Showing papers on "Slow-wave sleep published in 2007"

Neural substrates of awakening probed with optogenetic control of hypocretin neurons

Abstract: The neural underpinnings of sleep involve interactions between sleep-promoting areas such as the anterior hypothalamus, and arousal systems located in the posterior hypothalamus, the basal forebrain and the brainstem. Hypocretin (Hcrt, also known as orexin)-producing neurons in the lateral hypothalamus are important for arousal stability, and loss of Hcrt function has been linked to narcolepsy. However, it is unknown whether electrical activity arising from Hcrt neurons is sufficient to drive awakening from sleep states or is simply correlated with it. Here we directly probed the impact of Hcrt neuron activity on sleep state transitions with in vivo neural photostimulation, genetically targeting channelrhodopsin-2 to Hcrt cells and using an optical fibre to deliver light deep in the brain, directly into the lateral hypothalamus, of freely moving mice. We found that direct, selective, optogenetic photostimulation of Hcrt neurons increased the probability of transition to wakefulness from either slow wave sleep or rapid eye movement sleep. Notably, photostimulation using 5-30 Hz light pulse trains reduced latency to wakefulness, whereas 1 Hz trains did not. This study establishes a causal relationship between frequency-dependent activity of a genetically defined neural cell type and a specific mammalian behaviour central to clinical conditions and neurobehavioural physiology.

Odor cues during slow-wave sleep prompt declarative memory consolidation.

Abstract: Sleep facilitates memory consolidation. A widely held model assumes that this is because newly encoded memories undergo covert reactivation during sleep. We cued new memories in humans during sleep by presenting an odor that had been presented as context during prior learning, and so showed that reactivation indeed causes memory consolidation during sleep. Re-exposure to the odor during slow-wave sleep (SWS) improved the retention of hippocampus-dependent declarative memories but not of hippocampus-independent procedural memories. Odor re-exposure was ineffective during rapid eye movement sleep or wakefulness or when the odor had been omitted during prior learning. Concurring with these findings, functional magnetic resonance imaging revealed significant hippocampal activation in response to odor re-exposure during SWS.

The visual scoring of sleep in adults

Abstract: The 1968 Rechtschaffen and Kales (R & K) sleep scoring man- ual was published 15 years after REM sleep was discovered. Advances in the ensuing 28 years warranted a re-look at visual scoring of sleep stages. This paper describes the work of the AASM Visual Scoring Task Force, including methodology, a literature review and the rationale behind the new rules. Reliability studies of R & K scoring were reviewed; reliabil- ity was low for stage one and moderate for slow wave sleep. Evidence indicated that K complexes and slow waves are expressed maximal fron- tally, spindles centrally and alpha rhythm over the occipital region. Three derivations of EEG, two of electro-oculography, and one of chin EMG were recommended. Scoring by 30-second epochs was retained. New terminology for sleep stages was proposed. Attenuation of alpha rhythm was determined to be the most valid electrophysiological marker of sleep onset. Alternative measures were proposed for non-alpha generating subjects. K complexes associated with arousals were determined to be insufficient alone to define the new stage N2. No evidence was found to justify dividing slow wave sleep into two stages. No reasons were found to alter the current slow wave amplitude criteria at any age. The phenomena of REM sleep were defined. The rules for defining onset and termination of REM sleep periods were simplified. Movement time was eliminated and major body movements defined. Studies are needed to test the reliability of the new rules. Future advances in technology may require modification of these rules with time.

Polysomnographically measured sleep abnormalities in PTSD: A meta-analytic review.

Abstract: Although sleep complaints are common among patients with Posttraumatic stress disorder (PTSD), polysomnographic studies examining sleep abnormalities in PTSD have produced inconsistent results. To clarify discrepant findings, we conducted a meta-analytic review of 20 polysomnographic studies comparing sleep in people with and without PTSD. Results showed that PTSD patients had more stage 1 sleep, less slow wave sleep, and greater rapid-eye-movement density compared to people without PTSD. We also conducted exploratory analyses aimed at examining potential moderating variables (age, sex, and comorbid depression and substance use disorders). Overall, studies with a greater proportion of male participants or a low rate of comorbid depression tended to find more PTSD-related sleep disturbances. These findings suggest that sleep abnormalities exist in PTSD, and that some of the inconsistencies in prior findings may be explained by moderating variables.

