A predictive coding framework for rapid neural dynamics during sentence-level language comprehension

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Publication year
2015Source
Cortex, 68, (2015), pp. 155-168ISSN
Publication type
Article / Letter to editor

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Organization
Donders Centre for Cognitive Neuroimaging (DCCN)
Journal title
Cortex
Volume
vol. 68
Page start
p. 155
Page end
p. 168
Subject
110 000 Neurocognition of Language; 110 002 The binding problem for language; 110 024 The role of beta and gamma in unificationAbstract
There is a growing literature investigating the relationship between oscillatory neural dynamics measured using electroencephalography (EEG) and/or magnetoencephalography (MEG), and sentence-level language comprehension. Recent proposals have suggested a strong link between predictive coding accounts of the hierarchical flow of information in the brain, and oscillatory neural dynamics in the beta and gamma frequency ranges. We propose that findings relating beta and gamma oscillations to sentence-level language comprehension might be unified under such a predictive coding account. Our suggestion is that oscillatory activity in the beta frequency range may reflect both the active maintenance of the current network configuration responsible for representing the sentence-level meaning under construction, and the top-down propagation of predictions to hierarchically lower processing levels based on that representation. In addition, we suggest that oscillatory activity in the low and middle gamma range reflect the matching of top-down predictions with bottom-up linguistic input, while evoked high gamma might reflect the propagation of bottom-up prediction errors to higher levels of the processing hierarchy. We also discuss some of the implications of this predictive coding framework, and we outline ideas for how these might be tested experimentally. (C) 2015 Elsevier Ltd. All rights reserved.
This item appears in the following Collection(s)
- Academic publications [232016]
- Donders Centre for Cognitive Neuroimaging [3760]
- Electronic publications [115251]
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