CUED Publications database

Rapid visuomotor feedback gains are tuned to the task dynamics.

Franklin, S and Wolpert, DM and Franklin, DW (2017) Rapid visuomotor feedback gains are tuned to the task dynamics. J Neurophysiol. jn.00748.2016-.

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Abstract

Adaptation to novel dynamics requires learning a motor memory, or a new pattern of predictive feedforward motor commands. Recently we demonstrated the up-regulation of rapid visuomotor feedback gains early in curl force field learning, which decrease once a predictive motor memory is learned. However, even after learning is complete, these feedback gains are higher than those observed in the null field trials. Interestingly these up-regulated feedback gains in the curl field were not observed in a constant force field. We therefore suggest that adaptation also involves selectively tuning the feedback sensitivity of the sensorimotor control system to the environment. Here we test this hypothesis by measuring the rapid visuomotor feedback gains after subjects adapt to a variety of novel dynamics generated by a robotic manipulandum in three experiments. To probe the feedback gains, we measured the magnitude of the motor response to rapid shifts in the visual location of the hand during reaching. While the feedback gain magnitude remained similar over a larger than a four-fold increase in constant background load, the feedback gains scaled with increasing lateral resistance and increasing instability. The third experiment demonstrated that the feedback gains could also be independently tuned to perturbations to the left and right depending on the lateral resistance, demonstrating the fractionation of feedback gains to environmental dynamics. Our results demonstrate that the sensorimotor control system regulates the gain of the feedback system as part of the adaptation process to novel dynamics, appropriately tuning them to the environment.

Item Type: Article
Uncontrolled Keywords: adaptation learning motor control reaching movement visuomotor feedback
Subjects: UNSPECIFIED
Divisions: Div F > Computational and Biological Learning
Depositing User: Cron Job
Date Deposited: 27 Aug 2017 20:08
Last Modified: 14 Sep 2017 01:28
DOI: