Enhanced frontoparietal synchronized activation during the wake-sleep transition in patients with primary insomnia

Sleep alterations in major depressive disorder and insomnia disorder: A network meta-analysis of polysomnographic studies

Major depressive disorder (MDD) and Insomnia disorder (ID) are characterized by sleep alterations. To define their polysomnographic profiles, we conducted a Network Meta-Analysis comparing MDD and ID patients versus healthy controls (HCs). The literature search, conducted from 2008 up to January 2023 and following PRISMA guidelines, covered PubMed, Web of Science, Scopus, and Embase databases. We addressed publication bias using funnel plot asymmetry inspection and Egger's test, evaluated statistical heterogeneity with I2, and local and global inconsistencies with the separate indirect from direct evidence method and Q between designs, respectively. Pairwise meta-analyses employed a fixed-effects model, while network analysis utilized a random-effect approach. We evaluated 86 ID and 17 MDD studies, comparing sleep parameters for 636 MDDs versus 491 HCs, and 3661 IDs versus 2792 HCs. The network meta-analysis reported that patients with MDD have greater rapid eye movement (REM) sleep duration and REMs density, and lower REM sleep latency compared to IDs. ID patients instead exhibited lower total sleep time and time in bed, and greater wake after sleep onset and non-REM sleep stage 3 than MDD patients. This work emphasized sleep depth and continuity alterations in both MDD and ID, with major involvement of REM sleep in MDD.

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.

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.

Pharmacological management of co-morbid obstructive sleep apnoea and insomnia

INTRODUCTION

Clinical presentation of both insomnia and obstructive sleep apnea (COMISA) is common. Approximately 30% of clinical cohorts with OSA have insomnia symptoms and vice versa. The underlying pathophysiology of COMISA is multifactorial. This poses a complex clinical challenge. Currently, there are no clinical guidelines or recommendations outside of continuous positive airway pressure (CPAP) therapy and cognitive behavioral therapy for insomnia (CBTi). Clinically translatable precision medicine approaches to characterize individual causes or endotypes may help optimize future pharmacological management of COMISA.

AREAS COVERED

This review article provides an up-to-date account of COMISA and its consequences, the underlying pathophysiology of sleep apnea, insomnia and COMISA, current treatment approaches and limitations, pharmacotherapy targets and future priorities.

EXPERT OPINION

There are multiple promising emerging therapies, but clinical trial data specifically in COMISA populations are lacking. This is a priority for future investigation to inform development of evidence-based guidelines. Pharmacotherapies, particularly for insomnia, do not target the underlying causes of the disorder thus, are indicated for short-term use only and should remain second line. Future multidisciplinary research should be directed toward the multifactorial nature of COMISA and the challenges of adapting COMISA treatment in clinical practice and overcoming the practical barriers that health-care providers and consumers encounter.

The neurophysiologic landscape of the sleep onset: a systematic review

Background

The sleep onset process is an ill-defined complex process of transition from wakefulness to sleep, characterized by progressive modifications at the subjective, behavioural, cognitive, and physiological levels. To this date, there is no international consensus which could aid a principled characterisation of this process for clinical research purposes. The current review aims to systemise the current knowledge about the underlying mechanisms of the natural heterogeneity of this process.

Methods

In this systematic review, studies investigating the process of the sleep onset from 1970 to 2022 were identified using electronic database searches of PsychINFO, MEDLINE, and Embase.

Results

A total of 139 studies were included; 110 studies in healthy participants and 29 studies in participants with sleep disorders. Overall, there is a limited consensus across a body of research about what distinct biomarkers of the sleep onset constitute. Only sparse data exists on the physiology, neurophysiology and behavioural mechanisms of the sleep onset, with majority of studies concentrating on the non-rapid eye movement stage 2 (NREM 2) as a potentially better defined and a more reliable time point that separates sleep from the wake, on the sleep wake continuum.

Conclusions

The neurophysiologic landscape of sleep onset bears a complex pattern associated with a multitude of behavioural and physiological markers and remains poorly understood. The methodological variation and a heterogenous definition of the wake-sleep transition in various studies to date is understandable, given that sleep onset is a process that has fluctuating and ill-defined boundaries. Nonetheless, the principled characterisation of the sleep onset process is needed which will allow for a greater conceptualisation of the mechanisms underlying this process, further influencing the efficacy of current treatments for sleep disorders.

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.

Dissociation of Arousal Index Between REM and NREM Sleep in Elderly Adults with Cognitive Impairment, No Dementia: A Pilot Study

BACKGROUND

Sleep disruption in elderly has been associated with an increased risk of cognitive impairment and its transition into Alzheimer's disease (AD). High arousal indices (AIs) during sleep may serve as an early-stage biomarker of cognitive impairment non-dementia (CIND).

OBJECTIVE

Using full-night polysomnography (PSG), we investigated whether CIND is related to different AIs between NREM and REM sleep stages.

METHODS

Fourteen older adults voluntarily participated in this population-based study that included Mini-Mental State Examination, Neuropsi battery, Katz Index of Independence in Activities of Daily Living, and single-night PSG. Subjects were divided into two groups (n = 7 each) according to their results in Neuropsi memory and attention subtests: cognitively unimpaired (CU), with normal results; and CIND, with -2.5 standard deviations in memory and/or attention subtests. AIs per hour of sleep during N1, N2, N3, and REM stages were obtained and correlated with Neuropsi total score (NTS).

RESULTS

AI (REM)  was significantly higher in CU group than in CIND group. For the total sample, a positive correlation between AI (REM)  and NTS was found (r = 0.68, p = 0.006), which remained significant when controlling for the effect of age and education. In CIND group, the AI (N2)  was significantly higher than the AI (REM) .

CONCLUSION

In CIND older adults, this attenuation of normal arousal mechanisms in REM sleep are dissociated from the relative excess of arousals observed in stage N2. We propose as probable etiology an early hypoactivity at the locus coeruleus noradrenergic system, associated to its early pathological damage, present in the AD continuum.

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

Aim

To examine the 24-h hyperarousal hypothesis of insomnia using electroencephalographic (EEG) spectral analysis of overnight polysomnography (PSG) and daytime multiple sleep latency tests (MSLTs).

Methods

Standard PSG and MSLT were recorded in 31 chronic insomniacs (CIs) (21 females, mean age 36.19) and in 21 normal controls (NCs) (18 females, mean age 34.76). EEG spectral analyses were conducted and relative power was obtained for each sleep stage during PSG and each session during MSLTs. Subsequently, CIs were subdivided based on sleep efficiency (SE < or ≥ 85%) or mean sleep latency (MSL) of MSLT (< or ≥ 15 min), and beta power was compared among NCs and CIs subgroups. General liner regression analyses of beta power and PSG parameters were conducted.

