Sleep EEG Power Research Articles

Sleep spindle activity in childhood onset schizophrenia: Diminished and associated with clinical symptoms

Neuroimaging studies of childhood onset schizophrenia (COS), a rare yet severe form of schizophrenia with an onset before the age of 13 years, have shown continuity with adult onset schizophrenia. Previous research in adult patients has shown reduced sleep spindle activity, transient oscillations in the sleep electroencephalogram (EEG) generated through thalamocortical loops. The current study examines sleep spindle activity in patients with COS. Seventeen children and adolescents with COS (16 years ±6.6) underwent overnight sleep EEG recordings. Sleep spindle activity was compared between patients with COS and age and gender matched controls and correlated with clinical symptom severity. We found pronounced deficits in sleep spindle amplitude, duration, density and frequency in patients with COS (effect size = 0.61 to 1.96; dependent on metric and EEG derivation). Non-rapid eye movement (NREM) sleep EEG power and coherence in the sigma band (11–16 Hz) corresponding to spindle activity were also markedly diminished in patients with COS as compared to controls. Furthermore, the degree of deficit in power and coherence of spindles was strongly associated with clinician rated hallucinations and positive symptoms over widespread cortical regions. Our finding of diminished spindle activity and its association with hallucinations likely reflect dysfunction of the thalamocortical circuits in children and adolescents with COS. Given the relative ease of sleep EEG recordings in vulnerable populations, this study highlights the potential of such recordings to characterize brain function in schizophrenia.

0669 The Effects Of Continuous Positive Airway Pressure Therapy In Moderate To Severe Obstructive Sleep Apnea: A High-density EEG Study

Abstract Introduction A previous high-density electroencephalography (EEG) investigation in asymptomatic OSA showed regional deficits in sleep EEG power particularly slow wave activity (SWA) during NREM sleep in the parietal region. It is unclear whether treatment with CPAP can reverse local sleep EEG abnormalities in OSA, and whether any recovery is related to improvement in sleep-dependent memory consolidation. Methods Fifteen male participants (age 50.4±6.5yrs, AHI 51.7±23.5/h) with moderate-severe OSA (AHI>15/h) underwent overnight polysomnography with 256-channel high-density EEG at baseline and following 3 months of CPAP therapy. A word paired associates declarative memory task was administered before and after sleep. After artefact removal, spectral analysis was performed for all channels. Topographical power maps were calculated for standard frequency ranges for NREM sleep (164 channels within a 0.57 radius from the vertex). Maps were compared using both absolute and normalized power (z-scores computed for each subject) and differences between baseline and treatment were determined by statistical nonparametric mapping. Results In 11 CPAP compliant patients (intolerant of CPAP [n=3]/high-density EEG [n=1]), analysis of polysomnographic variables showed that total sleep time did not differ but N1 (baseline vs. treatment: 66.9 vs. 39.5 mins,p=0.008) and N2 (195.0 vs. 150.6 mins,p=0.002) sleep was lower and N3 (89.8 vs. 128.7 mins,p=0.003) was higher after CPAP. Topographic analysis of high-density EEG data revealed a regional increase in SWA (1-4.5Hz) EEG power during N3 sleep in a cluster of electrodes overlying the centro-parietal cortex (cluster mean t-value=2.87,p=0.02). The change in overnight declarative memory consolidation (% recognition) after CPAP was significantly correlated with the change in slow spindle frequency activity in frontal regions (cluster mean r=0.875,p=0.003). Conclusion CPAP treatment may enhance localised deficits in sleep EEG activity in OSA, and specific regional recovery may translate to memory improvements in the short-term. These data also highlight the potential for long-term therapeutic effects on cognitive outcomes in OSA. Support

The Effects of Presleep Slow Breathing and Music Listening on Polysomnographic Sleep Measures \u2013 a pilot trial

