Jalaleddini Kian, Minos Niu Chuanxin, Chakravarthi Raja Suraj, Joon Sohn Won, Loeb Gerald E, Sanger Terence D, Valero-Cuevas Francisco J
Division of Biokinesiology and Physical Therapy, University of Southern California, CA, United States of America.
J Neural Eng. 2017 Apr;14(2):025002. doi: 10.1088/1741-2552/aa59bd. Epub 2017 Jan 17.
We studied the fundamentals of muscle afferentation by building a Neuro-mechano-morphic system actuating a cadaveric finger. This system is a faithful implementation of the stretch reflex circuitry. It allowed the systematic exploration of the effects of different fusimotor drives to the muscle spindle on the closed-loop stretch reflex response.
As in Part I of this work, sensory neurons conveyed proprioceptive information from muscle spindles (with static and dynamic fusimotor drive) to populations of α-motor neurons (with recruitment and rate coding properties). The motor commands were transformed into tendon forces by a Hill-type muscle model (with activation-contraction dynamics) via brushless DC motors. Two independent afferented muscles emulated the forces of flexor digitorum profundus and the extensor indicis proprius muscles, forming an antagonist pair at the metacarpophalangeal joint of a cadaveric index finger. We measured the physical response to repetitions of bi-directional ramp-and-hold rotational perturbations for 81 combinations of static and dynamic fusimotor drives, across four ramp velocities, and three levels of constant cortical drive to the α-motor neuron pool.
We found that this system produced responses compatible with the physiological literature. Fusimotor and cortical drives had nonlinear effects on the reflex forces. In particular, only cortical drive affected the sensitivity of reflex forces to static fusimotor drive. In contrast, both static fusimotor and cortical drives reduced the sensitivity to dynamic fusimotor drive. Interestingly, realistic signal-dependent motor noise emerged naturally in our system without having been explicitly modeled.
We demonstrate that these fundamental features of spinal afferentation sufficed to produce muscle function. As such, our Neuro-mechano-morphic system is a viable platform to study the spinal mechanisms for healthy muscle function-and its pathologies such as dystonia and spasticity. In addition, it is a working prototype of a robust biomorphic controller for compliant robotic limbs and exoskeletons.
我们通过构建一个驱动尸体手指的神经机械形态系统来研究肌肉传入的基本原理。该系统是牵张反射回路的忠实实现。它允许系统地探索不同的肌梭运动驱动对闭环牵张反射反应的影响。
与本研究的第一部分一样,感觉神经元将来自肌梭的本体感觉信息(具有静态和动态肌梭运动驱动)传递给α运动神经元群体(具有募集和速率编码特性)。运动指令通过无刷直流电机由希尔型肌肉模型(具有激活-收缩动力学)转换为肌腱力。两块独立的传入肌肉模拟了指深屈肌和示指固有伸肌的力量,在尸体示指的掌指关节处形成一对拮抗肌。我们测量了在四个斜坡速度和三个恒定皮质驱动水平下,针对81种静态和动态肌梭运动驱动组合的双向斜坡-保持旋转扰动重复的物理反应。
我们发现该系统产生的反应与生理学文献一致。肌梭运动和皮质驱动对反射力有非线性影响。特别是,只有皮质驱动影响反射力对静态肌梭运动驱动的敏感性。相比之下,静态肌梭运动和皮质驱动都降低了对动态肌梭运动驱动的敏感性。有趣的是,逼真的信号依赖型运动噪声在我们的系统中自然出现,而无需明确建模。
我们证明了脊髓传入的这些基本特征足以产生肌肉功能。因此,我们的神经机械形态系统是研究健康肌肉功能的脊髓机制及其诸如肌张力障碍和痉挛等病理状况的可行平台。此外,它是用于柔顺机器人肢体和外骨骼的强大生物形态控制器的工作原型。