Results

CIs had significantly greater beta power in nighttime W, N1, N2, NREM, and in total overnight and in MSLT sessions compared with NCs. CIs with lower PSG-SE or longer MSLT-MSL showed higher beta power at nighttime. Compared with NCs, increased beta power was limited to CIs with lower PSG-SE or longer MSLT-MSL during MSLT sessions. In all subjects, total daytime beta was positively correlated to total overnight beta and MSL, total overnight beta was negatively related to SE. In CIs, total daytime beta and total overnight beta were positively correlated.

Conclusion

Our results support the hypothesis of 24-h cortical hyperarousal in insomnia. We conclude that 24-h cortical hyperarousal is clearly present in insomnia and is greater in insomnia with objective findings.

Hypogyrification in Generalized Anxiety Disorder and Associated with Insomnia Symptoms

PURPOSE

Insomnia is a recognized feature of generalized anxiety disorder (GAD). The underlying neural substrate of insomnia in GAD is still unclear. Cortical folding is a reliable index and possibly an endophenotype of psychiatric disease. The aim of this study was to explore whether the aberrant cortical morphology was associated with insomnia in GAD.

PATIENTS AND METHODS

We enrolled 73 patients with GAD and 74 matched healthy controls (HCs) to undergo neuropsychiatric assessment and 3.0 T magnetic resonance imaging scanning. Neuropsychiatric batteries included the 14-item Hamilton Anxiety Rating Scale (HAMA) and the Insomnia Severity Index (ISI). Using FreeSurfer7.1.1, we calculated local gyrification index, cortical thickness and surface area and identified group differences in these parameters. Then, we calculated the functional connectivity of these identified regions and determined functional alterations. The relationship between these neuroimaging indicators and clinical measurement was explored.

RESULTS

Compared with HCs, the LGI in the bilateral orbitofrontal cortex (OFC), bilateral insula, left middle frontal gyrus, left temporal pole, and left fusiform area was significantly decreased in GAD. GAD patients had concurrent decreased surface area in the left OFC and thicker right OFC. GAD patients also exhibited increased functional connectivity between the left insula and frontoparietal control network. In addition, a negative relationship was observed between decreased LGI in these limbic regions and ISI score.

CONCLUSION

GAD patients presented aberrant cortical folding in limbic network. Cortical morphology is a potential endophenotype in GAD, corresponding to an insomnia phenotype.

A novel EEG marker predicts perceived sleepiness and poor sleep quality

STUDY OBJECTIVES

To determine if a novel EEG-derived continuous index of sleep depth/alertness, the odds ratio product (ORP), predicts self-reported daytime sleepiness and poor sleep quality in two large population-based cohorts.

METHODS

ORP values which range from 0 (deep sleep) to 2.5 (fully alert) were calculated in 3s intervals during awake periods (ORPwake) and NREM sleep (ORPNREM) determined from home sleep studies in the HypnoLaus (N = 2162: 1106 females, 1056 males) and men androgen inflammation lifestyle environment and stress (MAILES) cohorts (N = 754 males). Logistic regression was used to examine associations between ORPwake, ORPNREM, and traditional polysomnography measures (as comparators) with excessive sleepiness (Epworth sleepiness scale >10) and poor sleep quality (Pittsburgh sleep quality index >5) and insomnia symptoms.

RESULTS

High ORPwake was associated with a ~30% increase in poor sleep quality in both HypnoLaus (odds ratio, OR, and 95% CI) 1.28 (1.09, 1.51), and MAILES 1.36 (1.10, 1.68). High ORPwake was also associated with a ~28% decrease in excessive daytime sleepiness in the MAILES dataset. ORPNREM was associated with a ~30% increase in poor sleep quality in HypnoLaus but not in MAILES. No consistent associations across cohorts were detected using traditional polysomnography markers.

CONCLUSIONS

ORP, a novel EEG-derived metric, measured during wake periods predicts poor sleep quality in two independent cohorts. Consistent with insomnia symptomatology of poor perceived sleep in the absence of excessive daytime sleepiness, ORPwake may provide valuable objective mechanistic insight into physiological hyperarousal.

Study Protocol for a Randomized Controlled Trial Assessing the Effectiveness of Personalized Computerized Cognitive Training for Individuals With Insomnia

Insomnia is a frequent and heightened pathology in the general population of developed countries, and its condition generally leads to health discomfort and performance drop in daily and work-related tasks. As current pharmacological treatments for insomnia do not always seem sufficient to mitigate impairment, contemporary cognitive approaches might shed light on developing complementary therapies for this population. We propose a cognitive stimulation intervention program based on the importance of cognitive abilities as precipitating and maintenance variables of sleep disturbances. A full phase I-II-III clinical trial is proposed in which the first two studies will serve to assess the safety of the intervention and to identify the maximum tolerated time of the computerized cognitive training (phase I) and the minimum effective number of training sessions (phase II) in the absence of adverse events or side effects. Next, a phase-III double-blind randomized controlled trial design will be set. Sixty individuals with insomnia aged 25 to 55 years will enroll in a home-based personalized computerized cognitive stimulation program for a total time of 8 weeks, training 5 days per week. Sixty insomnia patients matched in a variety of factors will constitute the active control group, where the orthogonal activities will not be cognitively demanding. Sleep, cognitive, emotional, and quality of life variables will be measured before and immediately after training. A linear mixed model and hierarchical regression analysis will be used to investigate intervention effects. The results derived from this study will be precious for future research and treatment in cognitive performance and clinical pathologies.

Clinical Trial Registration: [https://clinicaltrials.gov/], identifier [NCT05050292].

A Randomized Controlled Trial Comparing Neurofeedback and Cognitive-Behavioral Therapy for Insomnia Patients: Pilot Study

Insomnia is a common disease that negatively affects patients both mentally and physically. While insomnia disorder is mainly characterized by hyperarousal, a few studies that have directly intervened with cortical arousal. This study was conducted to investigate the effect of a neurofeedback protocol for reducing cortical arousal on insomnia compared to cognitive-behavioral treatment for insomnia (CBT-I). Seventeen adults with insomnia, free of other psychiatric illnesses, were randomly assigned to neurofeedback or CBT-I. All participants completed questionnaires on insomnia [Insomnia Severity Index (ISI)], sleep quality [Pittsburgh Sleep Quality Index (PSQI)], and dysfunctional cognition [Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-16)]. The neurofeedback group showed decreases in beta waves and increases in theta and alpha waves in various areas of the electroencephalogram (EEG), indicating lowered cortical arousal. The ISI and PSQI scores were significantly decreased, and sleep efficiency and sleep satisfaction were increased compared to the pre-treatment scores in both groups. DBAS scores decreased only in the CBT-I group (NF p = 0.173; CBT-I p = 0.012). This study confirmed that neurofeedback training could alleviate the symptoms of insomnia by reducing cortical hyperarousal in patients, despite the limited effect in reducing cognitive dysfunction compared to CBT-I.

