Context-Specificity of Locomotor Learning Is Developed during Childhood

Abstract

Humans can perform complex movements with speed and agility in the face of constantly changing task demands. To accomplish this, motor plans are adapted to account for errors in our movements because of changes in our body (e.g., growth or injury) or in the environment (e.g., walking on sand vs ice). It has been suggested that adaptation that occurs in response to changes in the state of our body will generalize across different movement contexts and environments, whereas adaptation that occurs with alterations in the external environment will be context-specific. Here, we asked whether the ability to form generalizable versus context-specific motor memories develops during childhood. We performed a cross-sectional study of context-specific locomotor adaptation in 35 children (3-18 years old) and 7 adults (19-31 years old). Subjects first adapted their gait and learned a new walking pattern on a split-belt treadmill, which has two belts that move each leg at a different speed. Then, subjects walked overground to assess the generalization of the adapted walking pattern across different environments. Our results show that the generalization of treadmill after-effects to overground walking decreases as subjects' age increases, indicating that age and experience are critical factors regulating the specificity of motor learning. Our results suggest that although basic locomotor patterns are established by two years of age, brain networks required for context-specific locomotor learning are still being developed throughout youth.

Keywords: development; generalization; kinematics; locomotion; motor adaptation; motor control.

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.

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.

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 TM_catch 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.

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 OG_early (panel B) and the last OG_late (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 OG_early and OG_late 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.

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 TM_early 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 TM_early 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.

Figure 6.

A, Scatter plots showing the relationship between variability in stepping and OG_early. 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.