Somatosensory inputs for arm control

生物马达控制的理论通常始于这样一种观点，即马达行为趋向于最佳性能，一般来说，这种优化标准在重现各种各样的发现方面非常成功。沿着这些思路，一种有影响力的方案是基于最优反馈控制。简而言之，应用于生物马达控制的想法是，马达命令是基于身体的状态和描述所执行行为的性能标准的成本函数来计算的(例如，在达到目标的同时惩罚能量消耗)。最终的结果是，神经系统通过调整反馈控制回路的增益，随着时间的推移和作为行为任务的函数，创造出目标导向的运动行为。因此，在这个框架下，了解神经系统如何处理感觉反馈对于理解运动的控制至关重要。我们的长期目标是确定最快的反馈环路(即通常称为伸展反射)的功能能力和神经组织，这些环路将肌肉和皮肤的感觉输入与现实世界的行为联系起来，如伸手、抓取和物体操纵。我的实验室从各个方面对这一重要的长期目标进行了攻击，包括理论工作、行为研究以及对人类和非人类灵长类动物的详细生理调查。这项建议中提出的工作重点是确定最优反馈控制框架下的中心成本函数的性质，特别是最小干预原则，这是最优反馈控制的基本预测。最小干预原则规定，只有最终影响任务成功的错误(由成本函数定义)才应得到纠正。不应该纠正最终不会影响任务成功的错误，因为在有噪音的情况下这样做实际上可能会引入错误，从而影响任务成功。因此，我们的短期目标是(1)详细说明在人体手臂姿势控制的背景下适用于体感反馈环的成本函数和潜在的神经机制，特别是那些通过脊髓电路产生的最快反应，以及(2)确定当接触到新的成本函数时，体感反馈环如何随着经验和学习的变化而变化。这项工作很重要，因为在自愿运动控制的背景下，相对于相关过程，人们对确定上肢伸展反射反应是如何根据任务要求进行调整并根据经验进行修改的了解很少。这可能会产生非常大的影响，因为我们的最新发现表明，在这方面，脊髓回路的能力迄今尚不清楚，我们现在将首先详细阐述这一点。

Theories of biological motor control often start from the view that motor behaviour tends towards optimal performance and, in general, such optimization criteria are extremely successful at reproducing a wide variety of findings. One influential scheme along these lines is based on optimal feedback control. Briefly, as applied to biological motor control the idea is that motor commands are computed based on the state of the body and a cost-function that describes the performance criteria of the behaviour being executed (e.g. reach the target while penalizing energy expenditure). The net result is that the nervous system creates goal-directed motor behaviour by adjusting the gains of feedback control loops over time and as a function of the behavioural task. Thus, under this framework, understanding how the nervous system processes sensory feedback is critical to understanding the control of movement. Our long-term objective is determining the functional capacity and neural organization of the fastest feedback loops (i.e. usually called stretch reflexes) that link sensory inputs from the muscles and skin to real-world behaviours like reaching, grasping, and object manipulation. My lab attacks this important long-term objective from all fronts including theoretical work, behavioural studies and detailed physiological investigations in humans and non-human primates. The work proposed in this proposal focuses on establishing the nature of the cost functions central under the optimal feedback control framework and specifically the minimum intervention principle, which is a fundamental prediction of optimal feedback control. The minimum intervention principle states that only errors that ultimately influence task success (as defined by the cost function) should be corrected. Errors that don't ultimately influence task success should not be corrected because doing so in the presence of noise may actually introduce errors that do influence task success. Thus, our short-term objectives, are to (1) detail the cost functions and underlying neural mechanisms that apply to somatosensory feedback loops in the context of postural control of the human arm, especially those fastest responses generated via circuits in the spinal cord, and (2) determine how the somatosensory feedback loops change with experience and learning when exposed to new cost functions. This work is important because determining how upper-limb stretch reflex responses are adjusted to task-demands and modified with experience is poorly understood relative to related processes in the context of voluntary motor control. It is likely to be of very high impact because our most recent findings suggest a hitherto unknown capacity of spinal circuits in this regard that we will now be the first to elaborate in detail.