Evidence map›Paper›PMID 36405080›Full record

ArticleFrontiers in human neuroscience2022

Quantitatively characterizing reflexive responses to pitch perturbations.

Elaine Kearney, Alfonso Nieto-Castañón, Riccardo Falsini, Ayoub Daliri, Elizabeth S Heller Murray, Dante J Smith, Frank H Guenther

Abstract read
In one paragraph

Article in Frontiers in human neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

5 citing papers in PubMed.

  1. Active inference and speech motor control.Psychonomic bulletin & review · 2026
    Review
  2. Article
  3. Article
  4. Do Not Cut Off Your Tail: A Mega-Analysis of Responses to Auditory Perturbation Experiments.Journal of speech, language, and hearing research : JSLHR · 2023
    Article
  5. DIVA Meets EEG: Model Validation Using Formant-Shift Reflex.Applied sciences (Basel, Switzerland) · 2023
    Article
4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Elaine KearneyDepartment of Speech, Language, and Hearing Sciences, Boston University, Boston, MA, United States.
Alfonso Nieto-CastañónDepartment of Speech, Language, and Hearing Sciences, Boston University, Boston, MA, United States.
Riccardo FalsiniDepartment of Speech, Language, and Hearing Sciences, Boston University, Boston, MA, United States.
Ayoub DaliriCollege of Health Solutions, Arizona State University, Tempe, AZ, United States.
Elizabeth S Heller MurrayDepartment of Communication Sciences and Disorders, Temple University, Philadelphia, PA, United States.
Dante J SmithGradutate Program for Neuroscience, Boston University, Boston, MA, United States.
Frank H GuentherDepartment of Speech, Language, and Hearing Sciences, Boston University, Boston, MA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

auditory feedbackcomputational modelingmotor controlpitchspeech production

Identifiers

PMID36405080
PMCPMC9666385

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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.