An HRV-fMRI-DTI Integrated Framework at Ultra-High Magnetic Field

The objective of the present study was to present a multimodal methodological framework to explore the central autonomic network (CAN), which modulates autonomic activity at brain level, thanks to magnetic resonance imaging (MRI) data acquired at ultra-high magnetic field. A pilot subject underwent a structural, diffusion weighted, and resting-state functional MRI (fMRI) acquisition at 7T, during which photopletismographic and respiration signals were simultaneously recorded. Sympathetic and vagal activity dynamics were estimated from the heart rate variability (HRV), and used to identify the brain functional correlates through an HRV-driven fMRI analysis. The activated brain regions were used to guide the diffusion tensor imaging analysis to estimate the structural connections underlying the autonomic-related brain activity, and characterize them in terms of fractional anisotropy (FA). Based on the HRV-fMRI ROIs, three types of brain connectivity were computed, which are FA-based, structural, and functional connectivity. The present pilot study enabled the data-driven identification of CAN brain regions and the corresponding white matter tracts, suggesting that the application on bigger samples may be an innovative trimodal approach to comprehensively investigate intrinsic central-level autonomic processes.