Exploration of joint redundancy but not task space variability facilitates supervised motor learning.
The number of joints and muscles in a human arm is more than what is required for reaching to a desired point in 3D space. Although previous studies have emphasized how such redundancy and the associated flexibility may play an important role in path planning, control of noise, and optimization of motion, whether and how redundancy might promote motor learning has not been investigated. In this work, we quantify redundancy space and investigate its significance and effect on motor learning. We propose that a larger redundancy space leads to faster learning across subjects. We observed this pattern in subjects learning novel kinematics (visuomotor adaptation) and dynamics (force-field adaptation). Interestingly, we also observed differences in the redundancy space between the dominant hand and nondominant hand that explained differences in the learning of dynamics. Taken together, these results provide support for the hypothesis that redundancy aids in motor learning and that the redundant component of motor variability is not noise.
['Singh|Puneet|P|', 'Jana|Sumitash|S|', 'Ghosal|Ashitava|A|', 'Murthy|Aditya|A|']
D000328:Adult D000368:Aged D001132:Arm D001696:Biomechanical Phenomena D004750:Enteral Nutrition D005260:Female D007839:Functional Laterality D006801:Humans D007596:Joints D007858:Learning D008297:Male D008875:Middle Aged D008954:Models, Biological D009048:Motor Skills D011597:Psychomotor Performance D013647:Task Performance and Analysis D055815:Young Adult
reaching minimum-intervention principle motor control motor noise supervised learning