Cited by 1,180Neurobiology of Language and BilingualismCategorization, perception, and languageReading and Literacy Development

Predicting Human Brain Activity Associated with the Meanings of Nouns

Open access
Mitchell, Tom M., Shinkareva, Svetlana V., Carlson, Andrew, Chang, Kai-Min, Malave, Vicente L., Mason, Robert A., Just, Marcel Adam·2008·Science

Abstract

The question of how the human brain represents conceptual knowledge has been debated in many scientific fields. Brain imaging studies have shown that different spatial patterns of neural activation are associated with thinking about different semantic categories of pictures and words (for example, tools, buildings, and animals). We present a computational model that predicts the functional magnetic resonance imaging (fMRI) neural activation associated with words for which fMRI data are not yet available. This model is trained with a combination of data from a trillion-word text corpus and observed fMRI data associated with viewing several dozen concrete nouns. Once trained, the model predicts fMRI activation for thousands of other concrete nouns in the text corpus, with highly significant accuracies over the 60 nouns for which we currently have fMRI data.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1126/science.1152876

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Current word embedding-based language encoding approaches treat each stimulus word independently and ignore context.

    “Current word embedding-based approaches treat each stimulus word independently and thus ignore the influence of context on language understanding.”

    From Incorporating Context into Language Encoding Models for fMRI (2018) · cites this paper as [15]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 28

  1. References 12 November 2007; accepted 3 April 2008 10.1126/science.ll52876 References and Notes 1. 3-V. Haxby et ai, Science 293, 2425 (2001). · DOI
  2. A. Ishai, L G. Ungedeider, A. Martin, J. L Scheuten, ]. V. Haxby, Proc Nati Acad. Sei. USA. 96, 9379 (1999).
  3. T, A. Carlson, P. Schrater, S. He, /. Cogn. Neurosa 15, 704 (2003).
  4. D. D. Cox, R. I. Savoy, Neuroimage 19, 261 (2003).
  5. S. ]. Hanson, T. Matsuka, ). V. Haxby, Neuroimage 23, 156 (2004).
  6. S. M. Polyn, V. S. Natu,}. D. Cohen, K. A. Norman, Science 310, 1963 (2005).
  7. A. ]. O'Toole, F. Jiang, H. Abdi? ]. V. Haxby, j. Cogn. Neurosa 17, 580 (2005).
  8. K. Kipper, A. Korhonen, H. Ryant? M. Palmer? Proceedings of the 5th International Conference on Language Resources and Evaluation, Genoa, Italy, 24 to 26 May 2006,
  9. G. Milter, R. Beckwith, C Fe?baum, D. Gross, K. j. Miller, ?nt I Lexicography 3, 235 (1990).
  10. C. Fellbaum? Ed., WordNet: An Electronic Lexical Database (Massachusetts Institute of Technology Press, Cambridge? MA, 1998).
  11. K. W. Church, P. Hanks, Comput Linguist 16, 22 (1990).
  12. T. K. Landauer, S. T. Dumais, PsychoL Rev. 104, 211 (1997).
  13. D. Lin, 5. Zhao? I. Oin, M. Zhou, Proceedings of the 18th International Joint Conference on Artificial intelligence, Acapulco, Mexico, August 2003 (Morgan Kaufmann, San Francisco, 2003), pp. 1492-1493.
  14. R, Snow, D. jurafsky, A. Ng? Proceedings of the 44th Annual Meeting of the Association for Computational Linguistics, Sydney, Australia, 17 to 21 July 2006.
  15. S. ]. Crutch? E. K. Warrington, Brain 126, 1821 (2003).
  16. D. Samson? A. Pillon, Brain Lang, 91, 252 (2004).
  17. A. Martin, L L Chao, Curr. Opin. Neurobioi. 11,194 (2001).
  18. R. F. Goldberg, C. A. Perfetti, W. Schneider? J. Neurosci. 26, 4917 (2006).
  19. B. Z. Mahon, A. Caramazza, in The Encyclopedia of Language and Linguistics, K. Brown? Ed. (Elsevier Science, Amsterdam? ed. 2, 2005).
  20. K. J. Friston er al, Hum. Brain Mapp. 2, 189 (1995).
  21. N. Tzourio-Mazoyer et ai, Neuroimage 15, 273 (2002).
  22. A. Martin, L G. Ungerteider, ]. V. Haxby, in The New Cognitive Neurosciences, M. 5. Gazzainga, Ed, (Massachusetts Institute of Technology Press, Cambridge, MA, ed. 2, 2000), pp. 1023-1036.
  23. K. A. Peiphrey, ]. P. Morris, C. R. Michelich, T. Allison, G. McCarthy, Cereb. Cortex 15, 1866 (2005).
  24. L M. Vaina, ]. Solomon, S. Chowdhury, P. Sinha, J. Belliveau, Proc Nati Acad Sei USA. 98, 11656 (2001).
  25. K. Sakai er ai, Magn. Reson. Med. 33, 736 (1995).
  26. D. R. Hardoon, j. Mourao-Miranda, M. Brammer? J. Shawe-Taylor, Neuroimage 37, 1250 (2007).
  27. J. D. Haynes, G. Rees, Nat Rev. Neurosa, 7, 523 (2006).
  28. K. A. Norman, S. M. Polyn, G. ). Detre, ]. V. Haxby, Trends Cogn. Sei 10, 424 (2006).

Cited by

Sorted by citations

Authors
Mitchell, T. M., Shinkareva, S. V., Carlson, A., Chang, K.-M., Malave, V. L., Mason, R. A., & Just, M. A.
Affiliations
University of South Carolina (US)
Corresponding author
Mitchell, Tom M.
Venue
Science
Published
2008-05-30
Volume
320
Issue
5880
Pages
1191-1195
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2168217710
Cited by
1,180
References
2
Citations by year
2026: 36 · 2025: 51 · 2024: 42 · 2023: 46 · 2022: 62 · 2021: 73 · 2020: 87 · 2019: 91 · 2018: 74 · 2017: 70 · 2016: 71 · 2015: 72 · 2014: 74 · 2013: 65 · 2012: 72
FWCI
33.52
Type
journal article
Language
en
Open access
Licence
other-oa
Locations
  • Science (publishedVersion)
  • PubMed (publishedVersion)
  • MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
  • KiltHub Repository (submittedVersion)
  • Figshare (submittedVersion, cc-by)
  • KiltHub Repository
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Categorization, perception, and language
  • Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
Keywords
semantic representation, concrete nouns, word meaning, functional MRI, computational model, text corpora, semantic categories, conceptual knowledge
MeSH terms
Adolescent, Adult, Brain, Brain Mapping, Female, Humans, Language, Magnetic Resonance Imaging, Male, Models, Neurological, Semantics, Speech Perception, Models, Statistical, Computational Biology

About these checks

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.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review