Common and distinct brain activity associated with risky and ambiguous decision-making

The Brain Salience Network at the Intersection of Pain and Substance use Disorders: Insights from Functional Neuroimaging Research

Purpose of Review

The brain's salience network (SN), primarily comprising the anterior insula and anterior cingulate cortex, plays a key role in detecting salient stimuli and processing physical and socioemotional pain (e.g., social rejection). Mounting evidence underscores an altered SN in the etiology and maintenance of substance use disorders (SUDs). This paper aims to synthesize recent functional neuroimaging research emphasizing the SN's involvement in SUDs and physical/socioemotional pain and explore the therapeutic prospects of targeting the SN for SUD treatment.

Recent Findings

The SN is repeatedly activated during the experience of both physical and socioemotional pain. Altered activation within the SN is associated with both SUDs and chronic pain conditions, characterized by aberrant activity and connectivity patterns as well as structural changes. Among individuals with SUDs, functional and structural alterations in the SN have been linked to abnormal salience attribution (e.g., heightened responsiveness to drug-related cues), impaired cognitive control (e.g., impulsivity), and compromised decision-making processes. The high prevalence of physical and socioemotional pain in the SUD population may further exacerbate SN alterations, thus contributing to hindered recovery progress and treatment failure. Interventions targeting the restoration of SN functioning, such as real-time functional MRI feedback, neuromodulation, and psychotherapeutic approaches, hold promise as innovative SUD treatments.

Summary

The review highlights the significance of alterations in the structure and function of the SN as potential mechanisms underlying the co-occurrence of SUDs and physical/socioemotional pain. Future work that integrates neuroimaging with other research methodologies will provide novel insights into the mechanistic role of the SN in SUDs and inform the development of next-generation treatment modalities.

The common and distinct brain basis associated with adult and adolescent risk-taking behavior: Evidence from the neuroimaging meta-analysis

Risk-taking is a common, complex, and multidimensional behavior construct that has significant implications for human health and well-being. Previous research has identified the neural mechanisms underlying risk-taking behavior in both adolescents and adults, yet the differences between adolescents' and adults' risk-taking in the brain remain elusive. This study firstly employs a comprehensive meta-analysis approach that includes 73 adult and 20 adolescent whole-brain experiments, incorporating observations from 1986 adults and 789 adolescents obtained from online databases, including Web of Science, PubMed, ScienceDirect, Google Scholar and Neurosynth. It then combines functional decoding methods to identify common and distinct brain regions and corresponding psychological processes associated with risk-taking behavior in these two cohorts. The results indicated that the neural bases underlying risk-taking behavior in both age groups are situated within the cognitive control, reward, and sensory networks. Subsequent contrast analysis revealed that adolescents and adults risk-taking engaged frontal pole within the fronto-parietal control network (FPN), but the former recruited more ventrolateral area and the latter recruited more dorsolateral area. Moreover, adolescents' risk-taking evoked brain area activity within the ventral attention network (VAN) and the default mode network (DMN) compared with adults, consistent with the functional decoding analyses. These findings provide new insights into the similarities and disparities of risk-taking neural substrates underlying different age cohorts, supporting future neuroimaging research on the dynamic changes of risk-taking.

Specialized late cingulo-opercular network activation elucidates the mechanisms underlying decisions about ambiguity

Cortical task control networks, including the cingulo-opercular (CO) network play a key role in decision-making across a variety of functional domains. In particular, the CO network functions in a performance reporting capacity that supports successful task performance, especially in response to errors and ambiguity. In two studies testing the contribution of the CO network to ambiguity processing, we presented a valence bias task in which masked clearly and ambiguously valenced emotional expressions were slowly revealed over several seconds. This slow reveal task design provides a window into the decision-making mechanisms as they unfold over the course of a trial. In the main study, the slow reveal task was administered to 32 young adults in the fMRI environment and BOLD time courses were extracted from regions of interest in three control networks. In a follow-up study, the task was administered to a larger, online sample (n = 81) using a more extended slow reveal design with additional unmasking frames. Positive judgments of surprised faces were uniquely accompanied by slower response times and strong, late activation in the CO network. These results support the initial negativity hypothesis, which posits that the default response to ambiguity is negative and positive judgments are associated with a more effortful controlled process, and additionally suggest that this controlled process is mediated by the CO network. Moreover, ambiguous trials were characterized by a second CO response at the end of the trial, firmly placing CO function late in the decision-making process.