[Characteristics of Sleep Electroencephalographic Power in Chronic Insomnia Patients]

OBJECTIVE

To study the sleep electroencephalogram (EEG) power features of patients with chronic insomnia.

METHODS

Retrospective analysis was performed with patients who met the ICD-10 diagnostic criteria for chronic insomnia, using polysomnography (PSG) to examine the overnight sleep EEG. The sleep architectures and relative EEG power across five frequency bands during overnight sleep were compared to study the differences between the insomnia and control groups. Furthermore, the correlation between EEG power and various PSG measures was also analyzed.

RESULTS

Forty-five subjects were enrolled in the study, including 25 chronic insomniacs (18 females, aged [36.2±10.7] years) and 20 controls (18 females, aged [36.1±7.6] years). Compared to those of the control group, insomnia patients had significantly lower value of delta power ([38.0±6.1] vs. [43.2±5.8], P<0.05) in the NREM1 stage, and increased value of beta power during total NREM, NREM1 and NREM2 (NREM sleep [5.4±2.3] vs. [3.8±1.4], NREM1 [11.3±3.5] vs. [8.7±2.8], and NREM2 [5.7±2.3] vs. [4.4±1.4], all P<0.05). For correlation analyses, in the insomnia group, a significantly positive correlation was found between the delta value during NREM sleep and the duration of NREM3 sleep ( r=0.527). The beta value during NREM sleep was found to be negatively correlated to the duration of NREM3 sleep ( r=－0.767). A positive correlation was found between the beta value during NREM sleep and the duration of NREM1 and NREM2 sleep ( r=0.486 and 0.589, respectively).

CONCLUSION

The results suggest that patients with chronic insomnia have decreased low-frequency EEG power, but increased high-frequency EEG power during NREM sleep. The findings indicate that cortex arousal level is elevated in chronic insomniacs during NREM sleep.

Sleep discrepancy is associated with alterations in the salience network in patients with insomnia disorder: An EEG-fMRI study

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Simultaneous EEG-fMRI was used to clarify the association between the brain functional connectivity and sleep discrepancy between self-report and polysomnography in patients with insomnia disorder.

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An altered anterior insula-based connectivity across wakefulness and all NREM stages.

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Sleep discrepancy was significantly associated with anterior insula–putamen/thalamus connectivity during wakefulness.

Background

Positron emission tomography – computed tomography (PET-CT) research has shown that sleep discrepancy recorded by self-report and polysomnography (PSG) may be related to the altered metabolic rate of the anterior insula (aINS) during non-rapid eye movement (NREM) sleep in patients with insomnia disorder. We aim to explore the functional connectivity of aINS across wake and NREM sleep in the patients and to reveal the association between aINS connectivity and sleep discrepancy.

Methods

Patients with insomnia disorder (n = 33) and healthy controls (n = 31) underwent simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) during nighttime sleep, and aINS-based connectivity was calculated across wake and NREM sleep. A linear mixed-effects model was used to assess the main effect of group and group-by-stage (wake, NREM stages 1–3) interaction effect on aINS connectivity. Similar mixed models were used to assess the potential correlation between aINS connectivity and the sleep misperception index (MI).

Results

A significant group-by-stage interaction effect on aINS-based connectivity was observed in the bilateral frontal gyrus, right inferior temporal gyrus, bilateral middle occipital gyrus and right postcentral gyrus (p < 0.05, corrected). There was also a significant group-by-MI interaction effect on aINS connectivity with the putamen and thalamus during wakefulness (p < 0.05 corrected); MI was significantly associated with aINS–putamen/thalamus connectivity in the control group, whereas the association was weak or even nonsignificant in the patient group. There was no significant main effect of group.

Conclusion

The waking activity of a neural pathway containing the aINS, putamen, and thalamus may underlie sleep perception, potentially providing important perspectives to reveal complex mechanisms of sleep discrepancy between self-report and PSG.

Effect of trazodone versus cognitive-behavioural treatment on high- and slow-frequency activity during non-rapid eye movement sleep in chronic insomnia: A pilot, randomized clinical trial

Trazodone and cognitive-behavioural treatment for insomnia (CBT-I) are widely used to treat patients with chronic insomnia. Although both treatments improve sleep continuity, no study has compared their comparative effectiveness in modifying spectral electroencephalographic (EEG) activity during sleep in humans. In this study, participants included 19 men and women with chronic insomnia who were randomized to either trazodone (n = 8) or CBT-I (n = 11) treatment for 3 months. We examined delta (0.39-3.91 Hz), theta (4.30-7.81 Hz), alpha (8.20-11.72 Hz), sigma (12.11-14.84 Hz), beta (15.23-35.16 Hz) and gamma (35.55-49.61 Hz) relative power during non-rapid eye movement (NREM) sleep at pre-treatment, 3- month post-treatment and 6-month follow-up. This study was registered in Clinical Trials (NCT01348542). We found trazodone but not CBT-I significantly decreased sigma (p = .041, d = 0.88; time × group p = .009) and beta (p = .005, d = 1.41; time × group p = .016) power during NREM sleep at post-treatment. Compared to CBT-I, trazodone increased delta (p = .018) and decreased sigma (p = .013) and beta (p = .023) power during NREM sleep at post-treatment. At follow-up, we did not observe significant changes in relative EEG power during NREM sleep in either the CBT-I or trazodone group compared to pre-treatment. Compared to CBT-I, trazodone decreased alpha (p = .039) and sigma (p = .009) power during NREM sleep at follow-up. In conclusion, trazodone, but not CBT-I, decreased fast-frequency EEG activity during NREM sleep. Compared to CBT-I, trazodone appears to have a stronger impact on cortical and physiological hyperarousal in patients with chronic insomnia.

Alterations in sleep electroencephalography synchrony in combat-exposed veterans with post-traumatic stress disorder

STUDY OBJECTIVES

We assessed whether the synchrony between brain regions, analyzed using electroencephalography (EEG) signals recorded during sleep, is altered in subjects with post-traumatic stress disorder (PTSD) and whether the results are reproducible across consecutive nights and subpopulations of the study.

METHODS

A total of 78 combat-exposed veteran men with (n = 31) and without (n = 47) PTSD completed two consecutive laboratory nights of high-density EEG recordings. We computed a measure of synchrony for each EEG channel-pair across three sleep stages (rapid eye movement [REM] and non-REM stages 2 and 3) and six frequency bands. We examined the median synchrony in 9 region-of-interest (ROI) pairs consisting of 6 bilateral brain regions (left and right frontal, central, and parietal regions) for 10 frequency-band and sleep-stage combinations. To assess reproducibility, we used the first 47 consecutive subjects (18 with PTSD) for initial discovery and the remaining 31 subjects (13 with PTSD) for replication.

