[The various sleep stages. Sleep of the newborn].
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Circadian Rhythm↗
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Results for “Sleep stages”
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Upper airway resistance syndrome: effect of nasal dilation, sleep stage, and sleep position.
BACKGROUND: The upper airway resistance syndrome (UARS) is one of the mild variants of obstructive sleep disordered breathing. Nasal obstruction is proposed as one of the mechanisms that lowers intrapharyngeal pressure and hence increases airway collapsibility. OBJECTIVE: We evaluated the effect of external nasal dilation and sleep position on sleep in UARS. METHOD: A double blind, randomized, controlled study with a crossover design (using therapeutic and placebo dilators) was conducted in 18 consecutive patients with UARS. Each patient had two overnight sleep studies one to two weeks apart. Cardiorespiratory parameters (AHI, percentage of time that SaO2 was more than 2% below awake [desaturation time] and mean overnight heart rate), sleep architecture (sleep stages, sleep efficiency, and arousal index), and body position were determined. RESULTS: Application of the external nasal dilator resulted in a significant increase in the nasal cross-sectional area (p < 0.001). Treatment reduced stage 1 sleep (as a percent of total sleep time) from 8.6 +/- 0.8% to 7.1 +/- 0.7 (SEM), p = 0.034). Desaturation time was significantly lower with treatment (12.2 +/- 2.2% on placebo versus 9.1 +/- 1.3 on treatment, p = 0.04). There were no additional significant effects on the cardiorespiratory parameters, sleep architecture, or MSLT when the entire night was examined. Controlling for interactions of sleep stage and position and treatment we found that treatment reduced desaturation time (p = 0.03) but not AHI or arousal index. AHI was significantly lower in the lateral position compared to the supine (p = 0.0001) and in NREM sleep compared to REM (p = 0.001). Desaturation time was significantly lower on the lateral compared to the supine position (p = 0.002) and in NREM sleep compared to REM (p = 0.006). Arousal index was highly dependent on sleep stage (p = 0.0001): the index was higher in stage 2 compared to slow wave sleep and REM. Sleep position and treatment had no significant effect on arousals. CONCLUSIONS: External nasal dilation reduced stage 1 sleep, an indirect marker of disrupted sleep, and desaturation time. There were no additional effects on sleep architecture or sleep disordered breathing. Both sleep position and sleep stage had a significant effect on sleep disordered breathing in UARS.
Airway Resistance↗
The relationships between memory systems and sleep stages.
Sleep function remains elusive despite our rapidly increasing comprehension of the processes generating and maintaining the different sleep stages. Several lines of evidence support the hypothesis that sleep is involved in the off-line reprocessing of recently-acquired memories. In this review, we summarize the main results obtained in the field of sleep and memory consolidation in both animals and humans, and try to connect sleep stages with the different memory systems. To this end, we have collated data obtained using several methodological approaches, including electrophysiological recordings of neuronal ensembles, post-training modifications of sleep architecture, sleep deprivation and functional neuroimaging studies. Broadly speaking, all the various studies emphasize the fact that the four long-term memory systems (procedural memory, perceptual representation system, semantic and episodic memory, according to Tulving's SPI model; Tulving, 1995) benefit either from non-rapid eye movement (NREM) (not just SWS) or rapid eye movement (REM) sleep, or from both sleep stages. Tulving's classification of memory systems appears more pertinent than the declarative/non-declarative dichotomy when it comes to understanding the role of sleep in memory. Indeed, this model allows us to resolve several contradictions, notably the fact that episodic and semantic memory (the two memory systems encompassed in declarative memory) appear to rely on different sleep stages. Likewise, this model provides an explanation for why the acquisition of various types of skills (perceptual-motor, sensory-perceptual and cognitive skills) and priming effects, subserved by different brain structures but all designated by the generic term of implicit or non-declarative memory, may not benefit from the same sleep stages.
Animals↗
[Actigraphy: methodological limits for evaluation of sleep stages and sleep structure of healthy probands].
