way.

Automatic Sleep Spindle Detection and Genetic Influence Estimation Using Continuous Wavelet Transform

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Adamczyk, M.; Genzel, L.K.E.; Dresler, M.; Steiger, A.; Friess, E.

2015-01-01

Mounting evidence for the role of sleep spindles in neuroplasticity has led to an increased interest in these non-rapid eye movement (NREM) sleep oscillations. It has been hypothesized that fast and slow spindles might play a different role in memory processing. Here, we present a new sleep spindle

Sleep spindles may predict response to cognitive-behavioral therapy for chronic insomnia.

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Dang-Vu, Thien Thanh; Hatch, Benjamin; Salimi, Ali; Mograss, Melodee; Boucetta, Soufiane; O'Byrne, Jordan; Brandewinder, Marie; Berthomier, Christian; Gouin, Jean-Philippe

2017-11-01

While cognitive-behavioral therapy for insomnia constitutes the first-line treatment for chronic insomnia, only few reports have investigated how sleep architecture relates to response to this treatment. In this pilot study, we aimed to determine whether pre-treatment sleep spindle density predicts treatment response to cognitive-behavioral therapy for insomnia. Twenty-four participants with chronic primary insomnia participated in a 6-week cognitive-behavioral therapy for insomnia performed in groups of 4-6 participants. Treatment response was assessed using the Pittsburgh Sleep Quality Index and the Insomnia Severity Index measured at pre- and post-treatment, and at 3- and 12-months' follow-up assessments. Secondary outcome measures were extracted from sleep diaries over 7 days and overnight polysomnography, obtained at pre- and post-treatment. Spindle density during stage N2-N3 sleep was extracted from polysomnography at pre-treatment. Hierarchical linear modeling analysis assessed whether sleep spindle density predicted response to cognitive-behavioral therapy. After adjusting for age, sex, and education level, lower spindle density at pre-treatment predicted poorer response over the 12-month follow-up, as reflected by a smaller reduction in Pittsburgh Sleep Quality Index over time. Reduced spindle density also predicted lower improvements in sleep diary sleep efficiency and wake after sleep onset immediately after treatment. There were no significant associations between spindle density and changes in the Insomnia Severity Index or polysomnography variables over time. These preliminary results suggest that inter-individual differences in sleep spindle density in insomnia may represent an endogenous biomarker predicting responsiveness to cognitive-behavioral therapy. Insomnia with altered spindle activity might constitute an insomnia subtype characterized by a neurophysiological vulnerability to sleep disruption associated with impaired responsiveness to

Sleep Spindles and Intelligence in Early Childhood--Developmental and Trait-Dependent Aspects

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Ujma, Péter P.; Sándor, Piroska; Szakadát, Sára; Gombos, Ferenc; Bódizs, Róbert

2016-01-01

Sleep spindles act as a powerful marker of individual differences in cognitive ability. Sleep spindle parameters correlate with both age-related changes in cognitive abilities and with the age-independent concept of IQ. While some studies have specifically demonstrated the relationship between sleep spindles and intelligence in young children, our…

Sleep Spindles as Biomarker for Early Detection of Neurodegenerative Disorders

DEFF Research Database (Denmark)

2015-01-01

The present invention relates to the use of sleep spindles as a novel biomarker for early diagnosis of synucleinopathies, in particular Parkinson's disease (PD). The method is based on automatic detection of sleep spindles. The method may be combined with measurements of one or more further...

Slow sleep spindle and procedural memory consolidation in patients with major depressive disorder

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Nishida M

2016-01-01

Full Text Available Masaki Nishida,1 Yusaku Nakashima,2 Toru Nishikawa11Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Yushima, Bunkyo, 2Medical Technology Research Laboratory, Research and Development Division, Medical Business Unit, Sony Corporation, Tokyo, JapanIntroduction: Evidence has accumulated, which indicates that, in healthy individuals, sleep enhances procedural memory consolidation, and that sleep spindle activity modulates this process. However, whether sleep-dependent procedural memory consolidation occurs in patients medicated for major depressive disorder remains unclear, as are the pharmacological and physiological mechanisms that underlie this process.Methods: Healthy control participants (n=17 and patients medicated for major depressive disorder (n=11 were recruited and subjected to a finger-tapping motor sequence test (MST; nondominant hand paradigm to compare the averaged scores of different learning phases (presleep, postsleep, and overnight improvement. Participants' brain activity was recorded during sleep with 16 electroencephalography channels (between MSTs. Sleep scoring and frequency analyses were performed on the electroencephalography data. Additionally, we evaluated sleep spindle activity, which divided the spindles into fast-frequency spindle activity (12.5–16 Hz and slow-frequency spindle activity (10.5–12.5 Hz.Result: Sleep-dependent motor memory consolidation in patients with depression was impaired in comparison with that in control participants. In patients with depression, age correlated negatively with overnight improvement. The duration of slow-wave sleep correlated with the magnitude of motor memory consolidation in patients with depression, but not in healthy controls. Slow-frequency spindle activity was associated with reduction in the magnitude of motor memory consolidation in both groups.Conclusion: Because the changes in slow

Sleep spindles during a nap correlate with post sleep memory performance for highly rewarded word-pairs.

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Studte, Sara; Bridger, Emma; Mecklinger, Axel

2017-04-01

The consolidation of new associations is thought to depend in part on physiological processes engaged during non-REM (NREM) sleep, such as slow oscillations and sleep spindles. Moreover, NREM sleep is thought to selectively benefit associations that are adaptive for the future. In line with this, the current study investigated whether different reward cues at encoding are associated with changes in sleep physiology and memory retention. Participants' associative memory was tested after learning a list of arbitrarily paired words both before and after taking a 90-min nap. During learning, word-pairs were preceded by a cue indicating either a high or a low reward for correct memory performance at test. The motivation manipulation successfully impacted retention such that memory declined to a greater extent from pre- to post sleep for low rewarded than for high rewarded word-pairs. In line with previous studies, positive correlations between spindle density during NREM sleep and general memory performance pre- and post-sleep were found. In addition to this, however, a selective positive relationship between memory performance for highly rewarded word-pairs at posttest and spindle density during NREM sleep was also observed. These results support the view that motivationally salient memories are preferentially consolidated and that sleep spindles may be an important underlying mechanism for selective consolidation. Copyright © 2016 Elsevier Inc. All rights reserved.

Sleep Spindle Characteristics in Children with Neurodevelopmental Disorders and Their Relation to Cognition

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Wise, Merrill S.

2016-01-01

Empirical evidence indicates that sleep spindles facilitate neuroplasticity and “off-line” processing during sleep, which supports learning, memory consolidation, and intellectual performance. Children with neurodevelopmental disorders (NDDs) exhibit characteristics that may increase both the risk for and vulnerability to abnormal spindle generation. Despite the high prevalence of sleep problems and cognitive deficits in children with NDD, only a few studies have examined the putative association between spindle characteristics and cognitive function. This paper reviews the literature regarding sleep spindle characteristics in children with NDD and their relation to cognition in light of what is known in typically developing children and based on the available evidence regarding children with NDD. We integrate available data, identify gaps in understanding, and recommend future research directions. Collectively, studies are limited by small sample sizes, heterogeneous populations with multiple comorbidities, and nonstandardized methods for collecting and analyzing findings. These limitations notwithstanding, the evidence suggests that future studies should examine associations between sleep spindle characteristics and cognitive function in children with and without NDD, and preliminary findings raise the intriguing question of whether enhancement or manipulation of sleep spindles could improve sleep-dependent memory and other aspects of cognitive function in this population. PMID:27478646

Sleep spindle density in narcolepsy

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Christensen, Julie Anja Engelhard; Nikolic, Miki; Hvidtfelt, Mathias

2017-01-01

BACKGROUND: Patients with narcolepsy type 1 (NT1) show alterations in sleep stage transitions, rapid-eye-movement (REM) and non-REM sleep due to the loss of hypocretinergic signaling. However, the sleep microstructure has not yet been evaluated in these patients. We aimed to evaluate whether...... the sleep spindle (SS) density is altered in patients with NT1 compared to controls and patients with narcolepsy type 2 (NT2). METHODS: All-night polysomnographic recordings from 28 NT1 patients, 19 NT2 patients, 20 controls (C) with narcolepsy-like symptoms, but with normal cerebrospinal fluid hypocretin...... levels and multiple sleep latency tests, and 18 healthy controls (HC) were included. Unspecified, slow, and fast SS were automatically detected, and SS densities were defined as number per minute and were computed across sleep stages and sleep cycles. The between-cycle trends of SS densities in N2...

Developmental Changes in Sleep Oscillations during Early Childhood

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Eckehard Olbrich

2017-01-01

Full Text Available Although quantitative analysis of the sleep electroencephalogram (EEG has uncovered important aspects of brain activity during sleep in adolescents and adults, similar findings from preschool-age children remain scarce. This study utilized our time-frequency method to examine sleep oscillations as characteristic features of human sleep EEG. Data were collected from a longitudinal sample of young children (n=8; 3 males at ages 2, 3, and 5 years. Following sleep stage scoring, we detected and characterized oscillatory events across age and examined how their features corresponded to spectral changes in the sleep EEG. Results indicated a developmental decrease in the incidence of delta and theta oscillations. Spindle oscillations, however, were almost absent at 2 years but pronounced at 5 years. All oscillatory event changes were stronger during light sleep than slow-wave sleep. Large interindividual differences in sleep oscillations and their characteristics (e.g., “ultrafast” spindle-like oscillations, theta oscillation incidence/frequency also existed. Changes in delta and spindle oscillations across early childhood may indicate early maturation of the thalamocortical system. Our analytic approach holds promise for revealing novel types of sleep oscillatory events that are specific to periods of rapid normal development across the lifespan and during other times of aberrant changes in neurobehavioral function.

Predicting EEG complexity from sleep macro and microstructure

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Chouvarda, I; Maglaveras, N; Mendez, M O; Rosso, V; Parrino, L; Grassi, A; Terzano, M; Bianchi, A M; Cerutti, S

2011-01-01

This work investigates the relation between the complexity of electroencephalography (EEG) signal, as measured by fractal dimension (FD), and normal sleep structure in terms of its macrostructure and microstructure. Sleep features are defined, encoding sleep stage and cyclic alternating pattern (CAP) related information, both in short and long term. The relevance of each sleep feature to the EEG FD is investigated, and the most informative ones are depicted. In order to quantitatively assess the relation between sleep characteristics and EEG dynamics, a modeling approach is proposed which employs subsets of the sleep macrostructure and microstructure features as input variables and predicts EEG FD based on these features of sleep micro/macrostructure. Different sleep feature sets are investigated along with linear and nonlinear models. Findings suggest that the EEG FD time series is best predicted by a nonlinear support vector machine (SVM) model, employing both sleep stage/transitions and CAP features at different time scales depending on the EEG activation subtype. This combination of features suggests that short-term and long-term history of macro and micro sleep events interact in a complex manner toward generating the dynamics of sleep

Spherical Harmonics Reveal Standing EEG Waves and Long-Range Neural Synchronization during Non-REM Sleep.

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Sivakumar, Siddharth S; Namath, Amalia G; Galán, Roberto F

2016-01-01

Previous work from our lab has demonstrated how the connectivity of brain circuits constrains the repertoire of activity patterns that those circuits can display. Specifically, we have shown that the principal components of spontaneous neural activity are uniquely determined by the underlying circuit connections, and that although the principal components do not uniquely resolve the circuit structure, they do reveal important features about it. Expanding upon this framework on a larger scale of neural dynamics, we have analyzed EEG data recorded with the standard 10-20 electrode system from 41 neurologically normal children and adolescents during stage 2, non-REM sleep. We show that the principal components of EEG spindles, or sigma waves (10-16 Hz), reveal non-propagating, standing waves in the form of spherical harmonics. We mathematically demonstrate that standing EEG waves exist when the spatial covariance and the Laplacian operator on the head's surface commute. This in turn implies that the covariance between two EEG channels decreases as the inverse of their relative distance; a relationship that we corroborate with empirical data. Using volume conduction theory, we then demonstrate that superficial current sources are more synchronized at larger distances, and determine the characteristic length of large-scale neural synchronization as 1.31 times the head radius, on average. Moreover, consistent with the hypothesis that EEG spindles are driven by thalamo-cortical rather than cortico-cortical loops, we also show that 8 additional patients with hypoplasia or complete agenesis of the corpus callosum, i.e., with deficient or no connectivity between cortical hemispheres, similarly exhibit standing EEG waves in the form of spherical harmonics. We conclude that spherical harmonics are a hallmark of spontaneous, large-scale synchronization of neural activity in the brain, which are associated with unconscious, light sleep. The analogy with spherical harmonics in

Lateralised sleep spindles relate to false memory generation.

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Shaw, John J; Monaghan, Padraic

2017-12-01

Sleep is known to enhance false memories: After presenting participants with lists of semantically related words, sleeping before recalling these words results in a greater acceptance of unseen "lure" words related in theme to previously seen words. Furthermore, the right hemisphere (RH) seems to be more prone to false memories than the left hemisphere (LH). In the current study, we investigated the sleep architecture associated with these false memory and lateralisation effects in a nap study. Participants viewed lists of related words, then stayed awake or slept for approximately 90min, and were then tested for recognition of previously seen-old, unseen-new, or unseen-lure words presented either to the LH or RH. Sleep increased acceptance of unseen-lure words as previously seen compared to the wake group, particularly for RH presentations of word lists. RH lateralised stage 2 sleep spindle density relative to the LH correlated with this increase in false memories, suggesting that RH sleep spindles enhanced false memories in the RH. Copyright © 2017 Elsevier Ltd. All rights reserved.

Declarative memory performance is associated with the number of sleep spindles in elderly women.

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Seeck-Hirschner, Mareen; Baier, Paul Christian; Weinhold, Sara Lena; Dittmar, Manuela; Heiermann, Steffanie; Aldenhoff, Josef B; Göder, Robert

2012-09-01

Recent evidence suggests that the sleep-dependent consolidation of declarative memory relies on the nonrapid eye movement rather than the rapid eye movement phase of sleep. In addition, it is known that aging is accompanied by changes in sleep and memory processes. Hence, the purpose of this study was to investigate the overnight consolidation of declarative memory in healthy elderly women. Sleep laboratory of University. Nineteen healthy elderly women (age range: 61-74 years). We used laboratory-based measures of sleep. To test declarative memory, the Rey-Osterrieth Complex Figure Test was performed. Declarative memory performance in elderly women was associated with Stage 2 sleep spindle density. Women characterized by high memory performance exhibited significantly higher numbers of sleep spindles and higher spindle density compared with women with generally low memory performance. The data strongly support theories suggesting a link between sleep spindle activity and declarative memory consolidation.

Sleep Spindle Density Predicts the Effect of Prior Knowledge on Memory Consolidation

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Lambon Ralph, Matthew A.; Kempkes, Marleen; Cousins, James N.; Lewis, Penelope A.

2016-01-01

Information that relates to a prior knowledge schema is remembered better and consolidates more rapidly than information that does not. Another factor that influences memory consolidation is sleep and growing evidence suggests that sleep-related processing is important for integration with existing knowledge. Here, we perform an examination of how sleep-related mechanisms interact with schema-dependent memory advantage. Participants first established a schema over 2 weeks. Next, they encoded new facts, which were either related to the schema or completely unrelated. After a 24 h retention interval, including a night of sleep, which we monitored with polysomnography, participants encoded a second set of facts. Finally, memory for all facts was tested in a functional magnetic resonance imaging scanner. Behaviorally, sleep spindle density predicted an increase of the schema benefit to memory across the retention interval. Higher spindle densities were associated with reduced decay of schema-related memories. Functionally, spindle density predicted increased disengagement of the hippocampus across 24 h for schema-related memories only. Together, these results suggest that sleep spindle activity is associated with the effect of prior knowledge on memory consolidation. SIGNIFICANCE STATEMENT Episodic memories are gradually assimilated into long-term memory and this process is strongly influenced by sleep. The consolidation of new information is also influenced by its relationship to existing knowledge structures, or schemas, but the role of sleep in such schema-related consolidation is unknown. We show that sleep spindle density predicts the extent to which schemas influence the consolidation of related facts. This is the first evidence that sleep is associated with the interaction between prior knowledge and long-term memory formation. PMID:27030764

White Matter Structure in Older Adults Moderates the Benefit of Sleep Spindles on Motor Memory Consolidation.

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Mander, Bryce A; Zhu, Alyssa H; Lindquist, John R; Villeneuve, Sylvia; Rao, Vikram; Lu, Brandon; Saletin, Jared M; Ancoli-Israel, Sonia; Jagust, William J; Walker, Matthew P

2017-11-29

Sleep spindles promote the consolidation of motor skill memory in young adults. Older adults, however, exhibit impoverished sleep-dependent motor memory consolidation. The underlying pathophysiological mechanism(s) explaining why motor memory consolidation in older adults fails to benefit from sleep remains unclear. Here, we demonstrate that male and female older adults show impoverished overnight motor skill memory consolidation relative to young adults, with the extent of impairment being associated with the degree of reduced frontal fast sleep spindle density. The magnitude of the loss of frontal fast sleep spindles in older adults was predicted by the degree of reduced white matter integrity throughout multiple white matter tracts known to connect subcortical and cortical brain regions. We further demonstrate that the structural integrity of selective white matter fiber tracts, specifically within right posterior corona radiata, right tapetum, and bilateral corpus callosum, statistically moderates whether sleep spindles promoted overnight consolidation of motor skill memory. Therefore, white matter integrity within tracts known to connect cortical sensorimotor control regions dictates the functional influence of sleep spindles on motor skill memory consolidation in the elderly. The deterioration of white matter fiber tracts associated with human brain aging thus appears to be one pathophysiological mechanism influencing subcortical-cortical propagation of sleep spindles and their related memory benefits. SIGNIFICANCE STATEMENT Numerous studies have shown that sleep spindle expression is reduced and sleep-dependent motor memory is impaired in older adults. However, the mechanisms underlying these alterations have remained unknown. The present study reveals that age-related degeneration of white matter within select fiber tracts is associated with reduced sleep spindles in older adults. We further demonstrate that, within these same fiber tracts, the degree of

A comparison of two sleep spindle detection methods based on all night averages: individually adjusted versus fixed frequencies

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Péter Przemyslaw Ujma

2015-02-01

Full Text Available Sleep spindles are frequently studied for their relationship with state and trait cognitive variables, and they are thought to play an important role in sleep-related memory consolidation. Due to their frequent occurrence in NREM sleep, the detection of sleep spindles is only feasible using automatic algorithms, of which a large number is available. We compared subject averages of the spindle parameters computed by a fixed frequency (11-13 Hz for slow spindles, 13-15 Hz for fast spindles automatic detection algorithm and the individual adjustment method (IAM, which uses individual frequency bands for sleep spindle detection. Fast spindle duration and amplitude are strongly correlated in the two algorithms, but there is little overlap in fast spindle density and slow spindle parameters in general. The agreement between fixed and manually determined sleep spindle frequencies is limited, especially in case of slow spindles. This is the most likely reason for the poor agreement between the two detection methods in case of slow spindle parameters. Our results suggest that while various algorithms may reliably detect fast spindles, a more sophisticated algorithm primed to individual spindle frequencies is necessary for the detection of slow spindles as well as individual variations in the number of spindles in general.

Topographical characteristics and principal component structure of the hypnagogic EEG.

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Tanaka, H; Hayashi, M; Hori, T

1997-07-01

The purpose of the present study was to identify the dominant topographic components of electroencephalographs (EEG) and their behavior during the waking-sleeping transition period. Somnography of nocturnal sleep was recorded on 10 male subjects. Each recording, from "lights-off" to 5 minutes after the appearance of the first sleep spindle, was analyzed. The typical EEG patterns during hypnagogic period were classified into nine EEG stages. Topographic maps demonstrated that the dominant areas of alpha-band activity moved from the posterior areas to anterior areas along the midline of the scalp. In delta-, theta-, and sigma-band activities, the differences of EEG amplitude between the focus areas (the dominant areas) and the surrounding areas increased as a function of EEG stage. To identify the dominant topographic components, a principal component analysis was carried out on a 12-channel EEG data set for each of six frequency bands. The dominant areas of alpha 2- (9.6-11.4 Hz) and alpha 3- (11.6-13.4 Hz) band activities moved from the posterior to anterior areas, respectively. The distribution of alpha 2-band activity on the scalp clearly changed just after EEG stage 3 (alpha intermittent, < 50%). On the other hand, alpha 3-band activity became dominant in anterior areas after the appearance of vertex sharp-wave bursts (EEG stage 7). For the sigma band, the amplitude of extensive areas from the frontal pole to the parietal showed a rapid rise after the onset of stage 7 (the appearance of vertex sharp-wave bursts). Based on the results, sleep onset process probably started before the onset of sleep stage 1 in standard criteria. On the other hand, the basic sleep process may start before the onset of sleep stage 2 or the manually scored spindles.

Singular spectrum analysis of sleep EEG in insomnia.

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Aydın, Serap; Saraoǧlu, Hamdi Melih; Kara, Sadık

2011-08-01

In the present study, the Singular Spectrum Analysis (SSA) is applied to sleep EEG segments collected from healthy volunteers and patients diagnosed by either psycho physiological insomnia or paradoxical insomnia. Then, the resulting singular spectra computed for both C3 and C4 recordings are assigned as the features to the Artificial Neural Network (ANN) architectures for EEG classification in diagnose. In tests, singular spectrum of particular sleep stages such as awake, REM, stage1 and stage2, are considered. Three clinical groups are successfully classified by using one hidden layer ANN architecture with respect to their singular spectra. The results show that the SSA can be applied to sleep EEG series to support the clinical findings in insomnia if ten trials are available for the specific sleep stages. In conclusion, the SSA can detect the oscillatory variations on sleep EEG. Therefore, different sleep stages meet different singular spectra. In addition, different healthy conditions generate different singular spectra for each sleep stage. In summary, the SSA can be proposed for EEG discrimination to support the clinical findings for psycho-psychological disorders.

Sleep spindles are related to schizotypal personality traits and thalamic glutamine/glutamate in healthy subjects.

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Lustenberger, Caroline; O'Gorman, Ruth L; Pugin, Fiona; Tüshaus, Laura; Wehrle, Flavia; Achermann, Peter; Huber, Reto

2015-03-01

Schizophrenia is a severe mental disorder affecting approximately 1% of the worldwide population. Yet, schizophrenia-like experiences (schizotypy) are very common in the healthy population, indicating a continuum between normal mental functioning and the psychosis found in schizophrenic patients. A continuum between schizotypy and schizophrenia would be supported if they share the same neurobiological origin. Two such neurobiological markers of schizophrenia are: (1) a reduction of sleep spindles (12-15 Hz oscillations during nonrapid eye movement sleep), likely reflecting deficits in thalamo-cortical circuits and (2) increased glutamine and glutamate (Glx) levels in the thalamus. Thus, this study aimed to investigate whether sleep spindles and Glx levels are related to schizotypal personality traits in healthy subjects. Twenty young male subjects underwent 2 all-night sleep electroencephalography recordings (128 electrodes). Sleep spindles were detected automatically. After those 2 nights, thalamic Glx levels were measured by magnetic resonance spectroscopy. Subjects completed a magical ideation scale to assess schizotypy. Sleep spindle density was negatively correlated with magical ideation (r = -.64, P .1). The common relationship of sleep spindle density with schizotypy and thalamic Glx levels indicates a neurobiological overlap between nonclinical schizotypy and schizophrenia. Thus, sleep spindle density and magical ideation may reflect the anatomy and efficiency of the thalamo-cortical system that shows pronounced impairment in patients with schizophrenia. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Statistical features of hypnagogic EEG measured by a new scoring system.

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Tanaka, H; Hayashi, M; Hori, T

1996-11-01

The purpose of this study was to examine the durations of individual occurrences of each of nine hypnagogic electroencephalographic (EEG) stages and the interchange relationship among these stages. Most of the alpha patterns (stages 1, 2, and 3), ripples (stage 5), and spindles (stage 9) tended to last > 2 minutes. On the other hand, histograms of the durations of time in EEG flattening (stage 4) and vertex sharp wave (stages 6, 7, and 8) patterns had peaks that lasted hypnagogic state. This was especially true for the first five stages. EEG stages with vertex sharp waves (stages 6, 7, and 8), however, showed less-smooth changes, with approximately 20% of all changes involving a jump of more than one stage. These results show that the basic EEG activities in the sleep onset period are the alpha, theta, and sleep spindles activities, whereas the activities of vertex sharp waves seem to have a secondary or enhancing role, instead of independent characteristics.

Recognizing of stereotypic patterns in epileptic EEG using empirical modes and wavelets

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Grubov, V. V.; Sitnikova, E.; Pavlov, A. N.; Koronovskii, A. A.; Hramov, A. E.

2017-11-01

Epileptic activity in the form of spike-wave discharges (SWD) appears in the electroencephalogram (EEG) during absence seizures. This paper evaluates two approaches for detecting stereotypic rhythmic activities in EEG, i.e., the continuous wavelet transform (CWT) and the empirical mode decomposition (EMD). The CWT is a well-known method of time-frequency analysis of EEG, whereas EMD is a relatively novel approach for extracting signal's waveforms. A new method for pattern recognition based on combination of CWT and EMD is proposed. It was found that this combined approach resulted to the sensitivity of 86.5% and specificity of 92.9% for sleep spindles and 97.6% and 93.2% for SWD, correspondingly. Considering strong within- and between-subjects variability of sleep spindles, the obtained efficiency in their detection was high in comparison with other methods based on CWT. It is concluded that the combination of a wavelet-based approach and empirical modes increases the quality of automatic detection of stereotypic patterns in rat's EEG.

PHYSIOLOGIC PATTERNS OF SLEEP ON EEG, MASKING OF EPILEPTIFORM ACTIVITY

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L. Yu. Glukhova

2013-01-01

Full Text Available Physiologic patterns of sleep on EEG can sometimes be similar to epileptiform activity and even to the EEG pattern of epileptic seizures, but they have no connection to epilepsy and their incorrect interpretation may lead to overdiagnosis of epilepsy. These sleep patterns include vertex transients, K-complexes, hypnagogic hypersynchrony, 14 and 6 Hz positive bursts, wicket-potentials, etc. The main distinctive features of acute physiological phenomena of sleep unlike epileptiform activity are stereotyped, monomorphic morphology of waves, which frequently has rhythmic, arcuate pattern, often with change of lateralization, mainly dominated in the first stages of sleep (N1-N2, with their reduction in the deeper stages and transition to delta sleep (N3. The correct interpretation of physiological sharp-wave phenomena of sleep on EEG requires considerable training and experience of the physician. Our review includes a variety of physiological sleep patterns, which can mimic epileptiform activity on EEG, their criteria of diagnostic with demonstration of own illustrations of EEG.

REM Sleep EEG Instability in REM Sleep Behavior Disorder and Clonazepam Effects.

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Ferri, Raffaele; Rundo, Francesco; Silvani, Alessandro; Zucconi, Marco; Bruni, Oliviero; Ferini-Strambi, Luigi; Plazzi, Giuseppe; Manconi, Mauro

2017-08-01

We aimed to analyze quantitatively rapid eye movement (REM) sleep electroencephalogram (EEG) in controls, drug-naïve idiopathic REM sleep behavior disorder patients (iRBD), and iRBD patients treated with clonazepam. Twenty-nine drug-naïve iRBD patients (mean age 68.2 years), 14 iRBD patients under chronic clonazepam therapy (mean age 66.3 years), and 21 controls (mean age 66.8 years) were recruited. Power spectra were obtained from sleep EEG (central derivation), using a 2-second sliding window, with 1-second steps. The power values of each REM sleep EEG spectral band (one every second) were normalized with respect to the average power value obtained during sleep stage 2 in the same individual. In drug-naïve patients, the normalized power values showed a less pronounced REM-related decrease of power in all bands with frequency sleep EEG structure changes found in this study disclose subtle but significant alterations in the cortical electrophysiology of RBD that might represent the early expression of the supposed neurodegenerative processes already taking place at this stage of the disease and might be the target of better and effective future therapeutic strategies for this condition. © Sleep Research Society 2017. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

The effects of eszopiclone on sleep spindles and memory consolidation in schizophrenia: a randomized placebo-controlled trial.

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Wamsley, Erin J; Shinn, Ann K; Tucker, Matthew A; Ono, Kim E; McKinley, Sophia K; Ely, Alice V; Goff, Donald C; Stickgold, Robert; Manoach, Dara S

2013-09-01

In schizophrenia there is a dramatic reduction of sleep spindles that predicts deficient sleep-dependent memory consolidation. Eszopiclone (Lunesta), a non-benzodiazepine hypnotic, acts on γ-aminobutyric acid (GABA) neurons in the thalamic reticular nucleus where spindles are generated. We investigated whether eszopiclone could increase spindles and thereby improve memory consolidation in schizophrenia. In a double-blind design, patients were randomly assigned to receive either placebo or 3 mg of eszopiclone. Patients completed Baseline and Treatment visits, each consisting of two consecutive nights of polysomnography. On the second night of each visit, patients were trained on the motor sequence task (MST) at bedtime and tested the following morning. Academic research center. Twenty-one chronic, medicated schizophrenia outpatients. We compared the effects of two nights of eszopiclone vs. placebo on stage 2 sleep spindles and overnight changes in MST performance. Eszopiclone increased the number and density of spindles over baseline levels significantly more than placebo, but did not significantly enhance overnight MST improvement. In the combined eszopiclone and placebo groups, spindle number and density predicted overnight MST improvement. Eszopiclone significantly increased sleep spindles, which correlated with overnight motor sequence task improvement. These findings provide partial support for the hypothesis that the spindle deficit in schizophrenia impairs sleep-dependent memory consolidation and may be ameliorated by eszopiclone. Larger samples may be needed to detect a significant effect on memory. Given the general role of sleep spindles in cognition, they offer a promising novel potential target for treating cognitive deficits in schizophrenia.

Automatic sleep spindle detection: Benchmarking with fine temporal resolution using open science tools

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Christian eO'Reilly

2015-06-01

Full Text Available Sleep spindle properties index cognitive faculties such as memory consolidation and diseases such as major depression. For this reason, scoring sleep spindle properties in polysomnographic recordings has become an important activity in both research and clinical settings. The tediousness of this manual task has motivated efforts for its automation. Although some progress has been made, increasing the temporal accuracy of spindle scoring and improving the performance assessment methodology are two aspects needing more attention. In this paper, four open-access automated spindle detectors with fine temporal resolution are proposed and tested against expert scoring of two proprietary and two open-access databases. Results highlight several findings: 1 that expert scoring and polysomnographic databases are important confounders when comparing the performance of spindle detectors tested using different databases or scorings; 2 because spindles are sparse events, specificity estimates are potentially misleading for assessing automated detector performance; 3 reporting the performance of spindle detectors exclusively with sensitivity and specificity estimates, as is often seen in the literature, is insufficient; including sensitivity, precision and a more comprehensive statistic such as Matthew’s correlation coefficient, F1-score, or Cohen’s κ is necessary for adequate evaluation; 4 reporting statistics for some reasonable range of decision thresholds provides a much more complete and useful benchmarking; 5 performance differences between tested automated detectors were found to be similar to those between available expert scorings; 6 much more development is needed to effectively compare the performance of spindle detectors developed by different research teams. Finally, this work clarifies a long-standing but only seldom posed question regarding whether expert scoring truly is a reliable gold standard for sleep spindle assessment.

Parietal Fast Sleep Spindle Density Decrease in Alzheimer's Disease and Amnesic Mild Cognitive Impairment

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Gorgoni, Maurizio; Lauri, Giulia; Truglia, Ilaria; Cordone, Susanna; Sarasso, Simone; Scarpelli, Serena; Mangiaruga, Anastasia; D'Atri, Aurora; Tempesta, Daniela; Ferrara, Michele; Marra, Camillo; Rossini, Paolo Maria; De Gennaro, Luigi

2016-01-01

Several studies have identified two types of sleep spindles: fast (13–15 Hz) centroparietal and slow (11–13 Hz) frontal spindles. Alterations in spindle activity have been observed in Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI). Only few studies have separately assessed fast and slow spindles in these patients showing a reduction of fast spindle count, but the possible local specificity of this phenomenon and its relation to cognitive decline severity are not clear. Moreover, fast and slow spindle density have never been assessed in AD/MCI. We have assessed fast and slow spindles in 15 AD patients, 15 amnesic MCI patients, and 15 healthy elderly controls (HC). Participants underwent baseline polysomnographic recording (19 cortical derivations). Spindles during nonrapid eye movements sleep were automatically detected, and spindle densities of the three groups were compared in the derivations where fast and slow spindles exhibited their maximum expression (parietal and frontal, resp.). AD and MCI patients showed a significant parietal fast spindle density decrease, positively correlated with Minimental State Examination scores. Our results suggest that AD-related changes in spindle density are specific for frequency and location, are related to cognitive decline severity, and may have an early onset in the pathology development. PMID:27066274

Insomnia and sleep misperception.

Science.gov (United States)

Bastien, C H; Ceklic, T; St-Hilaire, P; Desmarais, F; Pérusse, A D; Lefrançois, J; Pedneault-Drolet, M

2014-10-01

Sleep misperception is often observed in insomnia individuals (INS). The extent of misperception varies between different types of INS. The following paper comprised sections which will be aimed at studying the sleep EEG and compares it to subjective reports of sleep in individuals suffering from either psychophysiological insomnia or paradoxical insomnia and good sleeper controls. The EEG can be studied without any intervention (thus using the raw data) via either PSG or fine quantitative EEG analyses (power spectral analysis [PSA]), identifying EEG patterns as in the case of cyclic alternating patterns (CAPs) or by decorticating the EEG while scoring the different transient or phasic events (K-Complexes or sleep spindles). One can also act on the on-going EEG by delivering stimuli so to study their impact on cortical measures as in the case of event-related potential studies (ERPs). From the paucity of studies available using these different techniques, a general conclusion can be reached: sleep misperception is not an easy phenomenon to quantify and its clinical value is not well recognized. Still, while none of the techniques or EEG measures defined in the paper is available and/or recommended to diagnose insomnia, ERPs might be the most indicated technique to study hyperarousal and sleep quality in different types of INS. More research shall also be dedicated to EEG patterns and transient phasic events as these EEG scoring techniques can offer a unique insight of sleep misperception. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Assessment of sleep quality in powernapping

DEFF Research Database (Denmark)

Kooravand Takht Sabzy, Bashaer; Thomsen, Carsten E

2011-01-01

The purpose of this study is to assess the Sleep Quality (SQ) in powernapping. The contributed factors for SQ assessment are time of Sleep Onset (SO), Sleep Length (SL), Sleep Depth (SD), and detection of sleep events (K-complex (KC) and Sleep Spindle (SS)). Data from daytime nap for 10 subjects, 2...... days each, including EEG and ECG were recorded. The SD and sleep events were analyzed by applying spectral analysis. The SO time was detected by a combination of signal spectral analysis, Slow Rolling Eye Movement (SREM) detection, Heart Rate Variability (HRV) analysis and EEG segmentation using both...... Autocorrelation Function (ACF), and Crosscorrelation Function (CCF) methods. The EEG derivation FP1-FP2 filtered in a narrow band and used as an alternative to EOG for SREM detection. The ACF and CCF segmentation methods were also applied for detection of sleep events. The ACF method detects segment boundaries...

Overnight improvements in two REM sleep-sensitive tasks are associated with both REM and NREM sleep changes, sleep spindle features, and awakenings for dream recall.

Science.gov (United States)

Nielsen, T; O'Reilly, C; Carr, M; Dumel, G; Godin, I; Solomonova, E; Lara-Carrasco, J; Blanchette-Carrière, C; Paquette, T

2015-07-01

Memory consolidation is associated with sleep physiology but the contribution of specific sleep stages remains controversial. To clarify the contribution of REM sleep, participants were administered two REM sleep-sensitive tasks to determine if associated changes occurred only in REM sleep. Twenty-two participants (7 men) were administered the Corsi Block Tapping and Tower of Hanoi tasks prior to and again after a night of sleep. Task improvers and non-improvers were compared for sleep structure, sleep spindles, and dream recall. Control participants (N = 15) completed the tasks twice during the day without intervening sleep. Overnight Corsi Block improvement was associated with more REM sleep whereas Tower of Hanoi improvement was associated with more N2 sleep. Corsi Block improvement correlated positively with %REM sleep and Tower of Hanoi improvement with %N2 sleep. Post-hoc analyses suggest Tower of Hanoi effects-but not Corsi Block effects-are due to trait differences. Sleep spindle density was associated with Tower of Hanoi improvement whereas spindle amplitude correlated with Corsi Block improvement. Number of REM awakenings for dream reporting (but not dream recall per se) was associated with Corsi Block, but not Tower of Hanoi, improvement but was confounded with REM sleep time. This non-replication of one of 2 REM-sensitive task effects challenges both 'dual-process' and 'sequential' or 'sleep organization' models of sleep-dependent learning and points rather to capacity limitations on REM sleep. Experimental awakenings for sampling dream mentation may not perturb sleep-dependent learning effects; they may even enhance them. Copyright © 2014 Elsevier Inc. All rights reserved.

Occurrence of epileptiform discharges and sleep during EEG recordings in children after melatonin intake versus sleep-deprivation.

Science.gov (United States)

Gustafsson, Greta; Broström, Anders; Ulander, Martin; Vrethem, Magnus; Svanborg, Eva

2015-08-01

To determine if melatonin is equally efficient as partial sleep deprivation in inducing sleep without interfering with epileptiform discharges in EEG recordings in children 1-16 years old. We retrospectively analysed 129 EEGs recorded after melatonin intake and 113 EEGs recorded after partial sleep deprivation. Comparisons were made concerning occurrence of epileptiform discharges, the number of children who fell asleep and the technical quality of EEG recordings. Comparison between different age groups was also made. No significant differences were found regarding occurrence of epileptiform discharges (33% after melatonin intake, 36% after sleep deprivation), or proportion of unsuccessful EEGs (8% and 10%, respectively). Melatonin and sleep deprivation were equally efficient in inducing sleep (70% in both groups). Significantly more children aged 1-4 years obtained sleep after melatonin intake in comparison to sleep deprivation (82% vs. 58%, p⩽0.01), and in comparison to older children with melatonin induced sleep (58-67%, p⩽0.05). Sleep deprived children 9-12 years old had higher percentage of epileptiform discharges (62%, p⩽0.05) compared to younger sleep deprived children. Melatonin is equally efficient as partial sleep deprivation to induce sleep and does not affect the occurrence of epileptiform discharges in the EEG recording. Sleep deprivation could still be preferable in older children as melatonin probably has less sleep inducing effect. Melatonin induced sleep have advantages, especially in younger children as they fall asleep easier than after sleep deprivation. The procedure is easier for the parents than keeping a young child awake for half the night. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Removal of ocular artifacts from the REM sleep EEG

NARCIS (Netherlands)

Waterman, D.; Woestenburg, J.C.; Elton, M.; Hofman, W.; Kok, A.

1992-01-01

The present report concerns the first study in which electrooculographic (EOG) contamination of electroencephalographic (EEG) recordings in rapid eye movement (REM) sleep is systematically investigated. Contamination of REM sleep EEG recordings in six subjects was evaluated in the frequency domain.

Sleep in the human hippocampus: a stereo-EEG study.

Directory of Open Access Journals (Sweden)

Fabio Moroni

Full Text Available BACKGROUND: There is compelling evidence indicating that sleep plays a crucial role in the consolidation of new declarative, hippocampus-dependent memories. Given the increasing interest in the spatiotemporal relationships between cortical and hippocampal activity during sleep, this study aimed to shed more light on the basic features of human sleep in the hippocampus. METHODOLOGY/PRINCIPAL FINDINGS: We recorded intracerebral stereo-EEG directly from the hippocampus and neocortical sites in five epileptic patients undergoing presurgical evaluations. The time course of classical EEG frequency bands during the first three NREM-REM sleep cycles of the night was evaluated. We found that delta power shows, also in the hippocampus, the progressive decrease across sleep cycles, indicating that a form of homeostatic regulation of delta activity is present also in this subcortical structure. Hippocampal sleep was also characterized by: i a lower relative power in the slow oscillation range during NREM sleep compared to the scalp EEG; ii a flattening of the time course of the very low frequencies (up to 1 Hz across sleep cycles, with relatively high levels of power even during REM sleep; iii a decrease of power in the beta band during REM sleep, at odds with the typical increase of power in the cortical recordings. CONCLUSIONS/SIGNIFICANCE: Our data imply that cortical slow oscillation is attenuated in the hippocampal structures during NREM sleep. The most peculiar feature of hippocampal sleep is the increased synchronization of the EEG rhythms during REM periods. This state of resonance may have a supportive role for the processing/consolidation of memory.

Odds Ratio Product of Sleep EEG as a Continuous Measure of Sleep State

Science.gov (United States)

Younes, Magdy; Ostrowski, Michele; Soiferman, Marc; Younes, Henry; Younes, Mark; Raneri, Jill; Hanly, Patrick

2015-01-01

Study Objectives: To develop and validate an algorithm that provides a continuous estimate of sleep depth from the electroencephalogram (EEG). Design: Retrospective analysis of polysomnograms. Setting: Research laboratory. Participants: 114 patients who underwent clinical polysomnography in sleep centers at the University of Manitoba (n = 58) and the University of Calgary (n = 56). Interventions: None. Measurements and Results: Power spectrum of EEG was determined in 3-second epochs and divided into delta, theta, alpha-sigma, and beta frequency bands. The range of powers in each band was divided into 10 aliquots. EEG patterns were assigned a 4-digit number that reflects the relative power in the 4 frequency ranges (10,000 possible patterns). Probability of each pattern occurring in 30-s epochs staged awake was determined, resulting in a continuous probability value from 0% to 100%. This was divided by 40 (% of epochs staged awake) producing the odds ratio product (ORP), with a range of 0–2.5. In validation testing, average ORP decreased progressively as EEG progressed from wakefulness (2.19 ± 0.29) to stage N3 (0.13 ± 0.05). ORP sleep and ORP > 2.0 predicted wakefulness in > 95% of 30-s epochs. Epochs with intermediate ORP occurred in unstable sleep with a high arousal index (> 70/h) and were subject to much interrater scoring variability. There was an excellent correlation (r2 = 0.98) between ORP in current 30-s epochs and the likelihood of arousal or awakening occurring in the next 30-s epoch. Conclusions: Our results support the use of the odds ratio product (ORP) as a continuous measure of sleep depth. Citation: Younes M, Ostrowski M, Soiferman M, Younes H, Younes M, Raneri J, Hanly P. Odds ratio product of sleep EEG as a continuous measure of sleep state. SLEEP 2015;38(4):641–654. PMID:25348125

Regional reductions in sleep electroencephalography power in obstructive sleep apnea: a high-density EEG study.

Science.gov (United States)

Jones, Stephanie G; Riedner, Brady A; Smith, Richard F; Ferrarelli, Fabio; Tononi, Giulio; Davidson, Richard J; Benca, Ruth M

2014-02-01

Obstructive sleep apnea (OSA) is associated with significant alterations in neuronal integrity resulting from either hypoxemia and/or sleep loss. A large body of imaging research supports reductions in gray matter volume, alterations in white matter integrity and resting state activity, and functional abnormalities in response to cognitive challenge in various brain regions in patients with OSA. In this study, we used high-density electroencephalography (hdEEG), a functional imaging tool that could potentially be used during routine clinical care, to examine the regional distribution of neural activity in a non-clinical sample of untreated men and women with moderate/severe OSA. Sleep was recorded with 256-channel EEG in relatively healthy subjects with apnea-hypopnea index (AHI) > 10, as well as age-, sex-, and body mass index-matched controls selected from a research population initially recruited for a study on sleep and meditation. Sleep laboratory. Nine subjects with AHI > 10 and nine matched controls. N/A. Topographic analysis of hdEEG data revealed a broadband reduction in EEG power in a circumscribed region overlying the parietal cortex in OSA subjects. This parietal reduction in neural activity was present, to some extent, across all frequency bands in all stages and episodes of nonrapid eye movement sleep. This investigation suggests that regional deficits in electroencephalography (EEG) power generation may be a useful clinical marker for neural disruption in obstructive sleep apnea, and that high-density EEG may have the sensitivity to detect pathological cortical changes early in the disease process.

The multiple time scales of sleep dynamics as a challenge for modelling the sleeping brain.

Science.gov (United States)

Olbrich, Eckehard; Claussen, Jens Christian; Achermann, Peter

2011-10-13

A particular property of the sleeping brain is that it exhibits dynamics on very different time scales ranging from the typical sleep oscillations such as sleep spindles and slow waves that can be observed in electroencephalogram (EEG) segments of several seconds duration over the transitions between the different sleep stages on a time scale of minutes to the dynamical processes involved in sleep regulation with typical time constants in the range of hours. There is an increasing body of work on mathematical and computational models addressing these different dynamics, however, usually considering only processes on a single time scale. In this paper, we review and present a new analysis of the dynamics of human sleep EEG at the different time scales and relate the findings to recent modelling efforts pointing out both the achievements and remaining challenges.

High Resolution Topography of Age-Related Changes in Non-Rapid Eye Movement Sleep Electroencephalography.

Directory of Open Access Journals (Sweden)

Kate E Sprecher

Full Text Available Sleeping brain activity reflects brain anatomy and physiology. The aim of this study was to use high density (256 channel electroencephalography (EEG during sleep to characterize topographic changes in sleep EEG power across normal aging, with high spatial resolution. Sleep was evaluated in 92 healthy adults aged 18-65 years old using full polysomnography and high density EEG. After artifact removal, spectral power density was calculated for standard frequency bands for all channels, averaged across the NREM periods of the first 3 sleep cycles. To quantify topographic changes with age, maps were generated of the Pearson's coefficient of the correlation between power and age at each electrode. Significant correlations were determined by statistical non-parametric mapping. Absolute slow wave power declined significantly with increasing age across the entire scalp, whereas declines in theta and sigma power were significant only in frontal regions. Power in fast spindle frequencies declined significantly with increasing age frontally, whereas absolute power of slow spindle frequencies showed no significant change with age. When EEG power was normalized across the scalp, a left centro-parietal region showed significantly less age-related decline in power than the rest of the scalp. This partial preservation was particularly significant in the slow wave and sigma bands. The effect of age on sleep EEG varies substantially by region and frequency band. This non-uniformity should inform the design of future investigations of aging and sleep. This study provides normative data on the effect of age on sleep EEG topography, and provides a basis from which to explore the mechanisms of normal aging as well as neurodegenerative disorders for which age is a risk factor.

Comparison of quantitative EEG characteristics of quiet and active sleep in newborns.

Science.gov (United States)

Paul, Karel; Krajca, Vladimír; Roth, Zdenek; Melichar, Jan; Petránek, Svojmil

2003-11-01

The aim of the present study was to verify whether the proposed method of computer-supported EEG analysis is able to differentiate the EEG activity in quiet sleep (QS) from that in active sleep (AS) in newborns. A quantitative description of the neonatal EEG may contribute to a more exact evaluation of the functional state of the brain, as well as to a refinement of diagnostics of brain dysfunction manifesting itself frequently as 'dysrhythmia' or 'dysmaturity'. Twenty-one healthy newborns (10 full-term and 11 pre-term) were examined polygraphically (EEG-eight channels, respiration, ECG, EOG and EMG) in the course of sleep. From each EEG record, two 5-min samples (one from QS and one from AS) were subject to an off-line computerized analysis. The obtained data were averaged with respect to the sleep state and to the conceptional age. The number of variables was reduced by means of factor analysis. All factors identified by factor analysis were highly significantly influenced by sleep states in both developmental periods. Likewise, a comparison of the measured variables between QS and AS revealed many statistically significant differences. The variables describing (a) the number and length of quasi-stationary segments, (b) voltage and (c) power in delta and theta bands contributed to the greatest degree to the differentiation of EEGs between both sleep states. The presented method of the computerized EEG analysis which has good discriminative potential is adequately sensitive and describes the neonatal EEG with convenient accuracy.

