Difference in spectral power density of sleep electroencephalography between individuals without insomnia and frequent hypnotic users with insomnia complaints

Kang, Jae Myeong; Cho, Seo‐Eun; Moon, Jong Youn; Kim, Soo In; Kim, Jong Won; Kang, Seung-Gul

doi:10.1038/s41598-022-05378-6

Cited by 9 publications

(8 citation statements)

References 33 publications

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“…The spectral analysis was performed on overnight EEG, significant higher beta power in CIs during W, N1, N2, NREM, and whole night, which were consistent with data from previous studies ( Merica, 1998 ; Perlis et al, 2001a ; Corsi-Cabrera et al, 2012 ; Spiegelhalder et al, 2012 ; Kang et al, 2018 , 2022 ; Smagula et al, 2021 ; Shi et al, 2022 ; Xu et al, 2022 ; Zhang et al, 2022 ). In a recent meta-analysis, elevated relative beta power in W, NREM and whole night was also be demonstrated by Zhao et al; however, they did not explore EEG spectral power in specific N1, N2 and N3 stages, which differ in function and depth of sleep ( Zhao et al, 2021 ).…”

Section: Discussionsupporting

confidence: 86%

Elevated beta activity in the nighttime sleep and multiple sleep latency electroencephalograms of chronic insomnia patients

et al. 2022

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AimTo examine the 24-h hyperarousal hypothesis of insomnia using electroencephalographic (EEG) spectral analysis of overnight polysomnography (PSG) and daytime multiple sleep latency tests (MSLTs).MethodsStandard PSG and MSLT were recorded in 31 chronic insomniacs (CIs) (21 females, mean age 36.19) and in 21 normal controls (NCs) (18 females, mean age 34.76). EEG spectral analyses were conducted and relative power was obtained for each sleep stage during PSG and each session during MSLTs. Subsequently, CIs were subdivided based on sleep efficiency (SE < or ≥ 85%) or mean sleep latency (MSL) of MSLT (< or ≥ 15 min), and beta power was compared among NCs and CIs subgroups. General liner regression analyses of beta power and PSG parameters were conducted.ResultsCIs had significantly greater beta power in nighttime W, N1, N2, NREM, and in total overnight and in MSLT sessions compared with NCs. CIs with lower PSG-SE or longer MSLT-MSL showed higher beta power at nighttime. Compared with NCs, increased beta power was limited to CIs with lower PSG-SE or longer MSLT-MSL during MSLT sessions. In all subjects, total daytime beta was positively correlated to total overnight beta and MSL, total overnight beta was negatively related to SE. In CIs, total daytime beta and total overnight beta were positively correlated.ConclusionOur results support the hypothesis of 24-h cortical hyperarousal in insomnia. We conclude that 24-h cortical hyperarousal is clearly present in insomnia and is greater in insomnia with objective findings.

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Section: Discussionsupporting

confidence: 86%

Elevated beta activity in the nighttime sleep and multiple sleep latency electroencephalograms of chronic insomnia patients

et al. 2022

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“…In frequency domain analyses, the PSD was estimated within each 30-s epoch by Welch's method with 50% overlap and employing a Hamming window with size 1,000 points. The relative PSDs were calculated across various frequency bands, and for this study defined as slow oscillation (0.3-1 Hz), delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz), and gamma (30)(31)(32)(33)(34)(35). Relative PSDs were determined by dividing the PSD values for each specific frequency band (alpha, beta, and delta) by the total PSD calculated over the frequency range of 0.3 to 35 Hz.…”

Section: Eeg Processingmentioning

confidence: 99%

“…Within the sleep field, EEG-based PSDs are typically analysed at four frequency bands -delta (δ) (0.5-4 Hz), theta (θ) (4-8 Hz), alpha (α) (8-12 Hz), and beta (β) (12-30 Hz), though the exact thresholds used between studies may differ. Among patients with insomnia, beta frequency power has been found to be higher in non-rapid eye movement (NREM) stages, but lower in rapid eye movement (REM) stages compared to patients without insomnia (35). Among patients with narcolepsy, alpha power has been found to be higher in REM stages and delta power lower in NREM stage 1 (N1) compared to controls (36).…”

Section: Introductionmentioning

confidence: 96%

Excessive daytime sleepiness is associated with relative delta frequency power among patients with mild OSA

Howarth,

Tashakori,

Karhu

et al. 2024

Front. Neurol.

