A new Modelling Framework to Study Time-Varying Directional Brain-Heart Interactions: Preliminary Evaluations and...

Area of Science:

• Neuroscience
• Cardiology
• Systems Biology

Background:

• Brain-heart interactions are complex and bidirectional.
• Existing models often lack the ability to capture non-stationary and directional dynamics.
• Understanding neural-autonomic network function is crucial for diagnosing various conditions.

Purpose of the Study:

• To develop a novel multivariate modeling framework for analyzing time-varying, directional brain-heart interplay.
• To quantify information flow between the brain and heart using adaptive coupling coefficients.
• To assess brain-heart interactions during physiological perturbations.

Main Methods:

• Utilized electroencephalographic (EEG) signals and heart rate variability (HRV) series as inputs.
• Derived a multivariate formulation based on coupling functions linking cortical activity and heartbeat dynamics.
• Estimated adaptive coefficients by solving the model inverse problem.
• Applied the framework to data from 27 healthy volunteers undergoing a cold-pressor test.

Main Results:

• Demonstrated the estimation of directional brain-heart coupling coefficients.
• Observed significantly increased directional brain-heart coupling during prolonged baroreflex elicitation.
• Identified specific time delays and brain regions (fronto-parietal, temporal cortices) associated with enhanced coupling.
• Highlighted lateralization mechanisms in temporal cortices during brain-heart interaction.

Conclusions:

• The proposed framework enables a novel assessment of non-stationary, directional brain-heart interactions.
• The findings provide insights into the dynamic interplay within the central autonomic network.
• This methodology holds potential for clinical applications in understanding and diagnosing conditions involving brain-heart dysregulation.