EEG Power Spectra Response to a 4-h Phase Advance and Gaboxadol Treatment in 822 Men and Women

Ma, Junshui; Dijk, Derk‐Jan; Svetnik, Vladimir; Tymofyeyev, Yevgen; Ray, Shubhankar; Walsh, James K.; Deacon, Steve

doi:10.5664/jcsm.1316

Cited by 14 publications

(13 citation statements)

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“…PSG recordings included EEG (C3‐A2, C4‐A1, O2‐A1, O1‐A2), electrooculogram (EOG), electromyogram (EMG) and electrocardiogram (EKG). All PSG data were converted into European Data Format (EDF) and transferred to a central laboratory (Ma et al ., ,b) for scoring.…”

Section: Methodsmentioning

confidence: 99%

“…Polysomnographic recordings were processed using a high‐throughput automated system for EEG spectral analysis internally developed and validated at Merck (Ma et al ., ), and used in previously published spectral analyses (Ma et al ., ,b; Svetnik et al ., ). This system performs the following tasks: (1) transforming to a single standard, PSG recordings collected by different EEG acquisition centres and devices, utilizing sometimes different data formats, sampling rates, reference handling, etc.…”

Section: Methodsmentioning

confidence: 99%

“…This system performs the following tasks: (1) transforming to a single standard, PSG recordings collected by different EEG acquisition centres and devices, utilizing sometimes different data formats, sampling rates, reference handling, etc. ; (2) detection and removal of EMG‐ (Ma et al ., ), EOG‐ (Ma et al ., ,b) and EKG‐induced artefacts, as well as artefacts due to loose electrodes; (3) calculation of PSD using Welch's method (Welch, ), with a 4‐s Hamming window and a 1‐s overlap between two adjacent windows. As a result, for each 4‐s sleep segment of EEG free of artefacts, a PSD frequency profile was obtained in the frequency range from 1 Hz to 32 Hz with 1 Hz resolution.…”

Section: Methodsmentioning

confidence: 99%

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EEG spectral analysis of NREM sleep in a large sample of patients with insomnia and good sleepers: effects of age, sex and part of the night

Svetnik

Snyder

et al. 2016

Journal of Sleep Research

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SUMMARYPrevious studies of the differences between patients with insomnia and good sleepers with regard to quantitative electroencephalographic measures have mostly utilized small samples and consequently had limited ability to account for potentially important confounding factors of age, sex and part of the night. We conducted a power spectral analysis using a large database of sleep electroencephalographic recordings to evaluate differences between patients with insomnia (N = 803) and good sleepers (N = 811), while simultaneously accounting for these factors and their interaction. Comparisons of power as a function of age and part of the night were made between cohorts (patients with insomnia versus good sleepers) by sex. Absolute power in the delta, theta and sigma bands declined with age for both females and males. Females had significantly greater power than males at all ages, and for each band, cohort and part of the night. These sex differences were much greater than differences between patients with insomnia and good sleepers. Compared with good sleepers, patients with insomnia under age 40-45 years had reduced delta band power during Part 1 of the night. Females with insomnia over age 45 years had increased delta and theta band power in Parts 2 and 3 of the night, and males with insomnia under age 40 years had reduced theta power in Part 1. Females with insomnia had increased beta2 power in all parts of the night, and males with insomnia had reduced alpha power during all parts of the night. Relative power (the proportion that an individual frequency band contributes to the total power) decreased in the delta band and increased in all other bands with age for both cohorts, sexes and all parts of the night. This analysis provides a unique resource for quantitative information on the differences in power spectra between patients with insomnia and good sleepers accounting for age, sex and part of the night. IN TROD UCTI ONComparison of patients with primary insomnia (PI) and good sleepers (GS) based on electroencephalographic (EEG) data from polysomnographic (PSG) recordings has been an area of interest for sleep research. EEG activity during sleep is often described by traditional sleep stage scoring methods (Rechtschaffen and Kales, 1968). EEG activity can also be quantified by calculating the power spectral density (PSD)/profile at various frequencies or frequency bands (e.g. delta, theta, alpha, sigma, beta) directly from the EEG signal.In spite of the multitude of studies assessing power spectral profiles (Buysse et al.,

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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EEG spectral analysis of NREM sleep in a large sample of patients with insomnia and good sleepers: effects of age, sex and part of the night

Svetnik

Snyder

et al. 2016

Journal of Sleep Research

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“…(Note: Throughout this paper we refer to contrasts between biologically male and female research participants by the term sex difference, rather than the term gender difference, which connotes the assignment of, or preference for, different social roles.) Reported sex differences are earlier timing of clock gene rhythms in the brain (13), a shorter intrinsic circadian period of body temperature and melatonin rhythms (14, 15), earlier timing and larger amplitude of the melatonin rhythm (16), earlier timing and longer duration of sleep, and more slow-wave sleep (SWS) in women (15,(17)(18)(19). Whether these sex differences extend to the contribution of sleep and circadian rhythmicity in subjective and objective measures of waking function has not been documented.…”

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confidence: 99%

Sex differences in the circadian regulation of sleep and waking cognition in humans

