CUED Publications database

The temporal evolution of feedback gains rapidly update to task demands.

Dimitriou, M and Wolpert, DM and Franklin, DW (2013) The temporal evolution of feedback gains rapidly update to task demands. J Neurosci, 33. pp. 10898-10909.

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Recent theoretical frameworks such as optimal feedback control suggest that feedback gains should modulate throughout a movement and be tuned to task demands. Here we measured the visuomotor feedback gain throughout the course of movements made to "near" or "far" targets in human subjects. The visuomotor gain showed a systematic modulation over the time course of the reach, with the gain peaking at the middle of the movement and dropping rapidly as the target is approached. This modulation depends primarily on the proportion of the movement remaining, rather than hand position, suggesting that the modulation is sensitive to task demands. Model-predictive control suggests that the gains should be continuously recomputed throughout a movement. To test this, we investigated whether feedback gains update when the task goal is altered during a movement, that is when the target of the reach jumped. We measured the visuomotor gain either simultaneously with the jump or 100 ms after the jump. The visuomotor gain nonspecifically reduced for all target jumps when measured synchronously with the jump. However, the visuomotor gain 100 ms later showed an appropriate modulation for the revised task goal by increasing for jumps that increased the distance to the target and reducing for jumps that decreased the distance. We conclude that visuomotor feedback gain shows a temporal evolution related to task demands and that this evolution can be flexibly recomputed within 100 ms to accommodate online modifications to task goals.

Item Type: Article
Uncontrolled Keywords: Adult Analysis of Variance Data Interpretation, Statistical Electromyography Feedback, Psychological Female Goals Humans Male Models, Neurological Movement Photic Stimulation Psychomotor Performance Robotics Young Adult
Divisions: Div F > Computational and Biological Learning
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:14
Last Modified: 17 Jul 2018 06:08