Motor learning and consolidation: the case of visuomotor rotation

Abstract

Adaptation to visuomotor rotation is a particular form of motor learning distinct from force-field adaptation, sequence learning, and skill learning. Nevertheless, study of adaptation to visuomotor rotation has yielded a number of findings and principles that are likely of general importance to procedural learning and memory. First, rotation learning is implicit and appears to proceed through reduction in a visual prediction error generated by a forward model, such implicit adaptation occurs even when it is in conflict with an explicit task goal. Second, rotation learning is subject to different forms of interference: retrograde, anterograde through aftereffects, and contextual blocking of retrieval. Third, opposite rotations can be recalled within a short time interval without interference if implicit contextual cues (effector change) rather than explicit cues (color change) are used. Fourth, rotation learning consolidates both over time and with increased initial training (saturation learning).

Fig. 1

A. Typical experimental set-up with vision of the arm occluded. B. Directional error seen by a subject when they first are exposed to a 30° CCW rotation; only one target is shown

Fig. 2

Task conditions for conscious versus unconscious learning experiment. Each frame shows the start circle (S) and three of eight surrounding targets. The bull’s-eye pattern indicates the target proper (T_p), and the two open circles are the neighboring targets, 45° away. The arrows indicate the direction of hand and cursor movements (H and C, respectively). A, baseline. B, Early rotation (45° CCW). C, Late rotation. D, Washout. E, Rotation plus strategy. F, Strategy only. In A–D, subjects aim for T_p. In E and F, subjects aim for T_n. Taken from Mazzoni and Krakauer, 2006

Fig. 3

Time course of directional error (mean+/−SE, in degrees) at the endpoint for each group. A, Rotation plus strategy. B, Rotation. C, Strategy. Roman numerals indicate changes in condition or instruction. Taken from Mazzoni and Krakauer, 2006

Fig. 4

Interference with rotation learning by counter-rotation learning 15 minutes later. Rotation learning shown by progressive reduction in the directional error at peak velocity. Points represent the group cycle average, where each cycle is 16 movements. Null, baseline. Task A1, 30° CCW rotation. Task A2, 30° CW rotation. Task A2, 30° CCW rotation. (Remaining conditions not relevant to current discussion). Taken from Miall et al., 2003 (with permission)

Fig. 5

Interval-invariant interference with rotation learning by counter-rotation learning. Rotation learning (open circles and dashed lines) and re-learning (filled circles and solid lines) for four separate groups of 6 subjects A–D. Learning is shown by the progressive reduction of the directional error at peak velocity. Points represent the group average with SE for each cycle of eight movements, are fitted with a double exponential function. E. Percent change in error reduction, calculated from cycles 2–11, from learning to re-learning. Taken from Krakauer et al., 2005

Fig. 6

Decay of after-effects. Bar plots for the mean directional error for A, the first movement and B, the first cycle of the counter-rotation (30° CCW) for groups B–D in Fig. 5

Fig. 7

Evidence for retrograde interference and resistance to interference (consolidation) after washout of anterograde effects. Rotation learning (open circles anddashed lines) and re-learning (filled circles andsolid lines) for four separate groups of 6 subjects (A–D). Learning is shown by the progressive reduction of the directional error at peak velocity. Points represent the group average with SE for each cycle of eight movements, are fitted with a double exponential function. E. Percent change in error reduction, calculated from cycles 2–11, from learning to re-learning. Taken from Krakauer et al., (2005)

Fig. 8

Evidence for effectiveness of an implicit contextual cue: rotation learning at the wrist (R_wrist) is not interfered with by counter-rotation learning at the arm (CR_arm). A, R_wrist on day 2, after R_wrist followed by CR_arm 5 min later on day 1 (group 7, white squares, dashed curve). There was savings from R_wrist on day 1 to R_wrist on day 2 despite CR_arm. The thick black curve represents R_wrist on day 1 (group 1). B, Bar graph showing a statistically significant difference in the reduction in mean directional error in the first six cycles for R_wrist on day 1 versus day 2 (groups 1 and 7, mean difference = 6.49°, p =0.0036). This difference was absent when only CR_arm was learned on day 1, with no statistically significant difference in the reduction in mean directional error in the first six cycles for day 1 versus day 2 (groups 1 and 8, mean difference = 0.328°, p = 0.88). Taken from (Krakauer et al., 2006)

Fig. 9

Evidence for consolidation by saturation learning. Rotation learning (open circles anddashed lines) and re-learning (filled circles andsolid lines) for four separate groups of 6 subjects A–D. Learning is shown by the progressive reduction of the directional error at peak velocity. Points represent the group average with SE for each cycle of eight movements, are fitted with a double exponential function. E. Percent change in error reduction, calculated from cycles 2–11, from learning to re-learning. Taken from Krakauer et al., 2005