Evidence map›Paper›PMID 37506120›Full record

ArticlePLoS computational biology2023

Mechanisms of sensorimotor adaptation in a hierarchical state feedback control model of speech.

Kwang S Kim, Jessica L Gaines, Benjamin Parrell, Vikram Ramanarayanan, Srikantan S Nagarajan, John F Houde

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
4.4field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 17 citations in OpenAlex.

  1. Feasible cognition requires latent state.Biological cybernetics · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Active inference and speech motor control.Psychonomic bulletin & review · 2026
    Review
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  7. Article
  8. Article
  9. Neurophysiological Evidence of Sensory Prediction Errors Driving Speech Sensorimotor Adaptation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  10. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Kwang S KimDepartment of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, Indiana, United States of America.ORCID 0000-0002-3600-7090
Jessica L GainesGraduate Program in Bioengineering, University of California Berkeley-University of California San Francisco, San Francisco, California, United States of America.ORCID 0000-0002-2632-8851
Benjamin ParrellDepartment of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.ORCID 0000-0003-2610-2884
Vikram RamanarayananDepartment of Otolaryngology-Head and Neck Surgery, University of California San Francisco, San Francisco, California, United States of America.ORCID 0000-0001-7810-2769
Srikantan S NagarajanDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, United States of America.ORCID 0000-0001-7209-3857
John F HoudeDepartment of Otolaryngology-Head and Neck Surgery, University of California San Francisco, San Francisco, California, United States of America.
University of California, San Francisco · USPurdue University West Lafayette · USUniversity of Wisconsin–Madison · US

Funding

Understanding disorder-specific neural pathophysiology in laryngeal dystonia and voice tremorP50DC019900 · NIDCD · MASSACHUSETTS EYE AND EAR INFIRMARY · PI Kristina Simonyan · 2021 to 2026
$11.9M
The role of the cerebellum in speechR01DC017091 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI John Francis Houde, RICHARD IVRY · 2019 to 2026
$4.5M
Dynamic Brain Imaging of Speech in Primary Progressive AphasiaR01NS100440 · NINDS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MARIA LUISA GORNO TEMPINI, John Francis Houde · 2017 to 2026
$3.6M
Imaging sensorimotor adaptation and compensation of speechR01DC013979 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HOUDE, JOHN FRANCIS, NAGARAJAN, SRIKANTAN S. · 2014 to 2018
$1.7M
Role of auditory feedback in speech motor control in Alzheimer's diseaseR01DC017696 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HOUDE, JOHN FRANCIS, NAGARAJAN, SRIKANTAN S. · 2018 to 2020
$1.5M
Neural basis of auditory-motor adaptationF32DC019538 · NIDCD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KIM, KWANG SEOB · 2021 to 2023
$86k
NIDCD NIH HHS F32 DC019538NIDCD NIH HHS P50 DC019900NIDCD NIH HHS R01 DC013979NIDCD NIH HHS R01 DC017091NIDCD NIH HHS R01 DC017696NINDS NIH HHS R01 NS100440
6 · The paper itself

Abstract

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.

Indexed as

Adaptation, PhysiologicalSpeechFeedbackFeedback, SensoryHumansMovement

Identifiers

PMID37506120
PMCPMC10434967
OpenAlexW4385335114

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.