Showing papers on "Slow-wave sleep published in 2020"

Astrocytic Ca2+ signaling is reduced during sleep and is involved in the regulation of slow wave sleep

Abstract: Astrocytic Ca2+ signaling has been intensively studied in health and disease but has not been quantified during natural sleep. Here, we employ an activity-based algorithm to assess astrocytic Ca2+ signals in the neocortex of awake and naturally sleeping mice while monitoring neuronal Ca2+ activity, brain rhythms and behavior. We show that astrocytic Ca2+ signals exhibit distinct features across the sleep-wake cycle and are reduced during sleep compared to wakefulness. Moreover, an increase in astrocytic Ca2+ signaling precedes transitions from slow wave sleep to wakefulness, with a peak upon awakening exceeding the levels during whisking and locomotion. Finally, genetic ablation of an important astrocytic Ca2+ signaling pathway impairs slow wave sleep and results in an increased number of microarousals, abnormal brain rhythms, and an increased frequency of slow wave sleep state transitions and sleep spindles. Our findings demonstrate an essential role for astrocytic Ca2+ signaling in regulating slow wave sleep.

Deep learning for automated sleep staging using instantaneous heart rate.

Abstract: Clinical sleep evaluations currently require multimodal data collection and manual review by human experts, making them expensive and unsuitable for longer term studies Sleep staging using cardiac rhythm is an active area of research because it can be measured much more easily using a wide variety of both medical and consumer-grade devices In this study, we applied deep learning methods to create an algorithm for automated sleep stage scoring using the instantaneous heart rate (IHR) time series extracted from the electrocardiogram (ECG) We trained and validated an algorithm on over 10,000 nights of data from the Sleep Heart Health Study (SHHS) and Multi-Ethnic Study of Atherosclerosis (MESA) The algorithm has an overall performance of 077 accuracy and 066 kappa against the reference stages on a held-out portion of the SHHS dataset for classifying every 30 s of sleep into four classes: wake, light sleep, deep sleep, and rapid eye movement (REM) Moreover, we demonstrate that the algorithm generalizes well to an independent dataset of 993 subjects labeled by American Academy of Sleep Medicine (AASM) licensed clinical staff at Massachusetts General Hospital that was not used for training or validation Finally, we demonstrate that the stages predicted by our algorithm can reproduce previous clinical studies correlating sleep stages with comorbidities such as sleep apnea and hypertension as well as demographics such as age and gender

Stress and sleep: A survey based on wearable sleep trackers among medical and nursing staff in Wuhan during the COVID-19 pandemic

Abstract: Backgroud COVID-19 pandemic has significantly affected the sleep health of local medical and nursing staff. Aim We used wearable pulse oximeters to monitor and screen the medical and nursing staff working in hospitals designated for COVID-19 in the Wuhan area. This study aimed to establish a reliable basis to provide sleep intervention for the medical and nursing staff. Methods Thirty medical and nursing staff members with symptoms of insomnia were instructed to wear medical ring-shaped pulse oximeters to monitor their sleep overnight. We also used the Insomnia Severity Index (ISI) and the Chinese version of the Self-Reporting Questionnaire (SRQ-20) to evaluate the severity of insomnia and mental health status, respectively, for each participant. Results Among the 30 participants, only 26 completed the screening. Ten cases (38.5%) demonstrated moderate to severe sleep apnoea-hypopnea syndrome (SAHS) when using an oxygen desaturation index ≥15 times/hour as the cut-off value. Participants with comorbid moderate to severe SAHS had significantly higher ISI and SRQ scores (p values 0.034 and 0.016, respectively) than those in the insomnia group. Correlation analysis revealed that ISI was positively correlated with total sleep time (TST) (r=0.435, p=0.026), and negatively correlated with deep sleep (r=-0.495, p=0.010); furthermore, patient SRQ scores were positively correlated with TST, sleep efficiency (SE) and REM (rapid eyes movement) sleep % (r=0.454 and 0.389, 0.512; p=0.020, 0.050 and 0.008, respectively). Stepwise logistic regression indicated that SRQ-20 and sex were risk factors for insomnia with comorbid SAHS, and their OR values were 1.516 and 11.56 (95% CI 1.053 to 2.180 and 1.037 to 128.9), respectively. Conclusion Medical and nursing staff with insomnia showed clear signs of comorbid sleep apnoea attributable to stress. The wearable pulse oximeters accurately monitored the participants' breathing when asleep.

