The neural correlates of reciprocity are sensitive to prior experience of reciprocity

Connectome-based individualized prediction of reciprocity propensity and sensitivity to framing: a resting-state functional magnetic resonance imaging study

BACKGROUND

The social representation theory states that individual differences in reciprocity decisions are composed of a stable central core (i.e., reciprocity propensity, RP) and a contextual-dependent periphery (i.e., sensitivity to the framing effect; SFE, the effect by how the decision is presented). However, the neural underpinnings that explain RP and SFE are still unknown.

METHOD

Here, we employed prediction and lesion models to decode resting-state functional connectivity (RSFC) of RP and SFE for reciprocity decisions of healthy volunteers who underwent RS functional magnetic resonance imaging and completed one-shot trust (give frame) and distrust (take frame) games as trustees.

RESULTS

Regarding the central core, reciprocity rates were positively associated between the give and take frame. Neuroimaging results showed that inter-network RSFC between the default-mode network (DMN; associated with mentalizing) and cingulo-opercular network (associated with cognitive control) contributed to the prediction of reciprocity under both frames. Regarding the periphery, behavioral results demonstrated a significant framing effect-people reciprocated more in the give than in the take frame. Our neuroimaging results revealed that intra-network RSFC of DMN (associated with mentalizing) contributed dominantly to the prediction of SFE.

CONCLUSION

Our findings provide evidence for distinct neural mechanisms of RP and SFE in reciprocity decisions.

Neurobehavioral Mechanisms Supporting Trust and Reciprocity

Trust and reciprocity are cornerstones of human nature, both at the levels of close interpersonal relationships and economic/societal structures. Being able to both place trust in others and decide whether to reciprocate trust placed in us is rooted in implicit and explicit processes that guide expectations of others, help reduce social uncertainty, and build relationships. This review will highlight neurobehavioral mechanisms supporting trust and reciprocity, through the lens of implicit and explicit social appraisal and learning processes. Significant consideration will be given to the neural underpinnings of these implicit and explicit processes, and special focus will center on the underlying neurocomputational mechanisms facilitating the integration of implicit and explicit signals supporting trust and reciprocity. Finally, this review will conclude with a discussion of how we can leverage findings regarding the neurobehavioral mechanisms supporting trust and reciprocity to better inform our understanding of mental health disorders characterized by social dysfunction.

Identifying the Cognitive Correlates of Reciprocity in Children with Autism Spectrum Disorder

This study examined the cognitive correlates of reciprocity in children with autism spectrum disorder (ASD). A total of 59 children with ASD were assessed with the Interactive Drawing Task, Theory of Mind Task Battery, Children's Card Change Sort Task, and Children's Gambling Task respectively for their reciprocity, theory of mind, cool executive function (EF), and hot EF. The correlational findings revealed that cool EF (r = .482 and - .501, p < .01) and hot EF (r = .396, p < .05) were significantly correlated with children's total reciprocity. The regression models also showed that cool and hot EF abilities were significant predictors. Conclusively, cool and hot EF abilities are the correlates of reciprocity rather than of ToM in children with ASD.

Social decision-making in the brain: Input-state-output modelling reveals patterns of effective connectivity underlying reciprocal choices

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.