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Combining computational controls with natural text reveals new aspects of meaning composition

View ORCID ProfileMariya Toneva, Tom M. Mitchell, View ORCID ProfileLeila Wehbe
doi: https://doi.org/10.1101/2020.09.28.316935
Mariya Toneva
1Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA
2Neuroscience Institute, Carnegie Mellon University, Pittsburgh, USA
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  • ORCID record for Mariya Toneva
Tom M. Mitchell
1Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA
2Neuroscience Institute, Carnegie Mellon University, Pittsburgh, USA
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Leila Wehbe
1Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA
2Neuroscience Institute, Carnegie Mellon University, Pittsburgh, USA
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  • ORCID record for Leila Wehbe
  • For correspondence: lwehbe@cmu.edu
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Abstract

To study a core component of human intelligence—our ability to combine the meaning of words—neuroscientists look for neural correlates of meaning composition, such as brain activity proportional to the difficulty of understanding a sentence. However, little is known about the product of meaning composition—the combined meaning of words beyond their individual meaning. We term this product “supra-word meaning” and devise a computational representation for it by using recent neural network algorithms and a new technique to disentangle composed-from individual-word meaning. Using functional magnetic resonance imaging, we reveal that hubs that are thought to process lexical-level meaning also maintain supra-word meaning, suggesting a common substrate for lexical and combinatorial semantics. Surprisingly, we cannot detect supra-word meaning in magnetoencephalography, which suggests that composed meaning is maintained through a different neural mechanism than synchronized firing. This sensitivity difference has implications for past neuroimaging results and future wearable neurotechnology.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Title and Abstract revised; Figure 3 revised; Figure S4 added to Supplementary;

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted November 17, 2020.
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Combining computational controls with natural text reveals new aspects of meaning composition
Mariya Toneva, Tom M. Mitchell, Leila Wehbe
bioRxiv 2020.09.28.316935; doi: https://doi.org/10.1101/2020.09.28.316935
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Combining computational controls with natural text reveals new aspects of meaning composition
Mariya Toneva, Tom M. Mitchell, Leila Wehbe
bioRxiv 2020.09.28.316935; doi: https://doi.org/10.1101/2020.09.28.316935

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