NREM Slow-Wave Activity in Adolescents Is Differentially Associated With ADHD Levels and Normalized by Pharmacological Treatment.

BACKGROUND: A compelling hypothesis about attention-deficit/hyperactivity disorder (ADHD) etiopathogenesis is that the ADHD phenotype reflects a delay in cortical maturation. Slow-wave activity (SWA) of non-rapid eye movement (NREM) sleep electroencephalogram (EEG) is an electrophysiological index of sleep intensity reflecting cortical maturation. Available data on ADHD and SWA are conflicting, and developmental differences, or the effect of pharmacological treatment, are relatively unknown. METHODS: We examined, in samples (Mage = 16.4, SD = 1.2), of ever-medicated adolescents at risk for ADHD (n = 18; 72% boys), medication-naïve adolescents at risk for ADHD (n = 15, 67% boys), and adolescents not at risk for ADHD (n = 31, 61% boys) matched for chronological age and controlling for non-ADHD pharmacotherapy, whether ADHD pharmacotherapy modulates the association between NREM SWA and ADHD risk in home sleep. RESULTS: Findings indicated medication-naïve adolescents at risk for ADHD exhibited greater first sleep cycle and entire night NREM SWA than both ever-medicated adolescents at risk for ADHD and adolescents not at risk for ADHD and no difference between ever-medicated, at-risk adolescents, and not at-risk adolescents. CONCLUSIONS: Results support atypical cortical maturation in medication-naïve adolescents at risk for ADHD that appears to be normalized by ADHD pharmacotherapy in ever-medicated adolescents at risk for ADHD. Greater NREM SWA may reflect a compensatory mechanism in middle-later adolescents at risk for ADHD that normalizes an earlier occurring developmental delay.

Effects of morning and evening physical exercise on subjective and objective sleep quality: an ecological study.

To optimise the relationship between exercise and sleep quality, the intensity of exercise and its proximity to sleep are key factors to manage. Although low-to-moderate exercises promote sleep quality, late-evening vigorous exercise instead of morning should still be avoided. It potentially impacts the objective and subjective markers of sleep quality. In the present study, we investigated the effects of vigorous morning and evening exercise on objective and subjective sleep features in an ecological context. A total of 13 recreational runners (mean [SD] age 27.7 [7.2] years, four females) performed a 45-60 min run (70% maximal aerobic velocity) either in the MORNING (30 min to 2 h after waking-up) or in the EVENING (2 h to 30 min before sleep). The two exercise conditions were separated by a REST day. After each condition, sleep was objectively assessed using an electroencephalographic headband and subjectively using the Spiegel Sleep Inventory. Compared with REST, both MORNING and EVENING exercise increased the time spent in non-rapid eye movement (NREM, +24.9 min and +22.7 min; p = 0.01, η2 = 0.11, respectively). Longer NREM duration was mainly due to sleep stage 2 extension after both MORNING (+20.8 min) and EVENING (+22.8 min) exercise relative to REST (p = 0.02, η2 = 0.12). No other effect of exercise on either objective or subjective sleep could be observed. Exercise, independently of the time at which it takes place, leads to extended NREM sleep without other effects on sleep quality. Considering the crucial role of exercise in achieving good health, sleep hygiene guidelines should be updated to promote exercise at any time of the day.

Antiseizure medication ≤48 hours portends better prognosis in new-onset epilepsy.

BACKGROUND: Several studies found that patients with new-onset epilepsy (NOE) have higher seizure recurrence rates if they presented already prior seizures. These observations suggest that timing of antiseizure medication (ASM) is crucial and should be offered immediately after the first seizure. Here, we wanted to assess whether immediate ASM is associated with improved outcome. METHODS: Single-center study of 1010 patients (≥16 years) who presented with a possible first seizure in the emergency department between 1 March 2010 and 1 March 2017. A comprehensive workup was launched upon arrival, including routine electroencephalography (EEG), brain computed tomography/magnetic resonance imaging, long-term overnight EEG and specialized consultations. We followed patients for 5 years comparing the relapse rate in patients treated within 48 h to those with treatment >48 h. RESULTS: A total of 487 patients were diagnosed with NOE. Of the 416 patients (162 female, age: 54.6 ± 21.1 years) for whom the treatment start could be retrieved, 80% (333/416) were treated within 48 h. The recurrence rate after immediate treatment (32%; 107/333) was significantly lower than in patients treated later (56.6%; 47/83; p < 0.001). For patients for whom a complete 5-year-follow-up was available (N = 297, 123 female), those treated ≤48 h (N = 228; 76.8%) had a significantly higher chance of remaining seizure-free compared with patients treated later (N = 69; 23.2%; p < 0.001). CONCLUSIONS: In this retrospective study, immediate ASM therapy (i.e., within 48 h) was associated with better prognosis up to 5 years after the index event. Prospective studies are required to determine the value of immediate workup and drug therapy in NOE patients.

