Decision-making and performance in the Iowa Gambling Task: recent ERP findings and clinical implications

The Iowa Gambling Task (IGT) is a widely used tool for assessing decision-making in clinical populations. In each trial of the task, participants freely select from different playing card decks that vary in the magnitude and frequency of rewards and punishments. Good decks offer relatively smaller rewards on each trial yielding greater overall winnings while bad decks result in a net loss over time as high penalties negate any rewards earned. Comparing participants' rate of selecting good to bad decks can provide insight into learning in uncertain conditions across time. However, inconsistent patterns of deficits and learning within clinical and control populations are often observed in the task (eg., in depression). Thus, a clearer mechanistic understanding of the IGT is needed to fully understand the decision-making process. The goal of the current review is to synthesize the predominant empirical and theoretical literature of the IGT using event-related potentials (ERPs) derived from electroencephalogram (EEG). The review then explores how modifications of the IGT allow for event-related potentials to be captured at each stage of decision-making. Lastly, the review discusses how the modified version with ERPs can be further applied to directly assess the impact of emotion processing on decision-making, using findings from depression research as an example.