Central Sleep Apnea Alters Neuronal Excitability and Increases the Randomness in Sleep-Wake Transitions

Hila Dvir; Shu Guo; Shlomo Havlin; Ni Xin; Tai Jun; Daqing Li; Xu Zhifei; Rui Kang; Ronny P. Bartsch

doi:10.1109/tbme.2020.2979287

Central Sleep Apnea Alters Neuronal Excitability and Increases the Randomness in Sleep-Wake Transitions

Hila Dvir, Shu Guo, Shlomo Havlin, Ni Xin, Tai Jun, Daqing Li, Xu Zhifei, Rui Kang, Ronny P. Bartsch

Department of Physics

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

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.

Original language	English
Article number	9027993
Pages (from-to)	3185-3194
Number of pages	10
Journal	IEEE Transactions on Biomedical Engineering
Volume	67
Issue number	11
DOIs	https://doi.org/10.1109/tbme.2020.2979287
State	Published - Nov 2020

Bibliographical note

Publisher Copyright:
© 1964-2012 IEEE.

Funding

Foundation under Grant 7194262. (Hila Dvir and Shu Guo contributed Manuscript received October 27, 2019; revised January 8, 2020; accepted March 2, 2020. Date of publication March 9, 2020; date of current version October 20, 2020. This work was supported in part by the Shulamit Aloni Fellowship for Advancing Women in Exact Sciences and Engineering, Ministry of Science and Technology, Israel under Grant 3-13276, in part by the Colman-Soref Grant foundation Fellowship of the Council for Higher Education, Israel under Grant kra/colman/194, in part by the Israel Science Foundation under Grant 1657/16, in part by the German Israeli Foundation under Grant I-1372-303.7/2016, in part by Capital Funds for Health Improvement and Research under Grant 2018-1-2091, in part by Beijing Municipal Science and Technology Project under Grant Z161100000116050, in part by Pediatric Medical Coordinated Development Center of Beijing Municipal Administration under Grant XTZD20180101, and in part by Beijing Natural Science This work was supported in part by the Shulamit Aloni Fellowship for Advancing Women in Exact Sciences and Engineering, Ministry of Science and Technology, Israel under Grant 3-13276, in part by the Colman-Soref Grant foundation Fellowship of the Council for Higher Education, Israel under Grant kra/colman/194, in part by the Israel Science Foundation under Grant 1657/16, in part by the German Israeli Foundation under Grant I-1372-303.7/2016, in part by Capital Funds for Health Improvement and Research under Grant 2018-1-2091, in part by Beijing Municipal Science and Technology Project under Grant Z161100000116050, in part by Pediatric Medical Coordinated Development Center of Beijing Municipal Administration under Grant XTZD20180101, and in part by Beijing Natural Science Foundation under Grant 7194262.

Funders	Funder number
Beijing Natural Science
Capital Funds for Health Improvement and Research	2018-1-2091
Colman-Soref Grant foundation
Council for Higher Education, Israel	kra/colman/194
German Israeli Foundation	I-1372-303.7/2016
Israel Science Foundation	1657/16
Natural Science Foundation of Beijing Municipality	7194262
Ministry of science and technology, Israel	3-13276
Beijing Municipal Science and Technology Commission	Z161100000116050
Beijing Municipal Administration of Hospitals	XTZD20180101

Keywords

Central sleep apnea
excitability threshold
exponential distribution
power-law distribution
sleep arousals
sleep modeling
sleep-wake dynamics
wake-bout durations

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10.1109/tbme.2020.2979287

Cite this

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title = "Central Sleep Apnea Alters Neuronal Excitability and Increases the Randomness in Sleep-Wake Transitions",

abstract = "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.",

keywords = "Central sleep apnea, excitability threshold, exponential distribution, power-law distribution, sleep arousals, sleep modeling, sleep-wake dynamics, wake-bout durations",

author = "Hila Dvir and Shu Guo and Shlomo Havlin and Ni Xin and Tai Jun and Daqing Li and Xu Zhifei and Rui Kang and Bartsch, {Ronny P.}",

note = "Publisher Copyright: {\textcopyright} 1964-2012 IEEE.",

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AU - Guo, Shu

AU - Havlin, Shlomo

AU - Xin, Ni

AU - Jun, Tai

AU - Li, Daqing

AU - Zhifei, Xu

AU - Kang, Rui

AU - Bartsch, Ronny P.

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N2 - 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.

AB - 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.

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Central Sleep Apnea Alters Neuronal Excitability and Increases the Randomness in Sleep-Wake Transitions

Abstract

Bibliographical note

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Keywords

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