Deciding the best action in social settings requires decision-makers to consider their and others’ preferences, since the outcome depends on the actions of both. Numerous empirical investigations have demonstrated variability of behavior across individuals in strategic situations. While prosocial, moral, and emotional factors have been intensively investigated to explain this diversity, neuro-cognitive determinants of strategic decision-making and their relation with intelligence remain mostly unknown. This study presents a new model of the process of strategic decision-making in repeated interactions, first providing a precise measure of the environment’s complexity, and then analyzing how this complexity affects subjects’ performance and neural response. The results confirm the theoretical predictions of the model. The frequency of deviations from optimal behavior is explained by a combination of higher complexity of the strategic environment and cognitive skills of the individuals. Brain response correlates with strategic complexity, but only in the subgroups with higher cognitive skills. Furthermore, neural effects were only observed in a fronto-parietal network typically involved in single-agent tasks (the Multiple Demand Network), thus suggesting that neural processes dealing with cognitively demanding individual tasks also have a central role in interactive decision-making. Our findings contribute to understanding how cognitive factors shape strategic decision-making and may provide the neural pathway of the reported association between strategic sophistication and fluid intelligence.
|Original language||English (US)|
|State||Published - Dec 2022|
Bibliographical noteFunding Information:
This research was supported by the National Science Foundation (with Grant SES 1728056, Rules-based policies, and Intelligence in Strategic Behavior and the US Department of Defense, Grant W911NF2010242 to AR; and by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, Grants GRK1589/1 and FK:JA945/3-1 to JDH). DP is currently funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy “Science of Intelligence” (EXC 2002/1; project number 390523135). AR thanks the US Department of Defense, Grant W911NF2010242 for financial support. MM thanks the Italian Ministry of University and Research, Grant PRIN 2017K8ANN4, for financial support.
© 2022, The Author(s).
PubMed: MeSH publication types
- Journal Article
- Research Support, Non-U.S. Gov't
- Research Support, U.S. Gov't, Non-P.H.S.