scholarly journals Modeling the Role of Sensory Feedback in Speech Motor Control and Learning

2019 ◽  
Vol 62 (8S) ◽  
pp. 2963-2985 ◽  
Author(s):  
Benjamin Parrell ◽  
John Houde
Keyword(s):  
Motor Control ◽  
Motor System ◽  
Sensory Feedback ◽  
Computational Models ◽  
State Feedback Control ◽  
Speech Motor Control ◽  
Control Feedback ◽  
Motor Production ◽  
Speech Motor

Purpose While the speech motor system is sensitive to feedback perturbations, sensory feedback does not seem to be critical to speech motor production. How the speech motor system is able to be so flexible in its use of sensory feedback remains an open question. Method We draw on evidence from a variety of disciplines to summarize current understanding of the sensory systems' role in speech motor control, including both online control and motor learning. We focus particularly on computational models of speech motor control that incorporate sensory feedback, as these models provide clear encapsulations of different theories of sensory systems' function in speech production. These computational models include the well-established directions into velocities of articulators model and computational models that we have been developing in our labs based on the domain-general theory of state feedback control (feedback aware control of tasks in speech model). Results After establishing the architecture of the models, we show that both the directions into velocities of articulators and state feedback control/feedback aware control of tasks models can replicate key behaviors related to sensory feedback in the speech motor system. Although the models agree on many points, the underlying architecture of the 2 models differs in a few key ways, leading to different predictions in certain areas. We cover key disagreements between the models to show the limits of our current understanding and point toward areas where future experimental studies can resolve these questions. Conclusions Understanding the role of sensory information in the speech motor system is critical to understanding speech motor production and sensorimotor learning in healthy speakers as well as in disordered populations. Computational models, with their concrete implementations and testable predictions, are an important tool to understand this process. Comparison of different models can highlight areas of agreement and disagreement in the field and point toward future experiments to resolve important outstanding questions about the speech motor control system.

Taxonomies in Biology, Phonetics, Phonology, and Speech Motor Control

1990 ◽  
Vol 55 (4) ◽  
pp. 596-611 ◽  
Author(s):  
John W. Folkins ◽  
Ken M. Bleile
Keyword(s):  
Motor Control ◽  
Motor Performance ◽  
Motor System ◽  
Motor Deficits ◽  
Speech Motor Control ◽  
Phonetic Transcription ◽  
Phonological Deficits ◽  
And Performance ◽  
Speech Motor

This article begins with a review explaining the different purposes of biological taxonomies. Taxonomic units are often dependent on the purpose for which the taxonomy has been constructed. Biological taxonomies provide an analogy that we use to emphasize some of the distinctions among the units of phonetic transcription systems, competence phonologies, and performance phonologies. The units of both phonology and phonetic transcription are considered as possible units of the speech motor system, and some of the difficulties of this assumption are explained. Although phonemic units, like units of phonetic transcription, are useful for many purposes, it is not theoretically necessary to use units derived as part of competence phonologies in systems attempting to explain phonological performance or speech motor performance. In this regard, we challenge the concept of coarticulation, because it is based on assumptions about the role of phonological or phonetic units in speech motor control. We offer an integrated perspective that has implications for research in speech motor control and deficits of the speech motor system. We see speech motor deficits as distinct from, yet possibly interacting with, phonological deficits.

Don’t blame yourself: Conscious source monitoring modulates feedback control during speech production

2020 ◽  
Author(s):  
Matthias K. Franken ◽  
Robert Hartsuiker ◽  
Petter Johansson ◽  
Lars Hall ◽  
Andreas Lind
Keyword(s):  
Motor Control ◽  
Auditory Feedback ◽  
Sensory Feedback ◽  
Source Monitoring ◽  
External Source ◽  
The Self ◽  
Speech Motor Control ◽  
Sensory Event ◽  
Speech Motor

Sensory feedback plays an important role in speech motor control. One of the main sources of evidence for this are studies where online auditory feedback is perturbed during ongoing speech. In motor control, it is therefore crucial to distinguish between sensory feedback and externally generated sensory events. This is called source monitoring. Previous altered feedback studies have taken non-conscious source monitoring for granted, as automatic responses to altered sensory feedback imply that the feedback changes are processed as self-caused. However, the role of conscious source monitoring is unclear. The current study investigated whether conscious source monitoring modulates responses to unexpected pitch changes in auditory feedback. During a first block, some participants spontaneously attributed the pitch shifts to themselves (self-blamers) while others attributed them to an external source (other-blamers). Before block 2, all participants were informed that the pitch shifts were experimentally induced. The self-blamers then showed a reduction in response magnitude in block 2 compared with block 1, while the other-blamers did not. This suggests that conscious source monitoring modulates responses to altered auditory feedback, such that consciously ascribing feedback to oneself leads to larger compensation responses. These results can be accounted for within the dominant comparator framework, where conscious source monitoring could modulate the gain on sensory feedback. Alternatively, the results can be naturally explained from an inferential framework, where conscious knowledge may bias the priors in a Bayesian process to determine the most likely source of a sensory event.

