Confidence drives a neural confirmation bias

The precision test of metacognitive sensitivity and confidence criteria

Humans experience feelings of confidence in their decisions. In perception, these feelings are typically accurate - we tend to feel more confident about correct decisions. The degree of insight people have into the accuracy of their decisions is known as metacognitive sensitivity. Currently popular methods of estimating metacognitive sensitivity are subject to interpretive ambiguities because they assume people have normally shaped distributions of different experiences when they are repeatedly exposed to a single input. If this normality assumption is violated, calculations can erroneously underestimate metacognitive sensitivity. Here, we describe a means of estimating metacognitive sensitivity that is more robust to violations of the normality assumption. This improved method can easily be added to standard behavioral experiments, and the authors provide Matlab code to help researchers implement these analyses and experimental procedures.

Neural mechanisms underpinning metacognitive shifts driven by non-informative predictions

Humans constantly make predictions and such predictions allow us to prepare for future events. Yet, such benefits may come with drawbacks as premature predictions may potentially bias subsequent judgments. Here we examined how prediction influences our perceptual decisions and subsequent confidence judgments, on scenarios where the predictions were arbitrary and independent of the identity of the upcoming stimuli. We defined them as invalid and non-informative predictions. Behavioral results showed that, such non-informative predictions biased perceptual decisions in favor of the predicted choice, and such prediction-induced perceptual bias further increased the metacognitive efficiency. The functional MRI results showed that activities in the medial prefrontal cortex (mPFC) and subgenual anterior cingulate cortex (sgACC) encoded the response consistency between predictions and perceptual decisions. Activity in mPFC predicted the strength of this congruency bias across individuals. Moreover, the parametric encoding of confidence in putamen was modulated by prediction-choice consistency, such that activity in putamen was negatively correlated with confidence rating after inconsistent responses. These findings suggest that predictions, while made arbitrarily, orchestrate the neural representations of choice and confidence judgment.

Why metacognition matters in politically contested domains

Emerging evidence highlights the importance of metacognition - the capacity for insight into the reliability and fallibility of our own knowledge and thought - in politically contested domains. The present synthesis elucidates why metacognition matters in politically charged contexts and its potential impact on how individuals form beliefs, process evidence, and make decisions.

Neural Signatures of Evidence Accumulation Encode Subjective Perceptual Confidence Independent of Performance

Confidence is an adaptive computation when environmental feedback is absent, yet there is little consensus regarding how perceptual confidence is computed in the brain. Difficulty arises because confidence correlates with other factors, such as accuracy, response time (RT), or evidence quality. We investigated whether neural signatures of evidence accumulation during a perceptual choice predict subjective confidence independently of these factors. Using motion stimuli, a central-parietal positive-going electroencephalogram component (CPP) behaves as an accumulating decision variable that predicts evidence quality, RT, accuracy, and confidence (Experiment 1, N = 25 adults). When we psychophysically varied confidence while holding accuracy constant (Experiment 2, N = 25 adults), the CPP still predicted confidence. Statistically controlling for RT, accuracy, and evidence quality (Experiment 3, N = 24 adults), the CPP still explained unique variance in confidence. The results indicate that a predecision neural signature of evidence accumulation, the CPP, encodes subjective perceptual confidence in decision-making independent of task performance.

Confirmation Bias through Selective Use of Evidence in Human Cortex

Decision-makers often process new evidence selectively, depending on their current beliefs about the world. We asked whether such confirmation biases result from biases in the encoding of sensory evidence in the brain, or alternatively in the utilization of encoded evidence for behavior. Human participants estimated the source of a sequence of visual-spatial evidence samples while we measured cortical population activity with magnetoencephalography (MEG). Halfway through the sequence, participants were prompted to judge the more likely source category. Their processing of subsequent evidence depended on its consistency with the previously chosen category, but the encoding of evidence in cortical activity did not. Instead, the encoded evidence in parietal and primary visual cortex contributed less to the estimation report when that evidence was inconsistent with the previous choice. We conclude that confirmation bias originates from the way in which decision-makers utilize information encoded in the brain. This provides room for deliberative control.

Falling into the trap: A study of the cognitive neural mechanisms of immediate rewards impact on consumer attitudes toward forwarding perk advertisements

In the context of digital marketing, consumers often express aversion to perk advertisements yet find it challenging to resist the temptation and forward it, resulting in inconsistent attitudes and behaviors. This study, based on the Associative Propositional Evaluation model and the Confirmation Bias theory, utilizes event-related potential experiments to identify the interactive impacts of immediate rewards and information diagnosticity in advertisements on consumer attitude change in specific contexts. The research findings indicate that when rewards were present, information diagnosticity positively influences attitude change and the willingness to forward. However, when rewards were absent, the impact of information diagnosticity on attitude change and the willingness to forward is not significant, and neuroscientific evidence supports these findings. Theoretically, this study extends the research perspective on attitude change in online advertising contexts and broadens the application of the Associative Propositional Evaluation model in the field of consumer attitude change towards advertisements. In practice, this research holds significant guiding value for constraining platform manipulation of consumer cognitive behaviors, guiding the healthy development of platform economics, and promoting digital technology ethics.

What the eyes, confidence, and partner's identity can tell about change of mind

Perceptual confidence reflects the ability to evaluate the evidence that supports perceptual decisions. It is thought to play a critical role in guiding decision-making. However, only a few empirical studies have actually investigated the function of perceptual confidence. To address this issue, we designed a perceptual task in which participants provided a confidence judgment on the accuracy of their perceptual decision. Then, they viewed the response of a machine or human partner, and they were instructed to decide whether to keep or change their initial response. We observed that confidence predicted participants' changes of mind more than task difficulty and perceptual accuracy. Additionally, interacting with a machine, compared to a human, decreased confidence and increased participants tendency to change their initial decision, suggesting that both confidence and changes of mind are influenced by contextual factors, such as the identity of a partner. Finally, variations in confidence judgments but not change of mind were correlated with pre-response pupil dynamics, indicating that arousal changes are linked to confidence computations. This study contributes to our understanding of the factors influencing confidence and changes of mind and also evaluates the possibility of using pupil dynamics as a proxy of confidence.

