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      The Neuronal Basis of Predictive Coding Along the Auditory Pathway: From the Subcortical Roots to Cortical Deviance Detection

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          Abstract

          In this review, we attempt to integrate the empirical evidence regarding stimulus-specific adaptation (SSA) and mismatch negativity (MMN) under a predictive coding perspective (also known as Bayesian or hierarchical-inference model). We propose a renewed methodology for SSA study, which enables a further decomposition of deviance detection into repetition suppression and prediction error, thanks to the use of two controls previously introduced in MMN research: the many-standards and the cascade sequences. Focusing on data obtained with cellular recordings, we explain how deviance detection and prediction error are generated throughout hierarchical levels of processing, following two vectors of increasing computational complexity and abstraction along the auditory neuraxis: from subcortical toward cortical stations and from lemniscal toward nonlemniscal divisions. Then, we delve into the particular characteristics and contributions of subcortical and cortical structures to this generative mechanism of hierarchical inference, analyzing what is known about the role of neuromodulation and local microcircuitry in the emergence of mismatch signals. Finally, we describe how SSA and MMN are occurring at similar time frame and cortical locations, and both are affected by the manipulation of N-methyl- D-aspartate receptors. We conclude that there is enough empirical evidence to consider SSA and MMN, respectively, as the microscopic and macroscopic manifestations of the same physiological mechanism of deviance detection in the auditory cortex. Hence, the development of a common theoretical framework for SSA and MMN is all the more recommendable for future studies. In this regard, we suggest a shared nomenclature based on the predictive coding interpretation of deviance detection.

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          The mismatch negativity (MMN) in basic research of central auditory processing: a review.

          In the present article, the basic research using the mismatch negativity (MMN) and analogous results obtained by using the magnetoencephalography (MEG) and other brain-imaging technologies is reviewed. This response is elicited by any discriminable change in auditory stimulation but recent studies extended the notion of the MMN even to higher-order cognitive processes such as those involving grammar and semantic meaning. Moreover, MMN data also show the presence of automatic intelligent processes such as stimulus anticipation at the level of auditory cortex. In addition, the MMN enables one to establish the brain processes underlying the initiation of attention switch to, conscious perception of, sound change in an unattended stimulus stream.
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            Repetition and the brain: neural models of stimulus-specific effects.

            One of the most robust experience-related cortical dynamics is reduced neural activity when stimuli are repeated. This reduction has been linked to performance improvements due to repetition and also used to probe functional characteristics of neural populations. However, the underlying neural mechanisms are as yet unknown. Here, we consider three models that have been proposed to account for repetition-related reductions in neural activity, and evaluate them in terms of their ability to account for the main properties of this phenomenon as measured with single-cell recordings and neuroimaging techniques. We also discuss future directions for distinguishing between these models, which will be important for understanding the neural consequences of repetition and for interpreting repetition-related effects in neuroimaging data.
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              How inhibition shapes cortical activity.

              Cortical processing reflects the interplay of synaptic excitation and synaptic inhibition. Rapidly accumulating evidence is highlighting the crucial role of inhibition in shaping spontaneous and sensory-evoked cortical activity and thus underscores how a better knowledge of inhibitory circuits is necessary for our understanding of cortical function. We discuss current views of how inhibition regulates the function of cortical neurons and point to a number of important open questions. Copyright © 2011 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Trends Hear
                Trends Hear
                TIA
                sptia
                Trends in Hearing
                SAGE Publications (Sage CA: Los Angeles, CA )
                2331-2165
                19 July 2018
                Jan-Dec 2018
                : 22
                : 2331216518784822
                Affiliations
                [1 ]Auditory Neuroscience Laboratory (Lab 1), Institute of Neuroscience of Castile and León, University of Salamanca, Salamanca, Spain
                [2 ]Salamanca Institute for Biomedical Research, Spain
                [3 ]Department of Cell Biology and Pathology, Faculty of Medicine, University of Salamanca, Spain
                Author notes
                [*]Manuel S. Malmierca, Auditory Neuroscience Laboratory (Lab 1), Institute of Neuroscience of Castilla y León, University of Salamanca, Salamanca, Castile and León 37001, Spain. Email: msm@ 123456usal.es
                Author information
                http://orcid.org/0000-0001-5266-1941
                http://orcid.org/0000-0003-0168-7572
                Article
                10.1177_2331216518784822
                10.1177/2331216518784822
                6053868
                30022729
                9068ba8e-a550-491c-b083-0795fee5da86
                © The Author(s) 2018

                Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                : 6 February 2018
                : 29 May 2018
                Funding
                Funded by: the Spanish MINECO, FundRef ;
                Award ID: SAF2016-75803-P
                Categories
                ISAAR Special Issue: Review Article
                Custom metadata
                January-December 2018

                ssa,mmn,predictive coding,deviance detection,repetition suppression

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