Knowledge on efficient ways to reduce presleep arousal and, therefore, improve sleep, is scanty. We explored the effects of presleep slow breathing and music listening conditions on sleep quality and EEG power spectral density in young adults in a randomized, controlled trial with a crossover design. Participants’ (N = 20, 50% females) sleep was measured on two consecutive nights with polysomnography (40 nights), the other night serving as the control condition. The intervention condition was either a 30-minute slow breathing exercise or music listening (music by Max Richter: Sleep). The intervention and control conditions were placed in a random order. We measured heart rate variability prior to, during and after the intervention condition, and found that both interventions increased immediate heart rate variability. Music listening resulted in decreased N2 sleep, increased frontal beta1 power spectral density, and a trend towards increased N3 sleep was detected. In the slow breathing condition higher central delta power during N3 was observed. While some indices pointed to improved sleep quality in both intervention groups, neither condition had robust effects on sleep quality. These explorative findings warrant further replication in different populations.

Sleep neurophysiology in childhood onset schizophrenia.

Altered sleep neurophysiology has consistently been reported in adult patients with schizophrenia. Converging evidence suggests that childhood onset schizophrenia (COS), a rare but severe form of schizophrenia, is continuous with adult onset schizophrenia. The aim of the current study was to characterize sleep neurophysiology in COS. An overnight sleep electroencephalogram (EEG) was recorded in 17 children and adolescents with COS (16years±6.6) and 17 age and gender-matched controls. Non-rapid eye movement (NREM) and rapid eye movement (REM) sleep EEG power and coherence for the frequency bands delta (1.6-4.8Hz), theta (5-8.4Hz), alpha (8.6-11Hz), beta 1 (16.4-20.2Hz) and beta 2 (20.4-24.2Hz) were compared between COS patients and controls. COS patients exhibited significant and widespread deficits in beta power during NREM and REM sleep. With regard to coherence, we found increases in COS patients across brain regions, frequency bands and sleep states. This study demonstrates the utility of the sleep EEG for studying vulnerable populations and its potential to aid diagnosis.

Effects of Escitalopram on the Sleep EEG Power in Patients With Major Depressive Disorder

Effects of Escitalopram on the Sleep EEG Power in Patients With Major Depressive Disorder

Increased high-frequency NREM EEG power associated with mindfulness-based interventions for chronic insomnia: Preliminary findings from spectral analysis

ObjectiveMindfulness-based interventions (MBI) have been shown to reduce subjective symptoms of insomnia but the effects on objective measures remain unclear. The purpose of this study was to examine sleep EEG microarchitecture patterns from a randomized controlled trial of Mindfulness-Based Stress Reduction (MBSR) and Mindfulness-Based Therapy for Insomnia (MBTI). MethodsSleep EEG spectral analysis was conducted on 36 participants with chronic insomnia (>6 months) randomized to 8-week MBSR, MBTI, or self-monitoring control (SM). Overnight polysomnography with 6-channel EEG was conducted at baseline, post-treatment, and 6-month follow-up. Spectral power averaged from channels C3/C4 across NREM epochs (excluding N1) was examined for within-group changes and relationships with self-report measures. ResultsIncreases in absolute NREM beta (16–25 Hz) power were observed from baseline to post-treatment (p = .02, d = 0.53) and maintained at 6-month follow-up (p = .01, d = 0.57) in the combined MBI groups, and additionally in the gamma (25–40 Hz) range at follow-up for the MBTI group only. No significant changes in these frequency bands were observed for SM. Following mindfulness intervention, NREM beta was positively associated with Five-Facet Mindfulness (FFM) score (rho = 0.37, p = .091) and negatively associated with Insomnia Severity Index (rho = −0.43, p = .047). ConclusionThese results in people with insomnia corroborate prior reports of increased high-frequency sleep EEG power associated with mindfulness training. This change in beta EEG pattern merits further evaluation as a potential marker of the effects of mindfulness meditation on sleep, especially given the paradoxical findings in the context of insomnia. Clinical Trial Registrationclinicaltrials.gov, NCT00768781.