Unveiling deception: Characterizing false amber necklace messages on Facebook

BACKGROUND

Messages promoting the benefits of amber necklaces for children are common on social media, despite their health risks.

AIM

This study characterized Facebook posts with false content about the efficacy of amber necklaces in teething.

DESIGN

A sample of 500 English-language Facebook posts was analyzed by two investigators to determine the motivations, author's profile, and sentiments of posts. Latent Dirichlet Allocation topic modeling was used to identify salient terms and topics. An intertopic distance map was created to calculate the topic similarity. These data were analyzed using descriptive analysis, the Mann-Whitney U test, Cramer's V test, and multiple logistic regression models, regarding the time since initial posting and interaction metrics.

RESULTS

Most posts were made by business profiles and expressed positive sentiments, with social, psychological, and financial motivations. The posts were categorized into the topics "giveaway," "healing features," and "sales." Overperforming scores and total interaction increased with time since the initial posting. Posts with links had higher overperforming scores.

CONCLUSION

The findings suggest that Facebook posts about the efficacy of amber necklaces in teething are motivated by financial interests, using psychological and social mechanisms to achieve greater interaction with their target audience.

Impact of a Mock OSCE on Student Confidence in Applying the Pharmacists' Patient Care Process

The Medical and Pharmacy Student Collaboration (MAPSC) student organization at the University of Southern California, Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, created an extracurricular, peer-led, virtual group mock objective structured clinical examination (MOSCE) to expose first-year pharmacy students (P1s) to the Pharmacists' Patient Care Process (PPCP). The purpose of this study is to evaluate the impact of a MAPSC MOSCE on P1s self-reported confidence in applying the PPCP and on patient communication, medication knowledge, and clinical skills. An anonymous, optional, self-reported survey was administered to P1s before and after the event, where they rated their confidence on a scale of 0-100 (0 = not confident, 100 = certainly confident). The statistical analysis was a paired two-tailed t-test with a significance level of p < 0.05. A total of 152 P1s and 30 facilitators attended the MOSCE. One hundred thirty-nine students met the inclusion criteria and were included in the data analysis. There was a statistically significant difference in the change in self-reported confidence for all PPCP components and learning outcomes. The results of our study strongly indicate that introducing P1 students to the PPCP through a MAPSC MOSCE format is a valuable experience.

What could be the reasons for not losing weight even after following a weight loss program?

INTRODUCTION

Approximately four million people worldwide die annually because of obesity. Weight loss is commonly recommended as a first-line therapy in overweight and obese patients. Although many individuals attempt to lose weight, not everyone achieves optimal success. Few studies point out that weight loss eventually slows down, stagnates or reverses in 85% of the cases.

RESEARCH QUESTION

What could be the reasons for not losing weight even after following a weight loss program?

METHODS

A scoping review of the literature was performed using weight loss-related search terms such as 'Obesity,' 'Overweight,' 'Lifestyle,' 'weight loss,' 'Basal Metabolism,' 'physical activity,' 'adherence,' 'energy balance,' 'Sleep' and 'adaptations. The search involved reference tracking and database and web searches (PUBMED, Science Direct, Elsevier, Web of Science and Google Scholar). Original articles and review papers on weight loss involving human participants and adults aged > 18 years were selected. Approximately 231 articles were reviewed, and 185 were included based on the inclusion criteria.

DESIGN

Scoping review.

RESULTS

In this review, the factors associated with not losing weight have broadly been divided into five categories. Studies highlighting each subfactor were critically reviewed and discussed. A wide degree of interindividual variability in weight loss is common in studies even after controlling for variables such as adherence, sex, physical activity and baseline weight. In addition to these variables, variations in factors such as previous weight loss attempts, sleep habits, meal timings and medications can play a crucial role in upregulating or downregulating the association between energy deficit and weight loss results.

CONCLUSION

This review identifies and clarifies the role of several factors that may hinder weight loss after the exploration of existing evidence. Judging the effectiveness of respective lifestyle interventions by simply observing the 'general behavior of the groups' is not always applicable in clinical practice. Each individual must be monitored and advised as per their requirements and challenges.

How do humans give confidence? A comprehensive comparison of process models of perceptual metacognition

Humans have the metacognitive ability to assess the accuracy of their decisions via confidence judgments. Several computational models of confidence have been developed but not enough has been done to compare these models, making it difficult to adjudicate between them. Here, we compare 14 popular models of confidence that make various assumptions, such as confidence being derived from postdecisional evidence, from positive (decision-congruent) evidence, from posterior probability computations, or from a separate decision-making system for metacognitive judgments. We fit all models to three large experiments in which subjects completed a basic perceptual task with confidence ratings. In Experiments 1 and 2, the best-fitting model was the lognormal meta noise (LogN) model, which postulates that confidence is selectively corrupted by signal-dependent noise. However, in Experiment 3, the positive evidence (PE) model provided the best fits. We evaluated a new model combining the two consistently best-performing models-LogN and the weighted evidence and visibility (WEV). The resulting model, which we call logWEV, outperformed its individual counterparts and the PE model across all data sets, offering a better, more generalizable explanation for these data. Parameter and model recovery analyses showed mostly good recoverability but with important exceptions carrying implications for our ability to discriminate between models. Finally, we evaluated each model's ability to explain different patterns in the data, which led to additional insight into their performances. These results comprehensively characterize the relative adequacy of current confidence models to fit data from basic perceptual tasks and highlight the most plausible mechanisms underlying confidence generation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The roots of polarization in the individual reward system

Polarization raises concerns for democracy and society, which have expanded in the internet era where (mis)information has become ubiquitous, its transmission faster than ever, and the freedom and means of opinion expressions are expanding. The origin of polarization however remains unclear, with multiple social and emotional factors and individual reasoning biases likely to explain its current forms. In the present work, we adopt a principled approach and show that polarization tendencies can take root in biased reward processing of new information in favour of choice confirmatory evidence. Through agent-based simulations, we show that confirmation bias in individual learning is an independent mechanism and could be sufficient for creating polarization at group level independently of any additional assumptions about the opinions themselves, a priori beliefs about them, information transmission mechanisms or the structure of social relationship between individuals. This generative process can interact with polarization mechanisms described elsewhere, but constitutes an entrenched biological tendency that helps explain the extraordinary resilience of polarization against mitigating efforts such as dramatic informational change in the environment.

