Human Movement Laboratory (CSAM), Fondazione Salvatore Maugeri (IRCCS), Scientific Institute of Pavia, Italy.
Hum Mov Sci. 2011 Apr;30(2):262-78. doi: 10.1016/j.humov.2011.02.002. Epub 2011 Mar 25.
We investigated the adaptation of balancing behavior during a continuous, predictable perturbation of stance consisting of 3-min backward and forward horizontal sinusoidal oscillations of the support base. Two visual conditions (eyes-open, EO; eyes-closed, EC) and two oscillation frequencies (LF, 0.2 Hz; HF, 0.6 Hz) were used. Center of Mass (CoM) and Center of Pressure (CoP) oscillations and EMG of Soleus (Sol) and Tibialis Anterior (TA) were recorded. The time course of each variable was estimated through an exponential model. An adaptation index allowed comparison of the degree of adaptation of different variables. Muscle activity pattern was initially prominent under the more challenging conditions (HF, EC and EO; LF, EC) and diminished progressively to reach a steady state. At HF, the behavior of CoM and CoP was almost invariant. The time-constant of EMG adaptation was shorter for TA than for Sol. With EC, the adaptation index showed a larger decay in the TA than Sol activity at the end of the balancing trial, pointing to a different role of the two muscles in the adaptation process. At LF, CoM and CoP oscillations increased during the balancing trial to match the platform translations. This occurred regardless of the different EMG patterns under EO and EC. Contrary to CoM and CoP, the adaptation of the muscle activities had a similar time-course at both HF and LF, in spite of the two frequencies implying a different number of oscillation cycles. During adaptation, under critical balancing conditions (HF), postural muscle activity is tuned to that sufficient for keeping CoM within narrow limits. On the contrary, at LF, when vision permits, a similar decreasing pattern of muscle activity parallels a progressive increase in CoM oscillation amplitude, and the adaptive balancing behavior shifts from the initially reactive behavior to one of passive riding the platform. Adaptive balance control would rely on on-line computation of risk of falling and sensory inflow, while minimizing balance challenge and muscle effort. The results from this study contribute to the understanding of plasticity of the balance control mechanisms under posture-challenging conditions.
我们研究了在持续、可预测的姿势平衡干扰下的平衡行为适应，该干扰由支撑基础的 3 分钟向后和向前水平正弦摆动组成。使用了两种视觉条件（睁眼，EO；闭眼，EC）和两种摆动频率（LF，0.2 Hz；HF，0.6 Hz）。记录了重心（CoM）和压力中心（CoP）的摆动以及比目鱼肌（Sol）和胫骨前肌（TA）的肌电图。通过指数模型估计每个变量的时间过程。适应指数允许比较不同变量的适应程度。肌肉活动模式最初在更具挑战性的条件下（HF、EC 和 EO；LF、EC）突出，并逐渐减少以达到稳定状态。在 HF 下，CoM 和 CoP 的行为几乎不变。与 Sol 相比，TA 的肌电适应时间常数更短。在 EC 下，平衡试验结束时，TA 的适应指数显示出比 Sol 活动更大的衰减，这表明这两块肌肉在适应过程中扮演不同的角色。在 LF 下，CoM 和 CoP 的摆动在平衡试验中增加，以匹配平台的平移。这发生在 EO 和 EC 下不同的 EMG 模式下。与 CoM 和 CoP 相反，肌肉活动的适应具有相似的时间过程，尽管在 HF 和 LF 下，两种频率都暗示了不同数量的摆动周期。在适应过程中，在临界平衡条件（HF）下，姿势肌肉活动被调整为足以将 CoM 保持在狭窄范围内。相反，在 LF 下，当视觉允许时，肌肉活动的相似减少模式与 CoM 摆动幅度的逐渐增加平行，自适应平衡行为从最初的反应性行为转变为被动骑乘平台的行为。自适应平衡控制将依赖于对跌倒风险和感觉输入的在线计算，同时最小化平衡挑战和肌肉努力。这项研究的结果有助于理解在姿势挑战性条件下平衡控制机制的可塑性。