Study Protocol: Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS) project.

BACKGROUND: Objective and quantifiable markers are crucial for developing novel therapeutics for mental disorders by 1) stratifying clinically similar patients with different underlying neurobiological deficits and 2) objectively tracking disease trajectory and treatment response. Schizophrenia is often confounded with other psychiatric disorders, especially bipolar disorder, if based on cross-sectional symptoms. Awake and sleep EEG have shown promise in identifying neurophysiological differences as biomarkers for schizophrenia. However, most previous studies, while useful, were conducted in European and American populations, had small sample sizes, and utilized varying analytic methods, limiting comprehensive analyses or generalizability to diverse human populations. Furthermore, the extent to which wake and sleep neurophysiology metrics correlate with each other and with symptom severity or cognitive impairment remains unresolved. Moreover, how these neurophysiological markers compare across psychiatric conditions is not well characterized. The utility of biomarkers in clinical trials and practice would be significantly advanced by well-powered transdiagnostic studies. The Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS) project aims to address these questions through a large, multi-center cohort study involving East Asian populations. To promote transparency and reproducibility, we describe the protocol for the GRINS project. METHODS: The research procedure consists of an initial screening interview followed by three subsequent sessions: an introductory interview, an evaluation visit, and an overnight neurophysiological recording session. Data from multiple domains, including demographic and clinical characteristics, behavioral performance (cognitive tasks, motor sequence tasks), and neurophysiological metrics (both awake and sleep electroencephalography), are collected by research groups specialized in each domain. CONCLUSION: Pilot results from the GRINS project demonstrate the feasibility of this study protocol and highlight the importance of such research, as well as its potential to study a broader range of patients with psychiatric conditions. Through GRINS, we are generating a valuable dataset across multiple domains to identify neurophysiological markers of schizophrenia individually and in combination. By applying this protocol to related mental disorders often confounded with each other, we can gather information that offers insight into the neurophysiological characteristics and underlying mechanisms of these severe conditions, informing objective diagnosis, stratification for clinical research, and ultimately, the development of better-targeted treatment matching in the clinic.

Multivariate prediction of cognitive performance from the sleep electroencephalogram.

Human cognitive performance is a key function whose biological foundations have been partially revealed by genetic and brain imaging studies. The sleep electroencephalogram (EEG) is tightly linked to structural and functional features of the central nervous system and serves as another promising biomarker. We used data from MrOS, a large cohort of older men and cross-validated regularized regression to link sleep EEG features to cognitive performance in cross-sectional analyses. In independent validation samples 2.5-10% of variance in cognitive performance can be accounted for by sleep EEG features, depending on the covariates used. Demographic characteristics account for more covariance between sleep EEG and cognition than health variables, and consequently reduce this association by a greater degree, but even with the strictest covariate sets a statistically significant association is present. Sigma power in NREM and beta power in REM sleep were associated with better cognitive performance, while theta power in REM sleep was associated with worse performance, with no substantial effect of coherence and other sleep EEG metrics. Our findings show that cognitive performance is associated with the sleep EEG (r = 0.283), with the strongest effect ascribed to spindle-frequency activity. This association becomes weaker after adjusting for demographic (r = 0.186) and health variables (r = 0.155), but its resilience to covariate inclusion suggest that it also partially reflects trait-like differences in cognitive ability.

Comparison of Polysomnography, Single-Channel Electroencephalogram, Fitbit, and Sleep Logs in Patients With Psychiatric Disorders: Cross-Sectional Study.

