Dynamic modulation of inequality aversion in human interpersonal negotiations

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.