EEG Power Spectral Analysis of Abnormal Cortical Activations During REM/NREM Sleep in Obstructive Sleep Apnea

Co-localized optode-electrode design for multimodal functional near infrared spectroscopy and electroencephalography

Significance

Neuroscience of the everyday world requires continuous mobile brain imaging in real time and in ecologically valid environments, which aids in directly translating research for human benefit. Combined functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) studies have increased in demand, as the combined systems can provide great insights into cortical hemodynamics, neuronal activity, and neurovascular coupling. However, fNIRS-EEG studies remain limited in modularity and portability due to restrictions in combined cap designs, especially for high-density (HD) fNIRS measurements.

Aim

We have built and tested custom fNIRS sources that attach to electrodes without decreasing the overall modularity and portability of the probe.

Approach

To demonstrate the design's utility, we screened for any potential interference and performed a HD-fNIRS-EEG measurement with co-located opto-electrode positions during a modified Stroop task.

Results

No observable interference was present from the fNIRS source optodes in the EEG spectral analysis. The performance, fNIRS, and EEG results of the Stroop task supported the trends from previous research. We observed increased activation with both fNIRS and EEG within the regions of interest.

Conclusion

Overall, these results suggest that the co-localization method is a promising approach to multimodal imaging.

Abnormal power and spindle wave activity during sleep in young smokers

Introduction

Smoking is associated with significant alterations in sleep architecture. Previous studies have revealed changes in the subjective sleep of young smokers, but research on objective sleep assessment using polysomnography (PSG) is limited. This study aims to explore electroencephalography (EEG) power and sleep spindle activity during the sleep of young smokers, as well as to assess the relationship between sleep and smoking variables.

Methods

We collected overnight PSG data from 19 young smokers and 16 non-smokers and assessed nicotine dependence and cumulative effects using the Fagerstrom Nicotine Dependence Test (FTND) and pack-year. Power spectral analysis and sleep spindle detection are used to analyze EEG activity during sleep.

Results

Compared to the non-smokers, young smokers showed increased alpha power in the frontal and central regions and decreased delta power in the central region. The frontal region showed enhanced sleep spindle duration and density. Notably, both relative alpha power and sleep spindle duration in frontal showed a positive correlation with Pack-year.

Discussion

Sleep EEG power and sleep spindle activity in frontal may serve as biomarkers to assess the sleep quality of young smokers. It may improve the understanding of the relationship of sleep and smoking.

Lateralized differences in power spectra across different frequency bands during NREM sleep in patients with primary insomnia

Objective

To compare the electroencephalogram power spectrum of patients with primary insomnia and good sleep controls in multiple brain areas and different frequency bands during non-rapid eye movement sleep.

Methods

48 primary insomnias and 30 age-and gender-matched good sleep controls were recorded overnight with polysomnography. Power spectral analysis was performed in six brain areas (F3, F4, C3, C4, O1 and O2) and across seven frequency bands (delta, sigma, alpha, theta, beta1, beta2, and gamma) during non-rapid eye movement sleep between primary insomnias and good sleep controls.

Results

In primary insomnias, there were significant differences in frequency bands and areas. Compared to good sleep controls, delta power was lower in primary insomnias, while beta1, beta2, and gamma were higher. Beta2 power was substantially higher in all areas, sigma power was significantly higher on the right side, and gamma power was considerably higher on the left side in primary insomnias. The Beta1 power was positively correlated the number of awakenings (r = 0.3291, p = 0.02) in primary insomnias on the right side.

Conclusion

This study marked the first specialized comparison of power spectral analysis during non-rapid eye movement sleep in different areas and across different frequency bands. The result suggested that primary insomnias had reduced deep sleep (lower delta power) and hyperarousal state (higher beta 2 power). Primary insomnia was associated with significant fragmented sleep, and an increase in beta1 power was related to the number of awakenings.

Significance

These findings revealed the hemispheric lateralization characteristics of power spectral disturbances during non-rapid eye movement sleep in primary insomnias and provided valuable insights for selecting electrode placements in future power spectral analyses of primary insomnias.

Spontaneous oxycodone withdrawal disrupts sleep, diurnal, and electrophysiological dynamics in rats

