Pediatric Sleep Apnea: The Overnight Electroencephalogram as a Phenotypic Biomarker

Frontal Theta Asymmetry may be a new target for reducing the severity of depression and improving cognitive function in depressed patients

BACKGROUND

The prevalence of depressive disorder is increasing due to a variety of factors, which brings a huge strain on individuals, families and society. This study aims to investigate whether there is Frontal Theta Asymmetry (FTA) in depressed patients, and whether FTAs are related to depression severity and cognitive function changes in depressed patients.

METHODS

Participants who met the inclusion criteria were enrolled in this study. Socio-demographic data of each participant were recorded. Zung's self-rating Depression Scale was used to assess the depression status of participants. P300 was used to evaluate the cognitive function of participants. EEG data from participants were collected by the NeuroScan SynAmps RT EEG system. t-test, Wilcoxon rank-sum test and Chi-square test were used to detect the differences of different variables between the two groups. Multiple linear regression analysis and multiple logistic regression analysis were used to analyze relationships between FTAs in different regions and participants' depression status and cognitive function.

RESULTS

A total of 66 depressed participants and 47 healthy control participants were included in this study. The theta spectral power of the left frontal lobe was slightly stronger than that of the right frontal lobe in the depression group, while the opposite was true in the healthy control group. The FTA in F3/F4 had certain effects on the emergence of depression in participants, the emergence of depression in participants and Changes in cognitive function.

CONCLUSIONS

FTAs are helpful to assess the severity of depression and early identify cognitive impairment in patients with depression.

Altered Cortical Information Interaction During Respiratory Events in Children with Obstructive Sleep Apnea-Hypopnea Syndrome

Obstructive sleep apnea-hypopnea syndrome (OSAHS) significantly impairs children's growth and cognition. This study aims to elucidate the pathophysiological mechanisms underlying OSAHS in children, with a particular focus on the alterations in cortical information interaction during respiratory events. We analyzed sleep electroencephalography before, during, and after events, utilizing Symbolic Transfer Entropy (STE) for brain network construction and information flow assessment. The results showed a significant increase in STE after events in specific frequency bands during N2 and rapid eye movement (REM) stages, along with increased STE during N3 stage events. Moreover, a noteworthy rise in the information flow imbalance within and between hemispheres was found after events, displaying unique patterns in central sleep apnea and hypopnea. Importantly, some of these alterations were correlated with symptom severity. These findings highlight significant changes in brain region coordination and communication during respiratory events, offering novel insights into OSAHS pathophysiology in children.

Changes in Functional Connectivity of Hippocampal Subregions in Patients with Obstructive Sleep Apnea after Six Months of Continuous Positive Airway Pressure Treatment

Previous studies have shown that the structural and functional impairments of hippocampal subregions in patients with obstructive sleep apnea (OSA) are related to cognitive impairment. Continuous positive airway pressure (CPAP) treatment can improve the clinical symptoms of OSA. Therefore, this study aimed to investigate functional connectivity (FC) changes in hippocampal subregions of patients with OSA after six months of CPAP treatment (post-CPAP) and its relationship with neurocognitive function. We collected and analyzed baseline (pre-CPAP) and post-CPAP data from 20 patients with OSA, including sleep monitoring, clinical evaluation, and resting-state functional magnetic resonance imaging. The results showed that compared with pre-CPAP OSA patients, the FC between the right anterior hippocampal gyrus and multiple brain regions, and between the left anterior hippocampal gyrus and posterior central gyrus were reduced in post-CPAP OSA patients. By contrast, the FC between the left middle hippocampus and the left precentral gyrus was increased. The changes in FC in these brain regions were closely related to cognitive dysfunction. Therefore, our findings suggest that CPAP treatment can effectively change the FC patterns of hippocampal subregions in patients with OSA, facilitating a better understanding of the neural mechanisms of cognitive function improvement, and emphasizing the importance of early diagnosis and timely treatment of OSA.

Sleep Technology

Pediatric sleep providers frequently encounter issues related to sleep technology in clinical settings. In this review article, we discuss technical issues related to standard polysomnography, research on putative complementary novel metrics derived from polysomnographic signals as well as research on home sleep apnea testing in children and consumer sleep devices. Although developments across several of these domains are exciting, it remains a rapidly evolving area. When evaluating innovative devices and home sleep testing approaches, clinicians should be mindful of accurately interpreting diagnostic agreement statistics to apply these technologies appropriately.

Disrupted relationship between intrinsic neural timescales and alpha peak frequency during unconscious states - A high-density EEG study

Our brain processes the different timescales of our environment's temporal input stochastics. Is such a temporal input processing mechanism key for consciousness? To address this research question, we calculated measures of input processing on shorter (alpha peak frequency, APF) and longer (autocorrelation window, ACW) timescales on resting-state high-density EEG (256 channels) recordings and compared them across different consciousness levels (awake/conscious, ketamine and sevoflurane anaesthesia, unresponsive wakefulness, minimally conscious state). We replicate and extend previous findings of: (i) significantly longer ACW values, consistently over all states of unconsciousness, as measured with ACW-0 (an unprecedented longer version of the well-know ACW-50); (ii) significantly slower APF values, as measured with frequency sliding, in all four unconscious states. Most importantly, we report a highly significant correlation of ACW-0 and APF in the conscious state, while their relationship is disrupted in the unconscious states. In sum, we demonstrate the relevance of the brain's capacity for input processing on shorter (APF) and longer (ACW) timescales - including their relationship - for consciousness. Albeit indirectly, e.g., through the analysis of electrophysiological activity at rest, this supports the mechanism of temporo-spatial alignment to the environment's temporal input stochastics, through relating different neural timescales, as one key predisposing factor of consciousness.