Sleep homeostasis and cortical synchronization: III. A high-density EEG study of sleep slow waves in humans.

Abstract: SLOW WAVES ARE THE MOST OBVIOUS AND RECOGNIZABLE FEATURE OF THE HUMAN SLEEP EEG. IN ADDITION TO BEING INDICATIVE OF SLEEP DEPTH,5 SLOW waves are intimately related to sleep regulation: it is well known that SWA (EEG power between 0.5 and 4.0 Hz), which reflects the abundance of low-frequency waves in the EEG, increases as a function of prior waking and declines throughout the course of sleep.6–8 Although the regulation of SWA is suggestive of a restorative function of sleep, the mechanisms responsible for SWA homeostasis remain unclear. It was recently suggested that the level of SWA during sleep may be a function of the strength of cortical synapses due to the influence of synaptic efficacy on network synchronization.1, 2 According to the hypothesis, at the beginning of sleep, synaptic strength would be high due to learning processes occurring during wakefulness, whereas, by the end of sleep, synaptic strength would have decreased through a sleep-dependent process of synaptic downscaling. The hypothesized relationship between synaptic strength and the level of SWA was investigated in a companion paper using a large-scale model of sleep in the thalamocortical system.3 The simulation showed that decreasing synaptic strength among cortical neurons led to a decrease in sleep SWA.3 Intriguingly, synaptic strength reduction also resulted in characteristic changes to several slow-wave parameters, including a decrease in the number of high-amplitude slow waves, a decrease in the slope of slow waves, and more frequent waves with multiple peaks. In a second companion paper, we tested the model's predictions by employing local field potential (LFP) recordings in the rat to compare periods of early and late sleep.4 We found that the decline in SWA in the LFP was associated with the changes in slow-wave parameters predicted by the model. Furthermore, recovery after sleep deprivation resulted in an increased number of high-amplitude slow waves, steeper slopes, and fewer multipeak waves, suggesting that these observed changes in slow-wave parameters are a result of homeostatic sleep regulation and not circadian time. In the present paper, we tested the model's predictions in humans. We used all-night high-density EEG (hd-EEG) recordings to compare non-rapid eye movement (NREM) sleep slow waves at the beginning of the night, when the pressure to sleep is highest, to NREM sleep slow waves toward morning, when sleep pressure has largely dissipated. We found that, as predicted by computer simulations, and in line with rat LFP recordings, the homeostatic decline of SWA during sleep is coupled with a decreased incidence of high-amplitude slow waves, a decreased slope of slow waves, and an increased number of multipeak waves. Moreover, we found that individual peaks of the multipeak waves characteristic of late sleep have distinct cortical origins.

The effect of psychosocial stress on sleep: a review of polysomnographic evidence.

Abstract: This systematic review examines the effect of diverse psychosocial stressors on polysomnographic measures of sleep. Sixty-three articles were located and categorized in terms of the types of stressors imposed. Experimental stress resulted in fairly consistent changes: decreases in slow wave sleep, REM sleep, and sleep efficiency (SE), as well as increases in awakenings. Data were limited in terms of response to non-experimental stressors, except for the case of post-traumatic stress disorder (PTSD) on sleep, where a number of reports suggest that PTSD patients have increased awakenings and decreased SE. Future research needs to define stress more precisely in terms of duration and severity and to measure its impacts on sleep in populations that differ in terms of age, comorbid illness, gender, and so forth. Without such fine-grained analyses, it is difficult to draw definitive conclusions about this important area.

The visual scoring of sleep and arousal in infants and children.

