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Composition is the core driver of the language-selective network

View ORCID ProfileFrancis Mollica, Evgeniia Diachek, Zachary Mineroff, Hope Kean, Matthew Siegelman, Steven T. Piantadosi, Richard Futrell, Peng Qian, Evelina Fedorenko
doi: https://doi.org/10.1101/436204
Francis Mollica
1School of Psychological Sciences, University of Melbourne
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  • For correspondence: mollicaf@gmail.com
Evgeniia Diachek
3Psychology Department, Vanderbilt University
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Zachary Mineroff
5The METALS Program, Carnegie Mellon University
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Hope Kean
7Brain & Cognitive Sciences Department, MIT
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Matthew Siegelman
2Psychology Department, Columbia University
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Steven T. Piantadosi
4Psychology Department, UC Berkeley
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Richard Futrell
6Linguistics Department, UC Irvine
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Peng Qian
7Brain & Cognitive Sciences Department, MIT
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Evelina Fedorenko
7Brain & Cognitive Sciences Department, MIT
8McGovern Institute for Brain Research, MIT
9Psychiatry Department, Massachusetts General Hospital
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Abstract

The fronto-temporal language network responds robustly and selectively to sentences. But the features of linguistic input that drive this response and the computations these language areas support remain debated. Two key features of sentences are typically confounded in natural linguistic input: words in sentences a) are semantically and syntactically combinable into phrase- and clause-level meanings, and b) occur in an order licensed by the language’s grammar. Inspired by recent psycholinguistic work establishing that language processing is robust to word order violations, we hypothesized that the core linguistic computation is composition, and, thus, can take place even when the word order violates the grammatical constraints of the language. This hypothesis predicts that a linguistic string should elicit a sentence-level response in the language network as long as the words in that string can enter into dependency relationships as in typical sentences. We tested this prediction across two fMRI experiments (total N=47) by introducing a varying number of local word swaps into naturalistic sentences, leading to progressively less syntactically well-formed strings. Critically, local dependency relationships were preserved because combinable words remained close to each other. As predicted, word order degradation did not decrease the magnitude of the BOLD response in the language network, except when combinable words were so far apart that composition among nearby words was highly unlikely. This finding demonstrates that composition is robust to word order violations, and that the language regions respond as strongly as they do to naturalistic linguistic input as long as composition can take place.

Footnotes

  • Contact: Frank Mollica mollicaf{at}gmail.com or Ev Fedorenko evelina9{at}mit.edu

  • https://osf.io/y28fz/

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 4.0 International license.
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Posted December 20, 2019.
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Composition is the core driver of the language-selective network
Francis Mollica, Evgeniia Diachek, Zachary Mineroff, Hope Kean, Matthew Siegelman, Steven T. Piantadosi, Richard Futrell, Peng Qian, Evelina Fedorenko
bioRxiv 436204; doi: https://doi.org/10.1101/436204
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Composition is the core driver of the language-selective network
Francis Mollica, Evgeniia Diachek, Zachary Mineroff, Hope Kean, Matthew Siegelman, Steven T. Piantadosi, Richard Futrell, Peng Qian, Evelina Fedorenko
bioRxiv 436204; doi: https://doi.org/10.1101/436204

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