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.

Valuing life over the life cycle.

Adjusting the valuation of life along the (i) person-specific (age, health, wealth) and (ii) mortality risk-specific (beneficial or detrimental, temporary or permanent changes) dimensions is relevant in prioritizing healthcare interventions. These adjustments are provided by solving a life cycle model of consumption, leisure and health choices and the associated Hicksian variations for mortality changes. The calibrated model yields plausible Values of Life Year between 154K$ and 200K$ and Values of Statistical Life close to 6.0M$. The willingness to pay (WTP) and to accept (WTA) compensation are equal and symmetric for one-shot beneficial and detrimental changes in mortality risk. However, permanent, and expected longevity changes are both associated with larger willingness for gains, relative to losses, and larger WTA than WTP. Ageing lowers both variations via falling resources and health, lower marginal continuation utility of living and decreasing longevity returns of changes in mortality.

Exploring a formal approach to selecting studies for replication: A feasibility study in social neuroscience.

Replication of published results is crucial for ensuring the robustness and self-correction of research, yet replications are scarce in many fields. Replicating researchers will therefore often have to decide which of several relevant candidates to target for replication. Formal strategies for efficient study selection have been proposed, but none have been explored for practical feasibility - a prerequisite for validation. Here we move one step closer to efficient replication study selection by exploring the feasibility of a particular selection strategy that estimates replication value as a function of citation impact and sample size (Isager, van 't Veer, & Lakens, 2021). We tested our strategy on a sample of fMRI studies in social neuroscience. We first report our efforts to generate a representative candidate set of replication targets. We then explore the feasibility and reliability of estimating replication value for the targets in our set, resulting in a dataset of 1358 studies ranked on their value of prioritising them for replication. In addition, we carefully examine possible measures, test auxiliary assumptions, and identify boundary conditions of measuring value and uncertainty. We end our report by discussing how future validation studies might be designed. Our study demonstrates the importance of investigating how to implement study selection strategies in practice. Our sample and study design can be extended to explore the feasibility of other formal study selection strategies that have been proposed.

Rethinking the eidos, genos, and diaphora of the health utility concept: a psychological perspective.

The notion of utility gained a strong foothold in health economics over the last decades. However, the concept of health utility has not yet been decisively or irrefutably defined and the definitions that exist often do not take into account the current state of psychological literature. This perspective paper shows that the current definition of health utility emphasizes decision-making processes, deploys personal preferences, assumes psychological egoism, and attempts to objectively and cardinally measure utility. However, these foundational axioms that underly the current definition of health utility are not necessarily in concurrence with the current state of psychological literature. Due to these perceived shortcomings of the current health utility definition, it may be beneficial to redefine the concept of health utility in accordance with the current state of psychological literature. In order to develop such a revised definition of health utility the commonly deployed formula (Eidos = Genos + Diaphora) originating from Aristotle's metaphysics is applied. The revised definition of health utility proposed in this perspective paper alludes to health utility as 'the subjective value, expressed in terms of perceived pain or pleasure, that is attributed to the cognitive, affective and conative experience of one's own physical, mental and social health state, which is determined through self-reflection and interaction with significant others'. Although this revised definition does neither replace nor supersede other conceptualizations of health utility, it may serve as a refreshing avenue for further discussion and could, eventually, support policymakers and health economists in operationalizing and measuring health utility in an even more accurate and veracious manner.

Does Amount of Information Support Aesthetic Values?

Obtaining information from the world is important for survival. The brain, therefore, has special mechanisms to extract as much information as possible from sensory stimuli. Hence, given its importance, the amount of available information may underlie aesthetic values. Such information-based aesthetic values would be significant because they would compete with others to drive decision-making. In this article, we ask, "What is the evidence that amount of information support aesthetic values?" An important concept in the measurement of informational volume is entropy. Research on aesthetic values has thus used Shannon entropy to evaluate the contribution of quantity of information. We review here the concepts of information and aesthetic values, and research on the visual and auditory systems to probe whether the brain uses entropy or other relevant measures, specially, Fisher information, in aesthetic decisions. We conclude that information measures contribute to these decisions in two ways: first, the absolute quantity of information can modulate aesthetic preferences for certain sensory patterns. However, the preference for volume of information is highly individualized, with information-measures competing with organizing principles, such as rhythm and symmetry. In addition, people tend to be resistant to too much entropy, but not necessarily, high amounts of Fisher information. We show that this resistance may stem in part from the distribution of amount of information in natural sensory stimuli. Second, the measurement of entropic-like quantities over time reveal that they can modulate aesthetic decisions by varying degrees of surprise given temporally integrated expectations. We propose that amount of information underpins complex aesthetic values, possibly informing the brain on the allocation of resources or the situational appropriateness of some cognitive models.

