  Understanding, predicting, and learning from other people's actions are
fundamental human social-cognitive skills. Little is known about how and when
we consider other's actions and outcomes when making our own decisions. We
developed a novel task to study social influence in decision-making: the social
multi-armed bandit task. This task assesses how people learn policies for
optimal choices based on their own outcomes and another player's (observed)
outcomes. The majority of participants integrated information gained through
observation of their partner similarly as information gained through their own
actions. This lead to a suboptimal decision-making strategy. Interestingly,
event-related potentials time-locked to stimulus onset qualitatively similar
but the amplitudes are attenuated in the solo compared to the dyadic version.
This might indicate that arousal and attention after receiving a reward are
sustained when a second agent is present but not when playing alone.