BACKGROUND: Sleep disturbances are core symptoms of psychiatric disorders. Although various sleep measures have been developed to assess sleep patterns and quality of sleep, the concordance of these measures in patients with psychiatric disorders remains relatively elusive. OBJECTIVE: This study aims to examine the degree of agreement among 3 sleep recording methods and the consistency between subjective and objective sleep measures, with a specific focus on recently developed devices in a population of individuals with psychiatric disorders. METHODS: We analyzed 62 participants for this cross-sectional study, all having data for polysomnography (PSG), Zmachine, Fitbit, and sleep logs. Participants completed questionnaires on their symptoms and estimated sleep duration the morning after the overnight sleep assessment. The interclass correlation coefficients (ICCs) were calculated to evaluate the consistency between sleep parameters obtained from each instrument. Additionally, Bland-Altman plots were used to visually show differences and limits of agreement for sleep parameters measured by PSG, Zmachine, Fitbit, and sleep logs. RESULTS: The findings indicated a moderate agreement between PSG and Zmachine data for total sleep time (ICC=0.46; P<.001), wake after sleep onset (ICC=0.39; P=.002), and sleep efficiency (ICC=0.40; P=.006). In contrast, Fitbit demonstrated notable disagreement with PSG (total sleep time: ICC=0.08; wake after sleep onset: ICC=0.18; sleep efficiency: ICC=0.10) and exhibited particularly large discrepancies from the sleep logs (total sleep time: ICC=-0.01; wake after sleep onset: ICC=0.05; sleep efficiency: ICC=-0.02). Furthermore, subjective and objective concordance among PSG, Zmachine, and sleep logs appeared to be influenced by the severity of the depressive symptoms and obstructive sleep apnea, while these associations were not observed between the Fitbit and other sleep instruments. CONCLUSIONS: Our study results suggest that Fitbit accuracy is reduced in the presence of comorbid clinical symptoms. Although user-friendly, Fitbit has limitations that should be considered when assessing sleep in patients with psychiatric disorders.

Novel neuroelectrophysiological age index associated with imaging features of brain aging and sleep disorders.

Sleep architecture and microstructures alter with aging and sleep disorder-led accelerated aging. We proposed a sleep EEG based brain age prediction model using convolutional neural networks. We then associated the estimated brain age index with brain structural aging features, sleep disorders and various sleep parameters. Our model also showed a higher BAI (predicted brain age minus chronological age) is associated with cortical thinning in various functional areas. We found a higher BAI for sleep disorder groups compared to healthy sleepers, as well as significant differences in the spectral pattern of EEG among different sleep disorders (lower power in slow and ϑ waves for sleep apnea vs. higher power in ß and σ for insomnia), suggesting sleep disorder-dependent pathomechanisms of aging. Our results demonstrate that the new EEG-BAI can be a biomarker reflecting brain health in normal and various sleep disorder subjects, and may be used to assess treatment efficacy.

Environmental Factors Shape Sleep EEG Connectivity During Early Adolescence.

Quantifying the degree to which genetic and environmental factors shape brain network connectivity is critical to furthering our understanding of the developing human brain. Sleep, a state of sensory disengagement, provides a unique opportunity to study brain network activity noninvasively by means of sleep electroencephalography (EEG) coherence. We conducted a high-density sleep EEG study in monozygotic (MZ; n = 38; mean age = 12.46; 20 females) and dizygotic (DZ; n = 24; mean age = 12.50; 12 females) twins to assess the heritability of sleep EEG coherence in early adolescence-a period of significant brain rewiring. Structural equation modeling was used to estimate three latent factors: genes, environmental factors shared between twins and environmental factors unique to each twin. We found a strong contribution of unique environmental factors (66% of the variance) and moderate genetic influence (19% of the variance) on sleep EEG coherence across frequencies and sleep states. An exception to this was sleep spindle activity, an index of the thalamocortical network, which showed on average a genetic contribution of 48% across connections. Furthermore, we observed high intraindividual stability of coherence across two consecutive nights suggesting that despite only a modest genetic contribution, sleep EEG coherence is like a trait. Our findings in adolescent humans are in line with earlier findings in animals that show the primordial cerebral map and its connections are plastic and it is through interaction with the environment that the pattern of brain network connectivity is shaped. Therefore, even in twins living together, small differences in the environment may cascade into meaningful differences in brain connectivity.

