{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T21:55:29Z","timestamp":1790286929684,"version":"4.1.0"},"reference-count":55,"publisher":"American Association for the Advancement of Science (AAAS)","issue":"22","content-domain":{"domain":["www.science.org"],"crossmark-restriction":true},"short-container-title":["Sci. Adv."],"published-print":{"date-parts":[[2025,5,30]]},"abstract":"<jats:p>Successful engagement with the physical world requires the ability to predict future events and plan interventions to alter that future. Growing evidence implicates a set of regions in the human parietal and frontal lobes [also known as the \u201cphysics network\u201d (PN)] in such intuitive physical inferences. However, the central tenet of this hypothesis, that PN runs forward simulations to predict future states, remains untested. In this preregistered study, we first show that PN abstractly represents whether two objects are in contact with each other, a physical scene property critical for prediction (because objects\u2019 fates are intertwined when they are in contact). We then show that PN (but not other visual areas) carries abstract information about predicted future contact events (i.e., collisions). These findings support the hypothesis that PN contains a generative model of the physical world that conducts forward simulations, serving as the brain\u2019s \u201cphysics engine.\u201d<\/jats:p>","DOI":"10.1126\/sciadv.adr7429","type":"journal-article","created":{"date-parts":[[2025,5,30]],"date-time":"2025-05-30T13:58:53Z","timestamp":1748613533000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark","source":"Crossref","is-referenced-by-count":16,"title":["Decoding predicted future states from the brain\u2019s \u201cphysics engine\u201d"],"prefix":"10.1126","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5933-7893","authenticated-orcid":true,"given":"R. 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