Decision making under risk is central to human behavior. Economic decision theory suggests that value, risk, and risk aversion influence choice behavior. Although previous studies identified neural correlates of decision parameters, the contribution of these correlates to actual choices is unknown. In two different experiments, participants chose between risky and safe options. We identified discrete blood oxygen level-dependent (BOLD) correlates of value and risk in the ventral striatum and anterior cingulate, respectively. Notably, increasing inferior frontal gyrus activity to low risk and safe options correlated with higher risk aversion. Importantly, the combination of these BOLD responses effectively decoded the behavioral choice. Striatal value and cingulate risk responses increased the probability of a risky choice, whereas inferior frontal gyrus responses showed the inverse relationship. These findings suggest that the BOLD correlates of decision factors are appropriate for an ideal observer to detect behavioral choices. More generally, these biological data contribute to the validity of the theoretical decision parameters for actual decisions under risk.

When making choices under uncertainty, people usually consider both the expected value and risk of each option, and choose the one with the higher utility. Expected value increases the expected utility of an option for all individuals. Risk increases the utility of an option for risk-seeking individuals, but decreases it for risk averse individuals. In 2 separate experiments, one involving imperative (no-choice), the other choice situations, we investigated how predicted risk and expected value aggregate into a common reward signal in the human brain. Blood oxygen level dependent responses in lateral regions of the prefrontal cortex increased monotonically with increasing reward value in the absence of risk in both experiments. Risk enhanced these responses in risk-seeking participants, but reduced them in risk-averse participants. The aggregate value and risk responses in lateral prefrontal cortex contrasted with pure value signals independent of risk in the striatum. These results demonstrate an aggregate risk and value signal in the prefrontal cortex that would be compatible with basic assumptions underlying the mean-variance approach to utility. decision making ͉ fMRI ͉ utility ͉ mean-variance approach ͉ neuroeconomics

Individuals’ risk attitudes are known to guide choices about uncertain options. However, in the presence of others’ decisions, these choices can be swayed and manifest as riskier or safer behavior than one would express alone. To test the mechanisms underlying effective social ‘nudges’ in human decision-making, we used functional neuroimaging and a task in which participants made choices about gambles alone and after observing others’ selections. Against three alternative explanations, we found that observing others’ choices of gambles increased the subjective value (utility) of those gambles for the observer. This ‘other-conferred utility’ was encoded in ventromedial prefrontal cortex, and these neural signals predicted conformity. We further identified a parametric interaction with individual risk preferences in anterior cingulate cortex and insula. These data provide a neuromechanistic account of how information from others is integrated with individual preferences that may explain preference-congruent susceptibility to social signals of safety and risk.

In this article, we introduce the method of measuring skin conductance responses (SCR) reflecting peripheral (bodily) signals associated with emotions, decisions, and eventually behavior. While measuring SCR is a well-established, robust, widely used, and relatively inexpensive method, it has been rarely utilized in organizational research. We introduce the basic aspects of SCR methodology and explain the behavioral significance of the signal, especially in connection with the emotional experience. Importantly, we describe in detail a specific research protocol (fear conditioning) that serves as an illustrative example to support the initial steps for organizational scholars who are new to the method. We also provide the related scripts for stimulus presentation and basic data analysis, as well as an instructional video, with the aim to facilitate the dissemination of SCR methodology to organizational research. We conclude by suggesting potential future research questions that can be addressed using SCR measurements.

Reward probability crucially determines the value of outcomes. A basic phenomenon, defying explanation by traditional decision theories, is that people often overweigh small and underweigh large probabilities in choices under uncertainty. However, the neuronal basis of such reward probability distortions and their position in the decision process are largely unknown. We assessed individual probability distortions with behavioral pleasantness ratings and brain imaging in the absence of choice. Dorsolateral frontal cortex regions showed experience dependent overweighting of small, and underweighting of large, probabilities whereas ventral frontal regions showed the opposite pattern. These results demonstrate distorted neuronal coding of reward probabilities in the absence of choice, stress the importance of experience with probabilistic outcomes and contrast with linear probability coding in the striatum. Input of the distorted probability estimations to decision-making mechanisms are likely to contribute to well known inconsistencies in preferences formalized in theories of behavioral economics.

Humans possess evolved mechanisms to detect and reject contamination by potentially harmful foreign substances. These mechanisms may also function in the rejection of violations in the social order. Here, we propose that the disgust evaluation system may also be sensitive to culture mixing, especially when elements of own and foreign cultures occupy the same space at the same time (culture fusion). Across four studies, we observe support for this prediction. Paralleling disgust ratings for contaminants mixing with pure objects associated with the self (Study 1A), representations of blending and fusion between elements of own and foreign cultures were rated as more disgusting than simultaneous presentation of the same cultural elements without fusion (Studies 1B and 2). Disgust toward culture fusion was observed over and above incongruity associated with mixing two in-group cultural representations (Study 4). Moreover, selective disgust toward in-group–out-group culture fusion was especially pronounced among those endorsing higher levels of patriotism (Studies 1B, 2, and 4), but not when culture fusion involved two foreign representations (Study 3). These findings support the notion that the architecture for pathogenic- and food-based disgust may have been extended to reject external threats to the fidelity of in-group identity markers by out-group influences.

