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Dissociable effects of the implicit and explicit memory systems on learning control of reaching

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Abstract

Adaptive control of reaching depends on internal models that associate states in which the limb experienced a force perturbation with motor commands that can compensate for it. Limb state can be sensed via both vision and proprioception. However, adaptation of reaching in novel dynamics results in generalization in the intrinsic coordinates of the limb, suggesting that the proprioceptive states in which the limb was perturbed dominate representation of limb state. To test this hypothesis, we considered a task where position of the hand during a reach was correlated with patterns of force perturbation. This correlation could be sensed via vision, proprioception, or both. As predicted, when the correlations could be sensed only via proprioception, learning was significantly better as compared to when the correlations could only be sensed through vision. We found that learning with visual correlations resulted in subjects who could verbally describe the patterns of perturbations but this awareness was never observed in subjects who learned the task with only proprioceptive correlations. We manipulated the relative values of the visual and proprioceptive parameters and found that the probability of becoming aware strongly depended on the correlations that subjects could visually observe. In all conditions, aware subjects demonstrated a small but significant advantage in their ability to adapt their motor commands. Proprioceptive correlations produced an internal model that strongly influenced reaching performance yet did not lead to awareness. Visual correlations strongly increased the probability of becoming aware, yet had a much smaller but still significant effect on reaching performance. Therefore, practice resulted in acquisition of both implicit and explicit internal models.

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Acknowledgements

This work was supported by grants from the NIH (NS37422, NS46033).

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Correspondence to Reza Shadmehr.

Appendix

Appendix

We examined the kinematic features of movements in aware and unaware groups. To eliminate the kinematic differences due to different performance level, we compared two groups with similar learning performance, vision 14 cm aware and proprioception unaware groups. Figure 4a displays the average hand paths in the last training set from these two groups. The velocity perpendicular to the movement direction from each group is also displayed in Fig. 4b. For the left movement, both the field and catch trials in these two groups show very similar hand paths and velocity profiles. For the right movement, the aware vision 14 cm group shows less perturbation in both the field and catch trials, indicating larger stiffness of arm in the vision 14 cm group. But the relative ratio of perturbation in the field and catch trials remains similar in the two groups. We found no specific differences in kinematics between aware and unaware groups when the performance level was similar.

Fig. 4
figure 4

No kinematic differences between aware and unaware groups when at similar performance level. a. Average hand paths in the last training set from the aware vision 14 cm group (gray) and unaware proprioception group (black). Solid lines are field trials and dotted lines are catch trials. b. Average profiles of velocity perpendicular to the movement direction. The format is same as in (a)

Figure 5 displays learning index from the matched-aware, proprioceptive cue, visual cue-unaware(7 cm), flipped-aware, flipped-unaware groups as a function of set. An ANOVA test for the block effect in each group that consists of more than two subjects showed statistically significant effect at P<0.05. Because learning index increased monotonically with the set number, we took the mean learning index across sets as an overall learning index for each subject.

Fig. 5
figure 5

Learning index as a function of set number. Error bars represent standard errors of mean

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Hwang, E.J., Smith, M.A. & Shadmehr, R. Dissociable effects of the implicit and explicit memory systems on learning control of reaching. Exp Brain Res 173, 425–437 (2006). https://doi.org/10.1007/s00221-006-0391-0

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  • DOI: https://doi.org/10.1007/s00221-006-0391-0

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