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      A Simple 3-Parameter Model for Examining Adaptation in Speech and Voice Production

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          Abstract

          Sensorimotor adaptation experiments are commonly used to examine motor learning behavior and to uncover information about the underlying control mechanisms of many motor behaviors, including speech production. In the speech and voice domains, aspects of the acoustic signal are shifted/perturbed over time via auditory feedback manipulations. In response, speakers alter their production in the opposite direction of the shift so that their perceived production is closer to what they intended. This process relies on a combination of feedback and feedforward control mechanisms that are difficult to disentangle. The current study describes and tests a simple 3-parameter mathematical model that quantifies the relative contribution of feedback and feedforward control mechanisms to sensorimotor adaptation. The model is a simplified version of the DIVA model, an adaptive neural network model of speech motor control. The three fitting parameters of SimpleDIVA are associated with the three key subsystems involved in speech motor control, namely auditory feedback control, somatosensory feedback control, and feedforward control. The model is tested through computer simulations that identify optimal model fits to six existing sensorimotor adaptation datasets. We show its utility in (1) interpreting the results of adaptation experiments involving the first and second formant frequencies as well as fundamental frequency; (2) assessing the effects of masking noise in adaptation paradigms; (3) fitting more than one perturbation dimension simultaneously; (4) examining sensorimotor adaptation at different timepoints in the production signal; and (5) quantitatively predicting responses in one experiment using parameters derived from another experiment. The model simulations produce excellent fits to real data across different types of perturbations and experimental paradigms (mean correlation between data and model fits across all six studies = 0.95 ± 0.02). The model parameters provide a mechanistic explanation for the behavioral responses to the adaptation paradigm that are not readily available from the behavioral responses alone. Overall, SimpleDIVA offers new insights into speech and voice motor control and has the potential to inform future directions of speech rehabilitation research in disordered populations. Simulation software, including an easy-to-use graphical user interface, is publicly available to facilitate the use of the model in future studies.

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          Most cited references29

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          Learning of action through adaptive combination of motor primitives.

          Understanding how the brain constructs movements remains a fundamental challenge in neuroscience. The brain may control complex movements through flexible combination of motor primitives, where each primitive is an element of computation in the sensorimotor map that transforms desired limb trajectories into motor commands. Theoretical studies have shown that a system's ability to learn action depends on the shape of its primitives. Using a time-series analysis of error patterns, here we show that humans learn the dynamics of reaching movements through a flexible combination of primitives that have gaussian-like tuning functions encoding hand velocity. The wide tuning of the inferred primitives predicts limitations on the brain's ability to represent viscous dynamics. We find close agreement between the predicted limitations and the subjects' adaptation to new force fields. The mathematical properties of the derived primitives resemble the tuning curves of Purkinje cells in the cerebellum. The activity of these cells may encode primitives that underlie the learning of dynamics.
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            Somatosensory basis of speech production.

            The hypothesis that speech goals are defined acoustically and maintained by auditory feedback is a central idea in speech production research. An alternative proposal is that speech production is organized in terms of control signals that subserve movements and associated vocal-tract configurations. Indeed, the capacity for intelligible speech by deaf speakers suggests that somatosensory inputs related to movement play a role in speech production-but studies that might have documented a somatosensory component have been equivocal. For example, mechanical perturbations that have altered somatosensory feedback have simultaneously altered acoustics. Hence, any adaptation observed under these conditions may have been a consequence of acoustic change. Here we show that somatosensory information on its own is fundamental to the achievement of speech movements. This demonstration involves a dissociation of somatosensory and auditory feedback during speech production. Over time, subjects correct for the effects of a complex mechanical load that alters jaw movements (and hence somatosensory feedback), but which has no measurable or perceptible effect on acoustic output. The findings indicate that the positions of speech articulators and associated somatosensory inputs constitute a goal of speech movements that is wholly separate from the sounds produced.
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              Sensory preference in speech production revealed by simultaneous alteration of auditory and somatosensory feedback.

              The idea that humans learn and maintain accurate speech by carefully monitoring auditory feedback is widely held. But this view neglects the fact that auditory feedback is highly correlated with somatosensory feedback during speech production. Somatosensory feedback from speech movements could be a primary means by which cortical speech areas monitor the accuracy of produced speech. We tested this idea by placing the somatosensory and auditory systems in competition during speech motor learning. To do this, we combined two speech-learning paradigms to simultaneously alter somatosensory and auditory feedback in real time as subjects spoke. Somatosensory feedback was manipulated by using a robotic device that altered the motion path of the jaw. Auditory feedback was manipulated by changing the frequency of the first formant of the vowel sound and playing back the modified utterance to the subject through headphones. The amount of compensation for each perturbation was used as a measure of sensory reliance. All subjects were observed to correct for at least one of the perturbations, but auditory feedback was not dominant. Indeed, some subjects showed a stable preference for either somatosensory or auditory feedback during speech.
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                Author and article information

                Contributors
                Journal
                Front Psychol
                Front Psychol
                Front. Psychol.
                Frontiers in Psychology
                Frontiers Media S.A.
                1664-1078
                21 January 2020
                2019
                : 10
                : 2995
                Affiliations
                [1] 1Department of Speech, Language, and Hearing Sciences, Boston University , Boston, MA, United States
                [2] 2Department of Biomedical Engineering, Boston University , Boston, MA, United States
                [3] 3Department of Speech and Hearing Science, Arizona State University , Tempe, AZ, United States
                [4] 4Faculty of Health Sciences, The University of Sydney , Sydney, NSW, Australia
                [5] 5Department of Psychiatry, University of Michigan , Ann Arbor, MI, United States
                [6] 6Cognitive Imaging Research Center, Department of Radiology, Michigan State University , East Lansing, MI, United States
                [7] 7Graduate Program for Neuroscience, Boston University , Boston, MA, United States
                [8] 8The Picower Institute for Learning and Memory, Massachusetts Institute of Technology , Cambridge, MA, United States
                [9] 9Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital , Charlestown, MA, United States
                Author notes

                Edited by: Pascal van Lieshout, University of Toronto, Canada

                Reviewed by: Douglas M. Shiller, Université de Montréal, Canada; Ben Parrell, University of Wisconsin–Madison, United States

                *Correspondence: Elaine Kearney, ekearney@ 123456bu.edu

                This article was submitted to Language Sciences, a section of the journal Frontiers in Psychology

                Article
                10.3389/fpsyg.2019.02995
                6985569
                32038381
                b0cf623e-8fbb-40b8-b116-b94e2ae710cc
                Copyright © 2020 Kearney, Nieto-Castañón, Weerathunge, Falsini, Daliri, Abur, Ballard, Chang, Chao, Heller Murray, Scott and Guenther.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 29 April 2019
                : 17 December 2019
                Page count
                Figures: 12, Tables: 0, Equations: 4, References: 51, Pages: 16, Words: 0
                Funding
                Funded by: National Institute on Deafness and Other Communication Disorders 10.13039/100000055
                Award ID: R01 DC002852
                Award ID: R01 DC016270
                Award ID: P50 DC015446
                Award ID: R03 DC014045
                Award ID: R01 DC015570
                Award ID: R01 DC011277
                Award ID: T32 DC013017
                Award ID: F31 DC016197
                Categories
                Psychology
                Original Research

                Clinical Psychology & Psychiatry
                computational modeling,sensorimotor adaptation,motor control,speech production,voice,auditory feedback

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