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Neuro-computational models of language processing
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In: EISSN: 2333-9691 ; Annual Review of Linguistics ; https://hal.archives-ouvertes.fr/hal-03334485 ; Annual Review of Linguistics, Annual Reviews, In press, ⟨10.1146/lingbuzz/006147⟩ (2021)
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Comprehensive phenotyping of erythropoiesis in human bone marrow: Evaluation of normal and ineffective erythropoiesis
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In: ISSN: 0361-8609 ; EISSN: 1096-8652 ; American Journal of Hematology ; https://hal.archives-ouvertes.fr/hal-03388289 ; American Journal of Hematology, Wiley, 2021, 96 (9), pp.1064-1076. ⟨10.1002/ajh.26247⟩ (2021)
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Le Petit Prince: A multilingual fMRI corpus using ecological stimuli ...
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Le Petit Prince: A multilingual fMRI corpus using ecological stimuli ...
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Le Petit Prince: A multilingual fMRI corpus using ecological stimuli ...
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Le Petit Prince: A multilingual fMRI corpus using ecological stimuli ...
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Le Petit Prince: A multilingual fMRI corpus using ecological stimuli ...
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Modeling Conventionalization and Predictability within MWEs at the Brain Level
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In: Proceedings of the Society for Computation in Linguistics (2020)
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A Neurolinguistic Approach to Noncompositionality and Argument Structure
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Modeling Conventionalization and Predictability in Multi-Word Expressions at Brain-level
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In: CRCNS 2019 ; https://hal.inria.fr/hal-02272435 ; CRCNS 2019, Sep 2019, Austin (Texas), United States (2019)
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Hierarchical structure guides rapid linguistic predictions during naturalistic listening
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Abstract:
The grammar, or syntax, of human language is typically understood in terms of abstract hierarchical structures. However, theories of language processing that emphasize sequential information, not hierarchy, successfully model diverse phenomena. Recent work probing brain signals has shown mixed evidence for hierarchical information in some tasks. We ask whether sequential or hierarchical information guides the expectations that a human listener forms about a word’s part-of-speech when simply listening to every-day language. We compare the predictions of three computational models against electroencephalography signals recorded from human participants who listen passively to an audiobook story. We find that predictions based on hierarchical structure correlate with the human brain response above-and-beyond predictions based only on sequential information. This establishes a link between hierarchical linguistic structure and neural signals that generalizes across the range of syntactic structures found in every-day language.
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Keyword:
Research Article
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URL: https://doi.org/10.1371/journal.pone.0207741 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6334990/ http://www.ncbi.nlm.nih.gov/pubmed/30650078
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Localising Memory Retrieval and Syntactic Composition: An fMRI Study of Naturalistic Language Comprehension
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In: ISSN: 2327-3798 ; EISSN: 2327-3801 ; Language, Cognition and Neuroscience ; https://hal.archives-ouvertes.fr/hal-01930201 ; Language, Cognition and Neuroscience, Taylor and Francis, In press, 34 (4), pp.1-20. ⟨10.1080/23273798.2018.1518533⟩ (2018)
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Localising memory retrieval and syntactic composition: an fMRI study of naturalistic language comprehension ...
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Localising memory retrieval and syntactic composition: an fMRI study of naturalistic language comprehension ...
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Differentiating Phrase Structure Parsing and Memory Retrieval in the Brain
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In: Proceedings of the Society for Computation in Linguistics (2018)
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Neurophysiological dynamics of phrase-structure building during sentence processing
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In: ISSN: 0027-8424 ; EISSN: 1091-6490 ; Proceedings of the National Academy of Sciences of the United States of America ; https://hal.archives-ouvertes.fr/hal-02324920 ; Proceedings of the National Academy of Sciences of the United States of America , National Academy of Sciences, 2017, 114 (18), pp.E3669-E3678. ⟨10.1073/pnas.1701590114⟩ (2017)
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Neurophysiological dynamics of phrase-structure building during sentence processing
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Abstract Linguistic Structure Correlates with Temporal Activity during Naturalistic Comprehension
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