Investigating the complexity of respiratory patterns during the laryngeal chemoreflex

被引:14
作者
Dragomir, Andrei [1 ]
Akay, Yasemin [1 ]
Curran, Aidan K. [2 ]
Akay, Metin [1 ]
机构
[1] Arizona State Univ, Harrington Dept Bioengn, Ira A Fulton Sch Engn, Tempe, AZ 85287 USA
[2] Dartmouth Med Sch, Dept Physiol, Hanover, NH 03756 USA
关键词
D O I
10.1186/1743-0003-5-17
中图分类号
R318 [生物医学工程];
学科分类号
0831 [生物医学工程];
摘要
Background: The laryngeal chemoreflex exists in infants as a primary sensory mechanism for defending the airway from the aspiration of liquids. Previous studies have hypothesized that prolonged apnea associated with this reflex may be life threatening and might be a cause of sudden infant death syndrome. Methods: In this study we quantified the output of the respiratory neural network, the diaphragm EMG signal, during the laryngeal chemoreflex and eupnea in early postnatal (3-10 days) piglets. We tested the hypothesis that diaphragm EMG activity corresponding to reflex-related events involved in clearance (restorative) mechanisms such as cough and swallow exhibit lower complexity, suggesting that a synchronized homogeneous group of neurons in the central respiratory network are active during these events. Nonlinear dynamic analysis was performed using the approximate entropy to asses the complexity of respiratory patterns. Results: Diaphragm EMG, genioglossal activity EMG, as well as other physiological signals ( tracheal pressure, blood pressure and respiratory volume) were recorded from 5 unanesthetized chronically instrumented intact piglets. Approximate entropy values of the EMG during cough and swallow were found significantly (p < 0.05 and p < 0.01 respectively) lower than those of eupneic EMG. Conclusion: Reduced complexity values of the respiratory neural network output corresponding to coughs and swallows suggest synchronous neural activity of a homogeneous group of neurons. The higher complexity values exhibited by eupneic respiratory activity are the result of a more random behaviour, which is the outcome of the integrated action of several groups of neurons involved in the respiratory neural network.
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页数:8
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