Reassessing Syntax-Related ERP Components Using Popular Music Chord Sequences: A Model-Based Approach

dc.contributor.authorGoldman, Andrew
dc.date.accessioned2021-12-17T15:08:20Z
dc.date.available2021-12-17T15:08:20Z
dc.date.issued2021-12-01
dc.description.abstractElectroencephalographic 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.en
dc.identifier.citationAndrew Goldman, Peter M. C. Harrison, Tyreek Jackson, Marcus T. Pearce; Reassessing Syntax-Related ERP Components Using Popular Music Chord Sequences: A Model-Based Approach. Music Perception 1 December 2021; 39 (2): 118–144. doi: https://doi.org/10.1525/mp.2021.39.2.118en
dc.identifier.doihttps://doi.org/10.1525/mp.2021.39.2.118
dc.identifier.urihttps://hdl.handle.net/2022/27017
dc.language.isoenen
dc.publisherMusic Perceptionen
dc.relation.isversionofhttps://online.ucpress.edu/mp/article/39/2/118/118983/Reassessing-Syntax-Related-ERP-Components-Usingen
dc.subjectEEGen
dc.subjectERPen
dc.subjectmusic and languageen
dc.subjectcognitive neuroscienceen
dc.subjectstatistical learningen
dc.titleReassessing Syntax-Related ERP Components Using Popular Music Chord Sequences: A Model-Based Approachen
dc.typeArticleen

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