Literature DB >> 28501420

Manipulation of visual information affects control strategy during a visuomotor tracking task.

Paulina J M Bank1, Lucas R M Dobbe2, Carel G M Meskers3, Jurriaan H de Groot4, Erwin de Vlugt2.   

Abstract

Proper understanding of motor control requires insight into the extent and manner in which task performance and control strategy are influenced by various aspects of visual information. We therefore systematically manipulated the visual presentation (i.e., scaling factor and optical flow density) of a visuomotor tracking task without changing the task itself, and investigated the effect on performance, effort, motor control strategy (i.e., anticipatory or corrective steering) and underlying neuromechanical parameters (i.e., intrinsic muscle stiffness and damping, and proprioceptive and visual feedback). Twenty healthy participants controlled the left-right position of a virtual car (by means of wrist rotations in a haptic robot) to track a slightly curved virtual road (presented on a 60" LED screen), while small torque perturbations were applied to the wrist (1.25-20Hz multisine) for quantification of the neuromechanical parameters. This visuomotor tracking task was performed in conditions with low/medium/high scaling factor and low/high optical flow density. Task performance was high in all conditions (tracking accuracy 96.6%-100%); a higher scaling factor was associated with slightly better performance. As expected, participants did adapt their control strategy and the use of proprioceptive and visual feedback in response to changes in the visual presentation. These findings indicate that effects of visual representation on motor behavior should be taken into consideration in designing, interpreting and comparing experiments on motor control in health and disease. In future studies, these insights might be exploited to assess the sensory-motor adaptability in various clinical conditions.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Neuromechanical parameters; Strategy; System identification; Visual feedback; Visuomotor control

Mesh:

Year:  2017        PMID: 28501420     DOI: 10.1016/j.bbr.2017.04.056

Source DB:  PubMed          Journal:  Behav Brain Res        ISSN: 0166-4328            Impact factor:   3.332


  1 in total

1.  Effects of Future Information and Trajectory Complexity on Kinematic Signal and Muscle Activation during Visual-Motor Tracking.

Authors:  Linchuan Deng; Jie Luo; Yueling Lyu; Rong Song
Journal:  Entropy (Basel)       Date:  2021-01-15       Impact factor: 2.524

  1 in total

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