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

Integration of tai chi and repetitive transcranial magnetic stimulation for sleep disturbances in older adults: A pilot randomized controlled trial

BACKGROUND

The arousal state has been demonstrated to be involved in the fundamental pathophysiological mechanism of sleep disturbances. Tai chi (TC) and repetitive transcranial magnetic stimulation (rTMS) have been documented to alleviate sleep disturbances by interfering with different arousal components. It is reasonable to assume that combining TC and rTMS could induce synergistic and longer-lasting benefits for sleep disturbances.

METHODS

Thirty-eight older community-dwelling people were randomly assigned to one of three groups: TC plus rTMS (n = 12), TC alone (n = 13), and treat-as-usual (TAU) (n = 13). The interventions were conducted three times per week for 4 weeks for the two intervention groups. The primary outcome was the insomnia severity, while the secondary outcomes were the actigraphy-assessed sleep patterns, use of hypnotic medications, mood states, and quality of life. The mediator outcomes included self-reported somatic arousal and cognitive arousal as well as electroencephalogram (EEG)-assessed cortical arousal. The assessments were conducted at baseline (T0), post-intervention (T1), and 3-month follow-up (T2).

RESULTS

Significant improvements in the insomnia severity were observed in the TC plus rTMS group compared with the TAU group at T1 (Cohen's d = 1.62, p = 0.003) and T2 (Cohen's d = 1.97, p < 0.001). In contrast, significant improvements in the TC alone group were found only at T2 (Cohen's d = 1.03, p = 0.010) when compared with the TAU group. Significant interaction effects were noted on the actigraphy-assessed sleep efficiency (p = 0.015) and total sleep time (p = 0.004), depression (p = 0.003) and stress scores (p = 0.002), and mental function in relation to quality of life (p = 0.042). However, none of the mediators elucidated how combining TC and rTMS could improve the insomnia severity.

CONCLUSION

The research findings are expected to guide further clinical practice in the management of sleep disturbances among older adults using various interventions. Future studies are needed to unravel the underlying mechanism and optimize the protocol to maximize the therapeutic benefits.

The utility of wearable headband electroencephalography and pulse photoplethysmography to assess cortical and physiological arousal in individuals with stress-related mental disorders

Several stress-related mental disorders are characterised by disturbed sleep, but objective sleep biomarkers are not routinely examined in psychiatric patients. We examined the use of wearable-based sleep biomarkers in a psychiatric sample with headband electroencephalography (EEG) including pulse photoplethysmography (PPG), with an additional focus on microstructural elements as especially the shift from low to high frequencies appears relevant for several stress-related mental disorders. We analysed 371 nights of sufficient quality from 83 healthy participants and those with a confirmed stress-related mental disorder (anxiety-affective spectrum). The median value of macrostructural, microstructural (spectral slope fitting), and heart rate variables was calculated across nights and analysed at the individual level (N = 83). The headbands were accepted well by patients and the data quality was sufficient for most nights. The macrostructural analyses revealed trends for significance regarding sleep continuity but not sleep depth variables. The spectral analyses yielded no between-group differences except for a group × age interaction, with the normal age-related decline in the low versus high frequency power ratio flattening in the patient group. The PPG analyses showed that the mean heart rate was higher in the patient group in pre-sleep epochs, a difference that reduced during sleep and dissipated at wakefulness. Wearable devices that record EEG and/or PPG could be used over multiple nights to assess sleep fragmentation, spectral balance, and sympathetic drive throughout the sleep-wake cycle in patients with stress-related mental disorders and healthy controls, although macrostructural and spectral markers did not differ between the two groups.

Waking qEEG in older adults with insomnia and its associations with sleep reactivity and dysfunctional beliefs about sleep

Sleep quality often deteriorates with age, and insomnia among the elderly increases the risks of both physical and psychiatric disorders. To elucidate the mechanisms and identify useful diagnostic biomarkers for insomnia in the elderly, the current study investigated the associations of waking brain activity patterns with susceptibility to stress-induced insomnia (sleep reactivity) and dysfunctional beliefs about sleep, major factors precipitating and maintaining insomnia, respectively. Forty-five participants aged 60 years or older with insomnia completed self-reported measures assessing depression, anxiety, sleep quality, dysfunctional beliefs about sleep, and sleep reactivity. Participants were then examined by quantitative electroencephalography (qEEG) during wakefulness, and spectral analysis was conducted to examine associations of regional frequency band power with these insomnia-precipitating and -maintaining factors. Dysfunctional beliefs about sleep were significantly correlated with higher beta/high-beta frequency band powers, while sleep reactivity was correlated with higher theta and delta frequency band powers. These findings suggest that sleep reactivity of older adults is associated with widespread cortical deactivation leading to poor stress coping, while their dysfunctional beliefs about sleep are associated with hyperactivation which is related to cognitive processes. These associations suggest that cognitive inflexibility and maladaptive stress-coping contribute to insomnia among the elderly.

Interindividual differences in mindfulness are linked to sleep-electroencephalographic characteristics

STUDY OBJECTIVES

Mindfulness describes the ability to focus on the presence, including one's thoughts and feelings. Trait mindfulness-a person's inherent tendency to be mindful-has been connected to increased subjective sleep quality, but evidence from objective EEG-based sleep measures is lacking. Here, we investigate whether objective EEG-based sleep parameters explain interindividual differences in trait mindfulness.

METHODS

Whole-night polysomnographic data were gathered from 52 healthy adults (27 females; agemean = 21.5 [SE = 0.28]) in their homes using a portable high-density EEG device. Trait mindfulness was assessed using the Five Facet Mindfulness Questionnaire short form (FFMQ-SF).

RESULTS

Trait mindfulness was positively correlated at trend level with the percentage of rapid eye movement (REM), but not N1, N2, or slow wave sleep. Additionally, those exhibiting less REM beta/gamma power and NREM beta power displayed higher trait mindfulness and vice versa. Lastly, we replicated findings connecting higher trait mindfulness to better subjective sleep quality.

CONCLUSIONS

REM sleep is pivotal for emotional processing. Decreased REM high-frequency activity was suggested to reflect adrenergic reduction that defuses affective experiences. Increased NREM high-frequency activity is a marker for cognitive hyperarousal in insomnia. We speculate that differences in trait mindfulness might be explained by differences in REM- and NREM-sleep functions that promote ideal emotional regulation and prevent hyperarousal.

A systematic review of quantitative EEG findings in Fibromyalgia, Chronic Fatigue Syndrome and Long COVID

Fibromyalgia Syndrome (FMS), Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and Long COVID (LC) are similar multisymptom clinical syndromes but with difference in dominant symptoms in each individual. There is existing and emerging literature on possible functional alterations of the central nervous system in these conditions. This review aims to synthesise and appraise the literature on resting-state quantitative EEG (qEEG) in FMS, ME/CFS and LC, drawing on previous research on FMS and ME/CFS to help understand neuropathophysiology of the new condition LC. A systematic search of MEDLINE, Embase, CINHAL, PsycINFO and Web of Science databases for articles published between December 1994 and September 2023 was performed. Out of the initial 2510 studies identified, 17 articles were retrieved that met all the predetermined selection criteria, particularly of assessing qEEG changes in one of the three conditions compared to healthy controls. All studies scored moderate to high quality on the Newcastle-Ottawa scale. There was a general trend for decreased low-frequency EEG band activity (delta, theta, and alpha) and increased high-frequency EEG beta activity in FMS, differing to that found in ME/CFS. The limited LC studies included in this review focused mainly on cognitive impairments and showed mixed findings not consistent with patterns observed in FMS and ME/CFS. Our findings suggest different patterns of qEEG brainwave activity in FMS and ME/CFS. Further research is required to explore whether there are phenotypes within LC that have EEG signatures similar to FMS or ME/CFS. This could inform identification of reliable diagnostic markers and possible targets for neuromodulation therapies tailored to each clinical syndrome.

Inverse association between slow-wave sleep and low-grade inflammation in children and adolescents with major depressive disorder

OBJECTIVE

To investigate the relationship between both self-reported and objective sleep variables and low-grade inflammation in children and adolescents with major depressive disorder (MDD) of moderate to severe symptom severity.

METHODS

In this cross-sectional study, we examined twenty-nine children and adolescents diagnosed with MDD and twenty-nine healthy controls (HC). Following a one-week actigraphy assessment, comprehensive sleep evaluations were conducted, including a one-night sleep EEG measurement and self-reported sleep data. Plasma high-sensitivity C-reactive protein (hsCRP) was employed as a marker to assess low-grade inflammation.

