Sleep EEG spectral power is correlated with subjective-objective discrepancy of sleep onset latency in major depressive disorder

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.

Correlation Between Sleep Electroencephalogram, Brain-Derived Neurotrophic Factor, AVPR1B Gene Polymorphism, and Suicidal Behavior in Patients with Depression

The purpose of this article was to investigate the level of serum brain-derived neurotrophic factor and its relationship with suicidal symptoms and severity in mentally ill suicide attempt patients, and to explore the possible role of serum brain-derived neurotrophic factor (BDNF) in the occurrence of psychotic suicidal behavior. A retrospective analysis was performed on patients with depression in the neurology department of a hospital. General physical examination, neurological specialist examination, and cranial magnetic resonance imaging (MRI) examination were performed on any selected group. We applied the 24-item Hamilton Depression Scale, Hamilton Anxiety Scale, and Mini-Intelligence Mental State Scale, and performed polysomnography and electroencephalography (EEG) monitoring to conduct statistical analysis on sleep indicators. The amplitude of low-frequency fluctuation (ALFF) values of the right frontal gyrus, left posterior cerebellar lobe, right anterior cerebellar lobe, and right occipital lingual gyrus of the patient group were significantly lower than those of the control group. The ReHo values of the right superior parietal lobule, the left precuneus, and the right occipital lingual gyrus were significantly higher than those of the control group. The genotype and allele frequency distribution of FKBP5, AVPR1B, and CRHR2 gene SNPs had no significant difference between the case group and the control group (P > 0.05). The ReHo value of the precuneus is significantly correlated with the proportion of N3 sleep, and the dysfunction of the precuneus or default network may be related to the altered sleep structure in patients with depression. The GT and TT genotypes at rs9324924 of the NR3C1 gene are associated with suicide attempts.

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.

Insomnia subtypes characterised by objective sleep duration and NREM spectral power and the effect of acute sleep restriction: an exploratory analysis

Insomnia disorder (ID) is a heterogeneous disorder with proposed subtypes based on objective sleep duration. We speculated that insomnia subtyping with additional power spectral analysis and measurement of response to acute sleep restriction may be informative in overall assessment of ID. To explore alternative classifications of ID subtypes, insomnia patients (n = 99) underwent two consecutive overnight sleep studies: (i) habitual sleep opportunity (polysomnography, PSG) and, (ii) two hours less sleep opportunity (electroencephalography, EEG), with the first night compared to healthy controls (n = 25). ID subtypes were derived from data-driven classification of PSG, EEG spectral power and interhemispheric EEG asymmetry index. Three insomnia subtypes with different sleep duration and NREM spectral power were identified. One subtype (n = 26) had shorter sleep duration and lower NREM delta power than healthy controls (short-sleep delta-deficient; SSDD), the second subtype (n = 51) had normal sleep duration but lower NREM delta power than healthy controls (normal-sleep delta-deficient; NSDD) and a third subtype showed (n = 22) no difference in sleep duration or delta power from healthy controls (normal neurophysiological sleep; NNS). Acute sleep restriction improved multiple objective sleep measures across all insomnia subtypes including increased delta power in SSDD and NSDD, and improvements in subjective sleep quality for SSDD (p = 0.03), with a trend observed for NSDD (p = 0.057). These exploratory results suggest evidence of novel neurophysiological insomnia subtypes that may inform sleep state misperception in ID and with further research, may provide pathways for personalised care.

Profile of subjective-objective sleep discrepancy in patients with insomnia and sleep apnea

STUDY OBJECTIVES

Although subjective-objective sleep discrepancy has long been observed in patients with insomnia, the profiles of this discrepancy are poorly understood. Further, sleep discrepancy in insomnia with sleep comorbidities remains underexplored. We sought to better characterize sleep discrepancy among patient groups with and without insomnia and comorbid conditions such as obstructive sleep apnea (OSA).

METHODS

Using data from the Sleep Heart Health Study, we conducted a secondary analysis describing (1) the profile of self-reported and objective sleep measures in patients with insomnia (IS group; n = 73) and comorbid OSA (IS + OSA group; n = 143), compared with individuals with OSA only (OSA group; n = 296) and normal sleep control patients (NSC group; n = 126); (2) the comparative magnitude of sleep misperception between these 4 groups; and (3) the self-reported quality of life (QOL) in the 4 groups.

RESULTS

Subjective-objective sleep discrepancy existed in all 4 groups, including the NSC group. Controlling for age, sex, mental health conditions, sleep apnea severity, and objectively measured sleep time, the presence of self-reported insomnia had the strongest association with sleep discrepancy. In patients with insomnia, sleep onset latency was overestimated (7.8 ± 36.8 min in the IS group; P < .001 when compared to the NSC and OSA groups), with the largest differences seen in the comorbid IS + OSA group (15.0 ± 56.8 min). Insomnia conferred the most negative impact on QOL, with the combined IS + OSA group reporting the lowest QOL.

