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Linguistic category structure influences early auditory processing: Converging evidence from mismatch responses and cortical oscillations

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NEUROIMAGE 2016年 128卷 293-301页

作者： Scharinger, Mathias Monahan, Philip J. Idsardi, William J. Max Planck Inst Empir Aesthet Dept Language & Literature Gruneburgweg 14 D-60322 Frankfurt Germany Univ Toronto Scarborough Ctr French & Linguist Scarborough ON Canada Univ Toronto Dept Linguist Toronto ON M5S 1A1 Canada Univ Maryland Dept Linguist College Pk MD 20742 USA Univ Leipzig Biol Incl Cognit Psychol Inst Psychol D-04109 Leipzig Germany

While previous research has established that language-specific knowledge influences early auditory processing, it is still controversial as to what aspects of speech sound representations determine early speech perception. Here, we propose that early processing primarily depends on information propagated top-down from abstractly represented speech sound categories. In particular, we assume that mid-vowels (as in 'b (e) under bart') exert less top-down effects than the high-vowels (as in 'b (i) under bart') because of their less specific (default) tongue height position as compared to either high-or low-vowels (as in 'b (a) under bart'). We tested this assumption in a magnetoencephalography (MEG) study where we contrasted mid-and high-vowels, as well as the low-and high-vowels in a passive odd-ball paradigm. Overall, significant differences between deviants and standards indexed reliable mismatch negativity (MMN) responses between 200 and 300 ms post-stimulus onset. MMN amplitudes differed in the mid/high-vowel contrasts and were significantly reduced when a mid-vowel standard was followed by a high-vowel deviant, extending previous findings. Furthermore, mid-vowel standards showed reduced oscillatory power in the pre-stimulus beta-frequency band (18-26 Hz), compared to high-vowel standards. We take this as converging evidence for linguistic category structure to exert top-down influences on auditory processing. The findings are interpreted within the linguistic model of under specification and the neuropsychological predictive coding framework. (C) 2016 Elsevier Inc. All rights reserved.

关键词： Speech sound perception MEG Mismatch negativity Cortical oscillations Beta-band power Underspecification predictive coding

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Hierarchy of prediction errors for auditory events in human temporal and frontal cortex

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2016年第24期113卷 6755-6760页

作者： Duerschmid, Stefan Edwards, Erik Reichert, Christoph Dewar, Callum Hinrichs, Hermann Heinze, Hans-Jochen Kirsch, Heidi E. Dalal, Sarang S. Deouell, Leon Y. Knight, Robert T. Leibniz Inst Neurobiol Dept Behav Neurol D-39120 Magdeburg Germany Otto Von Guericke Univ Dept Neurol D-39120 Magdeburg Germany Univ Calif Berkeley Helen Wills Neurosci Inst Berkeley CA 94720 USA Univ Calif Berkeley Dept Psychol Berkeley CA 94720 USA Univ Calif San Francisco Dept Neurol San Francisco CA 94143 USA Otto Von Guericke Univ Forsch Campus Stimulate D-39106 Magdeburg Germany German Ctr Neurodegenerat Dis D-39120 Magdeburg Germany Otto Von Guericke Univ Ctr Behav Brain Sci D-39106 Magdeburg Germany Univ Konstanz Zukunftskolleg D-78457 Constance Germany Univ Konstanz Dept Psychol D-78457 Constance Germany Hebrew Univ Jerusalem Dept Psychol IL-91905 Jerusalem Israel Hebrew Univ Jerusalem Edmond & Lily Safra Ctr Brain Sci IL-91904 Jerusalem Israel

predictive coding theories posit that neural networks learn statistical regularities in the environment for comparison with actual outcomes, signaling a prediction error (PE) when sensory deviation occurs. PE studies in audition have capitalized on low-frequency event-related potentials (LF-ERPs), such as the mismatch negativity. However, local cortical activity is well-indexed by higher-frequency bands [high-gamma band (H.): 80-150 Hz]. We compared patterns of human H. and LF-ERPs in deviance detection using electrocorticographic recordings from subdural electrodes over frontal and temporal cortices. Patients listened to trains of task-irrelevant tones in two conditions differing in the predictability of a deviation from repetitive background stimuli (fully predictable vs. unpredictable deviants). We found deviance-related responses in both frequency bands over lateral temporal and inferior frontal cortex, with an earlier latency for H. than for LF-ERPs. Critically, frontal H. activity but not LF-ERPs discriminated between fully predictable and unpredictable changes, with frontal cortex sensitive to unpredictable events. The results highlight the role of frontal cortex and H. activity in deviance detection and PE generation.

