Variability and Stability in Skill Acquisition

技能习得的可变性和稳定性

基本信息

  • 批准号:
    7784660
  • 负责人:
  • 金额:
    $ 32.37万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2003
  • 资助国家:
    美国
  • 起止时间:
    2003-12-01 至 2015-06-30
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): The acquisition of perceptual-motor skills and their adaptation to changing task demands is fundamental to everyday life. Loss of skill and adaptability is detrimental to functioning and is present in many neurological diseases of the sensorimotor system. Hence, further insights into these processes and their rehabilitation is of utmost significance. To elucidate the processes underlying acquisition, adaptation, and control of movements the proposed research tests the hypothesis that the central nervous system is exquisitely sensitive to its own variability and not only reduces unwanted intrinsic noise but has also developed strategies that accommodate and even utilize this noise. This hypothesis rests on two assumptions: first, the sensorimotor system has intrinsic neuromotor noise arising from complex hierarchical processes; second, behavioral tasks are typically redundant and afford many different ways to achieve equivalent task outcomes. Hence, the brain seeks solutions with stability that are robust with respect to its noise. Work of the previous funding cycle established that there are three conceptually distinct routes to achieve task stability: Tolerance: During practice humans explore and traverse the space of solutions in order to find those strategies that are tolerant to error and noise. Covariation: Task redundancy offers solutions where covariation among relevant variables achieves the same result in task performance while allowing variation in individual variables. Noise: When necessary, the amplitude of the random components can be reduced. This three-pronged TCN-distinction presents the quantitative framework to evaluate the hypothesis that in acquiring skilled behavior the central nervous system develops "smart" solutions that reduce, accommodate, and utilize the inevitable neuromotor noise. Twelve new experiments test this hypothesis and take findings as the platform to design novel intervention techniques. The research is organized into three aims: Experiments under Aim 1 focus on Tolerance and test whether the system seeks solutions that best accommodate for the individual's variability. Conversely, we also test whether manipulating the individual's variability can accelerate adaptation to tolerant solutions. Experiments under Aim 2 examine how Covariation of variables is achieved such that intrinsic noise has minimal effect on the task result. Augmented information is administered to investigate whether the acquisition of such trajectories can be facilitated. Experiments under Aim 3 examine whether intrinsic neuromotor Noise can be reduced by adding extrinsic noise and manipulating error information. The proposed research will be conducted on two tasks in parallel: Skittles, a target-oriented discrete throwing action predominantly under feedforward control, and Ball Bouncing, a continuous perceptually-guided skill of rhythmically hitting a ball. By performing equivalent experimental manipulations to both tasks, we test the generality of our hypothesis that the nervous system accommodates and utilizes intrinsic neuromotor noise in skilled behavior. Results from this quantitative TCN-approach will shed light on the control and acquisition of movement skills in ways that have not been addressed in any other extant research. Importantly, we also make the much-desired transition from new basic insights directly to intervention techniques. We propose three types of interventions that specifically aim to optimize task tolerance, maximize covariation, and reduce noise. We thereby establish the necessary bridge from theoretical concepts to practical techniques that will be applicable to a variety of neurological deficits. While the research proposed here is focused on healthy humans, complementary work is currently under way in close collaboration with Dr. Terence Sanger at Stanford University Medical Center that tests these concepts in children with dyskinetic cerebral palsy. The proposed work on healthy humans is an international collaboration with Dr. Hermann M¿ller at the University of Giessen, Germany, and Dr. Tjeerd Dijkstra at the University of Nijmegen, Netherlands, and will involve student exchanges. PUBLIC HEALTH RELEVANCE: This proposal is directed at elucidating the processes underlying the acquisition, adaptation, and control of skilled movements. Our basic experiments are paired with studies that test interventions that directly capitalize on our basic insights. This dual approach provides a solid basis that will lead to a deeper understanding of skill acquisition and to theoretically grounded interventions to restore sensorimotor function in a variety of neurological disorders. The ongoing collaboration with Dr. Sanger at the Stanford Medical School aims to demonstrate that the intervention techniques developed here can achieve improvements in motor function and learning in children with dyskinetic cerebral palsy.
描述(由申请人提供):感知运动技能的习得及其对不断变化的任务需求的适应是日常生活的基础。技能和适应性的丧失对功能是有害的,并且存在于许多感觉运动系统的神经系统疾病中。因此,进一步了解这些过程及其恢复是至关重要的。为了阐明运动的获取、适应和控制的潜在过程,本研究提出了一种假设,即中枢神经系统对其自身的变异性非常敏感,不仅减少了不必要的内在噪音,而且还开发了适应甚至利用这些噪音的策略。这一假设基于两个假设:第一,感觉运动系统具有由复杂的层次过程引起的内在神经运动噪声;其次,行为任务通常是冗余的,提供了许多不同的方法来实现相同的任务结果。因此,大脑寻求稳定的解决方案,这些解决方案相对于它的噪音是稳健的。上一个资助周期的工作确定了实现任务稳定性的三个概念上不同的途径:容忍度:在实践中,人类探索和遍历解决方案的空间,以找到容忍错误和噪声的策略。协变:任务冗余提供了解决方案,其中相关变量之间的协变在允许单个变量变化的情况下在任务性能上达到相同的结果。噪声:必要时,可以降低随机分量的振幅。这种三管齐下的tcn区分提出了定量框架,以评估在获得熟练行为时,中枢神经系统开发“智能”解决方案,减少、适应和利用不可避免的神经运动噪声的假设。12项新的实验验证了这一假设,并将研究结果作为设计新的干预技术的平台。该研究分为三个目标:目标1下的实验侧重于容忍度,并测试系统是否寻求最能适应个体可变性的解决方案。相反,我们也测试了操纵个体的可变性是否可以加速对宽容解决方案的适应。目的2下的实验研究了如何实现变量的协变,从而使固有噪声对任务结果的影响最小。管理增强信息以调查是否可以促进此类轨迹的获取。Aim 3的实验研究了是否可以通过添加外部噪声和操纵误差信息来降低内在神经运动噪声。本研究将平行进行两项任务:Skittles(一种主要在前馈控制下的目标导向离散投掷动作)和Ball bounce(一种连续的有节奏的击球感知引导技能)。通过对这两项任务进行等效的实验操作,我们测试了神经系统在熟练行为中容纳和利用内在神经运动噪声这一假设的普遍性。这种定量的tcn方法的结果将以任何其他现有研究都没有解决的方式阐明运动技能的控制和获得。重要的是,我们也从新的基本见解直接过渡到干预技术。我们提出了三种类型的干预措施,专门针对优化任务容忍度,最大化协变和减少噪音。因此,我们建立了从理论概念到实际技术的必要桥梁,将适用于各种神经缺陷。虽然这里提出的研究重点是健康人,但目前正在与斯坦福大学医学中心的特伦斯·桑格博士密切合作,在患有运动障碍脑瘫的儿童中测试这些概念。拟议的健康人类工作是与德国吉森大学的Hermann M¿ller博士和荷兰奈梅亨大学的Tjeerd Dijkstra博士的国际合作,并将涉及学生交换。

