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Reversed Hand
Abstract

Visuomotor adaptation plays an important role in motor planning and execution. However, it remains unclear how sensorimotor transformations are recalibrated when visual and proprioceptive feedback are decoupled. To address this question, the present study asked participants to reach toward targets in a virtual reality (VR) environment. They were given visual feedback of their arm movements in VR that was either consistent (normal motion) with the virtual world or reflected (reversed motion) with respect to the left-right and vertical axes. Participants completed two normal motion experimental sessions, with a reversed motion session in between. While reaction time in the reversed motion session was longer than in the normal motion session, participants showed the learning improvement by completing trials in the second normal motion session faster than in the first. The reduction in reaction time was found to correlate with greater use of linear reaching trajectory strategies (measured using dynamic time warping) in the reversed and second normal motion sessions. This result appears consistent with linear motor movement planning guided by increased attention to visual feedback. Such strategical bias persisted into the second normal motion session. Participants in the reversed session were grouped into two clusters depending on their preference for proximal/distal and awkward/smooth motor movements. We found that participants who preferred distal-smooth movements produced more linear trajectories than those who preferred proximal-awkward movements.

BibTeX
					
@inproceedings{lin2017visuomotor,
    title={Visuomotor Adaptation and Sensory Recalibration in Reversed Hand Movement Task},
    author={Lin, J.H. and Zhu, Y. and Kubricht, J.R. and Zhu, S. and Lu, H.},
    booktitle={Proceedings of the 39th Annual Meeting of the Cognitive Science Society},
    pages={2579--2584},
    year={2017}
}
					
				
Acknowledgements

The work reported herein was supported by DARPA XAI grant N66001-17-2-4029, DARPA SIMPLEX grant N66001-15-C-4035, ONR MURI grant N00014-16-1-2007, a NSF grant BCS-1353391, and a NSF Graduate Research Fellowship.