Evidence for flexible motor costs in vertical arm movements: reduced gravity-related effort minimization under high accuracy constraints

The central nervous system (CNS) is thought to use motor strategies that minimize several criteria, such as end-point variability or effort, to plan optimal motor patterns. In the case of vertical arm movements, a large body of literature demonstrated that the brain uses a motor strategy that takes advantage of the mechanical effects of gravity to minimize muscle effort. Results from other studies suggested that the relative importance of each criterion may vary according to the task’s constraints. For example, it could be hypothesized that reduced end-point variability driven by high accuracy demands is detrimental to effort minimization. The present study probes this specific hypothesis using the framework of gravity-related effort minimization. We asked twenty young healthy participants to perform vertical arm reaching movements towards targets whose size varied across conditions. We recorded the arm kinematics and electromyographic activities of the anterior deltoid to study two well-known motor signatures of the gravity-related optimization process; i.e., directional asymmetries on velocity profiles and negative epochs on phasic muscular activities. The results showed that both indices were reduced as target size decreased, demonstrating that the gravity-related optimization process was reduced under high accuracy constraints. This phenomenon is consistent with the use of a trade-off strategy between effort and end-point variability. More generally, it suggests that the CNS is able to appropriately modulate the relative importance of varied motor costs when facing varying task demands.