Neuromotor noise, error tolerance and velocity-dependent costs in skilled performance.
Neuromotor noise, error tolerance and velocity-dependent costs in skilled performance.
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DOI：
10.1371/journal.pcbi.1002159
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发表时间：
2011-09
影响因子：
4.3
通讯作者：
Müller H
中科院分区：
文献类型：
--
作者：
Sternad D;Abe MO;Hu X;Müller H
在具有冗余的运动任务中，神经运动噪声可以导致执行的变化，同时在结果中实现相对不变。目前的研究考察了人类是否能找到容忍内在噪音的解决方案。使用虚拟设置中的投掷任务，其中无限的角度和速度组合在球释放时产生投掷精度，我们的计算方法允许对容忍噪声的解决策略进行定量预测。基于任务的数学模型计算了期望结果，并提供了容错策略的预测（假设1）。由于策略可以采取大范围的速度，第二个假设是，受试者选择最小化释放速度的策略，以避免与信号或速度相关的噪音或更高的能量需求相关的成本（假设2）。两个针对不同目标星座的实验验证了这两个假设。实验1的结果显示，被试选择了容错度高的溶液，尽管这些溶液的速度也相对较低。这两个好处似乎超过了许多科目，这些解决方案接近高禁区，也就是说，它们是有风险的。实验2分离了这两个假设。结果表明，尽管个体的解分布在一定的速度范围内，但个体的解与假设1一致。额外的分析表明，不存在速度相关的可变性增加，这可能是由于存在以特定任务方式引导可变性的解决方案歧管。因此，对信号相关噪声的普遍接受可能需要一些限定条件。这些发现对于理解中枢神经系统如何处理其固有的神经运动噪声具有重要意义。人们普遍认为，变异性或噪声存在于感觉运动系统的各个层面。面对这种噪音，中枢神经系统如何以足够的准确度产生功能性行为仍然是一个悬而未决的问题。当运动任务是冗余的，即许多不同的执行可以实现相同的任务目标时，这一点尤为重要。通过实验控制投掷运动作为模型任务，我们研究了人类如何获得耐受固有噪声的运动策略。基于一种新的基于任务冗余分析的变异性分析计算方法，我们验证了两个假设：1)受试者对噪声敏感，并寻求容忍这种噪声的解决方案。2)受试者回避高速度的解决方案以及与高速度相关的成本。对两个实验中可变性分布特性的分析表明，人类选择那些最大限度地容错的策略。这些发现对中枢神经系统的基本认识和康复背景下的学习具有重要意义。
In motor tasks with redundancy neuromotor noise can lead to variations in execution while achieving relative invariance in the result. The present study examined whether humans find solutions that are tolerant to intrinsic noise. Using a throwing task in a virtual set-up where an infinite set of angle and velocity combinations at ball release yield throwing accuracy, our computational approach permitted quantitative predictions about solution strategies that are tolerant to noise. Based on a mathematical model of the task expected results were computed and provided predictions about error-tolerant strategies (Hypothesis 1). As strategies can take on a large range of velocities, a second hypothesis was that subjects select strategies that minimize velocity at release to avoid costs associated with signal- or velocity-dependent noise or higher energy demands (Hypothesis 2). Two experiments with different target constellations tested these two hypotheses. Results of Experiment 1 showed that subjects chose solutions with high error-tolerance, although these solutions also had relatively low velocity. These two benefits seemed to outweigh that for many subjects these solutions were close to a high-penalty area, i.e. they were risky. Experiment 2 dissociated the two hypotheses. Results showed that individuals were consistent with Hypothesis 1 although their solutions were distributed over a range of velocities. Additional analyses revealed that a velocity-dependent increase in variability was absent, probably due to the presence of a solution manifold that channeled variability in a task-specific manner. Hence, the general acceptance of signal-dependent noise may need some qualification. These findings have significance for the fundamental understanding of how the central nervous system deals with its inherent neuromotor noise. It is widely recognized that variability or noise is present at all levels of the sensorimotor system. How the central nervous system generates functional behavior with a sufficient degree of accuracy in the face of this noise remains an open question. This is specifically relevant when the motor task is redundant, i.e., where many different executions can achieve the same task goal. Using an experimentally controlled throwing movement as model task we examined how humans acquire movement strategies that are tolerant to intrinsic noise. Based on a new computational approach that parses variability based on an analysis of task redundancy, we tested two hypotheses: 1) Subjects are sensitive to noise and seek solutions that are tolerant to this noise. 2) Subjects avoid solutions with high velocities and the costs associated with high velocities. Analysis of the distributional properties of variability in two experiments revealed that humans select those strategies that maximize error-tolerance. These findings have significance for fundamental understanding of the central nervous system and for learning in the context of rehabilitation.
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影响因子：
2.5
作者：
Jones, KE;Hamilton, AFD;Wolpert, DM
通讯作者：
Wolpert, DM
影响因子：
64.8
作者：
Harris, CM;Wolpert, DM
通讯作者：
Wolpert, DM
影响因子：
2
作者：
Cohen, R. G.;Sternad, D.
通讯作者：
Sternad, D.
DOI：
10.1037/0096-1523.30.1.212
发表时间：
2004-02-01
影响因子：
2.1
作者：
Müller, H;Sternad, D
通讯作者：
Sternad, D
影响因子：
1.4
作者：
Kudo, K;Ito, T;Ishikura, T
通讯作者：
Ishikura, T