Multimodal assessment shows misalignment of structural and functional thalamocortical connectivity in children and adolescents born very preterm.

Thalamocortical connections are altered following very preterm birth but it is unknown whether structural and functional alterations are linked and how they contribute to neurodevelopmental deficits. We used a multimodal approach in 27 very preterm and 35 term-born children and adolescents aged 10-16 years: Structural thalamocortical connectivity was quantified with two measures derived from probabilistic tractography of diffusion tensor data, namely the volume of thalamic segments with cortical connections and mean fractional anisotropy (FA) within the respective segments. High-density sleep EEG was recorded and sleep spindles were identified at each electrode. Sleep spindle density and integrated spindle activity (ISA) were calculated to quantify functional thalamocortical connectivity. In term-born participants, the volume of the global thalamic segment with cortical connections was strongly related to sleep spindles across the entire head (mean r â€‹= â€‹.53 â€‹± .10; range â€‹= â€‹0.35 to 0.78). Regionally, the volume of the thalamic segment connecting to frontal brain regions correlated with sleep spindle density in two clusters of electrodes over fronto-temporal brain regions (.42 â€‹± .06; 0.35 to 0.51 and 0.43 â€‹± .08; 0.35 to 0.62) and the volume of the thalamic segment connecting to parietal brain regions correlated with sleep spindle density over parietal brain regions (mean r â€‹= â€‹.43 â€‹± .07; 0.35 to 0.61). In very preterm participants, the volume of the thalamic segments was not associated with sleep spindles. In the very preterm group, mean FA within the global thalamic segment was negatively correlated with ISA over a cluster of frontal and temporo-occipital brain regions (mean r â€‹= â€‹-.53 â€‹± .07; -.41 to -.72). No association between mean FA and ISA was found in the term-born group. With this multimodal study protocol, we identified a potential misalignment between structural and functional thalamocortical connectivity in children and adolescents born very preterm. Eventually, this may shed further light on the neuronal mechanisms underlying neurodevelopmental sequelae of preterm birth.

Reliability of sleep spindle measurements in adolescents: How many nights are necessary?

Evidence of night-to-night variation in adolescent sleep spindle characteristics is lacking. Twelve adolescents (M = 15.8 ± 0.8 years, eight males) participated in a laboratory study involving 9 nights with 10 hr sleep opportunity. Sleep electroencephalograph was analysed and intra-class coefficients calculated to determine the reliability of sleep spindles across multiple nights of recording. Slow spindle amplitude and fast spindle density, duration and amplitude characteristics all had acceptable reliability within a single night of sleep recording. Slow spindle density and duration measurements needed a minimum of 4 and 2 nights, respectively, for reliable estimation. Theoretical and methodological implications are discussed.

Implication of Fast Activities of Spectral Analysis in Subjective Sleep Complaints of Elderly Women.

OBJECTIVE: In elderly patients, women have better qualities of sleep than men in objective parameters; however, women subjectively complain more about sleep disturbances than men. We performed visual scoring and spectral analysis of sleep electroencephalograms to explain these gender differences in the degree of arousal, the most representative marker in insomnia. METHODS: A total of 354 participants (≥60 years old) were recruited from a Korean community underwent nocturnal polysomnography (NPSG). A Fast Fourier transform was used for the spectral analysis of the NPSG data. Relative power was calculated as absolute power of each band divided by total absolute power. Difference in total sleep time (D_TST) is obtained by subtracting the total sleep time reported in Pittsburgh Sleep Quality Index (PSQI) from the TST measured by the NPSG. RESULTS: A total of 75 participants (women, 51) were finally analyzed. Women had higher PSQI, longer sleep latencies, sleep inefficiencies, and daytime dysfunctions compared to men. The percentage of stage 1 sleep was higher in men versus in women, whereas percentage of stage 3 sleep was higher in women than in men ( P = .001; P = .001). Women had higher relative alpha and beta powers than men during nonrapid eye movement (NREM) sleep ( P = .017; P = .015). During NREM sleep, beta power was negatively correlated with D_TST ( R = -0.250, P = .033), and relative alpha power in stage 3 sleep was positively correlated with sleep latency in PSQI ( R = 0.267, P = .022). CONCLUSION: Spectral analysis showed that women had more disturbed sleep than men. The result from the spectral analysis may explain hyperarousal in elderly women.

