High internight reliability of computer-measured NREM delta, sigma, and beta: biological implications

Electroencephalographic markers from routine sleep discriminate individuals who are vulnerable or resilient to sleep loss

Sleep loss impairs cognition; however, individuals differ in their response to sleep loss. Current methods to identify an individual's vulnerability to sleep loss involve time-consuming sleep-loss challenges and neurobehavioural tests. Here, we sought to identify electroencephalographic markers of sleep-loss vulnerability obtained from routine night sleep. We retrospectively analysed four studies in which 50 healthy young adults (21 women) completed a laboratory baseline-sleep phase followed by a sleep-loss challenge. After classifying subjects as resilient or vulnerable to sleep loss, we extracted three electroencephalographic features from four channels during the baseline nights, evaluated the discriminatory power of these features using the first two studies (discovery), and assessed reproducibility of the results using the remaining two studies (reproducibility). In the discovery analysis, we found that, compared to resilient subjects, vulnerable subjects exhibited: (1) higher slow-wave activity power in channel O1 (p < 0.0042, corrected for multiple comparisons) and in channels O2 and C3 (p < 0.05, uncorrected); (2) higher slow-wave activity rise rate in channels O1 and O2 (p < 0.05, uncorrected); and (3) lower sleep spindle frequency in channels C3 and C4 (p < 0.05, uncorrected). Our reproducibility analysis confirmed the discovery results on slow-wave activity power and slow-wave activity rise rate, and for these two electroencephalographic features we observed consistent group-difference trends across all four channels in both analyses. The higher slow-wave activity power and slow-wave activity rise rate in vulnerable individuals suggest that they have a persistently higher sleep pressure under normal rested conditions.

Protocol of the Budapest sleep, experiences, and traits study: An accessible resource for understanding associations between daily experiences, individual differences, and objectively measured sleep

Sleep is both a neurophysiological state and a biologically necessary behavior that performs a variety of indispensable roles for human health, development, and cognitive functioning. Despite this, comparatively little is known about the relationships between daily experiences and sleep features. Importantly, these relationships are bidirectional in nature, may be differently associated with subjectively and objectively assessed sleep, and may also be modulated by individual differences To address this challenge, we created the Budapest Sleep, Experiences, and Traits Study (BSETS), a multidisciplinary observational sleep study utilizing novel remote EEG devices. BSETS was designed to establish a dataset for future use in investigating the relationships between sleep features and daily experiences. In this paper we describe the protocol of the currently ongoing BSETS, which examines a community-dwelling sample of over 250 healthy participants who are studied in a naturalistic setting using a large questionnaire assessing psychological, demographic, and anthropometric information, as well as evening/morning diaries of sleep and daily experiences, and mobile EEG recordings over a period of 7 days. This dataset will become an accessible resource to the wider scientific community and can be utilized to investigate the complex multidirectional relationships between objectively and subjectively measured sleep, daily experiences, and individual differences, bestowing it with significant value for sleep researchers as well as practitioners working in clinical settings with patients suffering from disordered sleep.

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.

The sleep EEG envelope is a novel, neuronal firing-based human biomarker

Sleep EEG reflects voltage differences relative to a reference, while its spectrum reflects its composition of various frequencies. In contrast, the envelope of the sleep EEG reflects the instantaneous amplitude of oscillations, while its spectrum reflects the rhythmicity of the occurrence of these oscillations. The sleep EEG spectrum is known to relate to demographic, psychological and clinical characteristics, but the envelope spectrum has been rarely studied. In study 1, we demonstrate in human invasive data from cortex-penetrating microelectrodes and subdural grids that the sleep EEG envelope spectrum reflects neuronal firing. In study 2, we demonstrate that the scalp EEG envelope spectrum is stable within individuals. A multivariate learning algorithm could predict age (r = 0.6) and sex (r = 0.5) from the EEG envelope spectrum. With age, oscillations shifted from a 4-5 s rhythm to faster rhythms. Our results demonstrate that the sleep envelope spectrum is a promising biomarker of demographic and disease-related phenotypes.

Association of a novel EEG metric of sleep depth/intensity with attention-deficit/hyperactivity, learning, and internalizing disorders and their pharmacotherapy in adolescence

STUDY OBJECTIVES

Psychiatric/learning disorders are associated with sleep disturbances, including those arising from abnormal cortical activity. The odds ratio product (ORP) is a standardized electroencephalogram metric of sleep depth/intensity validated in adults, while ORP data in youth are lacking. We tested ORP as a measure of sleep depth/intensity in adolescents with and without psychiatric/learning disorders.

METHODS

Four hundred eighteen adolescents (median 16 years) underwent a 9-hour, in-lab polysomnography. Of them, 263 were typically developing (TD), 89 were unmedicated, and 66 were medicated for disorders including attention-deficit/hyperactivity (ADHD), learning (LD), and internalizing (ID). Central ORP during non-rapid eye movement (NREM) sleep was the primary outcome. Secondary/exploratory outcomes included central and frontal ORP during NREM stages, in the 9-seconds following arousals (ORP-9), in the first and second halves of the night, during REM sleep and wakefulness.

RESULTS

Unmedicated youth with ADHD/LD had greater central ORP than TD during stage 3 and in central and frontal regions during stage 2 and the second half of the sleep period, while ORP in youth with ADHD/LD on stimulants did not significantly differ from TD. Unmedicated youth with ID did not significantly differ from TD in ORP, while youth with ID on antidepressants had greater central and frontal ORP than TD during NREM and REM sleep, and higher ORP-9.

CONCLUSIONS

The greater ORP in unmedicated youth with ADHD/LD, and normalized levels in those on stimulants, suggests ORP is a useful metric of decreased NREM sleep depth/intensity in ADHD/LD. Antidepressants are associated with greater ORP/ORP-9, suggesting these medications induce cortical arousability.

Evidence of a maturational disruption in non-rapid eye movement sleep slow wave activity in youth with attention-deficit/hyperactivity, learning and internalizing disorders

BACKGROUND

Sleep slow wave activity (SWA) peaks during childhood and declines in the transition to adolescence during typical development (TD). It remains unknown whether this trajectory differs in youth with neuropsychiatric disorders.

METHODS

We analyzed sleep EEGs of 664 subjects 6 to 21 y (449 TD, 123 unmedicated, 92 medicated) and 114 subjects 7-12 y (median 10.5 y) followed-up at 18-22 y (median 19 y). SWA (0.4-4 Hz) power was calculated during non-rapid eye movement sleep.

