Title |
Beat Processing Is Pre-Attentive for Metrically Simple Rhythms with Clear Accents: An ERP Study
|
---|---|
Published in |
PLOS ONE, May 2014
|
DOI | 10.1371/journal.pone.0097467 |
Pubmed ID | |
Authors |
Fleur L. Bouwer, Titia L. Van Zuijen, Henkjan Honing |
Abstract |
The perception of a regular beat is fundamental to music processing. Here we examine whether the detection of a regular beat is pre-attentive for metrically simple, acoustically varying stimuli using the mismatch negativity (MMN), an ERP response elicited by violations of acoustic regularity irrespective of whether subjects are attending to the stimuli. Both musicians and non-musicians were presented with a varying rhythm with a clear accent structure in which occasionally a sound was omitted. We compared the MMN response to the omission of identical sounds in different metrical positions. Most importantly, we found that omissions in strong metrical positions, on the beat, elicited higher amplitude MMN responses than omissions in weak metrical positions, not on the beat. This suggests that the detection of a beat is pre-attentive when highly beat inducing stimuli are used. No effects of musical expertise were found. Our results suggest that for metrically simple rhythms with clear accents beat processing does not require attention or musical expertise. In addition, we discuss how the use of acoustically varying stimuli may influence ERP results when studying beat processing. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 20% |
Netherlands | 2 | 20% |
United States | 1 | 10% |
Unknown | 5 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 5 | 50% |
Scientists | 4 | 40% |
Practitioners (doctors, other healthcare professionals) | 1 | 10% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Colombia | 1 | <1% |
Germany | 1 | <1% |
Netherlands | 1 | <1% |
Spain | 1 | <1% |
United States | 1 | <1% |
Unknown | 124 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 25 | 19% |
Student > Master | 23 | 18% |
Researcher | 17 | 13% |
Student > Bachelor | 14 | 11% |
Professor > Associate Professor | 10 | 8% |
Other | 25 | 19% |
Unknown | 15 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 50 | 39% |
Neuroscience | 23 | 18% |
Arts and Humanities | 9 | 7% |
Agricultural and Biological Sciences | 7 | 5% |
Linguistics | 4 | 3% |
Other | 16 | 12% |
Unknown | 20 | 16% |