Machine learning-based classifying of risk-takers and risk-aversive individuals using resting-state EEG data: A pilot feasibility study

BACKGROUND

Decision-making is vital in interpersonal interactions and a country's economic and political conditions. People, especially managers, have to make decisions in different risky situations. There has been a growing interest in identifying managers' personality traits (i.e., risk-taking or risk-averse) in recent years. Although there are findings of signal decision-making and brain activity, the implementation of an intelligent brain-based technique to predict risk-averse and risk-taking managers is still in doubt.

METHODS

This study proposes an electroencephalogram (EEG)-based intelligent system to distinguish risk-taking managers from risk-averse ones by recording the EEG signals from 30 managers. In particular, wavelet transform, a time-frequency domain analysis method, was used on resting-state EEG data to extract statistical features. Then, a two-step statistical wrapper algorithm was used to select the appropriate features. The support vector machine classifier, a supervised learning method, was used to classify two groups of managers using chosen features.

RESULTS

Intersubject predictive performance could classify two groups of managers with 74.42% accuracy, 76.16% sensitivity, 72.32% specificity, and 75% F1-measure, indicating that machine learning (ML) models can distinguish between risk-taking and risk-averse managers using the features extracted from the alpha frequency band in 10 s analysis window size.

CONCLUSIONS

The findings of this study demonstrate the potential of using intelligent (ML-based) systems in distinguish between risk-taking and risk-averse managers using biological signals.

Neural and functional validation of fMRI-informed EEG model of right inferior frontal gyrus activity

The right inferior frontal gyrus (rIFG) is a region involved in the neural underpinning of cognitive control across several domains such as inhibitory control and attentional allocation process. Therefore, it constitutes a desirable neural target for brain-guided interventions such as neurofeedback (NF). To date, rIFG-NF has shown beneficial ability to rehabilitate or enhance cognitive functions using functional Magnetic Resonance Imaging (fMRI-NF). However, the utilization of fMRI-NF for clinical purposes is severely limited, due to its poor scalability. The present study aimed to overcome the limited applicability of fMRI-NF by developing and validating an EEG model of fMRI-defined rIFG activity (hereby termed "Electrical FingerPrint of rIFG"; rIFG-EFP). To validate the computational model, we employed two experiments in healthy individuals. The first study (n = 14) aimed to test the target engagement of the model by employing rIFG-EFP-NF training while simultaneously acquiring fMRI. The second study (n = 41) aimed to test the functional outcome of two sessions of rIFG-EFP-NF using a risk preference task (known to depict cognitive control processes), employed before and after the training. Results from the first study demonstrated neural target engagement as expected, showing associated rIFG-BOLD signal changing during simultaneous rIFG-EFP-NF training. Target anatomical specificity was verified by showing a more precise prediction of the rIFG-BOLD by the rIFG-EFP model compared to other EFP models. Results of the second study suggested that successful learning to up-regulate the rIFG-EFP signal through NF can reduce one's tendency for risk taking, indicating improved cognitive control after two sessions of rIFG-EFP-NF. Overall, our results confirm the validity of a scalable NF method for targeting rIFG activity by using an EEG probe.

Risk-taking in the human brain: An activation likelihood estimation meta-analysis of the balloon analog risk task (BART)

The Balloon Analog Risk Task (BART) is increasingly used to assess risk-taking behavior and brain function. However, the brain networks underlying risk-taking during the BART and its reliability remain controversial. Here, we combined the activation likelihood estimation (ALE) meta-analysis with both task-based and task-free functional connectivity (FC) analysis to quantitatively synthesize brain networks involved in risk-taking during the BART, and compared the differences between adults and adolescents studies. Based on 22 pooled publications, the ALE meta-analysis revealed multiple brain regions in the reward network, salience network, and executive control network underlying risk-taking during the BART. Compared with adult risk-taking, adolescent risk-taking showed greater activation in the insula, putamen, and prefrontal regions. The combination of meta-analytic connectivity modeling with task-free FC analysis further confirmed the involvement of the reward, salience, and cognitive control networks in the BART. These findings demonstrate the core brain networks for risk-taking during the BART and support the utility of the BART for future neuroimaging and developmental research.

