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The sensorimotor system has the constant challenge of dealing with the naturally occurring variability in our movements. Here, we investigated the potential roles of muscular co-contraction and visuomotor feedback responses to regulate movement variability. When we visually amplified movements, we found that the sensorimotor system primarily uses muscular co-contraction to regulate movement variability. Interestingly, we found that muscular co-contraction was modulated relative to inherent visuomotor feedback responses, suggesting an interplay between impedance and feedback control.

We routinely have physical interactions with others, whether it be handing someone a glass of water or jointly moving a heavy object together. These sensorimotor interactions between humans typically rely on visual feedback and haptic feedback. Recent single participant studies have highlighted that the unique noise and time delays of each sense must be considered to estimate the state, such as the position and velocity, of one's own movement. However we know little on how visual feedback and haptic feedback are used to estimate the state of another person. Here we tested how humans utilize visual feedback and haptic feedback to estimate the state of their partner during a collaborative sensorimotor task. Across two experiments, we show that visual feedback dominated over haptic feedback during collaboration. Specifically, we found that visual feedback led to comparatively lower task-relevant movement variability, smoother collaborative movements, and faster trial completion times. We also developed an optimal feedback controller that considered the noise and time delays of both visual feedback and haptic feedback to estimate the state of a partner. This model was able to capture both lower task-relevant movement variability and smoother collaborative movements. Taken together, our empirical and modeling results support the idea that visual accuracy is more important than haptic speed to perform state-estimation of a partner during collaboration.

From a baby’s babbling to a songbird practicing a new tune, exploration is critical to motor learning. A hallmark of exploration is the emergence of random walk behaviour along solution manifolds, where successive motor actions are not independent but rather become serially dependent. Such exploratory random walk behaviour is ubiquitous across species, neural firing, gait patterns, and reaching behaviour. Past work has suggested that exploratory random walk behaviour arises from an accumulation of movement variability and a lack of error-based corrections. Here we test a fundamentally different idea—that reinforcement-based processes regulate random walk behaviour to promote continual motor exploration to maximize success. Across three human reaching experiments we manipulated the size of both the visually displayed target and an unseen reward zone, as well as the probability of reinforcement feedback. Our empirical and modelling results parsimoniously support the notion that exploratory random walk behaviour emerges by utilizing knowledge of movement variability to update intended reach aim towards recently reinforced motor actions. This mechanism leads to active and continuous exploration of the solution manifold, currently thought by prominent theories to arise passively. The ability to continually explore muscle, joint, and task redundant solution manifolds is beneficial while acting in uncertain environments, during motor development, or when recovering from a neurological disorder to discover and learn new motor actions.

Background Muscle co-contraction is an accepted clinical measure to quantify the effects of aging on neuromuscular control and movement efficiency. However, evidence of increased muscle co-contraction in old compared to young adults remains inconclusive. Research Question Are there differences in lower-limb agonist/antagonist muscle co-contractions in young and old adults, and males and females, during walking and stair use? Methods In a retrospective study, we analyzed data from 20 healthy young and 19 healthy old adults during walking, stair ascent, and stair descent at self-selected speeds, including marker trajectories, ground reaction force, and electromyography activity. We calculated muscle co-contraction at the knee (vastus lateralis vs. biceps femoris) and ankle (tibialis anterior vs. medial gastrocnemius) using the ratio of the common area under a muscle pairs’ filtered and normalized electromyography curves to the sum of the areas under each muscle in that pair. Results Old compared to young adults displayed 18%–22% greater knee muscle co-contractions during the entire cycle of stair use activities. We found greater (17%–29%) knee muscle co-contractions in old compared to young adults during the swing phase of walking and stair use. We found no difference in ankle muscle co-contractions between the two age groups during all three activities. We found no difference in muscle co-contraction between males and females at the knee and ankle joints for all three activities. Significance Based on our findings, we recommend clinical evaluation to quantify the effects of aging through muscle co-contraction to include the knee joint during dynamic activities like walking and stair use, and independent evaluation of the stance and swing phases.