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      Pushing the Envelope: Developments in Neural Entrainment to Speech and the Biological Underpinnings of Prosody Perception

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          Abstract

          Prosodic cues in speech are indispensable for comprehending a speaker’s message, recognizing emphasis and emotion, parsing segmental units, and disambiguating syntactic structures. While it is commonly accepted that prosody provides a fundamental service to higher-level features of speech, the neural underpinnings of prosody processing are not clearly defined in the cognitive neuroscience literature. Many recent electrophysiological studies have examined speech comprehension by measuring neural entrainment to the speech amplitude envelope, using a variety of methods including phase-locking algorithms and stimulus reconstruction. Here we review recent evidence for neural tracking of the speech envelope and demonstrate the importance of prosodic contributions to the neural tracking of speech. Prosodic cues may offer a foundation for supporting neural synchronization to the speech envelope, which scaffolds linguistic processing. We argue that prosody has an inherent role in speech perception, and future research should fill the gap in our knowledge of how prosody contributes to speech envelope entrainment.

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          Most cited references114

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          On the interpretation of weight vectors of linear models in multivariate neuroimaging.

          The increase in spatiotemporal resolution of neuroimaging devices is accompanied by a trend towards more powerful multivariate analysis methods. Often it is desired to interpret the outcome of these methods with respect to the cognitive processes under study. Here we discuss which methods allow for such interpretations, and provide guidelines for choosing an appropriate analysis for a given experimental goal: For a surgeon who needs to decide where to remove brain tissue it is most important to determine the origin of cognitive functions and associated neural processes. In contrast, when communicating with paralyzed or comatose patients via brain-computer interfaces, it is most important to accurately extract the neural processes specific to a certain mental state. These equally important but complementary objectives require different analysis methods. Determining the origin of neural processes in time or space from the parameters of a data-driven model requires what we call a forward model of the data; such a model explains how the measured data was generated from the neural sources. Examples are general linear models (GLMs). Methods for the extraction of neural information from data can be considered as backward models, as they attempt to reverse the data generating process. Examples are multivariate classifiers. Here we demonstrate that the parameters of forward models are neurophysiologically interpretable in the sense that significant nonzero weights are only observed at channels the activity of which is related to the brain process under study. In contrast, the interpretation of backward model parameters can lead to wrong conclusions regarding the spatial or temporal origin of the neural signals of interest, since significant nonzero weights may also be observed at channels the activity of which is statistically independent of the brain process under study. As a remedy for the linear case, we propose a procedure for transforming backward models into forward models. This procedure enables the neurophysiological interpretation of the parameters of linear backward models. We hope that this work raises awareness for an often encountered problem and provides a theoretical basis for conducting better interpretable multivariate neuroimaging analyses. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.
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            Phase patterns of neuronal responses reliably discriminate speech in human auditory cortex.

            How natural speech is represented in the auditory cortex constitutes a major challenge for cognitive neuroscience. Although many single-unit and neuroimaging studies have yielded valuable insights about the processing of speech and matched complex sounds, the mechanisms underlying the analysis of speech dynamics in human auditory cortex remain largely unknown. Here, we show that the phase pattern of theta band (4-8 Hz) responses recorded from human auditory cortex with magnetoencephalography (MEG) reliably tracks and discriminates spoken sentences and that this discrimination ability is correlated with speech intelligibility. The findings suggest that an approximately 200 ms temporal window (period of theta oscillation) segments the incoming speech signal, resetting and sliding to track speech dynamics. This hypothesized mechanism for cortical speech analysis is based on the stimulus-induced modulation of inherent cortical rhythms and provides further evidence implicating the syllable as a computational primitive for the representation of spoken language.
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              Sensory processing in autism: a review of neurophysiologic findings.

              Atypical sensory-based behaviors are a ubiquitous feature of autism spectrum disorders (ASDs). In this article, we review the neural underpinnings of sensory processing in autism by reviewing the literature on neurophysiological responses to auditory, tactile, and visual stimuli in autistic individuals. We review studies of unimodal sensory processing and multisensory integration that use a variety of neuroimaging techniques, including electroencephalography (EEG), magnetoencephalography (MEG), and functional MRI. We then explore the impact of covert and overt attention on sensory processing. With additional characterization, neurophysiologic profiles of sensory processing in ASD may serve as valuable biomarkers for diagnosis and monitoring of therapeutic interventions for autism and reveal potential strategies and target brain regions for therapeutic interventions.
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                Author and article information

                Journal
                Brain Sci
                Brain Sci
                brainsci
                Brain Sciences
                MDPI
                2076-3425
                22 March 2019
                March 2019
                : 9
                : 3
                : 70
                Affiliations
                [1 ]Department of Otolaryngology, Vanderbilt University Medical Center, 1215 21st Ave S, Nashville, TN 37232, USA
                [2 ]Department of Psychology and Human Development, Vanderbilt University, 230 Appleton Place, Nashville, TN 37203, USA
                [3 ]Vanderbilt Kennedy Center, 110 Magnolia Circle, Nashville, TN 37203, USA; miriam.lense@ 123456vumc.org
                [4 ]Vanderbilt Brain Institute, Vanderbilt University, 2215 Garland Ave, Nashville, TN 37232, USA
                [5 ]The Curb Center for Art, Enterprise, and Public Policy, Vanderbilt University, 1801 Edgehill Avenue, Nashville, TN 37212, USA
                [6 ]Department of Psychology, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37240, USA
                Author notes
                Author information
                https://orcid.org/0000-0002-9492-2641
                https://orcid.org/0000-0003-1643-6979
                Article
                brainsci-09-00070
                10.3390/brainsci9030070
                6468669
                30909454
                2fc2fba3-ae0e-4ce0-b084-e69b4a168e46
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 31 December 2018
                : 15 March 2019
                Categories
                Review

                prosody,speech envelope,neural entrainment,rhythm,eeg
                prosody, speech envelope, neural entrainment, rhythm, eeg

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