We permanently deal with gravity force. Experimental evidences revealed that moving against gravity strongly differs from moving along the gravity vector. This directional asymmetry has been attributed to an optimal planning process that optimizes gravity force effects to minimize energy. Yet, only few studies have considered the case of vertical movements in the context of optimal control. What kind of cost is better suited to explain kinematic patterns in the vertical plane? Here, we aimed to understand further how the central nervous system (CNS) plans and controls vertical arm movements. Our reasoning was the following: if the CNS optimizes gravity mechanical effects on the moving limbs, kinematic patterns should change according to the direction and the magnitude of the gravity torque being encountered in the motion. Ten subjects carried out single-joint movements, i.e., rotation around the shoulder (whole arm), elbow (forearm), and wrist (hand) joints, in the vertical plane. Joint kinematics were analyzed and compared with various theoretical optimal model predictions (minimum absolute work-jerk, jerk, torque change, and variance). We found both direction-dependent and joint-dependent variations in several kinematic parameters. Notably, directional asymmetries decreased according to a proximodistal gradient. Numerical simulations revealed that our experimental findings could be attributed to an optimal motor planning (minimum absolute work-jerk) that integrates the direction and the magnitude of gravity torque and minimizes the absolute work of forces (energy-related cost) around each joint. Present results support the general idea that the CNS implements optimal solutions according to the dynamic context of the action.
Keywords: distal; gravity force; optimal control; proximal; reaching movement; sensorimotor control.