An increase in sleep slow waves predicts better working memory performance in healthy individuals

Sleep is imperative for brain health and well-being, and restorative sleep is associated with better cognitive functioning. Increasing evidence indicates that electrophysiological measures of sleep, especially slow wave activity (SWA), regulate the consolidation of motor and perceptual procedural memory. In contrast, the role of sleep EEG and SWA in modulating executive functions, including working memory (WM), has been far less characterized. Here, we investigated across-night changes in sleep EEG that may ameliorate WM performance. Participants (N = 25, M = 100%) underwent two consecutive nights with high-density EEG, along with N-back tasks, which were administered at three time points the day before and after the second night of sleep. Non-rapid eye movement sleep EEG power spectra, power topography, as well as several slow-wave parameters were computed and compared across nights. Improvers on the 1-back, but not non-improvers, showed a significant increase in SWA as well as in down slope and negative peak amplitude, in a fronto-parietal region, and these parameters increases predicted better WM performance. Overall, these findings show that slow-wave sleep has a beneficial effect on WM and that it can occur in the adult brain even after minimal training. This is especially relevant, when considering that WM and other executive function cognitive deficits are present in several neuropsychiatric disorders, and that slow-wave enhancing interventions can improve cognition, thus providing novel insights and treatment strategies for these patients.

Trait-like characteristics of sleep EEG power spectra in adolescents across sleep opportunity manipulations.

The electroencephalographic power spectra of non‐rapid eye movement sleep in adults demonstrate trait‐like consistency within participants across multiple nights, even when prior sleep deprivation is present. Here, we examined the extent to which this finding applies to adolescents who are habitually sleep restricted on school‐days and sleep longer on weekends. We evaluated 78 adolescents across three sleep restriction groups who underwent different permutations of adequate sleep (9 hr time‐in‐bed), sleep restriction (5 hr time‐in‐bed), afternoon naps (1 hr afternoon) and recovery sleep (9 hr time‐in‐bed) that simulate behaviour on school‐days and weekends. The control group comprised a further 22 adolescents who had 9 hr of sleep opportunity each night. Intra‐class correlation coefficients showed moderate to almost perfect within‐subject stability in electroencephalographic power spectra across multiple nights in both sleep restriction and control groups, even when changes to sleep macrostructure were observed. While nocturnal intra‐class correlation metrics were lower in the low‐frequency and spindle frequency bins in the sleep restriction compared with the control group, hierarchical clustering measures could still identify multi‐night electroencephalographic spectra as originating from the same individual. The trait‐like characteristics of electroencephalographic spectra from an adolescent remain identifiable despite the disruptive effects of multi‐night sleep restriction to sleep architecture.

Heritability of Sleep EEG Topography in Adolescence: Results from a Longitudinal Twin Study

The topographic distribution of sleep EEG power is a reflection of brain structure and function. The goal of this study was to examine the degree to which genes contribute to sleep EEG topography during adolescence, a period of brain restructuring and maturation. We recorded high-density sleep EEG in monozygotic (MZ; n = 28) and dizygotic (DZ; n = 22) adolescent twins (mean age = 13.2 ± 1.1 years) at two time points 6 months apart. The topographic distribution of normalized sleep EEG power was examined for the frequency bands delta (1–4.6 Hz) to gamma 2 (34.2–44 Hz) during NREM and REM sleep. We found highest heritability values in the beta band for NREM and REM sleep (0.44 ≤ h2 ≤ 0.57), while environmental factors shared amongst twin siblings accounted for the variance in the delta to sigma bands (0.59 ≤ c2 ≤ 0.83). Given that both genetic and environmental factors are reflected in sleep EEG topography, our results suggest that topography may provide a rich metric by which to understand brain function. Furthermore, the frequency specific parsing of the influence of genetic from environmental factors on topography suggests functionally distinct networks and reveals the mechanisms that shape these networks.