RESULTS

In the discovery analysis, five alpha-band synchrony pairs during non-REM sleep were consistently larger in PTSD subjects compared with controls (effect sizes ranging from 0.52 to 1.44) across consecutive nights: two between the left-frontal and left-parietal ROIs, one between the left-central and left-parietal ROIs, and two across central and parietal bilateral ROIs. These trends were preserved in the replication set.

CONCLUSION

PTSD subjects showed increased alpha-band synchrony during non-REM sleep in the left frontoparietal, left centro-parietal, and inter-parietal brain regions. Importantly, these trends were reproducible across consecutive nights and subpopulations. Thus, these alterations in alpha synchrony may be discriminatory of PTSD.

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

Insomnia disorder (ID) has become the second-most common mental disorder. Despite burgeoning evidence for increased high-frequency electroencephalography (EEG) activity and cortical hyperarousal in ID, the detailed spectral features of this disorder during wakefulness and different sleep stages remain unclear. Therefore, we adopted a meta-analytic approach to systematically assess existing evidence on EEG spectral features in ID. Hedges's g was calculated by 148 effect sizes from 24 studies involving 977 participants. Our results demonstrate that, throughout wakefulness and sleep, patients with ID exhibited increased beta band power, although such increases sometimes extended into neighboring frequency bands. Patients with ID also exhibited increased theta and gamma power during wakefulness, as well as increased alpha and sigma power during rapid eye movement (REM) sleep. In addition, ID was associated with decreased delta power and increased theta, alpha, and sigma power during NREM sleep. The EEG measures of absolute and relative power have similar sensitivity in detecting spectral features of ID during wakefulness and REM sleep; however, relative power appeared to be a more sensitive biomarker during NREM sleep. Our study is the first statistics-based review to quantify EEG power spectra across stages of sleep and wakefulness in patients with ID.

Patterns of Intrahemispheric EEG Asymmetry in Insomnia Sufferers: An Exploratory Study

Individuals with insomnia present unique patterns of electroencephalographic (EEG) asymmetry between homologous regions of each brain hemisphere, yet few studies have assessed asymmetry within the same hemisphere. Increase in intrahemispheric asymmetry during rapid eye movement (REM) sleep in good sleepers (GS) and disruption of REM sleep in insomnia sufferers (INS) both point out that this activity may be involved in the pathology of insomnia. The objective of the present exploratory study was to evaluate and quantify patterns of fronto-central, fronto-parietal, fronto-occipital, centro-parietal, centro-occipital and parieto-occipital intrahemispheric asymmetry in GS and INS, and to assess their association with sleep-wake misperception, daytime anxiety and depressive symptoms, as well as insomnia severity. This paper provides secondary analysis of standard EEG recorded in 43 INS and 19 GS for three nights in a sleep laboratory. Asymmetry measures were based on EEG power spectral analysis within 0.3–60 Hz computed between pairs of regions at frontal, central, parietal and occipital derivations. Repeated-measures ANOVAs were performed to assess group differences. Exploratory correlations were then performed on asymmetry and sleep-wake misperception, as well as self-reported daytime anxiety and depressive symptoms, and insomnia severity. INS presented increased delta and theta F3/P3 asymmetry during REM sleep compared with GS, positively associated with depressive and insomnia complaints. INS also exhibited decreased centro-occipital (C3/O1, C4/O2) and parieto-occipital (P3–O1, P4/O2) theta asymmetry during REM. These findings suggest that INS present specific patterns of intrahemispheric asymmetry, partially related to their clinical symptoms. Future studies may investigate the extent to which asymmetry is related to sleep-wake misperception or memory impairments.

Enhanced Vigilance Stability during Daytime in Insomnia Disorder

Central nervous hyperarousal is as a key component of current pathophysiological concepts of chronic insomnia disorder. However, there are still open questions regarding its exact nature and the mechanisms linking hyperarousal to sleep disturbance. Here, we aimed at studying waking state hyperarousal in insomnia by the perspective of resting-state vigilance dynamics. The VIGALL (Vigilance Algorithm Leipzig) algorithm has been developed to investigate resting-state vigilance dynamics, and it revealed, for example, enhanced vigilance stability in depressive patients. We hypothesized that patients with insomnia also show a more stable vigilance regulation. Thirty-four unmedicated patients with chronic insomnia and 25 healthy controls participated in a twenty-minute resting-state electroencephalography (EEG) measurement following a night of polysomnography. Insomnia patients showed enhanced EEG vigilance stability as compared to controls. The pattern of vigilance hyperstability differed from that reported previously in depressive patients. Vigilance hyperstability was also present in insomnia patients showing only mildly reduced sleep efficiency. In this subgroup, vigilance hyperstability correlated with measures of disturbed sleep continuity and arousal. Our data indicate that insomnia disorder is characterized by hyperarousal at night as well as during daytime.

Daytime Neurophysiological Hyperarousal in Chronic Insomnia: A Study of qEEG

Background: The hyperarousal model demonstrates that instability of sleep-wake regulation leads to insomnia symptoms and various neurophysiological hyperarousal states. Previous studies have shown that hyperarousal states that appear in chronic insomnia patients are not limited to sleep at nighttime but are stable characteristics that extend into the daytime. However, this phenomenon is mainly measured at bedtime, so it hard to determine whether it is maintained throughout a 24 h cycle or if it just appears at bedtime. Methods: We examined the resting state qEEG (quantitative electroencephalogram) and ECG (electrocardiogram) of chronic insomnia patients (n = 24) compared to good sleepers (n = 22) during the daytime. Results: As compared with controls, participants with insomnia showed a clearly high beta band activity in eyes closed condition at all brain areas. They showed a low frequency band at the frontal area; high frequency bands at the central and parietal areas were found in eyes open condition. Significantly higher heart rates were also found in the chronic insomnia group. Conclusion: These findings suggest that chronic insomnia patients were in a state of neurophysiological hyperarousal during the middle of the day due to abnormal arousal regulation.

Assessment of nonnegative matrix factorization algorithms for electroencephalography spectral analysis

BACKGROUND

Nonnegative matrix factorization (NMF) has been successfully used for electroencephalography (EEG) spectral analysis. Since NMF was proposed in the 1990s, many adaptive algorithms have been developed. However, the performance of their use in EEG data analysis has not been fully compared. Here, we provide a comparison of four NMF algorithms in terms of accuracy of estimation, stability (repeatability of the results) and time complexity of algorithms with simulated data. In the practical application of NMF algorithms, stability plays an important role, which was an emphasis in the comparison. A Hierarchical clustering algorithm was implemented to evaluate the stability of NMF algorithms.

