Abstract
Recent work shows that distributional semantic models can be used to decode patterns of brain activity associated with individual words and sentence meanings. However, it is yet unclear to what extent such models can be used to study and decode fMRI patterns associated with specific aspects of semantic composition such as the negation function. In this paper, we apply lexical and compositional semantic models to decode fMRI patterns associated with negated and affirmative sentences containing hand-action verbs. Our results show reduced decoding (correlation) of sentences where the verb is in the negated context, as compared to the affirmative one, within brain regions implicated in action-semantic processing. This supports behavioral and brain imaging studies, suggesting that negation involves reduced access to aspects of the affirmative mental representation. The results pave the way for testing alternate semantic models of negation against human semantic processing in the brain.- Anthology ID:
- P19-1508
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Anna Korhonen, David Traum, Lluís Màrquez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 5155–5165
- Language:
- URL:
- https://aclanthology.org/P19-1508
- DOI:
- 10.18653/v1/P19-1508
- Cite (ACL):
- Vesna Djokic, Jean Maillard, Luana Bulat, and Ekaterina Shutova. 2019. Modeling Affirmative and Negated Action Processing in the Brain with Lexical and Compositional Semantic Models. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 5155–5165, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Modeling Affirmative and Negated Action Processing in the Brain with Lexical and Compositional Semantic Models (Djokic et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/P19-1508.pdf