Good Decks Research Articles

Dark Triad Traits and Workplace Performance on the Iowa Gambling Task (IGT)

Background Psychologists have recently turned their focus to the “dark side” of workplace behavior, particularly negative traits that impact professional environments. Methods In this exploratory study, we examined the Dark Triad traits—Machiavellianism, narcissism, and psychopathy—among 3,112 bank employees. Additionally, we analyzed the Iowa Gambling Task (IGT) performance in a subset of 1,613 participants to explore correlations between Dark Triad traits and decision-making. We also investigated differences based on sex and job position. Results Our findings reveal that men scored higher on Dark Triad traits than women, reinforcing well-established findings. Furthermore, sales managers and premium client managers displayed the highest levels of Machiavellian strategies, though overall, bank employees showed significantly lower Machiavellianism scores compared to published Russian norms. While IGT performance showed no sex differences, it varied between managers and non-managers. A significant negative correlation emerged between Machiavellianism and psychopathy and good deck choices on the IGT, with a linear regression indicating that lower Dark Triad scores predicted better decision-making. Conclusion Further research is needed to explore the relationship between affective decision-making and dark personality traits.

The influence of social feedback on reward learning in the Iowa gambling task.

Learning, an important activity for both human and animals, has long been a focal point of research. During the learning process, subjects assimilate not only their own information but also information from others, a phenomenon known as social learning. While numerous studies have explored the impact of social feedback as a reward/punishment during learning, few studies have investigated whether social feedback facilitates or inhibits the learning of environmental rewards/punishments. This study aims to test the effects of social feedback on economic feedback and its cognitive processes by using the Iowa Gambling Task (IGT). One hundred ninety-two participants were recruited and categorized into one non-social feedback group and four social feedback groups. Participants in the social feedback groups were informed that after the outcome of each choice, they would also receive feedback from an online peer. This peer was a fictitious entity, with variations in identity (novice or expert) and feedback type (random or effective). The Outcome-Representation Learning model (ORL model) was used to quantify the cognitive components of learning. Behavioral results showed that both the identity of the peer and the type of feedback provided significantly influenced the deck selection, with effective social feedback increasing the ratio of chosen good decks. Results in the ORL model showed that the four social feedback groups exhibited lower learning rates for gain and loss compared to the nonsocial feedback group, which suggested, in the social feedback groups, the impact of the recent outcome on the update of value decreased. Parameters such as forgetfulness, win frequency, and deck perseverance in the expert-effective feedback group were significantly higher than those in the non-social feedback and expert-random feedback groups. These findings suggest that individuals proactively evaluate feedback providers and selectively adopt effective feedback to enhance learning.

Normatively irrelevant disgust interferes with decision under uncertainty: Insights from the Iowa gambling task.

This study investigates whether a not informative, irrelevant emotional reaction of disgust interferes with decision-making under uncertainty. We manipulate the Iowa Gambling Task (IGT) by associating a disgust-eliciting image with selections from Disadvantageous/Bad decks (Congruent condition) or Advantageous/Good decks (Incongruent condition). A Control condition without manipulations is also included. Results indicate an increased probability of selecting from a Good deck as the task unfolds in all conditions. However, this effect is modulated by the experimental manipulation. Specifically, we detect a detrimental effect (i.e., a significant decrease in the intercept) of the disgust-eliciting image in Incongruent condition (vs. Control), but this effect is limited to the early stages of the task (i.e., first twenty trials). No differences in performance trends are detected between Congruent and Control conditions. Anticipatory Skin Conductance Response, heart rate, and pupil dilation are also assessed as indexes of anticipatory autonomic activation following the Somatic Marker Hypothesis, but no effects are shown for the first two indexes in any of the conditions. Only a decreasing trend is detected for pupil dilation as the task unfolds in Control and Incongruent conditions. Results are discussed in line with the "risk as feelings" framework, the Somatic Marker Hypothesis, and IGT literature.

Not all bad decisions are alike: approach and avoidant bad decisions are associated with distinct network organization.

