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However, this may be inappropriate when the world changes and past experiences no longer predict what the future holds. Optimal learning models propose that observers decide whether to stick with or update their predictions by tracking the uncertainty or \u201cprecision\u201d of their expectations. However, contrasting theories of prediction have argued that we are prone to misestimate uncertainty\u2014leading to stubborn predictions that are difficult to dislodge. To compare these possibilities, we had participants learn novel perceptual predictions before using fMRI to record visual brain activity when predictive contingencies were disrupted\u2014meaning that previously \u201cexpected\u201d events became objectively improbable. Multivariate pattern analyses revealed that expected events continued to be decoded with greater fidelity from primary visual cortex, despite marked changes in the statistical structure of the environment, which rendered these expectations no longer valid. These results suggest that our perceptual systems do indeed form stubborn predictions even from short periods of learning\u2014and more generally suggest that top\u2013down expectations have the potential to help or hinder perceptual inference in bounded minds like ours.<\/jats:p>","DOI":"10.1162\/jocn_a_01997","type":"journal-article","created":{"date-parts":[[2023,4,21]],"date-time":"2023-04-21T12:18:15Z","timestamp":1682079495000},"page":"1133-1143","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":15,"title":["Stubborn Predictions in Primary Visual Cortex"],"prefix":"10.1162","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5511-3884","authenticated-orcid":true,"given":"Daniel","family":"Yon","sequence":"first","affiliation":[{"name":"Birkbeck, University of London, United Kingdom"}]},{"given":"Emily R.","family":"Thomas","sequence":"additional","affiliation":[{"name":"Birkbeck, University 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