Abstract

The quantification of functional brain-heart interplay through the dynamics of the central and autonomic nervous systems may provide effective biomarkers for cognitive, emotional, and autonomic state changes. Despite several computational models were proposed to this end, none provides a directional estimation of such interplay in a time-resolved and probabilistic fashion. In this study, a multivariate inhomogeneous point-process model for heartbeat dynamics is employed to derive subject-specific, time-resolved, functional estimates of the directional interplay occurring from the brain to the heart, whose activity is represented by electroencephalography and R-peaks intervals series. An inverse-Gaussian probability density function is used to predict heartbeat events as a function of neural dynamics, which is modeled as an exogenous input to the autoregressive cardiac dynamics. The performance is evaluated using heart rate variability and electroencephalography series gathered from 24 healthy volunteers undergoing a cold-pressor test, and the modeling goodness-of-fit is assessed through the time-rescaling theorem. The results suggest that cortical dynamics drives heartbeat series with specific time delays in the range of 30s to 60s and 90s to 120s from the peripheral thermal stress onset. The proposed framework provides novel insights in human neurophysiology, exploiting a fully probabilistic definition of the continuous functional brain-heart interplay.

Highlights

  • K NOWLEDGE of functional brain–body interplay is important because of the strong physiological and clinical reciprocal implications that exist between central and peripheral systems

  • Note that numbers consistently decrease in the cold-pressor test (CPT) session, suggesting a higher inter-subject variability following a CPT than the resting state, and functional brain–heart interplay estimates related to EEG oscillations in the δ band were not retained for further analyses

  • Aiming to verify whether the respiratory frequency lies within the HF band (0.15-0.4 Hz), we estimated the respiratory frequency for each experimental session, i.e., rest and CPT, by identifying the maximum of the signal frequency spectrum

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Summary

Introduction

K NOWLEDGE of functional brain–body interplay is important because of the strong physiological and clinical reciprocal implications that exist between central and peripheral systems. The discovering of the brain–heart interplay dynamics could yield insights regarding the joint activity, in physiologic and pathological conditions, of the autonomic nervous system (ANS) and the central nervous system (CNS) Such an interaction has been mainly formalized with the definition of the central autonomic network (CAN) [1]–[5], which includes brain regions involved in the control of the ANS, such as circulatory and autonomic regulation. The nucleus of the tractus solitarius, located in the medulla, is a relay center, connected to the dorsal motor nucleus of the vagus nerve The latter directly controls activation of the parasympathetic nerves innervating the cardiac system, while the sympathetic outflow is governed by the paraventricular nucleus, the rostral ventro-lateral medulla, and the rostral ventromedial medulla [5], [8]. Contrary to the sympathetic nerves having direct influence on heart period shortening, the activity of the parasympathetic nerves increases the heart period [5]

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