RESULTS

No significant difference in hsCRP levels was observed between participants with MDD and HC. Furthermore, after adjusting for sleep difficulties, hsCRP exhibited no correlation with the severity of depressive symptoms. In HC, levels of hsCRP were not linked to self-reported and objective sleep variables. In contrast, depressed participants showed a significant correlation between hsCRP levels and increased subjective insomnia severity (Insomnia Severity Index; r = 0.41, p < 0.05), increased time spent in the N2 sleep stage (r = 0.47, p < 0.01), and decreased time spent in slow-wave sleep (r = - 0.61, p < 0.001). Upon additional adjustments for body mass index, tobacco use and depression severity, only the inverse association between hsCRP and time spent in slow-wave sleep retained statistical significance. Moderation analysis indicated that group status (MDD vs. HC) significantly moderates the association between slow-wave sleep and hsCRP.

CONCLUSION

Our findings suggest that alterations in the architecture of slow-wave sleep may have a significant influence on modulating low-grade inflammatory processes in children and adolescents with MDD.

Hyperarousal features in the sleep architecture of individuals with and without insomnia

Sleep architecture encodes relevant information on the structure of sleep and has been used to assess hyperarousal in insomnia. This study investigated whether polysomnography-derived sleep architecture displays signs of hyperarousal in individuals with insomnia compared with individuals without insomnia. Data from Phase 3 clinical trials, private clinics and a cohort study were analysed. A comprehensive set of sleep architecture features previously associated with hyperarousal were retrospectively analysed focusing on sleep-wake transition probabilities, electroencephalographic spectra and sleep spindles, and enriched with a novel machine learning algorithm called the Wake Electroencephalographic Similarity Index. This analysis included 1710 individuals with insomnia and 1455 individuals without insomnia. Results indicate that individuals with insomnia had a higher likelihood of waking from all sleep stages, and showed increased relative alpha during Wake and N1 sleep and increased theta power during Wake when compared with individuals without insomnia. Relative delta power was decreased and Wake Electroencephalographic Similarity Index scores were elevated across all sleep stages except N3, suggesting more wake-like activity during these stages in individuals with insomnia. Additionally, sleep spindle density was decreased, and spindle dispersion was increased in individuals with insomnia. These findings suggest that insomnia is characterized by a dysfunction in sleep quality with a continuous hyperarousal, evidenced by changes in sleep-wake architecture.

A randomized controlled trial of alpha phase-locked auditory stimulation to treat symptoms of sleep onset insomnia

Sleep onset insomnia is a pervasive problem that contributes significantly to the poor health outcomes associated with insufficient sleep. Auditory stimuli phase-locked to slow-wave sleep oscillations have been shown to augment deep sleep, but it is unknown whether a similar approach can be used to accelerate sleep onset. The present randomized controlled crossover trial enrolled adults with objectively verified sleep onset latencies (SOLs) greater than 30 min to test the effect of auditory stimuli delivered at specific phases of participants' alpha oscillations prior to sleep onset. During the intervention week, participants wore an electroencephalogram (EEG)-enabled headband that delivered acoustic pulses timed to arrive anti-phase with alpha for 30 min (Stimulation). During the Sham week, the headband silently recorded EEG. The primary outcome was SOL determined by blinded scoring of EEG records. For the 21 subjects included in the analyses, stimulation had a significant effect on SOL according to a linear mixed effects model (p = 0.0019), and weekly average SOL decreased by 10.5 ± 15.9 min (29.3 ± 44.4%). These data suggest that phase-locked acoustic stimulation can be a viable alternative to pharmaceuticals to accelerate sleep onset in individuals with prolonged sleep onset latencies. Trial Registration: This trial was first registered on clinicaltrials.gov on 24/02/2023 under the name Sounds Locked to ElectroEncephalogram Phase For the Acceleration of Sleep Onset Time (SLEEPFAST), and assigned registry number NCT05743114.

Individualized Closed-Loop Acoustic Stimulation Suggests an Alpha Phase Dependence of Sound Evoked and Induced Brain Activity Measured with EEG Recordings

Following repetitive visual stimulation, post hoc phase analysis finds that visually evoked response magnitudes vary with the cortical alpha oscillation phase that temporally coincides with sensory stimulus. This approach has not successfully revealed an alpha phase dependence for auditory evoked or induced responses. Here, we test the feasibility of tracking alpha with scalp electroencephalogram (EEG) recordings and play sounds phase-locked to individualized alpha phases in real-time using a novel end-point corrected Hilbert transform (ecHT) algorithm implemented on a research device. Based on prior work, we hypothesize that sound-evoked and induced responses vary with the alpha phase at sound onset and the alpha phase that coincides with the early sound-evoked response potential (ERP) measured with EEG. Thus, we use each subject's individualized alpha frequency (IAF) and individual auditory ERP latency to define target trough and peak alpha phases that allow an early component of the auditory ERP to align to the estimated poststimulus peak and trough phases, respectively. With this closed-loop and individualized approach, we find opposing alpha phase-dependent effects on the auditory ERP and alpha oscillations that follow stimulus onset. Trough and peak phase-locked sounds result in distinct evoked and induced post-stimulus alpha level and frequency modulations. Though additional studies are needed to localize the sources underlying these phase-dependent effects, these results suggest a general principle for alpha phase-dependence of sensory processing that includes the auditory system. Moreover, this study demonstrates the feasibility of using individualized neurophysiological indices to deliver automated, closed-loop, phase-locked auditory stimulation.

Relationships between rumination and different types of rapid eye movement sleep in patients with chronic insomnia disorder

BACKGROUND AND OBJECTIVE

Rumination, a common factor of chronic insomnia disorder (CID) caused by cognitive-emotional arousal, is associated with an increased amount of rapid eye movement (REM) sleep. However, the specific subtypes, such as phasic REM and tonic REM, that contribute to the increased REM sleep have not been reported. This study aimed to determine the association between rumination and different REM sleep subtypes in patients with CID.

METHODS

This study enrolled 35 patients with CID and 27 age- and sex-matched healthy controls. The Immersion-Rumination Questionnaire evaluated participants' rumination, and the Insomnia Severity Index was used to assess insomnia severity. Finally, polysomnography was used to monitor objective sleep quality and quantification of different types of REM.

RESULTS

The CID patients had higher rumination scores than the healthy controls. They had a shorter REM sleep duration, less phasic REM, a lower percentage of phasic REM time, and a higher percentage of tonic REM time. Spectral analysis revealed that the patients affected by insomnia had higher β power during REM sleep, higher β and σ power during phasic REM sleep, and higher β, and γ power during tonic REM sleep. Partial correlation analysis showed that rumination in the CID patients correlated negatively with the duration of phasic REM sleep. Additionally, rumination correlated negatively with δ power in REM sleep and positively with β power in REM sleep, tonic REM sleep, phasic REM sleep, N3and N2 sleep in the patients with CID.

CONCLUSION

The CID patients had stronger rumination, reduced total and phasic REM sleep, and the stronger rumination was, the shorter phasic REM was and the higher fast (β) wave power in REM sleep.

Suvorexant alters dynamics of the sleep-electroencephalography-power spectrum and depressive-symptom trajectories during inpatient opioid withdrawal

STUDY OBJECTIVES

Opioid withdrawal is an aversive experience that often exacerbates depressive symptoms and poor sleep. The aims of the present study were to examine the effects of suvorexant on oscillatory sleep-electroencephalography (EEG) band power during medically managed opioid withdrawal, and to examine their association with withdrawal severity and depressive symptoms.

METHODS

Participants with opioid use disorder (N = 38: age-range:21-63, 87% male, 45% white) underwent an 11-day buprenorphine taper, in which they were randomly assigned to suvorexant (20 mg [n = 14] or 40 mg [n = 12]), or placebo [n = 12], while ambulatory sleep-EEG data was collected. Linear mixed-effect models were used to explore: (1) main and interactive effects of drug group, and time on sleep-EEG band power, and (2) associations between sleep-EEG band power change, depressive symptoms, and withdrawal severity.

RESULTS

Oscillatory spectral power tended to be greater in the suvorexant groups. Over the course of the study, decreases in delta power were observed in all study groups (β = -189.082, d = -0.522, p = <0.005), increases in beta power (20 mg: β = 2.579, d = 0.413, p = 0.009 | 40 mg β = 5.265, d = 0.847, p < 0.001) alpha power (20 mg: β = 158.304, d = 0.397, p = 0.009 | 40 mg: β = 250.212, d = 0.601, p = 0.001) and sigma power (20 mg: β = 48.97, d = 0.410, p < 0.001 | 40 mg: β = 71.54, d = 0.568, p < 0.001) were observed in the two suvorexant groups. During the four-night taper, decreases in delta power were associated with decreases in depressive symptoms (20 mg: β = 190.90, d = 0.308, p = 0.99 | 40 mg: β = 433.33, d = 0.889 p = <0.001), and withdrawal severity (20 mg: β = 215.55, d = 0.034, p = 0.006 | 40 mg: β = 192.64, d = -0.854, p = <0.001), in both suvorexant groups and increases in sigma power were associated with decreases in withdrawal severity (20 mg: β = -357.84, d = -0.659, p = 0.004 | 40 mg: β = -906.35, d = -1.053, p = <0.001). Post-taper decreases in delta (20 mg: β = 740.58, d = 0.964 p = <0.001 | 40 mg: β = 662.23, d = 0.882, p = <0.001) and sigma power (20 mg only: β = 335.54, d = 0.560, p = 0.023) were associated with reduced depressive symptoms in the placebo group.

