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Mirrored Prominent Deck B Phenomenon: Frequent Small Losses Override Infrequent Large Gains in the Inverted Iowa Gambling Task
Authors:Ching-Hung Lin  Tzu-Jiun Song  Yu-Kai Lin  Yao-Chu Chiu
Institution:1. Department of Psychology, Soochow University, Taipei, Taiwan.; 2. Laboratory of Integrated Brain Research, Department of Medical Research & Education, Taipei Veterans General Hospital, Taipei, Taiwan.; 3. Biomedical Electronics Translational Research Center, National Chiao Tung University, Hsinchu, Taiwan.; 4. Biomedical Engineering Research and Development Center, China Medical University Hospital, Taichung, Taiwan.; National Research & Technology Council, Argentina,
Abstract:Since Bechara et al. pioneered its development, the Iowa Gambling Task (IGT) has been widely applied to elucidate decision behavior and medial prefrontal function. Although most decision makers can hunch the final benefits of IGT, ventromedial prefrontal lesions generate a myopic choice pattern. Additionally, the Iowa group developed a revised IGT (inverted IGT, iIGT) to confirm the IGT validity. Each iIGT trial was generated from the trial of IGT by multiplying by a “−” to create an inverted monetary value. Thus, bad decks A and B in the IGT become good decks iA and iB in the iIGT; additionally, good decks C and D in the IGT become bad decks iC and iD in the iIGT. Furthermore, IGT possessed mostly the gain trials, and iIGT possessed mainly the loss trials. Therefore, IGT is a frequent-gain–based task, and iIGT is a frequent-loss–based task. However, a growing number of IGT-related studies have identified confounding factors in IGT (i.e., gain-loss frequency), which are demonstrated by the prominent deck B phenomenon (PDB phenomenon). Nevertheless, the mirrored PDB phenomenon and guiding power of gain-loss frequency in iIGT have seldom been reexamined. This experimental finding supports the prediction based on gain-loss frequency. This study identifies the mirrored PDB phenomenon. Frequent small losses override occasional large gains in deck iB of the iIGT. Learning curve analysis generally supports the phenomenon based on gain-loss frequency rather than final outcome. In terms of iIGT and simple versions of iIGT, results of this study demonstrate that high-frequency loss, rather than a satisfactory final outcome, dominates the preference of normal decision makers under uncertainty. Furthermore, normal subjects prefer “no immediate punishment” rather than “final reward” under uncertainty.
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