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When given unrestricted time to process an image, people are faster and more accurate at making categorical decisions about a depicted object (e.g., Labrador) if it is close in sensorimotor and linguistic distributional experience to its target category concept (e.g., dog). In this preregistered study, we examined whether sensorimotor and linguistic distributional information affect object categorisation differently as a function of time available for perceptual processing. Using an ultrarapid categorisation paradigm with backwards masking, we systematically varied onset timing (SOA) of a post-stimulus mask (17-133ms) following a briefly displayed (17ms) object. Preliminary results suggest that linguistic distributional distance between concept and category (e.g., Labrador → dog), but not sensorimotor distance, affects categorisation accuracy and RT even in rapid categorisation, and that these effects do not vary systematically by SOA. These findings support the role of a linguistic shortcut (i.e., using linguistic distributional instead of sensorimotor information) in rapid object categorisation.

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 semanticmemory. However, these explanations are not fully compatible with most recent views on the structure of the concep-tual system, which emphasise the role of sensorimotor (i.e., perception-action experience of the world) and linguisticinformation (i.e., statistical distribution of words in language) in conceptual processing. In a pre-registered wordpicturecategorisation study, we hypothesised that our novel measures of sensorimotor and linguistic distance would contribute tocategorical decision making, and would outperform traditional taxonomic levels (i.e., subordinate, basic, superordinate)in predicting the basic-level advantage. Results showed that, overall, our measures predicted the basic-level advantage atleast as well as taxonomic level. Sensorimotor information best explained processing speed, whereas taxonomic level bestexplained participants choices.

High immersion in virtual reality is often hypothesized toimprove learning and memory. This immersion benefit isfrequently attributed to presence, the user’s feeling of beingpresent inside the computer-generated environment.Obtaining learning gains due to high immersion may howeverbe difficult, as is evidenced by the null results of multiplestudies in this area. In the current study we investigated therole of presence in low- and high-immersion virtual realitysettings. No differences in performance in object location andspatial memory were found between low- and high-immersiveconditions. Yet, when considering self-report measures ofpresence, performance improvements in the high immersivecondition did become apparent. The finding of the importanceto consider the role of presence in virtual reality highlights thecomplexity of immersion effects in simulated environments