Foot placement relies on state estimation during visually guided walking
Foot placement relies on state estimation during visually guided walking
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DOI：
10.1152/jn.00015.2016
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发表时间：
2017-02-01
影响因子：
2.5
通讯作者：
Marigold, Daniel S.
中科院分区：
文献类型：
--
作者：
Maeda, Rodrigo S.;O'Connor, Shawn M.;Marigold, Daniel S.
当我们走路时，我们必须准确地放置我们的脚来稳定我们的运动和导航我们的环境。我们也必须达到这种精度，尽管不完美的感官反馈和意外干扰。在这项研究中，我们测试了神经系统是否使用状态估计来有益地将感觉反馈与前向模型预测相结合，以补偿这些挑战。具体来说，受试者在视觉引导的行走任务中佩戴棱镜镜片，我们使用棱镜镜片的一次又一次变化来增加视觉反馈的不确定性，并诱导该输入的重新加权。为了暴露改变的权重，我们增加了一个一致的棱镜位移，要求受试者调整他们对感知到的目标位置和步到该位置所需的运动命令之间的视觉运动映射关系的估计。在增加棱镜噪声的情况下，受试者对棱镜位移的反应具有较小的初始脚位误差，但需要更长的时间来适应，这与我们利用状态估计来补偿噪声的步行任务数学模型相一致。就像我们用手臂进行自主和离散的运动一样，我们的神经系统似乎在走路时使用状态估计来准确地将脚伸向地面。新的和值得注意的准确的脚的位置是必不可少的安全行走。我们使用计算模型和人类行走实验来测试我们的神经系统是如何达到这种准确性的。我们发现，我们对脚位置的控制将感官反馈与内部前向模型预测相结合，可以准确地估计身体的状态。我们的研究结果与最近的计算神经科学研究结果一致，表明状态估计是人类运动控制的一般机制。
As we walk, we must accurately place our feet to stabilize our motion and to navigate our environment. We must also achieve this accuracy despite imperfect sensory feedback and unexpected disturbances. In this study we tested whether the nervous system uses state estimation to beneficially combine sensory feedback with forward model predictions to compensate for these challenges. Specifically, subjects wore prism lenses during a visually guided walking task, and we used trial-by-trial variation in prism lenses to add uncertainty to visual feedback and induce a reweighting of this input. To expose altered weighting, we added a consistent prism shift that required subjects to adapt their estimate of the visuomotor mapping relationship between a perceived target location and the motor command necessary to step to that position. With added prism noise, subjects responded to the consistent prism shift with smaller initial foot placement error but took longer to adapt, compatible with our mathematical model of the walking task that leverages state estimation to compensate for noise. Much like when we perform voluntary and discrete movements with our arms, it appears our nervous systems uses state estimation during walking to accurately reach our foot to the ground.NEW & NOTEWORTHY Accurate foot placement is essential for safe walking. We used computational models and human walking experiments to test how our nervous system achieves this accuracy. We find that our control of foot placement beneficially combines sensory feedback with internal forward model predictions to accurately estimate the body's state. Our results match recent computational neuroscience findings for reaching movements, suggesting that state estimation is a general mechanism of human motor control.