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Published in: Journal of NeuroEngineering and Rehabilitation 1/2008

Open Access 01-12-2008 | Research

Investigating the complexity of respiratory patterns during the laryngeal chemoreflex

Authors: Andrei Dragomir, Yasemin Akay, Aidan K Curran, Metin Akay

Published in: Journal of NeuroEngineering and Rehabilitation | Issue 1/2008

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Abstract

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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Metadata
Title
Investigating the complexity of respiratory patterns during the laryngeal chemoreflex
Authors
Andrei Dragomir
Yasemin Akay
Aidan K Curran
Metin Akay
Publication date
01-12-2008
Publisher
BioMed Central
Published in
Journal of NeuroEngineering and Rehabilitation / Issue 1/2008
Electronic ISSN: 1743-0003
DOI
https://doi.org/10.1186/1743-0003-5-17

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