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平滑度最大化运动策略的获取与实施取决于空间精度要求。

The acquisition and implementation of the smoothness maximization motion strategy is dependent on spatial accuracy demands.

作者信息

Sosnik Ronen, Flash Tamar, Hauptmann Bjoern, Karni Avi

机构信息

Weizmann Institute of Science, Rehovot 71600, Israel.

出版信息

Exp Brain Res. 2007 Jan;176(2):311-31. doi: 10.1007/s00221-006-0617-1.

Abstract

We recently showed that extensive training on a sequence of planar hand trajectories passing through several targets resulted in the co-articulation of movement components and in the formation of new movement elements (primitives) (Sosnik et al. in Exp Brain Res 156(4):422-438, 2004). Reduction in movement duration was accompanied by the gradual replacing of a piecewise combination of rectilinear trajectories with a single, longer curved one, the latter affording the maximization of movement smoothness ("global motion planning"). The results from transfer experiments, conducted by the end of the last training session, have suggested that the participants have acquired movement elements whose attributes were solely dictated by the figural (i.e., geometrical) form of the path, rather than by both path geometry and its time derivatives. Here we show that the acquired movement generation strategy ("global motion planning") was not specific to the trained configuration or total movement duration. Performance gain (i.e., movement smoothness, defined by the fit of the data to the behavior, predicted by the "global planning" model) transferred to non-trained configurations in which the targets were spatially co-aligned or when participants were instructed to perform the task in a definite amount of time. Surprisingly, stringent accuracy demands, in transfer conditions, resulted not only in an increased movement duration but also in reverting to the straight trajectories (loss of co-articulation), implying that the performance gain was dependent on accuracy constraints. Only 28.5% of the participants (two out of seven) who were trained in the absence of visual feedback from the hand (dark condition) co-articulated by the end of the last training session compared to 75% (six out of eight) who were trained in the light, and none of them has acquired a geometrical motion primitive. Furthermore, six naive participants who trained in dark condition on large size targets have all co-articulated by the end of the last training session, still, none of them has acquired a geometrical motion primitive. Taken together, our results indicate that the acquisition of a geometrical motion primitive is dependent on the existence of visual feedback from the hand and that the implementation of the smoothness-maximization motion strategy is dependent on spatial accuracy demands. These findings imply that the specific features of the training experience (i.e., temporal or spatial task demands) determine the attributes of an acquired motion planning strategy and primitive.

摘要

我们最近的研究表明,对一系列穿过多个目标的平面手部轨迹进行大量训练,会导致运动成分的协同发音以及新运动元素(基元)的形成(Sosnik等人,《实验脑研究》,2004年,第156卷第4期,第422 - 438页)。运动持续时间的缩短伴随着用一条更长的单一曲线轨迹逐渐取代直线轨迹的分段组合,后者能使运动平滑度最大化(“全局运动规划”)。在最后一次训练结束时进行的迁移实验结果表明,参与者获得了运动元素,这些元素的属性仅由路径的图形(即几何)形式决定,而非由路径几何形状及其时间导数共同决定。在此我们表明,所获得的运动生成策略(“全局运动规划”)并非特定于训练的构型或总运动持续时间。性能提升(即运动平滑度,由数据与“全局规划”模型预测的行为拟合度定义)转移到了目标在空间上共线的未训练构型,或者当参与者被指示在一定时间内完成任务时。令人惊讶的是,在迁移条件下,严格的准确性要求不仅导致运动持续时间增加,还导致回归到直线轨迹(协同发音丧失),这意味着性能提升取决于准确性约束。在没有手部视觉反馈(黑暗条件)下接受训练的参与者中,只有28.5%(七人中有两人)在最后一次训练结束时实现了协同发音,相比之下,在有光照条件下训练的参与者中有75%(八人中有六人)实现了协同发音,而且他们中没有人获得几何运动基元。此外,在黑暗条件下对大尺寸目标进行训练的六名新手参与者在最后一次训练结束时都实现了协同发音,但他们中也没有人获得几何运动基元。综上所述,我们的结果表明,几何运动基元的获得依赖于手部视觉反馈的存在,而平滑度最大化运动策略的实施依赖于空间准确性要求。这些发现意味着训练经验的特定特征(即时间或空间任务要求)决定了所获得的运动规划策略和基元的属性。

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