Modelling brain representations of abstract concepts.

Autor: Daniel Kaiser, Arthur M Jacobs, Radoslaw M Cichy
Jazyk: angličtina
Rok vydání: 2022
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Zdroj: PLoS Computational Biology, Vol 18, Iss 2, p e1009837 (2022)
Druh dokumentu: article
ISSN: 1553-734X
1553-7358
DOI: 10.1371/journal.pcbi.1009837
Popis: conceptual representations are critical for human cognition. Despite their importance, key properties of these representations remain poorly understood. Here, we used computational models of distributional semantics to predict multivariate fMRI activity patterns during the activation and contextualization of abstract concepts. We devised a task in which participants had to embed abstract nouns into a story that they developed around a given background context. We found that representations in inferior parietal cortex were predicted by concept similarities emerging in models of distributional semantics. By constructing different model families, we reveal the models' learning trajectories and delineate how abstract and concrete training materials contribute to the formation of brain-like representations. These results inform theories about the format and emergence of abstract conceptual representations in the human brain.
Databáze: Directory of Open Access Journals
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