Opioid dependence is defined by an aversive withdrawal syndrome upon drug cessation that can motivate continued drug-taking, development of opioid use disorder, and precipitate relapse. An understudied but common opioid withdrawal symptom is disrupted sleep, reported as both insomnia and daytime sleepiness. Despite the prevalence and severity of sleep disturbances during opioid withdrawal, there is a gap in our understanding of their interactions. The goal of this study was to establish an in-depth, temporal signature of spontaneous oxycodone withdrawal effects on the diurnal composition of discrete sleep stages and the dynamic spectral properties of the electroencephalogram (EEG) signal in male rats. We continuously recorded EEG and electromyography (EMG) signals for 8 d of spontaneous withdrawal after a 14-d escalating-dose oxycodone regimen (0.5-8.0 mg/kg, 2×d; SC). During withdrawal, there was a profound loss (peaking on days 2-3) and gradual return of diurnal structure in sleep, body temperature, and locomotor activity, as well as decreased sleep and wake bout durations dependent on lights on/off. Withdrawal was associated with significant alterations in the slope of the aperiodic 1/f component of the EEG power spectrum, an established biomarker of arousal level. Early in withdrawal, NREM exhibited an acute flattening and return to baseline of both low (1-4 Hz) and high (15-50 Hz) frequency components of the 1/f spectrum. These findings suggest temporally dependent withdrawal effects on sleep, reflecting the complex way in which the allostatic forces of opioid withdrawal impinge upon sleep and diurnal processes. These foundational data based on continuous tracking of vigilance state, sleep stage composition, and spectral EEG properties provide a detailed construct with which to form and test hypotheses on the mechanisms of opioid-sleep interactions.

Non-invasive Gamma Brain Wave Optimization (BWO-G) for Cognitive and Emotional Recovery in an Adolescent: A Case Study on Radio Electric Asymmetric Conveyer (REAC) Neuro Psycho Physical Optimization (NPPO) BWO-G Treatment

This case report describes the application of the radio electric asymmetric conveyer (REAC) gamma brain wave optimization (BWO-G) treatment in a 16-year-old female patient with a history of emotional trauma, depressive symptoms, and gender dysphoria. The patient underwent 18 sessions of REAC Neuro Psycho Physical Optimization (NPPO) BWO-G, with quantitative electroencephalography (QEEG) conducted pre- and post-treatment. Initial QEEG analyses indicated altered brain wave activity, with peaks in alpha rhythm frequencies in occipital and right posterior temporal areas. Following treatment, significant improvements were observed, including a reduction in delta and theta rhythms and increased alpha and gamma rhythms, corresponding to enhanced cognitive clarity and emotional regulation. Clinically, the patient experienced reduced anxiety, improved mood, heightened social engagement, better auditory tolerance, and resumed weight management. These findings suggest that the REAC NPPO BWO-G treatment may be an effective, non-invasive approach to enhancing cognitive and neuropsychological resilience in individuals with complex psychosocial challenges.

Louis EK, McCarter SJ, Bukartyk J, Przybelski SA, Kamykowski MG, Spychalla AJ, Machulda MM, Boeve BF, Petersen RC, Jack CR, Lowe VJ, Graff-Radford J, Worrell GA, Somers VK, Varga AW, Vemuri P. Non-rapid eye movement sleep slow-wave activity features are associated with amyloid accumulation in older adults with obstructive sleep apnoea

Obstructive sleep apnoea (OSA) is associated with an increased risk for cognitive impairment and dementia, which likely involves Alzheimer's disease pathology. Non-rapid eye movement slow-wave activity (SWA) has been implicated in amyloid clearance, but it has not been studied in the context of longitudinal amyloid accumulation in OSA. This longitudinal retrospective study aims to investigate the relationship between polysomnographic and electrophysiological SWA features and amyloid accumulation. From the Mayo Clinic Study of Aging cohort, we identified 71 participants ≥60 years old with OSA (mean baseline age = 72.9 ± 7.5 years, 60.6% male, 93% cognitively unimpaired) who had at least 2 consecutive Amyloid Pittsburgh Compound B (PiB)-PET scans and a polysomnographic study within 5 years of the baseline scan and before the second scan. Annualized PiB-PET accumulation [global ΔPiB(log)/year] was estimated by the difference between the second and first log-transformed global PiB-PET uptake estimations divided by the interval between scans (years). Sixty-four participants were included in SWA analysis. SWA was characterized by the mean relative spectral power density (%) in slow oscillation (SO: 0.5-0.9 Hz) and delta (1-3.9 Hz) frequency bands and by their downslopes (SO-slope and delta-slope, respectively) during the diagnostic portion of polysomnography. We fit linear regression models to test for associations among global ΔPiB(log)/year, SWA features (mean SO% and delta% or mean SO-slope and delta-slope), and OSA severity markers, after adjusting for age at baseline PiB-PET, APOE ɛ4 and baseline amyloid positivity. For 1 SD increase in SO% and SO-slope, global ΔPiB(log)/year increased by 0.0033 (95% CI: 0.0001; 0.0064, P = 0.042) and 0.0069 (95% CI: 0.0009; 0.0129, P = 0.026), which were comparable to 32% and 59% of the effect size associated with baseline amyloid positivity, respectively. Delta-slope was associated with a reduction in global ΔPiB(log)/year by -0.0082 (95% CI: -0.0143; -0.0021, P = 0.009). Sleep apnoea severity was not associated with amyloid accumulation. Regional associations were stronger in the pre-frontal region. Both slow-wave slopes had more significant and widespread regional associations. Annualized PiB-PET accumulation was positively associated with SO and SO-slope, which may reflect altered sleep homeostasis due to increased homeostatic pressure in the setting of unmet sleep needs, increased synaptic strength, and/or hyper-excitability in OSA. Delta-slope was inversely associated with PiB-PET accumulation, suggesting it may represent residual physiological activity. Further investigation of SWA dynamics in the presence of sleep disorders before and after treatment is necessary for understanding the relationship between amyloid accumulation and SWA physiology.

