Russo Marta, Cesqui Benedetta, La Scaleia Barbara, Ceccarelli Francesca, Maselli Antonella, Moscatelli Alessandro, Zago Myrka, Lacquaniti Francesco, d'Avella Andrea
Centre of Space Bio-medicine, University of Rome Tor Vergata, Rome, Italy;
Centre of Space Bio-medicine, University of Rome Tor Vergata, Rome, Italy.
J Neurophysiol. 2017 Oct 1;118(4):2421-2434. doi: 10.1152/jn.00025.2017. Epub 2017 Aug 2.
To accurately time motor responses when intercepting falling balls we rely on an internal model of gravity. However, whether and how such a model is also used to estimate the spatial location of interception is still an open question. Here we addressed this issue by asking 25 participants to intercept balls projected from a fixed location 6 m in front of them and approaching along trajectories with different arrival locations, flight durations, and gravity accelerations (0 and 1). The trajectories were displayed in an immersive virtual reality system with a wide field of view. Participants intercepted approaching balls with a racket, and they were free to choose the time and place of interception. We found that participants often achieved a better performance with 1 than 0 balls. Moreover, the interception points were distributed along the direction of a 1 path for both 1 and 0 balls. In the latter case, interceptions tended to cluster on the upper half of the racket, indicating that participants aimed at a lower position than the actual 0 path. These results suggest that an internal model of gravity was probably used in predicting the interception locations. However, we found that the difference in performance between 1 and 0 balls was modulated by flight duration, the difference being larger for faster balls. In addition, the number of peaks in the hand speed profiles increased with flight duration, suggesting that visual information was used to adjust the motor response, correcting the prediction to some extent. Here we show that an internal model of gravity plays a key role in predicting where to intercept a fast-moving target. Participants also assumed an accelerated motion when intercepting balls approaching in a virtual environment at constant velocity. We also show that the role of visual information in guiding interceptive movement increases when more time is available.
为了在拦截下落的球时精确地确定运动反应的时间,我们依赖于重力的内部模型。然而,这样的模型是否以及如何也被用于估计拦截的空间位置仍是一个悬而未决的问题。在这里,我们通过让25名参与者拦截从他们前方6米处的固定位置投射出的球来解决这个问题,这些球沿着具有不同到达位置、飞行持续时间和重力加速度(0和1)的轨迹接近。轨迹显示在一个具有宽视野的沉浸式虚拟现实系统中。参与者用球拍拦截接近的球,并且他们可以自由选择拦截的时间和地点。我们发现,与拦截重力加速度为0的球相比,参与者在拦截重力加速度为1的球时通常表现得更好。此外,对于重力加速度为1和0的球,拦截点都沿着重力加速度为1的路径方向分布。在后一种情况下,拦截往往集中在球拍的上半部分,这表明参与者瞄准的位置比实际重力加速度为0的路径要低。这些结果表明,重力的内部模型可能被用于预测拦截位置。然而,我们发现重力加速度为1和0的球在表现上的差异受到飞行持续时间的调节,对于速度更快的球,差异更大。此外,手部速度曲线中的峰值数量随着飞行持续时间增加,这表明视觉信息被用于调整运动反应,在一定程度上校正了预测。在这里,我们表明重力的内部模型在预测何处拦截快速移动目标方面起着关键作用。当在虚拟环境中拦截以恒定速度接近的球时,参与者也假定了加速运动。我们还表明,当有更多时间可用时,视觉信息在引导拦截运动中的作用会增加。