Transfer of dynamic motor skills acquired during isometric training to free motion.
File(s)Melendez2017JNP.pdf (1.11 MB)
Accepted version
Author(s)
Melendez-Calderon, A
Tan, M
Fisher Bittmann, M
Burdet, E
Patton, JL
Type
Journal Article
Abstract
Recent studies have explored the prospects of learning to move without moving, by displaying virtual arm movement related to exerted force. However, it has yet to be tested whether learning the dynamics of moving can transfer to the corresponding movement. Here we present a series of experiments that investigate this isometric training paradigm. Subjects were asked to hold a handle and generate forces as their arms were constrained to a static position. A precise simulation of reaching was used to make a graphic rendering of an arm moving realistically in response to the measured interaction forces and simulated environmental forces. Such graphic rendering was displayed on a horizontal display that blocked their view to their actual (statically constrained) arm and encouraged them to believe they were moving. We studied adaptation of horizontal, planar, goal directed arm movements in a velocity-dependent force-field. Our results show that individuals can learn to compensate for such a force-field in a virtual environment, and transfer their new skills to the actual free motion condition, with performance comparable to practice while moving. Such non-moving techniques should impact various training conditions when moving may not be possible.
Date Issued
2017-07-01
Date Acceptance
2017-03-21
Citation
Journal of Neurophysiology, 2017, 118 (1), pp.219-233
ISSN
1522-1598
Publisher
American Physiological Society
Start Page
219
End Page
233
Journal / Book Title
Journal of Neurophysiology
Volume
118
Issue
1
Copyright Statement
© 2016 Journal of Neurophysiology.
Sponsor
Commission of the European Communities
Commission of the European Communities
Identifier
PII: jn.00614.2016
Grant Number
PITN-GA-2012-317488
644727
Subjects
Science & Technology
Life Sciences & Biomedicine
Neurosciences
Physiology
Neurosciences & Neurology
motor learning
motor adaptation
visual feedback
isometric
HUMAN REACHING MOVEMENTS
HUMAN ARM MOVEMENTS
INTERNAL-MODELS
VISUAL FEEDBACK
PROPRIOCEPTIVE FEEDBACK
VIRTUAL ENVIRONMENTS
IMPEDANCE CONTROL
ADAPTATION
ERRORS
FORCE
11 Medical And Health Sciences
17 Psychology And Cognitive Sciences
Neurology & Neurosurgery
Publication Status
Published