High-density electroencephalography as an innovative tool to explore sleep physiology and sleep related disorders

Customizable automated cleaning of multichannel sleep EEG in SleepTrip

While standard polysomnography has revealed the importance of the sleeping brain in health and disease, more specific insight into the relevant brain circuits requires high-density electroencephalography (EEG). However, identifying and handling sleep EEG artifacts becomes increasingly challenging with higher channel counts and/or volume of recordings. Whereas manual cleaning is time-consuming, subjective, and often yields data loss (e.g., complete removal of channels or epochs), automated approaches suitable and practical for overnight sleep EEG remain limited, especially when control over detection and repair behavior is desired. Here, we introduce a flexible approach for automated cleaning of multichannel sleep recordings, as part of the free Matlab-based toolbox SleepTrip. Key functionality includes 1) channel-wise detection of various artifact types encountered in sleep EEG, 2) channel- and time-resolved marking of data segments for repair through interpolation, and 3) visualization options to review and monitor performance. Functionality for Independent Component Analysis is also included. Extensive customization options allow tailoring cleaning behavior to data properties and analysis goals. By enabling computationally efficient and flexible automated data cleaning, this tool helps to facilitate fundamental and clinical sleep EEG research.

Region-specific changes in brain activity and memory after continuous positive airway pressure therapy in obstructive sleep apnea: a pilot high-density electroencephalography study

STUDY OBJECTIVES

Limited channel electroencephalography (EEG) investigations in obstructive sleep apnea (OSA) have revealed deficits in slow wave activity (SWA) and spindles during sleep and increased EEG slowing during resting wakefulness. High-density EEG (Hd-EEG) has also detected local parietal deficits in SWA (delta power) during NREM. It is unclear whether effective continuous positive airway pressure (CPAP) treatment reverses regional SWA deficits, and other regional sleep and wake EEG abnormalities, and whether any recovery relates to improved overnight memory consolidation.

METHODS

A clinical sample of men with moderate-severe OSA underwent sleep and resting wake recordings with 256-channel Hd-EEG before and after 3 months of CPAP. Declarative and procedural memory tasks were administered pre- and post-sleep. Topographical spectral power maps and differences between baseline and treatment were compared using t-tests and statistical nonparametric mapping (SnPM).

RESULTS

In 11 compliant CPAP users (5.2 ± 1.1 hours/night), total sleep time did not differ after CPAP but N1 and N2 sleep were lower and N3 was higher. Centro-parietal gamma power during N3 increased and fronto-central slow spindle activity during N2 decreased (SnPM < 0.05). No other significant differences in EEG power were observed. When averaged specifically within the parietal region, N3 delta power increased after CPAP (p = 0.0029) and was correlated with the change in overnight procedural memory consolidation (rho = 0.79, p = 0.03). During resting wakefulness, there were trends for reduced delta and theta power.

CONCLUSIONS

Effective CPAP treatment of OSA may correct regional EEG abnormalities, and regional recovery of SWA may relate to procedural memory improvements in the short term.

Sleep electroencephalography biomarkers of cognition in obstructive sleep apnea

Obstructive sleep apnea has been associated with cognitive impairment and may be linked to disorders of cognitive function. These associations may be a result of intermittent hypoxaemia, sleep fragmentation and changes in sleep microstructure in obstructive sleep apnea. Current clinical metrics of obstructive sleep apnea, such as the apnea-hypopnea index, are poor predictors of cognitive outcomes in obstructive sleep apnea. Sleep microstructure features, which can be identified on sleep electroencephalography of traditional overnight polysomnography, are increasingly being characterized in obstructive sleep apnea and may better predict cognitive outcomes. Here, we summarize the literature on several major sleep electroencephalography features (slow-wave activity, sleep spindles, K-complexes, cyclic alternating patterns, rapid eye movement sleep quantitative electroencephalography, odds ratio product) identified in obstructive sleep apnea. We will review the associations between these sleep electroencephalography features and cognition in obstructive sleep apnea, and examine how treatment of obstructive sleep apnea affects these associations. Lastly, evolving technologies in sleep electroencephalography analyses will also be discussed (e.g. high-density electroencephalography, machine learning) as potential predictors of cognitive function in obstructive sleep apnea.