Predictive cues elicit a liminal confirmation bias in the moral evaluation of real-world images

Previous research suggested that predictive cues enhance the preference and reduce the response time for congruent targets during bivalent food evaluation, indicating a confirmation bias. Less is known about how prior processing affects subjective moral evaluation. Here, we used three different types of predictive cues to elicit directional vs. non-predictive prior processing and then asked the participants to perform moral evaluations on a continuous scale from -10 ("very immoral") to +10 ("very moral") with a diverse set of real-world images. Our experimental image database balanced the morality of image content and the volatility of the ratings based on the means and standard deviations in a preliminary study. Ratings, response times, and gaze positions were measured to examine the effects of predictive cues on the moral evaluation of real-world images. We found that the moral ratings were in line with the expectations induced by the cues. Compared to the non-predictive condition, the moral evaluation in the directional conditions was more polarized. For neutral images, the predictive cues tilted the evaluations to positive vs. negative, indicating a decisive liminal influence. High-volatility images were impacted more than low-volatility images in ratings as well as response times. Furthermore, the gaze positions during the interval between the predictive cue and the image showed a spatial displacement in line with the cue instruction, indicating a response bias. Together, the results show that predictive cues elicit a liminal confirmation bias in moral image evaluation, much in the same way as in bivalent food evaluation.

Adaptive biasing of action-selective cortical build-up activity by stimulus history

Decisions under uncertainty are often biased by the history of preceding sensory input, behavioral choices, or received outcomes. Behavioral studies of perceptual decisions suggest that such history-dependent biases affect the accumulation of evidence and can be adapted to the correlation structure of the sensory environment. Here, we systematically varied this correlation structure while human participants performed a canonical perceptual choice task. We tracked the trial-by-trial variations of history biases via behavioral modeling and of a neural signature of decision formation via magnetoencephalography (MEG). The history bias was flexibly adapted to the environment and exerted a selective effect on the build-up (not baseline level) of action-selective motor cortical activity during decision formation. This effect added to the impact of the current stimulus. We conclude that the build-up of action plans in human motor cortical circuits is shaped by dynamic prior expectations that result from an adaptive interaction with the environment.

Prospective and Retrospective Metacognitive Abilities and Their Association with Impaired Self-awareness in Patients with Traumatic Brain Injury

Metacognitive impairment often occurs in patients with traumatic brain injury (TBI) and is associated with clinical problems. The aim of this study was to clarify the pathology of metacognitive impairment in TBI patients using a behavioral task, clinical assessment of self-awareness, and lesion-symptom mapping. Metacognitive abilities of TBI patients and healthy controls were assessed using a modified perceptual decision-making task. Self-awareness was assessed using the Patient Competency Rating Scale and the Frontal Systems Behavior Scale. The associations between estimated metacognitive abilities, self-awareness, and neuropsychological test results were examined. The correspondence between metacognitive disabilities and brain lesions was explored by ROI-based lesion-symptom mapping using structural magnetic resonance images. Overall, 25 TBI patients and 95 healthy controls were included in the analyses. Compared with that in healthy controls, the prospective metacognitive ability of TBI patients was lower, with metacognitive evaluations revealing a bias toward overestimating their abilities. Retrospective metacognitive ability showed a negative correlation with self-awareness but not with neuropsychological test results. In the lesion-symptom mapping analysis, the left pFC was associated with lower retrospective metacognitive ability. This study contributes to a better understanding of the pathology of metacognitive and self-awareness deficits in TBI patients and may explain the cause of impaired realistic goal setting and adaptive behavior in these patients.

Differences in metacognitive functioning between obsessive-compulsive disorder patients and highly compulsive individuals from the general population

BACKGROUND

Our confidence, a form of metacognition, guides our behavior. Confidence abnormalities have been found in obsessive-compulsive disorder (OCD). A first notion based on clinical case-control studies suggests lower confidence in OCD patients compared to healthy controls. Contrarily, studies in highly compulsive individuals from general population samples showed that obsessive-compulsive symptoms related positively or not at all to confidence. A second notion suggests that an impairment in confidence estimation and usage is related to compulsive behavior, which is more often supported by studies in general population samples. These opposite findings call into question whether findings from highly compulsive individuals from the general population are generalizable to OCD patient populations.

METHODS

To test this, we investigated confidence at three hierarchical levels: local confidence in single decisions, global confidence in task performance and higher-order self-beliefs in 40 OCD patients (medication-free, no comorbid diagnoses), 40 controls, and 40 matched highly compulsive individuals from the general population (HComp).

RESULTS

In line with the first notion we found that OCD patients exhibited relative underconfidence at all three hierarchical levels. In contrast, HComp individuals showed local and global overconfidence and worsened metacognitive sensitivity compared with OCD patients, in line with the second notion.

CONCLUSIONS

Metacognitive functioning observed in a general highly compulsive population, often used as an analog for OCD, is distinct from that in a clinical OCD population, suggesting that OC symptoms in these two groups relate differently to (meta)cognitive processes. These findings call for caution in generalizing (meta)cognitive findings from general population to clinical samples.

Metacognition, public health compliance, and vaccination willingness

Metacognition, our ability to reflect on our own beliefs, manifests itself in the confidence we have in these beliefs, and helps us guide our behavior in complex and uncertain environments. Here, we provide empirical tests of the importance of metacognition during the pandemic. Bayesian and frequentist analyses demonstrate that citizens with higher metacognitive sensitivity-where confidence differentiates correct from incorrect COVID-19 beliefs-reported higher willingness to vaccinate against COVID-19, and higher compliance with recommended public health measures. Notably, this benefit of accurate introspection held controlling for the accuracy of COVID-19 beliefs. By demonstrating how vaccination willingness and compliance may relate to insight into the varying accuracy of beliefs, rather than only the accuracy of the beliefs themselves, this research highlights the critical role of metacognitive ability in times of crisis. However, we do not find sufficient evidence to conclude that citizens with higher metacognitive sensitivity were more likely to comply with recommended public health measures when controlling for the absolute level of the confidence citizens had in their COVID-19 beliefs.

