Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-9415
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Main Title: Multi-Variate EEG Analysis as a Novel Tool to Examine Brain Responses to Naturalistic Music Stimuli
Author(s): Sturm, Irene
Dähne, Sven
Blankertz, Benjamin
Curio, Gabriel
Type: Article
Language Code: en
Abstract: Note onsets in music are acoustic landmarks providing auditory cues that underlie the perception of more complex phenomena such as beat, rhythm, and meter. For naturalistic ongoing sounds a detailed view on the neural representation of onset structure is hard to obtain, since, typically, stimulus-related EEG signatures are derived by averaging a high number of identical stimulus presentations. Here, we propose a novel multivariate regression-based method extracting onset-related brain responses from the ongoing EEG. We analyse EEG recordings of nine subjects who passively listened to stimuli from various sound categories encompassing simple tone sequences, full-length romantic piano pieces and natural (non-music) soundscapes. The regression approach reduces the 61-channel EEG to one time course optimally reflecting note onsets. The neural signatures derived by this procedure indeed resemble canonical onset-related ERPs, such as the N1-P2 complex. This EEG projection was then utilized to determine the Cortico-Acoustic Correlation (CACor), a measure of synchronization between EEG signal and stimulus. We demonstrate that a significant CACor (i) can be detected in an individual listener's EEG of a single presentation of a full-length complex naturalistic music stimulus, and (ii) it co-varies with the stimuli’s average magnitudes of sharpness, spectral centroid, and rhythmic complexity. In particular, the subset of stimuli eliciting a strong CACor also produces strongly coordinated tension ratings obtained from an independent listener group in a separate behavioral experiment. Thus musical features that lead to a marked physiological reflection of tone onsets also contribute to perceived tension in music.
URI: https://depositonce.tu-berlin.de/handle/11303/10463
http://dx.doi.org/10.14279/depositonce-9415
Issue Date: 28-Oct-2015
Date Available: 10-Dec-2019
DDC Class: 780 Musik
610 Medizin und Gesundheit
Subject(s): EEG
naturalistic music
CACor
License: https://creativecommons.org/licenses/by/4.0/
Journal Title: PLOS ONE
Publisher: Public Library of Science (PLoS)
Publisher Place: San Francisco
Volume: 10
Issue: 10
Article Number: e0141281
Publisher DOI: 10.1371/journal.pone.0141281
EISSN: 1932-6203
Appears in Collections:FG Neurotechnologie » Publications

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