RESULTS

In simulation-based comprehensive analysis of fit, stability, accuracy of estimation and time complexity, hierarchical alternating least squares (HALS) low-rank NMF algorithm (lraNMF_HALS) outperformed the other three NMF algorithms. In the application of lraNMF_HALS for real resting-state EEG data analysis, stable and interpretable features were extracted.

CONCLUSION

Based on the results of assessment, our recommendation is to use lraNMF_HALS, providing the most accurate and robust estimation.

Differences in electroencephalographic spectra during pre-sleep wakefulness, N1, and R sleep between comorbid insomnia and obstructive sleep apnea

PURPOSE

The neuropsychobiological effects of the comorbidity of insomnia and obstructive sleep apnea are not well studied. Our objective was to compare electroencephalographic spectra of patients with comorbid insomnia and sleep apnea syndrome to those of patients with sleep apnea syndrome alone during pre-sleep wakefulness and the N1 and R sleep periods.

METHOD

We performed electroencephalography and polysomnography on 10 patients with comorbid insomnia and sleep apnea and 10 with only sleep apnea. Electroencephalography spectra analysis was performed for absolute power in clinical bands in six derivations.

RESULTS

Compared to sleep apnea patients, comorbid patients had lower sleep efficiency and total sleep time, higher beta-1 power in the left frontal and central derivations during pre-sleep wakefulness, higher delta power in the left frontal and central derivations during the N1 stage, and higher beta-2 power in the left frontal and central, and right central derivations during the R stage.

CONCLUSIONS

Data suggest that patients with insomnia and sleep apnea, compared to patients with only sleep apnea, presented higher left high-frequency rhythms during pre-sleep wakefulness and R sleep stage, and may be for increased emotional and cognitive-related activity, while in stage N1, presented higher left delta power, which suggest some slowing after sleep deprivation.

Mechanism of excessive wake time when associated with obstructive sleep apnea or periodic limb movements

STUDY OBJECTIVES

It is uncertain whether obstructive apnea (OSA) or periodic limb movements (PLMs) contribute to excessive wake time (EWT) when EWT and these disorders coexist. We hypothesized that such EWT is an independent disorder related to central regulation of sleep depth. Accordingly, we compared sleep depth in patients with EWT and OSA/PLMs (EWT+P) with patients with EWT and no OSA/PLMs (EWT-NP) and patients with a normal wake time.

METHODS

A total of 267 participants were divided into five groups: (1) EWT+P: n = 100 (wake time > 20% total recording time; TRT) with OSA (apnea-hypopnea index 5-110 events/h) and/or PLMs (PLM index 10-151 events/h); (2) EWT-NP: n = 49 (wake time > 20%TRT), no associated pathology; (3) normal wake time (NWT)+P: n = 54 (wake time < 20%TRT, with OSA/PLMs); (4) NWT-NP: n = 26; (5) Healthy participants: n = 38 (no sleep complaints, NWT and no OSA/PLMs). Sleep depth was evaluated by the odds ratio product (ORP; 0 = deep sleep, 2.5 = fully alert). We also measured ORP in the 9 seconds immediately following arousals (ORP-9) to distinguish between peripheral and central mechanisms of light sleep.

RESULTS

ORP during sleep was higher (lighter sleep) in both EWT groups than in the three NWT groups (P < 1E-11) with no difference between those with and those without OSA/PLMs. ORP-9 was also significantly higher in the EWT groups than in the NWT groups (P < 1E-19), also with no difference between those with and without OSA/PLMs, indicating that the lighter sleep was of central origin. There were highly significant correlations between wake time and ORP-9 across all groups (P < 1E-35).

CONCLUSIONS

EWT associated with OSA/PLMs is independent of OSA/PLMs and related to abnormal central regulation of sleep depth.

Identification of Veterans With PTSD Based on EEG Features Collected During Sleep

Background: Previously, we identified sleep-electroencephalography (EEG) spectral power and synchrony features that differed significantly at a population-average level between subjects with and without posttraumatic stress disorder (PTSD). Here, we aimed to examine the extent to which a combination of such features could objectively identify individual subjects with PTSD. Methods: We analyzed EEG data recorded from 78 combat-exposed Veteran men with (n = 31) and without (n = 47) PTSD during two consecutive nights of sleep. To obviate the need for manual assessment of sleep staging and facilitate extraction of features from the EEG data, for each subject, we computed 780 stage-independent, whole-night features from the 10 most commonly used EEG channels. We performed feature selection and trained a logistic regression model using a training set consisting of the first 47 consecutive subjects (18 with PTSD) of the study. Then, we evaluated the model on a testing set consisting of the remaining 31 subjects (13 with PTSD). Results: Feature selection yielded three uncorrelated features that were consistent across the two consecutive nights and discriminative of PTSD. One feature was from the spectral power in the delta band (2-4 Hz) and the other two were from phase synchronies in the alpha (10-12 Hz) and gamma (32-40 Hz) bands. When we combined these features into a logistic regression model to predict the subjects in the testing set, the trained model yielded areas under the receiver operating characteristic curve of at least 0.80. Importantly, the model yielded a testing-set sensitivity of 0.85 and a positive predictive value (PPV) of 0.31. Conclusions: We identified robust stage-independent, whole-night features from EEG signals and combined them into a logistic regression model to discriminate subjects with and without PTSD. On the testing set, the model yielded a high sensitivity and a PPV that was twice the prevalence rate of PTSD in the U.S. Veteran population. We conclude that, using EEG signals collected during sleep, such a model can potentially serve as a means to objectively identify U.S. Veteran men with PTSD.

Altered modulation of beta band oscillations during memory encoding is predictive of lower subsequent recognition performance in post-traumatic stress disorder

We studied the relationship between electrophysiological markers of memory encoding, subsequent recognition performance, and severity of PTSD symptoms in service members with combat exposure (n = 40, age: 41.2 ± 7.2 years) and various levels of PTSD symptom severity assessed using the PTSD Check List for DSM V version (PCL-5). Brain activity was recorded using magnetoencephalography during a serial presentation of 86 images of outdoor scenes that were studied by participants for an upcoming recognition test. In a second session, the original images were shown intermixed with an equal number of novel images while participants performed the recognition task. Participants recognized 76.0% ± 12.1% of the original images and correctly categorized as novel 89.9% ± 7.0% of the novel images. A negative correlation was present between PCL-5 scores and discrimination performance (Spearman rs = -0.38, p = 0.016). PCL-5 scores were also negatively correlated with the recognition accuracy for original images (rs = -0.37, p = 0.02). Increases in theta and gamma power and decreases in alpha and beta power were observed over distributed brain networks during memory encoding. Higher PCL-5 scores were associated with less suppression of beta band power in bilateral ventral and medial temporal regions and in the left orbitofrontal cortex. These regions also showed positive correlations between the magnitude of suppression of beta power during encoding and subsequent recognition accuracy. These findings indicate that the lower recognition performance in participants with greater PTSD symptom severity may be due in part to ineffective encoding reflected in altered modulation of beta band oscillatory activity.