RESULTS

TD and unmedicated youth showed cubic central and frontal SWA trajectories from 6 to 21 y (p-cubic<0.05), with TD youth showing peaks in central SWA at 6.8 y and frontal at 8.2 y. Unmedicated attention-deficit/hyperactivity (ADHD) and/or learning disorders (LD) showed peak central SWA 2 y later (at 9.6 y, coinciding with peak frontal SWA) than TD, followed by a 67% steeper slope by 19 y. Frontal SWA peak and slope in unmedicated ADHD/LD, and that of central and frontal in internalizing disorders (ID), were similar to TD. Unmedicated ADHD/LD did not differ in the longitudinal SWA percent change by 18-22 y; unmedicated ID showed a lower longitudinal change in frontal SWA than TD. Medicated youth showed a linear decline in central and frontal SWA from 6 to 21 y (p-linear<0.05).

CONCLUSIONS

ADHD/LD youth show a maturational delay and potential topographical disruption in SWA during childhood and steeper decline throughout adolescence, suggesting faster synaptic pruning. Youth with ID experience less changes in frontal SWA by late adolescence. Psychotropic medications may impact the maturational trajectory of SWA, but not the magnitude of developmental decline by late adolescence.

The Fingerprint-Like Pattern of Nocturnal Brain Activity Demonstrated in Young Individuals is Also Present in Senior Adulthood

PURPOSE

The quantitative sleep EEG has been considered as electroencephalographic "fingerprint", ie, it is stable within but differs between individuals. So far, however, almost all studies addressing this aspect have been conducted in young men. It was therefore of interest to know whether the sleep EEG fingerprint concept holds true in older samples of both sexes.

PATIENTS AND METHODS

Data from three different subsamples of 30 healthy individuals each were reused for the present secondary analysis (young men (YM) = 25.6 ± 2.4 years, elderly men (EM) = 69.1 ± 5.5 years, elderly women (EW) = 67.8 ± 5.7 years). Individuals slept ten times in the sleep laboratory, resulting in a total of 900 study nights. However, to avoid misinterpretation due to intervention-related changes in sleep EEG power spectra, only the 3 sham nights without any intervention were included, reducing the datasets to 270. To determine stability of NREM sleep EEG power spectra between sham night pairs, within- and between-subject Manhattan distance measures were computed separately by sample.

RESULTS

Regardless of subsample and sham night pair, lowest distance measures, ie, largest similarity, were observed for within-subject power spectra comparisons (range of mean distance measures for EW from 3.82 to 4.06, for EM from 3.55 to 3.63, and for YM from 3.04 to 3.62). Moreover, intraindividual similarity did not differ substantially between samples. Between-subject power spectra distance measures were considerably larger (range of mean distance measures for EW from 12.95 to 13.15, for EM from 12.21 to 12.57, and for YM from 10.33 to 10.78) and varied significantly between young and elderly individuals.

CONCLUSION

The present results support the view that the sleep EEG power spectrum is an individual trait-like characteristic that remains unique up until old age. This finding may help to increase the sensitivity in measuring intervention effects.

Nocturnal Brain Activity Differs with Age and Sex: Comparisons of Sleep EEG Power Spectra Between Young and Elderly Men, and Between 60-80-Year-Old Men and Women

PURPOSE

Quantification of nocturnal EEG activity has emerged as a promising extension to the conventional sleep evaluation approach. To date, studies focusing on quantitative sleep EEG data in relation to age and sex have revealed considerable variation across lifespan and differences between men and women. However, sleep EEG power values from elderly individuals are still rare. The present secondary analysis aimed to fill this gap.

PARTICIPANTS AND METHODS

Sleep EEG data of 30 healthy elderly males (mean age ± SD: 69.1 ± 5.5 years), 30 healthy elderly females (67.8 ± 5.7 years), and of 30 healthy young males (25.6 ± 2.4 years) have been collected in three different studies with the same experimental design. Each individual contributed three polysomnographic recordings without any intervention to the analysis. Sleep recordings were performed and evaluated according to the standard of the American Academy of Sleep Medicine. Sleep EEG signals were derived from 19 electrode sites. Sleep-stage specific global and regional EEG power were compared between samples using a permutation-based statistic in combination with the threshold-free cluster enhancement method.

RESULTS

The present results showed pronounced differences in sleep EEG power between older men and women. The nocturnal EEG activity of older women was generally larger than that of older men, confirming previously reported variations with sex in younger individuals. Aging was reflected by differences in EEG power between young and elderly men for lower frequencies and for the sleep spindle frequency range, again consistent with prior studies.

CONCLUSION

The findings of this investigation complement those of earlier studies. They add to the understanding of nocturnal brain activity manifestation in senior adulthood and show how it differs with age in males. Unfortunately, the lack of information on young women prevents a similar insight for females.

Sex and Pubertal Differences in the Maturational Trajectories of Sleep Spindles in the Transition from Childhood to Adolescence: A Population-Based Study

Sleep spindles, bursts of electroencephalogram (EEG) activity in the σ-frequency (11–16 Hz) range, may be biomarkers of cortical development. Studies capturing the transition to adolescence are needed to delineate age-related, sex-related, and pubertal-related changes in sleep spindles at the population-level. We analyzed the sleep EEG of 572 subjects 6–21 years (48% female) and 332 subjects 5–12 years (46% female) followed-up at 12–22 years. From 6 to 21 years, spindle density (p quadratic = 0.019) and fast (12–16 Hz) spindle percent (p quadratic = 0.016) showed inverted U-shaped trajectories, with plateaus after 15 and 19 years, respectively. Spindle frequency increased (p linear < 0.001), while spindle power decreased (p linear < 0.001) from 6 to 21 years. The trajectories of spindle density, frequency, and fast spindle percent diverged between females and males, in whom density plateaued by 14 years, fast spindle percent by 16 years, and frequency by 18 years, while fast spindle percent and spindle frequency continued to increase until 21 years in females. Males experienced a longitudinal increase in spindle density 31% greater than females by 12–14 years (p = 0.006). Females experienced an increase in spindle frequency and fast spindle percent 2% and 41% greater, respectively, than males by 18–22 years (both p = 0.004), while males experienced a 14% greater decline in spindle power by 18–22 years (p = 0.018). Less mature adolescents (86% male) experienced a longitudinal increase in spindle density 36% greater than mature adolescents by 12–14 years (p = 0.002). Overall, males experience greater maturational changes in spindle density in the transition to adolescence, driven by later pubertal development, and sex differences become prominent in early adulthood when females have greater spindle power, frequency, and fast spindle percent.

