Data-driven Discovery of the Central Autonomic Network: Dynamic Integration of HRV and Multivariate fMRI Connectivity

INTRODUCTION: Although the interaction between the brain and the heart, through the autonomic nervous system, is an established phenomenon, multimodal studies that have explored their bidirectional interplay are still limited. AIM: In this context, the objective of the present study was to investigate the coupling between sympathetic and vagal dynamics and brain functional connectivity during resting state, thanks to simultaneously acquired electrocardiogram and functional magnetic resonance imaging (fMRI) data. METHODS: Twenty healthy controls (67.42 ± 10.81 years, 60% females) were included in the study. Unimodal fMRI and heart rate variability (HRV) results were integrated in a joint analysis framework. Trivariate dynamic functional connectivity (dFC) features were correlated with time-varying HRV parameters to identify brain regions involved in autonomic modulation. RESULTS: In a data-driven approach, the present analysis allowed to extract triplets of brain regions whose dFC was coupled with both sympathetic and vagal activity dynamics. The identified brain regions often belonged to the central autonomic network, which is a network of brain structures that are involved in the regulation of autonomic processes at high central level. CONCLUSION: The present multimodal HRV and fMRI dFC analysis provided new findings on the physiological brain-heart interactions, paving the way to explore the same mechanisms in disorders of the brain-heart axis.