Perceiving the direction of articulatory motion in point-light actions

Grasping performance depends upon the richness of hand feedback

Although visual feedback of the hand allows fast and accurate grasping actions, little is known about whether the nature of feedback of the hand affects performance. We investigated kinematics during precision grasping (with the index finger and thumb) when participants received different levels of hand feedback, with or without visual feedback of the target. Specifically, we compared performance when participants saw (1) no hand feedback; (2) only the two critical points on the index finger and thumb tips; (3) 21 points on all digit tips and hand joints; (4) 21 points connected by a "skeleton", or (5) full feedback of the hand wearing a glove. When less hand feedback was available, participants took longer to execute the movement because they allowed more time to slow the reach and close the hand. When target feedback was unavailable, participants took longer to plan the movement and reached with higher velocity. We were particularly interested in investigating maximum grip aperture (MGA), which can reflect the margin of error that participants allow to compensate for uncertainty. A trend suggested that MGA was smallest when ample feedback was available (skeleton and full hand feedback, regardless of target feedback) and when only essential information about hand and target was provided (2-point hand feedback + target feedback) but increased when non-essential points were included (21-point feedback). These results suggest that visual feedback of the hand affects grasping performance and that, while more feedback is usually beneficial, this is not necessarily always the case.

Flexible Orientation Tuning of Visual Representations of Human Body Postures: Evidence From Long-Term Priming

The proficiency of human observers to identify body postures is examined in three experiments. We use a posture decision task in which participants are primed with either anatomically possible or impossible postures (in the latter case the upper and lower body face in opposite directions). In a long-term priming paradigm (i.e., in an initial priming block of trials and a subsequent test phase several minutes later), we manipulate the relation between priming and test postures with respect to the identity of the person in the body postures (Experiment 1), the prototypicality of the depth orientations (Experiment 2), and the variability of the priming orientations (Experiment 3). Reaction time to the test postures is the main dependent variable. In Experiment 1 it is found that priming of postures does not depend on the exact visual appearance of the actor (either same priming and test female or male figure or different figures), supporting the hypothesis that posture priming primarily is determined by the spatial relations between the body parts and much less by characteristics of the person involved. Long-term priming in our paradigm apparently is based on the reactivation of high-level posture representations that make abstraction of the identity of the human figure. In Experiment 2 we observe that privileged or prototypical orientations (e.g., 3/4 views) do not affect long-term priming of body postures. In Experiment 3, we find that increasing or decreasing the variability between the priming and test figures influences reaction time performance. Collectively, these results provide a better understanding of the flexibility (e.g., invariant to identity) and limits (e.g., depending on depth orientation) of the processes supporting human posture recognition.

PLAViMoP: How to standardize and simplify the use of point-light displays

The study of biological point-light displays (PLDs) has fascinated researchers for more than 40 years. However, the mechanisms underlying PLD perception remain unclear, partly due to difficulties with precisely controlling and transforming PLD sequences. Furthermore, little agreement exists regarding how transformations are performed. This article introduces a new free-access program called PLAViMoP (Point-Light Display Visualization and Modification Platform) and presents the algorithms for PLD transformations actually included in the software. PLAViMoP fulfills two objectives. First, it standardizes and makes clear many classical spatial and kinematic transformations described in the PLD literature. Furthermore, given its optimized interface, PLAViMOP makes these transformations easy and fast to achieve. Overall, PLAViMoP could directly help scientists avoid technical difficulties and make possible the use of PLDs for nonacademic applications.