标题： 从抓握期间感觉运动皮层种群反应中解码手的运动学 显示英文标题

标题： Decoding hand kinematics from population responses in sensorimotor cortex during grasping

摘要： 手是一个由数十个自由度组成的复杂效应器，使我们能够灵活、精确且轻松地与物体交互。 在初级运动皮层（M1）和体感皮层（SC）中与灵巧手部动作相关的神经信号，受到的关注相比之下比与近端肢体控制相关的信号要少。 为了填补这一空白，我们训练三只猴子抓取大小、形状和方向不同的物体，同时追踪它们的手部姿势，并从M1和SC记录单单元活动。 然后，我们从这些区域的群体活动解码了30个关节的手部运动学。 我们发现，可以用少量的神经信号准确解码运动学，并且解码关节角度的性能高于解码关节角速度的性能，这与近端肢体解码器的结果相反。 我们得出结论，皮层信号可以用于脑机接口应用中的灵巧手控制，而且通过皮层内刺激可以利用SC中的姿势表示来闭合感觉运动环路。 显示英文摘要

摘要： The hand, a complex effector comprising dozens of degrees of freedom of movement, endows us with the ability to flexibly, precisely, and effortlessly interact with objects. The neural signals associated with dexterous hand movements in primary motor cortex (M1) and somatosensory cortex (SC) have received comparatively less attention than have those that are associated with proximal limb control. To fill this gap, we trained three monkeys to grasp objects varying in size, shape and orientation while tracking their hand postures and recording single-unit activity from M1 and SC. We then decoded their hand kinematics across 30 joints from population activity in these areas. We found that we could accurately decode kinematics with a small number of neural signals and that performance was higher for decoding joint angles than joint angular velocities, in contrast to what has been found with proximal limb decoders. We conclude that cortical signals can be used for dexterous hand control in brain machine interface applications and that postural representations in SC may be exploited via intracortical stimulation to close the sensorimotor loop.