The present set of experiments investigated the possibility that learned perceptual information can, under certain circumstances, be utilized by visuomotor programming. In Experiment 1 (N = 28), an association was established between the color and size of square wooden blocks (e.g., red = large; yellow = small, or vice-versa). In Experiment 2 (N = 28), an association was established between the shape and size of plastic objects (e.g., hexagon = large; circle = small, or vice-versa). It was expected that the learned associations would change the perceived size of two probe objects halfway in size between the large and small objects (the probe object matched by color or shape to the large group of objects would appear smaller than the probe object matched to the small group of objects as a result of within-group relative size comparisons). In both experiments, half of the participants grasped the target objects, and the other half estimated the size of the objects by opening their thumb and finger a matching amount. For Experiment 1, it was predicted that an influence of the lérned association on the treatment of the probe objects would be seen in manual estimations and in grip scaling because the kinematics of the grasping movement were very similar across trials. As predicted, the learned association between size and color was as easily incorporated into visually guided grasping as it was into visual perceptions. In Experiment 2, it was predicted that an influence of the learned perceptual association would be seen only in manual estimations, and not in grip scaling, because the variability in target object shape from trial to trial would demand changes in precontact finger posture across trials. Despite the significant effect of the size-shape association on size estimations, no influence was seen in preparatory grip scaling, probably because varying shape increased the metrical demands on visuomotor programming from those in Experiment 1. Together, the results suggest that visuomotor programming can make use of learned size information under some, but not all, conditions.
Theoretical Framework for Estimating Target-Object Shape by Using Location-Unknown Mobile Distance Sensors
