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Revisiting discrete versus continuous models of human behavior: The case of absolute pitch
Many human behaviors are discussed in terms of discrete categories. Quantizing behavior in this fashion may provide important traction for understanding the complexities of human experience, but it also may bias understanding of phenomena and associated mechanisms. One example of this is absolute pi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769265/ https://www.ncbi.nlm.nih.gov/pubmed/33370349 http://dx.doi.org/10.1371/journal.pone.0244308 |
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author | Van Hedger, Stephen C. Veillette, John Heald, Shannon L. M. Nusbaum, Howard C. |
author_facet | Van Hedger, Stephen C. Veillette, John Heald, Shannon L. M. Nusbaum, Howard C. |
author_sort | Van Hedger, Stephen C. |
collection | PubMed |
description | Many human behaviors are discussed in terms of discrete categories. Quantizing behavior in this fashion may provide important traction for understanding the complexities of human experience, but it also may bias understanding of phenomena and associated mechanisms. One example of this is absolute pitch (AP), which is often treated as a discrete trait that is either present or absent (i.e., with easily identifiable near-perfect “genuine” AP possessors and at-chance non-AP possessors) despite emerging evidence that pitch-labeling ability is not all-or-nothing. We used a large-scale online assessment to test the discrete model of AP, specifically by measuring how intermediate performers related to the typically defined “non-AP” and “genuine AP” populations. Consistent with prior research, individuals who performed at-chance (non-AP) reported beginning musical instruction much later than the near-perfect AP participants, and the highest performers were more likely to speak a tonal language than were the lowest performers (though this effect was not as statistically robust as one would expect from prior research). Critically, however, these developmental factors did not differentiate the near-perfect AP performers from the intermediate AP performers. Gaussian mixture modeling supported the existence of two performance distributions–the first distribution encompassed both the intermediate and near-perfect AP possessors, whereas the second distribution encompassed only the at-chance participants. Overall, these results provide support for conceptualizing intermediate levels of pitch-labeling ability along the same continuum as genuine AP-level pitch labeling ability—in other words, a continuous distribution of AP skill among all above-chance performers rather than discrete categories of ability. Expanding the inclusion criteria for AP makes it possible to test hypotheses about the mechanisms that underlie this ability and relate this ability to more general cognitive mechanisms involved in other abilities. |
format | Online Article Text |
id | pubmed-7769265 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-77692652021-01-08 Revisiting discrete versus continuous models of human behavior: The case of absolute pitch Van Hedger, Stephen C. Veillette, John Heald, Shannon L. M. Nusbaum, Howard C. PLoS One Research Article Many human behaviors are discussed in terms of discrete categories. Quantizing behavior in this fashion may provide important traction for understanding the complexities of human experience, but it also may bias understanding of phenomena and associated mechanisms. One example of this is absolute pitch (AP), which is often treated as a discrete trait that is either present or absent (i.e., with easily identifiable near-perfect “genuine” AP possessors and at-chance non-AP possessors) despite emerging evidence that pitch-labeling ability is not all-or-nothing. We used a large-scale online assessment to test the discrete model of AP, specifically by measuring how intermediate performers related to the typically defined “non-AP” and “genuine AP” populations. Consistent with prior research, individuals who performed at-chance (non-AP) reported beginning musical instruction much later than the near-perfect AP participants, and the highest performers were more likely to speak a tonal language than were the lowest performers (though this effect was not as statistically robust as one would expect from prior research). Critically, however, these developmental factors did not differentiate the near-perfect AP performers from the intermediate AP performers. Gaussian mixture modeling supported the existence of two performance distributions–the first distribution encompassed both the intermediate and near-perfect AP possessors, whereas the second distribution encompassed only the at-chance participants. Overall, these results provide support for conceptualizing intermediate levels of pitch-labeling ability along the same continuum as genuine AP-level pitch labeling ability—in other words, a continuous distribution of AP skill among all above-chance performers rather than discrete categories of ability. Expanding the inclusion criteria for AP makes it possible to test hypotheses about the mechanisms that underlie this ability and relate this ability to more general cognitive mechanisms involved in other abilities. Public Library of Science 2020-12-28 /pmc/articles/PMC7769265/ /pubmed/33370349 http://dx.doi.org/10.1371/journal.pone.0244308 Text en © 2020 Van Hedger et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Van Hedger, Stephen C. Veillette, John Heald, Shannon L. M. Nusbaum, Howard C. Revisiting discrete versus continuous models of human behavior: The case of absolute pitch |
title | Revisiting discrete versus continuous models of human behavior: The case of absolute pitch |
title_full | Revisiting discrete versus continuous models of human behavior: The case of absolute pitch |
title_fullStr | Revisiting discrete versus continuous models of human behavior: The case of absolute pitch |
title_full_unstemmed | Revisiting discrete versus continuous models of human behavior: The case of absolute pitch |
title_short | Revisiting discrete versus continuous models of human behavior: The case of absolute pitch |
title_sort | revisiting discrete versus continuous models of human behavior: the case of absolute pitch |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769265/ https://www.ncbi.nlm.nih.gov/pubmed/33370349 http://dx.doi.org/10.1371/journal.pone.0244308 |
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