We developed a computational system that accounts for the combined behavior of cerebral nervous system and musculoskeletal system, aiming to provide a useful tool for investigating the mechanisms underlying motor dysfunctions (e.g., Parkinson's disease) and exploring effective therapeutic approaches. The musculoskeletal system was modeled based on a finite element description of soft-tissues, in which the material behaviour of the muscle is separated into an active part and a passive part. The active part corresponds to muscle activation due to muscle fiber contraction, while the passive part represents the intrinsic mechanical property of muscle. In the description of muscle activation, the motor-unit activity model was introduced to take into account the effects of neural signals on the behaviour of motoneurons. In the model, the motor-unit force of a single muscle fiber is regulated by the number of motor units recruited and their firing rates of the active potential. The developed model system was applied to simulate an isometric muscle contraction behavior. The results showed the inhomogeneous distributions of the activated muscle fibers and motor-unit forces in the three-dimensional model.