Event-related potentials in response to feedback following risk-taking in the hot version of the Columbia Card Task

Risk-Taking Is Associated with Decreased Subjective Value Signals and Increased Prediction Error Signals in the Hot Columbia Card Task

It remains a pressing concern to understand how neural computations relate to risky decisions. However, most observations of brain-behavior relationships in the risk-taking domain lack a rigorous computational basis or fail to emulate of the dynamic, sequential nature of real-life risky decision-making. Recent advances emphasize the role of neural prediction error (PE) signals. We modeled, according to prospect theory, the choices of n = 43 human participants (33 females, 10 males) performing an EEG version of the hot Columbia Card Task, featuring rounds of sequential decisions between stopping (safe option) and continuing with increasing odds of a high loss (risky option). Single-trial regression EEG analyses yielded a subjective value signal at centroparietal (300-700 ms) and frontocentral (>800 ms) electrodes and in the delta band, as well as PE signals tied to the feedback-related negativity, P3a, and P3b, and in the theta band. Higher risk preference (total number of risky choices) was linked to attenuated subjective value signals but increased PE signals. Higher P3-like activity associated with the most positive PE in each round predicted stopping in the present round but not risk-taking in the subsequent round. Our findings indicate that decreased representation of decision values and increased sensitivity to winning despite low odds (positive PE) facilitate risky choices at the subject level. Strong neural responses when gains are least expected (the most positive PE on each round) adaptively contribute to safer choices at the trial-by-trial level but do not affect risky choice at the round-by-round level.

Adaptations of the balloon analog risk task for neuroimaging settings: a systematic review

Introduction

The Balloon Analog Risk Task (BART), a computerized behavioral paradigm, is one of the most common tools used to assess the risk-taking propensity of an individual. Since its initial behavioral version, the BART has been adapted to neuroimaging technique to explore brain networks of risk-taking behavior. However, while there are a variety of paradigms adapted to neuroimaging to date, no consensus has been reached on the best paradigm with the appropriate parameters to study the brain during risk-taking assessed by the BART. In this review of the literature, we aimed to identify the most appropriate BART parameters to adapt the initial paradigm to neuroimaging and increase the reliability of this tool.

Methods

A systematic review focused on the BART versions adapted to neuroimaging was performed in accordance with PRISMA guidelines.

Results

A total of 105 articles with 6,879 subjects identified from the PubMed database met the inclusion criteria. The BART was adapted in four neuroimaging techniques, mostly in functional magnetic resonance imaging or electroencephalography settings.

Discussion

First, to adapt the BART to neuroimaging, a delay was included between each trial, the total number of inflations was reduced between 12 and 30 pumps, and the number of trials was increased between 80 and 100 balloons, enabling us to respect the recording constraints of neuroimaging. Second, explicit feedback about the balloon burst limited the decisions under ambiguity associated with the first trials. Third, employing an outcome index that provides more informative measures than the standard average pump score, along with a model incorporating an exponential monotonic increase in explosion probability and a maximum explosion probability between 50 and 75%, can yield a reliable estimation of risk profile. Additionally, enhancing participant motivation can be achieved by increasing the reward in line with the risk level and implementing payment based on their performance in the BART. Although there is no universal adaptation of the BART to neuroimaging, and depending on the objectives of a study, an adjustment of parameters optimizes its evaluation and clinical utility in assessing risk-taking.

Uncertainty deconstructed: conceptual analysis and state-of-the-art review of the ERP correlates of risk and ambiguity in decision-making

Risk and uncertainty are central concepts of decision neuroscience. However, a comprehensive review of the literature shows that most studies define risk and uncertainty in an unclear fashion or use both terms interchangeably, which hinders the integration of the existing findings. We suggest uncertainty as an umbrella term that comprises scenarios characterized by outcome variance where relevant information about the type and likelihood of outcomes may be somewhat unavailable (ambiguity) and scenarios where the likelihood of outcomes is known (risk).These conceptual issues are problematic for studies on the temporal neurodynamics of decision-making under risk and ambiguity, because they lead to heterogeneity in task design and the interpretation of the results. To assess this problem, we conducted a state-of-the-art review of ERP studies on risk and ambiguity in decision-making. By employing the above definitions to 16 reviewed studies, our results suggest that: (a) research has focused more on risk than ambiguity processing; (b) studies assessing decision-making under risk often implemented descriptive-based paradigms, whereas studies assessing ambiguity processing equally implemented descriptive- and experience-based tasks; (c) descriptive-based studies link risk processing to increased frontal negativities (e.g., N2, N400) and both risk and ambiguity to reduced parietal positivities (e.g., P2, P3); (d) experience-based studies link risk to increased P3 amplitudes and ambiguity to increased frontal negativities and the LPC component; (e) both risk and ambiguity processing seem to be related with cognitive control, conflict monitoring, and increased cognitive demand; (f) further research and improved tasks are needed to dissociate risk and ambiguity processing.

Electrophysiological evidence for the effects of pain on the different stages of reward evaluation under a purchasing situation

Pain and reward have crucial roles in determining human behaviors. It is still unclear how pain influences different stages of reward processing. This study aimed to assess the physical pain’s impact on reward processing with event-related potential (ERP) method. In the present study, a flash sale game (reward-seeking task) was carried out, in which the participants were instructed to press a button as soon as possible to obtain the earphone (a reward) after experiencing either electric shock or not and finally evaluated the outcome of their response. High-temporal-resolution electroencephalogram data were simultaneously recorded to reveal the neural mechanism underlying the pain effect. The ERP analyses revealed that pain affected the feedback processing reflected by feedback-related negativity (FRN) and P300. Specifically, participants in the nopain situation exhibited greater FRN discrepancy between success and failure feedbacks relative to that in the pain situation. Moreover, the P300 amplitude was enhanced in the nopain condition compared to the pain condition regardless of the feedback valence. These results demonstrate that the pain reduced the sensitivity to the reward valence at the early stage and weakened the motivational salience at the late stage. Altogether, this study extends the understanding of the effect of pain on reward processing from the temporal perspective under a purchasing situation.