Decisions under ambiguity occurs daily for everyone. Subsequently, we all deliberate upon options to initiate an action most appropriate for current goal demands. Researchers has attempted to identify factors which contribute to risk taking, alongside the neurocircuitry underpinning it. Empirically, uncertain decision making is frequently assessed using the Iowa Gambling Task (IGT). Research have reliably identified varying regions implicating two broader circuits known as the reward and salience networks. However, considerable work has focused on contrasting "good" versus "bad" decisions. The present investigation attempted a unique approach to analyzing the modified IGT acquired during fMRI (n = 24) and focused on active and passive bad decisions to identify potential internetwork connectivity, dissociable connectivity patterns between approach and avoidant bad decisions, and their relationship with personality traits, which can be linked with behavioral approach styles. Network cluster analyses revealed general internetwork connectivity when passing (avoiding) good decks; however, the OFC was functionally disconnected from the rest of the selected brain regions when playing (approaching) bad decks. Decreased reward responsiveness was linked to increased functional connectivity between the lateral OFC and aSMG, while drive was associated with increased functional connectivity between dACC and aINS. We report evidence that approach and avoidant bad decisions are associated with distinct neural communication patterns. Avoidant decisions were marked by substantial network integration and coherence, contrasted with the general scarcity of internetwork communication observed for approach decisions. Furthermore, the present investigation observed preliminary evidence of personality traits linked with neural communication between salience and reward evaluative networks.

Investigating Factors Influencing Deck Conditions of Concrete Bridge and Steel Bridge Using an Interpretable Machine Learning Framework

Good deck condition is critical for a bridge to transport vehicles across physical obstacles on the landscape. This study uses the National Bridge Inventory data provided by LTBP InfoBridge to assess the influence of weather, structure, and traffic factors on deck conditions of concrete and steel bridges in the ten states with the highest percentage of bridges with poor deck conditions. For this analysis, an interpretable machine learning framework takes advantage of the high prediction accuracy while maintaining interpretability. A model is built for each structure type producing results that reveal the impacts of the factors on deck conditions for both types of bridges. The effects of various factors on the deck conditions of steel and concrete bridges are analyzed by comparing the similarities and differences among these factors. The results show that the concrete cast-in-place is the only deck structure associated with good deck conditions for steel bridges, while multiple other structure types associate with good deck conditions for concrete bridges. For the wearing surface, the bituminous wearing surface is highly associated with poor deck conditions of steel bridges. The number of snow days is negatively associated with the deck condition of steel bridges, while the concrete bridge could maintain a good performance with extremely long snow days. The findings also confirmed that increasing the truck percentage could deteriorate the deck conditions faster.

Enhancing the Psychometric Properties of the Iowa Gambling Task Using Full Generative Modeling.

Poor psychometrics, particularly low test-retest reliability, pose a major challenge for using behavioral tasks in individual differences research. Here, we demonstrate that full generative modeling of the Iowa Gambling Task (IGT) substantially improves test-retest reliability and may also enhance the IGT's validity for use in characterizing internalizing pathology, compared to the traditional analytic approach. IGT data was collected across two sessions, one month apart. Our full generative model incorporated (1) the Outcome Representation Learning (ORL) computational model at the person-level and (2) a group-level model that explicitly modeled test-retest reliability, along with other group-level effects. Compared to the traditional 'summary score' (proportion good decks selected), the ORL model provides a theoretically rich set of performance metrics (Reward Learning Rate , Punishment Learning Rate , Win Frequency Sensitivity , Perseveration Tendency , Memory Decay ), capturing distinct psychological processes. While test-retest reliability for the traditional summary score was only moderate (, BCa 95% CI [.04, .63]), test-retest reliabilities for ORL performance metrics produced by the full generative model were substantially improved, with test-retest correlations ranging between for the five ORL parameters. Further, while summary scores showed no substantial associations with internalizing symptoms, ORL parameters were significantly associated with internalizing symptoms. Specifically, Punishment Learning Rate was associated with higher self-reported depression and Perseveration Tendency was associated with lower self-reported anhedonia. Generative modeling offers promise for advancing individual differences research using the IGT, and behavioral tasks more generally, through enhancing task psychometrics.

