Abstract
In our daily life we often make complex actions comprised of linked movements, such as reaching for a cup of coffee and bringing it to our mouth to drink. Recent work has highlighted the role of such linked movements in the formation of independent motor memories, affecting the learning rate and ability to learn opposing force fields. However, while such work has described the angular generalization function representing the neural tuning of motor memory formation in state space, we have no understanding of how different movement kinematics (such as distance, speed or duration) affects the formation of these independent motor memories. Here we investigate such kinematic generalization for both passive and visual lead-in movements to probe their individual characteristics. After participants adapted to opposing force fields using training lead-in movements, the lead-in kinematics were modified on random trials to test generalization. For both visual and passive modalities, predictive compensation was sensitive to lead-in duration and peak speed, falling off away from the training condition. However, little decay was found with increasing lead-in distance. Interestingly, asymmetric transfer between lead-in movement modalities was also observed, with partial transfer from passive to visual, but very little vice versa. Overall these tuning effects were stronger for passive compared to visual lead-ins demonstrating the difference in these sensory inputs in regulating motor memories. Our results suggest these effects are a consequence of state estimation, with differences across modalities reflecting their different levels of sensory uncertainty arising as a consequence of dissimilar feedback delays.
Significance Statement Using a force field interference paradigm, we show that the generalization of motor memory is strongly tuned to variations in lead-in kinematics, with passive lead-ins exhibiting a stronger influence and sharper tuning than visual lead-ins. This asymmetry is mirrored in the transfer of adaptation between modalities, with stronger transfer from the passive to visual condition. We suggest these differences arise due to state estimation during the lead-in, with larger delays in visual signals increasing their uncertainty. This reduces their feedback weighting compared to proprioceptive signals, producing a smaller estimated state change, and therefore smaller decay in predictive force. Overall these results provide further evidence that the human motor system uses observer-based control, based on a forward model to estimate state.
Footnotes
Conflict of Interest The authors declare that they have no financial, personal, or professional interests that could be construed to have influenced the paper.
Title page for the Journal of Neuroscience