Actigraphy combined with EEG compared to polysomnography in sleep apnea patients

International Nuclear Information System (INIS)

Fietze, Ingo; Penzel, Thomas; Partinen, Markku; Sauter, Jochen; Küchler, Gert; Suvoro, Alexander; Hein, Holger

2015-01-01

An actigraph extended with electroencephalography (EEG), electroocculography (EOG) and electromyography (EMG) was compared to polysomnography in two studies on patients suffering from sleep disordered breathing. Study A with 30 subjects used a single lead EEG, and study B with 20 subjects used EOG and EMG in addition. Sleep was scored according to Rechtschaffen and Kales rules. Total sleep time (TST), sleep period time (SPT), sleep efficiency (SE), sustained sleep efficiency (SSE), sleep-onset latency (SL), and sleep stages were compared. For study A an epoch-by-epoch comparison of sleep stages revealed an overall agreement of 74.2%. Correlations were high for SE (0.98, p < 0.001), SSE (0.98, p < 0.001), TST (0.99, p < 0.001), SPT (0.99, p < 0.001), and SL (0.98, p < 0.001). Regarding the sleep stages, correlations were high for rapid eye movement (REM) (0.83, p < 0.001), light-sleep (0.78, p < 0.001), and deep sleep (0.73, p < 0.001). For study B, results of an epoch-by-epoch comparison of sleep stages showed an overall agreement of 75.5%. Correlations were high for SE (0.98, p < 0.001), SSE (0.98, p < 0.001), TST (0.87, p < 0.001), SL (0.98, p < 0.001), SPT (0.94, p < 0.001), and for rapid eye movement (REM) (0.91, p < 0.001), light-sleep (0.74, p < 0.001), and deep sleep (0.89, p < 0.001). In summary the study revealed high agreement between polysomnography and single lead EEG in sleep apnea patients. Deviations for REM were slightly higher for the single lead EEG compared to single lead EEG plus EOG/EMG. Both simplified systems proved to be reliable for comfortable out-patient sleep recording. (paper)

Sleep EEG Fingerprints Reveal Accelerated Thalamocortical Oscillatory Dynamics in Williams Syndrome

Science.gov (United States)

Bodizs, Robert; Gombos, Ferenc; Kovacs, Ilona

2012-01-01

Sleep EEG alterations are emerging features of several developmental disabilities, but detailed quantitative EEG data on the sleep phenotype of patients with Williams syndrome (WS, 7q11.23 microdeletion) is still lacking. Based on laboratory (Study I) and home sleep records (Study II) here we report WS-related features of the patterns of…

Generalized Information Equilibrium Approaches to EEG Sleep Stage Discrimination

Directory of Open Access Journals (Sweden)

Todd Zorick

2016-01-01

Full Text Available Recent advances in neuroscience have raised the hypothesis that the underlying pattern of neuronal activation which results in electroencephalography (EEG signals is via power-law distributed neuronal avalanches, while EEG signals are nonstationary. Therefore, spectral analysis of EEG may miss many properties inherent in such signals. A complete understanding of such dynamical systems requires knowledge of the underlying nonequilibrium thermodynamics. In recent work by Fielitz and Borchardt (2011, 2014, the concept of information equilibrium (IE in information transfer processes has successfully characterized many different systems far from thermodynamic equilibrium. We utilized a publicly available database of polysomnogram EEG data from fourteen subjects with eight different one-minute tracings of sleep stage 2 and waking and an overlapping set of eleven subjects with eight different one-minute tracings of sleep stage 3. We applied principles of IE to model EEG as a system that transfers (equilibrates information from the time domain to scalp-recorded voltages. We find that waking consciousness is readily distinguished from sleep stages 2 and 3 by several differences in mean information transfer constants. Principles of IE applied to EEG may therefore prove to be useful in the study of changes in brain function more generally.

Acute effect of carbamazepine on corticothalamic 5-9-Hz and thalamocortical spindle (10-16-Hz) oscillations in the rat.

Science.gov (United States)

Zheng, Thomas W; O'Brien, Terence J; Kulikova, Sofya P; Reid, Christopher A; Morris, Margaret J; Pinault, Didier

2014-03-01

A major side effect of carbamazepine (CBZ), a drug used to treat neurological and neuropsychiatric disorders, is drowsiness, a state characterized by increased slow-wave oscillations with the emergence of sleep spindles in the electroencephalogram (EEG). We conducted cortical EEG and thalamic cellular recordings in freely moving or lightly anesthetized rats to explore the impact of CBZ within the intact corticothalamic (CT)-thalamocortical (TC) network, more specifically on CT 5-9-Hz and TC spindle (10-16-Hz) oscillations. Two to three successive 5-9-Hz waves were followed by a spindle in the cortical EEG. A single systemic injection of CBZ (20 mg/kg) induced a significant increase in the power of EEG 5-9-Hz oscillations and spindles. Intracellular recordings of glutamatergic TC neurons revealed 5-9-Hz depolarizing wave-hyperpolarizing wave sequences prolonged by robust, rhythmic spindle-frequency hyperpolarizing waves. This hybrid sequence occurred during a slow hyperpolarizing trough, and was at least 10 times more frequent under the CBZ condition than under the control condition. The hyperpolarizing waves reversed at approximately -70 mV, and became depolarizing when recorded with KCl-filled intracellular micropipettes, indicating that they were GABAA receptor-mediated potentials. In neurons of the GABAergic thalamic reticular nucleus, the principal source of TC GABAergic inputs, CBZ augmented both the number and the duration of sequences of rhythmic spindle-frequency bursts of action potentials. This indicates that these GABAergic neurons are responsible for the generation of at least the spindle-frequency hyperpolarizing waves in TC neurons. In conclusion, CBZ potentiates GABAA receptor-mediated TC spindle oscillations. Furthermore, we propose that CT 5-9-Hz waves can trigger TC spindles. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Automated Sleep Stage Scoring by Decision Tree Learning

National Research Council Canada - National Science Library

Hanaoka, Masaaki

2001-01-01

... practice regarded as one of the most successful machine learning methods. In our method, first characteristics of EEG, EOG and EMG are compared with characteristic features of alpha waves, delta waves, sleep spindles, K-complexes and REMs...

DeepSleepNet: A Model for Automatic Sleep Stage Scoring Based on Raw Single-Channel EEG.

Science.gov (United States)

Supratak, Akara; Dong, Hao; Wu, Chao; Guo, Yike

2017-11-01

This paper proposes a deep learning model, named DeepSleepNet, for automatic sleep stage scoring based on raw single-channel EEG. Most of the existing methods rely on hand-engineered features, which require prior knowledge of sleep analysis. Only a few of them encode the temporal information, such as transition rules, which is important for identifying the next sleep stages, into the extracted features. In the proposed model, we utilize convolutional neural networks to extract time-invariant features, and bidirectional-long short-term memory to learn transition rules among sleep stages automatically from EEG epochs. We implement a two-step training algorithm to train our model efficiently. We evaluated our model using different single-channel EEGs (F4-EOG (left), Fpz-Cz, and Pz-Oz) from two public sleep data sets, that have different properties (e.g., sampling rate) and scoring standards (AASM and R&K). The results showed that our model achieved similar overall accuracy and macro F1-score (MASS: 86.2%-81.7, Sleep-EDF: 82.0%-76.9) compared with the state-of-the-art methods (MASS: 85.9%-80.5, Sleep-EDF: 78.9%-73.7) on both data sets. This demonstrated that, without changing the model architecture and the training algorithm, our model could automatically learn features for sleep stage scoring from different raw single-channel EEGs from different data sets without utilizing any hand-engineered features.

Sleep spindles: a physiological marker of age-related changes in gray matter in brain regions supporting motor skill memory consolidation.

Science.gov (United States)

Fogel, Stuart; Vien, Catherine; Karni, Avi; Benali, Habib; Carrier, Julie; Doyon, Julien

2017-01-01

Sleep is necessary for the optimal consolidation of procedural learning, and in particular, for motor sequential skills. Motor sequence learning remains intact with age, but sleep-dependent consolidation is impaired, suggesting that memory deficits for procedural skills are specifically impacted by age-related changes in sleep. Age-related changes in spindles may be responsible for impaired motor sequence learning consolidation, but the morphological basis for this deficit is unknown. Here, we found that gray matter in the hippocampus and cerebellum was positively correlated with both sleep spindles and offline improvements in performance in young participants but not in older participants. These results suggest that age-related changes in gray matter in the hippocampus relate to spindles and may underlie age-related deficits in sleep-related motor sequence memory consolidation. In this way, spindles can serve as a biological marker for structural brain changes and the related memory deficits in older adults. Copyright © 2016 Elsevier Inc. All rights reserved.

Sleep EEG in Boys with Attention Deficit Disorder

Directory of Open Access Journals (Sweden)

J Gordon Millichap

2007-11-01

Full Text Available Researchers at the University of Montreal, Canada, studied spectral analysis of non-REM sleep (stages 2, 3 and 4 and REM sleep EEG in 6 boys (age 10.3 +/- 1.2 with ADHD compared to 6 healthy controls.

Pilot prospective study of post-surgery sleep and EEG predictors of post-operative delirium.

Science.gov (United States)

Evans, Joanna L; Nadler, Jacob W; Preud'homme, Xavier A; Fang, Eric; Daughtry, Rommie L; Chapman, Joseph B; Attarian, David; Wellman, Samuel; Krystal, Andrew D

2017-08-01

Delirium is a common post-operative complication associated with significant costs, morbidity, and mortality. We sought sleep/EEG predictors of delirium present prior to delirium symptoms to facilitate developing and targeting therapies. Continuous EEG data were obtained in 12 patients post-orthopedic surgery from the day of surgery until delirium assessment on post-operative day 2 (POD2). Diminished total sleep time (r=-0.68; pdelirium severity. Patients experiencing delirium slept 2.4h less and took 2h longer to fall asleep. Greater waking EEG delta power (r=0.84; pdelirium severity. Loss of sleep on night1 post-surgery is an early predictor of subsequent delirium. EEG Delta Power alterations in waking and sleep appear to be later indicators of impending delirium. Further work is needed to evaluate reproducibility/generalizability and assess whether sleep loss contributes to causing delirium. This first study to prospectively collect continuous EEG data for an extended period prior to delirium onset identified EEG-derived indices that predict subsequent delirium that could aid in developing and targeting therapies. Copyright © 2017. Published by Elsevier B.V.

Enhancement of Neocortical-Medial Temporal EEG Correlations during Non-REM Sleep

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Nikolai Axmacher

2008-01-01

Full Text Available Interregional interactions of oscillatory activity are crucial for the integrated processing of multiple brain regions. However, while the EEG in virtually all brain structures passes through substantial modifications during sleep, it is still an open question whether interactions between neocortical and medial temporal EEG oscillations also depend on the state of alertness. Several previous studies in animals and humans suggest that hippocampal-neocortical interactions crucially depend on the state of alertness (i.e., waking state or sleep. Here, we analyzed scalp and intracranial EEG recordings during sleep and waking state in epilepsy patients undergoing presurgical evaluation. We found that the amplitudes of oscillations within the medial temporal lobe and the neocortex were more closely correlated during sleep, in particular during non-REM sleep, than during waking state. Possibly, the encoding of novel sensory inputs, which mainly occurs during waking state, requires that medial temporal dynamics are rather independent from neocortical dynamics, while the consolidation of memories during sleep may demand closer interactions between MTL and neocortex.

Developmental changes in brain connectivity assessed using the sleep EEG.

OpenAIRE

Tarokh L; Carskadon M A; Achermann P

2010-01-01

Adolescence represents a time of significant cortical restructuring. Current theories posit that during this period connections between frequently utilized neural networks are strengthened while underutilized synaptic connections are discarded. The aim of the present study was to examine the developmental evolution of connectivity between brain regions using the sleep EEG. All night sleep EEG recordings in two longitudinal cohorts (children and teens) followed at 1.5 3 year intervals and one ...

Reduction in time-to-sleep through EEG based brain state detection and audio stimulation.

Science.gov (United States)

Zhuo Zhang; Cuntai Guan; Ti Eu Chan; Juanhong Yu; Aung Aung Phyo Wai; Chuanchu Wang; Haihong Zhang

2015-08-01

We developed an EEG- and audio-based sleep sensing and enhancing system, called iSleep (interactive Sleep enhancement apparatus). The system adopts a closed-loop approach which optimizes the audio recording selection based on user's sleep status detected through our online EEG computing algorithm. The iSleep prototype comprises two major parts: 1) a sleeping mask integrated with a single channel EEG electrode and amplifier, a pair of stereo earphones and a microcontroller with wireless circuit for control and data streaming; 2) a mobile app to receive EEG signals for online sleep monitoring and audio playback control. In this study we attempt to validate our hypothesis that appropriate audio stimulation in relation to brain state can induce faster onset of sleep and improve the quality of a nap. We conduct experiments on 28 healthy subjects, each undergoing two nap sessions - one with a quiet background and one with our audio-stimulation. We compare the time-to-sleep in both sessions between two groups of subjects, e.g., fast and slow sleep onset groups. The p-value obtained from Wilcoxon Signed Rank Test is 1.22e-04 for slow onset group, which demonstrates that iSleep can significantly reduce the time-to-sleep for people with difficulty in falling sleep.

Proepileptic patterns in EEG of WAG/Rij rats

Science.gov (United States)

Grubov, Vadim V.; Sitnikova, Evgenia Yu.; Nedaivozov, Vladimir O.; Koronovskii, Alexey A.

2018-04-01

In this paper we study specific oscillatory patterns on EEG signals of WAG/Rij rats. These patterns are known as proepileptic because they occur in time period during the development of absence-epilepsy before fully-formed epileptic seizures. In the paper we analyze EEG signals of WAG/Rij rats with continuous wavelet transform and empirical mode decomposition in order to find particular features of epileptic spike-wave discharges and nonepileptic sleep spindles. Then we introduce proepileptic activity as patterns that combine features of epileptic and non-epileptic activity. We analyze proepileptic activity in order to specify its features and time-frequency structure.

A Comparison Study on Multidomain EEG Features for Sleep Stage Classification

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Yu Zhang

2017-01-01

Full Text Available Feature extraction from physiological signals of EEG (electroencephalogram is an essential part for sleep staging. In this study, multidomain feature extraction was investigated based on time domain analysis, nonlinear analysis, and frequency domain analysis. Unlike the traditional feature calculation in time domain, a sequence merging method was developed as a preprocessing procedure. The objective is to eliminate the clutter waveform and highlight the characteristic waveform for further analysis. The numbers of the characteristic activities were extracted as the features from time domain. The contributions of features from different domains to the sleep stages were compared. The effectiveness was further analyzed by automatic sleep stage classification and compared with the visual inspection. The overnight clinical sleep EEG recordings of 3 patients after the treatment of Continuous Positive Airway Pressure (CPAP were tested. The obtained results showed that the developed method can highlight the characteristic activity which is useful for both automatic sleep staging and visual inspection. Furthermore, it can be a training tool for better understanding the appearance of characteristic waveforms from raw sleep EEG which is mixed and complex in time domain.

Sleep-spindle detection: crowdsourcing and evaluating performance of experts, non-experts and automated methods

DEFF Research Database (Denmark)

Warby, Simon C.; Wendt, Sabrina Lyngbye; Welinder, Peter

2014-01-01

to crowdsource spindle identification by human experts and non-experts, and we compared their performance with that of automated detection algorithms in data from middle- to older-aged subjects from the general population. We also refined methods for forming group consensus and evaluating the performance...... of event detectors in physiological data such as electroencephalographic recordings from polysomnography. Compared to the expert group consensus gold standard, the highest performance was by individual experts and the non-expert group consensus, followed by automated spindle detectors. This analysis showed...... that crowdsourcing the scoring of sleep data is an efficient method to collect large data sets, even for difficult tasks such as spindle identification. Further refinements to spindle detection algorithms are needed for middle- to older-aged subjects....

NREM sleep oscillations and brain plasticity in aging

Directory of Open Access Journals (Sweden)

Stuart eFogel

2012-12-01

Full Text Available The human electroencephalogram (EEG during non-rapid eye movement sleep (NREM is characterized mainly by high-amplitude (> 75 µV, slow-frequency (< 4 Hz waves (slow waves; SW and sleep spindles (~11-15 Hz; > 0.25 s. These NREM oscillations play a crucial role in brain plasticity, and importantly, NREM sleep oscillations change considerably with aging. This review discusses the association between NREM sleep oscillations and cerebral plasticity as well as the functional impact of age-related changes on NREM sleep oscillations. We propose that age-related reduction in sleep-dependent memory consolidation may be due in part to changes in NREM sleep oscillations.

The effect of different EEG derivations on sleep staging in rats: the frontal midline–parietal bipolar electrode for sleep scoring

International Nuclear Information System (INIS)

Fang, Guangzhan; Zhang, Chunpeng; Xia, Yang; Lai, Yongxiu; Liu, Tiejun; You, Zili; Yao, Dezhong

2009-01-01

Most sleep-staging research has focused on developing and optimizing algorithms for sleep scoring, but little attention has been paid to the effect of different electroencephalogram (EEG) derivations on sleep staging. To explore the possible effects of EEG derivations, an automatic computer method was established and confirmed by agreement analysis between the computer and two independent raters, and four fronto-parietal bipolar leads were compared for sleep scoring in rats. The results demonstrated that different bipolar electrodes have significantly different sleep-staging accuracies, and that the optimal frontal electrode for sleep scoring is located at the anterior midline

Burst suppression in sleep in a routine outpatient EEG

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Ammar Kheder

2014-01-01

Full Text Available Burst suppression (BS is an electroencephalogram (EEG pattern that is characterized by brief bursts of spikes, sharp waves, or slow waves of relatively high amplitude alternating with periods of relatively flat EEG or isoelectric periods. The pattern is usually associated with coma, severe encephalopathy of various etiologies, or general anesthesia. We describe an unusual case of anoxic brain injury in which a BS pattern was seen during behaviorally defined sleep during a routine outpatient EEG study.

Decreased sleep spindle density in patients with idiopathic REM sleep behavior disorder and patients with Parkinson’s disease

DEFF Research Database (Denmark)

Christensen, Julie Anja Engelhard; Kempfner, Jacob; Zoetmulder, Marielle

2014-01-01

ObjectiveTo determine whether sleep spindles (SS) are potentially a biomarker for Parkinson’s disease (PD). MethodsFifteen PD patients with REM sleep behavior disorder (PD+RBD), 15 PD patients without RBD (PD−RBD), 15 idiopathic RBD (iRBD) patients and 15 age-matched controls underwent...... polysomnography (PSG). SS were scored in an extract of data from control subjects. An automatic SS detector using a Matching Pursuit (MP) algorithm and a Support Vector Machine (SVM) was developed and applied to the PSG recordings. The SS densities in N1, N2, N3, all NREM combined and REM sleep were obtained...

Non-thermal continuous and modulated electromagnetic radiation fields effects on sleep EEG of rats☆

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Mohammed, Haitham S.; Fahmy, Heba M.; Radwan, Nasr M.; Elsayed, Anwar A.

2012-01-01

In the present study, the alteration in the sleep EEG in rats due to chronic exposure to low-level non-thermal electromagnetic radiation was investigated. Two types of radiation fields were used; 900 MHz unmodulated wave and 900 MHz modulated at 8 and 16 Hz waves. Animals has exposed to radiation fields for 1 month (1 h/day). EEG power spectral analyses of exposed and control animals during slow wave sleep (SWS) and rapid eye movement sleep (REM sleep) revealed that the REM sleep is more susceptible to modulated radiofrequency radiation fields (RFR) than the SWS. The latency of REM sleep increased due to radiation exposure indicating a change in the ultradian rhythm of normal sleep cycles. The cumulative and irreversible effect of radiation exposure was proposed and the interaction of the extremely low frequency radiation with the similar EEG frequencies was suggested. PMID:25685416

Non-thermal continuous and modulated electromagnetic radiation fields effects on sleep EEG of rats

Directory of Open Access Journals (Sweden)

Haitham S. Mohammed

2013-03-01

Full Text Available In the present study, the alteration in the sleep EEG in rats due to chronic exposure to low-level non-thermal electromagnetic radiation was investigated. Two types of radiation fields were used; 900 MHz unmodulated wave and 900 MHz modulated at 8 and 16 Hz waves. Animals has exposed to radiation fields for 1 month (1 h/day. EEG power spectral analyses of exposed and control animals during slow wave sleep (SWS and rapid eye movement sleep (REM sleep revealed that the REM sleep is more susceptible to modulated radiofrequency radiation fields (RFR than the SWS. The latency of REM sleep increased due to radiation exposure indicating a change in the ultradian rhythm of normal sleep cycles. The cumulative and irreversible effect of radiation exposure was proposed and the interaction of the extremely low frequency radiation with the similar EEG frequencies was suggested.

Temporal correlation between two channels EEG of bipolar lead in the head midline is associated with sleep-wake stages.

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Li, Yanjun; Tang, Xiaoying; Xu, Zhi; Liu, Weifeng; Li, Jing

2016-03-01

Whether the temporal correlation between inter-leads Electroencephalogram (EEG) that located on the boundary between left and right brain hemispheres is associated with sleep stages or not is still unknown. The purpose of this paper is to evaluate the role of correlation coefficients between EEG leads Fpz-Cz and Pz-Oz for automatic classification of sleep stages. A total number of 39 EEG recordings (about 20 h each) were selected from the expanded sleep database in European data format for temporal correlation analysis. Original waveform of EEG was decomposed into sub-bands δ (1-4 Hz), θ (4-8 Hz), α (8-13 Hz) and β (13-30 Hz). The correlation coefficient between original EEG leads Fpz-Cz and Pz-Oz within frequency band 0.5-30 Hz was defined as r(EEG) and was calculated every 30 s, while that between the two leads EEG in sub-bands δ, θ, α and β were defined as r(δ), r(θ), r(α) and r(β), respectively. Classification of wakefulness and sleep was processed by fixed threshold that derived from the probability density function of correlation coefficients. There was no correlation between EEG leads Fpz-Cz and Pz-Oz during wakefulness (|r| r > 0.1 for r(EEG) and r(δ)), while low correlation existed during sleep (r ≈ -0.4 for r(EEG), r(δ), r(θ), r(α) and r(β)). There were significant differences (analysis of variance, P correlation index between EEG leads Fpz-Cz and Pz-Oz could distinguish all five types of wakefulness, rapid eye movement (REM) sleep, N1 sleep, N2 sleep and N3 sleep. In conclusion, the temporal correlation between EEG bipolar leads Fpz-Cz and Pz-Oz are highly associated with sleep-wake stages. Moreover, high accuracy of sleep-wake classification could be achieved by the temporal correlation within frequency band 0.5-30 Hz between EEG leads Fpz-Cz and Pz-Oz.

EEG transients in the sigma range during non-REM sleep predict learning in dogs

NARCIS (Netherlands)

Iotchev, I.B.; Kis, A.; Bodizs, R.; Luijtelaar, E.L.J.M. van; Kubinyi, E.

2017-01-01

Sleep spindles are phasic bursts of thalamo-cortical activity, visible in the cortex as transient oscillations in the sigma range (usually defined in humans as 12-14 or 9-16 Hz). They have been associated with sleep-dependent memory consolidation and sleep stability in humans and rodents.

Non-thermal continuous and modulated electromagnetic radiation fields effects on sleep EEG of rats ?

OpenAIRE

Mohammed, Haitham S.; Fahmy, Heba M.; Radwan, Nasr M.; Elsayed, Anwar A.

2012-01-01

In the present study, the alteration in the sleep EEG in rats due to chronic exposure to low-level non-thermal electromagnetic radiation was investigated. Two types of radiation fields were used; 900 MHz unmodulated wave and 900 MHz modulated at 8 and 16 Hz waves. Animals has exposed to radiation fields for 1 month (1 h/day). EEG power spectral analyses of exposed and control animals during slow wave sleep (SWS) and rapid eye movement sleep (REM sleep) revealed that the REM sleep is more susc...

Homeostatic and Circadian Contribution to EEG and Molecular State Variables of Sleep Regulation

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Curie, Thomas; Mongrain, Valérie; Dorsaz, Stéphane; Mang, Géraldine M.; Emmenegger, Yann; Franken, Paul

2013-01-01

Study Objectives: Besides their well-established role in circadian rhythms, our findings that the forebrain expression of the clock-genes Per2 and Dbp increases and decreases, respectively, in relation to time spent awake suggest they also play a role in the homeostatic aspect of sleep regulation. Here, we determined whether time of day modulates the effects of elevated sleep pressure on clock-gene expression. Time of day effects were assessed also for recognized electrophysiological (EEG delta power) and molecular (Homer1a) markers of sleep homeostasis. Design: EEG and qPCR data were obtained for baseline and recovery from 6-h sleep deprivation starting at ZT0, -6, -12, or -18. Setting: Mouse sleep laboratory. Participants: Male mice. Interventions: Sleep deprivation. Results: The sleep-deprivation induced changes in Per2 and Dbp expression importantly varied with time of day, such that Per2 could even decrease during sleep deprivations occurring at the decreasing phase in baseline. Dbp showed similar, albeit opposite dynamics. These unexpected results could be reliably predicted assuming that these transcripts behave according to a driven damped harmonic oscillator. As expected, the sleep-wake distribution accounted for a large degree of the changes in EEG delta power and Homer1a. Nevertheless, the sleep deprivation-induced increase in delta power varied also with time of day with higher than expected levels when recovery sleep started at dark onset. Conclusions: Per2 and delta power are widely used as exclusive state variables of the circadian and homeostatic process, respectively. Our findings demonstrate a considerable cross-talk between these two processes. As Per2 in the brain responds to both sleep loss and time of day, this molecule is well positioned to keep track of and to anticipate homeostatic sleep need. Citation: Curie T; Mongrain V; Dorsaz S; Mang GM; Emmenegger Y; Franken P. Homeostatic and circadian contribution to EEG and molecular state

Homeostatic and circadian contribution to EEG and molecular state variables of sleep regulation.

Science.gov (United States)

Curie, Thomas; Mongrain, Valérie; Dorsaz, Stéphane; Mang, Géraldine M; Emmenegger, Yann; Franken, Paul

2013-03-01

Besides their well-established role in circadian rhythms, our findings that the forebrain expression of the clock-genes Per2 and Dbp increases and decreases, respectively, in relation to time spent awake suggest they also play a role in the homeostatic aspect of sleep regulation. Here, we determined whether time of day modulates the effects of elevated sleep pressure on clock-gene expression. Time of day effects were assessed also for recognized electrophysiological (EEG delta power) and molecular (Homer1a) markers of sleep homeostasis. EEG and qPCR data were obtained for baseline and recovery from 6-h sleep deprivation starting at ZT0, -6, -12, or -18. Mouse sleep laboratory. Male mice. Sleep deprivation. The sleep-deprivation induced changes in Per2 and Dbp expression importantly varied with time of day, such that Per2 could even decrease during sleep deprivations occurring at the decreasing phase in baseline. Dbp showed similar, albeit opposite dynamics. These unexpected results could be reliably predicted assuming that these transcripts behave according to a driven damped harmonic oscillator. As expected, the sleep-wake distribution accounted for a large degree of the changes in EEG delta power and Homer1a. Nevertheless, the sleep deprivation-induced increase in delta power varied also with time of day with higher than expected levels when recovery sleep started at dark onset. Per2 and delta power are widely used as exclusive state variables of the circadian and homeostatic process, respectively. Our findings demonstrate a considerable cross-talk between these two processes. As Per2 in the brain responds to both sleep loss and time of day, this molecule is well positioned to keep track of and to anticipate homeostatic sleep need. Curie T; Mongrain V; Dorsaz S; Mang GM; Emmenegger Y; Franken P. Homeostatic and circadian contribution to EEG and molecular state variables of sleep regulation. SLEEP 2013;36(3):311-323.

Automatic characterization of sleep need dissipation dynamics using a single EEG signal.

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Garcia-Molina, Gary; Bellesi, Michele; Riedner, Brady; Pastoor, Sander; Pfundtner, Stefan; Tononi, Giulio

2015-01-01

In the two-process model of sleep regulation, slow-wave activity (SWA, i.e. the EEG power in the 0.5-4 Hz frequency band) is considered a direct indicator of sleep need. SWA builds up during non-rapid eye movement (NREM) sleep, declines before the onset of rapid-eye-movement (REM) sleep, remains low during REM and the level of increase in successive NREM episodes gets progressively lower. Sleep need dissipates with a speed that is proportional to SWA and can be characterized in terms of the initial sleep need, and the decay rate. The goal in this paper is to automatically characterize sleep need from a single EEG signal acquired at a frontal location. To achieve this, a highly specific and reasonably sensitive NREM detection algorithm is proposed that leverages the concept of a single-class Kernel-based classifier. Using automatic NREM detection, we propose a method to estimate the decay rate and the initial sleep need. This method was tested on experimental data from 8 subjects who recorded EEG during three nights at home. We found that on average the estimates of the decay rate and the initial sleep need have higher values when automatic NREM detection was used as compared to manual NREM annotation. However, the average variability of these estimates across multiple nights of the same subject was lower when the automatic NREM detection classifier was used. While this method slightly over estimates the sleep need parameters, the reduced variability across subjects makes it more effective for within subject statistical comparisons of a given sleep intervention.

Night and day variations of sleep in patients with disorders of consciousness.

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Wislowska, Malgorzata; Del Giudice, Renata; Lechinger, Julia; Wielek, Tomasz; Heib, Dominik P J; Pitiot, Alain; Pichler, Gerald; Michitsch, Gabriele; Donis, Johann; Schabus, Manuel

2017-03-21

Brain injuries substantially change the entire landscape of oscillatory dynamics and render detection of typical sleep patterns difficult. Yet, sleep is characterized not only by specific EEG waveforms, but also by its circadian organization. In the present study we investigated whether brain dynamics of patients with disorders of consciousness systematically change between day and night. We recorded ~24 h EEG at the bedside of 18 patients diagnosed to be vigilant but unaware (Unresponsive Wakefulness Syndrome) and 17 patients revealing signs of fluctuating consciousness (Minimally Conscious State). The day-to-night changes in (i) spectral power, (ii) sleep-specific oscillatory patterns and (iii) signal complexity were analyzed and compared to 26 healthy control subjects. Surprisingly, the prevalence of sleep spindles and slow waves did not systematically vary between day and night in patients, whereas day-night changes in EEG power spectra and signal complexity were revealed in minimally conscious but not unaware patients.

The 2007 AASM recommendations for EEG electrode placement in polysomnography: impact on sleep and cortical arousal scoring.

Science.gov (United States)

Ruehland, Warren R; O'Donoghue, Fergal J; Pierce, Robert J; Thornton, Andrew T; Singh, Parmjit; Copland, Janet M; Stevens, Bronwyn; Rochford, Peter D

2011-01-01

To examine the impact of using American Academy of Sleep Medicine (AASM) recommended EEG derivations (F4/M1, C4/M1, O2/M1) vs. a single derivation (C4/M1) in polysomnography (PSG) on the measurement of sleep and cortical arousals, including inter- and intra-observer variability. Prospective, non-blinded, randomized comparison. Three Australian tertiary-care hospital clinical sleep laboratories. 30 PSGs from consecutive patients investigated for obstructive sleep apnea (OSA) during December 2007 and January 2008. N/A. To examine the impact of EEG derivations on PSG summary statistics, 3 scorers from different Australian clinical sleep laboratories each scored separate sets of 10 PSGs twice, once using 3 EEG derivations and once using 1 EEG derivation. To examine the impact on inter- and intra-scorer reliability, all 3 scorers scored a subset of 10 PSGs 4 times, twice using each method. All PSGs were de-identified and scored in random order according to the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Using 3 referential EEG derivations during PSG, as recommended in the AASM manual, instead of a single central EEG derivation, as originally suggested by Rechtschaffen and Kales (1968), resulted in a mean ± SE decrease in N1 sleep of 9.6 ± 3.9 min (P = 0.018) and an increase in N3 sleep of 10.6 ± 2.8 min (P = 0.001). No significant differences were observed for any other sleep or arousal scoring summary statistics; nor were any differences observed in inter-scorer or intra-scorer reliability for scoring sleep or cortical arousals. This study provides information for those changing practice to comply with the 2007 AASM recommendations for EEG placement in PSG, for those using portable devices that are unable to comply with the recommendations due to limited channel options, and for the development of future standards for PSG scoring and recording. As the use of multiple EEG derivations only led to small changes in the distribution of derived sleep

Differential effects of sodium oxybate and baclofen on EEG, sleep, neurobehavioral performance, and memory.

Science.gov (United States)

Vienne, Julie; Lecciso, Gianpaolo; Constantinescu, Irina; Schwartz, Sophie; Franken, Paul; Heinzer, Raphaël; Tafti, Mehdi

2012-08-01

Sodium oxybate (SO) is a GABAβ agonist used to treat the sleep disorder narcolepsy. SO was shown to increase slow wave sleep (SWS) and EEG delta power (0.75-4.5 Hz), both indexes of NREM sleep (NREMS) intensity and depth, suggesting that SO enhances recuperative function of NREM. We investigated whether SO induces physiological deep sleep. SO was administered before an afternoon nap or before the subsequent experimental night in 13 healthy volunteers. The effects of SO were compared to baclofen (BAC), another GABAβ receptor agonist, to assess the role of GABAβ receptors in the SO response. As expected, a nap significantly decreased sleep need and intensity the subsequent night. Both drugs reversed this nap effect on the subsequent night by decreasing sleep latency and increasing total sleep time, SWS during the first NREMS episode, and EEG delta and theta (0.75-7.25 Hz) power during NREMS. The SO-induced increase in EEG delta and theta power was, however, not specific to NREMS and was also observed during REM sleep (REMS) and wakefulness. Moreover, the high levels of delta power during a nap following SO administration did not affect delta power the following night. SO and BAC taken before the nap did not improve subsequent psychomotor performance and subjective alertness, or memory consolidation. Finally, SO and BAC strongly promoted the appearance of sleep onset REM periods. The SO-induced EEG slow waves seem not to be functionally similar to physiological slow waves. Our findings also suggest a role for GABAβ receptors in REMS generation.

Quantitative Analysis of the Effects of Slow Wave Sleep Deprivation During the First 3 h of Sleep on Subsequent EEG Power Density

NARCIS (Netherlands)

Dijk, Derk Jan; Beersma, Domien G.M.; Daan, Serge; Bloem, Gerda M.; Hoofdakker, Rutger H. van den

1987-01-01

The relation between EEG power density during slow wave sleep (SWS) deprivation and power density during subsequent sleep was investigated. Nine young male adults slept in the laboratory for 3 consecutive nights. Spectral analysis of the EEG on the 2nd (baseline) night revealed an exponential

Sleep EEG findings in ICD-10 borderline personality disorder in Egypt.

Science.gov (United States)

Asaad, Tarek; Okasha, Tarek; Okasha, Ahmed

2002-09-01

Previous work has demonstrated that patients with borderline personality disorder show some similarities to patients with major depression, especially regarding their sleep profile. This study aimed at investigating such a hypothesis in an Egyptian sample, considering the possible influence of cultural differences. All night polysomnographic assessments were made for 20 ICD-10 diagnosed borderline patients (without co-morbid depression), in addition to 20 patients with major depression and 20 healthy matched controls. The two patient groups differed significantly from controls in their sleep profile, especially regarding sleep continuity measures, decreased SWS and REM sleep abnormalities. High similarity was found in EEG sleep profile of the two patient groups, though the changes were more robust in patients with depression. The small number of subjects precluded finer analyses of sleep microstructure by depressive symptoms. The great similarity in EEG sleep profile between borderline personality disorder patients and patients with major depression suggests a common biological origin for both conditions, with the difference being 'quantitative' rather than 'qualitative'. Our data are all the more compelling in that the presumed personality disturbance in the Egyptian culture manifests neurophysiologically as in the Western world.

Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.

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Shi, Jun; Liu, Xiao; Li, Yan; Zhang, Qi; Li, Yingjie; Ying, Shihui

2015-10-30

Electroencephalography (EEG) based sleep staging is commonly used in clinical routine. Feature extraction and representation plays a crucial role in EEG-based automatic classification of sleep stages. Sparse representation (SR) is a state-of-the-art unsupervised feature learning method suitable for EEG feature representation. Collaborative representation (CR) is an effective data coding method used as a classifier. Here we use CR as a data representation method to learn features from the EEG signal. A joint collaboration model is established to develop a multi-view learning algorithm, and generate joint CR (JCR) codes to fuse and represent multi-channel EEG signals. A two-stage multi-view learning-based sleep staging framework is then constructed, in which JCR and joint sparse representation (JSR) algorithms first fuse and learning the feature representation from multi-channel EEG signals, respectively. Multi-view JCR and JSR features are then integrated and sleep stages recognized by a multiple kernel extreme learning machine (MK-ELM) algorithm with grid search. The proposed two-stage multi-view learning algorithm achieves superior performance for sleep staging. With a K-means clustering based dictionary, the mean classification accuracy, sensitivity and specificity are 81.10 ± 0.15%, 71.42 ± 0.66% and 94.57 ± 0.07%, respectively; while with the dictionary learned using the submodular optimization method, they are 80.29 ± 0.22%, 71.26 ± 0.78% and 94.38 ± 0.10%, respectively. The two-stage multi-view learning based sleep staging framework outperforms all other classification methods compared in this work, while JCR is superior to JSR. The proposed multi-view learning framework has the potential for sleep staging based on multi-channel or multi-modality polysomnography signals. Copyright © 2015 Elsevier B.V. All rights reserved.

The use of Matlab for colour fuzzy representation of multichannel EEG short time spectra.

Science.gov (United States)

Bigan, C; Strungaru, R

1998-01-01

During the last years, a lot of EEG research efforts was directed to intelligent methods for automatic analysis of data from multichannel EEG recordings. However, all the applications reported were focused on specific single tasks like detection of one specific "event" in the EEG signal: spikes, sleep spindles, epileptic seizures, K complexes, alpha or other rhythms or even artefacts. The aim of this paper is to present a complex system being able to perform a representation of the dynamic changes in frequency components of each EEG channel. This representation uses colours as a powerful means to show the only one frequency range chosen from the shortest epoch of signal able to be processed with the conventional "Short Time Fast Fourier Transform" (S.T.F.F.T.) method.

Burst suppression in sleep in a routine outpatient EEG ?

OpenAIRE

Kheder, Ammar; Bianchi, Matt T.; Westover, M. Brandon

2014-01-01

Burst suppression (BS) is an electroencephalogram (EEG) pattern that is characterized by brief bursts of spikes, sharp waves, or slow waves of relatively high amplitude alternating with periods of relatively flat EEG or isoelectric periods. The pattern is usually associated with coma, severe encephalopathy of various etiologies, or general anesthesia. We describe an unusual case of anoxic brain injury in which a BS pattern was seen during behaviorally defined sleep during a routine outpatient...

Sleep disruption increases seizure susceptibility: Behavioral and EEG evaluation of an experimental model of sleep apnea.

Science.gov (United States)

Hrnčić, Dragan; Grubač, Željko; Rašić-Marković, Aleksandra; Šutulović, Nikola; Šušić, Veselinka; Bjekić-Macut, Jelica; Stanojlović, Olivera

2016-03-01

Sleep disruption accompanies sleep apnea as one of its major symptoms. Obstructive sleep apnea is particularly common in patients with refractory epilepsy, but causing factors underlying this are far from being resolved. Therefore, translational studies regarding this issue are important. Our aim was to investigate the effects of sleep disruption on seizure susceptibility of rats using experimental model of lindane-induced refractory seizures. Sleep disruption in male Wistar rats with implanted EEG electrodes was achieved by treadmill method (belt speed set on 0.02 m/s for working and 0.00 m/s for stop mode, respectively). Animals were assigned to experimental conditions lasting 6h: 1) sleep disruption (sleep interrupted, SI; 30s working and 90 s stop mode every 2 min; 180 cycles in total); 2) activity control (AC, 10 min working and 30 min stop mode, 9 cycles in total); 3) treadmill chamber control (TC, only stop mode). Afterwards, the animals were intraperitoneally treated with lindane (L, 4 mg/kg, SI+L, AC+L and TC+L groups) or dimethylsulfoxide (DMSO, SIc, ACc and TCc groups). Convulsive behavior was assessed by seizure incidence, latency time to first seizure, and its severity during 30 min after drug administration. Number and duration of ictal periods were determined in recorded EEGs. Incidence and severity of lindane-induced seizures were significantly increased, latency time significantly decreased in animals undergoing sleep disruption (SI+L group) compared with the animals from TC+L. Seizure latency was also significantly decreased in SI+L compared to AC+L groups. Number of ictal periods were increased and duration of it presented tendency to increase in SI+L comparing to AC+L. No convulsive signs were observed in TCc, ACc and SIc groups, as well as no ictal periods in EEG. These results indicate sleep disruption facilitates induction of epileptic activity in rodent model of lindane-epilepsy enabling translational research of this phenomenon. Copyright �

Automatic sleep stage classification based on EEG signals by using neural networks and wavelet packet coefficients.

Science.gov (United States)

Ebrahimi, Farideh; Mikaeili, Mohammad; Estrada, Edson; Nazeran, Homer

2008-01-01

Currently in the world there is an alarming number of people who suffer from sleep disorders. A number of biomedical signals, such as EEG, EMG, ECG and EOG are used in sleep labs among others for diagnosis and treatment of sleep related disorders. The usual method for sleep stage classification is visual inspection by a sleep specialist. This is a very time consuming and laborious exercise. Automatic sleep stage classification can facilitate this process. The definition of sleep stages and the sleep literature show that EEG signals are similar in Stage 1 of non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep. Therefore, in this work an attempt was made to classify four sleep stages consisting of Awake, Stage 1 + REM, Stage 2 and Slow Wave Stage based on the EEG signal alone. Wavelet packet coefficients and artificial neural networks were deployed for this purpose. Seven all night recordings from Physionet database were used in the study. The results demonstrated that these four sleep stages could be automatically discriminated from each other with a specificity of 94.4 +/- 4.5%, a of sensitivity 84.2+3.9% and an accuracy of 93.0 +/- 4.0%.

Relationship of slow and rapid EEG components of CAP to ASDA arousals in normal sleep.

Science.gov (United States)

Parrino, L; Smerieri, A; Rossi, M; Terzano, M G

2001-12-15

Besides arousals (according to the ASDA definition), sleep contains also K-complexes and delta bursts which, in spite of their sleep-like features, are endowed with activating effects on autonomic functions. The link between phasic delta activities and enhancement of vegetative functions indicates the possibility of physiological activation without sleep disruption (i.e., arousal without awakening). A functional connection seems to include slow (K-complexes and delta bursts) and rapid (arousals) EEG events within the comprehensive term of activating complexes. CAP (cyclic alternating pattern) is the spontaneous EEG rhythm that ties both slow and rapid activating complexes together during NREM sleep. The present study aims at exploring the relationship between arousals and CAP components in a selected sample of healthy sleepers. Polysomnographic analysis according to the scoring rules for sleep stages and arousals. CAP analysis included also tabulation of subtypes A1 (slow EEG activating complexes), A2 and A3 (activating complexes with fast EEG components). 40 sleep-lab accomplished recordings. Healthy subjects belonging to a wide age range (38 +/- 20 yrs.). N/A. Of all the arousals occurring in NREM sleep, 87% were inserted within CAP. Subtypes A2 and A3 of CAP corresponded strikingly with arousals (r=0.843; p<0.0001), while no statistical relationship emerged when arousals were matched with subtypes A1 of CAP. Subtypes A1 instead correlated positively with the percentages of deep sleep (r=0.366; p<0.02). The CAP subtype classification encompasses both the process of sleep maintenance (subtypes A1) and sleep fragmentation (subtypes A2 and A3), and provides a periodicity dimension to the activating events of NREM sleep.

Effects of SWS deprivation on subsequent EEG power density and spontaneous sleep duration

NARCIS (Netherlands)

Dijk, Derk Jan; Beersma, Domien G.M.

In order to test predictions of the 2-process model of sleep regulation, the effects of slow wave sleep (SWS) deprivation by acoustic stimulation during the first part of the sleep period on EEG power density and sleep duration were investigated in 2 experiments. In the first experiment, 8 subjects

Effects of partial sleep deprivation on slow waves during non-rapid eye movement sleep: A high density EEG investigation.

Science.gov (United States)

Plante, David T; Goldstein, Michael R; Cook, Jesse D; Smith, Richard; Riedner, Brady A; Rumble, Meredith E; Jelenchick, Lauren; Roth, Andrea; Tononi, Giulio; Benca, Ruth M; Peterson, Michael J

2016-02-01

Changes in slow waves during non-rapid eye movement (NREM) sleep in response to acute total sleep deprivation are well-established measures of sleep homeostasis. This investigation utilized high-density electroencephalography (hdEEG) to examine topographic changes in slow waves during repeated partial sleep deprivation. Twenty-four participants underwent a 6-day sleep restriction protocol. Spectral and period-amplitude analyses of sleep hdEEG data were used to examine changes in slow wave energy, count, amplitude, and slope relative to baseline. Changes in slow wave energy were dependent on the quantity of NREM sleep utilized for analysis, with widespread increases during sleep restriction and recovery when comparing data from the first portion of the sleep period, but restricted to recovery sleep if the entire sleep episode was considered. Period-amplitude analysis was less dependent on the quantity of NREM sleep utilized, and demonstrated topographic changes in the count, amplitude, and distribution of slow waves, with frontal increases in slow wave amplitude, numbers of high-amplitude waves, and amplitude/slopes of low amplitude waves resulting from partial sleep deprivation. Topographic changes in slow waves occur across the course of partial sleep restriction and recovery. These results demonstrate a homeostatic response to partial sleep loss in humans. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

EEG quantification of alertness: methods for early identification of individuals most susceptible to sleep deprivation

Science.gov (United States)

Berka, Chris; Levendowski, Daniel J.; Westbrook, Philip; Davis, Gene; Lumicao, Michelle N.; Olmstead, Richard E.; Popovic, Miodrag; Zivkovic, Vladimir T.; Ramsey, Caitlin K.

2005-05-01

Electroencephalographic (EEG) and neurocognitive measures were simultaneously acquired to quantify alertness from 24 participants during 44-hours of sleep deprivation. Performance on a three-choice vigilance task (3C-VT), paired-associate learning/memory task (PAL) and modified Maintenance of Wakefulness Test (MWT), and sleep technician-observed drowsiness (eye-closures, head-nods, EEG slowing) were quantified. The B-Alert system automatically classifies each second of EEG on an alertness/drowsiness continuum. B-Alert classifications were significantly correlated with technician-observations, visually scored EEG and performance measures. B-Alert classifications during 3C-VT, and technician observations and performance during the 3C-VT and PAL evidenced progressively increasing drowsiness as a result of sleep deprivation with a stabilizing effect observed at the batteries occurring between 0600 and 1100 suggesting a possible circadian effect similar to those reported in previous sleep deprivation studies. Participants were given an opportunity to take a 40-minute nap approximately 24-hours into the sleep deprivation portion of the study (i.e., 7 PM on Saturday). The nap was followed by a transient period of increased alertness. Approximately 8 hours after the nap, behavioral and physiological measures of drowsiness returned to levels prior to the nap. Cluster analysis was used to stratify individuals into three groups based on their level of impairment as a result of sleep deprivation. The combination of B-Alert and neuro-behavioral measures may identify individuals whose performance is most susceptible to sleep deprivation. These objective measures could be applied in an operational setting to provide a "biobehavioral assay" to determine vulnerability to sleep deprivation.

Sleep EEG of Microcephaly in Zika Outbreak.

