Computational models of autonomic regulation in gastric motility: Progress, challenges, and future directions

Abstract

The stomach is extensively innervated by the vagus nerve and the enteric nervous system. The mechanisms through which this innervation affects gastric motility are being unraveled, motivating the first concerted steps towards the incorporation autonomic regulation into computational models of gastric motility. Computational modeling has been valuable in advancing clinical treatment of other organs, such as the heart. However, to date, computational models of gastric motility have made simplifying assumptions about the link between gastric electrophysiology and motility. Advances in experimental neuroscience mean that these assumptions can be reviewed, and detailed models of autonomic regulation can be incorporated into computational models. This review covers these advances, as well as a vision for the utility of computational models of gastric motility. Diseases of the nervous system, such as Parkinson’s disease, can originate from the brain-gut axis and result in pathological gastric motility. Computational models are a valuable tool for understanding the mechanisms of disease and how treatment may affect gastric motility. This review also covers recent advances in experimental neuroscience that are fundamental to the development of physiology-driven computational models. A vision for the future of computational modeling of gastric motility is proposed and modeling approaches employed for existing mathematical models of autonomic regulation of other gastrointestinal organs and other organ systems are discussed.

Variational Iteration Method for solving Electrocardiography inverse problem

“…The heart muscle is anisotropic, the effects of these properties on heart tissue are discussed using the bidomain electrophoresis model, it is a microscopic model that describes the bioelectric behavior of the heart [4], The mathematical model of electrophysiology of the heart is a dynamic system that quantitatively describes the electrical processes occurring in the tissues of the heart [5]. The bidomain model is a system of nonlinear and convergent ordinary differential equations (ODEs), which used to model the gastric electrophysiology [6]. The use of the bidomain model is necessary for the correct modeling of the defibrillation response, and the error arising from the numerical solution of bidomain models is relatively small; various types of boundary condition can be imposed that can take into account the leakage of current to the surrounding tissues other than the myocardium [7].…”