Mixed models for optimal saving with labor income risk and interest-rate risk.

In this paper, optimal saving models with two risk components are studied: the labor income risk and the interest rate risk. These risks can be modeled probabilistically by random variables or possibilistically by fuzzy numbers. In mixed models, one of the components is probabilistic and the other one is possibilistic. After the construction of two mixed models of optimal saving, several notions of precautionary saving are defined. These measure the variation in optimal saving level when moving from one model to another (usually by adding a risk component). The main results of the paper establish necessary and sufficient conditions on the positivity of different precautionary savings. (This means that the presence of new risks generates extra-saving.).

Behavioral Theories That Have Influenced the Way Health State Preferences Are Elicited and Interpreted: A Bibliometric Mapping Analysis of the Time Trade-Off Method With VOSviewer Visualization.

Aim: The aim of this paper is to develop an understanding of how behavioral theories have influenced the way preferences for health-related quality of life are elicited and interpreted. We focus on the Time Trade-off (TTO) method given it represents the quality-adjusted life-year (QALY) concept-that survival in less-than-full health can be deemed equivalent to a shorter survival in full health. To our knowledge this is the first review using a combination of systematic scoping review, bibliometrics and VOSviewer visualization to map the development of ideas in health economics. Methods: A priori, we selected three behavioral theories to explore within our review, referred to here as Expected Utility Theory, Non-Expected Utility Theory and Probabilistic Choice Theory. A fourth topic, Order Effects, is defined broadly to encompass behavioral theories around timing/sequence of events. For the main search, Scopus was used to identify literature that had (a) elicited TTO values and/or (b) contributed to the way TTO values were elicited and interpreted, from inception to July 2021. Papers that focused on the latter category were given the label "behavioral" and underwent additional analyses. A two stage-screening was applied to assess eligibility. Co-citation, co-authorship and co-occurrence of keywords was used to chart the development of TTO over time. Results: A total of 1,727 records were retrieved from Scopus and were supplemented by an additional 188 papers. There were 856 applied and 280 behavioral papers included in the final corpus, with the behavioral set split equally into four sets of 70 papers to chart the development of keywords over time: (1) 1972-1999; (2) 2000-2010, (3) 2010-2015 and (4) 2015-2021. Discussion: The keyword analysis suggested that whilst some ideas transition quickly from economic theory to the TTO literature, such as the impact of Order Effects, others take longer to be assimilated, for example Non-Expected Utility models or failure of constant discounting. It is therefore important that researchers within health economics work more closely with those in mainstream economics and keep abreast of the wider economics and behavioral sciences to expedite the uptake of new and relevant ideas.

A Risk and Decision Analysis Framework to Evaluate Future PM2.5 Risk: A Case Study in Los Angeles-Long Beach Metro Area.

This study examines the L.A.-Long Beach Metro area concerning the future risk of the PM2.5 concentration increase. Population expansion, economic growth, and temperature increase are incorporated to estimate the probability of the magnitude of PM2.5 emission increase. Three possible sectors for the reduction of PM2.5 emissions are considered: ocean-going vessels, refineries, and electricity-generating units. The decision of how best to allocate emissions-reduction efforts among these three sectors is analyzed using a quantitative and qualitative decision-analysis framework. For quantitative analysis, Expected Monetary Value (EMV) and Expected Utility (EU) methods are used to select the optimal sector to invest in. Based on the EMV calculation, the refineries sector is 3.5 times and 6.4 times more worthy of investment compared to the electricity-generating units and the ocean-going vessels sector, respectively. For the qualitative analysis, three criteria (investment efficiency, implementation difficulty, time to become effective) are considered in the decision-making process and sensitivity analysis is conducted to inform the ocean-going vessel sector is the optimal alternative for all possible scenarios. The refineries sector is more preferred than the electricity-generating units sector when the implementation difficulty's weight is smaller than 50%. This study provides a valuable risk and decision analysis framework for analyzing the air pollution problem associated with the future PM2.5 concentration increase caused by three risk factors: population growth, economic growth, and climate change.