CONCLUSIONS

Self-reported insomnia is associated with sleep discrepancy and negative QOL. Those with comorbid OSA reported the greatest sleep discrepancy and the lowest QOL. Future research is warranted to further understand individual profiles of misperception and insomnia phenotypes.

CITATION

Ma Y, Goldstein MR, Davis RB, Yeh GY. Profile of subjective-objective sleep discrepancy in patients with insomnia and sleep apnea. J Clin Sleep Med. 2021;17(11):2155-2163.

Conscious experiences and high-density EEG patterns predicting subjective sleep depth

What accounts for feeling deeply asleep? Standard sleep recordings only incompletely reflect subjective aspects of sleep and some individuals with so-called sleep misperception frequently feel awake although sleep recordings indicate clear-cut sleep. To identify the determinants of sleep perception, we performed 787 awakenings in 20 good sleepers and 10 individuals with sleep misperception and interviewed them about their subjective sleep depth while they underwent high-density EEG sleep recordings. Surprisingly, in good sleepers, sleep was subjectively lightest in the first 2 h of non-rapid eye movement (NREM) sleep, generally considered the deepest sleep, and deepest in rapid eye movement (REM) sleep. Compared to good sleepers, sleep misperceptors felt more frequently awake during sleep and reported lighter REM sleep. At the EEG level, spatially widespread high-frequency power was inversely related to subjective sleep depth in NREM sleep in both groups and in REM sleep in misperceptors. Subjective sleep depth positively correlated with dream-like qualities of reports of mental activity. These findings challenge the widely held notion that slow wave sleep best accounts for feeling deeply asleep. Instead, they indicate that subjective sleep depth is inversely related to a neurophysiological process that predominates in early NREM sleep, becomes quiescent in REM sleep, and is reflected in high-frequency EEG activity. In sleep misperceptors, this process is more frequently active, more spatially widespread, and abnormally persists into REM sleep. These findings help identify the neuromodulatory systems involved in subjective sleep depth and are relevant for studies aiming to improve subjective sleep quality.

The Evolving Nexus of Sleep and Depression

Sleep disturbances and depression are closely linked and share a bidirectional relationship. These interconnections can inform the pathophysiology underlying each condition. Insomnia is an established and modifiable risk factor for depression, the treatment of which offers the critical opportunity to prevent major depressive episodes, a paradigm-shifting model for psychiatry. Identification of occult sleep disorders may also improve outcomes in treatment-resistant depression. Sleep alterations and manipulations may additionally clarify the mechanisms that underlie rapid-acting antidepressant therapies. Both sleep disturbance and depression are heterogeneous processes, and evolving standards in psychiatric research that consider the transdiagnostic components of each are more likely to lead to translational progress at their nexus. Emerging tools to objectively quantify sleep and its disturbances in the home environment offer great potential to advance clinical care and research, but nascent technologies require further advances and validation prior to widespread application at the interface of sleep and depression.

Spectral sleep electroencephalographic correlates of sleep efficiency, and discrepancies between actigraphy and self-reported measures, in older men

Discrepancies between actigraphic and self-reported sleep measures are common. Studies of people with insomnia, in whom both sleep disturbances and discrepancy are common, suggest disturbances and discrepancy reflect differences in the sleeping brain's activity measurable using spectral electroencephalogram (EEG). Disentangling effects of discrepancy and disturbance on sleep EEG could help target research on the consequences and treatments of different sleep phenotypes. We therefore categorized participants in a cohort study including 2,850 men (average age = 76 years, standard deviation = 5.5) into four groups using median splits on actigraphic and self-reported sleep efficiency (SE). We compared spectral power between these groups in 1-Hz bins up to 24 Hz. Compared with the concordant-high SE group: (a) the group with high actigraphic and low self-reported SE had higher spectral power from 11-15 Hz across the night; (b) both groups with low actigraphic SE had higher power across the 15-24 Hz range, predominantly in early cycles, and greater slow frequency power in later cycles. These findings suggest that perceived wakefulness undetected by actigraphy may result from or drive activity corresponding to spindles. We also found, consistent with hyperarousal models, that low SE detectable via actigraphy was related to higher frequency power in the beta range; actigraph-measured inefficiency was also associated with later slow oscillations, potentially representing attempts to dissipate homeostatic drive elevated from earlier hyperarousal. These distinct spectral EEG markers (of low SE measured with actigraphy vs. low perceived SE that is not captured by actigraphy) may have different causes or consequences.

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.

