Processing Graded Feedback: Electrophysiological Correlates of Learning from Small and Large Errors

Abstract

Feedback processing is important for learning and therefore may affect the consolidation of skills. Considerable research demonstrates electrophysiological differences between correct and incorrect feedback, but how we learn from small versus large errors is usually overlooked. This study investigated electrophysiological differences when processing small or large error feedback during a time estimation task. Data from high-learners and low-learners were analyzed separately. In both high- and low-learners, large error feedback was associated with higher feedback-related negativity (FRN) and small error feedback was associated with a larger P300 and increased amplitude over the motor related areas of the left hemisphere. In addition, small error feedback induced larger desynchronization in the alpha and beta bands with distinctly different topographies between the two learning groups: The high-learners showed a more localized decrease in beta power over the left frontocentral areas, and the low-learners showed a widespread reduction in the alpha power following small error feedback. Furthermore, only the high-learners showed an increase in phase synchronization between the midfrontal and left central areas. Importantly, this synchronization was correlated to how well the participants consolidated the estimation of the time interval. Thus, although large errors were associated with higher FRN, small errors were associated with larger oscillatory responses, which was more evident in the high-learners. Altogether, our results suggest an important role of the motor areas in the processing of error feedback for skill consolidation.

Why self-controlled feedback enhances motor learning: Answers from electroencephalography and indices of motivation

“…Regardless, to our knowledge, this is the first study to report intrinsic motivation and augmented feedback processing, when considered together, predict a measure of motor learning. One other study showed evidence that intrinsic motivation predicted motor learning (Saemi et al, 2011), but this study did not consider augmented feedback processing; and two other studies showed evidence augmented feedback processing predicted motor learning (Luft et al, 2013(Luft et al, , 2014, but these studies did not consider intrinsic motivation. Interestingly, intrinsic motivation and augmented feedback processing were not significantly correlated, suggesting that individuals who are more intrinsically motivated to learn do not necessarily engage in greater augmented feedback processing while learning.…”

“…Notably, the difference in FRN amplitude is unlikely related to the degree of error represented by the feedback. This is because the Yoked group received feedback after trials with larger errors (although this difference only approached conventional significance [p = .09]), and feedback indicating larger errors elicits greater FRN amplitudes (Luft et al, 2014). Thus, if FRN amplitude was being driven by the degree of error represented by the feedback, then the Yoked group would exhibit a larger FRN amplitude.…”

“…It could also be the case that self-control participants engage in greater augmented feedback processing because they are more intrinsically motivated to learn, and attempt to do so by utilizing augmented feedback to a greater extent. Regardless of why self-control participants may engage in greater augmented feedback processing, it is important to note that such processing is positively associated with motor learning (Luft, Nolte, & Bhattacharya, 2013;Luft, Takase, & Bhattacharya, 2014), but that empirical evidence that self-control participants engage in greater information (e.g., feedback) processing is lacking (Sanli et al, 2013).…”

Slow and Fast Responses: Two Mechanisms of Trial Outcome Processing Revealed by EEG Oscillations

“…According to the same logic, alpha suppression after feedback onset may be related to enhanced attention during feedback processing. Alpha oscillations are known to be suppressed by feedback presentation (Papo et al, 2007; Luft et al, 2014), although the effect is usually manifested during a later period of feedback processing. The difference in timing of the effect may be explained by the nature of the condensation task that demands greater attentional involvement in comparison with many behavioral tasks commonly used, thus leading to earlier attention-related alpha suppression.…”

Willing to wait: Elevated reward-processing EEG activity associated with a greater preference for larger-but-delayed rewards

“…Given that a similar pattern of enhanced beta power has been reported in the ventral striatum of animals during a reward-processing task (Berke, 2009; Courtemanche, Fujii, & Graybiel, 2003), it has been proposed that feedback-locked beta power represents reward-related signals from this region. Parietal feedback-locked beta power is reduced in humans following feedback during reward-learning tasks, such as the time estimation task (Luft, Nolte, et al, 2013; Luft, Takase, & Bhattacharya, 2013; van de Vijver et al, 2011). This reduction in feedback-locked beta power (desynchronization) is less pronounced when feedback indicates good performance, compared to bad performance.…”