Haggerty S E, Wu A R, Sienko K H, Kuo A D
Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan; and.
Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan.
J Neurophysiol. 2017 Aug 1;118(2):894-903. doi: 10.1152/jn.00428.2016. Epub 2017 Apr 26.
Control of standing posture requires fusion of multiple inputs including visual, vestibular, somatosensory, and other sensors, each having distinct dynamics. The semicircular canals, for example, have a unique high-pass filter response to angular velocity, quickly sensing a step change in head rotational velocity followed by a decay. To stabilize gaze direction despite this decay, the central nervous system supplies a neural "velocity storage" integrator, a filter that extends the angular velocity signal. Similar filtering might contribute temporal dynamics to posture control, as suggested by some state estimation models. However, such filtering has not been tested explicitly. We propose that posture control indeed entails a neural integrator for sensory inputs, and we test its behavior with classic sensory perturbations: a rotating optokinetic stimulus to the visual system and a galvanic vestibular stimulus to the vestibular system. A simple model illustrates how these two inputs and body tilt sensors might produce a postural tilt response in the frontal plane. The model integrates these signals through a direct weighted sum of inputs, with or without an indirect pathway containing a neural integrator. Comparison with experimental data from healthy adult subjects ( = 16) reveals that the direct weighting model alone is insufficient to explain resulting postural transients, as measured by lateral tilt of the trunk. In contrast, the neural integrator, shared by sensory signals, produces the dynamics of both optokinetic and galvanic vestibular responses. These results suggest that posture control may involve both direct and indirect pathways, which filter sensory signals and make them compatible for sensory fusion. Control of standing posture requires fusion of multiple inputs including visual, vestibular, somatosensory, and other sensors, each having distinct dynamics. We propose that postural control also entails a shared neural integrator. To test this theory, we perturbed standing subjects with classic sensory stimuli (optokinetic and galvanic vestibular stimulation) and found that our proposed shared filter reproduces the dynamics of subjects' postural responses.
站立姿势的控制需要融合多种输入信息，包括视觉、前庭、躯体感觉和其他传感器信息，每种信息都有独特的动态特性。例如，半规管对角速度具有独特的高通滤波器响应，能快速感知头部旋转速度的阶跃变化，随后信号衰减。为了在这种衰减情况下稳定注视方向，中枢神经系统提供了一个神经“速度存储”积分器，这是一种能扩展角速度信号的滤波器。正如一些状态估计模型所表明的，类似的滤波可能会为姿势控制贡献时间动态特性。然而，这种滤波尚未得到明确测试。我们提出姿势控制确实需要一个用于感觉输入的神经积分器，并通过经典的感觉扰动来测试其行为：对视觉系统施加旋转视动刺激，对前庭系统施加电刺激。一个简单的模型说明了这两种输入信息和身体倾斜传感器如何在额平面产生姿势倾斜反应。该模型通过输入的直接加权和来整合这些信号，有或没有包含神经积分器的间接通路。与健康成年受试者（(n = 16)）的实验数据比较表明，仅直接加权模型不足以解释所产生的姿势瞬态变化，如通过躯干侧倾测量的那样。相比之下，由感觉信号共享的神经积分器产生了视动和电刺激前庭反应的动态特性。这些结果表明，姿势控制可能涉及直接和间接通路，它们过滤感觉信号并使其适合感觉融合。站立姿势的控制需要融合多种输入信息，包括视觉、前庭、躯体感觉和其他传感器信息，每种信息都有独特的动态特性。我们提出姿势控制还需要一个共享的神经积分器。为了验证这一理论，我们用经典的感觉刺激（视动和电刺激前庭刺激）干扰站立的受试者，发现我们提出的共享滤波器再现了受试者姿势反应的动态特性。