Abstract: Age is probably the single most crucial factor determining how humans sleep Age and level of vigilance significantly influence the electroencephalogram (EEG) and the polysomnogram (PSG) The Pediatric Task Force provide an evidence-based review of the age-related development of the polysomnographic features of sleep in neonates, infants, and children, assessing the reliability and validity of these features, and assessing alternative methods of measurement We used this annotated supporting text to develop rules for scoring sleep and arousals in infants and children A pediatric EEG or PSG can only be determined to be normal by assessing whether the EEG patterns are appropriate for maturational age Sleep in infants at term can be scored as NREM and REM sleep because all the polysomnographic and EEG features of REM sleep are present and quiet sleep, if not NREM sleep, is at least "not REM sleep" The dominant posterior rhythm (DPR) of relaxed wakefulness increases in frequency with age: (1) 35-45 Hz in 75% of normal infants by 3-4 months post-term; (2) 5-6 Hz in most infants 5-6 months post-term; 3) 6 Hz in 70% of normal children by 2 months of age; and 3) 8 Hz (range 75-95 Hz) in 82% of normal children age 3 years, 9 Hz in 65% of 9-year-olds, and 10 Hz in 65% of 15-year-old controls Sleep spindles in children occur independently at two different frequencies and two different scalp locations: 110-1275 Hz over the frontal and 130-1475 Hz over the centroparietal electrodes; these findings are most prominent in children younger than 13 years Centroparietal spikes are often maximal over the vertex (Cz), less often maximal over the left central (C3) or right central (C4) EEG derivation About 50% of sleep spindles within a particular infant's PSG are asynchronous before 6 months of age, 30% at 1 year Based on this, we recommend that: (1) sleep spindles be scored as a polysomnographic signature of NREM stage 2 sleep (N2) at whatever age they are first seen in a PSG, typically present by 2 to 3 months post-term; (2) identify and score sleep spindles from the frontal and centroparietal EEG derivations, especially in infants and children younger than 13 years NREM sleep in an infant or child can be scored if the dominant posterior rhythm occupies 20% of the 30-second epoch contain 05 to 2 Hz >75 microV (usually 100-400 microV) activity as N3 The DPR should be scored in the EEG channel that is best observed, (typically occipital), but DPR reactive to eye opening can be seen in central electrodes Because sleep spindles occur independently over the frontal and central regions in children, they should be scored whether they occur in the frontal or central regions Because sleep spindles are asynchronous before age 2 years, simultaneous recording of left and right frontal and central activity may be warranted in children 1-2 years of age Simultaneous recording of left, right, and midline central electrodes may be appropriate because of the asynchronous nature of sleep spindles before age 2 years, but reliability testing is needed Evidence has shown that the PSG cannot reliably be used to identify neurological deficits or to predict behavior or outcome in infants because of significant diversity of results, even in normal infants Normal sleep EEG patterns and architecture are present in the first year of life, even in infants with severe neurological compromise Increasing evidence suggests that sleep and its disorders play critical roles in the development of healthy children and healthy adults thereafter Reliability studies comparing head-to-head different scoring criteria, recording techniques, and derivations are needed so that future scoring recommendations can be based on evidence rather than consensus opinion We need research comparing clinical outcomes with PSG measures to better inform clinicians and families exactly what meaning a PSG has in evaluating a child's suspected sleep disorder

Sleep homeostasis and cortical synchronization: I. Modeling the effects of synaptic strength on sleep slow waves.

Abstract: SLOW WAVES ARE A PROMINENT FEATURE OF NON-RAPID EYE MOVEMENT (NREM) SLEEP THAT CAN BE OBSERVED IN THE ELECTROENCEPHALOGRAM (EEG) and local field potentials (LFP). Slow-wave activity (SWA, EEG power 0.5–4.0 Hz) provides a reliable indicator of sleep need, as it increases as a function of prior waking and declines during sleep.1–3 Although the homeostatic regulation of SWA is suggestive of a restorative function of sleep, the underlying mechanisms remain unknown. Different mechanisms can be conceived that might lead to a progressive decline in SWA during sleep, such as an increase in the level of arousal-promoting neuromodulators or a reduction of accumulated metabolites (e.g., adenosine). A recent proposal suggests that the level of SWA may reflect the strength of corticocortical synapses and that a progressive reduction in synaptic strength during sleep would be associated with a corresponding decrease in SWA.4, 5 Mechanistically, stronger cortical connections would produce stronger network synchronization and thus a higher level of SWA, whereas weaker connections would reduce network synchronization and thereby SWA. Connections would become. on average, stronger at the end of a waking day due to synaptic potentiation associated with learning and would weaken during sleep due to sleep-dependent synaptic depression, as suggested by molecular and other evidence.4, 5 Supporting the hypothesis, procedures associated with synaptic potentiation and depression in local cortical areas lead to corresponding changes in sleep SWA. For example, sleep SWA increases over right parietal cortex after a visuomotor learning task6 and decreases over the right sensorimotor cortex after immobilization of the left arm.7 In this paper, we employed a large-scale computer model of the cat thalamocortical system to investigate in detail the relationship between synaptic strength and SWA. The model incorporates key aspects of the neuroanatomic organization of visual thalamocortical circuits, including more than 65,000 integrate-and-fire neurons organized into multiple cortical, thalamic, and reticular areas, and produces physiologically realistic sleep activity patterns.8 Specifically, due to the interaction between several intrinsic and synaptic currents, simulated neurons undergo slow oscillations at around 1 Hz between depolarized periods of activity (up states) and hyperpolarized periods of silence (down states), as observed in intracellular recordings in vivo.9, 10 These single-cell oscillations are synchronized by corticocortical connections and produce realistic slow waves in the calculated LFP. On the basis of this model, we examined the dynamics of single-cell oscillations, cortical synchronization, and LFP slow waves under conditions with a high or low strength of corticocortical connections. We show here that a reduction in cortical synaptic strength leads to a decrease in sleep SWA, a decreased incidence of large-amplitude slow waves, a decrease in their slope, and an increase in the number of multipeak waves. In 2 companion papers, we tested the predictions of the model by examining how slow waves change between early-sleep and late-sleep conditions using LFP recordings in rats11 and high-density EEG recordings in humans.12