Convergent gray matter alterations across drugs of abuse and network-level implications: A meta-analysis of structural MRI studies

BACKGROUND

Neuroimaging studies often consider brain alterations linked with substance abuse within the context of individual drugs (e.g., nicotine), while neurobiological theories of addiction emphasize common brain network-level alterations across drug classes. Using emergent meta-analytic techniques, we identified common structural brain alterations across drugs and characterized the functionally-connected networks with which such structurally altered regions interact.

METHODS

We identified 82 articles characterizing gray matter (GM) volume differences for substance users vs. controls. Using the anatomical likelihood estimation algorithm, we identified convergent GM reductions across drug classes. Next, we performed resting-state and meta-analytic functional connectivity analyses using each structurally altered region as a seed and computed whole-brain functional connectivity profiles as the union of both maps. We characterized an "extended network" by identifying brain areas demonstrating the highest degree of functional coupling with structurally impacted regions. Finally, hierarchical clustering was performed leveraging extended network nodes' functional connectivity profiles to delineate subnetworks.

RESULTS

Across drug classes, we identified medial frontal/ventromedial prefrontal, and multiple regions in anterior cingulate (ACC) and insula as regions displaying convergent GM reductions among users. Overlap of these regions' functional connectivity profiles identified ACC, inferior frontal, PCC, insula, superior temporal, and putamen as regions of an impacted extended network. Hierarchical clustering revealed 3 subnetworks closely corresponding to default mode (PCC, angular), salience (dACC, caudate), and executive control networks (dlPFC and parietal).

CONCLUSIONS

These outcomes suggest that substance-related structural brain alterations likely have implications for the functioning of canonical large-scale networks and the perpetuation of substance use and neurocognitive alterations.

A Systematic Review on Common and Distinct Neural Correlates of Risk-taking in Substance-related and Non-substance Related Addictions

Both substance-related as well as non-substance-related addictions may include recurrent engagement in risky actions despite adverse outcomes. We here apply a unified approach and review task-based neuroimaging studies on substance-related (SRAs) and non-substance related addictions (NSRAs) to examine commonalities and differences in neural correlates of risk-taking in these two addiction types. To this end, we conducted a systematic review adhering to the PRISMA guidelines. Two databases were searched with predefined search terms to identify neuroimaging studies on risk-taking tasks in individuals with addiction disorders. In total, 19 studies on SRAs (comprising a total of 648 individuals with SRAs) and 10 studies on NSRAs (comprising a total of 187 individuals with NSRAs) were included. Risk-related brain activation in SRAs and NSRAs was summarized individually and subsequently compared to each other. Results suggest convergent altered risk-related neural processes, including hyperactivity in the OFC and the striatum. As characteristic for both addiction types, these brain regions may represent an underlying mechanism of suboptimal decision-making. In contrast, decreased DLPFC activity may be specific to SRAs and decreased IFG activity could only be identified for NSRAs. The precuneus and posterior cingulate show elevated activity in SRAs, while findings regarding these areas were mixed in NSRAs. Additional scarce evidence suggests decreased ventral ACC activity and increased dorsal ACC activity in both addiction types. Associations between identified activation patterns with drug use severity underpin the clinical relevance of these findings. However, this exploratory evidence should be interpreted with caution and should be regarded as preliminary. Future research is needed to evaluate the findings gathered by this review.

Decision-Making Profiles and Their Associations with Cognitive Performance in Mild Cognitive Impairment

Background: It is crucial for older adults, especially those with mild cognitive impairment (MCI), to make profitable decisions routinely. However, the results regarding decision-making (DM) remain inconsistent. Objective: The present study assessed DM profiles under uncertainty conditions in individuals with MCI and their associations with multi-domain cognitive performance. Method: Fifty-three patients with MCI and forty-two age-, gender-, and education level-matched healthy controls (HCs) were administered a comprehensive neuropsychological battery test. The Iowa Gambling Task (IGT) and Game of Dice Task (GDT) were used to assess DM competence in conditions involving ambiguity and risk, respectively. In addition, Spearman’s correlations were used to examine relationships between GDT and multi-domain cognitive performance. Result: The final capital (FC) and frequency of utilization of negative feedback (FUNF) and positive feedback (FUPF) in the GDT were lower in MCI patients than in HCs. In addition, the number of shifts between safe and risky alternatives was significantly different across groups. However, IGT performance was comparable across groups. In the MCI patients, risky DM performance was associated with language, whereas in HCs was correlated with memory and executive functions. Besides, in MCI, performance on IGT was significantly correlated with social cognition. Conclusion: Individuals with mild cognitive impairment have difficulty utilizing feedback to make optimal decisions under risky situations. The association between decision-making performance and cognitive function is divergent regarding situational uncertainty and individuals’ cognitive status. In mild cognitive impairment and normal aging, decision-making under ambiguity needs further investigation.

