A Bayesian model of the jumping-to-conclusions bias and its relationship to psychopathology

The mechanisms by which delusion and anxiety affect the tendency to make hasty decisions (Jumping-to-Conclusions bias) remain unclear. This paper proposes a Bayesian computational model that explores the assignment of evidence weights as a potential explanation of the Jumping-to-Conclusions bias using the Beads Task. We also investigate the Beads Task as a repeated measure by varying the key aspects of the paradigm. The Bayesian model estimations from two online studies showed that higher delusional ideation promoted reduced belief updating but the impact of general and social anxiety on evidence weighting was inconsistent. The altered evidence weighting as a result of a psychopathological trait appeared insufficient in contributing to the Jumping-to-Conclusions bias. Variations in Beads Task aspects significantly affected subjective certainty at the point of decisions but not the number of draws to decisions. Repetitions of the Beads Task are feasible if one assesses the Jumping-to-Conclusions bias using number of draws to decisions.

Thinking about Believing: Can Metacognitive Reflection Encourage Belief Updating?

People often cling to their beliefs even in the face of counterevidence. The current study explored metacognitive reflection as a potential driver for belief updating. In a randomized controlled experiment (n = 155), participants rated their degree of agreement with a statement regarding genetic modification in humans. Following this, participants were presented with a passage containing an argument counter to their indicated belief. Participants in the metacognition condition were asked to deeply reflect on the ways in which the passage was similar to or different from their current beliefs. Participants in the control condition were asked to engage in more shallow reflection on the composition of the passage. After reflecting on the counterevidence, participants were asked to again rate their agreement with the statement regarding human gene modification. Both groups updated their initial beliefs to be more consistent with the presented counterevidence. Although greater belief updating was observed in those who metacognitively reflected on the passage, this effect did not reach significance (p = .055). These findings suggest that reflecting on counterevidence has the potential to encourage belief updating, regardless of whether that reflection is metacognitive in nature, and provide promise for future work investigating the role of metacognition in belief updating.

Does disconfirmatory evidence shape safety-and danger-related beliefs of trauma-exposed individuals?

Recent accounts of predictive processing in posttraumatic stress disorder (PTSD) suggest that trauma-exposed individuals struggle to update trauma-related hypotheses predicting danger, which may be involved in the etiology and maintenance of this disorder. Initial research supports this account, documenting an association between trauma-exposure, impaired expectation updating, and PTSD symptoms. Yet, no study to date has examined biased belief updating in PTSD using a scenario-based approach.Objective: Here, we examined the predictive processing account among trauma-exposed and non-trauma-exposed individuals using a modified Trauma-Related version of the Bias Against Disconfirmatory Evidence task.Method: The task presents both danger-and safety-related scenarios highly relevant for trauma-exposed individuals. For each scenario, participants viewed several explanations and rated their plausibility. Their ability to update their initial interpretation following new-contradictory information was assessed.Results: Preregistered analyses did not reveal any significant findings. Based on indications that our sample may not have been sufficiently powered, we conducted exploratory analyses in an extended sample of participants. These analyses yielded a significant association between reduced belief updating and PTSD symptoms which was evident for disconfirming both safety and danger scenarios. However, the effect sizes we found were in the small-to-medium range.Conclusion: Although preliminary, our current findings support initial evidence that individuals with higher PTSD symptoms show a higher resistance to update their beliefs upon new disconfirmatory evidence. Our results should be interpreted cautiously in light of the extended sample and the limitations of the current study.

Belief updating when confronted with scientific evidence: Examining the role of trust in science

In one exploratory study (N = 985) and one preregistered study (N = 1100), we investigated whether trust in science influences belief change on a medico-scientific issue when laypersons are confronted with scientific evidence. Moreover, we tested whether individuals with high trust in science trust science "blindly," meaning that their trust in a scientific claim's source prevents them from adequately evaluating the claim itself. Participants read eight fictitious studies on the efficacy of acupuncture, which were experimentally manipulated regarding direction (evidence favoring acupuncture vs diverging evidence) and quality (high vs low; only Study 2). Acupuncture-related beliefs were measured before and after reading. Moderator and mediator analyses showed that the magnitude of belief change indeed depends on trust in science. Furthermore, we found that people with high trust in science are better able to evaluate the quality of scientific studies, which, in turn, protects them from being influenced by low-quality evidence.

Can Invalid Information Be Ignored When It Is Detected?

With the rapid spread of information via social media, individuals are prone to misinformation exposure that they may utilize when forming beliefs. Over five experiments (total N = 815 adults, recruited through Amazon Mechanical Turk in the United States), we investigated whether people could ignore quantitative information when they judged for themselves that it was misreported. Participants recruited online viewed sets of values sampled from Gaussian distributions to estimate the underlying means. They attempted to ignore invalid information, which were outlier values inserted into the value sequences. Results indicated participants were able to detect outliers. Nevertheless, participants' estimates were still biased in the direction of the outlier, even when they were most certain that they detected invalid information. The addition of visual warning cues and different task scenarios did not fully eliminate systematic over- and underestimation. These findings suggest that individuals may incorporate invalid information they meant to ignore when forming beliefs.

Motivated Cognition in Cooperation

Successful cooperation is tightly linked to individuals' beliefs about their interaction partners, the decision setting, and existing norms, perceptions, and values. This article reviews and integrates findings from judgment and decision-making, social and cognitive psychology, political science, and economics, developing a systematic overview of the mechanisms underlying motivated cognition in cooperation. We elaborate on how theories and concepts related to motivated cognition developed in various disciplines define the concept and describe its functionality. We explain why beliefs play such an essential role in cooperation, how they can be distorted, and how this fosters or harms cooperation. We also highlight how individual differences and situational factors change the propensity to engage in motivated cognition. In the form of a construct map, we provide a visualization of the theoretical and empirical knowledge structure regarding the role of motivated cognition, including its many interdependencies, feedback loops, and moderating influences. We conclude with a brief suggestion for a future research agenda based on this compiled evidence.

