The analysis of short-term cardiovascular and cardiorespiratory regulation during altered conscious states, such as those induced by anesthesia, requires to employ time series analysis methods able to deal with the multivariate and multiscale nature of the observed dynamics. To meet this requirement, the present study exploits the extension to multiscale analysis of recently proposed information decomposition methods which allow to quantify, from short realizations, the amounts of joint, unique, redundant and synergistic information transferred within multivariate time series. These methods were applied to the spontaneous variability of heart period (HP), systolic arterial pressure (SAP) and respiration (RESP) in patients undergoing coronary artery bypass graft monitored before and after the induction of general anesthesia. We found that, after anesthesia induction, information is processed within the cardiovascular network in a scale-dependent way: at short time scales, a shift from synergistic to redundant information transferred from SAP and RESP to HP occurs, which is associated with enhanced baroreflex-mediated respiratory effects on arterial pressure; at longer time scales, the increased information transfer from SAP to HP denotes an enhancement of the baroreflex coupling related to slow cardiovascular oscillations.
|Number of pages||4|
|Publication status||Published - 2018|
All Science Journal Classification (ASJC) codes
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics