Is deck C an advantageous deck in the Iowa Gambling Task?

Abstract

BackgroundDunn et al. performed a critical review identifying some problems in the Somatic Marker Hypothesis (SMH). Most of the arguments presented by Dunn focused on the insufficiencies for replication of skin conductance responses and somatic brain loops, but the study did not carefully reassess the core-task of SMH. In a related study, Lin and Chiu et al. identified a serious problem, namely the "prominent deck B phenomenon" in the original IGT. Building on this observation, Lin and Chiu also posited that deck C rather than deck A was preferred by normal decision makers due to good gain-loss frequency rather than good final-outcome. To verify this hypothesis, a modified IGT was designed that possessed high contrast of gain-loss value in each trial, with the aim of achieving a balance between decks A and C in terms of gain-loss frequency. Based on the basic assumption of IGT, participants should prefer deck C to deck A based on consideration of final-outcome. In contrast, based on the prediction of gain-loss frequency, participants should have roughly equal preferences for decks A and C.MethodsThis investigation recruited 48 college students (24 males and 24 females) as participants. Two-stage IGT with high-contrast gain-loss value was launched to examine the deck C argument. Each participant completed the modified IGT twice and immediately afterwards was administered a questionnaire to assess their consciousness and final preferences following the game.ResultsThe experimental results supported the predictions regarding gain-loss frequency participants choose the deck C with nearly identical frequency to deck A, despite deck C having a better final outcome than deck A. The "sunken deck C" phenomenon is clearly identified in this version of IGT which achieves a balance in gain-loss frequency. Moreover, the "sunken deck C" phenomenon not only appears during the first stage, but also during the second stage of IGT. In addition, questionnaires indicated that normal decision makers disliked deck C at the consciousness (explicit) levels.ConclusionIn the modified version of IGT, deck C was no longer preferred by normal decision makers, despite having a better long-term outcome than deck A. This study identified two problems in the original IGT. First, the gain-loss frequency between decks A and C is pseudo-balanced. Second, the covered phenomenon leads to most IGT related studies misinterpreting the effect of gain-loss frequency in situations involving long-term outcomes, and even leads to overstatement of the foresight of normal decision makers.

Performance of healthy participants on the Iowa Gambling Task.

“…The frequency-of-losses effect has also been found in a different version of the IGT in which Chiu and Lin (2007) established a higher contrast between rewards and losses on each trial by increasing their magnitude while keeping the traditional long-term outcomes (i.e., -250 for 10 cards from the bad decks, and -F250 for 10 cards from the good decks). Chiu and Lin concluded that "the IGT contains some redundant procedures, confounding features, and problems in interpretation" and that "these problems should be refined to make the IGT a truly useful assessment tool" (Conclusion section, para.…”

Interactions among attention-deficit hyperactivity disorder (ADHD) and problem gambling in a probabilistic reward-learning task

“…Some other outcome measures used in this regard include total money won [38], total of cards selected on individual decks [29], comparison between the number of cards selected from the decks A and C (lowfrequency loses) and decks B and D (high-frequency loses) [29], and analysis of selections in the later trials versus the earlier ones [30,37]. This issue motivated us to compare the normalized number of good bets in the first-300 versus the last-100 trials.…”

“…This measure was calculated within four quartile time bins to show subjects' learning trends over trials. We also explored the behavioral performance by using the total number of good bets as in previous studies [29,30]. Finally, we computed a metric of participants' tendency to re-engage with a previous bet despite a negative/positive outcome.…”

The Role of Feedback in Decision Making

“…Uncertainty is compounded because the decision maker does not know how to incorporate feedback from their choice of decks, because they are unaware of how many total plays they are required to make. Given this fact, it may be the case that decision makers focus on the gain-loss frequency, rather than learning to make decisions that will contribute to a good final outcome (Chui & Lin, 2007). It is clear from the outset that the condition under which decisions are made is an uncertain one for two reasons: 1) not knowing the probabilities associated with the outcomes, 2) not knowing how to distribute one's choices because of being unaware of the length of the game.…”