Centre for Neuroscience Studies, Queen's University, Kingston, Canada.
PLoS Comput Biol. 2013;9(8):e1003177. doi: 10.1371/journal.pcbi.1003177. Epub 2013 Aug 15.
In every motor task, our brain must handle external forces acting on the body. For example, riding a bike on cobblestones or skating on irregular surface requires us to appropriately respond to external perturbations. In these situations, motor predictions cannot help anticipate the motion of the body induced by external factors, and direct use of delayed sensory feedback will tend to generate instability. Here, we show that to solve this problem the motor system uses a rapid sensory prediction to correct the estimated state of the limb. We used a postural task with mechanical perturbations to address whether sensory predictions were engaged in upper-limb corrective movements. Subjects altered their initial motor response in ∼60 ms, depending on the expected perturbation profile, suggesting the use of an internal model, or prior, in this corrective process. Further, we found trial-to-trial changes in corrective responses indicating a rapid update of these perturbation priors. We used a computational model based on Kalman filtering to show that the response modulation was compatible with a rapid correction of the estimated state engaged in the feedback response. Such a process may allow us to handle external disturbances encountered in virtually every physical activity, which is likely an important feature of skilled motor behaviour.
在每一个运动任务中,我们的大脑必须处理作用于身体的外力。例如,在鹅卵石上骑自行车或在不规则表面滑冰,要求我们对外部干扰做出适当的反应。在这些情况下,运动预测无法帮助预测身体在外力作用下的运动,而直接使用延迟的感觉反馈往往会导致不稳定。在这里,我们表明,为了解决这个问题,运动系统使用快速的感觉预测来校正肢体的估计状态。我们使用带有机械干扰的姿势任务来解决感觉预测是否参与上肢校正运动。根据预期的扰动轮廓,受试者在大约 60 毫秒内改变了他们的初始运动反应,这表明在这个校正过程中使用了内部模型或先验信息。此外,我们发现校正反应中的试验间变化表明这些扰动先验信息的快速更新。我们使用基于卡尔曼滤波的计算模型表明,响应调制与反馈响应中参与的估计状态的快速校正兼容。这样的过程可能使我们能够处理在几乎每一项体育活动中遇到的外部干扰,这可能是熟练运动行为的一个重要特征。