Département de Neurosciences, Université de Montréal, Montreal, Quebec, Canada.
J Neurophysiol. 2021 Apr 1;125(4):1022-1045. doi: 10.1152/jn.00688.2019. Epub 2021 Jan 27.
Studies of reach control with the body stationary have shown that proprioceptive and visual feedback signals contributing to rapid corrections during reaching are processed by neural circuits that incorporate knowledge about the physical properties of the limb (an internal model). However, among the most common spatial and mechanical perturbations to the limb are those caused by our body's own motion, suggesting that processing of vestibular signals for online reach control may reflect a similar level of sophistication. We investigated this hypothesis using galvanic vestibular stimulation (GVS) to selectively activate the vestibular sensors, simulating body rotation, as human subjects reached to remembered targets in different directions (forward, leftward, rightward). If vestibular signals contribute to purely kinematic/spatial corrections for body motion, GVS should evoke reach trajectory deviations of similar size in all directions. In contrast, biomechanical modeling predicts that if vestibular processing for online reach control takes into account knowledge of the physical properties of the limb and the forces applied on it by body motion, then GVS should evoke trajectory deviations that are significantly larger during forward and leftward reaches as compared with rightward reaches. When GVS was applied during reaching, the observed deviations were on average consistent with this prediction. In contrast, when GVS was instead applied before reaching, evoked deviations were similar across directions, as predicted for a purely spatial correction mechanism. These results suggest that vestibular signals, like proprioceptive and visual feedback, are processed for online reach control via sophisticated neural mechanisms that incorporate knowledge of limb biomechanics. Studies examining proprioceptive and visual contributions to rapid corrections for externally applied mechanical and spatial perturbations during reaching have provided evidence for flexible processing of sensory feedback that accounts for musculoskeletal system dynamics. Notably, however, such perturbations commonly arise from our body's own motion. In line with this, we provide compelling evidence that, similar to proprioceptive and visual signals, vestibular signals are processed for online reach control via sophisticated mechanisms that incorporate knowledge of limb biomechanics.
对固定身体状态下的手臂运动控制的研究表明，在手臂运动过程中快速修正时所涉及的本体感觉和视觉反馈信号，是由包含肢体物理属性（内部模型）知识的神经回路来处理的。然而，肢体最常见的空间和力学扰动来自于我们身体自身的运动，这表明前庭信号处理用于在线手臂运动控制可能反映出类似的复杂程度。我们使用电流前庭刺激（GVS）来选择性地激活前庭传感器，模拟身体旋转，以此来研究这个假说，当人类被试朝着不同方向（向前、向左、向右）的记忆目标伸手时，前庭信号是否有助于对身体运动进行纯运动/空间修正。如果前庭信号有助于对身体运动进行纯运动/空间修正，那么 GVS 应该会在所有方向上引起相似大小的手臂运动轨迹偏差。相比之下，生物力学建模预测，如果在线手臂运动控制的前庭处理考虑到了肢体的物理属性以及身体运动施加在其上的力，那么 GVS 应该会在向前和向左伸手时引起明显大于向右伸手时的轨迹偏差。当 GVS 在伸手过程中施加时，观察到的偏差平均与该预测一致。相比之下，当 GVS 在伸手之前施加时，由于预测的是一种纯粹的空间修正机制，所以引起的偏差在各个方向上是相似的。这些结果表明，与本体感觉和视觉反馈一样，前庭信号也通过包含肢体生物力学知识的复杂神经机制来处理在线手臂运动控制。研究考察了对外加机械和空间扰动进行快速修正时本体感觉和视觉反馈的贡献，为考虑到肌肉骨骼系统动力学的灵活处理感官反馈提供了证据。值得注意的是，这些扰动通常来自于我们身体的自身运动。与这一观点一致的是，我们提供了令人信服的证据表明，与本体感觉和视觉信号一样，前庭信号也是通过包含肢体生物力学知识的复杂机制来处理在线手臂运动控制的。
