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It has been proposed that these implicit expectations arise from an internal predictive coding model, based on knowledge acquired through processes such as statistical learning, but it is unclear how different types of statistical information affect listeners\u2019 <jats:italic>memory<\/jats:italic> for auditory stimuli. We used a combination of behavioral and computational methods to investigate memory for non\u2010linguistic auditory sequences. Participants repeatedly heard tone sequences varying systematically in their information\u2010theoretic properties. Expectedness ratings of tones were collected during three listening sessions, and a recognition memory test was given after each session. Information\u2010theoretic measures of sequential predictability significantly influenced listeners\u2019 expectedness ratings, and variations in these properties had a significant impact on memory performance. Predictable sequences yielded increasingly better memory performance with increasing exposure. Computational simulations using a probabilistic model of auditory expectation suggest that listeners dynamically formed a new, and increasingly accurate, implicit cognitive model of the information\u2010theoretic structure of the sequences throughout the experimental session.<\/jats:p>","DOI":"10.1111\/cogs.12477","type":"journal-article","created":{"date-parts":[[2017,1,25]],"date-time":"2017-01-25T12:52:59Z","timestamp":1485348779000},"page":"43-76","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":50,"title":["Information\u2010Theoretic Properties of Auditory Sequences Dynamically Influence Expectation and Memory"],"prefix":"10.1111","volume":"42","author":[{"given":"Kat","family":"Agres","sequence":"first","affiliation":[{"name":"School of Electronic Engineering and Computer Science Queen Mary University of London"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samer","family":"Abdallah","sequence":"additional","affiliation":[{"name":"Department of Computer Science University College London"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcus","family":"Pearce","sequence":"additional","affiliation":[{"name":"School of Electronic Engineering and Computer Science Queen Mary University of London"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2017,1,25]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1080\/09540090902733756"},{"key":"e_1_2_6_3_1","unstructured":"Abdallah S. &Plumbley M.(2010).predictive information multi\u2010information and binding information. 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