Toward a universal decoder of linguistic meaning from brain activation

Previous work decoding linguistic meaning from imaging data has generally been limited to a small number of semantic categories. Here, authors show that a decoder trained on neuroimaging data of single concepts sampling the semantic space can robustly decode meanings of semantically diverse new sent...

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Autores principales: Francisco Pereira, Bin Lou, Brianna Pritchett, Samuel Ritter, Samuel J. Gershman, Nancy Kanwisher, Matthew Botvinick, Evelina Fedorenko
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2018
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Acceso en línea:https://doaj.org/article/4eab538b394d41aca61a5cfdc4d5c391
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