Evidence map›Paper›PMID 38756493›Full record

ArticleFrontiers in psychology2024

The influence of social feedback on reward learning in the Iowa gambling task.

Ming Peng, Qiaochu Duan, Xiaoying Yang, Rui Tang, Lei Zhang, Hanshu Zhang, Xu Li

Abstract read
In one paragraph

Article in Frontiers in psychology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ming PengKey Laboratory of Adolescent Cyberpsychology and Behavior (CCNU), Ministry of Education, Wuhan, China.
Qiaochu DuanSchool of Psychology, Central China Normal University, Wuhan, China.
Xiaoying YangSchool of Psychology, Central China Normal University, Wuhan, China.
Rui TangSchool of Psychology, Central China Normal University, Wuhan, China.
Lei ZhangCentre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, United Kingdom.
Hanshu ZhangKey Laboratory of Adolescent Cyberpsychology and Behavior (CCNU), Ministry of Education, Wuhan, China.
Xu LiKey Laboratory of Adolescent Cyberpsychology and Behavior (CCNU), Ministry of Education, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Learning, an important activity for both human and animals, has long been a focal point of research. During the learning process, subjects assimilate not only their own information but also information from others, a phenomenon known as social learning. While numerous studies have explored the impact of social feedback as a reward/punishment during learning, few studies have investigated whether social feedback facilitates or inhibits the learning of environmental rewards/punishments. This study aims to test the effects of social feedback on economic feedback and its cognitive processes by using the Iowa Gambling Task (IGT). One hundred ninety-two participants were recruited and categorized into one non-social feedback group and four social feedback groups. Participants in the social feedback groups were informed that after the outcome of each choice, they would also receive feedback from an online peer. This peer was a fictitious entity, with variations in identity (novice or expert) and feedback type (random or effective). The Outcome-Representation Learning model (ORL model) was used to quantify the cognitive components of learning. Behavioral results showed that both the identity of the peer and the type of feedback provided significantly influenced the deck selection, with effective social feedback increasing the ratio of chosen good decks. Results in the ORL model showed that the four social feedback groups exhibited lower learning rates for gain and loss compared to the nonsocial feedback group, which suggested, in the social feedback groups, the impact of the recent outcome on the update of value decreased. Parameters such as forgetfulness, win frequency, and deck perseverance in the expert-effective feedback group were significantly higher than those in the non-social feedback and expert-random feedback groups. These findings suggest that individuals proactively evaluate feedback providers and selectively adopt effective feedback to enhance learning.

Indexed as

computational modelfeedback typeidentityIowa gambling taskreward learningsocial feedback

Identifiers

PMID38756493
PMCPMC11098015

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.