Paradoxical evidence weighting in confidence judgments for detection and discrimination

When making discrimination decisions between two stimulus categories, subjective confidence judgments are more positively affected by evidence in support of a decision than negatively affected by evidence against it. Recent theoretical proposals suggest that this "positive evidence bias" may be due to observers adopting a detection-like strategy when rating their confidence-one that has functional benefits for metacognition in real-world settings where detectability and discriminability often go hand in hand. However, it is unknown whether, or how, this evidence-weighting asymmetry affects detection decisions about the presence or absence of a stimulus. In four experiments, we first successfully replicate a positive evidence bias in discrimination confidence. We then show that detection decisions and confidence ratings paradoxically suffer from an opposite "negative evidence bias" to negatively weigh evidence even when it is optimal to assign it a positive weight. We show that the two effects are uncorrelated and discuss our findings in relation to models that account for a positive evidence bias as emerging from a confidence-specific heuristic, and alternative models where decision and confidence are generated by the same, Bayes-rational process.

Prior information differentially affects discrimination decisions and subjective confidence reports

According to Bayesian models, both decisions and confidence are based on the same precision-weighted integration of prior expectations ("priors") and incoming information ("likelihoods"). This assumes that priors are integrated optimally and equally in decisions and confidence, which has not been tested. In three experiments, we quantify how priors inform decisions and confidence. With a dual-decision task we create pairs of conditions that are matched in posterior information, but differ on whether the prior or likelihood is more informative. We find that priors are underweighted in discrimination decisions, but are less underweighted in confidence about those decisions, and this is not due to differences in processing time. The same patterns remain with exogenous probabilistic cues as priors. With a Bayesian model we quantify the weighting parameters for the prior at both levels, and find converging evidence that priors are more optimally used in explicit confidence, even when underused in decisions.

Factors influencing the update of beliefs regarding controversial political issues

Selectively integrating new information contributes to belief polarization and compromises public discourse. To better understand factors that underlie biased belief updating, I conducted three pre-registered studies covering different controversial political issues. The main hypothesis was that cognitively devaluing new information hinders belief updating. Support for this hypothesis was found in only one of the three issues. The only factor that consistently influenced belief updating across issues was the discrepancy between prior beliefs and new information. These results suggest that usually people do use evidence to correct their beliefs, but may refuse to do so if doubts about its generalizability arise.

Evidence or Confidence: What Is Really Monitored during a Decision?

Assessing our confidence in the choices we make is important to making adaptive decisions, and it is thus no surprise that we excel in this ability. However, standard models of decision-making, such as the drift-diffusion model (DDM), treat confidence assessment as a post hoc or parallel process that does not directly influence the choice, which depends only on accumulated evidence. Here, we pursue the alternative hypothesis that what is monitored during a decision is an evolving sense of confidence (that the to-be-selected option is the best) rather than raw evidence. Monitoring confidence has the appealing consequence that the decision threshold corresponds to a desired level of confidence for the choice, and that confidence improvements can be traded off against the resources required to secure them. We show that most previous findings on perceptual and value-based decisions traditionally interpreted from an evidence-accumulation perspective can be explained more parsimoniously from our novel confidence-driven perspective. Furthermore, we show that our novel confidence-driven DDM (cDDM) naturally generalizes to decisions involving any number of alternative options - which is notoriously not the case with traditional DDM or related models. Finally, we discuss future empirical evidence that could be useful in adjudicating between these alternatives.

Metacognitive effects of attitudinal (in)congruence on social media: relating processing fluency, subjective knowledge, and political participation

Introduction

Encountering political disagreements in our daily lives can discourage us from participating in democratic processes. To date, research has mainly focused on social motives or attitudinal mechanisms to explain this phenomenon. In the present study, we adopt a different approach and highlight metacognitive effects of attitudinal (in)congruence on processing fluency (i.e., perceived ease of processing) and subjective knowledge as well as their relationship with behavioral outcomes such as the intention to politically participate.

Methods

In a pre-registered online experiment (N = 1,258), participants saw a political social media post with six opinionated user-generated comments. These comments either all matched (congruent condition) or contradicted (incongruent condition) participants' personal opinions. Processing fluency, issue specific subjective knowledge, and intention to politically participate were then measured using established self-report scales.

Results

In line with our hypotheses, the congruent stimuli evoked a higher feeling of processing fluency than the incongruent ones (d = 0.21). Furthermore, participants in the congruent condition indicated a higher intention to politically participate (d = 0.23) and rated their own knowledge on the topic as higher (d = 0.22) than participants in the incongruent condition-even though the factual knowledge gain should be equal in both conditions. Finally, we observed positive relationships between processing fluency and subjective issue knowledge (β = 0.11) as well as between subjective issue knowledge and issue-specific political participation (β = 0.43).

Discussion

Our findings highlight the importance of considering metacognitive constructs such as subjective knowledge to explain political behaviors and suggest that attitudinal congruence influences the way we perceive our own knowledge and information processing.

