Kohen Dovrat, Karklinsky Matan, Meirovitch Yaron, Flash Tamar, Shmuelof Lior
Department of Computer Science and Applied Mathematics, Weizmann Institute of ScienceRehovot, Israel.
Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT)Cambridge, MA, United States.
Front Hum Neurosci. 2017 Jun 29;11:333. doi: 10.3389/fnhum.2017.00333. eCollection 2017.
When subjects are intentionally preparing a curved trajectory, they are engaged in a time-consuming trajectory planning process that is separate from target selection. To investigate the construction of such a plan, we examined the effect of artificially shortening preparation time on the performance of intentionally curved trajectories using the Timed Response task that enforces initiation of movements prematurely. Fifteen subjects performed obstacle avoidance movements toward one of four targets that were presented 25 or 350 ms before the "go" signal, imposing short and long preparation time conditions with mean values of 170 ms and 493 ms, respectively. While trajectories with short preparation times showed target specificity at their onset, they were significantly more variable and showed larger angular deviations from the lines connecting their initial position and the target, compared to the trajectories with long preparation times. Importantly, the trajectories of the short preparation time movements still reached their end-point targets accurately, with comparable movement durations. We hypothesize that success in the short preparation time condition is a result of an online control mechanism that allows further refinement of the plan during its execution and study this control mechanism with a novel trajectory analysis approach using minimum jerk optimization and geometrical modeling approaches. Results show a later agreement of the short preparation time trajectories with the optimal minimum jerk trajectory, accompanied by a later initiation of a parabolic segment. Both observations are consistent with the existence of an online trajectory planning process.Our results suggest that when preparation time is not sufficiently long, subjects execute a more variable and less optimally prepared initial trajectory and exploit online control mechanisms to refine their actions on the fly.
当受试者有意准备一条弯曲轨迹时，他们会参与一个耗时的轨迹规划过程，该过程与目标选择是分开的。为了研究这种计划的构建，我们使用了定时响应任务来人为缩短准备时间，以此研究其对有意弯曲轨迹性能的影响，该任务会强制运动过早开始。15名受试者朝着四个目标之一进行避障运动，这些目标在“开始”信号前25毫秒或350毫秒呈现，分别施加了平均准备时间为170毫秒和493毫秒的短准备时间和长准备时间条件。虽然短准备时间的轨迹在起始时表现出目标特异性，但与长准备时间的轨迹相比，它们的变异性明显更大，并且与连接其初始位置和目标的直线的角度偏差也更大。重要的是，短准备时间运动的轨迹仍然准确地到达了终点目标，且运动持续时间相当。我们假设在短准备时间条件下的成功是一种在线控制机制的结果，该机制允许在计划执行期间进一步优化计划，并使用最小急动优化和几何建模方法的新颖轨迹分析方法来研究这种控制机制。结果表明，短准备时间的轨迹与最优最小急动轨迹的一致性较晚，同时抛物线部分的起始也较晚。这两个观察结果都与在线轨迹规划过程的存在相一致。我们的结果表明，当准备时间不够长时，受试者会执行一个变异性更大、准备不太优化的初始轨迹，并利用在线控制机制即时优化他们的动作。