UNLABELLED: Purpose of the investigation was to evaluate the differences of movement density during the sleep stages and waking. 22 diurnally active, healthy, male volunteers of mean age 30.7 (+/-Standard deviation +/- 3.3) years and a Body-Mass-Index 23.6 +/- 3.3 kg/m2 participated in the study. All subjects were recorded in the sleep lab via cardiorespiratory polysomnography and wrist actigraphy (Ambulatory Monitoring, Ardsley, USA) worn on the non-dominant hand, for two consecutive nights. The activity data, consisting of the number of zero crossings (NZC) were recorded in 1-minute periods. Sleep stages were scored visually according to standard criteria. EEG- and actigraphy data were converted to the same data format (European Feature Files). Attaching the actimetry data to the sleep stages was calculated mean NZC for every sleep stage and Wake. In spite of high differences in total individual NZC we observed that most NZC occurred during Wake. NREM 1 movement density was significantly higher in 19 recordings (86%) than in any other sleep stage. In 18 cases (82%) lowest movement density was found in NREM 3/4 with significant difference to all other sleep stages. Within 50% of the recordings were found decreasing activity in the following sequence of stages: Wake > NREM 1 > REM > NREM 2 > NREM 3/4 However, in all other cases there was a varying pattern of activity. CONCLUSION: Although there is some correlation between motor activity and sleep stages, the predictive value of actimetry data analysis in the assessment of sleep structure appeared to be limited mainly by individual movement density, especially during REM and NREM 2.
Adult↗
[Auto sleep staging and sleep quality estimation based on BP neural network].
To estimate the sleep quality, a 3-layer BP neural network was studied. The EEG complexity and the power spectrum of sleep-multigraph served as the input vector of the network . All-night sleep-stage scoring was performed. Then several parameters (sleep period, shallow sleep period, deep sleep period, REM period, ratio of the wakeful period and sleep one) were defined to estimate the sleep quality. The experiments revealed that the estimated sleep condition was the same as the subjects' impression. The data on six cases of all-night sleep show that this method is available to estimate the sleep quality.
Electroencephalography↗
Relationship of epileptic seizures to sleep stage and sleep depth.
STUDY OBJECTIVES: Interictal epileptiform discharges (IEDs) are facilitated by NREM stages 3 and 4 sleep and as sleep is deepening. To determine whether sleep influences seizures in a similar way to IEDs, we examined seizure rates in various stages of sleep in epilepsy patients undergoing overnight video-EEG-polysomnography (VPSG). DESIGN: Cross-sectional study. SETTING: Neurology Department. PATIENTS, MEASUREMENTS, AND INTERVENTIONS: We reviewed VPSGs from our Sleep and Epilepsy Laboratories to identify patients with recorded seizures during sleep. A total of 55 patients having 117 seizures were identified. RESULTS: Ninety-five percent of seizures occurred in NREM sleep (61% in stage 2, 20% in stage 1, 14% in stages 3 and 4 combined), and 5% in REM sleep. Adjusting for time spent in each stage of sleep, patients had 0.34 seizures per hour in stage 1, 0.38 seizures per hour in stage 2, 0.29 seizures/hr in stage 3 and 4 combined, and 0.09 seizures per hour in REM sleep. Seizures/hour was higher in NREM sleep (0.35 for NREM and 0.09 for REM; p=0.0001). For single seizures occurring in 1 night, seizure rate was significantly higher in NREM stages 1 and 2 as compared to NREM stages 3 and 4 sleep. A significant increase in log delta power, an automated measure of sleep depth, was observed in the 10 minutes prior to seizures. CONCLUSIONS: Both seizures and IEDs are facilitated by NREM sleep. While deeper stages of NREM sleep activate IEDs, lighter stages of NREM sleep promote seizures, at least for single seizures occurring in 1 night.
Adolescent↗
Effect of ritanserin on sleep stages and sleep EEG in the rat.
