Beliefs, compulsive behavior and reduced confidence in control.

OCD has been conceptualized as a disorder arising from dysfunctional beliefs, such as overestimating threats or pathological doubts. Yet, how these beliefs lead to compulsions and obsessions remains unclear. Here, we develop a computational model to examine the specific beliefs that trigger and sustain compulsive behavior in a simple symptom-provoking scenario. Our results demonstrate that a single belief disturbance-a lack of confidence in the effectiveness of one's preventive (harm-avoiding) actions-can trigger and maintain compulsions and is directly linked to compulsion severity. This distrust can further explain a number of seemingly unrelated phenomena in OCD, including the role of not-just-right feelings, the link to intolerance to uncertainty, perfectionism, and overestimation of threat, and deficits in reversal and state learning. Our simulations shed new light on which underlying beliefs drive compulsive behavior and highlight the important role of perceived ability to exert control for OCD.

Putaminal dopamine modulates movement motivation in Parkinson's disease.

The relative inability to produce effortful movements is the most specific motor sign of Parkinson's disease, which is primarily characterized by loss of dopaminergic terminals in the putamen. The motor motivation hypothesis suggests that this motor deficit may not reflect a deficiency in motor control per se, but a deficiency in cost-benefit considerations for motor effort. For the first time, we investigated the quantitative effect of dopamine depletion on the motivation of motor effort in Parkinson's disease. A total of 21 early-stage, unmedicated patients with Parkinson's disease and 26 healthy controls were included. An incentivized force task was used to capture the amount of effort participants were willing to invest for different monetary incentive levels and dopamine transporter depletion in the bilateral putamen was assessed. Our results demonstrate that patients with Parkinson's disease applied significantly less grip force than healthy controls, especially for low incentive levels. Congruously, decrease of motor effort with greater loss of putaminal dopaminergic terminals was most pronounced for low incentive levels. This signifies that putaminal dopamine is most critical to motor effort when the trade-off with the benefit is poor. Taken together, we provide direct evidence that the reduction of effortful movements in Parkinson's disease depends on motivation and that this effect is associated with putaminal dopaminergic degeneration.

Preserved striatal innervation maintains motor function despite severe loss of nigral dopaminergic neurons.

Degeneration of dopaminergic neurons in the substantia nigra and their striatal axon terminals causes cardinal motor symptoms of Parkinson's disease. In idiopathic cases, high levels of mitochondrial DNA alterations, leading to mitochondrial dysfunction, are a central feature of these vulnerable neurons. Here we present a mouse model expressing the K320E variant of the mitochondrial helicase Twinkle in dopaminergic neurons, leading to accelerated mitochondrial DNA mutations. These K320E-TwinkleDaN mice showed normal motor function at 20 months of age, although ∼70% of nigral dopaminergic neurons had perished. Remaining neurons still preserved ∼75% of axon terminals in the dorsal striatum and enabled normal dopamine release. Transcriptome analysis and viral tracing confirmed compensatory axonal sprouting of the surviving neurons. We conclude that a small population of substantia nigra dopaminergic neurons is able to adapt to the accumulation of mitochondrial DNA mutations and maintain motor control.

Neural encoding of food and monetary reward delivery.

Different types of rewards such as food and money can similarly drive our behavior owing to shared brain processes encoding their subjective value. However, while the value of money is abstract and needs to be learned, the value of food is rooted in the innate processing of sensory properties and nutritional utilization. Yet, the actual consumption of food and the receipt of money have never been directly contrasted in the same experiment, questioning what unique neural processes differentiate those reward types. To fill this gap, we examined the distinct and common neural responses to the delivery of food and monetary rewards during fMRI. In a novel experimental approach, we parametrically manipulated the subjective value of food and monetary rewards by modulating the quantities of administered palatable milkshake and monetary gains. The receipt of increasing amounts of milkshake and money recruited the ventral striatum and the ventromedial prefrontal cortex, previously associated with value encoding. Notably, the consumption and the subsequent evaluation of increasing quantities of milkshake relative to money revealed an extended recruitment of brain regions related to taste, somatosensory processing, and salience. Moreover, we detected a decline of reward encoding in the ventral tegmental area, nucleus accumbens, and vmPFC, indicating that these regions may be susceptible to time-dependent effects upon accumulation of food and money rewards. Relative to monetary gains, the consumption and evaluation of palatable milkshakes engaged complex neural processing over and above value tracking, emphasizing the critical contribution of taste and other sensory properties to the processing of food rewards. Furthermore, our results highlight the need to closely monitor metabolic states and neural responses to the accumulation of rewards to pinpoint the mechanisms underlying time-dependent dynamics of reward-related processing.