Efficacy of Radio Electric Asymmetric Conveyer Neuro Psycho Physical Optimization - Brain Wave Optimization-Gamma (REAC NPPO BWO-G) Treatment in Neurovegetative Dysfunction: A Case Report of Enhanced Cognitive Processing and Stress Resilience

Neurovegetative dysfunction from chronic stress impairs cognition, emotional regulation, and quality of life, with limited relief from conventional therapies. The Radio Electric Asymmetric Conveyer (REAC) Neuro Psycho Physical Optimization - Brain Wave Optimization-Gamma (NPPO BWO-G) offers a novel non-invasive approach to restore autonomic balance through brain modulation. This case involves a 63-year-old businessman with atrial fibrillation, fatigue, cognitive decline, and sleep issues. Pre-treatment quantitative electroencephalogram (qEEG) showed low brain activity and excess delta rhythms. After REAC NPPO BWO-G sessions, the patient experienced improved brainwave patterns, cognitive clarity, stress management, and reduced fatigue. These results highlight its potential as a promising treatment for stress-related neurovegetative dysfunction, warranting further study.

Purkinje cell dysfunction causes disrupted sleep in ataxic mice

Purkinje cell dysfunction disrupts movement and causes disorders such as ataxia. Recent evidence suggests that Purkinje cell dysfunction may also alter sleep regulation. Here, we used an ataxic mouse model generated by silencing Purkinje cell neurotransmission (L7Cre;Vgatfx/fx) to better understand how cerebellar dysfunction impacts sleep physiology. We focused our analysis on sleep architecture and electrocorticography (ECoG) patterns based on their relevance to extracting physiological measurements during sleep. We found that circadian activity was unaltered in the mutant mice, although their sleep parameters and ECoG patterns were modified. The L7Cre;Vgatfx/fx mutant mice had decreased wakefulness and rapid eye movement (REM) sleep, whereas non-REM sleep was increased. The mutants had an extended latency to REM sleep, which is also observed in human patients with ataxia. Spectral analysis of ECoG signals revealed alterations in the power distribution across different frequency bands defining sleep. Therefore, Purkinje cell dysfunction may influence wakefulness and equilibrium of distinct sleep stages in ataxia. Our findings posit a connection between cerebellar dysfunction and disrupted sleep and underscore the importance of examining cerebellar circuit function in sleep disorders.

Quantitative electroencephalography as a potential biomarker in migraine

OBJECTIVE

The aim of this study was to investigate the utility of quantitative electroencephalography (QEEG) as a diagnostic tool for migraine and as an indicator of treatment response by comparing QEEG characteristics between migraine patients and controls, and monitoring changes in these characteristics alongside clinical symptoms in response to treatment BACKGROUND: We hypothesized that patients with migraine exhibit distinctive characteristics in QEEG measurements, which could be used as potential diagnostic biomarkers and as a tool for monitoring treatment response.

METHODS

A total of 720 patients were included in the study, comprising 619 patients with migraine and 101 subjects as a control group. QEEG measurements were analyzed for absolute power across specific frequency bands: delta wave (0.5-4 Hz), theta wave (4-8 Hz), alpha wave (8-12 Hz), beta wave (12-25 Hz), and high beta wave (25-30 Hz). The absolute power was normalized against a normative dataset from NeuroGuide, with electrodes being highlighted for significance if they exceeded 1.96. Clinical symptoms were also monitored for correlation with QEEG changes.

RESULTS

Our analysis showed that patients with migraine exhibited significantly higher absolute power across all frequencies, most markedly within the high beta frequency range. When considering electrodes with z-scores exceeding the threshold of 1.96 in the high beta range, a significant association with migraine diagnosis was observed (per 1 electrode increase, OR 1.06; 95% CI 1.01-1.11; p = .012). Moreover, pre- and posttreatment changes in QEEG measurements corresponded with changes in clinical symptoms.

CONCLUSION

Patients with migraine have distinctive QEEG measurements, particularly regarding absolute power and the number of electrodes that surpassed the z-score threshold in high beta wave activity. These findings suggest the potential of QEEG as a diagnostic biomarker and as a tool for monitoring treatment response in migraine patients, warranting further large-scale studies for confirmation and expansion.

EEG Power Spectral Density in NREM Sleep is Associated with the Degree of Hypoxia in Patients with Obstructive Sleep Apnea

Purpose

Obstructive sleep apnea (OSA) is a prevalent sleep-related breathing disorder. Research conducted on patients with OSA using electroencephalography (EEG) has revealed a noticeable shift in the overnight polysomnography (PSG) power spectrum. To better quantify the effects of OSA on brain function and to identify the most reliable predictors of pathological cortical activation, this study quantified the PSG power and its association with the degree of hypoxia in OSA patients.

