Search

Cooperation is fundamental for survival and a functioning society. With substantial individual variability in cooperativeness, we must learn whom to cooperate with, and often make these decisions on behalf of others. Understanding how people learn about the cooperativeness of others, and the neurocomputational mechanisms supporting this learning, is therefore essential. During functional magnetic resonance imaging scanning, participants completed a novel cooperation-partner-choice task where they learned to choose between cooperative and uncooperative partners through trial-and-error both for themselves and vicariously for another person. Interestingly, when choosing for themselves, participants made faster and more exploitative choices than when choosing for another person. Activity in the ventral striatum preferentially responded to prediction errors (PEs) during self-learning, whereas activity in the perigenual anterior cingulate cortex (ACC) signaled both personal and vicarious PEs. Multivariate pattern analyses showed distinct coding of personal and vicarious choice-making and outcome processing in the temporoparietal junction (TPJ), dorsal ACC, and striatum. Moreover, in right TPJ the activity pattern that differentiated self and other outcomes was associated with individual differences in exploitation tendency. We reveal neurocomputational mechanisms supporting cooperative learning and show that this learning is reflected in trial-by-trial univariate signals and multivariate patterns that can distinguish personal and vicarious choices.

In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data.

Existing research presents a working understanding of Borderline Personality Disorder (BPD) patients’ symptomatology, traits, and behavior in everyday life, but how they combine and utilize prior and likelihood (current sensory) information when making decisions remains unclear. Bayesian Decision Theory suggests that optimal decision-making behavior should combine and weigh both pieces of information according to their relative uncertainties, such that people rely more on the information with less uncertainty when making a decision. Though this optimal behavior has been observed in neuro-typical populations, prior literature suggests that certain neuro-atypical populations can deviate. Some characteristics of BPD patients, such as impulsive behavior and drastic changes in the overall perception of themselves and others, suggest that they may be over-relying on likelihood information and not sufficiently taking prior information into account. From a Bayesian perspective, this can be interpreted as having ‘weak’ priors which may lead to suboptimal decision-making. Here, we investigated this hypothesis by having BPD patients (n = 23) and healthy controls (n = 18) perform a coin-catching sensorimotor task with varying levels of prior and likelihood information uncertainty. Our results indicate that, contrary to our prediction, BPD patients were able to use prior information, and that their use of prior and likelihood information follows qualitatively Bayesian behavior. We found that BPD patients, at least in a lower-level and non-affective sensorimotor task, are still able to use both prior and likelihood information and react appropriately to the respective uncertainties. This could be suggesting that any potential deficits in the use of prior information may not be widespread or only be apparent in affectively-charged interpersonal contexts.

Correction to: Nature Human Behaviour https://doi.org/10.1038/s41562-021-01173-x, published online 2 August 2021.In the version of this article initially published, the following authors were omitted from the author list and the Author contributionssection for “investigation” and “writing and editing”: Nandor Hajdu (Institute of Psychology, ELTE Eötvös Loránd University, Budapest,Hungary), Jordane Boudesseul (Facultad de Psicología, Instituto de Investigación Científica, Universidad de Lima, Lima, Perú), RafałMuda (Faculty of Economics, Maria Curie-Sklodowska University, Lublin, Poland) and Sandersan Onie (Black Dog Institute, UNSWSydney, Sydney, Australia & Emotional Health for All Foundation, Jakarta, Indonesia). In addition, Saeideh FatahModares’ name wasoriginally misspelled as Saiedeh FatahModarres in the author list. Further, affiliations have been corrected for Maria Terskova (NationalResearch University Higher School of Economics, Moscow, Russia), Susana Ruiz Fernandez (FOM University of Applied Sciences,Essen; Leibniz-Institut fur Wissensmedien, Tubingen, and LEAD Research Network, Eberhard Karls University, Tubingen, Germany),Hendrik Godbersen (FOM University of Applied Sciences, Essen, Germany), Gulnaz Anjum (Department of Psychology, Simon FraserUniversity, Burnaby, Canada, and Department of Economics & Social Sciences, Institute of Business Administration, Karachi, Pakistan).

