Literature DB >> 29183793

The electrocortical response to rewarding and aversive feedback: The reward positivity does not reflect salience in simple gambling tasks.

Elizabeth M Mulligan1, Greg Hajcak2.   

Abstract

The Reward Positivity (RewP) is an event-related potential (ERP) potentiated to monetary gains and reduced to monetary losses. Recently, competing data suggest that more salient outcomes elicit a positivity relative to less salient outcomes, regardless of valence. However, all previous work testing the impact of salience on the RewP have examined expected versus unexpected outcomes. In the current study, participants completed the same gambling task twice in which feedback was equally probable: in one condition, feedback indicated monetary gain or loss-and in the other condition, feedback indicated either safety or punishment from subsequent electric shock. Traditional ERP and principal component analysis (PCA)-derived measures confirmed that the RewP was more positive to feedback signaling monetary gain and safety from shock compared to feedback signaling monetary loss and punishment with shock. These results align with models in which the RewP indexes reward-related processes, including reward prediction error models. Potential explanations for salience-based effects on the RewP are discussed.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  ERP; Punishment; Reinforcement; Reward positivity; Salience; Valence

Mesh:

Year:  2017        PMID: 29183793     DOI: 10.1016/j.ijpsycho.2017.11.015

Source DB:  PubMed          Journal:  Int J Psychophysiol        ISSN: 0167-8760            Impact factor:   2.997


  11 in total

1.  The role of avoidance motivation in the relationship between reward sensitivity and depression symptoms in adolescents: An ERP study.

Authors:  Alissa J Ellis; Giulia Salgari; David J Miklowitz; Sandra K Loo
Journal:  Psychiatry Res       Date:  2019-03-08       Impact factor: 3.222

2.  EEG correlates of physical effort and reward processing during reinforcement learning.

Authors:  Dimitrios J Palidis; Paul L Gribble
Journal:  J Neurophysiol       Date:  2020-07-29       Impact factor: 2.714

3.  Win, lose, or draw: Examining salience, reward memory, and depression with the reward positivity.

Authors:  Nathan M Hager; Matt R Judah; Eric Rawls
Journal:  Psychophysiology       Date:  2021-10-12       Impact factor: 4.016

4.  Reward-Related Neural Predictors and Mechanisms of Symptom Change in Cognitive Behavioral Therapy for Depressed Adolescent Girls.

Authors:  Christian A Webb; Randy P Auerbach; Erin Bondy; Colin H Stanton; Lindsay Appleman; Diego A Pizzagalli
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2020-07-23

5.  The aversion positivity: Mediofrontal cortical potentials reflect parametric aversive prediction errors and drive behavioral modification following negative reinforcement.

Authors:  Eric Rawls; Connie Lamm
Journal:  Cortex       Date:  2021-03-27       Impact factor: 4.644

6.  Contextual valence modulates the effect of choice on incentive processing.

Authors:  Shuting Mei; Wei Yi; Shiyu Zhou; Xun Liu; Ya Zheng
Journal:  Soc Cogn Affect Neurosci       Date:  2018-12-04       Impact factor: 3.436

7.  Monetary Incentives Modulate Feedback-related Brain Activity.

Authors:  Shuting Mei; Qi Li; Xun Liu; Ya Zheng
Journal:  Sci Rep       Date:  2018-08-09       Impact factor: 4.379

8.  Feedback-Related Negativity and Frontal Midline Theta Reflect Dissociable Processing of Reinforcement.

Authors:  Eric Rawls; Vladimir Miskovic; Shannin N Moody; Yoojin Lee; Elizabeth A Shirtcliff; Connie Lamm
Journal:  Front Hum Neurosci       Date:  2020-01-09       Impact factor: 3.169

9.  Emotional State and Feedback-Related Negativity Induced by Positive, Negative, and Combined Reinforcement.

Authors:  Shuyuan Xu; Yuyan Sun; Min Huang; Yanhong Huang; Jing Han; Xuemei Tang; Wei Ren
Journal:  Front Psychol       Date:  2021-05-10

10.  Processing of performance errors predicts memory formation: Enhanced feedback-related negativities for corrected versus repeated errors in an associative learning paradigm.

Authors:  Ellen R A de Bruijn; Rogier B Mars; Rob Hester
Journal:  Eur J Neurosci       Date:  2019-10-03       Impact factor: 3.386

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