Interactions of central and autonomic nervous systems in patients with sleep apnea–hypopnea syndrome during sleep

Wang, Tingting; Yang, Juan; Song, Yingjie; Pang, Feng; Guo, Xinwen; Luo, Yuxi

doi:10.1007/s11325-021-02429-6

Cited by 3 publications

(3 citation statements)

References 42 publications

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“…Additionally, novel statistical measures like transfer entropy have revealed that during sleep, more information flows from the autonomic to the central nervous system than in the reverse direction. Furthermore, specific activations of the autonomic nervous system during sleep reliably lead to distinct activity in the central nervous system, both in terms of cortical location and frequency content of EEG 27 . The fact that our ECG-based neural network performs comparably to PSG in determining sleep stages aligns with findings of a healthy interaction between the autonomic and central nervous systems and the idea that sleep is important for the brain and body.…”

Section: Discussionmentioning

confidence: 99%

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Electrocardiogram sleep staging on par with expert polysomnography

Jones,

Itti,

Sheth

2023

Preprint

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Accurate classification of sleep stages is crucial in sleep medicine and neuroscience research, providing valuable insights for diagnoses and understanding of brain states. The current gold standard for this task is polysomnography (PSG), an expensive and cumbersome process involving numerous electrodes, often performed in an unfamiliar clinic and professionally annotated. Although commercial devices like smartwatches track sleep, their performance compares poorly with PSG. To address this, we present a neural network that achieves gold-standard levels of agreement using a single lead of electrocardiogram (ECG) data (five-stage Cohen's kappa = 0.725 on subjects 5 to 90 years old). Our method offers an inexpensive, automated, and convenient alternative. Cardiosomnography, or a sleep study conducted with electrocardiography only, could take expert-level sleep studies outside the confines of clinics and laboratories and into realistic settings. This would render higher-quality studies accessible to a broader community, enabling improved sleep research and sleep-related healthcare interventions.

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Section: Discussionmentioning

confidence: 99%

“…The effectiveness of ECG in sleep medicine for detecting sleep disorders, such as apnea, has been demonstrated by numerous studies 27,31,32 . Building upon these findings, we propose that cardiosomnography—a sleep study conducted with electrocardiography only—can complement and supplement PSG in sleep medicine.…”

Section: Discussionmentioning

confidence: 99%

Electrocardiogram sleep staging on par with expert polysomnography

Jones,

Itti,

Sheth

2023

Preprint

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“…2019 ). Furthermore, a study using multivariate TE found that OSAHS severity significantly affected the information strength of the brain during light sleep ( Wang et al. 2022 ).…”

Section: Discussionmentioning

confidence: 99%

Abnormal interaction between cortical regions of obstructive sleep apnea hypopnea syndrome children

Shi,

Pang,

Chen

et al. 2023

Cerebral Cortex

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Obstructive sleep apnea hypopnea syndrome negatively affects the cognitive function of children. This study aims to find potential biomarkers for obstructive sleep apnea hypopnea syndrome in children by investigating the patterns of sleep electroencephalography networks. The participants included 16 mild obstructive sleep apnea hypopnea syndrome children, 12 severe obstructive sleep apnea hypopnea syndrome children, and 13 healthy controls. Effective brain networks were constructed using symbolic transfer entropy to assess cortical information interaction. The information flow pattern in the participants was evaluated using the parameters cross-within variation and the ratio of posterior-anterior information flow. Obstructive sleep apnea hypopnea syndrome children had a considerably higher symbolic transfer entropy in the full frequency band of N1, N2, and rapid eye movement (REM) stages (P < 0.05), and a significantly lower symbolic transfer entropy in full frequency band of N3 stage (P < 0.005), in comparison with the healthy controls. In addition, the cross-within variation of the β frequency band across all sleep stages were significantly lower in the obstructive sleep apnea hypopnea syndrome group than in the healthy controls (P < 0.05). What is more, the posterior-anterior information flowin the β frequency band of REM stage was significantly higher in mild obstructive sleep apnea hypopnea syndrome children than in the healthy controls (P < 0.05). These findings may serve as potential biomarkers for obstructive sleep apnea hypopnea syndrome in children and provide new insights into the pathophysiological mechanisms.

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