Melendez-Calderon Alejandro, Tan Michael, Bittmann Moria Fisher, Burdet Etienne, Patton James L
Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, Illinois;
Rehabilitation Institute of Chicago, Chicago, Illinois.
J Neurophysiol. 2017 Jul 1;118(1):219-233. doi: 10.1152/jn.00614.2016. Epub 2017 Mar 29.
Recent studies have explored the prospects of learning to move without moving, by displaying virtual arm movement related to exerted force. However, it has yet to be tested whether learning the dynamics of moving can transfer to the corresponding movement. Here we present a series of experiments that investigate this isometric training paradigm. Subjects were asked to hold a handle and generate forces as their arms were constrained to a static position. A precise simulation of reaching was used to make a graphic rendering of an arm moving realistically in response to the measured interaction forces and simulated environmental forces. Such graphic rendering was displayed on a horizontal display that blocked their view to their actual (statically constrained) arm and encouraged them to believe they were moving. We studied adaptation of horizontal, planar, goal-directed arm movements in a velocity-dependent force field. Our results show that individuals can learn to compensate for such a force field in a virtual environment and transfer their new skills to the actual free motion condition, with performance comparable to practice while moving. Such nonmoving techniques should impact various training conditions when moving may not be possible. This study provided early evidence supporting that training movement skills without moving is possible. In contrast to previous studies, our study involves ) exploiting cross-modal sensory interactions between vision and proprioception in a motionless setting to teach motor skills that could be transferable to a corresponding physical task, and ) evaluates the movement skill of controlling muscle-generated forces to execute arm movements in the presence of external forces that were only virtually present during training.
最近的研究通过展示与施加力相关的虚拟手臂运动,探索了不实际移动而学习移动的前景。然而,学习移动动力学是否能转移到相应的实际运动中,这一点尚未得到验证。在此,我们展示了一系列研究这种等距训练范式的实验。受试者被要求握住一个手柄,在手臂被固定在静态位置时施加力。利用精确的伸手动作模拟,根据测量到的相互作用力和模拟的环境力,生成一幅手臂逼真移动的图形渲染。这样的图形渲染显示在一个水平显示屏上,该显示屏挡住了他们对实际(静态约束)手臂的视线,并促使他们相信自己在移动。我们研究了在速度依赖力场中水平、平面、目标导向的手臂运动的适应性。我们的结果表明,个体能够在虚拟环境中学习补偿这种力场,并将新技能转移到实际的自由运动条件下,其表现与实际移动时的练习相当。当实际移动可能无法进行时,这种非移动技术应该会对各种训练条件产生影响。这项研究提供了早期证据,支持了不实际移动而训练运动技能是可行的。与之前的研究不同,我们的研究涉及:(1)在静止状态下利用视觉和本体感觉之间的跨模态感觉交互来教授可转移到相应身体任务的运动技能;(2)评估在仅在训练期间虚拟存在的外力情况下,控制肌肉产生的力以执行手臂运动的运动技能。