Reward magnitude modulates the near-miss effect: Insights from ERP and Bayesian hierarchical modeling.

In gambling scenarios, near misses are defined as non-winning outcomes that marginally fail to achieve a win. In contrast to clear losses (i.e., full misses), near misses evoke distinct psychological and physiological responses, a phenomenon known as the near-miss effect. Nevertheless, the factors that modulate this effect are not yet fully comprehended. By utilizing event-related potentials (ERPs), the current study investigated whether the magnitude of the missed reward modulates the near-miss effect. The behavioral findings indicated that, compared to full misses, near misses triggered a stronger tendency for counterfactual thinking, greater intensity of counterfactual thinking, more pronounced regret, enhanced gambling motivation, and heightened reward anticipation for the subsequent trial. Participants also reported a higher level of self-blame after near misses when the associated reward magnitude was larger. ERP analyses showed that the feedback-related negativity (FRN) amplitudes could distinguish near misses from full misses only when the missed reward was relatively large. Across all reward magnitude conditions, near misses also led to smaller P300 amplitudes than full misses. Crucially, Bayesian hierarchical modeling revealed that at the individual level, the difference in P300 amplitude between near misses and full misses was correlated with the magnitude of the self-blame discrepancy. These findings confirm that the reward magnitude significantly influences the near-miss effect, offering a potential explanation for the inconsistencies in previous literature and providing insights into the neural mechanisms underlying the processing of outcome proximity and reward value.