Limits to human movement planning in tasks with asymmetric gain landscapes

We studied human movement planning in a task with predefined costs and benefits to movement outcome. Participants pointed rapidly at stimulus configurations consisting of a target region and up to two penalty regions. Hits on the target and penalty regions resulted in monetary gains and losses. In previous studies involving single penalty regions or other symmetric target-penalty configurations, performance was optimal in the sense of maximizing expected gain. In this study, more complex, asymmetric configurations were used in which the two penalty regions carried different penalties. With these configurations, the landscape of expected gain as a function of mean end point (MEP) was spatially asymmetric. Further, the optimal movement plan with these configurations was sometimes counterintuitive (e.g., one should aim slightly inside the lesser penalty region). In one asymmetric condition, four out of six naïve participants' performed suboptimally, indicating that there are limits to human movement planning. Further, the suboptimal performance was inconsistent with a model in which participants misestimate motor variability but otherwise optimally plan their movement.