Maturational trajectories of non-rapid eye movement slow wave activity and odds ratio product in a population-based sample of youth

BACKGROUND

Brain maturation is reflected in the sleep electroencephalogram (EEG) by a decline in non-rapid eye movement (NREM) slow wave activity (SWA) throughout adolescence and a related decrease in sleep depth. However, this trajectory and its sex and pubertal differences lack replication in population-based samples. We tested age-related changes in SWA (0.4-4 Hz) power and odds ratio product (ORP), a standardized measure of sleep depth.

METHODS

We analyzed the sleep EEG of 572 subjects aged 6-21 y (48% female, 26% racial/ethnic minority) and 332 subjects 5-12 y followed-up at 12-22 y. Multivariable-adjusted analyses tested age-related cross-sectional and longitudinal trajectories of SWA and ORP.

RESULTS

SWA remained stable from age 6 to 10, decreased between ages 11 and 17, and plateaued from age 18 to 21 (p-cubic<0.001); females showed a longitudinal decline 23% greater than males by 13 y, while males experienced a steeper slope after 14 y and their longitudinal decline was 21% greater by 19 y. More mature adolescents (75% female) experienced a greater longitudinal decline in SWA than less mature adolescents by 14 y. ORP showed an age-related increasing trajectory (p-linear<0.001) with no sex or pubertal differences.

CONCLUSIONS

We provide population-level evidence for the maturational decline and sex and pubertal differences in SWA in the transition from childhood to adolescence, while introducing ORP as a novel metric in youth. Along with previous studies, the distinct trajectories observed suggest that age-related changes in SWA reflect brain maturation and local/synaptic processes during this developmental period, while those of ORP may reflect global/state control of NREM sleep depth.

Sleep spindle abnormalities related to Alzheimer's disease: a systematic mini-review

Accumulating evidence supports a bidirectional relationship between sleep disruption and Alzheimer's disease (AD) pathology. Among various sleep electroencephalography activities, the sleep spindle is one specific electroencephalographic rhythm that has potential to be a biomarker for AD. This review explores the association between sleep spindles and AD-related dementia from a neuropsychological perspective by a systematic re-examining of recent findings. In general, sleep spindles, characterized by density, amplitude, duration, and frequency, are disrupted in AD. Moreover, its functional coupling with slow oscillation also suffers in AD. While preliminary, our observations and comparisons suggest that spindle density rather than frequency and fast spindles rather than slow spindles could be more sensitive to AD-related dementia, and spindle plasticity provides possibilities for targeted interference. In conclusion, quantitative and qualitative features of sleep spindles represent potential non-invasive and cost-effective biomarkers for AD and provide both therapeutic and public health implications.

The heritability of the human K-complex: a twin study

Sleep electroencephalogram (EEG) has a trait-like nature. Several findings highlighted the heritability of spectral power in specific frequency ranges and sleep spindles during nonrapid eye movement (NREM) sleep. However, a genetic influence on the K-complex (KC), one of the electrophysiological hallmarks of NREM sleep, has never been assessed. Here, we investigated the heritability of the KC detected during NREM stage 2 comparing 10 monozygotic (MZ) and 10 dizygotic (DZ) twin pairs. Genetic variance analysis (GVA) and intraclass correlation coefficients (ICCs) were performed to assess the genetic effect and within-pair similarity for KC density, amplitude, and for the area under the curve (AUC) of the KC average waveform at Fz, Cz, and Pz scalp locations. Moreover, cluster analysis was performed on the KC average waveform profile. We observed a significant genetic effect on KC AUC at Cz and Pz, and on amplitude at Pz. Within-pair similarity (ICCs) was always significant for MZ twins except for KC density at Fz, whereas DZ twins always exhibited ICCs below the significance threshold, with the exception of density at Pz. The largest differences in within-pair similarity between MZ and DZ groups were observed again for AUC at Cz and Pz. MZ pairs accurately clustered for the KC average waveform with a higher frequency (successful clustering rate for MZ pairs: Fz = 60%; Cz = 80%; Pz = 90%) compared with DZ pairs (successful clustering rate for DZ pairs: Fz = 10%; Cz = 10%; Pz = none). Our results suggest the existence of a genetic influence on the human KC, particularly related to its morphology and maximally observable in central and parietal locations.

Preparing for Mars: human sleep and performance during a 13 month stay in Antarctica

Study Objectives

Manned spaceflights from Earth to Mars will likely become reality within the next decades. Humans will be exposed to prolonged isolation, confinement, and altered photoperiods under artificial atmospheric conditions, with potential adverse effects on sleep and performance. On Earth, polar environments serve as space analogs to study human adaptation; yet, few studies include polysomnography due to operational constraints.

Methods

Polysomnography, self-reported sleepiness and fatigue, and psychomotor performance were measured every 6 weeks in 13 males ("Hivernauts") during a 13 month winter-over campaign at Concordia (Antarctica). Stability and robustness of interindividual differences were examined by means of intraclass correlations.

Results

Hivernauts present with high-altitude periodic breathing, increased sleep onset latencies, and reduced psychomotor speed. Except for obstructive apneas, all sleep, sleepiness, and psychomotor performance variables remain stable over time. Individual differences in respiratory variables show the highest degree of stability and robustness, followed by fatigue and situational sleepiness, sleep fragmentation, and psychomotor speed, suggesting moderate to substantial trait-like characteristics for these variables. Phase delays are suspected in Hivernauts, both in individuals with imposed and self-selected bedtimes. A significant decline in psychomotor speed over time is observed in the latter group.

Conclusions

Space analog conditions such as isolated confinement, extreme photoperiods, and altered atmospheric conditions affect human sleep and performance. However, individual responses to these extreme environmental challenges show large differences and remain relatively stable under prolonged exposure. Ad hoc polysomnographic, including respiratory function monitoring is therefore recommended for selecting eligible candidates for extraterrestrial sojourns.

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.

Opportunities for utilizing polysomnography signals to characterize obstructive sleep apnea subtypes and severity

BACKGROUND

Obstructive sleep apnea (OSA) is a heterogeneous sleep disorder with many pathophysiological pathways to disease. Currently, the diagnosis and classification of OSA is based on the apnea-hypopnea index, which poorly correlates to underlying pathology and clinical consequences. A large number of in-laboratory sleep studies are performed around the world every year, already collecting an enormous amount of physiological data within an individual. Clinically, we have not yet fully taken advantage of this data, but combined with existing analytical approaches, we have the potential to transform the way OSA is managed within an individual patient. Currently, respiratory signals are used to count apneas and hypopneas, but patterns such as inspiratory flow signals can be used to predict optimal OSA treatment. Electrocardiographic data can reveal arrhythmias, but patterns such as heart rate variability can also be used to detect and classify OSA. Electroencephalography is used to score sleep stages and arousals, but specific patterns such as the odds-ratio product can be used to classify how OSA patients responds differently to arousals.

