{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T08:05:47Z","timestamp":1792137947067,"version":"4.4.0"},"reference-count":56,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2019,2,27]],"date-time":"2019-02-27T00:00:00Z","timestamp":1551225600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100000849","name":"National Centre for the Replacement, Refinement and Reduction of Animals in Research","doi-asserted-by":"publisher","award":["G0900797"],"award-info":[{"award-number":["G0900797"]}],"id":[{"id":"10.13039\/501100000849","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["physoc.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["The Journal of Physiology"],"published-print":{"date-parts":[[2019,3]]},"abstract":"<jats:sec>\n                    <jats:title>Key points<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>Nausea is an adverse experience characterised by alterations in autonomic and cerebral function.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Susceptibility to nausea is difficult to predict, but machine learning has yet to be applied to this field of study.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>The severity of nausea that individuals experience is related to the underlying morphology (shape) of the subcortex, namely of the amygdala, caudate and putamen; a functional brain network related to nausea severity was identified, which included the thalamus, cingulate cortices (anterior, mid\u2010 and posterior), caudate nucleus and nucleus accumbens.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Sympathetic nervous system function and sympathovagal balance, by heart rate variability, was closely related to both this nausea\u2010associated anatomical variation and the functional connectivity network, and machine learning accurately predicted susceptibility or resistance to nausea.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>These novel anatomical and functional brain biomarkers for nausea severity may permit objective identification of individuals susceptible to nausea, using artificial intelligence\/machine learning; brain data may be useful to identify individuals more susceptible to nausea.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Abstract<\/jats:title>\n                    <jats:p>\n                      Nausea is a highly individual and variable experience. The central processing of nausea remains poorly understood, although numerous influential factors have been proposed, including brain structure and function, as well as autonomic nervous system (ANS) activity. We investigated the role of these factors in nausea severity and if susceptibility to nausea could be predicted using machine learning. Twenty\u2010eight healthy participants (15 males; mean age 24\u00a0years) underwent quantification of resting sympathetic and parasympathetic nervous system activity by heart rate variability. All were exposed to a 10\u2010min motion\u2010sickness video during fMRI. Neuroanatomical shape differences of the subcortex and functional brain networks associated with the severity of nausea were investigated. A machine learning neural network was trained to predict nausea susceptibility, or resistance, using resting ANS data and detected brain features. Increasing nausea scores positively correlated with shape variation of the left amygdala, right caudate and bilateral putamen (corrected\n                      <jats:italic>P<\/jats:italic>\n                      \u00a0=\u00a00.05). A functional brain network linked to increasing nausea severity was identified implicating the thalamus, anterior, middle and posterior cingulate cortices, caudate nucleus and nucleus accumbens (corrected\n                      <jats:italic>P\u00a0=<\/jats:italic>\n                      \u00a00.043). Both neuroanatomical differences and the functional nausea\u2010brain network were closely related to sympathetic nervous system activity. Using these data, a machine learning model predicted susceptibility to nausea with an overall accuracy of 82.1%. Nausea severity relates to underlying subcortical morphology and a functional brain network; both measures are potential biomarkers in trials of anti\u2010nausea therapies. The use of machine learning should be further investigated as an objective means to develop models predicting nausea susceptibility.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1113\/jp277474","type":"journal-article","created":{"date-parts":[[2019,1,10]],"date-time":"2019-01-10T13:32:06Z","timestamp":1547127126000},"page":"1517-1529","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Functional brain networks and neuroanatomy underpinning nausea severity can predict nausea susceptibility using machine learning"],"prefix":"10.1113","volume":"597","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6248-7203","authenticated-orcid":false,"given":"James K.","family":"Ruffle","sequence":"first","affiliation":[{"name":"Centre for Neuroscience and Trauma Blizard Institute, Wingate Institute of Neurogastroenterology Barts and the London School of Medicine &amp; Dentistry Queen Mary University of London  26 Ashfield Street London E1 2AJ UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anya","family":"Patel","sequence":"additional","affiliation":[{"name":"Centre for Neuroscience and Trauma Blizard Institute, Wingate Institute of Neurogastroenterology Barts and the London School of Medicine &amp; Dentistry Queen Mary University of London  26 Ashfield Street London E1 2AJ UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincent","family":"Giampietro","sequence":"additional","affiliation":[{"name":"Department of Neuroimaging King's College London Institute of Psychiatry  Psychology &amp; Neuroscience London SE5 8AF UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew A.","family":"Howard","sequence":"additional","affiliation":[{"name":"Department of Neuroimaging King's College London Institute of Psychiatry  Psychology &amp; Neuroscience London SE5 8AF UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4231-1945","authenticated-orcid":false,"given":"Gareth J.","family":"Sanger","sequence":"additional","affiliation":[{"name":"Centre for Neuroscience and Trauma Blizard Institute, Wingate Institute of Neurogastroenterology Barts and the London School of Medicine &amp; Dentistry Queen Mary University of London  26 Ashfield Street London E1 2AJ UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul L. 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