The perceptual-cognitive ability to track multiple moving objects and its contribution to team sports performance has traditionally been studied in the laboratory under non-sports specific conditions. It is thus questionable whether the measured visual tracking performance and the underlying gaze activity reflected the actual ability of team sports players to track teammates and opponents on a real field. Using a Virtual Reality-based visual tracking task, the ability of participants to track multiple moving virtual players as they would do on a (...) soccer field was observed to pursue two objectives. See the influence of different scenario types on the visual tracking performance of soccer compared to non-soccer players. Observe the influence of spatial features of the simulated situations on gaze activity between soccer players and non-soccer players. The linear mixed model regression revealed a significant main effect of the group but no interaction effect between group and the type of trajectories, suggesting that the visual tracking ability of soccer players did not benefit from their specific knowledge when they faced scenarios with real game trajectories. Virtual players’ spatial dispersion and crowding affected the participants’ gaze activity and their visual tracking performance. Furthermore, the gaze activity of soccer players differed in some aspects from the gaze activity of non-soccer players. Assumptions are formulated as to the implication of these results in the difference in visual tracking performance between soccer players and non-soccer players. Overall, using soccer-specific trajectories might not be enough to replicate the representativeness of the field conditions in the study of visual tracking performance. Multitasking constraints should be considered along with motor-cognitive dual-tasks in future research to develop the representativeness of visual exploration conditions. (shrink)

Among all their sensations, agents need to distinguish between those caused by themselves and those caused by external causes. The ability to infer agency is particularly challenging under conditions of uncertainty. Within the predictive processing framework, this should happen through active control of prediction error that closes the action-perception loop. Here we use a novel, temporally-sensitive, behavioural proxy for prediction error to show that it is minimised most quickly when volatility is high and when participants report agency, regardless of the (...) accuracy of the judgement. We demonstrate broad effects of uncertainty on accuracy of agency judgements, movement, policy selection, and hypothesis switching. Measuring autism traits, we find differences in policy selection, sensitivity to uncertainty and hypothesis switching despite no difference in overall accuracy. (shrink)

The binding problem is fundamental to visual perception. It is the problem of associating an object's visual properties with itself and not with some other object. The problem is made particular difficult because different properties of an object, such as its color, shape, size, and motion, are often processed independently, sometimes in different cortical areas. The results of these separate analyses have to be combined before the object can be seen as a single coherent entity as opposed to a collection (...) of unconnected features. Visual bindings are typically initiated and updated in a serial fashion, one object at a time. Here, we show that one type of binding, location-identity bindings, can be updated in parallel. We do this by using two complementary techniques, the simultaneous-sequential paradigm and systems factorial technology. These techniques make different assumptions and rely on different behavioral measures, yet both came to the same conclusion. (shrink)

Semantic studies on diagrammatic notations (Barwise & Etchemendy, ; Shimojima, ; Stenning & Lemon, ) have revealed that the “non-deductive,” “emergent,” or “perceptual” effects of diagrams (Chandrasekaran, Kurup, Banerjee, Josephson, & Winkler, ; Kulpa, ; Larkin & Simon, ; Lindsay, ) are all rooted in the exploitation of spatial constraints on graphical structures. Thus, theoretically, this process is a key factor in inference with diagrams, explaining the frequently observed reduction of inferential load. The purpose of this study was to examine (...) the empirical basis for this theoretical suggestion, focusing on the reality of the constraint-exploitation strategy in actual practices of diagrammatic reasoning. Eye movements were recorded while participants used simple position diagrams to solve three- or four-term transitive inference problems. Our experiments revealed that the participants could exploit spatial constraints on graphical structures even when (a) they were not in the position of actually manipulating diagrams, (b) the semantic rule for the provided diagrams did not match their preferences, and (c) the constraint-exploitation strategy invited a partly adverse effect. These findings indicate that the hypothesized process is in fact robust, with the potential to broadly account for the inferential advantage of diagrams. (shrink)

Categorization is fundamental for spatial and motion representation in both the domain of artificial intelligence and human cognition. In this paper, we investigated whether motion categorizations designed in artificial intelligence can inform human cognition. More concretely, we investigated if such categorizations (also known as qualitative representations) can inform the psychological understanding of human perception and memory of motion scenes. To this end, we took two motion categorizations in artificial intelligence, Motion‐RCC and Motion‐OPRA1, and conducted four experiments on human perception and (...) memory. Participants viewed simple motion scenes and judged the similarity of transformed scenes with this reference scene. Those transformed scenes differed in none, one, or both Motion‐RCC and Motion‐OPRA1 categories. Importantly, we applied an equal absolute metric change to those transformed scenes, so that differences in the similarity judgments should be due only to differing categories. In Experiments 1a and 1b, where the reference stimulus and transformed stimuli were visible at the same time (perception), both Motion‐OPRA1 and Motion‐RCC influenced the similarity judgments, with a stronger influence of Motion‐OPRA1. In Experiments 2a and 2b, where participants first memorized the reference stimulus and viewed the transformed stimuli after a short blank (memory), only Motion‐OPRA1 had marked influences on the similarity judgments. Our findings demonstrate a link between human cognition and these motion categorizations developed in artificial intelligence. We argue for a continued and close multidisciplinary approach to investigating the representation of motion scenes. (shrink)