(A and B) Paradigms for simulated error-clamp experiment. These paradigms are the same as the paradigm shown in A, except that here one group (the NP group) of participants is exposed to an initial adaptation to a clockwise viscous-curl force field while the other group (the PN group) is exposed to an initial adaptation in the opposite direction (counterclockwise).

(C) Example force trajectories during the course of this learning paradigm. Force trajectories from selected error-clamp trials for one participant in each group are shown as red arrows with tips connected by dashed black lines. The blue line represents the force trajectory required to fully cancel the force field applied during the initial learning block for each participant. The same trials are shown for each participant, and each trial is labeled by a block identifier and the trial number within that block. For example, N97 is the 97th trial in the null-field practice block, A17 is the 17th trial in the initial adaptation block, and F1 is the first trial in the force-channel (error-clamp) block. Since the adaptation requires the production of lateral forces, only lateral forces are shown. Lateral forces (red arrows) in the baseline period are small and inconsistent in direction. However, during the initial adaptation block these lateral forces grow with training so that they nearly cancel the applied force field. After the extinction block, the first trials in the error-clamp block show a near-zero or negative pattern of lateral forces with respect to the forces displayed late in the initial adaptation block. However, by trials 12–15 in the error-clamp block, a small but consistent rebound of the pattern of lateral forces seen during initial adaptation emerges. This rebound substantially fades away by trial 90 in the error-clamp block.

(D) The average time course of adaptive changes in the pattern of lateral forces. Data from both the PN and NP groups are averaged together. The adaptation score corresponding to the force pattern displayed on a particular trial was assessed by computing a force-field compensation factor (see ). In short, this force-field compensation factor measures the fraction of (initial adaptation) force field that would be compensated by the pattern of lateral forces displayed on a particular trial by regressing the measured lateral force pattern onto the ideal pattern of lateral forces required to fully compensate the force field. The transient rebound of motor output in the error-clamp block matches the rebound predicted by the multi-rate model. The blue error bars represent experimental data (mean +/− standard error of the mean.). The green line is the best-fit multi-rate model, and the red and purple lines are the best-fit gain-specific and single-state models. The best-fit model parameters (with 95% confidence intervals) for the multi-rate model were A _{1} = 0.992 (0.990–0.994), B _{1} = 0.02 (0.013–0.025), A _{2} = 0.59 (0.43–0.76), and B _{2} = 0.21 (0.10–0.35).

(E) Summary of results from NP and PN groups. The asterisks indicate significant difference in lateral forces from baseline. Both groups display significant adaptation rebound by trials 10–20 of the error-clamp block compared to the initial error-clamp trials ( *p* < 0.01 for both the NP and PN groups taken separately, and *p* < 0.0001 for all participants taken together) and compared to baseline lateral force levels before learning ( *p* < 0.01 for the NP group, *p* < 0.001 for the PN group, and *p* < 0.0001 for all participants taken together).

NP, negative/positive group; PN, positive/negative group.

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