'High-Density-SleepCleaner': An open-source, semi-automatic artifact removal routine tailored to high-density sleep EEG

BACKGROUND

With up to 256 channels, high-density electroencephalography (hd-EEG) has become essential to the sleep research field. The vast amount of data resulting from this magnitude of channels in overnight EEG recordings complicates the removal of artifacts.

NEW METHOD

We present a new, semi-automatic artifact removal routine specifically designed for sleep hd-EEG recordings. By employing a graphical user interface (GUI), the user assesses epochs in regard to four sleep quality markers (SQMs). Based on their topography and underlying EEG signal, the user eventually removes artifactual values. To identify artifacts, the user is required to have basic knowledge of the typical (patho-)physiological EEG they are interested in, as well as artifactual EEG. The final output consists of a binary matrix (channels x epochs). Channels affected by artifacts can be restored in afflicted epochs using epoch-wise interpolation, a function included in the online repository.

RESULTS

The routine was applied in 54 overnight sleep hd-EEG recordings. The proportion of bad epochs highly depends on the number of channels required to be artifact-free. Between 95% and 100% of bad epochs could be restored using epoch-wise interpolation. We furthermore present a detailed examination of two extreme cases (with few and many artifacts). For both nights, the topography and cyclic pattern of delta power look as expected after artifact removal.

COMPARISON WITH EXISTING METHODS

Numerous artifact removal methods exist, yet their scope of application usually targets short wake EEG recordings. The proposed routine provides a transparent, practical, and efficient approach to identify artifacts in overnight sleep hd-EEG recordings.

CONCLUSION

This method reliably identifies artifacts simultaneously in all channels and epochs.

Local sleep: A new concept in brain plasticity

Traditionally, sleep and wakefulness have been considered as two global, mutually exclusive states. However, this view has been challenged by the discovery that sleep and wakefulness are actually locally regulated and that islands of these two states may often coexist in the same individual. Importantly, such a local regulation seems to be the key for many essential functions of sleep, including the maintenance of cognitive efficiency and the consolidation of new skills and memories. Indeed, local changes in sleep-related oscillations occur in brain areas that are used and involved in learning during wakefulness. In turn, these changes directly modulate experience-dependent brain adaptations and the consolidation of newly acquired memories. In line with these observations, alterations in the regional balance between wake- and sleep-like activity have been shown to accompany many pathologic conditions, including psychiatric and neurologic disorders. In the last decade, experimental research has started to shed light on the mechanisms involved in the local regulation of sleep and wakefulness. The results of this research have opened new avenues of investigation regarding the function of sleep and have revealed novel potential targets for the treatment of several pathologic conditions.

Gulf War veterans exhibit broadband sleep EEG power reductions in regions overlying the frontal lobe

AIMS

Nearly a third of U.S. veterans who deployed in support of the 1990-1991 Persian Gulf War are affected by Gulf War illness (GWI). Here we aimed to characterize whether subjective sleep complaints in GWI veterans are associated with objective sleep EEG disturbances relative to healthy veterans and controls; and whether Gulf War veterans show alterations in neural activity during sleep that differentiate them from healthy subjects.

MAIN METHODS

We used high-density EEG (HDEEG) to assess regional patterns of rapid eye movement (REM) sleep and non-REM (NREM) sleep between three groups: Gulf War male veterans with fatigue and GWI, Gulf War male veterans without fatigue or GWI, and control males. The groups were matched relative to age, sex and obstructive sleep apnea. Topographic comparisons of nocturnal NREM and REM sleep were made between groups for all frequency bands.

