Most human decisions are made among social others, and in what social context the choices are made is known to influence individuals' decisions. Social influence has been noted as an important factor that may nudge individuals to take more risks (e.g., initiation of substance use), but ironically also help individuals to take safer actions (e.g., successful abstinence). Such bi-directional impacts of social influence hint at the complexity of social information processing. Here, we first review the recent computational approaches that shed light on neural and behavioral mechanisms underlying social influence following basic computations involved in decision-making: valuation, action selection, and learning. We next review the studies on social influence from various fields including neuroeconomics, developmental psychology, social psychology, and cognitive neuroscience, and highlight three dimensions of determinants—who are the recipients, how the social contexts are presented, and to what domains and processes of decisions the influence is applied—that modulate the extent to which individuals are influenced by others. Throughout the review, we also introduce the brain regions that were suggested as neural instantiations of social influence from a large body of functional neuroimaging studies. Finally, we outline the remaining questions to be addressed in the translational application of computational and cognitive theories of social influence to psychopathology and health.

Smoking is a severe addictive health risk behavior and notorious for the high likelihood of relapse after attempted cessation. Such an addictive pattern in smoking has been associated with neurobiological changes in the brain. However, little is known whether the neural changes associated with chronic smoking persist after a long period of successful abstinence. To address this question, we examined resting state EEG (rsEEG) in heavy smokers who have been smoking for 20 years or more, past-smokers who have been successfully abstaining for 20 years or more, and non-smokers. Compared with chronic current- or past- smokers, non-smokers showed higher relative power in theta frequency band, showcasing long-lasting effects of smoking on the brain. A few rsEEG features in alpha frequency band also revealed reversible impacts of smoking, such that only current-smokers, but not past-smokers, showed distinctively higher patterns than non-smokers in their relative power, EEG reactivity—power changes between eyes-closed and eyes-open conditions—, and coherence between channels. Furthermore, rsEEG feature differences between current- and past- smokers were accounted for by individuals' self-reported smoking history and nicotine dependence. These data suggest long-lasting impacts of chronic smoking on the brain that are dissociable from the neural changes reversible with long-term abstinence.