Intellectual humility as a tool to combat false beliefs: An individual-based approach to belief revision

False beliefs pose significant societal threats, including health risks, political polarization and even violence. In two studies (N = 884) we explored the efficacy of an individual-based approach to correcting false beliefs. We examined whether the character virtue of intellectual humility (IH)-an appreciation of one's intellectual boundaries-encourages revising one's false beliefs in response to counter-information. Our research produced encouraging but also mixed findings. Among participants who held false beliefs about the risks of vaccines (Study 1) and the 2020 US Election being rigged (Study 2), those with higher IH explored more information opposing these false beliefs. This exploration of opposing information, in turn, predicted updating away from these inaccurate health and political beliefs. IH did not directly predict updating away from false beliefs, however, suggesting that this effect-if it exists-may not be particularly powerful. Taken together, these results provide moderate support for IH as a character trait that can foster belief revision but, simultaneously, suggest that alternate pathways to combat false beliefs and misinformation may be preferred.

Are depressive symptoms linked to a reduced pupillary response to novel positive information?-An eye tracking proof-of-concept study

Introduction

Depressive symptoms have been linked to difficulties in revising established negative beliefs in response to novel positive information. Recent predictive processing accounts have suggested that this bias in belief updating may be related to a blunted processing of positive prediction errors at the neural level. In this proof-of-concept study, pupil dilation in response to unexpected positive emotional information was examined as a psychophysiological marker of an attenuated processing of positive prediction errors associated with depressive symptoms.

Methods

Participants (N = 34) completed a modified version of the emotional Bias Against Disconfirmatory Evidence (BADE) task in which scenarios initially suggest negative interpretations that are later either confirmed or disconfirmed by additional information. Pupil dilation in response to the confirmatory and disconfirmatory information was recorded.

Results

Behavioral results showed that depressive symptoms were related to difficulties in revising negative interpretations despite disconfirmatory positive information. The eye tracking results pointed to a reduced pupil response to unexpected positive information among people with elevated depressive symptoms.

Discussion

Altogether, the present study demonstrates that the adapted emotional BADE task can be appropriate for examining psychophysiological aspects such as changes in pupil size along with behavioral responses. Furthermore, the results suggest that depression may be characterized by deviations in both behavioral (i.e., reduced updating of negative beliefs) and psychophysiological (i.e., decreased pupil dilation) responses to unexpected positive information. Future work should focus on a larger sample including clinically depressed patients to further explore these findings.

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.

There is no belief update bias for neutral events: failure to replicate Burton et al. (2022)

In a recent paper, Burton et al. claim that individuals update beliefs to a greater extent when learning an event is less likely compared to more likely than expected. Here, we investigate Burton's et al.'s, findings. First, we show how Burton et al.'s data do not in fact support a belief update bias for neutral events. Next, in an attempt to replicate their findings, we collect a new data set employing the original belief update task design, but with neutral events. A belief update bias for neutral events is not observed. Finally, we highlight the statistical errors and confounds in Burton et al.'s design and analysis. This includes mis-specifying a reinforcement learning approach to model the data and failing to follow standard computational model fitting sanity checks such as parameter recovery, model comparison and out of sample prediction. Together, the results find little evidence for biased updating for neutral events.

Resilience of primal world beliefs to the initial shock of the COVID-19 pandemic

INTRODUCTION

People hold general beliefs about the world called primals (e.g., the world is Safe, Intentional), which are strongly linked to individual differences in personality, behavior, and mental health. How such beliefs form or change across the lifespan is largely unknown, although theory suggests that beliefs become more negative after disruptive events. The COVID-19 pandemic provided an opportunity to test whether dramatic world changes and personal adversity affect beliefs.

METHOD

In a longitudinal, quasi-experimental, pre-registered design, 529 US participants (51% female, 76% White) provided ratings of primals before and several months after pandemic onset, and information about personal adversity (e.g., losing family, financial hardship). Data were compared to 398 participants without experience of the pandemic.

RESULTS

The average person in our sample showed no change in 23 of the 26 primals, including Safe, in response to the early pandemic, and only saw the world as slightly less Alive, Interactive, and Acceptable. Higher adversity, however, was associated with slight declines in some beliefs. One limitation is that participants were exclusively American.

CONCLUSION

Primals were remarkably stable during the initial shock wrought by a once-in-a-century pandemic, supporting a view of primals as stable lenses through which people interpret the world.

Computational mechanisms of belief updating in relation to psychotic-like experiences

Introduction

Psychotic-like experiences (PLEs) may occur due to changes in weighting prior beliefs and new evidence in the belief updating process. It is still unclear whether the acquisition or integration of stable beliefs is altered, and whether such alteration depends on the level of environmental and belief precision, which reflects the associated uncertainty. This motivated us to investigate uncertainty-related dynamics of belief updating in relation to PLEs using an online study design.

Methods

We selected a sample (n = 300) of participants who performed a belief updating task with sudden change points and provided self-report questionnaires for PLEs. The task required participants to observe bags dropping from a hidden helicopter, infer its position, and dynamically update their belief about the helicopter's position. Participants could optimize performance by adjusting learning rates according to inferred belief uncertainty (inverse prior precision) and the probability of environmental change points. We used a normative learning model to examine the relationship between adherence to specific model parameters and PLEs.

Results

PLEs were linked to lower accuracy in tracking the outcome (helicopter location) (β = 0.26 ± 0.11, p = 0.018) and to a smaller increase of belief precision across observations after a change point (β = -0.003 ± 0.0007, p < 0.001). PLEs were related to slower belief updating when participants encountered large prediction errors (β = -0.03 ± 0.009, p = 0.001). Computational modeling suggested that PLEs were associated with reduced overall belief updating in response to prediction errors (βPE = -1.00 ± 0.45, p = 0.028) and reduced modulation of updating at inferred environmental change points (βCPP = -0.84 ± 0.38, p = 0.023).