Patients and Methods

This retrospective study recruited 93 patients with OSA. OSA patients were divided into three groups based on their apnea-hypopnea index (AHI) scores. The clinical characteristics and sleep macrostructure of these patients were examined, followed by an analysis of PSG signals. Power spectral density (PSD) in five frequency bands was analyzed during nonrapid eye movement (NREM) sleep, rapid eye movement (REM) sleep, and wakefulness. Finally, correlation analysis was conducted to assess the relationships among PSD, PSG parameters, and serum levels of S100β and uric acid.

Results

Obstructive sleep apnea occurred during both the NREM and REM sleep phases. Except for a decrease in the duration of N2 sleep and an increase in the microarousal index, there were no significant differences in sleep architecture based on disease severity. Compared to the mild OSA group, the theta and alpha band PSD in the frontal and occipital regions during NREM sleep and wakefulness were significantly decreased in the moderate and severe OSA groups. Correlation analysis revealed that theta PSD in N1 and N3 stages were negatively correlated the AHI, oxygen desaturation index, SaO2<90% and microarousal index.

Conclusion

These findings imply that patients with more severe OSA exhibited considerable NREM hypoxia and abnormal brain activity in the frontal and occipital regions. Therefore, sleep EEG oscillation may be a useful neurophysiological indicator for assessing brain function and disease severity in patients with OSA.

Cerebellar deep brain stimulation as a dual-function therapeutic for restoring movement and sleep in dystonic mice

Dystonia arises with cerebellar dysfunction, which plays a key role in the emergence of multiple pathophysiological deficits that range from abnormal movements and postures to disrupted sleep. Current therapeutic interventions typically do not simultaneously address both the motor and non-motor (sleep-related) symptoms of dystonia, underscoring the necessity for a multi-functional therapeutic strategy. Deep brain stimulation (DBS) is effectively used to reduce motor symptoms in dystonia, with existing parallel evidence arguing for its potential to correct sleep disturbances. However, the simultaneous efficacy of DBS for improving sleep and motor dysfunction, specifically by targeting the cerebellum, remains underexplored. Here, we test the effect of cerebellar DBS in two genetic mouse models with dystonia that exhibit sleep defects- Ptf1a Cre ;Vglut2 fx/fx and Pdx1 Cre ;Vglut2 fx/fx -which have overlapping cerebellar circuit miswiring defects but differing severity in motor phenotypes. By targeting DBS to the cerebellar fastigial and interposed nuclei, we modulated sleep dysfunction by enhancing sleep quality and timing in both models. This DBS paradigm improved wakefulness (decreased) and rapid eye movement (REM) sleep (increased) in both mutants. Additionally, the latency to reach REM sleep, a deficit observed in human dystonia patients, was reduced in both models. Cerebellar DBS also induced alterations in the electrocorticogram (ECoG) patterns that define sleep states. As expected, DBS reduced the severe dystonic twisting motor symptoms that are observed in the Ptf1a Cre ;Vglut2 fx/fx mutant mice. These findings highlight the potential for using cerebellar DBS to improve sleep and reduce motor dysfunction in dystonia and uncover its potential as a dual-effect in vivo therapeutic strategy.

The Relationship Between Slow Wave Sleep and Blood Oxygen Saturation Among Patients With Apnea: Retrospective Study

Background and Objective Prior research suggests that slow wave sleep (SWS) is disrupted in people with obstructive sleep apnea (OSA). However, it was not clear whether the reduction in SWS is related to abnormal breathing or the extent of OSA as determined by the minimum oxygen saturation. Further, there is limited research on the relationship between oxygen saturation and SWS. The present study examined the relationship between SWS and minimum oxygen saturation levels in patients with OSA.Methods The sample consisted of 589 patients with OSA (mean age: 48.54 years) who completed full-night polysomnography.Results Results showed that there was a significant difference in SWS scores across three apnea-hypopnea index (AHI) groups (AHI score 5–15 for mild apnea, 16–30 for moderate apnea, and >30 for severe apnea). Lower SWS scores were observed in the severe apnea group. Additionally, results indicated that as oxygen saturation decreased, the SWS scores decreased.Conclusions Results from this study indicate that oxygen saturation significantly predicts SWS amounts. These findings suggest that interventions for low oxygen saturation could enhance the amounts of SWS. The clinical ramifications of these findings are worthy of consideration.