An Unsupervised Multichannel Artifact Detection Method for Sleep EEG Based on Riemannian Geometry.

In biomedical signal processing, we often face the problem of artifacts that distort the original signals. This concerns also sleep recordings, such as EEG. Artifacts may severely affect or even make impossible visual inspection, as well as automatic processing. Many proposed methods concentrate on certain artifact types. Therefore, artifact-free data are often obtained after sequential application of different methods. Moreover, single-channel approaches must be applied to all channels alternately. The aim of this study is to develop a multichannel artifact detection method for multichannel sleep EEG capable of rejecting different artifact types at once. The inspiration for the study is gained from recent advances in the field of Riemannian geometry. The method we propose is tested on real datasets. The performance of the proposed method is measured by comparing detection results with the expert labeling as a reference and evaluated against a simpler method based on Riemannian geometry that has previously been proposed, as well as against the state-of-the-art method FASTER. The obtained results prove the effectiveness of the proposed method.

Depression and Sleep.

Impaired sleep is both a risk factor and a symptom of depression. Objective sleep is assessed using the sleep electroencephalogram (EEG). Characteristic sleep-EEG changes in patients with depression include disinhibition of rapid eye movement (REM) sleep, changes of sleep continuity, and impaired non-REM sleep. Most antidepressants suppress REM sleep both in healthy volunteers and depressed patients. Various sleep-EEG variables may be suitable as biomarkers for diagnosis, prognosis, and prediction of therapy response in depression. In family studies of depression, enhanced REM density, a measure for frequency of rapid eye movements, is characteristic for an endophenotype. Cordance is an EEG measure distinctly correlated with regional brain perfusion. Prefrontal theta cordance, derived from REM sleep, appears to be a biomarker of antidepressant treatment response. Some predictive sleep-EEG markers of depression appear to be related to hypothalamo-pituitary-adrenocortical system activity.

Human Hippocampal Structure: A Novel Biomarker Predicting Mnemonic Vulnerability to, and Recovery from, Sleep Deprivation.

Sleep deprivation impairs the formation of new memories. However, marked interindividual variability exists in the degree to which sleep loss compromises learning, the mechanistic reasons for which are unclear. Furthermore, which physiological sleep processes restore learning ability following sleep deprivation are similarly unknown. Here, we demonstrate that the structural morphology of human hippocampal subfields represents one factor determining vulnerability (and conversely, resilience) to the impact of sleep deprivation on memory formation. Moreover, this same measure of brain morphology was further associated with the quality of nonrapid eye movement slow wave oscillations during recovery sleep, and by way of such activity, determined the success of memory restoration. Such findings provide a novel human biomarker of cognitive susceptibility to, and recovery from, sleep deprivation. Moreover, this metric may be of special predictive utility for professions in which memory function is paramount yet insufficient sleep is pervasive (e.g., aviation, military, and medicine).

Response to adrenocorticotropic in attention deficit hyperactivity disorder-like symptoms in electrical status epilepticus in sleep syndrome is related to electroencephalographic improvement: A retrospective study.

