Zahno Stephan, Beck Damian, Kredel Ralf, Klostermann André, Hossner Ernst-Joachim
Institute of Sport Science, University of Bern, Bern, Switzerland.
J Neurophysiol. 2025 Jul 1;134(1):94-106. doi: 10.1152/jn.00606.2024. Epub 2025 Jun 6.
Handling motor noise is fundamental to successful sensorimotor behavior, especially in high-risk situations. Research using finger-pointing tasks shows that humans account for motor noise and costs of potential outcomes in movement planning. However, does this mechanism generalize to more complex movement tasks? Here, we investigate sensorimotor behavior under risk in a virtual reality throwing task across three experiments with 20 participants each. Their task was to throw balls at a target circle, partially overlapped by a penalty circle. In the experiments, penalty magnitude and the distance between the circles were manipulated. We measured the location of their final gaze fixation before movement-as an indicator of their planned aiming point-and the ball's impact location. Without penalty, the final gaze fixation and the ball's impact location were both centered on the target. In the penalty condition, the location of the participants' final gaze fixations and the ball's impact shifted away from the penalty circle, with larger shifts for higher penalties and smaller distances. Interestingly, the shifts in the ball's impact locations were not only larger ("less risk seeking") but also closer to the statistically optimal (expected gain-maximizing) location compared with the fixated aim points. Movement trajectory analyses show that, in penalty conditions, the shifts away from the penalty zone increased until the final phases of the movement. Based on these results, we propose the hypothesis that risk evaluation is not completed in a pre-movement planning phase but is further optimized during movement execution. We extend the study of sensorimotor behavior under risk from simple finger-pointing movements (Trommershäuser et al., Trends Cogn Sci 12: 291-297, 2008) to a complex throwing task in virtual reality. Our results suggest that, in complex sensorimotor behavior, risk evaluation of potential movements is not confined to a cognitive planning phase before movement but is optimized in action, with the motor system continuously biasing competing action options toward regions of higher expected rewards.
处理运动噪声是成功的感觉运动行为的基础，尤其是在高风险情况下。使用手指指向任务的研究表明，人类在运动规划中会考虑运动噪声和潜在结果的成本。然而，这种机制是否能推广到更复杂的运动任务中呢？在这里，我们通过三个实验，对20名参与者在虚拟现实投掷任务中的风险下的感觉运动行为进行了研究。他们的任务是向一个目标圆圈投掷球，该目标圆圈部分与一个惩罚圆圈重叠。在实验中，我们操纵了惩罚幅度和圆圈之间的距离。我们测量了他们在运动前最后注视的位置——作为他们计划瞄准点的指标——以及球的撞击位置。在没有惩罚的情况下，最后注视的位置和球的撞击位置都以目标为中心。在有惩罚的情况下，参与者最后注视的位置和球的撞击位置都从惩罚圆圈移开，惩罚越大、距离越小，移动幅度就越大。有趣的是，与固定的瞄准点相比，球的撞击位置的移动不仅更大（“风险寻求更少”），而且更接近统计上的最优（预期收益最大化）位置。运动轨迹分析表明，在有惩罚的情况下，远离惩罚区域的移动会增加，直到运动的最后阶段。基于这些结果，我们提出了一个假设，即风险评估不是在运动前的规划阶段完成的，而是在运动执行过程中进一步优化的。我们将对风险下的感觉运动行为的研究从简单的手指指向运动（特罗默绍伊泽等人，《认知科学趋势》12: 291 - 297，2008年）扩展到虚拟现实中的复杂投掷任务。我们的结果表明，在复杂的感觉运动行为中，对潜在运动的风险评估并不局限于运动前的认知规划阶段，而是在行动中得到优化，运动系统不断地将相互竞争的行动选项偏向于预期回报更高的区域。
