Research & publications
Metaphor comprehension & production
In a series of studies, we demonstrated that the literal meaning of conventional metaphors such as early bird was available during metaphor comprehension. In a maze task, participants read two-word metaphors embedded in carrier sentences (e.g., John is an early bird so he can…). At the maze juncture, participants were slower and less accurate when the target word to continue the sentence (attend) was paired with a distractor related to the literal meaning of the metaphor (fly) compared to an unrelated one (cry). This effect, termed the metaphor awakening effect (MAE), shows the relationship between associated literal concepts accessed during the initial stages of metaphor comprehension and a subsequent literal cue. These findings support the minimalist model of metaphor processing, which posits that the literal meaning is available during metaphor comprehension.
Pissani, L., Meiser, M., & Demberg, V. (2025). Music-induced Positive Mood Stimulates Metaphor Production. Proceedings of the Annual Meeting of the Cognitive Science Society, 47. Retrieved from https://escholarship.org/uc/item/3d56910q
Pissani, L. & de Almeida, R. G. (under review). Familiarity, aptness, concreteness, metaphoricity, and structure norms for 300 two-word metaphors in context and in isolation. https://doi.org/10.17605/OSF.IO/XK3J9
Pissani, L., & de Almeida, R. G. (2023). Early birds can fly: Awakening the literal meaning of conventional metaphors further downstream. Metaphor and Symbol, 38(4), 346-362. https://doi.org/10.1080/10926488.2023.2225561
Pissani, L., & de Almeida, R. G. (2022). Can you mend a broken heart? Awakening conventional metaphors in the maze. Psychonomic Bulletin & Review, 29(1), 253-261.
https://doi.org/10.3758/s13423-021-01985-y
Pissani, L., & de Almeida, R. G. (2022). What happens to the literal meanings of metaphors? A review and a “minimalist” proposal. In M. Liu & S. Rotter (Eds.), Proceedings of the Fourth Workshop “Concepts in Action: Representation, Learning, and Application” (CARLA 2022). Retrieved from https://conceptresearch.github.io/CARLA/carla_workshop/abstracts_2022/Pissani_de-Almeida.pdf
Roncero, C., de Almeida, R. G., Pissani, L., & Patalas, I. (2021). A metaphor is not like a simile: Reading-time evidence for distinct interpretations for negated tropes. Metaphor and Symbol, 36(2), 85–98. https://doi.org/10.1080/10926488.2021.1882258
I investigate how individual factors such as linguistic experience (e.g., vocabulary size and print exposure), executive functioning (e.g.,working memory span and inhibitory control), general reasoning (e.g., abstract reasoning and cognitive reflection), and creativity (divergent and convergent) influence the comprehension and production of figurative language. I assess how these individual differences modulate the use of contextual information during slow- and fast-paced tasks. This research not only informs the mechanisms underlying pragmatic processing but also informs our understanding of how individual variability impacts language use across diverse populations.
Pissani, L., Scholman, M., & Demberg, V. (in preparation) Working memory and vocabulary knowledge increase activation of the literal meaning of metaphors during sentence comprehension
I am interested in the differences and similarities in how humans and large language models (LLMs) process pragmatic information. Pragmatic processing involves interpreting language beyond its literal meaning, incorporating context, background knowledge, and social cues. While LLMs have demonstrated exceptional abilities in various language tasks, it remains uncertain whether their capabilities compare to human performance when it comes to more creative tasks, such as the interpretation and generation of novel metaphors, humour comprehension, or other complex aspects of language that may require additional cognitive abilities.In a series of projects, my colleagues and I compare the performance of LLMs (e.g., LLaMA, OLMo, DeepSeek) on various language tasks with human data to inform both human cognition and LLMs skills and limitations.
Dzhubaeva, N., Trinley, K., & Pissani, L. (2025). Unstructured Minds, Predictable Machines: A Comparative Study of Narrative Cohesion in Human and LLM Stream-of-Consciousness Writing. In Proceedings of the ACL 2025 Student Research Workshop. https://openreview.net/forum?id=r2IxjKrGmD