Sub-Scalp Implantable Telemetric EEG (SITE) for the Management of Neurological and Behavioral Disorders beyond Epilepsy

Sub-scalp Implantable Telemetric EEG (SITE) devices are under development for the treatment of epilepsy. However, beyond epilepsy, continuous EEG analysis could revolutionize the management of patients suffering from all types of brain disorders. This article reviews decades of foundational EEG research, collected from short-term routine EEG studies of common neurological and behavioral disorders, that may guide future SITE management and research. Established quantitative EEG methods, like spectral EEG power density calculation combined with state-of-the-art machine learning techniques applied to SITE data, can identify new EEG biomarkers of neurological disease. From distinguishing syncopal events from seizures to predicting the risk of dementia, SITE-derived EEG biomarkers can provide clinicians with real-time information about diagnosis, treatment response, and disease progression.

Purkinje cell dysfunction causes disrupted sleep in ataxic mice

Purkinje cell dysfunction causes movement disorders such as ataxia, however, recent evidence suggests that Purkinje cell dysfunction may also alter sleep regulation. Here, we used an ataxia mouse model generated by silencing Purkinje cell neurotransmission ( L7 Cre ;Vgat fx/fx ) to better understand how cerebellar dysfunction impacts sleep physiology. We focused our analysis on sleep architecture and electrocorticography (ECoG) patterns based on their relevance to extracting physiological measurements during sleep. We found that circadian activity is unaltered in the mutant mice, although their sleep parameters and ECoG patterns are modified. The L7 Cre ;Vgat fx/fx mutant mice have decreased wakefulness and rapid eye movement (REM) sleep, while non-rapid eye movement (NREM) sleep is increased. The mutant mice have an extended latency to REM sleep, which is also observed in human ataxia patients. Spectral analysis of ECoG signals revealed alterations in the power distribution across different frequency bands defining sleep. Therefore, Purkinje cell dysfunction may influence wakefulness and equilibrium of distinct sleep stages in ataxia. Our findings posit a connection between cerebellar dysfunction and disrupted sleep and underscore the importance of examining cerebellar circuit function in sleep disorders.

Summary Statement

Utilizing a precise genetic mouse model of ataxia, we provide insights into the cerebellum's role in sleep regulation, highlighting its potential as a therapeutic target for motor disorders-related sleep disruptions.

The effect of burst suppression on cerebral blood flow and autoregulation: a scoping review of the human and animal literature

Background: Burst suppression (BS) is an electroencephalography (EEG) pattern in which there are isoelectric periods interspersed with bursts of cortical activity. Targeting BS through anaesthetic administration is used as a tool in the neuro-intensive care unit but its relationship with cerebral blood flow (CBF) and cerebral autoregulation (CA) is unclear. We performed a systematic scoping review investigating the effect of BS on CBF and CA in animals and humans. Methods: We searched MEDLINE, BIOSIS, EMBASE, SCOPUS and Cochrane library from inception to August 2022. The data that were collected included study population, methods to induce and measure BS, and the effect on CBF and CA. Results: Overall, there were 66 studies that were included in the final results, 41 of which examined animals, 24 of which examined humans, and 1 of which examined both. In almost all the studies, BS was induced using an anaesthetic. In most of the animal and human studies, BS was associated with a decrease in CBF and cerebral metabolism, even if the mean arterial pressure remained constant. The effect on CA during periods of stress (hypercapnia, hypothermia, etc.) was variable. Discussion: BS is associated with a reduction in cerebral metabolic demand and CBF, which may explain its usefulness in patients with brain injury. More evidence is needed to elucidate the connection between BS and CA.

EEG spectral power during REM sleep in patients with frontal brain tumor

BACKGROUND

The main objective of this research was to analyze the characteristics of electrical activity in the brain during REM (Rapid Eye Movements) sleep, by using an experimental model a pathology that affects the frontal lobes, such as brain tumors. In addition to determining the impact of variables such as the frontal area (dorsolateral, medial and orbital), laterality and size of the lesion; as well as the demographic and clinical characteristics of the patients evaluated.

METHODS

By using polysomnographic recordings, 10 patients were evaluated. We obtained power spectra through a homemade program. For quantitative EEG (Electroencephalogram) (qEEG) analysis, the Fast Fourier Transform (FFT) algorithm was used to obtain the spectral power of each participant, channel, and frequency band.

RESULTS

Sleep architecture and spectral power was found to be modified in patients compared to normative values. Other sociodemographic and clinical characteristics of the patients were also influenced, such as age range and antiepileptic drugs.

CONCLUSIONS

Brain tumors in the frontal lobe can modify the rhythmogenesis of REM sleep, possibly due to changes of brain plasticity as an effect of the pathology. In addition to this, through this study we were able to show the association between neuroanatomical and functional changes, on the characteristics of brain electrical activity in patients with frontal brain tumor. Finally, this qEEG analysis technique allows, on the one hand, to deepen the knowledge and relationship between psychophysiological processes and, on the other hand, to be able to guide therapeutic decisions.