Ritanserin (1.0 and 2.5 mg/kg i.p.) was administered to rats before the start, of the light period, and sleep was recorded during the subsequent 12 h. The higher dose reduced sleep in the first 3 h. Both doses caused a more prolonged suppression of REM sleep. Spectral analysis of the EEG in non-REM sleep showed an increase of power density in the low frequency range (1.5-6 Hz) and a depression in the high frequency range (8-25 Hz). Since these changes differ from those previously observed after sleep deprivation, it is premature to conclude that the drug induces a physiological sleep intensification.
Animals↗
Approaches to staging sleep in polysomnographic studies with epileptic activity.
BACKGROUND: The Standardized Sleep Manual of Rechtschaffen and Kales is well established and reliable in scoring the majority of polysomnograms (PSGs) encountered in clinical practice. In patients with epilepsy, however, abnormal brain activity may confound the interpretation of sleep waveforms. Our goal is to identify features that are problematic in analyzing sleep stages in patients with epilepsy and to offer approaches to score these PSGs. METHODS: Ninety eight PSGs from 43 patients with epilepsy were scored using Rechtschaffen and Kales guidelines. Features interfering with sleep staging were noted. RESULTS: In scoring polysomnograms (PSGs) of patients with epilepsy we noted epileptic seizures, interictal epileptiform discharges (IEDs) and abnormal EEG background to be features of epilepsy that compromised sleep scoring. Overall, 48% of the studies in our sample contained one or more of these epileptic features to the extent that sleep scoring by standard criteria was compromised. Approaches for staging sleep in the setting of these abnormalities are outlined. CONCLUSIONS: The Rechtschaffen and Kales method of sleep scoring is useful in staging the majority of PSGs of patients with epilepsy. However, we advocate some modifications because the abnormal electrical activity of epilepsy may interfere with accurate scoring of sleep waveforms. These approaches to scoring PSGs of patients with epilepsy will require empirical testing.
Electroencephalography↗
[Application of complexity sequence in sleep staging based on sleep EEG data].
In this paper an approach of time-window complexity sequence is applied to sleep EEG analysis. This approach can reduce the loss of state information due to the nonstationarity of EEG signal and the unevenness of state space, and can overcome certain limitations of the complexity itself to some extent. It will help to extract the state features of EEG in different sleep stages. In addition, we preprocess EEG by adopting ICA and wavelet transform (WT). The results show that some physiological artifact in EEG can be eliminated effectively by these methods, and the sleep staging based on sleep EEG data will be more exact.
Algorithms↗
Gastric acid secretion and sleep stages during natural night sleep.
Gastric acid secretion during natural sleep was studied in 4 healthy female volunteers for 11 nights. Acid output was measured by means of intragastric titration and a telemetering capsule, and sleep was monitored continuously by recording EEG and eye movements. Compared to the waking state, sleep was found to be associated with significantly lower levels of acid secretion. Although there were no significant differences between acid secretion during sleep stages 1 to 4 and rapid eye movement (REM), acid secretion decreased with deeper stages of sleep. During all REM phases only small amounts of acid were produced. Arousal or periods of waking in the course of the night, as well as waking in the morning, were associated with an increase in acid output.
Adult↗
Dynamics of heart rate and sleep stages in normals and patients with sleep apnea.
Sleep is not just the absence of wakefulness but a regulated process with an important restorative function. Based on electroencephalographic recordings and characteristic patterns and waveforms we can distinguish wakefulness and five sleep stages grouped into light sleep, deep sleep, and rapid-eye-movement (REM) sleep. In order to explore the functions of sleep and sleep stages, we investigated the dynamics of sleep stages over the night and of heart-rate variability during the different sleep stages. Sleep stages and intermediate wake states have different distributions of their duration and this allows us to create a model for the temporal sequence of sleep stages and wake states. Heart rate is easily accessed with a high precision by the recording and analysis of the electrocardiogram (ECG). Heart-rate regulation is part of the autonomous nervous system and sympathetic tone is strongly influenced by the sleep stages.
Heart Rate↗
[Slow eye movements and transitional periods of EEG sleep stages during daytime sleep].
