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Neurocomputational modelling of bilingual sentence comprehension and production


Time frame

January 2020 – December 2022

Project description

When bilinguals comprehend or produce sentences, they often display language transfer (influence from the properties of one language on the other language), code switching (the spontaneous use of both languages in one utterance) and cross-linguistic syntactic priming (re-use of syntactic structures from one language in the other). Although these phenomena form a fascinating window into the multilingual mind, very little is currently understood about the neural and cognitive mechanisms that underlie them. The project will tackle this issue by answering the following scientific questions:

  • Could typical bilingual behaviours be explained by general brain mechanisms (e.g. inhibitory control) or do they depend on specifically linguistic aspects?
  • What are the features, behaviours and limits of current computational models that simulate sentence processing and/or production in at least in two languages, specifically in comparison to data from psycholinguistic experiments (e.g., eye-tracking and neuroimaging)?

In particular, the project will begin by using neural network models of bilingual sentence processing, which have already been developed in the two collaborating laboratories, to explore how transfer, structural priming, and code switching could be explained by the interaction of general neural/cognitive mechanisms with the properties of the languages involved. This will lead to a novel model that integrates the insights from the two teams’ current models and that will greatly increase our understanding of multilingual sentence processing.


Bilingualism, neural networks, computational models, sentence processing


Nuffic Van Gogh programme


National French Institute for Mathematics and Computer Science, Bordeaux


Stefan Frank, stefan.frank@ru.nl