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. 2017 Jan 1;117(1):412-428.
doi: 10.1152/jn.01141.2015. Epub 2016 Nov 2.

Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning

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Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning

Alit Stark-Inbar et al. J Neurophysiol. .

Abstract

In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain.

New & noteworthy: We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the alternating serial reaction time task, exhibited good test-retest reliability in measures of learning and performance. However, the learning measures did not correlate between the two tasks, arguing against a shared process for implicit motor learning.

Keywords: adaptation; implicit learning; individual differences; reliability; sequence learning.

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Figures

Fig. 1.
Fig. 1.
Experimental tasks. A: visuomotor adaptation (VMA) task. The perturbation followed a pseudorandom walk of a global sinusoidal pattern. B: serial reaction time (SRT) task. On Random blocks (R) the stimulus positions were selected randomly, and on Sequence blocks (S) the stimulus positions followed a repeating 12-element sequence. C: alternating serial reaction time (ASRT) task. Odd-numbered elements follow a fixed sequence, and even-numbered elements are selected at random (r). This creates high- and low-frequency triplets (see text).
Fig. 2.
Fig. 2.
VMA results (n = 100). A: group average response (red, shaded region is group SE) to a gradual perturbation (black). For visualization purposes, the response function has been flipped, although the actual changes in movement heading were in the opposite direction of the perturbation. B: reliability of movement time, spatial variability, and learning rate between run 1 and run 2 (circles correspond to individual participants). Baseline movement time and spatial variability measures are taken from the baseline block. Learning rate is estimated from the model fit of the data from the perturbation blocks. C: correlations between different measures of performance. In all figures, r and P values represent the strength and significance of the Pearson correlation coefficients of the linear dependence between the variables of interest. Orthogonal (Deming) regression lines evaluate the relationship between variables of interest, without making assumptions concerning their dependence or independence.
Fig. 3.
Fig. 3.
SRT results (n = 53). A: group average of median RT (left) and accuracy (Acc; right) for run 1 (blue) and run 2 (red). Shaded areas represent group SE. B: reliability of RT, temporal variability, and learning between the run 1 and run 2 scores. Baseline metrics of RT and the SD of RT are taken from blocks 2–4 (early in training). Learning is calculated from the last 4 blocks (Random blocks 13 and 15 minus Sequence blocks 12 and 14). C: correlation between different measures of performance. D: reliability of learning (left) and correlation of learning and baseline metrics of learning at the midway probe (Random block 7 minus Sequence blocks 6 and 8) (center and right).
Fig. 4.
Fig. 4.
ASRT results (n = 25). A: group average of median RT for run 1 and run 2 (left), divided into low- and high-frequency triplets (center), and as difference scores (right). B: reliability of RT, temporal variability, and learning between run 1 and run 2 scores. Baseline metrics of RT and the SD of RT are based on data from blocks 2 and 3 (early in training); learning is averaged over blocks 4–45. C: correlations between different measures of performance.
Fig. 5.
Fig. 5.
Between-task correlations of learning scores. A: correlation between learning measures of visuomotor adaptation SRT using the final probe of SRT learning (left) and midway SRT learning (right). B: correlation between learning measures on visuomotor adaptation and ASRT. Note that the positive correlation is largely influenced by the participant who had the fastest rate of adaptation and exhibited the largest amount of sequence learning. When the correlation is recalculated without this individual, there is no correlation between the learning measures for the 2 tasks (r = −0.17, P = 0.48). C: histogram of responses on Likert scale to survey question probing awareness of the perturbation (VMA) or sequence (SRT and ASRT). Low values correspond to low awareness; high values correspond to high awareness. Although all of the scores are toward the lower end, there is a rightward shift of the distribution for the SRT task, indicative of higher awareness of the presence of a sequence.

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References

    1. Bachman JC. Specificity vs. generality in learning and performing two large muscle motor tasks. Res Q 32: 3–11, 1961.
    1. Baddeley RJ, Ingram HA, Miall RC. System identification applied to a visuomotor task: near-optimal human performance in a noisy changing task. J Neurosci 23: 3066–3075, 2003. - PMC - PubMed
    1. van Beers RJ. Motor learning is optimally tuned to the properties of motor noise. Neuron 63: 406–417, 2009. - PubMed
    1. Bernard JA, Seidler RD. Cerebellar contributions to visuomotor adaptation and motor sequence learning: an ALE meta-analysis. Front Hum Neurosci 7: 27, 2013. - PMC - PubMed
    1. Bernard JA, Seidler RD, Hassevoort KM, Benson BL, Welsh RC, Wiggins JL, Jaeggi SM, Buschkuehl M, Monk CS, Jonides J, Peltier SJ. Resting state cortico-cerebellar functional connectivity networks: a comparison of anatomical and self-organizing map approaches. Front Neuroanat 6: 31, 2012. - PMC - PubMed

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