Information about others' choices selectively alters risk tolerance and medial prefrontal cortex activation across adolescence and young adulthood

Adolescence is associated with major changes in the cognitive, emotional and social domains. One domain in which these processes intersect is decision-making. Previous research has shown that individuals’ attitudes towards risk and ambiguity shape their decision-making, and information about others’ choices can influence individuals’ decisions. However, it is currently unknown how information about others’ choices influences risk and ambiguity attitudes separately, and the degree to which others’ choices shape decision-making differentially across development from adolescence to young adulthood. The current study used a computational modeling framework to test how information about others’ choices influences these attitudes. Participants, aged 14–22 years, made a series of risky and ambiguous choices while undergoing fMRI scanning. On some trials, they viewed risky or safe choices of others. Results showed that participants aligned their choices toward the choice preferences of others. Moreover, the tendency to align choices was expressed in changes in risk attitude, but not ambiguity attitude. The change in risk attitude was positively related to neural activation in the medial prefrontal cortex. Results did not show age related differences in behavior and corresponding neural activation, indicating that the manner in which adolescents are influenced by peers is not ubiquitous but rather, is highly context-dependent.

The cue-reactivity paradigm: An ensemble of networks driving attention and cognition when viewing drug and natural reward-related stimuli

The cue-reactivity paradigm is a widely adopted neuroimaging probe engendering brain activity linked with attentional, affective, and reward processes following presentation of appetitive stimuli. Given the multiple mental operations invoked, we sought to decompose cue-related brain activity into constituent components employing emergent meta-analytic techniques when considering drug and natural reward-related cues. We conducted coordinate-based meta-analyses delineating common and distinct brain activity convergence across cue-reactivity studies (N = 196 articles) involving drug (n = 133) or natural (n = 63) visual stimuli. Across all studies, convergence was observed in limbic, cingulate, insula, and fronto-parieto-occipital regions. Drug-distinct convergence was observed in posterior cingulate, dorsolateral prefrontal, and temporo-parietal regions, whereas distinct-natural convergence was observed in thalamic, insular, orbitofrontal, and occipital regions. We characterized connectivity profiles of identified regions by leveraging task-independent and task-dependent MRI datasets, grouped these profiles into subnetworks, and linked each with putative mental operations. Outcomes suggest multifaceted brain activity during cue-reactivity can be decomposed into elemental processes and indicate that while drugs of abuse usurp the brain's natural-reward-processing system, some regions appear distinct to drug cue-reactivity.

Fear and anxiety in the face of COVID-19: Negative dispositions towards risk and uncertainty as vulnerability factors

In the face of the COVID-19 pandemic it is important to identify factors that make people particularly vulnerable of developing mental-health issues in order to provide case-specific treatments. In this article, we examine the roles of two psychological constructs - originally put forth in the behavioral decision sciences - in predicting interindividual differences in fear responses: general risk aversion (GRA) and intolerance of uncertainty (IU). We first provide a review of these constructs and illustrate why they may play important roles in shaping anxiety-related disorders. Thereafter we present an empirical study that collected survey data from 550 U.S. residents, comprising self-assessments of dispositions towards risk and uncertainty, anxiety- and depression levels, as well as demographic variables - to thus test the extent to which these psychological constructs are predictive of strong fear responses related to COVID-19 (i.e., mortal fear, racing heart). The results from Bayesian multi-model inference analyses showed that GRA and IU were more powerful predictors of fear responses than demographic variables. Moreover, the predictive power of these constructs was independent of general anxiety- and depression levels. Subsequent mediation analyses showed that the effects of GRA and IU were both direct and indirect via anxiety. We conclude by discussing possible treatment options, but also highlight that future research needs to further examine causal pathways and conceptual overlaps.