Illusion of knowledge in statistics among clinicians: evaluating the alignment between objective accuracy and subjective confidence, an online survey

Healthcare professionals' statistical illiteracy can impair medical decision quality and compromise patient safety. Previous studies have documented clinicians' insufficient proficiency in statistics and a tendency in overconfidence. However, an underexplored aspect is clinicians' awareness of their lack of statistical knowledge that precludes any corrective intervention attempt. Here, we investigated physicians', residents' and medical students' alignment between subjective confidence judgments and objective accuracy in basic medical statistics. We also examined how gender, profile of experience and practice of research activity affect this alignment, and the influence of problem framing (conditional probabilities, CP vs. natural frequencies, NF). Eight hundred ninety-eight clinicians completed an online survey assessing skill and confidence on three topics: vaccine efficacy, p value and diagnostic test results interpretation. Results evidenced an overall consistent poor proficiency in statistics often combined with high confidence, even in incorrect answers. We also demonstrate that despite overconfidence bias, clinicians show a degree of metacognitive sensitivity, as their confidence judgments discriminate between their correct and incorrect answers. Finally, we confirm the positive impact of the more intuitive NF framing on accuracy. Together, our results pave the way for the development of teaching recommendations and pedagogical interventions such as promoting metacognition on basic knowledge and statistical reasoning as well as the use of NF to tackle statistical illiteracy in the medical context.

Optimal policy for uncertainty estimation concurrent with decision making

Decision making often depends on vague information that leads to uncertainty, which is a quantity contingent not on choice but on probability distributions of sensory evidence and other cognitive variables. Uncertainty may be computed in parallel and interact with decision making. Here, we adapt the classic random-dot motion direction discrimination task to allow subjects to indicate their uncertainty without having to form a decision first. The subjects' choices and reaction times for perceptual decisions and uncertainty responses are measured, respectively. We then build a value-based model in which decisions are based on optimizing value computed from a drift-diffusion process. The model accounts for key features of subjects' behavior and the variation across the individuals. It explains how the addition of the uncertainty option affects perceptual decision making. Our work establishes a value-based theoretical framework for studying uncertainty and perceptual decisions that can be readily applied in future investigations of the underlying neural mechanism.

Neural activity tracking identity and confidence in social information

Humans learn about the environment either directly by interacting with it or indirectly by seeking information about it from social sources such as conspecifics. The degree of confidence in the information obtained through either route should determine the impact that it has on adapting and changing behaviour. We examined whether and how behavioural and neural computations differ during non-social learning as opposed to learning from social sources. Trial-wise confidence judgements about non-social and social information sources offered a window into this learning process. Despite matching exactly the statistical features of social and non-social conditions, confidence judgements were more accurate and less changeable when they were made about social as opposed to non-social information sources. In addition to subjective reports of confidence, differences were also apparent in the Bayesian estimates of participants' subjective beliefs. Univariate activity in dorsomedial prefrontal cortex and posterior temporoparietal junction more closely tracked confidence about social as opposed to non-social information sources. In addition, the multivariate patterns of activity in the same areas encoded identities of social information sources compared to non-social information sources.

Why and When Beliefs Change

Why people do or do not change their beliefs has been a long-standing puzzle. Sometimes people hold onto false beliefs despite ample contradictory evidence; sometimes they change their beliefs without sufficient reason. Here, we propose that the utility of a belief is derived from the potential outcomes associated with holding it. Outcomes can be internal (e.g., positive/negative feelings) or external (e.g., material gain/loss), and only some are dependent on belief accuracy. Belief change can then be understood as an economic transaction in which the multidimensional utility of the old belief is compared against that of the new belief. Change will occur when potential outcomes alter across attributes, for example because of changing environments or when certain outcomes are made more or less salient.

Generalized tendency to make extreme trait judgements from faces

People differ in their tendency to infer others' personalities and abilities from their faces. An extreme form of such face-based trait inference (FBTI) is problematic because of its unwarranted impact on real-world decision making. Evolutionary perspectives on FBTI suggest that its inter-individual variation would be trait-specific: e.g. those who make extreme face-based inferences about trustworthiness may not necessarily do so about dominance. However, there are several psychological variables that can increase the FBTI extremity across traits. Here, we show that there is a generalized individual tendency to make extreme FBTI across traits, in support of the latter view. We found that the degrees of extremity of face-based inferences about seven traits had high cross-trait correlations, constituting a general factor. This generalized FBTI extremity had good test-retest reliability and was neither an artefact of extreme nor socially desirable response biases. Moreover, it was positively associated with facial emotion recognition ability and tendencies to believe physiognomy and endorse stereotypes. Our results demonstrate that there are individuals who have a temporally stable disposition to draw extreme conclusions about various traits of others from facial appearance as well as their psychological characteristics.

Consensus Goals in the Field of Visual Metacognition

Despite the tangible progress in psychological and cognitive sciences over the last several years, these disciplines still trail other more mature sciences in identifying the most important questions that need to be solved. Reaching such consensus could lead to greater synergy across different laboratories, faster progress, and increased focus on solving important problems rather than pursuing isolated, niche efforts. Here, 26 researchers from the field of visual metacognition reached consensus on four long-term and two medium-term common goals. We describe the process that we followed, the goals themselves, and our plans for accomplishing these goals. If this effort proves successful within the next few years, such consensus building around common goals could be adopted more widely in psychological science.

The promise of a model-based psychiatry: building computational models of mental ill health

Computational models have great potential to revolutionise psychiatry research and clinical practice. These models are now used across multiple subfields, including computational psychiatry and precision psychiatry. Their goals vary from understanding mechanisms underlying disorders to deriving reliable classification and personalised predictions. Rapid growth of new tools and data sources (eg, digital data, gamification, and social media) requires an understanding of the constraints and advantages of different modelling approaches in psychiatry. In this Series paper, we take a critical look at the range of computational models that are used in psychiatry and evaluate their advantages and disadvantages for different purposes and data sources. We describe mechanism-driven and mechanism-agnostic computational models and discuss how interpretability of models is crucial for clinical translation. Based on these evaluations, we provide recommendations on how to build computational models that are clinically useful.

Two-Year-Olds' Eye Movements Reflect Confidence in Their Understanding of Words

We studied the fundamental issue of whether children evaluate the reliability of their language interpretation, that is, their confidence in understanding words. In two experiments, 2-year-olds (Experiment 1: N = 50; Experiment 2: N = 60) saw two objects and heard one of them being named; both objects were then hidden behind screens and children were asked to look toward the named object, which was eventually revealed. When children knew the label used, they showed increased postdecision persistence after a correct compared with an incorrect anticipatory look, a marker of confidence in word comprehension (Experiment 1). When interacting with an unreliable speaker, children showed accurate word comprehension but reduced confidence in the accuracy of their own choice, indicating that children's confidence estimates are influenced by social information (Experiment 2). Thus, by the age of 2 years, children can estimate their confidence during language comprehension, long before they can talk about their linguistic skills.

