Reward-based improvements in motor control are driven by multiple error-reducing mechanisms

Reward has a remarkable ability to invigorate motor behaviour, enabling individuals to select and execute actions with greater precision and speed. However, if reward is to be exploited in applied settings such as rehabilitation, a thorough understanding of its underlying mechanisms is required. Although reward-driven enhancement of movement execution has been proposed to occur through enhanced feedback control, an untested alternative is that it is driven by increased arm stiffness, an energy-consuming process that increases limb stability. First, we demonstrate that during reaching reward improves selection and execution performance concomitantly without interference. Computational analysis revealed that reward led to both an increase in feedback correction during movement and a reduction in motor noise near the target. We provide novel evidence that this noise reduction is driven by a reward-dependent increase in arm stiffness. Therefore, reward drives multiple error-reduction mechanisms which enable individuals to invigorate motor performance without compromising accuracy.