EXPRESS: Don’t blame yourself: Conscious source monitoring modulates feedback control during speech production

2022 ◽  
pp. 174702182210756
Author(s):  
Matthias K. Franken ◽  
Robert J Hartsuiker ◽  
Petter Johansson ◽  
Lars Hall ◽  
Andreas Lind
Keyword(s):  
Motor Control ◽  
Auditory Feedback ◽  
Sensory Feedback ◽  
Source Monitoring ◽  
External Source ◽  
The Self ◽  
Speech Motor Control ◽  
Sensory Event ◽  
Speech Motor

Sensory feedback plays an important role in speech motor control. One of the main sources of evidence for this are studies where online auditory feedback is perturbed during ongoing speech. In motor control, it is therefore crucial to distinguish between sensory feedback and externally generated sensory events. This is called source monitoring. Previous altered feedback studies have taken non-conscious source monitoring for granted, as automatic responses to altered sensory feedback imply that the feedback changes are processed as self-caused. However, the role of conscious source monitoring is unclear. The current study investigated whether conscious source monitoring modulates responses to unexpected pitch changes in auditory feedback. During a first block, some participants spontaneously attributed the pitch shifts to themselves (self-blamers) while others attributed them to an external source (other-blamers). Before block 2, all participants were informed that the pitch shifts were experimentally induced. The self-blamers then showed a reduction in response magnitude in block 2 compared with block 1, while the other-blamers did not. This suggests that conscious source monitoring modulates responses to altered auditory feedback, such that consciously ascribing feedback to oneself leads to larger compensation responses. These results can be accounted for within the dominant comparator framework, where conscious source monitoring could modulate the gain on sensory feedback. Alternatively, the results can be naturally explained from an inferential framework, where conscious knowledge may bias the priors in a Bayesian process to determine the most likely source of a sensory event.

Do We Have a “Mental Syllabary” in the Brain? An fMRI Study

Motor Control ◽  
2011 ◽  
Vol 15 (1) ◽  
pp. 34-51 ◽  
Author(s):  
Bettina Brendel ◽  
Michael Erb ◽  
Axel Riecker ◽  
Wolfgang Grodd ◽  
Hermann Ackermann ◽  
...  
Keyword(s):  
Motor Control ◽  
Low Frequency ◽  
Frequency Effect ◽  
Speech Motor Control ◽  
Motor Execution ◽  
Syllable Frequency ◽  
Fmri Study ◽  
The Brain ◽  
Speech Motor

The present study combines functional magnetic resonance imaging (fMRI) and reaction time (RT) measurements to further elucidate the influence of syllable frequency and complexity on speech motor control processes, i.e., overt reading of pseudowords. Tying in with a recent fMRI-study of our group we focused on the concept of a mental syllabary housing syllable sized ready-made motor plans for high- (HF), but not low-frequency (LF) syllables. The RT-analysis disclosed a frequency effect weakened by a simultaneous complexity effect for HF-syllables. In contrast, the fMRI data revealed no effect of syllable frequency, but point to an impact of syllable structure: Compared with CV-items, syllables with a complex onset (CCV) yielded higher hemodynamic activation in motor “execution” areas (left sensorimotor cortex, right inferior cerebellum), which is at least partially compatible with our previous study. We discuss the role of the syllable in speech motor control.

A Contribution to the Role of the Claustrum in Speech Motor Control Processes

2021 ◽  
Author(s):  
Manfred Pützer ◽  
Jean Richard Moringlane ◽  
Wolfgang Reith ◽  
Christoph M. Krick
Keyword(s):  
Motor Control ◽  
Speech Motor Control ◽  
Control Processes ◽  
Speech Motor

scholarly journals Knockout of Foxp2 disrupts vocal development in mice

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Gregg A. Castellucci ◽  
Matthew J. McGinley ◽  
David A. McCormick
Keyword(s):  
Motor Control ◽  
Model System ◽  
Courtship Song ◽  
Vocal Behavior ◽  
Speech Motor Control ◽  
Vocal Development ◽  
Rhythmic Structure ◽  
Adult Mice ◽  
Speech Motor

Abstract The FOXP2 gene is important for the development of proper speech motor control in humans. However, the role of the gene in general vocal behavior in other mammals, including mice, is unclear. Here, we track the vocal development of Foxp2 heterozygous knockout (Foxp2+/−) mice and their wildtype (WT) littermates from juvenile to adult ages, and observe severe abnormalities in the courtship song of Foxp2+/− mice. In comparison to their WT littermates, Foxp2+/− mice vocalized less, produced shorter syllable sequences, and possessed an abnormal syllable inventory. In addition, Foxp2+/− song also exhibited irregular rhythmic structure, and its development did not follow the consistent trajectories observed in WT vocalizations. These results demonstrate that the Foxp2 gene is critical for normal vocal behavior in juvenile and adult mice, and that Foxp2 mutant mice may provide a tractable model system for the study of the gene’s role in general vocal motor control.

