ArticleFrontiers in computational neuroscience2019
Tonality Tunes the Statistical Characteristics in Music: Computational Approaches on Statistical Learning.
Article in Frontiers in computational neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Statistical learning across cognitive and affective domains: a multidimensional review.Frontiers in integrative neuroscience · 2025Review
- Statistical Properties of Musical Creativity: Roles of Hierarchy and Uncertainty in Statistical Learning.Frontiers in neuroscience · 2021Review
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Abstract
Statistical learning is a learning mechanism based on transition probability in sequences such as music and language. Recent computational and neurophysiological studies suggest that the statistical learning contributes to production, action, and musical creativity as well as prediction and perception. The present study investigated how statistical structure interacts with tonalities in music based on various-order statistical models. To verify this in all 24 major and minor keys, the transition probabilities of the sequences containing the highest pitches in Bach's Well-Tempered Clavier, which is a collection of two series (No. 1 and No. 2) of preludes and fugues in all of the 24 major and minor keys, were calculated based on
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