When Should You Trust Your Doctor? Establishing a Theoretical Model to Evaluate the Value of Second Opinion Visits.

In order to produce a mathematical model for better understanding of the benefits and utilization of second opinions and to understand the contradiction between the value of second opinions and their perceived underuse, we developed an expected utility theory model to quantify their value. We use a case-based example to find types of biases that could affect second opinions. Although the baseline expected utility theory model presented assumes providers are rational, we relax this and discuss the implications for how these alternative specifications alter predicted use. We found that second opinions are valuable when diagnostic accuracy is variable across physicians or access to high-quality care is restricted. In a stylized simulation example in which about half (50.1%) of diagnoses were incorrect, receipt of 1 second opinion reduced the error rate to 25.8% and receipt of 2 second opinions reduced the error rate to 16.0%. After incorporating potential biases into the model, the value of second opinions increases only when aversion to changing the initial diagnosis is greater than aversion to correcting a mistake. Additionally, this model reveals that second opinions have value even when diagnostic accuracy is perfect. Further, when financial incentives differ from the incentives of the initial consult, a second opinion offers patients a reasonable bound of their treatment options. To conclude, we identify numerous reasons for underuse of second opinions. Specifically, value depends on the degree of diagnostic uncertainty, presence of behavioral biases, and variation in local compensation regimes. Despite their value, recent trends could actually decrease the value of second opinions.

Performance of Portfolios Based on the Expected Utility-Entropy Fund Rating Approach.

Yang and Qiu proposed and reframed an expected utility-entropy (EU-E) based decision model. Later on, a similar numerical representation for a risky choice was axiomatically developed by Luce et al. under the condition of segregation. Recently, we established a fund rating approach based on the EU-E decision model and Morningstar ratings. In this paper, we apply the approach to US mutual funds and construct portfolios using the best rating funds. Furthermore, we evaluate the performance of the fund ratings based on the EU-E decision model against Morningstar ratings by examining the performance of the three models in portfolio selection. The conclusions show that portfolios constructed using the ratings based on the EU-E models with moderate tradeoff coefficients perform better than those constructed using Morningstar. The conclusion is robust to different rebalancing intervals.

Nonhuman Primates Satisfy Utility Maximization in Compliance with the Continuity Axiom of Expected Utility Theory.

Expected Utility Theory (EUT), the first axiomatic theory of risky choice, describes choices as a utility maximization process: decision makers assign a subjective value (utility) to each choice option and choose the one with the highest utility. The continuity axiom, central to Expected Utility Theory and its modifications, is a necessary and sufficient condition for the definition of numerical utilities. The axiom requires decision makers to be indifferent between a gamble and a specific probabilistic combination of a more preferred and a less preferred gamble. While previous studies demonstrated that monkeys choose according to combinations of objective reward magnitude and probability, a concept-driven experimental approach for assessing the axiomatically defined conditions for maximizing utility by animals is missing. We experimentally tested the continuity axiom for a broad class of gamble types in 4 male rhesus macaque monkeys, showing that their choice behavior complied with the existence of a numerical utility measure as defined by the economic theory. We used the numerical quantity specified in the continuity axiom to characterize subjective preferences in a magnitude-probability space. This mapping highlighted a trade-off relation between reward magnitudes and probabilities, compatible with the existence of a utility function underlying subjective value computation. These results support the existence of a numerical utility function able to describe choices, allowing for the investigation of the neuronal substrates responsible for coding such rigorously defined quantity.SIGNIFICANCE STATEMENT A common assumption of several economic choice theories is that decisions result from the comparison of subjectively assigned values (utilities). This study demonstrated the compliance of monkey behavior with the continuity axiom of Expected Utility Theory, implying a subjective magnitude-probability trade-off relation, which supports the existence of numerical utility directly linked to the theoretical economic framework. We determined a numerical utility measure able to describe choices, which can serve as a correlate for the neuronal activity in the quest for brain structures and mechanisms guiding decisions.

