Power of Feedback-Induced Beta Oscillations Reflect Omission of Rewards: Evidence From an EEG Gambling Study.

Zachary Yaple,Nikita Novikov,Mario Martinez-Saito,Dmitrii Altukhov,Anna Shestakova,Vasily Klucharev

doi:10.3389/fnins.2018.00776

Abstract

The functional role of high beta oscillations (20–35 Hz) during feedback processing has been suggested to reflect unexpected gains. Using a novel gambling task that separates gains and losses across blocks and directly compares reception of monetary rewards to a ‘no-reward/punishment’ condition with equal probability we aimed to further investigate the role of beta oscillations. When contrasting different feedback conditions across rewards, we found that a late low beta component (12–20 Hz) had increased in power during the omission of rewards relative to the reception of rewards, while no differences were observed during the loss domain. These findings may indicate that late low beta oscillations in the context of feedback processing may respond to omission of gains relative to other potential outcomes. We speculate that late low beta oscillations may operate as a learning mechanism that signals the brain to make future adequate decisions. Overall, our study provides new insights for the role of late low beta oscillations in reward processing.

Highlights

Effective decision-making crucially relies on the ability to improve decisions based on the evaluation of feedback
Since beta oscillations were specific to gain blocks, corresponding to previous studies showing an increase in beta power during gains compared to losses (Cohen and Ranganath, 2007; MarcoPallerés et al, 2008, 2015; Cunillera et al, 2012; HajiHosseini et al, 2012), we aimed to perform a series of generalized linear models (GLMs) to predict whether beta power in the current trial (t) can predict the selection of risky decisions in the following trial (t + 1) within gain (Table 1A) and loss blocks (Table 1B)
In the current study we showed that late low beta oscillations between 12 and 20 Hz are functional sensitive to gain omission relative to other potential gains

Summary

Introduction

Effective decision-making crucially relies on the ability to improve decisions based on the evaluation of feedback. There is growing interest in the neural mechanisms associated with the processing of rewarding feedback. Using electroencephalography (EEG), many studies attempt to explore the neural mechanisms of feedback learning by examining neural oscillations. Many have attempted to explore the functional role of high beta oscillations (20–35 Hz) between 200 and 400 ms which tend to increase in oscillatory power in response to monetary gains compared to monetary losses (Marco-Pallerés et al, 2008). A further exploration in a follow up experiment demonstrated that beta oscillations tend to respond to rare rewarding events. When comparing cued gain and loss incentives with high or low probability, beta oscillations were stronger in power when the probability of cued rewards had a low relative to a high probability (HajiHosseini et al, 2012), suggesting that

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