OBJECTIVE

In this review, we examine these and many other existing computer-aided polysomnography signal processing algorithms and how they can reflect an individual's manifestation of OSA.

SIGNIFICANCE

Together with current technological advance, it is only a matter of time before advanced automatic signal processing and analysis is widely applied to precision medicine of OSA in the clinical setting.

Shared Genetic Control of Brain Activity During Sleep and Insulin Secretion: A Laboratory-Based Family Study

Over the past 20 years, a large body of experimental and epidemiologic evidence has linked sleep duration and quality to glucose homeostasis, although the mechanistic pathways remain unclear. The aim of the current study was to determine whether genetic variation influencing both sleep and glucose regulation could underlie their functional relationship. We hypothesized that the genetic regulation of electroencephalographic (EEG) activity during non-rapid eye movement sleep, a highly heritable trait with fingerprint reproducibility, is correlated with the genetic control of metabolic traits including insulin sensitivity and β-cell function. We tested our hypotheses through univariate and bivariate heritability analyses in a three-generation pedigree with in-depth phenotyping of both sleep EEG and metabolic traits in 48 family members. Our analyses accounted for age, sex, adiposity, and the use of psychoactive medications. In univariate analyses, we found significant heritability for measures of fasting insulin sensitivity and β-cell function, for time spent in slow-wave sleep, and for EEG spectral power in the delta, theta, and sigma ranges. Bivariate heritability analyses provided the first evidence for a shared genetic control of brain activity during deep sleep and fasting insulin secretion rate.

Determinants of Slow-Wave Activity in Overweight and Obese Adults: Roles of Sex, Obstructive Sleep Apnea and Testosterone Levels

Background: Slow-wave activity (SWA) in non-rapid eye movement (NREM) sleep, obtained by spectral analysis of the electroencephalogram, is a marker of the depth or intensity of NREM sleep. Higher levels of SWA are associated with lower arousability during NREM sleep and protect against sleep fragmentation. Multiple studies have documented that SWA levels are higher in lean women, compared to age-matched lean men, but whether these differences persist in obese subjects is unclear. Obstructive sleep apnea (OSA), a condition associated with obesity, is more prevalent in men than in women. Sex differences in SWA could therefore be one of the factors predisposing men to OSA. Furthermore, we hypothesized that higher levels of testosterone may be associated with lower levels of SWA. Objective: The aim of the current study was to identify sex differences in the determinants of SWA in young and middle-aged overweight and obese adults. Methods: We enrolled 101 overweight and obese but otherwise healthy participants from the community (44 men, 57 women) in this cross-sectional study. Participants underwent an overnight in-laboratory polysomnogram. The recordings were submitted to sleep staging and spectral analysis. Sex differences and the potential contribution of testosterone levels were evaluated after adjusting for age, body mass index and race/ethnicity. Results: OSA was present in 66% of men and in 44% of women. After adjustment for differences in age, race/ethnicity and BMI, the odds ratio for OSA in men vs. women was 3.17 (95% CI 1.14-9.43, p = 0.027). There was a graded inverse relationship between the apnea-hypopnea index (AHI) and SWA in men (β = -0.21, p = 0.018) but not in women (β = 0.10, p = 0.207). In a multivariate regression model, higher testosterone levels were independently associated with lower SWA in men after controlling for age, race/ethnicity and apnea-hypopnea index (β = -0.56, p = 0.025). Conclusion: Increasing severity of OSA was associated with significant decrease in sleep intensity in men but not in women. Higher testosterone levels were associated with lower sleep intensity in men. Men with higher testosterone levels may therefore have lower arousal thresholds and higher ventilatory instability in NREM sleep, and be at greater risk of OSA.

The sleep EEG spectrum is a sexually dimorphic marker of general intelligence

The shape of the EEG spectrum in sleep relies on genetic and anatomical factors and forms an individual "EEG fingerprint". Spectral components of EEG were shown to be connected to mental ability both in sleep and wakefulness. EEG sleep spindle correlates of intelligence, however, exhibit a sexual dimorphism, with a more pronounced association to intelligence in females than males. In a sample of 151 healthy individuals, we investigated how intelligence is related to spectral components of full-night sleep EEG, while controlling for the effects of age. A positive linear association between intelligence and REM anterior beta power was found in females but not males. Transient, spindle-like "REM beta tufts" are described in the EEG of healthy subjects, which may reflect the functioning of a recently described cingular-prefrontal emotion and motor regulation network. REM sleep frontal high delta power was a negative correlate of intelligence. NREM alpha and sigma spectral power correlations with intelligence did not unequivocally remain significant after multiple comparisons correction, but exhibited a similar sexual dimorphism. These results suggest that the neural oscillatory correlates of intelligence in sleep are sexually dimorphic, and they are not restricted to either sleep spindles or NREM sleep.

Genetic Markers of Sleep and Sleepiness

The circadian clock interacts with the sleep homeostatic drive in humans. Chronotype and sleep parameters show substantial heritability, underscoring a genetic component to these measures. This article reviews the genetic underpinnings of chronotype and of sleep, including sleepiness, sleep quality and latency, and sleep timing and duration in healthy adult sleepers, drawing on candidate gene and genome-wide association studies. Notably, both circadian and noncircadian genes associate with individual differences in chronotype and in sleep parameters. The article concludes with a brief discussion of future research directions.

Short- and Long-Term Sleep Stability in Insomniacs and Healthy Controls

STUDY OBJECTIVES

Assess the short- and long-term stability of sleep duration in patients with insomnia and normal-sleeping controls.

DESIGN

Observational short-term and prospective studies.

SETTING

Sleep laboratory.

PARTICIPANTS

Patients with insomnia (n = 150) and controls (n = 151) were recruited from the local community or sleep disorders clinic. A subsample of 95 men from the Penn State Adult Cohort (PSAC) were followed up 2.6 y after their initial visit.

MEASUREMENTS

Participants underwent a physical examination and 8-h polysomnography (PSG) recording for 3 consecutive nights (controls and insomniacs), or 2 single nights separated by several years (PSAC). Intraclass correlation coefficients (ICCs) assessed the stability of the variables total sleep time (TST), sleep onset latency (SOL), and wake after sleep onset (WASO). We also examined persistence of the first-night classification of "short" versus "normal" sleep duration on subsequent nights.

