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Quantitatively characterizing reflexive responses to pitch perturbations
BACKGROUND: Reflexive pitch perturbation experiments are commonly used to investigate the neural mechanisms underlying vocal motor control. In these experiments, the fundamental frequency–the acoustic correlate of pitch–of a speech signal is shifted unexpectedly and played back to the speaker via he...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9666385/ https://www.ncbi.nlm.nih.gov/pubmed/36405080 http://dx.doi.org/10.3389/fnhum.2022.929687 |
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author | Kearney, Elaine Nieto-Castañón, Alfonso Falsini, Riccardo Daliri, Ayoub Heller Murray, Elizabeth S. Smith, Dante J. Guenther, Frank H. |
author_facet | Kearney, Elaine Nieto-Castañón, Alfonso Falsini, Riccardo Daliri, Ayoub Heller Murray, Elizabeth S. Smith, Dante J. Guenther, Frank H. |
author_sort | Kearney, Elaine |
collection | PubMed |
description | BACKGROUND: Reflexive pitch perturbation experiments are commonly used to investigate the neural mechanisms underlying vocal motor control. In these experiments, the fundamental frequency–the acoustic correlate of pitch–of a speech signal is shifted unexpectedly and played back to the speaker via headphones in near real-time. In response to the shift, speakers increase or decrease their fundamental frequency in the direction opposing the shift so that their perceived pitch is closer to what they intended. The goal of the current work is to develop a quantitative model of responses to reflexive perturbations that can be interpreted in terms of the physiological mechanisms underlying the response and that captures both group-mean data and individual subject responses. METHODS: A model framework was established that allowed the specification of several models based on Proportional-Integral-Derivative and State-Space/Directions Into Velocities of Articulators (DIVA) model classes. The performance of 19 models was compared in fitting experimental data from two published studies. The models were evaluated in terms of their ability to capture both population-level responses and individual differences in sensorimotor control processes. RESULTS: A three-parameter DIVA model performed best when fitting group-mean data from both studies; this model is equivalent to a single-rate state-space model and a first-order low pass filter model. The same model also provided stable estimates of parameters across samples from individual subject data and performed among the best models to differentiate between subjects. The three parameters correspond to gains in the auditory feedback controller’s response to a perceived error, the delay of this response, and the gain of the somatosensory feedback controller’s “resistance” to this correction. Excellent fits were also obtained from a four-parameter model with an additional auditory velocity error term; this model was better able to capture multi-component reflexive responses seen in some individual subjects. CONCLUSION: Our results demonstrate the stereotyped nature of an individual’s responses to pitch perturbations. Further, we identified a model that captures population responses to pitch perturbations and characterizes individual differences in a stable manner with parameters that relate to underlying motor control capabilities. Future work will evaluate the model in characterizing responses from individuals with communication disorders. |
format | Online Article Text |
id | pubmed-9666385 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96663852022-11-17 Quantitatively characterizing reflexive responses to pitch perturbations Kearney, Elaine Nieto-Castañón, Alfonso Falsini, Riccardo Daliri, Ayoub Heller Murray, Elizabeth S. Smith, Dante J. Guenther, Frank H. Front Hum Neurosci Human Neuroscience BACKGROUND: Reflexive pitch perturbation experiments are commonly used to investigate the neural mechanisms underlying vocal motor control. In these experiments, the fundamental frequency–the acoustic correlate of pitch–of a speech signal is shifted unexpectedly and played back to the speaker via headphones in near real-time. In response to the shift, speakers increase or decrease their fundamental frequency in the direction opposing the shift so that their perceived pitch is closer to what they intended. The goal of the current work is to develop a quantitative model of responses to reflexive perturbations that can be interpreted in terms of the physiological mechanisms underlying the response and that captures both group-mean data and individual subject responses. METHODS: A model framework was established that allowed the specification of several models based on Proportional-Integral-Derivative and State-Space/Directions Into Velocities of Articulators (DIVA) model classes. The performance of 19 models was compared in fitting experimental data from two published studies. The models were evaluated in terms of their ability to capture both population-level responses and individual differences in sensorimotor control processes. RESULTS: A three-parameter DIVA model performed best when fitting group-mean data from both studies; this model is equivalent to a single-rate state-space model and a first-order low pass filter model. The same model also provided stable estimates of parameters across samples from individual subject data and performed among the best models to differentiate between subjects. The three parameters correspond to gains in the auditory feedback controller’s response to a perceived error, the delay of this response, and the gain of the somatosensory feedback controller’s “resistance” to this correction. Excellent fits were also obtained from a four-parameter model with an additional auditory velocity error term; this model was better able to capture multi-component reflexive responses seen in some individual subjects. CONCLUSION: Our results demonstrate the stereotyped nature of an individual’s responses to pitch perturbations. Further, we identified a model that captures population responses to pitch perturbations and characterizes individual differences in a stable manner with parameters that relate to underlying motor control capabilities. Future work will evaluate the model in characterizing responses from individuals with communication disorders. Frontiers Media S.A. 2022-11-02 /pmc/articles/PMC9666385/ /pubmed/36405080 http://dx.doi.org/10.3389/fnhum.2022.929687 Text en Copyright © 2022 Kearney, Nieto-Castañón, Falsini, Daliri, Heller Murray, Smith and Guenther. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Human Neuroscience Kearney, Elaine Nieto-Castañón, Alfonso Falsini, Riccardo Daliri, Ayoub Heller Murray, Elizabeth S. Smith, Dante J. Guenther, Frank H. Quantitatively characterizing reflexive responses to pitch perturbations |
title | Quantitatively characterizing reflexive responses to pitch perturbations |
title_full | Quantitatively characterizing reflexive responses to pitch perturbations |
title_fullStr | Quantitatively characterizing reflexive responses to pitch perturbations |
title_full_unstemmed | Quantitatively characterizing reflexive responses to pitch perturbations |
title_short | Quantitatively characterizing reflexive responses to pitch perturbations |
title_sort | quantitatively characterizing reflexive responses to pitch perturbations |
topic | Human Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9666385/ https://www.ncbi.nlm.nih.gov/pubmed/36405080 http://dx.doi.org/10.3389/fnhum.2022.929687 |
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