Science.gov (United States)

Kanda, Paulo Afonso Medeiros; Aguiar, Aline de Almeida Xavier; Miranda, Jose Lucivan; Falcao, Alexandre Loverde; Andrade, Claudia Suenia; Reis, Luigi Neves Dos Santos; Almeida, Ellen White R Bacelar; Bello, Yanes Brum; Monfredinho, Arthur; Kanda, Rafael Guimaraes

2018-01-01

Microcephaly (MC), previously considered rare, is now a health emergency of international concern because of the devastating Zika virus pandemic outbreak of 2015. The authors describe the electroencephalogram (EEG) findings in sleep EEG of epileptic children who were born with microcephaly in areas of Brazil with active Zika virus transmission between 2014 and 2017. The authors reviewed EEGs from 23 children. Nine were females (39.2%), and the age distribution varied from 4 to 48 months. MC was associated with mother positive serology to toxoplasmosis (toxo), rubella (rub), herpes, and dengue (1 case); toxo (1 case); chikungunya virus (CHIKV) (1 case); syphilis (1 case); and Zika virus (ZIKV) (10 cases). In addition, 1 case was associated with perinatal hypoxia and causes of 9 cases remain unknown. The main background EEG abnormality was diffuse slowing (10 cases), followed by classic (3 cases) and modified (5 cases) hypsarrhythmia. A distinct EEG pattern was seen in ZIKV (5 cases), toxo (2 cases), and undetermined cause (1 case). It was characterized by runs of frontocentrotemporal 4.5-13 Hz activity (7 cases) or diffuse and bilateral runs of 18-24 Hz (1 case). In ZIKV, this rhythmic activity was associated with hypsarrhythmia or slow background. Further studies are necessary to determine if this association is suggestive of ZIKV infection. The authors believe that EEG should be included in the investigation of all newly diagnosed congenital MC, especially those occurring in areas of autochthonous transmission of ZIKV.

The role of sleep spindles and slow-wave activity in integrating new information in semantic memory.

Science.gov (United States)

Tamminen, Jakke; Lambon Ralph, Matthew A; Lewis, Penelope A

2013-09-25

Assimilating new information into existing knowledge is a fundamental part of consolidating new memories and allowing them to guide behavior optimally and is vital for conceptual knowledge (semantic memory), which is accrued over many years. Sleep is important for memory consolidation, but its impact upon assimilation of new information into existing semantic knowledge has received minimal examination. Here, we examined the integration process by training human participants on novel words with meanings that fell into densely or sparsely populated areas of semantic memory in two separate sessions. Overnight sleep was polysomnographically monitored after each training session and recall was tested immediately after training, after a night of sleep, and 1 week later. Results showed that participants learned equal numbers of both word types, thus equating amount and difficulty of learning across the conditions. Measures of word recognition speed showed a disadvantage for novel words in dense semantic neighborhoods, presumably due to interference from many semantically related concepts, suggesting that the novel words had been successfully integrated into semantic memory. Most critically, semantic neighborhood density influenced sleep architecture, with participants exhibiting more sleep spindles and slow-wave activity after learning the sparse compared with the dense neighborhood words. These findings provide the first evidence that spindles and slow-wave activity mediate integration of new information into existing semantic networks.

Automated EEG sleep staging in the term-age baby using a generative modelling approach

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Pillay, Kirubin; Dereymaeker, Anneleen; Jansen, Katrien; Naulaers, Gunnar; Van Huffel, Sabine; De Vos, Maarten

2018-06-01

Objective. We develop a method for automated four-state sleep classification of preterm and term-born babies at term-age of 38-40 weeks postmenstrual age (the age since the last menstrual cycle of the mother) using multichannel electroencephalogram (EEG) recordings. At this critical age, EEG differentiates from broader quiet sleep (QS) and active sleep (AS) stages to four, more complex states, and the quality and timing of this differentiation is indicative of the level of brain development. However, existing methods for automated sleep classification remain focussed only on QS and AS sleep classification. Approach. EEG features were calculated from 16 EEG recordings, in 30 s epochs, and personalized feature scaling used to correct for some of the inter-recording variability, by standardizing each recording’s feature data using its mean and standard deviation. Hidden Markov models (HMMs) and Gaussian mixture models (GMMs) were trained, with the HMM incorporating knowledge of the sleep state transition probabilities. Performance of the GMM and HMM (with and without scaling) were compared, and Cohen’s kappa agreement calculated between the estimates and clinicians’ visual labels. Main results. For four-state classification, the HMM proved superior to the GMM. With the inclusion of personalized feature scaling, mean kappa (±standard deviation) was 0.62 (±0.16) compared to the GMM value of 0.55 (±0.15). Without feature scaling, kappas for the HMM and GMM dropped to 0.56 (±0.18) and 0.51 (±0.15), respectively. Significance. This is the first study to present a successful method for the automated staging of four states in term-age sleep using multichannel EEG. Results suggested a benefit in incorporating transition information using an HMM, and correcting for inter-recording variability through personalized feature scaling. Determining the timing and quality of these states are indicative of developmental delays in both preterm and term-born babies that may

Cortical connectivity modulation during sleep onset: A study via graph theory on EEG data.

Science.gov (United States)

Vecchio, Fabrizio; Miraglia, Francesca; Gorgoni, Maurizio; Ferrara, Michele; Iberite, Francesco; Bramanti, Placido; De Gennaro, Luigi; Rossini, Paolo Maria

2017-11-01

Sleep onset is characterized by a specific and orchestrated pattern of frequency and topographical EEG changes. Conventional power analyses of electroencephalographic (EEG) and computational assessments of network dynamics have described an earlier synchronization of the centrofrontal areas rhythms and a spread of synchronizing signals from associative prefrontal to posterior areas. Here, we assess how "small world" characteristics of the brain networks, as reflected in the EEG rhythms, are modified in the wakefulness-sleep transition comparing the pre- and post-sleep onset epochs. The results show that sleep onset is characterized by a less ordered brain network (as reflected by the higher value of small world) in the sigma band for the frontal lobes indicating stronger connectivity, and a more ordered brain network in the low frequency delta and theta bands indicating disconnection on the remaining brain areas. Our results depict the timing and topography of the specific mechanisms for the maintenance of functional connectivity of frontal brain regions at the sleep onset, also providing a possible explanation for the prevalence of the frontal-to-posterior information flow directionality previously observed after sleep onset. Hum Brain Mapp 38:5456-5464, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Experienced Mindfulness Meditators Exhibit Higher Parietal-Occipital EEG Gamma Activity during NREM Sleep

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Ferrarelli, Fabio; Smith, Richard; Dentico, Daniela; Riedner, Brady A.; Zennig, Corinna; Benca, Ruth M.; Lutz, Antoine; Davidson, Richard J.; Tononi, Giulio

2013-01-01

Over the past several years meditation practice has gained increasing attention as a non-pharmacological intervention to provide health related benefits, from promoting general wellness to alleviating the symptoms of a variety of medical conditions. However, the effects of meditation training on brain activity still need to be fully characterized. Sleep provides a unique approach to explore the meditation-related plastic changes in brain function. In this study we performed sleep high-density electroencephalographic (hdEEG) recordings in long-term meditators (LTM) of Buddhist meditation practices (approximately 8700 mean hours of life practice) and meditation naive individuals. We found that LTM had increased parietal-occipital EEG gamma power during NREM sleep. This increase was specific for the gamma range (25–40 Hz), was not related to the level of spontaneous arousal during NREM and was positively correlated with the length of lifetime daily meditation practice. Altogether, these findings indicate that meditation practice produces measurable changes in spontaneous brain activity, and suggest that EEG gamma activity during sleep represents a sensitive measure of the long-lasting, plastic effects of meditative training on brain function. PMID:24015304

Increased overall cortical connectivity with syndrome specific local decreases suggested by atypical sleep-EEG synchronization in Williams syndrome.

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Gombos, Ferenc; Bódizs, Róbert; Kovács, Ilona

2017-07-21

Williams syndrome (7q11.23 microdeletion) is characterized by specific alterations in neurocognitive architecture and functioning, as well as disordered sleep. Here we analyze the region, sleep state and frequency-specific EEG synchronization of whole night sleep recordings of 21 Williams syndrome and 21 typically developing age- and gender-matched subjects by calculating weighted phase lag indexes. We found broadband increases in inter- and intrahemispheric neural connectivity for both NREM and REM sleep EEG of Williams syndrome subjects. These effects consisted of increased theta, high sigma, and beta/low gamma synchronization, whereas alpha synchronization was characterized by a peculiar Williams syndrome-specific decrease during NREM states (intra- and interhemispheric centro-temporal) and REM phases of sleep (occipital intra-area synchronization). We also found a decrease in short range, occipital connectivity of NREM sleep EEG theta activity. The striking increased overall synchronization of sleep EEG in Williams syndrome subjects is consistent with the recently reported increase in synaptic and dendritic density in stem-cell based Williams syndrome models, whereas decreased alpha and occipital connectivity might reflect and underpin the altered microarchitecture of primary visual cortex and disordered visuospatial functioning of Williams syndrome subjects.

Graph Theoretical Analysis of BOLD Functional Connectivity during Human Sleep without EEG Monitoring.

Directory of Open Access Journals (Sweden)

Jun Lv

Full Text Available Functional brain networks of human have been revealed to have small-world properties by both analyzing electroencephalogram (EEG and functional magnetic resonance imaging (fMRI time series.In our study, by using graph theoretical analysis, we attempted to investigate the changes of paralimbic-limbic cortex between wake and sleep states. Ten healthy young people were recruited to our experiment. Data from 2 subjects were excluded for the reason that they had not fallen asleep during the experiment. For each subject, blood oxygen level dependency (BOLD images were acquired to analyze brain network, and peripheral pulse signals were obtained continuously to identify if the subject was in sleep periods. Results of fMRI showed that brain networks exhibited stronger small-world characteristics during sleep state as compared to wake state, which was in consistent with previous studies using EEG synchronization. Moreover, we observed that compared with wake state, paralimbic-limbic cortex had less connectivity with neocortical system and centrencephalic structure in sleep.In conclusion, this is the first study, to our knowledge, has observed that small-world properties of brain functional networks altered when human sleeps without EEG synchronization. Moreover, we speculate that paralimbic-limbic cortex organization owns an efficient defense mechanism responsible for suppressing the external environment interference when humans sleep, which is consistent with the hypothesis that the paralimbic-limbic cortex may be functionally disconnected from brain regions which directly mediate their interactions with the external environment. Our findings also provide a reasonable explanation why stable sleep exhibits homeostasis which is far less susceptible to outside world.

Expert and crowd-sourced validation of an individualized sleep spindle detection method employing complex demodulation and individualized normalization

Directory of Open Access Journals (Sweden)

Laura eRay

2015-09-01

Full Text Available A spindle detection method was developed that: 1 extracts the signal of interest (i.e., spindle-related phasic changes in sigma relative to ongoing background sigma activity using complex demodulation, 2 accounts for variations of spindle characteristics across the night, scalp derivations and between individuals, and 3 employs a minimum number of sometimes arbitrary, user-defined parameters. Complex demodulation was used to extract instantaneous power in the spindle band. To account for intra- and inter-individual differences, the signal was z-score transformed using a 60s sliding window, per channel, over the course of the recording. Spindle events were detected with a z-score threshold corresponding to a low probability (e.g., 99th percentile. Spindle characteristics, such as amplitude, duration and oscillatory frequency, were derived for each individual spindle following detection, which permits spindles to be subsequently and flexibly categorized as slow or fast spindles from a single detection pass. Spindles were automatically detected in 15 young healthy subjects. Two experts manually identified spindles from C3 during Stage 2 sleep, from each recording; one employing conventional guidelines, and the other, identifying spindles with the aid of a sigma (11-16 Hz filtered channel. These spindles were then compared between raters and to the automated detection to identify the presence of true positives, true negatives, false positives and false negatives. This method of automated spindle detection resolves or avoids many of the limitations that complicate automated spindle detection, and performs well compared to a group of non-experts, and importantly, has good external validity with respect to the extant literature in terms of the characteristics of automatically detected spindles.

Wake and Sleep EEG in Patients With Huntington Disease: An eLORETA Study and Review of the Literature.

Science.gov (United States)

Piano, Carla; Mazzucchi, Edoardo; Bentivoglio, Anna Rita; Losurdo, Anna; Calandra Buonaura, Giovanna; Imperatori, Claudio; Cortelli, Pietro; Della Marca, Giacomo

2017-01-01

The aim of the study was to evaluate the EEG modifications in patients with Huntington disease (HD) compared with controls, by means of the exact LOw REsolution Tomography (eLORETA) software. We evaluated EEG changes during wake, non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. Moreover, we reviewed the literature concerning EEG modifications in HD. Twenty-three consecutive adult patients affected by HD were enrolled, 14 women and 9 men, mean age was 57.0 ± 12.4 years. Control subjects were healthy volunteers (mean age 58.2 ± 14.6 years). EEG and polygraphic recordings were performed during wake (before sleep) and during sleep. Sources of EEG activities were determined using the eLORETA software. In wake EEG, significant differences between patients and controls were detected in the delta frequency band (threshold T = ±4.606; P < .01) in the Brodmann areas (BAs) 3, 4, and 6 bilaterally. In NREM sleep, HD patients showed increased alpha power (T = ±4.516; P < .01) in BAs 4 and 6 bilaterally; decreased theta power (T = ±4.516; P < .01) in the BAs 23, 29, and 30; and decreased beta power (T = ±4.516; P < .01) in the left BA 30. During REM, HD patients presented decreased theta and alpha power (threshold T = ±4.640; P < .01) in the BAs 23, 29, 30, and 31 bilaterally. In conclusion, EEG data suggest a motor cortex dysfunction during wake and sleep in HD patients, which correlates with the clinical and polysomnographic evidence of increased motor activity during wake and NREM, and nearly absent motor abnormalities in REM. © EEG and Clinical Neuroscience Society (ECNS) 2016.

Interrelationship of sleep and juvenile myoclonic epilepsy (JME): a sleep questionnaire-, EEG-, and polysomnography (PSG)-based prospective case-control study.

Science.gov (United States)

Ramachandraiah, C T; Sinha, S; Taly, A B; Rao, S; Satishchandra, P

2012-11-01

We studied the effects of 'epilepsy on sleep and its architecture' and 'sleep on the occurrence and distribution of interictal epileptiform discharges (ED)' using 'sleep questionnaires', 'EEG', and 'PSG' in patients with JME. Forty patients with JME [20 on valproate (Group I - 20.8±4.0 years; M: F=9:11) and 20 drug-naïve (Group II - 24.4±6.7 years; M: F=9:11)] and 20 controls (M: F=9:11; age: 23.5±4.7 years) underwent assessment with Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), overnight PSG, and scalp-EEG. Epileptiform discharges (EDs) were quantified in different sleep stages. The 'ED Index' was derived as number of EDs/min per stage. Statistical Package for the Social Sciences (SPSS) vs. 11 was used for statistical analysis. A 'p' EEG revealed EDs in 22/40 (Group I: 7 and Group II: 15) patients. Thirty-five patients had EDs in various sleep stages during PSG (Group I: 17 and Group II: 18): N1 - Group I: 9 and Group II: 14, N2 - Group I: 14 and Group II: 14, N3 - Group I: 14 and Group II: 10, and REM - Group I: 9 and Group II: 11. The ED Index was higher during N2/N3 in Group I and N1/REM in Group II. The epileptiform discharges were frequently associated with arousals in N1/REM and K-complexes in N2. There was no other significant difference between Groups I and II. In conclusion, there was poor sleep quality in patients with JME compared to controls, especially those on valproate who had altered sleep architecture. Epileptiform activity was observed more often in sleep than wakefulness. Sleep stages had variable effect on epileptiform discharges with light sleep having a facilitatory effect in the drug-naïve group and slow wave sleep having a facilitatory effect in the valproate group. Copyright © 2012 Elsevier Inc. All rights reserved.

Sex Differences in the Sleep EEG of Young Adults : Visual Scoring and Spectral Analysis

NARCIS (Netherlands)

Dijk, Derk Jan; Beersma, Domien G.M.; Bloem, Gerda M.

1989-01-01

Baseline sleep of 13 men (mean age of 23.5 years) and 15 women (21.9 years) was analyzed. Visual scoring of the electroencephalograms (EEGs) revealed no significant differences between the sexes in the amounts of slow-wave sleep and rapid-eye-movement (REM) sleep. Spectral analysis, however,

Acute toxicity and sleep-wake EEG analysis of Stachtarpheta ...

African Journals Online (AJOL)

The effect of systemic administration of TASC on sleep architecture in rats was also evaluated in Sprague-Dawley rats that were chronically implanted with electrodes for electroencephalogram (EEG) and electromyogram (EMG) recording. The acute toxicity test revealed no lethal effect with doses of SCCR (up to 2000 ...

Closed-Loop Targeted Memory Reactivation during Sleep Improves Spatial Navigation.

Science.gov (United States)

Shimizu, Renee E; Connolly, Patrick M; Cellini, Nicola; Armstrong, Diana M; Hernandez, Lexus T; Estrada, Rolando; Aguilar, Mario; Weisend, Michael P; Mednick, Sara C; Simons, Stephen B

2018-01-01

Sounds associated with newly learned information that are replayed during non-rapid eye movement (NREM) sleep can improve recall in simple tasks. The mechanism for this improvement is presumed to be reactivation of the newly learned memory during sleep when consolidation takes place. We have developed an EEG-based closed-loop system to precisely deliver sensory stimulation at the time of down-state to up-state transitions during NREM sleep. Here, we demonstrate that applying this technology to participants performing a realistic navigation task in virtual reality results in a significant improvement in navigation efficiency after sleep that is accompanied by increases in the spectral power especially in the fast (12-15 Hz) sleep spindle band. Our results show promise for the application of sleep-based interventions to drive improvement in real-world tasks.

Data-driven modeling of sleep EEG and EOG reveals characteristics indicative of pre-Parkinson's and Parkinson's disease.

Science.gov (United States)

Christensen, Julie A E; Zoetmulder, Marielle; Koch, Henriette; Frandsen, Rune; Arvastson, Lars; Christensen, Søren R; Jennum, Poul; Sorensen, Helge B D

2014-09-30

Manual scoring of sleep relies on identifying certain characteristics in polysomnograph (PSG) signals. However, these characteristics are disrupted in patients with neurodegenerative diseases. This study evaluates sleep using a topic modeling and unsupervised learning approach to identify sleep topics directly from electroencephalography (EEG) and electrooculography (EOG). PSG data from control subjects were used to develop an EOG and an EEG topic model. The models were applied to PSG data from 23 control subjects, 25 patients with periodic leg movements (PLMs), 31 patients with idiopathic REM sleep behavior disorder (iRBD) and 36 patients with Parkinson's disease (PD). The data were divided into training and validation datasets and features reflecting EEG and EOG characteristics based on topics were computed. The most discriminative feature subset for separating iRBD/PD and PLM/controls was estimated using a Lasso-regularized regression model. The features with highest discriminability were the number and stability of EEG topics linked to REM and N3, respectively. Validation of the model indicated a sensitivity of 91.4% and a specificity of 68.8% when classifying iRBD/PD patients. The topics showed visual accordance with the manually scored sleep stages, and the features revealed sleep characteristics containing information indicative of neurodegeneration. This study suggests that the amount of N3 and the ability to maintain NREM and REM sleep have potential as early PD biomarkers. Data-driven analysis of sleep may contribute to the evaluation of neurodegenerative patients. Copyright © 2014 Elsevier B.V. All rights reserved.

Quantitative analysis of sleep EEG microstructure in the time-frequency domain.

Science.gov (United States)

De Carli, Fabrizio; Nobili, Lino; Beelke, Manolo; Watanabe, Tsuyoshi; Smerieri, Arianna; Parrino, Liborio; Terzano, Mario Giovanni; Ferrillo, Franco

2004-06-30

A number of phasic events influence sleep quality and sleep macrostructure. The detection of arousals and the analysis of cyclic alternating patterns (CAP) support the evaluation of sleep fragmentation and instability. Sixteen polygraphic overnight recordings were visually inspected for conventional Rechtscaffen and Kales scoring, while arousals were detected following the criteria of the American Sleep Disorders Association (ASDA). Three electroencephalograph (EEG) segments were associated to each event, corresponding to background activity, pre-arousal period and arousal. The study was supplemented by the analysis of time-frequency distribution of EEG within each subtype of phase A in the CAP. The arousals were characterized by the increase of alpha and beta power with regard to background. Within NREM sleep most of the arousals were preceded by a transient increase of delta power. The time-frequency evolution of the phase A of the CAP sequence showed a strong prevalence of delta activity during the whole A1, but high amplitude delta waves were found also in the first 2/3 s of A2 and A3, followed by desynchronization. Our results underline the strict relationship between the ASDA arousals, and the subtype A2 and A3 within the CAP: in both the association between a short sequence of transient slow waves and the successive increase of frequency and decrease of amplitude characterizes the arousal response.

Mobile Healthcare for Automatic Driving Sleep-Onset Detection Using Wavelet-Based EEG and Respiration Signals

Directory of Open Access Journals (Sweden)

Boon-Giin Lee

2014-09-01

Full Text Available Driving drowsiness is a major cause of traffic accidents worldwide and has drawn the attention of researchers in recent decades. This paper presents an application for in-vehicle non-intrusive mobile-device-based automatic detection of driver sleep-onset in real time. The proposed application classifies the driving mental fatigue condition by analyzing the electroencephalogram (EEG and respiration signals of a driver in the time and frequency domains. Our concept is heavily reliant on mobile technology, particularly remote physiological monitoring using Bluetooth. Respiratory events are gathered, and eight-channel EEG readings are captured from the frontal, central, and parietal (Fpz-Cz, Pz-Oz regions. EEGs are preprocessed with a Butterworth bandpass filter, and features are subsequently extracted from the filtered EEG signals by employing the wavelet-packet-transform (WPT method to categorize the signals into four frequency bands: α, β, θ, and δ. A mutual information (MI technique selects the most descriptive features for further classification. The reduction in the number of prominent features improves the sleep-onset classification speed in the support vector machine (SVM and results in a high sleep-onset recognition rate. Test results reveal that the combined use of the EEG and respiration signals results in 98.6% recognition accuracy. Our proposed application explores the possibility of processing long-term multi-channel signals.

Closed-Loop Targeted Memory Reactivation during Sleep Improves Spatial Navigation

Directory of Open Access Journals (Sweden)

Renee E. Shimizu

2018-02-01

Full Text Available Sounds associated with newly learned information that are replayed during non-rapid eye movement (NREM sleep can improve recall in simple tasks. The mechanism for this improvement is presumed to be reactivation of the newly learned memory during sleep when consolidation takes place. We have developed an EEG-based closed-loop system to precisely deliver sensory stimulation at the time of down-state to up-state transitions during NREM sleep. Here, we demonstrate that applying this technology to participants performing a realistic navigation task in virtual reality results in a significant improvement in navigation efficiency after sleep that is accompanied by increases in the spectral power especially in the fast (12–15 Hz sleep spindle band. Our results show promise for the application of sleep-based interventions to drive improvement in real-world tasks.

Characterization of sleep need dissipation using EEG based slow-wave activity analysis in two age groups

NARCIS (Netherlands)

Garcia-Molina, G.; Baehr, K.; Steele, B.; Tsoneva, T.K.; Pfundtner, S.; Mahadevan, A.; Papas, N.; Riedner, B.; Tononi, G.; White, D.

2017-01-01

Introduction: In the two-process model of sleep regulation, slow-wave activity (SWA, EEG power in the 0.5–4 Hz band) is a direct indicator of sleep need. SWA builds up during NREM sleep, declines before the onset of REM sleep, remains low during REM and the level of increase in successive NREM

Low Activity Microstates During Sleep.

Science.gov (United States)

Miyawaki, Hiroyuki; Billeh, Yazan N; Diba, Kamran

2017-06-01

To better understand the distinct activity patterns of the brain during sleep, we observed and investigated periods of diminished oscillatory and population spiking activity lasting for seconds during non-rapid eye movement (non-REM) sleep, which we call "LOW" activity sleep. We analyzed spiking and local field potential (LFP) activity of hippocampal CA1 region alongside neocortical electroencephalogram (EEG) and electromyogram (EMG) in 19 sessions from four male Long-Evans rats (260-360 g) during natural wake/sleep across the 24-hr cycle as well as data from other brain regions obtained from http://crcns.org.1,2. LOW states lasted longer than OFF/DOWN states and were distinguished by a subset of "LOW-active" cells. LOW activity sleep was preceded and followed by increased sharp-wave ripple activity. We also observed decreased slow-wave activity and sleep spindles in the hippocampal LFP and neocortical EEG upon LOW onset, with a partial rebound immediately after LOW. LOW states demonstrated activity patterns consistent with sleep but frequently transitioned into microarousals and showed EMG and LFP differences from small-amplitude irregular activity during quiet waking. Their likelihood decreased within individual non-REM epochs yet increased over the course of sleep. By analyzing data from the entorhinal cortex of rats,1 as well as the hippocampus, the medial prefrontal cortex, the postsubiculum, and the anterior thalamus of mice,2 obtained from http://crcns.org, we confirmed that LOW states corresponded to markedly diminished activity simultaneously in all of these regions. We propose that LOW states are an important microstate within non-REM sleep that provide respite from high-activity sleep and may serve a restorative function. © Sleep Research Society 2017. Published by Oxford University Press [on behalf of the Sleep Research Society].

Different Effects of Sleep Deprivation and Torpor on EEG Slow-Wave Characteristics in Djungarian Hamsters.

Science.gov (United States)

Vyazovskiy, V V; Palchykova, S; Achermann, P; Tobler, I; Deboer, T

2017-02-01

It has been shown previously in Djungarian hamsters that the initial electroencephalography (EEG) slow-wave activity (power in the 0.5-4.0 Hz band; SWA) in non-rapid eye movement (NREM) sleep following an episode of daily torpor is consistently enhanced, similar to the SWA increase after sleep deprivation (SD). However, it is unknown whether the network mechanisms underlying the SWA increase after torpor and SD are similar. EEG slow waves recorded in the neocortex during sleep reflect synchronized transitions between periods of activity and silence among large neuronal populations. We therefore set out to investigate characteristics of individual cortical EEG slow waves recorded during NREM sleep after 4 h SD and during sleep after emergence from an episode of daily torpor in adult male Djungarian hamsters. We found that during the first hour after both SD and torpor, the SWA increase was associated with an increase in slow-wave incidence and amplitude. However, the slopes of single slow waves during NREM sleep were steeper in the first hour after SD but not after torpor, and, in contrast to sleep after SD, the magnitude of change in slopes after torpor was unrelated to the changes in SWA. Furthermore, slow-wave slopes decreased progressively within the first 2 h after SD, while a progressive increase in slow-wave slopes was apparent during the first 2 h after torpor. The data suggest that prolonged waking and torpor have different effects on cortical network activity underlying slow-wave characteristics, while resulting in a similar homeostatic sleep response of SWA. We suggest that sleep plays an important role in network homeostasis after both waking and torpor, consistent with a recovery function for both states. © The Author 2017. Published by Oxford University Press.

[Daytime tiredness correlated with nocturnal respiratory and arousal variables in patients with sleep apnea: polysomnographic and EEG mapping studies].

Science.gov (United States)

Saletu, M; Hauer, C; Anderer, P; Saletu-Zyhlarz, G; Gruber, G; Oberndorfer, S; Mandl, M; Popovic, R; Saletu, B

2000-03-24

There is evidence that daytime tiredness is caused by apnea/hypopnea with oxygen desaturation and/or by sleep fragmentation due to arousals. The aim of this study was to investigate objective and subjective sleep and awakening quality and daytime vigilance--objectified by midmorning mapping of vigilance-controlled EEG (V-EEG)--in sleep apnea patients (N: 18), as compared with age- and sex-matched normal controls (N: 18) as well as to correlate nocturnal respiratory distress and arousals to daytime brain function. Statistical analyses demonstrated a deterioration in subjective and objective sleep and awakening quality in apnea patients. Midmorning V-EEG mapping in apnea patients exhibited less total power, more delta and theta, less alpha and beta activity, as well as a slower dominant frequency and centroid of the total activity compared to controls, which suggests a vigilance decrement. The Spearman rank correlation between 6 polysomnographically registered respiratory variables and 36 diurnal quantitative EEG measures demonstrated the following: the higher the apnea, apnea-hypopnea, snoring and desaturation indices and the lower the minimum and average low oxygen saturation, the more pronounced was diurnal tiredness. Eleven arousal measures based on ASDA criteria showed the following significant correlations: the higher the nocturnal arousal index and the more arousals due to hypopneas, the greater was daytime tiredness. On the other hand, the greater the average frequency change during arousals and the more spontaneous arousals, the better was daytime vigilance. Our findings show that, in contrast to the lengthy Multiple Sleep Latency (MSLT) and Maintenance of Wakefulness (MWT) tests which evaluate sleep pressure under resting conditions conducive to sleep, V-EEG mapping provides a brief objective measure of a sleep apnea patient's daytime tiredness under conditions of wakefulness more appropriate to reflect the patient's everyday life.

Adenosine A1 receptors in human sleep regulation studied by electroencephalography (EEG) and positron emission tomography (PET)

International Nuclear Information System (INIS)

Geissler, E.

2007-01-01

Sleep is an essential physiological process. However, the functions of sleep and the endogenous mechanisms involved in sleep regulation are only partially understood. Convergent lines of evidence support the hypothesis that the build-up of sleep propensity during wakefulness and its decline during sleep are associated with alterations in brain adenosine levels and adenosine receptor concentrations. The non-selective A 1 and A 2A adenosine receptor antagonist caffeine stimulates alertness and is known to attenuate changes in the waking and sleep electroencephalogram (EEG) typically observed after prolonged waking. Several findings point to an important function of the adenosine A 1 receptor (A 1 AR) in the modulation of vigilance states. The A 1 AR is densely expressed in brain regions involved in sleep regulation, and pharmacological manipulations affecting the A 1 AR were shown to influence sleep propensity and sleep depth. However, an involvement of the A 2A adenosine receptor (A 2A AR) is also assumed. The distinct functions of the A 1 and A 2A receptor subtypes in sleep-wake regulation and in mediating the effects of caffeine have not been identified so far. The selective adenosine A 1 receptor antagonist, 8-cyclopentyl-3-(3- 18 Ffluoropropyl)- 1-propylxanthine ( 18 F-CPFPX), offers the opportunity to get further insights into adenosinergic mechanisms by in vivo imaging of the A 1 AR subtype with positron emission tomography (PET). The aim of this thesis was to elucidate the role of adenosine A 1 receptors in human sleep regulation, combining 18 F-CPFPX PET brain imaging and EEG recordings, the gold standard in sleep research. It was hypothesized that sleep deprivation would induce adenosine accumulation and/or changes in A 1 AR density. Thus, the question was addressed whether these effects of prolonged wakefulness can be visualized by altered 18 F-CPFPX binding. Moreover, it was investigated whether radioligand uptake might be influenced by caffeine, since

Sleep: An Open-Source Python Software for Visualization, Analysis, and Staging of Sleep Data.

Science.gov (United States)

Combrisson, Etienne; Vallat, Raphael; Eichenlaub, Jean-Baptiste; O'Reilly, Christian; Lajnef, Tarek; Guillot, Aymeric; Ruby, Perrine M; Jerbi, Karim

2017-01-01

We introduce Sleep, a new Python open-source graphical user interface (GUI) dedicated to visualization, scoring and analyses of sleep data. Among its most prominent features are: (1) Dynamic display of polysomnographic data, spectrogram, hypnogram and topographic maps with several customizable parameters, (2) Implementation of several automatic detection of sleep features such as spindles, K-complexes, slow waves, and rapid eye movements (REM), (3) Implementation of practical signal processing tools such as re-referencing or filtering, and (4) Display of main descriptive statistics including publication-ready tables and figures. The software package supports loading and reading raw EEG data from standard file formats such as European Data Format, in addition to a range of commercial data formats. Most importantly, Sleep is built on top of the VisPy library, which provides GPU-based fast and high-level visualization. As a result, it is capable of efficiently handling and displaying large sleep datasets. Sleep is freely available (http://visbrain.org/sleep) and comes with sample datasets and an extensive documentation. Novel functionalities will continue to be added and open-science community efforts are expected to enhance the capacities of this module.

Sleep: An Open-Source Python Software for Visualization, Analysis, and Staging of Sleep Data

Directory of Open Access Journals (Sweden)

Etienne Combrisson

2017-09-01

Full Text Available We introduce Sleep, a new Python open-source graphical user interface (GUI dedicated to visualization, scoring and analyses of sleep data. Among its most prominent features are: (1 Dynamic display of polysomnographic data, spectrogram, hypnogram and topographic maps with several customizable parameters, (2 Implementation of several automatic detection of sleep features such as spindles, K-complexes, slow waves, and rapid eye movements (REM, (3 Implementation of practical signal processing tools such as re-referencing or filtering, and (4 Display of main descriptive statistics including publication-ready tables and figures. The software package supports loading and reading raw EEG data from standard file formats such as European Data Format, in addition to a range of commercial data formats. Most importantly, Sleep is built on top of the VisPy library, which provides GPU-based fast and high-level visualization. As a result, it is capable of efficiently handling and displaying large sleep datasets. Sleep is freely available (http://visbrain.org/sleep and comes with sample datasets and an extensive documentation. Novel functionalities will continue to be added and open-science community efforts are expected to enhance the capacities of this module.

Promoting Sleep Oscillations and Their Functional Coupling by Transcranial Stimulation Enhances Memory Consolidation in Mild Cognitive Impairment.

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Ladenbauer, Julia; Ladenbauer, Josef; Külzow, Nadine; de Boor, Rebecca; Avramova, Elena; Grittner, Ulrike; Flöel, Agnes

2017-07-26

Alzheimer's disease (AD) not only involves loss of memory functions, but also prominent deterioration of sleep physiology, which is already evident at the stage of mild cognitive impairment (MCI). Cortical slow oscillations (SO; 0.5-1 Hz) and thalamocortical spindle activity (12-15 Hz) during sleep, and their temporal coordination, are considered critical for memory formation. We investigated the potential of slow oscillatory transcranial direct current stimulation (so-tDCS), applied during a daytime nap in a sleep-state-dependent manner, to modulate these activity patterns and sleep-related memory consolidation in nine male and seven female human patients with MCI. Stimulation significantly increased overall SO and spindle power, amplified spindle power during SO up-phases, and led to stronger synchronization between SO and spindle power fluctuations in EEG recordings. Moreover, visual declarative memory was improved by so-tDCS compared with sham stimulation and was associated with stronger synchronization. These findings indicate a well-tolerated therapeutic approach for disordered sleep physiology and memory deficits in MCI patients and advance our understanding of offline memory consolidation. SIGNIFICANCE STATEMENT In the light of increasing evidence that sleep disruption is crucially involved in the progression of Alzheimer's disease (AD), sleep appears as a promising treatment target in this pathology, particularly to counteract memory decline. This study demonstrates the potential of a noninvasive brain stimulation method during sleep in patients with mild cognitive impairment (MCI), a precursor of AD, and advances our understanding of its mechanism. We provide first time evidence that slow oscillatory transcranial stimulation amplifies the functional cross-frequency coupling between memory-relevant brain oscillations and improves visual memory consolidation in patients with MCI. Copyright © 2017 the authors 0270-6474/17/377111-14$15.00/0.

Hippocampal sleep features: relations to human memory function

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Michele eFerrara

2012-04-01

Full Text Available The recent spread of intracranial EEG recordings techniques for presurgical evaluation of drug-resistant epileptic patients is providing new information on the activity of different brain structures during both wakefulness and sleep. The interest has been mainly focused on the medial temporal lobe, and in particular the hippocampal formation, whose peculiar local sleep features have been recently described, providing support to the idea that sleep is not a spatially global phenomenon. The study of the hippocampal sleep electrophysiology is particularly interesting because of its central role in the declarative memory formation. Recent data indicate that sleep contributes to memory formation. Therefore, it is relevant to understand whether specific pattern of activity taking place during sleep are related to memory consolidation processes. Fascinating similarities between different states of consciousness (wakefulness, REM sleep, NREM sleep in some electrophysiological mechanisms underlying cognitive processes have been reported. For instance, large-scale synchrony in gamma activity is important for waking memory and perception processes, and its changes during sleep may be the neurophysiological substrate of sleep-related deficits of declarative memory. Hippocampal activity seems to specifically support memory consolidation during sleep, through specific coordinated neurophysiological events (slow waves, spindles, ripples that would facilitate the integration of new information into the pre-existing cortical networks. A few studies indeed provided direct evidence that rhinal ripples as well as slow hippocampal oscillations are correlated with memory consolidation in humans. More detailed electrophysiological investigations assessing the specific relations between different types of memory consolidation and hippocampal EEG features are in order. These studies will add an important piece of knowledge to the elucidation of the ultimate sleep

Hippocampal Sleep Features: Relations to Human Memory Function

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Ferrara, Michele; Moroni, Fabio; De Gennaro, Luigi; Nobili, Lino

2012-01-01

The recent spread of intracranial electroencephalographic (EEG) recording techniques for presurgical evaluation of drug-resistant epileptic patients is providing new information on the activity of different brain structures during both wakefulness and sleep. The interest has been mainly focused on the medial temporal lobe, and in particular the hippocampal formation, whose peculiar local sleep features have been recently described, providing support to the idea that sleep is not a spatially global phenomenon. The study of the hippocampal sleep electrophysiology is particularly interesting because of its central role in the declarative memory formation. Recent data indicate that sleep contributes to memory formation. Therefore, it is relevant to understand whether specific patterns of activity taking place during sleep are related to memory consolidation processes. Fascinating similarities between different states of consciousness (wakefulness, REM sleep, non-REM sleep) in some electrophysiological mechanisms underlying cognitive processes have been reported. For instance, large-scale synchrony in gamma activity is important for waking memory and perception processes, and its changes during sleep may be the neurophysiological substrate of sleep-related deficits of declarative memory. Hippocampal activity seems to specifically support memory consolidation during sleep, through specific coordinated neurophysiological events (slow waves, spindles, ripples) that would facilitate the integration of new information into the pre-existing cortical networks. A few studies indeed provided direct evidence that rhinal ripples as well as slow hippocampal oscillations are correlated with memory consolidation in humans. More detailed electrophysiological investigations assessing the specific relations between different types of memory consolidation and hippocampal EEG features are in order. These studies will add an important piece of knowledge to the elucidation of the ultimate

Comparison of feature and classifier algorithms for online automatic sleep staging based on a single EEG signal

NARCIS (Netherlands)

Radha, M.; Garcia Molina, G.; Poel, M.; Tononi, G.

2014-01-01

Automatic sleep staging on an online basis has recently emerged as a research topic motivated by fundamental sleep research. The aim of this paper is to find optimal signal processing methods and machine learning algorithms to achieve online sleep staging on the basis of a single EEG signal. The

Targeted Memory Reactivation during Sleep Depends on Prior Learning.

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Creery, Jessica D; Oudiette, Delphine; Antony, James W; Paller, Ken A

2015-05-01

When sounds associated with learning are presented again during slow-wave sleep, targeted memory reactivation (TMR) can produce improvements in subsequent location recall. Here we used TMR to investigate memory consolidation during an afternoon nap as a function of prior learning. Twenty healthy individuals (8 male, 19-23 y old). Participants learned to associate each of 50 common objects with a unique screen location. When each object appeared, its characteristic sound was played. After electroencephalography (EEG) electrodes were applied, location recall was assessed for each object, followed by a 90-min interval for sleep. During EEG-verified slow-wave sleep, half of the sounds were quietly presented over white noise. Recall was assessed 3 h after initial learning. A beneficial effect of TMR was found in the form of higher recall accuracy for cued objects compared to uncued objects when pre-sleep accuracy was used as an explanatory variable. An analysis of individual differences revealed that this benefit was greater for participants with higher pre-sleep recall accuracy. In an analysis for individual objects, cueing benefits were apparent as long as initial recall was not highly accurate. Sleep physiology analyses revealed that the cueing benefit correlated with delta power and fast spindle density. These findings substantiate the use of targeted memory reactivation (TMR) methods for manipulating consolidation during sleep. TMR can selectively strengthen memory storage for object-location associations learned prior to sleep, except for those near-perfectly memorized. Neural measures found in conjunction with TMR-induced strengthening provide additional evidence about mechanisms of sleep consolidation. © 2015 Associated Professional Sleep Societies, LLC.

Aircraft noise effects on sleep: a systematic comparison of EEG awakenings and automatically detected cardiac activations

International Nuclear Information System (INIS)

Basner, Mathias; Müller, Uwe; Elmenhorst, Eva-Maria; Kluge, Götz; Griefahn, Barbara

2008-01-01

Polysomnography is the gold standard for investigating noise effects on sleep, but data collection and analysis are sumptuous and expensive. We recently developed an algorithm for the automatic identification of cardiac activations associated with cortical arousals, which uses heart rate information derived from a single electrocardiogram (ECG) channel. We hypothesized that cardiac activations can be used as estimates for EEG awakenings. Polysomnographic EEG awakenings and automatically detected cardiac activations were systematically compared using laboratory data of 112 subjects (47 male, mean ± SD age 37.9 ± 13 years), 985 nights and 23 855 aircraft noise events (ANEs). The probability of automatically detected cardiac activations increased monotonically with increasing maximum sound pressure levels of ANEs, exceeding the probability of EEG awakenings by up to 18.1%. If spontaneous reactions were taken into account, exposure–response curves were practically identical for EEG awakenings and cardiac activations. Automatically detected cardiac activations may be used as estimates for EEG awakenings. More investigations are needed to further validate the ECG algorithm in the field and to investigate inter-individual differences in its ability to predict EEG awakenings. This inexpensive, objective and non-invasive method facilitates large-scale field studies on the effects of traffic noise on sleep

Sleep-dependent memory consolidation in healthy aging and mild cognitive impairment.

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Pace-Schott, Edward F; Spencer, Rebecca M C

2015-01-01

Sleep quality and architecture as well as sleep's homeostatic and circadian controls change with healthy aging. Changes include reductions in slow-wave sleep's (SWS) percent and spectral power in the sleep electroencephalogram (EEG), number and amplitude of sleep spindles, rapid eye movement (REM) density and the amplitude of circadian rhythms, as well as a phase advance (moved earlier in time) of the brain's circadian clock. With mild cognitive impairment (MCI) there are further reductions of sleep quality, SWS, spindles, and percent REM, all of which further diminish, along with a profound disruption of circadian rhythmicity, with the conversion to Alzheimer's disease (AD). Sleep disorders may represent risk factors for dementias (e.g., REM Behavior Disorder presages Parkinson's disease) and sleep disorders are themselves extremely prevalent in neurodegenerative diseases. Working memory , formation of new episodic memories, and processing speed all decline with healthy aging whereas semantic, recognition, and emotional declarative memory are spared. In MCI, episodic and working memory further decline along with declines in semantic memory. In young adults, sleep-dependent memory consolidation (SDC) is widely observed for both declarative and procedural memory tasks. However, with healthy aging, although SDC for declarative memory is preserved, certain procedural tasks, such as motor-sequence learning, do not show SDC. In younger adults, fragmentation of sleep can reduce SDC, and a normative increase in sleep fragmentation may account for reduced SDC with healthy aging. Whereas sleep disorders such as insomnia, obstructive sleep apnea, and narcolepsy can impair SDC in the absence of neurodegenerative changes, the incidence of sleep disorders increases both with normal aging and, further, with neurodegenerative disease. Specific features of sleep architecture, such as sleep spindles and SWS are strongly linked to SDC. Diminution of these features with healthy aging

Non-REM sleep EEG power distribution in fatigue and sleepiness.

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Neu, Daniel; Mairesse, Olivier; Verbanck, Paul; Linkowski, Paul; Le Bon, Olivier

2014-04-01

The aim of this study is to contribute to the sleep-related differentiation between daytime fatigue and sleepiness. 135 subjects presenting with sleep apnea-hypopnea syndrome (SAHS, n=58) or chronic fatigue syndrome (CFS, n=52) with respective sleepiness or fatigue complaints and a control group (n=25) underwent polysomnography and psychometric assessments for fatigue, sleepiness, affective symptoms and perceived sleep quality. Sleep EEG spectral analysis for ultra slow, delta, theta, alpha, sigma and beta power bands was performed on frontal, central and occipital derivations. Patient groups presented with impaired subjective sleep quality and higher affective symptom intensity. CFS patients presented with highest fatigue and SAHS patients with highest sleepiness levels. All groups showed similar total sleep time. Subject groups mainly differed in sleep efficiency, wake after sleep onset, duration of light sleep (N1, N2) and slow wave sleep, as well as in sleep fragmentation and respiratory disturbance. Relative non-REM sleep power spectra distributions suggest a pattern of power exchange in higher frequency bands at the expense of central ultra slow power in CFS patients during all non-REM stages. In SAHS patients, however, we found an opposite pattern at occipital sites during N1 and N2. Slow wave activity presents as a crossroad of fatigue and sleepiness with, however, different spectral power band distributions during non-REM sleep. The homeostatic function of sleep might be compromised in CFS patients and could explain why, in contrast to sleepiness, fatigue does not resolve with sleep in these patients. The present findings thus contribute to the differentiation of both phenomena. Copyright © 2014 Elsevier Inc. All rights reserved.

Changes in EEG power density of non-REM sleep in depressed patients during treatment with trazodone

NARCIS (Netherlands)

Bemmel, Alex L. van; Beersma, Domien G.M.; Hoofdakker, Rutger H. van den

1995-01-01

Recently, it was hypothesized that acute or cumulative suppression of non-REM sleep intensity might be related to the therapeutic effects of antidepressants. This intensity has been proposed to be expressed in the EEG power density in non-REM sleep. In the present study, the relationship was

Sleep EEG Changes during Adolescence: An Index of a Fundamental Brain Reorganization

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Feinberg, Irwin; Campbell, Ian G.

2010-01-01

Delta (1-4 Hz) EEG power in non-rapid eye movement (NREM) sleep declines massively during adolescence. This observation stimulated the hypothesis that during adolescence the human brain undergoes an extensive reorganization driven by synaptic elimination. The parallel declines in synaptic density, delta wave amplitude and cortical metabolic rate…

Extraction of features from sleep EEG for Bayesian assessment of brain development.

Directory of Open Access Journals (Sweden)

Vitaly Schetinin

Full Text Available Brain development can be evaluated by experts analysing age-related patterns in sleep electroencephalograms (EEG. Natural variations in the patterns, noise, and artefacts affect the evaluation accuracy as well as experts' agreement. The knowledge of predictive posterior distribution allows experts to estimate confidence intervals within which decisions are distributed. Bayesian approach to probabilistic inference has provided accurate estimates of intervals of interest. In this paper we propose a new feature extraction technique for Bayesian assessment and estimation of predictive distribution in a case of newborn brain development assessment. The new EEG features are verified within the Bayesian framework on a large EEG data set including 1,100 recordings made from newborns in 10 age groups. The proposed features are highly correlated with brain maturation and their use increases the assessment accuracy.

Neural correlates of dream lucidity obtained from contrasting lucid versus non-lucid REM sleep: a combined EEG/fMRI case study.

Science.gov (United States)

Dresler, Martin; Wehrle, Renate; Spoormaker, Victor I; Koch, Stefan P; Holsboer, Florian; Steiger, Axel; Obrig, Hellmuth; Sämann, Philipp G; Czisch, Michael

2012-07-01

To investigate the neural correlates of lucid dreaming. Parallel EEG/fMRI recordings of night sleep. Sleep laboratory and fMRI facilities. Four experienced lucid dreamers. N/A. Out of 4 participants, one subject had 2 episodes of verified lucid REM sleep of sufficient length to be analyzed by fMRI. During lucid dreaming the bilateral precuneus, cuneus, parietal lobules, and prefrontal and occipito-temporal cortices activated strongly as compared with non-lucid REM sleep. In line with recent EEG data, lucid dreaming was associated with a reactivation of areas which are normally deactivated during REM sleep. This pattern of activity can explain the recovery of reflective cognitive capabilities that are the hallmark of lucid dreaming.

EEG Changes across Multiple Nights of Sleep Restriction and Recovery in Adolescents: The Need for Sleep Study.

