EEG Spectral Analysis in Primary Insomnia: NREM Period Effects and Sex Differences

Buysse, Daniel J.; Germain, Anne; Hall, Martica; Moul, Douglas E.; Nofzinger, Eric A.; Begley, Amy; Ehlers, Cindy L.; Thompson, Wesley K.; Kupfer, David J.

doi:10.1093/sleep/31.12.1673

Cited by 148 publications

(130 citation statements)

References 68 publications

Supporting

Mentioning

118

Contrasting

Order By: Relevance

“…Analysis of covariance (ANCOVA) was used to test for group differences in clinical and sleep characteristics of the groups covarying for age and sex. EEG spectral power was first compared power within the traditional frequency bands: delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), sigma (12)(13)(14)(15)(16), low beta (16)(17)(18)(19)(20), and high beta (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32). Because group differences may not coincide with these traditional frequency bins, we also analyzed the data in individual 1 Hz frequencies, again using ANCOVA.…”

Section: Discussionmentioning

confidence: 99%

“…8,15,16 In a study done by our own group looking at NREM periods and sex differences in EEG spectral analysis in primary insomnia, we found increased beta power in the fi rst NREM period among women with primary insomnia. 17 Daytime symptoms are another component of primary insomnia, and one of the main reasons why patients seek care. 18 Although symptoms of fatigue and tiredness have long been associated with insomnia, studies of physiological sleepiness typically show increased alertness, at least in younger and middle-aged adults with insomnia.…”

Section: Eeg Power During Waking and Nrem Sleep In Primary Insomniamentioning

confidence: 99%

See 1 more Smart Citation

EEG Power During Waking and NREM Sleep in Primary Insomnia

Pietrone

Cashmere

et al. 2013

Journal of Clinical Sleep Medicine

Self Cite

View full text Add to dashboard Cite

Objective: Pathophysiological models of insomnia invoke the concept of 24-hour hyperarousal, which could lead to symptoms and physiological fi ndings during waking and sleep. We hypothesized that this arousal could be seen in the waking electroencephalogram (EEG) of individuals with primary insomnia (PI), and that waking EEG power would correlate with non-REM (NREM) EEG. Methods: Subjects included 50 PI and 32 good sleeper controls (GSC). Five minutes of eyes closed waking EEG were collected at subjects' usual bedtimes, followed by polysomnography (PSG) at habitual sleep times. An automated algorithm and visual editing were used to remove artifacts from waking and sleep EEGs, followed by power spectral analysis to estimate power from 0.5-32 Hz. Results: We did not fi nd signifi cant differences in waking or NREM EEG spectral power of PI and GSC. Signifi cant correlations between waking and NREM sleep power were observed across all frequency bands in the PI group and in most frequency bands in the GSC group. Conclusions: The absence of signifi cant differences between groups in waking or NREM EEG power suggests that our sample was not characterized by a high degree of cortical arousal. The consistent correlations between waking and NREM EEG power suggest that, in samples with elevated NREM EEG beta activity, waking EEG power may show a similar pattern. S C I E N T I F I C I N V E S T I G A T I O N SU p to one-third of adults in the US complain of problems with sleep, and approximately 10% to 15% meet criteria for insomnia disorder.1,2 Primary insomnia, a disorder characterized by diffi culty falling asleep, staying asleep, or early awakening without signifi cant comorbid psychiatric or physical illness, has long been used as a model to study the pathophysiology of insomnia.3 Multiple studies have demonstrated that insomnia is associated with physiological markers of elevated arousal during both wakefulness and sleep, suggesting that 24-hour hyperarousal may be a defi ning feature of this condition.4,5 The 24-hour hyperarousal model has been supported by data including increased whole-body metabolic rate during waking and sleep, increased ACTH and cortisol secretion before and during early sleep, and elevated heart rate and beta frequency spectral power during non-REM (NREM) sleep. 5-9Impaired cognitive performance may also be related to hyperarousal and sleep disruption in insomnia.10 Physiological measures of hyperarousal or stress, such as HPA axis activation with increased cortisol secretion, may constitute one mechanism by which insomnia is a risk factor for development of depression associated with increased stress. 11-13Multiple studies have looked at quantitative electroencephalogram (EEG) as a marker of arousal during sleep in individuals with insomnia. One of the earliest studies identifi ed a slower increase and reduced levels of power in all frequency bands below beta frequency during NREM, coupled with increased 14 This fi nding of elevated beta frequency spectral power in sleep has been documented i...