Discussion

We conclude that PLEs are associated with altered dynamics of belief updating. These findings support the idea that the process of balancing prior belief and new evidence, as a function of environmental uncertainty, is altered in PLEs, which may contribute to the development of delusions. Specifically, slower learning after large prediction errors in people with high PLEs may result in rigid beliefs. Disregarding environmental change points may limit the flexibility to establish new beliefs in the face of contradictory evidence. The present study fosters a deeper understanding of inferential belief updating mechanisms underlying PLEs.

Correcting COVID-19 vaccine misinformation in 10 countries

What can be done to reduce misperceptions about COVID-19 vaccines? We present results from experiments conducted simultaneously on YouGov samples in 10 countries (N = 10 600), which reveal that factual corrections consistently reduce false beliefs about vaccines. With results from these 10 countries, we find that exposure to corrections increases belief accuracy by 0.16 on a 4-point scale, while exposure to misinformation decreases belief accuracy by 0.09 on the same scale. We are unable to find evidence that either misinformation or factual corrections affect intent to vaccinate or vaccine attitudes. Our findings on effect duration are less conclusive; when we recontacted participants two weeks later, we observed 39% of the initial accuracy increase, yet this result narrowly misses conventional thresholds of statistical significance (p = 0.06). Taken together, our results illustrate both the possibilities and limitations of factual corrections. Evidence from 10 highly diverse populations shows that exposure to factual information reduces belief in falsehoods about vaccines, but has minimal influence on subsequent behaviours and attitudes.

Updating Contextual Sensory Expectations for Adaptive Behavior

The brain has the extraordinary capacity to construct predictive models of the environment by internalizing statistical regularities in the sensory inputs. The resulting sensory expectations shape how we perceive and react to the world; at the neural level, this relates to decreased neural responses to expected than unexpected stimuli ("expectation suppression"). Crucially, expectations may need revision as context changes. However, existing research has often neglected this issue. Further, it is unclear whether contextual revisions apply selectively to expectations relevant to the task at hand, hence serving adaptive behavior. The present fMRI study examined how contextual visual expectations spread throughout the cortical hierarchy as we update our beliefs. We created a volatile environment: two alternating contexts contained different sequences of object images, thereby producing context-dependent expectations that needed revision when the context changed. Human participants of both sexes attended a training session before scanning to learn the contextual sequences. The fMRI experiment then tested for the emergence of contextual expectation suppression in two separate tasks, respectively, with task-relevant and task-irrelevant expectations. Effects of contextual expectation emerged progressively across the cortical hierarchy as participants attuned themselves to the context: expectation suppression appeared first in the insula, inferior frontal gyrus, and posterior parietal cortex, followed by the ventral visual stream, up to early visual cortex. This applied selectively to task-relevant expectations. Together, the present results suggest that an insular and frontoparietal executive control network may guide the flexible deployment of contextual sensory expectations for adaptive behavior in our complex and dynamic world.SIGNIFICANCE STATEMENT The world is structured by statistical regularities, which we use to predict the future. This is often accompanied by suppressed neural responses to expected compared with unexpected events ("expectation suppression"). Crucially, the world is also highly volatile and context-dependent: expected events may become unexpected when the context changes, thus raising the crucial need for belief updating. However, this issue has generally been neglected. By setting up a volatile environment, we show that expectation suppression emerges first in executive control regions, followed by relevant sensory areas, only when observers use their expectations to optimize behavior. This provides surprising yet clear evidence on how the brain controls the updating of sensory expectations for adaptive behavior in our ever-changing world.

Authority Brings Responsibility: Feedback from Experts Promotes an Overweighting of Health-Related Pseudoscientific Beliefs

The popularity and spread of health-related pseudoscientific practices is a worldwide problem. Despite being counteracted by competent agents of our societies, their prevalence and spread continue to grow. Current research has focused on identifying which characteristics make us more likely to hold pseudoscientific beliefs. However, how we hold these beliefs despite all the available information against them is a question that remains unanswered. Here, we aimed to assess if the development of health-related pseudoscientific beliefs could be driven by a positive bias in belief updating. Additionally, we aimed to explore whether this bias could be exacerbated, depending on source credibility. In this study, participants (N = 116) underwent a belief updating task where they offered their agreement with various health-related pseudoscientific statements before and after receiving supporting and discrediting feedback from (a) experts (doctors), (b) peers, or (c) a random number generator. Our results suggest that when receiving feedback from experts (but not from peers or random feedback), the participants preferentially integrated supporting information relative to discrediting information about health-related pseudoscience. We discuss the implications of this biased belief updating pattern on health-related pseudoscientific research and suggest new strategies for intervention focused on increasing awareness, training, and consensus among healthcare practitioners.

How childhood maltreatment alters perception and cognition - the predictive processing account of borderline personality disorder

Borderline personality disorder (BPD) is a severe mental disorder, comprised of heterogeneous psychological and neurobiological pathologies. Here, we propose a predictive processing (PP) account of BPD to integrate these seemingly unrelated pathologies. In particular, we argue that the experience of childhood maltreatment, which is highly prevalent in BPD, leaves a developmental legacy with two facets: first, a coarse-grained, alexithymic model of self and others - leading to a rigidity and inflexibility concerning beliefs about self and others. Second, this developmental legacy leads to a loss of confidence or precision afforded beliefs about the consequences of social behavior. This results in an over reliance on sensory evidence and social feedback, with concomitant lability, impulsivity and hypersensitivity. In terms of PP, people with BPD show a distorted belief updating in response to new information with two opposing manifestations: rapid changes in beliefs and a lack of belief updating despite disconfirmatory evidence. This account of distorted information processing has the potential to explain both the instability (of affect, self-image, and interpersonal relationships) and the rigidity (of beliefs about self and others) which is typical of BPD. At the neurobiological level, we propose that enhanced levels of dopamine are associated with the increased integration of negative social feedback, and we also discuss the hypothesis of an impaired inhibitory control of the prefrontal cortex in the processing of negative social information. Our account may provide a new understanding not only of the clinical aspects of BPD, but also a unifying theory of the corresponding neurobiological pathologies. We conclude by outlining some directions for future research on the behavioral, neurobiological, and computational underpinnings of this model, and point to some clinical implications of it.

