Simultaneous and separable latent encoding of arm movement direction and kinematics in motor cortex

Little is known about if and how multiple features of movement are simultaneously encoded by population activity in motor cortex. Using neural activity from dorsal premotor cortex (PMd) and motor cortex (M1) as monkeys performed a sequential arm movement task, in this talk I will show that the direction and kinematics of arm movements are simultaneously but separably encoded in the low-dimensional trajectories of population activity. Trajectories of population activity encoded the direction of arm movement, with the distances between neural trajectories proportional to the difference in angle between the directions they encoded. By contrast, different durations of arm movements in the same direction were encoded by how long the neural trajectory took to traverse. A recurrent neural network (RNN) model of our results suggested the direction and duration could be independently controlled by respectively rotating the inputs to motor cortex and scaling the effective neuron time constant within motor cortex. Our results propose a mechanism for the simultaneous yet independent control of multiple arm movement features by motor cortex.