Optimal use of limb mechanics distributes control during bimanual tasks

Bimanual tasks involve the coordination of both arms, which often offers redundancy in the ways a task can be completed. The distribution of control across limbs is often considered from the perspective of handedness. In this context, although there are differences across dominant and nondominant arms during reaching control ( Sainburg 2002 ), previous studies have shown that the brain tends to favor the dominant arm when performing bimanual tasks ( Salimpour and Shadmehr 2014 ). However, biomechanical factors known to influence planning and control in unimanual tasks may also generate limb asymmetries in force generation, but their influence on bimanual control has remained unexplored. We investigated this issue in a series of experiments in which participants were instructed to generate a 20-N force with both arms, with or without perturbation of the target force during the trial. We modeled the task in the framework of optimal feedback control of a two-link model with six human-like muscles groups. The biomechanical model predicted a differential contribution of each arm dependent on the orientation of the target force and joint configuration that was quantitatively matched by the participants' behavior, regardless of handedness. Responses to visual perturbations were strongly influenced by the perturbation direction, such that online corrections also reflected an optimal use of limb biomechanics. These results show that the nervous system takes biomechanical constraints into account when optimizing the distribution of forces generated across limbs during both movement planning and feedback control of a bimanual task. NEW & NOTEWORTHY Here, we studied a bimanual force production task to examine the effects of biomechanical constraints on the distribution of control across limbs. Our findings show that the central nervous system optimizes the distribution of force across the two arms according to the joint configuration of the upper limbs. We further show that the underlying mechanisms influence both movement planning and online corrective responses to sudden changes in the target force.