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Updated: Aug 14, 2026
Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
Published on: June 15, 2018
Scatterplot analysis of EEG slow-wave magnitude and heart rate variability: an integrative exploration of cerebral
Terry B J Kuo1, Cheryl C H Yang
1Institute of Neuroscience, Tzu Chi University, Hualien 970, Taiwan.
Study Objectives:
To explore interactions between cerebral cortical and autonomic functions in different sleep-wake states.
Design:
Active waking (AW), quiet sleep (QS), and paradoxical sleep (PS) of adult male Wistar-Kyoto rats (WKY) on their daytime sleep were compared.
Participants:
Ten WKY.
Interventions:
All rats had electrodes implanted for polygraphic recordings. One week later, a 6-hour daytime sleep-wakefulness recording session was performed.
Measurements And Results:
A scatterplot analysis of electroencephalogram (EEG) slow-wave magnitude (0.5-4 Hz) and heart rate variability (HRV) was applied in each rat. The EEG slow-wave-RR interval scatterplot from all of the recordings revealed a propeller-like pattern. If the scatterplot was divided into AW, PS, and QS according to the corresponding EEG mean power frequency and nuchal electromyogram, the EEG slow wave-RR interval relationship became nil, negative, and positive for AW, PS, and QS, respectively. A significant negative relationship was found for EEG slow-wave and high-frequency power of HRV (HF) coupling during PS and for EEG slow wave and low-frequency power of HRV to HF ratio (LF/HF) coupling during QS. The optimal time lags for the slow wave-LF/HF relationship were different between PS and QS.
Conclusions:
Bradycardia noted in QS and PS was related to sympathetic suppression and vagal excitation, respectively. The EEG slow wave-HRV scatterplot may provide unique insights into studies of sleep, and such a relationship may delineate the sleep-state-dependent fluctuations in autonomic nervous system activity.
