A central challenge for myoelectric limb prostheses resides in the fact that, as the level of amputation becomes more proximal, the number of functions to be replaced increases, while the number of muscles available to collect input signals for control decreases. Differential activation of compartments from a single muscle could provide additional control sites. However, such feat is not naturally under voluntary control. In this study, we investigated the feasibility of learning to differentially activate the two heads of the bicep brachii muscle (BBM), by using biofeedback via high-density surface electromyography (HD-sEMG). Using a one degree of freedom Fitts’ law test, we observed that eight subjects could learn to control the center of gravity of BBM’s myoelectric activity. In addition, we examined the activations patterns of BBM that allow for the decoding of distal hand movements. These patterns were found highly individual, but different enough to allow for decoding of motor volition of distal joints. These findings represent promising venues to increase the functionality of myoelectrically controlled upper limb prostheses.