Evidence map›Paper›PMID 33615385›Full record

ArticleSocial cognitive and affective neuroscience2021

The hierarchical sensitivity to social misalignment during decision-making under uncertainty.

Yongling Lin, Ruolei Gu, Shenghua Luan, Li Hu, Shaozheng Qin, Yue-Jia Luo

Abstract read
In one paragraph

Article in Social cognitive and affective neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yongling LinState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.ORCID 0000-0001-8825-2760
Ruolei GuDepartment of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.
Shenghua LuanDepartment of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.
Li HuDepartment of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China.
Shaozheng QinState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.ORCID 0000-0002-1859-2150
Yue-Jia LuoState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Social misalignment occurs when a person's attitudes and opinions deviate from those of others. We investigated how individuals react to social misalignment in risky (outcome probabilities are known) or ambiguous (outcome probabilities are unknown) decision contexts. During each trial, participants played a forced-choice gamble, and they observed the decisions of four other players after they made a tentative decision, followed by an opportunity to keep or change their initial decision. Behavioral and event-related potential data were collected. Behaviorally, the stronger the participants' initial preference, the less likely they were to switch their decisions, whereas the more their decisions were misaligned with the majority, the more likely they were to switch. Electrophysiological results showed a hierarchical processing pattern of social misalignment. Misalignment was first detected binarily (i.e. match/mismatch) at an early stage, as indexed by the N1 component. During the second stage, participants became sensitive to low levels of misalignment, which were indexed by the feedback-related negativity. The degree of social misalignment was processed in greater detail, as indexed by the P3 component. Moreover, such hierarchical neural sensitivity is generalizable across different decision contexts (i.e. risky and ambiguous). These findings demonstrate a fine-grained neural sensitivity to social misalignment during decision-making under uncertainty.

Indexed as

UncertaintyAttitudeBrainDecision MakingElectroencephalographyEvoked PotentialsFemaleHumansMaleYoung Adultdecision-makingevent-related potentialsocial conformitysocial misalignmentuncertainty

Identifiers

PMID33615385
PMCPMC8138082

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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.