KEY FINDINGS

Topographic analysis revealed a broadband reduction in EEG power in a circumscribed region overlying the frontal lobe in both groups of Gulf War veterans, regardless of GWI and fatigue. This frontal reduction in neural activity was present, to some extent, across all frequency bands in NREM and REM sleep.

SIGNIFICANCE

Given that our findings were observed in all Gulf War veterans, it appears unlikely that frontal sleep HDEEG power reductions prove wholly responsible for fatigue symptoms. These results provide avenues for research which may someday contribute to improved clinical care of formerly deployed veterans of the Persian Gulf War.

Low Complexity Automatic Stationary Wavelet Transform for Elimination of Eye Blinks from EEG

The electroencephalogram signal (EEG) often suffers from various artifacts and noises that have physiological and non-physiological origins. Among these artifacts, eye blink, due to its amplitude is considered to have the most influence on EEG analysis. In this paper, a low complexity approach based on Stationary Wavelet Transform (SWT) and skewness is proposed to remove eye blink artifacts from EEG signals. The proposed method is compared against Automatic Wavelet Independent Components Analysis (AWICA) and Enhanced AWICA. Normalized Root Mean Square Error (NRMSE), Peak Signal-to-Noise Ratio (PSNR), and correlation coefficient ( ρ ) between filtered and pure EEG signals are utilized to quantify artifact removal performance. The proposed approach shows smaller NRMSE, larger PSNR, and larger correlation coefficient values compared to the other methods. Furthermore, the speed of execution of the proposed method is considerably faster than other methods, which makes it more suitable for real-time processing.

Sleep disturbances in schizophrenia: what we know, what still needs to be done

Sleep disturbances are commonly observed in schizophrenia (SCZ) and are associated with worse psychotic symptoms and poorer clinical outcomes. Early polysomnography studies have focused on characterizing differences in sleep architecture between patients with SCZ and healthy controls. More recently, research has focused on sleep-specific EEG oscillations, such as sleep spindles and slow waves, which reflect the integrity of underlying thalamo-cortical networks. Furthermore, high-density (hd)-EEG (≥64 channels), which affords enhanced spatial resolution, has been employed to better localize abnormalities in sleep characteristics and related thalamo-cortical circuits in patients with SCZ and related disorders. In this article, we will review the most relevant sleep abnormalities reported in SCZ, with an emphasis on recent findings, and propose directions for future research.

Topographic deficits in sleep spindle density and duration point to frontal thalamo-cortical dysfunctions in first-episode psychosis

Sleep spindles are NREM sleep EEG oscillations, which are initiated within the thalamus and are regulated by thalamo-cortical circuits. Previous work from our and other research groups has shown marked spindle deficits in patients with schizophrenia (SCZ). However, the presence of spindle impairments at illness onset, including which parameters are most affected, their topographic characteristics, and their relationships with clinical symptoms have yet to be characterized. In this study we performed sleep high density (hd)-EEG recordings in twenty-seven first-episode psychosis (FEP) patients and twenty-three healthy controls (HC). Several spindle parameters-amplitude, duration, and density-were calculated and compared across groups. FEP patients showed reduced spindle duration and density, but not in spindle amplitude relative to HC. These spindles reductions were localized in a frontal area and predicted the severity of FEP patients' negative symptoms. Altogether, these findings indicate that spindle deficits are present at the beginning of psychosis, contribute to clinical symptomatology, and point to frontal thalamo-cortical dysfunctions, thus providing a potential treatment target for early interventions in SCZ and related psychotic disorders.

Sleep, Sleep Disorders, and Mild Traumatic Brain Injury. What We Know and What We Need to Know: Findings from a National Working Group

Disturbed sleep is one of the most common complaints following traumatic brain injury (TBI) and worsens morbidity and long-term sequelae. Further, sleep and TBI share neurophysiologic underpinnings with direct relevance to recovery from TBI. As such, disturbed sleep and clinical sleep disorders represent modifiable treatment targets to improve outcomes in TBI. This paper presents key findings from a national working group on sleep and TBI, with a specific focus on the testing and development of sleep-related therapeutic interventions for mild TBI (mTBI). First, mTBI and sleep physiology are briefly reviewed. Next, essential empirical and clinical questions and knowledge gaps are addressed. Finally, actionable recommendations are offered to guide active and efficient collaboration between academic, industry, and governmental stakeholders.

