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Randomized Controlled Trial
. 2012 Dec;108(12):3313-21.
doi: 10.1152/jn.00122.2012. Epub 2012 Sep 12.

Can proprioceptive training improve motor learning?

Affiliations
Randomized Controlled Trial

Can proprioceptive training improve motor learning?

Jeremy D Wong et al. J Neurophysiol. 2012 Dec.

Abstract

Recent work has investigated the link between motor learning and sensory function in arm movement control. A number of findings are consistent with the idea that motor learning is associated with systematic changes to proprioception (Haith A, Jackson C, Mial R, Vijayakumar S. Adv Neural Inf Process Syst 21: 593-600, 2008; Ostry DJ, Darainy M, Mattar AA, Wong J, Gribble PL. J Neurosci 30: 5384-5393, 2010; Vahdat S, Darainy M, Milner TE, Ostry DJ. J Neurosci 31: 16907-16915, 2011). Here, we tested whether motor learning could be improved by providing subjects with proprioceptive training on a desired hand trajectory. Subjects were instructed to reproduce both the time-varying position and velocity of novel, complex hand trajectories. Subjects underwent 3 days of training with 90 movement trials per day. Active movement trials were interleaved with demonstration trials. For control subjects, these interleaved demonstration trials consisted of visual demonstration alone. A second group of subjects received visual and proprioceptive demonstration simultaneously; this group was presented with the same visual stimulus, but, in addition, their limb was moved through the target trajectory by a robot using servo control. Subjects who experienced the additional proprioceptive demonstration of the desired trajectory showed greater improvements during training movements than control subjects who only received visual information. This benefit of adding proprioceptive training was seen in both movement speed and position error. Interestingly, additional control subjects who received proprioceptive guidance while actively moving their arm during demonstration trials did not show the same improvement in positional accuracy. These findings support the idea that the addition of proprioceptive training can augment motor learning, and that this benefit is greatest when the subject passively experiences the goal movement.

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Figures

Fig. 1.
Fig. 1.
Experimental apparatus and learning task. A: subjects performed arm movements while grasping a robotic manipulandum and attempted to draw a perfect circle. B: position trace of the circle in space (x and y coordinates) and as functions of time for example subject: final baseline movement, shown in black, relative to desired movement, in gray.
Fig. 2.
Fig. 2.
Motor learning. A: cross correlation index: mean (±SE) cross correlation index of performed movement to desired movement, averaged in bins of 10 movements. An index of 0 indicates no difference between the produced and desired movement trajectories. Data are from passive (PASS) subjects and control (CTRL) subjects. B: mean cross correlation index averaged across training days. Statistical significance: *P < 0.05; **P < 0.01.
Fig. 3.
Fig. 3.
Mean tangential velocity. A: mean (±SE) tangential velocity for subjects in the PASS group and the CTRL group, averaged in 10 movement bins. Subjects learn to generate movements close to the average velocity profile (shown by dashed line). B: averaged across training days (*P < 0.05).
Fig. 4.
Fig. 4.
Positional error. A: mean (±SE) absolute radial error throughout learning for PASS and CTRL subject groups, averaged over 10 movement bins. Subjects demonstrate reduction of this error over the course of learning. B: averaged across training days (**P < 0.01).
Fig. 5.
Fig. 5.
Cross correlation index: data as shown in Fig. 2 (means ± SE), with the addition of reverse (REV) subjects and active (ACT) subjects. Again, data were averaged over 10 movement bins.
Fig. 6.
Fig. 6.
Mean tangential velocity: data as shown in Fig. 3 (means ± SE), with the addition of REV subjects and ACT subjects. Data were averaged over 10 movement bins.
Fig. 7.
Fig. 7.
Positional error: data as shown in Fig. 2 (means ± SE), with the addition of REV subjects and ACT subjects. Data averaged over 10 movement bins.
Fig. 8.
Fig. 8.
Cursive writing experiment. In this experiment subjects were required to copy the written proper noun “Liz,” shown from an overhead view (left) and by x (top right) and y (bottom right) coordinates as functions of time. One example subject, final baseline movement, is shown in black relative to the desired movement in gray.
Fig. 9.
Fig. 9.
Cross correlation index of produced to desired hand position for subjects in the PASS and CTRL groups on the cursive writing task across the 3 training days.

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