Appropriately Tuning Stochastic-Psychometric Properties of the Balloon Analog Risk Task

The Balloon Analog Risk Task (BART) allows to experimentally assess individuals’ risk-taking profiles in an ecologically sound setting. Many psychological and neuroscientific studies implemented the BART for its simplicity and intuitive nature. However, some issues in the design of the BART are systematically unconsidered in experimental paradigms, which may bias the estimation of individual risk-taking profiles. Since there are no methodological guidelines for implementing the BART, many variables (e.g., the maximum explosion probabilities, the rationale underlying stochastic events) vary inconstantly across experiments, possibly producing contrasting results. Moreover, the standard version of the BART is affected by the interaction of an individual-dependent, unavoidable source of stochasticity with a trial-dependent, more ambiguous source of stochasticity (i.e., the probability of the balloon to explode). This paper shows the most appropriate experimental choices for having the lowest error in the approximation of risk-taking profiles. Performance tests of a series of simulated data suggest that a more controlled, eventually non-stochastic version of the BART, better approximates original risk-taking profiles. Selecting optimal BART parameters is particularly important in neuroscience experiments to optimize the number of trials in a time window appropriate for acquiring neuroimaging data. We also provide helpful suggestions to researchers in many fields to allow the implementation of optimized risk-taking experiments using the BART.

A Bayesian method for measuring risk propensity in the Balloon Analogue Risk Task

The Balloon Analogue Risk Task (BART) is widely-used to measure risk propensity in theoretical, clinical, and applied research. In the task, people choose either to pump a balloon to increase its value at the risk of the balloon bursting and losing all value, or to bank the current value of the balloon. Risk propensity is most commonly measured as the average number of pumps on trials for which the balloon does not burst. Burst trials are excluded because they necessarily underestimate the number of pumps people intended to make. However, their exclusion discards relevant information about people's risk propensity. A better measure of risk propensity uses the statistical method of censoring to incorporate all of the trials. We develop a new Bayesian method, based on censoring, for measuring both risk propensity and behavioral consistency in the BART. Through applications to previous data we demonstrate how the method can be extended to consider the correlation of risk propensity with external measures, and to compare differences in risk propensity between groups. We provide implementations of all of these methods in R, MATLAB, and the GUI-based statistical software JASP.

The assessment of physical risk taking: Preliminary construct validation of a new behavioral measure

Risk taking is a complex heterogeneous construct that has proven difficult to assess, especially when using behavioral tasks. We present an exploratory investigation of new measure–the Assessment of Physical Risk Taking (APRT). APRT produces a variety of different outcome scores and is designed as a comprehensive assessment of the probability of success and failure, and magnitude of reward and punishment of different types of simulated physically risky behaviors. Effects observed on the simulated behaviors are hypothesized to reflect similar effects on real world physical risks. Participants (N = 224) completed APRT in a laboratory setting, half of whom had a 1.5 s delay interposed between button presses. Exploratory analyses utilizing generalized estimating equations examined the main effects and two-way interactions among five within-subject factors, as well as two-way interactions between the within-subject factors and Delay across four APRT outcome scores. Results indicated that Injury Magnitude and Injury Probability exerted stronger effects than any of the other independent variables. Participants also completed several self-report measures of risk taking and associated constructs (e.g., sensation seeking), which were correlated with APRT scores to assess the preliminary convergent and divergent validity of the new measure. After correcting for multiple comparisons, APRT scores correlated with self-reported risk taking in thrilling, physically dangerous activities specifically, but only for those who did not have a delay between APRT responses. This promising exploratory investigation highlights the need for future studies comparing APRT to other behavioral risk taking tasks, examining the robustness of the observed APRT effects, and investigating how APRT may predict real-world physical risk taking.

Event-related potentials in response to feedback following risk-taking in the hot version of the Columbia Card Task

Given the importance of risk-taking in individuals' personal and professional life, several behavioral tasks for measuring the construct have been developed. Recently, a new task was introduced, the Columbia Card Task (CCT). This task measures participants' risk levels and establishes how sensitive participants are to gains, losses, and probabilities when taking risk. So far, the CCT has been examined in behavioral studies and in combination with several (neuro)biological techniques. However, no electroencephalography (EEG) research has been done on the task. The present study fills this gap and helps to validate this relatively new experimental task. To this end, n = 126 students were asked to complete self-reports (reward responsiveness, impulsiveness, and sensation-seeking) and to perform the CCT (and other risk tasks) in an EEG setup. The results show that feedback appraisal after risky decision-making in the CCT was accompanied by a feedback-related negativity (FRN) and a P300, which were stronger in response to negative than positive feedback. Correlations between the FRN and P300 difference wave on the one hand and risk-related self-reports and behavior on the other were nonsignificant and small, but were mostly in the expected direction. This pattern did not change after excluding participants with psychiatric/neurological disorders and outliers. Excluding participants with reversed (positive > negative) difference waves strengthened FRN correlations. The impact such individuals can have on the data should be taken into account in future studies. Regarding the CCT in particular, future studies should also address its oddball structure and its masking of true values (censoring).