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| Main Authors: | , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.01537 |
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| _version_ | 1866913083704737792 |
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| author | He, Rui Palominos, Claudio Vallisa, Samuele Yang, Ni Zhang, Han Santos, Miguel Ángel Santos Rezaii, Neguine Valero, Sergi Huang, Yonghua Li, Huan Jiang, Hong Peng, Yongjun Alonso-Sánchez, Maria Francisca Stein, Frederike Kircher, Tilo Homan, Philipp Sommer, Iris Palaniyappan, Lena Hinzen, Wolfram |
| author_facet | He, Rui Palominos, Claudio Vallisa, Samuele Yang, Ni Zhang, Han Santos, Miguel Ángel Santos Rezaii, Neguine Valero, Sergi Huang, Yonghua Li, Huan Jiang, Hong Peng, Yongjun Alonso-Sánchez, Maria Francisca Stein, Frederike Kircher, Tilo Homan, Philipp Sommer, Iris Palaniyappan, Lena Hinzen, Wolfram |
| contents | Isolated word meanings are inherently uncertain. This uncertainty reduces when they are combined and anchored in context. We propose that grammar compresses meaning uncertainty cross-linguistically, which is reflected in brain and selectively disrupted in disorders. Compression was operationalized as the relative difference between non-contextual surprisal estimated from lexical frequency, and contextual surprisal from grammar-sensitive models. In narratives from 20 languages, contextual surprisal reduced frequency-based surprisal. This reduction closely tracked the surprisal cost of reversing word order, and scaled with richer, non-redundant lexis as organized by more complex but optimal dependency structure. During fMRI, surprisal and its reduction explained BOLD activity for comprehension and production in overlapping but distinct regions. Uncertainty reduction was significantly attenuated in aphasia, dementia, and schizophrenia, but remained intact where primary deficit is not language. These findings position uncertainty reduction via grammar as a foundational concept that illuminates principles, brain basis, and disruptions of language. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_01537 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | The grip of grammar on meaning uncertainty: cross-linguistic evidence, neural correlates, and clinical relevance He, Rui Palominos, Claudio Vallisa, Samuele Yang, Ni Zhang, Han Santos, Miguel Ángel Santos Rezaii, Neguine Valero, Sergi Huang, Yonghua Li, Huan Jiang, Hong Peng, Yongjun Alonso-Sánchez, Maria Francisca Stein, Frederike Kircher, Tilo Homan, Philipp Sommer, Iris Palaniyappan, Lena Hinzen, Wolfram Computation and Language Isolated word meanings are inherently uncertain. This uncertainty reduces when they are combined and anchored in context. We propose that grammar compresses meaning uncertainty cross-linguistically, which is reflected in brain and selectively disrupted in disorders. Compression was operationalized as the relative difference between non-contextual surprisal estimated from lexical frequency, and contextual surprisal from grammar-sensitive models. In narratives from 20 languages, contextual surprisal reduced frequency-based surprisal. This reduction closely tracked the surprisal cost of reversing word order, and scaled with richer, non-redundant lexis as organized by more complex but optimal dependency structure. During fMRI, surprisal and its reduction explained BOLD activity for comprehension and production in overlapping but distinct regions. Uncertainty reduction was significantly attenuated in aphasia, dementia, and schizophrenia, but remained intact where primary deficit is not language. These findings position uncertainty reduction via grammar as a foundational concept that illuminates principles, brain basis, and disruptions of language. |
| title | The grip of grammar on meaning uncertainty: cross-linguistic evidence, neural correlates, and clinical relevance |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2605.01537 |