Testing Bayesian models of belief updating in the context of depressive symptomatology

OBJECTIVES

Predictive processing approaches to belief updating in depression propose that depression is related to more negative and more precise priors. Also, belief updating is assumed be negatively biased in comparison to normative Bayesian updating. There is a lack of efficient methods to mathematically model belief updating in depression.

METHODS

We validated a novel performance belief updating paradigm in a nonclinical sample (N = 133). Participants repeatedly participated in a non-self-related emotion recognition task and received false feedback. Effects of the feedback manipulation and differences in depressive symptoms on belief updating were analysed in Bayesian multilevel analyses.

RESULTS

Beliefs were successfully manipulated through the feedback provided. Depressive symptoms were associated with more negative updating than normative Bayesian updating but results were influenced by few cases. No evidence of biased change in beliefs or overly precise priors was found. Depressive symptoms were associated with more negative updating of generalised performance beliefs.

CONCLUSIONS

There was cautious support for negatively biased belief updating associated with depressive symptoms, especially for generalised beliefs. The content of the task may not be self-relevant enough to cause strong biases. Further explication of Bayesian models of depression and replication in clinical samples is needed.

Psychological inoculation can reduce susceptibility to misinformation in large rational agent networks

The unchecked spread of misinformation is recognized as an increasing threat to public, scientific and democratic health. Online networks are a contributing cause of this spread, with echo chambers and polarization indicative of the interplay between the search behaviours of users and reinforcement processes within the system they inhabit. Recent empirical work has focused on interventions aimed at inoculating people against misinformation, yielding success on the individual level. However, given the evolving, dynamic information context of online networks, important questions remain regarding how such inoculation interventions interact with network systems. Here we use an agent-based model of a social network populated with belief-updating users. We find that although equally rational agents may be assisted by inoculation interventions to reject misinformation, even among such agents, intervention efficacy is temporally sensitive. We find that as beliefs disseminate, users form self-reinforcing echo chambers, leading to belief consolidation-irrespective of their veracity. Interrupting this process requires 'front-loading' of inoculation interventions by targeting critical thresholds of network users before consolidation occurs. We further demonstrate the value of harnessing tipping point dynamics for herd immunity effects, and note that inoculation processes do not necessarily lead to increased rates of 'false-positive' rejections of truthful communications.

Social influence in adolescence as a double-edged sword

Social learning is fundamental to human development, helping individuals adapt to changing circumstances and cooperate in groups. During the formative years of adolescence, the social environment shapes people's socio-cognitive skills needed in adulthood. Although peer influence among adolescents is traditionally associated with risky and unruly conduct, with long-term negative effects on educational, economic and health outcomes, recent findings suggest that peers may also have a positive impact. Here, we present a series of experiments with 10-20-year-olds (n = 146) showing that positive and negative peer effects reflect a domain-general factor of social information use which declines during adolescence. Exposure to disobedient peers provoked rule breaking, and selfish peers reduced prosocial behaviour, particularly in early adolescence. However, compliant peers also promoted rule compliance and fair peers increased prosociality. A belief formation task further revealed that younger adolescents tend to assimilate social information, while older adolescents prioritize personal views. Our results highlight early adolescence as a key window for peer-based interventions to improve developmental trajectories.

Increased Belief Instability in Psychotic Disorders Predicts Treatment Response to Metacognitive Training

BACKGROUND AND HYPOTHESIS

In a complex world, gathering information and adjusting our beliefs about the world is of paramount importance. The literature suggests that patients with psychotic disorders display a tendency to draw early conclusions based on limited evidence, referred to as the jumping-to-conclusions bias, but few studies have examined the computational mechanisms underlying this and related belief-updating biases. Here, we employ a computational approach to understand the relationship between jumping-to-conclusions, psychotic disorders, and delusions.

STUDY DESIGN

We modeled probabilistic reasoning of 261 patients with psychotic disorders and 56 healthy controls during an information sampling task-the fish task-with the Hierarchical Gaussian Filter. Subsequently, we examined the clinical utility of this computational approach by testing whether computational parameters, obtained from fitting the model to each individual's behavior, could predict treatment response to Metacognitive Training using machine learning.

STUDY RESULTS

We observed differences in probabilistic reasoning between patients with psychotic disorders and healthy controls, participants with and without jumping-to-conclusions bias, but not between patients with low and high current delusions. The computational analysis suggested that belief instability was increased in patients with psychotic disorders. Jumping-to-conclusions was associated with both increased belief instability and greater prior uncertainty. Lastly, belief instability predicted treatment response to Metacognitive Training at the individual level.

CONCLUSIONS

Our results point towards increased belief instability as a key computational mechanism underlying probabilistic reasoning in psychotic disorders. We provide a proof-of-concept that this computational approach may be useful to help identify suitable treatments for individual patients with psychotic disorders.

Is depression associated with reduced optimistic belief updating?

