Seeing all the obstacles in your way: the effect of visual feedback and visual feedback schedule on obstacle avoidance while reaching

Human reaching behaviour displays sophisticated obstacle avoidance. Recently, we demonstrated that the obstacle avoidance system in normal participants is sensitive to both the position and size of obstacles (Chapman and Goodale in Exp Brain Res 191:83–97, 2008). A limitation in this previous study was that reaches were performed without visual feedback, and were not made to a specific target (i.e. the target was a long strip instead of a point). Many studies have shown that both the introduction of visual feedback and the order in which the feedback is presented (visual feedback schedule) significantly alter performance in simple visuomotor tasks (Zelaznik et al. in J Mot Behav 15:217–236, 1983). Thus, the present study was designed to compare obstacle avoidance when reaches were made to a discrete target with vision (V) and with no vision (NV) under different three visual feedback schedules (blocked, random, and alternating). Twenty-four right-handed participants performed reaches in the presence of one, two, or no obstacles placed mid-reach. In addition to replicating previous work with reaching without vision, we showed that robust avoidance behaviour occurred when reaches were made to a specific target, when reaching with only one object present, and, critically, when vision of the hand was available during the reach. Moreover, the visual feedback schedule also had a significant effect on several kinematic measures—but only on the NV trials. That is, regardless of its predictability or recent availability, vision was used in the same way for all reaches. In contrast, performance on blocked-NV trials was markedly different from performance on NV trials presented under random or alternating schedules. In addition to extending our understanding of obstacle avoidance during reaching, our results suggest that, in a complex and more natural reach-to-point task, the human visuomotor system is optimized to use visual feedback.