Association between slow-wave activity, cognition and behaviour in children with sleep-disordered breathing

Weichard, Aidan; Walter, Lisa M.; Hollis, Samantha; Nixon, Gillian M.; Davey, Margot J; Horne, Rosemary Sylvia Claire; Biggs, Sarah Nichole

doi:10.1016/j.sleep.2016.06.004

Cited by 16 publications

(4 citation statements)

References 36 publications

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“…Sleep EEG has shown the potential to provide physiologically based cognitive information (Weichard et al, 2016;Brockmann et al, 2018Brockmann et al, , 2020Christiansz et al, 2018) that would obviate the need for traditional neurocognitive tests, yet secure an estimate of risk for OSA-associated morbidities. However, all previous studies exploring sleep EEG and cognition focused on very specific EEG attributes, such as spindles or delta activity (Weichard et al, 2016;Brockmann et al, 2018Brockmann et al, , 2020Christiansz et al, 2018). Consequently, how OSA alters the overnight electrical behavior of the brain of children, and whether such alterations indicate cognitive deficits, remains unclear.…”

Section: Introductionmentioning

confidence: 99%

Pediatric Sleep Apnea: The Overnight Electroencephalogram as a Phenotypic Biomarker

et al. 2021

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Pediatric obstructive sleep apnea (OSA) is a prevalent disorder that disrupts sleep and is associated with neurocognitive and behavioral negative consequences, potentially hampering the development of children for years. However, its relationships with sleep electroencephalogram (EEG) have been scarcely investigated. Here, our main objective was to characterize the overnight EEG of OSA-affected children and its putative relationships with polysomnographic measures and cognitive functions. A two-step analysis involving 294 children (176 controls, 57% males, age range: 5–9 years) was conducted for this purpose. First, the activity and irregularity of overnight EEG spectrum were characterized in the typical frequency bands by means of relative spectral power and spectral entropy, respectively: δ1 (0.1–2 Hz), δ2 (2–4 Hz), θ (4–8 Hz), α (8–13 Hz), σ (10–16 Hz), β1 (13–19 Hz), β2 (19–30 Hz), and γ (30–70 Hz). Then, a correlation network analysis was conducted to evaluate relationships between them, six polysomnography variables (apnea–hypopnea index, respiratory arousal index, spontaneous arousal index, overnight minimum blood oxygen saturation, wake time after sleep onset, and sleep efficiency), and six cognitive scores (differential ability scales, Peabody picture vocabulary test, expressive vocabulary test, design copying, phonological processing, and tower test). We found that as the severity of the disease increases, OSA broadly affects sleep EEG to the point that the information from the different frequency bands becomes more similar, regardless of activity or irregularity. EEG activity and irregularity information from the most severely affected children were significantly associated with polysomnographic variables, which were coherent with both micro and macro sleep disruptions. We hypothesize that the EEG changes caused by OSA could be related to the occurrence of respiratory-related arousals, as well as thalamic inhibition in the slow oscillation generation due to increases in arousal levels aimed at recovery from respiratory events. Furthermore, relationships between sleep EEG and cognitive scores emerged regarding language, visual–spatial processing, and executive function with pronounced associations found with EEG irregularity in δ1 (Peabody picture vocabulary test and expressive vocabulary test maximum absolute correlations 0.61 and 0.54) and β2 (phonological processing, 0.74; design copying, 0.65; and Tow 0.52). Our results show that overnight EEG informs both sleep alterations and cognitive effects of pediatric OSA. Moreover, EEG irregularity provides new information that complements and expands the classic EEG activity analysis. These findings lay the foundation for the use of sleep EEG to assess cognitive changes in pediatric OSA.

