Papers by Luana Bulat
Decoding Brain Activity Associated with Literal and Metaphoric Sentence Comprehension Using Distributional Semantic Models (2020.tacl-1)
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| Challenge: | Existing research has focused on applying semantic models to decode brain activity associated with the meaning of individual words. |
| Approach: | They evaluate a range of semantic models to capture metaphor processing in the brain . they found that compositional models and word embeddings capture differences in the processing of literal and metaphoric sentences . |
| Outcome: | The proposed models capture differences in the processing of literal and metaphoric sentences, providing support for the idea that the literal meaning is not fully accessible during familiar metaphor comprehension. |
Modeling Affirmative and Negated Action Processing in the Brain with Lexical and Compositional Semantic Models (P19-1)
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| Challenge: | Existing studies have shown that distributional semantic models can be used to decode fMRI patterns associated with specific aspects of semantic composition, such as the negation function. |
| Approach: | They apply lexical and compositional semantic models to decode fMRI patterns associated with negated and affirmative sentences containing hand-action verbs. |
| Outcome: | The proposed models show reduced decoding of sentences where the verb is in the negated context, as compared to the affirmative one, within brain regions implicated in action-semantic processing. |