Data-driven modeling of the neural dynamics underlying language processing
[S.l. : s.n.]
Number of pages
Utrecht University, 14 april 2020
Promotores : Ramsey, N.F., Gerven, M.A.J. van Co-promotor : Freudenburg, Z.V.
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SW OZ DCC AI
SubjectCognitive artificial intelligence
In this thesis, we use data-driven techniques in an attempt to explain the neural data during speech and language perception in unconstrained naturalistic setup. We aim to use a combination of data exploration approaches and data-driven feature extraction models to provide a more bottom-up way of studying the neural responses. We hope that these data-driven strategies can confirm some of the previous theory-based neurolinguistic findings but at the same time offer new insight regarding how the human brain processes speech related information.
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