When asked to evaluate their probability of experiencing a negative life event, healthy individuals update their beliefs more following good news than bad. This is referred to as optimistic belief updating. By contrast, individuals with depression update their beliefs by a similar amount, showing reduced optimism. We conducted the first independent replication of this effect and extended this work to examine whether reduced optimistic belief updating in depression also occurs for positive life events. Replicating previous research, healthy and depression groups differed in belief updating for negative events (β = 0.71, 95% CI: 0.24, 1.18). Whereas healthy participants updated their beliefs more following good news than bad, individuals experiencing depression lacked this bias. However, our findings for positive events were inconclusive. While we did not find statistical evidence that patterns of belief updating between groups varied by valence (β = -0.51, 95% CI: -1.16, 0.15), mean update scores suggested that both groups showed largely similar updating for positive life events. Our results add confidence to previous findings that depression is characterized by negative future expectations maintained by reduced updating in response to good news. However, further research is required to understand the specificity of this to negative events, and into refining methods for quantifying belief updating in clinical and non-clinical research.

Models of Dynamic Belief Updating in Psychosis-A Review Across Different Computational Approaches

To understand the dysfunctional mechanisms underlying maladaptive reasoning of psychosis, computational models of decision making have widely been applied over the past decade. Thereby, a particular focus has been on the degree to which beliefs are updated based on new evidence, expressed by the learning rate in computational models. Higher order beliefs about the stability of the environment can determine the attribution of meaningfulness to events that deviate from existing beliefs by interpreting these either as noise or as true systematic changes (volatility). Both, the inappropriate downplaying of important changes as noise (belief update too low) as well as the overly flexible adaptation to random events (belief update too high) were theoretically and empirically linked to symptoms of psychosis. Whereas models with fixed learning rates fail to adjust learning in reaction to dynamic changes, increasingly complex learning models have been adopted in samples with clinical and subclinical psychosis lately. These ranged from advanced reinforcement learning models, over fully Bayesian belief updating models to approximations of fully Bayesian models with hierarchical learning or change point detection algorithms. It remains difficult to draw comparisons across findings of learning alterations in psychosis modeled by different approaches e.g., the Hierarchical Gaussian Filter and change point detection. Therefore, this review aims to summarize and compare computational definitions and findings of dynamic belief updating without perceptual ambiguity in (sub)clinical psychosis across these different mathematical approaches. There was strong heterogeneity in tasks and samples. Overall, individuals with schizophrenia and delusion-proneness showed lower behavioral performance linked to failed differentiation between uninformative noise and environmental change. This was indicated by increased belief updating and an overestimation of volatility, which was associated with cognitive deficits. Correlational evidence for computational mechanisms and positive symptoms is still sparse and might diverge from the group finding of instable beliefs. Based on the reviewed studies, we highlight some aspects to be considered to advance the field with regard to task design, modeling approach, and inclusion of participants across the psychosis spectrum. Taken together, our review shows that computational psychiatry offers powerful tools to advance our mechanistic insights into the cognitive anatomy of psychotic experiences.

Optimism where there is none: Asymmetric belief updating observed with valence-neutral life events

How people update their beliefs when faced with new information is integral to everyday life. A sizeable body of literature suggests that people's belief updating is optimistically biased, such that their beliefs are updated more in response to good news than bad news. However, recent research demonstrates that findings previously interpreted as evidence of optimistic belief updating may be the result of flaws in experimental design, rather than motivated reasoning. In light of this controversy, we conduct three pre-registered variations of the standard belief updating paradigm (combined N = 300) in which we test for asymmetric belief updating with neutral, non-valenced stimuli using analytic approaches found in previous research. We find evidence of seemingly biased belief updating with neutral stimuli - results that cannot be attributed to a motivational, valence-based, optimism account - and further show that there is uninterpretable variability across samples and analytic techniques. Jointly, these results serve to highlight the methodological flaws in current optimistic belief updating research.

All or nothing belief updating in patients with schizophrenia reduces precision and flexibility of beliefs

Schizophrenia is characterized by abnormal perceptions and beliefs, but the computational mechanisms through which these abnormalities emerge remain unclear. One prominent hypothesis asserts that such abnormalities result from overly precise representations of prior knowledge, which in turn lead beliefs to become insensitive to feedback. In contrast, another prominent hypothesis asserts that such abnormalities result from a tendency to interpret prediction errors as indicating meaningful change, leading to the assignment of aberrant salience to noisy or misleading information. Here we examine behaviour of patients and control subjects in a behavioural paradigm capable of adjudicating between these competing hypotheses and characterizing belief updates directly on individual trials. We show that patients are more prone to completely ignoring new information and perseverating on previous responses, but when they do update, tend to do so completely. This updating strategy limits the integration of information over time, reducing both the flexibility and precision of beliefs and provides a potential explanation for how patients could simultaneously show over-sensitivity and under-sensitivity to feedback in different paradigms.

Optimistic amnesia: how online and offline processing shape belief updating and memory biases in immediate and long-term optimism biases

When people are confronted with feedback that counters their prior beliefs, they preferentially rely on desirable rather than undesirable feedback in belief updating, i.e. an optimism bias. In two pre-registered EEG studies employing an adverse life event probability estimation task, we investigated the neurocognitive processes that support the formation and the change of optimism biases in immediate and 24 h delayed tests. We found that optimistic belief updating biases not only emerged immediately but also became significantly larger after 24 h, suggesting an active role of valence-dependent offline consolidation processes in the change of optimism biases. Participants also showed optimistic memory biases: they were less accurate in remembering undesirable than desirable feedback probabilities, with inferior memories of undesirable feedback associated with lower belief updating in the delayed test. Examining event-related brain potentials (ERPs) revealed that desirability of feedback biased initial encoding: desirable feedback elicited larger P300s than undesirable feedback, with larger P300 amplitudes predicting both higher belief updating and memory accuracies. These results suggest that desirability of feedback could bias both online and offline memory-related processes such as encoding and consolidation, with both processes contributing to the formation and change of optimism biases.