项目成果

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Dagmar Sternad其他文献

Dagmar Sternad的其他文献

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{{ truncateString('Dagmar Sternad', 18)}}的其他基金

Predictability in Complex Object Control
复杂对象控制的可预测性
  • 批准号:
    9306697
  • 财政年份:
    2015
  • 资助金额:
    $ 32.37万
  • 项目类别:
Predictability in Complex Object Control
复杂对象控制的可预测性
  • 批准号:
    9055880
  • 财政年份:
    2015
  • 资助金额:
    $ 32.37万
  • 项目类别:
Predictability in Complex Object Control
复杂对象控制的可预测性
  • 批准号:
    9733026
  • 财政年份:
    2015
  • 资助金额:
    $ 32.37万
  • 项目类别:
Predictability in complex object control
复杂对象控制的可预测性
  • 批准号:
    10365518
  • 财政年份:
    2015
  • 资助金额:
    $ 32.37万
  • 项目类别:
Predictability in complex object control
复杂对象控制的可预测性
  • 批准号:
    10576826
  • 财政年份:
    2015
  • 资助金额:
    $ 32.37万
  • 项目类别:
Predictability in Complex Object Control
复杂对象控制的可预测性
  • 批准号:
    9150309
  • 财政年份:
    2015
  • 资助金额:
    $ 32.37万
  • 项目类别:
VARIABILITY AND STABILITY IN SKILL ACQUISITION
技能习得的可变性和稳定性
  • 批准号:
    6709754
  • 财政年份:
    2003
  • 资助金额:
    $ 32.37万
  • 项目类别:
Variability and Stability in Skill Acquisition
技能习得的可变性和稳定性
  • 批准号:
    8496836
  • 财政年份:
    2003
  • 资助金额:
    $ 32.37万
  • 项目类别:
Variability and Stability in Skill Acquisition
技能习得的可变性和稳定性
  • 批准号:
    8110502
  • 财政年份:
    2003
  • 资助金额:
    $ 32.37万
  • 项目类别:
VARIABILITY AND STABILITY IN SKILL ACQUISITION
技能习得的可变性和稳定性
  • 批准号:
    7027060
  • 财政年份:
    2003
  • 资助金额:
    $ 32.37万
  • 项目类别:

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