INTRODUCTION: Encephalopathy with electrical status epilepticus in sleep (ESES) syndrome is a rare epilepsy syndrome of childhood that is characterized by sleep-induced epileptiform discharges and problems with cognition or behavior. The neuropsychiatric symptoms in ESES syndrome, among which the ADHD-like symptoms are prominent, bear a close resemblance to symptoms in various developmental disorders. Positive response to adrenocorticotropic hormone (ACTH) is associated with the normalization of the EEG and improvement of neuropsychiatric function. This study aimed to determine the improvement in ADHD-like symptoms in response to ACTH and establish a relationship between improvement in clinical symptoms and EEG parameters. METHODS: Seventy-five patients with ESES syndrome, who had clinically displayed ADHD-like symptoms, had been treated with ACTH for ESES, and their medical records were retrospectively reviewed. Sleep EEGs were recorded at referral and follow-up visits, and short courses of ACTH were administered when spike-wave index (SWI) was ≥15%. The assessment of treatment effectiveness was based on reduction in SWI and the clinician-reported improvement in ADHD-like symptoms. Statistical analyses were conducted in order to investigate the relationship between the clinical and EEG parameters. RESULTS: Following treatment with ACTH, a reduction in SWI in all the patients was accompanied by a mean improvement of 67% in ADHD-like symptoms. Disappearance/reduction of foci and cessation/reduction of seizures were achieved in patients with formerly antiepileptic-resistant seizures. Multiple linear regressions established that pretreatment SWI and treatment delay predicted posttreatment SWI, while reduction in SWI, treatment delay, and the presence of foci predicted improvement in ADHD-like symptoms. DISCUSSION: Improvement in ADHD-like symptoms showed high correlation and was timely with the resolution of ESES. It is suggested that ESES and ADHD may be the two different expressions of a common neurobiological abnormality. With enhanced interpretation of sleep EEG, a more thorough assessment and treatment of neurodevelopmental disorders is possible.

Sleep microstructure dynamics and neurocognitive performance in obstructive sleep apnea syndrome patients.

The present study examined the relationship between the increment in cyclic alternating patterns (CAPs) in sleep electroencephalography and neurocognitive decline in obstructive Sleep Apnea Syndrome (OSAS) patients through source localization of the phase-A of CAPs. All-night polysomnographic recordings of 10 OSAS patients and 4 control subjects along with their cognitive profile using the Addenbrooke's Cognitive Examination (ACE) test were acquired. The neuropsychological assessment involved five key domains including attention and orientation, verbal fluency, memory, language and visuo-spatial skills. The standardized low-resolution brain electromagnetic tomography (sLORETA) tool was used to source-localize the phase-A of CAPs in sleep EEG aiming to investigate the correlation between CAP phase-A and cognitive functions. Our findings suggested a significant increase in CAP rates among OSAS subjects versus control subjects. Moreover, sLORETA revealed that CAP phase-A is mostly activated in frontoparietal cortices. As CAP rate increases, the activity of phase-A in such areas is dramatically enhanced leading to arousal instability, lower sleep efficiency and a possibly impaired cortical capacity to consolidate cognitive inputs in frontal and parietal areas during sleep. As such, cognitive domains including verbal fluency, memory and visuo-spatial skills which predominantly relate to frontoparietal areas tend to be affected. Based on our findings, CAP activity may possibly be considered as a predictor of cognitive decline among OSAS patients.

The study of sleep disorder factors in patients with Guillain-Barré syndrome.

In this study, we explore the sleep disorders and its associated factors in patients with Guillain-Barré syndrome (GBS), so as to work out appropriate interventions to promote early recovery of the patients. This study subjects included 49 patients with GBS who had been admitted to the Department of Neurology at The Affiliated Hospital of Hebei University, fulfilling National Institute of Neurological and Communicative Diseases and Stroke (NINCDS) criteria for GBS; 37 cases were male and 12 female (age: 27-68 years). Patients were evaluated once daily for two consecutive weeks. By using Wong and Baker Face Scale (WBFS) to evaluate the numbness and pain in patients, 0 points representing completely no pain and 10 points represents the most severity of the pain reactions; the same applies for numbness. The GBS Disability Scale (GBS DS) is used to evaluate the severity of GBS. The Hospital Anxiety and Depression Scale (HADS) is used to evaluate the anxiety and depression the patient is experiencing. All patients take routine EMG and sleep EEG. The sleep quality of the subjects was evaluated by the Pittsburgh Sleep Quality Index Scale (PSQI) and Richard Campbell Sleep Rating Scale. This study found that the application of ventilators, numbness, anxiety and severe limb movement disorders are the main factors causing sleep disorders. Cerebrospinal fluid (CSF) protein concentration is also associated with sleep disorders. But, no obvious abnormalities were found in sleep EEG. The application of the ventilator, numbness, anxiety and severe limb movement disorder are main factors causing sleep disorders. CSF protein concentration is also associated with sleep disorders.

Morning and evening physical exercise differentially regulate the autonomic nervous system during nocturnal sleep in humans.