A general consensus persists that sensory-perceptual differences in autism, such as hypersensitivities to light or sound, result from an overreliance on new (rather than prior) sensory observations. However, conflicting Bayesian accounts of autism remain unresolved as to whether such alterations are caused by more precise sensory observations (precise likelihood model) or by forming a less precise model of the sensory context (hypo-priors model). We used a decision-under-uncertainty paradigm that manipulated uncertainty in both likelihoods and priors. Contrary to model predictions we found no differences in reliance on likelihood in autistic group (AS) compared to neurotypicals (NT) and found no differences in subjective prior variance between groups. However, we found reduced context adjustment in the AS group compared to NT. Further, the AS group showed heightened variability in their relative weighting of sensory information (vs. prior) on a trial-by-trial basis. When participants were aligned on a continuum of autistic traits, we found no associations with likelihood reliance or prior variance but found an increased likelihood precision with autistic traits. These findings together provide empirical evidence for intact priors, precise likelihood, reduced context updating and heightened variability during sensory learning in autism.

Background: Impulsivity as a multidimensional construct is commonly linked with a wide range of mental health disorders, such as Bipolar Disorder (BD) and Borderline Personality Disorder (BorPD). Previous research suggests that individuals with BD and BorPD are more likely to be associated with lower academic achievement. This experiment aims to investigate the interrelation between BD or BorPD traits, impulsivity, and poor academic performance (GPA). Method: Our pre-registered study tested bipolar and borderline personality traits from a sample of 125 college students. Two behavioral tasks (Two-choice impulsivity paradigm; Go/no-go) and a self-report questionnaire (Barratt Impulsiveness Scale, BIS-11) were used to measure impulsivity. Students’ Grade Point Averages (GPAs) were also collected. Results: Both bipolar and borderline personality traits were positively correlated with the self-report impulsivity questionnaire (BIS-11) but not with the behavioral tasks. Students’ GPA were not significantly correlated with BD, BorPD traits, and impulsivity measures (behavioral and self-report). The self-report impulsivity questionnaire (BIS-11) was only significantly correlated with the Go/no-go task performance, but not the two-choice impulsivity paradigm. Limitations: This study is a correlational study in which participants have pre-existing conditions, therefore we cannot get a causal relationship. Besides, due to the normative sample, the study can only look at traits instead of diagnosis. Conclusions: Results from this study suggest that students with bipolar and/or borderline personality traits tend to have higher self-report impulsivity, without a noticeable impact on their GPA. Our results also support the growing consensus that impulsivity describes a diverse set of processes and traits.

BackgroundFunctional connectivity measures have garnered interest as possible biomarkers of psychiatric disorders including borderline personality disorder (BPD). However, small sample sizes and lack of within-study replications have led to divergent findings with no clear spatial foci. Therefore, we adopted an exploratory full-brain approach in the current study to evaluate which combinations of regions are most consistently predictive of BPD diagnosis.MethodsWe studied fMRI resting state functional connectivity in matched subsamples of 116 BPD and 72 control individuals defined by three grouping strategies: 1) referral diagnosis, 2) clinical diagnostic interview excluding patients no longer filling diagnostic criteria or controls scoring above threshold in a screening questionnaire and 3) self-reported symptom severity. We predicted BPD status using classifiers with repeated cross-validation based on multiscale functional connectivity within and between regions of interest (ROIs) covering the whole brain— global ROI-based network, seed-based ROI-connectivity, functional consistency and voxel-to-voxel connectivity within and between ROIs. Finally, we evaluated the generalizability of the classification in the left-out portion of non-matched data.ResultsFull-brain connectivity allowed successful classification (~70%) of BPD patients vs. control individuals in matched inner cross-validation. The classification remained significant when applied to unmatched out-of-sample data, but accuracies were lower (~61–70%) than in fully matched samples. The over-estimation of inner cross-validation accuracy was exacerbated by univariate regression of nuisance variables, particularly in smaller samples. Highest seed-based accuracies were in a similar range to global accuracies (~70–75%), but spatially more specific. In the seed-based classification, the regions implicated most often included midline, temporal and somatomotor regions. Highest accuracies were achieved with the clinical interview followed by referral diagnosis group definition. Self-report results remained at chance level. The accuracies were affected by an interaction of medications and global signal and univariate nuisance regression. Pairwise correlations, local consistencies and fine-scale connectivity matrices were not significantly predictive of BPD after multiple comparison corrections, but weak local effects coincided with the most discriminative ROIs in the classification. ConclusionsOur multivariate results indicate that complex global functional connectivity differences are moderately predictive of BPD despite heterogeneity of the patient population. However, univariate nuisance regression applied to full cross-validation dataset can cause inflation of accuracies compared with left-out test data.

