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      Great expectations: Is there evidence for predictive coding in auditory cortex?

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      Neuroscience
      Elsevier BV

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          Abstract

          Predictive coding is possibly one of the most influential, comprehensive, and controversial theories of neural function. While proponents praise its explanatory potential, critics object that key tenets of the theory are untested or even untestable. The present article critically examines existing evidence for predictive coding in the auditory modality. Specifically, we identify five key assumptions of the theory and evaluate each in the light of animal, human and modeling studies of auditory pattern processing. For the first two assumptions - that neural responses are shaped by expectations and that these expectations are hierarchically organized - animal and human studies provide compelling evidence. The anticipatory, predictive nature of these expectations also enjoys empirical support, especially from studies on unexpected stimulus omission. However, for the existence of separate error and prediction neurons, a key assumption of the theory, evidence is lacking. More work exists on the proposed oscillatory signatures of predictive coding, and on the relation between attention and precision. However, results on these latter two assumptions are mixed or contradictory. Looking to the future, more collaboration between human and animal studies, aided by model-based analyses will be needed to test specific assumptions and implementations of predictive coding - and, as such, help determine whether this popular grand theory can fulfill its expectations.

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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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              A neuronal model of a global workspace in effortful cognitive tasks

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                Author and article information

                Journal
                Neuroscience
                Neuroscience
                Elsevier BV
                03064522
                August 2017
                August 2017
                :
                :
                Article
                10.1016/j.neuroscience.2017.07.061
                28782642
                0813889b-8e13-4580-9392-e44257192d94
                © 2017

                http://www.elsevier.com/tdm/userlicense/1.0/

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