Features of virtually all voluntary movements are represented in the primary motor cortex. The movements can be ongoing, imminent, delayed, or imagined. Our goal was to investigate the dynamics of movement representation in the motor cortex. To do this we trained a fully recurrent neural network to continually output the direction and magnitude of movements required to reach randomly changing targets. Model neurons developed preferred directions and other properties similar to real motor cortical neurons. The key finding is that when the target for a reaching movement changes location, the ensemble representation of the movement changes nearly monotonically, and the individual neurons comprising the representation exhibit strong, nonmonotonic transients. These transients serve as internal recurrent signals that force the ensemble representation to change more rapidly than if it were limited by the time constants of individual neurons. These transients, if they exist, could be observed in experiments that require only slight modifications of the standard paradigm used to investigate movement representation in the motor cortex.