Driving drowsiness detection using spectral signatures of EEG-based neurophysiology

Introduction: Drowsy driving is a significant factor causing dire road crashes and casualties around the world. Detecting it earlier and more effectively can significantly reduce the lethal aftereffects and increase road safety. As physiological conditions originate from the human brain, so neurophysiological signatures in drowsy and alert states may be investigated for this purpose. In this preface, A passive brain-computer interface (pBCI) scheme using multichannel electroencephalography (EEG) brain signals is developed for spatially localized and accurate detection of human drowsiness during driving tasks.

Methods: This pBCI modality acquired electrophysiological patterns of 12 healthy subjects from the prefrontal (PFC), frontal (FC), and occipital cortices (OC) of the brain. Neurological states are recorded using six EEG channels spread over the right and left hemispheres in the PFC, FC, and OC of the sleep-deprived subjects during simulated driving tasks. In post-hoc analysis, spectral signatures of the δ, θ, α, and β rhythms are extracted in terms of spectral band powers and their ratios with a temporal correlation over the complete span of the experiment. Minimum redundancy maximum relevance, Chi-square, and ReliefF feature selection methods are used and aggregated with a Z-score based approach for global feature ranking. The extracted drowsiness attributes are classified using decision trees, discriminant analysis, logistic regression, naïve Bayes, support vector machines, k-nearest neighbors, and ensemble classifiers. The binary classification results are reported with confusion matrix-based performance assessment metrics.

Results: In inter-classifier comparison, the optimized ensemble model achieved the best results of drowsiness classification with 85.6% accuracy and precision, 89.7% recall, 87.6% F1-score, 80% specificity, 70.3% Matthews correlation coefficient, 70.2% Cohen’s kappa score, and 91% area under the receiver operating characteristic curve with 76-ms execution time. In inter-channel comparison, the best results were obtained at the F8 electrode position in the right FC of the brain. The significance of all the results was validated with a p-value of less than 0.05 using statistical hypothesis testing methods.

Conclusions: The proposed scheme has achieved better results for driving drowsiness detection with the accomplishment of multiple objectives. The predictor importance approach has reduced the feature extraction cost and computational complexity is minimized with the use of conventional machine learning classifiers resulting in low-cost hardware and software requirements. The channel selection approach has spatially localized the most promising brain region for drowsiness detection with only a single EEG channel (F8) which reduces the physical intrusiveness in normal driving operation. This pBCI scheme has a good potential for practical applications requiring earlier, more accurate, and less disruptive drowsiness detection using the spectral information of EEG biosignals.

Transcranial magnetic stimulation cortical oscillations and improve cognition in obstructive sleep apnea patients

BACKGROUND

Transcranial magnetic stimulation (TMS) is a noninvasive tool to improve cognition. Relevant clinical studies are mainly focused on neurological and psychiatric diseases. However, cognition decline and psychiatric disorders are popular in obstructive sleep apnea (OSA) patients. We aimed to investigate the effect of TMS over the left dorsolateral prefrontal cortex (DLPFC) on cognition test performance and to compare the changes in quantitative electroencephalogram (EEG) before and after stimulation for OSA.

METHODS

This study recruited 42 OSA patients diagnosed with polysomnography according to American Academy of Sleep Medicine guidelines. TMS (intermittent theta-burst stimulation paradigm; 2 s on, 8 s off, 600 pulses*3, intermittent 15 min) was performed on the DLPFC. Cambridge Automated Neuropsychological Test Battery was used to assess cognitive performance. EEG oscillations were computed via power spectral density with MATLAB software.

RESULTS

Real-TMS group displayed a significant improvement in visual memory, sustain attention performance, as well as the outcome of working memory. However, the executive function of latency was changed in both groups. Furthermore, TMS resulted in a significant increase in the relative power spectral density of the theta band and beta band in the parietal, temporal, and anterior regions, respectively.

CONCLUSIONS

In summary, our findings indicate that TMS can safely modulate cortical oscillations and improve cognition in OSA patients. In the future, TMS can be utilized as an alternative treatment option to improve cognition in OSA patients.

A Novel In-Home Sleep Monitoring System Based on Fully Integrated Multichannel Front-End Chip and Its Multilevel Analyses

OBJECTIVE

A novel in-home sleep monitoring system with an 8-channel biopotential acquisition front-end chip is presented and validated via multilevel data analyses and comparision with advanced polysomnography.

METHODS AND PROCEDURES

The chip includes a cascaded low-noise programmable gain amplifier (PGA) and 24-bit [Formula: see text]-[Formula: see text] analog-to-digital converter (ADC). The PGA is based on three op-amp structure while the ADC adopts cascade of integrator feedforward and feedback (CIFF-B) architecture. An innovative chopper-modulated input-scaling-down technique enhances the dynamic range. The proposed system and commercial polysomnography were used for in-home sleep monitoring of 20 healthy participants. The consistency and significance of the two groups' data were analyzed.