Confirmation bias is adaptive when coupled with efficient metacognition

Biases in the consideration of evidence can reduce the chances of consensus between people with different viewpoints. While such altered information processing typically leads to detrimental performance in laboratory tasks, the ubiquitous nature of confirmation bias makes it unlikely that selective information processing is universally harmful. Here, we suggest that confirmation bias is adaptive to the extent that agents have good metacognition, allowing them to downweight contradictory information when correct but still able to seek new information when they realize they are wrong. Using simulation-based modelling, we explore how the adaptiveness of holding a confirmation bias depends on such metacognitive insight. We find that the behavioural consequences of selective information processing are systematically affected by agents' introspective abilities. Strikingly, we find that selective information processing can even improve decision-making when compared with unbiased evidence accumulation, as long as it is accompanied by good metacognition. These results further suggest that interventions which boost people's metacognition might be efficient in alleviating the negative effects of selective information processing on issues such as political polarization.

This article is part of the theme issue ‘The political brain: neurocognitive and computational mechanisms’.

Causal Role of the Dorsolateral Prefrontal Cortex in Belief Updating under Uncertainty

Adaptive performance in uncertain environments depends on the ability to continuously update internal beliefs about environmental states. Recent correlative evidence suggests that a frontoparietal network including the dorsolateral prefrontal cortex (dlPFC) supports belief updating under uncertainty, but whether the dlPFC serves a "causal" role in this process is currently not clear. To elucidate its contribution, we leveraged transcranial direct current stimulation (tDCS) over the right dlPFC, while 91 participants performed an incentivized belief-updating task. Participants also underwent a psychosocial stress or control manipulation to investigate the role of stress, which is known to modulate dlPFC functioning. We observed enhanced monetary value updating after anodal tDCS when it was normatively expected from a Bayesian perspective. A model-based analysis indicates that this effect was driven by belief updating. However, we also observed enhanced non-normative value updating, which might have been driven instead by expectancy violation. Enhanced normative and non-normative value updating reflected increased vs. decreased Bayesian rationality, respectively. Furthermore, cortisol increases were associated with enhanced positive, but not with negative, value updating. The present study thereby sheds light on the causal role of the right dlPFC in the remarkable human ability to navigate uncertain environments by continuously updating prior knowledge following new evidence.

Paranoia as a deficit in non-social belief updating

Paranoia is the belief that harm is intended by others. It may arise from selective pressures to infer and avoid social threats, particularly in ambiguous or changing circumstances. We propose that uncertainty may be sufficient to elicit learning differences in paranoid individuals, without social threat. We used reversal learning behavior and computational modeling to estimate belief updating across individuals with and without mental illness, online participants, and rats chronically exposed to methamphetamine, an elicitor of paranoia in humans. Paranoia is associated with a stronger prior on volatility, accompanied by elevated sensitivity to perceived changes in the task environment. Methamphetamine exposure in rats recapitulates this impaired uncertainty-driven belief updating and rigid anticipation of a volatile environment. Our work provides evidence of fundamental, domain-general learning differences in paranoid individuals. This paradigm enables further assessment of the interplay between uncertainty and belief-updating across individuals and species.

Everyone has had fleeting concerns that others might be against them at some point in their lives. Sometimes these concerns can escalate into paranoia and become debilitating. Paranoia is a common symptom in serious mental illnesses like schizophrenia. It can cause extreme distress and is linked with an increased risk of violence towards oneself or others. Understanding what happens in the brains of people experiencing paranoia might lead to better ways to treat or manage it.

Some experts argue that paranoia is caused by errors in the way people assess social situations. An alternative idea is that paranoia stems from the way the brain forms and updates beliefs about the world. Now, Reed et al. show that both people with paranoia and rats exposed to a paranoia-inducing substance expect the world will change frequently, change their minds often, and have a harder time learning in response to changing circumstances.

In the experiments, human volunteers with and without psychiatric disorders played a game where the best choices change. Then, the participants completed a survey to assess their level of paranoia. People with higher levels of paranoia predicted more changes would occur and made less predictable choices. In a second set of experiments, rats were put in a cage with three holes where they sometimes received sugar rewards. Some of the rats received methamphetamine, a drug that causes paranoia in humans. Rats given the drug also expected the location of the sugar reward would change often. The drugged animals had harder time learning and adapting to changing circumstances.

The experiments suggest that brain processes found in both rats, which are less social than humans, and humans contribute to paranoia. This suggests paranoia may make it harder to update beliefs. This may help scientists understand what causes paranoia and develop therapies or drugs that can reduce paranoia. This information may also help scientists understand why during societal crises like wars or natural disasters humans are prone to believing conspiracies. This is particularly important now as the world grapples with climate change and a global pandemic. Reed et al. note paranoia may impede the coordination of collaborative solutions to these challenging situations.

Pupil diameter encodes the idiosyncratic, cognitive complexity of belief updating

Pupils tend to dilate in response to surprising events, but it is not known whether these responses are primarily stimulus driven or instead reflect a more nuanced relationship between pupil-linked arousal systems and cognitive expectations. Using an auditory adaptive decision-making task, we show that evoked pupil diameter is more parsimoniously described as signaling violations of learned, top-down expectations than changes in low-level stimulus properties. We further show that both baseline and evoked pupil diameter is modulated by the degree to which individual subjects use these violations to update their subsequent expectations, as reflected in the complexity of their updating strategy. Together these results demonstrate a central role for idiosyncratic cognitive processing in how arousal systems respond to new inputs and, via our complexity-based analyses, offer a potential framework for understanding these effects in terms of both inference processes aimed to reduce belief uncertainty and more traditional notions of mental effort.