关键词： predictive coding prediction error mismatch negativity frontal cortex high gamma-activity

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Linguistic priors shape categorical perception

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LANGUAGE COGNITION AND NEUROSCIENCE 2016年第1期31卷 159-165页

作者： Simanova, Irina Francken, Jolien C. de Lange, Floris P. Bekkering, Harold Radboud Univ Nijmegen Donders Inst Brain Cognit & Behav NL-6525 ED Nijmegen Netherlands

This article reviews recent literature on the role of top-down feedback processes in semantic representations in the brain. Empirical studies on perception and theoretical models of semantic cognition show that sensory input is filtered and interpreted based on predictions from higher order cognitive areas. Here, we review the present evidence to the proposal that linguistic constructs, in particular, words, could serve as effective priors, facilitating perception and integration of sensory information. We address a number of theoretical questions arising from this assumption. The focus here is if linguistic categories have a direct top-down effect on early stages of perception;or rather interact with later processing stages such as semantic analysis. We discuss experimental approaches that could discriminate between these possibilities. Taken together, this article provides a review on the interaction between language and perception from the predictive perspective, and suggests avenues to investigate the underlying mechanisms from this perspective.

关键词： Naming predictive coding top-down effects multisensory integration language and thought

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Perceptual learning of degraded speech by minimizing prediction error

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2016年第12期113卷 E1747-E1756页

作者： Sohoglu, Ediz Davis, Matthew H. MRC Cognit & Brain Sci Unit Cambridge CB2 7EF England UCL Ear Inst London WC1X 8EE England

Human perception is shaped by past experience on multiple time-scales. Sudden and dramatic changes in perception occur when prior knowledge or expectations match stimulus content. These immediate effects contrast with the longer-term, more gradual improvements that are characteristic of perceptual learning. Despite extensive investigation of these two experience-dependent phenomena, there is considerable debate about whether they result from common or dissociable neural mechanisms. Here we test single-and dual-mechanism accounts of experience-dependent changes in perception using concurrent magnetoencephalographic and EEG recordings of neural responses evoked by degraded speech. When speech clarity was enhanced by prior knowledge obtained from matching text, we observed reduced neural activity in a peri-auditory region of the superior temporal gyrus (STG). Critically, longer-term improvements in the accuracy of speech recognition following perceptual learning resulted in reduced activity in a nearly identical STG region. Moreover, short-term neural changes caused by prior knowledge and longer-term neural changes arising from perceptual learning were correlated across subjects with the magnitude of learning-induced changes in recognition accuracy. These experience-dependent effects on neural processing could be dissociated from the neural effect of hearing physically clearer speech, which similarly enhanced perception but increased rather than decreased STG responses. Hence, the observed neural effects of prior knowledge and perceptual learning cannot be attributed to epiphenomenal changes in listening effort that accompany enhanced perception. Instead, our results support a predictive coding account of speech perception;computational simulations show how a single mechanism, minimization of prediction error, can drive immediate perceptual effects of prior knowledge and longer-term perceptual learning of degraded speech.

关键词： perceptual learning predictive coding speech perception magnetoencephalography vocoded speech

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Brain oscillations and connectivity in autism spectrum disorders (ASD): new approaches to methodology, measurement and modelling

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NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS 2016年 71卷 601-620页

作者： Kessler, K. Seymour, R. A. Rippon, G. Aston Univ Sch Life & Hlth Sci Aston Brain Ctr Birmingham B4 7ET W Midlands England

Although atypical social behaviour remains a key characterisation of ASD, the presence of sensory and perceptual abnormalities has been given a more central role in recent classification changes. An understanding of the origins of such aberrations could thus prove a fruitful focus for ASD research. Early neurocognitive models of ASD suggested that the study of high frequency activity in the brain as a measure of cortical connectivity might provide the key to understanding the neural correlates of sensory and perceptual deviations in ASD. As our review shows, the findings from subsequent research have been inconsistent, with a lack of agreement about the nature of any high frequency disturbances in ASD brains. Based on the application of new techniques using more sophisticated measures of brain synchronisation, direction of information flow, and invoking the coupling between high and low frequency bands, we propose a framework which could reconcile apparently conflicting findings in this area and would be consistent both with emerging neurocognitive models of autism and with the heterogeneity of the condition. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Autism Brain oscillations Gamma Brain connectivity predictive coding

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Selective Activation of the Deep Layers of the Human Primary Visual Cortex by Top-Down Feedback

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CURRENT BIOLOGY 2016年第3期26卷 371-376页

