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Research ArticleResearch Article: New Research, Cognition and Behavior

Context-Specificity of Locomotor Learning Is Developed during Childhood

Dulce M. Mariscal, Erin V. L. Vasudevan, Laura A. Malone, Gelsy Torres-Oviedo and Amy J. Bastian
eNeuro 28 March 2022, 9 (2) ENEURO.0369-21.2022; https://doi.org/10.1523/ENEURO.0369-21.2022
Dulce M. Mariscal
1Bioengineering Department, University of Pittsburgh, Pittsburgh, PA 15260
2Center for Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA 15213
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  • ORCID record for Dulce M. Mariscal
Erin V. L. Vasudevan
6Kennedy Krieger Institute, Baltimore, MD, 21205
7School of Health Technology and Management, Stony Brook University, Stony Brook, NY, 11794
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Laura A. Malone
4Neurology Department, Johns Hopkins University, Baltimore, MD, 21205
5Physical Medicine, and Rehabilitation Department, Johns Hopkins University, Baltimore, MD, 21205
6Kennedy Krieger Institute, Baltimore, MD, 21205
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Gelsy Torres-Oviedo
1Bioengineering Department, University of Pittsburgh, Pittsburgh, PA 15260
2Center for Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA 15213
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Amy J. Bastian
3Neuroscience Department, Johns Hopkins University, Baltimore, MD, 21205
6Kennedy Krieger Institute, Baltimore, MD, 21205
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    Figure 1.

    A, Overall paradigm. In all groups, baseline behavior was recorded overground and subsequently on the treadmill. Then subjects were adapted for a total of 15 min divided into three blocks of 5 min each separated by a break. A 10-s catch condition was introduced when subjects had been adapted for 10 min. Aftereffects were also assessed overground after 5 min of re-adaptation to the split condition. Finally, subjects returned to the treadmill where they walked for 5 min to determine the washout of learning specific to the treadmill from the remaining aftereffects. B, Diagram of marker locations. Limb angle convention is shown on the stick figure. C, Limb angle trajectories plotted as a function of time in early split-belt adaptation; two cycles are shown. Limb angles are positive when the limb is in front of the trunk (flexion). Phase quantifies the lag producing the largest cross-correlation between the two legs. When the legs move in anti-phase, the lag of 0.5 leads to the largest cross-correlation. D, Limb angle trajectories are shown in gray and angle axes about which each leg oscillates are shown in black. In this example, slow limb (solid line) oscillates more forward with respect to the vertical axis than the fast limb (dashed line). The center of oscillation quantifies the difference in where the legs oscillate, illustrated by the distance between two black lines. E, An example of kinematic data of two consecutive steps is shown. Kinematic data for every two steps were used to calculate step symmetry, defined as the difference in step lengths normalized by the sum of step lengths.Figure Contributions: Gelsy Torres-Oviedo created schematics for general paradigm and gait parameters.

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    Figure 2.

    A, Time courses for gait parameters characterizing the behavior during split-belt walking of all age groups. Every dot represents the group average of five strides and color shaded areas indicate standard error (SE). Children adapted their gait more slowly during the split-belt condition. For visualization purposes, gray background indicates the strides used for computing Adapt, used in the scatter plots in panel B. B, Correlation results of Age versus Adapt before overground walking. Adapt quantified the extent to which subjects changed their gait during the adaptation period. Large numbers indicate more adjustments during split-belt walking. Dots indicate individual subjects’ data and colors indicate subjects age groups. We found a significant effect of age in phase shift and step length asymmetry, indicating that younger subjects adapted less over the same period of split-belt walking than older children or young adults. This effect is not observed in the center of oscillation, which is a more variable parameter. Dotted line is shown as reference for a linear regression. Arbitrary units (a.u.).Figure Contributions: Gelsy Torres-Oviedo, Erin Vasudevan, and Laura Malone performed the experiments. Dulce Mariscal and Gelsy Torres-Oviedo analyzed the data.

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    Figure 3.

    A, Time courses during catch condition for two age groups. Every dot represents the group average of five strides and color shaded areas indicate SE. Gray area indicates the strides used for the regression analysis displayed in panel B. B, Correlations results of Age versus aftereffects on the treadmill during the catch trial (TMcatch); y-axis indicates the magnitude of aftereffects on the treadmill TMcatch for each individual; x-axis indicates the age of each participant at the time of the experiment. Dots indicate individual subjects’ data and colors indicate subjects’ age group. We did not find an age effect indicating that all individuals recalibrated their movements after split-belt walking. Arbitrary units (a.u.).Figure Contributions: Gelsy Torres-Oviedo, Erin Vasudevan, and Laura Malone performed the experiments. Dulce Mariscal and Gelsy Torres-Oviedo analyzed the data.

