Abstract
The expected value of an uncertain decision is the product of the probability of the chosen outcome occurring and the value of the outcome. Trommerhäuser et al. (2003) showed that people aimed to an 'optimal movement endpoint' that was modeled based on the participants' endpoint variability (probability) and the cost associated with a penalty region (value) that partially overlapped the target. Although it is predicted that the endpoint should change as a function of endpoint variability, optimal endpoint has only been examined after extensive training. Shifts in endpoint during training, while theoretically relevant, were not examined. The present study was designed to explore the change in endpoint as variability changes with practice. Participants made 300 aiming movements to a target worth +100pts with an overlapping penalty region worth -500pts. The optimal model suggests that mean endpoint should be farther from the penalty region early in practice when endpoint variability is higher - increasing target misses but decreasing costly penalty hits. As variability decreases, the endpoint should shift closer to the optimal location. In contrast to predictions, participants' mean movement endpoint started closer to the penalty region and shifted away with increasing practice, even as endpoint variability decreased. These results indicate that people may have to receive feedback in the form of hitting the penalty region to change to a more optimal movement planning strategy.Acknowledgments: This research was funded by NSERC