Childhood high-frequency EEG activity during sleep is associated with incident insomnia symptoms in adolescence

BACKGROUND

Insomnia has been associated in cross-sectional studies with increased beta (15-35 Hz) electroencephalogram (EEG) power during nonrapid eye movement (NREM) sleep, an index of cortical hyperarousal. However, it is unknown whether this cortical hyperarousal is present before individuals with insomnia develop the disorder. To fill this gap, we examined the association of childhood sleep high-frequency EEG activity with incident insomnia symptoms (i.e., absence of insomnia symptoms in childhood but presence in adolescence).

METHODS

We studied a case-control subsample of 45 children (6-11 years) from the Penn State Child Cohort, a population-based random sample of 421 children, who were followed up after 8 years as adolescents (13-20 years). We examined low-beta (15-25 Hz) and high-beta (25-35 Hz) relative power at central EEG derivations during NREM sleep and, in secondary analyses, during sleep onset latency, sleep onset, and REM sleep. Incident insomnia symptoms were defined as the absence of parent-reported difficulty falling and/or staying asleep during childhood and a self-report of these insomnia symptoms during adolescence.

RESULTS

Childhood high-beta power during NREM sleep was significantly increased in children who developed insomnia symptoms in adolescence (n = 25) as compared to normal sleeping controls (n = 20; p = .03). Multivariable-adjusted logistic regression models showed that increased childhood high-beta EEG power during NREM sleep was associated with a threefold increased odds (95% CI = 1.12-7.98) of incident insomnia symptoms in adolescence. No other significant relationships were observed for other sleep/wake states or EEG frequency bands.

CONCLUSIONS

Increased childhood high-frequency EEG power during NREM sleep is associated with incident insomnia symptoms in adolescence. This study indicates that cortical hyperarousal during sleep may be a premorbid neurophysiological sign of insomnia, which may mediate the increased risk of psychiatric disorders associated with insomnia.

Clinical and Electrophysiological Differences between Subjects with Dysphonetic Dyslexia and Non-Specific Reading Delay

Reading is essentially a two-channel function, requiring the integration of intact visual and auditory processes both peripheral and central. It is essential for normal reading that these component processes go forward automatically. Based on this model, Boder described three main subtypes of dyslexia: dysphonetic dyslexia (DD), dyseidetic, mixed and besides a fourth group defined non-specific reading delay (NSRD). The subtypes are identified by an algorithm that considers the reading quotient and the % of errors in the spelling test. Chiarenza and Bindelli have developed the Direct Test of Reading and Spelling (DTRS), a computerized, modified and validated version to the Italian language of the Boder test. The sample consisted of 169 subjects with DD and 36 children with NSRD. The diagnosis of dyslexia was made according to the DSM-V criteria. The DTRS was used to identify the dyslexia subtypes and the NSRD group. 2⁻5 min of artefact-free EEG (electroencephalogram), recorded at rest with eyes closed, according to 10⁻20 system were analyzed. Stability based Biomarkers identification methodology was applied to the DTRS and the quantitative EEG (QEEG). The reading quotients and the errors of the reading and spelling test were significantly different in the two groups. The DD group had significantly higher activity in delta and theta bands compared to NSRD group in the frontal, central and parietal areas bilaterally. The classification equation for the QEEG, both at the scalp and the sources levels, obtained an area under the robust Receiver Operating Curve (ROC) of 0.73. However, we obtained a discrimination equation for the DTRS items which did not participate in the Boder classification algorithm, with a specificity and sensitivity of 0.94 to discriminate DD from NSRD. These results demonstrate for the first time the existence of different neuropsychological and neurophysiological patterns between children with DD and children with NSRD. They may also provide clinicians and therapists warning signals deriving from the anamnesis and the results of the DTRS that should lead to an earlier diagnosis of reading delay, which is usually very late diagnosed and therefore, untreated until the secondary school level.

Hyperarousal and Beyond: New Insights to the Pathophysiology of Insomnia Disorder through Functional Neuroimaging Studies

Neuroimaging studies have produced seemingly contradictory findings in regards to the pathophysiology of insomnia. Although most study results are interpreted from the perspective of a "hyperarousal" model, the aggregate findings from neuroimaging studies suggest a more complex model is needed. We provide a review of the major findings from neuroimaging studies, then discuss them in relation to a heuristic model of sleep-wake states that involves three major factors: wake drive, sleep drive, and level of conscious awareness. We propose that insomnia involves dysregulation in these factors, resulting in subtle dysregulation of sleep-wake states throughout the 24 h light/dark cycle.

More Severe Insomnia Complaints in People with Stronger Long-Range Temporal Correlations in Wake Resting-State EEG

The complaints of people suffering from Insomnia Disorder (ID) concern both sleep and daytime functioning. However, little is known about wake brain temporal dynamics in people with ID. We therefore assessed possible alterations in Long-Range Temporal Correlations (LRTC) in the amplitude fluctuations of band-filtered oscillations in electroencephalography (EEG) recordings. We investigated whether LRTC differ between cases with ID and matched controls. Within both groups, we moreover investigated whether individual differences in subjective insomnia complaints are associated with LRTC. Resting-state high-density EEG (256-channel) was recorded in 52 participants with ID and 43 age- and sex-matched controls, during Eyes Open (EO) and Eyes Closed (EC). Detrended fluctuation analysis was applied to the amplitude envelope of band-filtered EEG oscillations (theta, alpha, sigma, beta-1, beta-2) to obtain the Hurst exponents (H), as measures of LRTC. Participants rated their subjective insomnia complaints using the Insomnia Severity Index (ISI). Through general linear models, we evaluated whether H, aggregated across electrodes and frequencies, differed between cases and controls, or showed within-group associations with individual differences in ISI. Additionally, we characterized the spatio-spectral profiles of group differences and associations using non-parametric statistics. H did not differ between cases with ID and controls in any of the frequency bands, neither during EO nor EC. During EO, however, within-group associations between H and ISI indicated that individuals who experienced worse sleep quality had stronger LRTC. Spatio-spectral profiles indicated that the associations held most prominently for the amplitude fluctuations of parietal theta oscillations within the ID group, and of centro-frontal beta-1 oscillations in controls. While people suffering from insomnia experience substantially worse sleep quality than controls, their brain dynamics express similar strength of LRTC. In each group, however, individuals experiencing worse sleep quality tend to have stronger LRTC during eyes open wakefulness, in a spatio-spectral range specific for each group. Taken together, the findings indicate that subjective insomnia complaints involve distinct dynamical processes in people with ID and controls. The findings are in agreement with recent reports on decreasing LRTC with sleep depth, and with the hypothesis that sleep balances brain excitability.

