Decades of research have established that decision-making is dramatically impacted by both the rewards an individual receives and the behavior of others. How do these distinct influences exert their influence on an individual’s actions, and can the resulting behavior be effectively captured in a computational model? To address this question, we employed a novel spatial foraging game in which groups of three participants sought to find the most rewarding location in an unfamiliar two-dimensional space. As the game transitioned from one block to the next, the availability of information regarding other group members was varied systematically, revealing the relative impacts of feedback from the environment and information from other group members on individual decision-making. Both reward-based and socially-based sources of information exerted a significant influence on behavior, and a computational model incorporating these effects was able to recapitulate several key trends in the behavioral data. In addition, our findings suggest how these sources were processed and combined during decision-making. Analysis of reaction time, location of gaze, and functional magnetic resonance imaging (fMRI) data indicated that these distinct sources of information were integrated simultaneously for each decision, rather than exerting their influence in a separate, all-or-none fashion across separate subsets of trials. These findings add to our understanding of how the separate influences of reward from the environment and information derived from other social agents are combined to produce decisions.
All Science Journal Classification (ASJC) codes
- Cognitive Neuroscience
- Behavioral Neuroscience
- Computational model
- Social cognition