ArticleJournal of cognitive neuroscience2020
A Compositional Neural Architecture for Language.
Article in Journal of cognitive neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed.
- Neural tracking of prosodic and statistical rhythms jointly supports artificial language learning.iScience · 2026Article
- Constituent-constrained word prediction during language comprehension.Nature neuroscience · 2026Article
- Shared Neural Computations for Syntactic and Morphological Structures: Evidence From Mandarin Chinese.Cognitive science · 2026Article
- Linguistic structure and language familiarity sharpen phoneme encoding in the brain.Communications biology · 2026Article
- The rhythm of sensory input shapes audio-visual temporal processing.British journal of psychology (London, England : 1953) · 2026Article
- The evolution of phonemic verbal fluency test: bridging tradition with contemporary insights.Frontiers in psychology · 2026Review
- Genealogies of organizational closure: from logical paradox to mind in life.Frontiers in artificial intelligence · 2026Review
- Left Perisylvian Rhythms Encode Prosody and Syntax during Delayed Sentence Repetition.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- The "Podcast" ECoG dataset for modeling neural activity during natural language comprehension.Scientific data · 2025Article
- Decoding the Neural Dynamics of Headed Syntactic Structure Building.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- The "Podcast" ECoG dataset for modeling neural activity during natural language comprehension.bioRxiv : the preprint server for biology · 2025Article
- Language-specific neural dynamics extend syntax into the time domain.PLoS biology · 2025Article
- What's Surprising About Surprisal.Computational brain & behavior · 2025Article
- Abstract rule generalization for composing novel meaning recruits a frontoparietal control network.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- The structure and statistics of language jointly shape cross-frequency neural dynamics during spoken language comprehension.Nature communications · 2024Article
- Segmenting and Predicting Musical Phrase Structure Exploits Neural Gain Modulation and Phase Precession.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Early language experience modulates the tradeoff between acoustic-temporal and lexico-semantic cortical tracking of speech.iScience · 2024Article
- Structural and sequential regularities modulate phrase-rate neural tracking.Scientific reports · 2024Article
- Shared functional specialization in transformer-based language models and the human brain.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
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Abstract
Hierarchical structure and compositionality imbue human language with unparalleled expressive power and set it apart from other perception-action systems. However, neither formal nor neurobiological models account for how these defining computational properties might arise in a physiological system. I attempt to reconcile hierarchy and compositionality with principles from cell assembly computation in neuroscience; the result is an emerging theory of how the brain could convert distributed perceptual representations into hierarchical structures across multiple timescales while representing interpretable incremental stages of (de)compositional meaning. The model's architecture-a multidimensional coordinate system based on neurophysiological models of sensory processing-proposes that a manifold of neural trajectories encodes sensory, motor, and abstract linguistic states. Gain modulation, including inhibition, tunes the path in the manifold in accordance with behavior and is how latent structure is inferred. As a consequence, predictive information about upcoming sensory input during production and comprehension is available without a separate operation. The proposed processing mechanism is synthesized from current models of neural entrainment to speech, concepts from systems neuroscience and category theory, and a symbolic-connectionist computational model that uses time and rhythm to structure information. I build on evidence from cognitive neuroscience and computational modeling that suggests a formal and mechanistic alignment between structure building and neural oscillations, and moves toward unifying basic insights from linguistics and psycholinguistics with the currency of neural computation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.