Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, CB2 1PZ, UK.
Curr Biol. 2010 Oct 12;20(19):1763-7. doi: 10.1016/j.cub.2010.08.049. Epub 2010 Sep 16.
Modern theories of motor control incorporate forward models that combine sensory information and motor commands to predict future sensory states. Such models circumvent unavoidable neural delays associated with on-line feedback control. Here we show that signals in human muscle spindle afferents during unconstrained wrist and finger movements predict future kinematic states of their parent muscle. Specifically, we show that the discharges of type Ia afferents are best correlated with the velocity of length changes in their parent muscles approximately 100-160 ms in the future and that their discharges vary depending on motor sequences in a way that cannot be explained by the state of their parent muscle alone. We therefore conclude that muscle spindles can act as "forward sensory models": they are affected both by the current state of their parent muscle and by efferent (fusimotor) control, and their discharges represent future kinematic states. If this conjecture is correct, then sensorimotor learning implies learning how to control not only the skeletal muscles but also the fusimotor system.
现代运动控制理论包含了前向模型,该模型结合了感觉信息和运动指令,以预测未来的感觉状态。这种模型避免了与在线反馈控制相关的不可避免的神经延迟。在这里,我们表明,在不受约束的手腕和手指运动期间,人类肌梭传入神经的信号可以预测其母体肌肉的未来运动状态。具体来说,我们表明,Ia 型传入神经的放电与它们母体肌肉长度变化的速度最相关,大约在未来 100-160 毫秒,并且它们的放电根据运动序列而变化,这种变化不能仅用它们母体肌肉的状态来解释。因此,我们得出结论,肌梭可以作为“前向感觉模型”:它们既受到母体肌肉当前状态的影响,也受到传出(梭内肌)控制的影响,它们的放电代表未来的运动状态。如果这个假设是正确的,那么感觉运动学习意味着不仅要学习如何控制骨骼肌,还要学习如何控制梭内肌系统。