Evidence map›Paper›PMID 38454134›Full record

ArticleCommunications biology2024

The cortical representation of language timescales is shared between reading and listening.

Catherine Chen, Tom Dupré la Tour, Jack L Gallant, Daniel Klein, Fatma Deniz

Abstract read
In one paragraph

Article in Communications biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Bilingual language processing relies on shared semantic representations that are modulated by each language.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Hierarchical dynamic coding coordinates speech comprehension in the human brain.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Divergences between Language Models and Human Brains.Advances in neural information processing systems · 2024
    Article
  7. Crafting Interpretable Embeddings for Language Neuroscience by Asking LLMs Questions.Advances in neural information processing systems · 2024
    Article
  8. Scaling laws for language encoding models in fMRI.Advances in neural information processing systems · 2023
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Catherine ChenDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA. cathychen@berkeley.edu.ORCID 0000-0002-1112-1559
Tom Dupré la TourHelen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.ORCID 0000-0002-2674-1670
Jack L GallantHelen Wills Neuroscience Institute, University of California, Berkeley, CA, USA.ORCID 0000-0001-7273-1054
Daniel KleinDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA.
Fatma DenizHelen Wills Neuroscience Institute, University of California, Berkeley, CA, USA. deniz@tu-berlin.de.ORCID 0000-0001-6051-7288

Funding

Visual Representation and AttentionR01EY019684 · NEI · UNIVERSITY OF CALIFORNIA BERKELEY · PI GALLANT, JACK L · 2010 to 2018
$2.9M
Attentional Modulation of Brain RepresentationsR01EY022454 · NEI · UNIVERSITY OF CALIFORNIA BERKELEY · PI GALLANT, JACK L · 2013 to 2016
$1.6M
Bundesministerium für Bildung und Forschung (Federal Ministry of Education and Research) BMBF 01GQ1906National Science Foundation (NSF) DGE 1752814National Science Foundation (NSF) Nat-1912373NEI NIH HHS R01 EY019684NEI NIH HHS R01 EY022454
6 · The paper itself

Abstract

Language comprehension involves integrating low-level sensory inputs into a hierarchy of increasingly high-level features. Prior work studied brain representations of different levels of the language hierarchy, but has not determined whether these brain representations are shared between written and spoken language. To address this issue, we analyze fMRI BOLD data that were recorded while participants read and listened to the same narratives in each modality. Levels of the language hierarchy are operationalized as timescales, where each timescale refers to a set of spectral components of a language stimulus. Voxelwise encoding models are used to determine where different timescales are represented across the cerebral cortex, for each modality separately. These models reveal that between the two modalities timescale representations are organized similarly across the cortical surface. Our results suggest that, after low-level sensory processing, language integration proceeds similarly regardless of stimulus modality.

Indexed as

LanguageReadingBrainBrain MappingCerebral CortexHumans

Identifiers

PMID38454134
PMCPMC11245628

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.