ArticlePLoS biology2022
Neural dynamics differentially encode phrases and sentences during spoken language comprehension.
Article in PLoS biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 44 citations in OpenAlex.
- A quantum-cognitive approach to dynamic meaning construction.Frontiers in psychology · 2026Article
- Hierarchical linguistic predictions and cross-level information updating during narrative comprehension.Communications biology · 2025Article
- Left Perisylvian Rhythms Encode Prosody and Syntax during Delayed Sentence Repetition.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Application of machine learning and temporal response function modeling of EEG data for differential diagnosis in primary progressive aphasia.Scientific reports · 2025Article
- Decoding the Neural Dynamics of Headed Syntactic Structure Building.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Natural language processing models reveal neural dynamics of human conversation.Nature communications · 2025Article
- Language-specific neural dynamics extend syntax into the time domain.PLoS biology · 2025Article
- What's Surprising About Surprisal.Computational brain & behavior · 2025Article
- The structure and statistics of language jointly shape cross-frequency neural dynamics during spoken language comprehension.Nature communications · 2024Article
- Phase-dependent word perception emerges from region-specific sensitivity to the statistics of language.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Alpha and Beta Oscillations Differentially Support Word Production in a Rule-Switching Task.eNeuro · 2024Article
- Lexical Surprisal Shapes the Time Course of Syntactic Structure Building.Neurobiology of language (Cambridge, Mass.) · 2024Article
- Intonation Units in Spontaneous Speech Evoke a Neural Response.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- A tradeoff between acoustic and linguistic feature encoding in spoken language comprehension.eLife · 2023Article
- Delta-Band Neural Responses to Individual Words Are Modulated by Sentence Processing.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Naturalistic Spoken Language Comprehension Is Supported by Alpha and Beta Oscillations.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Aligning statistical models with inference goals in the neuroscience of language: A dual-dependency taxonomy.Imaging neuroscience (Cambridge, Mass.)Article
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3 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Human language stands out in the natural world as a biological signal that uses a structured system to combine the meanings of small linguistic units (e.g., words) into larger constituents (e.g., phrases and sentences). However, the physical dynamics of speech (or sign) do not stand in a one-to-one relationship with the meanings listeners perceive. Instead, listeners infer meaning based on their knowledge of the language. The neural readouts of the perceptual and cognitive processes underlying these inferences are still poorly understood. In the present study, we used scalp electroencephalography (EEG) to compare the neural response to phrases (e.g., the red vase) and sentences (e.g., the vase is red), which were close in semantic meaning and had been synthesized to be physically indistinguishable. Differences in structure were well captured in the reorganization of neural phase responses in delta (approximately <2 Hz) and theta bands (approximately 2 to 7 Hz),and in power and power connectivity changes in the alpha band (approximately 7.5 to 13.5 Hz). Consistent with predictions from a computational model, sentences showed more power, more power connectivity, and more phase synchronization than phrases did. Theta-gamma phase-amplitude coupling occurred, but did not differ between the syntactic structures. Spectral-temporal response function (STRF) modeling revealed different encoding states for phrases and sentences, over and above the acoustically driven neural response. Our findings provide a comprehensive description of how the brain encodes and separates linguistic structures in the dynamics of neural responses. They imply that phase synchronization and strength of connectivity are readouts for the constituent structure of language. The results provide a novel basis for future neurophysiological research on linguistic structure representation in the brain, and, together with our simulations, support time-based binding as a mechanism of structure encoding in neural dynamics.
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