Dyadic interactions often involve a dynamic process of mutual reciprocity; to steer a series of exchanges towards a desired outcome, both interactants must adapt their own behaviour according to that of their interaction partner. Understanding the brain processes behind such bidirectional reciprocity is therefore central to social neuroscience, but this requires measurement of both individuals’ brains during real-world exchanges. We achieved this by performing functional magnetic resonance imaging (fMRI) on pairs of male individuals simultaneously while they interacted in a modified iterated Ultimatum Game (iUG). In this modification, both players could express their intent and maximise their own monetary gain by reciprocating their partner’s behaviour – they could promote generosity through cooperation and/or discourage unfair play with retaliation. By developing a novel model of reciprocity adapted from behavioural economics, we then show that each player’s choices can be predicted accurately by estimating expected utility (EU) not only in terms of immediate payoff, but also as a reaction to their opponent’s prior behaviour. Finally, for the first time we reveal that brain signals implicated in social decision making are modulated by these estimates of EU, and become correlated more strongly between interacting players who reciprocate one another.

During social interactions, decision‐making involves mutual reciprocity—each individual's choices are simultaneously a consequence of, and antecedent to those of their interaction partner. Neuroeconomic research has begun to unveil the brain networks underpinning social decision‐making, but we know little about the patterns of neural connectivity within them that give rise to reciprocal choices. To investigate this, the present study measured the behaviour and brain function of pairs of individuals (N = 66) whilst they played multiple rounds of economic exchange comprising an iterated ultimatum game. During these exchanges, both players could attempt to maximise their overall monetary gain by reciprocating their opponent's prior behaviour—they could promote generosity by rewarding it, and/or discourage unfair play through retaliation. By adapting a model of reciprocity from experimental economics, we show that players' choices on each exchange are captured accurately by estimating their expected utility (EU) as a reciprocal reaction to their opponent's prior behaviour. We then demonstrate neural responses that map onto these reciprocal choices in two brain regions implicated in social decision‐making: right anterior insula (AI) and anterior/anterior‐mid cingulate cortex (aMCC). Finally, with behavioural Dynamic Causal Modelling, we identified player‐specific patterns of effective connectivity between these brain regions with which we estimated each player's choices with over 70% accuracy; namely, bidirectional connections between AI and aMCC that are modulated differentially by estimates of EU from our reciprocity model. This input‐state‐output modelling procedure therefore reveals systematic brain–behaviour relationships associated with the reciprocal choices characterising interactive social decision‐making.