BackgroundOur aims were to evaluate critically the evidence from systematic reviews as well as narrative reviews of the effects of melatonin (MLT) on health and to identify the potential mechanisms of action involved.MethodsAn umbrella review of the evidence across systematic reviews and narrative reviews of endogenous and exogenous (supplementation) MLT was undertaken. The Oxman checklist for assessing the methodological quality of the included systematic reviews was utilised. The following databases were searched: MEDLINE, EMBASE, Web of Science, CENTRAL, PsycINFO and CINAHL. In addition, reference lists were screened. We included reviews of the effects of MLT on any type of health-related outcome measure.ResultsAltogether, 195 reviews met the inclusion criteria. Most were of low methodological quality (mean -4.5, standard deviation 6.7). Of those, 164 did not pool the data and were synthesised narratively (qualitatively) whereas the remaining 31 used meta-analytic techniques and were synthesised quantitatively. Seven meta-analyses were significant with P values less than 0.001 under the random-effects model. These pertained to sleep latency, pre-operative anxiety, prevention of agitation and risk of breast cancer.ConclusionsThere is an abundance of reviews evaluating the effects of exogenous and endogenous MLT on health. In general, MLT has been shown to be associated with a wide variety of health outcomes in clinically and methodologically heterogeneous populations. Many reviews stressed the need for more high-quality randomised clinical trials to reduce the existing uncertainties.Electronic supplementary materialThe online version of this article (10.1186/s12916-017-1000-8) contains supplementary material, which is available to authorized users.

Background Depression is a prevalent mental disorder that is undiagnosed and untreated in half of all cases. Wearable activity trackers collect fine-grained sensor data characterizing the behavior and physiology of users (ie, digital biomarkers), which could be used for timely, unobtrusive, and scalable depression screening. Objective The aim of this study was to examine the predictive ability of digital biomarkers, based on sensor data from consumer-grade wearables, to detect risk of depression in a working population. Methods This was a cross-sectional study of 290 healthy working adults. Participants wore Fitbit Charge 2 devices for 14 consecutive days and completed a health survey, including screening for depressive symptoms using the 9-item Patient Health Questionnaire (PHQ-9), at baseline and 2 weeks later. We extracted a range of known and novel digital biomarkers characterizing physical activity, sleep patterns, and circadian rhythms from wearables using steps, heart rate, energy expenditure, and sleep data. Associations between severity of depressive symptoms and digital biomarkers were examined with Spearman correlation and multiple regression analyses adjusted for potential confounders, including sociodemographic characteristics, alcohol consumption, smoking, self-rated health, subjective sleep characteristics, and loneliness. Supervised machine learning with statistically selected digital biomarkers was used to predict risk of depression (ie, symptom severity and screening status). We used varying cutoff scores from an acceptable PHQ-9 score range to define the depression group and different subsamples for classification, while the set of statistically selected digital biomarkers remained the same. For the performance evaluation, we used k-fold cross-validation and obtained accuracy measures from the holdout folds. Results A total of 267 participants were included in the analysis. The mean age of the participants was 33 (SD 8.6, range 21-64) years. Out of 267 participants, there was a mild female bias displayed (n=170, 63.7%). The majority of the participants were Chinese (n=211, 79.0%), single (n=163, 61.0%), and had a university degree (n=238, 89.1%). We found that a greater severity of depressive symptoms was robustly associated with greater variation of nighttime heart rate between 2 AM and 4 AM and between 4 AM and 6 AM; it was also associated with lower regularity of weekday circadian rhythms based on steps and estimated with nonparametric measures of interdaily stability and autocorrelation as well as fewer steps-based daily peaks. Despite several reliable associations, our evidence showed limited ability of digital biomarkers to detect depression in the whole sample of working adults. However, in balanced and contrasted subsamples comprised of depressed and healthy participants with no risk of depression (ie, no or minimal depressive symptoms), the model achieved an accuracy of 80%, a sensitivity of 82%, and a specificity of 78% in detecting subjects at high risk of depression. Conclusions Digital biomarkers that have been discovered and are based on behavioral and physiological data from consumer wearables could detect increased risk of depression and have the potential to assist in depression screening, yet current evidence shows limited predictive ability. Machine learning models combining these digital biomarkers could discriminate between individuals with a high risk of depression and individuals with no risk.