Controllability boosts neural and cognitive signatures of changes-of-mind in uncertain environments

In uncertain environments, seeking information about alternative choice options is essential for adaptive learning and decision-making. However, information seeking is usually confounded with changes-of-mind about the reliability of the preferred option. Here, we exploited the fact that information seeking requires control over which option to sample to isolate its behavioral and neurophysiological signatures. We found that changes-of-mind occurring with control require more evidence against the current option, are associated with reduced confidence, but are nevertheless more likely to be confirmed on the next decision. Multimodal neurophysiological recordings showed that these changes-of-mind are preceded by stronger activation of the dorsal attention network in magnetoencephalography, and followed by increased pupil-linked arousal during the presentation of decision outcomes. Together, these findings indicate that information seeking increases the saliency of evidence perceived as the direct consequence of one's own actions.

Psychiatrically relevant signatures of domain-general decision-making and metacognition in the general population

Human behaviours are guided by how confident we feel in our abilities. When confidence does not reflect objective performance, this can impact critical adaptive functions and impair life quality. Distorted decision-making and confidence have been associated with mental health problems. Here, utilising advances in computational and transdiagnostic psychiatry, we sought to map relationships between psychopathology and both decision-making and confidence in the general population across two online studies (N's = 344 and 473, respectively). The results revealed dissociable decision-making and confidence signatures related to distinct symptom dimensions. A dimension characterised by compulsivity and intrusive thoughts was found to be associated with reduced objective accuracy but, paradoxically, increased absolute confidence, whereas a dimension characterized by anxiety and depression was associated with systematically low confidence in the absence of impairments in objective accuracy. These relationships replicated across both studies and distinct cognitive domains (perception and general knowledge), suggesting that they are reliable and domain general. Additionally, whereas Big-5 personality traits also predicted objective task performance, only symptom dimensions related to subjective confidence. Domain-general signatures of decision-making and metacognition characterise distinct psychological dispositions and psychopathology in the general population and implicate confidence as a central component of mental health.

Belief traps: Tackling the inertia of harmful beliefs

Beliefs are a key element of healthy cognition. Yet overly rigid beliefs are the basis of societal problems including prejudices, psychiatric disorders, and conspiracy theories. Recent findings from neurobiology, psychiatry, and social sciences show how resilience of beliefs is boosted by stressful conditions. This implies the possibility of self-propelled societal deterioration where rigid beliefs harm the quality of personal and political decisions, evoking more-stressful conditions that further rigidify beliefs. Measures reducing social stress, including economic policies such as universal base income, may be the most effective ways to counteract this vicious cycle.

Beliefs can be highly resilient in the sense that they are not easily abandoned in the face of counterevidence. This has the advantage of guiding consistent behavior and judgments but may also have destructive consequences for individuals, nature, and society. For instance, pathological beliefs can sustain psychiatric disorders, the belief that rhinoceros horn is an aphrodisiac may drive a species extinct, beliefs about gender or race may fuel discrimination, and belief in conspiracy theories can undermine democracy. Here, we present a unifying framework of how self-amplifying feedbacks shape the inertia of beliefs on levels ranging from neuronal networks to social systems. Sustained exposure to counterevidence can destabilize rigid beliefs but requires organized rational override as in cognitive behavioral therapy for pathological beliefs or institutional control of discrimination to reduce racial biases. Black-and-white thinking is a major risk factor for the formation of resilient beliefs associated with psychiatric disorders as well as prejudices and conspiracy thinking. Such dichotomous thinking is characteristic of a lack of cognitive resources, which may be exacerbated by stress. This could help explain why conspiracy thinking and psychiatric disorders tend to peak during crises. A corollary is that addressing social factors such as poverty, social cleavage, and lack of education may be the most effective way to prevent the emergence of rigid beliefs, and thus of problems ranging from psychiatric disorders to prejudices, conspiracy theories, and posttruth politics.

The computational roots of positivity and confirmation biases in reinforcement learning

Humans do not integrate new information objectively: outcomes carrying a positive affective value and evidence confirming one's own prior belief are overweighed. Until recently, theoretical and empirical accounts of the positivity and confirmation biases assumed them to be specific to 'high-level' belief updates. We present evidence against this account. Learning rates in reinforcement learning (RL) tasks, estimated across different contexts and species, generally present the same characteristic asymmetry, suggesting that belief and value updating processes share key computational principles and distortions. This bias generates over-optimistic expectations about the probability of making the right choices and, consequently, generates over-optimistic reward expectations. We discuss the normative and neurobiological roots of these RL biases and their position within the greater picture of behavioral decision-making theories.

Divergent effects of absolute evidence magnitude on decision accuracy and confidence in perceptual judgements

Whether people change their mind after making a perceptual judgement may depend on how confident they are in their decision. Recently, it was shown that, when making perceptual judgements about stimuli containing high levels of 'absolute evidence' (i.e., the overall magnitude of sensory evidence across choice options), people make less accurate decisions and are also slower to change their mind and correct their mistakes. Here we report two studies that investigated whether high levels of absolute evidence also lead to increased decision confidence. We used a luminance judgment task in which participants decided which of two dynamic, flickering stimuli was brighter. After making a decision, participants rated their confidence. We manipulated relative evidence (i.e., the mean luminance difference between the two stimuli) and absolute evidence (i.e., the summed luminance of the two stimuli). In the first experiment, we found that higher absolute evidence was associated with decreased decision accuracy but increased decision confidence. In the second experiment, we additionally manipulated the degree of luminance variability to assess whether the observed effects were due to differences in perceived evidence variability. We replicated the results of the first experiment but did not find substantial effects of luminance variability on confidence ratings. Our findings support the view that decisions and confidence judgements are based on partly dissociable sources of information, and suggest that decisions initially made with higher confidence may be more resistant to subsequent changes of mind.

