Decoding Brain Activity Associated with Literal and Metaphoric Sentence Comprehension Using Distributional Semantic Models

Recent years have seen a growing interest within the natural language processing (NLP)community in evaluating the ability of semantic models to capture human meaning representation in the brain. Existing research has mainly focused on applying semantic models to de-code brain activity patterns associated with the meaning of individual words, and, more recently, this approach has been extended to sentences and larger text fragments. Our work is the first to investigate metaphor process-ing in the brain in this context. We evaluate a range of semantic models (word embeddings, compositional, and visual models) in their ability to decode brain activity associated with reading of both literal and metaphoric sentences. Our results suggest that compositional models and word embeddings are able to capture differences in the processing of literal and metaphoric sentences, providing sup-port for the idea that the literal meaning is not fully accessible during familiar metaphor comprehension

Reconstructing Metaphorical Meaning

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Évaluation de la compétence sémantique : comment les adultes et les enfants comprennent-ils les mots «semblable» et «différent» ?

Glucksberg Sam. Évaluation de la compétence sémantique : comment les adultes et les enfants comprennent-ils les mots «semblable» et «différent» ?. In: Bulletin de psychologie, tome 29, numéro spécial, 1976. Spécial annuel 1976 : La mémoire sémantique. pp. 289-294

Similarity and attribution in concept combination: Reply to Wisniewski

Wisniewski raises several important points in his comment on our study of the (non)role of similarity in concept combination. He notes that feature diagnosticity is an important factor in property attribution. He also points out that relational interpretations of combined concepts depend on thematic role plausibility, not constituent similarity. We agree with both of these points. Wisniewski further identifies a possible item artifact that might account for our results. However, reexamination of those items fails to support this hypothesis. Wisniewski also claims that an alignment process is necessary to specify how an attributed property should be instantiated in the combined concept. We argue instead that postcomprehension elaboration processes can account for specific property instantiations. Finally, we suggest that the perceive

Relevance and Feature Accessibility in Combined Concepts

When comprehending combined concepts (e.g., 'peeled apples'), two kinds of features are potentially accessible. Phrase features are true only of the phrase (e.g., "white"), while noun features are true of both the phrase and the head noun (e.g., "round"). Phrase features are verified more quickly and more accurately than noun features. No satisfactory account of this phrase feature priority has been put forth. We propose that relevance can explain the phrase feature priority. In Experiment 1, the differential accessibility of noun and phrase features was reversed by context paragraphs that made noun features relevant. Experiment 2 more subtly replicated this effect using a single-word context. We conclude that the phrase feature priority is attributable to the discourse strategy of assigning relevance to modifiers of combined concepts

Contextual Activation of Features of Combined Concepts

We examine how context affects the accessibility of features of combined concepts. A 'contrast hypothesis' suggests that contrasting a to-be-verified feature in the context hinders its later verification. Results of Experiment 1 instead support a priming hypothesis whereby features are differentially activated by contexts. Experiment 2 demonstrates that this priming effect is positive rather than negative, even when feature verification follows a contextual combined concept that is inconsistent with the to-be-verified feature. We conclude that context can differentially activate features of combined concepts, and that it may do so by way of semantic priming