In reinforcement learning theory, humans learn from the outcomes of their actions and update the expected value of their future choices accordingly. To act in a socially adaptive manner, we must...Show moreIn reinforcement learning theory, humans learn from the outcomes of their actions and update the expected value of their future choices accordingly. To act in a socially adaptive manner, we must learn about the consequences our actions have on both ourselves and others. In the current study, empathy was tested as a trait which influences our ability to learn to make decisions which benefit others. It was hypothesised that higher empathy would lead to improved prosocial learning, and that feelings of responsibility for others would meditate such effect. A probabilistic prosocial reinforcement learning task was used, whereby 30 healthy males aged between 19 and 34 played a game to win monetary rewards for themselves, another person, or no-one. ANOVA analysis revealed that participants showed higher learning rates when playing for others rather than themselves, which is not congruent with previous research. The potential reasons for this finding are discussed. Correlation analysis of accuracy rates and computational learning rates with empathy scores revealed no relationships between trait empathy and prosocial learning. Further analysis failed to show feelings of responsibility for others mediating the effect of empathy on prosocial learning. Thus, the current study found no evidence for empathy having a role in prosocial learning, nor for feeling responsible for others as a mediator. The current sample did, however, perform as well or better for others than for themselves, which may be due to cultural differences or testing occurring during the Covid-19 pandemic when empathy, prosocial actions, and social responsibility were increased.Show less