Validity, potential clinical utility, and comparison of consumer and research-grade activity trackers in Insomnia Disorder I: In-lab validation against polysomnography.

Abstract: Consumer activity trackers claiming to measure sleep/wake patterns are ubiquitous within clinical and consumer settings. However, validation of these devices in sleep disorder populations are lacking. We examined 1 night of sleep in 42 individuals with insomnia (mean = 49.14 ± 17.54 years) using polysomnography, a wrist actigraph (Actiwatch Spectrum Pro: AWS) and a consumer activity tracker (Fitbit Alta HR: FBA). Epoch-by-epoch analysis and Bland-Altman methods evaluated each device against polysomnography for sleep/wake detection, total sleep time, sleep efficiency, wake after sleep onset and sleep latency. FBA sleep stage classification of light sleep (N1 + N2), deep sleep (N3) and rapid eye movement was also compared with polysomnography. Compared with polysomnography, both activity trackers displayed high accuracy (81.12% versus 82.80%, AWS and FBA respectively; ns) and sensitivity (sleep detection; 96.66% versus 96.04%, respectively; ns) but low specificity (wake detection; 39.09% versus 44.76%, respectively; p = .037). Both trackers overestimated total sleep time and sleep efficiency, and underestimated sleep latency and wake after sleep onset. FBA demonstrated sleep stage sensitivity and specificity, respectively, of 79.39% and 58.77% (light), 49.04% and 95.54% (deep), 65.97% and 91.53% (rapid eye movement). Both devices were more accurate in detecting sleep than wake, with equivalent sensitivity, but statistically different specificity. FBA provided equivalent estimates as AWS for all traditional actigraphy sleep parameters. FBA also showed high specificity when identifying N3, and rapid eye movement, though sensitivity was modest. Thus, it underestimates these sleep stages and overestimates light sleep, demonstrating more shallow sleep than actually obtained. Whether FBA could serve as a low-cost substitute for actigraphy in insomnia requires further investigation.

Susceptibility to auditory closed-loop stimulation of sleep slow oscillations changes with age

Abstract: Study Objectives Cortical slow oscillations (SOs) and thalamocortical sleep spindles hallmark slow wave sleep and facilitate memory consolidation, both of which are reduced with age. Experiments utilizing auditory closed-loop stimulation to enhance these oscillations showed great potential in young and older subjects. However, the magnitude of responses has yet to be compared between these age groups. We examined the possibility of enhancing SOs and performance on different memory tasks in a healthy middle-aged population using this stimulation and contrast effects to younger adults. Methods In a within-subject design, 17 subjects (55.7 ± 1.0 years) received auditory stimulation in synchrony with SO up-states, which was compared to a no-stimulation sham condition. Overnight memory consolidation was assessed for declarative word-pairs and procedural finger-tapping skill. Post-sleep encoding capabilities were tested with a picture recognition task. Electrophysiological effects of stimulation were compared to a previous younger cohort (n = 11, 24.2 ± 0.9 years). Results Overnight retention and post-sleep encoding performance of the older cohort revealed no beneficial effect of stimulation, which contrasts with the enhancing effect the same stimulation protocol had in our younger cohort. Auditory stimulation prolonged endogenous SO trains and induced sleep spindles phase-locked to SO up-states in the older population. However, responses were markedly reduced compared to younger subjects. Additionally, the temporal dynamics of stimulation effects on SOs and spindles differed between age groups. Conclusions Our findings suggest that the susceptibility to auditory stimulation during sleep drastically changes with age and reveal the difficulties of translating a functional protocol from younger to older populations.

Network Physiology of Cortico-Muscular Interactions.