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    Figure 4.

    A, Time courses during over ground walking for two age groups. Every dot represents the group average of five strides and color shaded areas indicate SE. Gray area indicates the strides used for the regression analysis displayed in panels B, C. B, C, Regression analyses showing the relation between age and aftereffects during the initial OGearly (panel B) and the last OGlate (panel C) steps of the postadaptation period overground in all kinematic parameters. Dots indicate individual subjects’ data and colors indicate the different age groups. Age was a significant predictor of OGearly and OGlate in all step length asymmetry and phase shift, such that younger subjects exhibited greater aftereffects overground than older children and young adults. Dotted line is shown as reference for a linear regression. Arbitrary units (a.u.).Figure Contributions: Gelsy Torres-Oviedo, Erin Vasudevan, and Laura Malone performed the experiments. Dulce Mariscal and Gelsy Torres-Oviedo analyzed the data.

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    Figure 5.

    A, Time courses during treadmill walking postadaptation for two age groups. Every dot represents the group average of five strides and color shaded areas indicate SE. Gray area indicates the strides used for the regression analysis displayed in panels B. B, Correlations analyses showing the relation between age and aftereffects during the initial TMearly steps of the postadaptation period on the treadmill in all kinematic parameters. Colors indicate the different age groups. Dots indicate individual subjects’ data. Age was a significant predictor of TMearly in all step length asymmetry, such that younger subjects exhibited greater aftereffects overground than older children and young adults. Dotted line is shown as reference for a linear regression. Arbitrary units (a.u.).Figure Contributions: Gelsy Torres-Oviedo, Erin Vasudevan, and Laura Malone performed the experiments. Dulce Mariscal and Gelsy Torres-Oviedo analyzed the data.

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    Figure 6.

    A, Scatter plots showing the relationship between variability in stepping and OGearly. Colors indicate the different sensory conditions. Variability in behavior was a significant factor that predicted the transfer of adaptation effects to over ground walking. The magnitude of transfer was positively related to the subjects’ behavior variability: the more variable were subjects during adaptation, the more carry-over of aftereffects to over ground. B, Scatter plots showing the correlation between age and baseline variability. There is a significant correlation between age and baseline variability in all gait parameters. These regressions show that children become less variable as in their gait pattern as they develop during childhood. Arbitrary units (a.u.).Figure Contributions: Gelsy Torres-Oviedo, Erin Vasudevan, and Laura Malone performed the experiments. Dulce Mariscal and Gelsy Torres-Oviedo analyzed the data.

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    Table 1.

    Age group characteristics

    Age groupNumber of subjectsNumber of femalesAge range (years)Mean ± SD (years)Mean speeds (m/s; slow, fast)
    3–5 y/o723.1–5.94.7 ± 0.9(0.49, 0.98)
    6–8 y/o726.5–9.07.9 ± 1.0(0.79, 1.57)
    9–11 y/o729.4–11.010.5 ± 0.6(0.75, 1.5)
    12–14 y/o7212.4–14.313.3 ± 0.7(0.88, 1.76)
    15–17 y/o7315.1–17.916.3 ± 1.2(0.95, 1.90)
    Young adults (>18 y/o)7319.6–31.525.5 ± 4.0(0.94, 1.89)
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Context-Specificity of Locomotor Learning Is Developed during Childhood
Dulce M. Mariscal, Erin V. L. Vasudevan, Laura A. Malone, Gelsy Torres-Oviedo, Amy J. Bastian
eNeuro 28 March 2022, 9 (2) ENEURO.0369-21.2022; DOI: 10.1523/ENEURO.0369-21.2022

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Context-Specificity of Locomotor Learning Is Developed during Childhood
Dulce M. Mariscal, Erin V. L. Vasudevan, Laura A. Malone, Gelsy Torres-Oviedo, Amy J. Bastian
eNeuro 28 March 2022, 9 (2) ENEURO.0369-21.2022; DOI: 10.1523/ENEURO.0369-21.2022
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Keywords

  • development
  • generalization
  • kinematics
  • locomotion
  • motor adaptation
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