Department of Psychology and Sports Science, Justus Liebig University Giessen, Germany; nemolab, University of Giessen, Justus Liebig University Giessen, Germany.
Department of Sports Science and Sport Center, University of Augsburg, Germany.
Hum Mov Sci. 2022 Oct;85:103001. doi: 10.1016/j.humov.2022.103001. Epub 2022 Sep 9.
Improving tracking performance requires numerous adjustments in the motor system, including peripheral muscle functions and central motor commands. These commands can rely on sensory feedback processing during tracking, i.e., closed-loop control. In the case of repeated tracking sequences, these commands can rely on an inner representation of the target trajectory to optimize pre-planning, i.e., open-loop control. Implicit learning in a continuous tracking task with repeated sequences proves the availability of an inner target representation, which emerges by learning task regularities, even without explicit knowledge. We hypothesize that the actual use of open-loop or closed-loop control is influenced by the demand for attention. Specifically, we suggest that closed-loop control and its development during practice need attentional resources, whereas open-loop control can work and evolve in a more automatic way without attentional demands. To test this, we investigated motor-control strategies when extensively practicing a continuous compensatory force-tracking task using isometric leg muscle activation, either as a single-motor task or as a motor-cognitive dual task. After training, we found evidence for predominantly closed-loop control in the single-task training group and for open-loop control in the dual-task training group. In particular, we ascertained dual-task motor costs and a weakly developed implicit knowledge of task regularities in the single-task training group. In contrast, in the dual-task training group dual-task motor costs disappeared, while implicit learning was clearly observed. We conclude that motor-cognitive dual-task training may boost implicit motor learning, without necessarily impeding concurrent improvement in the cognitive task. Data repository: reserved doi: https://doi.org/10.5281/zenodo.6759377.
提高跟踪性能需要对运动系统进行大量调整,包括外周肌肉功能和中枢运动指令。这些指令可以依赖于跟踪过程中的感觉反馈处理,即闭环控制。在重复跟踪序列的情况下,这些指令可以依赖于目标轨迹的内部表示来优化预规划,即开环控制。在具有重复序列的连续跟踪任务中的内隐学习证明了存在内部目标表示,这种表示是通过学习任务规律而出现的,即使没有明确的知识。我们假设,开环或闭环控制的实际使用受到注意力需求的影响。具体来说,我们建议闭环控制及其在实践中的发展需要注意力资源,而开环控制可以以更自动的方式工作和演变,而不需要注意力需求。为了验证这一点,我们研究了在使用等长腿部肌肉激活的连续补偿力跟踪任务中广泛练习时的运动控制策略,无论是作为单一任务还是作为运动认知双重任务。在训练后,我们发现单一任务训练组主要表现为闭环控制,而双重任务训练组表现为开环控制。特别是,我们在单一任务训练组中确定了双重任务运动成本和对任务规律的弱内隐知识,而在双重任务训练组中则没有。相比之下,在双重任务训练组中,双重任务运动成本消失了,而明显观察到了内隐学习。我们得出结论,运动认知双重任务训练可以促进内隐运动学习,而不一定会阻碍认知任务的同时提高。数据存储库:保留的 doi: https://doi.org/10.5281/zenodo.6759377。