Interindividual variability in visuo-proprioceptive integration for the morphokinetic control of hand movements
Poster Presentation

Joëlle Rouhana
LPMC, MSHS, 99 avenue du Recteur Pineau, 86000 Poitiers, France

Philippe Boulinguez
LPMC, MSHS, 99 avenue du Recteur Pineau, 86000 Poitiers, France

     Abstract ID Number: 161
     Full text: Not available
     Last modified: April 18, 2005

Abstract
This study deals with the idea that dominance effects (viewed as the privileged use of one source of information among others) vary both according to the processes under scrutiny (perceptual encoding, movement online control) and across subjects. Classical paradigms of addition/suppression of sensory information were adapted in the methods, handling all conditions of visual and proprioceptive feedbacks both for 1) stimulus encoding (movement trajectories to be reproduced: with or without passive movements, with or without vision) and for 2) execution control (with or without active movement, with or without vision). Kinematic analyses revealed that most subjects (60%) show visual dominance for encoding movement trajectory. Conversely, for execution control, subjects are largely distributed along a proprioceptive to visual dominance continuum. Dominance profiles for encoding of movement trajectory depend on the relative sensory resolution of visual and proprioceptive signals. Conversely, sensory dominance for online control is unrelated to sensory resolution. These results show that the central nervous system can select different combinations of sensory inputs on the basis of the computation in which the resulting estimate will be used. They are partly reminiscent of recent studies demonstrating that coding the position of the arm for movement vector planning would rely mostly on visual input, whereas the estimate used to compute the joint-based motor command would rather rely on proprioceptive signals (e.g., Sober & Sabes, 2003). However, we suggest that such various forms of dominance are subject to an important interindividual variability. Current neuromimetic models predict this variability could be linked to long term adaptive mechanisms varying with subjects’ experience.