RESULTS

Stability of TST, SOL, and WASO based on 1 night were slight to moderate in both patients with insomnia (ICC = 0.37-0.57) and controls (ICC = 0.39-0.59), and became substantial to almost perfect when based on the average of 3 nights (ICC = 0.64-0.81). We observed similar degrees of stability for TST and WASO in the longitudinal sample, with moderate stability based on a single night and substantial stability based on both nights. In examining the persistence of "short" and "normal" sleep duration, 71.4% (controls), 74.7% (patients with insomnia), and 72.6% (longitudinal sample) of participants retained their first-night classifications over subsequent nights.

CONCLUSIONS

Sleep duration variables, particularly total sleep time based on 3 consecutive nights in both patients with insomnia and controls or two single-night recordings separated by several years, are stable and reflect a person's habitual sleep. Furthermore, a single night in the laboratory may be useful for reliably classifying one's sleep duration.

Genetics of rapid eye movement sleep in humans

The trait-like nature of electroencephalogram (EEG) is well established. Furthermore, EEG of wake and non-rapid eye movement (non-REM) sleep has been shown to be highly heritable. However, the genetic effects on REM sleep EEG microstructure are as yet unknown. REM sleep is of special interest since animal and human data suggest a connection between REM sleep abnormalities and the pathophysiology of psychiatric and neurological diseases. Here we report the results of a study in monozygotic (MZ) and dizygotic (DZ) twins examining the heritability of REM sleep EEG. We studied the architecture, spectral composition and phasic parameters of REM sleep and identified genetic effects on whole investigated EEG frequency spectrum as well as phasic REM parameters (REM density, REM activity and organization of REMs in bursts). In addition, cluster analysis based on the morphology of the EEG frequency spectrum revealed that the similarity among MZ twins is close to intra-individual stability. The observed strong genetic effects on REM sleep characteristics establish REM sleep as an important source of endophenotypes for psychiatric and neurological diseases.

Defending sleepwalkers with science and an illustrative case

OBJECTIVE

To test whether laboratory-based research differentiating sleepwalkers (SW) from controls (C) can be applied in an uncontrolled forensic case as evidence the alleged crime was committed during an arousal from sleep in which the mind is not fully conscious due to a SW disorder.

METHODS

A PSG study recorded 8 months after the defendant was charged was analyzed independently by spectral analysis. Slow wave activity (SWA) and cyclic alternating pattern (CAP) rates were computed. Clinical interviews and police records were reviewed for data re: the defendant's sleep prior to the event and use of drugs, alcohol, and stimulants.

RESULTS

The SWA distribution was abnormally low and flat, significantly lower than published controls; in the first NREM cycle, CAP rate 55 was above normal. Two weeks of prior sleep deprivation was confirmed from interviews and defendant's observed daytime sleepiness. Caffeine intake the day before the event was calculated at 826 mg over 14 hours. Snoring and a mild breathing disorder were present in the PSG.

CONCLUSION

Testimony based on spectral analysis of PSG recorded following an alleged criminal event supported a SW explanation for the non-rational behaviors charged. The defendant was acquitted of all charges and has been successfully treated.

Impact of GH replacement therapy on sleep in adult patients with GH deficiency of pituitary origin

OBJECTIVES

We previously reported that adult patients with GH deficiency (GHD) due to a confirmed or likely pituitary defect, compared with healthy controls individually matched for age, gender, and BMI, have more slow-wave sleep (SWS) and higher delta activity (a marker of SWS intensity). Here, we examined the impact of recombinant human GH (rhGH) therapy, compared with placebo, on objective sleep quality in a subset of patients from the same cohort.

DESIGN

Single-blind, randomized, crossover design study.

METHODS

Fourteen patients with untreated GHD of confirmed or likely pituitary origin, aged 22-74 years, participated in the study. Patients with associated hormonal deficiencies were on appropriate replacement therapy. Polygraphic sleep recordings, with bedtimes individually tailored to habitual sleep times, were performed after 4 months on rhGH or placebo.

RESULTS

Valid data were obtained in 13 patients. At the end of the rhGH treatment period, patients had a shorter sleep period time than at the end of the placebo period (479±11 vs 431±19 min respectively; P=0.005), primarily due to an earlier wake-up time, and a decrease in the intensity of SWS (delta activity) (559±125 vs 794±219 μV(2) respectively; P=0.048).

CONCLUSIONS

Four months of rhGH replacement therapy partly reversed sleep disturbances previously observed in untreated patients. The decrease in delta activity associated with rhGH treatment adds further evidence to the hypothesis that the excess of high-intensity SWS observed in untreated pituitary GHD patients is likely to result from overactivity of the hypothalamic GHRH system due to the lack of negative feedback inhibition by GH.

About sleep's role in memory

Over more than a century of research has established the fact that sleep benefits the retention of memory. In this review we aim to comprehensively cover the field of "sleep and memory" research by providing a historical perspective on concepts and a discussion of more recent key findings. Whereas initial theories posed a passive role for sleep enhancing memories by protecting them from interfering stimuli, current theories highlight an active role for sleep in which memories undergo a process of system consolidation during sleep. Whereas older research concentrated on the role of rapid-eye-movement (REM) sleep, recent work has revealed the importance of slow-wave sleep (SWS) for memory consolidation and also enlightened some of the underlying electrophysiological, neurochemical, and genetic mechanisms, as well as developmental aspects in these processes. Specifically, newer findings characterize sleep as a brain state optimizing memory consolidation, in opposition to the waking brain being optimized for encoding of memories. Consolidation originates from reactivation of recently encoded neuronal memory representations, which occur during SWS and transform respective representations for integration into long-term memory. Ensuing REM sleep may stabilize transformed memories. While elaborated with respect to hippocampus-dependent memories, the concept of an active redistribution of memory representations from networks serving as temporary store into long-term stores might hold also for non-hippocampus-dependent memory, and even for nonneuronal, i.e., immunological memories, giving rise to the idea that the offline consolidation of memory during sleep represents a principle of long-term memory formation established in quite different physiological systems.