This study modeled spite sensitivity (the worry that others are willing to incur a loss to hurt you), which is thought to undergird suspiciousness and persecutory ideation. Two samples performed a parametric, non-iterative trust game known as the Minnesota Trust Game (MTG). The MTG is designed to distinguish suspicious decision-making from otherwise rational mistrust by incentivizing the player to trust in certain situations. Individuals who do not trust even under these circumstances are particularly suspicious of their potential partner’s intentions. In Sample 1, 243 undergraduates who completed the MTG showed less trust as the amount of money they could lose increased. However, for choices where partners had a financial disincentive to betray the player, variation in the willingness to trust the partner was associated with suspicious beliefs. To further examine spite sensitivity, we modified the Fehr-Schmidt (1999) inequity aversion model, which compares unequal outcomes in social decision-making tasks, to include the possibility for spite sensitivity. In this case, an anticipated partner’s dislike of advantageous inequity (i.e., guilt) parameter could take on negative values, with negative guilt indicating spite. We hypothesized that the anticipated guilt parameter would be strongly related to suspicious beliefs. Our modification of the Fehr-Schmidt model improved estimation of MTG behavior. We isolated the estimation of partner’s spite-guilt, which was highly correlated with choices most associated with persecutory ideation. We replicated our findings in a second sample, where the estimated spite-guilt parameter correlated with self-reported suspiciousness. The “Suspiciousness” condition, unique to the MTG, can be modeled to isolate spite sensitivity, suggesting that spite sensitivity is separate from inequity aversion or risk aversion, and may provide a means to quantify persecution. The MTG offers promise for future studies to quantify persecutory beliefs in clinical populations.

Emotions play an important role in everyday decision-making, but emotional awareness can vary greatly between people. Alexithymia, a trait characterized by little or no awareness of one’s emotions, is broadly associated with poor mental health and increased risk of suicide. Alexithymia is fairly common, affecting as much as 10% of people in Western cultures. Understanding how alexithymia relates to decision-making may therefore have wide-reaching impacts on the quality of life for many individuals. We designed and preregistered a study that examined the relationship between alexithymia and decision-making across different task-types. Data were collected from a community sample (N = 123) and participants completed a social, an emotional, and a perceptual decision-making task, as well as a short alexithymia questionnaire. For each task, we considered multiple aspects of the decision-making process, examining participants’ accuracy, confidence, and metacognitive ability (i.e. the ability to retrospectively distinguish between correct and incorrect responses). We found no relationship between alexithymia and performance or metacognitive ability in any task. However, alexithymia was negatively correlated with confidence in both the perceptual and emotional tasks. Furthermore, confidence in one’s decision was strongly, positively correlated across task types, but both accuracy and metacognitive ability showed no relationship between tasks. These results suggest that confidence may be a trait-like, affective component of decision-making, while performance and metacognitive sensitivity appear more task-specific. Furthermore, our results challenge the current limitations of the alexithymia construct, suggesting that alexithymia may have consequences on cognitive processes beyond emotion recognition alone.

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion regulation strategy which modifies how one thinks about a situation. Participants from 87 countries/regions (N = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vs. both control conditions) had consistent effects in reducing negative emotions and increasing positive emotions across different measures. Reconstrual and repurposing had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world to build resilience during the pandemic and beyond.

Borderline personality disorder (BorPD) is characterized by instability and mood dysregulation, unstable relationships and distorted self-image. Identification of underlying anatomical and physiological changes is crucial to refine current treatments and develop new ones. In this perspective, previous magnetic resonance imaging studies have highlighted alterations associated with BorPD phenotype. In particular, diffusion-weighted imaging/Diffusion tensor imaging (DWI/DTI) has identified many white matter structural alterations in individuals with this diagnosis. Although in its infancy, limiting this line of investigation is a lack of direction at the field level. Hence, the present paper aims to conduct a meta-analysis of DWI/DTI findings in individuals with a diagnosis of BorPD, testing the hypothesis that there are specific white matter alterations associated with BorPD. To this end, we performed a meta-analysis of the existing literature of DWI/DTI in BorPD representing a total of 123 individuals with BorPD and 117 Controls. Our results indicated that individuals with BorPD show regions of reduced fractional anisotropy in the corpus callosum and fornix. These results survived all jack-knife reshuffles and showed no publication bias. This suggests that alterations in these structures may contribute to psychopathology. Further, the present results lend support to extant psychological and biological models of BorPD.

