Biomedical Engineering, Marquette University, Milwaukee, Wisconsin;
J Neurophysiol. 2014 Feb;111(4):868-87. doi: 10.1152/jn.00314.2012. Epub 2013 Nov 20.
We examined whether visual and proprioceptive estimates of transient (midreach) target capture errors contribute to motor adaptation according to the probabilistic rules of information integration used for perception. Healthy adult humans grasped and moved a robotic handle between targets in the horizontal plane while the robot generated springlike loads that varied unpredictably from trial to trial. For some trials, a visual cursor faithfully tracked hand motion. In others, the handle's position was locked and subjects viewed motion of a point-mass cursor driven by hand forces. In yet other trials, cursor feedback was dissociated from hand motion or altogether eliminated. We used time- and frequency-domain analyses to characterize how sensorimotor memories influence performance on subsequent reaches. When the senses were used separately, subjects were better at rejecting physical disturbances applied to the hand than virtual disturbances applied to the cursor. In part, this observation reflected differences in how participants used sensorimotor memories to adapt to perturbations when performance feedback was limited to only proprioceptive or visual information channels. When both vision and proprioception were available to guide movement, subjects processed memories in a manner indistinguishable from the vision-only condition, regardless of whether the cursor tracked the hand faithfully or whether we experimentally dissociated motions of the hand and cursor. This was true even though, on average, perceptual uncertainty in the proprioceptive estimation of movement extent exceeded that of visual estimation by just 47%. In contrast to perceptual tasks wherein vision and proprioception both contribute to an optimal estimate of limb state, our findings support a switched-input, multisensory model of predictive load compensation wherein visual feedback of transient performance errors overwhelmingly dominates proprioception in determining adaptive reach performance.
我们考察了视觉和本体感觉对短暂（中途）目标捕获误差的估计是否根据用于感知的信息整合概率规则有助于运动适应。健康的成年人类在水平平面上抓取和移动机器人手柄，同时机器人产生的弹簧力从一次试验到另一次试验不可预测地变化。对于一些试验，视觉光标忠实地跟踪手部运动。在其他试验中，手柄的位置被锁定，并且受试者观察由手部力驱动的质点光标运动。在其他试验中，光标反馈与手部运动分离或完全消除。我们使用时域和频域分析来描述感觉运动记忆如何影响后续到达的性能。当单独使用感官时，受试者在拒绝施加到手部的物理干扰方面比施加到光标上的虚拟干扰更好。部分观察结果反映了参与者在仅使用本体感觉或视觉信息通道提供性能反馈时，如何使用感觉运动记忆来适应扰动的差异。当视觉和本体感觉都可用于引导运动时，无论光标是否忠实地跟踪手部，或者我们是否实验性地分离手部和光标运动，受试者以与仅视觉条件不可区分的方式处理记忆。即使在本体感觉对运动幅度的估计的感知不确定性平均仅比视觉估计高出 47%的情况下，也是如此。与视觉和本体感觉都有助于肢体状态的最佳估计的感知任务相反，我们的研究结果支持了一种切换输入、多感觉预测负载补偿模型，其中对瞬态性能误差的视觉反馈在确定自适应到达性能方面极大地主导本体感觉。