RESULTS

Fabricated in 180 nm BCD technology, the input-referred noise, input impedance, common-mode rejection ratio, and dynamic range of the acquisition front-end chip were [Formula: see text]Vpp, 1.25 GN), 113.9 dB, and 119.8 dB. The kappa coefficients between the sleep stage labels of the three scorers were 0.80, 0.76, and 0.79. The consistency of the slowing index, multiscale entropy, and percentile features between the two devices reached 0.958, 0.885, and 0.834. The macro sleep architecture characteristics of the two devices were not significantly different (all p [Formula: see text] 0.05).

CONCLUSION

The proposed chip was applied to develop an in-home sleep monitoring system with significantly reduced size, power, and cost. Multilevel analyses demonstrated that this system collects stable and accurate in-home sleep data.

CLINICAL IMPACT

The proposed system can be applied for long-term in-home sleep monitoring outside of laboratory environments and sleep disorders screening that with low cost.

Disrupted sleep in dystonia depends on cerebellar function but not motor symptoms in mice

Although dystonia is the third most common movement disorder, patients often also experience debilitating nonmotor defects including impaired sleep. The cerebellum is a central component of a "dystonia network" that plays various roles in sleep regulation. Importantly, the primary driver of sleep impairments in dystonia remains poorly understood. The cerebellum, along with other nodes in the motor circuit, could disrupt sleep. However, it is unclear how the cerebellum might alter sleep and mobility. To disentangle the impact of cerebellar dysfunction on motion and sleep, we generated two mouse genetic models of dystonia that have overlapping cerebellar circuit miswiring but show differing motor phenotype severity: Ptf1a ^Cre ;Vglut2 ^fx/fx and Pdx1 ^Cre ;Vglut2 ^fx/fx mice. In both models, excitatory climbing fiber to Purkinje cell neurotransmission is blocked, but only the Ptf1a ^Cre ;Vglut2 ^fx/fx mice have severe twisting. Using in vivo ECoG and EMG recordings we found that both mutants spend greater time awake and in NREM sleep at the expense of REM sleep. The increase in awake time is driven by longer awake bouts rather than an increase in bout number. We also found a longer latency to reach REM in both mutants, which is similar to what is reported in human dystonia. We uncovered independent but parallel roles for cerebellar circuit dysfunction and motor defects in promoting sleep quality versus posture impairments in dystonia.

Sleep Spindle Characteristics and Relationship with Memory Ability in Patients with Obstructive Sleep Apnea-Hypopnea Syndrome

Obstructive sleep apnea syndrome (OSAS) causes intermittent hypoxia and sleep disruption in the brain, resulting in cognitive dysfunction, but its pathogenesis is unclear. The sleep spindle wave is a transient neural event involved in sleep memory consolidation and synaptic plasticity. This study aimed to investigate the characteristics of sleep spindle activity and its relationship with memory ability in patients with OSAS. A total of 119 patients, who were divided into the OSAS group (n = 59, AHI ≥ 15) and control group (n = 60, AHI < 15) according to the Apnea Hypopnea Index (AHI), were enrolled and underwent polysomnography. Power spectral density (PSD) and omega complexity were used to analyze the characteristics of single and different brain regions of sleep spindles. Memory-related cognitive functions were assessed in all subjects, including logical memory, digit ordering, pattern recognition, spatial recognition and spatial working memory. The spindle PSD of the OSAS group was significantly slower than the control group, regardless of the slow, fast, or total spindle. The complexity of the spindles in the prefrontal and central region decreased significantly, whereas it increased in the occipital region. Sleep spindle PSD was positively correlated with logical memory and working memory. Spindle complexity was positively correlated with immediate logical and visual memory in the prefrontal region and positively correlated with immediate/delayed logical and working memory in the central region. In contrast, spindle complexity in the occipital region negatively correlated with delayed logical memory. Spindle hyperconnectivity in the prefrontal and central regions underlies declines in logical, visual and working memory and weak connections in the occipital spindles underlie the decline in delayed logical memory.

Fuzzy Approximate Entropy of Extrema Based on Multiple Moving Averages as a Novel Approach in Obstructive Sleep Apnea Screening

OBJECTIVE

Obstructive sleep apnea (OSA) is a respiratory disease associated with autonomic nervous system dysfunction. As a novel method for analyzing OSA depending on heart rate variability, fuzzy approximate entropy of extrema based on multiple moving averages (Emma-fApEn) can effectively assess the sympathetic tension limits, thereby realizing a good performance in the disease severity screening.

METHOD

Sixty 6-h electrocardiogram recordings (20 healthy, 16 mild/moderate OSA and 34 severe OSA) from the PhysioNet database were used in this study. The performances of minima of Emma-fApEn (fApEn-minima), maxima of Emma-fApEn (fApEn-maxima) and classic time-frequency domain indices for each recording were assessed by significance analysis, correlation analysis, parameter optimization and OSA screening.

