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https://hdl.handle.net/2440/119449
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Type: | Journal article |
Title: | Sleep-dependent memory consolidation and incremental sentence comprehension: computational dependencies during language learning as revealed by neuronal oscillations |
Author: | Cross, Z.R. Kohler, M.J. Schlesewsky, M. Gaskell, M.G. Bornkessel-Schlesewsky, I. |
Citation: | Frontiers in Human Neuroscience, 2018; 12:1-1-18-18 |
Publisher: | Frontiers |
Issue Date: | 2018 |
ISSN: | 1662-5161 1662-5161 |
Statement of Responsibility: | Zachariah R. Cross, Mark J. Kohler, Matthias Schlesewsky, M. G. Gaskell and Ina Bornkessel-Schlesewsky |
Abstract: | We hypothesize a beneficial influence of sleep on the consolidation of the combinatorial mechanisms underlying incremental sentence comprehension. These predictions are grounded in recent work examining the effect of sleep on the consolidation of linguistic information, which demonstrate that sleep-dependent neurophysiological activity consolidates the meaning of novel words and simple grammatical rules. However, the sleep-dependent consolidation of sentence-level combinatorics has not been studied to date. Here, we propose that dissociable aspects of sleep neurophysiology consolidate two different types of combinatory mechanisms in human language: sequence-based (order-sensitive) and dependency-based (order-insensitive) combinatorics. The distinction between the two types of combinatorics is motivated both by cross-linguistic considerations and the neurobiological underpinnings of human language. Unifying this perspective with principles of sleep-dependent memory consolidation, we posit that a function of sleep is to optimize the consolidation of sequence-based knowledge (the when) and the establishment of semantic schemas of unordered items (the what) that underpin cross-linguistic variations in sentence comprehension. This hypothesis builds on the proposal that sleep is involved in the construction of predictive codes, a unified principle of brain function that supports incremental sentence comprehension. Finally, we discuss neurophysiological measures (EEG/MEG) that could be used to test these claims, such as the quantification of neuronal oscillations, which reflect basic mechanisms of information processing in the brain. |
Keywords: | Language learning; sentence comprehension; sleep and memory; neuronal oscillations; predictive coding |
Rights: | © 2018 Cross, Kohler, Schlesewsky, Gaskell and Bornkessel- Schlesewsky. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
DOI: | 10.3389/fnhum.2018.00018 |
Grant ID: | http://purl.org/au-research/grants/arc/FT160100437 |
Published version: | http://dx.doi.org/10.3389/fnhum.2018.00018 |
Appears in Collections: | Aurora harvest 8 Psychology publications |
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hdl_119449.pdf | Published Version | 1.53 MB | Adobe PDF | View/Open |
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