Influence of Task Complexity and Sensory Feedback on Cortical Control of Grasp Force

摘要 在像挥动网球拍这样复杂而动态的动作中，人类可以熟练地控制自己的抓握， 就像拿着公文包一样简单和静态。这两项任务都需要使用感觉反馈来实现 并保持适当的抓地力。有证据表明，运动和躯体感觉皮质 交流与任务相关的信息，以实现熟练的移动。我们的首要目标是发现 抓握力控制背后的运动皮质动力学，并决定这些动力学的程度 由躯体感觉反馈的行为背景和皮质交流所介导。 我们建议利用独特的实验范式来研究抓握的皮层控制。 四肢瘫痪患者大脑皮质内的双向人脑-计算机接口研究 植入运动和体感皮质的电极阵列。以前的工作，主要集中在 运动，已经证明了运动皮质表现出的种群动态受低- 空间流形。我们已经在人类运动皮质中发现了类似的动态反应，其中包含 关于抓取力的信息。但是，这些响应依赖于任务，并且可以随着 上臂近端运动的复杂性发生变化。在这里，我们将扩展这项工作，以研究上下文- 一系列静态和动态手部和手臂运动对M1动力学的依赖 公开和隐蔽的(即想象的)行为。 复杂的运动控制依赖于感觉信息来塑造从运动发出的神经控制信号 大脑皮层，但对控制的信息从躯体感觉到运动皮质的流动知之甚少 那只手的。我们的目标是量化一系列任务背景下的大脑皮层交流路径 通过对运动和躯体感觉皮层同步神经记录的分析。然后我们将使用 皮层内微刺激在提供任务相关感觉的同时探测这些通讯通路 反馈以及与任务无关的刺激作为对照。最后，我们将使用脑机接口来 测试皮质通讯回路内是否有可塑性的可能性，或者 通信受到区域间动态的限制。成功完成这项提案将导致 对M1在动态和静态抓取行为中的作用的新认识。我们将量化如何 躯体感觉输入与M1的沟通以及皮质沟通通路是否可以 通过训练进行修改，这与理解技能学习和提高康复水平有关。

ABSTRACT Humans can skillfully control their grasp during actions as complex and dynamic as swinging a tennis racket, and as simple and static as holding a briefcase. Both tasks require the use of sensory feedback to achieve and maintain an appropriate grasp force. There is evidence that motor and somatosensory cortices communicate task-relevant information in order to enable skillful movement. Our primary goal is to uncover the motor cortical dynamics underlying grasp force control and determine the extent to which these dynamics are mediated by behavioral context and corticocortical communication of somatosensory feedback. We propose to study the cortical control of grasp by leveraging the unique experimental paradigms afforded by a bidirectional human brain-computer interface study in which participants with tetraplegia have intracortical electrode arrays implanted in motor and somatosensory cortex. Previous work, primarily focused on reaching movements, has demonstrated that motor cortex exhibits population dynamics that are constrained within low- dimensional manifold. We have identified similar dynamic responses within human motor cortex that contain information about grasp force. However, these responses are task-dependent and can change as the complexity of the proximal arm movement changes. Here we will extend that work to study the context- dependence of M1 dynamics across a range of static and dynamic hand and arm movements including both overt and covert (i.e., imagined) behaviors. Sophisticated motor control relies on sensory information to shape neural control signals emanating from motor cortex, yet very little is known about the flow of information from somatosensory to motor cortex for the control of the hand. We aim to quantify the corticocortical communication pathways across a range of task contexts through the analysis of simultaneous neural recordings in motor and somatosensory cortex. We will then use intracortical microstimulation to probe these communication pathways while providing task-relevant sensory feedback as well as task-irrelevant stimulation as a control. Finally, we will use a brain-computer interface to test whether there is the potential for plasticity within the corticocortical communication circuits, or whether communication is constrained by between-area dynamics. Successful completion of this proposal will lead to new knowledge about the role of M1 in dynamic and static grasp behaviors. We will quantify how somatosensory input is communicated with M1 and whether corticocortical communication pathways can be modified through training, which has relevance to understanding skill learning and improving rehabilitation.