Time Scales and Motor Learning

我们如何学习投球或演奏乐器，或执行任何其他熟练的运动任务？我们的日常经验告诉我们，练习是关键，我们预计在熟练表演的道路上会有起伏。但运动科学的研究人员在获得运动技能的时间过程中看到了特定的模式，这种模式揭示了运动学习的本质。几十年来，这些模式一直被解读为揭示了学习的幂定律，它适用于所有时间尺度，从几天的渐进改进到几分钟甚至几秒钟内的快速改进。然而，最近的进展表明，情况比之前想象的要复杂得多。在国家科学基金会的资助下，纽威尔博士将从动态系统的角度研究运动学习时间尺度上的这些复杂性。在他的方法中，学习被形式化为吸引子景观的演变，其中海拔对应于从当前学习状态到目标状态的距离。关键假设是，学习曲线受吸引子景观动态的支配，吸引子组织的分叉打断了吸引子景观动态。分叉提供了一种对日常经验的科学理解，在这种经历中，练习的工作在突然的时刻得到了回报，就像一个孩子在学习骑自行车时突然得到了回报。这项研究承诺为学习的动态系统理论奠定基础，不仅是运动技能，而且是生物和认知系统中的各种学习。

How do we learn to throw a ball or play an instrument, or perform any other skilled motor task? Our everyday experience tells us that practice is the key, with the anticipation that there will be ups and downs on the road to skilled performance. But researchers in the movement sciences see specific patterns in the time course of acquiring a motor skill, patterns that reveal the nature of motor learning.For decades those patterns have been interpreted as revealing a power law of learning that holds across all time scales, from gradual improvements that occur over days to rapid improvements that occur in a matter of minutes or even seconds. Recent advances however have shown the picture to be more complex that previously thought. With funding from the National Science Foundation, Dr. Newell will investigate those complexities in the time scales of motor learning from a dynamic systems perspective. On his approach, learning is formalized as the evolution of an attractor landscape, where elevation corresponds to distance from the current state of learning to the goal state. The critical hypothesis is that learning curves are governed by attractor landscape dynamics, which are punctuated by bifurcations of the attractor organization. Bifurcations provide a scientific understanding of the everyday experience in which the work of practice pays off in sudden moment, as when a child suddenly gets it when learning to ride a bicycle. The research promises to build a foundation for dynamic systems theories of learning, not only for motor skills but for learning of all kinds in biological and cognitive systems