Real-time biofeedback integrated into neuromuscular training reduces high-risk knee biomechanics and increases functional brain connectivity: A preliminary longitudinal investigation.

Prospective evidence indicates that functional biomechanics and brain connectivity may predispose an athlete to an anterior cruciate ligament injury, revealing novel neural linkages for targeted neuromuscular training interventions. The purpose of this study was to determine the efficacy of a real-time biofeedback system for altering knee biomechanics and brain functional connectivity. Seventeen healthy, young, physically active female athletes completed 6 weeks of augmented neuromuscular training (aNMT) utilizing real-time, interactive visual biofeedback and 13 served as untrained controls. A drop vertical jump and resting state functional magnetic resonance imaging were separately completed at pre- and posttest time points to assess sensorimotor adaptation. The aNMT group had a significant reduction in peak knee abduction moment (pKAM) compared to controls (p = .03, d = 0.71). The aNMT group also exhibited a significant increase in functional connectivity between the right supplementary motor area and the left thalamus (p = .0473 after false discovery rate correction). Greater percent change in pKAM was also related to increased connectivity between the right cerebellum and right thalamus for the aNMT group (p = .0292 after false discovery rate correction, r2  = .62). No significant changes were observed for the controls (ps > .05). Our data provide preliminary evidence of potential neural mechanisms for aNMT-induced motor adaptations that reduce injury risk. Future research is warranted to understand the role of neuromuscular training alone and how each component of aNMT influences biomechanics and functional connectivity.

Fractal gait patterns are retained after entrainment to a fractal stimulus.

Previous work has shown that fractal patterns in gait can be altered by entraining to a fractal stimulus. However, little is understood about how long those patterns are retained or which factors may influence stronger entrainment or retention. In experiment one, participants walked on a treadmill for 45 continuous minutes, which was separated into three phases. The first 15 minutes (pre-synchronization phase) consisted of walking without a fractal stimulus, the second 15 minutes consisted of walking while entraining to a fractal visual stimulus (synchronization phase), and the last 15 minutes (post-synchronization phase) consisted of walking without the stimulus to determine if the patterns adopted from the stimulus were retained. Fractal gait patterns were strengthened during the synchronization phase and were retained in the post-synchronization phase. In experiment two, similar methods were used to compare a continuous fractal stimulus to a discrete fractal stimulus to determine which stimulus type led to more persistent fractal gait patterns in the synchronization and post-synchronization (i.e., retention) phases. Both stimulus types led to equally persistent patterns in the synchronization phase, but only the discrete fractal stimulus led to retention of the patterns. The results add to the growing body of literature showing that fractal gait patterns can be manipulated in a predictable manner. Further, our results add to the literature by showing that the newly adopted gait patterns are retained for up to 15 minutes after entrainment and showed that a discrete visual stimulus is a better method to influence retention.