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Computational models of autonomic regulation in gastric motility: Progress, challenges, and future directions
- Source :
- Frontiers in Neuroscience, Vol 17 (2023)
- Publication Year :
- 2023
- Publisher :
- Frontiers Media S.A., 2023.
-
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.
Details
- Language :
- English
- ISSN :
- 1662453X
- Volume :
- 17
- Database :
- Directory of Open Access Journals
- Journal :
- Frontiers in Neuroscience
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.9e7ab4a74a144faf8d6bed44185c1b41
- Document Type :
- article
- Full Text :
- https://doi.org/10.3389/fnins.2023.1146097