Cited by 214Neurobiology of Language and BilingualismReading and Literacy DevelopmentTactile and Sensory Interactions

The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index; none of the 42 sources its claims cite is checked for support yet.

The Representation of Semantic Information Across Human Cerebral Cortex During Listening Versus Reading Is Invariant to Stimulus Modality

Open access
Deniz, Fatma, Nunez-Elizalde, Anwar O., Huth, Alexander G., Gallant, Jack L.·2019·The Journal of Neuroscience

Abstract

An integral part of human language is the capacity to extract meaning from spoken and written words, but the precise relationship between brain representations of information perceived by listening versus reading is unclear. Prior neuroimaging studies have shown that semantic information in spoken language is represented in multiple regions in the human cerebral cortex, while amodal semantic information appears to be represented in a few broad brain regions. However, previous studies were too insensitive to determine whether semantic representations were shared at a fine level of detail rather than merely at a coarse scale. We used fMRI to record brain activity in two separate experiments while participants listened to or read several hours of the same narrative stories, and then created voxelwise encoding models to characterize semantic selectivity in each voxel and in each individual participant. We find that semantic tuning during listening and reading are highly correlated in most semantically selective regions of cortex, and models estimated using one modality accurately predict voxel responses in the other modality. These results suggest that the representation of language semantics is independent of the sensory modality through which the semantic information is received. SIGNIFICANCE STATEMENT Humans can comprehend the meaning of words from both spoken and written language. It is therefore important to understand the relationship between the brain representations of spoken or written text. Here, we show that although the representation of semantic information in the human brain is quite complex, the semantic representations evoked by listening versus reading are almost identical. These results suggest that the representation of language semantics is independent of the sensory modality through which the semantic information is received.

Overview

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TL;DR

Using fMRI and voxelwise encoding models, the authors compared semantic selectivity while the same participants listened to or read the same narrative stories. They found that semantic tuning is highly correlated across modalities in most semantically selective cortex, and models fit in one modality accurately predict responses in the other.

Key findings

  • Semantic model prediction was broadly distributed across lateral temporal, ventral temporal, lateral parietal, medial parietal, and prefrontal cortices in both listening and reading, with maximum MNI-space prediction accuracy of 0.27 ± 0.03 for listening and 0.28 ± 0.03 for reading.
  • Listening and reading semantic principal component projections were significantly correlated for at least the first five semantic PCs; correlations weakened after the sixth PC but remained above chance until the seventh.
  • Voxelwise semantic model weights estimated during listening and reading were strongly correlated in many bilateral temporal, parietal, and prefrontal regions, especially for voxels semantically selective in both modalities.
  • Cross-modal prediction was accurate throughout most of the semantic system: models fit to listening predicted reading responses, and models fit to reading predicted listening responses, while sensory-cortex voxels were not well predicted cross-modally.

Methods

  • Nine participants (six male, three female) listened to and read more than two hours of narrative stories from The Moth Radio Hour; reading used rapid serial visual presentation with each word timed to match its spoken duration.
  • fMRI BOLD responses were modeled voxelwise with banded ridge regression using a 985-dimensional word co-occurrence semantic feature space plus nuisance regressors (motion-energy, spectral, phoneme, letter, word rate, syntax, etc.), with FIR hemodynamic modeling and cross-validated regularization.
  • Model performance was assessed on a held-out story using Pearson correlation, permutation tests with 10,000 iterations, and FDR correction; cross-modality prediction used weights from one modality to predict responses in the other.

Limitations

  • The paper states that its semantic feature space is only one possible representation of semantics and may miss long-timescale conceptual knowledge, metaphors, humor, sarcasm, and narrative information, which could have modality-specific representations.
  • The paper notes that RSVP reading differs from natural reading because readers cannot control which word to read at each point in time, though timing was matched to listening.
  • The paper also notes that within-modality data were collected largely within sessions while between-modality data were collected across sessions, so within-modality prediction accuracy is likely somewhat higher for that reason alone; an evident additional limitation is the small sample of nine participants, two of whom were authors.

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Integrity signals

Registry

Crossref · 10.1523/jneurosci.0675-19.2019

Cites

85 of 85 references verified0 citation errors · 0 not checkable

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  • It may state two separate claims as one. 13
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40 of 40
  • The paper relies on this without support.

    RSVP reading differs from natural reading in that the reader has no control over which word to read at each point in time.

    “RSVP reading is different than natural reading because during RSVP the reader has no control over which word to read at each point in time.”
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Citations

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Research works printed but not linked: 5

  1. 10.2307/2346101 · DOI
  2. Bergstra, 2011, Algorithms for hyper-parameter optimization, 24, 2546
  3. 10.1002/(SICI)1097-0193(1999)7:1<29::AID-HBM3>3.0.CO;2-R · DOI
  4. 10.1016/S1053-8119(02)91132-8 · DOI · Paper page
  5. Oliphant TE (2006) A guide to NumPy, Vol 1, p 85. USA: Trelgol Publishing.

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Metadata

Authors
Deniz, F., Nunez-Elizalde, A. O., Huth, A. G., & Gallant, J. L.
Affiliations
  • International Computer Science Institute (US)
  • University of California, Berkeley (US)
Venue
The Journal of Neuroscience
Published
2019-08-19
Volume
39
Issue
39
Pages
7722-7736
ISSN
  • 0270-6474 (ISSN-L)
  • 1529-2401
OpenAlex
W2968395892
Cited by
214
References
78
Citations by year
2026: 19 · 2025: 44 · 2024: 24 · 2023: 37 · 2022: 28 · 2021: 36 · 2020: 25 · 2019: 1
FWCI
12.99
Type
journal article
Language
en
Open access
Locations
  • Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by-nc-sa)
Funders
  • National Science Foundation (CCF0-939370, 0939370, 1208203)
  • Deutscher Akademischer Austauschdienst
  • National Institutes of Health (5r01ey019684-08)
  • Advanced Research Projects Agency
  • National Eye Institute (R01-EY019684, R01EY022454, EY022454, EY019684)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
  • Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Tactile and Sensory Interactions
Keywords
semantic representation, spoken language, written language, narrative stories, language comprehension, cerebral cortex
MeSH terms
Acoustic Stimulation, Adult, Auditory Perception, Cerebral Cortex, Female, Humans, Magnetic Resonance Imaging, Male, Models, Neurological, Photic Stimulation, Reading, Semantics, Visual Perception, Comprehension

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