Theta and beta account for the two-impacted components of social influence on risk decision-making

Social influence in risky decision-making means changing risky behavior after observing other’s choices. Although attributes’ prioritization can alter subjective value of a particular option while choice bias can affect the tendency toward it, previous studies have not simultaneously examined these two components. Here, participants made risky or safety choices, observed a model whose risk preference either matched (control) or opposed (inconsistent) their own, then repeated the task. Behavioral and EEG data were collected, and drift-diffusion model (DDM) was used to decompose different components. After observing an opposing preference, risk-seeking participants chose safety options more often, and risk-aversion participants chose risky options more often, indicating social influence. Model comparison favored an attribute-wise DDM. Social influence altered two distinct components in risky decisions: the weight of amount in value computation (more negative after observing the opposing model) and the starting point (shifting toward the options chosen more often). Multivariate pattern analysis linked these components to distinct neural signatures: theta activity (≈500 ms after option onset) tracked the amount weighting, whereas pre-option beta activity tracked the starting point. Together, the results show that social influence reshapes risky decisions by reweighting amount and shifting choice bias, each supported by dissociable electrophysiological dynamics.