The performance of motor tasks requires the coordinated control and continuous adjustment of myriad individual muscles. The basic commands for the successful performance of a sensorimotor task originate in "higher" centers such as the motor cortex, but the actual muscle activation and resulting torques and motion are considerably shaped by the integrative function of the spinal interneurons. The relative contributions of brain and spinal cord are less clear for reaching movements than for automatic tasks such as locomotion. We have modeled a two-axis, four-muscle wrist joint with realistic musculoskeletal mechanics and proprioceptors and a network of regulatory circuitry based on the classical types of spinal interneurons (propriospinal, monosynaptic Ia-excitatory, reciprocal Ia-inhibitory, Renshaw inhibitory, and Ib-inhibitory pathways) and their supraspinal control (via biasing activity, presynaptic inhibition, and fusimotor gain). The modeled system has a very large number of control inputs, not unlike the real spinal cord that the brain must learn to control to produce desired behaviors. It was surprisingly easy to program this model to emulate actual performance in four very different but well described behaviors: (1) stabilizing responses to force perturbations; (2) rapid movement to position target; (3) isometric force to a target level; and (4) adaptation to viscous curl force fields. Our general hypothesis is that, despite its complexity, such regulatory circuitry substantially simplifies the tasks of learning and producing complex movements.