Effects of daily physical exercise in the morning or in the evening were examined on circadian rhythms in plasma melatonin and core body temperature of healthy young males who stayed in an experimental facility for 7 days under dim light conditions (<10 lux). Sleep polysomnogram (PSG) and heart rate variability (HRV) were also measured. Subjects performed 2-h intermittent physical exercise with a bicycle ergometer at ZT3 or at ZT10 for four consecutive days, where zeitgeber time 0 (ZT0) was the time of wake-up. The rising phase of plasma melatonin rhythm was delayed by 1.1 h without exercise. Phase-delay shifts of a similar extent were detected by morning and evening exercise. But the falling phase shifted only after evening exercise by 1.0 h. The sleep PSG did not change after morning exercise, while Stage 1+2 sleep significantly decreased by 13.0% without exercise, and RE sleep decreased by 10.5% after evening exercise. The nocturnal decline of rectal temperature was attenuated by evening exercise, but not by morning exercise. HRV during sleep changed differentially. Very low frequency (VLF) waves increased without exercise. VLF, low frequency (LF), and high frequency (HF) waves increased after morning exercise, whereas HR increased after evening exercise. Morning exercise eventually enhanced the parasympathetic activity, as indicated by HRV, while evening exercise activated the sympathetic activity, as indicated by increase in heart rate in the following nocturnal sleep. These findings indicated differential effects of morning and evening exercise on the circadian melatonin rhythm, PSG, and HRV.

Sleep respiratory disturbances and arousals at moderate altitude have overlapping electroencephalogram spectral signatures.

An ascent to altitude has been shown to result in more central apneas and a shift towards lighter sleep in healthy individuals. This study employs spectral analysis to investigate the impact of respiratory disturbances (central/obstructive apnea and hypopnea or periodic breathing) at moderate altitude on the sleep electroencephalogram (EEG) and to compare EEG changes resulting from respiratory disturbances and arousals. Data were collected from 51 healthy male subjects who spent 1 night at moderate altitude (2590 m). Power density spectra of Stage 2 sleep were calculated in a subset (20) of these participants with sufficient artefact-free data for (a) epochs with respiratory events without an accompanying arousal, (b) epochs containing an arousal and (c) epochs of undisturbed Stage 2 sleep containing neither arousal nor respiratory events. Both arousals and respiratory disturbances resulted in reduced power in the delta, theta and spindle frequency range and increased beta power compared to undisturbed sleep. The similarity of the EEG changes resulting from altitude-induced respiratory disturbances and arousals indicates that central apneas are associated with micro-arousals, not apparent by visual inspection of the EEG. Our findings may have implications for sleep in patients and mountain tourists with central apneas and suggest that respiratory disturbances not accompanied by an arousal may, none the less, impact sleep quality and impair recuperative processes associated with sleep more than previously believed.

Gastroesophageal reflux disease vs. Panayiotopoulos syndrome: an underestimated misdiagnosis in pediatric age?

Autonomic signs and symptoms could be of epileptic or nonepileptic origin, and the differential diagnosis depends on a number of factors which include the nature of the autonomic manifestations themselves, the occurrence of other nonictal autonomic signs/symptoms, and the age of the patient. Here, we describe twelve children (aged from ten months to six years at the onset of the symptoms) with Panayiotopoulos syndrome misdiagnosed as gastroesophageal reflux disease. Gastroesophageal reflux disease and Panayiotopoulos syndrome may represent an underestimated diagnostic challenge. When the signs/symptoms occur mainly during sleep, a sleep EEG or, if available, a polysomnographic evaluation may be the most useful investigation to make a differential diagnosis between autonomic epileptic and nonepileptic disorders. An early detection can reduce both the high morbidity related to mismanagement and the high costs to the national health service related to the incorrect diagnostic and therapeutic approaches. To decide if antiseizure therapy is required, one should take into account both the frequency and severity of epileptic seizures and the tendency to have potentially lethal autonomic cardiorespiratory involvement. In conclusion, we would emphasize the need to make a differential diagnosis between gastroesophageal reflux disease and Panayiotopoulos syndrome in patients with "an unusual" late-onset picture of GERD and acid therapy-resistant gastroesophageal reflux, especially if associated with other autonomic symptoms and signs.