Neuromechanical model of esophageal transport

Esophageal transport involves the recruitment of a large-scale distributed neural network as neurophysiological activity regulates the contraction of the esophageal muscle fibers. Some esophageal disorders are suspected to be directly related to neurological dysfunction. Hence, to achieve a better understanding of esophageal pathophysiology, one must incorporate quantitative neuromechanical models. The goal of this work is to develop such a model, which has not been developed before. To do so, we develop a 1D model of peristaltic flow in an elastic tube, where the traveling contraction is implemented by varying the rest cross-sectional area (CSA) of the tube. The rest CSA is computed based on a neuronal feedback model, triggered by stretch receptors and cell-to-cell communication. Unlike prior neuromechanical models, our mathematical model accounts for the gradient of increasing inhibitory innervation distally along the esophagus – an important feature implicated in key aspects of neural activation patterns of the esophagus. Thus, we can investigate the effect of gradient pattern, stretch receptors, and bolus size on the resulting peristaltic motion. By producing such model, we can understand the emergent peristaltic behavior of the esophagus, and the associated pathophysiology.