Beyond the FRN: Broadening the time-course of EEG and ERP components implicated in reward processing

Abstract

Most reward-related electroencephalogram (EEG) studies focus exclusively on the feedback-related negativity (FRN, also known as feedback negativity or FN, medial-frontal negativity or MFN, feedback error-related negativity or fERN, and reward positivity or RewP). This component is usually measured approximately 200-300 ms post-feedback at a single electrode in the frontal-central area (e.g., Fz or FCz). The present review argues that this singular focus on the FRN fails to leverage EEG's greatest strength, its temporal resolution, by underutilizing the rich variety of event-related potential (ERP) and EEG time-frequency components encompassing the wider temporal heterogeneity of reward processing. The primary objective of this review is to provide a comprehensive understanding of often overlooked ERP and EEG correlates beyond the FRN in the context of reward processing with the secondary goal of guiding future research toward multistage experimental designs and multicomponent analyses that leverage the temporal power of EEG. We comprehensively review reward-related ERPs (including the FRN, readiness potential or RP, stimulus-preceding negativity or SPN, contingent-negative variation or CNV, cue-related N2 and P3, Feedback-P3, and late-positive potential or LPP/slow-wave), and reward-related EEG time-frequency components (changes in power at alpha, beta, theta, and delta bands). These electrophysiological signatures display distinct time-courses, scalp topographies, and reflect independent psychological processes during anticipatory and/or outcome stages of reward processing. Special consideration is given to the time-course of each component and factors that significantly contribute to component variation. Concluding remarks identify current limitations along with recommendations for potential important future directions.

Reappraisal and suppression emotion-regulation tendencies differentially predict reward-responsivity and psychological well-being

“…al., 2001; Salamone & Correa, 2012; Breiter et al, 2001; McClure et al, 2003). As reflected below, reward processing involves neurocognitive processes unfolding rapidly and in close temporal proximity (Glazer, Kelley, Pornpattananangkul, Mittal, & Nusslock, 2018), making it difficult to experimentally isolate reward-anticipation and reward-outcome processes.…”

“…We selected the time estimation task for two reasons. First, it allows us to separate reward-processing into different temporal stages (Glazer et al, 2018; Pornpattananangkul & Nusslock, 2015; 2016). Second, the time-estimation task was the first reward task used to demonstrate the FRN/RewP (Milner 1997) and is commonly used to elicit the SPN (Damen and Brunia, 1994).…”

Neural processing of iterated prisoner’s dilemma outcomes indicates next-round choice and speed to reciprocate cooperation

“…Among ERPs in value-based decision making studies, the first stage of (visual) feedback processing is represented by the N1, an occipital bilateral complex indicating early cortical perceptual processing 29 . It is often followed by the feedback-related negativity (FRN), a difference waveform interpreted as the first learning stage in outcome processing 25 . Its dependency on reward valence, magnitude and expectancy has served to interpret it as a prediction error signal in the reinforcement learning framework [30][31][32][33][34] .…”

“…The FRN primarily reflects reproducible differences between optimal and worst reward outcomes, and may be weaker relative to ongoing background P3 activity 35 . Careful consideration is thus required in FRN estimation as different approaches may lead to inconsistent effects 36 (see 25,33 for a review). The P3 (or alternatively, the P3b subcomponent) is a widely studied ERP from the perceptual decision-making literature, with centro-parietal and/or temporo-parietal scalp distributions [37][38][39][40][41][42] .…”

“…For the iPD, such studies have primarily relied on dyadic measures from hyperscanning methods [22][23][24] , addressing strategic choice during partner gameplay and associations with inter-subject functional connectivity patterns. Of a relatively simpler scope, eventrelated potential (ERP) and spectrotemporal analysis are nevertheless prominent techniques to infer the neural bases and timing of economic decision-making 25 . Their application to the iPD has been relatively scarce 26,27 , including only one ERP study of the early (i.e.…”