Recent results have shown that effects of pictorial illusions in grasping may decrease over the course of an experiment. This can be explained as an effect of sensorimotor learning if we consider a pictorial size illusion as simply a perturbation of visually perceived size. However, some studies have reported very constant illusion effects over trials. In the present paper, we apply an error-correction model of adaptation to experimental data of N=40 participants grasping the Müller-Lyer illusion. Specifically, participants grasped targets embedded in incremental and decremental Müller-Lyer illusion displays in (1) the same block in pseudo-randomised order, and (2) separate blocks of only one type of illusion each. Consistent with predictions of our model, we found an effect of interference between the two types when they were presented intermixed, explaining why adaptation rates may vary depending on the experimental design. We also systematically varied the number of object sizes per block, which turned out to have no effect on the rate of adaptation. This was also in accordance with our model. We discuss implications for the illusion literature, and lay out how error-correction models can explain perception-action dissociations in some, but not all grasping-of-illusion paradigms in a parsimonious and plausible way, without assuming different illusion effects.
Depth cue reweighting is a feedback-driven learning process that modifies the relative influences of different sources of three-dimensional shape information in perceptual judgments and or motor planning. In this study, we investigated the mechanism supporting reweighting of stereo and texture information by manipulating the haptic feedback obtained during a series of grasping movements. At the end of each grasp, the fingers closed down on a physical object that was consistent with one of the two cues, depending on the condition. Previous studies have shown that this style of visuomotor training leads to cue reweighting for perceptual judgments, but the time course has never been documented for a single training session, and many questions remain regarding the underlying mechanism, such as the pattern of feedback signals required to drive reweighting. We address these issues in two experiments, finding short-term changes in the motor response consistent with cue reweighting: the slope of the grip aperture with respect to the reliable cue increased, whereas the slope with respect to the unreliable cue decreased. Critically, Experiment 2 shows that slope changes do not occur when one of the cues is rendered with a constant bias; the grip aperture simply becomes uniformly larger or smaller. Our findings support a model of cue reweighting driven by altered correlations between haptic feedback and individual cues, rather than simple mismatches, which can be resolved by other mechanisms such as sensorimotor adaptation or cue recalibration.
The ability to predict the dynamics of objects, linking applied force to motion, underlies our capacity to perform many of the tasks we carry out on a daily basis. Thus, a fundamental question is how the dynamics of the myriad objects we interact with are organized in memory. Using a custom-built three-dimensional robotic interface that allowed us to simulate objects of varying appearance and weight, we examined how participants learned the weights of sets of objects that they repeatedly lifted. We find strong support for the novel hypothesis that motor memories of object dynamics are organized categorically, in terms of families, based on covariation in their visual and mechanical properties. A striking prediction of this hypothesis, supported by our findings and not predicted by standard associative map models, is that outlier objects with weights that deviate from the family-predicted weight will never be learned despite causing repeated lifting errors.
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