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Section: Introductionmentioning

confidence: 99%

Pediatric Sleep Apnea: The Overnight Electroencephalogram as a Phenotypic Biomarker

et al. 2021

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“…For instance, Youssef and colleagues [39] reported in a meta-analytic study a high incidence of 20% to 30% of OSA in patients with full syndromal ADHD as well as attentional deficits in 95% of patients with OSA. Most previous studies on the association between OSA and behavioral functions in children have reported that OSA is associated with internalizing and externalizing problems such as hyperactivity, attention deficits, aggressiveness, anxiety, and social and thought problems in children [40][41][42][43][44].…”

Section: Discussionmentioning

confidence: 99%

Associations among High Risk for Sleep-disordered Breathing, Related Risk Factors, and Attention Deficit/Hyperactivity Symptoms in Elementary School Children

Kim

et al. 2020

Clin Psychopharmacol Neurosci

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Objective Habitual snoring is a common problem in children. We evaluated the association between a high risk for sleep-disordered breathing and attention deficit/hyperactivity symptoms. Methods Parents of 13,560 children aged 6 to 12 years responded to questionnaires including items on habitual snoring and the Korean attention deficit/hyperactivity disorder rating scale. The snoring score comprised the number of “yes” responses to habitual-snoring items, and a high risk for sleep-disordered breathing was defined as a snoring score ≥ 2. Results The odds ratio (OR) of a high risk for sleep-disordered breathing was significantly higher in boys (OR = 1.47; p < 0.001), overweight children (OR = 2.20; p < 0.001), and children with current secondhand-smoking exposure (OR = 1.38; p < 0.001). The Korean attention deficit/hyperactivity disorder rating scale score increased significantly with the snoring score (0 vs. 1, B = 1.56, p < 0.001; 0 vs. 2, B = 2.44, p < 0.001; 0 vs. 3, B = 2.48, p < 0.001; 0 vs. 4, B = 3.95; p < 0.001). Conclusion Our study confirms several risk factors of sleep-disordered breathing, namely male sex, overweight, and exposure to tobacco smoking, and found a positive association between habitual snoring and attention deficit/hyperactivity symptoms.

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“…A study of healthy adults showed that increases in REM prefrontal theta power activity are associated with improved emotional memory consolidation [ 17 ] and that abnormal increases in faster REM frequencies (frontal REM gamma activity) reflect amygdala reactivity on fMRI studies [ 18 ]. A number of pediatric studies also report associations between NREM 3 (N3, deep sleep) and NREM SWA and externalizing behaviors in TD children and those with pediatric sleep disorder studies [ 19 , 20 , 21 ]. Insight into associations between REM and NREM sleep with problematic behaviors in children with ASD could identify potential objective biomarkers of mood or disruptive behavior disorders in a population with known restricted communication skills as well as serve as potential targets for sleep-based therapeutics.…”

Section: Introductionmentioning

confidence: 99%

Neurobehavioral Associations with NREM and REM Sleep Architecture in Children with Autism Spectrum Disorder

et al. 2022

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Objective: Insomnia and daytime behavioral problems are common issues in pediatric autism spectrum disorder (ASD), yet specific underlying relationships with NonRapid Eye Movement sleep (NREM) and Rapid Eye Movement (REM) sleep architecture are understudied. We hypothesize that REM sleep alterations (REM%, REM EEG power) are associated with more internalizing behaviors and NREM sleep deficits (N3%; slow wave activity (SWA) 0.5–3 Hz EEG power) are associated with increased externalizing behaviors in children with ASD vs. typical developing controls (TD). Methods: In an age- and gender-matched pediatric cohort of n = 23 ASD and n = 20 TD participants, we collected macro/micro sleep architecture with overnight home polysomnogram and daytime behavior scores with Child Behavior Checklist (CBCL) scores. Results: Controlling for non-verbal IQ and medication use, ASD and TD children have similar REM and NREM sleep architecture. Only ASD children show positive relationships between REM%, REM theta power and REM beta power with internalizing scores. Only TD participants showed an inverse relationship between NREM SWA and externalizing scores. Conclusion: REM sleep measures reflect concerning internalizing behaviours in ASD and could serve as a biomarker for mood disorders in this population. While improving deep sleep may help externalizing behaviours in TD, we do not find evidence of this relationship in ASD.

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Association between slow-wave activity, cognition and behaviour in children with sleep-disordered breathing

Cited by 16 publications

References 36 publications

Pediatric Sleep Apnea: The Overnight Electroencephalogram as a Phenotypic Biomarker

Pediatric Sleep Apnea: The Overnight Electroencephalogram as a Phenotypic Biomarker

Associations among High Risk for Sleep-disordered Breathing, Related Risk Factors, and Attention Deficit/Hyperactivity Symptoms in Elementary School Children

Neurobehavioral Associations with NREM and REM Sleep Architecture in Children with Autism Spectrum Disorder

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