Evidence map›Paper›PMID 35422086›Full record

ArticleCommunications biology2022

Dynamic modulation of inequality aversion in human interpersonal negotiations.

Daniel A J Murphy, Jiaxin Xie, Catherine J Harmer, Michael Browning, Erdem Pulcu

Abstract read
In one paragraph

Article in Communications biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
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

5 authors.

Daniel A J MurphyUniversity of Oxford Medical School, Oxford, UK.
Jiaxin XieUniversity of Oxford, Department of Psychiatry, Oxford, UK.
Catherine J HarmerUniversity of Oxford, Department of Psychiatry, Oxford, UK.
Michael BrowningUniversity of Oxford, Department of Psychiatry, Oxford, UK.
Erdem PulcuUniversity of Oxford, Department of Psychiatry, Oxford, UK. erdem.pulcu@psych.ox.ac.uk.ORCID 0000-0002-2170-0677

Funding

Department of HealthMedical Research Council MR/N008103/1Medical Research Council MR/S035591/1
6 · The paper itself

Abstract

Negotiating with others about how finite resources should be distributed is an important aspect of human social life. However, little is known about mechanisms underlying human social-interactive decision-making in gradually evolving environments. Here, we report results from an iterative Ultimatum Game (UG), in which the proposer's facial emotions and offer amounts were sampled probabilistically based on the participant's decisions. Our model-free results confirm the prediction that both the proposer's facial emotions and the offer amount should influence acceptance rates. Model-based analyses extend these findings, indicating that participants' decisions in the UG are guided by aversion to inequality. We highlight that the proposer's facial affective reactions to participant decisions dynamically modulate how human decision-makers perceive self-other inequality, relaxing its otherwise negative influence on decision values. This cognitive model underlies how offers initially rejected can gradually become more acceptable under increasing affective load (predictive accuracy ~86%). Furthermore, modelling human choice behaviour isolated the role of the central arousal systems, assessed by measuring pupil size. We demonstrate that pupil-linked central arousal systems selectively encode a key component of subjective decision values: the magnitude of self-other inequality. Taken together, our results demonstrate that, under affective influence, aversion to inequality is a malleable cognitive process.

Indexed as

Games, ExperimentalNegotiatingAffectDecision MakingEmotionsHumans

Identifiers

PMID35422086
PMCPMC9010408

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.