Restoration of normal motor control in Parkinson's disease during REM sleep

Abstract: Although normal subjects do not move during REM sleep, patients with Parkinson's disease may experience REM sleep behaviour disorder (RBD). The characteristics of the abnormal REM sleep movements in RBD have, however, not been studied. We interviewed one hundred consecutive non-demented patients with Parkinson's disease and their bed partners using a structured questionnaire assessing the presence of RBD. They rated the quality of movements, voice and facial expression during RBD as being better, equal or worse than in awake ON levodopa condition. Night-time sleep and movements were video-monitored during polysomnography in 51 patients to evaluate the presence of bradykinesia, tremor and hypophonia during REM sleep. Fifty-nine patients had clinical RBD with 53/59 bed partners able to evaluate them. All 53 (100%) reported an improvement of at least one component of motor control during RBD. By history, movements were improved in 87% patients (faster, 87%; stronger, 87%; smoother, 51%), speech was better in 77% patients (more intelligible, 77%; louder, 38%; better articulated, 57%) and facial expression was normalized in 47% patients. Thirty-eight per cent of bed partners reported that movements were 'much better', even in the most disabled patients. The video-monitored purposeful movements in REM sleep were also surprisingly fast, ample, coordinated and symmetrical, without obvious sign of parkinsonism. The movements were, however, jerky, violent and often repetitive. While all patients had asymmetrical parkinsonism when awake, most of the time they used the more disabled arm, hand and leg during the RBD (P = 0.04). Movements involved six times as often the upper limbs and the face as the lower limbs (OR: 5.9, P = 0.004). The percentage of time containing tremor EMG activity decreased with sleep stages from 34.9 +/- 15.5% during wakefulness, to 3.6 +/- 5.7% during non-REM sleep stages 1-2, 1.4 +/- 3.0% during non-REM sleep stages 3-4, and 0.06 +/- 0.2% during REM sleep (in this last case, it was subclinical tremor). The restored motor control during REM sleep suggests a transient 'levodopa-like' reestablishment of the basal ganglia loop. Alternatively, parkinsonism may disappear by REM sleep-related disjunction between pyramidal and extrapyramidal systems. We suggest the following model: the movements during the RBD would be generated by the motor cortex and would follow the pyramidal tract bypassing the extrapyramidal system. These movements would eventually be transmitted to lower motor neurons because of brainstem lesions interrupting the pontomedullary pathways which mediate the REM sleep atonia.

The effect of opioids on sleep architecture.

Abstract: STUDY OBJECTIVES The effect of opioid medications on sleep architecture has been demonstrated in patients with comorbid pain or opioid addiction. This study examined whether commonly used opioid medications have an adverse effect on sleep architecture in healthy adults. METHODS Forty-two healthy subjects were examined with polysomnography after a bedtime dose of placebo, sustained-release morphine sulfate (15 mg), or methadone (5 mg) on each of 3 different nights in a double-blind multiple crossover study in a sleep laboratory in the General Clinical Research Center at an academic medical center. RESULTS Both opioid drugs significantly reduced deep sleep and increased stage 2 sleep (both p < .01); neither had an effect on sleep efficiency, wake after sleep onset, or total sleep time. CONCLUSIONS Single doses of oral opioid medications can significantly affect sleep architecture in healthy adults, and observed reductions in slow-wave sleep following opioid administration may have important implications for the pathogenesis of opioid-use related fatigue.

