Doing it your way: How individual movement styles affect action prediction

Individuals show significant variations in performing a motor act. Previous studies in the action observation literature have largely ignored this ubiquitous, if often unwanted, characteristic of motor performance, assuming movement patterns to be highly similar across repetitions and individuals. In the present study, we examined the possibility that individual variations in motor style directly influence the ability to understand and predict others’ actions. To this end, we first recorded grasping movements performed with different intents and used a two-step cluster analysis to identify quantitatively ‘clusters’ of movements performed with similar movement styles (Experiment 1). Next, using videos of the same movements, we proceeded to examine the influence of these styles on the ability to judge intention from action observation (Experiments 2 and 3). We found that motor styles directly influenced observers’ ability to ‘read’ others’ intention, with some styles always being less ‘readable’ than others. These results provide experimental support for the significance of motor variability for action prediction, suggesting that the ability to predict what another person is likely to do next directly depends on her individual movement style

The visible face of intention: why kinematics matters

A key component of social understanding is the ability to read intentions from movements. But how do we discern intentions in others’ actions? What kind of intention information is actually available in the features of others’ movements? Based on the assumption that intentions are hidden away in the other person’s mind, standard theories of social cognition have mainly focused on the contribution of higher level processes. Here, we delineate an alternative approach to the problem of intention-from-movement understanding. We argue that intentions become “visible” in the surface flow of agents’ motions. Consequently, the ability to understand others’ intentions cannot be divorced from the capability to detect essential kinematics. This hypothesis has far reaching implications for how we know other minds and predict others’ behavior

Decoding intentions from movement kinematics

How do we understand the intentions of other people? There has been a longstanding controversy over whether it is possible to understand others’ intentions by simply observing their movements. Here, we show that indeed movement kinematics can form the basis for intention detection. By combining kinematics and psychophysical methods with classification and regression tree (CART) modeling, we found that observers utilized a subset of discriminant kinematic features over the total kinematic pattern in order to detect intention from observation of simple motor acts. Intention discriminability covaried with movement kinematics on a trial-by-trial basis, and was directly related to the expression of discriminative features in the observed movements. These findings demonstrate a definable and measurable relationship between the specific features of observed movements and the ability to discriminate intention, providing quantitative evidence of the significance of movement kinematics for anticipating others’ intentional actions

Anticipatory action planning in blind and sighted individuals

Several studies on visually guided reach-to-grasp movements have documented that how objects are grasped differs depending on the actions one intends to perform subsequently. However, no previous study has examined whether this differential grasping may also occur without visual input. In this study, we used motion capture technology to investigate the influence of visual feedback and prior visual experience on the modulation of kinematics by intention in sighted (in both full-vision and no-vision conditions), early-blind and late-blind participants. Results provide evidence of modulation of kinematics by intention to a similar degree under both full-vision and no-vision conditions. Moreover, they demonstrate that prior visual experience has little impact on the tailoring of grasping movements to intention. This suggests that sequential action planning does not depend on visual input, and may instead be ascribed to the function of multisensory-motor cortical network that operates and develops not only in light, but also in darkness