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Ong, Ju Lynn; Lo, June C; Gooley, Joshua J; Chee, Michael W L

2016-06-01

To investigate sleep EEG changes in adolescents across 7 nights of sleep restriction to 5 h time in bed [TIB]) and 3 recovery nights of 9 h TIB. A parallel-group design, quasi-laboratory study was conducted in a boarding school. Fifty-five healthy adolescents (25 males, age = 15-19 y) who reported habitual TIBs of approximately 6 h on week nights (group average) but extended their sleep on weekends were randomly assigned to Sleep Restriction (SR) or Control groups. Participants underwent a 2-week protocol comprising 3 baseline nights (TIB = 9 h), 7 nights of sleep opportunity manipulation (TIB = 5 h for the SR and 9 h for the Control group), and 3 nights of recovery sleep (TIB = 9 h). Polysomnography was obtained on two baseline, three manipulation, and two recovery nights. Across the sleep restriction nights, total SWS duration was preserved relative to the 9 h baseline sleep opportunity, while other sleep stages were reduced. Considering only the first 5 h of sleep opportunity, SR participants had reduced N1 duration and wake after sleep onset (WASO), and increased total sleep time (TST), rapid eye movement (REM) sleep, and slow wave sleep (SWS) relative to baseline. Total REM sleep, N2, and TST duration remained above baseline levels by the third recovery sleep episode. In spite of preservation of SWS duration over multiple nights of sleep restriction, adolescents accustomed to curtailing nocturnal sleep on school day nights evidence residual effects on sleep macro-structure, even after three nights of recovery sleep. Older teenagers may not be as resilient to successive nights of sleep restriction as is commonly believed. © 2016 Associated Professional Sleep Societies, LLC.

Individual differences in the effects of mobile phone exposure on human sleep: rethinking the problem.

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Loughran, Sarah P; McKenzie, Raymond J; Jackson, Melinda L; Howard, Mark E; Croft, Rodney J

2012-01-01

Mobile phone exposure-related effects on the human electroencephalogram (EEG) have been shown during both waking and sleep states, albeit with slight differences in the frequency affected. This discrepancy, combined with studies that failed to find effects, has led many to conclude that no consistent effects exist. We hypothesised that these differences might partly be due to individual variability in response, and that mobile phone emissions may in fact have large but differential effects on human brain activity. Twenty volunteers from our previous study underwent an adaptation night followed by two experimental nights in which they were randomly exposed to two conditions (Active and Sham), followed by a full-night sleep episode. The EEG spectral power was increased in the sleep spindle frequency range in the first 30 min of non-rapid eye movement (non-REM) sleep following Active exposure. This increase was more prominent in the participants that showed an increase in the original study. These results confirm previous findings of mobile phone-like emissions affecting the EEG during non-REM sleep. Importantly, this low-level effect was also shown to be sensitive to individual variability. Furthermore, this indicates that previous negative results are not strong evidence for a lack of an effect and, given the far-reaching implications of mobile phone research, we may need to rethink the interpretation of results and the manner in which research is conducted in this field. Copyright © 2011 Wiley Periodicals, Inc.

What the cerveau isolé preparation tells us nowadays about sleep-wake mechanisms?

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Gottesmann, C

1988-01-01

The intercollicular transected preparation opened a rich field for investigations of sleep-wake mechanisms. Initial results showed that brain stem ascending influences are essential for maintaining an activated cortex. It was subsequently shown that the forebrain also develops activating influences, since EEG desynchronization of the cortex reappears in the chronic cerveau isolé preparation, and continuous or almost continuous theta rhythm is able to occur in the acute cerveau isolé preparation. A brief "intermediate stage" of sleep occurs during natural sleep just prior to and after paradoxical sleep. It is characterized by cortical spindle bursts, hippocampal low frequency theta activity (two patterns of the acute cerveau isolé preparation) and is accompanied by a very low thalamic transmission level, suggesting a cerveau isolé-like state. The chronic cerveau isolé preparation also demonstrates that the executive processes of paradoxical sleep are located in the lower brain stem, while the occurrence of this sleep stage seems to be modulated by forebrain structures.

Adenosine A{sub 1} receptors in human sleep regulation studied by electroencephalography (EEG) and positron emission tomography (PET)[Dissertation 17227

Energy Technology Data Exchange (ETDEWEB)

Geissler, E

2007-07-01

Sleep is an essential physiological process. However, the functions of sleep and the endogenous mechanisms involved in sleep regulation are only partially understood. Convergent lines of evidence support the hypothesis that the build-up of sleep propensity during wakefulness and its decline during sleep are associated with alterations in brain adenosine levels and adenosine receptor concentrations. The non-selective A{sub 1} and A{sub 2A} adenosine receptor antagonist caffeine stimulates alertness and is known to attenuate changes in the waking and sleep electroencephalogram (EEG) typically observed after prolonged waking. Several findings point to an important function of the adenosine A{sub 1} receptor (A{sub 1}AR) in the modulation of vigilance states. The A{sub 1}AR is densely expressed in brain regions involved in sleep regulation, and pharmacological manipulations affecting the A{sub 1}AR were shown to influence sleep propensity and sleep depth. However, an involvement of the A{sub 2A} adenosine receptor (A{sub 2A}AR) is also assumed. The distinct functions of the A{sub 1} and A{sub 2A} receptor subtypes in sleep-wake regulation and in mediating the effects of caffeine have not been identified so far. The selective adenosine A{sub 1} receptor antagonist, 8-cyclopentyl-3-(3-{sup 18}Ffluoropropyl)- 1-propylxanthine ({sup 18}F-CPFPX), offers the opportunity to get further insights into adenosinergic mechanisms by in vivo imaging of the A{sub 1}AR subtype with positron emission tomography (PET). The aim of this thesis was to elucidate the role of adenosine A{sub 1} receptors in human sleep regulation, combining {sup 18}F-CPFPX PET brain imaging and EEG recordings, the gold standard in sleep research. It was hypothesized that sleep deprivation would induce adenosine accumulation and/or changes in A{sub 1}AR density. Thus, the question was addressed whether these effects of prolonged wakefulness can be visualized by altered {sup 18}F-CPFPX binding. Moreover, it was

Deep convolutional neural networks for interpretable analysis of EEG sleep stage scoring

DEFF Research Database (Denmark)

Vilamala, Albert; Madsen, Kristoffer Hougaard; Hansen, Lars K.

2017-01-01

to purse for an automatic stage scoring based on machine learning techniques have been carried out over the last years. In this work, we resort to multitaper spectral analysis to create visually interpretable images of sleep patterns from EEG signals as inputs to a deep convolutional network trained...... to solve visual recognition tasks. As a working example of transfer learning, a system able to accurately classify sleep stages in new unseen patients is presented. Evaluations in a widely-used publicly available dataset favourably compare to state-of-the-art results, while providing a framework for visual...

Evidence for age-associated disinhibition of the wake drive provided by scoring principal components of the resting EEG spectrum in sleep-provoking conditions.

Science.gov (United States)

Putilov, Arcady A; Donskaya, Olga G

2016-01-01

Age-associated changes in different bandwidths of the human electroencephalographic (EEG) spectrum are well documented, but their functional significance is poorly understood. This spectrum seems to represent summation of simultaneous influences of several sleep-wake regulatory processes. Scoring of its orthogonal (uncorrelated) principal components can help in separation of the brain signatures of these processes. In particular, the opposite age-associated changes were documented for scores on the two largest (1st and 2nd) principal components of the sleep EEG spectrum. A decrease of the first score and an increase of the second score can reflect, respectively, the weakening of the sleep drive and disinhibition of the opposing wake drive with age. In order to support the suggestion of age-associated disinhibition of the wake drive from the antagonistic influence of the sleep drive, we analyzed principal component scores of the resting EEG spectra obtained in sleep deprivation experiments with 81 healthy young adults aged between 19 and 26 and 40 healthy older adults aged between 45 and 66 years. At the second day of the sleep deprivation experiments, frontal scores on the 1st principal component of the EEG spectrum demonstrated an age-associated reduction of response to eyes closed relaxation. Scores on the 2nd principal component were either initially increased during wakefulness or less responsive to such sleep-provoking conditions (frontal and occipital scores, respectively). These results are in line with the suggestion of disinhibition of the wake drive with age. They provide an explanation of why older adults are less vulnerable to sleep deprivation than young adults.

Decreased sleep spindle density in patients with idiopathic REM sleep behavior disorder and patients with Parkinson's disease.

Science.gov (United States)

Christensen, Julie A E; Kempfner, Jacob; Zoetmulder, Marielle; Leonthin, Helle L; Arvastson, Lars; Christensen, Søren R; Sorensen, Helge B D; Jennum, Poul

2014-03-01

To determine whether sleep spindles (SS) are potentially a biomarker for Parkinson's disease (PD). Fifteen PD patients with REM sleep behavior disorder (PD+RBD), 15 PD patients without RBD (PD-RBD), 15 idiopathic RBD (iRBD) patients and 15 age-matched controls underwent polysomnography (PSG). SS were scored in an extract of data from control subjects. An automatic SS detector using a Matching Pursuit (MP) algorithm and a Support Vector Machine (SVM) was developed and applied to the PSG recordings. The SS densities in N1, N2, N3, all NREM combined and REM sleep were obtained and evaluated across the groups. The SS detector achieved a sensitivity of 84.7% and a specificity of 84.5%. At a significance level of α=1%, the iRBD and PD+RBD patients had a significantly lower SS density than the control group in N2, N3 and all NREM stages combined. At a significance level of α=5%, PD-RBD had a significantly lower SS density in N2 and all NREM stages combined. The lower SS density suggests involvement in pre-thalamic fibers involved in SS generation. SS density is a potential early PD biomarker. It is likely that an automatic SS detector could be a supportive diagnostic tool in the evaluation of iRBD and PD patients. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Usefulness of a simple sleep-deprived EEG protocol for epilepsy diagnosis in de novo subjects.

Science.gov (United States)

Giorgi, Filippo S; Perini, Daria; Maestri, Michelangelo; Guida, Melania; Pizzanelli, Chiara; Caserta, Anna; Iudice, Alfonso; Bonanni, Enrica

2013-11-01

In case series concerning the role of EEG after sleep deprivation (SD-EEG) in epilepsy, patients' features and protocols vary dramatically from one report to another. In this study, we assessed the usefulness of a simple SD-EEG method in well characterized patients. Among the 963 adult subjects submitted to SD-EEG at our Center, in the period 2003-2010, we retrospectively selected for analysis only those: (1) evaluated for suspected epileptic seizures; (2) with a normal/non-specific baseline EEG; (3) still drug-free at the time of SD-EEG; (4) with an MRI analysis; (5) with at least 1 year follow-up. SD-EEG consisted in SD from 2:00 AM and laboratory EEG from 8:00 AM to 10:30 AM. We analyzed epileptic interictal abnormalities (IIAs) and their correlations with patients' features. Epilepsy was confirmed in 131 patients. SD-EEG showed IIAs in 41.2% of all patients with epilepsy, and a 91.1% specificity for epilepsy diagnosis; IIAs types observed during SD-EEG are different in generalized versus focal epilepsies; for focal epilepsies, the IIAs yield in SD-EEG is higher than in second routine EEG. This simple SD-EEG protocol is very useful in de novo patients with suspected seizures. This study sheds new light on the role of SD-EEG in specific epilepsy populations. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Clusters of Insomnia Disorder: An Exploratory Cluster Analysis of Objective Sleep Parameters Reveals Differences in Neurocognitive Functioning, Quantitative EEG, and Heart Rate Variability

Science.gov (United States)

Miller, Christopher B.; Bartlett, Delwyn J.; Mullins, Anna E.; Dodds, Kirsty L.; Gordon, Christopher J.; Kyle, Simon D.; Kim, Jong Won; D'Rozario, Angela L.; Lee, Rico S.C.; Comas, Maria; Marshall, Nathaniel S.; Yee, Brendon J.; Espie, Colin A.; Grunstein, Ronald R.

2016-01-01

Study Objectives: To empirically derive and evaluate potential clusters of Insomnia Disorder through cluster analysis from polysomnography (PSG). We hypothesized that clusters would differ on neurocognitive performance, sleep-onset measures of quantitative (q)-EEG and heart rate variability (HRV). Methods: Research volunteers with Insomnia Disorder (DSM-5) completed a neurocognitive assessment and overnight PSG measures of total sleep time (TST), wake time after sleep onset (WASO), and sleep onset latency (SOL) were used to determine clusters. Results: From 96 volunteers with Insomnia Disorder, cluster analysis derived at least two clusters from objective sleep parameters: Insomnia with normal objective sleep duration (I-NSD: n = 53) and Insomnia with short sleep duration (I-SSD: n = 43). At sleep onset, differences in HRV between I-NSD and I-SSD clusters suggest attenuated parasympathetic activity in I-SSD (P insomnia clusters derived from cluster analysis differ in sleep onset HRV. Preliminary data suggest evidence for three clusters in insomnia with differences for sustained attention and sleep-onset q-EEG. Clinical Trial Registration: Insomnia 100 sleep study: Australia New Zealand Clinical Trials Registry (ANZCTR) identification number 12612000049875. URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=347742. Citation: Miller CB, Bartlett DJ, Mullins AE, Dodds KL, Gordon CJ, Kyle SD, Kim JW, D'Rozario AL, Lee RS, Comas M, Marshall NS, Yee BJ, Espie CA, Grunstein RR. Clusters of Insomnia Disorder: an exploratory cluster analysis of objective sleep parameters reveals differences in neurocognitive functioning, quantitative EEG, and heart rate variability. SLEEP 2016;39(11):1993–2004. PMID:27568796

Long-range correlations of different EEG derivations in rats: sleep stage-dependent generators may play a key role

International Nuclear Information System (INIS)

Fang, Guangzhan; Xia, Yang; Lai, Yongxiu; You, Zili; Yao, Dezhong

2010-01-01

For the electroencephalogram (EEG), topographic differences in the long-range temporal correlations would imply that these signals might be affected by specific mechanisms related to the generation of a given neuronal process. So the properties of the generators of various EEG oscillations might be investigated by their spatial differences of the long-range temporal correlations. In the present study, these correlations were characterized with respect to their topography during different vigilance states by detrended fluctuation analysis (DFA). The results indicated that (1) most of the scaling exponents acquired from different EEG derivations for various oscillations were significantly different in each vigilance state; these differences might be resulted from the different quantities and different locations of sleep stage-dependent generators of various neuronal processes; (2) there might be multiple generators of delta and theta over the brain and many of them were sleep stage-dependent; (3) the best site of the frontal electrode in a fronto-parietal bipolar electrode for sleep staging might be above the anterior midline cortex. We suggest that DFA analysis can be used to explore the properties of the generators of a given neuronal oscillation, and the localizations of these generators if more electrodes are involved

Transient decoupling of cortical EEGs following arousals during NREM sleep in middle-aged and elderly women.

Science.gov (United States)

Ramanand, Pravitha; Bruce, Margaret C; Bruce, Eugene N

2010-08-01

Spontaneous cortical arousals in non-REM sleep increase with age and contribute to sleep fragmentation in the elderly. EEG spectral power in the faster frequencies exhibits well-described shifts during arousals. On the other hand, EEG activities also exhibit correlations, which are interpreted as an index of interdependence between distant cortical neural activities. The possibility of changes to the interdependence between cortical regions due to an arousal has not been considered. In this work, using previously recorded C3A2 and C4A1 EEG signals from two groups of adults, middle-aged (42-50 years) and elderly (71-86 years) women, we examined the effects of spontaneous arousals in NREM sleep on cortical interdependence. We quantified the auto- and cross-correlations in these signals using mutual information and characterized these correlations in periods before the onset and following the end of arousals. The pre-arousal period exhibited significantly higher interdependence between central regions than that following the arousal in both age groups (middle-aged: p=0.004, elderly: ppower changes characteristic of an arousal are no longer visible. The findings suggest that the state following an arousal characterized by lower interdependence may resemble a more vigilant period during which the system may be vulnerable to more arousals. Copyright 2010 Elsevier B.V. All rights reserved.

Role of the gluten-free diet on neurological-EEG findings and sleep disordered breathing in children with celiac disease.

Science.gov (United States)

Parisi, P; Pietropaoli, N; Ferretti, A; Nenna, R; Mastrogiorgio, G; Del Pozzo, M; Principessa, L; Bonamico, M; Villa, M P

2015-02-01

To determine whether celiac children are at risk for EEG-neurological features and sleep disordered breathing (SDB), and whether an appropriate gluten-free diet (GFD) influences these disorders. We consecutively enrolled 19 children with a new biopsy-proven celiac disease (CD) diagnosis. At CD diagnosis and after 6 months of GFD, each patient underwent a general and neurological examination, an electroencephalogram, a questionnaire about neurological features, and a validated questionnaire about SDB: OSA (obstructive sleep apnea) scores0 predict OSA. At CD diagnosis, 37% of patients complained headache that affected daily activities and 32% showed positive OSA score. The EEG examinations revealed abnormal finding in 48% of children. After 6 months of GFD headache disappeared in 72% of children and EEG abnormalities in 78%; all children showed negative OSA score. According to our preliminary data, in the presence of unexplained EEG abnormalities and/or other neurological disorders/SDB an atypical or silent CD should also be taken into account. Copyright © 2014 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

The effect of CPAP treatment on EEG of OSAS patients.

Science.gov (United States)

Zhang, Cheng; Lv, Jun; Zhou, Junhong; Su, Li; Feng, Liping; Ma, Jing; Wang, Guangfa; Zhang, Jue

2015-12-01

Continuous positive airway pressure (CPAP) is currently the most effective treatment method for obstructive sleep apnea syndrome (OSAS). The purpose of this study was to compare the sleep electroencephalogram (EEG) changes before and after the application of CPAP to OSAS patients. A retrospective study was conducted and 45 sequential patients who received both polysomnography (PSG) and CPAP titration were included. The raw data of sleep EEG were extracted and analyzed by engineers using two main factors: fractal dimension (FD) and the zero-crossing rate of detrended FD (zDFD). FD was an effective indicator reflecting the EEG complexity and zDFD was useful to reflect the variability of the EEG complexity. The FD and zDFD indexes of sleep EEG of 45 OSAS patients before and after CPAP titration were analyzed. The age of 45 OSAS patients was 52.7 ± 5.6 years old and the patients include 12 females and 33 males. After CPAP treatment, FD of EEG in non-rapid eye movement (NREM) sleep decreased significantly (P CPAP therapy (P CPAP therapy had a significant influence on sleep EEG in patients with OSAHS, which lead to a more stable EEG pattern. This may be one of the mechanisms that CPAP could improve sleep quality and brain function of OSAS patients.

Clusters of Insomnia Disorder: An Exploratory Cluster Analysis of Objective Sleep Parameters Reveals Differences in Neurocognitive Functioning, Quantitative EEG, and Heart Rate Variability.

Science.gov (United States)

Miller, Christopher B; Bartlett, Delwyn J; Mullins, Anna E; Dodds, Kirsty L; Gordon, Christopher J; Kyle, Simon D; Kim, Jong Won; D'Rozario, Angela L; Lee, Rico S C; Comas, Maria; Marshall, Nathaniel S; Yee, Brendon J; Espie, Colin A; Grunstein, Ronald R

2016-11-01

To empirically derive and evaluate potential clusters of Insomnia Disorder through cluster analysis from polysomnography (PSG). We hypothesized that clusters would differ on neurocognitive performance, sleep-onset measures of quantitative ( q )-EEG and heart rate variability (HRV). Research volunteers with Insomnia Disorder (DSM-5) completed a neurocognitive assessment and overnight PSG measures of total sleep time (TST), wake time after sleep onset (WASO), and sleep onset latency (SOL) were used to determine clusters. From 96 volunteers with Insomnia Disorder, cluster analysis derived at least two clusters from objective sleep parameters: Insomnia with normal objective sleep duration (I-NSD: n = 53) and Insomnia with short sleep duration (I-SSD: n = 43). At sleep onset, differences in HRV between I-NSD and I-SSD clusters suggest attenuated parasympathetic activity in I-SSD (P insomnia clusters derived from cluster analysis differ in sleep onset HRV. Preliminary data suggest evidence for three clusters in insomnia with differences for sustained attention and sleep-onset q -EEG. Insomnia 100 sleep study: Australia New Zealand Clinical Trials Registry (ANZCTR) identification number 12612000049875. URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=347742. © 2016 Associated Professional Sleep Societies, LLC.

Data-driven modeling of sleep EEG and EOG reveals characteristics indicative of pre-Parkinson's and Parkinson's disease

DEFF Research Database (Denmark)

Christensen, Julie Anja Engelhard; Zoetmulder, Marielle; Koch, Henriette

2014-01-01

patients with idiopathic REM sleep behavior disorder (iRBD) and 36 patients with Parkinson's disease (PD). The data were divided into training and validation datasets and features reflecting EEG and EOG characteristics based on topics were computed. The most discriminative feature subset for separating i...... and the ability to maintain NREM and REM sleep have potential as early PD biomarkers. Data-driven analysis of sleep may contribute to the evaluation of neurodegenerative patients. (C) 2014 Elsevier B.V. All rights reserved.......Background: Manual scoring of sleep relies on identifying certain characteristics in polysomnograph (PSG) signals. However, these characteristics are disrupted in patients with neurodegenerative diseases. New method: This study evaluates sleep using a topic modeling and unsupervised learning...

Sleep electroencephalography as a biomarker in depression

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Steiger A

2015-04-01

Full Text Available Axel Steiger, Marcel Pawlowski, Mayumi Kimura Max Planck Institute of Psychiatry, Munich, Germany Abstract: The sleep electroencephalogram (EEG provides biomarkers of depression, which may help with diagnosis, prediction of therapy response, and prognosis in the treatment of depression. In patients with depression, characteristic sleep EEG changes include impaired sleep continuity, disinhibition of rapid-eye-movement (REM sleep, and impaired non-REM sleep. Most antidepressants suppress REM sleep in depressed patients, healthy volunteers, and in animal models. REM suppression appears to be an important, but not an absolute requirement, for antidepressive effects of a substance. Enhanced REM density, a measure for frequency of REM, characterizes high-risk probands for affective disorders. REM-sleep changes were also found in animal models of depression. Sleep-EEG variables were shown to predict the response to treatment with antidepressants. Furthermore, certain clusters of sleep EEG variables predicted the course of the disorder for several years. Some of the predicted sleep EEG markers appear to be related to hypothalamic–pituitary–adrenal system activity. Keywords: biomarkers, depression, sleep EEG, antidepressants, prediction, animal models

Cyclic alternating pattern and interictal epileptiform discharges during morning sleep after sleep deprivation in temporal lobe epilepsy.

Science.gov (United States)

Giorgi, Filippo Sean; Maestri, Michelangelo; Guida, Melania; Carnicelli, Luca; Caciagli, Lorenzo; Ferri, Raffaele; Bonuccelli, Ubaldo; Bonanni, Enrica

2017-08-01

Sleep deprivation (SD) increases the occurrence of interictal epileptiform discharges (IED) compared to basal EEG in temporal lobe epilepsy (TLE). In adults, EEG after SD is usually performed in the morning after SD. We aimed to evaluate whether morning sleep after SD bears additional IED-inducing effects compared with nocturnal physiological sleep, and whether changes in sleep stability (described by the cyclic alternating pattern-CAP) play a significant role. Adult patients with TLE underwent in-lab night polysomnography (n-PSG) and, within 7days from n-PSG, they underwent also a morning EEG after night SD (SD-EEG). We included only TLE patients in which both recordings showed IED. SD-EEG consisted of waking up patients at 2:00 AM and performing video EEG at 8:00 AM. For both recordings, we obtained the following markers for the first sleep cycle: IED/h (Spike Index, SI), sleep macrostructure, microstructure (NREM CAP rate; A1, A2 and A3 Indices), and SI association with CAP variables. The macrostructure of the first sleep cycle was similar in n-PSG and morning SD-EEG, whereas CAP rate and SI were significantly higher in SD-EEG. SI increase was selectively associated with CAP phases. SD increases the instability of morning recovery sleep compared with n-PSG, and particularly enhances CAP A1 phases, which are associated with the majority of IED. Thus, higher instability of morning recovery sleep may account at least in part for the increased IED yield in SD-EEG in TLE patients. Copyright © 2017 Elsevier Inc. All rights reserved.

Close relationship between fMRI signals and transient heart rate changes accompanying K-complex. Simultaneous EEG/fMRI study

International Nuclear Information System (INIS)

Kan, Shigeyuki; Koike, Takahiko; Miyauchi, Satoru; Misaki, Masaya

2009-01-01

Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) allows the investigation of spontaneous activities in the human brain. Recently, by using this technique, increases in fMRI signal accompanying transient EEG activities such as sleep spindles and slow waves were reported. Although these fMRI signal increases appear to arise as a result of the neural activities being reflected in the EEG, when the influence of physiological activities upon fMRI signals are taken into consideration, it is highly controversial that fMRI signal increases accompanying transient EEG activities reflect actual neural activities. In the present study, we conducted simultaneous fMRI and polysomnograph recording of 18 normal adults, to study the effect of transient heart rate changes after a K-complex on fMRI signals. Significant fMRI signal increase was observed in the cerebellum, the ventral thalamus, the dorsal part of the brainstem, the periventricular white matter and the ventricle (quadrigeminal cistern). On the other hand, significant fMRI signal decrease was observed only in the right insula. Moreover, intensities of fMRI signal increase that was accompanied by a K-complex correlated positively with the magnitude of heart rate changes after a K-complex. Previous studies have reported that K-complex is closely related with sympathetic nervous activity and that the attributes of perfusion regulation in the brain differ during wakefulness and sleep. By taking these findings into consideration, our present results indicate that a close relationship exists between a K-complex and the changes in cardio- and neurovascular regulations that are mediated by the autonomic nervous system during sleep; further, these results indicate that transient heart rate changes after a K-complex can affect the fMRI signal generated in certain brain regions. (author)

Topographic mapping of electroencephalography coherence in hypnagogic state.

Science.gov (United States)

Tanaka, H; Hayashi, M; Hori, T

1998-04-01

The present study examined the topographic characteristics of hypnagogic electroencephalography (EEG), using topographic mapping of EEG power and coherence corresponding to nine EEG stages (Hori's hypnagogic EEG stages). EEG stages 1 and 2, the EEG stages 3-8, and the EEG stage 9 each correspond with standard sleep stage W, 1 and 2, respectively. The dominant topographic components of delta and theta activities increased clearly from the vertex sharp-wave stage (the EEG stages 6 and 7) in the anterior-central areas. The dominant topographic component of alpha 3 activities increased clearly from the EEG stage 9 in the anterior-central areas. The dominant topographic component of sigma activities increased clearly from the EEG stage 8 in the central-parietal area. These results suggested basic sleep process might start before the onset of sleep stage 2 or of the manually scored spindles.

Cordance derived from REM sleep EEG as a biomarker for treatment response in depression--a naturalistic study after antidepressant medication.

Science.gov (United States)

Adamczyk, Marek; Gazea, Mary; Wollweber, Bastian; Holsboer, Florian; Dresler, Martin; Steiger, Axel; Pawlowski, Marcel

2015-04-01

To evaluate whether prefrontal cordance in theta frequency band derived from REM sleep EEG after the first week of antidepressant medication could characterize the treatment response after 4 weeks of therapy in depressed patients. 20 in-patients (15 females, 5 males) with a depressive episode and 20 healthy matched controls were recruited into 4-week, open label, case-control study. Patients were treated with various antidepressants. No significant differences in age (responders (mean ± SD): 45 ± 22) years; non-responders: 49 ± 12 years), medication or Hamilton Depression Rating Scale (HAM-D) score (responders: 23.8 ± 4.5; non-responders 24.5 ± 7.6) at inclusion into the study were found between responders and non-responders. Response to treatment was defined as a ≥50% reduction of HAM-D score at the end of four weeks of active medication. Sleep EEG of patients was recorded after the first and the fourth week of medication. Cordance was computed for prefrontal EEG channels in theta frequency band during tonic REM sleep. The group of 8 responders had significantly higher prefrontal theta cordance in relation to the group of 12 non-responders after the first week of antidepressant medication. This finding was significant also when controlling for age, gender and number of previous depressive episodes (F1,15 = 6.025, P = .027). Furthermore, prefrontal cordance of all patients showed significant positive correlation (r = 0.52; P = .019) with the improvement of HAM-D score between the inclusion week and fourth week of medication. The results suggest that prefrontal cordance derived from REM sleep EEG could provide a biomarker for the response to antidepressant treatment in depressed patients. Copyright © 2015 Elsevier Ltd. All rights reserved.

Linear and non-linear interdependence of EEG and HRV frequency bands in human sleep.

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Chaparro-Vargas, Ramiro; Dissanayaka, P Chamila; Patti, Chanakya Reddy; Schilling, Claudia; Schredl, Michael; Cvetkovic, Dean

2014-01-01

The characterisation of functional interdependencies of the autonomic nervous system (ANS) stands an evergrowing interest to unveil electroencephalographic (EEG) and Heart Rate Variability (HRV) interactions. This paper presents a biosignal processing approach as a supportive computational resource in the estimation of sleep dynamics. The application of linear, non-linear methods and statistical tests upon 10 overnight polysomnographic (PSG) recordings, allowed the computation of wavelet coherence and phase locking values, in order to identify discerning features amongst the clinical healthy subjects. Our findings showed that neuronal oscillations θ, α and σ interact with cardiac power bands at mid-to-high rank of coherence and phase locking, particularly during NREM sleep stages.

Automatic REM Sleep Detection Associated with Idiopathic REM Sleep Behavior Disorder

DEFF Research Database (Denmark)

Kempfner, Jacob; Sørensen, Gertrud Laura; Sørensen, Helge Bjarup Dissing

2011-01-01

Rapid eye movement sleep Behavior Disorder (RBD) is a strong early marker of later development of Parkinsonism. Currently there are no objective methods to identify and discriminate abnormal from normal motor activity during REM sleep. Therefore, a REM sleep detection without the use of chin...... electromyography (EMG) is useful. This is addressed by analyzing the classification performance when implementing two automatic REM sleep detectors. The first detector uses the electroencephalography (EEG), electrooculography (EOG) and EMG to detect REM sleep, while the second detector only uses the EEG and EOG......, an automatic computerized REM detection algorithm has been implemented, using wavelet packet combined with artificial neural network. Results: When using the EEG, EOG and EMG modalities, it was possible to correctly classify REM sleep with an average Area Under Curve (AUC) equal to 0:900:03 for normal subjects...

Automatic REM sleep detection associated with idiopathic rem sleep Behavior Disorder

DEFF Research Database (Denmark)

Kempfner, J; Sørensen, Gertrud Laura; Sorensen, H B D

2011-01-01

Rapid eye movement sleep Behavior Disorder (RBD) is a strong early marker of later development of Parkinsonism. Currently there are no objective methods to identify and discriminate abnormal from normal motor activity during REM sleep. Therefore, a REM sleep detection without the use of chin...... electromyography (EMG) is useful. This is addressed by analyzing the classification performance when implementing two automatic REM sleep detectors. The first detector uses the electroencephalography (EEG), electrooculography (EOG) and EMG to detect REM sleep, while the second detector only uses the EEG and EOG....

Pontas positivas occipitais transitórias no eletrencefalograma de pacientes epilépticos submetidos a privação do sono Sleep occipital positive transient spikes seen at EEG of epileptic patients submitted to sleep deprivation

Directory of Open Access Journals (Sweden)

Gilson Edmar Gonçalves e Silva

2007-06-01

Full Text Available OBJETIVO: Comparar o aparecimento do grafoelemento de ponta positiva occipital transitória do sono em eletrencefalograma (EEG de pacientes epilépticos com e sem privação do sono, como método de ativação. MÉTODO: Foram analisados 40 EEG de 20 pacientes epilépticos com idade variando de 12 a 43 anos sendo 60% do sexo masculino, atendidos no Hospital das Clínicas da Universidade Federal de Pernambuco, no período de 1995 a 2000. Foram incluídos pacientes com epilepsia diagnosticada clinicamente e EEG sem alteração. Cada paciente foi submetido a um EEG sem privação de sono e outro após 36 horas de privação. O registro dos dois EEG foi separado por intervalo de 48 horas, obedecendo ao protocolo padrão. O efeito da privação do sono foi avaliado pelo aparecimento do grafoelemento PPOTS durante o estágio NREM do sono. RESULTADOS: No EEG sem privação do sono, a PPOTS foi identificada em 6 (30% pacientes no estágio I e em 1 (5% paciente em ambos os estágios I e II NREM. Após privação do sono, PPOTS estiveram ausentes em apenas um paciente, mas presentes em 25% casos no estágio I NREM e em 70%, nos estágios I e II NREM. CONCLUSÃO: O aumento da freqüência de PPOTS após privação do sono, parece indicar a existência da liberação de neurotransmissores excitatórios, o que pode contribuir significativamente para a investigação da excitabilidade cerebral.OBJECTIVE: To compare the presence of "sleep occipital positive transient spikes" (SOPTS in the electroencephalogram (EEG of epileptic patients without sleep deprivation (SD to those with SD, as an activation method. METHOD: The author analyzed 40 EEG of 20 epileptic patients, aging from 12 to 43 years, 60%, males. Those patients were attempted at the Clinics Hospital of Universidade Federal de Pernambuco, from 1995 to 2000. Every patient included in this study had epilepsy clinically diagnosed and all EEG without abnormalities. Each subject was submitted to one EEG

Sustained sleep fragmentation induces sleep homeostasis in mice

KAUST Repository

Baud, Maxime O.; Magistretti, Pierre J.; Petit, Jean Marie

2015-01-01

Study Objectives: Sleep fragmentation (SF) is an integral feature of sleep apnea and other prevalent sleep disorders. Although the effect of repetitive arousals on cognitive performance is well documented, the effects of long-term SF on electroencephalography (EEG) and molecular markers of sleep homeostasis remain poorly investigated. To address this question, we developed a mouse model of chronic SF and characterized its effect on EEG spectral frequencies and the expression of genes previously linked to sleep homeostasis including clock genes, heat shock proteins, and plasticity-related genes. Design: N/A. Setting: Animal sleep research laboratory. Participants : Sixty-six C57BL6/J adult mice. Interventions: Instrumental sleep disruption at a rate of 60/h during 14 days Measurements and Results: Locomotor activity and EEG were recorded during 14 days of SF followed by recovery for 2 days. Despite a dramatic number of arousals and decreased sleep bout duration, SF minimally reduced total quantity of sleep and did not significantly alter its circadian distribution. Spectral analysis during SF revealed a homeostatic drive for slow wave activity (SWA; 1-4 Hz) and other frequencies as well (4-40 Hz). Recordings during recovery revealed slow wave sleep consolidation and a transient rebound in SWA, and paradoxical sleep duration. The expression of selected genes was not induced following chronic SF. Conclusions: Chronic sleep fragmentation (SF) increased sleep pressure confirming that altered quality with preserved quantity triggers core sleep homeostasis mechanisms. However, it did not induce the expression of genes induced by sleep loss, suggesting that these molecular pathways are not sustainably activated in chronic diseases involving SF.

Sustained sleep fragmentation induces sleep homeostasis in mice

KAUST Repository

Baud, Maxime O.

2015-04-01

Study Objectives: Sleep fragmentation (SF) is an integral feature of sleep apnea and other prevalent sleep disorders. Although the effect of repetitive arousals on cognitive performance is well documented, the effects of long-term SF on electroencephalography (EEG) and molecular markers of sleep homeostasis remain poorly investigated. To address this question, we developed a mouse model of chronic SF and characterized its effect on EEG spectral frequencies and the expression of genes previously linked to sleep homeostasis including clock genes, heat shock proteins, and plasticity-related genes. Design: N/A. Setting: Animal sleep research laboratory. Participants : Sixty-six C57BL6/J adult mice. Interventions: Instrumental sleep disruption at a rate of 60/h during 14 days Measurements and Results: Locomotor activity and EEG were recorded during 14 days of SF followed by recovery for 2 days. Despite a dramatic number of arousals and decreased sleep bout duration, SF minimally reduced total quantity of sleep and did not significantly alter its circadian distribution. Spectral analysis during SF revealed a homeostatic drive for slow wave activity (SWA; 1-4 Hz) and other frequencies as well (4-40 Hz). Recordings during recovery revealed slow wave sleep consolidation and a transient rebound in SWA, and paradoxical sleep duration. The expression of selected genes was not induced following chronic SF. Conclusions: Chronic sleep fragmentation (SF) increased sleep pressure confirming that altered quality with preserved quantity triggers core sleep homeostasis mechanisms. However, it did not induce the expression of genes induced by sleep loss, suggesting that these molecular pathways are not sustainably activated in chronic diseases involving SF.

Topography of Slow Sigma Power during Sleep is Associated with Processing Speed in Preschool Children.

Science.gov (United States)

Doucette, Margaret R; Kurth, Salome; Chevalier, Nicolas; Munakata, Yuko; LeBourgeois, Monique K

2015-11-04

Cognitive development is influenced by maturational changes in processing speed, a construct reflecting the rapidity of executing cognitive operations. Although cognitive ability and processing speed are linked to spindles and sigma power in the sleep electroencephalogram (EEG), little is known about such associations in early childhood, a time of major neuronal refinement. We calculated EEG power for slow (10-13 Hz) and fast (13.25-17 Hz) sigma power from all-night high-density electroencephalography (EEG) in a cross-sectional sample of healthy preschool children (n = 10, 4.3 ± 1.0 years). Processing speed was assessed as simple reaction time. On average, reaction time was 1409 ± 251 ms; slow sigma power was 4.0 ± 1.5 μV²; and fast sigma power was 0.9 ± 0.2 μV². Both slow and fast sigma power predominated over central areas. Only slow sigma power was correlated with processing speed in a large parietal electrode cluster (p power predicted faster reaction time. Our findings indicate regional correlates between sigma power and processing speed that are specific to early childhood and provide novel insights into the neurobiological features of the EEG that may underlie developing cognitive abilities.

Time course of EEG slow-wave activity in pre-school children with sleep disordered breathing: a possible mechanism for daytime deficits?

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Biggs, Sarah N; Walter, Lisa M; Nisbet, Lauren C; Jackman, Angela R; Anderson, Vicki; Nixon, Gillian M; Davey, Margot J; Trinder, John; Hoffmann, Robert; Armitage, Roseanne; Horne, Rosemary S C

2012-09-01

Daytime deficits in children with sleep disordered breathing (SDB) are theorized to result from hypoxic insult to the developing brain or fragmented sleep. Yet, these do not explain why deficits occur in primary snorers (PS). The time course of slow wave EEG activity (SWA), a proxy of homeostatic regulation and cortical maturation, may provide insight. Clinical and control subjects (N=175: mean age 4.3±0.9 y: 61% male) participated in overnight polysomnography (PSG). Standard sleep scoring and power spectral analyses were conducted on EEG (C4/A1; 0.5-sleep stages and respiratory parameters. Repeated-measures ANCOVA evaluated group differences in the time course of SWA. Four groups were classified: controls (OAHI ≤ 1 event/h; no clinical history); PS (OAHI ≤ 1 event/h; clinical history); mild OSA (OAHI=1-5 events/h); and moderate to severe OSA (MS OSA: OAHI>5 events/h). Group differences were found in the percentage of time spent in NREM Stages 1 and 4 (psleep pressure but impaired restorative sleep function in pre-school children with SDB, providing new insights into the possible mechanism for daytime deficits observed in all severities of SDB. Copyright © 2012 Elsevier B.V. All rights reserved.

On the need of objective vigilance monitoring: Effects of sleep loss on target detection and task-negative activity using combined EEG/fMRI

Directory of Open Access Journals (Sweden)

Michael eCzisch

2012-04-01

Full Text Available Sleep loss affects attention by reducing levels of arousal and alertness. The neural mechanisms underlying the compensatory efforts of the brain to maintain attention and performance after sleep deprivation are not fully understood. Previous neuroimaging studies of sleep deprivation have not been able to exclude the effects of reduced arousal and vigilance when examining cerebral responses to cognitive challenges. Here, we used a simultaneous electroencephalography (EEG and functional magnetic resonance imaging (fMRI approach to study the effects of 36 hours of total sleep deprivation (TSD. Specifically, we focused on changes in selective attention processes as induced by an active acoustic oddball task, with the ability to isolate runs with objective EEG signs of high or reduced vigilance. At high vigilance, task-related activity appears to be sustained by compensatory co-activation of insular regions, but task-negative activity in the right posterior node of the default mode network is altered following TSD. When EEG shows signs of reduced vigilance, task-positive activity was massively impaired, but task-negative activation was showing levels comparable with the control condition after a well-rested night. Our results suggest that loss of strict anti-correlation between task-positive and task-negative activation reflects the effects of TSD, while the actual state of vigilance and task performance either affects task-related or task-negative activity.

Resting state EEG correlates of memory consolidation.

Science.gov (United States)

Brokaw, Kate; Tishler, Ward; Manceor, Stephanie; Hamilton, Kelly; Gaulden, Andrew; Parr, Elaine; Wamsley, Erin J

2016-04-01

Numerous studies demonstrate that post-training sleep benefits human memory. At the same time, emerging data suggest that other resting states may similarly facilitate consolidation. In order to identify the conditions under which non-sleep resting states benefit memory, we conducted an EEG (electroencephalographic) study of verbal memory retention across 15min of eyes-closed rest. Participants (n=26) listened to a short story and then either rested with their eyes closed, or else completed a distractor task for 15min. A delayed recall test was administered immediately following the rest period. We found, first, that quiet rest enhanced memory for the short story. Improved memory was associated with a particular EEG signature of increased slow oscillatory activity (rest can facilitate memory, and that this may occur via an active process of consolidation supported by slow oscillatory EEG activity and characterized by decreased attention to the external environment. Slow oscillatory EEG rhythms are proposed to facilitate memory consolidation during sleep by promoting hippocampal-cortical communication. Our findings suggest that EEG slow oscillations could play a significant role in memory consolidation during other resting states as well. Copyright © 2016 Elsevier Inc. All rights reserved.

Sleep to the beat: A nap favours consolidation of timing.

Science.gov (United States)

Verweij, Ilse M; Onuki, Yoshiyuki; Van Someren, Eus J W; Van der Werf, Ysbrand D

2016-06-01

Growing evidence suggests that sleep is important for procedural learning, but few studies have investigated the effect of sleep on the temporal aspects of motor skill learning. We assessed the effect of a 90-min day-time nap on learning a motor timing task, using 2 adaptations of a serial interception sequence learning (SISL) task. Forty-two right-handed participants performed the task before and after a 90-min period of sleep or wake. Electroencephalography (EEG) was recorded throughout. The motor task consisted of a sequential spatial pattern and was performed according to 2 different timing conditions, that is, either following a sequential or a random temporal pattern. The increase in accuracy was compared between groups using a mixed linear regression model. Within the sleep group, performance improvement was modeled based on sleep characteristics, including spindle- and slow-wave density. The sleep group, but not the wake group, showed improvement in the random temporal, but especially and significantly more strongly in the sequential temporal condition. None of the sleep characteristics predicted improvement on either general of the timing conditions. In conclusion, a daytime nap improves performance on a timing task. We show that performance on the task with a sequential timing sequence benefits more from sleep than motor timing. More important, the temporal sequence did not benefit initial learning, because differences arose only after an offline period and specifically when this period contained sleep. Sleep appears to aid in the extraction of regularities for optimal subsequent performance. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Quantitative topographic differentiation of the neonatal EEG.

Science.gov (United States)

Paul, Karel; Krajca, Vladimír; Roth, Zdenek; Melichar, Jan; Petránek, Svojmil

2006-09-01

To test the discriminatory topographic potential of a new method of the automatic EEG analysis in neonates. A quantitative description of the neonatal EEG can contribute to the objective assessment of the functional state of the brain, and may improve the precision of diagnosing cerebral dysfunctions manifested by 'disorganization', 'dysrhythmia' or 'dysmaturity'. 21 healthy, full-term newborns were examined polygraphically during sleep (EEG-8 referential derivations, respiration, ECG, EOG, EMG). From each EEG record, two 5-min samples (one from the middle of quiet sleep, the other from the middle of active sleep) were subject to subsequent automatic analysis and were described by 13 variables: spectral features and features describing shape and variability of the signal. The data from individual infants were averaged and the number of variables was reduced by factor analysis. All factors identified by factor analysis were statistically significantly influenced by the location of derivation. A large number of statistically significant differences were also established when comparing the effects of individual derivations on each of the 13 measured variables. Both spectral features and features describing shape and variability of the signal are largely accountable for the topographic differentiation of the neonatal EEG. The presented method of the automatic EEG analysis is capable to assess the topographic characteristics of the neonatal EEG, and it is adequately sensitive and describes the neonatal electroencephalogram with sufficient precision. The discriminatory capability of the used method represents a promise for their application in the clinical practice.

The early electroclinical manifestations of infantile spasms: A video EEG study

Directory of Open Access Journals (Sweden)

Mary Iype

2016-01-01

Full Text Available Purpose: Infantile spasms are described as flexor extensor and mixed; but more features of their semiology and ictal electroencephalography (EEG changes are sparse in the literature. The purpose of the study was to describe the clinical and ictal video-EEG characteristics of consecutive cases with infantile spasms and to try to find an association with the etiology. Materials and Methods: The clinical phenomenology and EEG characteristics on video-EEG were analyzed in 16 babies with infantile spasms. Results: A total of 869 spasms were reviewed. Nine (56.3% showed focal seizures at least once during the recording and 1 (6.3% had multifocal myoclonus in addition to the spasms. The duration of the cluster and interval between spasms was totally variable in all patients. Lateralizing phenomena were present in at least some of the spasms in all patients. Unilateral manual automatism in the form of holding the pinna was noted in three patients following the spasm. The ictal EEG activity in the majority (75% was the slow wave. Four (25% showed fast generalized spindle-like ictal discharges. Spikes, spike and wave activity, or electrodecremental pattern alone during the ictus was seen in none. On bivariate analysis, no factor noted on the video EEG had association with the etiology. Conclusion: Infantile spasms could be associated with focal and other seizures, has unique, non-uniform and variable semiology from patient to patient. The ictal EEG manifestation in the majority (75% of our patients was the slow wave transient with 25% showing generalized fast spindle-like activity.

Pharmaco-EEG Studies in Animals: A History-Based Introduction to Contemporary Translational Applications.

Science.gov (United States)

Drinkenburg, Wilhelmus H I M; Ahnaou, Abdallah; Ruigt, Gé S F

2015-01-01

Current research on the effects of pharmacological agents on human neurophysiology finds its roots in animal research, which is also reflected in contemporary animal pharmaco-electroencephalography (p-EEG) applications. The contributions, present value and translational appreciation of animal p-EEG-based applications are strongly interlinked with progress in recording and neuroscience analysis methodology. After the pioneering years in the late 19th and early 20th century, animal p-EEG research flourished in the pharmaceutical industry in the early 1980s. However, around the turn of the millennium the emergence of structurally and functionally revealing imaging techniques and the increasing application of molecular biology caused a temporary reduction in the use of EEG as a window into the brain for the prediction of drug efficacy. Today, animal p-EEG is applied again for its biomarker potential - extensive databases of p-EEG and polysomnography studies in rats and mice hold EEG signatures of a broad collection of psychoactive reference and test compounds. A multitude of functional EEG measures has been investigated, ranging from simple spectral power and sleep-wake parameters to advanced neuronal connectivity and plasticity parameters. Compared to clinical p-EEG studies, where the level of vigilance can be well controlled, changes in sleep-waking behaviour are generally a prominent confounding variable in animal p-EEG studies and need to be dealt with. Contributions of rodent pharmaco-sleep EEG research are outlined to illustrate the value and limitations of such preclinical p-EEG data for pharmacodynamic and chronopharmacological drug profiling. Contemporary applications of p-EEG and pharmaco-sleep EEG recordings in animals provide a common and relatively inexpensive window into the functional brain early in the preclinical and clinical development of psychoactive drugs in comparison to other brain imaging techniques. They provide information on the impact of

Characterization of early and mature electrophysiological biomarkers of patients with Parkinson’s disease

DEFF Research Database (Denmark)

Christensen, Julie Anja Engelhard

eye movements during sleep, 2) altered amount and stability of data-determined stages linked to N3 and REM sleep, 3) more REM-NREM sleep transitions determined by a data-driven model, 4) decreased spindle density and 5) altered spindle morphology compared to non-NDD subjects. In conclusion...... exist [83]. Sleep disturbances are common non-motor symptoms of PD, and strong findings associating a specific sleep disorder ("iRBD") to Parkinsonism suggest that sleep disturbances might precede the clinical diagnosis of PD. Analysis of sleep thus hold potential to serve as early disease...... identification, but as the current standard for sleep analysis relies on manual scorings guided by standards designed to fit healthy and normal sleep, manual sleep analysis of pathological sleep lacks substance. This dissertation hypothesizes that automated sleep analysis can identify altered patterns of EEG...

