Literature DB >> 25634316

Valence-separated representation of reward prediction error in feedback-related negativity and positivity.

Yu Bai1, Kentaro Katahira, Hideki Ohira.   

Abstract

Feedback-related negativity (FRN) is an event-related brain potential (ERP) component elicited by errors and negative outcomes. Previous studies proposed that FRN reflects the activity of a general error-processing system that incorporates reward prediction error (RPE). However, other studies reported inconsistent results on this issue - namely, that FRN only reflects the valence of feedback and that the magnitude of RPE is reflected by the other ERP component called P300. The present study focused on the relationship between the FRN amplitude and RPE. ERPs were recorded during a reversal learning task performed by the participants, and a computational model was used to estimate trial-by-trial RPEs, which we correlated with the ERPs. The results indicated that FRN and P300 reflected the magnitude of RPE in negative outcomes and positive outcomes, respectively. In addition, the correlation between RPE and the P300 amplitude was stronger than the correlation between RPE and the FRN amplitude. These differences in the correlation between ERP and RPE components may explain the inconsistent results reported by previous studies; the asymmetry in the correlations might make it difficult to detect the effect of the RPE magnitude on the FRN and makes it appear that the FRN only reflects the valence of feedback.

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Year:  2015        PMID: 25634316     DOI: 10.1097/WNR.0000000000000318

Source DB:  PubMed          Journal:  Neuroreport        ISSN: 0959-4965            Impact factor:   1.837


  5 in total

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2.  The Effect of Reduced Learning Ability on Avoidance in Psychopathy: A Computational Approach.

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Journal:  PLoS Comput Biol       Date:  2021-02-09       Impact factor: 4.475

4.  Single-trial modeling separates multiple overlapping prediction errors during reward processing in human EEG.

Authors:  Colin W Hoy; Sheila C Steiner; Robert T Knight
Journal:  Commun Biol       Date:  2021-07-23

5.  Post-response βγ power predicts the degree of choice-based learning in internally guided decision-making.

Authors:  Takashi Nakao; Noriaki Kanayama; Kentaro Katahira; Misaki Odani; Yosuke Ito; Yuki Hirata; Reika Nasuno; Hanako Ozaki; Ryosuke Hiramoto; Makoto Miyatani; Georg Northoff
Journal:  Sci Rep       Date:  2016-08-31       Impact factor: 4.379

  5 in total

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