CONCLUSIONS

Results highlight a complex and nuanced relationship between sleep-EEG power and symptoms of depression and withdrawal. Changes in delta power may represent a mechanism influencing depressive symptoms and withdrawal.

High stability of EEG spectral power across polysomnography and multiple sleep latency tests in good sleepers and chronic insomniacs

To assess the stability of electroencephalographic (EEG) spectral features across overnight polysomnography (PSG) and daytime multiple sleep latency tests (MSLTs) in chronic insomniacs (CIs) and normal controls (NCs). A total of 20 NCs and 22 CIs underwent standard PSG and MSLTs. Spectral analyses were performed on EEG data from PSG and MSLTs and absolute and relative power in central, frontal and occipital channels were obtained for wake (W) and non-rapid eye movement sleep stage 1 and 2 (N1, N2). Intraclass correlation coefficients (ICCs) were used to assess the stability of EEG spectral power across PSG and MSLTs for W, N1 and N2. The absolute power of all frequency bands except delta exhibited high stability across PSG and MSLTs in both NCs and CIs (ICCs ranged from 0.430 to 0.978). Although delta absolute power was stable in NCs during N1 and N2 stages (ICCs ranged from 0.571 to 0.835), it tended to be less stable in CIs during W and sleep stages (ICCs ranged from 0.042 to 0.807). We also observed lower stability of relative power compared to absolute power though the majority of relative power outcomes maintained high stability in both groups (ICCs in relative power ranged from 0.044 to 0.962). Most EEG spectral bandwidths across PSG and MSLT in W, N1 and N2 show high stability in good sleepers and chronic insomniacs. EEG signals from either an overnight PSG or a daytime MSLT may be useful for reliably exploring EEG spectral features during wakefulness or sleep.

Cortical hyperarousal in individuals with frequent nightmares

Nightmares are common among the general population and psychiatric patients and have been associated with signs of nocturnal arousal such as increased heart rate or increased high-frequency electroencephalographic (EEG) activity. However, it is still unclear, whether these characteristics are more of a trait occurring in people with frequent nightmares or rather indicators of the nightmare state. We compared participants with frequent nightmares (NM group; n = 30) and healthy controls (controls; n = 27) who spent 4 nights in the sleep laboratory over the course of 8 weeks. The NM group received six sessions of imagery rehearsal therapy (IRT), the 'gold standard' of cognitive-behavioural therapy for nightmares, between the second and the third night. Sleep architecture and spectral power were compared between groups, and between nights of nightmare occurrence and nights without nightmare occurrence in the NM group. Additionally, changes before and after therapy were recorded. The NM group showed increased beta (16.25-31 Hz) and low gamma (31.25-35 Hz) power during the entire night compared to the controls, but not when comparing nights of nightmare occurrence to those without. Moreover, low gamma activity in rapid eye movement sleep was reduced after therapy in the NM group. Our findings indicate, cortical hyperarousal is more of a trait in people with frequent nightmares within a network of other symptoms, but also malleable by therapy. This is not only a new finding for IRT but could also lead to improved treatment options in the future that directly target high-frequency EEG activity.

Fundamentals of sleep regulation: Model and benchmark values for fractal and oscillatory neurodynamics

Homeostatic, circadian and ultradian mechanisms play crucial roles in the regulation of sleep. Evidence suggests that ratios of low-to-high frequency power in the electroencephalogram (EEG) spectrum indicate the instantaneous level of sleep pressure, influenced by factors such as individual sleep-wake history, current sleep stage, age-related differences and brain topography characteristics. These effects are well captured and reflected in the spectral exponent, a composite measure of the constant low-to-high frequency ratio in the periodogram, which is scale-free and exhibits lower interindividual variability compared to slow wave activity, potentially serving as a suitable standardization and reference measure. Here we propose an index of sleep homeostasis based on the spectral exponent, reflecting the level of membrane hyperpolarization and/or network bistability in the central nervous system in humans. In addition, we advance the idea that the U-shaped overnight deceleration of oscillatory slow and fast sleep spindle frequencies marks the biological night, providing somnologists with an EEG-index of circadian sleep regulation. Evidence supporting this assertion comes from studies based on sleep replacement, forced desynchrony protocols and high-resolution analyses of sleep spindles. Finally, ultradian sleep regulatory mechanisms are indicated by the recurrent, abrupt shifts in dominant oscillatory frequencies, with spindle ranges signifying non-rapid eye movement and non-spindle oscillations - rapid eye movement phases of the sleep cycles. Reconsidering the indicators of fundamental sleep regulatory processes in the framework of the new Fractal and Oscillatory Adjustment Model (FOAM) offers an appealing opportunity to bridge the gap between the two-process model of sleep regulation and clinical somnology.

Does sleep promote adaptation to acute stress: An experimental study

Objectives

Evidence of the impact of chronic stress on sleep is abundant, yet experimental sleep studies with a focus on acute stress are scarce and the results are mixed. Our study aimed to fill this gap by experimentally investigating the effects of pre-sleep social stress on sleep dynamics during the subsequent night, as measured with polysomnography (PSG).

Methods

Thirty-four healthy individuals (65% females, Mage = 25.76 years SD = 3.35) underwent a stress-inducing (SC) or neutral control condition (CC) in virtual reality (VR). We used overnight EEG measurements to analyze the basic sleep parameters and power spectral density (PSD) across the sleep cycles, and measured heart rate and its variability (HRV), skin electrodermal activity (EDA), and salivary cortisol to capture physiological arousal during the VR task and the pre-sleep period.

Results

Following acute stress (SC), the amount of slow-wave sleep (SWS) was higher and N2 sleep lower relative to CC, specifically in the first sleep cycle. In SC, PSD was elevated in the beta-low (16-24 Hz) and beta-high (25-35 Hz) frequency ranges during both stages N2 and SWS over the entire night.

Conclusions

Sleep promoted adaptation to acute social stress by a longer duration of SWS in the subsequent sleep period, especially in early sleep. A similar homeostatic effect towards restorative sleep is well-evidenced in animal model stress studies but has not been previously reported in experimental human studies. Whether the high-frequency PSD activity during stages N2 and SWS also serves in the resolution of transient stress, remains open.

Hyperarousal-state of Insomnia Disorder in Wake-resting State Quantitative Electroencephalography

Objective

: Insomnia is associated with elevated high-frequency electroencephalogram power in the waking state. Although affective symptoms (e.g., depression and anxiety) are commonly comorbid with insomnia, few reports distinguished objective sleep disturbance from affective symptoms. In this study, we investigated whether daytime electroencephalographic activity explains insomnia, even after controlling for the effects of affective symptoms.

Methods

: A total of 107 participants were divided into the insomnia disorder (n = 58) and healthy control (n = 49) groups using the Mini-International Neuropsychiatric Interview and diagnostic criteria for insomnia disorder. The participants underwent daytime resting-state electroencephalography sessions (64 channels, eye-closed).

Results

: The insomnia group showed higher levels of anxiety, depression, and insomnia than the healthy group, as well as increased beta [t(105) = -2.56, p = 0.012] and gamma [t(105) = -2.44, p = 0.016] spectra. Among all participants, insomnia symptoms positively correlated with the intensity of beta (r = 0.28, p ＜ 0.01) and gamma (r = 0.25, p ＜ 0.05) spectra. Through hierarchical multiple regression, the beta power showed the additional ability to predict insomnia symptoms beyond the effect of anxiety (ΔR2 = 0.041, p = 0.018).

Conclusion

: Our results showed a significant relationship between beta electroencephalographic activity and insomnia symptoms, after adjusting for other clinical correlates, and serve as further evidence for the hyperarousal theory of insomnia. Moreover, resting-state quantitative electroencephalography may be a supplementary tool to assess insomnia.

All-night spectral and microstate EEG analysis in patients with recurrent isolated sleep paralysis

The pathophysiology of recurrent isolated sleep paralysis (RISP) has yet to be fully clarified. Very little research has been performed on electroencephalographic (EEG) signatures outside RISP episodes. This study aimed to investigate whether sleep is disturbed even without the occurrence of a RISP episode and in a stage different than conventional REM sleep. 17 RISP patients and 17 control subjects underwent two consecutive full-night video-polysomnography recordings. Spectral analysis was performed on all sleep stages in the delta, theta, and alpha band. EEG microstate (MS) analysis was performed on the NREM 3 phase due to the overall high correlation of subject template maps with canonical templates. Spectral analysis showed a significantly higher power of theta band activity in REM and NREM 2 sleep stages in RISP patients. The observed rise was also apparent in other sleep stages. Conversely, alpha power showed a downward trend in RISP patients' deep sleep. MS maps similar to canonical topographies were obtained indicating the preservation of prototypical EEG generators in RISP patients. RISP patients showed significant differences in the temporal dynamics of MS, expressed by different transitions between MS C and D and between MS A and B. Both spectral analysis and MS characteristics showed abnormalities in the sleep of non-episodic RISP subjects. Our findings suggest that in order to understand the neurobiological background of RISP, there is a need to extend the analyzes beyond REM-related processes and highlight the value of EEG microstate dynamics as promising functional biomarkers of RISP.

