Proprioceptive feedback is a critical component of voluntary movement planning and execution. Neuroprosthetic technologies aiming at restoring movement must interact with it to restore accurate motor control. Optimization and design of such technologies depends on the availability of quantitative insights into the neural dynamics of proprioceptive afferents during functional movements. However, recording proprioceptive neural activity during unconstrained movements in clinically relevant animal models presents formidable challenges. In this work, we developed a computational framework to estimate the spatiotemporal patterns of proprioceptive inputs to the cervical spinal cord during three-dimensional arm movements in monkeys. We extended a biomechanical model of the monkey arm with ex-vivo measurements, and combined it with models of mammalian group-Ia, Ib and II afferent fibers. We then used experimental recordings of arm kinematics and muscle activity of two monkeys performing a reaching and grasping task to estimate muscle stretches and forces with computational biomechanics. Finally, we projected the simulated proprioceptive firing rates onto the cervical spinal roots, thus obtaining spatiotemporal maps of spinal proprioceptive inputs during voluntary movements. Estimated maps show complex and markedly distinct patterns of neural activity for each of the fiber populations spanning the spinal cord rostro-caudally. Our results indicate that reproducing the proprioceptive information flow to the cervical spinal cord requires complex spatio-temporal modulation of each spinal root. Our model can support the design of neuroprosthetic technologies as well as in-silico investigations of the primate sensorimotor system.

中文翻译：

---

三维到达和抓握过程中颈脊髓的本体感受输入的时空图

本体感觉反馈是自愿运动计划和执行的重要组成部分。旨在恢复运动的神经修复技术必须与之交互以恢复精确的运动控制。此类技术的优化和设计取决于对功能性运动过程中本体感受传入神经动力学的定量认识。然而，在临床相关的动物模型中不受约束的运动过程中记录本体感受神经活动提出了巨大的挑战。在这项工作中，我们开发了一个计算框架，以估计猴子在三维手臂运动过程中颈脊髓的本体感受输入的时空模式。我们通过离体测量扩展了猴臂的生物力学模型，并将其与哺乳动物Ia，Ib和II类传入纤维模型结合起来。然后，我们使用实验性记录的两只猴子的手臂运动学和肌肉活动来执行伸手和抓紧任务，以通过计算生物力学估算肌肉的伸展和力量。最后，我们将模拟的本体感受射速投射到颈椎脊髓的根部，从而获得自愿运动过程中脊髓本体感受输入的时空图。估计的图显示了跨越尾状脊髓的每个纤维种群的神经活动的复杂且明显不同的模式。我们的结果表明，将本体感受信息流复制到颈脊髓需要对每个脊髓根部进行复杂的时空调制。