Sleep EEG spectral power is correlated with subjective-objective discrepancy of sleep onset latency in major depressive disorder

We aimed to identify the sleep electroencephalography (EEG) spectral power correlates of the subjective-objective discrepancy (SOD) of sleep onset latency (SOL) in major depressive disorder (MDD), primary insomnia (PI), and normal sleeping control (NSC) groups. We examined relative power values in standard frequency bands of the EEG spectra during the first Non-Rapid Eye Movement (NREM) sleep period as correlates of SOD of SOL between sleep diary and polysomnography in MDD (n = 36), PI (n = 19), and NSC (n = 23) groups. We also compared the relative spectral power of sleep EEG among MDD (n = 40), PI (n = 19), and NSC (n = 23) groups. SOD of SOL in MDD patients was positively correlated with relative sigma (r = 0.622, p corrected < 0.001), beta power (r = 0.559, p corrected = 0.002), and alpha power (r = 0.469, p corrected = 0.024) in the first NREM sleep period. There was no significant difference of sleep EEG power spectra among the three groups. SOD was positively correlated with high frequency EEG in MDD. High frequency EEG power is thought to be associated with hyperarousal and memory consolidation, and future larger-scale studies may further elucidate the neurophysiological mechanisms underlying SOD of sleep onset duration.

Sleep architecture and EEG power spectra in recently detoxified alcohol dependent patients.

Persistent sleep abnormalities during abstinence are a harbinger for relapse in patients with chronic alcohol dependence. The present study aimed to compare polysomnography (PSG) data between 'recently detoxified' patients with chronic alcohol dependence and healthy controls. Both conventional sleep architectural and power spectral analyses were conducted. Twenty subjects in each of the groups were enrolled. A 2 nights' sleep (first-habituation and second-experimental) PSG data was collected. Computer assisted scoring supplemented by manual method using the Rechtschaffen and Kales criteria were used for sleep staging. Twenty eight channels were used for the EEG recording. Spectral power across early NREM (Non-rapid-eye-movement), Slow Wave Sleep and REM was computed using the Welch's averaged periodogram method. Results on conventional sleep staging showed that patients had significantly lesser total sleep time, sleep efficiency and stage shifts and longer sleep onset latency; while duration of each NREM stages were significantly lower, and latency of stage 2 NREM was significantly longer in patients. After controlling for multiple comparisons, spectral power analysis revealed significant differences only during REM sleep and specifically in high frequency (beta and gamma) bands. Stating the mutually complementary role of conventional and spectral analyses of polysomnography EEG data, we conclude that sleep abnormalities are fairly evident in recently detoxified alcohol dependent patients.

EEG power spectrum maturation in preterm fetal growth restricted infants

Power spectral analysis of the electroencephalogram (EEG) is a non-invasive method to examine infant brain maturation. Preterm fetal growth restricted (p-FGR) neonates display an altered EEG power spectrum compared to appropriate-for-gestational-age (AGA) peers, suggesting delayed brain maturation. Longitudinal studies investigating EEG power spectrum maturation in p-FGR infants are lacking, however. We thus aimed to investigate brain maturation using sleep EEG power spectral analysis in p-FGR infants compared to preterm and term AGA controls (p-AGA and t-AGA, respectively). EEG was recorded during spontaneous sleep in 13 p-FGR, 17 p-AGA and 19 t-AGA infants at 1 and 6 months post-term age. Infant sleep states (active and quiet sleep) were scored using standard criteria. Power spectral analysis of a single-channel EEG (C3-M2/C4-M1) was performed using Fast Fourier Transform. The EEG power spectrum was divided into delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), sigma (12–14 Hz) and beta (14–30 Hz) frequency bands. Relative (%) powers and the spectral edge frequency were calculated. The spectral edge frequency was significantly higher in p-FGR infants compared to p-AGA controls in quiet sleep at 1 month post-term age (p < .01). This was due to significantly reduced %-delta and significantly increased %-theta, %-alpha and %-beta power (p < .01 for all) compared to p-AGA infants. p-FGR infants also showed significantly increased %-beta power compared to t-AGA infants (p < .05). No group differences were observed in active sleep or at 6 months post-term age. In conclusion, p-FGR infants show altered sleep EEG power spectrum maturation compared to AGA peers. However, changes resolved by 6 months post-term age.