Bridge Deck Deterioration: Reasons and Patterns

The deck condition of bridges is one of the most important factors impacting the connectivity and efficiency of transportation networks. Bridges with quickly deteriorating deck conditions are a huge financial burden for transportation agencies and can downgrade the efficiency of the whole transportation network. This study utilizes an interpretable machine learning framework, Shapley additive explanation (SHAP), to investigate the associations between various factors, such as wearing surface, deck structure, and so forth, and bridges with quickly deteriorating deck conditions nationwide. An XGBoost model is trained to perform the binary classification task on a heavily imbalanced dataset and classify relatively young bridges (less than 20 years old) with poor/fair deck conditions and relatively old bridges (30–40 years old) with good deck conditions in the National Bridge Inventory (NBI) database. The accuracy of the predictive model is 0.91, and the AUC score is about 0.83. After applying this well-performed predictive model on the interpretable machine learning framework, the results revealed that without wearing surface, corrugated steel deck structure, wide bridge structure, and long span are highly associated with bridges with quickly deteriorating decks. The results also show that bridges with a relatively low average daily traffic (ADT) or truck percentage of ADT are in a dilemma zone, where the overall traffic or truck volume of the bridge is not low enough to prevent fast deterioration, but not high enough for eligibility for the funding required for more durable materials during construction or appropriate maintenance.

Normatively Irrelevant Affective Cues Affect Risk-Taking under Uncertainty: Insights from the Iowa Gambling Task (IGT), Skin Conductance Response, and Heart Rate Variability.

Being able to distinguish between safe and risky options is paramount in making functional choices. However, deliberate manipulation of decision-makers emotions can lead to risky behaviors. This study aims at understanding how affective reactions driven by normatively irrelevant affective cues can interfere with risk-taking. Good and Bad decks of the Iowa Gambling Task have been manipulated to make them unpleasant through a negative auditory manipulation. Anticipatory skin conductance response (SCR) and heart rate variability (HRV) have been investigated in line with the somatic marker hypothesis. Results showed fewer selections from Good decks when they were negatively manipulated (i.e., Incongruent condition). No effect of the manipulation was detected when Bad decks were negatively manipulated (i.e., Congruent condition). Higher anticipatory SCR was associated with Bad decks in Congruent condition. Slower heart rate was found before selections from Good decks in Control and Congruent condition and from Bad decks in Incongruent condition. Differences in heart rate between Bad and Good decks were also detected in Congruent condition. Results shed light on how normatively irrelevant affective cues can interfere with risk-taking.

Autonomic responses to choice outcomes: Links to task performance and reinforcement-learning parameters

Previous work has shown that autonomic responses to choice feedback can predict subsequent decision-making. In this study, we tested whether skin conductance responses (SCRs) and heart rate (HR) decelerations following the presentation of choice outcomes predict Iowa Gambling Task performance in nonclinical participants (n = 64). We also examined how these signals related to parameters of a reinforcement-learning (RL) model. Feedback SCRs and HR decelerations were greater following outcomes that included losses and choices from the bad decks defined by their negative expected value. In addition, SCRs predicted task performance. A hierarchical Bayesian RL model indicated that greater feedback SCR for the bad decks compared to good decks was associated with stronger loss aversion and a lower learning rate, both of which predicted higher performance. These results suggest that feedback-related SCRs are linked to individual differences in outcome evaluation and learning processes that guide reinforcement-learning.