Abstract: Skeletal muscle activity is continuously modulated across physiologic states to provide coordination, flexibility and responsiveness to body tasks and external inputs. Despite the central role the muscular system plays in facilitating vital body functions, the network of brain-muscle interactions required to control hundreds of muscles and synchronize their activation in relation to distinct physiologic states has not been investigated. Recent approaches have focused on general associations between individual brain rhythms and muscle activation during movement tasks. However, the specific forms of coupling, the functional network of cortico-muscular coordination, and how network structure and dynamics are modulated by autonomic regulation across physiologic states remains unknown. To identify and quantify the cortico-muscular interaction network and uncover basic features of neuro-autonomic control of muscle function, we investigate the coupling between synchronous bursts in cortical rhythms and peripheral muscle activation during sleep and wake. Utilizing the concept of time delay stability and a novel network physiology approach, we find that the brain-muscle network exhibits complex dynamic patterns of communication involving multiple brain rhythms across cortical locations and different electromyographic frequency bands. Moreover, our results show that during each physiologic state the cortico-muscular network is characterized by a specific profile of network links strength, where particular brain rhythms play role of main mediators of interaction and control. Further, we discover a hierarchical reorganization in network structure across physiologic states, with high connectivity and network link strength during wake, intermediate during REM and light sleep, and low during deep sleep, a sleep-stage stratification that demonstrates a unique association between physiologic states and cortico-muscular network structure. The reported empirical observations are consistent across individual subjects, indicating universal behavior in network structure and dynamics, and high sensitivity of cortico-muscular control to changes in autonomic regulation, even at low levels of physical activity and muscle tone during sleep. Our findings demonstrate previously unrecognized basic principles of brain-muscle network communication and control, and provide new perspectives on the regulatory mechanisms of brain dynamics and locomotor activation, with potential clinical implications for neurodegenerative, movement and sleep disorders, and for developing efficient treatment strategies.

Sleep spindles facilitate selective memory consolidation

Abstract: Sleep has been shown to be critical for memory consolidation, and recent research has demonstrated that this consolidation effect is selective, with certain memories being prioritized for strengthening. Initial strength of a memory appears to be one metric the brain uses to prioritize memory traces for sleep-based consolidation, but the role of consolidation-mediating cortical oscillations, such as sleep spindles and slow oscillations, has not been explored. Here, N=54 participants studied pairs of words to three distinct encoding strengths, with recall being tested immediately following learning and again six hours later. N=36 had a two-hour afternoon nap opportunity following learning, whilst the remaining (n=18) remained awake throughout. Results showed a selective benefit of sleep on memory, with sleep preferentially consolidating weakly encoded items (p=.003). The magnitude of this effect (d=0.90, 95% CI=0.29-1.50) was similar when compared to a previous study examining the benefits of a full night of sleep (d=1.36, 95% CI=0.59-2.12). Within the nap group, consolidation of weakly encoded items was associated with sleep spindle density during slow wave sleep (r=.48, p=.003). This association was present when separately examining spindles coupled (r=.41, p=.013), and uncoupled (r=.44, p=.007) with slow oscillations. Memory was significantly better in individuals who showed an amount of slow oscillation-spindle coupling that was greater than what would be expected by chance (p=.006, d=1.15). These relationships were unique to weakly encoded items, with spindles not correlating with memory for intermediate or strong items. This suggests that sleep spindles facilitate selective memory consolidation, guided in part by memory strength.

Slow Waves Promote Sleep-Dependent Plasticity and Functional Recovery after Stroke.

Abstract: Functional recovery after stroke is associated with a remapping of neural circuits. This reorganization is often associated with low-frequency, high-amplitude oscillations in the peri-infarct zone in both rodents and humans. These oscillations are reminiscent of sleep slow waves (SW) and suggestive of a role for sleep in brain plasticity that occur during stroke recovery; however, direct evidence is missing. Using a stroke model in male mice, we showed that stroke was followed by a transient increase in NREM sleep accompanied by reduced amplitude and slope of ipsilateral NREM sleep SW. We next used 5 ms optical activation of Channelrhodopsin 2-expressing pyramidal neurons, or 200 ms silencing of Archeorhodopsin T-expressing pyramidal neurons, to generate local cortical UP, or DOWN, states, respectively, both sharing similarities with spontaneous NREM SW in freely moving mice. Importantly, we found that single optogenetically evoked SW (SWopto) in the peri-infarct zone, randomly distributed during sleep, significantly improved fine motor movements of the limb corresponding to the sensorimotor stroke lesion site compared with spontaneous recovery and control conditions, while motor strength remained unchanged. In contrast, SWopto during wakefulness had no effect. Furthermore, chronic SWopto during sleep were associated with local axonal sprouting as revealed by the increase of anatomic presynaptic and postsynaptic markers in the peri-infarct zone and corresponding contralesional areas to cortical circuit reorganization during stroke recovery. These results support a role for sleep SW in cortical circuit plasticity and sensorimotor recovery after stroke and provide a clinically relevant framework for rehabilitation strategies using neuromodulation during sleep. SIGNIFICANCE STATEMENT Brain stroke is one of the leading causes of death and major disabilities in the elderly worldwide. A better understanding of the pathophysiological mechanisms underlying spontaneous brain plasticity after stroke, together with an optimization of rehabilitative strategies, are essential to improve stroke treatments. Here, we investigate the role of optogenetically induced sleep slow waves in an animal model of ischemic stroke and identify sleep as a window for poststroke intervention that promotes neuroplasticity and facilitates sensorimotor recovery.

