Moving faster while preserving accuracy.

Achieving movements with accuracy despite the inevitable variability of the neuromuscular mechanisms is an important everyday life problem, which has to be solved for the production of any adapted motor act, such as walking, writing, catching, or pointing. To solve this problem when we have to make goal-directed movements as fast as possible, we systematically increase movement time when accuracy requirements increase, a ubiquitous phenomenon qualified as speed-accuracy trade-off. It has been proposed that this speed-accuracy trade-off reflects an optimal compromise between speed and accuracy in the presence of biological noise and that increasing movement speed inevitably leads to decreased motor accuracy. However, the recent finding that muscle cocontraction improves movement accuracy may challenge this view and begs the question of how movement speed control and cocontraction control coexist. Here, we show that humans are in fact able to move faster while preserving movement accuracy, by using a strategy where muscles are cocontracted around the joint. As this energetically costly cocontraction strategy was not naturally used, this result has two important implications. It first demonstrates that a speed modulation strategy is preferred to a cocontraction strategy for fast, accurate movements, and it also suggests that energy economy prevents us to execute accurate movements as fast as we could do. Consequently, we propose that the mechanisms underlying the speed-accuracy trade-off are more complex than previously thought, and suggest the existence of a previously unknown speed-energy-accuracy trade-off for goal-directed movements.

Adaptation of motor behavior to preserve task success in the presence of muscle fatigue.

To achieve task goals in the various contexts of everyday life, the CNS has to adapt to short time scale changes in the properties of the neuromuscular system, such as those induced by fatigue. Here we investigated how humans preserve task success despite fatigue-induced changes within the neuromuscular system, when they have to aim at a target as fast and as accurately as possible. In such a task, subjects generally choose a compromise between speed and accuracy that has been formalized as Fitts's law. We first characterized the effect of fatigue on Fitts's law in an experiment where participants had to perform fast but accurate elbow movements aimed at targets of different sizes, before and after a fatiguing exercise that reduced maximal voluntary force by approximately 30%. We found that movements were slower to guarantee task success in the presence of fatigue. We then used an optimal control model to determine how fatigue-induced changes in variables such as noise in motor commands, muscle contraction and relaxation times, and the gain between neural activation and muscle force may contribute to changes in Fitts's law with fatigue. We concluded that the observed behavior was not due to the lack of available force, but very likely reflected the fact that the CNS uses the same optimal strategy with a fatigued neuromuscular plant that notably exhibits increased signal-dependent noise in motor commands. This strategy appears necessary to preserve task success in the presence of acute changes in the neuromuscular system.