Sleep-Wake Differences in Relative Regional Cerebral Metabolic Rate for Glucose among Patients with Insomnia Compared with Good Sleepers

STUDY OBJECTIVES

The neurobiological mechanisms of insomnia may involve altered patterns of activation across sleep-wake states in brain regions associated with cognition, self-referential processes, affect, and sleep-wake promotion. The objective of this study was to compare relative regional cerebral metabolic rate for glucose (rCMRglc) in these brain regions across wake and nonrapid eye movement (NREM) sleep states in patients with primary insomnia (PI) and good sleeper controls (GS).

METHODS

Participants included 44 PI and 40 GS matched for age (mean = 37 y old, range 21-60), sex, and race. We conducted [18F]fluoro-2-deoxy-D-glucose positron emission tomography scans in PI and GS during both morning wakefulness and NREM sleep at night. Repeated measures analysis of variance was used to test for group (PI vs. GS) by state (wake vs. NREM sleep) interactions in relative rCMRglc.

RESULTS

Significant group-by-state interactions in relative rCMRglc were found in the precuneus/posterior cingulate cortex, left middle frontal gyrus, left inferior/superior parietal lobules, left lingual/fusiform/occipital gyri, and right lingual gyrus. All clusters were significant at Pcorrected < 0.05.

CONCLUSIONS

Insomnia was characterized by regional alterations in relative glucose metabolism across NREM sleep and wakefulness. Significant group-by-state interactions in relative rCMRglc suggest that insomnia is associated with impaired disengagement of brain regions involved in cognition (left frontoparietal), self-referential processes (precuneus/posterior cingulate), and affect (left middle frontal, fusiform/lingual gyri) during NREM sleep, or alternatively, to impaired engagement of these regions during wakefulness.

Insomnia is Associated with Cortical Hyperarousal as Early as Adolescence

STUDY OBJECTIVES

To examine whether insomnia is associated with spectral electroencephalographic (EEG) dynamics in the beta (15-35Hz) range during sleep in an adolescent general population sample.

METHODS

A case-control sample of 44 adolescents from the Penn State Child Cohort underwent a 9-h polysomnography, clinical history and physical examination. We examined low-beta (15-25 Hz) and high-beta (25-35 Hz) relative power at central EEG derivations during sleep onset latency (SOL), sleep onset (SO), non-rapid eye movement (NREM) sleep, and wake after sleep onset (WASO).

RESULTS

Compared to controls (n = 21), individuals with insomnia (n = 23) showed increased SOL and WASO and decreased sleep duration and efficiency, while no differences in sleep architecture were found. Insomniacs showed increased low-beta and high-beta relative power during SOL, SO, and NREM sleep as compared to controls. High-beta relative power was greater during all sleep and wake states in insomniacs with short sleep duration as compared to individuals with insomnia with normal sleep duration.

CONCLUSIONS

Adolescent insomnia is associated with increased beta EEG power during sleep, which suggests that cortical hyperarousal is present in individuals with insomnia as early as adolescence. Interestingly, cortical hyperarousal is greatest in individuals with insomnia with short sleep duration and may explain the sleep complaints of those with normal sleep duration. Disturbed cortical networks may be a shared mechanism putting individuals with insomnia at risk of psychiatric disorders.

Wake High-Density Electroencephalographic Spatiospectral Signatures of Insomnia

STUDY OBJECTIVES

Although daytime complaints are a defining characteristic of insomnia, most EEG studies evaluated sleep only. We used high-density electroencephalography to investigate wake resting state oscillations characteristic of insomnia disorder (ID) at a fine-grained spatiospectral resolution.

METHODS

A case-control assessment during eyes open (EO) and eyes closed (EC) was performed in a laboratory for human physiology. Participants (n = 94, 74 female, 21-70 y) were recruited through www.sleepregistry.nl: 51 with ID, according to DSM-5 and 43 matched controls. Exclusion criteria were any somatic, neurological or psychiatric condition. Group differences in the spectral power topographies across multiple frequencies (1.5 to 40 Hz) were evaluated using permutation-based inference with Threshold-Free Cluster-Enhancement, to correct for multiple comparisons.

RESULTS

As compared to controls, participants with ID showed less power in a narrow upper alpha band (11-12.7 Hz, peak: 11.7 Hz) over bilateral frontal and left temporal regions during EO, and more power in a broad beta frequency range (16.3-40 Hz, peak: 19 Hz) globally during EC. Source estimates suggested global rather than cortically localized group differences.

CONCLUSIONS

The widespread high power in a broad beta band reported previously during sleep in insomnia is present as well during eyes closed wakefulness, suggestive of a round-the-clock hyperarousal. Low power in the upper alpha band during eyes open is consistent with low cortical inhibition and attentional filtering. The fine-grained HD-EEG findings suggest that, while more feasible than PSG, wake EEG of short duration with a few well-chosen electrodes and frequency bands, can provide valuable features of insomnia.

Regional Patterns of Elevated Alpha and High-Frequency Electroencephalographic Activity during Nonrapid Eye Movement Sleep in Chronic Insomnia: A Pilot Study

STUDY OBJECTIVES

To examine nonrapid eye movement (NREM) sleep in insomnia using high-density electroencephalography (EEG).

METHODS

All-night sleep recordings with 256 channel high-density EEG were analyzed for 8 insomnia subjects (5 females) and 8 sex and age-matched controls without sleep complaints. Spectral analyses were conducted using unpaired t-tests and topographical differences between groups were assessed using statistical non-parametric mapping. Five minute segments of deep NREM sleep were further analyzed using sLORETA cortical source imaging.

RESULTS

The initial topographic analysis of all-night NREM sleep EEG revealed that insomnia subjects had more high-frequency EEG activity (> 16 Hz) compared to good sleeping controls and that the difference between groups was widespread across the scalp. In addition, the analysis also showed that there was a more circumscribed difference in theta (4-8 Hz) and alpha (8-12 Hz) power bands between groups. When deep NREM sleep (N3) was examined separately, the high-frequency difference between groups diminished, whereas the higher regional alpha activity in insomnia subjects persisted. Source imaging analysis demonstrated that sensory and sensorimotor cortical areas consistently exhibited elevated levels of alpha activity during deep NREM sleep in insomnia subjects relative to good sleeping controls.

CONCLUSIONS

These results suggest that even during the deepest stage of sleep, sensory and sensorimotor areas in insomnia subjects may still be relatively active compared to control subjects and to the rest of the sleeping brain.