Sleep architecture in insomniacs with severe benzodiazepine abuse

Benzodiazepines (BZDs) are the most commonly prescribed compounds in insomnia. A long-term of BZDs use may cause dependence and abuse. The aim of this study was to evaluate sleep architecture and microstructure (in terms of cyclic alternating pattern - CAP - analysis and of sleep EEG power spectral analysis) in a group of long-term users of high doses of BZDs for their primary chronic insomnia. Twenty patients consecutively admitted at the Sleep Centre for drug discontinuation and 13 matched healthy controls underwent a full nocturnal video-polysomnographic recording, after one adaptation night. Significant differences were found in time in bed, REM sleep latency and sleep stage 1% which were increased in patients compared to controls, while CAP rate was dramatically decreased. During NREM sleep, patients showed a clear decrease in the relative power of delta band. Our data demonstrate that in adults with chronic insomnia, long-term use of high doses of BZDs induces a severe disruption of sleep microstructure, while sleep architecture seems to be much less affected. The long term use of high doses of BZDs for chronic insomnia induces a marked depression of slow wave activity and of its physiological instability.

Transdermal Nicotine Patch Effects on EEG Power Spectra and Heart Rate Variability During Sleep of Healthy Male Adults.

ObjectiveThe effect of transdermal nicotine patch on sleep physiology is not well established. The current study aimed to examine the influence of nicotine patch on homeostatic sleep propensity and autonomic nervous system.MethodsWe studied 16 non-smoking young healthy volunteers with nocturnal polysomnography in a double blind crossover design between sleep with and without nicotine patch. We compared the sleep variables, sleep EEG power spectra, and heart rate variability.ResultsThe night with nicotine patch showed significant increase in sleep latency, wake after sleep onset, and stage 1 sleep; and decrease in total sleep time, sleep efficiency, and percentage of REM sleep. Also, spectral analysis of the sleep EEG in the night with nicotine patch revealed decreased slow wave activity in stage 2 and REM sleep and increased alpha activity in the first NREM-REM sleep cycle. Heart rate variability showed no differences between the 2 nights, but the low to high ratio (a parameter indicative of sympathetic nervous system activity) positively correlated with wake after sleep onset in night with nicotine patch.ConclusionTransdermal nicotine patch significantly disrupts sleep continuity, sleep architecture, and homeostatic sleep propensity. The overactivation of the sympathetic nervous system may be responsible for these changes.

Stage 2 Sleep EEG Sigma Activity and Motor Learning in Childhood ADHD: A Pilot Study

Attention deficit hyperactivity disorder (ADHD) is associated with deficits in motor learning and sleep. In healthy adults, overnight improvements in motor skills are associated with sleep spindle activity in the sleep electroencephalogram (EEG). This association is poorly characterized in children, particularly in pediatric ADHD. Polysomnographic sleep was monitored in 7 children with ADHD and 14 typically developing controls. All children were trained on a validated motor sequence task (MST) in the evening with retesting the following morning. Analyses focused on MST precision (speed–accuracy trade-off). NREM Stage 2 sleep EEG power spectral analyses focused on spindle-frequency EEG activity in the sigma (12–15 Hz) band. The ADHD group demonstrated a selective decrease in power within the sigma band. Evening MST precision was lower in ADHD, yet no difference in performance was observed following sleep. Moreover, ADHD status moderated the association between slow sleep spindle activity (12–13.5 Hz) and overnight improvement; spindle-frequency EEG activity was positively associated with performance improvements in children with ADHD but not in controls. These data highlight the importance of sleep in supporting next-day behavior in ADHD while indicating that differences in sleep neurophysiology may contribute to deficits in this population.

