Information dynamics in cardiorespiratory analyses: application to controlled breathing

Abstract

Voluntary adjustment of the breathing pattern is widely used to deal with stress-related conditions. In this study, effects of slow and fast breathing with a low and high inspiratory to expiratory time on heart rate variability (HRV) are evaluated by means of information dynamics. Information transfer is quantified both as the traditional transfer entropy as well as the cross entropy, where the latter does not condition on the past of HRV, thereby taking the highly unidirectional relation between respiration and heart rate into account. The results show that the cross entropy is more suited to quantify cardiorespiratory information transfer as this measure increases during slow breathing, indicating the increased cardiorespiratory coupling and suggesting the shift towards vagal activation during slow breathing. Additionally we found that controlled breathing, either slow or fast, results as well in an increase in cardiorespiratory coupling, compared to spontaneous breathing, which demonstrates the beneficial effects of instructed breathing.