Sleep EEG fingerprints reveal accelerated thalamocortical oscillatory dynamics in Williams syndrome

Sleep EEG alterations are emerging features of several developmental disabilities, but detailed quantitative EEG data on the sleep phenotype of patients with Williams syndrome (WS, 7q11.23 microdeletion) is still lacking. Based on laboratory (Study I) and home sleep records (Study II) here we report WS-related features of the patterns of antero-posterior 8-16 Hz non-rapid-eye-movement (NREM) sleep EEG power distributions. Participants in Study I were 9 WS and 9 typically developing (TD) controls matched for age (14-29 years) and sex, and sleeping for two consecutive nights in the laboratory. WS participants were characterized by region-independent decreases in 10.50-12.50 Hz and central increases in 14.75-15.75 Hz EEG power. Region-independent decreases and increases in z-scores of the spectra were observed in the 10.25-12.25 Hz and 14-16 Hz ranges, respectively. Moreover, in the EEG spectra of participants with WS a lower probability for the emergence of a frontally dominant peak was observed. Parietal fast sigma peaks and the antero-posterior shifts in power distributions were of higher frequencies in WS (~1 Hz difference). A 1 year follow-up of 9 WS and 3 TD participants, as well as their inclusion into larger samples (20 WS and 20 TD, age: 6-29 years) of a two-night ambulatory home polysomnography study confirmed the WS-specific decrease in alpha/low sigma power (8-11.75 Hz) and the pattern of z-score differences (decreases: 8.50-11.25 Hz; increases: 13.5-14 Hz), including the antero-posterior shifts in power distribution (0.5 Hz) and some features of the spectral peaks. Altogether these data suggest a decrease in alpha/low sigma power, as well as a redistribution of NREM sleep 8-16 Hz EEG power toward the higher frequencies and/or a higher frequency of NREM sleep thalamocortical oscillations in WS.

Evaluation of the association of menopausal status with delta and beta EEG activity during sleep

STUDY OBJECTIVES

Women report increasing sleep difficulties during menopause, but polysomnographic measures do not detect sleep disturbances. We examined whether two spectral analysis sleep measures, delta and beta power, were related to menopausal status.

DESIGN

The Study of Women's Health Across the Nation (SWAN) Sleep Study compared cross-sectionally spectral sleep measures in women in different stages of menopause.

SETTING

Sleep EEG was recorded in the participants' homes with ambulatory recorders.

PARTICIPANTS

A multi-ethnic cohort of premenopausal and early perimenopausal (n = 189), late perimenopausal (n = 73), and postmenopausal (n = 59) women.

MEASUREMENTS

EEG power in the delta and beta frequency bands was calculated for all night NREM and all night REM sleep. Physical, medical, psychological, and socioeconomic data were collected from questionnaires and diaries.

RESULTS

Beta EEG power in NREM and REM sleep in late perimenopausal and postmenopausal women exceeded that in pre- and early perimenopausal women. Neither all night delta power nor the trend in delta power across the night differed by menopausal status. In a multivariate model that controlled for the physical, demographic, behavioral, psychological, and health-related changes that accompany menopause, beta power in both NREM and REM sleep EEG was significantly related to menopausal status. The frequency of hot flashes explained part but not all of the relation of beta power to menopausal status.

CONCLUSIONS

Elevated beta EEG power in late perimenopausal and postmenopausal women provides an objective measure of disturbed sleep quality in these women. Elevated beta EEG activity suggests that arousal level during sleep is higher in these women.

The genetic and molecular regulation of sleep: from fruit flies to humans

It has been known for a long time that genetic factors affect sleep quantity and quality. Genetic screens have identified several mutations that affect sleep across species, pointing to an evolutionary conserved regulation of sleep. Moreover, it has also been recognized that sleep affects gene expression. These findings have given valuable insights into the molecular underpinnings of sleep regulation and function that might lead the way to more efficient treatments for sleep disorders.

The individual adjustment method of sleep spindle analysis: methodological improvements and roots in the fingerprint paradigm

Evidence supports the robustness and stability of individual differences in non-rapid eye movement (NREM) sleep electroencephalogram (EEG) spectra with a special emphasis on the 9-16 Hz range corresponding to sleep spindle activity. These differences cast doubt on the universal validity of sleep spindle analysis methods based on strict amplitude and frequency criteria or a set of templates of natural spindles. We aim to improve sleep spindle analysis by the individual adjustments of frequency and amplitude criteria, the use of a minimum set of a priori knowledge, and by clear dissections of slow- and fast sleep spindles as well as to transcend the concept of visual inspection as being the ultimate test of the method's validity. We defined spindles as those segments of the NREM sleep EEG which contribute to the two peak regions within the 9-16 Hz EEG spectra. These segments behaved as slow- and fast sleep spindles in terms of topography and sleep cycle effects, while age correlated negatively with the occurrence of fast type events only. Automatic detections covered 92.9% of visual spindle detections (A&VD). More than half of the automatic detections (58.41%) were exclusively automatic detections (EADs). The spectra of EAD correlated significantly and positively with the spectra of A&VD as well as with the average (AVG) spectra. However, both EAD and A&VD had higher individual-specific spindle spectra than AVG had. Results suggest that the individual adjustment method (IAM) detects EEG segments possessing the individual-specific spindle spectra with higher sensitivity than visual scoring does.

Heritability of sleep electroencephalogram

BACKGROUND

Understanding the basis of sleep-related endophenotypes might help to pinpoint factors modulating susceptibility to psychiatric disorders. However, the genetic underpinnings of sleep microarchitecture in humans remain largely unknown. Here we report on the results of a classical twin study in monozygotic (MZ) and dizygotic (DZ) twin pairs examining the genetic effect on sleep electroencephalogram (EEG) composition.

METHODS

Polysomnographic recordings were obtained in 35 pairs of MZ (26.4 +/- 5.4 years, 17-43 years, 17 male pairs, 18 female pairs) and 14 same-gender pairs of DZ twins (22.1 +/- 2.7 years, 18-26 years, 7 male pairs, 7 female pairs). The EEG power spectra were generated on the basis of Fast Fourier transformations combined with conventional sleep parameters, according to standardized criteria.

RESULTS

We tested the genetic variance contributing to the observed overall variance of the sleep measures and found that the relative contributions of the delta, theta, alpha, and sigma frequency bands at central derivations were significantly correlated to the genetic background. In these frequency bands, MZ twins also showed within-pair concordance in spectral power that was significantly higher than that of DZ twins.

CONCLUSIONS

The broad overlap of EEG frequencies during non-REM sleep and wakefulness, which shows a significant genetic variance, supports the hypothesis of common neuronal mechanisms generating EEG oscillations in humans. Our findings strongly support the suitability of the spectral composition of non-REM sleep for defining endophenotypes.