0125 Sleep Deprivation Impairs the Ability to Overcome Pre-Existing Framing Bias

Abstract Introduction When presented with a choice between sure gains or losses versus gambles, people tend to select sure gains over gambles, but gambles over sure losses. This pre-existing framing bias is embedded in the Framed Gambling Task (FGT), in which subjects choose between a sure option (gain or loss) and a gamble (card from one of two decks). For optimal performance, subjects need to recognize that one deck (‘good deck’) results in better average outcomes than the other deck (‘bad deck’) and select the gamble or sure option depending on the deck (good/bad) rather than the frame (sure loss/gain). A speeded version of the FGT, with 2s response deadlines to induce time pressure, was used in a laboratory total sleep deprivation (TSD) study to determine the impact of sleep loss on the ability to overcome pre-existing framing bias. Methods Eight-six subjects (ages 21–38; 47 females) were randomized (2:1 ratio) to a TSD condition (n=56) or control condition (n=30). They completed the speeded FGT at 11:00 on the baseline day (session 1), and again the following day (session 2) after 27h of wakefulness (TSD group) or 3h of wakefulness (control group). Performance accuracy was defined in terms of optimal task performance, i.e., gambling when the good deck was presented and not gambling when the bad deck was presented. Each test bout had 72 trials across three trial blocks. Results Accuracy improved across trial blocks (F1,84=20.44, p<0.001). In session 2, the TSD group showed lower accuracy (condition by session interaction: F2,84=4.15, p=0.045) and less improvement across trial blocks (condition by session by trial block interaction: F2,168=3.97, p=0.021) than the control group. Even under TSD, the frequency of response timeouts (RT>2s) was low (<3.5% of trials). Conclusion Sleep deprivation degraded FGT performance under time pressure, indicating reduced ability to overcome pre-existing framing bias. Support PRMRP award W81XWH-16-1-0319

Neural Correlates of Successful and Unsuccessful Strategical Mechanisms Involved in Uncertain Decision-Making

The ability to develop successful long-term strategies in uncertain situations relies on complex neural mechanisms. Although lesion studies have shown some of the mechanisms involved, it is still unknown why some healthy subjects are able to make the right decision whereas others are not. The aim of our study was to investigate neurophysiological differences underlying this ability to develop a successful strategy in a group of healthy subjects playing a monetary card game called the Iowa Gambling Task (IGT). In this task, subjects have to win and earn money by choosing between four decks of cards, two were advantageous in the long term and two disadvantageous. Twenty healthy right-handed subjects performed the IGT while their cerebral activity was recorded by electroencephalography. Based on their behavioral performances, two groups of subjects could clearly be distinguished: one who selected the good decks and thus succeeded in developing a Favorable strategy (9 subjects) and one who remained Undecided (11 subjects). No neural difference was found between each group before the selection of a deck, but in both groups a greater negativity was found emerging from the right superior frontal gyrus 600 ms before a disadvantageous selection. During the processing of the feedback, an attenuation of the P200 and P300 waveforms was found for the Undecided group, and a P300 originating from the medial frontal gyrus was found in response to a loss only in the Favorable group. Our results suggest that undecided subjects are hyposensitive to the valence of the cards during gambling, which affects the feedback processing.

Post learning sleep improves cognitive-emotional decision-making: evidence for a 'deck B sleep effect' in the Iowa Gambling Task.

The Iowa Gambling Task (IGT) is widely used to assess real life decision-making impairment in a wide variety of clinical populations. Our study evaluated how IGT learning occurs across two sessions, and whether a period of intervening sleep between sessions can enhance learning. Furthermore, we investigate whether pre-sleep learning is necessary for this improvement. A 200-trial version of the IGT was administered at two sessions separated by wake, sleep or sleep and wake (time-of-day control). Participants were categorized as learners and non-learners based on initial performance in session one. In session one, participants initially preferred the high-frequency reward decks B and D, however, a subset of learners decreased choice from negative expected value ‘bad’ deck B and increased choices towards with a positive expected value ‘good’ decks (decks C and D). The learners who had a period of sleep (sleep and sleep/wake control conditions) between sessions showed significantly larger reduction in choices from deck B and increase in choices from good decks compared to learners that had intervening wake. Our results are the first to show that post-learning sleep can improve performance on a complex decision-making task such as the IGT. These results provide new insights into IGT learning and have important implications for understanding the neural mechanisms of “sleeping on” a decision.

Performance and awareness in the Iowa Gambling Task

Newell & Shanks (N&S) conclude that healthy participants learn to differentiate between the good and bad decks of the Iowa Gambling Task, and that healthy participants even have conscious knowledge about the task's payoff structure. Improved methods of analysis and new behavioral findings suggest that this conclusion is premature.

