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Pupil drift rate indexes groove ratings

Groove, understood as an enjoyable compulsion to move to musical rhythms, typically varies along an inverted U-curve with increasing rhythmic complexity (e.g., syncopation, pickups). Predictive coding accounts posit that moderate complexity drives us to move to reduce sensory prediction errors and m...

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Autores principales: Spiech, Connor, Sioros, George, Endestad, Tor, Danielsen, Anne, Laeng, Bruno
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270355/
https://www.ncbi.nlm.nih.gov/pubmed/35804069
http://dx.doi.org/10.1038/s41598-022-15763-w
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author Spiech, Connor
Sioros, George
Endestad, Tor
Danielsen, Anne
Laeng, Bruno
author_facet Spiech, Connor
Sioros, George
Endestad, Tor
Danielsen, Anne
Laeng, Bruno
author_sort Spiech, Connor
collection PubMed
description Groove, understood as an enjoyable compulsion to move to musical rhythms, typically varies along an inverted U-curve with increasing rhythmic complexity (e.g., syncopation, pickups). Predictive coding accounts posit that moderate complexity drives us to move to reduce sensory prediction errors and model the temporal structure. While musicologists generally distinguish the effects of pickups (anacruses) and syncopations, their difference remains unexplored in groove. We used pupillometry as an index to noradrenergic arousal while subjects listened to and rated drumbeats varying in rhythmic complexity. We replicated the inverted U-shaped relationship between rhythmic complexity and groove and showed this is modulated by musical ability, based on a psychoacoustic beat perception test. The pupil drift rates suggest that groovier rhythms hold attention longer than ones rated less groovy. Moreover, we found complementary effects of syncopations and pickups on groove ratings and pupil size, respectively, discovering a distinct predictive process related to pickups. We suggest that the brain deploys attention to pickups to sharpen subsequent strong beats, augmenting the predictive scaffolding’s focus on beats that reduce syncopations’ prediction errors. This interpretation is in accordance with groove envisioned as an embodied resolution of precision-weighted prediction error.
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spelling pubmed-92703552022-07-10 Pupil drift rate indexes groove ratings Spiech, Connor Sioros, George Endestad, Tor Danielsen, Anne Laeng, Bruno Sci Rep Article Groove, understood as an enjoyable compulsion to move to musical rhythms, typically varies along an inverted U-curve with increasing rhythmic complexity (e.g., syncopation, pickups). Predictive coding accounts posit that moderate complexity drives us to move to reduce sensory prediction errors and model the temporal structure. While musicologists generally distinguish the effects of pickups (anacruses) and syncopations, their difference remains unexplored in groove. We used pupillometry as an index to noradrenergic arousal while subjects listened to and rated drumbeats varying in rhythmic complexity. We replicated the inverted U-shaped relationship between rhythmic complexity and groove and showed this is modulated by musical ability, based on a psychoacoustic beat perception test. The pupil drift rates suggest that groovier rhythms hold attention longer than ones rated less groovy. Moreover, we found complementary effects of syncopations and pickups on groove ratings and pupil size, respectively, discovering a distinct predictive process related to pickups. We suggest that the brain deploys attention to pickups to sharpen subsequent strong beats, augmenting the predictive scaffolding’s focus on beats that reduce syncopations’ prediction errors. This interpretation is in accordance with groove envisioned as an embodied resolution of precision-weighted prediction error. Nature Publishing Group UK 2022-07-08 /pmc/articles/PMC9270355/ /pubmed/35804069 http://dx.doi.org/10.1038/s41598-022-15763-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Spiech, Connor
Sioros, George
Endestad, Tor
Danielsen, Anne
Laeng, Bruno
Pupil drift rate indexes groove ratings
title Pupil drift rate indexes groove ratings
title_full Pupil drift rate indexes groove ratings
title_fullStr Pupil drift rate indexes groove ratings
title_full_unstemmed Pupil drift rate indexes groove ratings
title_short Pupil drift rate indexes groove ratings
title_sort pupil drift rate indexes groove ratings
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270355/
https://www.ncbi.nlm.nih.gov/pubmed/35804069
http://dx.doi.org/10.1038/s41598-022-15763-w
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