David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
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Topics in Cognitive Science 4 (4):554-567 (2012)
Much of what we know and love about music is based on implicitly acquired mental representations of musical pitches and the relationships between them. While previous studies have shown that these mental representations of music can be acquired rapidly and can influence preference, it is still unclear which aspects of music influence learning and preference formation. This article reports two experiments that use an artificial musical system to examine two questions: (1) which aspects of music matter most for learning, and (2) which aspects of music matter most for preference formation. Two aspects of music are tested: melody and harmony. In Experiment 1 we tested the learning and liking of a new musical system that is manipulated melodically so that only some of the possible conditional probabilities between successive notes are presented. In Experiment 2 we administered the same tests for learning and liking, but we used a musical system that is manipulated harmonically to eliminate the property of harmonic whole-integer ratios between pitches. Results show that disrupting melody (Experiment 1) disabled the learning of music without disrupting preference formation, whereas disrupting harmony (Experiment 2) does not affect learning and memory but disrupts preference formation. Results point to a possible dissociation between learning and preference in musical knowledge
|Keywords||Harmony Pitch Preference Music Melody Grammar Learning Cognition|
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References found in this work BETA
Jenny R. Saffran, Elizabeth K. Johnson, Richard N. Aslin & Elissa L. Newport (1999). Statistical Learning of Tone Sequences by Human Infants and Adults. Cognition 70 (1):27-52.
Arthur S. Reber (1967). Implicit Learning of Artificial Grammars. Journal of Verbal Learning and Verbal Behavior 6:855-863.
Martin Rohrmeier, Patrick Rebuschat & Ian Cross (2011). Incidental and Online Learning of Melodic Structure. Consciousness and Cognition 20 (2):214-222.
Zoltan Dienes & Christopher Longuet‐Higgins (2004). Can Musical Transformations Be Implicitly Learned? Cognitive Science 28 (4):531-558.
Leonard B. Meyer (1956). Emotion and Meaning in Music. [Chicago]University of Chicago Press.
Citations of this work BETA
Martin Rohrmeier & Patrick Rebuschat (2012). Implicit Learning and Acquisition of Music. Topics in Cognitive Science 4 (4):525-553.
Adrian Currie & Anton Killin (2016). Musical Pluralism and the Science of Music. European Journal for Philosophy of Science 6 (1):9-30.
Valorie N. Salimpoor, David H. Zald, Robert J. Zatorre, Alain Dagher & Anthony Randal McIntosh (2015). Predictions and the Brain: How Musical Sounds Become Rewarding. Trends in Cognitive Sciences 19 (2):86-91.
David Huron (2012). Two Challenges in Cognitive Musicology. Topics in Cognitive Science 4 (4):678-684.
Marcus Pearce & Martin Rohrmeier (2012). Music Cognition and the Cognitive Sciences. Topics in Cognitive Science 4 (4):468-484.
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