0000000000622126
AUTHOR
Helder Pinto
Assessing Transfer Entropy in cardiovascular and respiratory time series: A VARFI approach
In the study of complex biomedical systems represented by multivariate stochastic processes, such as the cardiovascular and respiratory systems, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. Recently, the quantification of multiscale complexity based on linear parametric models, incorporating autoregressive coefficients and fractional integration, encompassing short term dynamics and long-range correlations, was extended to multivariate time series. Within this Vector AutoRegressive Fractionally Integrated (VARFI) framework formalized for Gaussian processes, in this work we propose to estimate the Transfer Entropy, or equivalently G…
Multiscale partial information decomposition of dynamic processes with short and long-range correlations: theory and application to cardiovascular control.
Abstract Objective. In this work, an analytical framework for the multiscale analysis of multivariate Gaussian processes is presented, whereby the computation of Partial Information Decomposition measures is achieved accounting for the simultaneous presence of short-term dynamics and long-range correlations. Approach. We consider physiological time series mapping the activity of the cardiac, vascular and respiratory systems in the field of Network Physiology. In this context, the multiscale representation of transfer entropy within the network of interactions among Systolic arterial pressure (S), respiration (R) and heart period (H), as well as the decomposition into unique, redundant and s…
Frequency Domain Information Decomposition: Application to Plateau Waves of Intracranial Pressure
The sustainment and/or resurgence of Plateau Waves (PWs) reveals a borderline cerebral situation of the pressure-volume relationship and is related to increased mortality. The intense systemic stress caused by PWs can be evidenced by the study of Heart Rate Variability (HRV), which is an indicator of the activity of the autonomic nervous system, namely the sympathetic and parasympathetic imbalance. In this work, heart and brain crosstalk interactions will be analyzed using a spectral decomposition of multivariate information measures, which provides frequency-specific quantification of the information shared between a target and two source time series. The spectral measures of information h…
Assessing Transfer Entropy in cardiovascular and respiratory time series: A VARFI approach
In the study of complex biomedical systems represented by multivariate stochastic processes, such as the cardiovascular and respiratory systems, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. Recently, the quantification of multiscale complexity based on linear parametric models, incorporating autoregressive coefficients and fractional integration, encompassing short term dynamics and long-range correlations, was extended to multivariate time series. Within this Vector AutoRegressive Fractionally Integrated (VARFI) framework formalized for Gaussian processes, in this work we propose to estimate the Transfer Entropy, or equivalently G…
Assessing Transfer Entropy in cardiovascular and respiratory time series under long-range correlations.
Heart Period (H) results from the activity of several coexisting control mechanisms, involving Systolic Arterial Pressure (S) and Respiration (R), which operate across multiple time scales encompassing not only short-term dynamics but also long-range correlations. In this work, multiscale representation of Transfer Entropy (TE) and of its decomposition in the network of these three interacting processes is obtained by extending the multivariate approach based on linear parametric VAR models to the Vector AutoRegressive Fractionally Integrated (VARFI) framework for Gaussian processes. This approach allows to dissect the different contributions to cardiac dynamics accounting for the simultane…