Suppression of Sleep Spindle Rhythmogenesis in Mice with Deletion of CaV3.2 and CaV3.3 T-type Ca2+ Channels

Low-threshold voltage-gated T-type Ca(2+) channels (T-channels or CaV3 channels) sustain oscillatory discharges of thalamocortical (TC) and nucleus Reticularis thalami (nRt) cells. The CaV3.3 subtype dominates nRt rhythmic bursting and mediates a substantial fraction of spindle power in the NREM sleep EEG. CaV3.2 channels are also found in nRt, but whether these contribute to nRt-dependent spindle generation is unexplored. We investigated thalamic rhythmogenesis in mice lacking this subtype in isolation (CaV3.2KO mice) or in concomitance with CaV3.3 deletion (CaV3.double-knockout (DKO) mice). We examined discharge characteristics of thalamic cells and intrathalamic evoked synaptic transmission in brain slices from wild-type, CaV3.2KO and CaV3.DKO mice through patch-clamp recordings. The sleep profile of freely behaving CaV3.2KO and CaV3.DKO mice was assessed by polysomnographic recordings. CaV3.2 channel deficiency left nRt discharge properties largely unaltered, but additional deletion of CaV3.3 channels fully abolished low-threshold whole-cell Ca(2+) currents and bursting, and suppressed burst-mediated inhibitory responses in TC cells. CaV3.DKO mice had more fragmented sleep, with shorter NREM sleep episodes and more frequent microarousals. The NREM sleep EEG power spectrum displayed a relative suppression of the σ frequency band (10-15 Hz), which was accompanied by an increase in the δ band (1-4 Hz). Consistent with previous findings, CaV3.3 channels dominate nRt rhythmogenesis, but the lack of CaV3.2 channels further aggravates neuronal, synaptic, and EEG deficits. Therefore, CaV3.2 channels can boost intrathalamic synaptic transmission, and might play a modulatory role adjusting the relative presence of NREM sleep EEG rhythms.

Region-specific response to shortened sleep in childhood: Associations with performance and myelination

Sleep is required for plasticity processes underlying brain maturation in animals. Sleep problems in childhood predict later psychological and social problems over and above demographic factors. Yet, it remains unknown how inadequate sleep in children affects brain activity and behavior and how developing neural networks drive this relationship. All-night high-density EEG (128 channels) was obtained in 13 healthy children (5–12 y, 6 f) during habitual sleep (HS) and restricted sleep (RS, 50% of HS via delayed bedtime). Myelin-specific mcDESPOT magnetic resonance imaging was recorded in all subjects. Reaction times (auditory oddball) task were measured before and after sleep in both conditions. Sleep restriction increased non-REM sleep EEG power, which was most pronounced in slow-wave activity (SWA, 1–4.5 Hz; RS/HS). This homeostatic response occurred within prefrontal and parieto-occipital regions. The parieto-occipital SWA increase was inversely related to myelin content in the optic radiation (partial [factor age] correlation r = −0.57, p = 0.03, 1-tailed). Overnight performance improvement in reaction time correlated with the prefrontal SWA increase ( r = 0.79 p = 0.02; partial [factor age] r = 0.81 p = 0.03, 1-tailed). These results provide evidence for increased sleep need in developing neural networks in children, and extend animal findings showing that sleep is a fundamental contributor to neurodevelopment. Long-term effects of insufficient sleep may negatively impact the development of the neural networks that are involved in the generation of sleep slow-waves.

Early adolescent cognitive gains are marked by increased sleep EEG coherence.

Although the increases in cognitive capacities of adolescent humans are concurrent with significant cortical restructuring, functional associations between these phenomena are unclear. We examined the association between cortical development, as measured by the sleep EEG, and cognitive performance in a sample of 9/10 year olds followed up 1 to 3 years later. Our cognitive measures included a response inhibition task (Stroop), an executive control task (Trail Making), and a verbal fluency task (FAS). We correlated sleep EEG measures of power and intra-hemispheric coherence at the initial assessment with performance at that assessment. In addition we correlated the rate of change across assessments in sleep EEG measures with the rate of change in performance. We found no correlation between sleep EEG power and performance on cognitive tasks for the initial assessment. In contrast, we found a significant correlation of the rate of change in intra-hemispheric coherence for the sigma band (11 to 16 Hz) with rate of change in performance on the Stroop (r = 0.61; p<0.02) and Trail Making (r = −0.51; p<0.02) but no association for the FAS. Thus, plastic changes in connectivity (i.e., sleep EEG coherence) were associated with improvement in complex cognitive function.

Aging and sleep in Williams syndrome: accelerated sleep deterioration and decelerated slow wave sleep decrement.

Specific developmental and aging trajectories characterize sleep electroencephalogram (EEG) of typically developing (TD) subjects. Williams syndrome (WS) is marked by sleep alterations and accelerated aging of several anatomo-functional and cognitive measures. Here we test the hypothesis of a premature aging of sleep in WS. Age-related changes of home recorded sleep EEG of 42 subjects (21 WS, 21 age- and gender matched TD subjects, age: 6-29 years) were tested by Pearson correlations and homogeneity-of-slopes analysis. Typical developmental/aging effects of sleep EEGs were observed in TD subjects. Accelerated aging in WS was confirmed by overall sleep/wake measures. Specifically, premature aging was evident in accelerated age-dependent declines in WS subjects' sleep efficiency, as well as in steeper age-related rises in wakefulness and wake after sleep onset (WASO) of the WS group. In contrast, NREM sleep-related measures indicated atypical decelerations of the developmental trends of WS subjects, characterized by the slowing down of the age-related slow wave sleep (SWS) declines mirrored by the lack of age-dependent increase in Stage 2 (S2) sleep. Age-effects in sleep EEG power spectra were not different among the groups. Objectively measured sleep disruption of subjects with WS is age-dependent and increasing with age. Moreover, these data suggest atypical pre- and postpubertal neural development in WS, with sleep/wake balance and REM sleep time indicating accelerated aging while NREM sleep composition revealing signs of an as yet unidentified, perhaps compensatory developmental delay.

Non-REM sleep EEG power distribution in fatigue and sleepiness

ObjectivesThe aim of this study is to contribute to the sleep-related differentiation between daytime fatigue and sleepiness. Methods135 subjects presenting with sleep apnea–hypopnea syndrome (SAHS, n=58) or chronic fatigue syndrome (CFS, n=52) with respective sleepiness or fatigue complaints and a control group (n=25) underwent polysomnography and psychometric assessments for fatigue, sleepiness, affective symptoms and perceived sleep quality. Sleep EEG spectral analysis for ultra slow, delta, theta, alpha, sigma and beta power bands was performed on frontal, central and occipital derivations. ResultsPatient groups presented with impaired subjective sleep quality and higher affective symptom intensity. CFS patients presented with highest fatigue and SAHS patients with highest sleepiness levels. All groups showed similar total sleep time. Subject groups mainly differed in sleep efficiency, wake after sleep onset, duration of light sleep (N1, N2) and slow wave sleep, as well as in sleep fragmentation and respiratory disturbance. Relative non-REM sleep power spectra distributions suggest a pattern of power exchange in higher frequency bands at the expense of central ultra slow power in CFS patients during all non-REM stages. In SAHS patients, however, we found an opposite pattern at occipital sites during N1 and N2. ConclusionsSlow wave activity presents as a crossroad of fatigue and sleepiness with, however, different spectral power band distributions during non-REM sleep. The homeostatic function of sleep might be compromised in CFS patients and could explain why, in contrast to sleepiness, fatigue does not resolve with sleep in these patients. The present findings thus contribute to the differentiation of both phenomena.