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Frequency modulation of the autonomic nervous systems by very‐low frequency rhythms in heart rate variability
Author(s) -
Zhong Yuru,
Jan KungMing,
Moore Leon C.,
Chon Ki H.
Publication year - 2006
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.20.5.a1425
Subject(s) - heart rate variability , rhythm , autonomic nervous system , heart rate , heart rhythm , medicine , frequency modulation , neuroscience , cardiology , biology , computer science , telecommunications , blood pressure , radio frequency
Interactions between the sympathetic nervous system (SNS) and the parasympathetic nervous system (PNS) have been long recognized, but the presence of further interactions between these systems and the mechanisms responsible for the spectral power in the very low frequency (VLF) rhythms of heart rate (HR) data has not been investigated. The goal of our study was to determine if the mechanisms responsible for the VLF rhythms interact with the autonomic nervous system (ANS) components (SNS & PNS). ECG data were collected from 7 healthy subjects. The subjects were instructed to breath at a fixed frequency of 0.3 Hz to enable more accurate extraction of the time‐varying amplitudes estimated via a wavelet transform (WT). A double WT was used to examine how the frequencies associated with the ANS are modulated by the presence of the VLF. First, a WT was used on the HR data to separate the low frequency (LF) and high frequency (HF) components and to extract the time‐varying amplitudes in these two frequency bands. Next, a second WT was performed on the extracted amplitudes. This resultant double WT revealed VLF frequency modulation (FM) in both bands, with a peak centered at 0.01–0.03 Hz, as well as FM of HF by the LF. These results confirm the presence of nonlinear interactions between the LF and HF, and suggest that these couplings are modulated by the VLF. Furthermore, WT is a necessary and important analysis tool for this purpose because it is designed to handle time‐varying dynamics associated with such nonlinear interaction phenomena. Funded by HL076358