Paper: Quantitative modeling of the neural representation of adjective-noun phrases to account for fMRI activation

ACL ID P09-1072
Title Quantitative modeling of the neural representation of adjective-noun phrases to account for fMRI activation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

Recent advances in functional Magnetic Resonance Imaging (fMRI) offer a significant new approach to studying semantic represen- tations in humans by making it possible to di- rectly observe brain activity while people comprehend words and sentences. In this study, we investigate how humans compre- hend adjective-noun phrases (e.g. strong dog) while their neural activity is recorded. Classi- fication analysis shows that the distributed pattern of neural activity contains sufficient signal to decode differences among phrases. Furthermore, vector-based semantic models can explain a significant portion of system- atic variance in the observed neural activity. Multiplicative composition models of the two-word phrase outperform additive models, consistent with the assumption that ...