Technical Note: Modulation of fMRI brainstem responses by transcutaneous vagus nerve stimulation.

Our increasing knowledge about gut-brain interaction is revolutionising the understanding of the links between digestion, mood, health, and even decision making in our everyday lives. In support of this interaction, the vagus nerve is a crucial pathway transmitting diverse gut-derived signals to the brain to monitor of metabolic status, digestive processes, or immune control to adapt behavioural and autonomic responses. Hence, neuromodulation methods targeting the vagus nerve are currently explored as a treatment option in a number of clinical disorders, including diabetes, chronic pain, and depression. The non-invasive variant of vagus nerve stimulation (VNS), transcutaneous auricular VNS (taVNS), has been implicated in both acute and long-lasting effects by modulating afferent vagus nerve target areas in the brain. The physiology of neither of those effects is, however, well understood, and evidence for neuronal response upon taVNS in vagal afferent projection regions in the brainstem and its downstream targets remain to be established. Therefore, to examine time-dependent effects of taVNS on brainstem neuronal responses in healthy human subjects, we applied taVNS during task-free fMRI in a single-blinded crossover design. During fMRI data acquisition, we either stimulated the left earlobe (sham), or the target zone of the auricular branch of the vagus nerve in the outer ear (cymba conchae, verum) for several minutes, both followed by a short 'stimulation OFF' period. Time-dependent effects were assessed by averaging the BOLD response for consecutive 1-minute periods in an ROI-based analysis of the brainstem. We found a significant response to acute taVNS stimulation, relative to the control condition, in downstream targets of vagal afferents, including the nucleus of the solitary tract, the substantia nigra, and the subthalamic nucleus. Most of these brainstem regions remarkably showed increased activity in response to taVNS, and these effect sustained during the post-stimulation period. These data demonstrate that taVNS activates key brainstem regions, and highlight the potential of this approach to modulate vagal afferent signalling. Furthermore, we show that carry-over effects need to be considered when interpreting fMRI data in the context of general vagal neurophysiology and its modulation by taVNS.

Sour grapes and sweet victories: How actions shape preferences.

Classical decision theory postulates that choices proceed from subjective values assigned to the probable outcomes of alternative actions. Some authors have argued that opposite causality should also be envisaged, with choices influencing subsequent values expressed in desirability ratings. The idea is that agents may increase their ratings of items that they have chosen in the first place, which has been typically explained by the need to reduce cognitive dissonance. However, evidence in favor of this reverse causality has been the topic of intense debates that have not reached consensus so far. Here, we take a novel approach using Bayesian techniques to compare models in which choices arise from stable (but noisy) underlying values (one-way causality) versus models in which values are in turn influenced by choices (two-way causality). Moreover, we examined whether in addition to choices, other components of previous actions, such as the effort invested and the eventual action outcome (success or failure), could also impact subsequent values. Finally, we assessed whether the putative changes in values were only expressed in explicit ratings, or whether they would also affect other value-related behaviors such as subsequent choices. Behavioral data were obtained from healthy participants in a rating-choice-rating-choice-rating paradigm, where the choice task involves deciding whether or not to exert a given physical effort to obtain a particular food item. Bayesian selection favored two-way causality models, where changes in value due to previous actions affected subsequent ratings, choices and action outcomes. Altogether, these findings may help explain how values and actions drift when several decisions are made successively, hence highlighting some shortcomings of classical decision theory.

Influence of vmPFC on dmPFC Predicts Valence-Guided Belief Formation.

