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Social decision‐making in the brain: Input‐state‐output modelling reveals patterns of effective connectivity underlying reciprocal choices
Author(s) -
Shaw Daniel,
Czekóová Kristína,
Gajdoš Martin,
Staněk Rostislav,
Špalek Jiří,
Brázdil Milan
Publication year - 2019
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.24446
Subject(s) - reciprocity (cultural anthropology) , social decision making , reciprocal , ultimatum game , psychology , social preferences , generosity , anterior cingulate cortex , cognitive psychology , reciprocal inhibition , social psychology , cognition , neuroscience , linguistics , philosophy , theology , inhibitory postsynaptic potential
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.