Original Research ARTICLE
Association between phase coupling of respiratory sinus arrhythmia and slow wave brain activity during sleep
- 1Biosystem Engineering, Yamagata University, Japan
Phase coupling of respiratory sinus arrhythmia (RSA) has been proposed to be an alternative measure for evaluating autonomic nervous system activity. The aim of this study was to analyze how phase coupling of RSA is altered during sleep, in order to explore whether this measure is a predictor of slow wave sleep (SWS). Overnight electroencephalograms (EEG), electrocardiograms (ECG), and breathing using inductance plethysmography were recorded from 30 healthy volunteers (six females, age range 21 – 64, 31.6 ± 14.7 years). Slow wave activity was evaluated by the envelope of the amplitude of the EEG delta-wave (0.5 – 4 Hz). The RSA was extracted from the change in the R-R interval (RRI) by band-pass filter, where pass band frequencies were determined from the profile of the power spectral density for respiration. The analytic signals of RSA and respiration were obtained by Hilbert transform, after which the amplitude of RSA (ARSA) and the degree of phase coupling (lambda) were quantified. Additionally, the normalized high-frequency component (HFn) of the frequency-domain heart rate variability (HRV) was calculated. Using auto- and cross-correlation analyses, we found that overnight profiles of lambda and delta-wave were correlated, with significant cross-correlation coefficients (0.461 ± 0.107). The delta-wave and HFn were also correlated (0.426 ± 0.115). These correlations were higher than that for the relationship between delta-wave and ARSA (0.212 ± 0.161). The variation of lambda precedes the onset of the delta-wave by approximately 3 min, suggesting a vagal enhancement prior to the onset of SWS. Auto correlation analysis revealed that the periodicity of lambda was quite similar to that of the delta-wave (88.3 ± 15.7 min vs. 88.6 ± 16.3 min, lambda-cycle = 0.938 × delta-cycle + 5.77 min, r = 0.902). These results suggest that phase coupling analysis of RSA appears to be a marker for predicting SWS intervals, thereby complementing other noninvasive tools and diagnostic efforts.
Keywords: Autonomic Nervous System, slow wave sleep, respiratory sinus arrhythmia, phase coherence, sleep cycle
Received: 23 May 2018;
Accepted: 05 Sep 2018.
Edited by:Ahsan H. Khandoker, Khalifa University, United Arab Emirates
Reviewed by:Thomas Penzel, Charité Universitätsmedizin Berlin, Germany
Guanghao Sun, University of Electro-Communications, Japan
Copyright: © 2018 Niizeki and Saitoh. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Prof. Kyuichi Niizeki, Yamagata University, Biosystem Engineering, Yamagata, Japan, firstname.lastname@example.org