Sensorimotor adaptation error signals are derived from realistic predictions of movement outcomes

Abstract

Neural systems that control movement maintain accuracy by adaptively altering motor commands in response to errors. It is often assumed that the error signal that drives adaptation is equivalent to the sensory error observed at the conclusion of a movement; for saccades, this is typically the visual (retinal) error. However, we instead propose that the adaptation error signal is derived as the difference between the observed visual error and a realistic prediction of movement outcome. Using a modified saccade-adaptation task in human subjects, we precisely controlled the amount of error experienced at the conclusion of a movement by back-stepping the target so that the saccade is hypometric (positive retinal error), but less hypometric than if the target had not moved (smaller retinal error than expected). This separates prediction error from both visual errors and motor corrections. Despite positive visual errors and forward-directed motor corrections, we found an adaptive decrease in saccade amplitudes, a finding that is well-explained by the employment of a prediction-based error signal. Furthermore, adaptive changes in movement size were linearly correlated to the disparity between the predicted and observed movement outcomes, in agreement with the forward-model hypothesis of motor learning, which states that adaptation error signals incorporate predictions of motor outcomes computed using a copy of the motor command (efference copy).

The relative importance of retinal error and prediction in saccadic adaptation

“…In the Large-On condition, retinal error was 0.69 Ϯ 0.50°and target step size was Ϫ1.66 Ϯ 0.31°. Again, granting that small positive retinal errors cause amplitudedecreasing adaptation (Wong and Shelhamer 2010), if both errors were equally effective at evoking adaptation there should be ϳ40% more adaptation in session 2 relative to session 1; instead, we found 200% more adaptation in session 2. Specifically, the amplitude decrease was 0.31°in session 1 (from 11.82 Ϯ 0.12°to 11.51 Ϯ 0.15°) and 1.54°in session 2 (from 11.65 Ϯ 0.12°to 10.11 Ϯ 0.12°).…”

“…Here we altered the distributions of retinal error by removing the target on selected trials. Wong and Shelhamer (2010) took advantage of the fact that large saccades tend to fall short of the target and displaced the target during the saccade to a position about midway between its initial position and the mean saccade landing position. This situation created a mean positive retinal error, which would be expected to cause an increase in saccade amplitude.…”

“…Deubel (1991) showed that an intrasaccadic shift of a large random grating, containing a transient target that could not be identified after the saccade, resulted in saccade adaptation, suggesting that there was a low-level mechanism for visual comparison across a saccade. More directly, when subjects were instructed to make saccades 75% of the way to a target and the target was stepped back by Ͻ25%, the saccade amplitude decreased, even though the target lay beyond the fovea after the saccades (Bahcall and Kowler 2000), a result similar to that of Wong and Shelhamer (2010). Furthermore, adaptation occurs when subjects make saccades to the center of a circular array of dots that makes an intrasaccadic step, even though there is no single stimulus near the fovea (Bahcall and Kowler 2000).…”

Generalization patterns for reach adaptation and proprioceptive recalibration differ after visuomotor learning

“…We have previously suggested that two independent error signals, 1) the discrepancy between the desired and actual movement, known as the sensorimotor error signal (Wong and Shelhamer 2011), and 2) the discrepancy between visual and proprioceptive estimates of hand position, which we refer to as the cross-sensory error signal, may be primarily responsible for changes in movements and felt hand position, respectively . Furthermore, changes in felt hand position may contribute to reach adaptation when only a cross-sensory error signal is present Salomonczyk et al 2013).…”

Visual cues that are effective for contextual saccade adaptation

“…There is increasing evidence that saccade adaptation uses sensory prediction errors as its key error signal (Bahcall and Kowler 2000;Chen-Harris et al 2008;Ethier et al 2008;Wong and Shelhamer 2011;Collins and Wallman 2012;Herman et al 2013b), rather than simple sensory (retinal) error (Wallman and Fuchs 1998;Noto and Robinson 2001). In the parlance of internal model theories, a "forward model" estimates the predicted sensory error of a movement, while an "inverse model" translates the desired movement goal into the necessary motor commands to control the dynamics of the eye and muscle plant.…”