When updating beliefs about their future prospects, people tend to disregard bad news. By combining fMRI with computational and dynamic causal modeling, we identified neurocircuitry mechanisms underlying this optimism bias to test for valence-guided belief formation. In each trial of the fMRI task, participants (n = 24, 10 male) estimated the base rate (eBR) and their risks of experiencing negative future events, were confronted with the actual BR, and finally had the opportunity to update their initial self-related risk estimate. We demonstrated an optimism bias by revealing greater belief updates in response to good over bad news (i.e., learning that the actual BR is lower or higher than expected) while controlling for confounds (estimation error and personal relevance of the new information). Updating was favorable when the final belief about risks improved (or at least did not worsen) relative to the initial risk estimate. This valence of updating was encoded by the ventromedial prefrontal cortex (vmPFC) associated with the valuation of rewards. Within the updating circuit, the vmPFC filtered the incoming signal in a valence-dependent manner and influenced the dorsomedial prefrontal cortex (dmPFC). Both the valence-encoding activity in the vmPFC and its influence on the dmPFC predicted individual magnitudes of the optimism bias. Our results indicate that updating was biased by the motivation to maximize desirable beliefs, mediated by the influence of the valuation system on further cognitive processing. Therefore, although it provides the very basis for human reasoning, belief formation is essentially distorted to promote desired conclusions.SIGNIFICANCE STATEMENT The question of whether human reasoning is biased by desires and goals is crucial for everyday social, professional, and economic decisions. How much our belief formation is influenced by what we want to believe is, however, still debated. Our study confirms that belief updates are indeed optimistically biased. Critically, the bias depends on the recruitment of the brain valuation system and the influence of this system on neural regions involved in reasoning. These neurocircuit interactions support the notion that the motivation to maximize pleasant beliefs reinforces those cognitive processes that are most likely to yield the desired conclusion.

Modulation of midbrain neurocircuitry by intranasal insulin.

Insulin modulates dopamine neuron activity in midbrain and affects processes underlying food intake behaviour, including impulsivity and reward processing. Here, we used intranasal administration and task-free functional MRI in humans to assess time- and dose-dependent effects of insulin on functional connectivity of the dopaminergic midbrain - and how these effects varied depending on systemic insulin sensitivity as measured by HOMA-IR. Specifically, we used a repeated-measures design with factors dose (placebo, 40 IU, 100 IU, 160 IU), time (7 time points during a 90 min post-intervention interval), and group (low vs. high HOMA-IR). A factorial analysis identified a three-way interaction (with whole-brain significance) with regard to functional connectivity between midbrain and the ventromedial prefrontal cortex. This interaction demonstrates that systemic insulin sensitivity modulates the temporal course and dose-dependent effects of intranasal insulin on midbrain functional connectivity. It suggests that altered insulin sensitivity may impact on dopaminergic projections of the midbrain and might underlie the dysregulation of reward-related and motivational behaviour in obesity and diabetes. Perhaps most importantly, the time courses of midbrain functional connectivity we present may provide useful guidance for the design of future human studies that utilize intranasal insulin administration.

Cortical parcellation based on structural connectivity: A case for generative models.

One of the major challenges in systems neuroscience is to identify brain networks and unravel their significance for brain function -this has led to the concept of the 'connectome'. Connectomes are currently extensively studied in large-scale international efforts at multiple scales, and follow different definitions with respect to their connections as well as their elements. Perhaps the most promising avenue for defining the elements of connectomes originates from the notion that individual brain areas maintain distinct (long-range) connection profiles. These connectivity patterns determine the areas' functional properties and also allow for their anatomical delineation and mapping. This rationale has motivated the concept of connectivity-based cortex parcellation. In the past ten years, non-invasive mapping of human brain connectivity has led to immense advances in the development of parcellation techniques and their applications. Unfortunately, many of these approaches primarily aim for confirmation of well-known, existing architectonic maps and, to that end, unsuitably incorporate prior knowledge and frequently build on circular argumentation. Often, current approaches also tend to disregard the specific apertures of connectivity measurements, as well as the anatomical specificities of cortical areas, such as spatial compactness, regional heterogeneity, inter-subject variability, the multi-scaling nature of connectivity information, and potential hierarchical organisation. From a methodological perspective, however, a useful framework that regards all of these aspects in an unbiased way is technically demanding. In this commentary, we first outline the concept of connectivity-based cortex parcellation and discuss its prospects and limitations in particular with respect to structural connectivity. To improve reliability and efficiency, we then strongly advocate for connectivity-based cortex parcellation as a modelling approach; that is, an approximation of the data based on (model) parameter inference. As such, a parcellation algorithm can be formally tested for robustness -the precision of its predictions can be quantified and statistics about potential generalization of the results can be derived. Such a framework also allows the question of model constraints to be reformulated in terms of hypothesis testing through model selection and offers a formative way to integrate anatomical knowledge in terms of prior distributions.

Choose, rate or squeeze: Comparison of economic value functions elicited by different behavioral tasks.

