Comparison between spectral analysis and symbolic dynamics as a tool for cardiac autonomic modulation study in rats and mice

Abstract

The study of cardiovascular variability, such as heart rate variability (HRV), is of great importance since it allows, in an indirect way, the assessment of cardiovascular autonomic function. Commonly, the HRV is represented by the oscillations of cardiac intervals over time, and classical methods for evaluation of these oscillations include time and frequency domain parameters. In the frequency domain, spectral analysis quantifies the power of each frequency component present in HRV, representing the cardiac sympathetic and parasympathetic modulation by the total power in specific frequency bands. The spectral analysis is very important and its appearance was a milestone in the study of HRV. However, as it is based on a purely linear model, this approach becomes limited since the regulatory mechanisms of HRV are known to be nonlinear. An interesting alternative to the spectral analysis appeared in 2001, namely symbolic dynamics, and take the advantage of not being restricted to a linear model. Symbolic dynamics has been demonstrating to be very useful for analysis of cardiac autonomic modulation, in some cases with better performances than spectral analysis. Despite several scientific studies showing the importance of symbolic analysis, most of them studied humans, generating an application gap of this methodology for experimental animals such as rats and mice. This project aims at studying the validity of symbolic analysis for the study of cardiac autonomic modulation in rats and mice and compares its performance to the spectral analysis, creating a background for future studies. The data to be used in this project had already been collected in several other studies in Cardiovascular Physiology Lab of FMRP derived from normal and pathophysiological experimental models, as well as after administration of autonomic blockers (adrenergic and cholinergic types).