Dissociating variability and effort as determinants of coordination.
Dissociating variability and effort as determinants of coordination.
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DOI：
10.1371/journal.pcbi.1000345
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发表时间：
2009-04
影响因子：
4.3
通讯作者：
Diedrichsen J
中科院分区：
文献类型：
--
作者：
O'Sullivan I;Burdet E;Diedrichsen J
在协调运动时，神经系统通常必须决定如何在多个冗余的效应器之间分配工作。在这里，我们展示了人类通过试图最小化运动输出的可变性和所涉及的努力来解决这个问题。在以前研究运动的时间形状的研究中，这两种选择性压力尽管具有非常不同的理论含义，但无法区分；因为运动系统中的噪音随着运动指令的增加而增加，最大限度地减少努力或变异性会导致非常相似的预测。然而，当必须组合具有不同噪声和努力特性的多个效应器时，这两个成本项可以分离。在这里，我们通过研究人类如何在两个手指之间分享力量产生来衡量变异性和协调努力的重要性。为了捕捉变异性，我们确定了食指和小指的变异系数。对于作用力，我们使用平方作用力和由每个效应器的最大强度归一化的平方作用力总和。然后，这些术语被用来预测一项任务的最佳力分布，在这项任务中，参与者必须通过使用不同的手指组合按压两个等距传感器来产生4-16N的目标总力。通过将预测的手指分布与参与者选择的实际分布进行比较，我们能够估计1：7的可变性和努力的相对重要性，其中非标准化的努力是最重要的。我们的结果表明，神经系统使用多效应器冗余来最小化所产生的输出和努力的可变性，尽管努力成本明显大于可变性成本。当我们做动作时，我们通常有很多选择来组合肌肉或四肢以达到想要的结果。尽管有这种自由，某些效应器组合是一致使用的。为什么？为了检验这个问题，我们要求参与者同时用左手的一个手指按一个按钮，用右手的一个手指按另一个按钮。参与者的目标是产生一支与目标力量尽可能精确匹配的联合力量。不同的手指有不同的力量和噪音特征，这让我们能够检查参与者是否将两个手指结合在一起，以最大限度地减少总体努力或总体变异性。以前的研究无法将这两个因素分开，因为他们关注的是没有多个效应器冗余的运动，其中噪音总是随着力的增加而增加。在我们的简单方案中，我们表明受试者协调两个手指以最大限度地减少努力，但也减少变异性，比例为7：1。这一结果表明，神经系统通过同时考虑努力和噪音信息来学习协调不同的肌肉或肢体。这些结果对于理解大脑如何在受伤或中风后重新学习协调运动具有重要意义。
When coordinating movements, the nervous system often has to decide how to distribute work across a number of redundant effectors. Here, we show that humans solve this problem by trying to minimize both the variability of motor output and the effort involved. In previous studies that investigated the temporal shape of movements, these two selective pressures, despite having very different theoretical implications, could not be distinguished; because noise in the motor system increases with the motor commands, minimization of effort or variability leads to very similar predictions. When multiple effectors with different noise and effort characteristics have to be combined, however, these two cost terms can be dissociated. Here, we measure the importance of variability and effort in coordination by studying how humans share force production between two fingers. To capture variability, we identified the coefficient of variation of the index and little fingers. For effort, we used the sum of squared forces and the sum of squared forces normalized by the maximum strength of each effector. These terms were then used to predict the optimal force distribution for a task in which participants had to produce a target total force of 4–16 N, by pressing onto two isometric transducers using different combinations of fingers. By comparing the predicted distribution across fingers to the actual distribution chosen by participants, we were able to estimate the relative importance of variability and effort of 1∶7, with the unnormalized effort being most important. Our results indicate that the nervous system uses multi-effector redundancy to minimize both the variability of the produced output and effort, although effort costs clearly outweighed variability costs. When performing actions, we often have many options of how to combine muscles or limbs to achieve a desired outcome. Despite this freedom, certain effector combinations are used consistently. Why? To examine this question, we asked participants to press one button with a finger from the left hand and another button with a finger from the right hand simultaneously. Participants' goal was to generate a combined force that would match a target force as accurately as possible. Different fingers have distinct strength and noise characteristics, allowing us to examine if participants combined the two fingers to minimize the overall effort or the overall variability. Prior studies have been unable to dissociate these two factors, because they have focused on movements without multi-effector redundancy, where noise always increases with increasing levels of force. With our simple protocol, we show that subjects coordinate the two fingers to minimize mainly effort, but also variability, in a proportion of 7∶1. This result suggests that the nervous system learns to coordinate different muscles or limbs by considering both effort and noise information simultaneously. These results have important implications for understanding how the brain relearns to coordinate movements following injury or stroke.
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影响因子：
64.8
作者：
Harris, CM;Wolpert, DM
通讯作者：
Wolpert, DM
影响因子：
64.8
作者：
Burdet, E;Osu, R;Kawato, M
通讯作者：
Kawato, M
影响因子：
25
作者：
Todorov, E;Jordan, MI
通讯作者：
Jordan, MI
影响因子：
2.5
作者：
Fagg, AH;Shah, A;Barto, AG
通讯作者：
Barto, AG
DOI：
10.1115/1.2796044
发表时间：
1996-11-01
影响因子：
1.7
作者：
Buchanan, TS;Shreeve, DA
通讯作者：
Shreeve, DA