Kluzik JoAnn, Diedrichsen Jörn, Shadmehr Reza, Bastian Amy J
Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
J Neurophysiol. 2008 Sep;100(3):1455-64. doi: 10.1152/jn.90334.2008. Epub 2008 Jul 2.
We make errors when learning to use a new tool. However, the cause of error may be ambiguous: is it because we misestimated properties of the tool or of our own arm? We considered a well-studied adaptation task in which people made goal-directed reaching movements while holding the handle of a robotic arm. The robot produced viscous forces that perturbed reach trajectories. As reaching improved with practice, did people recalibrate an internal model of their arm, or did they build an internal model of the novel tool (robot), or both? What factors influenced how the brain solved this credit assignment problem? To investigate these questions, we compared transfer of adaptation between three conditions: catch trials in which robot forces were turned off unannounced, robot-null trials in which subjects were told that forces were turned off, and free-space trials in which subjects still held the handle but watched as it was detached from the robot. Transfer to free space was 40% of that observed in unannounced catch trials. We next hypothesized that transfer to free space might increase if the training field changed gradually, rather than abruptly. Indeed, this method increased transfer to free space from 40 to 60%. Therefore although practice with a novel tool resulted in formation of an internal model of the tool, it also appeared to produce a transient change in the internal model of the subject's arm. Gradual changes in the tool's dynamics increased the extent to which the nervous system recalibrated the model of the subject's own arm.
我们在学习使用新工具时会犯错。然而，错误的原因可能并不明确：是因为我们错误估计了工具的特性，还是我们自己手臂的特性？我们考虑了一个经过充分研究的适应性任务，在这个任务中，人们在握住机器人手臂的手柄时进行目标导向的伸手动作。机器人产生粘性力来干扰伸手轨迹。随着练习伸手动作得到改善，人们是重新校准了他们手臂的内部模型，还是构建了新工具（机器人）的内部模型，或者两者都有？哪些因素影响大脑解决这个归因问题的方式？为了研究这些问题，我们比较了三种条件下的适应性转移：在突然关闭机器人力量的捕捉试验、告知受试者力量已关闭的机器人无效试验以及受试者仍然握住手柄但看着它与机器人分离的自由空间试验。向自由空间的转移是在未宣布的捕捉试验中观察到的转移的40%。接下来我们假设，如果训练场逐渐变化而不是突然变化，向自由空间的转移可能会增加。事实上，这种方法将向自由空间的转移从40%提高到了60%。因此，虽然使用新工具的练习导致了工具内部模型的形成，但它似乎也在受试者手臂的内部模型中产生了短暂的变化。工具动力学的逐渐变化增加了神经系统重新校准受试者自身手臂模型的程度。