Four-Year Trends in Sleep Duration and Quality: A Longitudinal Study Using Data from a Commercially Available Sleep Tracker.

Abstract: Background: Population estimates of sleep duration and quality are inconsistent because they rely primarily on self-reported data. Passive and ubiquitous digital tracking and wearable devices may provide more accurate estimates of sleep duration and quality. Objective: This study aimed to identify trends in sleep duration and quality in New York City based on 2 million nights of data from users of a popular mobile sleep app. Methods: We examined sleep duration and quality using 2,161,067 nights of data captured from 2015 to 2018 by Sleep Cycle, a popular sleep-tracking app. In this analysis, we explored differences in sleep parameters based on demographic factors, including age and sex. We used graphical matrix representations of data (heat maps) and geospatial analyses to compare sleep duration (in hours) and sleep quality (based on time in bed, deep sleep time, sleep consistency, and number of times fully awake), considering potential effects of day of the week and seasonality. Results: Women represented 46.43% (1,003,421/2,161,067) of the sample, and men represented 53.57% (1,157,646/2,161,067) of individuals in the sample. The average age of the sample was 31.0 years (SD 10.6). The mean sleep duration of the total sample was 7.11 hours (SD 1.4). Women slept longer on average (mean 7.27 hours, SD 1.4) than men (mean 7 hours, SD 1.3; PPP<.001). Conclusions: Our study of data from a commercially available sleep tracker showed that women experienced longer sleep duration and higher sleep quality in nearly every age group than men, and a low proportion of young adults obtained the recommended sleep duration. Future research may compare sleep measures obtained via wearable sleep trackers with validated research-grade measures of sleep.

Development of Automated Sleep Stage Classification System Using Multivariate Projection-Based Fixed Boundary Empirical Wavelet Transform and Entropy Features Extracted from Multichannel EEG Signals.

Abstract: The categorization of sleep stages helps to diagnose different sleep-related ailments. In this paper, an entropy-based information–theoretic approach is introduced for the automated categorization of sleep stages using multi-channel electroencephalogram (EEG) signals. This approach comprises of three stages. First, the decomposition of multi-channel EEG signals into sub-band signals or modes is performed using a novel multivariate projection-based fixed boundary empirical wavelet transform (MPFBEWT) filter bank. Second, entropy features such as bubble and dispersion entropies are computed from the modes of multi-channel EEG signals. Third, a hybrid learning classifier based on class-specific residuals using sparse representation and distances from nearest neighbors is used to categorize sleep stages automatically using entropy-based features computed from MPFBEWT domain modes of multi-channel EEG signals. The proposed approach is evaluated using the multi-channel EEG signals obtained from the cyclic alternating pattern (CAP) sleep database. Our results reveal that the proposed sleep staging approach has obtained accuracies of 91.77%, 88.14%, 80.13%, and 73.88% for the automated categorization of wake vs. sleep, wake vs. rapid eye movement (REM) vs. Non-REM, wake vs. light sleep vs. deep sleep vs. REM sleep, and wake vs. S1-sleep vs. S2-sleep vs. S3-sleep vs. REM sleep schemes, respectively. The developed method has obtained the highest overall accuracy compared to the state-of-art approaches and is ready to be tested with more subjects before clinical application.

Role of Ovarian Hormones in the Modulation of Sleep in Females Across the Adult Lifespan.

Abstract: Ovarian hormones, including 17β-estradiol, are implicated in numerous physiological processes, including sleep. Beginning at puberty, girls report more sleep complaints than boys, which is maintained throughout the reproductive life stage. Sleep problems are exacerbated during the menopausal transition, evidenced by greater risk for sleep disorders. There is emerging evidence that menopause-associated hormone loss contributes to this elevated risk, but age is also an important factor. The extent to which menopause-associated sleep disturbance persists into postmenopause above and beyond the effects of age remains unknown. Untreated sleep disturbances have important implications for cognitive health, as they are emerging as risk factors for dementia. Given that sleep loss impairs memory, an important knowledge gap concerns the role played by menopause-associated hormone loss in exacerbating sleep disturbance and ultimately, cognitive function in aging women. In this review, we take a translational approach to illustrate the contribution of ovarian hormones in maintaining the sleep-wake cycle in younger and middle-aged females, with evidence implicating 17β-estradiol in supporting the memory-promoting effects of sleep. Sleep physiology is briefly reviewed before turning to behavioural and neural evidence from young females linking 17β-estradiol to sleep-wake cycle maintenance. Implications of menopause-associated 17β-estradiol loss is also reviewed before discussing how ovarian hormones may support the memory-promoting effects of sleep, and why menopause may exacerbate pathological aging via effects on sleep. While still in its infancy, this research area offers a new sex-based perspective on aging research, with a focus on a modifiable risk factor for pathological aging.

