In this study, a controller for robotic motion based on neuroscientific principles was developed and implemented using an artificial neural element and a conventional robotic arm. With independent control over arm final position, velocity, acceleration, and deceleration, this system offers a more smooth, efficient and life-like motion than conventional open-loop methods. The system makes use of a single positional sensor, and derives all other sensory feedback signals from that sensor's output. The controller is a discrete neuromime, with an excitatory input dedicated to a "start" directive, and inhibitory synapses for position, velocity, acceleration, deceleration, and hard limiters. The system is easily upgradable to additional excitatory and inhibitory inputs, and will be able to mimic a broad range of motion trajectories, with emphasis on those derived from human elbow joint measurements.