To Decompress or Not? An Expected Utility Inspired Approach To Shared decision-making For Supratentorial Ischemic Stroke.

Patients with large territorial supratentorial infarctions are at high risk of cerebral edema, increased intracranial pressure, tissue herniation and death. There is strong evidence supporting prompt decompressive craniectomy after large hemispheric ischemic stroke as a means to reduce mortality. Nevertheless, functional outcomes can vary significantly. Clinical trials have traditionally judged these outcomes by a priori dichotomization without taking into account individual patient and caregiver preferences. If these are not incorporated into shared decision-making, there are significant risks in both directions, i.e. producing outcomes that may be judged as unacceptable to survivors, or not offering life-saving treatments to patients that according to their own values could be beneficial. In the absence of decision aids, we explore insights from decision theory and propose an expected utility-inspired approach as a supplementary navigating tool in the decision-making process. Four patient case scenarios are discussed as a demonstration of using individualized rankings of outcome preferences, and deriving expected utilities for interventions such as decompressive craniectomy versus medical therapy. The ultimate aim of the suggested approach is to assure that patient values are elicited and incorporated, and possible range and nature of outcomes are discussed, and by attempting to connect best available means to patient individualized ends.

Convergence of optimal expected utility for a sequence of binomial models.

We consider the convergence of the solution of a discrete-time utility maximization problem for a sequence of binomial models to the Black-Scholes-Merton model for general utility functions. In previous work by D. Kreps and the second named author a counter-example for positively skewed non-symmetric binomial models has been constructed, while the symmetric case was left as an open problem. In the present article we show that convergence holds for the symmetric case and for negatively skewed binomial models. The proof depends on some rather fine estimates of the tail behaviors of binomial random variables. We also review some general results on the convergence of discrete models to Black-Scholes-Merton as developed in a recent monograph by D. Kreps.

Corrigendum: Social Influence in Adolescent Decision-Making: A Formal Framework.

[This corrects the article DOI: 10.3389/fpsyg.2019.01915.].

Irrational Responses to Risk Preference Questionnaires by Patients with Diabetes with or without Retinopathy and Comparison with Those without Diabetes.

PURPOSE: The risk preferences of patients with diabetes have profound effects on the progression of complications. The present study aimed to clarify whether the preferences of patients with diabetes and retinopathy are deliberately risk-seeking or irrational and whether this propensity is specific to those with retinopathy or is also found in patients without retinopathy compared with those without diabetes. PATIENTS AND METHODS: A total of 394 patients with diabetes (264 without retinopathy and 130 with retinopathy) and 198 patients without diabetes agreed to participate in this survey. The questions were modified versions of those from the Japan Household Survey on Consumer Preferences and Satisfaction, which sought to determine the participants' personal socioeconomic status and risk preferences. In the questionnaires, responses were analyzed by determining the participants' willingness to pay for a lottery ticket and for an insurance policy. Irrational responses were defined as violations of two axioms of the Expected Utility Theory: completeness and transitivity. RESULTS: The incidence of irrational responses increased with age and was associated with educational level. The incidence of irrational responses was significantly higher in patients with retinopathy than in those without retinopathy after adjusting for age and educational level. There was no significant difference in the incidence of irrational responses between patients with diabetes but without retinopathy and those without diabetes. CONCLUSION: The risk-seeking behavior of patients with diabetes and retinopathy was not deliberate but was irrational under uncertainty. Medical professionals should be aware of their patients' propensity to make irrational decisions, which is an important risk factor for the progression of retinopathy in patients with diabetes regardless of age and educational level.

COVID-19, the Swedish 'Experiment', and Me.

In this personal vision paper the Swedish approach to COVID-19 prompts an exploration of how and why assuming individual rationality coupled with minimal social restriction may be as good a solution as any and better than most. A COVID sub-model is developed and populated with probabilities for four outcomes of infecting another person (asymptomatic, sick, hospitalized, dead), conditional on three observable characteristics (sex, age, and BMI), and (dis)utilities for three categories of person (nearest/dearest, friends/colleagues and unknown others) experiencing those outcomes. The implications for a liberal democracy are drawn, based on the assumptions that individual citizens will and should maximise their informed expected utility, exhibiting 'commons sense' as well as common sense.