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Eeg Power During Waking and Nrem Sleep In Primary Insomniamentioning

confidence: 99%

EEG Power During Waking and NREM Sleep in Primary Insomnia

Pietrone

Cashmere

et al. 2013

Journal of Clinical Sleep Medicine

Self Cite

View full text Add to dashboard Cite

show abstract

“…Electroencephalographic hyper excitability has been described in this kind of patients [13,14]. Another study has described an increment of corticosteroids and adrenaline [15].…”

Section: Introductionmentioning

confidence: 88%

Electroencephalographic Abnormalities in Patients with Idiopathic Insomnia

Yoaly¹,

Lechuga

Escandón

et al. 2011

View full text Add to dashboard Cite

show abstract

“…b) Investigation of paradoxical insomnia: Previous studies identified microstructure abnormalities in patients with paradoxical insomnia (Krystal et al 2002;Perlis et al 2001;Parrino et al 2009). All reported abnormalities (increased beta activity (Perlis et al 2001), decreased delta and increased alpha/beta activity (Buysse et al 2008), and cyclic alternating pattern (Parrino et al 2009)) result in a higher ORP during non-REM sleep (Younes et al 2015a). Thus, having ORP NR available in clinical studies may help identify patients with abnormal sleep quality from those in whom the problem is in perception of sleep.…”

Section: Arousability Index (%)mentioning

confidence: 98%

“…Furthermore, it is now well established that a hyperarousal state exists in some patients with primary insomnia (Bonnet and Arand 2010;Riemann et al 2010). The EEG representation of the hyperarousal state is an increase in power in the beta frequency range during sleep (Freedman 1986;Krystal et al 2002;Perlis et al 2001;Buysse et al 2008). ORP is extremely sensitive to relative EEG beta power (Younes et al 2015a).…”

Section: Arousability Index (%)mentioning

confidence: 99%

The case for using digital EEG analysis in clinical sleep medicine

Younes

2017

Sleep Science Practice

View full text Add to dashboard Cite

Evaluation of sleep in clinical polysomnograms continues to rely almost exclusively on visual scoring that implements rules proposed by Rechtschaffen and Kales nearly 50 years ago. Apart from its cost and timeconsuming nature, visual scoring has limitations including: A) Sleep depth, which is a continuous variable, is treated as if it changes in a stepwise fashion from light (stage 1), to intermediate (stage 2) to deep (stage 3). B) Even with this limited scale, there is considerable inter-scorer variability, particularly in scoring stages 1 and 3 of non-REM sleep, thereby adding uncertainty to %time spent in these stages as a reliable metric for evaluating sleep depth. C) Limitation in scoring some of EEG features, including 1) arousal intensity, 2) extent of Alpha intrusion and 3) frequency, and characteristics of sleep spindles and K complexes. Digital analysis can solve these problems but producing a reliable system has been a challenge. In this review I begin with recent advances in digital scoring of sleep according to the Rechtschaffen and Kales rules and conclude that this technology has progressed enough to make it possible to obtain reliable, reproducible scoring, comparable in accuracy to scoring by highly experienced technologists, with minimal editing. This is followed by description of several new metrics that can be obtained if digital scoring systems were to be used routinely in clinical studies. The scientific evidence supporting the potential of these metrics to positively impact sleep medicine practice and the wide range of such metrics in patients studied in the sleep laboratory are highlighted.

show abstract

EEG Spectral Analysis in Primary Insomnia: NREM Period Effects and Sex Differences

Abstract: Women with PI, but not men, showed increased high-frequency and low-frequency EEG activity during NREM sleep compared to GSC, particularly in early NREM periods. Sex and NREM period may moderate quantitative EEG differences between PI and GSC.

Cited by 148 publications

References 68 publications

EEG Power During Waking and NREM Sleep in Primary Insomnia

EEG Power During Waking and NREM Sleep in Primary Insomnia

Electroencephalographic Abnormalities in Patients with Idiopathic Insomnia

The case for using digital EEG analysis in clinical sleep medicine

Contact Info

Product

Resources

About