Neurophysiological Parameters Influencing Sleep-Wake Discrepancy in Insomnia Disorder: A Preliminary Analysis on Alpha Rhythm during Sleep Onset

Sleep state misperception (SSM) is a common issue in insomnia disorder (ID), causing a discrepancy between objective and subjective sleep/wake time estimation and increased daytime impairments. In this context, the hyperarousal theory assumes that sustained central nervous system activation contributes to the SSM. This study investigates factors influencing SSM during sleep latency (SL) and total sleep time (TST). Objective polysomnographic sleep variables (the alpha density index, latency-to-sleep stages and the first K-complex, and Rapid Eye Movement (REM) arousal density) and subjective sleep indices, taken from sleep diaries, were analyzed in 16 ID patients. Correlation analyses revealed a positive association between the degree of SL misperception (SLm) and the percentage of epochs that contained a visually scored stereotyped alpha rhythm during objective SL. A regression analysis showed that the REM arousal density and alpha density index significantly predicted TST misperception (TSTm). Furthermore, the degree of SLm was associated with an increased probability of transitioning from stage 1 of non-REM sleep to wakefulness during subjective SL. These findings support the role of hyperarousal in SSM and highlight the importance of alpha activity in unravelling the heterogeneous underpinnings of SSM.

Subjective sleep onset latency is influenced by sleep structure and body heat loss in human subjects

The present study examined the relationship between subjective sleep onset latency (SOL), sleep structure, changes in skin and body temperature, and subjective evaluation of sleep in healthy young adults to elucidate the pathophysiological mechanisms of insomnia. A total of 28 participants (age 21.54 [0.50] years) with no sleep problems participated in a 1-h polysomnographic recording that obtained objective sleep parameters during the daytime while skin and body temperatures were recorded. The distal-proximal skin temperature gradient (DPG) was calculated. Subjective parameters, such as subjective SOL, sleep time, and restorative sleepiness, were evaluated before and after sleep. Most participants estimated their sleep latency as being longer than their actual SOL (13.7 versus 7.6 min). Objective SOL was significantly correlated with each sleep stage parameter whereas subjective SOL was negatively correlated with Stage N2 sleep duration (Rho = -0.454, p = 0.020), slow-wave activity and delta power (Rho = -0.500, p = 0.011 and Rho = -0.432, p = 0.031, respectively), and ΔDPG (the degree of reduction of heat loss before and after lights-off). Stepwise regression analysis showed that ΔDPG was the strongest predictive factor in explaining the length of subjective SOL. The degree of heat dissipation before and after lights-off contributed most to the sensation of falling asleep in healthy young adults. This finding may be helpful for elucidating the physiological mechanisms of insomnia and its treatment.

Neural mechanisms of attentional bias to emotional faces in patients with chronic insomnia disorder

OBJECTIVE

This study used event-related potential (ERP) and resting-state functional connectivity (rs-FC) approaches to investigate the neural mechanisms underlying the emotional attention bias in patients with chronic insomnia disorder (CID).

METHODS

Twenty-five patients with CID and thirty-three demographically matched healthy controls (HCs) completed clinical questionnaires and underwent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) scans. EEG analysis examined the group differences in terms of reaction times, P3 amplitudes, event-related spectral perturbations, and inter-trial phase synchrony. Subsequently, seed-based rs-FC analysis of the amygdala nuclei (including the central-medial amygdala [CMA] and basolateral amygdala [BLA]) was performed. The relationship between P3 amplitude, rs-FC and clinical symptom severity in patients with CID was further investigated by correlation analysis.

RESULTS

CID patients exhibited shorter reaction times than HCs in both standard and deviant stimuli, with the abnormalities becoming more pronounced as attention allocation increased. Compared to HCs, ERP analysis revealed increased P3 amplitude, theta wave power, and inter-trial synchrony in CID patients. The rs-FC analysis showed increased connectivity of the BLA-occipital pole, CMA-precuneus, and CMA-angular gyrus and decreased connectivity of the CMA-thalamus in CID patients. Notably, correlation analysis of the EEG and fMRI measurements showed a significant positive correlation between the P3 amplitude and the rs-FC of the CMA-PCU.

CONCLUSION

This study confirms an emotional attention bias in CID, specifically in the neural mechanisms of attention processing that vary depending on the allocation of attentional resources. Abnormal connectivity in the emotion-cognition networks may constitute the neural basis of the abnormal scalp activation pattern.

Sex differences in body temperature and neural power spectra in response to repeated restraint stress

Repeated stress is associated with an increased risk of developing psychiatric illnesses such as post-traumatic stress disorder (PTSD), which is more common in women, yet the neurobiology behind this sex difference is unknown. Habituation to repeated stress is impaired in PTSD, and recent preclinical studies have shown that female rats do not habituate as fully as male rats to repeated stress, which leads to impairments in cognition and sleep. Further research should examine sex differences after repeated stress in other relevant measures, such as body temperature and neural activity. In this study, we analyzed core body temperature and EEG power spectra in adult male and female rats during restraint, as well as during sleep transitions following stress. We found that core body temperature of male rats habituated to repeated restraint more fully than female rats. Additionally, we found that females had a higher average beta band power than males on both days of restraint, indicating higher levels of arousal. Lastly, we observed that females had lower delta band power than males during sleep transitions on Day 1 of restraint, however, females demonstrated higher delta band power than males by Day 5 of restraint. This suggests that it may take females longer to initiate sleep recovery compared with males. These findings indicate that there are differences in the physiological and neural processes of males and females after repeated stress. Understanding the way that the stress response is regulated in both sexes can provide insight into individualized treatment for stress-related disorders.

Is There a Difference in EEG Characteristics in Acute, Chronic, and Experimentally Induced Musculoskeletal Pain States? a Systematic Review

Electroencephalographic (EEG) alterations have been demonstrated in acute, chronic, and experimentally induced musculoskeletal (MSK) pain conditions. However, there is no cumulative evidence on the associated EEG characteristics differentiating acute, chronic, and experimentally induced musculoskeletal pain states, especially compared to healthy controls. The present systematic review was performed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines (PRISMA) to review and summarize available evidence for cortical brain activity and connectivity alterations in acute, chronic, and experimentally induced MSK pain states. Five electronic databases were systematically searched from their inception to 2022. A total of 3471 articles were screened, and 26 full articles (five studies on chronic pain and 21 studies on experimentally induced pain) were included for the final synthesis. Using the Downs and Black risk of assessment tool, 92% of the studies were assessed as low to moderate quality. The review identified a 'very low' level of evidence for the changes in EEG and subjective outcome measures for both chronic and experimentally induced MSK pain based on the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria. Overall, the findings of this review indicate a trend toward decreased alpha and beta EEG power in evoked chronic clinical pain conditions and increased theta and alpha power in resting-state EEG recorded from chronic MSK pain conditions. EEG characteristics are unclear under experimentally induced pain conditions.

Identifying the insomnia-related psychological issues associated with hyperarousal: A network perspective

Hyperarousal, recognized as a fundamental characteristic of insomnia for decades, has yielded limited evidence concerning its direct psychological associations. This study aimed to explore the psychological factors linked to hyperarousal within the framework of interrelated variables. Two independent samples, comprising n = 917 and n = 652 young adults, were included in the study. Employing the first dataset as a discovery sample and the second dataset as a replication sample, network analyses were conducted using 26 variables derived from 17 scales. The objective was to estimate the direct and indirect associations between psychological issues, including hyperarousal and insomnia. Additionally, linear regression analysis was employed to assess the convergence of findings obtained from the network analysis. Network analyses in both samples converged to reveal direct associations between insomnia severity and several psychological factors, including negative sleep beliefs, physical fatigue, insomnia response to stress, hyperarousal, self-reported depression, and mental fatigue. Notably, the nodes with relative importance within the network include trait anxiety, depressive rumination, hyperarousal, perfectionism sub-dimension of concern over mistakes, and private self-consciousness. Hyperarousal is one of the key factors linking insomnia with a variety of psychological issues, including emotion-related factors (rumination, perveived stress), sleep-related factors (dysfunctional sleep beliefs and attitudes, insomnia response to stress, fatigue, chronotype), and self-related factors (self-consciousness, perfectionism). The results suggest that forthcoming strategies for enhancing the treatment efficacy of insomnia could consider supplementary interventions that specifically address hyperarousal, other factors directly linked to insomnia, or the hub nodes within the network.