Borderline personality disorder (BorPD) is characterized by instability and impulsivity of mood, relationships and self-image. This disease is an important area of public health policy; compared to other psychiatric disorders, individuals with BorPD experience the most severe functional impairments. Nevertheless, for the patients that do recover, this recovery is stable and only few relapse back to psychopathology. Given its high rate of remission, the rewards of effective treatment options are clear. Identification of underlying anatomical and physiological changes is crucial to refine current treatments and develop new ones. In this perspective, previous magnetic resonance imaging studies have highlighted alterations associated with BorPD phenotype. In particular, diffusion weighted imaging (DWI) has identified many white matter structural alterations in individuals with this diagnosis. Although in its infancy, limiting this line of investigation is a lack of direction at the field level. Hence, the present paper aims to conduct a meta-analysis of DWI findings in individuals with a diagnosis of BorPD, testing the hypothesis that there are specific white matter alterations associated with BorPD. To this end, we performed a meta-analysis of the existing literature of DWI in BorPD representing a total of 123 individuals with BorPD and 117 Controls. Our results indicated that individuals with BorPD show regions of reduced fractional anisotropy in the corpus callosum and fornix. These results survived all jack-knife reshuffles and showed no publication bias. This suggest that alterations in these structures may contribute to psychopathology. Further, the present results lend support to extant psychological and biological models of BorPD.

Borderline Personality Disorder (BPD) is a complex psychological condition characterised by affective instability, cognitive impairment, problematic behaviours and social dysfunction. Due to the variability in symptomatic profiles, efforts have recently been directed towards comprehending the disorder from a neurological standpoint within the aforementioned domains. Although adolescent-onset BPD is now reliably diagnosed as the adult-onset variant, a limited number of studies address the neural correlates of first presentation BPD. Moreover, research investigating the outcomes of therapeutic interventions on brain function and morphology is scarce. Preliminary findings consistently cite the involvement of grey matter deficiencies of the orbitofrontal cortex, hippocampus and amygdala in the neuropathology of BPD. Additionally, frontolimbic white matter deficits are thought to be implicated. Functionally, over-activity in limbic regions such as the cingulate cortices and amygdala are believed to partially account for emotion dysregulation, though the neural correlates of cognitive, social and behavioural impairments are relatively poorly understood. The present review will endeavour to evaluate the existing neurobiological evidence for BPD in adolescence as well as adulthood. Finally, a rudimentary neurodevelopmental model of BPD will be proposed.

According to the Justified True Belief account of knowledge (JTB), a person can only truly know something if they have a belief that is both justified and true (i.e., knowledge is justified true belief). This account was challenged by Gettier (1963), who argued that JTB does not explain knowledge attributions in certain situations, later called Gettier-type cases, wherein a protagonist is justified in believing something to be true but their belief was only correct due to luck. Lay people may not attribute knowledge to protagonists with justified but only luckily true beliefs. While some research has found evidence for these so-called Gettier intuitions (e.g., Machery et al., 2017a), Turri et al. (2015) found that participants attributed knowledge in Gettier-type cases at rates similar to cases of justified true belief. In a large-scale, cross-cultural conceptual replication of Turri and colleagues’ (2015) Experiment 1 (N = 4724), we failed to replicate this null result using a within-subjects design and three vignettes across 19 geopolitical regions. Instead, participants demonstrated Gettier intuitions; they were 1.86 times more likely to attribute knowledge to protagonists in standard cases of justified true belief than to protagonists in Gettier-type cases. These results suggest that Gettier intuitions may be common across different scenarios and cultural contexts. When assessing the knowledge of others, lay people may rely on a shared set of epistemic intuitions (i.e., a core folk epistemology) that requires more than simply justification, belief, and truth. However, the size of the Gettier intuition effect did vary by vignette, and the Turri et al. (2015) vignette produced the smallest effect. Thus, epistemic intuitions may also depend on contextual factors unrelated to the criteria of knowledge, such as the characteristics of the protagonist being evaluated.

