Evidence map›Paper›PMID 39187713›Full record

ArticleNature human behaviour2024

Neural populations in the language network differ in the size of their temporal receptive windows.

Tamar I Regev, Colton Casto, Eghbal A Hosseini, Markus Adamek, Anthony L Ritaccio, Jon T Willie, Peter Brunner, Evelina Fedorenko

Abstract read
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Article in Nature human behaviour, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
  2. The Extended Language Network: Language-Responsive Brain Areas Whose Contributions to Language Remain To Be Discovered.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
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  6. Do Language Models Know Who Did What to Whom?Open mind : discoveries in cognitive science · 2026
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  7. Review
  8. A distinct set of brain areas process prosody-the melody of speech.bioRxiv : the preprint server for biology · 2025
    Article
  9. The cerebellar components of the human language network.bioRxiv : the preprint server for biology · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. TopoNets: High performing vision and language models with brain-like topography.... International Conference on Learning Representations · 2025
    Article
  14. Article
  15. Article
  16. High-level language brain regions process sublexical regularities.Cerebral cortex (New York, N.Y. : 1991) · 2024
    Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Tamar I Regev *Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA. tamarr@mit.edu.ORCID http://orcid.org/0000-0003-0639-0890
Colton Casto *Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA. ccasto@mit.edu.ORCID http://orcid.org/0000-0001-6966-1470
Eghbal A HosseiniBrain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA.
Markus AdamekNational Center for Adaptive Neurotechnologies, Albany, NY, USA.ORCID http://orcid.org/0000-0001-8519-9212
Anthony L RitaccioDepartment of Neurology, Mayo Clinic, Jacksonville, FL, USA.
Jon T WillieNational Center for Adaptive Neurotechnologies, Albany, NY, USA.ORCID http://orcid.org/0000-0001-9565-4338
Peter BrunnerNational Center for Adaptive Neurotechnologies, Albany, NY, USA.ORCID http://orcid.org/0000-0002-2588-2754
Evelina FedorenkoBrain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA. evelina9@mit.edu.ORCID http://orcid.org/0000-0003-3823-514X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite long knowing what brain areas support language comprehension, our knowledge of the neural computations that these frontal and temporal regions implement remains limited. One important unresolved question concerns functional differences among the neural populations that comprise the language network. Here we leveraged the high spatiotemporal resolution of human intracranial recordings (n = 22) to examine responses to sentences and linguistically degraded conditions. We discovered three response profiles that differ in their temporal dynamics. These profiles appear to reflect different temporal receptive windows, with average windows of about 1, 4 and 6 words, respectively. Neural populations exhibiting these profiles are interleaved across the language network, which suggests that all language regions have direct access to distinct, multiscale representations of linguistic input-a property that may be critical for the efficiency and robustness of language processing.

Indexed as

LanguageAdultComprehensionElectrocorticographyFemaleHumansMaleNerve NetSpeech PerceptionTemporal LobeYoung Adult

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Registered trials

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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.