Electroencephalography microstates as novel functional biomarkers for insomnia disorder

Background

Insomnia disorder (ID) is one of the most common mental disorders. Research on ID focuses on exploring its mechanism of disease, novel treatments and treatment outcome prediction. An emerging technique in this field is the use of electroencephalography (EEG) microstates, which offer a new method of EEG feature extraction that incorporates information from both temporal and spatial dimensions.

Aims

To explore the electrophysiological mechanisms of repetitive transcranial magnetic stimulation (rTMS) for ID treatment and use baseline microstate metrics for the prediction of its efficacy.

Methods

This study included 60 patients with ID and 40 age-matched and gender-matched good sleep controls (GSC). Their resting-state EEG microstates were analysed, and the Pittsburgh Sleep Quality Index (PSQI) and polysomnography (PSG) were collected to assess sleep quality. The 60 patients with ID were equally divided into active and sham groups to receive rTMS for 20 days to test whether rTMS had a moderating effect on abnormal microstates in patients with ID. Furthermore, in an independent group of 90 patients with ID who received rTMS treatment, patients were divided into optimal and suboptimal groups based on their median PSQI reduction rate. Baseline EEG microstates were used to build a machine-learning predictive model for the effects of rTMS treatment.

Results

The class D microstate was less frequent and contribute in patients with ID, and these abnormalities were associated with sleep onset latency as measured by PSG. Additionally, the abnormalities were partially reversed to the levels observed in the GSC group following rTMS treatment. The baseline microstate characteristics could predict the therapeutic effect of ID after 20 days of rTMS, with an accuracy of 80.13%.

Conclusions

Our study highlights the value of EEG microstates as functional biomarkers of ID and provides a new perspective for studying the neurophysiological mechanisms of ID. In addition, we predicted the therapeutic effect of rTMS on ID based on the baseline microstates of patients with ID. This finding carries great practical significance for the selection of therapeutic options for patients with ID.

Revisiting the Psychobiological Inhibition Model: a conceptual framework for understanding and treating insomnia using cognitive and behavioural therapeutics (CBTx)

Sleep is a biological imperative, so one might wonder "what has psychology got to do with it?" A person's behaviours, thoughts, emotions and interactions with the environment inevitably serve for good, or for ill, as the "setting conditions" for the expression of sleep. Put simply, although sleep is not a psychological phenomenon, sleep has crucial behavioural dependencies. Consequently, the Psychobiological Inhibition Model can embrace numerous, potentially interacting, pathways to the persistence of this ubiquitous disorder, providing an overarching conceptual framework for why and how insomnia develops. The clinical guideline treatment for chronic insomnia is cognitive behavioural therapy. Although typically delivered as "talking therapy", cognitive behavioural therapy is not some form of "psychobabble". Rather, the Psychobiological Inhibition Model framework for insomnia articulates how specific techniques can correct the various ways in which the expression of normal sleep and circadian brain-behaviour relationships have become disrupted. Indeed, cognitive behavioural therapy is best conceived of as an approach to treatment rather than being one specific agent. A shift in emphasis towards a cognitive and behavioural therapeutics formulary would provide improved impetus to understanding of how insomnia develops, and of how it may best be treated in any given patient.

Neural mechanisms of working memory dysfunction in patients with chronic insomnia disorder

OBJECTIVE

This study aimed to investigate the neural mechanisms underlying working memory impairment in patients with chronic insomnia disorder (CID) using event-related potentials (ERP) and resting-state functional connectivity (rsFC) approaches.

METHODS

Participants, including CID patients and healthy controls (HCs), completed clinical scales and underwent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). EEG analysis compared reaction times, P3 amplitudes, event-related spectral perturbations (ERSP), and inter-trial phase synchronisation (ITPS) between CID patients and HCs. Subsequently, frontal regions (i.e., the Superior Frontal Gyrus [SFG] and Middle Frontal Gyrus [MFG]) corresponding to the EEG were selected as seeds for rsFC analysis. Correlation analyses were conducted to further investigate the relationship between functional connectivity abnormalities in brain regions and clinical symptom severity and P3 amplitude in CID patients.

RESULTS

Compared to HCs, CID patients exhibited slower reaction times across all working memory conditions, with the deficits becoming more pronounced as memory load increased. ERP analysis revealed increased P3 amplitude, theta wave power, and reduced inter-trial synchrony in CID patients. rsFC analysis showed decreased connectivity of SFG-posterior cingulated cortex (PCC), SFG-MFG, and MFG-frontal pole (FP), and increased connectivity of MFG- Middle Temporal Gyrus (MTG)in CID patients. Importantly, a significant correlation was found between the rsFC of SFG-MTG and P3 amplitude during 1-back.

CONCLUSION

This study confirms deficits in working memory capacity in patients with CID, specifically in the neural mechanisms of cognitive processing that vary depending on the level of cognitive load. Alterations in connectivity patterns within and between the frontal and temporal regions may be the neural basis of the cognitive impairment.

Hyperarousal in insomnia disorder: Current evidence and potential mechanisms

Insomnia disorder is among the most frequent mental disorders, making research on its aetiology and pathophysiology particularly important. A unifying element of many aetiological and pathophysiological models is that they support or even centre on the role of some form of hyperarousal. In this theoretical review, we aim to summarise the current evidence on hyperarousal in insomnia. Hyperarousal is discussed as a state of relatively increased arousal in physiological, cortical and cognitive-emotional domains. Regarding physiological hyperarousal, there is no conclusive evidence for the involvement of autonomous variables such as heart rate and heart rate variability, whereas recent evidence points to a pathophysiological role of neuroendocrine variables. In addition, current literature supports a central involvement of cortical arousal, that is, high-frequency electroencephalographic activity. An increasingly important focus in the literature is on the role of other microstructural sleep parameters, especially the existence of microarousals during sleep. Beyond that, a broad range of evidence exists supporting the role of cognitive-emotional hyperarousal in the form of insomnia-related thought and worries, and their concomitant emotional symptoms. Besides being a state marker of insomnia, hyperarousal is considered crucial for the predisposition to insomnia and for the development of comorbid mental disorders. Thus, beyond presenting evidence from cross-sectional studies on markers of hyperarousal in insomnia, hypotheses about the mechanisms of hyperarousal are presented. Nevertheless, longitudinal studies are needed to further elucidate the mechanism of hyperarousal throughout the course of the disorder, and future studies should also focus on similarities and differences in hyperarousal across different diagnostic entities.

Mechanisms of cognitive behavioural therapy for insomnia

Although much is known now about behavioural, cognitive and physiological consequences of insomnia, little is known about changes after cognitive behavioural therapy for insomnia on these particular factors. We here report baseline findings on each of these factors in insomnia, after which we address findings on their changes after cognitive behavioural therapy. Sleep restriction remains the strongest determinant of insomnia treatment success. Cognitive interventions addressing dysfunctional beliefs and attitudes about sleep, sleep-related selective attention, worry and rumination further drive effectiveness of cognitive behavioural therapy for insomnia. Future studies should focus on physiological changes after cognitive behavioural therapy for insomnia, such as changes in hyperarousal and brain activity, as literature on these changes is sparse. We introduce a detailed clinical research agenda on how to address this topic.

The importance and limitations of polysomnography in insomnia disorder-a critical appraisal

The importance polysomnography (PSG) in the diagnosis and treatment process of insomnia disorder (ID) remains highly disputed. This review summarises the state of the science regarding PSG indications and findings in ID, and the indications to conduct PSG in ID as stated by relevant guidelines. It then highlights the most relevant questions regarding the topic, including the relevance of ID subtyping, to allow an individualised pharmacological or psychotherapeutic treatment approach.

EEG Biofeedback Decreases Theta and Beta Power While Increasing Alpha Power in Insomniacs: An Open-Label Study

Insomnia, often associated with anxiety and depression, is a prevalent sleep disorder. Biofeedback (BFB) treatment can help patients gain voluntary control over physiological events such as by utilizing electroencephalography (EEG) and electromyography (EMG) power. Previous studies have rarely predicted biofeedback efficacy by measuring the changes in relative EEG power; therefore, we investigated the clinical efficacy of biofeedback for insomnia and its potential neural mechanisms. We administered biofeedback to 82 patients with insomnia, of whom 68 completed 10 sessions and 14 completed 20 sessions. The average age of the participants was 49.38 ± 12.78 years, with 26 men and 56 women. Each biofeedback session consisted of 5 min of EMG and 30 min of EEG feedback, with 2 min of data recorded before and after the session. Sessions were conducted every other day, and four scale measures were taken before the first, fifth, and tenth sessions and after the twentieth session. After 20 sessions of biofeedback treatment, scores on the Pittsburgh Sleep Quality Index (PSQI) were significantly reduced compared with those before treatment (-5.5 ± 1.43,t = -3.85, p = 0.006), and scores on the Beck Depression Inventory (BDI-II) (-7.15 ± 2.43, t = -2.94, p = 0.012) and the State-Trait Anxiety Inventory (STAI) (STAI-S: -12.36 ± 3.40, t = -3.63, p = 0.003; and STAI-T: -9.86 ± 2.38, t = -4.41, p = 0.001) were significantly lower after treatment than before treatment. Beta and theta power were significantly reduced after treatment, compared with before treatment (F = 6.25, p = 0.014; and F = 11.91, p = 0.001). Alpha power was increased after treatment, compared with before treatment, but the difference was not prominently significant (p > 0.05). EMG activity was significantly decreased after treatment, compared with before treatment (F = 2.11, p = 0.015). Our findings suggest that BFB treatment based on alpha power and prefrontal EMG relieves insomnia as well as anxiety and depression and may be associated with increased alpha power, decreased beta and theta power, and decreased EMG power.