Humans actively sample evidence to support prior beliefs

No one likes to be wrong. Previous research has shown that participants may underweight information incompatible with previous choices, a phenomenon called confirmation bias. In this paper, we argue that a similar bias exists in the way information is actively sought. We investigate how choice influences information gathering using a perceptual choice task and find that participants sample more information from a previously chosen alternative. Furthermore, the higher the confidence in the initial choice, the more biased information sampling becomes. As a consequence, when faced with the possibility of revising an earlier decision, participants are more likely to stick with their original choice, even when incorrect. Critically, we show that agency controls this phenomenon. The effect disappears in a fixed sampling condition where presentation of evidence is controlled by the experimenter, suggesting that the way in which confirmatory evidence is acquired critically impacts the decision process. These results suggest active information acquisition plays a critical role in the propagation of strongly held beliefs over time.

Evidence integration and decision confidence are modulated by stimulus consistency

Evidence integration is a normative algorithm for choosing between alternatives with noisy evidence, which has been successful in accounting for vast amounts of behavioural and neural data. However, this mechanism has been challenged by non-integration heuristics, and tracking decision boundaries has proven elusive. Here we first show that the decision boundaries can be extracted using a model-free behavioural method termed decision classification boundary, which optimizes choice classification based on the accumulated evidence. Using this method, we provide direct support for evidence integration over non-integration heuristics, show that the decision boundaries collapse across time and identify an integration bias whereby incoming evidence is modulated based on its consistency with preceding information. This consistency bias, which is a form of pre-decision confirmation bias, was supported in four cross-domain experiments, showing that choice accuracy and decision confidence are modulated by stimulus consistency. Strikingly, despite its seeming sub-optimality, the consistency bias fosters performance by enhancing robustness to integration noise.

The Cognition/Metacognition Trade-Off

Integration to boundary is an optimal decision algorithm that accumulates evidence until the posterior reaches a decision boundary, resulting in the fastest decisions for a target accuracy. Here, we demonstrated that this advantage incurs a cost in metacognitive accuracy (confidence), generating a cognition/metacognition trade-off. Using computational modeling, we found that integration to a fixed boundary results in less variability in evidence integration and thus reduces metacognitive accuracy, compared with a collapsing-boundary or a random-timer strategy. We examined how decision strategy affects metacognitive accuracy in three cross-domain experiments, in which 102 university students completed a free-response session (evidence terminated by the participant's response) and an interrogation session (fixed number of evidence samples controlled by the experimenter). In both sessions, participants observed a sequence of evidence and reported their choice and confidence. As predicted, the interrogation protocol (preventing integration to boundary) enhanced metacognitive accuracy. We also found that in the free-response sessions, participants integrated evidence to a collapsing boundary-a strategy that achieves an efficient compromise between optimizing choice and metacognitive accuracy.

Distinct neurocomputational mechanisms support informational and socially normative conformity

A change of mind in response to social influence could be driven by informational conformity to increase accuracy, or by normative conformity to comply with social norms such as reciprocity. Disentangling the behavioural, cognitive, and neurobiological underpinnings of informational and normative conformity have proven elusive. Here, participants underwent fMRI while performing a perceptual task that involved both advice-taking and advice-giving to human and computer partners. The concurrent inclusion of 2 different social roles and 2 different social partners revealed distinct behavioural and neural markers for informational and normative conformity. Dorsal anterior cingulate cortex (dACC) BOLD response tracked informational conformity towards both human and computer but tracked normative conformity only when interacting with humans. A network of brain areas (dorsomedial prefrontal cortex (dmPFC) and temporoparietal junction (TPJ)) that tracked normative conformity increased their functional coupling with the dACC when interacting with humans. These findings enable differentiating the neural mechanisms by which different types of conformity shape social changes of mind.

Perceptual reality monitoring: Neural mechanisms dissociating imagination from reality

There is increasing evidence that imagination relies on similar neural mechanisms as externally triggered perception. This overlap presents a challenge for perceptual reality monitoring: deciding what is real and what is imagined. Here, we explore how perceptual reality monitoring might be implemented in the brain. We first describe sensory and cognitive factors that could dissociate imagery and perception and conclude that no single factor unambiguously signals whether an experience is internally or externally generated. We suggest that reality monitoring is implemented by higher-level cortical circuits that evaluate first-order sensory and cognitive factors to determine the source of sensory signals. According to this interpretation, perceptual reality monitoring shares core computations with metacognition. This multi-level architecture might explain several types of source confusion as well as dissociations between simply knowing whether something is real and actually experiencing it as real. We discuss avenues for future research to further our understanding of perceptual reality monitoring, an endeavour that has important implications for our understanding of clinical symptoms as well as general cognitive function.

Do propranolol and amisulpride modulate confidence in risk-taking?

Background: Making rational choices and being able to consciously reflect on the goodness of these choices is important for successfully navigating the world. Value-based decisions have been extensively studied, but we know little about the factors that influence our confidence in value-based choice. Particularly, we know very little about the neurotransmitters that may mediate these processes.  Methods: In this double-blind, placebo-controlled study design involving 61 healthy human subjects (30 female), we assessed the contributions of dopamine (400 mg amisulpride) and noradrenaline (40 mg propranolol) to value-based decision making and the subjective confidence therein in a monetary risky gambling task.  Results: We did not find any significant effect of either of the two pharmacological manipulations, neither on value-based decision making, nor on subjective confidence.   Conclusion: We discuss these (null) findings, and release all relevant data and code. This will allow researchers to further interrogate the data, to counteract publication biases in favour of significant findings, and to use our study as a source for balanced meta-analyses.

