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New paper: Influence of language on perception and concept formation in a brain-constrained deep neural network model

Malte Henningsen-Schomers, Max Garagnani and Friedemann Pulvermüller have used a brain-constrained neural network model to investigate the influence of language on concept formation. The model acquired several distinct concrete and abstract concepts with or without an associated linguistic label. The resulting neural representations were evaluated on two properties: whether instances of a concept were similar to each other, and whether instances of distinctly different concepts were dissimilar.

They have found that supplying a label referring to the different concepts improved both within-concept similarity and between-concept dissimilarity. This effect was particularly striking for abstract concepts: without a label, abstract concepts scored low on both properties.

These results offer a neurobiological explanation for causal effects of language strcuture both on concept formation and perceptuo-motor processing of acquired concepts. Furthermore, they offer a novel prediction: such "Whorfian" effects of language on perception should be modulated by the concreteness and abstractness of the acquired concept, with a stronger effect on abstract concepts.

You can read the full paper published in Philosophical Transactions of the Royal Society B here, and explore the data with an interactive data visualization here.

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