Proprioceptive integration in motor control.

Muscle vibration alters both perceived limb position and velocity by increasing muscle spindle afferent firing rates. In particular the type Ia afferents are affected, which mainly encode muscle stretch velocity. Predictive frameworks of sensorimotor control, such as Active Inference and Optimal Feedback Control, suggest that velocity signals should inform position estimates. Such a function would predict that errors in perceived limb position and velocity should be correlated, but this prediction remains empirically underexplored. We hypothesised that an online evaluation of the integral of sensed velocity influences the perceived arm position during active movements. Using a virtual reality-based reaching task we investigated how vibration-biased proprioceptive feedback influences voluntary movement control and inference of arm position and movement. Our results suggest that muscle vibration biases perceived movement velocity, with downstream effects on perceived limb position and reflexive corrections of movement speed. We found that (i) antagonist vibration during active movement caused participants to overestimate their movement speed while also slowing down, (ii) movement speed and endpoint errors were correlated, with muscle vibration affecting both in congruent directions and (iii) adjustments in movement speed to muscle vibration are sufficiently fast to be reflexive. Together these findings support the hypothesis that proprioceptive velocity signals are integrated to augment inference of position, consistent with predictive frameworks of sensorimotor control. KEY POINTS: During movement without visual feedback, the central nervous system (CNS) has access to both position- and velocity-based proprioceptive signals, which are used to estimate limb state. Muscle vibration biases the perception of limb position, as seen in the classically observed pattern of biased endpoint errors, through the stimulation of primary (type Ia) muscle spindles, primarily a velocity sensor. We investigated how proprioceptive velocity signals affect position estimation during movement by applying muscle vibration while measuring perceived movement speed, actual movement speed and endpoint errors in a virtual reality (VR)-based reaching task. We show that errors in perceived limb position and velocity are correlated during active movements, consistent with predictive frameworks of sensorimotor control. These findings support the idea that the CNS maintains a self-consistent estimate of limb state across both position and velocity domains.