The neurotransmitter dopamine is crucial for decision-making under uncertainty, but its computational role is still a subject of intense debate. To test its potential roles, we invited patients with Parkinson’s disease (PD), who have less internally generated dopamine, to participate in a visual decision-making task in which uncertainty in both prior and current sensory information was varied. Behaviour during these tasks is often predicted by Bayesian statistics. We found that many aspects of uncertainty processing were conserved in PD patients: they could learn the prior uncertainty and utilize both prior and current sensory information. As predicted by prominent theories, we found that dopaminergic medication influenced the weight given to sensory information. However, as PD patients learned, this bias disappeared. In addition, throughout the experiment the patients exhibited lower sensitivity to current sensory uncertainty compared with age-matched controls. Our results provide empirical evidence for the idea that dopamine levels, which are affected by PD and the drugs used for its treatment, influence the reliance on new information. How does the neurotransmitter dopamine and Parkinson’s disease (PD) affect decision-making under uncertainty? Vilares and Kording find that dopamine levels, which are affected by PD and the drugs used for its treatment, influence reliance on new versus prior information in decision-making.

Criminal convictions require proof that a prohibited act was performed in a statutorily specified mental state. Different legal consequences, including greater punishments, are mandated for those who act in a state of knowledge, compared with a state of recklessness. Existing research, however, suggests people have trouble classifying defendants as knowing, rather than reckless, even when instructed on the relevant legal criteria. We used a machine-learning technique on brain imaging data to predict, with high accuracy, which mental state our participants were in. This predictive ability depended on both the magnitude of the risks and the amount of information about those risks possessed by the participants. Our results provide neural evidence of a detectable difference in the mental state of knowledge in contrast to recklessness and suggest, as a proof of principle, the possibility of inferring from brain data in which legally relevant category a person belongs. Some potential legal implications of this result are discussed.

Bayesian statistics defines how new information, given by a likelihood, should be combined with previously acquired information, given by a prior distribution. Many experiments have shown that humans make use of such priors in cognitive, perceptual, and motor tasks, but where do priors come from? As people never experience the same situation twice, they can only construct priors by generalizing from similar past experiences. Here we examine the generalization of priors over stochastic visuomotor perturbations in reaching experiments. In particular, we look into how the first two moments of the prior—the mean and variance (uncertainty)—generalize. We find that uncertainty appears to generalize differently from the mean of the prior, and an interesting asymmetry arises when the mean and the uncertainty are manipulated simultaneously.

Experiments on humans and other animals have shown that uncertainty due to unreliable or incomplete information affects behavior. Recent studies have formalized uncertainty and asked which behaviors would minimize its effect. This formalization results in a wide range of Bayesian models that derive from assumptions about the world, and it often seems unclear how these models relate to one another. In this review, we use the concept of graphical models to analyze differences and commonalities across Bayesian approaches to the modeling of behavioral and neural data. We review behavioral and neural data associated with each type of Bayesian model and explain how these models can be related. We finish with an overview of different theories that propose possible ways in which the brain can represent uncertainty.

Objective To assess the effect of exercise training by using the Nintendo Wii Fit video game and balance board system on balance and gait in adults with Parkinson disease (PD). Design A prospective interventional cohort study. Setting An outpatient group exercise class. Participants Ten subjects with PD, Hoehn and Yahr stages 2.5 or 3, with a mean age of 67.1 years; 4 men, 6 women. Interventions The subjects participated in supervised group exercise sessions 3 times per week for 8 weeks by practicing 3 different Wii balance board games (marble tracking, skiing, and bubble rafting) adjusted for their individualized function level. The subjects trained for 10 minutes per game, a total of 30 minutes training per session. Main Outcome Measurements Pre-and postexercise training, a physical therapist evaluated subjects' function by using the Berg Balance Scale, Dynamic Gait Index, and Sharpened Romberg with eyes open and closed. Postural sway was assessed at rest and with tracking tasks by using the Wii balance board. The subjects rated their confidence in balance by using the Activities-specific Balance Confidence scale and depression on the Geriatric Depression Scale. Results Balance as measured by the Berg Balance Scale improved significantly, with an increase of 3.3 points ( P = .016). The Dynamic Gait Index improved as well (mean increase, 2.8; P = .004), as did postural sway measured with the balance board (decreased variance in stance with eyes open by 31%; P = .049). Although the Sharpened Romberg with eyes closed increased by 6.85 points and with eyes opened by 3.3 points, improvements neared significance only for eyes closed ( P = .07 versus P = .188). There were no significant changes on patient ratings for the Activities-specific Balance Confidence (mean decrease, −1%; P = .922) or the Geriatric Depression Scale (mean increase, 2.2; P = .188). Conclusions An 8-week exercise training class by using the Wii Fit balance board improved selective measures of balance and gait in adults with PD. However, no significant changes were seen in mood or confidence regarding balance.