scholarly journals The FACTS model of speech motor control: fusing state estimation and task-based control

2019 ◽  
Author(s):  
Benjamin Parrell ◽  
Vikram Ramanarayanan ◽  
Srikantan Nagarajan ◽  
John Houde
Keyword(s):  
Motor Control ◽  
Vocal Tract ◽  
Internal State ◽  
State Feedback Control ◽  
Speech Motor Control ◽  
State Estimate ◽  
Somatosensory Feedback ◽  
Current State ◽  
Trade Offs ◽  
Speech Motor

ABSTRACTWe present a new computational model of speech motor control: the Feedback-Aware Control of Tasks in Speech or FACTS model. This model is based on a state feedback control architecture, which is widely accepted in non-speech motor domains. The FACTS model employs a hierarchical observer-based architecture, with a distinct higher-level controller of speech tasks and a lower-level controller of speech articulators. The task controller is modeled as a dynamical system governing the creation of desired constrictions in the vocal tract, based on the Task Dynamics model. Critically, both the task and articulatory controllers rely on an internal estimate of the current state of the vocal tract to generate motor commands. This internal state estimate is derived from initial predictions based on efference copy of applied controls. The resulting state estimate is then used to generate predictions of expected auditory and somatosensory feedback, and a comparison between predicted feedback and actual feedback is used to update the internal state prediction. We show that the FACTS model is able to qualitatively replicate many characteristics of the human speech system: the model is robust to noise in both the sensory and motor pathways, is relatively unaffected by a loss of auditory feedback but is more significantly impacted by the loss of somatosensory feedback, and responds appropriately to externally-imposed alterations of auditory and somatosensory feedback. The model also replicates previously hypothesized trade-offs between reliance on auditory and somatosensory feedback in speech motor control and shows for the first time how this relationship may be mediated by acuity in each sensory domain. These results have important implications for our understanding of the speech motor control system in humans.

scholarly journals The Role of Sensory Feedback in Developmental Stuttering: A Review

2021 ◽  
pp. 1-27
Author(s):  
Abigail R. Bradshaw ◽  
Daniel R. Lametti ◽  
Carolyn McGettigan
Keyword(s):  
Auditory Feedback ◽  
Sensory Feedback ◽  
Neurodevelopmental Disorder ◽  
Speech Motor Control ◽  
Compensatory Strategies ◽  
Speech Control ◽  
Developmental Stuttering ◽  
Speech Motor ◽  
Lines Of Evidence

Abstract Developmental stuttering is a neurodevelopmental disorder that severely affects speech fluency. Multiple lines of evidence point to a role of sensory feedback in the disorder; this has led to a number of theories proposing different disruptions to the use of sensory feedback during speech motor control in people who stutter. The purpose of this review was to bring together evidence from studies using altered auditory feedback paradigms with people who stutter, in order to evaluate the predictions of these different theories. This review highlights converging evidence for particular patterns of differences in the responses of people who stutter to feedback perturbations. The implications for hypotheses on the nature of the disruption to sensorimotor control of speech in the disorder are discussed, with reference to neurocomputational models of speech control (predominantly, the DIVA model; Guenther et al., 2006; Tourville et al., 2008). While some consistent patterns are emerging from this evidence, it is clear that more work in this area is needed with developmental samples in particular, in order to tease apart differences related to symptom onset from those related to compensatory strategies that develop with experience of stuttering.

scholarly journals Human larynx motor cortices coordinates respiration for vocal-motor control

2020 ◽  
Author(s):  
Michel Belyk ◽  
Rachel Brown ◽  
Deryk S Beal ◽  
Alard Roebroeck ◽  
Carolyn McGettigan ◽  
...  
Keyword(s):  
Motor Control ◽  
Motor System ◽  
Human Species ◽  
Ultra High Field ◽  
Motor Pathways ◽  
Evolution Of Speech ◽  
Human Motor ◽  
Powerful Mechanism ◽  
Speech Motor

Vocal flexibility is a hallmark of the human species, most particularly the capacity to speak and sing. The human motor system is unique in having two separate representations of the laryngeal muscles, where only one would be expected. The dorsal larynx area is known to integrate respiratory function which is provides a powerful mechanism in support of speech motor control, while less is known about the contributions of the ventral larynx. We localised the dorsal and ventral larynx motor cortices by having participants sing wordless melodies while undergoing ultra-high field functional magnetic resonance imaging and tested the involvement of respiratory motor control in the same regions by having participants whistle simple melodies. Surprisingly, both singing and whistling increased activation of both ‘larynx areas’ despite the lack of involvement of the larynx during whistling. We provide the first evidence that this level of integration is not exclusive to the dLMC, suggesting a greater role of the vLMC in the evolution of speech than previously supposed. With this broader understanding of the human vocal-motor system, we outline predictions about the descending motor pathways that give these cortical areas access to both the laryngeal and respiratory systems.

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