Measures of the coupling between fluctuating brain network organization and heartbeat dynamics

Abstract

Abstract In recent years, there has been an increasing interest in studying brain-heart interactions. Methodological advancements have been proposed to investigate how these organs communicate, which has led to new insights into neural functions. However, most frameworks only look at the interaction of one brain region with heartbeat dynamics, overlooking that the brain has functional networks that change dynamically in response to internal/external demands. We propose a new framework for assessing the functional interplay between cortical networks and cardiac dynamics from electrophysiological recordings. We focused on fluctuating network metrics obtained from EEG connectivity data. Specifically, we quantified the coupling between cardiac sympathetic-vagal activity and brain network metrics of clustering, efficiency, assortativity and modularity. We validate our proposal using open-source datasets: one involving emotion elicitation in healthy individuals, and another with resting-state data from patients with Parkinson’s disease. Our results suggest that the connection between cortical network segregation and cardiac dynamics may offer valuable insights into the affective state of healthy participants, and alterations in the network physiology of Parkinson’s disease. By considering multiple network properties, this framework may offer a more comprehensive understanding of brain-heart interactions. Our findings hold promise in the development of biomarkers for diagnostic and cognitive/motor function evaluation.