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The meaning emerging from combining words can be detected in space but not time

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.

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Fig. 1: fMRI and MEG reveal different aspects of meaning composition.

References

  1. 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.

    Article  Google Scholar 

  2. 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.

  3. 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.

    Article  Google Scholar 

  4. 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.

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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).

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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

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