Validating the PVL-Delta model for the Iowa gambling task

Decision-making deficits in clinical populations are often assessed with the Iowa gambling task (IGT). Performance on this task is driven by latent psychological processes, the assessment of which requires an analysis using cognitive models. Two popular examples of such models are the Expectancy Valence (EV) and Prospect Valence Learning (PVL) models. These models have recently been subjected to sophisticated procedures of model checking, spawning a hybrid version of the EV and PVL models—the PVL-Delta model. In order to test the validity of the PVL-Delta model we present a parameter space partitioning (PSP) study and a test of selective influence. The PSP study allows one to assess the choice patterns that the PVL-Delta model generates across its entire parameter space. The PSP study revealed that the model accounts for empirical choice patterns featuring a preference for the good decks or the decks with infrequent losses; however, the model fails to account for empirical choice patterns featuring a preference for the bad decks. The test of selective influence investigates the effectiveness of experimental manipulations designed to target only a single model parameter. This test showed that the manipulations were successful for all but one parameter. To conclude, despite a few shortcomings, the PVL-Delta model seems to be a better IGT model than the popular EV and PVL models.

The deficit of decision-making in male subjects with antisocial personality disorder

Objective To investigate the capabilities of decision-making in male subjects with Antisocial personality disorder(ASPD). Methods A total of 76 male ASPD subjects were compared with matched 60 healthy controls on the Iowa Gambling Task.At the same time, All of them were evaluated with Self- Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), Mini-Mental State Examination (MMSE), the MMPI Personality Disorder Scales (MMPI-Pd) and The Barratt Impulsiveness Scale (BIS-11). Results The ASPD group selected less advantageous cards (the number of cards selected from the advantageous decks minus the number of cards selected from disadvantageous decks) than healthy controls ((-4.13±18.27)time, (6.03±19.43) time respectively, t(134)=-3.132, P=0.002). A 2(group)×5(block) ANOVA (analysis of variance) on the cards of net advantageous from the gambling task revealed a significant main effect of group (F(1, 134)=9.811, P=0.002). Meanwhile, the ANOVA revealed a significant main effect of block(F(4, 536)=15.456, P<0.001). The results showed that healthy controls and ASPD group gradually shifted their selections toward the good decks as the game progresses.The study indicated the total number of advantageous cards for subjects with antisocial personality disorder were negative correlation to the MMPI-Pd(r=-0.232, P=0.006). Conclusion The present study suggests that the decision-making impairment might be in the male subjects with antisocial personality disorder.The deficit of decision-making for ASPD might be attributed to the dysfunction of the orbitofrontal, dorsolateral frontal, and anterior cingulate cortex. Key words: Antisocial personality disorder; Decision making; Cognition

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.

The interaction between expected values and risk levels in a modified Iowa gambling task

Performance on the Iowa gambling task (IGT) supports somatic marker hypothesis (SMH), which proposes that the process of decision making depends on emotion (Damasio, 1994). However, the bad decks in the IGT are also more risky and that confounds the results. To resolve this issue, the IGT-Yen, a variant of the IGT, was created to independently examine the effects of expected value and risk. After 20 trials, participants selected more high-risk bad decks than low-risk bad decks and more low-risk good decks than high-risk good decks. Greater anticipatory skin conductance levels (SCLs) were associated with choosing high-risk bad decks compared to choosing low-risk bad decks in trials 21–80, and greater anticipatory SCLs were associated with choosing low-risk good decks compared to choosing high-risk good decks in trials 81–100. Therefore, the anticipatory SCLs were associated with expected values of the decks and with their levels of risk.