A standard view in neuroeconomics is that to make a choice, an agent first assigns subjective values to available options, and then compares them to select the best. In choice tasks, these cardinal values are typically inferred from the preference expressed by subjects between options presented in pairs. Alternatively, cardinal values can be directly elicited by asking subjects to place a cursor on an analog scale (rating task) or to exert a force on a power grip (effort task). These tasks can vary in many respects: they can notably be more or less costly and consequential. Here, we compared the value functions elicited by choice, rating and effort tasks on options composed of two monetary amounts: one for the subject (gain) and one for a charity (donation). Bayesian model selection showed that despite important differences between the three tasks, they all elicited a same value function, with similar weighting of gain and donation, but variable concavity. Moreover, value functions elicited by the different tasks could predict choices with equivalent accuracy. Our finding therefore suggests that comparable value functions can account for various motivated behaviors, beyond economic choice. Nevertheless, we report slight differences in the computational efficiency of parameter estimation that may guide the design of future studies.

Computational Dissection of Dopamine Motor and Motivational Functions in Humans.

UNLABELLED: Motor dysfunction (e.g., bradykinesia) and motivational deficit (i.e., apathy) are hallmarks of Parkinson's disease (PD). Yet, it remains unclear whether these two symptoms arise from a same dopaminergic dysfunction. Here, we develop a computational model that articulates motor control to economic decision theory, to dissect the motor and motivational functions of dopamine in humans. This model can capture different aspects of the behavior: choice (which action is selected) and vigor (action speed and intensity). It was used to characterize the behavior of 24 PD patients, tested both when medicated and unmedicated, in two behavioral tasks: an incentive motivation task that involved producing a physical effort, knowing that it would be multiplied by reward level to calculate the payoff, and a binary choice task that involved choosing between high reward/high effort and low reward/low effort options. Model-free analyses in both tasks showed the same two effects when comparing unmedicated patients to medicated patients: dopamine depletion (1) decreased the amount of effort that patients were willing to produce for a given reward and (2) slowed down the production of this effort, regardless of reward level. Model-based analyses captured these effects with two independent parameters, namely reward sensitivity and motor activation rate. These two parameters were respectively predictive of medication effects on clinical measures of apathy and motor dysfunction. More generally, we suggest that such computational phenotyping might help characterizing deficits and refining treatments in neuropsychiatric disorders. SIGNIFICANCE STATEMENT: Many neurological conditions are characterized by motor and motivational deficits, which both result in reduced behavior. It remains extremely difficult to disentangle whether these patients are simply unable or do not want to produce a behavior. Here, we propose a model-based analysis of the behavior produced in tasks that involve trading physical efforts for monetary rewards, to quantify parameters that capture motor dynamics as well as sensitivity to reward, effort, and fatigue. Applied to Parkinson's disease, this computational analysis revealed two independent effects of dopamine enhancers, which predicted clinical improvement in motor and motivational deficits. Such computational profiling might provide a useful explanatory level, between neural dysfunction and clinical manifestations, for characterizing neuropsychiatric disorders and personalizing treatments.

An Obesity-Predisposing Variant of the FTO Gene Regulates D2R-Dependent Reward Learning.

Variations in the fat mass and obesity-associated (FTO) gene are linked to obesity. However, the underlying neurobiological mechanisms by which these genetic variants influence obesity, behavior, and brain are unknown. Given that Fto regulates D2/3R signaling in mice, we tested in humans whether variants in FTO would interact with a variant in the ANKK1 gene, which alters D2R signaling and is also associated with obesity. In a behavioral and fMRI study, we demonstrate that gene variants of FTO affect dopamine (D2)-dependent midbrain brain responses to reward learning and behavioral responses associated with learning from negative outcome in humans. Furthermore, dynamic causal modeling confirmed that FTO variants modulate the connectivity in a basic reward circuit of meso-striato-prefrontal regions, suggesting a mechanism by which genetic predisposition alters reward processing not only in obesity, but also in other disorders with altered D2R-dependent impulse control, such as addiction. Significance statement: Variations in the fat mass and obesity-associated (FTO) gene are associated with obesity. Here we demonstrate that variants of FTO affect dopamine-dependent midbrain brain responses and learning from negative outcomes in humans during a reward learning task. Furthermore, FTO variants modulate the connectivity in a basic reward circuit of meso-striato-prefrontal regions, suggesting a mechanism by which genetic vulnerability in reward processing can increase predisposition to obesity.

