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Movement kinematics affect action prediction comparing human to non-human point-light actions
(2012)
The influence of movement kinematics on the accuracy of predicting the time course of another individual's actions was studied. A human point-light shape was animated with human movement (natural condition) and with artificial movement that was more uniform regarding velocity profiles and trajectories (artificial condition). During brief occlusions, the participants predicted the actions in order to judge after occlusion whether the actions were continued coherently in time or shifted to an earlier or later frame. Error rates and reaction times were increased in the artificial compared to the natural condition. The findings suggest a perceptual advantage for movement with a human velocity profile, corresponding to the notion of a close interaction between observed and executed movement. The results are discussed in the framework of the simulation account and alternative interpretations are provided on the basis of correlations between the velocity profiles of natural and artificial movements with prediction performance.
The notion of action simulation refers to the ability to re-enact foreign actions (i.e., actions observed in other individuals). Simulating others’ actions implies a mirroring of their activities, based on one’s own sensonmotor competencies. Here, we discuss theoretical and experimental approaches to action simulation and the study of its representational underpinnings. One focus of our discussion is on the timing of internal simulation and its relation to the timing of external action, and a paradigm that requires participants to predict the future course of actions that are temporarily occluded from view. We address transitions between perceptual mechanisms (referring to action representation before and after occlusion) and simulation mechanisms (referring to action representation during occlusion). Findings suggest that action simulation runs in real-time; acting on newly created action representations rather than relying on continuous visual extrapolations. A further focus of our discussion pertains to the functional characteristics of the mechanisms involved in predicting other people’s actions. We propose that two processes are engaged, dynamic updating and static matching, which may draw on both semantic and motor information. In a concluding section, we discuss these findings in the context of broader theoretical issues related to action and event representation, arguing that a detailed functional analysis of action simulation in cognitive, neural, and computational terms may help to further advance our understanding of action cognition and motor control.