Slow eye movements (SEMs) were analyzed in 28 young adult females during daytime sleep. Data from transitional periods of each EEG stage were obtained by accumulating its epoch series synchronized to the onset or termination of the other stages. Sleepiness was reported by the subject by pressing a button switch. SEMs were prominent at the transitional period of stage W approaching the onset of stage 1 (sleep tendency). They declined with deepening of sleep at the transitional periods of EEG stages 22 and 2, and disappeared completely during slow wave sleep (SWS) periods. The recovery of SEMs occurred towards awakening at every EEG transitional period except for SWS. The individual difference in the appearance of SEMs was partly explained by a positive correlation with stage 3 latency: the longer the latency was, the larger the mean SEMs. Perceived sleepiness increased in proportion to SEMs during the entry and re-entry periods to sleep. These results suggest that SEMs are strongly associated with a wake-sleep transition.
Adult↗
Cardiorespiratory-based sleep staging in subjects with obstructive sleep apnea.
A cardiorespiratory-based automatic sleep staging system for subjects with sleep-disordered breathing is described. A simplified three-state system is used: Wakefulness (W), rapid eye movement (REM) sleep (R), and non-REM sleep (S). The system scores the sleep stages in standard 30-s epochs. A number of features associated with the epoch RR-intervals, an inductance plethysmography estimate of rib cage respiratory effort, and an electrocardiogram-derived respiration (EDR) signal were investigated. A subject-specific quadratic discriminant classifier was trained, randomly choosing 20% of the subject's epochs (in appropriate proportions of W, S and R) as the training data. The remaining 80% of epochs were presented to the classifier for testing. An estimated classification accuracy of 79% (Cohen's kappa value of 0.56) was achieved. When a similar subject-independent classifier was trained, using epochs from all other subjects as the training data, a drop in classification accuracy to 67% (kappa = 0.32) was observed. The subjects were further broken in groups of low apnoea-hypopnea index (AHI) and high AHI and the experiments repeated. The subject-specific classifier performed better on subjects with low AHI than high AHI; the performance of the subject-independent classifier is not correlated with AHI. For comparison an electroencephalograms (EEGs)-based classifier was trained utilizing several standard EEG features. The subject-specific classifier yielded an accuracy of 87% (kappa = 0.75), and an accuracy of 84% (kappa = 0.68) was obtained for the subject-independent classifier, indicating that EEG features are quite robust across subjects. We conclude that the cardiorespiratory signals provide moderate sleep-staging accuracy, however, features exhibit significant subject dependence which presents potential limits to the use of these signals in a general subject-independent sleep staging system.
Algorithms↗
Motor responsiveness to stimuli presented during sleep: the influence of time-of-testing on sleep stage analyses.
The relationship between time-of-night of testing (circadian factors) and motor responsiveness to stimuli presented during different stages of sleep was examined. Nine males slept for two nonconsecutive nights in the laboratory. On Night 1, tympanic temperature was assessed at 30 min intervals. On Night 2, responsiveness was assessed with an incremental series of tones presented in sleep stages 2, 3/4, and REM throughout the night. Subjects were instructed to make a microswitch closure to the tones. Results showed that for all stages, responsiveness decreased across thirds of the night. Because the distribution of each sleep stage differed across the night, the effects on responsiveness due to time-of-testing and to sleep stage were confounded. When time-of-testing was held constant, responsiveness was greater in stages 2 and REM than in stage 3/4. When time-of-testing was not held constant, effects nearly opposite of the latter could be demonstrated.
Arousal↗
Assessment of the nocturnal blood pressure relative to sleep stages in patients with obstructive sleep apnea.