Sleep Homeostasis and Cortical Synchronization: II. A Local Field Potential Study of Sleep Slow Waves in the Rat

Abstract: Study Objective: Sleep slow-wave activity (SWA, EEG power between 0.5 and 4.0 Hz) decreases homeostatically in the course of non-rapid eye movement sleep (NREM) sleep. According to a recent hypothesis, the homeostatic decrease of sleep SWA is due to a progressive decrease in the strength of corticocortical connections. This hypothesis was evaluated in a large-scale thalamocortical model, which showed that a decrease in synaptic strength, implemented through a reduction of postsynaptic currents, resulted in lower sleep SWA in simulated local field potentials (LFP). The decrease in SWA was associated with a decreased proportion of high-amplitude slow waves, a decreased slope of the slow waves, and an increase in the number of multipeak waves. Here we tested the model predictions by obtaining LFP recordings from the rat cerebral cortex and comparing conditions of high homeostatic sleep pressure (early sleep) and low homeostatic sleep pressure (late sleep). Design: Intracortical LFP recordings during baseline sleep and after 6 hours of sleep deprivation. Setting: Basic sleep research laboratory. Patients or Participants: WKY adult male rats. Interventions: N/A. Measurements and Results: Early sleep (sleep at the beginning of the major sleep phase, sleep immediately after sleep deprivation) was associated with (1) high SWA, (2) many large slow waves, (3) steep slope of slow waves, and (4) rare occurrence of multipeak waves. By contrast, late sleep (sleep at the end of the major sleep phase, sleep several hours after the end of sleep deprivation) was associated with (1) low SWA, (2) few high-amplitude slow waves, (3) reduced slope of slow waves, and (4) more frequent multipeak waves. Conclusion: In rats, changes in sleep SWA are associated with changes in the amplitude and slope of slow waves, and in the number of multipeak waves. Such changes in slow-wave parameters are compatible with the hypothesis that average synaptic strength decreases in the course of sleep.

Experimental Evidence for Phase Synchronization Transitions in the Human Cardiorespiratory System

Abstract: Transitions in the dynamics of complex systems can be characterized by changes in the synchronization behavior of their components. Taking the human cardiorespiratory system as an example and using an automated procedure for screening the synchrograms of 112 healthy subjects we study the frequency and the distribution of synchronization episodes under different physiological conditions that occur during sleep. We find that phase synchronization between heartbeat and breathing is significantly enhanced during non-rapid-eye-movement (non-REM) sleep (deep sleep and light sleep) and reduced during REM sleep. Our results suggest that the synchronization is mainly due to a weak influence of the breathing oscillator upon the heartbeat oscillator, which is disturbed in the presence of long-term correlated noise, superimposed by the activity of higher brain regions during REM sleep.

Midlife decline in declarative memory consolidation is correlated with a decline in slow wave sleep

Abstract: Sleep architecture as well as memory function are strongly age dependent. Slow wave sleep (SWS), in particular, decreases dramatically with increasing age, starting already beyond the age of 30. SWS normally predominates during early nocturnal sleep and is implicated in declarative memory consolidation. However, the consequences of changes in sleep across the life span for sleep-associated memory consolidation have not been evaluated so far. Here, we compared declarative memory consolidation (for word-pair associates) during sleep in young and middle-aged healthy humans. The age groups (18-25 vs. 48-55 yr) did not differ with regard to learning performance before retention periods that covered, respectively, the first and second half of nocturnal sleep. However, after early retention sleep, where the younger subjects showed distinctly more SWS than the middle-aged (62.3 +/- 3.7 min vs. 18.4 +/- 7.2 min, P < 0.001), retrieval of the word pairs in the middle-aged was clearly worse than in the young (P < 0.001). In contrast, declarative memory retention did not differ between groups after late sleep, where retention was generally worse than after early sleep (P = 0.005). Retention of declarative memories was the same in both age groups when sleep periods containing equal amounts of SWS were compared, i.e., across late sleep in the young and across early sleep in the middle-aged. Our results indicate a decline in sleep-associated declarative memory consolidation that develops already during midlife and is associated with a decrease in early nocturnal SWS.

