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Neurophysiological evidence of sensory prediction errors driving speech sensorimotor adaptation

The human sensorimotor system has a remarkable ability to quickly and efficiently learn movements from sensory experience. A prominent example is sensorimotor adaptation, learning that characterizes the sensorimotor system’s response to persistent sensory errors by adjusting future movements to comp...

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Autores principales: Kim, Kwang S., Hinkley, Leighton B., Dale, Corby L., Nagarajan, Srikantan S., Houde, John F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634734/
https://www.ncbi.nlm.nih.gov/pubmed/37961099
http://dx.doi.org/10.1101/2023.10.22.563504
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author Kim, Kwang S.
Hinkley, Leighton B.
Dale, Corby L.
Nagarajan, Srikantan S.
Houde, John F.
author_facet Kim, Kwang S.
Hinkley, Leighton B.
Dale, Corby L.
Nagarajan, Srikantan S.
Houde, John F.
author_sort Kim, Kwang S.
collection PubMed
description The human sensorimotor system has a remarkable ability to quickly and efficiently learn movements from sensory experience. A prominent example is sensorimotor adaptation, learning that characterizes the sensorimotor system’s response to persistent sensory errors by adjusting future movements to compensate for those errors. Despite being essential for maintaining and fine-tuning motor control, mechanisms underlying sensorimotor adaptation remain unclear. A component of sensorimotor adaptation is implicit (i.e., the learner is unaware of the learning process) which has been suggested to result from sensory prediction errors–the discrepancies between predicted sensory consequences of motor commands and actual sensory feedback. However, to date no direct neurophysiological evidence that sensory prediction errors drive adaptation has been demonstrated. Here, we examined prediction errors via magnetoencephalography (MEG) imaging of the auditory cortex during sensorimotor adaptation of speech to altered auditory feedback, an entirely implicit adaptation task. Specifically, we measured how speaking-induced suppression (SIS)--a neural representation of auditory prediction errors--changed over the trials of the adaptation experiment. SIS refers to the suppression of auditory cortical response to speech onset (in particular, the M100 response) to self-produced speech when compared to the response to passive listening to identical playback of that speech. SIS was reduced (reflecting larger prediction errors) during the early learning phase compared to the initial unaltered feedback phase. Furthermore, reduction in SIS positively correlated with behavioral adaptation extents, suggesting that larger prediction errors were associated with more learning. In contrast, such a reduction in SIS was not found in a control experiment in which participants heard unaltered feedback and thus did not adapt. In addition, in some participants who reached a plateau in the late learning phase, SIS increased (reflecting smaller prediction errors), demonstrating that prediction errors were minimal when there was no further adaptation. Together, these findings provide the first neurophysiological evidence for the hypothesis that prediction errors drive human sensorimotor adaptation.
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spelling pubmed-106347342023-11-13 Neurophysiological evidence of sensory prediction errors driving speech sensorimotor adaptation Kim, Kwang S. Hinkley, Leighton B. Dale, Corby L. Nagarajan, Srikantan S. Houde, John F. bioRxiv Article The human sensorimotor system has a remarkable ability to quickly and efficiently learn movements from sensory experience. A prominent example is sensorimotor adaptation, learning that characterizes the sensorimotor system’s response to persistent sensory errors by adjusting future movements to compensate for those errors. Despite being essential for maintaining and fine-tuning motor control, mechanisms underlying sensorimotor adaptation remain unclear. A component of sensorimotor adaptation is implicit (i.e., the learner is unaware of the learning process) which has been suggested to result from sensory prediction errors–the discrepancies between predicted sensory consequences of motor commands and actual sensory feedback. However, to date no direct neurophysiological evidence that sensory prediction errors drive adaptation has been demonstrated. Here, we examined prediction errors via magnetoencephalography (MEG) imaging of the auditory cortex during sensorimotor adaptation of speech to altered auditory feedback, an entirely implicit adaptation task. Specifically, we measured how speaking-induced suppression (SIS)--a neural representation of auditory prediction errors--changed over the trials of the adaptation experiment. SIS refers to the suppression of auditory cortical response to speech onset (in particular, the M100 response) to self-produced speech when compared to the response to passive listening to identical playback of that speech. SIS was reduced (reflecting larger prediction errors) during the early learning phase compared to the initial unaltered feedback phase. Furthermore, reduction in SIS positively correlated with behavioral adaptation extents, suggesting that larger prediction errors were associated with more learning. In contrast, such a reduction in SIS was not found in a control experiment in which participants heard unaltered feedback and thus did not adapt. In addition, in some participants who reached a plateau in the late learning phase, SIS increased (reflecting smaller prediction errors), demonstrating that prediction errors were minimal when there was no further adaptation. Together, these findings provide the first neurophysiological evidence for the hypothesis that prediction errors drive human sensorimotor adaptation. Cold Spring Harbor Laboratory 2023-11-06 /pmc/articles/PMC10634734/ /pubmed/37961099 http://dx.doi.org/10.1101/2023.10.22.563504 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Kim, Kwang S.
Hinkley, Leighton B.
Dale, Corby L.
Nagarajan, Srikantan S.
Houde, John F.
Neurophysiological evidence of sensory prediction errors driving speech sensorimotor adaptation
title Neurophysiological evidence of sensory prediction errors driving speech sensorimotor adaptation
title_full Neurophysiological evidence of sensory prediction errors driving speech sensorimotor adaptation
title_fullStr Neurophysiological evidence of sensory prediction errors driving speech sensorimotor adaptation
title_full_unstemmed Neurophysiological evidence of sensory prediction errors driving speech sensorimotor adaptation
title_short Neurophysiological evidence of sensory prediction errors driving speech sensorimotor adaptation
title_sort neurophysiological evidence of sensory prediction errors driving speech sensorimotor adaptation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634734/
https://www.ncbi.nlm.nih.gov/pubmed/37961099
http://dx.doi.org/10.1101/2023.10.22.563504
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