作者： Kok, Peter Bains, Lauren J. van Mourik, Tim Norris, David G. de lange, Floris P. Radboud Univ Nijmegen Donders Inst Brain Cognit & Behav Kapittelweg 29 NL-6525 ED Nijmegen Netherlands UNESCO Weltkulturerbe Zollverein Leitstand Kokerei Zollverein Erwin L Hahn Inst Magnet Resonance Imaging Kokereiallee 7 D-45141 Essen Germany Univ Twente MIRA Inst Biomed Technol & Tech Med POB 217 NL-7500 AE Enschede Netherlands

In addition to bottom-up input, the visual cortex receives large amounts of feedback from other cortical areas [1-3]. One compelling example of feedback activation of early visual neurons in the absence of bottom-up input occurs during the famous Kanizsa illusion, where a triangular shape is perceived, even in regions of the image where there is no bottom-up visual evidence for it. This illusion increases the firing activity of neurons in the primary visual cortex with a receptive field on the illusory contour [4]. Feedback signals are largely segregated from feedforward signals within each cortical area, with feedforward signals arriving in the middle layer, while top-down feedback avoids the middle layers and predominantly targets deep and superficial layers [1, 2, 5, 6]. Therefore, the feedback-mediated activity increase in V1 during the perception of illusory shapes should lead to a specific laminar activity profile that is distinct from the activity elicited by bottom-up stimulation. Here, we used fMRI at high field (7 T) to empirically test this hypothesis, by probing the cortical response to illusory figures in human V1 at different cortical depths [7-14]. We found that, whereas bottom-up stimulation activated all cortical layers, feedback activity induced by illusory figures led to a selective activation of the deep layers of V1. These results demonstrate the potential for non-invasive recordings of neural activity with laminar specificity in humans and elucidate the role of top-down signals during perceptual processing.

关键词： perceptual inference shape perception predictive coding laminar fMRI

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Action-Based Learning of Multistate Objects in the Medial Temporal Lobe

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CEREBRAL CORTEX 2016年第5期26卷 1853-1865页

作者： Hindy, Nicholas C. Turk-Browne, Nicholas B. Princeton Univ Princeton Neurosci Inst Princeton NJ 08544 USA Princeton Univ Dept Psychol Princeton NJ 08544 USA

Actions constrain perception by changing the appearance of objects in the environment. As such, they provide an interactive basis for learning the structure of visual input. If an action systematically transforms one stimulus into another, then these stimuli are more likely to reflect different states of the same persisting object over time. Here we show that such multistate objects are represented in the human medial temporal lobe-the result of a mechanism in which actions influence associative learning of how objects transition between states. We further demonstrate that greater recruitment of these action-based representations during object perception is accompanied by attenuated activity in stimulus-selective visual cortex. In this way, our interactions with the environment help build visual knowledge that predictively facilitates perceptual processing.

关键词： action medial temporal lobe object perception predictive coding representational similarity

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Neuroadaptive technology enables implicit cursor control based on medial prefrontal cortex activity

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2016年第52期113卷 14898-14903页

作者： Zander, Thorsten O. Krol, Laurens R. Birbaumer, Niels P. Gramann, Klaus Tech Univ Berlin Biol Psychol & Neuroergon D-10623 Berlin Germany Tech Univ Berlin Team PhyPA Physiol Parameters Adaptat D-10623 Berlin Germany Univ Tubingen Inst Med Psychol & Behav Neurobiol D-72076 Tubingen Germany Wyss Ctr Bio & Neuroengn CH-1202 Geneva Switzerland Univ Calif San Diego Ctr Adv Neurol Engn San Diego CA 92093 USA

The effectiveness of today's human-machine interaction is limited by a communication bottleneck as operators are required to translate high-level concepts into a machine-mandated sequence of instructions. In contrast, we demonstrate effective, goal-oriented control of a computer system without any form of explicit communication from the human operator. Instead, the system generated the necessary input itself, based on real-time analysis of brain activity. Specific brain responses were evoked by violating the operators' expectations to varying degrees. The evoked brain activity demonstrated detectable differences reflecting congruency with or deviations from the operators' expectations. Real-time analysis of this activity was used to build a user model of those expectations, thus representing the optimal (expected) state as perceived by the operator. Based on this model, which was continuously updated, the computer automatically adapted itself to the expectations of its operator. Further analyses showed this evoked activity to originate from the medial prefrontal cortex and to exhibit a linear correspondence to the degree of expectation violation. These findings extend our understanding of human predictive coding and provide evidence that the information used to generate the user model is task-specific and reflects goal congruency. This paper demonstrates a form of interaction without any explicit input by the operator, enabling computer systems to become neuroadaptive, that is, to automatically adapt to specific aspects of their operator's mindset. Neuroadaptive technology significantly widens the communication bottleneck and has the potential to fundamentally change the way we interact with technology.

