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  Dynamics of functional networks for syllable and word-level processing

Rimmele, J. M., Sun, Y., Michalareas, G., Ghitza, O., & Poeppel, D. (2023). Dynamics of functional networks for syllable and word-level processing. Neurobiology of Language, 4(1), 120-144. doi:10.1162/nol_a_00089.

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This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/legalcode.

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 Creators:
Rimmele, Johanna Maria1, 2, 3, Author                 
Sun, Yue1, 3, Author                 
Michalareas, Giorgos1, 3, Author                 
Ghitza, Oded1, 4, Author           
Poeppel, David1, 2, 5, 6, Author                 
Affiliations:
1Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Max Planck Society, ou_2421697              
2Max Planck NYU Center for Language, Music and Emotion, Frankfurt am Main, Germany; New York, NY, USA, ou_persistent22              
3Department of Cognitive Neuropsychology, Max Planck Institute for Empirical Aesthetics, Max Planck Society, Grüneburgweg 14, 60322 Frankfurt am Main, DE, ou_3351901              
4College of Biomedical Engineering & Hearing Research Center, Boston University, Boston, MA, USA, ou_persistent22              
5Department of Psychology and Center for Neural Science, New York University , New York, NY, USA, ou_persistent22              
6Ernst Strüngmann Institute for Neuroscience, Frankfurt am Main, Germany, ou_persistent22              

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Free keywords: speech, word, syllable transitions, frequency tagging, MEG
 Abstract: Speech comprehension requires the ability to temporally segment the acoustic input for higher-level linguistic analysis. Oscillation-based approaches suggest that low-frequency auditory cortex oscillations track syllable-sized acoustic information and therefore emphasize the relevance of syllabic-level acoustic processing for speech segmentation. How syllabic processing interacts with higher levels of speech processing, beyond segmentation, including the anatomical and neurophysiological characteristics of the networks involved, is debated. In two MEG experiments, we investigate lexical and sublexical word-level processing and the interactions with (acoustic) syllable processing using a frequency-tagging paradigm. Participants listened to disyllabic words presented at a rate of 4 syllables/s. Lexical content (native language), sublexical syllable-to-syllable transitions (foreign language), or mere syllabic information (pseudo-words) were presented. Two conjectures were evaluated: (i) syllable-to-syllable transitions contribute to word-level processing; and (ii) processing of words activates brain areas that interact with acoustic syllable processing. We show that syllable-to-syllable transition information compared to mere syllable information, activated a bilateral superior, middle temporal and inferior frontal network. Lexical content resulted, additionally, in increased neural activity. Evidence for an interaction of word- and acoustic syllable-level processing was inconclusive. Decreases in syllable tracking (cerebroacoustic coherence) in auditory cortex and increases in cross-frequency coupling between right superior and middle temporal and frontal areas were found when lexical content was present compared to all other conditions; however, not when conditions were compared separately. The data provide experimental insight into how subtle and sensitive syllable-to-syllable transition information for word-level processing is.

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Language(s): eng - English
 Dates: 2021-04-182022-11-072023-03-08
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1162/nol_a_00089
 Degree: -

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Title: Neurobiology of Language
Source Genre: Journal
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Publ. Info: Cambridge, MA, USA : MIT Press
Pages: - Volume / Issue: 4 (1) Sequence Number: - Start / End Page: 120 - 144 Identifier: ISSN: 2641-4368
CoNE: https://pure.mpg.de/cone/journals/resource/2641-4368