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Signals from heart transplant recipients can be considered to be a naturalsource of information for a better understanding of the impact of the autonomicnervous system on the complexity of heart rate variability. Beat-to-beat heartrate variability can be represented as a network of increments betweensubsequent $RR$-intervals, which makes possible the visualization of short-termheart period fluctuations. A network is constructed of vertices representingincrements between subsequent $RR$-intervals, and edges which connect adjacent$RR$-increments. Two modes of visualization of such a network are proposed. Themethod described is applied to nocturnal Holter signals recorded from healthyyoung people and from cardiac transplant recipients. Additionally, the analysisis performed on surrogate data: shuffled RR-intervals (to display short-rangedependence), and shuffled phases of the Fourier Transform of RR-intervals (tofilter out linear dependences). Important nonlinear properties of autonomicnocturnal regulation in short-term variability in healthy young persons areassociated with $RR$-increments: accelerations and decelerations of a sizegreater than about 35 ms. They reveal that large accelerations are more likelyantipersistent, while large decelerations are more likely persistent. Changesin $RR$-increments in a heart deprived of autonomic supervision are much lowerthan in a healthy individual, and appear to be maintained around a homeostaticstate, but there are indications that this dynamics is nonlinear. The method isfruitful in the evaluation of the vagal activity - the quantity and quality ofthe vagal tone - during the nocturnal rest of healthy young people. The methodalso successfully extracts nonlinear effects related to intrinsic mechanisms ofthe heart regulation.

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