A Simplified Model of Choice Behavior under Uncertainty.

The Iowa Gambling Task (IGT) has been standardized as a clinical assessment tool (Bechara, 2007). Nonetheless, numerous research groups have attempted to modify IGT models to optimize parameters for predicting the choice behavior of normal controls and patients. A decade ago, most researchers considered the expected utility (EU) model (Busemeyer and Stout, 2002) to be the optimal model for predicting choice behavior under uncertainty. However, in recent years, studies have demonstrated that models with the prospect utility (PU) function are more effective than the EU models in the IGT (Ahn et al., 2008). Nevertheless, after some preliminary tests based on our behavioral dataset and modeling, it was determined that the Ahn et al. (2008) PU model is not optimal due to some incompatible results. This study aims to modify the Ahn et al. (2008) PU model to a simplified model and used the IGT performance of 145 subjects as the benchmark data for comparison. In our simplified PU model, the best goodness-of-fit was found mostly as the value of α approached zero. More specifically, we retested the key parameters α, λ, and A in the PU model. Notably, the influence of the parameters α, λ, and A has a hierarchical power structure in terms of manipulating the goodness-of-fit in the PU model. Additionally, we found that the parameters λ and A may be ineffective when the parameter α is close to zero in the PU model. The present simplified model demonstrated that decision makers mostly adopted the strategy of gain-stay loss-shift rather than foreseeing the long-term outcome. However, there are other behavioral variables that are not well revealed under these dynamic-uncertainty situations. Therefore, the optimal behavioral models may not have been found yet. In short, the best model for predicting choice behavior under dynamic-uncertainty situations should be further evaluated.

Are normal decision-makers sensitive to changes in value contrast under uncertainty? Evidence from the Iowa Gambling Task.

The Iowa Gambling Task (IGT) developed by Bechara et al. in 1994 is used to diagnose patients with Ventromedial Medial Prefrontal Cortex (VMPFC) lesions, and it has become a landmark in research on decision making. According to Bechara et al., the manipulation of progressive increments of monetary value can normalize the performance of patients with VMPFC lesions; thus, they developed a computerized version of the IGT. However, the empirical results showed that patients' performances did not improve as a result of this manipulation, which suggested that patients with VMPFC lesions performed myopically for future consequences. Using the original version of the IGT, some IGT studies have demonstrated that increments of monetary value significantly influence the performance of normal subjects in the IGT. However, other research has resulted in inconsistent findings. In this study, we used the computerized IGT (1X-IGT) and manipulated the value contrast of progressive increments (i.e., by designing the 10X-IGT, which contained 10 times of progressive increment) to investigate the influence of value contrast on the performance of normal subjects. The resulting empirical observations indicated that the value contrast (1X- vs. 10X-IGT) of the progressive increment had no effect on the performance of normal subjects. This study also provides a discussion of the issue of value in IGT-related studies. Moreover, we found the "prominent deck B phenomenon" in both versions of the IGT, which indicated that the normal subjects were guided mostly by the gain-loss frequency, rather than by the monetary value contrast. In sum, the behavioral performance of normal subjects demonstrated a low correlation with changes in monetary value, even in the 10X-IGT.

Reexamining the validity and reliability of the clinical version of the iowa gambling task: evidence from a normal subject group.

Over past decade, the Iowa gambling task (IGT) has been utilized to test various decision deficits induced by neurological damage or psychiatric disorders. The IGT has recently been standardized for identifying 13 different neuropsychological disorders. Neuropsychological patients choose bad decks frequently, and normal subjects prefer good expected value (EV) decks. However, the IGT has several validity and reliability problems. Some research groups have pointed out that the validity of IGT is influenced by the personality and emotional state of subjects. Additionally, several other studies have proposed that the "prominent deck B phenomenon" (PDB phenomenon) - that is, normal subjects preferring bad deck B - may be the most serious problem confronting IGT validity. Specifically, deck B offers a high frequency of gains but negative EV. In the standard IGT administration, choice behavior can be understood with reference to gain-loss frequency (GLF) rather than inferred future consequences (EV, the basic assumption of IGT). Furthermore, using two different criteria (basic assumption vs. professional norm) results in significantly different classification results. Therefore, we recruited 72 normal subjects to test the validity and reliability of IGT. Each subject performed three runs of the computer-based clinical IGT version. The PDB phenomenon has been observed to a significant degree in the first and second stages of the clinical IGT version. Obviously, validity, reliability, and the practice effect were unstable between two given stages. The present form of the clinical IGT version has only one stage, so its use should be reconsidered for examining normal decision makers; results from patient groups must also be interpreted with great care. GLF could be the main factor to be considered in establishing the constructional validity and reliability of the clinical IGT version.

Mirrored prominent deck B phenomenon: frequent small losses override infrequent large gains in the inverted Iowa Gambling Task.

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.