Ravaioli Elena, Oie Kelvin S, Kiemel Tim, Chiari Lorenzo, Jeka John J
Department of Kinesiology, University of Maryland, College Park, MD 20742-2611, USA.
Exp Brain Res. 2005 Jan;160(4):450-9. doi: 10.1007/s00221-004-2030-y. Epub 2004 Oct 9.
Recent models of human postural control have focused on the nonlinear properties inherent to fusing sensory information from multiple modalities. In general, these models are underconstrained, requiring additional experimental data to clarify the properties of such nonlinearities. Here we report an experiment suggesting that new or multiple mechanisms may be needed to capture the integration of vision into the postural control scheme. Subjects were presented with visual displays whose motion consisted of two components: a constant-amplitude, 0.2 Hz oscillation, and constant-velocity translation from left to right at velocities between 0 cm/s and 4 cm/s. Postural sway variability increased systematically with translation velocity, but remained below that observed in the eyes-closed condition, indicating that the postural control system is able to use visual information to stabilize sway even at translation velocities as high as 4 cm/s. Gain initially increased as translation velocity increased from 0 cm/s to 1 cm/s and then decreased. The changes in gain and variability provided a clear indication of nonlinearity in the postural response across conditions, which were interpreted in terms of sensory reweighting. The fact that gain did not decrease at low translation velocities suggests that the postural control system is able to decompose relative visual motion into environmental motion and self-motion. The eventual decrease in gain suggests that nonlinearities in sensory noise levels (state-dependent noise) may also contribute to the sensory reweighting involved in postural control. These results provide important constraints and suggest that multiple mechanisms may be required to model the nonlinearities involved in sensory fusion for upright stance control.
近期的人体姿势控制模型聚焦于融合多种模态感官信息所固有的非线性特性。总体而言,这些模型约束不足,需要更多实验数据来阐明此类非线性的特性。在此,我们报告一项实验,该实验表明可能需要新的或多种机制来捕捉视觉在姿势控制方案中的整合情况。向受试者展示视觉显示器,其运动由两个部分组成:振幅恒定的0.2赫兹振荡,以及以0厘米/秒至4厘米/秒的速度从左至右的匀速平移。姿势摆动变异性随平移速度系统性增加,但仍低于闭眼条件下观察到的值,这表明姿势控制系统即使在高达4厘米/秒的平移速度下也能够利用视觉信息来稳定摆动。增益最初随着平移速度从0厘米/秒增加到1厘米/秒而增加,然后下降。增益和变异性的变化清楚地表明了不同条件下姿势反应中的非线性,这可以从感官重新加权的角度来解释。增益在低平移速度下没有下降这一事实表明姿势控制系统能够将相对视觉运动分解为环境运动和自身运动。增益最终下降表明感官噪声水平的非线性(状态依赖噪声)也可能有助于姿势控制中涉及的感官重新加权。这些结果提供了重要的约束条件,并表明可能需要多种机制来模拟直立姿势控制中感官融合所涉及的非线性。