关键词： human-computer interaction passive brain-computer interfaces electroencephalogram predictive coding neuroadaptive technology

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A touch with words: Dynamic synergies between manual actions and language

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NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS 2016年第0期68卷 59-95页

作者： Garcia, Adolfo M. Ibanez, Agustin Favaloro Univ INECO Fdn Inst Cognit & Translat Neurosci INCyT Lab Expt Psychol & Neurosci LPEN Buenos Aires DF Argentina Consejo Nacl Invest Cient & Tecn Natl Sci & Tech Res Council Buenos Aires DF Argentina Natl Univ Cuyo UNCuyo Fac Elementary & Special Educ FEEyE Mendoza Argentina Univ Autonoma Caribe Barranquilla Colombia Adolfo Ibanez Univ Sch Psychol CSCN Santiago Chile Australian Res Council ACR Ctr Excellence Cognit & its Disorders Sydney NSW Australia

Manual actions are a hallmark of humanness. Their underlying neural circuitry gives rise to species specific skills and interacts with language processes. In particular, multiple studies show that hand-related expressions - verbal units evoking manual activity - variously affect concurrent manual actions, yielding apparently controversial results (interference, facilitation, or null effects) in varied time windows. Through a systematic review of 108 experiments, we show that such effects are driven by several factors, such as the level of verbal processing, action complexity, and the time-lag between linguistic and motor processes. We reconcile key empirical patterns by introducing the Hand-Action-Network Dynamic Language Embodiment (HANDLE) model, an integrative framework based on neural coupling dynamics and predictive-coding principles. To conclude, we assess HANDLE against the backdrop of other action-cognition theories, illustrate its potential applications to understand high-level deficits in motor disorders, and discuss key challenges for further development. In sum, our work aligns with the 'pragmatic turn', moving away from passive and static representationalist perspectives to a more dynamic, enactive, and embodied conceptualization of cognitive processes. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Language embodiment Hand-related language Manual-action networks predictive coding Enactive cognition

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Sensory Deviancy Detection Measured Directly Within the Human Nucleus Accumbens

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CEREBRAL CORTEX 2016年第3期26卷 1168-1175页

作者： Duerschmid, Stefan Zaehle, Tino Hinrichs, Hermann Heinze, Hans-Jochen Voges, Juergen Garrido, Marta I. Dolan, Raymond J. Knight, Robert T. Univ Calif Berkeley Helen Wills Neurosci Inst Berkeley CA 94720 USA Univ Calif Berkeley Dept Psychol 3210 Tolman Hall Berkeley CA 94720 USA Leibniz Inst Neurobiol Dept Behav Neurol Magdeburg Germany Univ Magdeburg Dept Neurol D-39106 Magdeburg Germany Univ Magdeburg Dept Stereotact Neurosurg D-39106 Magdeburg Germany German Ctr Neurodegenerat Dis DZNE Magdeburg Germany Univ Queensland Forschungscampus STIMULATE Brisbane Qld 4072 Australia Univ Queensland Queensland Brain Inst Brisbane Qld 4072 Australia Univ Queensland Ctr Adv Imaging Brisbane Qld 4072 Australia Univ Queensland Australian Res Council Ctr Excellence Integrat Br Brisbane Qld 4072 Australia UCL Wellcome Trust Ctr Neuroimaging London England Humboldt Univ D-10099 Berlin Germany Max Planck UCL Ctr Computat Psychiat & Ageing Res London England

Rapid changes in the environment evoke a comparison between expectancy and actual outcome to inform optimal subsequent behavior. The nucleus accumbens (NAcc), a key interface between the hippocampus and neocortical regions, is a candidate region for mediating this comparison. Here, we report event-related potentials obtained from the NAcc using direct intracranial recordings in 5 human participants while they listened to trains of auditory stimuli differing in their degree of deviation from repetitive background stimuli. NAcc recordings revealed an early mismatch signal (50-220 ms) in response to all deviants. NAcc activity in this time window was also sensitive to the statistics of stimulus deviancy, with larger amplitudes as a function of the level of deviancy. Importantly, this NAcc mismatch signal also predicted generation of longer latency scalp potentials (300-400 ms). The results provide direct human evidence that the NAcc is a key component of a network engaged in encoding statistics of the sensory environmental.

关键词： auditory mismatch P3 prediction error predictive coding nucleus accumbens saliency

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