Beta-gamma oscillation reveals learning from unexpected reward in learners versus non-learners.

Abstract:

:Beta-gamma oscillation has been demonstrated to be sensitive to unexpected reward feedback. However, it remains unclear whether beta-gamma activity manifests individual differences in reinforcement learning processing. Given that individuals differ largely in reinforcement learning tasks, we adapted the Friedland task and split subjects into two groups: learners who learned to choose the optimal card after training and non-learners who did not learn well. We used recorded electroencephalography signals to test the difference in brain activity between the learners and non-learners groups when participants conducted a time estimation task and received win and loss feedback in expected and unexpected conditions. The results revealed that the unexpected condition elicited a larger reward positivity amplitude than did the expected condition, but only in the learners group. No significant difference was found between the two groups for the expectancy effect on frontal-midline theta. The current results thus demonstrate that for learners, unexpected win feedback elicits a larger beta-gamma oscillation than expected win feedback, while this was not the case for non-learners. These results indicate that beta-gamma oscillation may reflect effective learning from positive reward prediction error, a finding that adds to the existing theories on learning processes.

journal_name

Neuropsychologia

journal_title

Neuropsychologia

authors

Wang J,Zhang J,Li P,Martens S,Luo Y

doi

10.1016/j.neuropsychologia.2019.06.002

subject

Has Abstract

pub_date

2019-08-01 00:00:00

pages

266-274

eissn

0028-3932

issn

1873-3514

pii

S0028-3932(18)30366-X

journal_volume

131

pub_type

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