Beta spectral power during sleep is associated with impaired recall of extinguished fear

The failure to retain memory for extinguished fear plays a major role in the maintenance of posttraumatic stress disorder (PTSD), with successful extinction recall necessary for symptom reduction. Disturbed sleep, a hallmark symptom of PTSD, impairs fear extinction recall. However, our understanding of the electrophysiological mechanisms underpinning sleep's role in extinction retention remains underdetermined. We examined the relationship between the microarchitecture of sleep and extinction recall in healthy humans (n = 71, both male and females included) and a pilot study in individuals with PTSD (n = 12). Participants underwent a fear conditioning and extinction protocol over 2 days, with sleep recording occurring between conditioning and extinction. Twenty-four hours after extinction learning, participants underwent extinction recall. Power spectral density (PSD) was computed for pre- and post-extinction learning sleep. Increased beta-band PSD (~17-26 Hz) during pre-extinction learning sleep was associated with worse extinction recall in healthy participants (r = 0.41, p = .004). Beta PSD was highly stable across three nights of sleep (intraclass correlation coefficients > 0.92). Results suggest beta-band PSD is specifically implicated in difficulties recalling extinguished fear.

Amygdala resting-state functional connectivity alterations in patients with chronic insomnia disorder: correlation with electroencephalography beta power during sleep

STUDY OBJECTIVES

This study investigated alterations in resting-state functional connectivity (RSFC) and hyperarousal biomarkers in patients with chronic insomnia disorder (CID), compared with good sleepers (GS). We also examined the relationships between altered RSFC and hyperarousal biomarkers.

METHODS

Fifty patients with CID and 52 GS completed self-reporting questionnaires, and then underwent polysomnography and resting-state functional magnetic resonance imaging. We analyzed RSFC in the amygdala (AMG) and anterior insula (aINS), which are core regions of the salience network that are likely to be involved in hyperarousal. We also analyzed electroencephalography (EEG) relative beta power and heart rate variability (HRV) parameters (e.g. low and high frequency) during sleep. We then tested between-group differences in the RSFC and hyperarousal biomarkers; we examined correlations of RSFC with EEG beta power and HRV.

RESULTS

Compared with GS, patients with CID showed more negative RSFC between the right amygdala (R.AMG) and left supramarginal gyrus (L.SMG), but less positive RSFC between the left aINS and bilateral lateral prefrontal cortex. The R.AMG-L.SMG RSFC was negatively correlated with EEG beta power in central regions (C3: r = -0.336, p = 0.012; C4: r = -0.314, p = 0.024).

CONCLUSIONS

Decreased RSFC between the R.AMG and L.SMG in patients with insomnia may reflect the difficulty in cortical top-down regulation of the AMG, indicating daytime hyperarousal. Individuals who experience hyperarousal during the daytime may also exhibit cortical hyperarousal during sleep, as indicated by increased EEG beta power.

A wearable EEG system for closed-loop neuromodulation of sleep-related oscillations

Objective.Healthy sleep plays a critical role in general well-being. Enhancement of slow-wave sleep by targeting acoustic stimuli to particular phases of delta (0.5-2 Hz) waves has shown promise as a non-invasive approach to improve sleep quality. Closed-loop stimulation during other sleep phases targeting oscillations at higher frequencies such as theta (4-7 Hz) or alpha (8-12 Hz) could be another approach to realize additional health benefits. However, systems to track and deliver stimulation relative to the instantaneous phase of electroencephalogram (EEG) signals at these higher frequencies have yet to be demonstrated outside of controlled laboratory settings.Approach.Here we examine the feasibility of using an endpoint-corrected version of the Hilbert transform (ecHT) algorithm implemented on a headband wearable device to measure alpha phase and deliver phase-locked auditory stimulation during the transition from wakefulness to sleep, during which alpha power is greatest. First, the ecHT algorithm is implementedin silicoto evaluate the performance characteristics of this algorithm across a range of sleep-related oscillatory frequencies. Secondly, a pilot sleep study tests feasibility to use the wearable device by users in the home setting for measurement of EEG activity during sleep and delivery of real-time phase-locked stimulation.Main results.The ecHT is capable of computing the instantaneous phase of oscillating signals with high precision, allowing auditory stimulation to be delivered at the intended phases of neural oscillations with low phase error. The wearable system was capable of measuring sleep-related neural activity with sufficient fidelity for sleep stage scoring during the at-home study, and phase-tracking performance matched simulated results. Users were able to successfully operate the system independently using the companion smartphone app to collect data and administer stimulation, and presentation of auditory stimuli during sleep initiation did not negatively impact sleep onset.Significance.This study demonstrates the feasibility of closed-loop real-time tracking and neuromodulation of a range of sleep-related oscillations using a wearable EEG device. Preliminary results suggest that this approach could be used to deliver non-invasive neuromodulation across all phases of sleep.

The potential of biomarkers for diagnosing insomnia: Consensus statement of the WFSBP Task Force on Sleep Disorders

OBJECTIVES

Thus far, the diagnosis of insomnia is based on purely clinical criteria. Although a broad range of altered physiological parameters has been identified in insomniacs, the evidence to establish their diagnostic usefulness is very limited. Purpose of this WFSBP Task Force consensus paper is to systematically evaluate a series of biomarkers as potential diagnostic tools for insomnia.

METHODS

A newly created grading system was used for assessing the validity of various measurements in establishing the diagnosis of insomnia; these measurements originated from relevant studies selected and reviewed by experts.

RESULTS

The measurements with the highest diagnostic performance were those derived from psychometric instruments. Biological measurements which emerged as potentially useful diagnostic instruments were polysomnography-derived cyclic alternating pattern, actigraphy, and BDNF levels, followed by heart rate around sleep onset, deficient melatonin rhythm, and certain neuroimaging patterns (mainly for the activity of frontal and pre-frontal cortex, hippocampus and basal ganglia); yet, these findings need replication, as well as establishment of commonly accepted methodology and diagnostic cut-off points. Routine polysomnography, EEG spectral analysis, heart rate variability, skin conductance, thermoregulation, oxygen consumption, HPA axis, and inflammation indices were not shown to be of satisfactory diagnostic value.

CONCLUSIONS

Apart from psychometric instruments which are confirmed to be the gold standard in diagnosing insomnia, six biomarkers emerge as being potentially useful for this purpose.

Beyond the symptom: the biology of fatigue

A workshop titled "Beyond the Symptom: The Biology of Fatigue" was held virtually September 27-28, 2021. It was jointly organized by the Sleep Research Society and the Neurobiology of Fatigue Working Group of the NIH Blueprint Neuroscience Research Program. For access to the presentations and video recordings, see: https://neuroscienceblueprint.nih.gov/about/event/beyond-symptom-biology-fatigue. The goals of this workshop were to bring together clinicians and scientists who use a variety of research approaches to understand fatigue in multiple conditions and to identify key gaps in our understanding of the biology of fatigue. This workshop summary distills key issues discussed in this workshop and provides a list of promising directions for future research on this topic. We do not attempt to provide a comprehensive review of the state of our understanding of fatigue, nor to provide a comprehensive reprise of the many excellent presentations. Rather, our goal is to highlight key advances and to focus on questions and future approaches to answering them.

Resting-state EEG as a potential indicator to predict sleep quality in depressive patients

OBJECTIVES

To investigate the changes in sleep quality, heart rate variability (HRV) and resting-state electroencephalogram (rsEEG) in patients with major depressive disorder (MDD), and to explore whether HRV and rsEEG may be served as more convenient tools to assess sleep quality in MDD patients.

METHOD

We included a total of 91 subjects (46 healthy controls and 45 MDD patients) and compared their sleep quality, HRV and power spectra of rsEEG. Correlation analyses were conducted to discuss the relationship between HRV and seven factors of PSQI. Multiple linear regression model was used to examine whether absolute band power could predict sleep quality in MDD patients.

