Modeling Brain-Heart Interaction: A Review of Mechanistic Dynamical Models

Brain-heart interaction (BHI) is fundamental to autonomic regulation and also shapes perceptual salience, attentional control, decision-making under load, and affective reactivity. Beyond these functions, BHI has been consistently implicated in clinical studies in cardiovascular, neurological, and psychiatric conditions. This reality makes the investigation of bidirectional BHI mechanisms-and the derivation of interpretable biomarkers- - indispensable for cardiovascular, physiological, and neuroscientific research that treats the body as an interoceptive network of interacting organs rather than isolated systems. The growing interest in this perspective has generated a broad spectrum of frameworks, from signal-processing pipelines and computational models to dynamical systems. Building on previous surveys that have thoroughly mapped the field and deepened our understanding, this review offers a complementary perspective centered on mechanistic, physiology-inspired models of dynamical systems. For each model, we identify the physiological subsystem described, clarify core assumptions, and assess strengths and limitations. We then outline the technical perspectives necessary to realize the full potential of these approaches - especially for inferring latent interoceptive quantities that govern directional BHI but are not directly observable, and for integrating explicit brain modeling into these frameworks to better capture the neural mechanisms driving autonomic and cardiovascular dynamics. Mechanistic dynamical modeling has, over decades, deepened our understanding of physiology and pathology and informed the mapping and treatment of diverse conditions. Our objective is to provide a comprehensive account of state-of-the-art dynamical models, delineate methodological directions, and highlight application areas where such models can yield explanatory insight, reliable prediction, and actionable clinical targets.