Encoding, Consolidation, and Renormalization in Depression: Synaptic Homeostasis, Plasticity, and Sleep Integrate Rapid Antidepressant Effects.

Abstract: Recent studies have strived to find an association between rapid antidepressant effects and a specific subset of pharmacological targets and molecular pathways. Here, we propose a broader hypothesis of encoding, consolidation, and renormalization in depression (ENCORE-D), which suggests that, fundamentally, rapid and sustained antidepressant effects rely on intrinsic homeostatic mechanisms evoked as a response to the acute pharmacological or physiologic effects triggered by the treatment. We review evidence that supports the notion that various treatments with a rapid onset of action, such as ketamine, electroconvulsive therapy, and sleep deprivation, share the ability to acutely excite cortical networks, which increases synaptic potentiation, alters patterns of functional connectivity, and ameliorates depressive symptoms. We proceed to examine how the initial effects are short-lived and, as such, require both consolidation during wake and maintenance throughout sleep to remain sustained. Here, we incorporate elements from the synaptic homeostasis hypothesis and theorize that the fundamental mechanisms of synaptic plasticity and sleep, particularly the homeostatic emergence of slow-wave electroencephalogram activity and the renormalization of synaptic strength, are at the center of sustained antidepressant effects. We conclude by discussing the various implications of the ENCORE-D hypothesis and offer several considerations for future experimental and clinical research. SIGNIFICANCE STATEMENT: Proposed molecular perspectives of rapid antidepressant effects fail to appreciate the temporal distribution of the effects of ketamine on cortical excitation and plasticity as well as the prolonged influence on depressive symptoms. The encoding, consolidation, and renormalization in depression hypothesis proposes that the lasting clinical effects can be best explained by adaptive functional and structural alterations in neural circuitries set in motion in response to the acute pharmacological effects of ketamine (i.e., changes evoked during the engagement of receptor targets such as N-methyl-D-aspartate receptors) or other putative rapid-acting antidepressants. The present hypothesis opens a completely new avenue for conceptualizing and targeting brain mechanisms that are important for antidepressant effects wherein sleep and synaptic homeostasis are at the center stage.

Moderate-intensity exercise performed in the evening does not impair sleep in healthy males.

Abstract: The aim of this study was to examine the effect of single bouts of moderate-intensity aerobic exercise and moderate-intensity resistance exercise performed in the evening on the sleep of healthy yo...

(Not so) Smart sleep tracking through the phone: Findings from a polysomnography study testing the reliability of four sleep applications

Abstract: An increasing number of sleep applications are currently available and are being widely used for in-home sleep tracking. The present study assessed four smartphone applications (Sleep Cycle-Accelerometer, SCa; Sleep Cycle-Microphone, SCm; Sense, Se; Smart Alarm, SA) designed for sleep-wake detection through sound and movement sensors, by comparing their performance with polysomnography. Twenty-one healthy participants (six males, 15 females) used the four sleep applications running on iPhone (provided by the experimenter) simultaneously with portable polysomnography recording at home, while sleeping alone for two consecutive nights. Whereas all apps showed a significant correlation with polysomnography-time in bed, only SA offered significant correlations for sleep efficacy. Furthermore, SA seemed to be quite effective in reliable detection of total sleep time and also light sleep; however, it underestimated wake and partially overestimated deep sleep. None of the apps resulted capable of detecting and scoring rapid eye movement sleep. To sum up, SC (functioning through both accelerometer and microphone) and Se did not result sufficiently reliable in sleep-wake detection compared with polysomnography. SA, the only application offering the possibility of an epoch-by-epoch analysis, showed higher accuracy than the other apps in comparison with polysomnography, but it still shows some limitations, particularly regarding wake and deep sleep detection. Developing scoring algorithms specific for smartphone sleep detection and adding external sensors to record other physiological parameters may overcome the present limits of sleep tracking through smart phone apps.

