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• W2738853669 abstract "On the limits of dynamic imagination: A mental extrapolation task Florent Levillain (levillain@lutin-userlab.fr) Laboratoire “Cognitions Humaine et Artificielle” Universite Paris 8 – 2 rue de la Liberte 93526 Saint-Denis France Luca L. Bonatti (lucabonatti@mac.com) ICREA and Universitat Pompeu Fabra Carrier Roc Boronat, 138, 08018 Barcelona, Spain Abstract To mentally extrapolate the trajectory of a moving object which disappears from sight, it is possible to exploit two different sources of information. One source is the memory of the last visible movement of the object, and the other is its inferred movement through time. It is often assumed that these cues are integrated into dynamical analog mental representations. To investigate the nature of the mental representation of imagined movements, we used a new experimental paradigm for which a causality attribution task was combined with motion prediction task. Participants were instructed to imagine the trajectory of a moving object disappearing behind a screen while estimating the degree to which the movement was caused by another moving object. We show that the predicted movement departs from a correct extrapolation based on accurate memory for velocity. Furthermore the mental representation of the physical and causal structure of the dynamical events did not appear to be as detailed as a theory of mental simulation would predict. Keywords: mental imagery, prediction of motion, perception of causality. Introduction Correctly performing actions on moving objects typically requires a high level of accuracy. Tasks, such as hitting or catching a ball show that humans can accurately and consistently represent the timing of a visible moving object and anticipate its future positions (Regan, 1982). However, when the stimulus is not visible, such as when it is temporarily occluded, it is not clear how precisely we can time a non visible movement and whether we possess an extrapolation mechanism that can time non visible displacements. Interception tasks are mostly driven by kinematic properties, whereas mental extrapolation may be more influenced by cognitive factors, particularly by how we represent the causal interactions of the objects within a scene. In studies of mental imagery, it is putatively assumed that the mind builds analog representations that can be used ti estimate possible outcomes of dynamical events (Johnson- Laird, 1983) or to reveal spatial properties of objects ( K o s s l y n , 1 9 9 4 ) . S i m i l a r l y, d y n a m i c a l a n a l o g representations may subserve the ability to represent the timing structure of an invisible dynamical event (Shepard & Cooper, 1982; Schwartz, 1999). Additionally, dynamical analog representations could integrate variables related to the physical structure of the environment. Results suggesting that humans are capable of recognizing physically correct object movements (Kaiser et al., 1992), along with findings showing that we can perceive high-level properties of these stimuli, such as their causal relations (Leslie, 1994), or agency status (Premack, 1990), support this possibility. Indeed, it has been claimed that internalizing invariant properties of the environment is evolutionarily adaptive (Hubbard, 1995; Shepard, 2001). Thus, it is plausible to conjecture that information regarding the dynamic properties of a scene that we are capable of representing (for example, their causal relations, or the amount of physical forces acting upon an object) is integrated in a unique mental simulation. This being the case, such a dynamical representation may allow for accurate prediction of future states of invisible events. Alternatively, the prediction of motion and the representation of other forms of physical information may be independent, and hence not merged into a single optimal simulation of dynamical events. In the present article, we aim to determine the ability to accurately estimate motions of invisible objects and to clarify how participants integrate an intuitive causal understanding of the represented events into a mental representation of motion . Experiment 1 Experiment one determined the accuracy for predicting the position of a moving object that is no longer visible. Participants were required to predict the time-to-arrival of an animated ball at different positions after its disappearance. We also tested how the representation of causal relations influenced participants' accuracy for predicting invisible dynamical events. If the information used to compute the velocity of an object is integrated with the information used to compute the causal structure of the scene, we would expect that events considered as causally correct are predicted more precisely than events considered as causally anomalous. However, if the two kinds of information are processed separately, we should observe a dissociation between the accuracy of online predictions of imagined position and the perception of causal correctness. In every experimental condition, there were two moving objects, a launcher and a target, the movement of the target behind the occluder was to be predicted, while the causal relation between the launcher and the target, which could vary both in spatial and temporal contiguity, was to be estimated." @default.
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• W2738853669 date "2010-01-01" @default.
• W2738853669 modified "2023-09-25" @default.
• W2738853669 title "On the limits of dynamic imagination: A mental extrapolation task" @default.
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