Differential Reward Learning for Self and Others Predicts Self-Reported Altruism

In social environments, decisions not only determine rewards for oneself but also for others. However, individual differences in pro-social behaviors have been typically studied through self-report. We developed a decision-making paradigm in which participants chose from card decks with differing rewards for themselves and charity; some decks gave similar rewards to both, while others gave higher rewards for one or the other. We used a reinforcement-learning model that estimated each participant''s relative weighting of self versus charity reward. As shown both in choices and model parameters, individuals who showed relatively better learning of rewards for charity – compared to themselves – were more likely to engage in pro-social behavior outside of a laboratory setting indicated by self-report. Overall rates of reward learning, however, did not predict individual differences in pro-social tendencies. These results support the idea that biases toward learning about social rewards are associated with one''s altruistic tendencies.