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  1. Pitches that Wire Together Fire Together: Scale Degree Associations Across Time Predict Melodic Expectations.Niels J. Verosky & Emily Morgan - 2021 - Cognitive Science 45 (10):e13037.
    The ongoing generation of expectations is fundamental to listeners’ experience of music, but research into types of statistical information that listeners extract from musical melodies has tended to emphasize transition probabilities and n‐grams, with limited consideration given to other types of statistical learning that may be relevant. Temporal associations between scale degrees represent a different type of information present in musical melodies that can be learned from musical corpora using expectation networks, a computationally simple method based on activation and decay. (...)
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  • Exploring Cognitive Relations Between Prediction in Language and Music.Aniruddh D. Patel & Emily Morgan - 2017 - Cognitive Science 41 (S2):303-320.
    The online processing of both music and language involves making predictions about upcoming material, but the relationship between prediction in these two domains is not well understood. Electrophysiological methods for studying individual differences in prediction in language processing have opened the door to new questions. Specifically, we ask whether individuals with musical training predict upcoming linguistic material more strongly and/or more accurately than non-musicians. We propose two reasons why prediction in these two domains might be linked: Musicians may have greater (...)
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  • Statistical learning and Gestalt-like principles predict melodic expectations.Emily Morgan, Allison Fogel, Anjali Nair & Aniruddh D. Patel - 2019 - Cognition 189 (C):23-34.
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