Neurocomputational account of how the human brain decides when to have a break.

No pain, no gain: cost-benefit trade-off has been formalized in classical decision theory to account for how we choose whether to engage effort. However, how the brain decides when to have breaks in the course of effort production remains poorly understood. We propose that decisions to cease and resume work are triggered by a cost evidence accumulation signal reaching upper and lower bounds, respectively. We developed a task in which participants are free to exert a physical effort knowing that their payoff would be proportional to their effort duration. Functional MRI and magnetoencephalography recordings conjointly revealed that the theoretical cost evidence accumulation signal was expressed in proprioceptive regions (bilateral posterior insula). Furthermore, the slopes and bounds of the accumulation process were adapted to the difficulty of the task and the money at stake. Cost evidence accumulation might therefore provide a dynamical mechanistic account of how the human brain maximizes benefits while preventing exhaustion.

VBA: a probabilistic treatment of nonlinear models for neurobiological and behavioural data.

This work is in line with an on-going effort tending toward a computational (quantitative and refutable) understanding of human neuro-cognitive processes. Many sophisticated models for behavioural and neurobiological data have flourished during the past decade. Most of these models are partly unspecified (i.e. they have unknown parameters) and nonlinear. This makes them difficult to peer with a formal statistical data analysis framework. In turn, this compromises the reproducibility of model-based empirical studies. This work exposes a software toolbox that provides generic, efficient and robust probabilistic solutions to the three problems of model-based analysis of empirical data: (i) data simulation, (ii) parameter estimation/model selection, and (iii) experimental design optimization.

A model of reward- and effort-based optimal decision making and motor control.

Costs (e.g. energetic expenditure) and benefits (e.g. food) are central determinants of behavior. In ecology and economics, they are combined to form a utility function which is maximized to guide choices. This principle is widely used in neuroscience as a normative model of decision and action, but current versions of this model fail to consider how decisions are actually converted into actions (i.e. the formation of trajectories). Here, we describe an approach where decision making and motor control are optimal, iterative processes derived from the maximization of the discounted, weighted difference between expected rewards and foreseeable motor efforts. The model accounts for decision making in cost/benefit situations, and detailed characteristics of control and goal tracking in realistic motor tasks. As a normative construction, the model is relevant to address the neural bases and pathological aspects of decision making and motor control.

Liraglutide restores impaired associative learning in individuals with obesity.

Survival under selective pressure is driven by the ability of our brain to use sensory information to our advantage to control physiological needs. To that end, neural circuits receive and integrate external environmental cues and internal metabolic signals to form learned sensory associations, consequently motivating and adapting our behaviour. The dopaminergic midbrain plays a crucial role in learning adaptive behaviour and is particularly sensitive to peripheral metabolic signals, including intestinal peptides, such as glucagon-like peptide 1 (GLP-1). In a single-blinded, randomized, controlled, crossover basic human functional magnetic resonance imaging study relying on a computational model of the adaptive learning process underlying behavioural responses, we show that adaptive learning is reduced when metabolic sensing is impaired in obesity, as indexed by reduced insulin sensitivity (participants: N = 30 with normal insulin sensitivity; N = 24 with impaired insulin sensitivity). Treatment with the GLP-1 receptor agonist liraglutide normalizes impaired learning of sensory associations in men and women with obesity. Collectively, our findings reveal that GLP-1 receptor activation modulates associative learning in people with obesity via its central effects within the mesoaccumbens pathway. These findings provide evidence for how metabolic signals can act as neuromodulators to adapt our behaviour to our body's internal state and how GLP-1 receptor agonists work in clinics.

Habitual daily intake of a sweet and fatty snack modulates reward processing in humans.

Western diets rich in fat and sugar promote excess calorie intake and weight gain; however, the underlying mechanisms are unclear. Despite a well-documented association between obesity and altered brain dopamine function, it remains elusive whether these alterations are (1) pre-existing, increasing the individual susceptibility to weight gain, (2) secondary to obesity, or (3) directly attributable to repeated exposure to western diet. To close this gap, we performed a randomized, controlled study (NCT05574660) with normal-weight participants exposed to a high-fat/high-sugar snack or a low-fat/low-sugar snack for 8 weeks in addition to their regular diet. The high-fat/high-sugar intervention decreased the preference for low-fat food while increasing brain response to food and associative learning independent of food cues or reward. These alterations were independent of changes in body weight and metabolic parameters, indicating a direct effect of high-fat, high-sugar foods on neurobehavioral adaptations that may increase the risk for overeating and weight gain.