Confidence Modulates the Conformity Behavior of the Investors and Neural Responses of Social Influence in Crowdfunding

The decision about whether to invest can be affected by the choices or opinions of others known as a form of social influence. People make decisions with fluctuating confidence, which plays an important role in the decision process. However, it remains a fair amount of confusion regarding the effect of confidence on the social influence as well as the underlying neural mechanism. The current study applied a willingness-to-invest task with the event-related potentials method to examine the behavioral and neural manifestations of social influence and its interaction with confidence in the context of crowdfunding investment. The behavioral results demonstrate that the conformity tendency of the people increased when their willingness-to-invest deviated far from the group. Besides, when the people felt less confident about their initial judgment, they were more likely to follow the herd. In conjunction with the behavioral findings, the neural results of the social information processing indicate different susceptibilities to small and big conflicts between the own willingness of the people and the group, with small conflict evoked less negative feedback-related negativity (FRN) and more positive late positive potential (LPP). Moreover, confidence only modulated the later neural processing by eliciting larger LPP in the low confidence, implying more reliance on social information. These results corroborate previous findings regarding the conformity effect and its neural mechanism in investment decision and meanwhile extend the existing works of literature through providing behavioral and neural evidence to the effect of confidence on the social influence in the crowdfunding marketplace.

A confirmation bias in perceptual decision-making due to hierarchical approximate inference

Making good decisions requires updating beliefs according to new evidence. This is a dynamical process that is prone to biases: in some cases, beliefs become entrenched and resistant to new evidence (leading to primacy effects), while in other cases, beliefs fade over time and rely primarily on later evidence (leading to recency effects). How and why either type of bias dominates in a given context is an important open question. Here, we study this question in classic perceptual decision-making tasks, where, puzzlingly, previous empirical studies differ in the kinds of biases they observe, ranging from primacy to recency, despite seemingly equivalent tasks. We present a new model, based on hierarchical approximate inference and derived from normative principles, that not only explains both primacy and recency effects in existing studies, but also predicts how the type of bias should depend on the statistics of stimuli in a given task. We verify this prediction in a novel visual discrimination task with human observers, finding that each observer's temporal bias changed as the result of changing the key stimulus statistics identified by our model. The key dynamic that leads to a primacy bias in our model is an overweighting of new sensory information that agrees with the observer's existing belief-a type of 'confirmation bias'. By fitting an extended drift-diffusion model to our data we rule out an alternative explanation for primacy effects due to bounded integration. Taken together, our results resolve a major discrepancy among existing perceptual decision-making studies, and suggest that a key source of bias in human decision-making is approximate hierarchical inference.

Contested science: Individuals with higher metacognitive insight into interpretation of evidence are less likely to polarize

Societal polarization over contested science has increased in recent years. To explain this development, political, sociological, and psychological research has identified societal macro-phenomena as well as cognitive micro-level factors that explain how citizens reason about the science. Here we take a radically different perspective, and highlight the effects of metacognition: How citizens reason about their own reasoning. Leveraging methods from Signal Detection Theory, we investigated the importance of metacognitive insight for polarization for the heavily contested topic of climate change, and the less heavily contested topic of nanotechnology. We found that, for climate change (but not for nanotechnology), higher insight into the accuracy of own interpretations of the available scientific evidence related to a lower likelihood of polarization over the science. This finding held irrespective of the direction of the scientific evidence (endorsing or rejecting anthropogenicity of climate change). Furthermore, the polarizing effect of scientific evidence could be traced back to higher metacognitive insight fostering belief-updating in the direction of the evidence at the expense of own, prior beliefs. By demonstrating how metacognition links to polarization, the present research adds to our understanding of the drivers of societal polarization over science.

Joint contributions of metacognition and self-beliefs to uncertainty-guided checking behavior

Checking behavior is a natural and adaptive strategy for resolving uncertainty in everyday situations. Here, we aimed at investigating the psychological drivers of checking and its regulation by uncertainty, in non-clinical participants and controlled experimental settings. We found that the sensitivity of participants' explicit confidence judgments to actual performance (explicit metacognition) predicted the extent to which their checking strategy was regulated by uncertainty. Yet, a more implicit measure of metacognition (derived from asking participants to opt between trials) did not contribute to the regulation of checking behavior. Meanwhile, how participants scaled on questionnaires eliciting self-beliefs such as self-confidence and self-reported obsessive-compulsive symptoms also predicted participants' uncertainty-guided checking tendencies. Altogether, these findings demonstrate that checking behavior is likely the outcome of a core explicit metacognitive process operating at the scale of single decisions, while remaining influenced by general self-beliefs. Our findings are thus consistent with two mechanisms (micro vs. macro) through which this otherwise adaptive behavior could go awry in certain psychiatric disorders such as obsessive-compulsive disorder.

I know better! Emerging metacognition allows adolescents to ignore false advice

Adolescents aspire for independence. Successful independence means knowing when to rely on one's own knowledge and when to listen to others. A critical prerequisite thus is a well-developed metacognitive ability to accurately assess the quality of one's own knowledge. Little is known about whether the strive to become an independent decision maker in adolescence is underpinned by the necessary metacognitive skills. Here, we demonstrate that metacognition matures from childhood to adolescence (N = 107) and that this process coincides with greater independent decision-making. We show that adolescents, in contrast to children, take on others' advice less often, but only when the advice is misleading. Finally, we demonstrate that adolescents' reduced reliance on others' advice is explained by their increased metacognitive skills, suggesting that a developing ability to introspect may support independent decision-making in adolescence.

Understanding neural signals of post-decisional performance monitoring: An integrative review

Performance monitoring is a key cognitive function, allowing to detect mistakes and adapt future behavior. Post-decisional neural signals have been identified that are sensitive to decision accuracy, decision confidence and subsequent adaptation. Here, we review recent work that supports an understanding of late error/confidence signals in terms of the computational process of post-decisional evidence accumulation. We argue that the error positivity, a positive-going centro-parietal potential measured through scalp electrophysiology, reflects the post-decisional evidence accumulation process itself, which follows a boundary crossing event corresponding to initial decision commitment. This proposal provides a powerful explanation for both the morphological characteristics of the signal and its relation to various expressions of performance monitoring. Moreover, it suggests that the error positivity -a signal with thus far unique properties in cognitive neuroscience - can be leveraged to furnish key new insights into the inputs to, adaptation, and consequences of the post-decisional accumulation process.