The virtual physiological human gets nerves! How to account for the action of the nervous system in multiphysics simulations of human organs

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dc.contributor.authorAlexiadis, Alessio
dc.contributor.authorSimmons, M. J. H.
dc.contributor.authorStamatopoulos, K.
dc.contributor.authorBatchelor, H. K.
dc.contributor.authorMoulitsas, Irene
dc.date.accessioned2021-04-15T10:04:27Z
dc.date.available2021-04-15T10:04:27Z
dc.date.issued2021-04-14
dc.description.abstractThis article shows how to couple multiphysics and artificial neural networks to design computer models of human organs that autonomously adapt their behaviour to environmental stimuli. The model simulates motility in the intestine and adjusts its contraction patterns to the physical properties of the luminal content. Multiphysics reproduces the solid mechanics of the intestinal membrane and the fluid mechanics of the luminal content; the artificial neural network replicates the activity of the enteric nervous system. Previous studies recommended training the network with reinforcement learning. Here, we show that reinforcement learning alone is not enough; the input– output structure of the network should also mimic the basic circuit of the enteric nervous system. Simulations are validated against in vivo measurements of high-amplitude propagating contractions in the human intestine. When the network has the same input–output structure of the nervous system, the model performs well even when faced with conditions outside its training range. The model is trained to optimize transport, but it also keeps stress in the membrane low, which is exactly what occurs in the real intestine. Moreover, the model responds to atypical variations of its functioning with ‘symptoms’ that reflect those arising in diseases. If the healthy intestine model is made artificially ill by adding digital inflammation, motility patterns are disrupted in a way consistent with inflammatory pathologies such as inflammatory bowel disease.en_UK
dc.identifier.citationAlexiadis A, Simmons MJH, Stamatopoulos K, et al., (2021) The virtual physiological human gets nerves! How to account for the action of the nervous system in multiphysics simulations of human organs. Interface, Volume 18, Issue 177, April 2021, Article number 20201024en_UK
dc.identifier.issn1742-5662
dc.identifier.urihttps://doi.org/10.1098/rsif.2020.1024
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/16575
dc.language.isoenen_UK
dc.publisherThe Royal Societyen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectreinforcement learningen_UK
dc.subjectvirtual humanen_UK
dc.subjectmathematical modelling of the intestineen_UK
dc.titleThe virtual physiological human gets nerves! How to account for the action of the nervous system in multiphysics simulations of human organsen_UK
dc.typeArticleen_UK

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