The relevance of sleep abnormalities to chronic inflammatory conditions.

Abstract: Sleep is vital to health and quality of life while sleep abnormalities are associated with adverse health consequences. Nevertheless, sleep problems are not generally considered by clinicians in the management of chronic inflammatory conditions (CIC) such as asthma, RA, SLE and IBD. To determine whether this practice is justified, we reviewed the literature on sleep and chronic inflammatory diseases, including effects of sleep on immune system and inflammation. We found that a change in the sleep-wake cycle is often one of the first responses to acute inflammation and infection and that the reciprocal effect of sleep on the immune system in acute states is often protective and restorative. For example, slow wave sleep can attenuate proinflammatory immune responses while sleep deprivation can aggravate those responses. The role of sleep in CIC is not well explored. We found a substantial body of published evidence that sleep disturbances can worsen the course of CIC, aggravate disease symptoms such as pain and fatigue, and increase disease activity and lower quality of life. The mechanism underlying these effects probably involves dysregulation of the immune system. All this suggests that managing sleep disturbances should be considered as an important factor in the overall management of CIC.

Sleep disturbances in depressed pregnant women and their newborns.

Abstract: Pregnant women (N = 253) were recruited during their second trimester of pregnancy (M = 22.3 weeks gestation) and assigned to depressed (N = 83) and non-depressed groups based on a SCID diagnosis of depression. They were then given self-report measures on sleep disturbance, depression, anxiety and anger, and their urine was assayed for norepinephrine and cortisol. These measures were repeated during their third trimester (M = 32.4 weeks). Their newborns were then observed during sleep. During both the second and third trimesters, the depressed women had more sleep disturbances and higher depression, anxiety and anger scores. They also had higher norepinephrine and cortisol levels. The newborns of the depressed mothers also had more sleep disturbances including less time in deep sleep and more time in indeterminate (disorganized) sleep, and they were more active and cried/fussed more.

Major depressive disorder, sleep EEG and agomelatine: an open-label study.

Abstract: This open study evaluates the effect of agomelatine, a melatonergic receptor agonist and 5-HT2C antagonist antidepressant, on sleep architecture in patients suffering from major depressive disorder. Fifteen outpatients with a baseline HAMD score ≽20 were treated with 25 mg/d agomelatine for 42 d. Polysomographic studies were performed at baseline, day 7, day 14, and day 42. Sleep efficiency, time awake after sleep onset and the total amount of slow-wave sleep (SWS) increased at week 6. The increase of SWS was predominant during the first sleep cycle. The amount of SWS decreased throughout the first four sleep cycles from day 7 and delta ratio increased from day 14 onwards. No change in rapid eye movement (REM) latency, amount of REM or REM density was observed and agomelatine was well tolerated. In conclusion agomelatine improved sleep continuity and quality. It normalized the distribution of SWS sleep and delta power throughout the night.

Ketogenic Diet Improves Sleep Quality in Children with Therapy-resistant Epilepsy.

Abstract: Summary: Purpose: The study purpose was to evaluate sleep structure during ketogenic diet (KD) treatment in children with therapy-resistant epilepsy and to correlate possible alterations with changes in clinical effects on seizure reduction, seizure severity, quality of life (QOL), and behavior. Methods: Eighteen children were examined with ambulatory polysomnographic recordings initially and after 3 months of KD treatment. Eleven children continued with the KD and were also evaluated after 12 months. Sleep parameters were estimated. Seizure frequency was recorded in a diary and seizure severity in the National Health Seizure Severity Scale (NHS3). QOL was assessed with a visual analogue scale. Child behavior checklist and Ponsford and Kinsella's rating scale of attentional behavior were used. Results: KD induced a significant decrease in total sleep (p = 0.05) and total night sleep (p = 0.006). Slow wave sleep was preserved, rapid eye movement (REM) sleep increased (p = 0.01), sleep stage 2 decreased (p = 0.004), and sleep stage 1 was unchanged. Eleven children continued with the KD and were also evaluated after 12 months. They showed a significant decrease in daytime sleep (p = 0.01) and a further increase in REM sleep (p = 0.06). Seizure frequency (p = 0.001, p = 0.003), seizure severity (p < 0.001, p = 0.005) and QOL (p < 0.001, p = 0.005) were significantly improved at 3 and 12 months. Attentional behavior was also improved, significantly so at 3 months (p = 0.003). There was a significant correlation between increased REM sleep and improvement in QOL (Spearman r = 0.6, p = 0.01) at 3 months. Conclusion: KD decreases sleep and improves sleep quality in children with therapy-resistant epilepsy. The improvement in sleep quality, with increased REM sleep, seems to contribute to the improvement in QOL. (Less)