Circulating uridine dynamically and adaptively regulates food intake in humans.

Feeding behavior must be continuously adjusted to match energy needs. Recent discoveries in murine models identified uridine as a regulator of energy balance. Here, we explore its contribution to the complex control of food intake in humans by administering a single dose of uridine monophosphate (UMP; 0.5 or 1 g) to healthy participants in two placebo-controlled studies designed to assess food behavior (registration: DRKS00014874). We establish that endogenous circulating uridine correlates with hunger and ensuing food consumption. It also dynamically decreases upon caloric ingestion, prompting its potential role in a negative feedback loop regulating energy intake. We further demonstrate that oral UMP administration temporarily increases circulating uridine and-when within the physiological range-enhances hunger and caloric intake proportionally to participants' basal energy needs. Overall, uridine appears as a potential target to tackle dysfunctions of feeding behavior in humans.

GLP-1 and hunger modulate incentive motivation depending on insulin sensitivity in humans.

OBJECTIVE: To regulate food intake, our brain constantly integrates external cues, such as the incentive value of a potential food reward, with internal state signals, such as hunger feelings. Incentive motivation refers to the processes that translate an expected reward into the effort spent to obtain the reward; the magnitude and probability of a reward involved in prompting motivated behaviour are encoded by the dopaminergic (DA) midbrain and its mesoaccumbens DA projections. This type of reward circuity is particularly sensitive to the metabolic state signalled by peripheral mediators, such as insulin or glucagon-like peptide 1 (GLP-1). While in rodents the modulatory effect of metabolic state signals on motivated behaviour is well documented, evidence of state-dependent modulation and the role of incentive motivation underlying overeating in humans is lacking. METHODS: In a randomised, placebo-controlled, crossover design, 21 lean (body mass index [BMI] < 25 kg/m2) and 16 obese (BMI³ 30 kg/m2) volunteer participants received either liraglutide as a GLP-1 analogue or placebo on two separate testing days. Incentive motivation was measured using a behavioural task in which participants were required to exert physical effort using a handgrip to win different amounts of food and monetary rewards. Hunger levels were measured using visual analogue scales; insulin, glucose, and systemic insulin resistance as assessed by the homeostasis model assessment of insulin resistance (HOMA-IR) were quantified at baseline. RESULTS: In this report, we demonstrate that incentive motivation increases with hunger in lean humans (F(1,42) = 5.31, p = 0.026, ß = 0.19) independently of incentive type (food and non-food reward). This effect of hunger is not evident in obese humans (F(1,62) = 1.93, p = 0.17, ß = -0.12). Motivational drive related to hunger is affected by peripheral insulin sensitivity (two-way interaction, F(1, 35) = 6.23, p = 0.017, ß = -0.281). In humans with higher insulin sensitivity, hunger increases motivation, while poorer insulin sensitivity dampens the motivational effect of hunger. The GLP-1 analogue application blunts the interaction effect of hunger on motivation depending on insulin sensitivity (three-way interaction, F(1, 127) = 5.11, p = 0.026); no difference in motivated behaviour could be found between humans with normal or impaired insulin sensitivity under GLP-1 administration. CONCLUSION: We report a differential effect of hunger on motivation depending on insulin sensitivity. We further revealed the modulatory role of GLP-1 in adaptive, motivated behaviour in humans and its interaction with peripheral insulin sensitivity and hunger. Our results suggest that GLP-1 might restore dysregulated processes of midbrain DA function and hence motivational behaviour in insulin-resistant humans.

Brief Report: Reduced Optimism Bias in Self-Referential Belief Updating in High-Functioning Autism.

Previous research has demonstrated irrational asymmetry in belief updating: people tend to take into account good news and neglect bad news. Contradicting formal learning principles, belief updates were on average larger after better-than-expected information than after worse-than-expected information. In the present study, typically developing subjects demonstrated this optimism bias in self-referential judgments. In contrast, adults with high-functioning autism spectrum disorder (ASD) were significantly less biased when updating self-referential beliefs (each group n = 21, matched for age, gender and IQ). These findings indicate a weaker influence of self-enhancing motives on prospective judgments in ASD. Reduced susceptibility to emotional and motivational biases in reasoning in ASD could elucidate impairments of social cognition, but may also confer important cognitive benefits.