Kwang S Kim, Leighton B Hinkley, Kurtis Brent, Jessica L Gaines, Alvincé L Pongos, Saloni Gupta, Corby L Dale, Srikantan S Nagarajan, John F Houde
{"title":"Neurophysiological evidence of sensory prediction errors driving speech sensorimotor adaptation.","authors":"Kwang S Kim, Leighton B Hinkley, Kurtis Brent, Jessica L Gaines, Alvincé L Pongos, Saloni Gupta, Corby L Dale, Srikantan S Nagarajan, John F Houde","doi":"10.1523/JNEUROSCI.2084-24.2025","DOIUrl":null,"url":null,"abstract":"<p><p>The human sensorimotor system has a remarkable ability to 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. A component of sensorimotor adaptation is implicit (i.e., the learner is unaware of the learning) which has been suggested to result from sensory prediction errors-discrepancies between predicted sensory consequences of motor commands and actual sensory feedback. However, neurophysiological evidence that sensory prediction errors drive adaptation has never been directly demonstrated. Here, we examined prediction errors via magnetoencephalography 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. In both male and female speakers, reduction in SIS (reflecting larger prediction errors) during the early learning phase compared to the initial unaltered feedback phase 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, demonstrating that prediction errors were minimal when there was no further adaptation. Together, these findings provide the first direct neurophysiological evidence for the hypothesis that prediction errors drive sensorimotor adaptation.<b>Significance Statement</b> This work investigates mechanisms of sensorimotor adaptation, the phenomenon of motor learning due to exposure to altered sensory feedback. Models of motor control have hypothesized that sensorimotor adaptation is driven by sensory prediction errors - the discrepancy between predicted and actual sensory feedback. Here, we provide for the first time direct neurophysiological evidence that speech sensorimotor adaptation is indeed driven by sensory prediction errors using magnetoencephalography (MEG) imaging of auditory cortex during speaking.</p>","PeriodicalId":50114,"journal":{"name":"Journal of Neuroscience","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1523/JNEUROSCI.2084-24.2025","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The human sensorimotor system has a remarkable ability to 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. A component of sensorimotor adaptation is implicit (i.e., the learner is unaware of the learning) which has been suggested to result from sensory prediction errors-discrepancies between predicted sensory consequences of motor commands and actual sensory feedback. However, neurophysiological evidence that sensory prediction errors drive adaptation has never been directly demonstrated. Here, we examined prediction errors via magnetoencephalography 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. In both male and female speakers, reduction in SIS (reflecting larger prediction errors) during the early learning phase compared to the initial unaltered feedback phase 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, demonstrating that prediction errors were minimal when there was no further adaptation. Together, these findings provide the first direct neurophysiological evidence for the hypothesis that prediction errors drive sensorimotor adaptation.Significance Statement This work investigates mechanisms of sensorimotor adaptation, the phenomenon of motor learning due to exposure to altered sensory feedback. Models of motor control have hypothesized that sensorimotor adaptation is driven by sensory prediction errors - the discrepancy between predicted and actual sensory feedback. Here, we provide for the first time direct neurophysiological evidence that speech sensorimotor adaptation is indeed driven by sensory prediction errors using magnetoencephalography (MEG) imaging of auditory cortex during speaking.
期刊介绍:
JNeurosci (ISSN 0270-6474) is an official journal of the Society for Neuroscience. It is published weekly by the Society, fifty weeks a year, one volume a year. JNeurosci publishes papers on a broad range of topics of general interest to those working on the nervous system. Authors now have an Open Choice option for their published articles