Repeated sleep restriction in rats leads to homeostatic and allostatic responses during recovery sleep

Abstract: Recent studies indicate that chronic sleep restriction can have negative consequences for brain function and peripheral physiology and can contribute to the allostatic load throughout the body. Interestingly, few studies have examined how the sleep–wake system itself responds to repeated sleep restriction. In this study, rats were subjected to a sleep-restriction protocol consisting of 20 h of sleep deprivation (SD) followed by a 4-h sleep opportunity each day for 5 consecutive days. In response to the first 20-h SD block on day 1, animals responded during the 4-h sleep opportunity with enhanced sleep intensity [i.e., nonrapid eye movement (NREM) delta power] and increased rapid eye movement sleep time compared with baseline. This sleep pattern is indicative of a homeostatic response to acute sleep loss. Remarkably, after the 20-h SD blocks on days 2–5, animals failed to exhibit a compensatory NREM delta power response during the 4-h sleep opportunities and failed to increase NREM and rapid eye movement sleep times, despite accumulating a sleep debt each consecutive day. After losing ≈35 h of sleep over 5 days of sleep restriction, animals regained virtually none of their lost sleep, even during a full 3-day recovery period. These data demonstrate that the compensatory/homeostatic sleep response to acute SD does not generalize to conditions of chronic partial sleep loss. We propose that the change in sleep–wake regulation in the context of repeated sleep restriction reflects an allostatic process, and that the allostatic load produced by SD has direct effects on the sleep–wake regulatory system.

Classification of human sleep stages based on EEG processing using hidden Markov models

Abstract: The goal of this work was to describe an automated system for classification of human sleep stages. Classification of sleep stages is an important problem of diagnosis and treatment of human sleep disorders. The developed classification method is based on calculation of characteristics of the main sleep rhythms. It uses hidden Markov models. The method is highly accurate and provides reliable identification of the main stages of sleep. The results of automatic classification are in good agreement with the results of sleep stage identification performed by an expert somnologist using Rechtschaffen and Kales rules. This substantiates the applicability of the developed classification system to clinical diagnosis.

Sleep architecture and NREM alterations in children and adolescents with Asperger syndrome.

Abstract: Study Objectives: To analyze sleep in children with Asperger syndrome (AS) by means of standard sleep questionnaires, to evaluate sleep architecture and NREM sleep alterations by means of cyclic alternating pattern (CAP) and to correlate objective sleep parameters with cognitive behavioral measures. Design: Cross-sectional study involving validated sleep questionnaires, neuropsychological scales, and PSG recording. Setting: Sleep medicine center. Participants: Eight children with AS, 10 children with autism, and 12 healthy control children. Interventions: N/A Measurements and Results: Children with AS had a higher prevalence of problems of initiating sleep and daytime sleepiness. Sleep architecture parameters showed minor differences between the 3 groups. CAP parameters showed an increased percentage of A1 and a decreased percentage of A2 subtypes in subjects with AS vs. controls. All A subtype indexes (number per hour of NREM sleep) were decreased, mostly in sleep stage 2 but not in SWS. With respect to children with autism, subjects with AS showed increased CAP rate in SWS and A1 percentage. In subjects with AS, verbal IQ had a significant positive correlation with total CAP rate and CAP rate in SWS and with global and SWS A1 index. The percentage of A2 negatively correlated with full scale IQ, verbal and performance IQ. CBCL total score correlated positively with CAP rate and A1 index while externalizing score correlated negatively with A3%. Conclusions: This study shows peculiar CAP modifications in children with AS and represents an attempt to correlate the quantification of sleep EEG oscillations with the degree of mental ability/disability.