In 1628 William Harvey wrote, ?Every affection of the mind that is attended with either pain or pleasure, hope or fear, is the cause of an agitation whose influence extends to the heart.? Despite centuries of recognition of the fundamental connection between the brain and heart, there is still very poor understanding of the role of autonomic control in normal cardiac control and in the paroxysmal nature of life threatening cardiac events. To predict the mechanisms underlying the interaction between nervous system discharge and the resultant emergent cardiac and vascular events would finally allow for individual identification and specific targeting of arrhythmia provoking conditions by drugs or even by direct electrical stimulation. We propose to develop the Neurocardiovascular Simulator suite to solve this problem. The proposed simulator is unparalleled, as it will integrate anatomical and functional data ranging from the atomic level for ion channels and key signaling proteins to subcellular to cellular, organ, and systems data and simulations. Importantly, our simulator incorporates multiscale variability that reflects individual subject differences, allowing for a uniquely predictive tool. Experiment- informed simulator predictions will be used to further guide ongoing experiments in SPARC projects and to interpret patient data, allowing for tight integration and synergy across multiple arms of the SPARC initiative. The simulator has 8 tasks. In Task 1, we model neural circuitry. In Task 2, we incorporate into the simulator the anatomical features required for intrinsic autonomic regulation of cardiovascular function. In Task 3, we simulate synaptic control of vascular and cardiac myocytes. Task 4 involves modeling autonomic effects on subcellular signaling and electrophysiology in vascular and cardiac myocytes, while Task 5 deals with atomic-scale details of the molecular interactions in the adrenergic signaling cascade. Task 6 integrates data from the previous 5 tasks to predict autonomic effects on the cardiovascular system. In Task 7, we develop tools (workflows) for model dissemination and use by others. Finally, in Task 8 we incorporate into the simulator uncertainty quantification, sensitivity analysis, and robustness tests. The proposed studies have the potential of transforming our understanding of how cardiac and vascular function is regulated by the autonomic nervous system and provide insights into how this neuro-cardiovascular axis could be clinically tuned with molecular precision to improve patient outcomes.
The autonomic nervous system connects the heart and the brain. This connection allows tuning cardiovascular function to physiological demands. Our project aims to develop a computationally-based simulator to predict neural control of cardiac and vascular function in individuals.
