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Central sleep apnea alters neuronal excitability and increases the randomness in sleep-wake transitions
IEEE Transactions on Biomedical Engineering ( IF 4.6 ) Pub Date : 2020-11-01 , DOI: 10.1109/tbme.2020.2979287
Hila Dvir , Shu Guo , Shlomo Havlin , Ni Xin , Tai Jun , Daqing Li , Xu Zhifei , Rui Kang , Ronny P. Bartsch

Objective: While most studies on Central Sleep Apnea (CSA) have focused on breathing and metabolic disorders, the neuronal dysfunction that causes CSA remains largely unknown. Here, we investigate the underlying neuronal mechanism of CSA by studying the sleep-wake dynamics as derived from hypnograms. Methods: We analyze sleep data of seven groups of subjects: healthy adults (n = 48), adults with obstructive sleep apnea (OSA) (n = 29), adults with CSA (n = 25), healthy children (n = 40), children with OSA (n = 18), children with CSA (n = 73) and CSA children treated with CPAP (n = 10). We calculate sleep-wake parameters based on the probability distributions of wake-bout durations and sleep-bout durations. We compare these parameters with results obtained from a neuronal model that simulates the interplay between sleep- and wake-promoting neurons. Results: We find that sleep arousals of CSA patients show a characteristic time scale (i.e., exponential distribution) in contrast to the scale-invariant (i.e., power-law) distribution that has been reported for arousals in healthy sleep. Furthermore, we show that this change in arousal statistics is caused by triggering more arousals of similar durations, which through our model can be related to a higher excitability threshold in sleep-promoting neurons in CSA patients. Conclusions: We propose a neuronal mechanism to shed light on CSA pathophysiology and a method to discriminate between CSA and OSA. We show that higher neuronal excitability thresholds can lead to complex reorganization of sleep-wake dynamics. Significance: The derived sleep parameters enable a more specific evaluation of CSA severity and can be used for CSA diagnosis and monitor CSA treatment.

中文翻译:

中枢性睡眠呼吸暂停改变神经元兴奋性并增加睡眠-觉醒过渡的随机性

目的:虽然大多数关于中枢性睡眠呼吸暂停 (CSA) 的研究都集中在呼吸和代谢紊乱上,但导致 CSA 的神经元功能障碍在很大程度上仍然未知。在这里,我们通过研究来自催眠图的睡眠-觉醒动态来研究 CSA 的潜在神经元机制。方法:我们分析了七组受试者的睡眠数据:健康成人(n = 48)、阻塞性睡眠呼吸暂停(OSA)成人(n = 29)、CSA成人(n = 25)、健康儿童(n = 40) 、OSA 儿童(n = 18)、CSA 儿童(n = 73)和接受 CPAP 治疗的 CSA 儿童(n = 10)。我们根据觉醒持续时间和睡眠持续时间的概率分布计算睡眠-觉醒参数。我们将这些参数与从模拟睡眠和唤醒神经元之间相互作用的神经元模型获得的结果进行比较。结果:我们发现 CSA 患者的睡眠觉醒显示出一个特征时间尺度(即指数分布),这与已报道的健康睡眠觉醒的尺度不变(即幂律)分布形成对比。此外,我们表明唤醒统计的这种变化是由触发更多类似持续时间的唤醒引起的,通过我们的模型,这可能与 CSA 患者睡眠促进神经元的更高兴奋性阈值有关。结论:我们提出了一种揭示 CSA 病理生理学的神经元机制和一种区分 CSA 和 OSA 的方法。我们表明,较高的神经元兴奋性阈值可导致睡眠-觉醒动态的复杂重组。意义:
更新日期:2020-11-01
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