Neural correlate of the construction of sentence meaning
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Significance: How do circuits of neurons in your brain extract and hold the meaning of a sentence? To start to address this unanswered question, we measured neural activity from the surface of the human brain in patients being mapped out before neurosurgery, as they read sentences. In many electrodes, neural activity increased steadily over the course of the sentence, but the same was not found when participants read lists of words or pronounceable nonwords, or grammatical nonword strings (“Jabberwocky”). This build-up of neural activity appears to reflect neither word meaning nor syntax alone, but the representation of complex meanings.
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Medium-level regions (areas along A1+ to STS) represent sentences.
“while medium-level regions (areas along A1+ to STS) represent sentences (36, 37).”
From Amplification of local changes along the timescale processing hierarchy (2017) · cites this paper as [37]
The human language network is sensitive to abstract hierarchical rules across isolated phrases, naturalistic narratives, and syntactically well-formed but semantically empty stimuli.
“it is sensitive to abstract hierarchical rules in isolated phrases and sentences [31, 108, 109, 110], in naturalistic narratives [111, 112, 113, 114], and in syntactically well-formed but semantically empty (”
From Dissociating language and thought in large language models (2024) · cites this paper as [108]
The perisylvian fronto-temporal language network shows enhanced activity for stimuli that contain meaningful lexical items and sentence-level syntax.
“The perisylvian fronto-temporal language network shows enhanced activity for stimuli that contain meaningful lexical items and sentence-level syntax (e.g. Fedorenko et al., 2016).”
From Computer code comprehension shares neural resources with formal logical inference in the fronto-parietal network (2020) · cites this paper as Fedorenko et al., 2016
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Hosseini, E., Casto, C., Zaslavsky, N., Conwell, C., Richardson, M., & Fedorenko, E. (2024) · doi:10.1101/2024.12.26.629294 · Cited by 10 · see citing works
Self-citation
- Authors
- Fedorenko, E., Scott, T. L., Brunner, P., Coon, W. G., Pritchett, B., Schalk, G., & Kanwisher, N.
- Affiliations
- Harvard University (US)
- Boston University (US)
- New York State Department of Health (US)
- McGovern Institute for Brain Research (US)
- Corresponding author
- Fedorenko, Evelina
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2016-09-26
- Volume
- 113
- Issue
- 41
- Pages
- E6256-E6262
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC5068329
- OpenAlex
- W2526072446
- Cited by
- 199
- References
- 88
- Citations by year
- 2026: 16 · 2025: 27 · 2024: 26 · 2023: 28 · 2022: 21 · 2021: 24 · 2020: 19 · 2019: 11 · 2018: 14 · 2017: 11 · 2016: 2
- FWCI
- 8.04
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Funders
- HHS | NIH | National Institute of Biomedical Imaging and Bioengineering (EB00856, EB006356, EB018783)
- HHS | NIH | National Institute of Child Health and Human Development (HD-057522)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
- Social Sciences › Psychology › Developmental and Educational Psychology › Language Development and Disorders
- Keywords
- sentence comprehension, sentence meaning, gamma power, intracranial recordings, language comprehension, compositional semantics, syntactic processing, word meaning, working memory, cognitive load, attention, human language evolution
- MeSH terms
- Adolescent, Adult, Brain, Cerebral Cortex, Electrodes, Female, Humans, Semantics, Young Adult
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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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