Abstract
ABSTRACTBackgroundA joint symbolic analysis (JSA) is applied to assess the strength of the cardiovascular coupling from spontaneous beat-to-beat variability of the heart period (HP) and the systolic arterial pressure (SAP) during an experimental protocol inducing a gradual baroreflex unloading evoked by postural change (i.e. graded head-up tilt).Method:The adopted JSA can quantify the degree of association between the HP and SAP variabilities as a function of the time scale of the HP and SAP patterns. Traditional linear tools assessing the HP-SAP coupling strength, such as squared correlation coefficient, squared coherence function, and percentage of baroreflex sequences, were computed as well for comparison.Results:We found that: i) JSA indicated that the strength of the cardiovascular coupling at slow temporal scales gradually increased with the magnitude of the orthostatic challenge, while that at fast temporal scales gradually decreased; ii) the squared correlation coefficient and percentage of baroreflex sequences did not detect this behavior; iii) even though squared coherence function could measure the magnitude of the HP-SAP coupling as a function of the time scale, it was less powerful than JSA owing to the larger dispersion of the frequency domain indexes.Conclusion:Due to its peculiar features and high statistical power, JSA deserves applications to pathological groups in which the link between HP and SAP variabilities is lost or decreased due to the overall depression or impairment of the cardiovascular control.
Highlights
Symbolic analysis (SA) is a prominent approach utilized in many fields of science to tackle the complexity of the behavior of a dynamical system and describe the interactions among its subparts[1]
The main findings of the study can be summarized as follows: i) the joint SA (JSA) indicated that the strength of the cardiovascular coupling at slow time scales gradually increased with the magnitude of the orthostatic challenge, while coupling at fast time scales gradually decreased; ii) this result could not be achieved by a global time domain index of heart period (HP)-systolic arterial pressure (SAP) coupling strength such as the squared correlation coefficient and percentage of baroreflex sequences; iii) the JSA seemed to be more powerful than squared coherence function as a likely result of a more limited dispersion of symbolic indexes
The joint pattern 2UV-2UV connected together rapidly changing HP and SAP patterns featuring fast temporal scales, while the joint pattern 0V-0V linked together very stable HP and SAP patterns characterized by slow time scales
Summary
Symbolic analysis (SA) is a prominent approach utilized in many fields of science to tackle the complexity of the behavior of a dynamical system and describe the interactions among its subparts[1]. SA is based on a coarse graining procedure symbolizing the time course of one (or more) of the variables describing the behavior of the dynamical system. The symbolization procedure creates an alphabet of states that are visited during the functioning of the system. In the field of cardiovascular control analysis, univariate SA has been largely applied to heart period (HP) variability given the ability of this. Higher levels of integration of neural reflexes can be studied when JSA is gated according to a periodical input such as the respiratory activity[15]
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