Trait interindividual differences in the sleep physiology of healthy young adults

Despite decades of sleep research by means of polysomnography (PSG), systematic interindividual differences in PSG-assessed sleep parameters have been scarcely investigated. The present study is the first to quantify interindividual variability in standard PSG-assessed variables of sleep structure in terms of stability and robustness as well as magnitude. Twenty-one carefully screened healthy young adults were studied continuously in a strictly controlled laboratory environment, where their PSGs were recorded for eight nights interspersed with three separate 36 h sleep deprivation periods. All PSG records were scored blind to subject and condition, using conventional criteria, and delta power in the non-REM sleep EEG was computed for four electrode derivations. Interindividual differences in sleep variables were examined for stability and robustness, respectively, by comparing results across equivalent nights (e.g. baseline nights) and across experimentally differentiated nights (baseline nights versus recovery nights following sleep deprivation). Among 18 sleep variables analyzed, all except slow-wave sleep (SWS) latency were found to exhibit significantly stable and robust--i.e. trait-like--interindividual differences. This was quantified by means of intraclass correlation coefficients (ICCs), which ranged from 36% to 89% across physiologic variables, and were highest for SWS (73%) and delta power in the non-REM sleep EEG (78-89%). The magnitude of the trait interindividual differences was considerable, consistently exceeding the magnitude of the group-average effect on sleep structure of 36 h total sleep deprivation. Notably, for non-REM delta power--a putative marker of sleep homeostasis--the interindividual differences were from 9.9 to 12.8 times greater than the group-average increase following sleep deprivation relative to baseline. Physiologic sleep variables did not vary among subjects in a completely independent manner--61.1% of their combined variance clustered in three trait dimensions, which appeared to represent sleep duration, sleep intensity, and sleep discontinuity. Any independent functional significance of these sleep physiologic phenotypes remains to be determined.

Within-subject reliability and inter-session stability of EEG power and coherent activity in women evaluated monthly over nine months

OBJECTIVE

Quantitative EEG parameters during resting conditions are used as baseline in research on cognition and in serial-EEG recordings. Despite its increasing use in cognitive research and the numerous evidences of the existence of sex differences in EEG, EEG stability has been mainly investigated in men. Particularly, studies on stability of coherent activity are scarce. The aim of this study was to investigate within-subject reliability and inter-session stability of resting EEG over a nine-month period in women.

METHODS

Within-subject reliability and inter-session stability were analyzed for absolute power and inter- and intrahemispheric coherent activity at central and posterior regions, once a month, in resting conditions, with eyes open and closed.

RESULTS

Within-subject reliability was very high (r>0.89) for all subjects and EEG parameters. Inter-session stability was higher with eyes closed and for interhemispheric coherent activity, and poorer with eyes open especially in the alpha band.

CONCLUSIONS

Present results indicate high reliability of the pattern of power and coherent activity of each individual woman during rest, and group stability of EEG activity with eyes closed at least over a nine-month period.

SIGNIFICANCE

These results provide information on EEG stability in women over a long period.

Prediction of general mental ability based on neural oscillation measures of sleep

The usual assessment of general mental ability (or intelligence) is based on performance attained in reasoning and problem-solving tasks. Differences in general mental ability have been associated with event-related neural activity patterns of the wakeful working brain or physical, chemical and electrical brain features measured during wakeful resting conditions. Recent evidences suggest that specific sleep electroencephalogram oscillations are related to wakeful cognitive performances. Our aim is to reveal the relationship between non-rapid eye movement sleep-specific oscillations (the slow oscillation, delta activity, slow and fast sleep spindle density, the grouping of slow and fast sleep spindles) and general mental ability assessed by the Raven Progressive Matrices Test (RPMT). The grouping of fast sleep spindles by the cortical slow oscillation in the left frontopolar derivation (Fp1) as well as the density of fast sleep spindles over the right frontal area (Fp2, F4), correlated positively with general mental ability. Data from those selected electrodes that showed the high correlations with general mental ability explained almost 70% of interindividual variance in RPMT scores. Results suggest that individual differences in general mental ability are reflected in fast sleep spindle-related oscillatory activity measured over the frontal cortex.

An electroencephalographic fingerprint of human sleep

Homeostatic and circadian processes are basic mechanisms of human sleep which challenge the common knowledge of large individual variations in sleep need or differences in circadian types. However, since sleep research has mostly focused on group measures, an approach which emphasizes the similarities between subjects, the biological foundations of the individual differences in normal sleep are still poorly understood. In the present work, we assessed individual differences in a range of EEG frequencies including sigma activity during non-REM sleep (8.0-15.5 Hz range) in a group of 10 subjects who had participated in a slow-wave sleep (SWS) deprivation study. We showed that, like a "fingerprint", a particular topographic distribution of the electroencephalogram (EEG) power along the antero-posterior cortical axis distinguishes each individual during non-REM sleep. This individual EEG-trait is substantially invariant across six consecutive nights characterized by large experimentally induced changes of sleep architecture. One possible hypothesis is that these EEG invariances can be related to individual differences in genetically determined functional brain anatomy, rather than to sleep-dependent mechanisms.

Progressive aging does not alter the interaction between autonomic cardiac activity and delta EEG power

OBJECTIVE

We tested the hypothesis that the reductions of the changes in the respective influence of the cardiac sympathetic and vagal activity control and delta EEG activity with aging alter the interactions between the heart rate variability (HRV) and the delta sleep EEG power band.

METHODS

A polysomnography was performed on 16 healthy young men and 19 healthy middle-aged men across the first 3 NREM-REM cycles. Spectral analysis was applied to electrocardiogram and electroencephalogram recordings. High Frequency (HF(nu)) of HRV as well as the maximum of cross-spectrum, coherency, gain and phase shifts between HF(nu) and delta sleep EEG power band were compared between both groups.

RESULTS

Young men experienced more deep sleep than middle-aged men (P<0.001). In middle-aged subjects, HF(nu) was lower than the HF(nu) of their younger counterparts (P<0.001), but they showed similar increases during NREM sleep and similar decreases during REM sleep as the young subjects. Cross-spectrum values, coherency, gain and phase shifts between HF(nu) and delta were identical between the two groups. Modifications in HF(nu) show parallel changes and precede changes in delta EEG band by a similar leads of 11+/-6min in young men and 9+/-7 min in middle-aged men (P=0.23).

CONCLUSIONS

Reduced changes in the respective influence of the cardiac sympathetic and vagal activity and delta EEG activity with progressive aging do not alter the relationship and phase difference between changes in the relative predominant cardiac vagal activity and delta power in middle-aged men.

