Pupillary correlates of computations underlying human responder behaviour in the Ultimatum Game

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. Here, we report results from a novel iterative Ultimatum Game (UG) task, in which the proposers facial emotions and offer amounts were sampled probabilistically based on the participants decisions, creating a gradually evolving social-interactive decision-making environment. Our model-free results confirm the prediction that both the proposers facial emotions and the offer amount influence human choice behaviour. These main effects demonstrate that biases in facial emotion recognition also contribute to violations of the Rational Actor model (i.e. all offers should be accepted). Model-based analyses extend these findings, indicating that participants decisions are guided by an aversion to inequality in the UG. We highlight that the proposers facial responses to participant decisions dynamically modulate how human decision-makers perceive self-other inequality, relaxing its otherwise negative influence on decision values. In iterative games, this cognitive model underlies how offers initially rejected can gradually become more acceptable under increasing affective load, and accurately predicts 86% of participant decisions. Activity of the central arousal systems, assessed by measuring pupil size, encode a key element of this model: proposers affective reactions in response to participant decisions. Taken together, our results demonstrate that, under affective load, participants aversion to inequality is a malleable cognitive process which is modulated by the activity of the pupil-linked central arousal systems.