Automatic classification of background EEG activity in healthy and sick neonates

Science.gov (United States)

Löfhede, Johan; Thordstein, Magnus; Löfgren, Nils; Flisberg, Anders; Rosa-Zurera, Manuel; Kjellmer, Ingemar; Lindecrantz, Kaj

2010-02-01

The overall aim of our research is to develop methods for a monitoring system to be used at neonatal intensive care units. When monitoring a baby, a range of different types of background activity needs to be considered. In this work, we have developed a scheme for automatic classification of background EEG activity in newborn babies. EEG from six full-term babies who were displaying a burst suppression pattern while suffering from the after-effects of asphyxia during birth was included along with EEG from 20 full-term healthy newborn babies. The signals from the healthy babies were divided into four behavioural states: active awake, quiet awake, active sleep and quiet sleep. By using a number of features extracted from the EEG together with Fisher's linear discriminant classifier we have managed to achieve 100% correct classification when separating burst suppression EEG from all four healthy EEG types and 93% true positive classification when separating quiet sleep from the other types. The other three sleep stages could not be classified. When the pathological burst suppression pattern was detected, the analysis was taken one step further and the signal was segmented into burst and suppression, allowing clinically relevant parameters such as suppression length and burst suppression ratio to be calculated. The segmentation of the burst suppression EEG works well, with a probability of error around 4%.

EEG-guided transcranial magnetic stimulation reveals rapid shifts in motor cortical excitability during the human sleep slow oscillation

DEFF Research Database (Denmark)

Bergmann, Til O; Mölle, Matthias; Schmidt, Marlit A

2012-01-01

Evoked cortical responses do not follow a rigid input–output function but are dynamically shaped by intrinsic neural properties at the time of stimulation. Recent research has emphasized the role of oscillatory activity in determining cortical excitability. Here we employed EEG-guided transcranial......, closely resembling a spontaneous SO. However, both MEPs and TEPs were consistently larger when evoked during SO up-states than during down-states, and ampliudes within each SO state depended on the actual EEG potential at the time and site of stimulation. These results provide first-time evidence...... magnetic stimulation (TMS) during non-rapid eye movement sleep to examine whether the spontaneous

Cordance derived from REM sleep EEG as a biomarker for treatment response in depression--a naturalistic study after antidepressant medication

NARCIS (Netherlands)

Adamczyk, M.; Gazea, M.; Wollweber, B.; Holsboer, F.; Dresler, M.; Steiger, A.; Pawlowski, M.

2015-01-01

OBJECTIVE: To evaluate whether prefrontal cordance in theta frequency band derived from REM sleep EEG after the first week of antidepressant medication could characterize the treatment response after 4 weeks of therapy in depressed patients. METHOD: 20 in-patients (15 females, 5 males) with a

Ketamine increases the frequency of electroencephalographic bicoherence peak on the alpha spindle area induced with propofol.

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Hayashi, K; Tsuda, N; Sawa, T; Hagihira, S

2007-09-01

The reticular and thalamocortical system is known to play a prominent role in spindle wave activity, and the spindle wave is related to the sedative effects of anaesthetics. Recently, bispectral analysis of the EEG has been developed as a better method to indicate nonlinear regulation including the thalamocortical system linking to the cortical area. In the present study, in order to explore the interference of ketamine with the nonlinear regulation of the sub-cortical system, we examined the effect of ketamine on spindle alpha waves through the bispectral analysis. The study included 21 patients. Anaesthesia was induced and maintained using a propofol-TCI system (target-controlled infusion, with target concentration 3.5 microg ml(-1)). An A-2000 BIS monitor was used and the raw EEG signals were collected via an RS232 interface on a personal computer. Bicoherence, the normalized bispectrum, and power spectrum were analysed before and after i.v. administration of 1 mg kg(-1) racemic ketamine. Propofol caused alpha peaks in both power and bicoherence spectra, with average frequencies of 10.6 (SD 0.9) Hz and 10.7 (1.0) Hz, respectively. The addition of ketamine significantly shifted each peak to frequencies of 14.4 (1.4) Hz and 13.6 (1.5) Hz, respectively [P < 0.05, mean (SD)]. Ketamine shifted the alpha peaks of bicoherence induced by propofol to higher frequencies. This suggests that ketamine changes the alpha spindle rhythms through the modulation of the nonlinear sub-cortical reverberating network.

Voluntary Sleep Loss in Rats

Science.gov (United States)

Oonk, Marcella; Krueger, James M.; Davis, Christopher J.

2016-01-01

Study Objectives: Animal sleep deprivation (SDEP), in contrast to human SDEP, is involuntary and involves repeated exposure to aversive stimuli including the inability of the animal to control the waking stimulus. Therefore, we explored intracranial self-stimulation (ICSS), an operant behavior, as a method for voluntary SDEP in rodents. Methods: Male Sprague-Dawley rats were implanted with electroencephalography/electromyography (EEG/EMG) recording electrodes and a unilateral bipolar electrode into the lateral hypothalamus. Rats were allowed to self-stimulate, or underwent gentle handling-induced SDEP (GH-SDEP), during the first 6 h of the light phase, after which they were allowed to sleep. Other rats performed the 6 h ICSS and 1 w later were subjected to 6 h of noncontingent stimulation (NCS). During NCS the individual stimulation patterns recorded during ICSS were replayed. Results: After GH-SDEP, ICSS, or NCS, time in nonrapid eye movement (NREM) sleep and rapid eye movement (REM) sleep increased. Further, in the 24 h after SDEP, rats recovered all of the REM sleep lost during SDEP, but only 75% to 80% of the NREM sleep lost, regardless of the SDEP method. The magnitude of EEG slow wave responses occurring during NREM sleep also increased after SDEP treatments. However, NREM sleep EEG slow wave activity (SWA) responses were attenuated following ICSS, compared to GH-SDEP and NCS. Conclusions: We conclude that ICSS and NCS can be used to sleep deprive rats. Changes in rebound NREM sleep EEG SWA occurring after ICSS, NCS, and GH-SDEP suggest that nonspecific effects of the SDEP procedure differentially affect recovery sleep phenotypes. Citation: Oonk M, Krueger JM, Davis CJ. Voluntary sleep loss in rats. SLEEP 2016;39(7):1467–1479. PMID:27166236

Cerebral blood flow during paroxysmal EEG activation induced by sleep in patients with complex partial seizures

International Nuclear Information System (INIS)

Gozukirmizi, E.; Meyer, J.S.; Okabe, T.; Amano, T.; Mortel, K.; Karacan, I.

1982-01-01

Cerebral blood flow (CBF) measurements were combined with sleep polysomnography in nine patients with complex partial seizures. Two methods were used: the 133Xe method for measuring regional (rCBF) and the stable xenon CT method for local (LCBF). Compared to nonepileptic subjects, who show diffuse CBF decreases during stages I-II, non-REM sleep onset, patients with complex partial seizures show statistically significant increases in CBF which are maximal in regions where the EEG focus is localized and are predominantly seen in one temporal region but are also propagated to other cerebral areas. Both CBF methods gave comparable results, but greater statistical significance was achieved by stable xenon CT methodology. CBF increases are more diffuse than predicted by EEG paroxysmal activity recorded from scalp electrodes. An advantage of the 133Xe inhalation method was achievement of reliable data despite movement of the head. This was attributed to the use of a helmet which maintained the probes approximated to the scalp. Disadvantages were poor resolution (7 cm3) and two-dimensional information. The advantage of stable xenon CT method is excellent resolution (80 mm3) in three dimensions, but a disadvantage is that movement of the head in patients with seizure disorders may limit satisfactory measurements

Pharmaco-EEG: A Study of Individualized Medicine in Clinical Practice.

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Swatzyna, Ronald J; Kozlowski, Gerald P; Tarnow, Jay D

2015-07-01

Pharmaco-electroencephalography (Pharmaco-EEG) studies using clinical EEG and quantitative EEG (qEEG) technologies have existed for more than 4 decades. This is a promising area that could improve psychotropic intervention using neurological data. One of the objectives in our clinical practice has been to collect EEG and quantitative EEG (qEEG) data. In the past 5 years, we have identified a subset of refractory cases (n = 386) found to contain commonalities of a small number of electrophysiological features in the following diagnostic categories: mood, anxiety, autistic spectrum, and attention deficit disorders, Four abnormalities were noted in the majority of medication failure cases and these abnormalities did not appear to significantly align with their diagnoses. Those were the following: encephalopathy, focal slowing, beta spindles, and transient discharges. To analyze the relationship noted, they were tested for association with the assigned diagnoses. Fisher's exact test and binary logistics regression found very little (6%) association between particular EEG/qEEG abnormalities and diagnoses. Findings from studies of this type suggest that EEG/qEEG provides individualized understanding of pharmacotherapy failures and has the potential to improve medication selection. © EEG and Clinical Neuroscience Society (ECNS) 2014.

Optimizing detection and analysis of slow waves in sleep EEG.

Science.gov (United States)

Mensen, Armand; Riedner, Brady; Tononi, Giulio

2016-12-01

Analysis of individual slow waves in EEG recording during sleep provides both greater sensitivity and specificity compared to spectral power measures. However, parameters for detection and analysis have not been widely explored and validated. We present a new, open-source, Matlab based, toolbox for the automatic detection and analysis of slow waves; with adjustable parameter settings, as well as manual correction and exploration of the results using a multi-faceted visualization tool. We explore a large search space of parameter settings for slow wave detection and measure their effects on a selection of outcome parameters. Every choice of parameter setting had some effect on at least one outcome parameter. In general, the largest effect sizes were found when choosing the EEG reference, type of canonical waveform, and amplitude thresholding. Previously published methods accurately detect large, global waves but are conservative and miss the detection of smaller amplitude, local slow waves. The toolbox has additional benefits in terms of speed, user-interface, and visualization options to compare and contrast slow waves. The exploration of parameter settings in the toolbox highlights the importance of careful selection of detection METHODS: The sensitivity and specificity of the automated detection can be improved by manually adding or deleting entire waves and or specific channels using the toolbox visualization functions. The toolbox standardizes the detection procedure, sets the stage for reliable results and comparisons and is easy to use without previous programming experience. Copyright © 2016 Elsevier B.V. All rights reserved.

Night sleep in patients with vegetative state.

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Pavlov, Yuri G; Gais, Steffen; Müller, Friedemann; Schönauer, Monika; Schäpers, Barbara; Born, Jan; Kotchoubey, Boris

2017-10-01

Polysomnographic recording of night sleep was carried out in 15 patients with the diagnosis vegetative state (syn. unresponsive wakefulness syndrome). Sleep scoring was performed by three raters, and confirmed by means of a spectral power analysis of the electroencephalogram, electrooculogram and electromyogram. All patients but one exhibited at least some signs of sleep. In particular, sleep stage N1 was found in 13 patients, N2 in 14 patients, N3 in nine patients, and rapid eye movement sleep in 10 patients. Three patients exhibited all phenomena characteristic for normal sleep, including spindles and rapid eye movements. However, in all but one patient, sleep patterns were severely disturbed as compared with normative data. All patients had frequent and long periods of wakefulness during the night. In some apparent rapid eye movement sleep episodes, no eye movements were recorded. Sleep spindles were detected in five patients only, and their density was very low. We conclude that the majority of vegetative state patients retain some important circadian changes. Further studies are necessary to disentangle multiple factors potentially affecting sleep pattern of vegetative state patients. © 2017 European Sleep Research Society.

Juvenile myoclonic epilepsy: clinical and EEG features

DEFF Research Database (Denmark)

Pedersen, S B; Petersen, K A

1998-01-01

We aimed to characterize the clinical profile and EEG features of 43 patients with juvenile myoclonic epilepsy. In a retrospective design we studied the records of, and re-interviewed, 43 patients diagnosed with JME from the epilepsy clinic data base. Furthermore, available EEGs were re...... were sleep deprivation (84%), stress (70%), and alcohol consumption (51%). EEG findings included rapid spike-wave and polyspike-wave....

Juvenile myoclonic epilepsy: clinical and EEG features

DEFF Research Database (Denmark)

Pedersen, S B; Petersen, K A

1998-01-01

We aimed to characterize the clinical profile and EEG features of 43 patients with juvenile myoclonic epilepsy. In a retrospective design we studied the records of, and re-interviewed, 43 patients diagnosed with JME from the epilepsy clinic data base. Furthermore, available EEGs were re-evaluated...... were sleep deprivation (84%), stress (70%), and alcohol consumption (51%). EEG findings included rapid spike-wave and polyspike-wave....

The pacemaker role of thalamic reticular nucleus in controlling spike-wave discharges and spindles.

Science.gov (United States)

Fan, Denggui; Liao, Fucheng; Wang, Qingyun

2017-07-01

Absence epilepsy, characterized by 2-4 Hz spike-wave discharges (SWDs), can be caused by pathological interactions within the thalamocortical system. Cortical spindling oscillations are also demonstrated to involve the oscillatory thalamocortical rhythms generated by the synaptic circuitry of the thalamus and cortex. This implies that SWDs and spindling oscillations can share the common thalamocortical mechanism. Additionally, the thalamic reticular nucleus (RE) is hypothesized to regulate the onsets and propagations of both the epileptic SWDs and sleep spindles. Based on the proposed single-compartment thalamocortical neural field model, we firstly investigate the stimulation effect of RE on the initiations, terminations, and transitions of SWDs. It is shown that the activations and deactivations of RE triggered by single-pulse stimuli can drive the cortical subsystem to behave as the experimentally observed onsets and self-abatements of SWDs, as well as the transitions from 2-spike and wave discharges (2-SWDs) to SWDs. In particular, with increasing inhibition from RE to the specific relay nucleus (TC), rich transition behaviors in cortex can be obtained through the upstream projection path, RE→TC→Cortex. Although some of the complex dynamical patterns can be expected from the earlier single compartment thalamocortical model, the effect of brain network topology on the emergence of SWDs and spindles, as well as the transitions between them, has not been fully investigated. We thereby develop a spatially extended 3-compartment coupled network model with open-/closed-end connective configurations, to investigate the spatiotemporal effect of RE on the SWDs and spindles. Results show that the degrees of activations of RE 1 can induce the rich spatiotemporal evolution properties including the propagations from SWDs to spindles within different compartments and the transitions between them, through the RE 1 →TC 1 →Cortex 1 and Cortex 1 →Cortex 2 →Cortex 3

The pacemaker role of thalamic reticular nucleus in controlling spike-wave discharges and spindles

Science.gov (United States)

Fan, Denggui; Liao, Fucheng; Wang, Qingyun

2017-07-01

Absence epilepsy, characterized by 2-4 Hz spike-wave discharges (SWDs), can be caused by pathological interactions within the thalamocortical system. Cortical spindling oscillations are also demonstrated to involve the oscillatory thalamocortical rhythms generated by the synaptic circuitry of the thalamus and cortex. This implies that SWDs and spindling oscillations can share the common thalamocortical mechanism. Additionally, the thalamic reticular nucleus (RE) is hypothesized to regulate the onsets and propagations of both the epileptic SWDs and sleep spindles. Based on the proposed single-compartment thalamocortical neural field model, we firstly investigate the stimulation effect of RE on the initiations, terminations, and transitions of SWDs. It is shown that the activations and deactivations of RE triggered by single-pulse stimuli can drive the cortical subsystem to behave as the experimentally observed onsets and self-abatements of SWDs, as well as the transitions from 2-spike and wave discharges (2-SWDs) to SWDs. In particular, with increasing inhibition from RE to the specific relay nucleus (TC), rich transition behaviors in cortex can be obtained through the upstream projection path, RE → TC → Cortex . Although some of the complex dynamical patterns can be expected from the earlier single compartment thalamocortical model, the effect of brain network topology on the emergence of SWDs and spindles, as well as the transitions between them, has not been fully investigated. We thereby develop a spatially extended 3-compartment coupled network model with open-/closed-end connective configurations, to investigate the spatiotemporal effect of RE on the SWDs and spindles. Results show that the degrees of activations of RE 1 can induce the rich spatiotemporal evolution properties including the propagations from SWDs to spindles within different compartments and the transitions between them, through the RE 1 → TC 1 → Cortex 1 and Cortex 1 → Cortex 2 �

The EEG as an index of neuromodulator balance in memory and mental illness

Directory of Open Access Journals (Sweden)

Costa eVakalopoulos

2014-04-01

Full Text Available 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.

The EEG as an index of neuromodulator balance in memory and mental illness.

Science.gov (United States)

Vakalopoulos, Costa

2014-01-01

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.

Rett syndrome: EEG presentation.

Science.gov (United States)

Robertson, R; Langill, L; Wong, P K; Ho, H H

1988-11-01

Rett syndrome, a degenerative neurological disorder of girls, has a classical presentation and typical EEG findings. The electroencephalograms (EEGs) of 7 girls whose records have been followed from the onset of symptoms to the age of 5 or more are presented. These findings are tabulated with the Clinical Staging System of Hagberg and Witt-Engerström (1986). The records show a progressive deterioration in background rhythms in waking and sleep. The abnormalities of the background activity may only become evident at 4-5 years of age or during stage 2--the Rapid Destructive Stage. The marked contrast between waking and sleep background may not occur until stage 3--the Pseudostationary Stage. In essence EEG changes appear to lag behind clinical symptomatology by 1-3 years. An unexpected, but frequent, abnormality was central spikes seen in 5 of 7 girls. They appeared to be age related and could be evoked by tactile stimulation in 2 patients. We hypothesize that the prominent 'hand washing' mannerism may be self-stimulating and related to the appearance of central spike discharges.

Effects of three hypnotics on the sleep-wakefulness cycle in sleep-disturbed rats.

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Shinomiya, Kazuaki; Shigemoto, Yuki; Omichi, Junji; Utsu, Yoshiaki; Mio, Mitsunobu; Kamei, Chiaki

2004-04-01

New sleep disturbance model in rats is useful for estimating the characteristics of some hypnotics. The present study was undertaken to investigate the utility of a sleep disturbance model by placing rats on a grid suspended over water using three kinds of hypnotics, that is, short-acting benzodiazepine (triazolam), intermediate-acting benzodiazepine (flunitrazepam) and long-acting barbiturate (phenobarbital). Electrodes for measurement of EEG and EMG were implanted into the frontal cortex and the dorsal neck muscle of rats. EEG and EMG were recorded with an electroencephalogram. SleepSign ver.2.0 was used for EEG and EMG analysis. Total times of wakefulness, non-REM and REM sleep were measured from 0900 to 1500 hours. In rats placed on the grid suspended over water up to 1 cm under the grid surface, not only triazolam but also flunitrazepam and phenobarbital caused a shortening of sleep latency. Both flunitrazepam and phenobarbital were effective in increasing of total non-REM sleep time in rats placed on sawdust or the grid, and the effects of both drugs in rats placed on the grid were larger than those in rats placed on sawdust. Measurement of the hourly non-REM sleep time was useful for investigating the peak time and duration of effect of the three hypnotics. Phenobarbital showed a decrease in total REM sleep time in rats placed on the grid, although both triazolam and flunitrazepam were without effect. The present insomnia model can be used as a sleep disturbance model for testing not only the sleep-inducing effects but also the sleep-maintaining effects including non-REM sleep and REM sleep of hypnotics.

Early and Later Life Stress Alter Brain Activity and Sleep in Rats

Science.gov (United States)

Mrdalj, Jelena; Pallesen, Ståle; Milde, Anne Marita; Jellestad, Finn Konow; Murison, Robert; Ursin, Reidun; Bjorvatn, Bjørn; Grønli, Janne

2013-01-01

Exposure to early life stress may profoundly influence the developing brain in lasting ways. Neuropsychiatric disorders associated with early life adversity may involve neural changes reflected in EEG power as a measure of brain activity and disturbed sleep. The main aim of the present study was for the first time to characterize possible changes in adult EEG power after postnatal maternal separation in rats. Furthermore, in the same animals, we investigated how EEG power and sleep architecture were affected after exposure to a chronic mild stress protocol. During postnatal day 2–14 male rats were exposed to either long maternal separation (180 min) or brief maternal separation (10 min). Long maternally separated offspring showed a sleep-wake nonspecific reduction in adult EEG power at the frontal EEG derivation compared to the brief maternally separated group. The quality of slow wave sleep differed as the long maternally separated group showed lower delta power in the frontal-frontal EEG and a slower reduction of the sleep pressure. Exposure to chronic mild stress led to a lower EEG power in both groups. Chronic exposure to mild stressors affected sleep differently in the two groups of maternal separation. Long maternally separated offspring showed more total sleep time, more episodes of rapid eye movement sleep and higher percentage of non-rapid eye movement episodes ending in rapid eye movement sleep compared to brief maternal separation. Chronic stress affected similarly other sleep parameters and flattened the sleep homeostasis curves in all offspring. The results confirm that early environmental conditions modulate the brain functioning in a long-lasting way. PMID:23922857

The scoring of arousal in sleep: reliability, validity, and alternatives.

Science.gov (United States)

Bonnet, Michael H; Doghramji, Karl; Roehrs, Timothy; Stepanski, Edward J; Sheldon, Stephen H; Walters, Arthur S; Wise, Merrill; Chesson, Andrew L

2007-03-15

The reliability and validity of EEG arousals and other types of arousal are reviewed. Brief arousals during sleep had been observed for many years, but the evolution of sleep medicine in the 1980s directed new attention to these events. Early studies at that time in animals and humans linked brief EEG arousals and associated fragmentation of sleep to daytime sleepiness and degraded performance. Increasing interest in scoring of EEG arousals led the ASDA to publish a scoring manual in 1992. The current review summarizes numerous studies that have examined scoring reliability for these EEG arousals. Validity of EEG arousals was explored by review of studies that empirically varied arousals and found deficits similar to those found after total sleep deprivation depending upon the rate and extent of sleep fragmentation. Additional data from patients with clinical sleep disorders prior to and after effective treatment has also shown a continuing relationship between reduction in pathology-related arousals and improved sleep and daytime function. Finally, many suggestions have been made to refine arousal scoring to include additional elements (e.g., CAP), change the time frame, or focus on other physiological responses such as heart rate or blood pressure changes. Evidence to support the reliability and validity of these measures is presented. It was concluded that the scoring of EEG arousals has added much to our understanding of the sleep process but that significant work on the neurophysiology of arousal needs to be done. Additional refinement of arousal scoring will provide improved insight into sleep pathology and recovery.

Slow wave and REM sleep deprivation effects on explicit and implicit memory during sleep.

Science.gov (United States)

Casey, Sarah J; Solomons, Luke C; Steier, Joerg; Kabra, Neeraj; Burnside, Anna; Pengo, Martino F; Moxham, John; Goldstein, Laura H; Kopelman, Michael D

2016-11-01

It has been debated whether different stages in the human sleep cycle preferentially mediate the consolidation of explicit and implicit memories, or whether all of the stages in succession are necessary for optimal consolidation. Here we investigated whether the selective deprivation of slow wave sleep (SWS) or rapid eye movement (REM) sleep over an entire night would have a specific effect on consolidation in explicit and implicit memory tasks. Participants completed a set of explicit and implicit memory tasks at night, prior to sleep. They had 1 control night of undisturbed sleep and 2 experimental nights, during which either SWS or REM sleep was selectively deprived across the entire night (sleep conditions counterbalanced across participants). Polysomnography recordings quantified precisely the amount of SWS and REM sleep that occurred during each of the sleep conditions, and spindle counts were recorded. In the morning, participants completed the experimental tasks in the same sequence as the night before. SWS deprivation disrupted the consolidation of explicit memories for visuospatial information (ηp2 = .23), and both SWS (ηp2 = .53) and REM sleep (ηp2 = .52) deprivation adversely affected explicit verbal recall. Neither SWS nor REM sleep deprivation affected aspects of short-term or working memory, and did not affect measures of verbal implicit memory. Spindle counts did not correlate significantly with memory performance. These findings demonstrate the importance of measuring the sleep cycles throughout the entire night, and the contribution of both SWS and REM sleep to memory consolidation. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Topography of Slow Sigma Power during Sleep is Associated with Processing Speed in Preschool Children

Directory of Open Access Journals (Sweden)

Margaret R. Doucette

2015-11-01

Full Text Available Cognitive development is influenced by maturational changes in processing speed, a construct reflecting the rapidity of executing cognitive operations. Although cognitive ability and processing speed are linked to spindles and sigma power in the sleep electroencephalogram (EEG, little is known about such associations in early childhood, a time of major neuronal refinement. We calculated EEG power for slow (10–13 Hz and fast (13.25–17 Hz sigma power from all-night high-density electroencephalography (EEG in a cross-sectional sample of healthy preschool children (n = 10, 4.3 ± 1.0 years. Processing speed was assessed as simple reaction time. On average, reaction time was 1409 ± 251 ms; slow sigma power was 4.0 ± 1.5 μV2; and fast sigma power was 0.9 ± 0.2 μV2. Both slow and fast sigma power predominated over central areas. Only slow sigma power was correlated with processing speed in a large parietal electrode cluster (p < 0.05, r ranging from −0.6 to −0.8, such that greater power predicted faster reaction time. Our findings indicate regional correlates between sigma power and processing speed that are specific to early childhood and provide novel insights into the neurobiological features of the EEG that may underlie developing cognitive abilities.

EEG in children, in the laboratory or at the patient's bedside.

Science.gov (United States)

Kaminska, A; Cheliout-Heraut, F; Eisermann, M; Touzery de Villepin, A; Lamblin, M D

2015-03-01

In pediatrics, EEG recordings are performed on patients from the neonatal period up to young adults. This means adapting techniques to many different conditions, concerning not only the patient's age, the need for asepsis and the patient's behavior, but also the environment (e.g. in the laboratory, at the patient's bedside, or in the neonatal intensive care unit [NICU]). Technical requirements depend on age, indication and the type of examination; in infancy, there should be a minimum of 12 EEG electrodes, ECG and respiration recording. In epileptology, surface EMG is also necessary to characterize the type of seizures and refine the diagnosis of epilepsy syndrome, on which physicians will base their treatment choice. The role of the EEG technician is essential because the quality of the recording, its analysis and conclusion will depend on the quality of the technical set-up and the interaction with the child. Sleep is a systematic part of the study up to the age of 5 years for several reasons: sleep EEG yields information on brain maturation; the EEG tracing during wakefulness can contain too many artefacts; and some grapho-elements, key to the diagnosis, only appear during sleep. The time of the examination must be chosen according to the child's usual nap times, possibly after sleep deprivation. Grapho-elements and spatio-temporal organization of the EEG vary with age, and normal variants and unusual aspects are quite wide for any given age; this is why a physician experienced in pediatric EEG should perform the interpretation. This chapter concerns EEG performed in infants, children and adolescents, its technical aspects according to age and indications (general pediatrics, emergency, epilepsy). Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Differential modulation of global and local neural oscillations in REM sleep by homeostatic sleep regulation.

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Kim, Bowon; Kocsis, Bernat; Hwang, Eunjin; Kim, Youngsoo; Strecker, Robert E; McCarley, Robert W; Choi, Jee Hyun

2017-02-28

Homeostatic rebound in rapid eye movement (REM) sleep normally occurs after acute sleep deprivation, but REM sleep rebound settles on a persistently elevated level despite continued accumulation of REM sleep debt during chronic sleep restriction (CSR). Using high-density EEG in mice, we studied how this pattern of global regulation is implemented in cortical regions with different functions and network architectures. We found that across all areas, slow oscillations repeated the behavioral pattern of persistent enhancement during CSR, whereas high-frequency oscillations showed progressive increases. This pattern followed a common rule despite marked topographic differences. The findings suggest that REM sleep slow oscillations may translate top-down homeostatic control to widely separated brain regions whereas fast oscillations synchronizing local neuronal ensembles escape this global command. These patterns of EEG oscillation changes are interpreted to reconcile two prevailing theories of the function of sleep, synaptic homeostasis and sleep dependent memory consolidation.

fMRI Artefact Rejection and Sleep Scoring Toolbox

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Yves Leclercq

2011-01-01

Full Text Available We started writing the “fMRI artefact rejection and sleep scoring toolbox”, or “FAST”, to process our sleep EEG-fMRI data, that is, the simultaneous recording of electroencephalographic and functional magnetic resonance imaging data acquired while a subject is asleep. FAST tackles three crucial issues typical of this kind of data: (1 data manipulation (viewing, comparing, chunking, etc. of long continuous M/EEG recordings, (2 rejection of the fMRI-induced artefact in the EEG signal, and (3 manual sleep-scoring of the M/EEG recording. Currently, the toolbox can efficiently deal with these issues via a GUI, SPM8 batching system or hand-written script. The tools developed are, of course, also useful for other EEG applications, for example, involving simultaneous EEG-fMRI acquisition, continuous EEG eye-balling, and manipulation. Even though the toolbox was originally devised for EEG data, it will also gracefully handle MEG data without any problem. “FAST” is developed in Matlab as an add-on toolbox for SPM8 and, therefore, internally uses its SPM8-meeg data format. “FAST” is available for free, under the GNU-GPL.

Effects of CPAP-therapy on brain electrical activity in obstructive sleep apneic patients: a combined EEG study using LORETA and Omega complexity : reversible alterations of brain activity in OSAS.

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Toth, Marton; Faludi, Bela; Kondakor, Istvan

2012-10-01

Effects of initiation of continuous positive airway pressure (CPAP) therapy on EEG background activity were investigated in patients with obstructive sleep apnea syndrome (OSAS, N = 25) to test possible reversibility of alterations of brain electrical activity caused by chronic hypoxia. Normal control group (N = 14) was also examined. Two EEG examinations were done in each groups: at night and in the next morning. Global and regional (left vs. right, anterior vs. posterior) measures of spatial complexity (Omega complexity) were used to characterize the degree of spatial synchrony of EEG. Low resolution electromagnetic tomography (LORETA) was used to localize generators of EEG activity in separate frequency bands. Before CPAP-treatment, a significantly lower Omega complexity was found globally and over the right hemisphere. Due to CPAP-treatment, these significant differences vanished. Significantly decreased Omega complexity was found in the anterior region after treatment. LORETA showed a decreased activity in all of the beta bands after therapy in the right hippocampus, premotor and temporo-parietal cortex, and bilaterally in the precuneus, paracentral and posterior cingulate cortex. No significant changes were seen in control group. Comparing controls and patients before sleep, an increased alpha2 band activity was seen bilaterally in the precuneus, paracentral and posterior cingulate cortex, while in the morning an increased beta3 band activity in the left precentral and bilateral premotor cortex and a decreased delta band activity in the right temporo-parietal cortex and insula were observed. These findings indicate that effect of sleep on EEG background activity is different in OSAS patients and normal controls. In OSAS patients, significant changes lead to a more normal EEG after a night under CPAP-treatment. Compensatory alterations of brain electrical activity in regions associated with influencing sympathetic outflow, visuospatial abilities, long

Exercise Effects on Sleep Physiology

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Sunao eUchida

2012-04-01

Full Text Available This mini-review focuses on the effects of exercise on sleep. In its early days, sleep research largely focused on central nervous system (CNS physiology using standardized tabulations of several sleep-specific landmark electroencephalogram (EEG waveforms. Though coarse, this method has enabled the observation and inspection of numerous uninterrupted sleep phenomena. Thus, research on the effects of exercise on sleep began, in the 1960’s, with a focus primarily on sleep EEG (CNS sleep changes. Those early studies found only small effects of exercise on sleep. More recent sleep research has explored not only CNS functioning, but somatic physiology as well. As physical exercise mostly affects somatic functions, endocrine and autonomic nervous system (ANS changes that occur during sleep should be affected by daytime exercise. Since endocrinological, metabolic and autonomic changes can be measured during sleep, it should be possible to assess exercise effects on somatic physiology in addition to CNS sleep quality, building from standard polysomnographic (PSG techniques. Incorporating measures of somatic physiology in the quantitative assessment of sleep could further our understanding of sleep's function as an auto-regulatory, global phenomenon.

Sleep mechanisms: Sleep deprivation and detection of changing levels of consciousness

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Dement, W. C.; Barchas, J. D.

1972-01-01

An attempt was made to obtain information relevant to assessing the need to sleep and make up for lost sleep. Physiological and behavioral parameters were used as measuring parameters. Sleep deprivation in a restricted environment, derivation of data relevant to determining sleepiness from EEG, and the development of the Sanford Sleepiness Scale were discussed.

Evaluation of an automated single-channel sleep staging algorithm

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Wang Y

2015-09-01

Full Text Available Ying Wang,1 Kenneth A Loparo,1,2 Monica R Kelly,3 Richard F Kaplan1 1General Sleep Corporation, Euclid, OH, 2Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, 3Department of Psychology, University of Arizona, Tucson, AZ, USA Background: We previously published the performance evaluation of an automated electroencephalography (EEG-based single-channel sleep–wake detection algorithm called Z-ALG used by the Zmachine® sleep monitoring system. The objective of this paper is to evaluate the performance of a new algorithm called Z-PLUS, which further differentiates sleep as detected by Z-ALG into Light Sleep, Deep Sleep, and Rapid Eye Movement (REM Sleep, against laboratory polysomnography (PSG using a consensus of expert visual scorers. Methods: Single night, in-lab PSG recordings from 99 subjects (52F/47M, 18–60 years, median age 32.7 years, including both normal sleepers and those reporting a variety of sleep complaints consistent with chronic insomnia, sleep apnea, and restless leg syndrome, as well as those taking selective serotonin reuptake inhibitor/serotonin–norepinephrine reuptake inhibitor antidepressant medications, previously evaluated using Z-ALG were re-examined using Z-PLUS. EEG data collected from electrodes placed at the differential-mastoids (A1–A2 were processed by Z-ALG to determine wake and sleep, then those epochs detected as sleep were further processed by Z-PLUS to differentiate into Light Sleep, Deep Sleep, and REM. EEG data were visually scored by multiple certified polysomnographic technologists according to the Rechtschaffen and Kales criterion, and then combined using a majority-voting rule to create a PSG Consensus score file for each of the 99 subjects. Z-PLUS output was compared to the PSG Consensus score files for both epoch-by-epoch (eg, sensitivity, specificity, and kappa and sleep stage-related statistics (eg, Latency to Deep Sleep, Latency to REM

Effects of an alkaloid-rich extract from Mitragyna speciosa leaves and fluoxetine on sleep profiles, EEG spectral frequency and ethanol withdrawal symptoms in rats.

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Cheaha, Dania; Keawpradub, Niwat; Sawangjaroen, Kitja; Phukpattaranont, Pimpimol; Kumarnsit, Ekkasit

2015-10-15

Many antidepressants are effective in alleviating ethanol withdrawal symptoms. However, most of them suppress rapid eye movement (REM) sleep. Thus, development of antidepressants without undesirable side effects would be preferable. Previously, crude alkaloid extract from Mitragyna speciosa (MS) Korth was found to produce antidepressant activities. It was hypothesized that the alkaloid extract from MS may attenuate ethanol withdrawal without REM sleep disturbance. Adult male Wistar rats implanted with electrodes over the frontal and parietal cortices were used for two separated studies. For an acute study, 10 mg/kg fluoxetine or 60 mg/kg alkaloid extract from MS were administered intragastrically. Electroencephalographic (EEG) signals were recorded for 3 h to examine sleep profiles and EEG fingerprints. Another set of animal was used for an ethanol withdrawal study. They were rendered dependent on ethanol via a modified liquid diet (MLD) containing ethanol ad libitum for 28 days. On day 29, fluoxetine (10 mg/kg) or alkaloid extract from MS (60 mg/kg) were administered 15 min before the ethanol-containing MLD was replaced with an isocaloric ethanol-free MLD to induced ethanol withdrawal symptoms. The sleep analysis revealed that alkaloid extract from MS did not change any REM parameters which included average duration of each REM episode, total REM time, number of REM episode and REM latency whereas fluoxetine significantly suppressed all REM parameters and delayed REM latency. However, power spectral analysis revealed similar fingerprints for fluoxetine and alkaloid extract from MS characterized by decreasing powers in the slow frequency range in frontal and parietal cortical EEG. Neither treatment affected spontaneous motor activity. Finally, both alkaloid extract from MS and fluoxetine were found to significantly attenuate ethanol withdrawal-induced hyperexcitability (increases gamma activity) in both cortices and to reduce locomotor activity. The present study

REM sleep deprivation during 5 hours leads to an immediate REM sleep rebound and to suppression of non-REM sleep intensity

NARCIS (Netherlands)

Beersma, D.G.M.; Dijk, D.J.; Blok, Guus; Everhardus, I.

Nine healthy male subjects were deprived of REM sleep during the first 5 h after sleep onset. Afterwards recovery sleep was undisturbed. During the deprivation period the non-REM EEG power spectrum was reduced when compared to baseline for the frequencies up to 7 Hz, despite the fact that non-REM

Auditory feedback blocks memory benefits of cueing during sleep.

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Schreiner, Thomas; Lehmann, Mick; Rasch, Björn

2015-10-28

It is now widely accepted that re-exposure to memory cues during sleep reactivates memories and can improve later recall. However, the underlying mechanisms are still unknown. As reactivation during wakefulness renders memories sensitive to updating, it remains an intriguing question whether reactivated memories during sleep also become susceptible to incorporating further information after the cue. Here we show that the memory benefits of cueing Dutch vocabulary during sleep are in fact completely blocked when memory cues are directly followed by either correct or conflicting auditory feedback, or a pure tone. In addition, immediate (but not delayed) auditory stimulation abolishes the characteristic increases in oscillatory theta and spindle activity typically associated with successful reactivation during sleep as revealed by high-density electroencephalography. We conclude that plastic processes associated with theta and spindle oscillations occurring during a sensitive period immediately after the cue are necessary for stabilizing reactivated memory traces during sleep.

Mutual information measures applied to EEG signals for sleepiness characterization

OpenAIRE

Melia, Umberto Sergio Pio; Guaita, Marc; Vallverdú Ferrer, Montserrat; Embid, Cristina; Vilaseca, I; Salamero, Manuel; Santamaria, Joan

2015-01-01

Excessive daytime sleepiness (EDS) is one of the main symptoms of several sleep related disorders with a great impact on the patient lives. While many studies have been carried out in order to assess daytime sleepiness, the automatic EDS detection still remains an open problem. In this work, a novel approach to this issue based on non-linear dynamical analysis of EEG signal was proposed. Multichannel EEG signals were recorded during five maintenance of wakefulness (MWT) and multiple sleep lat...

Functional ADA polymorphism increases sleep depth and reduces vigilant attention in humans.

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Bachmann, Valérie; Klaus, Federica; Bodenmann, Sereina; Schäfer, Nikolaus; Brugger, Peter; Huber, Susanne; Berger, Wolfgang; Landolt, Hans-Peter

2012-04-01

Homeostatically regulated slow-wave oscillations in non-rapid eye movement (REM) sleep may reflect synaptic changes across the sleep-wake continuum and the restorative function of sleep. The nonsynonymous c.22G>A polymorphism (rs73598374) of adenosine deaminase (ADA) reduces the conversion of adenosine to inosine and predicts baseline differences in sleep slow-wave oscillations. We hypothesized that this polymorphism affects cognitive functions, and investigated whether it modulates electroencephalogram (EEG), behavioral, subjective, and biochemical responses to sleep deprivation. Attention, learning, memory, and executive functioning were quantified in healthy adults. Right-handed carriers of the variant allele (G/A genotype, n = 29) performed worse on the d2 attention task than G/G homozygotes (n = 191). To test whether this difference reflects elevated homeostatic sleep pressure, sleep and sleep EEG before and after sleep deprivation were studied in 2 prospectively matched groups of G/A and G/G genotype subjects. Deep sleep and EEG 0.75- to 1.5-Hz oscillations in non-REM sleep were significantly higher in G/A than in G/G genotype. Moreover, attention and vigor were reduced, whereas waking EEG alpha activity (8.5-12 Hz), sleepiness, fatigue, and α-amylase in saliva were enhanced. These convergent data demonstrate that genetic reduction of ADA activity elevates sleep pressure and plays a key role in sleep and waking quality in humans.

Mutual information measures applied to EEG signals for sleepiness characterization.

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Melia, Umberto; Guaita, Marc; Vallverdú, Montserrat; Embid, Cristina; Vilaseca, Isabel; Salamero, Manel; Santamaria, Joan

2015-03-01

Excessive daytime sleepiness (EDS) is one of the main symptoms of several sleep related disorders with a great impact on the patient lives. While many studies have been carried out in order to assess daytime sleepiness, the automatic EDS detection still remains an open problem. In this work, a novel approach to this issue based on non-linear dynamical analysis of EEG signal was proposed. Multichannel EEG signals were recorded during five maintenance of wakefulness (MWT) and multiple sleep latency (MSLT) tests alternated throughout the day from patients suffering from sleep disordered breathing. A group of 20 patients with excessive daytime sleepiness (EDS) was compared with a group of 20 patients without daytime sleepiness (WDS), by analyzing 60-s EEG windows in waking state. Measures obtained from cross-mutual information function (CMIF) and auto-mutual-information function (AMIF) were calculated in the EEG. These functions permitted a quantification of the complexity properties of the EEG signal and the non-linear couplings between different zones of the scalp. Statistical differences between EDS and WDS groups were found in β band during MSLT events (p-value CMIF measures yielded sensitivity and specificity above 80% and AUC of ROC above 0.85 in classifying EDS and WDS patients. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

The Neuronal Transition Probability (NTP) Model for the Dynamic Progression of Non-REM Sleep EEG: The Role of the Suprachiasmatic Nucleus

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Merica, H

2011-01-01

Little attention has gone into linking to its neuronal substrates the dynamic structure of non-rapid-eye-movement (NREM) sleep, defined as the pattern of time-course power in all frequency bands across an entire episode. Using the spectral power time-courses in the sleep electroencephalogram (EEG), we showed in the typical first episode, several moves towards-and-away from deep sleep, each having an identical pattern linking the major frequency bands beta, sigma and delta. The neuronal transition probability model (NTP) - in fitting the data well - successfully explained the pattern as resulting from stochastic transitions of the firing-rates of the thalamically-projecting brainstem-activating neurons, alternating between two steady dynamic-states (towards-and-away from deep sleep) each initiated by a so-far unidentified flip-flop. The aims here are to identify this flip-flop and to demonstrate that the model fits well all NREM episodes, not just the first. Using published data on suprachiasmatic nucleus (SCN...

Sleep disturbances in IDDM patients with nocturnal hypoglycemia

DEFF Research Database (Denmark)

Bendtson, I; Gade, J; Thomsen, C E

1992-01-01

Eight insulin-dependent diabetic patients were studied to evaluate sleep patterns during normoglycemia and spontaneous and insulin-induced hypoglycemia. Two channels of electroencephalogram (EEG), electromyogram and actooculogram were recorded. The signals were analyzed off-line, using...... a polygraphic sleep analysis system. The scoring was mainly based on the color density spectral array of the EEG. Blood glucose and growth hormone were measured serially. Asymptomatic, spontaneous nocturnal hypoglycemia occurred in 38% of the nights. Conventional sleep analysis showed a tendency toward...

Sleep-dependent facilitation of episodic memory details.

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van der Helm, Els; Gujar, Ninad; Nishida, Masaki; Walker, Matthew P

2011-01-01

While a role for sleep in declarative memory processing is established, the qualitative nature of this consolidation benefit, and the physiological mechanisms mediating it, remain debated. Here, we investigate the impact of sleep physiology on characteristics of episodic memory using an item- (memory elements) and context- (contextual details associated with those elements) learning paradigm; the latter being especially dependent on the hippocampus. Following back-to-back encoding of two word lists, each associated with a different context, participants were assigned to either a Nap-group, who obtained a 120-min nap, or a No Nap-group. Six hours post-encoding, participants performed a recognition test involving item-memory and context-memory judgments. In contrast to item-memory, which demonstrated no between-group differences, a significant benefit in context-memory developed in the Nap-group, the extent of which correlated both with the amount of stage-2 NREM sleep and frontal fast sleep-spindles. Furthermore, a difference was observed on the basis of word-list order, with the sleep benefit and associated physiological correlations being selective for the second word-list, learned last (most proximal to sleep). These findings suggest that sleep may preferentially benefit contextual (hippocampal-dependent) aspects of memory, supported by sleep-spindle oscillations, and that the temporal order of initial learning differentially determines subsequent offline consolidation.

Sleep-dependent facilitation of episodic memory details.

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Els van der Helm

Full Text Available While a role for sleep in declarative memory processing is established, the qualitative nature of this consolidation benefit, and the physiological mechanisms mediating it, remain debated. Here, we investigate the impact of sleep physiology on characteristics of episodic memory using an item- (memory elements and context- (contextual details associated with those elements learning paradigm; the latter being especially dependent on the hippocampus. Following back-to-back encoding of two word lists, each associated with a different context, participants were assigned to either a Nap-group, who obtained a 120-min nap, or a No Nap-group. Six hours post-encoding, participants performed a recognition test involving item-memory and context-memory judgments. In contrast to item-memory, which demonstrated no between-group differences, a significant benefit in context-memory developed in the Nap-group, the extent of which correlated both with the amount of stage-2 NREM sleep and frontal fast sleep-spindles. Furthermore, a difference was observed on the basis of word-list order, with the sleep benefit and associated physiological correlations being selective for the second word-list, learned last (most proximal to sleep. These findings suggest that sleep may preferentially benefit contextual (hippocampal-dependent aspects of memory, supported by sleep-spindle oscillations, and that the temporal order of initial learning differentially determines subsequent offline consolidation.

Time delay between cardiac and brain activity during sleep transitions

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Long, Xi; Arends, Johan B.; Aarts, Ronald M.; Haakma, Reinder; Fonseca, Pedro; Rolink, Jérôme

2015-04-01

Human sleep consists of wake, rapid-eye-movement (REM) sleep, and non-REM (NREM) sleep that includes light and deep sleep stages. This work investigated the time delay between changes of cardiac and brain activity for sleep transitions. Here, the brain activity was quantified by electroencephalographic (EEG) mean frequency and the cardiac parameters included heart rate, standard deviation of heartbeat intervals, and their low- and high-frequency spectral powers. Using a cross-correlation analysis, we found that the cardiac variations during wake-sleep and NREM sleep transitions preceded the EEG changes by 1-3 min but this was not the case for REM sleep transitions. These important findings can be further used to predict the onset and ending of some sleep stages in an early manner.

Automatic sleep scoring: a search for an optimal combination of measures.

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Krakovská, Anna; Mezeiová, Kristína

2011-09-01

The objective of this study is to find the best set of characteristics of polysomnographic signals for the automatic classification of sleep stages. A selection was made from 74 measures, including linear spectral measures, interdependency measures, and nonlinear measures of complexity that were computed for the all-night polysomnographic recordings of 20 healthy subjects. The adopted multidimensional analysis involved quadratic discriminant analysis, forward selection procedure, and selection by the best subset procedure. Two situations were considered: the use of four polysomnographic signals (EEG, EMG, EOG, and ECG) and the use of the EEG alone. For the given database, the best automatic sleep classifier achieved approximately an 81% agreement with the hypnograms of experts. The classifier was based on the next 14 features of polysomnographic signals: the ratio of powers in the beta and delta frequency range (EEG, channel C3), the fractal exponent (EMG), the variance (EOG), the absolute power in the sigma 1 band (EEG, C3), the relative power in the delta 2 band (EEG, O2), theta/gamma (EEG, C3), theta/alpha (EEG, O1), sigma/gamma (EEG, C4), the coherence in the delta 1 band (EEG, O1-O2), the entropy (EMG), the absolute theta 2 (EEG, Fp1), theta/alpha (EEG, Fp1), the sigma 2 coherence (EEG, O1-C3), and the zero-crossing rate (ECG); however, even with only four features, we could perform sleep scoring with a 74% accuracy, which is comparable to the inter-rater agreement between two independent specialists. We have shown that 4-14 carefully selected polysomnographic features were sufficient for successful sleep scoring. The efficiency of the corresponding automatic classifiers was verified and conclusively demonstrated on all-night recordings from healthy adults. Copyright © 2011 Elsevier B.V. All rights reserved.