To determine the mean blood pressure relative to sleep stages, two nocturnal cardiorespiratory polysomnographs were recorded in 60 male patients with hypertension and obstructive sleep apnea (OSA). The mean age was 50.2 years, the BMI 32.0 kg/m2, the respiratory disturbance index (RDI) 44, and the blood pressure by the WHO protocol 158/98 mm Hg. A new evaluation program was used to determine the invasively measured mean arterial pressure (mean +/- SEM) and heart rate (mean +/- SEM) during sleep (mean total sleep time 361 +/- 48 min) referred to sleep stages 1 (99.5 +/- 1.5 mm Hg/67.6 +/- 1.1 bpm), 2 (98.7 +/- 1.6 mm Hg/66.6 +/- 1.1 bpm), 3 (97.6 +/- 1.8 mm Hg/67.4 +/- 1.3 bpm), and 4 (97.6 +/- 2.2 mm Hg/66.3 +/- 1.6 bpm) and to REM sleep (103.3 +/- 1.7 mm Hg/68 +/- 1.2 bpm) as 1 s mean values and to compare them with the waking state (98.3 +/- 1.6 mm Hg/83.6 +/- 1.1 bpm). There was no physiological fall in blood pressure in patients with pronounced OSA. Sleep-stage-specific analysis of invasive continuous blood pressure signals is the gold standard. The sleep structure is disturbed less than with other methods.
Adult↗
Analysis of the sleep stages in sleep-wakefulness regimens of varied length.
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Adolescent↗
Heart rate variability during sleep stages in normals and in patients with sleep apnea.
Heart rate and heart rate variability are under the control of the autonomous nervous system. It can be assumed that during sleep internal influences dominate the autonomous nervous system. During the different sleep stages heart rate regulation differs in normal subjects. Obstructive sleep apnea is a disorder which has its origin in sleep and has strong modulating effects on the autonomous nervous system with prominent heart rate variations in consequence. In order to separate the influences of sleep stages and sleep apnea on heart rate variability we applied detrended fluctuation analysis in 12 healthy subjects and 20 patients with sleep apnea. We could show that the differences between sleep stages observed in healthy subjects were still present in subjects with sleep apnea despite their cyclical variation in heart rate. We conclude, that detrended fluctuation analysis is able to separate the influences of sleep stages and sleep apnea on heart rate variability.
Autonomic Nervous System↗
Arousals and sleep stages in patients with obstructive sleep apnoea syndrome: Changes under nCPAP treatment.
Nocturnal arousals are the essential cause of disturbed sleep structure in patients with obstructive sleep apnoea syndrome (OSAS). The aim of this study was to analyse the relationship between sleep stages, respiratory (type-R) and movement (type-M) related EEG arousals. Furthermore, the value of these arousals as a criterion for the efficiency of nCPAP treatment was estimated. We examined 38 male patients aged between 30 and 71 (49.1 +/- 20.9 SD) y. All patients suffered from OSAS. The mean respiratory disturbance index (RDI) was 47.3 +/- 27.8 per h. Polysomnographic monitoring was carried out on 4 subsequent nights: baseline night, 2 nights of nCPAP titration and nCPAP control night. Sleep was visually scored and EEG arousals were classified into type R and M, depending on whether changes of respiration or movement caused the arousal. The RDI, the R index (type-R/h), the M index (type-M/h) and the R and M indices in different sleep stages were calculated. During the baseline night a deficit of slow wave sleep (SWS) and REM sleep was found. Furthermore there were more type-R than type-M arousals registered (17.4 h-1 [3.6-43.6] vs. 5.9 h-1 [1.6-11.8]) (P < 0.01). They occurred during stages NREM 1, NREM 2 and REM (P < 0.01). An SWS sleep rebound and a reduction of the SWS and REM latencies were already found during the first CPAP night. The R index was reduced during the first CPAP night in all sleep stages (P < 0.01) and remained approximately the same in the following 2 nights (3. CPAP night: 1.1 h-1 [0.3-5.0]). Type M arousals occurred more in stages 1 and 2 (P < 0.01), and remained unchanged under nCPAP. We concluded that differentiation of nocturnal arousals may provide more detailed information regarding the influence of breathing disturbances on sleep. Respiratory related, not movement related, arousals may be a useful additional tool in judging the efficiency of OSAS.
Adult↗