Rapid Adaptation of Reactive Force Control When Lifting Objects

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Markovik, Simona
Precision Grip , Reactive Motor Control , Motor Control
The control of object manipulation tasks involves the close interplay of predictive and reactive control mechanisms. For example, when lifting an object, people typically predict the weight based on object size and material as well as sensorimotor memory obtained from previous lifts of the object. When lifting objects with a precision grip, people increase vertical load force to a target level that slightly exceeds the predicted weight. When the object is heavier than expected, the mismatch between expected and actual tactile signals associated with lift-off triggers a corrective action within ~100 ms, that involves probing increases in load force that continue until the object is lifted. Here we investigated whether this correction action can be adaptively influenced by experience. Participants repeatedly lifted an object that was instrumented with force sensors to measure the forces applied by the fingertips, with weight that could be varied without the knowledge of the participant. In 80% of trials, the weight was set to 2 N and, in different blocks of 110 trials, the remaining 20 % of trials (2 trials randomly selected from each successive 10 trials) was set to either 4 or 6 N. We found that the rate of change of the reflexively triggered increase in load force that occurred in the 4 or 6 N trials, scaled with the additional weight. That is, following the initial increase in load force to ~2 N, the subsequent increase in load force was more rapid for the 6 N object than the 4 N object. In contrast, the onset time of the reactive increase in load force was independent of the additional weight. Finally, this adaptation of reactive load force control took place quickly and was evident after only a few lifts of the heavier weight. These results indicate that the reactive increases in load force that occur when a lifted object is heavier than expected can be adapted and tuned, to refine behavior. This further suggests that multiple predictions can be generated about object weight when lifting.
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