The association of mothers' and fathers' insomnia symptoms with school-aged children's sleep assessed by parent report and in-home sleep-electroencephalography.

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Urfer-Maurer, Natalie; Weidmann, Rebekka; Brand, Serge; Holsboer-Trachsler, Edith; Grob, Alexander; Weber, Peter; Lemola, Sakari

2017-10-01

Sleep plays an essential role for children's well-being. Because children's sleep is associated with parental sleep patterns, it must be considered in the family context. As a first aim of the present study, we test whether parental insomnia symptoms are related to children's in-home sleep-electroencephalography (EEG). Second, we examine the association between parental insomnia symptoms and maternal and paternal perception of children's sleep using actor-partner interdependence models. A total of 191 healthy children enrolled in public school and aged 7-12 years took part in the study. Ninety-six were formerly very preterm born children. Children underwent in-home sleep-EEG, and parents reported children's sleep-related behavior by using the German version of the Children's Sleep Habits Questionnaire. Further, parents completed the Insomnia Severity Index to report their own insomnia symptoms. Maternal but not paternal insomnia symptoms were related to less children's EEG-derived total sleep time, more stage 2 sleep, less slow wave sleep, later sleep onset time, and later awakening time. Mothers' and fathers' own insomnia symptoms were related to their reports of children's bedtime resistance, sleep duration, sleep anxiety, night wakings, and/or daytime sleepiness. Moreover, maternal insomnia symptoms were associated with paternal reports of children's bedtime resistance, sleep anxiety, and sleep-disordered breathing. The associations between parental insomnia symptoms and parents' perception of children's sleep could not be explained by children's objectively measured sleep. Mothers' insomnia symptoms and children's objective sleep patterns are associated. Moreover, the parents' own insomnia symptoms might bias their perception of children's sleep-related behavior problems. Copyright © 2017 Elsevier B.V. All rights reserved.

Human ASPM participates in spindle organisation, spindle orientation and cytokinesis

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Woods C Geoffrey

2010-11-01

Full Text Available Abstract Background Mutations in the Abnormal Spindle Microcephaly related gene (ASPM are the commonest cause of autosomal recessive primary microcephaly (MCPH a disorder characterised by a small brain and associated mental retardation. ASPM encodes a mitotic spindle pole associated protein. It is suggested that the MCPH phenotype arises from proliferation defects in neural progenitor cells (NPC. Results We show that ASPM is a microtubule minus end-associated protein that is recruited in a microtubule-dependent manner to the pericentriolar matrix (PCM at the spindle poles during mitosis. ASPM siRNA reduces ASPM protein at the spindle poles in cultured U2OS cells and severely perturbs a number of aspects of mitosis, including the orientation of the mitotic spindle, the main determinant of developmental asymmetrical cell division. The majority of ASPM depleted mitotic cells fail to complete cytokinesis. In MCPH patient fibroblasts we show that a pathogenic ASPM splice site mutation results in the expression of a novel variant protein lacking a tripeptide motif, a minimal alteration that correlates with a dramatic decrease in ASPM spindle pole localisation. Moreover, expression of dominant-negative ASPM C-terminal fragments cause severe spindle assembly defects and cytokinesis failure in cultured cells. Conclusions These observations indicate that ASPM participates in spindle organisation, spindle positioning and cytokinesis in all dividing cells and that the extreme C-terminus of the protein is required for ASPM localisation and function. Our data supports the hypothesis that the MCPH phenotype caused by ASPM mutation is a consequence of mitotic aberrations during neurogenesis. We propose the effects of ASPM mutation are tolerated in somatic cells but have profound consequences for the symmetrical division of NPCs, due to the unusual morphology of these cells. This antagonises the early expansion of the progenitor pool that underpins cortical

[Temporary disappearance of EEG activity during reversible respiratory failure in rabbits and cats].

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Jurco, M; Tomori, Z; Tkácová, R; Calfa, J

1989-02-01

The dynamics of changes of EEG activity was studied on the model of reversible respiratory failure in rabbits and cats in pentobarbital anesthesia. During N2 inhalation, apnea of 60 second duration, and subsequent resuscitation the electrocorticogram in bifrontal and bioccipital connection was recorded. Evaluation of 19 episodes of apnea in 7 rabbits and of 25 episodes in 8 cats yielded the following results: 1. During hyperventilation induced by N2 inhalation a certain activation of the EEG was observed (spindles more pronounced, increased occurrence rate of discharges of the reticular activation system). 2. At the onset of apnea the EEG was still distinct, suggesting that primary apnea is presumably not caused by anoxia and the accompanying electric silence of the structures that control respiration. 3. Disappearance of EEG occurred within 50 seconds from the onset of apnea in rabbits and within 30 seconds in cats. 4. After repeated episodes of apnea lasting for 60 sec., artificial ventilation mostly resulted in normalization of EEG.

Deep sleep after social stress: NREM sleep slow-wave activity is enhanced in both winners and losers of a conflict.

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Kamphuis, Jeanine; Lancel, Marike; Koolhaas, Jaap M; Meerlo, Peter

2015-07-01

Sleep is considered to be a recovery process of prior wakefulness. Not only duration of the waking period affects sleep architecture and sleep EEG, the quality of wakefulness is also highly important. Studies in rats have shown that social defeat stress, in which experimental animals are attacked and defeated by a dominant conspecific, is followed by an acute increase in NREM sleep EEG slow wave activity (SWA). However, it is not known whether this effect is specific for the stress of social defeat or a result of the conflict per se. In the present experiment, we examined how sleep is affected in both the winners and losers of a social conflict. Sleep-wake patterns and sleep EEG were recorded in male wild-type Groningen rats that were subjected to 1h of social conflict in the middle of the light phase. All animals were confronted with a conspecific of similar aggression level and the conflict took place in a neutral arena where both individuals had an equal chance to either win or lose the conflict. NREM sleep SWA was significantly increased after the social conflict compared to baseline values and a gentle stimulation control condition. REM sleep was significantly suppressed in the first hours after the conflict. Winners and losers did not differ significantly in NREM sleep time, NREM sleep SWA and REM sleep time immediately after the conflict. Losers tended to have slightly more NREM sleep later in the recovery period. This study shows that in rats a social conflict with an unpredictable outcome has quantitatively and qualitatively largely similar acute effects on subsequent sleep in winners and losers. Copyright © 2015 Elsevier Inc. All rights reserved.

Pain and the alpha-sleep anomaly: a mechanism of sleep disruption in facioscapulohumeral muscular dystrophy.

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Della Marca, Giacomo; Frusciante, Roberto; Vollono, Catello; Iannaccone, Elisabetta; Dittoni, Serena; Losurdo, Anna; Testani, Elisa; Gnoni, Valentina; Colicchio, Salvatore; Di Blasi, Chiara; Erra, Carmen; Mazza, Salvatore; Ricci, Enzo

2013-04-01

To measure the presence of the alpha-sleep anomaly in facioscapulohumeral muscular dystrophy (FSHD) and to evaluate the association between the sleep electroencephalogram (EEG) pattern and the presence of musculoskeletal pain. Cross-sectional study. Sleep laboratory. Fifty-five consecutive adult FSHD patients, 26 women and 29 men, age 49.6 ± 15.1 years (range 18-76). Questionnaires and polysomnography. Patients were asked to indicate if in the 3 months before the sleep study they presented persisting or recurring musculoskeletal pain. Patients who reported pain were asked to fill in the Italian version of the Brief Pain Inventory and the McGill Pain questionnaire, and a 101-point visual analog scale (VAS) for pain intensity. Polysomnographic recordings were performed. EEG was analyzed by means of Fast Fourier Transform. Four power spectra bands (δ 0-4 Hz, θ 4-8 Hz, α 8-14 Hz, β 14-32 Hz) were computed. Sleep macrostructure parameters and alpha/delta EEG power ratio during non rapid eye movement (NREM) sleep were compared between patients with and without pain. Forty-two patients in our sample reported chronic pain. VAS mean score was 55.2 ± 23.8 (range 10-100), pain rating index score was 13.8 ± 10.2, and present pain intensity was 2.5 ± 0.8. The statistical analysis documented an increased occurrence of the alpha and beta rhythms during NREM sleep in FSHD patients with pain. Significant correlations were observed between the alpha/delta power ratio during NREM sleep and pain measures. Chronic musculoskeletal pain is frequent in FSHD patients, and it represents a major mechanism of sleep disruption. Wiley Periodicals, Inc.

Sleep: a physiological "cerveau isolé" stage?

Science.gov (United States)

Gottesmann, C; User, P; Gioanni, H

1980-01-01

Rapid or paradoxical sleep in the rat is usually preceded and often followed by a stage of short duration characterized by large spindles in the frontal cortex and theta rhythm in the hippocampus. The midbrain transection induces for hours the same electrophysiological patterns suggesting the existence in the rat of a short physiologically isolated, forebrain stage during sleep.

Simultaneous recording of EEG and electromyographic polygraphy increases the diagnostic yield of video-EEG monitoring.

Science.gov (United States)

Hill, Aron T; Briggs, Belinda A; Seneviratne, Udaya

2014-06-01

To investigate the usefulness of adjunctive electromyographic (EMG) polygraphy in the diagnosis of clinical events captured during long-term video-EEG monitoring. A total of 40 patients (21 women, 19 men) aged between 19 and 72 years (mean 43) investigated using video-EEG monitoring were studied. Electromyographic activity was simultaneously recorded with EEG in four patients selected on clinical grounds. In these patients, surface EMG electrodes were placed over muscles suspected to be activated during a typical clinical event. Of the 40 patients investigated, 24 (60%) were given a diagnosis, whereas 16 (40%) remained undiagnosed. All four patients receiving adjunctive EMG polygraphy obtained a diagnosis, with three of these diagnoses being exclusively reliant on the EMG recordings. Specifically, one patient was diagnosed with propriospinal myoclonus, another patient was diagnosed with facio-mandibular myoclonus, and a third patient was found to have bruxism and periodic leg movements of sleep. The information obtained from surface EMG recordings aided the diagnosis of clinical events captured during video-EEG monitoring in 7.5% of the total cohort. This study suggests that EEG-EMG polygraphy may be used as a technique of improving the diagnostic yield of video-EEG monitoring in selected cases.

Detection of a sleep disorder predicting Parkinson's disease

DEFF Research Database (Denmark)

Hansen, Ingeborg H.; Marcussen, Mikkel; Christensen, Julie Anja Engelhard

2013-01-01

Idiopathic rapid eye-movement (REM) sleep behavior disorder (iRBD) has been found to be a strong early predictor for later development into Parkinson's disease (PD). iRBD is diagnosed by polysomnography but the manual evaluation is laborious, why the aims of this study are to develop supportive...... methods for detecting iRBD from electroencephalo-graphic (EEG) signals recorded during REM sleep. This method classified subjects from their EEG similarity with the two classes iRBD patients and control subjects. The feature sets used for classifying subjects were based on the relative powers of the EEG...

Decoding sequence learning from single-trial intracranial EEG in humans.

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Marzia De Lucia

Full Text Available We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep or a later consolidated phase (day 2, after sleep, whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence. Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.

Serial EEG findings in anti-NMDA receptor encephalitis: correlation between clinical course and EEG.

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Ueda, Jun; Kawamoto, Michi; Hikiami, Ryota; Ishii, Junko; Yoshimura, Hajime; Matsumoto, Riki; Kohara, Nobuo

2017-12-01

Anti-NMDA receptor encephalitis is a paraneoplastic encephalitis characterised by psychiatric features, involuntary movement, and autonomic instability. Various EEG findings in patients with anti-NMDA receptor encephalitis have been reported, however, the correlation between the EEG findings and clinical course of anti-NMDA receptor encephalitis remains unclear. We describe a patient with anti-NMDA receptor encephalitis with a focus on EEG findings, which included: status epilepticus, generalised rhythmic delta activity, excess beta activity, extreme delta brush, and paroxysmal alpha activity upon arousal from sleep, which we term"arousal alpha pattern". Initially, status epilepticus was observed on the EEG when the patient was comatose with conjugate deviation. The EEG then indicated excess beta activity, followed by the emergence of continuous slow activity, including generalised rhythmic delta activity and extreme delta brush, in the most severe phase. Slow activity gradually faded in parallel with clinical amelioration. Excess beta activity persisted, even after the patient became almost independent in daily activities, and finally disappeared with full recovery. In summary, our patient with anti-NMDA receptor encephalitis demonstrated slow activity on the EEG, including extreme delta brush during the most severe phase, which gradually faded in parallel with clinical amelioration, with excess beta activity persisting into the recovery phase.

Preserved sleep microstructure in blind individuals

DEFF Research Database (Denmark)

Aubin, Sébrina; Christensen, Julie A.E.; Jennum, Poul

2018-01-01

, as light is the primary zeitgeber of the master biological clock found in the suprachiasmatic nucleus of the hypothalamus. In addition, a greater number of sleep disturbances is often reported in blind individuals. Here, we examined various electroencephalographic microstructural components of sleep, both...... during rapid-eye-movement (REM) sleep and non-REM (NREM) sleep, between blind individuals, including both of early and late onset, and normal-sighted controls. During wakefulness, occipital alpha oscillations were lower, or absent in blind individuals. During sleep, differences were observed across...... electrode derivations between the early and late blind samples, which may reflect altered cortical networking in early blindness. Despite these differences in power spectra density, the electroencephalography microstructure of sleep, including sleep spindles, slow wave activity, and sawtooth waves, remained...

A study on CT findings and electroencephalographic findings in severely handicapped children

International Nuclear Information System (INIS)

Nakashima, Masao; Nishimura, Masaaki; Kachi, Shozo; Sugimoto, Kimiyuki; Saito, Msahiko; Yamada, Shigeaki; Kameyama, Yoshio; Tanaka, Minoru; Hiraizumi, Yasuhisa.

1987-01-01

Sleep electroencephalographic (EEG) and computed tomographic (CT) features were examined in 40 institutionalized severely handicapped persons. Cranial CT appearance fell into five major types: (I) no abnormal findings (n=2), (II) generalized brain atrophy (n=16), (III) diffuse parenchymal disturbance (n=10), (IV) brain malformation (n=4), and (V) localized brain disturbance (n=8). In the I group, one person had normal EEG findings as well, but another person had the presence of focal spikes without spindles on EEG. Five of the II group had no abnormal EEG findings; ten had abnormality in basic waves and/or localized paroxysmal waves; and one had generalized spike-and-slow wave complex. All persons in the III group had flattening or disappearance of spindle waves. In the IV group, two persons with cerebral malformation and one with linear nevus sebaceous syndrome in association with hypoplasia of the cerebral hemisphere had abnormality in basic waves and localized paroxysmal waves. In the remaining one person with deficit of vermis cerebelli, there was no EEG abnormality. Among the last group of persons, there was no EEG abnormality corresponding to CT features. (Namekawa, K)

Added diagnostic value of magnetoencephalography (MEG) in patients suspected for epilepsy, where previous, extensive EEG workup was unrevealing

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Duez, Lene; Beniczky, Sándor; Tankisi, Hatice

2016-01-01

was calculated from the cases where abnormalities were seen in MEG but not EEG. RESULTS: Twenty-two patients had the diagnosis epilepsy according to the reference standard. MEG-EEG detected abnormalities, and supported the diagnosis in nine of the 22 patients with the diagnosis epilepsy at one-year follow......OBJECTIVE: To elucidate the possible additional diagnostic yield of MEG in the workup of patients with suspected epilepsy, where repeated EEGs, including sleep-recordings failed to identify abnormalities. METHODS: Fifty-two consecutive patients with clinical suspicion of epilepsy and at least three...... normal EEGs, including sleep-EEG, were prospectively analyzed. The reference standard was inferred from the diagnosis obtained from the medical charts, after at least one-year follow-up. MEG (306-channel, whole-head) and simultaneous EEG (MEG-EEG) was recorded for one hour. The added sensitivity of MEG...

Increased delta power and discrepancies in objective and subjective sleep measurements in borderline personality disorder.

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Philipsen, Alexandra; Feige, Bernd; Al-Shajlawi, Anam; Schmahl, Christian; Bohus, Martin; Richter, Harald; Voderholzer, Ulrich; Lieb, Klaus; Riemann, Dieter

2005-09-01

Previous studies have shown depression-like sleep abnormalities in borderline personality disorder (BPD). However, findings in BPD are not unequivocal for REM dysregulation, as well as for a decrement of slow wave sleep and sleep continuity disturbances. Earlier findings in sleep EEG abnormalities in BPD may have been confounded by concomitant depressive symptoms. Twenty unmedicated female BPD patients without current comorbid major depression and 20 sex- and age-matched control subjects entered the study. Conventional polysomnographic parameters and for the first time sleep EEG spectral power analysis was performed on two sleep laboratory nights. Subjective sleep parameters were collected by sleep questionnaires in order to assess the relationship between objective and subjective sleep measurements. BPD patients showed a tendency for shortened REM latency and significantly decreased NonREM sleep (stage 2). Spectral EEG analysis showed increased delta power in total NREM sleep as well as in REM sleep in BPD patients. Subjective ratings documented drastically impaired sleep quality in BPD patients for the two weeks before the study and during the two laboratory nights. Not-depressed BPD patients only showed tendencies for depression-like REM sleep abnormalities. Surprisingly, BPD patients displayed higher levels of delta power in the sleep EEG in NREM sleep than healthy control subjects. There was a marked discrepancy between objective and subjective sleep measurements, which indicates an altered perception of sleep in BPD. The underlying psychological and neurobiological mechanisms of these alterations are still unclear and need to be clarified in future studies including interventions on a pharmacological and cognitive-behavioral level.

EEG recording after sleep deprivation in a series of patients with juvenile myoclonic epilepsy Registros eletrencefalográficos após privação de sono em uma série de pacientes com epilepsia mioclônica juvenil

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Nise Alessandra de Carvalho Sousa

2005-06-01

Full Text Available Seizures in Juvenile Myoclonic Epilepsy (JME are dependent on the sleep-wake cycle and precipitant factors, among which sleep deprivation (SD is one of the most important. Still an under diagnosed syndrome, misinterpretation of the EEGs contributes to diagnostic delay. Despite this, a quantitative EEG investigation of SD effects has not been performed. We investigated the effect of SD on EEGs in 41 patients, aged 16-50 yr. (mean 25.4, who had not yet had syndromic diagnosis after a mean delay of 8.2 yr. Two EEG recordings separated by a 48-hour interval were taken at 7 a.m. preceded by a period of 6 hours of sleep (routine EEG and after SD (sleep-deprived EEG. The same protocol was followed and included a rest wakefulness recording, photic stimulation, hyperventilation and a post-hyperventilation period. The EEGs were analyzed as to the effect of SD on the number, duration, morphology, localization and predominance of abnormalities in the different stages. A discharge index (DI was calculated. Out of the 41 patients, 4 presented both normal EEG recordings. In 37 (90.2% there were epileptiform discharges (ED. The number of patients with ED ascended from 26 (70.3% in the routine EEG to 32 (86.5% in the sleep-deprived exam. The presence of generalized spike-wave and multispike-wave increased from 20 (54.1% and 13 (35.1% in the first EEG to 29 (78.4% and 19 (51.4% in the second, respectively (pNa epilepsia mioclônica juvenil (EMJ, uma síndrome epiléptica ainda subdiagnosticada, as crises são dependentes do ciclo vigília-sono e de fatores precipitantes, entre os quais a privação de sono (PS é um dos mais importantes. A interpretação inadequada dos EEGs contribui para atraso no diagnóstico. Ainda não foi realizada investigação quantitativa sobre os efeitos da PS. Avaliamos o efeito da PS nos EEGs de 41 pacientes entre 16 e 50 anos (média 25,4 com EMJ em dois registros eletrencefalográficos, separados por intervalo de 48 horas. Os

Functional imaging of sleep vertex sharp transients.

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Stern, John M; Caporro, Matteo; Haneef, Zulfi; Yeh, Hsiang J; Buttinelli, Carla; Lenartowicz, Agatha; Mumford, Jeanette A; Parvizi, Josef; Poldrack, Russell A

2011-07-01

The vertex sharp transient (VST) is an electroencephalographic (EEG) discharge that is an early marker of non-REM sleep. It has been recognized since the beginning of sleep physiology research, but its source and function remain mostly unexplained. We investigated VST generation using functional MRI (fMRI). Simultaneous EEG and fMRI were recorded from seven individuals in drowsiness and light sleep. VST occurrences on EEG were modeled with fMRI using an impulse function convolved with a hemodynamic response function to identify cerebral regions correlating to the VSTs. A resulting statistical image was thresholded at Z>2.3. Two hundred VSTs were identified. Significantly increased signal was present bilaterally in medial central, lateral precentral, posterior superior temporal, and medial occipital cortex. No regions of decreased signal were present. The regions are consistent with electrophysiologic evidence from animal models and functional imaging of human sleep, but the results are specific to VSTs. The regions principally encompass the primary sensorimotor cortical regions for vision, hearing, and touch. The results depict a network comprising the presumed VST generator and its associated regions. The associated regions functional similarity for primary sensation suggests a role for VSTs in sensory experience during sleep. Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Sex-related differences in sleep slow wave activity in major depressive disorder: a high-density EEG investigation.

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Plante, David T; Landsness, Eric C; Peterson, Michael J; Goldstein, Michael R; Riedner, Brady A; Wanger, Timothy; Guokas, Jeffrey J; Tononi, Giulio; Benca, Ruth M

2012-09-18

Sleep disturbance plays an important role in major depressive disorder (MDD). Prior investigations have demonstrated that slow wave activity (SWA) during sleep is altered in MDD; however, results have not been consistent across studies, which may be due in part to sex-related differences in SWA and/or limited spatial resolution of spectral analyses. This study sought to characterize SWA in MDD utilizing high-density electroencephalography (hdEEG) to examine the topography of SWA across the cortex in MDD, as well as sex-related variation in SWA topography in the disorder. All-night recordings with 256 channel hdEEG were collected in 30 unipolar MDD subjects (19 women) and 30 age and sex-matched control subjects. Spectral analyses of SWA were performed to determine group differences. SWA was compared between MDD and controls, including analyses stratified by sex, using statistical non-parametric mapping to correct for multiple comparisons of topographic data. As a group, MDD subjects demonstrated significant increases in all-night SWA primarily in bilateral prefrontal channels. When stratified by sex, MDD women demonstrated global increases in SWA relative to age-matched controls that were most consistent in bilateral prefrontal regions; however, MDD men showed no significant differences relative to age-matched controls. Further analyses demonstrated increased SWA in MDD women was most prominent in the first portion of the night. Women, but not men with MDD demonstrate significant increases in SWA in multiple cortical areas relative to control subjects. Further research is warranted to investigate the role of SWA in MDD, and to clarify how increased SWA in women with MDD is related to the pathophysiology of the disorder.

Brain Networks are Independently Modulated by Donepezil, Sleep, and Sleep Deprivation.

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Wirsich, Jonathan; Rey, Marc; Guye, Maxime; Bénar, Christian; Lanteaume, Laura; Ridley, Ben; Confort-Gouny, Sylviane; Cassé-Perrot, Catherine; Soulier, Elisabeth; Viout, Patrick; Rouby, Franck; Lefebvre, Marie-Noëlle; Audebert, Christine; Truillet, Romain; Jouve, Elisabeth; Payoux, Pierre; Bartrés-Faz, David; Bordet, Régis; Richardson, Jill C; Babiloni, Claudio; Rossini, Paolo Maria; Micallef, Joelle; Blin, Olivier; Ranjeva, Jean-Philippe

2018-05-01

Resting-state connectivity has been widely studied in the healthy and pathological brain. Less well-characterized are the brain networks altered during pharmacological interventions and their possible interaction with vigilance. In the hopes of finding new biomarkers which can be used to identify cortical activity and cognitive processes linked to the effects of drugs to treat neurodegenerative diseases such as Alzheimer's disease, the analysis of networks altered by medication would be particularly interesting. Eleven healthy subjects were recruited in the context of the European Innovative Medicines Initiative 'PharmaCog'. Each underwent five sessions of simultaneous EEG-fMRI in order to investigate the effects of donepezil and memantine before and after sleep deprivation (SD). The SD approach has been previously proposed as a model for cognitive impairment in healthy subjects. By applying network based statistics (NBS), we observed altered brain networks significantly linked to donepezil intake and sleep deprivation. Taking into account the sleep stages extracted from the EEG data we revealed that a network linked to sleep is interacting with sleep deprivation but not with medication intake. We successfully extracted the functional resting-state networks modified by donepezil intake, sleep and SD. We observed donepezil induced whole brain connectivity alterations forming a network separated from the changes induced by sleep and SD, a result which shows the utility of this approach to check for the validity of pharmacological resting-state analysis of the tested medications without the need of taking into account the subject specific vigilance.

Comparisons of Portable Sleep Monitors of Different Modalities: Potential as Naturalistic Sleep Recorders

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Masahiro Matsuo

2016-07-01

Full Text Available Background: Humans spend more than a fourth of their life sleeping, and sleep quality has been significantly linked to health. However, the objective examination of ambulatory sleep quality remains a challenge, since sleep is a state of unconsciousness, which limits the reliability of self-reports. Therefore, a non-invasive, continuous, and objective method for the recording and analysis of naturalistic sleep is required.Objective: Portable sleep recording devices provide a suitable solution for the ambulatory analysis of sleep quality. In this study, the performance of two activity-based sleep monitors (Actiwatch and MTN-210 and a single-channel EEG-based sleep monitor (SleepScope were compared in order to examine their reliability for the assessment of sleep quality.Methods: Twenty healthy adults were recruited for this study. First, data from daily activity recorded by Actiwatch and MTN-210 were compared to determine whether MTN-210, a more affordable device, could yield data similar to Actiwatch, the de-facto standard. In addition, sleep detection ability was examined using data obtained by polysomnography as reference. One simple analysis included comparing the sleep/wake detection ability of Actiwatch, MTN-210, and SleepScope. Furthermore, the fidelity of sleep stage determination was examined using SleepScope in finer time resolution. Results: The results indicate that MTN-210 demonstrates an activity pattern comparable to that of Actiwatch, although their sensitivity preferences were not identical. Moreover, MTN-210 provides assessment of sleep duration comparable to that of the wrist-worn Actiwatch when MTN-210 was attached to the body. SleepScope featured superior overall sleep detection performance among the three methods tested. Furthermore, SleepScope was able to provide information regarding sleep architecture, although systemic bias was found. Conclusion: The present results suggest that single-channel EEG-based sleep monitors are

Role of slow oscillatory activity and slow wave sleep in consolidation of episodic-like memory in rats.

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Oyanedel, Carlos N; Binder, Sonja; Kelemen, Eduard; Petersen, Kimberley; Born, Jan; Inostroza, Marion

2014-12-15

Our previous experiments showed that sleep in rats enhances consolidation of hippocampus dependent episodic-like memory, i.e. the ability to remember an event bound into specific spatio-temporal context. Here we tested the hypothesis that this enhancing effect of sleep is linked to the occurrence of slow oscillatory and spindle activity during slow wave sleep (SWS). Rats were tested on an episodic-like memory task and on three additional tasks covering separately the where (object place recognition), when (temporal memory), and what (novel object recognition) components of episodic memory. In each task, the sample phase (encoding) was followed by an 80-min retention interval that covered either a period of regular morning sleep or sleep deprivation. Memory during retrieval was tested using preferential exploration of novelty vs. familiarity. Consistent with previous findings, the rats which had slept during the retention interval showed significantly stronger episodic-like memory and spatial memory, and a trend of improved temporal memory (although not significant). Object recognition memory was similarly retained across sleep and sleep deprivation retention intervals. Recall of episodic-like memory was associated with increased slow oscillatory activity (0.85-2.0Hz) during SWS in the retention interval. Spatial memory was associated with increased proportions of SWS. Against our hypothesis, a relationship between spindle activity and episodic-like memory performance was not detected, but spindle activity was associated with object recognition memory. The results provide support for the role of SWS and slow oscillatory activity in consolidating hippocampus-dependent memory, the role of spindles in this process needs to be further examined. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Deep sleep after social stress : NREM sleep slow-wave activity is enhanced in both winners and losers of a conflict

NARCIS (Netherlands)

Kamphuis, Jeanine; Lancel, Marike; Koolhaas, Jaap M.; Meerlo, Peter

Sleep is considered to be a recovery process of prior wakefulness. Not only duration of the waking period affects sleep architecture and sleep EEG, the quality of wakefulness is also highly important. Studies in rats have shown that social defeat stress, in which experimental animals are attacked

Novel method for high-throughput phenotyping of sleep in mice.

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Pack, Allan I; Galante, Raymond J; Maislin, Greg; Cater, Jacqueline; Metaxas, Dimitris; Lu, Shan; Zhang, Lin; Von Smith, Randy; Kay, Timothy; Lian, Jie; Svenson, Karen; Peters, Luanne L

2007-01-17

Assessment of sleep in mice currently requires initial implantation of chronic electrodes for assessment of electroencephalogram (EEG) and electromyogram (EMG) followed by time to recover from surgery. Hence, it is not ideal for high-throughput screening. To address this deficiency, a method of assessment of sleep and wakefulness in mice has been developed based on assessment of activity/inactivity either by digital video analysis or by breaking infrared beams in the mouse cage. It is based on the algorithm that any episode of continuous inactivity of > or =40 s is predicted to be sleep. The method gives excellent agreement in C57BL/6J male mice with simultaneous assessment of sleep by EEG/EMG recording. The average agreement over 8,640 10-s epochs in 24 h is 92% (n = 7 mice) with agreement in individual mice being 88-94%. Average EEG/EMG determined sleep per 2-h interval across the day was 59.4 min. The estimated mean difference (bias) per 2-h interval between inactivity-defined sleep and EEG/EMG-defined sleep was only 1.0 min (95% confidence interval for mean bias -0.06 to +2.6 min). The standard deviation of differences (precision) was 7.5 min per 2-h interval with 95% limits of agreement ranging from -13.7 to +15.7 min. Although bias significantly varied by time of day (P = 0.0007), the magnitude of time-of-day differences was not large (average bias during lights on and lights off was +5.0 and -3.0 min per 2-h interval, respectively). This method has applications in chemical mutagenesis and for studies of molecular changes in brain with sleep/wakefulness.

Altered Sleep Homeostasis in Rev-erbα Knockout Mice.

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Mang, Géraldine M; La Spada, Francesco; Emmenegger, Yann; Chappuis, Sylvie; Ripperger, Jürgen A; Albrecht, Urs; Franken, Paul

2016-03-01

The nuclear receptor REV-ERBα is a potent, constitutive transcriptional repressor critical for the regulation of key circadian and metabolic genes. Recently, REV-ERBα's involvement in learning, neurogenesis, mood, and dopamine turnover was demonstrated suggesting a specific role in central nervous system functioning. We have previously shown that the brain expression of several core clock genes, including Rev-erbα, is modulated by sleep loss. We here test the consequences of a loss of REV-ERBα on the homeostatic regulation of sleep. EEG/EMG signals were recorded in Rev-erbα knockout (KO) mice and their wild type (WT) littermates during baseline, sleep deprivation, and recovery. Cortical gene expression measurements after sleep deprivation were contrasted to baseline. Although baseline sleep/wake duration was remarkably similar, KO mice showed an advance of the sleep/wake distribution relative to the light-dark cycle. After sleep onset in baseline and after sleep deprivation, both EEG delta power (1-4 Hz) and sleep consolidation were reduced in KO mice indicating a slower increase of homeostatic sleep need during wakefulness. This slower increase might relate to the smaller increase in theta and gamma power observed in the waking EEG prior to sleep onset under both conditions. Indeed, the increased theta activity during wakefulness predicted delta power in subsequent NREM sleep. Lack of Rev-erbα increased Bmal1, Npas2, Clock, and Fabp7 expression, confirming the direct regulation of these genes by REV-ERBα also in the brain. Our results add further proof to the notion that clock genes are involved in sleep homeostasis. Because accumulating evidence directly links REV-ERBα to dopamine signaling the altered homeostatic regulation of sleep reported here are discussed in that context. © 2016 Associated Professional Sleep Societies, LLC.

Modeling aircraft noise induced sleep disturbance

Science.gov (United States)

McGuire, Sarah M.

occurrence of rapid eye movements, sleep spindles, and slow wave sleep. Using these features an approach for classifying sleep stages every one second during the night was developed. From observation of the results of the sleep stage classification, it was determined how to add faster dynamics to the nonlinear dynamic model. Slow and fast REM activity are modeled separately and the activity in the gamma frequency band of the EEG signal is used to model both spontaneous and noise-induced awakenings. The nonlinear model predicts changes in sleep structure similar to those found by other researchers and reported in the sleep literature and similar to those found in obtained survey data. To compare sleep disturbance model predictions, flight operations data from US airports were obtained and sleep disturbance in communities was predicted for different operations scenarios using the modified Markov model, the nonlinear dynamic model, and other aircraft noise awakening models. Similarities and differences in model predictions were evaluated in order to determine if the use of the developed sleep structure model leads to improved predictions of the impact of nighttime noise on communities.

Sleep-Related Disorders in Children with Attention-Deficit Hyperactivity Disorder: Preliminary Results of a Full Sleep Assessment Study.

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Miano, Silvia; Esposito, Maria; Foderaro, Giuseppe; Ramelli, Gian Paolo; Pezzoli, Valdo; Manconi, Mauro

2016-11-01

We present the preliminary results of a prospective case-control sleep study in children with a diagnosis of attention-deficit hyperactivity disorder (ADHD). A deep sleep assessment including sleep questionnaires, sleep habits, a video-polysomnographic recording with full high-density electroencephalography (EEG) and cardiorespiratory polygraphy, multiple sleep latency test, and 1-week actigraphic recording were performed to verify whether children with ADHD may be classified into one of the following five phenotypes: (1) hypoarousal state, resembling narcolepsy, which may be considered a "primary" form of ADHD; (2) delayed sleep onset insomnia; (3) sleep-disordered breathing; (4) restless legs syndrome and/or periodic limb movements; and (5) sleep epilepsy and/or EEG interictal epileptiform discharges. Fifteen consecutive outpatients with ADHD were recruited (two female, mean age 10.6 ± 2.2, age range 8-13.7 years) over 6 months. The narcolepsy-like sleep phenotype was observed in three children, the sleep onset insomnia phenotype was observed in one child, mild obstructive sleep apnea was observed in three children, sleep hyperkinesia and/or PLMs were observed in five children, while IEDs and or nocturnal epilepsy were observed in three children. Depending on the sleep phenotype, children received melatonin, iron supplementation, antiepileptic drugs, or stimulants. Our study further highlights the need to design an efficient sleep diagnostic algorithm for children with ADHD, thereby more accurately identifying cases in which a full sleep assessment is indicated. © 2016 John Wiley & Sons Ltd.

Multiple sleep alterations in mice lacking cannabinoid type 1 receptors.

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Alessandro Silvani

Full Text Available Cannabinoid type 1 (CB1 receptors are highly expressed in the brain and play a role in behavior control. Endogenous cannabinoid signaling is modulated by high-fat diet (HFD. We investigated the consequences of congenital lack of CB1 receptors on sleep in mice fed standard diet (SD and HFD. CB1 cannabinoid receptor knock-out (KO and wild-type (WT mice were fed SD or HFD for 4 months (n = 9-10 per group. Mice were instrumented with electroencephalographic (EEG and electromyographic electrodes. Recordings were performed during baseline (48 hours, sleep deprivation (gentle handling, 6 hours, sleep recovery (18 hours, and after cage switch (insomnia model paradigm, 6 hours. We found multiple significant effects of genotype on sleep. In particular, KO spent more time awake and less time in non-rapid-eye-movement sleep (NREMS and rapid-eye-movement sleep (REMS than WT during the dark (active period but not during the light (rest period, enhancing the day-night variation of wake-sleep amounts. KO had slower EEG theta rhythm during REMS. REMS homeostasis after sleep deprivation was less effective in KO than in WT. Finally, KO habituated more rapidly to the arousing effect of the cage-switch test than WT. We did not find any significant effects of diet or of diet x genotype interaction on sleep. The occurrence of multiple sleep alterations in KO indicates important roles of CB1 cannabinoid receptors in limiting arousal during the active period of the day, in sleep regulation, and in sleep EEG in mice.

Targeted memory reactivation during slow wave sleep facilitates emotional memory consolidation.

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Cairney, Scott A; Durrant, Simon J; Hulleman, Johan; Lewis, Penelope A

2014-04-01

To investigate the mechanisms by which auditory targeted memory reactivation (TMR) during slow wave sleep (SWS) influences the consolidation of emotionally negative and neutral memories. Each of 72 (36 negative, 36 neutral) picture-location associations were encoded with a semantically related sound. During a subsequent nap, half of the sounds were replayed in SWS, before picture-location recall was examined in a final test. Manchester Sleep Laboratory, University of Manchester. 15 adults (3 male) mean age = 20.40 (standard deviation ± 3.07). TMR with auditory cues during SWS. Performance was assessed by memory accuracy and recall response times (RTs). Data were analyzed with a 2 (sound: replayed/not replayed) × 2 (emotion: negative/neutral) repeated measures analysis of covariance with SWS duration, and then SWS spindles, as the mean-centered covariate. Both analyses revealed a significant three-way interaction for RTs but not memory accuracy. Critically, SWS duration and SWS spindles predicted faster memory judgments for negative, relative to neutral, picture locations that were cued with TMR. TMR initiates an enhanced consolidation process during subsequent SWS, wherein sleep spindles mediate the selective enhancement of reactivated emotional memories.

Short Meditation Trainings Enhance Non-REM Sleep Low-Frequency Oscillations.

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Daniela Dentico

Full Text Available We have recently shown higher parietal-occipital EEG gamma activity during sleep in long-term meditators compared to meditation-naive individuals. This gamma increase was specific for NREM sleep, was present throughout the entire night and correlated with meditation expertise, thus suggesting underlying long-lasting neuroplastic changes induced through prolonged training. The aim of this study was to explore the neuroplastic changes acutely induced by 2 intensive days of different meditation practices in the same group of practitioners. We also repeated baseline recordings in a meditation-naive cohort to account for time effects on sleep EEG activity.High-density EEG recordings of human brain activity were acquired over the course of whole sleep nights following intervention.Sound-attenuated sleep research room.Twenty-four long-term meditators and twenty-four meditation-naïve controls.Two 8-h sessions of either a mindfulness-based meditation or a form of meditation designed to cultivate compassion and loving kindness, hereafter referred to as compassion meditation.We found an increase in EEG low-frequency oscillatory activities (1-12 Hz, centered around 7-8 Hz over prefrontal and left parietal electrodes across whole night NREM cycles. This power increase peaked early in the night and extended during the third cycle to high-frequencies up to the gamma range (25-40 Hz. There was no difference in sleep EEG activity between meditation styles in long-term meditators nor in the meditation naïve group across different time points. Furthermore, the prefrontal-parietal changes were dependent on meditation life experience.This low-frequency prefrontal-parietal activation likely reflects acute, meditation-related plastic changes occurring during wakefulness, and may underlie a top-down regulation from frontal and anterior parietal areas to the posterior parietal and occipital regions showing chronic, long-lasting plastic changes in long-term meditators.

Short Meditation Trainings Enhance Non-REM Sleep Low-Frequency Oscillations.

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Dentico, Daniela; Ferrarelli, Fabio; Riedner, Brady A; Smith, Richard; Zennig, Corinna; Lutz, Antoine; Tononi, Giulio; Davidson, Richard J

2016-01-01

We have recently shown higher parietal-occipital EEG gamma activity during sleep in long-term meditators compared to meditation-naive individuals. This gamma increase was specific for NREM sleep, was present throughout the entire night and correlated with meditation expertise, thus suggesting underlying long-lasting neuroplastic changes induced through prolonged training. The aim of this study was to explore the neuroplastic changes acutely induced by 2 intensive days of different meditation practices in the same group of practitioners. We also repeated baseline recordings in a meditation-naive cohort to account for time effects on sleep EEG activity. High-density EEG recordings of human brain activity were acquired over the course of whole sleep nights following intervention. Sound-attenuated sleep research room. Twenty-four long-term meditators and twenty-four meditation-naïve controls. Two 8-h sessions of either a mindfulness-based meditation or a form of meditation designed to cultivate compassion and loving kindness, hereafter referred to as compassion meditation. We found an increase in EEG low-frequency oscillatory activities (1-12 Hz, centered around 7-8 Hz) over prefrontal and left parietal electrodes across whole night NREM cycles. This power increase peaked early in the night and extended during the third cycle to high-frequencies up to the gamma range (25-40 Hz). There was no difference in sleep EEG activity between meditation styles in long-term meditators nor in the meditation naïve group across different time points. Furthermore, the prefrontal-parietal changes were dependent on meditation life experience. This low-frequency prefrontal-parietal activation likely reflects acute, meditation-related plastic changes occurring during wakefulness, and may underlie a top-down regulation from frontal and anterior parietal areas to the posterior parietal and occipital regions showing chronic, long-lasting plastic changes in long-term meditators.

Dynamics of large-scale brain activity in normal arousal states and epileptic seizures

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Robinson, P. A.; Rennie, C. J.; Rowe, D. L.

2002-04-01

Links between electroencephalograms (EEGs) and underlying aspects of neurophysiology and anatomy are poorly understood. Here a nonlinear continuum model of large-scale brain electrical activity is used to analyze arousal states and their stability and nonlinear dynamics for physiologically realistic parameters. A simple ordered arousal sequence in a reduced parameter space is inferred and found to be consistent with experimentally determined parameters of waking states. Instabilities arise at spectral peaks of the major clinically observed EEG rhythms-mainly slow wave, delta, theta, alpha, and sleep spindle-with each instability zone lying near its most common experimental precursor arousal states in the reduced space. Theta, alpha, and spindle instabilities evolve toward low-dimensional nonlinear limit cycles that correspond closely to EEGs of petit mal seizures for theta instability, and grand mal seizures for the other types. Nonlinear stimulus-induced entrainment and seizures are also seen, EEG spectra and potentials evoked by stimuli are reproduced, and numerous other points of experimental agreement are found. Inverse modeling enables physiological parameters underlying observed EEGs to be determined by a new, noninvasive route. This model thus provides a single, powerful framework for quantitative understanding of a wide variety of brain phenomena.

Effect of Low-Level Laser Stimulation on EEG Power in Normal Subjects with Closed Eyes

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Jih-Huah Wu

2013-01-01

Full Text Available In a previous study, we found that the low-level laser (LLL stimulation at the palm with a frequency of 10 Hz was able to induce significant brain activation in normal subjects with opened eyes. However, the electroencephalography (EEG changes to LLL stimulation in subjects with closed eyes have not been studied. In the present study, the laser array stimulator was applied to deliver insensible laser stimulations to the palm of the tested subjects with closed eyes (the laser group. The EEG activities before, during, and after the laser stimulation were collected. The EEG amplitude powers of each EEG frequency band at 19 locations were calculated. These power data were then analyzed by SPSS software using repeated-measure ANOVAs and appropriate posthoc tests. We found a pronounced decrease in the EEG power in alpha-bandwidth during laser simulation and then less decrease in the EEG power in delta-bandwidth in normal subjects with laser stimulation. The EEG power in beta-bandwidth in the right occipital area also decreased significantly in the laser group. We suggest that LLL stimulation might be conducive to falling into sleep in patients with sleep problems.

Sleep, Torpor and Memory Impairment

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Palchykova, S.; Tobler, I.

It is now well known that daily torpor induces a sleep deficit. Djungarian hamsters emerging from this hypometabolic state spend most of the time in sleep. This sleep is characterized by high initial values of EEG slow-wave activity (SWA) that monotonically decline during recovery sleep. These features resemble the changes seen in numerous species during recovery after prolonged wakefulness or sleep deprivation (SD). When hamsters are totally or partially sleep deprived immediately after emerging from torpor, an additional increase in SWA can be induced. It has been therefore postulated, that these slow- waves are homeostatically regulated, as predicted by the two-process model of sleep regulation, and that during daily torpor a sleep deficit is accumulated as it is during prolonged waking. The predominance of SWA in the frontal EEG observed both after SD and daily torpor provides further evidence for the similarity of these conditions. It has been shown in several animal and human studies that sleep can enhance memory consolidation, and that SD leads to memory impairment. Preliminary data obtained in the Djungarian hamster showed that both SD and daily torpor result in object recognition deficits. Thus, animals subjected to SD immediately after learning, or if they underwent an episode of daily torpor between learning and retention, displayed impaired recognition memory for complex object scenes. The investigation of daily torpor can reveal mechanisms that could have important implications for hypometabolic state induction in other mammalian species, including humans.

Sleep in the domestic hen (Gallus domesticus).

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van Luijtelaar, E L; van der Grinten, C P; Blokhuis, H J; Coenen, A M

1987-01-01

Electrophysiological recordings were made of five closely observed hens, all permanently implanted with both EEG and EMG electrodes. Five behavioural postures were distinguished and percentages of wakefulness, sleep and presumably paradoxical sleep (PS) were determined during the third and sixth hour of the dark period. Substantial agreement was generally found between behaviour and sleep with the exception of sitting or standing motionless with at least one eye open. During two thirds of this behavioural posture, the EEG showed large amplitude slow waves undistinguishable from slow wave sleep. Characteristics of PS were determined: periods were short, whereas its percentage increased during the night. Furthermore, EMG atonia was never found. An all night recording was made, and delta activity (2-5 Hz) was filtered and plotted against time for three of the hens. A significant decrease in delta activity across the night was found. Differences and similarities between sleep in hens and in mammals are discussed. Although large similarities exist it is concluded that some properties of birds' sleep make it unique and are a challenge for further study.

Effects of social stimuli on sleep in mice : non-rapid-eye-movement (NREM) sleep is promoted by aggressive interaction but not by sexual interaction

NARCIS (Netherlands)

Meerlo, Peter; Turek, Fred W.

2001-01-01

Sleep is generally considered to be a process of recovery from prior wakefulness. In addition to being affected by the duration of the waking period, sleep architecture and sleep EEG also depend on the quality of wakefulness. In the present experiment, we examined how sleep is affected by different

Global field synchronization in gamma range of the sleep EEG tracks sleep depth: Artifact introduced by a rectangular analysis window.

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Rusterholz, Thomas; Achermann, Peter; Dürr, Roland; Koenig, Thomas; Tarokh, Leila

2017-06-01

Investigating functional connectivity between brain networks has become an area of interest in neuroscience. Several methods for investigating connectivity have recently been developed, however, these techniques need to be applied with care. We demonstrate that global field synchronization (GFS), a global measure of phase alignment in the EEG as a function of frequency, must be applied considering signal processing principles in order to yield valid results. Multichannel EEG (27 derivations) was analyzed for GFS based on the complex spectrum derived by the fast Fourier transform (FFT). We examined the effect of window functions on GFS, in particular of non-rectangular windows. Applying a rectangular window when calculating the FFT revealed high GFS values for high frequencies (>15Hz) that were highly correlated (r=0.9) with spectral power in the lower frequency range (0.75-4.5Hz) and tracked the depth of sleep. This turned out to be spurious synchronization. With a non-rectangular window (Tukey or Hanning window) these high frequency synchronization vanished. Both, GFS and power density spectra significantly differed for rectangular and non-rectangular windows. Previous papers using GFS typically did not specify the applied window and may have used a rectangular window function. However, the demonstrated impact of the window function raises the question of the validity of some previous findings at higher frequencies. We demonstrated that it is crucial to apply an appropriate window function for determining synchronization measures based on a spectral approach to avoid spurious synchronization in the beta/gamma range. Copyright © 2017 Elsevier B.V. All rights reserved.

Acquired auditory agnosia in childhood and normal sleep electroencephalography subsequently diagnosed as Landau-Kleffner syndrome: a report of three cases.

