Implementing ACL Injury Prevention in Daily Sports Practice—It’s Not Just the Program: Let’s Build Together, Involve the Context, and Improve the Content

Although the benefits of current anterior cruciate ligament (ACL) injury prevention programmes have been demonstrated in efficacy studies, they, unfortunately, have had limited public health impact to date. For example, the incidence of ACL injuries continues to rise in adolescent athletes. Raising awareness and educating coaches and athletes is not enough to facilitate the widespread, sustained use of these programmes in the real-world setting. Considering the profound burden of ACL injuries, it is necessary to continue to improve the current ACL injury prevention programmes through co-creation. First, the uptake of the programmes should be optimized by a better appreciation and understanding of the individual, socio-cultural and environmental context (i.e., community). Second, the content of the programmes should be optimized to better reflect the demands of the sport by creating more ownership and increasing motivation (incorporating challenging, sport-specific and fun elements) with the end-users. In addition, implicit motor learning, random practice and differential learning are concepts that should be integrated when practising to obtain the most optimal results when learning or finetuning skills.

Learning from the path not taken: Sensory prediction errors are sufficient for implicit adaptation of withheld movements

Current theories of motor control emphasize forward models as a critical component of the brain's motor execution and learning networks. These internal models are thought to predict the consequences of movement before sensory feedback from these movements can reach the brain, allowing for smooth, continuous online motor performance and for the computation of prediction errors that drive implicit motor learning. Taking this framework to its logical extreme, we tested the hypothesis that movements are not necessary for the generation of predictions, the computation of prediction errors, and implicit motor adaptation. Human participants were cued to move a computer mouse to a visually displayed target and were subsequently cued to withhold those movements on a subset of trials. Visual errors displayed on both trials with and without movements to the target induced single-trial learning. Furthermore, learning on trials without movements persisted when accompanying movement trials were never paired with errors and when movement and sensory feedback trajectories were decoupled. These data provide compelling evidence supporting an internal model framework in which forward models generate sensory predictions independent of the generation of movements.

Taking aim at the perceptual side of motor learning: Exploring how explicit and implicit learning encode perceptual error information through depth vision

Motor learning in visuomotor adaptation tasks results from both explicit and implicit processes, each responding differently to an error signal. While the motor output side of these processes is extensively studied, their visual input side is relatively unknown. We investigated if and how depth perception affects the computation of error information by explicit and implicit motor learning. Two groups of participants threw virtual darts at a virtual dartboard while receiving perturbed endpoint feedback. The Delayed group was allowed to re-aim and their feedback was delayed to emphasize explicit learning, while the Clamped group received clamped cursor feedback which they were told to ignore, and continued to aim straight at the target to emphasize implicit adaptation. Both groups played this game in a highly detailed virtual environment (Depth condition) and in an empty environment (No-Depth condition). The Delayed group showed an increase in error sensitivity under Depth relative to No-Depth conditions. In contrast, the Clamped group adapted to the same degree under both conditions. The movement kinematics of the Delayed participants also changed under the Depth condition, consistent with the target appearing more distant, unlike the Clamped group. A comparison of the Delayed behavioral data with a perceptual task from the same individuals showed that the effect of the Depth condition on the re-aiming direction was consistent with an increase in the scaling of the error distance and size. These findings suggest that explicit and implicit learning processes may rely on different sources of perceptual information.

Publisher Correction: Implicit motor learning within three trials

An amendment to this paper has been published and can be accessed via a link at the top of the paper.