Fast but fleeting: adaptive motor learning processes associated with aging and cognitive decline

Abstract

Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly-and that has been linked to explicit memory-and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines.

Keywords: aging; explicit memory; human; motor control; motor learning; state-space model.

Figure 1.

Experimental paradigm and two-state learning model. A, Schedule of force-field perturbations (purple line) applied over the four phases of the experiment. Note that the direction of the perturbations was counterbalanced across participants. At various times during the familiarization and adaptation phases and throughout the error-clamp phase, channel trials (gray bars) were used to track to progression of learning. B, Simulation using the two-state model showing the contributions of the fast (blue trace) and slow (red trace) learning processes to predicted motor performance (adaptation; black trace) across the experiment. C, In the two-state model, each process maintains a separate state (x_f and x_s) estimate, and these sum to provide an estimate of the perturbation (f) that is used as the motor command. Each state is updated based on the error from the previous trial (f − x) weighted by the learning rate (B) and also decays from trial to trial as specified by the retention factor (A).

Figure 2.

A, Illustration of the spatial paired-associate learning (explicit memory) task. During the learning phase (left), the masks at the target locations are removed one at a time revealing either an empty box or a box containing one of the memory stimuli (right). During the test phase (middle), these memory stimuli are presented one at a time at the central home position, and the participant selects the target location they remember being associated with the stimulus. B, C, Average accuracy and reaction time in the explicit memory task (B), and average facilitation scores on the word priming, dot-clearing (implicit memory) task (C) for younger and older adults. Vertical lines represent ±1 SE.

Figure 3.

A, Averages, for younger (blue) and older (red) adults, of the lateral deviation of the hand path at peak velocity throughout the experiment. The height of the shaded regions denote ±1 SE. The ○ and × symbols represent channel trials for younger and older adults, respectively. B, Comparisons between younger and older adults in the mean lateral deviations for trials 2–6 and the last five trials of the adaptation and counter-adaptation phases, respectively.

Figure 4.

The average adaptation index for all channel trials in younger (blue trace) and older (red trace) adults across all phases of the experiment. The height of the shaded regions represents ±1 SE. The blue and red circles represent the comparison of the adaptation index on each trial from 0 for younger and older adults, respectively. The black circles denote the comparison between younger and older adults for each trial. Filled circles indicate that the comparison was significant (p < 0.05).

Figure 5.

The two-state model fit to the individual data of representative younger and older adults. For each individual, the empirical data (adaptation index scores) are plotted for each channel trial as black circles. The motor output predicted by the model (black traces) and the states of the fast (blue traces) and slow (red traces) motor learning processes are shown as a function of trial. The retention factors (A_f, A_s) and learning rates (B_f, B_s) of the fast and slow processes are displayed for each participant, along with the R² value comparing the two-state model with a one-state model.

Figure 6.

A, Average fits for younger (blue) and older (red) adults of the two-state model based on individual fits. The dots represent the average adaptation indices on channel trials for the younger (blue) and older (red) adults. The predicted motor output and the states of the fast and slow learning processes are denoted by solid, dashed, and dotted lines, respectively. The height of the shaded region represents ±1 SE. B, Average slow retention factor for younger and older adults. The vertical lines represent ±1 SE.

Figure 7.

A, Correlation between explicit memory performance and the interaction between the fast and slow retention factors for the older adults. B, The average adaptation index for all channel trials in younger adults (blue trace) and older adults above (light blue trace) and below (red trace) the median explicit memory accuracy. The height of the shaded regions represents ±1 SE.