Convergence of optimal expected utility for a sequence of discrete-time markets.

We examine Kreps' conjecture that optimal expected utility in the classic Black-Scholes-Merton (BSM) economy is the limit of optimal expected utility for a sequence of discrete-time economies that "approach" the BSM economy in a natural sense: The nth discrete-time economy is generated by a scaled n-step random walk, based on an unscaled random variable ζ with mean 0, variance 1, and bounded support. We confirm Kreps' conjecture if the consumer's utility function U has asymptotic elasticity strictly less than one, and we provide a counterexample to the conjecture for a utility function U with asymptotic elasticity equal to 1, for ζ such that E [ ζ 3 ] > 0 .

Deciding Under Uncertainty: The Case of Refractory Intracranial Hypertension.

A challenging clinical conundrum arises in severe traumatic brain injury patients who develop intractable intracranial hypertension. For these patients, high morbidity interventions such as surgical decompression and barbiturate coma have to be considered against a backdrop of uncertain outcomes including prolonged states of disordered consciousness and severe disability. The clinical evidence available to guide shared decision-making is mainly limited to one randomized controlled trial, the RESCUEicp. However, since the publication of this trial significant controversy has been ongoing over the interpretation of the results. Is the mortality benefit from surgery merely a trade off for unacceptable long-term disability? How should treatment options, possible outcomes, and results from the trial be communicated to surrogates? How do we incorporate patient values into forming plans of care? The aim of this article is to sketch an approach based on insights from Decision Theory, and specifically deciding under uncertainty. The mainstream normative decision theory, Expected Utility (EU) theory, essentially says that, in situations of uncertainty, one should prefer the option with greatest expected desirability or value. The steps required to compute expected utilities include listing the possible outcomes of available interventions, assigning each outcome a utility ranking representing an individual patient's preferences, and a conditional probability given each intervention. This is a conceptual framework meant to supplement, and enhance shared decision making by assuring that patient values are elicited and incorporated, the possible range and nature of outcomes is discussed, and finally by attempting to connect best available means to patient-individualized ends.

Dynamic utility: the sixth reciprocity mechanism for the evolution of cooperation.

Game theory has been extensively applied to elucidate the evolutionary mechanism of cooperative behaviour. Dilemmas in game theory are important elements that disturb the promotion of cooperation. An important question is how to escape from dilemmas. Recently, a dynamic utility function (DUF) that considers an individual's current status (wealth) and that can be applied to game theory was developed. The DUF is different from the famous five reciprocity mechanisms called Nowak's five rules. Under the DUF, cooperation is promoted by poor players in the chicken game, with no changes in the prisoner's dilemma and stag-hunt games. In this paper, by comparing the strengths of the two dilemmas, we show that the DUF is a novel reciprocity mechanism (sixth rule) that differs from Nowak's five rules. We also show the difference in dilemma relaxation between dynamic game theory and (traditional) static game theory when the DUF and one of the five rules are combined. Our results indicate that poor players unequivocally promote cooperation in any dynamic game. Unlike conventional rules that have to be brought into game settings, this sixth rule is universally (canonical form) applicable to any game because all repeated/evolutionary games are dynamic in principle.

Bayesian networks for supply chain risk, resilience and ripple effect analysis: A literature review.

In the broad sense, the Bayesian networks (BN) are probabilistic graphical models that possess unique methodical features to model dependencies in complex networks, such as forward and backward propagation (inference) of disruptions. BNs have transitioned from an emerging topic to a growing research area in supply chain (SC) resilience and risk analysis. As a result, there is an acute need to review existing literature to ascertain recent developments and uncover future areas of research. Despite the increasing number of publications on BNs in the domain of SC uncertainty, an extensive review on their application to SC risk and resilience is lacking. To address this gap, we analyzed research articles published in peer-reviewed academic journals from 2007 to 2019 using network analysis, visualization-based scientometric analysis, and clustering analysis. Through this study, we contribute to literature by discussing the challenges of current research, and, more importantly, identifying and proposing future research directions. The results of our survey show that further debate on the theory and application of BNs to SC resilience and risk management is a significant area of interest for both academics and practitioners. The applications of BNs, and their conjunction with machine learning algorithms to solve big data SC problems relating to uncertainty and risk, are also discussed.