Time Scales and Motor Learning

时间尺度和运动学习

• 批准号: 0518845
• 负责人: Karl Newell
• 金额: --
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0518845&HistoricalAwards=false
• 关键词: Time; Scales; Motor; Learning

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

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，在达到熟练演奏的道路上会遇到坎坷。 但运动科学领域的研究人员发现了获得运动技能的时间过程中的特定模式，这些模式揭示了运动学习的本质。几十年来，这些模式一直被解释为揭示了适用于所有时间尺度的学习幂律，从几天内的逐渐改进到几分钟甚至几秒钟内发生的快速改进。 然而，最近的进展表明情况比之前想象的更加复杂。 在国家科学基金会的资助下，纽厄尔博士将从动态系统的角度研究运动学习时间尺度的复杂性。 在他的方法中，学习被形式化为吸引子景观的演变，其中高度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控制，吸引子组织的分叉会打断吸引子景观动态。 分岔提供了对日常经验的科学理解，在这种经验中，练习的工作会突然得到回报，就像孩子在学习骑自行车时突然得到回报一样。 该研究有望为学习的动态系统理论奠定基础，不仅适用于运动技能，还适用于生物和认知系统中的各种学习