ArticleNature computational science2022
Combining computational controls with natural text reveals aspects of meaning composition.
Article in Nature computational science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Review
- Higher visual areas act like domain-general filters with strong selectivity and functional specialization.Nature communications · 2026Article
- Aligning brains into a shared space improves their alignment with large language models.Nature computational science · 2026Article
- Hierarchical linguistic predictions and cross-level information updating during narrative comprehension.Communications biology · 2025Article
- Mind captioning: Evolving descriptive text of mental content from human brain activity.Science advances · 2025Article
- Progress, challenges and future of linguistic neural decoding with deep learning.Communications biology · 2025Review
- Cortical language areas are coupled via a soft hierarchy of model-based linguistic features.bioRxiv : the preprint server for biology · 2025Article
- Low-Rank Tensor Encoding Models Decompose Natural Speech Comprehension Processes.bioRxiv : the preprint server for biology · 2025Article
- A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations.Neuron · 2024Article
- A conditional latent autoregressive recurrent model for generation and forecasting of beam dynamics in particle accelerators.Scientific reports · 2024Article
- The language network as a natural kind within the broader landscape of the human brain.Nature reviews. Neuroscience · 2024Review
- Article
- Driving and suppressing the human language network using large language models.Nature human behaviour · 2024Article
- Predictive Coding or Just Feature Discovery? An Alternative Account of Why Language Models Fit Brain Data.Neurobiology of language (Cambridge, Mass.) · 2024Article
- Divergences between Language Models and Human Brains.Advances in neural information processing systems · 2024Article
- Computational Language Modeling and the Promise of In Silico Experimentation.Neurobiology of language (Cambridge, Mass.) · 2024Article
- Driving and suppressing the human language network using large language models.bioRxiv : the preprint server for biology · 2023Article
- Bayesian Surprise Predicts Human Event Segmentation in Story Listening.Cognitive science · 2023Article
- Article
- Evidence of a predictive coding hierarchy in the human brain listening to speech.Nature human behaviour · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
To study a core component of human intelligence-our ability to combine the meaning of words-neuroscientists have looked to linguistics. However, linguistic theories are insufficient to account for all brain responses reflecting linguistic composition. In contrast, we adopt a data-driven approach to study the composed meaning of words beyond their individual meaning, which we term 'supra-word meaning'. We construct a computational representation for supra-word meaning and study its brain basis through brain recordings from two complementary imaging modalities. Using functional magnetic resonance imaging, we reveal that hubs that are thought to process lexical meaning also maintain supra-word meaning, suggesting a common substrate for lexical and combinatorial semantics. Surprisingly, we cannot detect supra-word meaning in magnetoencephalography, which suggests that composed meaning might be maintained through a different neural mechanism than the synchronized firing of pyramidal cells. This sensitivity difference has implications for past neuroimaging results and future wearable neurotechnology.
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Registered trials
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