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      The Application of EEG Mu Rhythm Measures to Neurophysiological Research in Stuttering

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          Abstract

          Deficits in basal ganglia-based inhibitory and timing circuits along with sensorimotor internal modeling mechanisms are thought to underlie stuttering. However, much remains to be learned regarding the precise manner how these deficits contribute to disrupting both speech and cognitive functions in those who stutter. Herein, we examine the suitability of electroencephalographic (EEG) mu rhythms for addressing these deficits. We review some previous findings of mu rhythm activity differentiating stuttering from non-stuttering individuals and present some new preliminary findings capturing stuttering-related deficits in working memory. Mu rhythms are characterized by spectral peaks in alpha (8–13 Hz) and beta (14–25 Hz) frequency bands (mu-alpha and mu-beta). They emanate from premotor/motor regions and are influenced by basal ganglia and sensorimotor function. More specifically, alpha peaks (mu-alpha) are sensitive to basal ganglia-based inhibitory signals and sensory-to-motor feedback. Beta peaks (mu-beta) are sensitive to changes in timing and capture motor-to-sensory (i.e., forward model) projections. Observing simultaneous changes in mu-alpha and mu-beta across the time-course of specific events provides a rich window for observing neurophysiological deficits associated with stuttering in both speech and cognitive tasks and can provide a better understanding of the functional relationship between these stuttering symptoms. We review how independent component analysis (ICA) can extract mu rhythms from raw EEG signals in speech production tasks, such that changes in alpha and beta power are mapped to myogenic activity from articulators. We review findings from speech production and auditory discrimination tasks demonstrating that mu-alpha and mu-beta are highly sensitive to capturing sensorimotor and basal ganglia deficits associated with stuttering with high temporal precision. Novel findings from a non-word repetition (working memory) task are also included. They show reduced mu-alpha suppression in a stuttering group compared to a typically fluent group. Finally, we review current limitations and directions for future research.

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          Working Memory: Theories, Models, and Controversies

          I present an account of the origins and development of the multicomponent approach to working memory, making a distinction between the overall theoretical framework, which has remained relatively stable, and the attempts to build more specific models within this framework. I follow this with a brief discussion of alternative models and their relationship to the framework. I conclude with speculations on further developments and a comment on the value of attempting to apply models and theories beyond the laboratory studies on which they are typically based.
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            An integrated theory of language production and comprehension.

            Currently, production and comprehension are regarded as quite distinct in accounts of language processing. In rejecting this dichotomy, we instead assert that producing and understanding are interwoven, and that this interweaving is what enables people to predict themselves and each other. We start by noting that production and comprehension are forms of action and action perception. We then consider the evidence for interweaving in action, action perception, and joint action, and explain such evidence in terms of prediction. Specifically, we assume that actors construct forward models of their actions before they execute those actions, and that perceivers of others' actions covertly imitate those actions, then construct forward models of those actions. We use these accounts of action, action perception, and joint action to develop accounts of production, comprehension, and interactive language. Importantly, they incorporate well-defined levels of linguistic representation (such as semantics, syntax, and phonology). We show (a) how speakers and comprehenders use covert imitation and forward modeling to make predictions at these levels of representation, (b) how they interweave production and comprehension processes, and (c) how they use these predictions to monitor the upcoming utterances. We show how these accounts explain a range of behavioral and neuroscientific data on language processing and discuss some of the implications of our proposal.
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              Reorganization and plasticity in the adult brain during learning of motor skills.

              On the basis of brain imaging studies, Doyon and Ungerleider recently proposed a model describing the cerebral plasticity that occurs in both cortico-striatal and cortico-cerebellar systems of the adult brain during learning of new motor skilled behaviors. This theoretical framework makes several testable predictions with regards to the contribution of these neural systems based on the phase (fast, slow, consolidation, automatization, and retention) and nature of the motor learning processes (motor sequence versus motor adaptation) acquired through repeated practice. There has been recent behavioral, lesion and additional neuroimaging studies that have addressed the assumptions made in this theory that will help in the revision of this model.
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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                10 January 2020
                2019
                : 13
                : 458
                Affiliations
                [1] 1Department of Speech and Hearing Sciences, Elson S. Floyd College of Medicine, Washington State University , Spokane, WA, United States
                [2] 2Epley Center for Health Professions, Communication Sciences and Disorders, University of Arkansas , Fayetteville, AR, United States
                [3] 3Department of Communication Sciences and Disorders, Idaho State University , Pocatello, ID, United States
                [4] 4College of Health Professions, Department of Audiology and Speech-Pathology, University of Tennessee Health Science Center , Knoxville, TN, United States
                Author notes

                Edited by: Maja Rogić Vidaković, University of Split, Croatia

                Reviewed by: Josko Soda, University of Split, Croatia; Giovanni Di Liberto, École Normale Supérieure, France

                *Correspondence: Tim Saltuklaroglu tsaltukl@ 123456uthsc.edu

                Specialty section: This article was submitted to Speech and Language, a section of the journal Frontiers in Human Neuroscience

                Article
                10.3389/fnhum.2019.00458
                6965028
                31998103
                b2f47433-c5cd-4071-af31-4ad2e5cb3616
                Copyright © 2020 Jenson, Bowers, Hudock and Saltuklaroglu.

                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
                : 01 August 2019
                : 13 December 2019
                Page count
                Figures: 7, Tables: 2, Equations: 0, References: 155, Pages: 21, Words: 16659
                Categories
                Human Neuroscience
                Original Research

                Neurosciences
                stuttering,mu rhythm,sensorimotor integration,speech production,speech perception,working memory,internal models,basal ganglia

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