A multiscale predictive digital twin for neurocardiac modulation in rabbits

Study Purpose: Predicting the effect of efferent stimulation of the sympathetic and parasympathetic branches of the autonomic nervous system on the cardiac sinoatrial node and ventricular myocardium with a multiscale model that integrates data from the atomistic, subcellular, cellular and systems scale.

Data Collection: Not applicable – it is a computational study.

Primary conclusion: We have developed computational workflows for the multi-layered model.  A multi-layered model representation of the autonomic nervous system that includes sympathetic and parasympathetic branches, each with sparse random intralayer connectivity, synaptic dynamics and conductance based integrate-and-fire neurons, generates firing patterns in agreement with experiment.

Curator's Notes

Experimental Design: We present a multiscale model of autonomic control of cardiac electrophysiology that integrates data from the atomistic, subcellular, cellular and systems scale and predicts the effect of efferent stimulation of the sympathetic and parasympathetic branches of the autonomic nervous system on the cardiac sinoatrial node and ventricular myocardium.

Completeness: This dataset is complete.

Subjects & Samples: This is a computational model dataset; thus no subjects are described.

Primary vs derivative data: Not applicable. This is a computational study. Only a configuration file to view and run the simulation on the o²S²PARC platform is provided.

Code Availability: o²S²PARC template for the computational workflow can be found here