Short-term savings after washout.

<p>A) Angular reach errors during the first presentation of a visuomotor disturbance, washout (while grasping robot) and subsequent presentation of the same disturbance B) Inferred body and world rotation parameters during adaptation and the corresponding probability of relevance. C) Angular reach errors from first and second presentation of visuomotor disturbance overlaid.</p

Error clamps and spontaneous rebound.

<p>A) Inferred body and world rotation parameters and probability of relevance during adaptation to a visuomotor disturbance and subsequent error clamp. In the error clamp, feedback indicates a lack of errors regardless of movements. B) Experimental data of normalized reaching forces during adaptation to a force disturbance and subsequent error clamp (reproduced from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002210#pcbi.1002210-Scheidt1" target="_blank">[24]</a>). C) Inferred body and world rotations and the probability of relevance during presentation of a visuomotor disturbance, visuomotor disturbance of opposite orientation and subsequent error clamp. D) Experimental data of normalized reaching forces during a force disturbance, opposite disturbance and subsequent error clamp (reproduced from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002210#pcbi.1002210-Smith1" target="_blank">[5]</a>).</p

Savings after a gradually introduced disturbance.

<p>A) Inferred body and world rotations and probability of relevance while a disturbance is gradually introduced, washout (after experiment has ended) and presentation of full disturbance on a second day. B) Angular reach errors on first and second day after adapting to a gradually (grey lines), or suddenly (black lines) introduced disturbance. C) Experimental findings of same adaptations (reproduced from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002210#pcbi.1002210-Klassen1" target="_blank">[23]</a>).</p

The likelihood of relevance.

<p>A) Before adapting, estimates for body and world disturbances are zero. The hand's path, along with the estimated hand and cursor location, fall along a straight path to the target. The large observed errors (red and blue arrows) of the perturbed visual display indicate the likelihood of a world disturbance being relevant is high. B) During adaptation, the hand's path is adjusted to compensate for the estimated body and world disturbances. Even though errors between the estimated cursor location and the observed cursor location have been reduced (blue arrow), the large error between the estimated hand location and the observed feedback (red arrow) continues to indicate the likelihood for the world parameter relevance is still high.</p

Long-term savings and interference.

<p>A) Inferred body and world rotations and the corresponding probability of relevance during the first presentation of a visuomotor disturbance, washout (after experiment has ended) and subsequent presentation of the same disturbance on a second day. B) Angular reach errors from the first and second presentation of the visuomotor disturbance overlaid. C) Experimental findings after the same adaptation (reproduced from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002210#pcbi.1002210-Krakauer3" target="_blank">[19]</a>). D) Inferred body and world rotations and probability of relevance during a visuomotor disturbance, an oppositely oriented disturbance, washout (after experiment has ended) and subsequent presentation of the original disturbance on a second day. E) Angular reach errors from the first and second presentation of disturbance overlaid. F) Experimental findings after same adaptation (reproduced from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002210#pcbi.1002210-Krakauer3" target="_blank">[19]</a>).</p

Example subjects and model data in the <i>CLIFF+NOISE LARGE</i> block.

<p>A), D) Across-subject/model average trajectories for position and force, respectively. B), E) The subject and model with the best fit. C), F) The subject and model with the poorest fit. In all panels solid and dashed lines indicate subject and model mean trajectories, respectively. Shaded regions represent either +/− SEM (panels A and D) or +/− standard deviation across trajectories (remaining panels).</p

Example subjects and model data in the <i>NULL</i> block (velocity profiles not shown).

<p>A), D) Across-subject/model average trajectories for position and force, respectively. B), E) The subject and model with the best fit. C), F) The subject and model with the poorest fit. In all panels solid and dashed lines indicate subject and model mean trajectories, respectively. Shaded regions represent either +/− SEM (panels A and D) or +/− standard deviation across trajectories (remaining panels).</p

Example subjects and model data in the <i>CLIFF</i> block (velocity profiles not shown).

<p>A), D) Across-subject/model average trajectories for position and force, respectively. B), E) The subject and model with the best fit. C), F) The subject and model with the poorest fit. In all panels solid and dashed lines indicate subject and model mean trajectories, respectively. Shaded regions represent either +/− SEM (panels A and D) or +/− standard deviation across trajectories (remaining panels).</p

Experimental set up and display.

<p>Subjects were seated in front of a screen, holding a handle mounted to a force transducer. By pushing/pulling on the handle subjects accelerated/decelerated the vertical motion of a cursor that moved horizontally across the screen. On the right edge of the screen was a color-coded target that depicted rewards decreasing quadractically from the central target.</p

The four averaged behavioral metrics (peak vertical displacement, mean cursor position, peak positive and negative forces) of individual subjects plotted against their model predictions.

<p>The dashed line represents a one-to-one relationship between subject behavior and model predictions while the blue line is the least squares regression fit to the data. The slope and 95% confidence interval for each fit are displayed in the plots. Individual subjects are depicted with various shapes and the four blocks are color-coded (<i>NULL</i>: light blue, <i>CLIFF</i>: pink, <i>CLIFF</i>+<i>NOISE-SMALL</i>: green, and <i>CLIFF</i>+<i>NOISE-LARGE</i>: purple).</p