Biology subjects

Mortensen, E. S.

Publications and source records attributed to Mortensen, E. S..

3 recordsLinked to original sources

bioRxiv2026

When Velocity Becomes Position: Proprioceptive Contributions to State Estimation

In this study, we investigate the relative contributions of positional- and velocity-based proprioceptive feedback to state estimation when visual feedback of the hand is unavailable. We performed a virtual reality experiment in which healthy human participants (N = 22) completed two tasks: a continuous target-tracking task and a sequential reaching task. In both cases, visual feedback of the hand position was withheld, except for a brief moment, during which an offset to the left or right was sometimes applied. By analysing the movement path following the offset visual feedback and comparing it to the non-offset condition, we can infer the extent to which the brain relies on rate-of-change feedback compared to absolute positional feedback for estimating the hand position. We compare and contrast our empirical data with simulated movements from a computational model based on Bayesian sensory integration under varied assumptions of the reliance on positional and velocity-based cues. Our human and simulated data together indicate a heavy reliance on velocity-based proprioceptive feedback, as movement offsets induced by biased visual feedback decay slowly during both target tracking and sequential reaching tasks. The eventual convergence between offset and non-offset trials demonstrates that absolute positional information is incorporated, albeit slowly. Author summaryThe brain continually estimates the current pose and movement of the body, supporting motor control and giving rise to the perception of the bodys state. When visual feedback is lacking, we rely heavily on the sense of proprioception to infer the state of the body. Key among the proprioceptive receptors are the muscle spindle afferents, which are divided into two specialised subgroups: one that signals absolute muscle length, and the other that signals the rate-of-change of muscle length. In this study, we investigate the extent to which the brain utilises rate-of-change information to supplement its inference of the current body position. While such a function would fit well within several of the most popular theories of sensorimotor control, the investigation of this process has so far received limited attention. By having a group of research participants complete two virtual reality-based experiments, we demonstrate that the performed movements remain relative to a visually induced offset. By further simulating the same tasks in a computational model based on Bayesian sensory integration, we can show that this pattern of behaviour is well explained by assuming a relatively high reliance on rate-of-change versus absolute proprioceptive feedback.

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bioRxiv2025

Implications of recursive Bayesian Sensory Inference

In this article, we examine how the balance between velocity-based and position-based proprioceptive feedback influences state estimation during motor control. We introduce a computational model of arm state inference grounded in Bayesian sensory integration and compare its behaviour to findings from three classical sensorimotor studies. The model allows us to contrast the predicted behaviour of two proprioceptive configurations: one relying primarily on position signals and another relying primarily on velocity signals, reflecting the distinct contributions of type II and type Ia muscle spindle afferents. Our simulations show that a system with strong reliance on velocity-based feedback tends to represent movement relative to previously estimated positions. In a simulated reaching task with briefly presented offset visual feedback, such an Agent produces systematic endpoint errors even after visual feedback is removed. In contrast, an Agent relying mainly on positional feedback is able to correctly update its inferred hand position after visual feedback is removed, thereby limiting this type of biased endpoint errors. When biased visual feedback remains continuously available, or when muscle vibration is simulated, the two configurations produce very similar behaviour. These results indicate that markedly different assumptions about the weighting of positional and velocity proprioceptive cues can yield similar observable behaviour in some of the often-used experimental setups designed to probe state inference processes. This underscores the importance of carefully considering the composition of proprioceptive signals when building computational models and interpreting human sensorimotor experiments. We highlight the task conditions under which our model predicts clear behavioural differences arising from the relative contribution of velocity versus positional feedback. 1 Author summaryDuring motor control, the central nervous system tracks both the position and movement of our limbs. Even with our eyes closed, we can bring the tips of our index fingers together, a feat that depends on sensory signals from specialised receptors in our muscles. One set of these receptors is most sensitive to the rate of muscle lengthening, providing information about movement, while another set signals the muscles current length, giving us a sense of posture. There has so far been limited discussion of the extent to which these two feedback channels are used to augment one another. For example, signals about the rate of muscle lengthening reflect how our pose is changing from moment to moment, but it remains unknown to what extent the brain uses this information to update its estimate of limb position. In this study, we simulate three classical sensorimotor experiments while varying the precision of these two types of sensory feedback. Two simulations show that different assumptions can yield similar movement patterns, highlighting the need for caution when interpreting such experiments. The third suggests that movement-related feedback may contribute more to our sense of limb position than previously recognised.

neuroscience↗

bioRxiv2025

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 both 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 pointsO_LIDuring 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. C_LIO_LIMuscle 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. C_LIO_LIWe 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. C_LIO_LIWe show that errors in perceived limb position and velocity are correlated during active movements, consistent with predictive frameworks of sensorimotor control. C_LIO_LIThese findings support the idea that the CNS maintains a self-consistent estimate of limb state across both position and velocity domains. C_LI

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