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Mechanisms of sensorimotor adaptation in a hierarchical state feedback control model of speech
Upon perceiving sensory errors during movements, the human sensorimotor system updates future movements to compensate for the errors, a phenomenon called sensorimotor adaptation. One component of this adaptation is thought to be driven by sensory prediction errors–discrepancies between predicted and...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10434967/ https://www.ncbi.nlm.nih.gov/pubmed/37506120 http://dx.doi.org/10.1371/journal.pcbi.1011244 |
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author | Kim, Kwang S. Gaines, Jessica L. Parrell, Benjamin Ramanarayanan, Vikram Nagarajan, Srikantan S. Houde, John F. |
author_facet | Kim, Kwang S. Gaines, Jessica L. Parrell, Benjamin Ramanarayanan, Vikram Nagarajan, Srikantan S. Houde, John F. |
author_sort | Kim, Kwang S. |
collection | PubMed |
description | Upon perceiving sensory errors during movements, the human sensorimotor system updates future movements to compensate for the errors, a phenomenon called sensorimotor adaptation. One component of this adaptation is thought to be driven by sensory prediction errors–discrepancies between predicted and actual sensory feedback. However, the mechanisms by which prediction errors drive adaptation remain unclear. Here, auditory prediction error-based mechanisms involved in speech auditory-motor adaptation were examined via the feedback aware control of tasks in speech (FACTS) model. Consistent with theoretical perspectives in both non-speech and speech motor control, the hierarchical architecture of FACTS relies on both the higher-level task (vocal tract constrictions) as well as lower-level articulatory state representations. Importantly, FACTS also computes sensory prediction errors as a part of its state feedback control mechanism, a well-established framework in the field of motor control. We explored potential adaptation mechanisms and found that adaptive behavior was present only when prediction errors updated the articulatory-to-task state transformation. In contrast, designs in which prediction errors updated forward sensory prediction models alone did not generate adaptation. Thus, FACTS demonstrated that 1) prediction errors can drive adaptation through task-level updates, and 2) adaptation is likely driven by updates to task-level control rather than (only) to forward predictive models. Additionally, simulating adaptation with FACTS generated a number of important hypotheses regarding previously reported phenomena such as identifying the source(s) of incomplete adaptation and driving factor(s) for changes in the second formant frequency during adaptation to the first formant perturbation. The proposed model design paves the way for a hierarchical state feedback control framework to be examined in the context of sensorimotor adaptation in both speech and non-speech effector systems. |
format | Online Article Text |
id | pubmed-10434967 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-104349672023-08-18 Mechanisms of sensorimotor adaptation in a hierarchical state feedback control model of speech Kim, Kwang S. Gaines, Jessica L. Parrell, Benjamin Ramanarayanan, Vikram Nagarajan, Srikantan S. Houde, John F. PLoS Comput Biol Research Article Upon perceiving sensory errors during movements, the human sensorimotor system updates future movements to compensate for the errors, a phenomenon called sensorimotor adaptation. One component of this adaptation is thought to be driven by sensory prediction errors–discrepancies between predicted and actual sensory feedback. However, the mechanisms by which prediction errors drive adaptation remain unclear. Here, auditory prediction error-based mechanisms involved in speech auditory-motor adaptation were examined via the feedback aware control of tasks in speech (FACTS) model. Consistent with theoretical perspectives in both non-speech and speech motor control, the hierarchical architecture of FACTS relies on both the higher-level task (vocal tract constrictions) as well as lower-level articulatory state representations. Importantly, FACTS also computes sensory prediction errors as a part of its state feedback control mechanism, a well-established framework in the field of motor control. We explored potential adaptation mechanisms and found that adaptive behavior was present only when prediction errors updated the articulatory-to-task state transformation. In contrast, designs in which prediction errors updated forward sensory prediction models alone did not generate adaptation. Thus, FACTS demonstrated that 1) prediction errors can drive adaptation through task-level updates, and 2) adaptation is likely driven by updates to task-level control rather than (only) to forward predictive models. Additionally, simulating adaptation with FACTS generated a number of important hypotheses regarding previously reported phenomena such as identifying the source(s) of incomplete adaptation and driving factor(s) for changes in the second formant frequency during adaptation to the first formant perturbation. The proposed model design paves the way for a hierarchical state feedback control framework to be examined in the context of sensorimotor adaptation in both speech and non-speech effector systems. Public Library of Science 2023-07-28 /pmc/articles/PMC10434967/ /pubmed/37506120 http://dx.doi.org/10.1371/journal.pcbi.1011244 Text en © 2023 Kim et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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 Kim, Kwang S. Gaines, Jessica L. Parrell, Benjamin Ramanarayanan, Vikram Nagarajan, Srikantan S. Houde, John F. Mechanisms of sensorimotor adaptation in a hierarchical state feedback control model of speech |
title | Mechanisms of sensorimotor adaptation in a hierarchical state feedback control model of speech |
title_full | Mechanisms of sensorimotor adaptation in a hierarchical state feedback control model of speech |
title_fullStr | Mechanisms of sensorimotor adaptation in a hierarchical state feedback control model of speech |
title_full_unstemmed | Mechanisms of sensorimotor adaptation in a hierarchical state feedback control model of speech |
title_short | Mechanisms of sensorimotor adaptation in a hierarchical state feedback control model of speech |
title_sort | mechanisms of sensorimotor adaptation in a hierarchical state feedback control model of speech |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10434967/ https://www.ncbi.nlm.nih.gov/pubmed/37506120 http://dx.doi.org/10.1371/journal.pcbi.1011244 |
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