Rethinking post-traumatic stress disorder - A predictive processing perspective

Predictive processing has become a popular framework in neuroscience and computational psychiatry, where it has provided a new understanding of various mental disorders. Here, we apply the predictive processing account to post-traumatic stress disorder (PTSD). We argue that the experience of a traumatic event in Bayesian terms can be understood as a perceptual hypothesis that is subsequently given a very high a-priori likelihood due to its (life-) threatening significance; thus, this hypothesis is re-selected although it does not fit the actual sensory input. Based on this account, we re-conceptualise the symptom clusters of PTSD through the lens of a predictive processing model. We particularly focus on re-experiencing symptoms as the hallmark symptoms of PTSD, and discuss the occurrence of flashbacks in terms of perceptual and interoceptive inference. This account provides not only a new understanding of the clinical profile of PTSD, but also a unifying framework for the corresponding pathologies at the neurobiological level. Finally, we derive directions for future research and discuss implications for psychological and pharmacological interventions.

Monetary feedback modulates performance and electrophysiological indices of belief updating in reward learning

Belief updating entails the incorporation of new information about the environment into internal models of the world. Bayesian inference is the statistically optimal strategy for performing belief updating in the presence of uncertainty. An important open question is whether the use of cognitive strategies that implement Bayesian inference is dependent upon motivational state and, if so, how this is reflected in electrophysiological signatures of belief updating in the brain. Here, we recorded the EEG of participants performing a simple reward learning task with both monetary and nonmonetary instructive feedback conditions. Our aim was to distinguish the influence of the rewarding properties of feedback on belief updating from the information content of the feedback itself. A Bayesian updating model allowed us to quantify different aspects of belief updating across trials, including the size of belief updates and the uncertainty of beliefs. Faster learning rates were observed in the monetary feedback condition compared to the instructive feedback condition, while belief updates were generally larger, and belief uncertainty smaller, with monetary compared to instructive feedback. Larger amplitudes in the monetary feedback condition were found for three ERP components: the P3a, the feedback-related negativity, and the late positive potential. These findings suggest that motivational state influences inference strategies in reward learning, and this is reflected in the electrophysiological correlates of belief updating.

A distinct inferential mechanism for delusions in schizophrenia

Delusions, a core symptom of psychosis, are false beliefs that are rigidly held with strong conviction despite contradictory evidence. Alterations in inferential processes have long been proposed to underlie delusional pathology, but previous attempts to show this have failed to yield compelling evidence for a specific relationship between inferential abnormalities and delusional severity in schizophrenia. Using a novel, incentivized information-sampling task (a modified version of the beads task), alongside well-characterized decision-making tasks, we sought a mechanistic understanding of delusions in a sample of medicated and unmedicated patients with schizophrenia who exhibited a wide range of delusion severity. In this novel task, participants chose whether to draw beads from one of two hidden jars or to guess the identity of the hidden jar, in order to minimize financial loss from a monetary endowment, and concurrently reported their probability estimates for the hidden jar. We found that patients with higher delusion severity exhibited increased information seeking (i.e. increased draws-to-decision behaviour). This increase was highly specific to delusion severity as compared to the severity of other psychotic symptoms, working-memory capacity, and other clinical and socio-demographic characteristics. Delusion-related increases in information seeking were present in unmedicated patients, indicating that they were unlikely due to antipsychotic medication. In addition, after adjusting for delusion severity, patients as a whole exhibited decreased information seeking relative to healthy individuals, a decrease that correlated with lower socioeconomic status. Computational analyses of reported probability estimates further showed that more delusional patients exhibited abnormal belief updating characterized by stronger reliance on prior beliefs formed early in the inferential process, a feature that correlated with increased information seeking in patients. Other decision-making parameters that could have theoretically explained the delusion effects, such as those related to subjective valuation, were uncorrelated with both delusional severity and information seeking among the patients. In turn, we found some preliminary evidence that subjective valuation (rather than belief updating) may explain group differences in information seeking unrelated to delusions. Together, these results suggest that abnormalities in belief updating, characterized by stronger reliance on prior beliefs formed by incorporating information presented earlier in the inferential process, may be a core computational mechanism of delusional ideation in psychosis. Our results thus provide direct empirical support for an inferential mechanism that naturally captures the characteristic rigidity associated with delusional beliefs.

Computation in Psychotherapy, or How Computational Psychiatry Can Aid Learning-Based Psychological Therapies

Learning-based therapies, such as cognitive-behavioral therapy, are used worldwide, and their efficacy is endorsed by health and research funding agencies. However, the mechanisms behind both their strengths and their weaknesses are inadequately understood. Here we describe how advances in computational modeling may help formalize and test hypotheses regarding how patients make inferences, which are core postulates of these therapies. Specifically, we highlight the relevance of computations with regard to the development, maintenance, and therapeutic change in psychiatric disorders. A Bayesian approach helps delineate which apparent inferential biases and aberrant beliefs are in fact near-normative, given patients' current concerns, and which are not. As examples, we formalize three hypotheses. First, high-level dysfunctional beliefs should be treated as beliefs over models of the world. There is a need to test how, and whether, people apply these high-level beliefs to guide the formation of lower level beliefs important for real-life decision making, conditional on their experiences. Second, during the genesis of a disorder, maladaptive beliefs grow because more benign alternative schemas are discounted during belief updating. Third, we propose that when patients learn within therapy but fail to benefit in real life, this can be accounted for by a mechanism that we term overaccommodation, similar to that used to explain fear reinstatement. Beyond these specifics, an ambitious collaborative research program between computational psychiatry researchers, therapists, and experts-by-experience needs to form testable predictions out of factors claimed to be important for therapy.

