Autonomic organization of respirocardial function in healthy human neonates in quiet and active sleep

It is not known on which time scales the nonlinear respirocardial interactions occur. This work's aim is to quantitatively assess functional respirocardial organization during quiet and active sleep of healthy full-term neonates by autonomic information flow (AIF) without limitation on specific time scales. Representing respirocardial interactions on a global time scale AIF carries information on a wider scope of interdependencies than known linear and nonlinear measures described. It assesses the complexity of heart rate fluctuations (HRF) and respiratory movements (RM) and their interaction comprising both linear and nonlinear properties. Thus, we hypothesized AIF to characterize novel aspects of sleep state-dependent respirocardial interaction.

RM and ECG-derived HRF of six healthy full-term neonates were studied. We analyzed their power spectra, coherence, auto- and cross-correlation and complexity estimated on local ("next sample" prediction) and global time scales (an integral over AIF predicting for all time lags in HRF and RM).

We found the global AIF of HRF and RM to differ significantly between active and quiet sleep in all neonates, whereas on a local time scale this applied to the HRF AIF only. HRF complexity was larger in quiet than in active sleep. Respirocardial interaction was less complex in quiet versus active sleep in the high frequency band only.

Complex sleep state-related changes of respirocardial interdependencies cannot be identified completely on the local time scale. Considering the global time scale of respirocardial interactions allows a more complete physiological interpretation with regard to the underlying autonomic dynamics.