Waking EEG signs of non-restoring sleep in primary insomnia patients

OBJECTIVE

Subjective feelings of insufficient and non-restorative sleep are core symptoms of primary insomnia. Sleep has a restorative effect on next-day waking EEG activity, whereas sleep loss has non-restorative effects in good sleepers. We proposed to explore waking EEG activity in primary insomniacs the evening before, and the morning after, a night of sleep, in order to detect signs of morning hyper-arousal and non-restoring sleep that might explain the subjective feelings despite the absence of objective signs in polysomnography.

METHOD

Pre-sleep (10 pm) and post-sleep (10 am) waking EEG activity was analyzed in 10 non-medicated primary insomniacs and matched control subjects. Beta and Gamma absolute power and EEG temporal coupling were obtained. Participants also evaluated subjective sleep quantity and quality.

RESULTS

Insomnia patients evaluated their sleep as non-restorative and insufficient. Compared to pre-sleep, during post-sleep control subjects exhibited significantly decreased Beta and Gamma power and reduced synchronization among anterior and posterior regions, consistent with restoring effects of sleep. Insomnia patients showed no beneficial effects of sleep on these EEG parameters.

CONCLUSION

Insomniacs are hyper-aroused during morning wakefulness and they do not benefit from preceding sleep.

SIGNIFICANCE

Our study adds new knowledge to our understanding of the physiopathology of insomnia.

The pathophysiology of insomnia

Insomnia disorder is characterized by chronic dissatisfaction with sleep quantity or quality that is associated with difficulty falling asleep, frequent nighttime awakenings with difficulty returning to sleep, and/or awakening earlier in the morning than desired. Although progress has been made in our understanding of the nature, etiology, and pathophysiology of insomnia, there is still no universally accepted model. Greater understanding of the pathophysiology of insomnia may provide important information regarding how, and under what conditions, the disorder develops and is maintained as well as potential targets for prevention and treatment. The aims of this report are (1) to summarize current knowledge on the pathophysiology of insomnia and (2) to present a model of the pathophysiology of insomnia that considers evidence from various domains of research. Working within several models of insomnia, evidence for the pathophysiology of the disorder is presented across levels of analysis, from genetic to molecular and cellular mechanisms, neural circuitry, physiologic mechanisms, sleep behavior, and self-report. We discuss the role of hyperarousal as an overarching theme that guides our conceptualization of insomnia. Finally, we propose a model of the pathophysiology of insomnia that integrates the various types of evidence presented.

Insomnia and its impact on physical and mental health

In contrast to the association of insomnia with mental health, its association with physical health has remained largely unexplored until recently. Based on findings that insomnia with objective short sleep duration is associated with activation of both limbs of the stress system and other indices of physiological hyperarousal, which should adversely affect physical and mental health, we have recently demonstrated that this insomnia phenotype is associated with a significant risk of cardiometabolic and neurocognitive morbidity and mortality. In contrast, insomnia with normal sleep duration is associated with sleep misperception and cognitive-emotional arousal, but not with signs of physiological hyperarousal or cardiometabolic or neurocognitive morbidity. Interestingly, both insomnia phenotypes are associated with mental health, although most likely through different pathophysiological mechanisms. We propose that objective measures of sleep duration may become part of the routine evaluation and diagnosis of insomnia, and that these two insomnia phenotypes may respond differentially to biological versus psychological treatments.

Insomnia with Short Sleep Duration: Nosological, Diagnostic, and Treatment Implications

The diagnosis of insomnia is based solely on subjective complaints. This has contributed to the low reliability and validity of the current nosology of insomnia as well as to its lack of firm association with clinically relevant outcomes such as cardiometabolic and neurocognitive morbidity. We review evidence that insomnia with objective short sleep duration is associated with physiological hyperarousal, higher risk for hypertension, diabetes, neurocognitive impairment, and mortality as well as with a persistent course. It also appears that objective short sleep duration in poor sleepers is a biological marker of genetic predisposition to chronic insomnia. In contrast, insomnia with objective normal sleep duration is associated with cognitive-emotional and cortical arousal and sleep misperception but not with signs of physiological hyperarousal or medical complications. Thus, short sleep duration in insomnia may be a reliable marker of the biological severity and medical impact of the disorder. We propose that (a) objective measures of sleep be included in the diagnosis of insomnia and its subtypes, (b) objective measures of sleep obtained in the home environment of the patient would become part of the routine assessment and diagnosis of insomnia in a clinician's office setting, and (c) insomnia with short sleep duration may respond better to biological treatments, whereas insomnia with normal sleep duration may respond primarily to psychological therapies.

Psychological functioning measures in patients with primary insomnia and sleep state misperception

OBJECTIVE

Sleep state misperception (SSM) is a term used in the International Classification of Sleep Disorders to indicate people who mistakenly perceive their sleep as wakefulness. SSM is a form of primary insomnia. The aim of this study was to record psychological functioning measures (anxiety, depression, ability to feel pleasure, obsessive-compulsive traits) in a population of patients with primary insomnia and to evaluate the relationship between these measures and the patients' perception of their sleep.

MATERIALS AND METHODS

Seventy-six consecutive patients with primary insomnia were enrolled: 34 men and 42 women, mean age 53.9 ± 13.1. Sleep study included the following: Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, Berlin's Questionnaire and home-based polysomnography. Psychometric evaluation included the following: Self-Administered Anxiety Scale, Beck's Depression Inventory, Maudsley's Obsessive Compulsive Inventory, Snaith-Hamilton Pleasure Scale, Eating Attitude Test.

RESULTS

All patients with insomnia had psychometric scores higher than the general population, but very few patients, in both groups, had anxiety or depression scores consistent with severe mood or anxiety disorders. Comparisons between subjective and objective scores confirmed that most sleep parameters were underestimated. Patients with SSM had lower anxiety scores as compared to patients without SSM.

CONCLUSIONS

The study did not succeed in identifying any predictor of sleep misperception. We speculate that a group of patients, rather than being extremely worried by their insomnia, may have a sort of agnosia of their sleep.

The pathophysiology of insomnia: from models to molecules (and back)

PURPOSE OF REVIEW

To provide an overview of foundational theories on the psychosocial and neurobiological mechanisms that underlie the pathophysiology of insomnia, a review of recent findings from across the spectrum of sleep sciences that are germane to conceptualizations of insomnia, and how such findings contribute to newer integrative models.

RECENT FINDINGS

Recent findings come from a broad diversity of the sleep research spectrum including basic animal science, sleep neuroscience, especially sleep-wake regulation, psychoneuroimmunology, human genetics, epidemiology, psychology, and from the clinical research realm.

SUMMARY

Our review focuses on the factors contributing to insomnia and to its maintenance over time as well as the theoretical models developed (and developing) to explain this pathophysiology. Early theoretical contributions have provided a backbone for insomnia research; the sleep sciences, in turn, have supported novel and increasingly complex theoretical models of insomnia. The overarching contention is that integrative models are needed that are fully comprehensive in scope.