EEG spectral analysis in insomnia disorder: A systematic review and meta-analysis

Zhao, Wenrui; Someren, Eus J.W. Van; Li, Chenyu; Chen, Xinyuan; Gui, Wenjun; Tian, Yu; Liu, Yunrui; Lei, Xu

doi:10.1016/j.smrv.2021.101457

Cited by 143 publications

(101 citation statements)

References 68 publications

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“…Differences regarding spindle characteristics between patients with ID and good sleepers were noted, albeit inconsistently. Recently published meta-analysis indicated that patients with ID exhibit signi cant increases in relative sigma power (a proxy for spindles) during NREM sleep and absolute sigma power during rapid eye movement (REM) sleep (Zhao et al, 2021). Bastien and colleagues visually examined the total spindle number and density during N2 sleep in patients with ID (Bastien et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Spindle-related brain activation in patients with insomnia disorder: An EEG-fMRI study

Shao

Zou

Tabarak

et al. 2021

Brain Imaging and Behavior

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Sleep spindles have been implicated in sleep protection, depression and anxiety. However, spindle-related brain imaging mechanism underpinning the de cient sleep protection and emotional regulation in insomnia disorder (ID) remains elusive. The aim of the current study is to investigate the relationship between spindle-related brain activations and sleep quality, symptoms of depression and anxiety in patients with ID. Participants (n = 46, 29 females, 18-60 years) were recruited through advertisements including 16 with ID, according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and 30 matched controls. Group differences in spindle-related brain activations were analyzed using multimodality data acquired with simultaneous electroencephalography and functional magnetic resonance imaging during sleep. Compared with controls, patients with ID showed signi cantly decreased bilateral spindle-related brain activations in the cingulate gyrus (familywise error corrected p 0.05, cluster size 3834 mm 3 ). Activations in the cingulate gyrus were negatively correlated with Self-Rating Depression Scale scores (r = -0.454, p = 0.002), Self-Rating Anxiety Scale scores (r = -0.362, p = 0.014) and subjective sleep onset latency (r = -0.374, p = 0.010), while positively correlated with subjective total sleep time (r = 0.343, p = 0.020), in the pooled sample. Besides, activations in the cingulate gyrus were negatively correlated with scores on the Self-Rating Depression Scale (r = -0.650, p = 0.006), in the ID group. These ndings underscore the key role of spindle-related brain activations in the cingulate gyrus in subjective sleep quality and emotional regulation in ID.

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Section: Introductionmentioning

confidence: 99%

Spindle-related brain activation in patients with insomnia disorder: An EEG-fMRI study

Shao

Zou

Tabarak

et al. 2021

Brain Imaging and Behavior

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“…Power spectral analysis of EEG (sometimes referred to as quantitative EEG [qEEG]) provides a more sensitive and objective marker of neurophysiological features of sleep, some of which may be unique to specific patient phenotypes. For example, several studies have used qEEG to calculate the mean absolute power of given frequency bands (delta, alpha, theta, sigma, and beta), usually averaged over NREM and REM sleep, some of which have been shown to be predictive of insomnia (Krystal et al, 2002;Krystal and Edinger, 2010;Lunsford-Avery et al, 2021;Zhao et al, 2021) and OSA (D'Rozario et al, 2017;Appleton et al, 2019). Emerging evidence also suggests that qEEG markers are associated with vigilance and cognitive performance (Vakulin et al, 2016;Djonlagic et al, 2021;Mullins et al, 2021).…”

Section: Fourier-based Analysis Of Sleep Signals: Quantitative Electroencephalographymentioning

confidence: 99%

New and Emerging Approaches to Better Define Sleep Disruption and Its Consequences

et al. 2021

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Current approaches to quantify and diagnose sleep disorders and circadian rhythm disruption are imprecise, laborious, and often do not relate well to key clinical and health outcomes. Newer emerging approaches that aim to overcome the practical and technical constraints of current sleep metrics have considerable potential to better explain sleep disorder pathophysiology and thus to more precisely align diagnostic, treatment and management approaches to underlying pathology. These include more fine-grained and continuous EEG signal feature detection and novel oxygenation metrics to better encapsulate hypoxia duration, frequency, and magnitude readily possible via more advanced data acquisition and scoring algorithm approaches. Recent technological advances may also soon facilitate simple assessment of circadian rhythm physiology at home to enable sleep disorder diagnostics even for “non-circadian rhythm” sleep disorders, such as chronic insomnia and sleep apnea, which in many cases also include a circadian disruption component. Bringing these novel approaches into the clinic and the home settings should be a priority for the field. Modern sleep tracking technology can also further facilitate the transition of sleep diagnostics from the laboratory to the home, where environmental factors such as noise and light could usefully inform clinical decision-making. The “endpoint” of these new and emerging assessments will be better targeted therapies that directly address underlying sleep disorder pathophysiology via an individualized, precision medicine approach. This review outlines the current state-of-the-art in sleep and circadian monitoring and diagnostics and covers several new and emerging approaches to better define sleep disruption and its consequences.

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“…High frequency EEG rhythms (e.g., beta rhythms) during sleep are theorized to be a component of a hyperarousal syndrome present in Insomnia Disorder [ (54)(55)(56)(57)(58)(59)(60); though see (61) who failed to detect this in a large meta-analytic study], a condition commonly comorbid with anxiety and traumatic-stress disorders, such as PTSD. However, associations between elevated beta power and PTSD symptomatology remains mixed.…”

Section: Beta Spectral Power Decreased In Ptsdmentioning

confidence: 99%

Sleep Power Spectral Density and Spindles in PTSD and Their Relationship to Symptom Severity

et al. 2021

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Sleep disturbances are common in post-traumatic stress disorder (PTSD), although which sleep microarchitectural characteristics reliably classify those with and without PTSD remains equivocal. Here, we investigated sleep microarchitectural differences (i.e., spectral power, spindle activity) in trauma-exposed individuals that met (n = 45) or did not meet (n = 52) criteria for PTSD and how these differences relate to post-traumatic and related psychopathological symptoms. Using ecologically-relevant home sleep polysomnography recordings, we show that individuals with PTSD exhibit decreased beta spectral power during NREM sleep and increased fast sleep spindle peak frequencies. Contrary to prior reports, spectral power in the beta frequency range (20.31–29.88 Hz) was associated with reduced PTSD symptoms, reduced depression, anxiety and stress and greater subjective ability to regulate emotions. Increased fast frequency spindle activity was not associated with individual differences in psychopathology. Our findings may suggest an adaptive role for beta power during sleep in individuals exposed to a trauma, potentially conferring resilience. Further, we add to a growing body of evidence that spindle activity may be an important biomarker for studying PTSD pathophysiology.

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EEG spectral analysis in insomnia disorder: A systematic review and meta-analysis

Cited by 143 publications

References 68 publications

Spindle-related brain activation in patients with insomnia disorder: An EEG-fMRI study

Spindle-related brain activation in patients with insomnia disorder: An EEG-fMRI study

New and Emerging Approaches to Better Define Sleep Disruption and Its Consequences

Sleep Power Spectral Density and Spindles in PTSD and Their Relationship to Symptom Severity

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