RESULTS

We found higher PSQI scores and lower levels of HRV in depressive individuals compared with healthy controls. In MDD patients, sleep latency was negatively correlated with RMSSD and HF. Delta, theta, and alpha band power of rsEEG were higher in MDD patients. Regression analyses showed delta band power of TP8, as well as theta, alpha band power of AF3 predicts PSQI score of MDD patients.

CONCLUSIONS

The findings of our study show that some aspects of sleep problems had negative correlations with parasympathetic activity and the regression model supports that the band power of rsEEG may be used as a potential indicator to evaluate the sleep quality in MDD patients.

SIGNIFICANCE

Cortical hyperarousal may be one of the reasons leading to poor sleep quality of MDD patients. And resting-state EEG can be used as a potential indicator for clinical assessment of MDD patients' sleep quality.

The Treatment of Insomnia Secondary to Generalized Anxiety Disorder: Evaluating Escitalopram Use With Concomitant High-Resolution, Relational, Resonance-Based, Electroencephalic Mirroring (HIRREM)

Patient autonomy is important. However, what if a patient seeks out poorly studied treatment options? In this case report, we describe a patient with insomnia secondary to generalized anxiety disorder (GAD) who was prescribed escitalopram but additionally used High-Resolution, Relational, Resonance-Based, Electroencephalic Mirroring (HIRREM) therapy. HIRREM is an electroencephalogram (EEG)-based therapy that has been evaluated for use in the treatment of various conditions including insomnia. However, there has only been one randomized clinical trial supporting the use of HIRREM for insomnia, and the Food and Drug Administration (FDA) has not approved HIRREM for insomnia. A few months after the patient initiated HIRREM therapy and escitalopram cessation, the patient's insomnia did not recur. We propose a case for how we approached educating a patient who was seeking out an alternative poorly tested therapy by helping him perform a cost-benefit analysis composed of treatment efficacy, cost, and side effects.

Insomnia

OBJECTIVE

This article provides an overview of the current definitions, diagnostic tools, and overall management of insomnia.

LATEST DEVELOPMENTS

The treatment of insomnia has shifted over time, with a growing emphasis on nonpharmacologic therapies as a first-line intervention and the leveraging of technology to aid in the dissemination of these therapies. With this evolution, the definition of insomnia has changed to reflect a common treatment pathway. As pharmacologic treatment options have increased, so has concern about the dangerous short-term and long-term adverse effects of these treatment options.

ESSENTIAL POINTS

Insomnia is a common disorder, frequently overlapping with other neurologic and psychiatric disorders, which can cause significant distress and disruption to patients' lives. Nonpharmacologic therapies are highly effective and are now considered first-line treatments. Although efficacy is variable, numerous pharmacologic interventions are available, and many options come with considerable concern about adverse effects, particularly in populations over 65 years old.

Automatic Detection of Chronic Insomnia from Polysomnographic and Clinical Variables Using Machine Learning

Insomnia is defined subjectively by the presence and frequency of specific clinical symptoms and an association with distress. Although sleep study data has shown some weak associations, no objective test can currently be used to predict insomnia. The purpose of this study was to use previously reported and relatively crafted insomnia-related polysomnographic variables in machine learning models to classify groups with and without insomnia. Demographics, diagnosed depression, Epworth Sleepiness Scale (ESS), and features derived from electroencephalography (EEG), arousals, and sleep stages from 3,407 sleep clinic patients (2,617 without insomnia and 790 insomnia patients based on responses to a set of questions) were included in this analysis. The number of features were reduced using pair-wise correlation and recursive feature elimination. Predictive value of three machine learning models (logistic regression, neural network, and support vector machine) was investigated, and the best performance was achieved with logistic regression, yielding a balanced accuracy of 71%. The most important features in predicting insomnia were depression, age, sex, duration of longest arousal, ESS score, and EEG power in theta and sigma bands across all sleep stages. Results indicate potential of machine learning-based screening for insomnia using clinical variables and EEG.

Highly Activated Neuronal Firings Monitored by Implantable Microelectrode Array in the Paraventricular Thalamus of Insomnia Rats

Insomnia is a common sleep disorder around the world, which is harmful to people's health, daily life, and work. The paraventricular thalamus (PVT) plays an essential role in the sleep-wake transition. However, high temporal-spatial resolution microdevice technology is lacking for accurate detection and regulation of deep brain nuclei. The means for analyzing sleep-wake mechanisms and treating sleep disorders are limited. To detect the relationship between the PVT and insomnia, we designed and fabricated a special microelectrode array (MEA) to record electrophysiological signals of the PVT for insomnia and control rats. Platinum nanoparticles (PtNPs) were modified onto an MEA, which caused the impedance to decrease and improved the signal-to-noise ratio. We established the model of insomnia in rats and analyzed and compared the neural signals in detail before and after insomnia. In insomnia, the spike firing rate was increased from 5.48 ± 0.28 spike/s to 7.39 ± 0.65 spike/s, and the power of local field potential (LFP) decreased in the delta frequency band and increased in the beta frequency band. Furthermore, the synchronicity between PVT neurons declined, and burst-like firing was observed. Our study found neurons of the PVT were more activated in the insomnia state than in the control state. It also provided an effective MEA to detect the deep brain signals at the cellular level, which conformed with macroscopical LFP and insomnia symptoms. These results laid the foundation for studying PVT and the sleep-wake mechanism and were also helpful for treating sleep disorders.

Thalamic network under wakefulness after sleep onset and its coupling with daytime fatigue in insomnia disorder: An EEG-fMRI study

BACKGROUND

Fatigue is the most common daytime impairment of insomnia disorder (ID). Thalamus is acknowledged as the key brain region closely associated with fatigue. However, the thalamus-based neurobiological mechanisms of fatigue in patients with ID remain unknown.

METHODS

Forty-two ID patients and twenty-eight well-matched healthy controls (HCs) underwent simultaneous electroencephalography--functional magnetic resonance imaging. We calculated the functional connectivity (FC) between the thalamic seed and each voxel across the whole brain in two conditions of wakefulness--after sleep onset (WASO) and before sleep onset. A linear mixed effect model was used to determine the condition effect of the thalamic FC. The correlation between daytime fatigue and the thalamic connectivity was explored.

RESULTS

After sleep onset, the connectivity with the bilateral thalamus was increased in the cerebellar and cortical regions. Compared with HCs, ID patients showed significantly lower FC between left thalamus and left cerebellum under the WASO condition. Furthermore, thalamic connectivity with cerebellum under the WASO condition was negatively correlated with Fatigue Severity Scale scores in the pooled sample.

CONCLUSIONS

These findings contribute to an emerging framework that reveals the link between insomnia-related daytime fatigue and the altered thalamic network after sleep onset, further highlighting the possibility that this neural pathway is a therapeutic target for meaningfully mitigating fatigue.

The Good Sleeper Scale-15 items: a questionnaire for the standardised assessment of good sleepers

Research with 'good sleepers' is ubiquitous, yet there are no standardised criteria to identify a 'good sleeper'. The present study aimed to create and validate a questionnaire for identifying good sleepers for use in research studies known as the Good Sleeper Scale-15 items (GSS-15). Data were derived from a population-based survey of Australian adults (n = 2,044). A total of 23 items were chosen for possible inclusion. An exploratory factor analysis (EFA) was conducted on ~10% of the survey dataset (n = 191) for factor identification and item reduction. A confirmatory factor analysis (CFA) was conducted on the remaining data (n = 1,853) to test model fit. Receiver operating characteristic curves and correlations were conducted to derive cut-off scores and test associations with sleep, daytime functioning, health, and quality-of-life. The EFA identified six factors: 'Sleep Difficulties', 'Timing', 'Duration', 'Regularity', 'Adequacy', and 'Perceived Sleep Problem'. The CFA showed that model fit was high and comparable to other sleep instruments, χ² (63) = 378.22, p < 0.001, root mean square error of approximation = 0.05, with acceptable internal consistency (α = 0.76). Strong correlations were consistently found between GSS-15 global scores and outcomes, including 'a good night's sleep' (r = 0.7), 'feeling un-refreshed' (r = -0.59), and 'experienced sleepiness' (r = -0.51), p < 0.001. Cut-off scores were derived to categorise individuals likely to be a good sleeper (GSS-15 score ≥40) and those very likely to be a good sleeper (GSS-15 score ≥45). The GSS-15 is a freely available, robust questionnaire that will assist in identifying good sleepers for the purpose of sleep research. Future work will test relationships with other sleep measures in community and clinical samples.

