The fluid movement of an arm requires multiple spatiotemporal parameters to be set independently. Recent studies have argued that arm movements are generated by the collective dynamics of neurons in motor cortex. An untested prediction of this hypothesis is that independent parameters of movement must map to independent components of the neural dynamics. Using a task where three male monkeys made a sequence of reaching movements to randomly placed targets, we show that the spatial and temporal parameters of arm movements are independently encoded in the low-dimensional trajectories of population activity in motor cortex: each movement’s direction corresponds to a fixed neural trajectory through neural state space and its speed to how quickly that trajectory is traversed. Recurrent neural network models show that this coding allows independent control over the spatial and temporal parameters of movement by separate network parameters. Our results support a key prediction of the dynamical systems view of motor cortex, and also argue that not all parameters of movement are defined by different trajectories of population activity.

手臂的流体运动需要独立设置多个时空参数。最近的研究认为，手臂运动是由运动皮层神经元的集体动力学产生的。该假设的一个未经检验的预测是运动的独立参数必须映射到神经动力学的独立组成部分。通过三只雄性猴子对随机放置的目标进行一系列到达动作的任务，我们表明手臂运动的空间和时间参数独立编码在运动皮层群体活动的低维轨迹中：每个运动的方向对应于通过神经状态空间的固定神经轨迹及其速度，即穿过该轨迹的速度。循环神经网络模型表明，这种编码允许通过单独的网络参数独立控制运动的空间和时间参数。我们的结果支持了运动皮层动力系统观点的关键预测，并且还认为并非所有运动参数都是由不同的群体活动轨迹定义的。