Visualization of short-term heart period variability with network tools as a method for quantifying autonomic drive

Abstract

Introduction and purposeSignals from heart transplant recipients can be considered to be a natural source of information for a better understanding of the impact of the autonomic nervous system on the complexity of heart rate variability. Beat-to-beat heart rate variability can be represented as a network of increments between subsequent RR-intervals, which makes possible the visualization of short-term heart period fluctuations. Methods A network is constructed of vertices representing increments between subsequent RRintervals, and edges which connect adjacent RR-increments. Two modes of visualization of such a network are proposed. The method described is applied to nocturnal Holter signals recorded from healthy young people and from cardiac transplant recipients. Additionally, the analysis is performed on surrogate data: shuffled RR-intervals (to display short-range dependence), and shuffled phases of the Fourier Transform of RR-intervals (to filter out linear dependences).Results Important nonlinear properties of autonomic nocturnal regulation in short-term variability in healthy young persons are associated with RR-increments: accelerations and decelerations of a size greater than about 35 ms. They reveal that large accelerations are more likely antipersistent, while large decelerations are more likely persistent.Changes in RR-increments in a heart deprived of autonomic supervision are much lower than in a healthy individual, and appear to be maintained around a homeostatic state, but there are indications that this dynamics is nonlinear. ConclusionThe method is fruitful in the evaluation of the vagal activity -the quantity and quality of the vagal tone -during the nocturnal rest of healthy young people. The method also successfully extracts nonlinear effects related to intrinsic mechanisms of the heart regulation.Since the vagal part of autonomic regulation is considered to be responsible for nocturnal heart rhythm with large accelerations and decelerations, we hypothesize that vagal activity is a crucial source of the complexity in short-term heart rate variability.