Speech compensation responses and sensorimotor adaptation to formant feedback perturbations

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Control of speech formants is important for the production of distinguishable speech sounds and is achieved with both feedback and learned feedforward control. However, it is unclear whether the learning of feedforward control involves the mechanisms of feedback control. Speakers have been shown to compensate for unpredictable transient mid-utterance perturbations of pitch and loudness feedback, demonstrating online feedback control of these speech features. To determine whether similar feedback control mechanisms exist in the production of formants, responses to unpredictable vowel formant feedback perturbations were examined. Results showed similar within-trial compensatory responses to formant perturbations that were presented at utterance onset and mid-utterance. The relationship between online feedback compensation to unpredictable formant perturbations and sensorimotor adaptation to consistent formant perturbations was further examined. Within-trial online compensation responses were not correlated with across-trial sensorimotor adaptation. A detailed analysis of within-trial time course dynamics across trials during sensorimotor adaptation revealed that across-trial sensorimotor adaptation responses did not result from an incorporation of within-trial compensation response. These findings suggest that online feedback compensation and sensorimotor adaptation are governed by distinct neural mechanisms. These findings have important implications for models of speech motor control in terms of how feedback and feedforward control mechanisms are implemented.

Related collections

Most cited references 61

Record: found
Abstract: found
Article: not found

Error correction, sensory prediction, and adaptation in motor control.

Andrew D. A. C. Smith, John Krakauer, Reza Shadmehr (2009)

Motor control is the study of how organisms make accurate goal-directed movements. Here we consider two problems that the motor system must solve in order to achieve such control. The first problem is that sensory feedback is noisy and delayed, which can make movements inaccurate and unstable. The second problem is that the relationship between a motor command and the movement it produces is variable, as the body and the environment can both change. A solution is to build adaptive internal models of the body and the world. The predictions of these internal models, called forward models because they transform motor commands into sensory consequences, can be used to both produce a lifetime of calibrated movements, and to improve the ability of the sensory system to estimate the state of the body and the world around it. Forward models are only useful if they produce unbiased predictions. Evidence shows that forward models remain calibrated through motor adaptation: learning driven by sensory prediction errors.

0 comments Cited 218 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

The neuronal representation of pitch in primate auditory cortex.

Xiaoqin Wang, Daniel Bendor (2005)

Pitch perception is critical for identifying and segregating auditory objects, especially in the context of music and speech. The perception of pitch is not unique to humans and has been experimentally demonstrated in several animal species. Pitch is the subjective attribute of a sound's fundamental frequency (f(0)) that is determined by both the temporal regularity and average repetition rate of its acoustic waveform. Spectrally dissimilar sounds can have the same pitch if they share a common f(0). Even when the acoustic energy at f(0) is removed ('missing fundamental') the same pitch is still perceived. Despite its importance for hearing, how pitch is represented in the cerebral cortex is unknown. Here we show the existence of neurons in the auditory cortex of marmoset monkeys that respond to both pure tones and missing fundamental harmonic complex sounds with the same f(0), providing a neural correlate for pitch constancy. These pitch-selective neurons are located in a restricted low-frequency cortical region near the anterolateral border of the primary auditory cortex, and is consistent with the location of a pitch-selective area identified in recent imaging studies in humans.

0 comments Cited 123 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Speech Production as State Feedback Control

John F. Houde, Srikantan Nagarajan (2011)

Spoken language exists because of a remarkable neural process. Inside a speaker's brain, an intended message gives rise to neural signals activating the muscles of the vocal tract. The process is remarkable because these muscles are activated in just the right way that the vocal tract produces sounds a listener understands as the intended message. What is the best approach to understanding the neural substrate of this crucial motor control process? One of the key recent modeling developments in neuroscience has been the use of state feedback control (SFC) theory to explain the role of the CNS in motor control. SFC postulates that the CNS controls motor output by (1) estimating the current dynamic state of the thing (e.g., arm) being controlled, and (2) generating controls based on this estimated state. SFC has successfully predicted a great range of non-speech motor phenomena, but as yet has not received attention in the speech motor control community. Here, we review some of the key characteristics of speech motor control and what they say about the role of the CNS in the process. We then discuss prior efforts to model the role of CNS in speech motor control, and argue that these models have inherent limitations – limitations that are overcome by an SFC model of speech motor control which we describe. We conclude by discussing a plausible neural substrate of our model.

0 comments Cited 106 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Inez Raharjo

Srikantan S. Nagarajan

Journal

Journal ID (nlm-ta): J Acoust Soc Am

Journal ID (iso-abbrev): J Acoust Soc Am

Journal ID (coden): JASMAN

Title: The Journal of the Acoustical Society of America

Publisher: Acoustical Society of America

ISSN (Print): 0001-4966

ISSN (Electronic): 1520-8524

Publication date (Print): February 2021

Publication date (Electronic): 17 February 2021

Publication date PMC-release: 17 February 2021

Volume: 149

Issue: 2

Pages: 1147-1161

Affiliations

[1 ]University of California, Berkeley and University of California, San Francisco, Graduate Program in Bioengineering

[2 ]Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California San Francisco , San Francisco, California 94143, USA

[3 ]Speech Neuroscience Laboratory, Department of Otolaryngology—Head and Neck Surgery, University of California San Francisco , San Francisco, California 94143, USA

Author notes

[a)]

ORCID: 0000-0003-4305-0334.

[b)]

Electronic mail: srikantan.nagarajan@ 123456ucsf.edu

Author information

Hardik Kothare https://orcid.org/0000-0003-4305-0334

Article

Publisher ID: 10.0003440 Publisher-manuscript ID: JASA-05436

DOI: 10.1121/10.0003440

PMC ID: 7892200

PubMed ID: 33639824

SO-VID: 7a4fda1e-3b00-486d-a282-7de09233dd3d

License:

0001-4966/2021/149(2)/1147/15

All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

History

Date received : 27 March 2020

Date revision received : 11 January 2021

Date accepted : 13 January 2021