Electroencephalographic changes associated with subjective under- and overestimation of sleep duration

Feeling awake although sleep recordings indicate clear-cut sleep sometimes occurs in good sleepers and to an extreme degree in patients with so-called paradoxical insomnia. It is unknown what underlies sleep misperception, as standard polysomnographic (PSG) parameters are often normal in these cases. Here we asked whether regional changes in brain activity could account for the mismatch between objective and subjective total sleep times (TST). To set cutoffs and define the norm, we first evaluated sleep perception in a population-based sample, consisting of 2,092 individuals who underwent a full PSG at home and estimated TST the next day. We then compared participants with a low mismatch (normoestimators, n = 1,147, ±0.5 SD of mean) with those who severely underestimated (n = 52, &lt;2.5th percentile) or overestimated TST (n = 53, &gt;97.5th percentile). Compared with normoestimators, underestimators displayed higher electroencephalographic (EEG) activation (beta/delta power ratio) in both rapid eye movement (REM) and non-rapid eye movement (NREM) sleep, while overestimators showed lower EEG activation (significant in REM sleep). To spatially map these changes, we performed a second experiment, in which 24 healthy subjects and 10 insomnia patients underwent high-density sleep EEG recordings. Similarly to underestimators, patients displayed increased EEG activation during NREM sleep, which we localized to central-posterior brain areas. Our results indicate that a relative shift from low- to high-frequency spectral power in central-posterior brain regions, not readily apparent in conventional PSG parameters, is associated with underestimation of sleep duration. This challenges the concept of sleep misperception, and suggests that instead of misperceiving sleep, insomnia patients may correctly perceive subtle shifts toward wake-like brain activity.

A Novel Microwave Treatment for Sleep Disorders and Classification of Sleep Stages Using Multi-Scale Entropy

The aim of this study was to develop an integrated system of non-contact sleep stage detection and sleep disorder treatment for health monitoring. Hence, a method of brain activity detection based on microwave scattering technology instead of scalp electroencephalogram was developed to evaluate the sleep stage. First, microwaves at a specific frequency were used to penetrate the functional sites of the brain in patients with sleep disorders to change the firing frequency of the activated areas of the brain and analyze and evaluate statistically the effects on sleep improvement. Then, a wavelet packet algorithm was used to decompose the microwave transmission signal, the refined composite multiscale sample entropy, the refined composite multiscale fluctuation-based dispersion entropy and multivariate multiscale weighted permutation entropy were obtained as features from the wavelet packet coefficient. Finally, the mutual information-principal component analysis feature selection method was used to optimize the feature set and random forest was used to classify and evaluate the sleep stage. The results show that after four times of microwave modulation treatment, sleep efficiency improved continuously, the overall maintenance was above 80%, and the insomnia rate was reduced gradually. The overall classification accuracy of the four sleep stages was 86.4%. The results indicate that the microwaves with a certain frequency can treat sleep disorders and detect abnormal brain activity. Therefore, the microwave scattering method is of great significance in the development of a new brain disease treatment, diagnosis and clinical application system.

The paradox of paradoxical insomnia: A theoretical review towards a unifying evidence-based definition

Paradoxical insomnia is one of the most intriguing yet challenging subtypes of insomnia. Despite being recognized for a long time by the international community, it is still unclear whether this entity really exists, which are its features and boundaries. Much of the debate is fuelled by the lack of a consensus on its precise definition. To help filling some of the existing gaps, a systematic review of the literature was conducted, through which 19 different quantitative definitions were obtained. These definitions were then applied to two distinct datasets. The first consisted of 200 chronic primary insomnia patients, diagnosed according to the DSM-IV-TR criteria. The second consisted of 200 age- and sex-matched healthy persons without insomnia. For each dataset, available data from the objective sleep parameters and their subjective estimation were imported and analysed in MATLAB. Depending on the definition used, the prevalence of paradoxical insomnia ranged from 8 to 66%, while agreement between different definitions ranged from -0.19 to 0.9 (using Cohen's kappa coefficient). Based on the results garnered, necessary features for a quantitative definition of paradoxical insomnia were identified. Several open questions remain, such as whether there is a minimum number of hours a patient should sleep to fulfill the criteria for a diagnosis of paradoxical insomnia, and whether sleep latency can be used in the definition along with total sleep time. We conclude by advocating continued study of paradoxical insomnia and sleep state misperception and by providing specific directions for future research. STATEMENT OF SIGNIFICANCE: The current understanding of paradoxical insomnia and, more broadly, of sleep state misperception, is greatly hampered by the lack of agreement on a quantitative and evidence-base measure of the discrepancy between subjective and objective sleep evaluation. The current study provides a critical analysis about the strength and the limitations of the available definitions, using both a data-driven and a theory-driven approach. The overarching goal is to motivate a rigorous discussion involving the main experts of the field, to build a consensus, and develop an evidence-based measure of sleep state misperception and/or of paradoxical insomnia.