Sensorimotor Cortical Activity during Respiratory Arousals in Obstructive Sleep Apnea

Intensity of respiratory cortical arousals (RCA) is a pathophysiologic trait in obstructive sleep apnea (OSA) patients. We investigated the brain oscillatory features related to respiratory arousals in moderate and severe OSA. Raw electroencephalography (EEG) data recorded during polysomnography (PSG) of 102 OSA patients (32 females, mean age 51.6 ± 12 years) were retrospectively analyzed. Among all patients, 47 had moderate (respiratory distress index, RDI = 15−30/h) and 55 had severe (RDI > 30/h) OSA. Twenty RCA per sleep stage in each patient were randomly selected and a total of 10131 RCAs were analyzed. EEG signals obtained during, five seconds before and after the occurrence of each arousal were analyzed. The entropy (approximate (ApEn) and spectral (SpEn)) during each sleep stage (N1, N2 and REM) and area under the curve (AUC) of the EEG signal during the RCA was computed. Severe OSA compared to moderate OSA patients showed a significant decrease (p < 0.0001) in the AUC of the EEG signal during the RCA. Similarly, a significant decrease in spectral entropy, both before and after the RCA was observed, was observed in severe OSA patients when compared to moderate OSA patients. Contrarily, the approximate entropy showed an inverse pattern. The highest increase in approximate entropy was found in sleep stage N1. In conclusion, the dynamic range of sensorimotor cortical activity during respiratory arousals is sleep-stage specific, dependent on the frequency of respiratory events and uncoupled from autonomic activation. These findings could be useful for differential diagnosis of severe OSA from moderate OSA.

Gain-of-function mutations in KCNK3 cause a developmental disorder with sleep apnea

Sleep apnea is a common disorder that represents a global public health burden. KCNK3 encodes TASK-1, a K+ channel implicated in the control of breathing, but its link with sleep apnea remains poorly understood. Here we describe a new developmental disorder with associated sleep apnea (developmental delay with sleep apnea, or DDSA) caused by rare de novo gain-of-function mutations in KCNK3. The mutations cluster around the 'X-gate', a gating motif that controls channel opening, and produce overactive channels that no longer respond to inhibition by G-protein-coupled receptor pathways. However, despite their defective X-gating, these mutant channels can still be inhibited by a range of known TASK channel inhibitors. These results not only highlight an important new role for TASK-1 K+ channels and their link with sleep apnea but also identify possible therapeutic strategies.

Neurocognitive Consequences in Children with Sleep Disordered Breathing: Who Is at Risk?

Sleep-disordered breathing (SDB) is a prevalent disease in children characterized by snoring and narrowing of the upper airway leading to gas exchange abnormalities during sleep as well as sleep fragmentation. SDB has been consistently associated with problematic behaviors and adverse neurocognitive consequences in children but causality and determinants of susceptibility remain incompletely defined. Since the 1990s several studies have enlightened these associations and consistently reported poorer academic performance, lower scores on neurocognitive tests, and behavioral abnormalities in children suffering from SDB. However, not all children with SDB develop such consequences, and severity of SDB based on standard diagnostic indices has often failed to discriminate among those children with or without neurocognitive risk. Accordingly, a search for discovery of markers and clinically useful tools that can detect those children at risk for developing cognitive and behavioral deficits has been ongoing. Here, we review the advances in this field and the search for possible detection approaches and unique phenotypes of children with SDB who are at greater risk of developing neurocognitive consequences.

Slow EEG Oscillation to Characterize Pediatric Sleep Apnea and Associated Cognitive Impairments

Previous studies have suggested that the typical slow oscillations (SO) characteristics during sleep could be modified in the presence of pediatric obstructive sleep apnea (OSA). Here, we evaluate whether these modifications are significant and if they may reflect cognitive deficits. We recorded the overnight electroencephalogram (EEG) of 294 pediatric subjects (5-9 years old) using eight channels. Then, we divided the cohort in three OSA severity groups (no OSA, mild, and moderate/severe) to characterize the corresponding SO using the spectral maximum in the slow wave sleep (SWS) band δ₁: 0.1-2 Hz (Maxs o), as well as the frequency where this maximum is located (FreqMaxso). Spectral entropy (SpecEn) from δ₁ was also included in the analyses. A correlation analysis was performed to evaluate associations of these spectral measures with six OSA-related clinical variables and six cognitive scores. Our results indicate that Maxso could be used as a moderate/severe OSA biomarker while providing useful information regarding verbal and visuo-spatial impairments, and that FreqMaxso emerges as an even more robust indicator of visuospatial function. In addition, we uncovered novel insights regarding the ability of SpecEn in δ₁ to characterize OSA-related disruption of sleep homeostasis. Our findings suggest that the information from SO may be useful to automatically characterize moderate/severe pediatric OSA and its cognitive consequences. Clinical Relevance- This study contributes towards reaching an objective quantifiable and automated assessment of the potential cognitive consequences of pediatric sleep apnea.

Conventional Machine Learning Methods Applied to the Automatic Diagnosis of Sleep Apnea

The overnight polysomnography shows a range of drawbacks to diagnose obstructive sleep apnea (OSA) that have led to the search for artificial intelligence-based alternatives. Many classic machine learning methods have been already evaluated for this purpose. In this chapter, we show the main approaches found in the scientific literature along with the most used data to develop the models, useful and large easily available databases, and suitable methods to assess performances. In addition, a range of results from selected studies are presented as examples of these methods. Very high diagnostic performances are reported in these results regardless of the approaches taken. This leads us to conclude that conventional machine learning methods are useful techniques to develop new OSA diagnosis simplification proposals and to act as benchmark for other more recent methods such as deep learning.