Reach Adaptation: What Determines Whether We Learn an Internal Model of the Tool or Adapt the Model of Our Arm?
- 1 September 2008
- journal article
- research article
- Published by American Physiological Society in Journal of Neurophysiology
- Vol. 100 (3) , 1455-1464
- https://doi.org/10.1152/jn.90334.2008
Abstract
We make errors when learning to use a new tool. However, the cause of error may be ambiguous: is it because we misestimated properties of the tool or of our own arm? We considered a well-studied adaptation task in which people made goal-directed reaching movements while holding the handle of a robotic arm. The robot produced viscous forces that perturbed reach trajectories. As reaching improved with practice, did people recalibrate an internal model of their arm, or did they build an internal model of the novel tool (robot), or both? What factors influenced how the brain solved this credit assignment problem? To investigate these questions, we compared transfer of adaptation between three conditions: catch trials in which robot forces were turned off unannounced, robot-null trials in which subjects were told that forces were turned off, and free-space trials in which subjects still held the handle but watched as it was detached from the robot. Transfer to free space was 40% of that observed in unannounced catch trials. We next hypothesized that transfer to free space might increase if the training field changed gradually, rather than abruptly. Indeed, this method increased transfer to free space from 40 to 60%. Therefore although practice with a novel tool resulted in formation of an internal model of the tool, it also appeared to produce a transient change in the internal model of the subject's arm. Gradual changes in the tool's dynamics increased the extent to which the nervous system recalibrated the model of the subject's own arm.Keywords
This publication has 37 references indexed in Scilit:
- Adaptive Control of Saccades via Internal FeedbackJournal of Neuroscience, 2008
- Are there distinct neural representations of object and limb dynamics?Experimental Brain Research, 2006
- Dissociable effects of the implicit and explicit memory systems on learning control of reachingExperimental Brain Research, 2006
- Adaptation and generalization in acceleration-dependent force fieldsExperimental Brain Research, 2005
- Neural Correlates of Reach ErrorsJournal of Neuroscience, 2005
- Internal models of limb dynamics and the encoding of limb stateJournal of Neural Engineering, 2005
- Learned Dynamics of Reaching Movements Generalize From Dominant to Nondominant ArmJournal of Neurophysiology, 2003
- MOSAIC Model for Sensorimotor Learning and ControlNeural Computation, 2001
- The Motor System Does Not Learn the Dynamics of the Arm by Rote Memorization of Past ExperienceJournal of Neurophysiology, 1997
- Motor learning by field approximation.Proceedings of the National Academy of Sciences, 1996