Search results for "cardiovascular control"
showing 10 items of 17 documents
Redundancy and synergy in interactions among basic cardiovascular oscillations
2020
The cardiovascular control system comprises a complex network of various control mechanisms operating on many time scales resulting in complex and mutually interconnected output signals (e.g. heart rate, systolic and diastolic blood pressures). The analysis of these interconnections could noninvasively provide an information on the regulatory mechanisms involved in cardiovascular control and thus could be potentially applied to better characterize cardiovascular dysregulation in pathological conditions. Our study demonstrates that the strength of interactions among signals changes with the time scale and as a response to changed autonomic state (orthostasis compared to supine rest). Novel i…
Dynamic cerebrovascular autoregulation in patients prone to postural syncope: Comparison of techniques assessing the autoregulation index from sponta…
2021
Abstract Three approaches to the assessment of cerebrovascular autoregulation (CA) via the computation of the autoregulation index (ARI) from spontaneous variability of mean arterial pressure (MAP) and mean cerebral blood flow velocity (MCBFV) were applied: 1) a time domain method (TDM); 2) a nonparametric method (nonPM); 3) a parametric method (PM). Performances were tested over matched and surrogate unmatched pairs. Data were analyzed at supine resting (REST) and during the early phase of 60° head-up tilt (TILT) in 13 subjects with previous history of postural syncope (SYNC, age: 28 ± 9 yrs.; 5 males) and 13 control individuals (noSYNC, age: 27 ± 8 yrs.; 5 males). Analysis was completed b…
Spectral decomposition of cerebrovascular and cardiovascular interactions in patients prone to postural syncope and healthy controls.
2022
We present a framework for the linear parametric analysis of pairwise interactions in bivariate time series in the time and frequency domains, which allows the evaluation of total, causal and instantaneous interactions and connects time- and frequency-domain measures. The framework is applied to physiological time series to investigate the cerebrovascular regulation from the variability of mean cerebral blood flow velocity (CBFV) and mean arterial pressure (MAP), and the cardiovascular regulation from the variability of heart period (HP) and systolic arterial pressure (SAP). We analyze time series acquired at rest and during the early and late phase of head-up tilt in subjects developing or…
A new framework for the time- and frequency-domain assessment of high-order interactions in networks of random processes
2022
While the standard network description of complex systems is based on quantifying the link between pairs of system units, higher-order interactions (HOIs) involving three or more units often play a major role in governing the collective network behavior. This work introduces a new approach to quantify pairwise and HOIs for multivariate rhythmic processes interacting across multiple time scales. We define the so-called O-information rate (OIR) as a new metric to assess HOIs for multivariate time series, and present a framework to decompose the OIR into measures quantifying Granger-causal and instantaneous influences, as well as to expand all measures in the frequency domain. The framework ex…
Lag-specific transfer entropy as a tool to assess cardiovascular and cardiorespiratory information transfer
2014
In the study of interacting physiological systems, model-free tools for time series analysis are fundamental to provide a proper description of how the coupling among systems arises from the multiple involved regulatory mechanisms. This study presents an approach which evaluates direction, magnitude, and exact timing of the information transfer between two time series belonging to a multivariate dataset. The approach performs a decomposition of the well-known transfer entropy (TE) which achieves 1) identifying, according to a lag-specific information-theoretic formulation of the concept of Granger causality, the set of time lags associated with significant information transfer, and 2) assig…
Assessing causality in brain dynamics and cardiovascular control
2013
Understanding how different cerebral areas interact to produce an integrated behaviour and disentangling the mechanisms that contribute to cardiovascular control are two of the major challenges of brain and cardiovascular neuroscience. The increasing availability of simultaneous continuous
Multiscale partial information decomposition of dynamic processes with short and long-range correlations: theory and application to cardiovascular co…
2022
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…
Wiener-Granger Causality in Network Physiology with Applications to Cardiovascular Control and Neuroscience
2016
Since the operative definition given by C. W. J. Granger of an idea expressed by N. Wiener, the Wiener–Granger causality (WGC) has been one of the most relevant concepts exploited by modern time series analysis. Indeed, in networks formed by multiple components, working according to the notion of segregation and interacting with each other according to the principle of integration, inferring causality has opened a window on the effective connectivity of the network and has linked experimental evidences to functions and mechanisms. This tutorial reviews predictability improvement, information-based and frequency domain methods for inferring WGC among physiological processes from multivariate…
Exploring metrics for the characterization of the cerebral autoregulation during head-up tilt and propofol general anesthesia
2022
Techniques grounded on the simultaneous utilization of Tiecks' second order differential equations and spontaneous variability of mean arterial pressure (MAP) and mean cerebral blood flow velocity (MCBFV), recorded from middle cerebral arteries through a transcranial Doppler device, provide a characterization of cerebral autoregulation (CA) via the autoregulation index (ARI). These methods exploit two metrics for comparing the measured MCBFV series with the version predicted by Tiecks' model: normalized mean square prediction error (NMSPE) and normalized correlation rho. The aim of this study is to assess the two metrics for ARI computation in 13 healthy subjects (age: 27 & PLUSMN; 8 yr…
Disentangling cardiovascular control mechanisms during head-down tilt via joint transfer entropy and self-entropy decompositions
2015
A full decomposition of the predictive entropy (PE) of the spontaneous variations of the heart period (HP) given systolic arterial pressure (SAP) and respiration (R) is proposed. The PE of HP is decomposed into the joint transfer entropy (JTE) from SAP and R to HP and self-entropy (SE) of HP. The SE is the sum of three terms quantifying the synergistic/redundant contributions of HP and SAP, when taken individually and jointly, to SE and one term conditioned on HP and SAP denoted as the conditional SE (CSE) of HP given SAP and R. The JTE from SAP and R to HP is the sum of two terms attributable to SAP or R plus an extra term describing the redundant/synergistic contribution to the JTE. All q…