Neurophysiological dynamics of phrase-structure building during sentence processing
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Significance: According to most linguists, the syntactic structure of sentences involves a tree-like hierarchy of nested phrases, as in the sentence [happy linguists] [draw [a diagram]]. Here, we searched for the neural implementation of this hypothetical construct. Epileptic patients volunteered to perform a language task while implanted with intracranial electrodes for clinical purposes. While patients read sentences one word at a time, neural activation in left-hemisphere language areas increased with each successive word but decreased suddenly whenever words could be merged into a phrase. This may be the neural footprint of “merge,” a fundamental tree-building operation that has been hypothesized to allow for the recursive properties of human language.
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Grammatically motivated predictions derived from a phrase-structure parser provided the best fit to gamma fluctuations.
“While word-yoked gamma power was explained using computational models that estimated forward-entropy and word-surprisal, (similar to Willems et al., 2016), grammatically motivated predictions derived from a phrase-structure parser provided the best fit to gamma fluctuations.”
From Grounding the neurobiology of language in first principles: The necessity of non-language-centric explanations for language comprehension (2018) · cites this paper as Nelson et al., 2017
Nelson et al. (2017) documented a gradual increase in high-gamma power during single word reading of sentences, which decreased at points where words could be merged into a constituent phrase.
“They documented a gradual increase in high-gamma power during single word reading of sentences, which decreased at points where words could be merged into a constituent phrase.”
From Grounding the neurobiology of language in first principles: The necessity of non-language-centric explanations for language comprehension (2018) · cites this paper as Nelson et al. (2017)
The degree to which prior context constrains future complements appears to mediate both Gamma and alpha activity, suggesting their interplay is crucial and that coupled changes in alpha and gamma power may be a signature of efficient forward-looking predictions.
“The fact that the degree to which prior context constrains future complements appears to mediate both Gamma (Nelson et al., 2017) and alpha (Rommers et al., 2017) activity suggests their interplay is crucial, and that coupled changes in alpha and gamma power may be a signature of efficient forward-looking predictions.”
From Grounding the neurobiology of language in first principles: The necessity of non-language-centric explanations for language comprehension (2018) · cites this paper as Nelson et al., 2017
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Self-citationNeurocomputational Models of Language Processing
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Self-citationDistributed Sensitivity to Syntax and Semantics throughout the Language Network
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Self-citationThe Cortical Maps of Hierarchical Linguistic Structures during Speech Perception
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Eye activity tracks task-relevant structures during speech and auditory sequence perception
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Localizing syntactic predictions using recurrent neural network grammars
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Self-citationSequences of Intonation Units form a ~ 1 Hz rhythm
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Self-citationLe Petit Prince multilingual naturalistic fMRI corpus
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Self-citationA Faculdade da Linguagem: um objeto biológico, uma janela para a mente e uma ponte entre disciplinas
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The measurement, evolution, and neural representation of action grammars of human behavior
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A neuronal retuning hypothesis of sentence-specificity in Broca’s area
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A compositional neural code in high-level visual cortex can explain jumbled word reading
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The emergence of number and syntax units in LSTM language modelsPreprint
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Self-citationROSE: A neurocomputational architecture for syntax
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Self-citationNo evidence of theory of mind reasoning in the human language network
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Hierarchical dynamic coding coordinates speech comprehension in the human brain
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Effects of Structure and Meaning on Cortical Tracking of Linguistic Units in Naturalistic Speech
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Neural tracking of phrases in spoken language comprehension is automatic and task-dependent
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Frequency-specific brain dynamics related to prediction during language comprehension
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SLING: A framework for frame semantic parsingPreprint
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Delta-band neural activity primarily tracks sentences instead of semantic properties of words
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Natural language processing models reveal neural dynamics of human conversation
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Brain correlates of constituent structure in sign language comprehension
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Self-citationPhase synchronization varies systematically with linguistic structure composition
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Left posterior temporal cortex is sensitive to syntax within conceptually matched Arabic expressions
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Diverging neural dynamics for syntactic structure building in naturalistic speaking and listening
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Word Frequency and Predictability Dissociate in Naturalistic Reading
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Self-citationDelta-Band Neural Responses to Individual Words Are Modulated by Sentence Processing
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Distinguishing Syntactic Operations in the Brain: Dependency and Phrase-Structure Parsing
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Discrete Sequential Information Coding: Heteroclinic Cognitive Dynamics
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- Authors
- Nelson, M. J., El Karoui, I., Giber, K., Yang, X., Cohen, L., Koopman, H., Cash, S. S., Naccache, L., Hale, J. T., Pallier, C., & Dehaene, S.
- Affiliations
- Inserm (FR)
- Institut National de la Santé et de la Recherche Médicale (INSERM) U1127, Centre National de la Recherche Scientifique (CNRS) UMR7225, Université Pierre et Marie Curie (UPMC) Paris 6, Institut du Cerveau et de la Moelle Épinière Research Center (ICM), 75013 Paris, France;
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114;
- Stanford University (US)
- Centre National de la Recherche Scientifique (FR)
- University of California, Los Angeles (US)
- Harvard University (US)
- Cornell University (US)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2017-04-17
- Volume
- 114
- Issue
- 18
- Pages
- E3669-E3678
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC5422821
- OpenAlex
- W2606837722
- Cited by
- 319
- References
- 65
- Citations by year
- 2026: 25 · 2025: 36 · 2024: 37 · 2023: 41 · 2022: 33 · 2021: 39 · 2020: 32 · 2019: 34 · 2018: 29 · 2017: 13
- FWCI
- 16.96
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion, other-oa)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- EC | European Research Council (NeuroSyntax)
- Agence Nationale de la Recherche (140301)
- AXA Research Fund (Doctoral Fellowship)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
- Social Sciences › Arts and Humanities › Language and Linguistics › Syntax, Semantics, Linguistic Variation
- Keywords
- sentence processing, phrase structure, syntactic analysis, Merge operation, high-gamma power, superior temporal cortex, inferior frontal cortex, middle temporal gyrus, bottom-up parsing, intracranial recordings
- MeSH terms
- Brain, Female, Frontal Lobe, Humans, Male, Models, Neurological, Speech, Temporal Lobe
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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