Sleep and anxiety in late childhood and early adolescence

PURPOSE OF REVIEW

Adolescence is a period of dynamic change in both sleep and emotional systems, with related increases in problems controlling emotion and behavior. Youth with anxiety enter adolescence with pre-existing vulnerabilities in systems of sleep and emotion that may place them at heightened risk. This review summarizes recent research on sleep and anxiety during the transition to adolescence, and highlights emerging themes.

RECENT FINDINGS

Prospective studies support that sleep predicts anxiety symptoms in early adolescence. Notably, robust evidence for subjective sleep problems in anxious youth is not well corroborated by objective assessments. Longitudinal designs and methodology that carefully examine dimensions of anxiety and sleep may clarify inconsistencies. Preliminary evidence suggests that late childhood to early adolescence may be a sensitive period for escalating problems with sleep and anxiety. Recent advances in the neuroscience of sleep can further refine integrative mechanistic models of developmental psychopathology - the role of sleep in emotional learning and memory is provided as an example.

SUMMARY

Sleep problems are common and prospectively predict escalating anxiety symptoms. Precision is needed regarding the nature of sleep disruption, and how and when sleep affects various aspects of developmental trajectories. This precision, along with advances in the neuroscience of sleep, may lead to developmentally informed translational interventions.

Long-term Continuous EEG Monitoring in Small Rodent Models of Human Disease Using the Epoch Wireless Transmitter System

Many progressive neurologic diseases in humans, such as epilepsy, require pre-clinical animal models that slowly develop the disease in order to test interventions at various stages of the disease process. These animal models are particularly difficult to implement in immature rodents, a classic model organism for laboratory study of these disorders. Recording continuous EEG in young animal models of seizures and other neurological disorders presents a technical challenge due to the small physical size of young rodents and their dependence on the dam prior to weaning. Therefore, there is not only a clear need for improving pre-clinical research that will better identify those therapies suitable for translation to the clinic but also a need for new devices capable of recording continuous EEG in immature rodents. Here, we describe the technology behind and demonstrate the use of a novel miniature telemetry system, specifically engineered for use in immature rats or mice, which is also effective for use in adult animals.

Sleep in patients with schizophrenia

Numerous electrophysiological and neuroimaging studies have reported neurophysiological and cognitive deficits in schizophrenia patients during wakefulness. However, these findings have been inconsistently replicated across different groups of patients, thus complicating the identification of underlying neuronal defects. Sleep minimizes possible waking-related confounds, including decreased motivation and presence of active symptoms. Additionally, the two main sleep rhythms, slow waves and spindles, reflect the intrinsic activity of corticothalamic circuits and are associated with cognitive activities, including learning and memory, occurring during wakefulness. In this review I will present the most relevant sleep findings in schizophrenia, with particular emphasis on several recent studies that have consistently reported sleep spindle deficits in patients with schizophrenia. I will then elaborate on how these findings may contribute to a better understanding of the neurobiology of schizophrenia as well as to the development of novel pharmacological and non-pharmacological interventions to ameliorate the symptoms and cognitive impairments of schizophrenia patients.

Genetics of human sleep behavioral phenotypes

Quality sleep is critical for daily functions of human beings and thus the timing and duration of sleep are tightly controlled. However, rare genetic variants affecting sleep regulatory mechanisms can result in sleep phenotypes of extremely deviated sleep/wake onset time or duration. Using genetic analyses in families with multiple members expressing particular sleep phenotypes, these sleep-associated genetic variants can be identified. Deciphering the nature of these genetic variants using animal models or biochemical methods helps further our understanding of sleep processes. In this chapter, we describe the methods for studying genetics of human sleep behavioral phenotypes.