Stimulation Augments Spike Sequence Replay and Memory Consolidation during Slow-Wave Sleep

Abstract: Newly acquired memory traces are spontaneously reactivated during slow-wave sleep (SWS), leading to the consolidation of recent memories. Empirical studies found that sensory stimulation during SWS can selectively enhance memory consolidation with the effect depending on the phase of stimulation. In this new study, we aimed to understand the mechanisms behind the role of sensory stimulation on memory consolidation using computational models implementing effects of neuromodulators to simulate transitions between awake and SWS sleep, and synaptic plasticity to allow the change of synaptic connections due to the training in awake or replay during sleep. We found that when closed-loop stimulation was applied during the Down states of sleep slow oscillation, particularly right before the transition from Down to Up state, it significantly affected the spatiotemporal pattern of the slow waves and maximized memory replay. In contrast, when the stimulation was presented during the Up states, it did not have a significant impact on the slow waves or memory performance after sleep. For multiple memories trained in awake, presenting stimulation cues associated with specific memory trace could selectively augment replay and enhance consolidation of that memory and interfere with consolidation of the others (particularly weak) memories. Our study proposes a synaptic-level mechanism of how memory consolidation is affected by sensory stimulation during sleep.SIGNIFICANCE STATEMENT Stimulation, such as training-associated cues or auditory stimulation, during sleep can augment consolidation of the newly encoded memories. In this study, we used a computational model of the thalamocortical system to describe the mechanisms behind the role of stimulation in memory consolidation during slow-wave sleep. Our study suggests that stimulation preferentially strengthens memory traces when delivered at a specific phase of the slow oscillation, just before the Down to Up state transition when it makes the largest impact on the spatiotemporal pattern of sleep slow waves. In the presence of multiple memories, presenting sensory cues during sleep could selectively strengthen selected memories. Our study proposes a synaptic-level mechanism of how memory consolidation is affected by sensory stimulation during sleep.

Hypnotic suggestions given before nighttime sleep extend slow-wave sleep as compared to a control text in highly hypnotizable subjects.

Abstract: While slow-wave sleep (SWS) is fundamental for maintaining health and well-being, it is typically reduced with stress or age. The authors have previously reported that hypnotic suggestions before s...

Sleep Terrors: An Updated Review.

Abstract: Background Sleep terrors are common, frightening, but fortunately benign events. Familiarity with this condition is important so that an accurate diagnosis can be made. Objective To familiarize physicians with the clinical manifestations, diagnosis, and management of children with sleep terrors. Methods A PubMed search was completed in Clinical Queries using the key terms "sleep terrors" OR "night terrors". The search strategy included meta-analyses, randomized controlled trials, clinical trials, observational studies, and reviews. Only papers published in the English literature were included in this review. The information retrieved from the above search was used in the compilation of the present article. Results It is estimated that sleep terrors occur in 1 to 6.5% of children 1 to 12 years of age. Sleep terrors typically occur in children between 4 and 12 years of age, with a peak between 5 and 7 years of age. The exact etiology is not known. Developmental, environmental, organic, psychological, and genetic factors have been identified as a potential cause of sleep terrors. Sleep terrors tend to occur within the first three hours of the major sleep episode, during arousal from stage three or four non-rapid eye movement (NREM) sleep. In a typical attack, the child awakens abruptly from sleep, sits upright in bed or jumps out of bed, screams in terror and intense fear, is panicky, and has a frightened expression. The child is confused and incoherent: verbalization is generally present but disorganized. Autonomic hyperactivity is manifested by tachycardia, tachypnea, diaphoresis, flushed face, dilated pupils, agitation, tremulousness, and increased muscle tone. The child is difficult to arouse and console and may express feelings of anxiety or doom. In the majority of cases, the patient does not awaken fully and settles back to quiet and deep sleep. There is retrograde amnesia for the attack the following morning. Attempts to interrupt a sleep terror episode should be avoided. As sleep deprivation can predispose to sleep terrors, it is important that the child has good sleep hygiene and an appropriate sleeping environment. Medical intervention is usually not necessary, but clonazepam may be considered on a short-term basis at bedtime if sleep terrors are frequent and severe or are associated with functional impairment, such as fatigue, daytime sleepiness, and distress. Anticipatory awakening, performed approximately half an hour before the child is most likely to experience a sleep terror episode, is often effective for the treatment of frequently occurring sleep terrors. Conclusion Most children outgrow the disorder by late adolescence. In the majority of cases, there is no specific treatment other than reassurance and parental education. Underlying conditions, however, should be treated if possible and precipitating factors should be avoided.