Mathematical modeling of risk-taking in bipolar disorder: Evidence of reduced behavioral consistency, with altered loss aversion specific to those with history of substance use disorder

Computational Modeling Interpretation Underlying Elevated Risk-Taking Propensity in the Dynamic Risky Investment Process of Non-Labor Income

Introduction

Money source influences risk-taking behaviors. Although studies consistently indicated that individuals demonstrate a higher propensity to make risky investments when utilizing non-labor income as opposed to labor income, explanations as to why non-labor income leads to continuously blowing money into risky investments are scarce.

Methods

The current study leverages a computational modeling approach to compare the differences in the dynamic risk investment process among individuals endowed with income from different sources (ie, non-labor income vs labor income) to understand the shaping force of higher risk-taking propensity in individuals with non-labor income. A total of 103 participants were recruited and completed the Balloon Analogue Risk Task (BART) with an equal monetary endowment, either as a token for completion of survey questionnaires (representing labor income) or as a prize from a lucky draw game (representing non-labor income).

Results

We found that individuals endowed with non-labor income made more risky investments in BART compared to those with labor income. With computational modeling, we further identified two key differences in the dynamic risk investment processes between individuals endowed with labor and those with non-labor income. Specifically, individuals endowed with non-labor income had a higher preset expectation for risk-taking and displayed desensitization towards losses during risk investments, in contrast to individuals with labor income.

Discussion

This study contributed to a better understanding of the psychological mechanisms of why individuals make more risk-taking behaviors with non-labor income, namely higher preset expectations of risk-taking and desensitization towards losses. Future research could validate these findings across diverse samples with varying backgrounds and adopt different manipulations of labor and non-labor income to enhance the external validity of our study.

Evaluation of bidirectional relationships between risk preference and mood disorders: A 2-sample Mendelian randomization study

BACKGROUND

Risk preference is often defined as the tendency to engage in risky activities. Increasing evidence shows that risk preference is associated with mood disorders. However, the causality and direction of this association are not clear.

METHODS

Genome-wide association study summary data of risk preference in 939,908 participants from UK Biobank and 23andMe were used to identify general risk preference. Data for 413,466 individuals taken from The Psychiatric Genomics Consortium were used to identify bipolar disorder (BP). Data for 807,553 individuals taken from The Psychiatric Genomics Consortium were used to identify major depressive disorder (MDD). The weighted median, inverse-variance weighting, and Mendelian randomization-Egger methods were used for the Mendelian randomization analysis to estimate a causal effect and detect directional pleiotropy.

RESULTS

GWAS summary data were obtained from three combined samples, containing 939,908, 413,466 and 807,553 individuals of European ancestry. Mendelian randomization evidence suggested that risk preference increased the onset of BP, and BP also increased risk preference (P < 0.001). In contrast, there were no reliable results to describe the relationship of risk preference with MDD (P > 0.05). Furthermore, there was no significant relationship between MDD and risk preference.

CONCLUSION

Using large-scale GWAS data, robust evidence supports a mutual relationship between risk preference and BP, but no relationship between risk preference and MDD was observed. This study indicates a potential marker for the early identification of MDD and BP. Additionally, it shows that reducing risk preferences for patients with BP may be a valuable intervention for treating BP.

Insular and Striatal Correlates of Uncertain Risky Reward Pursuit in Schizophrenia

BACKGROUND AND HYPOTHESIS

Risk-taking in specific contexts can be beneficial, leading to rewarding outcomes. Schizophrenia is associated with disadvantageous decision-making, as subjects pursue uncertain risky rewards less than controls. However, it is unclear whether this behavior is associated with more risk sensitivity or less reward incentivization. Matching on demographics and intelligence quotient (IQ), we determined whether risk-taking was more associated with brain activation in regions affiliated with risk evaluation or reward processing.

STUDY DESIGN

Subjects (30 schizophrenia/schizoaffective disorder, 30 controls) completed a modified, fMRI Balloon Analogue Risk Task. Brain activation was modeled during decisions to pursue risky rewards and parametrically modeled according to risk level.

STUDY RESULTS

The schizophrenia group exhibited less risky-reward pursuit despite previous adverse outcomes (Average Explosions; F(1,59) = 4.06, P = .048) but the comparable point at which risk-taking was volitionally discontinued (Adjusted Pumps; F(1,59) = 2.65, P = .11). Less activation was found in schizophrenia via whole brain and region of interest (ROI) analyses in the right (F(1,59) = 14.91, P < 0.001) and left (F(1,59) = 16.34, P < 0.001) nucleus accumbens (NAcc) during decisions to pursue rewards relative to riskiness. Risk-taking correlated with IQ in schizophrenia, but not controls. Path analyses of average ROI activation revealed less statistically determined influence of anterior insula upon dorsal anterior cingulate bilaterally (left: χ2 = 12.73, P < .001; right: χ2 = 9.54, P = .002) during risky reward pursuit in schizophrenia.

CONCLUSIONS

NAcc activation in schizophrenia varied less according to the relative riskiness of uncertain rewards compared to controls, suggesting aberrations in reward processing. The lack of activation differences in other regions suggests similar risk evaluation. Less insular influence on the anterior cingulate may relate to attenuated salience attribution or inability for risk-related brain region collaboration to sufficiently perceive situational risk.