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Modelling brain representations of abstract concepts.

ABSTRACT: 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.

SUBMITTER: Kaiser D

PROVIDER: S-EPMC8849470 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Modelling brain representations of abstract concepts.

Kaiser Daniel D Jacobs Arthur M AM Cichy Radoslaw M RM

PLoS computational biology 20220204 2

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 in ...[more]

PMID: 35120139

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