We used computational models built using neural networks to predict what brain areas process the new meaning that emerges when words are combined. The brain activity evoked by this composed meaning was detected only with some brain recording modalities, a finding that might have consequences for brain–computer interfaces.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 /Â 30Â days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$99.00 per year
only $8.25 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
References
Pylkkänen, L. Neural basis of basic composition: what we have learned from the red–boat studies and their extensions. Philos. Trans. Roy. Soc. B 375, 20190299 (2020). A review article that presents the current progress in understanding meaning composition in the brain.
Peters, M. E. et al. Deep contextualized word representations. In Proc. NAACL-HLT 2227–2237 (Association for Computational Linguistics, 2018). This paper presents ELMo, a neural network language model that outperformed the then state-of-the-art model at many language tasks.
Wehbe, L. et al. Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses. PLoS ONE 9, e112575 (2014). This paper describes the naturalistic reading experiment from which we obtained our fMRI data.
Wehbe, L., Vaswani, A., Knight, K. & Mitchell, T. Aligning context-based statistical models of language with brain activity during reading. In Proc. 2014 Conf. on Empirical Methods in Natural Language Processing (EMNLP) 233–243 (Association for Computational Linguistics, 2014). This paper describes the naturalistic reading experiment from which we obtained our MEG data.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This is a summary of: Toneva, M. et al. Combining computational controls with natural text reveals aspects of meaning composition. Nat. Comput. Sci. https://doi.org/10.1038/s43588-022-00354-6 (2022).
Rights and permissions
About this article
Cite this article
The meaning emerging from combining words can be detected in space but not time. Nat Comput Sci 2, 783–784 (2022). https://doi.org/10.1038/s43588-022-00361-7
Published:
Issue Date:
DOI: https://doi.org/10.1038/s43588-022-00361-7