Andrew Goldman, Peter M. C. Harrison, Tyreek Jackson, M. Pearce
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Reassessing Syntax-Related ERP Components Using Popular Music Chord Sequences
Electroencephalographic responses to unexpected musical events allow researchers to test listeners’ internal models of syntax. One major challenge is dissociating cognitive syntactic violations—based on the abstract identity of a particular musical structure—from unexpected acoustic features. Despite careful controls in past studies, recent work by Bigand, Delbe, Poulin-Carronnat, Leman, and Tillmann (2014) has argued that ERP findings attributed to cognitive surprisal cannot be unequivocally separated from sensory surprisal. Here we report a novel EEG paradigm that uses three auditory short-term memory models and one cognitive model to predict surprisal as indexed by several ERP components (ERAN, N5, P600, and P3a), directly comparing sensory and cognitive contributions. Our paradigm parameterizes a large set of stimuli rather than using categorically “high” and “low” surprisal conditions, addressing issues with past work in which participants may learn where to expect violations and may be biased by local context. The cognitive model (Harrison & Pearce, 2018) predicted higher P3a amplitudes, as did Leman’s (2000) model, indicating both sensory and cognitive contributions to expectation violation. However, no model predicted ERAN, N5, or P600 amplitudes, raising questions about whether traditional interpretations of these ERP components generalize to broader collections of stimuli or rather are limited to less naturalistic stimuli.
期刊介绍:
Music Perception charts the ongoing scholarly discussion and study of musical phenomena. Publishing original empirical and theoretical papers, methodological articles and critical reviews from renowned scientists and musicians, Music Perception is a repository of insightful research. The broad range of disciplines covered in the journal includes: •Psychology •Psychophysics •Linguistics •Neurology •Neurophysiology •Artificial intelligence •Computer technology •Physical and architectural acoustics •Music theory