Neuro-computational models of language processing
John Hale, Luca Campanelli, Jixing Li, Shohini Bhattasali, Christophe Pallier, Jonathan Brennan
August 2021
 

Efforts to understand the brain bases of language face the mapping problem: at what level do linguistic computations and representations connect to human neurobiology? We review one approach to this problem that relies on rigorously defined computational models to specify the links between linguistic features and neural signals. Such tools can be used to estimate linguistic predictions, model linguistic features, or specify a sequence of processing steps that may be quantitatively fit to neural signals collected while participants use language. Progress has been helped by advances in machine learning, attention to linguistically interpretable models, and openly shared datasets that allow researchers to compare and contrast a variety of models. We describe one such dataset in detail in the supplementary materials.
Format: [ pdf ]
Reference: lingbuzz/006147
(please use that when you cite this article)
Published in: Annual Review of Linguistics
keywords: brain, neurolinguistics, cognitive model, syntax
previous versions: v1 [August 2021]
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