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People are generally more accurate at categorizing objects at the basic level (e.g., dog) than at more general, superordinate categories (e.g., animal). Recent research has suggested that this basic‐level advantage emerges from the linguistic‐distributional and sensorimotor relationship between a category concept and object concept, but the proposed mechanisms have not been subject to a formal computational test. In this paper, we present a computational model of category verification that allows linguistic distributional information and sensorimotor experience to interact in a grounded implementation of a full‐size adult conceptual system. In simulations across multiple datasets, we demonstrate that the model performs the task of category verification at a level comparable to human participants, and—critically—that its operation naturally gives rise to the basic‐level‐advantage phenomenon. That is, concepts are easier to categorize when there is a high degree of overlap in sensorimotor experience and/or linguistic distributional knowledge between category and member concepts, and the basic‐level advantage emerges as an overall behavioral artifact of this linguistic and sensorimotor overlap. Findings support the linguistic–sensorimotor preparation account of the basic‐level advantage and, more broadly, linguistic–sensorimotor theories of the conceptual system. [ABSTRACT FROM AUTHOR]

The basic-level advantage is one of the best-known effects in human categorisation. Traditional accounts argue that basic-level categories present a maximally informative or entry level into a taxonomic organisation of concepts in semantic memory. However, these explanations are not fully compatible with most recent views on the structure of the conceptual system such as linguistic-simulation accounts, which emphasise the dual role of sensorimotor (i.e., perception-action experience of the world) and linguistic distributional information (i.e., statistical distribution of words in language) in conceptual processing. In four preregistered word→picture categorisation studies, we examined whether novel measures of sensorimotor and linguistic distance contribute to the basic level-advantage in categorical decision-making. Results showed that overlap in sensorimotor experience between category concept and member concept (e.g., animal→dog) predicted RT and accuracy at least as well as a traditional division into discrete subordinate, basic, and superordinate taxonomic levels. Furthermore, linguistic distributional information contributed to capturing effects of graded category structure where typicality ratings did not. Finally, when image label production frequency was taken into account (i.e., how often people actually produced specific labels for images), linguistic distributional information predicted RT and accuracy above and beyond sensorimotor information. These findings add to our understanding of how sensorimotor-linguistic theories of the conceptual system can explain categorisation behaviour. [ABSTRACT FROM AUTHOR]