Experiments on humans and other animals have shown that uncertainty due to unreliable or incomplete information affects behavior. Recent studies have formalized uncertainty and asked which behaviors would minimize its effect. This formalization results in a wide range of Bayesian models that derive from assumptions about the world, and it often seems unclear how these models relate to one another. In this review, we use the concept of graphical models to analyze differences and commonalities across Bayesian approaches to the modeling of behavioral and neural data. We review behavioral and neural data associated with each type of Bayesian model and explain how these models can be related. We finish with an overview of different theories that propose possible ways in which the brain can represent uncertainty.

A large number of experiments have asked to what degree human reaching movements can be understood as being close to optimal in a statistical sense. However, little is known about whether these principles are relevant for other classes of movements. Here we analyzed movement in a task that is similar to surfing or snowboarding. Human subjects stand on a force plate that measures their center of pressure. This center of pressure affects the acceleration of a cursor that is displayed in a noisy fashion (as a cloud of dots) on a projection screen while the subject is incentivized to keep the cursor close to a fixed position. We find that salient aspects of observed behavior are well-described by optimal control models where a Bayesian estimation model (Kalman filter) is combined with an optimal controller (either a Linear-Quadratic-Regulator or Bang-bang controller). We find evidence that subjects integrate information over time taking into account uncertainty. However, behavior in this continuous steering task appears to be a highly non-linear function of the visual feedback. While the nervous system appears to implement Bayes-like mechanisms for a full-body, dynamic task, it may additionally take into account the specific costs and constraints of the task., Author Summary There is a growing body of work demonstrating that humans are close to statistically optimal in both their perception of the world and their actions on it. That is, we seem to combine information from our sensors with the constraints and costs of moving to minimize our errors and effort. Most of the evidence for this type of behavior comes from tasks such as reaching in a small workspace or standing on a force plate passively viewing a stimulus. Although humans appear to be near-optimal for these tasks, it is not clear whether the theory holds for other tasks. Here we introduce a full-body, goal-directed task similar to surfing or snowboarding where subjects steer a cursor with their center of pressure. We find that subjects respond to sensory uncertainty near-optimally in this task, but their behavior is highly non-linear. This suggests that the computations performed by the nervous system may take into account a more complicated set of costs and constraints than previously supposed.

Summary Background Uncertainty shapes our perception of the world and the decisions we make. Two aspects of uncertainty are commonly distinguished: uncertainty in previously acquired knowledge (prior) and uncertainty in current sensory information (likelihood). Previous studies have established that humans can take both types of uncertainty into account, often in a way predicted by Bayesian statistics. However, the neural representations underlying these parameters remain poorly understood. Results By varying prior and likelihood uncertainty in a decision-making task while performing neuroimaging in humans, we found that prior and likelihood uncertainty had quite distinct representations. Whereas likelihood uncertainty activated brain regions along the early stages of the visuomotor pathway, representations of prior uncertainty were identified in specialized brain areas outside this pathway, including putamen, amygdala, insula, and orbitofrontal cortex. Furthermore, the magnitude of brain activity in the putamen predicted individuals' personal tendencies to rely more on either prior or current information. Conclusions Our results suggest different pathways by which prior and likelihood uncertainty map onto the human brain and provide a potential neural correlate for higher reliance on current or prior knowledge. Overall, these findings offer insights into the neural pathways that may allow humans to make decisions close to the optimal defined by a Bayesian statistical framework.

Trust and reciprocity facilitate cooperation and are relevant to virtually all human interactions. They are typically studied using trust games: one subject gives (entrusts) money to another subject, which may return some of the proceeds (reciprocate). Currently, however, it is unclear whether trust and reciprocity in monetary transactions are similar in other settings, such as physical effort. Trust and reciprocity of physical effort are important as many everyday decisions imply an exchange of physical effort, and such exchange is central to labor relations. Here we studied a trust game based on physical effort and compared the results with those of a computationally equivalent monetary trust game. We found no significant difference between effort and money conditions in both the amount trusted and the quantity reciprocated. Moreover, there is a high positive correlation in subjects' behavior across conditions. This suggests that trust and reciprocity may be character traits: subjects that are trustful/trustworthy in monetary settings behave similarly during exchanges of physical effort. Our results validate the use of trust games to study exchanges in physical effort and to characterize inter-subject differences in trust and reciprocity, and also suggest a new behavioral paradigm to study these differences.