Neural representations of the concepts in simple sentences: Concept activation prediction and context effects.
Neuroimage
; 157: 511-520, 2017 08 15.
Article
en En
| MEDLINE
| ID: mdl-28629977
ABSTRACT
Although it has been possible to identify individual concepts from a concept's brain activation pattern, there have been significant obstacles to identifying a proposition from its fMRI signature. Here we demonstrate the ability to decode individual prototype sentences from readers' brain activation patterns, by using theory-driven regions of interest and semantic properties. It is possible to predict the fMRI brain activation patterns evoked by propositions and words which are entirely new to the model with reliably above-chance rank accuracy. The two core components implemented in the model that reflect the theory were the choice of intermediate semantic features and the brain regions associated with the neurosemantic dimensions. This approach also predicts the neural representation of object nouns across participants, studies, and sentence contexts. Moreover, we find that the neural representation of an agent-verb-object proto-sentence is more accurately characterized by the neural signatures of its components as they occur in a similar context than by the neural signatures of these components as they occur in isolation.
Palabras clave
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Psicolingüística
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Mapeo Encefálico
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Formación de Concepto
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Lenguaje
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Modelos Teóricos
Tipo de estudio:
Prognostic_studies
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Risk_factors_studies
Idioma:
En
Revista:
Neuroimage
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2017
Tipo del documento:
Article