Neural Encoding of the Reliability of Directional Information During the Preparation of Targeted Movements

Visual information about the location of an upcoming target can be used to prepare an appropriate motor response and reduce its reaction time. Here, we investigated the brain mechanisms associated with the reliability of directional information used for motor preparation. We recorded brain activity using magnetoencephalography (MEG) during a delayed reaching task in which a visual cue provided valid information about the location of the upcoming target with 50, 75, or 100% reliability. We found that reaction time increased as cue reliability decreased and that trials with invalid cues had longer reaction times than trials with valid cues. MEG channel analysis showed that during the late cue period the power of the beta-band from left mid-anterior channels, contralateral to the responding hand, correlated with the reliability of the cue. This effect was source localized over a large motor-related cortical and subcortical network. In addition, during invalid-cue trials there was a phasic increase of theta-band power following target onset from left posterior channels, localized to the left occipito-parietal cortex. Furthermore, the theta-beta cross-frequency coupling between left mid-occipital and motor cortex transiently increased before responses to invalid-cue trials. In conclusion, beta-band power in motor-related areas reflected the reliability of directional information used during motor preparation, whereas phasic theta-band activity may have signaled whether the target was at the expected location or not. These results elucidate mechanisms of interaction between attentional and motor processes.

Adapting behavioural interventions to compensate for cognitive dysfunction in persons with opioid use disorder

Treatment for opioid use disorder (OUD) is often in the context of biobehavioural interventions, consisting of medication for OUD (for example, methadone and buprenorphine), which is accompanied by psychoeducation and/or behavioural therapies. Patients with OUD often display weaknesses in cognitive function that may impact the efficacy of such behavioural interventions. A review of the literature was conducted to: (1) describe common cognitive dysfunction profiles among patients with OUD, (2) outline intervention approaches for patients with OUD, (3) consider the cognitive demands that interventions place on patients with OUD and (4) identify potential accommodation strategies that may be used to optimise treatment outcomes. Cognitive profiles of patients with OUD often include weaknesses in executive function, attention, memory and information processing. Behavioural interventions require the patients' ability to learn, understand and remember information (placing specific cognitive demands on patients). Accommodation strategies are, therefore, needed for patients with challenges in one or more of these areas. Research on accommodation strategies for patients with OUD is very limited. We applied research from populations with similar cognitive profiles to form a comprehensive collection of potential strategies to compensate for cognitive dysfunction among patients with OUD. The cognitive profiles and accommodation strategies included in this review are intended to inform future intervention research aimed at improving outcomes among patients with OUD.

Hypoactivation in the precuneus and posterior cingulate cortex during ambiguous decision making in individuals with HIV

People with human immunodeficiency virus (HIV) often have neurocognitive impairment. People with HIV make riskier decisions when the outcome probabilities are known, and have abnormal neural architecture underlying risky decision making. However, ambiguous decision making, when the outcome probabilities are unknown, is more common in daily life, but the neural architecture underlying ambiguous decision making in people with HIV is unknown. Eighteen people with HIV and 20 controls completed a decision making task while undergoing functional magnetic resonance imaging scanning. Participants chose between a certain reward and uncertain reward with a known (risky) or unknown (ambiguous) probability of winning. There were three levels of risk: high, medium, and low. Ambiguous > risky brain activity was compared between groups. Ambiguous > risky brain activity was correlated with emotional/psychiatric functioning in people with HIV. Both groups were similarly ambiguity-averse. People with HIV were more risk-averse than controls and chose the high-risk uncertain option less often. People with HIV had hypoactivity in the precuneus, posterior cingulate cortex (PCC), and fusiform gyrus during ambiguous > medium risk decision making. Ambiguous > medium risk brain activity was negatively correlated with emotional/psychiatric functioning in individuals with HIV. To make ambiguous decisions, people with HIV underrecruit key regions of the default mode network, which are thought to integrate internally and externally derived information to come to a decision. These regions and related cognitive processes may be candidates for interventions to improve decision-making outcomes in people with HIV.

Better the devil you know than the devil you don't: Neural processing of risk and ambiguity

Risk and ambiguity are inherent in virtually all human decision-making. Risk refers to a situation in which we know the precise probability of potential outcomes of each option, whereas ambiguity refers to a situation in which outcome probabilities are not known. A large body of research has shown that individuals prefer known risks to ambiguity, a phenomenon known as ambiguity aversion. One heated debate concerns whether risky and ambiguous decisions rely on the same or distinct neural circuits. In the current meta-analyses, we integrated the results of neuroimaging research on decision-making under risk (n = 69) and ambiguity (n = 31). Our results showed that both processing of risk and ambiguity showed convergence in anterior insula, indicating a key role of anterior insula in encoding uncertainty. Risk additionally engaged dorsomedial prefrontal cortex (dmPFC) and ventral striatum, whereas ambiguity specifically recruited the dorsolateral prefrontal cortex (dlPFC), inferior parietal lobe (IPL) and right anterior insula. Our findings demonstrate overlapping and distinct neural substrates underlying different types of uncertainty, guiding future neuroimaging research on risk-taking and ambiguity aversion.

