scholarly journals Vestibular modulation of visuomotor feedback gains in reaching

2019 ◽  
Vol 122 (3) ◽  
pp. 947-957 ◽  
Author(s):  
Leonie Oostwoud Wijdenes ◽  
Robert J. van Beers ◽  
W. Pieter Medendorp

Humans quickly and sophisticatedly correct their movements in response to changes in the world, such as when reaching to a target that abruptly changes its location. The vigor of these movement corrections is time-dependent, increasing if the time left to make the correction decreases, which can be explained by optimal feedback control (OFC) theory as an increase of optimal feedback gains. It is unknown whether corrections for changes in the world are as sophisticated under full-body motion. For successful visually probed motor corrections during full-body motion, not only the motion of the hand relative to the body needs to be taken into account, but also the motion of the hand in the world should be considered, because their relative positions are changing. Here, in two experiments, we show that visuomotor feedback corrections in response to target jumps are more vigorous for faster passive full-body translational acceleration than for slower acceleration, suggesting that vestibular information modulates visuomotor feedback gains. Interestingly, these corrections do not demonstrate the time-dependent characteristics that body-stationary visuomotor feedback gains typically show, such that an optimal feedback control model fell short to explain them. We further show that the vigor of corrections generally decreased over the course of trials within the experiment, suggesting that the sensorimotor system adjusted its gains when learning to integrate the vestibular input into hand motor control. NEW & NOTEWORTHY Vestibular information is used in the control of reaching movements to world-stationary visual targets, while the body moves. Here, we show that vestibular information also modulates the corrective reach responses when the target changes position during the body motion: visuomotor feedback gains increase for faster body acceleration. Our results suggest that vestibular information is integrated into fast visuomotor control of reaching movements.

2017 ◽  
Vol 118 (1) ◽  
pp. 84-92 ◽  
Author(s):  
Johannes Keyser ◽  
W. Pieter Medendorp ◽  
Luc P. J. Selen

When reaching for an earth-fixed object during self-rotation, the motor system should appropriately integrate vestibular signals and sensory predictions to compensate for the intervening motion and its induced inertial forces. While it is well established that this integration occurs rapidly, it is unknown whether vestibular feedback is specifically processed dependent on the behavioral goal. Here, we studied whether vestibular signals evoke fixed responses with the aim to preserve the hand trajectory in space or are processed more flexibly, correcting trajectories only in task-relevant spatial dimensions. We used galvanic vestibular stimulation to perturb reaching movements toward a narrow or a wide target. Results show that the same vestibular stimulation led to smaller trajectory corrections to the wide than the narrow target. We interpret this reduced compensation as a task-dependent modulation of vestibular feedback responses, tuned to minimally intervene with the task-irrelevant dimension of the reach. These task-dependent vestibular feedback corrections are in accordance with a central prediction of optimal feedback control theory and mirror the sophistication seen in feedback responses to mechanical and visual perturbations of the upper limb. NEW & NOTEWORTHY Correcting limb movements for external perturbations is a hallmark of flexible sensorimotor behavior. While visual and mechanical perturbations are corrected in a task-dependent manner, it is unclear whether a vestibular perturbation, naturally arising when the body moves, is selectively processed in reach control. We show, using galvanic vestibular stimulation, that reach corrections to vestibular perturbations are task dependent, consistent with a prediction of optimal feedback control theory.


2014 ◽  
Vol 112 (9) ◽  
pp. 2218-2233 ◽  
Author(s):  
David W. Franklin ◽  
Sae Franklin ◽  
Daniel M. Wolpert

Recent studies have highlighted the modulation and control of feedback gains as support for optimal feedback control. While many experiments contrast feedback gains across different environments, only a few have demonstrated the appropriate modulation of feedback gains from one movement to the next. Here we extend previous work by examining whether different visuomotor feedback gains can be learned for different directions of movement or perturbation directions in the same posture. To do this we measure visuomotor responses (involuntary motor responses to shifts in the visual feedback of the hand) during reaching movements. Previous work has demonstrated that these feedback responses can be modulated depending on the statistical distributions of the environment. Specifically, feedback gains were upregulated for task-relevant environments and downregulated for task-irrelevant environments. Using these two statistical distributions, the first experiment examined whether these feedback responses could be independently modulated for the same limb posture for two directions of movement (same limb posture but on either an inward or outward movement), while the second examined whether the feedback responses could modulate, within a single movement, to perturbations to the left or right of the reach. Both experiments demonstrated that visuomotor feedback responses could be learned independently such that the response was appropriate for the environment. This work demonstrates that feedback gains can be simultaneously tuned (upregulated and downregulated) depending on the state of the body and the environment. The results indicate the degree to which feedback responses can be fractionated in order to adapt to the world.


Author(s):  
Jongeun Choi ◽  
Dejan Milutinović

This tutorial paper presents the expositions of stochastic optimal feedback control theory and Bayesian spatiotemporal models in the context of robotics applications. The presented material is self-contained so that readers can grasp the most important concepts and acquire knowledge needed to jump-start their research. To facilitate this, we provide a series of educational examples from robotics and mobile sensor networks.


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