Learning from experience: event-related potential correlates of reward processing, neural adaptation, and behavioral choice

Abstract

To behave adaptively, we must learn from the consequences of our actions. Studies using event-related potentials (ERPs) have been informative with respect to the question of how such learning occurs. These studies have revealed a frontocentral negativity termed the feedback-related negativity (FRN) that appears after negative feedback. According to one prominent theory, the FRN tracks the difference between the values of actual and expected outcomes, or reward prediction errors. As such, the FRN provides a tool for studying reward valuation and decision making. We begin this review by examining the neural significance of the FRN. We then examine its functional significance. To understand the cognitive processes that occur when the FRN is generated, we explore variables that influence its appearance and amplitude. Specifically, we evaluate four hypotheses: (1) the FRN encodes a quantitative reward prediction error; (2) the FRN is evoked by outcomes and by stimuli that predict outcomes; (3) the FRN and behavior change with experience; and (4) the system that produces the FRN is maximally engaged by volitional actions.

Copyright © 2012 Elsevier Ltd. All rights reserved.

Figures

Figure 1

The error-related negativity (ERN) appears in response-locked waveforms as the difference between error trials and correct trials. The ERN emerges at the time of movement onset and peaks 100 ms after response errors. The feedback-related negativity (FRN) appears in feedback-locked waveforms as the difference between negative feedback and positive feedback. The FRN emerges at 200 ms and peaks 300 ms after negative feedback (adapted from Nieuwenhuis et al., 2002).

Figure 2

Feedback-locked ERPs for probable and improbable wins and losses (colored lines), and FRN difference waves (colored regions) (data from the no instruction condition of Walsh & Anderson, 2011a).

Figure 3

Topography of the FRN following probable outcomes (losses | 33% Cue – wins | 66% Cue) and improbable outcomes (losses | 66% Cue – wins | 33% Cue) (data from the no instruction condition of Walsh & Anderson, 2011a).

Figure 4

Equivalent dipole solutions from source localization studies. Miltner et al. (1997) fit dipoles for three experiment conditions, and Hewig et al. (2007) fit dipoles for two experiment contrasts. Several studies modeled the FRN using two-dipole solutions (Carlson et al., 2011; Foti et al., 2011; Müller et al., 2005; Nieuwenhuis et al., 2005a; Ruchsow et al., 2002).

Figure 5

Model FRNs and observed FRNs. Squares correspond to cue-locked FRNs, and circles correspond to feedback-locked FRNs.