Santhi

Lázár

McCabe

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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The sleep-wake cycle and circadian rhythmicity both contribute to brain function, but whether this contribution differs between men and women and how it varies across cognitive domains and subjective dimensions has not been established. We examined the circadian and sleep-wake-dependent regulation of cognition in 16 men and 18 women in a forced desynchrony protocol and quantified the separate contributions of circadian phase, prior sleep, and elapsed time awake on cognition and sleep. The largest circadian effects were observed for reported sleepiness, mood, and reported effort; the effects on working memory and temporal processing were smaller. Although these effects were seen in both men and women, there were quantitative differences. The amplitude of the circadian modulation was larger in women in 11 of 39 performance measures so that their performance was more impaired in the early morning hours. Principal components analysis of the performance measures yielded three factors, accuracy, effort, and speed, which reflect core performance characteristics in a range of cognitive tasks and therefore are likely to be important for everyday performance. The largest circadian modulation was observed for effort, whereas accuracy exhibited the largest sex difference in circadian modulation. The sex differences in the circadian modulation of cognition could not be explained by sex differences in the circadian amplitude of plasma melatonin and electroencephalographic slow-wave activity. These data establish the impact of circadian rhythmicity and sex on waking cognition and have implications for understanding the regulation of brain function, cognition, and affect in shift-work, jetlag, and aging.cognition | biological rhythms | gender | slow wave sleep | melatonin C ircadian rhythms are generated by a set of core "clock" genes and are present in nearly every cell of the body and brain (1). These local clocks and rhythms are synchronized by neural and endocrine pathways originating from the master circadian pacemaker located in the suprachiasmatic nucleus (SCN) (2, 3). In addition, the timing of behaviors such as food intake and sleep and associated changes in local and systemic cues contribute to the temporal organization in peripheral tissues outside the SCN (4, 5). In view of the pervasiveness of circadian rhythms, it is not surprising that they affect many aspects of physiology, behavior, and cognition in health and in disease. Indeed, circadian abnormalities have been implicated in disorders of sleep, mood, and cognition (6), in deleterious responses to shift work (7), depression (8), and Alzheimer's disease (9). The prevalence of most of these disorders is higher in women than in men (10), and their impact on psychological functions and quality of life of patients differs between the sexes (11).Women are underrepresented in both circadian and sleep research (12), although sex differences in human circadian and sleep characteristics are emerging from the few studies that contrast men and women. (Note: Throughout thi...

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“…Therefore, additional design variables that could be optimized to provide more robust designs, including covariates (smoking or alcohol habits, weight, and gender) that have demonstrated pronounced effect in sleep patterns 19,34,35 or additional cross-over arms, can be examined without overtly increasing the runtimes. For example, the high uncertainty for the theoretical dose effect parameters D 50 (TP1) in the 'From awake' sub-model and D 50 (TP3) in the 'From asleep' sub-model could be merely a consequence of the limit of the number of crossovers explored, and the impact of additional cross-over arms could be explored with modest increase in runtime.…”

Section: Discussionmentioning

confidence: 99%

Optimal clinical trial design based on a dichotomous Markov-chain mixed-effect sleep model

Ernest

Nyberg

Karlsson

et al. 2014

J Pharmacokinet Pharmacodyn

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Optimal clinical trial design based on a dichotomous Markov-chain mixed-effect sleep model. Pharmacokinetics and Pharmacodynamics, 41(6) Journal of Abstract.Objectives: D-optimal designs for discrete-type responses have been derived using generalized linear mixed models, simulation based methods and analytical approximations for computing the Fisher information matrix (FIM) of non-linear mixed effect models with homogeneous probabilities over time. In this work, D-optimal designs using an analytical approximation of the FIM for a dichotomous, non-homogeneous, Markov-chain phase advanced sleep non-linear mixed effect model was investigated. Methods:The non-linear mixed effect model consisted of transition probabilities of dichotomous sleep data estimated as logistic functions using piecewise linear functions. Theoretical linear and nonlinear dose effects were added to the transition probabilities to modify the probability of being in either sleep stage. D-optimal designs were computed by determining an analytical approximation the FIM for each Markov component (one where the previous state was awake and another where the previous state was asleep). Each Markov component FIM was weighted either equally or by the average probability of response being awake or asleep over the night and summed to derive the total FIM (FIM total ). The reference designs were placebo, 0.1, 1-, 6-, 10-and 20-mg dosing for a 2-to 6-way crossover study in 6 dosing groups. Optimized design variables were dose and number of subjects in each dose group. The designs were validated using stochastic simulation/re-estimation (SSE).Results: Contrary to expectations, the predicted parameter uncertainty obtained via FIM total was larger than the uncertainty in parameter estimates computed by SSE. Nevertheless, the D-optimal designs decreased the uncertainty of parameter estimates relative to the reference designs. Additionally, the improvement for the D-optimal designs were more pronounced using SSE than predicted via FIM total . Conclusion: Through the use of an approximate analytic solution and weighting schemes, the FIM total for a non-homogeneous, dichotomous Markov-chain phase advanced sleep model was computed and provided more efficient trial designs and increased NLMEM parameter precision.

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EEG Power Spectra Response to a 4-h Phase Advance and Gaboxadol Treatment in 822 Men and Women

Cited by 14 publications

References 49 publications

EEG spectral analysis of NREM sleep in a large sample of patients with insomnia and good sleepers: effects of age, sex and part of the night

EEG spectral analysis of NREM sleep in a large sample of patients with insomnia and good sleepers: effects of age, sex and part of the night

Sex differences in the circadian regulation of sleep and waking cognition in humans

Optimal clinical trial design based on a dichotomous Markov-chain mixed-effect sleep model

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