Visuomotor adaptation needs a validation of prediction error by feedback error

Abstract

The processes underlying short-term plasticity induced by visuomotor adaptation to a shifted visual field are still debated. Two main sources of error can induce motor adaptation: reaching feedback errors, which correspond to visually perceived discrepancies between hand and target positions, and errors between predicted and actual visual reafferences of the moving hand. These two sources of error are closely intertwined and difficult to disentangle, as both the target and the reaching limb are simultaneously visible. Accordingly, the goal of the present study was to clarify the relative contributions of these two types of errors during a pointing task under prism-displaced vision. In “terminal feedback error” condition, viewing of their hand by subjects was allowed only at movement end, simultaneously with viewing of the target. In “movement prediction error” condition, viewing of the hand was limited to movement duration, in the absence of any visual target, and error signals arose solely from comparisons between predicted and actual reafferences of the hand. In order to prevent intentional corrections of errors, a subthreshold, progressive stepwise increase in prism deviation was used, so that subjects remained unaware of the visual deviation applied in both conditions. An adaptive aftereffect was observed in the “terminal feedback error” condition only. As far as subjects remained unaware of the optical deviation and self-assigned pointing errors, prediction error alone was insufficient to induce adaptation. These results indicate a critical role of hand-to-target feedback error signals in visuomotor adaptation; consistent with recent neurophysiological findings, they suggest that a combination of feedback and prediction error signals is necessary for eliciting aftereffects. They also suggest that feedback error updates the prediction of reafferences when a visual perturbation is introduced gradually and cognitive factors are eliminated or strongly attenuated.

Eye-Hand Coordination during Visuomotor Adaptation with Different Rotation Angles: Effects of Terminal Visual Feedback

“…Such implicit adaptation occurs even when prisms introduce large rotations, so that participants are aware of the exposure [58,59]. It also occurs when terminal visual feedback is applied [60] or when continuous feedback is applied only in the last portion of reaching [61]. These observations seem to contradict the current results, where adaptive changes under terminal feedback were primarily through explicit learning.…”

“…Different visuomotor processes underlying reaching between natural and tool-use settings were revealed recently [49,62,63]. Moreover, the current task required controls of both the hand’s initial trajectory direction and stopping at the target, whereas prism adaptations often require mainly the control of the hand’s initial trajectory direction, such as throwing a ball [59] or rapid pointing being mechanically stopped as the finger lands on the target [60]. Taken together, the sensorimotor processing required for learning the current task was more complex than in the case of prism adaptations, thereby making it difficult to create an internal model of the applied rotation, in turn attenuating implicit adaptation.…”

Sensory prediction errors, not performance errors, update memories in visuomotor adaptation

“…Fourth, our results of condition 4 show that participants exhibited the drift without target error feedback. This result is in line with previous studies showing visuomotor adaptation without explicit targets 9, 10 ; but see 23 . Fifth, despite large differences in performance during adaptation between conditions with and without PE1 available, there was no difference between conditions in delayed washout, with a remarkable superimposition of the decay in washout across conditions.…”

The Errors of Our Ways: Understanding Error Representations in Cerebellar-Dependent Motor Learning

“…One of the more important uses of motor predictions is in computing sensory prediction errors that are used to guide present and future actions [6, 7]. Many investigators have proposed that sensory prediction errors are the critical error signals for both online control and motor learning [6, 7, 20–24]. …”

“…Several of these alternative performance measures have been shown, at least to some degree, to contribute to the control of movement and induce adaptation [32–35]. However, this review focuses on sensory prediction errors because extensive evidence consistently supports their role in motor adaptation and dominance over other types of errors in updating a forward internal model [6, 7, 21, 22, 24, 32, 36]. …”