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BackgroundExcessive daytime sleepiness (EDS) is a cause of low quality of life among obstructive sleep apnoea (OSA) patients. Current methods of assessing and predicting EDS are limited due to time constraints or differences in subjective experience and scoring. Electroencephalogram (EEG) power spectral densities (PSDs) have shown differences between OSA and non-OSA patients, and fatigued and non-fatigued patients. Therefore, polysomnographic EEG PSDs may be useful to assess the extent of EDS among patients with OSA.MethodsPatients presenting to Israel Loewenstein hospital reporting daytime sleepiness who recorded mild OSA on polysomnography and undertook a multiple sleep latency test. Alpha, beta, and delta relative powers were assessed between patients categorized as non-sleepy (mean sleep latency (MSL) ≥10 min) and sleepy (MSL <10 min).Results139 patients (74% male) were included for analysis. 73 (53%) were categorized as sleepy (median MSL 6.5 min). There were no significant differences in demographics or polysomnographic parameters between sleepy and non-sleepy groups. In multivariate analysis, increasing relative delta frequency power was associated with increased odds of sleepiness (OR 1.025 (95% CI 1.024–1.026)), while relative alpha and beta powers were associated with decreased odds. The effect size of delta PSD on sleepiness was significantly greater than that of either alpha or beta frequencies.ConclusionDelta PSD during polysomnography is significantly associated with a greater degree of objective daytime sleepiness among patients with mild OSA. Further research is needed to corroborate our findings and identify the direction of potential causal correlation between delta PSD and EDS.

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“…Periodic activity is traditionally examined in the frequency bands delta (0.5-4 Hz), theta (4-7.5 Hz), alpha (7.5-12 Hz), beta (16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), and gamma (>30 Hz). During wakefulness, the brain exhibits high-frequency low-amplitude activity, and as the subject transitions to NREM sleep, the activity transitions into a low-frequency high-amplitude pattern.…”

Section: Introduction Sleep Neurophysiology and Eegmentioning

confidence: 99%

“…[24,25]. The transition from lighter to deeper NREM sleep is associated with increased slope of the EEG power spectrum, along with increases in the amplitude of the delta band and a decrease in the amplitude the alpha band [26]. Wakefulness also is signified by a presence of alpha and gamma peaks, and REM (rapid eye movement) sleep is correlated with increases in gamma and theta but not alpha peaks [27].…”

Section: Introduction Sleep Neurophysiology and Eegmentioning

confidence: 99%

Corticothalamic modelling of sleep neurophysiology with applications to mobile EEG

Morshedzadeh,

Kadak,

Bastiaens

et al. 2024

Preprint

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Recent developments in mathematical modelling of EEG data enable estimation and tracking of otherwise-inaccessible neurophysiological parameters over the course of a night’s sleep. Likewise, advancements in wearable electronics have enabled easier & more affordable at-home collection of sleep EEG data. The convergence of these two advances, namely neurophysiological modelling for mobile sleep EEG, has the potential to significantly improve sleep assessments in research and the clinic. However, this subject area has received limited attention in existing literature. To address this, we used an established mathematical model of the corticothalamic system to analyze EEG power spectra from 5 datasets, spanning from in-lab, research-grade systems to at-home mobile EEG devices. In the present work, we compare the convergent and divergent features of the data and the estimated physiological model parameters. While data quality and characteristics differ considerably, several key patterns consistent with previous theoretical and empirical work are observed. During the transition from lighter to deeper NREM stages, i) the exponent of the aperiodic (1/f) spectral component is increased, ii) bottom-up thalamocortical drive is reduced, iii) corticocortical connection strengths are increased. This effect, which we observe in healthy individuals across all 5 datasets, is interestingly absent in individuals taking SSRI antidepressants, suggesting possible effects of ascending neuromodulatory systems on corticothalamic oscillations. Our results provide a proof-of-principle for the utility and feasibility of this physiological modelling-based approach to analyzing data from mobile EEG devices, providing a mechanistic measure of brain physiology during sleep at home or in the lab.

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Difference in spectral power density of sleep electroencephalography between individuals without insomnia and frequent hypnotic users with insomnia complaints

Cited by 9 publications

References 33 publications

Elevated beta activity in the nighttime sleep and multiple sleep latency electroencephalograms of chronic insomnia patients

Elevated beta activity in the nighttime sleep and multiple sleep latency electroencephalograms of chronic insomnia patients

Excessive daytime sleepiness is associated with relative delta frequency power among patients with mild OSA

Corticothalamic modelling of sleep neurophysiology with applications to mobile EEG

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