Measuring the Rate of Information Exchange in Point-Process Data With Application to Cardiovascular Variability

Abstract

The amount of information exchanged per unit of time between two dynamic processes is an important concept for the analysis of complex systems. Theoretical formulations and data-efficient estimators have been recently introduced for this quantity, known as the mutual information rate (MIR), allowing its continuous-time computation for event-based data sets measured as realizations of coupled point processes. This work presents the implementation of MIR for point process applications in Network Physiology and cardiovascular variability, which typically feature short and noisy experimental time series. We assess the bias of MIR estimated for uncoupled point processes in the frame of surrogate data, and we compensate it by introducing a corrected MIR (cMIR) measure designed to return zero values when the two processes do not exchange information. The method is first tested extensively in synthetic point processes including a physiologically-based model of the heartbeat dynamics and the blood pressure propagation times, where we show the ability of cMIR to compensate the negative bias of MIR and return statistically significant values even for weakly coupled processes. The method is then assessed in real point-process data measured from healthy subjects during different physiological conditions, showing that cMIR between heartbeat and pressure propagation times increases significantly during postural stress, though not during mental stress. These results document that cMIR reflects physiological mechanisms of cardiovascular variability related to the joint neural autonomic modulation of heart rate and arterial compliance.

Analysis of Cardiac Pulse Arrival Time Series at Rest and during Physiological Stress

“…Such complex regulatory mechanisms occurring during a mental stress condition produce a decrease of mean PAT (see Fig. 2(a)) linked to a decrease in PEP, due to weakening of parasympathetic activity and a positive inotropic effect [26], and to a decrease in PTT, as found in similar studies [26], [29], [36]. These two similar trends lead to a lower PAT variability during the arithmetic stress phase, as documented by our results in Fig.…”

“…The reduction of the mean PAT (see Fig. 2(a)) mostly reflects the trend of PTT, moreover it is important to underline how mechanisms of regulation of PEP and PTT act differently for each subject and within each heartbeat, thus leading to a high variability of PAT during orthostatic stress [29] (see Fig. 2(b)).…”

Feasibility of Ultra-Short Term Analysis of Heart Rate and Systolic Arterial Pressure Variability at Rest and During Stress via Time-domain and Entropy-based Measures

“…3(a.1,b.1)) have been related to the decreased venous return [59–61]. The resulting cardiac filling associated with SAP decrease leads to an activation of the baroreflex response during postural stress and thus to an enhanced involvement of baroceptive mechanism and vasoconstrictor activity in response to the physiological perturbation, which in turn produces an increased heart rate [59–62]. The opposite trends reported for mental stress (see Fig.…”

Network Physiology of Exercise: Beyond Molecular and Omics Perspectives

“…Several interaction-based measures like connectivity, entropy, phase coherence, Hurst exponent, Lyapunov exponent, etc. can be used to detect such behavior [15,23,25,62,94,[95][96][97][98][99][100][101].…”