RESULTS

fApEn-minima and fApEn-maxima had significant differences between the severe OSA group and the other two groups, while the mean value (Mean) and the ratio of low-frequency power and high-frequency power (LH) could significantly differentiate OSA recordings from healthy recordings. The correlation coefficient between fApEn-minima and apnea-hypopnea index was the highest (|R| = 0.705). Machine learning methods were used to evaluate the performances of the above four indices. Random forest (RF) achieved the highest accuracy of 96.67% in OSA screening and 91.67% in severe OSA screening, with a good balance in both.

CONCLUSION

Emma-fApEn may be used as a simple preliminary detection tool to assess the severity of OSA prior to polysomnography analysis.

Electroencephalography Theta/Beta Ratio Decreases in Patients with Severe Obstructive Sleep Apnea

Purpose

Accumulating evidence suggests that theta/beta ratio (TBR), an electroencephalographic (EEG) frequency band parameter, might serve as an objective marker of executive cognitive control in healthy adults. Obstructive sleep apnea (OSA) has a detrimental impact on patients' behavior and cognitive performance while whether TBR is different in OSA population has not been reported. This study aimed to explore the difference in relative EEG spectral power and TBR during sleep between patients with severe OSA and non-OSA groups.

Patients and Methods

142 participants with in-laboratory nocturnal PSG recording were included, among which 100 participants suffered severe OSA (apnea hypopnea index, AHI > 30 events/hour; OSA group) and 42 participants had no OSA (AHI ≤ 5 events/h; control group). The fast Fourier transformation was used to compute the EEG power spectrum for total sleep duration within contiguous 30-second epochs of sleep. The demographic and polysomnographic characteristics, relative EEG spectral power and TBR of the two groups were compared.

Results

It was found that the beta band power during NREM sleep and total sleep was significantly higher in the OSA group than controls (p < 0.001, p = 0.012, respectively), and the theta band power during NREM sleep and total sleep was significantly lower in the OSA group than controls (p = 0.019, p = 0.014, respectively). TBR during NREM sleep, REM sleep and total sleep was significantly lower in the OSA group compared to the control group (p < 0.001 for NREM sleep and total sleep, p = 0.015 for REM sleep). TBR was negatively correlated with AHI during NREM sleep (r=-0.324, p < 0.001) and total sleep (r=-0. 312, p < 0.001).

Conclusion

TBR was significantly decreased in severe OSA patients compared to the controls, which was attributed to both increased beta power and decreased theta power. TBR may be a stable EEG-biomarker of OSA patients, which may accurately and reliably identify phenotype of patients.

Getting More from the Sleep Recording

Sleep studies have typically followed criteria established many decades ago, but emerging technologies allow signal analyses that go far beyond the scoring rules for manual analysis of sleep recordings. These technologies may apply to the analysis of signals obtained in standard polysomnography in addition to novel signals more recently developed that provide both direct and indirect measures of sleep and breathing in the ambulatory setting. Automated analysis of signals such as electroencephalogram and oxygen saturation, in addition to heart rate and rhythm, provides a wealth of additional information on sleep and breathing disturbances and their potential for comorbidity.

Effect of continuous positive air pressure on cognitive impairment associated with obstructive sleep apnea

Obstructive sleep apnea (OSA) is a kind of sleep-related breathing disorder, involving multiple organs and systems, which can lead to cognitive impairment. At present, the pathophysiological mechanism of cognitive impairment related to OSA is not clear. It is still unknown whether continuous positive airway pressure (CPAP) has therapeutic effect on cognitive impairment in patients with OSA. These patients repeatedly experience intermittent hypoxia and have sleep fragmentation, which results in abnormal brain structure and function, characterizing by extensive cognitive impairment. Appropriate CPAP can correct the abnormal pathophysiological process of OSA patients, restore brain structure and function to a certain extent, and improve cognitive function. Domestic OSA patients have poor acceptance and compliance to CPAP, while the therapeutic effect of CPAP depends on the timing of treatment and compliance, so many patients do not get effective treatment. Systematically expounding the influence of CPAP on the cognitive function of patients with OSA can help clinicians and patients improve their understanding of CPAP treatment and establish a correct concept of early and standardized treatment.

Effects of Obstructive Sleep Apnea and CPAP on Cognitive Function

PURPOSE OF REVIEW

Obstructive sleep apnea (OSA) is characterized by repetitive episodes of complete or partial upper airway obstruction during sleep. Studies indicate that OSA is an independent risk factor for cognitive decline in older patients. The purpose of this paper is to critically review the recent literature on the cognitive effects of untreated OSA and the benefits of treatment across cognitive domains.

RECENT FINDINGS

OSA's greatest impact appears to be on attention, vigilance, and information processing speed. Furthermore, the presence of OSA seems to have a significant impact on development and progression of mild cognitive impairment (MCI). Impact of OSA treatment, particularly with CPAP, appears to mitigate and slow the rate of cognitive decline and may reduce the risk of dementia. Larger properly controlled studies, of a prospective nature, are required to further elucidate the degree of treatment effect. More studies are needed on other treatments for OSA such as oral mandibular devices and hypoglossal nerve stimulation.