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van Bogaert, Patrick; King, Mary D; Paquier, Philippe; Wetzburger, Catherine; Labasse, Catherine; Dubru, Jean-Marie; Deonna, Thierry

2013-06-01

  We report three cases of Landau-Kleffner syndrome (LKS) in children (two females, one male) in whom diagnosis was delayed because the sleep electroencephalography (EEG) was initially normal.   Case histories including EEG, positron emission tomography findings, and long-term outcome were reviewed.   Auditory agnosia occurred between the age of 2 years and 3 years 6 months, after a period of normal language development. Initial awake and sleep EEG, recorded weeks to months after the onset of language regression, during a nap period in two cases and during a full night of sleep in the third case, was normal. Repeat EEG between 2 months and 2 years later showed epileptiform discharges during wakefulness and strongly activated by sleep, with a pattern of continuous spike-waves during slow-wave sleep in two patients. Patients were diagnosed with LKS and treated with various antiepileptic regimens, including corticosteroids. One patient in whom EEG became normal on hydrocortisone is making significant recovery. The other two patients did not exhibit a sustained response to treatment and remained severely impaired.   Sleep EEG may be normal in the early phase of acquired auditory agnosia. EEG should be repeated frequently in individuals in whom a firm clinical diagnosis is made to facilitate early treatment. © The Authors. Developmental Medicine & Child Neurology © 2012 Mac Keith Press.

Recent progress of neuroimaging studies on sleeping brain

International Nuclear Information System (INIS)

Sasaki, Yuka

2012-01-01

Although sleep is a familiar phenomenon, its functions are yet to be elucidated. Understanding these functions of sleep is an important focus area in neuroscience. Electroencephalography (EEG) has been the predominantly used method in human sleep research but does not provide detailed spatial information about brain activation during sleep. To supplement the spatial information provided by this method, researchers have started using a combination of EEG and various advanced neuroimaging techniques that have been recently developed, including positron emission tomography (PET) and magnetic resonance imaging (MRI). In this paper, we will review the recent progress in sleep studies, especially studies that have used such advanced neuroimaging techniques. First, we will briefly introduce several neuroimaging techniques available for use in sleep studies. Next, we will review the spatiotemporal brain activation patterns during non-rapid eye movement (NREM) and rapid eye movement (REM) sleep, the dynamics of functional connectivity during sleep, and the consolidation of learning and memory during sleep; studies on the neural correlates of dreams, which have not yet been identified, will also be discussed. Lastly, possible directions for future research in this area will be discussed. (author)

[Recent progress of neuroimaging studies on sleeping brain].

Science.gov (United States)

Sasaki, Yuka

2012-06-01

Although sleep is a familiar phenomenon, its functions are yet to be elucidated. Understanding these functions of sleep is an important focus area in neuroscience. Electroencephalography (EEG) has been the predominantly used method in human sleep research but does not provide detailed spatial information about brain activation during sleep. To supplement the spatial information provided by this method, researchers have started using a combination of EEG and various advanced neuroimaging techniques that have been recently developed, including positron emission tomography (PET) and magnetic resonance imaging (MRI). In this paper, we will review the recent progress in sleep studies, especially studies that have used such advanced neuroimaging techniques. First, we will briefly introduce several neuroimaging techniques available for use in sleep studies. Next, we will review the spatiotemporal brain activation patterns during non-rapid eye movement (NREM) and rapid eye movement (REM) sleep, the dynamics of functional connectivity during sleep, and the consolidation of learning and memory during sleep; studies on the neural correlates of dreams, which have not yet been identified, will also be discussed. Lastly, possible directions for future research in this area will be discussed.

Spindle-like thalamocortical synchronization in a rat brain slice preparation.

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Tancredi, V; Biagini, G; D'Antuono, M; Louvel, J; Pumain, R; Avoli, M

2000-08-01

We obtained rat brain slices (550-650 microm) that contained part of the frontoparietal cortex along with a portion of the thalamic ventrobasal complex (VB) and of the reticular nucleus (RTN). Maintained reciprocal thalamocortical connectivity was demonstrated by VB stimulation, which elicited orthodromic and antidromic responses in the cortex, along with re-entry of thalamocortical firing originating in VB neurons excited by cortical output activity. In addition, orthodromic responses were recorded in VB and RTN following stimuli delivered in the cortex. Spontaneous and stimulus-induced coherent rhythmic oscillations (duration = 0.4-3.5 s; frequency = 9-16 Hz) occurred in cortex, VB, and RTN during application of medium containing low concentrations of the K(+) channel blocker 4-aminopyridine (0.5-1 microM). This activity, which resembled electroencephalograph (EEG) spindles recorded in vivo, disappeared in both cortex and thalamus during application of the excitatory amino acid receptor antagonist kynurenic acid in VB (n = 6). By contrast, cortical application of kynurenic acid (n = 4) abolished spindle-like oscillations at this site, but not those recorded in VB, where their frequency was higher than under control conditions. Our findings demonstrate the preservation of reciprocally interconnected cortical and thalamic neuron networks that generate thalamocortical spindle-like oscillations in an in vitro rat brain slice. As shown in intact animals, these oscillations originate in the thalamus where they are presumably caused by interactions between RTN and VB neurons. We propose that this preparation may help to analyze thalamocortical synchronization and to understand the physiopathogenesis of absence attacks.

CAP, epilepsy and motor events during sleep: the unifying role of arousal.

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Parrino, Liborio; Halasz, Peter; Tassinari, Carlo Alberto; Terzano, Mario Giovanni

2006-08-01

Arousal systems play a topical neurophysiologic role in protecting and tailoring sleep duration and depth. When they appear in NREM sleep, arousal responses are not limited to a single EEG pattern but are part of a continuous spectrum of EEG modifications ranging from high-voltage slow rhythms to low amplitude fast activities. The hierarchic features of arousal responses are reflected in the phase A subtypes of CAP (cyclic alternating pattern) including both slow arousals (dominated by the ASDA arousals). CAP is an infraslow oscillation with a periodicity of 20-40s that participates in the dynamic organization of sleep and in the activation of motor events. Physiologic, paraphysiologic and pathologic motor activities during NREM sleep are always associated with a stereotyped arousal pattern characterized by an initial increase in EEG delta power and heart rate, followed by a progressive activation of faster EEG frequencies. These findings suggest that motor patterns are already written in the brain codes (central pattern generators) embraced with an automatic sequence of EEG-vegetative events, but require a certain degree of activation (arousal) to become visibly apparent. Arousal can appear either spontaneously or be elicited by internal (epileptic burst) or external (noise, respiratory disturbance) stimuli. Whether the outcome is a physiologic movement, a muscle jerk or a major epileptic attack will depend on a number of ongoing factors (sleep stage, delta power, neuro-motor network) but all events share the common trait of arousal-activated phenomena.

Unsupervised online classifier in sleep scoring for sleep deprivation studies.

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Libourel, Paul-Antoine; Corneyllie, Alexandra; Luppi, Pierre-Hervé; Chouvet, Guy; Gervasoni, Damien

2015-05-01

This study was designed to evaluate an unsupervised adaptive algorithm for real-time detection of sleep and wake states in rodents. We designed a Bayesian classifier that automatically extracts electroencephalogram (EEG) and electromyogram (EMG) features and categorizes non-overlapping 5-s epochs into one of the three major sleep and wake states without any human supervision. This sleep-scoring algorithm is coupled online with a new device to perform selective paradoxical sleep deprivation (PSD). Controlled laboratory settings for chronic polygraphic sleep recordings and selective PSD. Ten adult Sprague-Dawley rats instrumented for chronic polysomnographic recordings. The performance of the algorithm is evaluated by comparison with the score obtained by a human expert reader. Online detection of PS is then validated with a PSD protocol with duration of 72 hours. Our algorithm gave a high concordance with human scoring with an average κ coefficient > 70%. Notably, the specificity to detect PS reached 92%. Selective PSD using real-time detection of PS strongly reduced PS amounts, leaving only brief PS bouts necessary for the detection of PS in EEG and EMG signals (4.7 ± 0.7% over 72 h, versus 8.9 ± 0.5% in baseline), and was followed by a significant PS rebound (23.3 ± 3.3% over 150 minutes). Our fully unsupervised data-driven algorithm overcomes some limitations of the other automated methods such as the selection of representative descriptors or threshold settings. When used online and coupled with our sleep deprivation device, it represents a better option for selective PSD than other methods like the tedious gentle handling or the platform method. © 2015 Associated Professional Sleep Societies, LLC.

Coupling of Thalamocortical Sleep Oscillations Are Important for Memory Consolidation in Humans.

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Mohammad Niknazar

Full Text Available Sleep, specifically non-rapid eye movement (NREM sleep, is thought to play a critical role in the consolidation of recent memories. Two main oscillatory activities observed during NREM, cortical slow oscillations (SO, 0.5-1.0 Hz and thalamic spindles (12-15 Hz, have been shown to independently correlate with memory improvement. Yet, it is not known how these thalamocortical events interact, or the significance of this interaction, during the consolidation process. Here, we found that systemic administration of the GABAergic drug (zolpidem increased both the phase-amplitude coupling between SO and spindles, and verbal memory improvement in humans. These results suggest that thalamic spindles that occur during transitions to the cortical SO Up state are optimal for memory consolidation. Our study predicts that the timely interactions between cortical and thalamic events during consolidation, contribute to memory improvement and is mediated by the level of inhibitory neurotransmission.

Astrocytic modulation of sleep homeostasis and cognitive consequences of sleep loss.

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Halassa, Michael M; Florian, Cedrick; Fellin, Tommaso; Munoz, James R; Lee, So-Young; Abel, Ted; Haydon, Philip G; Frank, Marcos G

2009-01-29

Astrocytes modulate neuronal activity by releasing chemical transmitters via a process termed gliotransmission. The role of this process in the control of behavior is unknown. Since one outcome of SNARE-dependent gliotransmission is the regulation of extracellular adenosine and because adenosine promotes sleep, we genetically inhibited the release of gliotransmitters and asked if astrocytes play an unsuspected role in sleep regulation. Inhibiting gliotransmission attenuated the accumulation of sleep pressure, assessed by measuring the slow wave activity of the EEG during NREM sleep, and prevented cognitive deficits associated with sleep loss. Since the sleep-suppressing effects of the A1 receptor antagonist CPT were prevented following inhibition of gliotransmission and because intracerebroventricular delivery of CPT to wild-type mice mimicked the transgenic phenotype, we conclude that astrocytes modulate the accumulation of sleep pressure and its cognitive consequences through a pathway involving A1 receptors.

Neurophysiological basis of rapid eye movement sleep behavior disorder

DEFF Research Database (Denmark)

Jennum, Poul; Christensen, Julie Anja Engelhard; Zoetmulder, Marielle

2016-01-01

Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia characterized by a history of recurrent nocturnal dream enactment behavior and loss of skeletal muscle atonia and increased phasic muscle activity during REM sleep: REM sleep without atonia. RBD and associated comorbidities have...... recently been identified as one of the most specific and potentially sensitive risk factors for later development of any of the alpha-synucleinopathies: Parkinson's disease, dementia with Lewy bodies, and other atypical parkinsonian syndromes. Several other sleep-related abnormalities have recently been...... identified in patients with RBD/Parkinson's disease who experience abnormalities in sleep electroencephalographic frequencies, sleep-wake transitions, wake and sleep stability, occurrence and morphology of sleep spindles, and electrooculography measures. These findings suggest a gradual involvement...

Human genetics and sleep behavior.

Science.gov (United States)

Shi, Guangsen; Wu, David; Ptáček, Louis J; Fu, Ying-Hui

2017-06-01

Why we sleep remains one of the greatest mysteries in science. In the past few years, great advances have been made to better understand this phenomenon. Human genetics has contributed significantly to this movement, as many features of sleep have been found to be heritable. Discoveries about these genetic variations that affect human sleep will aid us in understanding the underlying mechanism of sleep. Here we summarize recent discoveries about the genetic variations affecting the timing of sleep, duration of sleep and EEG patterns. To conclude, we also discuss some of the sleep-related neurological disorders such as Autism Spectrum Disorder (ASD) and Alzheimer's Disease (AD) and the potential challenges and future directions of human genetics in sleep research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Correntropy measures to detect daytime sleepiness from EEG signals

International Nuclear Information System (INIS)

Melia, Umberto; Vallverdú, Montserrat; Caminal, Pere; Guaita, Marc; Montserrat, Josep M; Vilaseca, Isabel; Salamero, Manel; Gaig, Carles; Santamaria, Joan

2014-01-01

Excessive daytime sleepiness (EDS) is one of the main symptoms of several sleep related disorders and has a great impact on patients’ lives. While many studies have been carried out in order to assess daytime sleepiness, automatic EDS detection still remains an open problem. In this work, a novel approach to this issue based on correntropy function analysis of EEG signals was proposed in order to detect patients suffering from EDS. Multichannel EEG signals were recorded during five Maintenance of Wakefulness Tests (MWT) and Multiple Sleep Latency Tests (MSLT) alternated throughout the day for patients suffering from sleep disordered breathing (SDB). A group of 20 patients with EDS was compared with a group of 20 patients without daytime sleepiness (WDS), by analyzing 60 s EEG windows in a waking state. Measures obtained from the cross-correntropy function (CCORR) and auto-correntropy function (ACORR) were calculated in the EEG frequency bands: δ, 0.1–4 Hz; θ, 4–8 Hz; α, 8–12 Hz; β, 12–30 Hz; total band TB, 0.1–45 Hz. These functions permitted the quantification of complex signal properties and the non-linear couplings between different areas of the scalp. Statistical differences between EDS and WDS groups were mainly found in the β band during MSLT events (p-value < 0.0001). The WDS group presented more complexity in the occipital zone than the EDS group, while a stronger nonlinear coupling between the occipital and frontal regions was detected in EDS patients than in the WDS group. At best, ACORR and CCORR measures yielded sensitivity and specificity above 80% and the area under ROC curve (AUC) was above 0.85 in classifying EDS and WDS patients. These performances represent an improvement with respect to classical EEG indices applied in the same database (sensitivity and specificity were never above 80% and AUC was under 0.75). (paper)

Interobserver variability in recognizing arousal in respiratory sleep disorders.

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Drinnan, M J; Murray, A; Griffiths, C J; Gibson, G J

1998-08-01

Daytime sleepiness is a common consequence of repeated arousal in obstructive sleep apnea (OSA). Arousal indices are sometimes used to make decisions on treatment, but there is no evidence that arousals are detected similarly even by experienced observers. Using the American Sleep Disorders Association (ASDA) definition of arousal in terms of the accompanying electroencephalogram (EEG) changes, we have quantified interobserver agreement for arousal scoring and identified factors affecting it. Ten patients with suspected OSA were studied; three representative EEG events during each of light, slow-wave, and rapid-eye-movement (REM) sleep were extracted from each record (90 events total) and evaluated by experts in 14 sleep laboratories. Observers differed (ANOVA, p ASDA definition of arousal is only moderately repeatable. Account should be taken of this variability when results from different centers are compared.

Imaging the dorsal hippocampus: light reflectance relationships to electroencephalographic patterns during sleep

DEFF Research Database (Denmark)

Rector, D M; Poe, G R; Kristensen, Morten Pilgaard

1995-01-01

We assessed the correspondence of 660 nm light reflectance changes from the dorsal hippocampus with slow wave electroencephalographic (EEG) activity during quiet sleep (QS) and rapid eye movement (REM) sleep in four cats. An optic probe, attached to a charge-coupled-device (CCD) video camera...... as EEG changes. Dividing the image into 10 subregions revealed that reflectance changes at the rhythmical slow wave activity band (RSA, 4-6 Hz) persisted in localized regions during QS and REM sleep, but regional changes showed considerable wave-by-wave independence between areas and from slow wave...

Wireless sleep monitoring headband to identify sleep and track fatigue

Science.gov (United States)

Ramasamy, Mouli; Oh, Sechang; Varadan, Vijay K.

2014-04-01

Detection of sleepiness and drowsiness in human beings has been a daunting task for both engineering and medical technologies. Accuracy, precision and promptness of detection have always been an issue that has to be dealt by technologists. Commonly, the rudimentary bio potential signals - ECG, EOG, EEG and EMG are used to classify and discriminate sleep from being awake. However, the potential drawbacks may be high false detections, low precision, obtrusiveness, aftermath analysis, etc. To overcome the disadvantages, this paper proposes the design of a wireless and a real time monitoring system to track sleep and detect fatigue. This concept involves the use of EOG and EEG to measure the blink rate and asses the person's condition. In this user friendly and intuitive approach, EOG and EEG signals are obtained by the dry gold wire nano-sensors fabricated on the inner side of a flexible headband. The acquired signals are then electrically transmitted to the data processing and transmission unit, which transmits the processed data to the receiver/monitoring module through WCDMA/GSM communication. This module is equipped with a software program to process, feature extract, analyze, display and store the information. Thereby, immediate detection of a person falling asleep is made feasible and, tracking the sleep cycle continuously provides an insight about the experienced fatigue level. The novel approach of using a wireless, real time, dry sensor on a flexible substrate reduces the obtrusiveness, and techniques adopted in the electronics and software facilitates and substantial increase in efficiency, accuracy and precision.

WARMING UP FOR SLEEP - GROUND-SQUIRRELS SLEEP DURING AROUSALS FROM HIBERNATION

NARCIS (Netherlands)

DAAN, S; BARNES, BM; STRIJKSTRA, AM

1991-01-01

Hypothermia during mammalian hibernation is periodically interrupted by arousals to euthermy, the function of which is unknown. We report that arctic ground squirrels (Spermophilus parryii) consistently sleep during these arousals, and that their EEG shows the decrease in slow wave activity

Sleep physiology in toddlers: Effects of missing a nap on subsequent night sleep

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Jonathan M. Lassonde

2016-10-01

Full Text Available The shift from a biphasic to a monophasic sleep schedule is a fundamental milestone in early childhood. This transition, however, may result in periods of acute sleep loss as children may nap on some but not all days. Although data indicating the behavioral consequences of nap deprivation in young children are accumulating, little is known about changes to sleep neurophysiology following daytime sleep loss. This study addresses this gap in knowledge by examining the effects of acute nap deprivation on subsequent nighttime sleep electroencephalographic (EEG parameters in toddlers. Healthy children (n=25; 11 males; ages 30–36 months followed a strict sleep schedule for ≥5 days before sleep EEG recordings performed on 2 non-consecutive days: one after 13 h of prior wakefulness and another at the same clock time but preceded by a daytime nap. Total slow-wave energy (SWE was computed as cumulative slow-wave activity (SWA; EEG power in 0.75–4.5 Hz range over time. Nap and subsequent night SWE were added and compared to SWE of the night after a missed nap. During the night following a missed nap, children fell asleep faster (11.9±8.7 min versus 37.3±22.1 min; d=1.6, p=0.01, slept longer (10.1±0.7 h versus 9.6±0.6 h; d=0.7, p<0.01 and exhibited greater SWA (133.3±37.5% versus 93.0±4.7%; d=0.9, p<0.01 compared to a night after a daytime nap. SWE for combined nap and subsequent night sleep did not significantly differ from the night following nap deprivation (12141.1±3872.9 μV²*h versus 11,588±3270.8 μV²*h; d=0.6, p=0.12. However, compared to a night following a missed nap, children experienced greater time in bed (13.0±0.8 h versus 10.9±0.5 h; d=3.1, p<0.01 and total sleep time (11.2±0.8 h versus 10.1±0.7 h; d=1.4, p<0.01. Shorter sleep latency, longer sleep duration, and increased SWA in the night following a missed nap indicate that toddlers experience a physiologically meaningful homeostatic challenge after prolonged

Ultradian rhythms in pituitary and adrenal hormones: their relations to sleep.

Science.gov (United States)

Gronfier, C; Brandenberger, G

1998-02-01

Sleep and circadian rhythmicity both influence the 24-h profiles of the main pituitary and adrenal hormones. From studies using experimental strategies including complete and partial sleep deprivation, acute and chronic shifts in the sleep period, or complete sleep-wake reversal as occurs with transmeridian travel or shift-work, it appears that prolactin (PRL) and growth hormone (GH) profiles are mainly sleep related, while cortisol profile is mainly controlled by the circadian clock with a weak influence of sleep processes. Thyrotropin (TSH) profile is under the dual influence of sleep and circadian rhythmicity. Recent studies, in which we used spectral analysis of sleep electroencephalogram (EEG) rather than visual scoring of sleep stages, have evaluated the temporal associations between pulsatile hormonal release and the variations in sleep EEG activity. Pulses in PRL and in GH are positively linked to increases in delta wave activity, whereas TSH and cortisol pulses are related to decreases in delta wave activity. It is yet not clear whether sleep influences endocrine secretion, or conversely, whether hormone secretion affects sleep structure. These well-defined relationships raise the question of their physiological significance and of their clinical implications.

Increased Arousal Levels and Decreased Sleep by Brain Music in Rats

Institute of Scientific and Technical Information of China (English)

Guang-Zhan Fang; Chun-Peng Zhang; Dan Wu; Yang Xia; Yong-Xiu Lai; De-Zhong Yao

2009-01-01

More and more studies have been reported on whether music and other types of auditory stimulation would improve the quality of sleep.Many of these studies have found significant results,but others argue that music is not significantly better than the tones or control conditions in improving sleep.For further understanding the relationship between music and sleep or music and arousal,the present study therefore examines the effects of brain music on sleep and arousal by means of biofeedback.The music is from the transformation of rapid eye movement (REM) sleep electroencephalogram (EEG) of rats using an algorithm in the Chengdu Brain Music (CBM) system.When the brain music was played back to rats,EEG data were recorded to assess the efficacy of music to induce or improve sleep,or increase arousal levels by sleep staging,etc.Our results demonstrate that exposure to the brain music increases arousal levels and decreases sleep in rats,and the underlying mechanism of decreased non-rapid eye movement (NREM) and REM sleep may be different.

Effects of carbamazepine on dexamethasone suppression and sleep electroencephalography in borderline personality disorder.

Science.gov (United States)

De la Fuente, José M; Bobes, Julio; Vizuete, Coro; Mendlewicz, Julien

2002-01-01

The pathophysiology of borderline personality disorder (BPD) remains obscure, but there is mounting evidence of brain dysfunction without focal abnormality. The dexamethasone suppression test (DST) and sleep electroencephalography (sleep EEG) have been studied in BPD, but the findings seem to be related to a concomitant axis I diagnosis of major depression (MD) rather than to BPD itself. There is no effective treatment for BPD. Carbamazepine (CBZ) has shown contradictory results and in a previous study, our results were negative. In this study, we investigated the effects of CBZ versus placebo on the DST and sleep EEG in a sample of 20 BPD patients without concomitant MD. CBZ given at doses that are therapeutic for epilepsy and affective disorders may have an effect on the DST and sleep EEG in BPD. CBZ significantly increased the postdexamethasone plasma cortisol values. This did not parallel MD or an increase in the Hamilton depression rating scores. CBZ also increased slow wave sleep (SWS). The mechanisms by which CBZ increased postdexamethasone plasma cortisol levels and SWS in BPD are discussed. Copyright 2002 S. Karger AG, Basel

Predictable Internal Brain Dynamics in EEG and Its Relation to Conscious States

Directory of Open Access Journals (Sweden)

Jaewook eYoo

2014-06-01

Full Text Available Consciousness is a complex and multi-faceted phenomenon defying scientific explanation. Part of the reason why this is the case is due to its subjective nature. In our previous computational experiments, to avoid such a subjective trap, we took a strategy to investigate objective necessary conditions of consciousness. Our basic hypothesis was that predictive internal dynamics serves as such a condition. This is in line with theories of consciousness that treat retention (memory, protention (anticipation, and primary impression as the tripartite temporal structure of consciousness. To test our hypothesis, we analyzed publicly available sleep and awake electroencephalogram (EEG data. Our results show that EEG signals from awake or rapid eye movement (REM sleep states have more predictable dynamics compared to those from slow-wave sleep (SWS. Since awakeness and REM sleep are associated with conscious states and SWS with unconscious or less consciousness states, these results support our hypothesis. The results suggest an intricate relationship among prediction, consciousness, and time, with potential applications to time perception and neurorobotics.

The diagnostic value of power spectra analysis of the sleep electroencephalography in narcoleptic patients

DEFF Research Database (Denmark)

Christensen, Julie Anja Engelhard; Munk, Emil Gammelmark Schreiner; Peppard, Paul E.

2015-01-01

Objective: Manifestations of narcolepsy with cataplexy (NC) include disturbed nocturnal sleep – hereunder sleep–wake instability, decreased latency to rapid eye movement (REM) sleep, and dissociated REM sleep events. In this study, we characterized the electroencephalography (EEG) of various sleep...... show (1) increased alpha power in REM sleep, (2) decreased sigma power in wakefulness, and (3) decreased delta power in stage N1 versus wakefulness. Sensitivity of these features ranged from 4% to 10% with specificity around 98%, and it did not vary substantially with and without treatment. Conclusions......: EEG spectral analysis of REM sleep, wake, and differences between N1 and wakefulness contain diagnostic features of NC. These traits may represent sleepiness and dissociated REM sleep in patients with NC. However, the features are not sufficient for differentiating NC from controls, and further...

Consistently high sports/exercise activity is associated with better sleep quality, continuity and depth in midlife women: the SWAN sleep study.

Science.gov (United States)

Kline, Christopher E; Irish, Leah A; Krafty, Robert T; Sternfeld, Barbara; Kravitz, Howard M; Buysse, Daniel J; Bromberger, Joyce T; Dugan, Sheila A; Hall, Martica H

2013-09-01

To examine relationships between different physical activity (PA) domains and sleep, and the influence of consistent PA on sleep, in midlife women. Cross-sectional. Community-based. 339 women in the Study of Women's Health Across the Nation Sleep Study (52.1 ± 2.1 y). None. Sleep was examined using questionnaires, diaries and in-home polysomnography (PSG). PA was assessed in three domains (Active Living, Household/Caregiving, Sports/Exercise) using the Kaiser Physical Activity Survey (KPAS) up to 4 times over 6 years preceding the sleep assessments. The association between recent PA and sleep was evaluated using KPAS scores immediately preceding the sleep assessments. The association between the historical PA pattern and sleep was examined by categorizing PA in each KPAS domain according to its pattern over the 6 years preceding sleep assessments (consistently low, inconsistent/consistently moderate, or consistently high). Greater recent Sports/Exercise activity was associated with better sleep quality (diary "restedness" [P sleep continuity (diary sleep efficiency [SE; P = 0.02]) and depth (higher NREM delta electroencephalographic [EEG] power [P = 0.04], lower NREM beta EEG power [P Sports/Exercise activity was also associated with better Pittsburgh Sleep Quality Index scores (P = 0.02) and higher PSG-assessed SE (P sleep and Active Living or Household/Caregiving activity (either recent or historical pattern) were noted. Consistently high levels of recreational physical activity, but not lifestyle- or household-related activity, are associated with better sleep in midlife women. Increasing recreational physical activity early in midlife may protect against sleep disturbance in this population.

Social stress induces high intensity sleep in rats

NARCIS (Netherlands)

Meerlo, P; Pragt, Bertrand J.; Daan, S

1997-01-01

We studied the effect of social stress on sleep electroencephalogram (EEG) in rats. Animals were subjected to a single social defeat by introducing them in the cage of an aggressive male conspecific for 1 h. The animals responded to the social conflict by a sharp increase in EEG slow-wave activity

Chronic widespread musculoskeletal pain, fatigue, depression and disordered sleep in chronic post-SARS syndrome; a case-controlled study.

Science.gov (United States)

Moldofsky, Harvey; Patcai, John

2011-03-24

The long term adverse effects of Severe Acute Respiratory Syndrome (SARS), a viral disease, are poorly understood. Sleep physiology, somatic and mood symptoms of 22 Toronto subjects, 21 of whom were healthcare workers, (19 females, 3 males, mean age 46.29 yrs.+/- 11.02) who remained unable to return to their former occupation (mean 19.8 months, range: 13 to 36 months following SARS) were compared to 7 healthy female subjects. Because of their clinical similarities to patients with fibromyalgia syndrome (FMS) these post-SARS subjects were similarly compared to 21 drug free female patients, (mean age 42.4 +/- 11.8 yrs.) who fulfilled criteria for fibromyalgia. Chronic post-SARS is characterized by persistent fatigue, diffuse myalgia, weakness, depression, and nonrestorative sleep with associated REM-related apneas/hypopneas, an elevated sleep EEG cyclical alternating pattern, and alpha EEG sleep anomaly. Post- SARS patients had symptoms of pre and post-sleep fatigue and post sleep sleepiness that were similar to the symptoms of patients with FMS, and similar to symptoms of patients with chronic fatigue syndrome. Both post-SARS and FMS groups had sleep instability as indicated by the high sleep EEG cyclical alternating pattern rate. The post-SARS group had a lower rating of the alpha EEG sleep anomaly as compared to the FMS patients. The post-SARS group also reported less pre-sleep and post-sleep musculoskeletal pain symptoms. The clinical and sleep features of chronic post-SARS form a syndrome of chronic fatigue, pain, weakness, depression and sleep disturbance, which overlaps with the clinical and sleep features of FMS and chronic fatigue syndrome.

Automatic sleep classification using a data-driven topic model reveals latent sleep states

DEFF Research Database (Denmark)

Koch, Henriette; Christensen, Julie Anja Engelhard; Frandsen, Rune

2014-01-01

Latent Dirichlet Allocation. Model application was tested on control subjects and patients with periodic leg movements (PLM) representing a non-neurodegenerative group, and patients with idiopathic REM sleep behavior disorder (iRBD) and Parkinson's Disease (PD) representing a neurodegenerative group......Background: The golden standard for sleep classification uses manual scoring of polysomnography despite points of criticism such as oversimplification, low inter-rater reliability and the standard being designed on young and healthy subjects. New method: To meet the criticism and reveal the latent...... sleep states, this study developed a general and automatic sleep classifier using a data-driven approach. Spectral EEG and EOG measures and eye correlation in 1 s windows were calculated and each sleep epoch was expressed as a mixture of probabilities of latent sleep states by using the topic model...

Characterisation of the Effects of Sleep Deprivation on the Electroencephalogram Using Permutation Lempel–Ziv Complexity, a Non-Linear Analysis Tool

Directory of Open Access Journals (Sweden)

Pinar Deniz Tosun

2017-12-01

Full Text Available Specific patterns of brain activity during sleep and waking are recorded in the electroencephalogram (EEG. Time-frequency analysis methods have been widely used to analyse the EEG and identified characteristic oscillations for each vigilance state (VS, i.e., wakefulness, rapid-eye movement (REM and non-rapid-eye movement (NREM sleep. However, other aspects such as change of patterns associated with brain dynamics may not be captured unless a non-linear-based analysis method is used. In this pilot study, Permutation Lempel–Ziv complexity (PLZC, a novel symbolic dynamics analysis method, was used to characterise the changes in the EEG in sleep and wakefulness during baseline and recovery from sleep deprivation (SD. The results obtained with PLZC were contrasted with a related non-linear method, Lempel–Ziv complexity (LZC. Both measure the emergence of new patterns. However, LZC is dependent on the absolute amplitude of the EEG, while PLZC is only dependent on the relative amplitude due to symbolisation procedure and thus, more resistant to noise. We showed that PLZC discriminates activated brain states associated with wakefulness and REM sleep, which both displayed higher complexity, compared to NREM sleep. Additionally, significantly lower PLZC values were measured in NREM sleep during the recovery period following SD compared to baseline, suggesting a reduced emergence of new activity patterns in the EEG. These findings were validated using PLZC on surrogate data. By contrast, LZC was merely reflecting changes in the spectral composition of the EEG. Overall, this study implies that PLZC is a robust non-linear complexity measure, which is not dependent on amplitude variations in the signal, and which may be useful to further assess EEG alterations induced by environmental or pharmacological manipulations.

A prospective study of levetiracetam efficacy in epileptic syndromes with continuous spikes-waves during slow sleep

DEFF Research Database (Denmark)

Atkins, Mary; Nikanorova, Marina

2011-01-01

To evaluate the add-on effect of levetiracetam (LEV) treatment on the EEG and clinical status of children with continuous spikes-waves during slow sleep (CSWS).......To evaluate the add-on effect of levetiracetam (LEV) treatment on the EEG and clinical status of children with continuous spikes-waves during slow sleep (CSWS)....

Individual Differences in White Matter Diffusion Affect Sleep Oscillations

NARCIS (Netherlands)

Piantoni, G.; Poil, S.S.; Linkenkaer-Hansen, K.; Verweij, I.M.; Ramautar, J.R.; van Someren, E.J.W.; van der Werf, Y.D.

2013-01-01

The characteristic oscillations of the sleeping brain, spindles and slow waves, show trait-like, within-subject stability and a remarkable interindividual variability that correlates with functionally relevant measures such as memory performance and intelligence. Yet, the mechanisms underlying these

Monitoring sleep depth: analysis of bispectral index (BIS) based on polysomnographic recordings and sleep deprivation.

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Giménez, Sandra; Romero, Sergio; Alonso, Joan Francesc; Mañanas, Miguel Ángel; Pujol, Anna; Baxarias, Pilar; Antonijoan, Rosa Maria

2017-02-01

The assessment and management of sleep are increasingly recommended in the clinical practice. Polysomnography (PSG) is considered the gold standard test to monitor sleep objectively, but some practical and technical constraints exist due to environmental and patient considerations. Bispectral index (BIS) monitoring is commonly used in clinical practice for guiding anesthetic administration and provides an index based on relationships between EEG components. Due to similarities in EEG synchronization between anesthesia and sleep, several studies have assessed BIS as a sleep monitor with contradictory results. The aim of this study was to evaluate objectively both the feasibility and reliability of BIS for sleep monitoring through a robust methodology, which included full PSG recordings at a baseline situation and after 40 h of sleep deprivation. Results confirmed that the BIS index was highly correlated with the hypnogram (0.89 ± 0.02), showing a progressive decrease as sleep deepened, and an increase during REM sleep (awake: 91.77 ± 8.42; stage N1: 83.95 ± 11.05; stage N2: 71.71 ± 11.99; stage N3: 42.41 ± 9.14; REM: 80.11 ± 8.73). Mean and median BIS values were lower in the post-deprivation night than in the baseline night, showing statistical differences for the slow wave sleep (baseline: 42.41 ± 9.14 vs. post-deprivation: 39.49 ± 10.27; p = 0.02). BIS scores were able to discriminate properly between deep (N3) and light (N1, N2) sleep. BIS values during REM overlapped those of other sleep stages, although EMG activity provided by the BIS monitor could help to identify REM sleep if needed. In conclusion, BIS monitors could provide a useful measure of sleep depth in especially particular situations such as intensive care units, and they could be used as an alternative for sleep monitoring in order to reduce PSG-derived costs and to increase capacity in ambulatory care.

[Pharmacology of a new sleep inducer, 1H-1,2,4-triazolyl benzophenone derivative, 450191-S (II). Sleep-inducing activity and effect on the motor system].

Science.gov (United States)

Yamamoto, K; Matsushita, A; Sawada, T; Naito, Y; Yoshimura, K; Takesue, H; Utsumi, S; Kawasaki, K; Hirono, S; Koshida, H

1984-07-01

The sleep-inducing activity and effect on the motor system of the 1H-1,2,4-triazolyl benzophenone derivative 450191-S were examined behaviorally, electroencephalographically and electro-physiologically with various species of animals and were compared with those of diazepam, nitrazepam, estazolam and triazolam. In the rhesus monkey, rabbit and rat with chronically indwelling brain electrodes, 0.6 to 3 mg/kg, p.o. of 450191-S caused a shorter latency of sleep onset, an increase of and a stable continuity of slow wave deep sleep (SWDS) with higher amplitude, and the appearance of clear spindle bursts in the slow wave light sleeping (SWLS) state with little muscle relaxation. Animals treated with nitrazepam and/or estazolam showed a smaller increase in SWDS and its unstable continuity with remarkable disturbance of gait. The doses needed to induce sleep in the rhesus monkey were 0.6 to 1 mg/kg p.o. for 450191-S, 3 mg/kg for nitrazepam, 1 mg/kg for estazolam and 0.3 mg/kg for triazolam. The cat treated with 450191-S showed the phenomena caused by benzodiazepines (BDZ), i.e., behavioral excitation and decrease of frequencies in the hippocampal theta waves. The suppressive effects of 450191-S on the EEG arousal reaction and/or blood pressure elevation induced by hypothalamic stimulation in the rabbit suggested that the inhibitory effects acted on the posterior hypothalamus to the limbic system. The inhibitory effect of 450191-S on the amygdaloid kindling in the rat was as potent as those of diazepam and nitrazepam. Successive daily oral administration of both 3 mg/kg of 450191-S and/or 3 to 6 mg/kg of nitrazepam for 15 days in the rabbit caused slight decrease of SWDS and increase of fast wave (REM) sleep (FWS). During the withdrawal period of both compounds, a slight but insignificant increase in the waking state was noticed for 1 to 2 days, but not a rebound increase of FWS. Intravenously administered 450191-S showed the same action as BDZ on the spinal reflex and the

Regional Patterns of Elevated Alpha and High-Frequency Electroencephalographic Activity during Nonrapid Eye Movement Sleep in Chronic Insomnia: A Pilot Study.

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Riedner, Brady A; Goldstein, Michael R; Plante, David T; Rumble, Meredith E; Ferrarelli, Fabio; Tononi, Giulio; Benca, Ruth M

2016-04-01

To examine nonrapid eye movement (NREM) sleep in insomnia using high-density electroencephalography (EEG). All-night sleep recordings with 256 channel high-density EEG were analyzed for 8 insomnia subjects (5 females) and 8 sex and age-matched controls without sleep complaints. Spectral analyses were conducted using unpaired t-tests and topographical differences between groups were assessed using statistical non-parametric mapping. Five minute segments of deep NREM sleep were further analyzed using sLORETA cortical source imaging. The initial topographic analysis of all-night NREM sleep EEG revealed that insomnia subjects had more high-frequency EEG activity (> 16 Hz) compared to good sleeping controls and that the difference between groups was widespread across the scalp. In addition, the analysis also showed that there was a more circumscribed difference in theta (4-8 Hz) and alpha (8-12 Hz) power bands between groups. When deep NREM sleep (N3) was examined separately, the high-frequency difference between groups diminished, whereas the higher regional alpha activity in insomnia subjects persisted. Source imaging analysis demonstrated that sensory and sensorimotor cortical areas consistently exhibited elevated levels of alpha activity during deep NREM sleep in insomnia subjects relative to good sleeping controls. These results suggest that even during the deepest stage of sleep, sensory and sensorimotor areas in insomnia subjects may still be relatively active compared to control subjects and to the rest of the sleeping brain. © 2016 Associated Professional Sleep Societies, LLC.

Accuracy of Spindle Units with Hydrostatic Bearings

Directory of Open Access Journals (Sweden)

Fedorynenko Dmytro

2016-06-01

Full Text Available The work is devoted to the research of precision regularities in a spindle unit by the trajectory of the spindle installed on hydrostatic bearings. The mathematical model of trajectories spindle with lumped parameters that allows to define the position of the spindle with regard the simultaneous influence of design parameters, geometrical deviations ofform, temperature deformation bearing surfaces, the random nature of operational parameters and technical loads of hydrostatic bearings has been developed. Based on the results of numerical modeling the influence of shape errors of bearing surface of hydrostatic bearing on the statistical characteristics of the radius vector trajectories of the spindle by varying the values rotational speed of the spindle and oil pressure in front hydrostatic bearing has been developed. The obtained statistical regularities of precision spindle unit have been confirmed experimentally. It has been shown that an effective way to increase the precision of spindle units is to regulate the size of the gap in hydrostatic spindle bearings. The new design of an adjustable hydrostatic bearing, which can improve the accuracy of regulation size gap has been proposed.

Automatic SLEEP staging: From young aduslts to elderly patients using multi-class support vector machine

DEFF Research Database (Denmark)

Kempfner, Jacob; Jennum, Poul; Sorensen, Helge B. D.

2013-01-01

an automatic sleep stage detector, which can separate wakefulness, rapid-eye-movement (REM) sleep and non-REM (NREM) sleep using only EEG and EOG. Most sleep events, which define the sleep stages, are reduced with age. This is addressed by focusing on the amplitude of the clinical EEG bands......Aging is a process that is inevitable, and makes our body vulnerable to age-related diseases. Age is the most consistent factor affecting the sleep structure. Therefore, new automatic sleep staging methods, to be used in both of young and elderly patients, are needed. This study proposes......, and not the affected sleep events. The age-related influences are then reduced by robust subject-specific scaling. The classification of the three sleep stages are achieved by a multi-class support vector machine using the one-versus-rest scheme. It was possible to obtain a high classification accuracy of 0...

Sleep for cognitive enhancement

Directory of Open Access Journals (Sweden)

Susanne eDiekelmann

2014-04-01

Full Text Available Sleep is essential for effective cognitive functioning. Loosing even a few hours of sleep can have detrimental effects on a wide variety of cognitive processes such as attention, language, reasoning, decision making, learning and memory. While sleep is necessary to ensure normal healthy cognitive functioning, it can also enhance performance beyond the boundaries of the normal condition. This article discusses the enhancing potential of sleep, mainly focusing on the domain of learning and memory. Sleep is known to facilitate the consolidation of memories learned before sleep as well as the acquisition of new memories to be learned after sleep. According to a widely held model this beneficial effect of sleep relies on the neuronal reactivation of memories during sleep that is associated with sleep-specific brain oscillations (slow oscillations, spindles, ripples as well as a characteristic neurotransmitter milieu. Recent research indicates that memory processing during sleep can be boosted by (i cueing memory reactivation during sleep, (ii stimulating sleep-specific brain oscillations, and (iii targeting specific neurotransmitter systems pharmacologically. Olfactory and auditory cues can be used, for example, to increase reactivation of associated memories during post-learning sleep. Intensifying neocortical slow oscillations (the hallmark of slow wave sleep by electrical or auditory stimulation and modulating specific neurotransmitters such as noradrenaline and glutamate likewise facilitates memory processing during sleep. With this evidence in mind, this article concludes by discussing different methodological caveats and ethical issues that should be considered when thinking about using sleep for cognitive enhancement in everyday applications.

Deletion of the Snord116/SNORD116 Alters Sleep in Mice and Patients with Prader-Willi Syndrome.

Science.gov (United States)

Lassi, Glenda; Priano, Lorenzo; Maggi, Silvia; Garcia-Garcia, Celina; Balzani, Edoardo; El-Assawy, Nadia; Pagani, Marco; Tinarelli, Federico; Giardino, Daniela; Mauro, Alessandro; Peters, Jo; Gozzi, Alessandro; Grugni, Graziano; Tucci, Valter

2016-03-01

Sleep-wake disturbances are often reported in Prader-Willi syndrome (PWS), a rare neurodevelopmental syndrome that is associated with paternally-expressed genomic imprinting defects within the human chromosome region 15q11-13. One of the candidate genes, prevalently expressed in the brain, is the small nucleolar ribonucleic acid-116 (SNORD116). Here we conducted a translational study into the sleep abnormalities of PWS, testing the hypothesis that SNORD116 is responsible for sleep defects that characterize the syndrome. We studied sleep in mutant mice that carry a deletion of Snord116 at the orthologous locus (mouse chromosome 7) of the human PWS critical region (PWScr). In particular, we assessed EEG and temperature profiles, across 24-h, in PWScr (m+/p-) heterozygous mutants compared to wild-type littermates. High-resolution magnetic resonance imaging (MRI) was performed to explore morphoanatomical differences according to the genotype. Moreover, we complemented the mouse work by presenting two patients with a diagnosis of PWS and characterized by atypical small deletions of SNORD116. We compared the individual EEG parameters of patients with healthy subjects and with a cohort of obese subjects. By studying the mouse mutant line PWScr(m+/p-), we observed specific rapid eye movement (REM) sleep alterations including abnormal electroencephalograph (EEG) theta waves. Remarkably, we observed identical sleep/EEG defects in the two PWS cases. We report brain morphological abnormalities that are associated with the EEG alterations. In particular, mouse mutants have a bilateral reduction of the gray matter volume in the ventral hippocampus and in the septum areas, which are pivotal structures for maintaining theta rhythms throughout the brain. In PWScr(m+/p-) mice we also observed increased body temperature that is coherent with REM sleep alterations in mice and human patients. Our study indicates that paternally expressed Snord116 is involved in the 24-h regulation of

Detecting interictal discharges in first seizure patients: ambulatory EEG or EEG after sleep deprivation?

NARCIS (Netherlands)

Geut, I.; Weenink, S.; Knottnerus, I.L.H.; van Putten, Michel J.A.M.

2017-01-01

Purpose Uncertainty about recurrence after a first unprovoked seizure is a significant psychological burden for patients, and motivates the need for diagnostic tools with high sensitivity and specificity to assess recurrence risk. As the sensitivity of a routine EEG after a first unprovoked seizure

Bottom-Up versus Top-Down Induction of Sleep by Zolpidem Acting on Histaminergic and Neocortex Neurons

Science.gov (United States)

Uygun, David S.; Ye, Zhiwen; Zecharia, Anna Y.; Harding, Edward C.; Yu, Xiao; Yustos, Raquel; Vyssotski, Alexei L.; Brickley, Stephen G.

2016-01-01

Zolpidem, a GABAA receptor-positive modulator, is the gold-standard drug for treating insomnia. Zolpidem prolongs IPSCs to decrease sleep latency and increase sleep time, effects that depend on α2 and/or α3 subunit-containing receptors. Compared with natural NREM sleep, zolpidem also decreases the EEG power, an effect that depends on α1 subunit-containing receptors, and which may make zolpidem-induced sleep less optimal. In this paper, we investigate whether zolpidem needs to potentiate only particular GABAergic pathways to induce sleep without reducing EEG power. Mice with a knock-in F77I mutation in the GABAA receptor γ2 subunit gene are zolpidem-insensitive. Using these mice, GABAA receptors in the frontal motor neocortex and hypothalamic (tuberomammillary nucleus) histaminergic-neurons of γ2I77 mice were made selectively sensitive to zolpidem by genetically swapping the γ2I77 subunits with γ2F77 subunits. When histamine neurons were made selectively zolpidem-sensitive, systemic administration of zolpidem shortened sleep latency and increased sleep time. But in contrast to the effect of zolpidem on wild-type mice, the power in the EEG spectra of NREM sleep was not decreased, suggesting that these EEG power-reducing effects of zolpidem do not depend on reduced histamine release. Selective potentiation of GABAA receptors in the frontal cortex by systemic zolpidem administration also reduced sleep latency, but less so than for histamine neurons. These results could help with the design of new sedatives that induce a more natural sleep. SIGNIFICANCE STATEMENT Many people who find it hard to get to sleep take sedatives. Zolpidem (Ambien) is the most widely prescribed “sleeping pill.” It makes the inhibitory neurotransmitter GABA work better at its receptors throughout the brain. The sleep induced by zolpidem does not resemble natural sleep because it produces a lower power in the brain waves that occur while we are sleeping. We show using mouse genetics

Characterization of Sleep Using Bispectral Analysis

National Research Council Canada - National Science Library

McPherson, Cameron

2001-01-01

This study investigated the relationship between a Bispectral Index (BIS), as measured by Aspect Medical Systems' A-1000 EEG monitor, and clinical sleep staging based on the Rechtschaffen and Kales (RK...

Sleep-related modifications of EEG connectivity in the sensory-motor networks in Huntington Disease: An eLORETA study and review of the literature.