How many hours do you sleep? A comparison of subjective and objective sleep duration measures in a sample of insomnia patients and good sleepers

Our objective was to assess the agreement and linear relationships amongst multiple measures of sleep duration in a sample of patients with insomnia disorder and good sleeper controls. We retrospectively analysed data from 123 patients with insomnia disorder and 123 age- and gender-matched good sleeper controls who completed a simple subjective habitual sleep duration question (Pittsburgh Sleep Quality Index), a sleep diary (5-14 days), 2 nights of polysomnography, and two corresponding morning subjective estimates of sleep duration. Descriptive statistics, linear regression analyses and Bland-Altman plots were used to describe the relationship and (dis)agreement between sleep duration measures. Relationships between polysomnography and the simple question as well as between polysomnography and sleep diary were weak to non-existent. Subjective measures and polysomnography did not agree. Sleep duration measured with the Pittsburgh Sleep Quality Index or sleep diary was about 2 hr above or up to 4 hr below polysomnography-measured sleep duration. Patients with insomnia disorder, on average, reported shorter sleep duration compared with polysomnography, while good sleeper controls, on average, reported longer sleep duration compared with polysomnography. The results suggest that subjective and objective measures apparently capture different aspects of sleep, even when nominally addressing the same value (sleep duration). They disagree in both patients with insomnia disorder and good sleeper controls, but in different directions. Studies assessing sleep duration should take into account both the investigated population and the assessment method when interpreting results. Future studies should continue to investigate possible psychological and physiological correlates of sleep (mis)perception.

The potential of electroencephalography coherence to predict the outcome of repetitive transcranial magnetic stimulation in insomnia disorder

BACKGROUND

It is unknown whether repetitive Transcranial Magnetic Stimulation (rTMS) could improve sleep quality by modulating electroencephalography (EEG) connectivity of insomnia disorder (ID) patients. Great heterogeneity had been found in the clinical outcomes of rTMS for ID. The study aimed to investigate the potential mechanisms of rTMS therapy for ID and develop models to predict clinical outcomes.

METHODS

In Study 1, 50 ID patients were randomly divided into active and sham groups, and subjected to 20 sessions of treatment with 1 Hz rTMS over the left dorsolateral prefrontal cortex. EEG during awake, Polysomnography, and clinical assessment were collected and analyzed before and after rTMS. In Study 2, 120 ID patients were subjected to active rTMS stimulation and were then separated into optimal and sub-optimal groups due to the median of Pittsburgh Sleep Quality Index reduction rate. Machine learning models were developed based on baseline EEG coherence to predict rTMS treatment effects.

RESULTS

In Study 1, decreased EEG coherence in theta and alpha bands were observed after rTMS treatment, and changes in theta band (F7-O1) coherence were correlated with changes in sleep efficiency. In Study 2, baseline EEG coherence in theta, alpha, and beta bands showed the potential to predict the treatment effects of rTMS for ID.

CONCLUSION

rTMS improved sleep quality of ID patients by modulating the abnormal EEG coherence. Baseline EEG coherence between certain channels in theta, alpha, and beta bands could act as potential biomarkers to predict the therapeutic effects.

Concussed Neural Signature is Substantially Different than Fatigue Neural Signature in Non-concussed Controls

Traumatic brain injuries can result in short-lived and long-lasting neurological impairment. Identifying the correct recovery timeframe is challenging, as balance-based metrics may be negatively impacted if testing is performed soon after exercise. Thirty-two healthy controls and seventeen concussed individuals performed a series of balance challenges, including virtual reality optical flow perturbation. The control group completed a backpacking protocol to induce moderate fatigue. Concussed participants had lower spectral power in the motor cortex and central sulcus when compared to fatigued controls. Moreover, concussed participants experienced a decrease in overall theta band spectral power while fatigued controls showed an increase in theta band spectral power. This neural signature may be useful to distinguish between concussed and non-concussed fatigued participants in future assessments.

Effects on resting-state EEG phase-amplitude coupling in insomnia disorder patients following 1 Hz left dorsolateral prefrontal cortex rTMS

Despite burgeoning evidence for cortical hyperarousal in insomnia disorder, the existing results on electroencephalography spectral features are highly heterogeneous. Phase-amplitude coupling, which refers to the modulation of the low-frequency phase to a high-frequency amplitude, is probably a more sensitive quantitative measure for characterizing abnormal neural oscillations and explaining the therapeutic effect of repetitive transcranial magnetic stimulation in the treatment of patients with insomnia disorder. Sixty insomnia disorder patients were randomly divided into the active and sham treatment groups to receive 4 weeks of repetitive transcranial magnetic stimulation treatment. Behavioral assessments, resting-state electroencephalography recordings, and sleep polysomnography recordings were performed before and after repetitive transcranial magnetic stimulation treatment. Forty good sleeper controls underwent the same assessment. We demonstrated that phase-amplitude coupling values in the frontal and temporal lobes were weaker in Insomnia disorder patients than in those with good sleeper controls at baseline and that phase-amplitude coupling values near the intervention area were significantly enhanced after active repetitive transcranial magnetic stimulation treatment. Furthermore, the enhancement of phase-amplitude coupling values was significantly correlated with the improvement of sleep quality. This study revealed the potential of phase-amplitude coupling in assessing the severity of insomnia disorder and the efficacy of repetitive transcranial magnetic stimulation treatment, providing new insights on the abnormal physiological mechanisms and future treatments for insomnia disorder.

No alterations in potential indirect markers of locus coeruleus-norepinephrine function in insomnia disorder

The norepinephrine locus coeruleus system (LC NE) represents a promising treatment target in patients with insomnia disorder (ID) due to its well understood links to arousal and sleep regulation. However, consistent markers of LC NE activity are lacking. This study measured three potential indirect markers of LC NE activity - REM sleep, P3 amplitude during an auditory oddball paradigm (as a marker of phasic LC activation), and baseline pupil diameter (as a marker of tonic LC activation). The parameters were then combined in a statistical model and tested to compare LC NE activity between 20 subjects with insomnia disorder (13 female; age 44.2 ± 15.1 year) and 20 healthy, good sleeping controls (GSC; 11 female; age 45.4 ± 11.6 year). No group differences regarding the primary outcome parameters were detected. Specifically, insomnia disorder did not display the hypothesised changes in markers of LC NE function. While increased LC NE function remains an interesting speculative pathway for hyperarousal in insomnia disorder, the investigated markers do not appear closely related to each other and fail to discriminate between insomnia disorder and good sleeping controls in these samples.

On the relationship between EEG spectral analysis and pre-sleep cognitive arousal in insomnia disorder: towards an integrated model of cognitive and cortical arousal

According to the hyperarousal model, insomnia is characterised by increased arousal in the cortical, cognitive, and physiological domains. However, the interaction between these arousal domains is poorly understood. The present observational case-control study aimed to investigate cortical arousal during the night, pre-sleep cognitive arousal and the relationship between these two domains. A total of 109 patients with insomnia disorder (ID) and 109 age-and gender matched healthy controls were investigated on two sleep laboratory nights. Electroencephalographic (EEG) spectral power during non-rapid eye movement (NREM) and REM sleep was analysed as a measure of cortical arousal. In addition, patients completed the Pre-Sleep Arousal Scale (PSAS), which consists of two subscales, one for cognitive arousal (PSAS-CA) and one for self-reported somatic arousal (PSAS-SA). The relationship between the subscale scores and EEG spectral power was calculated by multi- and univariate analyses of variance. During NREM and REM sleep, patients with ID showed significantly increased spectral power in the EEG gamma band. In addition, patients with ID showed significantly increased scores on both subscales of the PSAS. The PSAS-CA score was significantly associated with increased NREM and REM gamma power, whereas PSAS-SA was associated with decreases in NREM and REM gamma power. Consistent with our hypothesis, patients with ID showed increased cortical and cognitive arousal. Moreover, there was an association between these two arousal domains, which may indicate that cortical arousal during the night is (at least in part) elicited by pre-sleep worry and rumination.

Enhanced intrathalamic morphological connectivity in patients with chronic insomnia

This study aimed to systematically investigate abnormal morphological connectivity in subregions of the thalamus and examine the clinical relevance of this connectivity in patients with chronic insomnia. One hundred and two patients with chronic insomnia (aged 45.50 [34.75 ~ 58.00] years; 24 men, 78 women) and one hundred and one healthy controls (aged 45.00 [34.00 ~ 55.00] years; 32 men, 69 women) were recruited. Intrathalamic and thalamocortical morphological connectivity in the thalamic subregions defined in the Human Brainnetome Atlas were computed and compared between the two groups. Spearman's correlation was used to estimate the association between thalamic morphological connectivity alterations and clinical variables. Compared with the control group, the insomnia group exhibited higher intrathalamic mean morphological connectivity than the control group, though no alterations in thalamocortical morphological connectivity were observed. However, no correlation was found between altered intrathalamic morphological connectivity and behavioral scales. In addition, alterations in morphological connectivity among thalamic subregions were found mainly in the left medial premotor thalamus, left medial prefrontal thalamus, and left sensory thalamus; however, these results were no longer significant after correction. Our findings suggest increased intrathalamic morphological connectivity in patients with chronic insomnia, thus enriching the understanding of morphological connectivity at the individual level and providing new perspectives for clinical interventions and diagnostic imaging.