The Role of Risk Aversion in Non-Conscious Decision Making

To what extent can people choose advantageously without knowing why they are making those choices? This hotly debated question has capitalized on the Iowa Gambling Task (IGT), in which people often learn to choose advantageously without appearing to know why. However, because the IGT is unconstrained in many respects, this finding remains debated and other interpretations are possible (e.g., risk aversion, ambiguity aversion, limits of working memory, or insensitivity to reward/punishment can explain the finding of the IGT). Here we devised an improved variant of the IGT in which the deck-payoff contingency switches after subjects repeatedly choose from a good deck, offering the statistical power of repeated within-subject measures based on learning the reward contingencies associated with each deck. We found that participants exhibited low confidence in their choices, as probed with post-decision wagering, despite high accuracy in selecting advantageous decks in the task, which is putative evidence for non-conscious decision making. However, such a behavioral dissociation could also be explained by risk aversion, a tendency to avoid risky decisions under uncertainty. By explicitly measuring risk aversion for each individual, we predicted subjects’ post-decision wagering using Bayesian modeling. We found that risk aversion indeed does play a role, but that it did not explain the entire effect. Moreover, independently measured risk aversion was uncorrelated with risk aversion exhibited during our version of the IGT, raising the possibility that the latter risk aversion may be non-conscious. Our findings support the idea that people can make optimal choices without being fully aware of the basis of their decision. We suggest that non-conscious decision making may be mediated by emotional feelings of risk that are based on mechanisms distinct from those that support cognitive assessment of risk.

Characterization of Children’s Affective Decision Making: Sensitivity to the Frequency of Punishment and Reward

Affective decision making is an individual ability to make choice under risk and uncertainty. The Iowa Gambling Task (IGT) developed by Bechara has been widely used to assess decision behavior under uncertainty. The original IGT was designed to examine the decision making that is profitable in the future. In IGT participants have to develop a long-term profitable monetary scenario in a situation of uncertainty and a conflict between the chance of encountering an immediate large reward (US$100) in two long-term loosing decks (A and B; US$250 per10 cards) and the chance of encountering an immediate small reward (US$50) in two long-term winning decks (C and D; US$+250 per 10 cards). According to the research, it is found that normal adults choose more from the good decks while individuals with pre-frontal ventromedial cortex (VM-PFC) never learned to choose more from the good decks. Bechara consider that patients with VM-PFC opting for choices that yield high immediate gains in spite of higher future losses. While there is a large amount of research on the IGT in the adult population, there is less work done on children. In order to examine whether young children would show a similar preference for immediate prospects, the modification IGT adopted considering children unique features. Basically, development of affective decision making was studied in 120 children at the age of 3 and 5 using modified IGT. Results shows young children are inclined to make advantageous choices, in particular, when the probability of punishment is higher. Children act sensitively towards the frequency of rewards and punishments. Compared with the age of 3 and 4, the study also implies that the age of 4 and 5 ones could make more advantageous choice by increasing the frequency of reward in advantage cards. In conclusion, both standards and reversed tasks show children’s decision making deficits might be associated with sensitivity to frequency of punishment. However, this is not noticeable among younger aged group. The abilities of affective decision making be developed extremely fast between 3 and 4 years old.

The deficit of decision-making in Parkinson's disease

To investigate the characteristics of decision-making impairment in Parkinson's disease (PD) patients. A total of 20 individuals with idiopathic PD were compared with matched health controls on the Iowa Gambling Task, A series of battery including the assessment working memory, visual spatial ability and verbal fluency was also administered. The severity of disease was assessed based on the Hohen and Yahr scale. The results showed that PD group impaired on verbal fluency, working memory and decision-making task. In Iowa gambling task, the PD group selected more disadvantageous cards than health controls (51.6 +/- 5.8, 46.8 +/- 8.2 respectively), the difference between two groups is significant (t((38)) = 2.12, P = 0.04). A 2 (group) x 5 (block) ANOVA (analysis of variance) on the scores of advantageous from the gambling task revealed a significant main effect of group (F((1, 38)) = 6.16, P = 0.01). The ANOVA also revealed a significant main effect of block (F((4, 152)) = 2.43, P = 0.04). The results showed that health controls gradually shifted their selections toward the good decks as the game progresses, but the PD group did not exhibit this stable advantageous shift in decision-making. Meanwhile, the study indicated the total number of disadvantageous cards for PD was positive correlation to the degrees of severity to clinical symptom. The present study suggests that the decision-making impairment might be in early PD. The deficit of decision-making for PD might be attributed to the dysfunction of the orbito-frontal cortex.