Science.gov (United States)

Piano, Carla; Imperatori, Claudio; Losurdo, Anna; Bentivoglio, Anna Rita; Cortelli, Pietro; Della Marca, Giacomo

2017-07-01

To evaluate EEG functional connectivity in the sensory-motor network, during wake and sleep, in patients with Huntington Disease (HD). 23 patients with HD and 23 age- and sex-matched healthy controls were enrolled. EEG connectivity analysis was performed by means of exact Low Resolution Electric Tomography (eLORETA). In wake, HD patients showed an increase of delta lagged phase synchronization (T=3.60; p<0.05) among Broadman's Areas (BA) 6-8 bilaterally; right BA 6-8 and right BA 1-2-3; left BA 1-2-3 and left BA 4. In NREM, HD patients showed an increase of delta lagged phase synchronization (T=3.56; p<0.05) among left BA 1-2-3 and right BA 6-8. In REM, HD patients showed an increase of lagged phase synchronization (T=3.60; p<0.05) among the BA 6-8 bilaterally (delta band); left BA 1-2-3 and right BA 1-2-3 (theta); left BA 1-2-3 and right BA 4 (theta); left BA 1-2-3 and right BA 1-2-3 (alpha). Our results may reflect an abnormal function of the motor areas or an effort to counterbalance the pathological motor output. Our results may help to understand the pathophysiology of sleep-related movement disorders in Huntington's Disease, and to define therapeutically strategies. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Enhanced Memory Consolidation Via Automatic Sound Stimulation During Non-REM Sleep.

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Leminen, Miika M; Virkkala, Jussi; Saure, Emma; Paajanen, Teemu; Zee, Phyllis C; Santostasi, Giovanni; Hublin, Christer; Müller, Kiti; Porkka-Heiskanen, Tarja; Huotilainen, Minna; Paunio, Tiina

2017-03-01

Slow-wave sleep (SWS) slow waves and sleep spindle activity have been shown to be crucial for memory consolidation. Recently, memory consolidation has been causally facilitated in human participants via auditory stimuli phase-locked to SWS slow waves. Here, we aimed to develop a new acoustic stimulus protocol to facilitate learning and to validate it using different memory tasks. Most importantly, the stimulation setup was automated to be applicable for ambulatory home use. Fifteen healthy participants slept 3 nights in the laboratory. Learning was tested with 4 memory tasks (word pairs, serial finger tapping, picture recognition, and face-name association). Additional questionnaires addressed subjective sleep quality and overnight changes in mood. During the stimulus night, auditory stimuli were adjusted and targeted by an unsupervised algorithm to be phase-locked to the negative peak of slow waves in SWS. During the control night no sounds were presented. Results showed that the sound stimulation increased both slow wave (p = .002) and sleep spindle activity (p memory performance was compared between stimulus and control nights, we found a significant effect in word pair task but not in other memory tasks. The stimulation did not affect sleep structure or subjective sleep quality. We showed that the memory effect of the SWS-targeted individually triggered single-sound stimulation is specific to verbal associative memory. Moreover, the ambulatory and automated sound stimulus setup was promising and allows for a broad range of potential follow-up studies in the future. © Sleep Research Society 2017. Published by Oxford University Press [on behalf of the Sleep Research Society].

Train hard, sleep well? Perceived training load, sleep quantity and sleep stage distribution in elite level athletes.

Science.gov (United States)

Knufinke, Melanie; Nieuwenhuys, Arne; Geurts, Sabine A E; Møst, Els I S; Maase, Kamiel; Moen, Maarten H; Coenen, Anton M L; Kompier, Michiel A J

2018-04-01

Sleep is essential for recovery and performance in elite athletes. While it is generally assumed that exercise benefits sleep, high training load may jeopardize sleep and hence limit adequate recovery. To examine this, the current study assessed objective sleep quantity and sleep stage distributions in elite athletes and calculated their association with perceived training load. Mixed-methods. Perceived training load, actigraphy and one-channel EEG recordings were collected among 98 elite athletes during 7 consecutive days of regular training. Actigraphy revealed total sleep durations of 7:50±1:08h, sleep onset latencies of 13±15min, wake after sleep onset of 33±17min and sleep efficiencies of 88±5%. Distribution of sleep stages indicated 51±9% light sleep, 21±8% deep sleep, and 27±7% REM sleep. On average, perceived training load was 5.40±2.50 (scale 1-10), showing large daily variability. Mixed-effects models revealed no alteration in sleep quantity or sleep stage distributions as a function of day-to-day variation in preceding training load (all p's>.05). Results indicate healthy sleep durations, but elevated wake after sleep onset, suggesting a potential need for sleep optimization. Large proportions of deep sleep potentially reflect an elevated recovery need. With sleep quantity and sleep stage distributions remaining irresponsive to variations in perceived training load, it is questionable whether athletes' current sleep provides sufficient recovery after strenuous exercise. Copyright © 2017 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

A hidden Markov model to assess drug-induced sleep fragmentation in the telemetered rat.

Science.gov (United States)

Diack, C; Ackaert, O; Ploeger, B A; van der Graaf, P H; Gurrell, R; Ivarsson, M; Fairman, D

2011-12-01

Drug-induced sleep fragmentation can cause sleep disturbances either via their intended pharmacological action or as a side effect. Examples of disturbances include excessive daytime sleepiness, insomnia and nightmares. Developing drugs without these side effects requires insight into the mechanisms leading to sleep disturbance. The characterization of the circadian sleep pattern by EEG following drug exposure has improved our understanding of these mechanisms and their translatability across species. The EEG shows frequent transitions between specific sleep states leading to multiple correlated sojourns in these states. We have developed a Markov model to consider the high correlation in the data and quantitatively compared sleep disturbance in telemetered rats induced by methylphenidate, which is known to disturb sleep, and of a new chemical entity (NCE). It was assumed that these drugs could either accelerate or decelerate the transitions between the sleep states. The difference in sleep disturbance of methylphenidate and the NCE were quantitated and different mechanisms of action on rebound sleep were identified. The estimated effect showed that both compounds induce sleep fragmentation with methylphenidate being fivefold more potent compared to the NCE.

Two cases of childhood narcolepsy mimicking epileptic seizures in video-EEG/EMG.

Science.gov (United States)

Yanagishita, Tomoe; Ito, Susumu; Ohtani, Yui; Eto, Kaoru; Kanbayashi, Takashi; Oguni, Hirokazu; Nagata, Satoru

2018-06-06

Narcolepsy is characterized by excessive sleepiness, hypnagogic hallucinations, and sleep paralysis, and can occur with or without cataplexy. Here, we report two children with narcolepsy presenting with cataplexy mimicking epileptic seizures as determined by long-term video-electroencephalography (EEG) and electromyography (EMG) monitoring. Case 1 was a 15-year-old girl presenting with recurrent episodes of "convulsions" and loss of consciousness, who was referred to our hospital with a diagnosis of epilepsy showing "convulsions" and "complex partial seizures". The long-term video-polygraph showed a clonic attack lasting for 15 s, which corresponded to 1-2 Hz with interruption of mentalis EMG discharges lasting for 70-300 ms without any EEG changes. Narcolepsy was suspected due to the attack induced by hearty laughs and the presence of sleep attacks, and confirmed by low orexin levels in cerebrospinal fluid (CSF). Case 2 was an 11-year-old girl presenting with recurrent episodes of myoclonic attacks simultaneously with dropping objects immediately after hearty laughs, in addition to sleep attacks, hypnagogic hallucinations, and sleep paralysis. The long-term video-polygraph showed a subtle attack, characterized by dropping chopsticks from her hand, which corresponded to an interruption of ongoing deltoid EMG discharges lasting 140 ms without any EEG changes. A diagnosis of narcolepsy was confirmed by the low orexin levels in CSF. These cases demonstrate that children with narcolepsy may have attacks of cataplexy that resemble clonic or myoclonic seizures. Copyright © 2018 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

EEG recordings as a source for the detection of IRBD

DEFF Research Database (Denmark)

Bisgaard, Sissel; Duun-Christensen, Bolette; Kempfner, Lykke

2015-01-01

The purpose of this pilot study was to develop a supportive algorithm for the detection of idiopathic Rapid Eye-Movement (REM) sleep Behaviour Disorder (iRBD) from EEG recordings. iRBD is defined as REM sleep without atonia with no current sign of neurodegenerative disease, and is one...... of the earliest known biomarkers of Parkinson's Disease (PD). It is currently diagnosed by polysomnography (PSG), primarily based on EMG recordings during REM sleep. The algorithm was developed using data collected from 42 control subjects and 34 iRBD subjects. A feature was developed to represent high amplitude...

EPILEPTIC ENCEPHALOPATHY WITH CONTINUOUS SPIKES-WAVES ACTIVITY DURING SLEEP

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E. D. Belousova

2012-01-01

Full Text Available The author represents the review and discussion of current scientific literature devoted to epileptic encephalopathy with continuous spikes-waves activity during sleep — the special form of partly reversible age-dependent epileptic encephalopathy, characterized by triad of symptoms: continuous prolonged epileptiform (spike-wave activity on EEG in sleep, epileptic seizures and cognitive disorders. The author describes the aspects of classification, pathogenesis and etiology, prevalence, clinical picture and diagnostics of this disorder, including the peculiar anomalies on EEG. The especial attention is given to approaches to the treatment of epileptic encephalopathy with continuous spikeswaves activity during sleep. Efficacy of valproates, corticosteroid hormones and antiepileptic drugs of other groups is considered. The author represents own experience of treatment this disorder with corticosteroids, scheme of therapy and assessment of efficacy.

Neonatal thalamic hemorrhage is strongly associated with electrical status epilepticus in slow wave sleep.

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Kersbergen, Karina J; de Vries, Linda S; Leijten, Frans S S; Braun, Kees P J; Nievelstein, Rutger A J; Groenendaal, Floris; Benders, Manon J N L; Jansen, Floor E

2013-04-01

Thalamic hemorrhage has been associated with neonatal cerebral sinovenous thrombosis (CSVT), especially when the straight sinus is involved, and often presents with neonatal seizures. Early thalamic injury has previously been shown to predispose to epilepsy and electrical status epilepticus in slow wave sleep (ESES). The objective of this study was to assess the prevalence of sleep-induced epileptic electroencephalography (EEG) abnormalities and postneonatal epilepsy after neonatal thalamic hemorrhage associated with CSVT, in the absence of more widespread cerebral damage. Between 2003 and 2008 15 neonates were diagnosed with a thalamic hemorrhage due to suspected or proven CSVT. Neurodevelopment and the history of seizures were assessed at follow-up in the outpatient clinic in all 14 survivors (age 2-9 years). Whole-night or sleep-deprived EEG recordings were obtained to assess the prevalence of interictal epileptiform activity (EA) and calculate a sleep-induced spike and wave index (SWI). Three children were diagnosed with classic ESES (SWI >85%). Two children had ESES spectrum disorder (SWI between 50% and 85%), and in two children significant sleep-induced epileptiform activity (SIEA) was noted (SWI between 25% and 50%). Two other children were diagnosed with focal epilepsy, in the absence of sleep-induced epileptiform EEG abnormalities. Five children (age 2-7 years) had normal EEG recordings at follow-up. Deficits in neurodevelopment were seen significantly more often in children with ESES, ESES spectrum, or SIEA. Neonates with thalamic hemorrhage associated with straight sinus thrombosis, without evidence of more widespread cerebral damage, are at high risk of developing ESES (spectrum) disorder (35%), SIEA (14%), or focal epilepsy (14%). Electrographic abnormalities may already be present prior to recognition of cognitive deficits. Early diagnosis may guide parents and caregivers, and subsequent treatment may improve neurodevelopmental outcome. Routine

How many sleep stages do we need for an efficient automatic insomnia diagnosis?

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Hamida, Sana Tmar-Ben; Glos, Martin; Penzel, Thomas; Ahmed, Beena

2016-08-01

Tools used by clinicians to diagnose and treat insomnia typically include sleep diaries and questionnaires. Overnight polysomnography (PSG) recordings are used when the initial diagnosis is uncertain due to the presence of other sleep disorders or when the treatment, either behavioral or pharmacologic, is unsuccessful. However, the analysis and the scoring of PSG data are time-consuming. To simplify the diagnosis process, in this paper we have proposed an efficient insomnia detection algorithm based on a central single electroencephalographic (EEG) channel (C3) using only deep sleep. We also analyzed several spectral and statistical EEG features of good sleeper controls and subjects suffering from insomnia in different sleep stages to identify the features that offered the best discrimination between the two groups. Our proposed algorithm was evaluated using EEG recordings from 19 patients diagnosed with primary insomnia (11 females, 8 males) and 16 matched control subjects (11 females, 5 males). The sensitivity of our algorithm is 92%, the specificity is 89.9%, the Cohen's kappa is 0.81 and the agreement is 91%, indicating the effectiveness of our proposed method.

Cordycepin Increases Nonrapid Eye Movement Sleep via Adenosine Receptors in Rats.

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Hu, Zhenzhen; Lee, Chung-Il; Shah, Vikash Kumar; Oh, Eun-Hye; Han, Jin-Yi; Bae, Jae-Ryong; Lee, Kinam; Chong, Myong-Soo; Hong, Jin Tae; Oh, Ki-Wan

2013-01-01

Cordycepin (3'-deoxyadenosine) is a naturally occurring adenosine analogue and one of the bioactive constituents isolated from Cordyceps militaris/Cordyceps sinensis, species of the fungal genus Cordyceps. It has traditionally been a prized Chinese folk medicine for the human well-being. Because of similarity of chemical structure of adenosine, cordycepin has been focused on the diverse effects of the central nervous systems (CNSs), like sleep regulation. Therefore, this study was undertaken to know whether cordycepin increases the natural sleep in rats, and its effect is mediated by adenosine receptors (ARs). Sleep was recorded using electroencephalogram (EEG) for 4 hours after oral administration of cordycepin in rats. Sleep architecture and EEG power spectra were analyzed. Cordycepin reduced sleep-wake cycles and increased nonrapid eye movement (NREM) sleep. Interestingly, cordycepin increased θ (theta) waves power density during NREM sleep. In addition, the protein levels of AR subtypes (A1, A2A, and A2B) were increased after the administration of cordycepin, especially in the rat hypothalamus which plays an important role in sleep regulation. Therefore, we suggest that cordycepin increases theta waves power density during NREM sleep via nonspecific AR in rats. In addition, this experiment can provide basic evidence that cordycepin may be helpful for sleep-disturbed subjects.

Cordycepin Increases Nonrapid Eye Movement Sleep via Adenosine Receptors in Rats

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Zhenzhen Hu

2013-01-01

Full Text Available Cordycepin (3′-deoxyadenosine is a naturally occurring adenosine analogue and one of the bioactive constituents isolated from Cordyceps militaris/Cordyceps sinensis, species of the fungal genus Cordyceps. It has traditionally been a prized Chinese folk medicine for the human well-being. Because of similarity of chemical structure of adenosine, cordycepin has been focused on the diverse effects of the central nervous systems (CNSs, like sleep regulation. Therefore, this study was undertaken to know whether cordycepin increases the natural sleep in rats, and its effect is mediated by adenosine receptors (ARs. Sleep was recorded using electroencephalogram (EEG for 4 hours after oral administration of cordycepin in rats. Sleep architecture and EEG power spectra were analyzed. Cordycepin reduced sleep-wake cycles and increased nonrapid eye movement (NREM sleep. Interestingly, cordycepin increased θ (theta waves power density during NREM sleep. In addition, the protein levels of AR subtypes (A1, A2A, and A2B were increased after the administration of cordycepin, especially in the rat hypothalamus which plays an important role in sleep regulation. Therefore, we suggest that cordycepin increases theta waves power density during NREM sleep via nonspecific AR in rats. In addition, this experiment can provide basic evidence that cordycepin may be helpful for sleep-disturbed subjects.

Mechanical design principles of a mitotic spindle.

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Ward, Jonathan J; Roque, Hélio; Antony, Claude; Nédélec, François

2014-12-18

An organised spindle is crucial to the fidelity of chromosome segregation, but the relationship between spindle structure and function is not well understood in any cell type. The anaphase B spindle in fission yeast has a slender morphology and must elongate against compressive forces. This 'pushing' mode of chromosome transport renders the spindle susceptible to breakage, as observed in cells with a variety of defects. Here we perform electron tomographic analyses of the spindle, which suggest that it organises a limited supply of structural components to increase its compressive strength. Structural integrity is maintained throughout the spindle's fourfold elongation by organising microtubules into a rigid transverse array, preserving correct microtubule number and dynamically rescaling microtubule length.

A transition-constrained discrete hidden Markov model for automatic sleep staging

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Pan Shing-Tai

2012-08-01

Full Text Available Abstract Background Approximately one-third of the human lifespan is spent sleeping. To diagnose sleep problems, all-night polysomnographic (PSG recordings including electroencephalograms (EEGs, electrooculograms (EOGs and electromyograms (EMGs, are usually acquired from the patient and scored by a well-trained expert according to Rechtschaffen & Kales (R&K rules. Visual sleep scoring is a time-consuming and subjective process. Therefore, the development of an automatic sleep scoring method is desirable. Method The EEG, EOG and EMG signals from twenty subjects were measured. In addition to selecting sleep characteristics based on the 1968 R&K rules, features utilized in other research were collected. Thirteen features were utilized including temporal and spectrum analyses of the EEG, EOG and EMG signals, and a total of 158 hours of sleep data were recorded. Ten subjects were used to train the Discrete Hidden Markov Model (DHMM, and the remaining ten were tested by the trained DHMM for recognition. Furthermore, the 2-fold cross validation was performed during this experiment. Results Overall agreement between the expert and the results presented is 85.29%. With the exception of S1, the sensitivities of each stage were more than 81%. The most accurate stage was SWS (94.9%, and the least-accurately classified stage was S1 ( Conclusion The results of the experiments demonstrate that the proposed method significantly enhances the recognition rate when compared with prior studies.

Standardized Computer-based Organized Reporting of EEG: SCORE

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Beniczky, Sándor; Aurlien, Harald; Brøgger, Jan C; Fuglsang-Frederiksen, Anders; Martins-da-Silva, António; Trinka, Eugen; Visser, Gerhard; Rubboli, Guido; Hjalgrim, Helle; Stefan, Hermann; Rosén, Ingmar; Zarubova, Jana; Dobesberger, Judith; Alving, Jørgen; Andersen, Kjeld V; Fabricius, Martin; Atkins, Mary D; Neufeld, Miri; Plouin, Perrine; Marusic, Petr; Pressler, Ronit; Mameniskiene, Ruta; Hopfengärtner, Rüdiger; Emde Boas, Walter; Wolf, Peter

2013-01-01

The electroencephalography (EEG) signal has a high complexity, and the process of extracting clinically relevant features is achieved by visual analysis of the recordings. The interobserver agreement in EEG interpretation is only moderate. This is partly due to the method of reporting the findings in free-text format. The purpose of our endeavor was to create a computer-based system for EEG assessment and reporting, where the physicians would construct the reports by choosing from predefined elements for each relevant EEG feature, as well as the clinical phenomena (for video-EEG recordings). A working group of EEG experts took part in consensus workshops in Dianalund, Denmark, in 2010 and 2011. The faculty was approved by the Commission on European Affairs of the International League Against Epilepsy (ILAE). The working group produced a consensus proposal that went through a pan-European review process, organized by the European Chapter of the International Federation of Clinical Neurophysiology. The Standardised Computer-based Organised Reporting of EEG (SCORE) software was constructed based on the terms and features of the consensus statement and it was tested in the clinical practice. The main elements of SCORE are the following: personal data of the patient, referral data, recording conditions, modulators, background activity, drowsiness and sleep, interictal findings, “episodes” (clinical or subclinical events), physiologic patterns, patterns of uncertain significance, artifacts, polygraphic channels, and diagnostic significance. The following specific aspects of the neonatal EEGs are scored: alertness, temporal organization, and spatial organization. For each EEG finding, relevant features are scored using predefined terms. Definitions are provided for all EEG terms and features. SCORE can potentially improve the quality of EEG assessment and reporting; it will help incorporate the results of computer-assisted analysis into the report, it will make

Sustained attention performance during sleep deprivation associates with instability in behavior and physiologic measures at baseline.

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Chua, Eric Chern-Pin; Yeo, Sing-Chen; Lee, Ivan Tian-Guang; Tan, Luuan-Chin; Lau, Pauline; Cai, Shiwei; Zhang, Xiaodong; Puvanendran, Kathiravelu; Gooley, Joshua J

2014-01-01

To identify baseline behavioral and physiologic markers that associate with individual differences in sustained attention during sleep deprivation. In a retrospective study, ocular, electrocardiogram, and electroencephalogram (EEG) measures were compared in subjects who were characterized as resilient (n = 15) or vulnerable (n = 15) to the effects of total sleep deprivation on sustained attention. Chronobiology and Sleep Laboratory, Duke-NUS Graduate Medical School Singapore. Healthy volunteers aged 22-32 years from the general population. Subjects were kept awake for at least 26 hours under constant environmental conditions. Every 2 hours, sustained attention was assessed using a 10-minute psychomotor vigilance task (PVT). During baseline sleep and recovery sleep, EEG slow wave activity was similar in resilient versus vulnerable subjects, suggesting that individual differences in vulnerability to sleep loss were not related to differences in homeostatic sleep regulation. Rather, irrespective of time elapsed since wake, subjects who were vulnerable to sleep deprivation exhibited slower and more variable PVT response times, lower and more variable heart rate, and higher and more variable EEG spectral power in the theta frequency band (6.0-7.5 Hz). Performance decrements in sustained attention during sleep deprivation associate with instability in behavioral and physiologic measures at baseline. Small individual differences in sustained attention that are present at baseline are amplified during prolonged wakefulness, thus contributing to large between-subjects differences in performance and sleepiness.

Electroencephalogram approximate entropy influenced by both age and sleep

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Gerick M. H. Lee

2013-12-01

Full Text Available The use of information-based measures to assess changes in conscious state is an increasingly popular topic. Though recent results have seemed to justify the merits of such methods, little has been done to investigate the applicability of such measures to children. For our work, we used the approximate entropy (ApEn, a measure previously shown to correlate with changes in conscious state when applied to the electroencephalogram (EEG, and sought to confirm whether previously reported trends in adult ApEn values across wake and sleep were present in children. Besides validating the prior findings that ApEn decreases from wake to sleep (including wake, rapid eye movement [REM] sleep, and non-REM sleep in adults, we found that previously reported ApEn decreases across vigilance states in adults were also present in children (ApEn trends for both age groups: wake > REM sleep > non-REM sleep. When comparing ApEn values between age groups, adults had significantly larger ApEn values than children during wakefulness. After the application of an 8 Hz high-pass filter to the EEG signal, ApEn values were recalculated. The number of electrodes with significant vigilance state effects dropped from all 109 electrodes with the original 1 Hz filter to 1 electrode with the 8 Hz filter. The number of electrodes with significant age effects dropped from ten to four. Our results support the notion that ApEn can reliably distinguish between vigilance states, with low-frequency sleep-related oscillations implicated as the driver of changes between vigilance states. We suggest that the observed differences between adult and child ApEn values during wake may reflect differences in connectivity between age groups, a factor which may be important in the use of EEG to measure consciousness.

A Contribution for the Automatic Sleep Classification Based on the Itakura-Saito Spectral Distance

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Cardoso, Eduardo; Batista, Arnaldo; Rodrigues, Rui; Ortigueira, Manuel; Bárbara, Cristina; Martinho, Cristina; Rato, Raul

Sleep staging is a crucial step before the scoring the sleep apnoea, in subjects that are tested for this condition. These patients undergo a whole night polysomnography recording that includes EEG, EOG, ECG, EMG and respiratory signals. Sleep staging refers to the quantification of its depth. Despite the commercial sleep software being able to stage the sleep, there is a general lack of confidence amongst health practitioners of these machine results. Generally the sleep scoring is done over the visual inspection of the overnight patient EEG recording, which takes the attention of an expert medical practitioner over a couple of hours. This contributes to a waiting list of two years for patients of the Portuguese Health Service. In this work we have used a spectral comparison method called Itakura distance to be able to make a distinction between sleepy and awake epochs in a night EEG recording, therefore automatically doing the staging. We have used the data from 20 patients of Hospital Pulido Valente, which had been previously visually expert scored. Our technique results were promising, in a way that Itakura distance can, by itself, distinguish with a good degree of certainty the N2, N3 and awake states. Pre-processing stages for artefact reduction and baseline removal using Wavelets were applied.

Sleep staging with movement-related signals.

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Jansen, B H; Shankar, K

1993-05-01

Body movement related signals (i.e., activity due to postural changes and the ballistocardiac effort) were recorded from six normal volunteers using the static-charge-sensitive bed (SCSB). Visual sleep staging was performed on the basis of simultaneously recorded EEG, EMG and EOG signals. A statistical classification technique was used to determine if reliable sleep staging could be performed using only the SCSB signal. A classification rate of between 52% and 75% was obtained for sleep staging in the five conventional sleep stages and the awake state. These rates improved from 78% to 89% for classification between awake, REM and non-REM sleep and from 86% to 98% for awake versus asleep classification.

Slow oscillation electrical brain stimulation during waking promotes EEG theta activity and memory encoding

DEFF Research Database (Denmark)

Kirov, Roumen; Weiss, Carsten; Siebner, Hartwig R

2009-01-01

typically occurring during this state of sleep were also enhanced. Here, we show that the same tSOS applied in the waking brain also induced an increase in endogenous EEG slow oscillations (0.4-1.2 Hz), although in a topographically restricted fashion. Applied during wakefulness tSOS, additionally, resulted......The application of transcranial slow oscillation stimulation (tSOS; 0.75 Hz) was previously shown to enhance widespread endogenous EEG slow oscillatory activity when applied during a sleep period characterized by emerging endogenous slow oscillatory activity. Processes of memory consolidation...... induced by tSOS critically depend on brain state. In response to tSOS during wakefulness the brain transposes stimulation by responding preferentially with theta oscillations and facilitated encoding....

Thermal-Signature-Based Sleep Analysis Sensor

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Ali Seba

2017-10-01

Full Text Available This paper addresses the development of a new technique in the sleep analysis domain. Sleep is defined as a periodic physiological state during which vigilance is suspended and reactivity to external stimulations diminished. We sleep on average between six and nine hours per night and our sleep is composed of four to six cycles of about 90 min each. Each of these cycles is composed of a succession of several stages of sleep that vary in depth. Analysis of sleep is usually done via polysomnography. This examination consists of recording, among other things, electrical cerebral activity by electroencephalography (EEG, ocular movements by electrooculography (EOG, and chin muscle tone by electromyography (EMG. Recordings are made mostly in a hospital, more specifically in a service for monitoring the pathologies related to sleep. The readings are then interpreted manually by an expert to generate a hypnogram, a curve showing the succession of sleep stages during the night in 30s epochs. The proposed method is based on the follow-up of the thermal signature that makes it possible to classify the activity into three classes: “awakening,” “calm sleep,” and “restless sleep”. The contribution of this non-invasive method is part of the screening of sleep disorders, to be validated by a more complete analysis of the sleep. The measure provided by this new system, based on temperature monitoring (patient and ambient, aims to be integrated into the tele-medicine platform developed within the framework of the Smart-EEG project by the SYEL–SYstèmes ELectroniques team. Analysis of the data collected during the first surveys carried out with this method showed a correlation between thermal signature and activity during sleep. The advantage of this method lies in its simplicity and the possibility of carrying out measurements of activity during sleep and without direct contact with the patient at home or hospitals.

Shared Genetic Control of Brain Activity During Sleep and Insulin Secretion: A Laboratory-Based Family Study.

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Morselli, Lisa L; Gamazon, Eric R; Tasali, Esra; Cox, Nancy J; Van Cauter, Eve; Davis, Lea K

2018-01-01

Over the past 20 years, a large body of experimental and epidemiologic evidence has linked sleep duration and quality to glucose homeostasis, although the mechanistic pathways remain unclear. The aim of the current study was to determine whether genetic variation influencing both sleep and glucose regulation could underlie their functional relationship. We hypothesized that the genetic regulation of electroencephalographic (EEG) activity during non-rapid eye movement sleep, a highly heritable trait with fingerprint reproducibility, is correlated with the genetic control of metabolic traits including insulin sensitivity and β-cell function. We tested our hypotheses through univariate and bivariate heritability analyses in a three-generation pedigree with in-depth phenotyping of both sleep EEG and metabolic traits in 48 family members. Our analyses accounted for age, sex, adiposity, and the use of psychoactive medications. In univariate analyses, we found significant heritability for measures of fasting insulin sensitivity and β-cell function, for time spent in slow-wave sleep, and for EEG spectral power in the delta, theta, and sigma ranges. Bivariate heritability analyses provided the first evidence for a shared genetic control of brain activity during deep sleep and fasting insulin secretion rate. © 2017 by the American Diabetes Association.

The Utility of EEG in Attention Deficit Hyperactivity Disorder: A Replication Study.

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Swatzyna, Ronald J; Tarnow, Jay D; Roark, Alexandra; Mardick, Jacob

2017-07-01

The routine use of stimulants in pediatrics has increased dramatically over the past 3 decades and the long-term consequences have yet to be fully studied. Since 1978 there have been 7 articles identifying electroencephalogram (EEG) abnormalities, particularly epileptiform discharges in children with attention deficit hyperactivity disorder (ADHD). Many have studied the prevalence of these discharges in this population with varying results. An article published in 2011 suggests that EEG technology should be considered prior to prescribing stimulants to children diagnosed with ADHD due to a high prevalence of epileptiform discharges. The 2011 study found a higher prevalence (26%) of epileptiform discharges when using 23-hour and sleep-deprived EEGs in comparison with other methods of activation (hyperventilation or photostimulation) and conventional EEG. We sought to replicate the 2011 results using conventional EEG with the added qEEG technologies of automatic spike detection and low-resolution electromagnetic tomography analysis (LORETA) brain mapping. Our results showed 32% prevalence of epileptiform discharges, which suggests that an EEG should be considered prior to prescribing stimulant medications.

The Spindle Cell Neoplasms of the Oral Cavity.

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Shamim, Thorakkal

2015-01-01

Spindle cell neoplasms are defined as neoplasms that consist of spindle-shaped cells in the histopathology. Spindle cell neoplasms can affect the oral cavity. In the oral cavity, the origin of the spindle cell neoplasms may be traced to epithelial, mesenchymal and odontogenic components. This article aims to review the spindle cell neoplasms of the oral cavity with emphasis on histopathology.

Sleep homeostatic pressure and PER3 VNTR gene polymorphism influence antidepressant response to sleep deprivation in bipolar depression.

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Dallaspezia, Sara; Locatelli, Clara; Lorenzi, Cristina; Pirovano, Adele; Colombo, Cristina; Benedetti, Francesco

2016-03-01

Combined Total sleep deprivation (TSD) and light therapy (LT) cause a rapid improvement in bipolar depression which has been hypothesized to be paralleled by changes in sleep homeostasis. Recent studies showed that bipolar patients had lower changes of EEG theta power after sleep and responders to antidepressant TSD+LT slept less and showed a lower increase of EEG theta power then non-responders. A polymorphism in PER3 gene has been associated with diurnal preference, sleep structure and homeostatic response to sleep deprivation in healthy subjects. We hypothesized that the individual variability in the homeostatic response to TSD could be a correlate of antidepressant response and be influenced by genetic factors. We administered three TSD+LT cycles to bipolar depressed patients. Severity of depression was rated on Hamilton Depression Rating Scale. Actigraphic recordings were performed in a group of patients. PER3 polymorphism influenced changes in total sleep time (F=2.24; p=0.024): while PER3(4/4) and PER3(4/5) patients showed a reduction in it after treatment, PER3(5/5) subjects showed an increase of about 40min, suggesting a higher homeostatic pressure. The same polymorphism influenced the change of depressive symptomatology during treatment (F=3.72; p=0.028). Sleep information was recorded till the day after the end of treatment: a longer period of observation could give more information about the possible maintenance of allostatic adaptation. A higher sleep homeostatic pressure reduced the antidepressant response to TSD+LT, while an allostatic adaptation to sleep loss was associated with better response. This process seems to be under genetic control. Copyright © 2015 Elsevier B.V. All rights reserved.

Formation and suppression of acoustic memories during human sleep.

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Andrillon, Thomas; Pressnitzer, Daniel; Léger, Damien; Kouider, Sid

2017-08-08

Sleep and memory are deeply related, but the nature of the neuroplastic processes induced by sleep remains unclear. Here, we report that memory traces can be both formed or suppressed during sleep, depending on sleep phase. We played samples of acoustic noise to sleeping human listeners. Repeated exposure to a novel noise during Rapid Eye Movements (REM) or light non-REM (NREM) sleep leads to improvements in behavioral performance upon awakening. Strikingly, the same exposure during deep NREM sleep leads to impaired performance upon awakening. Electroencephalographic markers of learning extracted during sleep confirm a dissociation between sleep facilitating memory formation (light NREM and REM sleep) and sleep suppressing learning (deep NREM sleep). We can trace these neural changes back to transient sleep events, such as spindles for memory facilitation and slow waves for suppression. Thus, highly selective memory processes are active during human sleep, with intertwined episodes of facilitative and suppressive plasticity.Though memory and sleep are related, it is still unclear whether new memories can be formed during sleep. Here, authors show that people could learn new sounds during REM or light non-REM sleep, but that learning was suppressed when sounds were played during deep NREM sleep.

Can we still dream when the mind is blank? Sleep and dream mentations in auto-activation deficit.

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Leu-Semenescu, Smaranda; Uguccioni, Ginevra; Golmard, Jean-Louis; Czernecki, Virginie; Yelnik, Jerome; Dubois, Bruno; Forgeot d'Arc, Baudouin; Grabli, David; Levy, Richard; Arnulf, Isabelle

2013-10-01

Bilateral damage to the basal ganglia causes auto-activation deficit, a neuropsychological syndrome characterized by striking apathy, with a loss of self-driven behaviour that is partially reversible with external stimulation. Some patients with auto-activation deficit also experience a mental emptiness, which is defined as an absence of any self-reported thoughts. We asked whether this deficit in spontaneous activation of mental processing may be reversed during REM sleep, when dreaming activity is potentially elicited by bottom-up brainstem stimulation on the cortex. Sleep and video monitoring over two nights and cognitive tests were performed on 13 patients with auto-activation deficit secondary to bilateral striato-pallidal lesions and 13 healthy subjects. Dream mentations were collected from home diaries and after forced awakenings in non-REM and REM sleep. The home diaries were blindly analysed for length, complexity and bizarreness. A mental blank during wakefulness was complete in six patients and partial in one patient. Four (31%) patients with auto-activation deficit (versus 92% of control subjects) reported mentations when awakened from REM sleep, even when they demonstrated a mental blank during the daytime (n = 2). However, the patients' dream reports were infrequent, short, devoid of any bizarre or emotional elements and tended to be less complex than the dream mentations of control subjects. The sleep duration, continuity and stages were similar between the groups, except for a striking absence of sleep spindles in 6 of 13 patients with auto-activation deficit, despite an intact thalamus. The presence of spontaneous dreams in REM sleep in the absence of thoughts during wakefulness in patients with auto-activation deficit supports the idea that simple dream imagery is generated by brainstem stimulation and is sent to the sensory cortex. However, the lack of complexity in these dream mentations suggests that the full dreaming process (scenario

Heart-Rate Variability During Deep Sleep in World-Class Alpine Skiers: A Time-Efficient Alternative to Morning Supine Measurements.

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Herzig, David; Testorelli, Moreno; Olstad, Daniela Schäfer; Erlacher, Daniel; Achermann, Peter; Eser, Prisca; Wilhelm, Matthias

2017-05-01

It is increasingly popular to use heart-rate variability (HRV) to tailor training for athletes. A time-efficient method is HRV assessment during deep sleep. To validate the selection of deep-sleep segments identified by RR intervals with simultaneous electroencephalography (EEG) recordings and to compare HRV parameters of these segments with those of standard morning supine measurements. In 11 world-class alpine skiers, RR intervals were monitored during 10 nights, and simultaneous EEGs were recorded during 2-4 nights. Deep sleep was determined from the HRV signal and verified by delta power from the EEG recordings. Four further segments were chosen for HRV determination, namely, a 4-h segment from midnight to 4 AM and three 5-min segments: 1 just before awakening, 1 after waking in supine position, and 1 in standing after orthostatic challenge. Training load was recorded every day. A total of 80 night and 68 morning measurements of 9 athletes were analyzed. Good correspondence between the phases selected by RR intervals vs those selected by EEG was found. Concerning root-mean-squared difference of successive RR intervals (RMSSD), a marker for parasympathetic activity, the best relationship with the morning supine measurement was found in deep sleep. HRV is a simple tool for approximating deep-sleep phases, and HRV measurement during deep sleep could provide a time-efficient alternative to HRV in supine position.

Regional Patterns of Elevated Alpha and High-Frequency Electroencephalographic Activity during Nonrapid Eye Movement Sleep in Chronic Insomnia: A Pilot Study

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Riedner, Brady A.; Goldstein, Michael R.; Plante, David T.; Rumble, Meredith E.; Ferrarelli, Fabio; Tononi, Giulio; Benca, Ruth M.

2016-01-01

Study Objectives: To examine nonrapid eye movement (NREM) sleep in insomnia using high-density electroencephalography (EEG). Methods: All-night sleep recordings with 256 channel high-density EEG were analyzed for 8 insomnia subjects (5 females) and 8 sex and age-matched controls without sleep complaints. Spectral analyses were conducted using unpaired t-tests and topographical differences between groups were assessed using statistical non-parametric mapping. Five minute segments of deep NREM sleep were further analyzed using sLORETA cortical source imaging. Results: The initial topographic analysis of all-night NREM sleep EEG revealed that insomnia subjects had more high-frequency EEG activity (> 16 Hz) compared to good sleeping controls and that the difference between groups was widespread across the scalp. In addition, the analysis also showed that there was a more circumscribed difference in theta (4–8 Hz) and alpha (8–12 Hz) power bands between groups. When deep NREM sleep (N3) was examined separately, the high-frequency difference between groups diminished, whereas the higher regional alpha activity in insomnia subjects persisted. Source imaging analysis demonstrated that sensory and sensorimotor cortical areas consistently exhibited elevated levels of alpha activity during deep NREM sleep in insomnia subjects relative to good sleeping controls. Conclusions: These results suggest that even during the deepest stage of sleep, sensory and sensorimotor areas in insomnia subjects may still be relatively active compared to control subjects and to the rest of the sleeping brain. Citation: Riedner BA, Goldstein MR, Plante DT, Rumble ME, Ferrarelli F, Tononi G, Benca RM. Regional patterns of elevated alpha and high-frequency electroencephalographic activity during nonrapid eye movement sleep in chronic insomnia: a pilot study. SLEEP 2016;39(4):801–812. PMID:26943465

Assessment of Itakura Distance as a valuable feature for computer-aided classification of sleep stages.

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Ebrahimi, F; Mikaili, M; Estrada, E; Nazeran, H

2007-01-01

Staging and detection of various states of sleep derived from EEG and other biomedical signals have proven to be very helpful in diagnosis, prognosis and remedy of various sleep related disorders. The time consuming and costly process of visual scoring of sleep stages by a specialist has always motivated researchers to develop an automatic sleep scoring system and the first step toward achieving this task is finding discriminating characteristics (or features) for each stage. A vast variety of these features and methods have been investigated in the sleep literature with different degrees of success. In this study, we investigated the performance of a newly introduced measure: the Itakura Distance (ID), as a similarity measure between EEG and EOG signals. This work demonstrated and further confirmed the outcomes of our previous research that the Itakura Distance serves as a valuable similarity measure to differentiate between different sleep stages.

EEG criteria predictive of complicated evolution in idiopathic rolandic epilepsy.

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Massa, R; de Saint-Martin, A; Carcangiu, R; Rudolf, G; Seegmuller, C; Kleitz, C; Metz-Lutz, M N; Hirsch, E; Marescaux, C

2001-09-25

Although so-called "benign" epilepsy with centrotemporal spikes (BECTS) always has an excellent prognosis with regard to seizure remission, behavioral problems and cognitive dysfunctions may sometimes develop in its course. To search for clinical or EEG markers allowing early detection of patients prone to such complications, the authors conducted a prospective study in a cohort of unselected patients with BECTS. In 35 children with BECTS, academic, familial, neurologic, neuropsychological, and wake and sleep EEG evaluations were repeated every 6 to 12 months from the beginning of the seizure disorder up to complete recovery. In 25 of 35 patients (72%), behavioral and intellectual functioning remained unimpaired. In 10 of 35 patients (28%), educational performance and familial maladjustment occurred. These sociofamilial problems were correlated with impulsivity, learning difficulties, attention disorders, and minor (7/35 cases, 20%) or serious (3/35 cases, 8%) auditory-verbal or visual-spatial deficits. Worsening phases started 2 to 36 months after onset and persisted for 9 to 39 months. Occurrence of atypical evolutions was significantly correlated with five qualitative and one quantitative interictal EEG pattern: intermittent slow-wave focus, multiple asynchronous spike-wave foci, long spike-wave clusters, generalized 3-c/s "absence-like" spike-wave discharges, conjunction of interictal paroxysms with negative or positive myoclonia, and abundance of interictal abnormalities during wakefulness and sleep. Clinical deterioration was not linked with seizure characteristics or treatment. Different combinations of at least three of six distinctive interictal EEG patterns and their long-lasting (> or =6-month) persistence seem to be the hallmarks of patients with BECTS at risk for neuropsychological impairments.

Rats Housed on Corncob Bedding Show Less Slow-Wave Sleep

OpenAIRE

Leys, Laura J; McGaraughty, Steve; Radek, Richard J

2012-01-01

Despite the reported advantages of corncob bedding, questions have emerged about how comfortable animals find this type of bedding as a resting surface. In this study, encephalography (EEG) was used to compare the effects of corncob and aspen-chip bedding on rat slow-wave sleep (SWS). According to a facility-wide initiative, rats that were weaned on aspen-chip bedding were switched to corncob bedding in home cages and EEG recording chambers. Spontaneous EEG recordings obtained for 5 wk after ...

Age-related changes in sleep-wake rhythm in dog.

Science.gov (United States)

Takeuchi, Takashi; Harada, Etsumori

2002-10-17

To investigate a sleep-wake rhythm in aged dogs, a radio-telemetry monitoring was carried out for 24 h. Electrodes and telemetry device were surgically implanted in four aged dogs (16-18 years old) and four young dogs (3-4 years old). Electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG) were recorded simultaneously as parameters to determine vigilance states and an autonomic nervous function. Wakefulness, slow wave sleep (SWS) and paradoxical sleep (PS) were identified according to the EEG and EMG pattern. We also examined whether absolute powers and the low frequency-to-high frequency ratio (LF/HF) derived from the heart rate variability power spectrum could detect shifts in autonomic balance correlated with aging. The aged dogs showed a marked reduction of PS and a fragmentation of wakefulness in the daytime and a sleep disruption in the night. The pattern of 24 h sleep and waking was dramatically altered in the aged dog. It was characterized by an increase in the total amount of time spent in SWS during the daytime followed by an increasing of time spent in wakefulness during the night. Furthermore, LF/HF ratio showed a very low amplitude of variance throughout the day in the aged dog. These results suggest that the aged dog is a useful model to investigate sleep disorders in human such as daytime drowsiness, difficulties in sleep maintenance. The abnormality in sleep-wake cycle might be reflected by the altered autonomic balance in the aged dogs.

Dissociative symptoms and sleep parameters--an all-night polysomnography study in patients with insomnia.

Science.gov (United States)

Van Der Kloet, Dalena; Giesbrecht, Timo; Franck, Erik; Van Gastel, Ann; De Volder, Ilse; Van Den Eede, Filip; Verschuere, Bruno; Merckelbach, Harald

2013-08-01

Dissociative disorders encompass a range of symptoms varying from severe absent-mindedness and memory problems to confusion about one's own identity. Recent studies suggest that these symptoms may be the by-products of a labile sleep-wake cycle. In the current study, we explored this issue in patients suffering from insomnia (N=46). We investigated whether these patients have raised levels of dissociative symptoms and whether these are related to objective sleep parameters. Patients stayed for at least one night in a specialized sleep clinic, while sleep EEG data were obtained. In addition, they completed self-report measures on dissociative symptoms, psychological problems, and sleep characteristics. Dissociative symptom levels were elevated in patients suffering from insomnia, and were correlated with unusual sleep experiences and poor sleep quality. Longer REM sleep periods and less time spent awake during the night were predictive of dissociation. This is the first study to show that insomnia patients have raised dissociative symptom levels and that their dissociative symptoms are related to objective EEG parameters. These findings are important because they may inspire sleep-related treatment methods for dissociative disorders. Copyright © 2013 Elsevier Inc. All rights reserved.

A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series.

Science.gov (United States)

Chambon, Stanislas; Galtier, Mathieu N; Arnal, Pierrick J; Wainrib, Gilles; Gramfort, Alexandre

2018-04-01

Sleep stage classification constitutes an important preliminary exam in the diagnosis of sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30 s of the signal of a sleep stage, based on the visual inspection of signals such as electroencephalograms (EEGs), electrooculograms (EOGs), electrocardiograms, and electromyograms (EMGs). We introduce here the first deep learning approach for sleep stage classification that learns end-to-end without computing spectrograms or extracting handcrafted features, that exploits all multivariate and multimodal polysomnography (PSG) signals (EEG, EMG, and EOG), and that can exploit the temporal context of each 30-s window of data. For each modality, the first layer learns linear spatial filters that exploit the array of sensors to increase the signal-to-noise ratio, and the last layer feeds the learnt representation to a softmax classifier. Our model is compared to alternative automatic approaches based on convolutional networks or decisions trees. Results obtained on 61 publicly available PSG records with up to 20 EEG channels demonstrate that our network architecture yields the state-of-the-art performance. Our study reveals a number of insights on the spatiotemporal distribution of the signal of interest: a good tradeoff for optimal classification performance measured with balanced accuracy is to use 6 EEG with 2 EOG (left and right) and 3 EMG chin channels. Also exploiting 1 min of data before and after each data segment offers the strongest improvement when a limited number of channels are available. As sleep experts, our system exploits the multivariate and multimodal nature of PSG signals in order to deliver the state-of-the-art classification performance with a small computational cost.

Diagnostic value of sleep stage dissociation as visualized on a 2-dimensional sleep state space in human narcolepsy

DEFF Research Database (Denmark)

Olsen, Anders Vinther; Stephansen, Jens; Leary, Eileen B.

2017-01-01

Type 1 narcolepsy (NT1) is characterized by symptoms believed to represent Rapid Eye Movement (REM) sleep stage dissociations, occurrences where features of wake and REM sleep are intermingled, resulting in a mixed state. We hypothesized that sleep stage dissociations can be objectively detected...... through the analysis of nocturnal Polysomnography (PSG) data, and that those affecting REM sleep can be used as a diagnostic feature for narcolepsy. A Linear Discriminant Analysis (LDA) model using 38 features extracted from EOG, EMG and EEG was used in control subjects to select features differentiating...... wake, stage N1, N2, N3 and REM sleep. Sleep stage differentiation was next represented in a 2D projection. Features characteristic of sleep stage differences were estimated from the residual sleep stage probability in the 2D space. Using this model we evaluated PSG data from NT1 and non...

Measuring mitotic spindle dynamics in budding yeast

Science.gov (United States)

Plumb, Kemp

In order to carry out its life cycle and produce viable progeny through cell division, a cell must successfully coordinate and execute a number of complex processes with high fidelity, in an environment dominated by thermal noise. One important example of such a process is the assembly and positioning of the mitotic spindle prior to chromosome segregation. The mitotic spindle is a modular structure composed of two spindle pole bodies, separated in space and spanned by filamentous proteins called microtubules, along which the genetic material of the cell is held. The spindle is responsible for alignment and subsequent segregation of chromosomes into two equal parts; proper spindle positioning and timing ensure that genetic material is appropriately divided amongst mother and daughter cells. In this thesis, I describe fluorescence confocal microscopy and automated image analysis algorithms, which I have used to observe and analyze the real space dynamics of the mitotic spindle in budding yeast. The software can locate structures in three spatial dimensions and track their movement in time. By selecting fluorescent proteins which specifically label the spindle poles and cell periphery, mitotic spindle dynamics have been measured in a coordinate system relevant to the cell division. I describe how I have characterised the accuracy and precision of the algorithms by simulating fluorescence data for both spindle poles and the budding yeast cell surface. In this thesis I also describe the construction of a microfluidic apparatus that allows for the measurement of long time-scale dynamics of individual cells and the development of a cell population. The tools developed in this thesis work will facilitate in-depth quantitative analysis of the non-equilibrium processes in living cells.