SIGNIFICANCE

Interaction between the cardiac sympathetic and vagal activity with delta EEG activity is maintained in middle-aged men.

Interdependency between heart rate variability and sleep EEG: linear/non-linear?

OBJECTIVE

To investigate whether the interdependency between heart rate variability (HRV) and sleep electroencephalogram (EEG) power spectra is linear or non-linear.

METHODS

Heart rate and sleep EEG signals were recorded in 8 healthy young men. Spectral analysis was applied to electrocardiogram and EEG sleep recordings. Synchronization likelihood was computed over the first 3 non-rapid eye movement-rapid eye movement sleep cycles between normalized high frequency of RR intervals (RRI) and all electroencephalographic frequency bands. Comparison to surrogate data of different types was used to attest statistical significance of the coupling between RRI and EEG power bands and its linear or non-linear character.

RESULTS

Synchronization likelihood values were statistically greater than univariate surrogate synchronization for all sleep bands both at the individual and the group levels. With reference to multivariate surrogates, synchronization values were statistically greater at the group level and, in a majority of cases, for individual comparison except for sigma and beta bands.

CONCLUSIONS

While all electroencephalographic power bands are linked to normalized high frequency RRI band, this interdependency is non-linear for delta, theta and alpha bands.

SIGNIFICANCE

Non-linear description is required to capture the full interdependent dynamics of HRV and sleep EEG power bands.

Rapid eye movement density shows trends across REM periods but is uncorrelated with NREM delta in young and elderly human subjects

Saccade-like eye movements are the most prominent phasic component of rapid eye movement (REM) sleep. Eye movement density (EMD) appears to be negatively related to sleep depth. Thus, EMD is depressed by sleep deprivation. We sought to determine in 19 young normal (YN) and 19 elderly normal (EN) subjects: (a) whether EMD is correlated with delta EEG in baseline sleep; (b) whether EMD is increased by daytime naps; and (c) whether EMD patterns across sleep cycles differ in the two age groups. Subjects participated in four separate 2-day recording sessions, each consisting of a baseline night, a daytime nap, and post nap night. EMD was measured as 0.3-2 Hz integrated amplitude (IA)/20 s stage REM. EMD was not correlated with rate of non rapid eye movement (NREM) delta production (power/min) in the baseline sleep of either group. Changes in EMD and delta power/min on post nap nights also were uncorrelated. These data indicate that very strong changes in sleep depth (state) are required to overcome the individual stability (traits) of NREM delta and eye movement density. ANOVA for EMD across REM periods 1-4 showed a significant cycle effect and a significant age x cycle interaction. These effects were mainly due to YNs having depressed EMD in the first REM period, likely due to the low arousal level early in sleep in these subjects. Compared with waking saccades the saccade eye movements of REM sleep have received little investigation. Further study of these movements could shed new light on neurophysiology of REM sleep. Such studies might also be clinically useful because the density of these movements appears to be related to depression and (independently) to cognitive function in individuals with brain impairment.

Circadian rhythms in humans' delta sleep electroencephalogram

Eight healthy young male volunteers entered a 20-40 min ultrashort sleep-wake schedule for 78 h in the time-isolation facility. Rectal temperature was continuously recorded. Sleep electroencephalograms (EEGs) obtained during 20 min nap trials were stored in the computer and later analyzed by fast Fourier transform. A two-way repeated-measures ANOVA (with day and time-of-day as the repeated measures) revealed significant circadian rhythms in the powers of sigma and delta sleep EEGs, and in rectal temperature. These results obtained under conditions in which behavioral confounding factors of retiring and rising were experimentally minimized suggest that the circadian pacemaker contributes to determining the hours of day when one can sleep deeply.

Internight reliability and benchmark values for computer analyses of non-rapid eye movement (NREM) and REM EEG in normal young adult and elderly subjects

OBJECTIVE

To determine the reliability of computer measured non-rapid eye movement (NREM) and REM frequency bands in the 0.3-45 Hz range and to provide benchmark data for these measures in young normal (YN) and elderly normal (EN) subjects (Ss).

METHODS

Sleep EEG was recorded in 19 YN and 19 EN Ss on 4 non-consecutive baseline nights and simultaneously quantified as fast Fourier transform (FFT) power and 3 zero-cross period-amplitude (PA) measures: integrated amplitude, time in band and average wave amplitude.

RESULTS

The shapes of both the FFT and PA spectra differed among Ss but were highly consistent within individuals. Inter-night reliability of the separate frequency bands was correspondingly high. Despite substantial age effects, the reliability of computer-measured sleep EEG in the elderly equaled that of the YN Ss. Within both the YN and EN groups, the shapes of the NREM and REM spectral curves differed significantly. The NREM and REM also differed significantly in the two age groups.

CONCLUSIONS

Computer-measured sleep EEG is highly reliable across non-consecutive nights in both young and elderly normal Ss. The trait-like stability of these measures suggests they are genetically determined. This possibility is supported by twin study data that show strong heritability for FFT-measured waking EEG. The different shapes of NREM and REM spectra add further evidence that these are fundamentally different states of brain organization. The age differences in spectral shape, along with PA data for wave incidence, demonstrate that age effects on sleep EEG are not caused by changes in skull impedance or other non-cerebral factors.

Effects of hypnotics on the sleep EEG of healthy young adults: new data and psychopharmacologic implications

Benzodiazepine hypnotics increase NREM sleep and alter its EEG by reducing delta (0.3-3 Hz) and increasing sigma (12-15 Hz) and beta (15-23 Hz) activity. We tested whether the nonbenzodiazepine hypnotic, zolpidem (10 mg), produced the same pattern of sleep and EEG changes as two "classical" benzodiazepines, triazolam (0.25 mg) and temazepam (30 mg). Sleep EEG of 16 subjects was analyzed with period amplitude analysis for 3 nights during drug administration or placebo. The effects of zolpidem were in the same direction but generally of smaller magnitude than those of the classical benzodiazepines. These differences are more likely the result of non-equivalent dosages than different pharmacologic actions. Period amplitude analysis showed that the decreased delta activity resulted mainly from a decrease in wave amplitude. In contrast, the increased sigma and beta activity were produced by increased wave incidence. Delta suppression increased with repeated drug administration but sigma and beta stimulation did not. While these findings have little relevance for the clinical choice of hypnotics they may hold important implications for the brain mechanisms involved in hypnotic tolerance and withdrawal delirium.