Key result
Frequency domain analysis is more suitable than time domain analysis for quantifying complex sympathetic nerve discharge signals, which may help maintain cardiovascular homeostasis.
Frequency domain analysis is superior to time domain analysis for quantifying the complex, multi-frequency rhythmic activity of sympathetic nerve discharge.
Researchers should prioritize spectral methods for autonomic signals; leaves open clinical translation pending validation.
Like virtually all other physiological control systems, the sympathetic nervous system controlling cardiovascular function is characterized by the presence of rhythmic activity. Despite the prevalence of rhythms, their function is often not obvious, which leads to the question, what can one learn about the neural control of autonomic function by studying sympathetic nervous system rhythms? 2. Sympathetic nerve discharge (SND) is characterized by a mixture of periodicities ranging between approximately 0.04 and 10 Hz, depending on the physiological conditions, type of nerve being analysed and the species. The present article illustrates why frequency domain (power density spectral) analysis is more suitable than time domain (autocorrelation) analysis to quantify a complex signal (i.e. one with multiple frequency components) such as SND. 3. The present article entertains the possibilities that rhythmic activity may lead to more effective activation of sympathetic neurons than randomly occurring activity, that rhythmicity is important for coordinating activity in different sympathetic nerves and in formulating complex cardiovascular response patterns and that sympathetic rhythmicity may help maintain homeostasis.
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Barman et al. (2007) conducted a review in Sympathetic nerve discharge rhythms. Frequency domain analysis vs. Time domain analysis was evaluated. Frequency domain analysis is more suitable than time domain analysis for quantifying complex sympathetic nerve discharge signals, which may help maintain cardiovascular homeostasis.
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