{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T19:31:19Z","timestamp":1770838279778,"version":"3.50.1"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1013937","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T00:00:00Z","timestamp":1770768000000}}],"reference-count":87,"publisher":"Public Library of Science (PLoS)","issue":"2","license":[{"start":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T00:00:00Z","timestamp":1770163200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Government of Canada New Frontiers in Research","award":["NFRFE-2021-00458"],"award-info":[{"award-number":["NFRFE-2021-00458"]}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>A fundamental problem of visuomotor adaptation research is to understand how the brain is capable to asymptotically remove a predictable exogenous disturbance from a visual error signal using limited sensor information by re-calibration of hand movement. From a control theory perspective, the most striking aspect of this problem is that it falls squarely in the realm of the internal model principle of control theory. Despite this fact, the relationship between the internal model principle and models of visuomotor adaptation is currently not well developed.<\/jats:p>\n                  <jats:p>\n                    This paper aims to close this gap by proposing an abstract discrete-time state space model of visuomotor adaptation based on the internal model principle. The proposed\n                    <jats:italic>DO Model<\/jats:italic>\n                    , a metonym for its most important component, a disturbance observer, addresses key modeling requirements: modular architecture, physically relevant signals, parameters tied to atomic behaviors, and capacity for abstraction. The two main computational modules are a disturbance observer, a recently developed class of internal models, and a feedforward system that learns from the disturbance observer to improve feedforward motor commands.\n                  <\/jats:p>","DOI":"10.1371\/journal.pcbi.1013937","type":"journal-article","created":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T18:40:29Z","timestamp":1770230429000},"page":"e1013937","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Modeling human visuomotor adaptation with a disturbance observer framework"],"prefix":"10.1371","volume":"22","author":[{"given":"Gaurav","family":"Sharma","sequence":"first","affiliation":[]},{"given":"Bernard Marius","family":"\u2019t Hart","sequence":"additional","affiliation":[]},{"given":"Jean-Jacques","family":"Orban de Xivry","sequence":"additional","affiliation":[]},{"given":"Denise Y.P.","family":"Henriques","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8275-3716","authenticated-orcid":true,"given":"Mireille E.","family":"Broucke","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2026,2,4]]},"reference":[{"key":"pcbi.1013937.ref001","doi-asserted-by":"crossref","first-page":"1761","DOI":"10.1093\/cercor\/bhq246","article-title":"Dissociating the roles of the cerebellum and motor cortex during adaptive learning: The motor cortex retains what the cerebellum learns","volume":"21","author":"J Galea","year":"2011","journal-title":"Cerebral Cortex."},{"key":"pcbi.1013937.ref002","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/978-1-4614-5465-6_1","article-title":"Model-based and model-free mechanisms of human motor learning","volume":"782","author":"AM Haith","year":"2013","journal-title":"Adv Exp Med Biol."},{"issue":"3","key":"pcbi.1013937.ref003","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1002012","article-title":"Learning from sensory and reward prediction errors during motor adaptation","volume":"7","author":"J Izawa","year":"2011","journal-title":"PLoS Comput Biol."},{"issue":"10","key":"pcbi.1013937.ref004","doi-asserted-by":"crossref","first-page":"3478","DOI":"10.1093\/cercor\/bhx214","article-title":"Learning similar actions by reinforcement or sensory-prediction errors rely on distinct physiological mechanisms","volume":"28","author":"S Uehara","year":"2018","journal-title":"Cereb Cortex."},{"key":"pcbi.1013937.ref005","doi-asserted-by":"crossref","unstructured":"Morehead JR, Orban de Xivry J-J. 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