Decreased sensitivity to risk levels in ventral stratum in major depressive disorder during risky decision-making

BACKGROUND

Reduced decision-making ability in depressive people has been observed both in daily life and experimental behavioral studies. However, the neurobiology of dysfunction in decision-making among depressive people is still unclear.

METHODS

The study included 63 patients with major depressive disorder (MDD) and 49 healthy controls (HCs). The balloon analog risk task (BART), a risky decision-making paradigm, was used in a functional magnetic resonance imaging experiment to evaluate how brain activation was modulated by different levels of risk.

RESULTS

No significant difference in behavioral performance was found. In prespecified brain regions, the activation of the left ventral stratum (VS) in MDD patients showed reduced modulation by risk levels compared with HCs. No significant group difference was found in prespecified dorsal anterior cingulate cortex (dACC) and right dorsal lateral prefrontal cortex (DLPFC).

LIMITATIONS

BART did not isolate stages of making a choice and experiencing the outcome of the choice.

CONCLUSION

The left VS was less sensitive to risk levels in MDD patients compared with HCs, indicating inefficient reward processing in risky decision-making in MDD.

The transcranial direct current stimulation over prefrontal cortex combined with the cognitive training reduced the cue-induced craving in female individuals with methamphetamine use disorder: A randomized controlled trial

BACKGROUND

Craving and cognitive deficits are potential treatment targets for methamphetamine use disorder (MUD). Previous studies implied that transcranial direct current stimulation (tDCS) and cognitive training respectively improve these symptoms, but the combined effect is unknown. In this study, we investigated the combined effects of tDCS over dorsolateral prefrontal cortex (DLPFC) and computerized cognitive addiction therapy (CCAT) on cue-induced craving and cognitive functions among female individuals with MUD.

METHODS

Seventy-five patients with MUD were randomly assigned to three groups: CCAT + tDCS group, CCAT + sham tDCS group and the control group. The former two groups received 20 sessions of cognitive training combined 1.5 mA active/sham tDCS over DLPFC (20min/session, 5times/week), while the control group received usual care which includes routine medical care, health education, physical exercises and psychological support related to relapse prevention. The cue-induced craving and cognitive functions were tested at the baseline, the end of 2nd week and 4th week.

RESULTS

The CCAT + tDCS group showed a significant reduction in cue-induced craving after 4-week intervention. Moreover, the craving score of the real CCAT + tDCS group was significantly lower than that of the CCAT + sham tDCS group and that of the control group at the end of 4th week. A significant improvement in accuracy of TWOB task was only observed in the CCAT + tDCS group at the end of 4th week when compared to baseline. Unexpectedly, participants who received CCAT plus active or sham tDCS did not change their discounting, whereas those in the control group performed more impulsively over time.

CONCLUSIONS

The study found that the intervention of tDCS over DLPFC combined with CCAT may have potential benefit in improving treatment outcome in patients with MUD. More research is needed to explore the underlying mechanism.

Transcranial direct current stimulation over the right dorsolateral prefrontal cortex has distinct effects on choices involving risk and ambiguity

Human's uncertain decision-making involves choices of risk (with known probabilities) and ambiguity (with unknown probabilities). For risky and ambiguous decision-making processes, neural differences are rarely exhibited. To clarify the causal role of the right dorsolateral prefrontal cortex (DLPFC) in uncertain situations, we used transcranial direct current stimulation (tDCS) to demonstrate the involvement of the right DLPFC in decisions involving risk and ambiguity. Participants received either anodal or cathodal tDCS at 1.5 mA or sham stimulation over the right DLPFC and subsequently undertook tasks of risk and ambiguity. The results revealed that a preference for ambiguity could be measurably increased in individuals through anodal stimulation, but no significant differences were observed in the preferences for risky choices among groups. These findings suggest that different neural mechanisms underlie risky and ambiguous decisions because the right DLPFC primarily affects ambiguous behavior.