Valence-Dependent Belief Updating: Computational Validation

People tend to update beliefs about their future outcomes in a valence-dependent way: they are likely to incorporate good news and to neglect bad news. However, belief formation is a complex process which depends not only on motivational factors such as the desire for favorable conclusions, but also on multiple cognitive variables such as prior beliefs, knowledge about personal vulnerabilities and resources, and the size of the probabilities and estimation errors. Thus, we applied computational modeling in order to test for valence-induced biases in updating while formally controlling for relevant cognitive factors. We compared biased and unbiased Bayesian models of belief updating, and specified alternative models based on reinforcement learning. The experiment consisted of 80 trials with 80 different adverse future life events. In each trial, participants estimated the base rate of one of these events and estimated their own risk of experiencing the event before and after being confronted with the actual base rate. Belief updates corresponded to the difference between the two self-risk estimates. Valence-dependent updating was assessed by comparing trials with good news (better-than-expected base rates) with trials with bad news (worse-than-expected base rates). After receiving bad relative to good news, participants' updates were smaller and deviated more strongly from rational Bayesian predictions, indicating a valence-induced bias. Model comparison revealed that the biased (i.e., optimistic) Bayesian model of belief updating better accounted for data than the unbiased (i.e., rational) Bayesian model, confirming that the valence of the new information influenced the amount of updating. Moreover, alternative computational modeling based on reinforcement learning demonstrated higher learning rates for good than for bad news, as well as a moderating role of personal knowledge. Finally, in this specific experimental context, the approach based on reinforcement learning was superior to the Bayesian approach. The computational validation of valence-dependent belief updating represents a novel support for a genuine optimism bias in human belief formation. Moreover, the precise control of relevant cognitive variables justifies the conclusion that the motivation to adopt the most favorable self-referential conclusions biases human judgments.

Processing political misinformation: comprehending the Trump phenomenon

This study investigated the cognitive processing of true and false political information. Specifically, it examined the impact of source credibility on the assessment of veracity when information comes from a polarizing source (Experiment 1), and effectiveness of explanations when they come from one's own political party or an opposition party (Experiment 2). These experiments were conducted prior to the 2016 Presidential election. Participants rated their belief in factual and incorrect statements that President Trump made on the campaign trail; facts were subsequently affirmed and misinformation retracted. Participants then re-rated their belief immediately or after a delay. Experiment 1 found that (i) if information was attributed to Trump, Republican supporters of Trump believed it more than if it was presented without attribution, whereas the opposite was true for Democrats and (ii) although Trump supporters reduced their belief in misinformation items following a correction, they did not change their voting preferences. Experiment 2 revealed that the explanation's source had relatively little impact, and belief updating was more influenced by perceived credibility of the individual initially purporting the information. These findings suggest that people use political figures as a heuristic to guide evaluation of what is true or false, yet do not necessarily insist on veracity as a prerequisite for supporting political candidates.

Distinct oxytocin effects on belief updating in response to desirable and undesirable feedback

Humans update their beliefs upon feedback and, accordingly, modify their behaviors to adapt to the complex, changing social environment. However, people tend to incorporate desirable (better than expected) feedback into their beliefs but to discount undesirable (worse than expected) feedback. Such optimistic updating has evolved as an advantageous mechanism for social adaptation. Here, we examine the role of oxytocin (OT)-an evolutionary ancient neuropeptide pivotal for social adaptation-in belief updating upon desirable and undesirable feedback in three studies (n = 320). Using a double-blind, placebo-controlled between-subjects design, we show that intranasally administered OT (IN-OT) augments optimistic belief updating by facilitating updates of desirable feedback but impairing updates of undesirable feedback. The IN-OT-induced impairment in belief updating upon undesirable feedback is more salient in individuals with high, rather than with low, depression or anxiety traits. IN-OT selectively enhances learning rate (the strength of association between estimation error and subsequent update) of desirable feedback. IN-OT also increases participants' confidence in their estimates after receiving desirable but not undesirable feedback, and the OT effect on confidence updating upon desirable feedback mediates the effect of IN-OT on optimistic belief updating. Our findings reveal distinct functional roles of OT in updating the first-order estimation and second-order confidence judgment in response to desirable and undesirable feedback, suggesting a molecular substrate for optimistic belief updating.

Human Frontal-Subcortical Circuit and Asymmetric Belief Updating

How humans integrate information to form beliefs about reality is a question that has engaged scientists for centuries, yet the biological system supporting this process is not well understood. One of the most salient attributes of information is valence. Whether a piece of news is good or bad is critical in determining whether it will alter our beliefs. Here, we reveal a frontal-subcortical circuit in the left hemisphere that is simultaneously associated with enhanced integration of favorable information into beliefs and impaired integration of unfavorable information. Specifically, for favorable information, stronger white matter connectivity within this system, particularly between the left inferior frontal gyrus (IFG) and left subcortical regions (including the amygdala, hippocampus, thalamus, putamen, and pallidum), as well as insular cortex, is associated with greater change in belief. However, for unfavorable information, stronger connectivity within this system, particularly between the left IFG and left pallidum, putamen, and insular cortex, is associated with reduced change in beliefs. These novel results are consistent with models suggesting that partially separable processes govern learning from favorable and unfavorable information.

SIGNIFICANCE STATEMENT

Beliefs of what may happen in the future are important, because they guide decisions and actions. Here, we illuminate how structural brain connectivity is related to the generation of subjective beliefs. We focus on how the valence of information is related to people's tendency to alter their beliefs. By quantifying the extent to which participants update their beliefs in response to desirable and undesirable information and relating those measures to the strength of white matter connectivity using diffusion tensor imaging, we characterize a left frontal-subcortical system that is associated simultaneously with greater belief updating in response to favorable information and reduced belief updating in response to unfavorable information. This neural architecture may allow valence to be incorporated into belief updating.

Single-Trial Event-Related Potential Correlates of Belief Updating(1,2,3)

Belief updating—the process by which an agent alters an internal model of its environment—is a core function of the CNS. Recent theory has proposed broad principles by which belief updating might operate, but more precise details of its implementation in the human brain remain unclear. In order to address this question, we studied how two components of the human event-related potential encoded different aspects of belief updating. Participants completed a novel perceptual learning task while electroencephalography was recorded. Participants learned the mapping between the contrast of a dynamic visual stimulus and a monetary reward and updated their beliefs about a target contrast on each trial. A Bayesian computational model was formulated to estimate belief states at each trial and was used to quantify the following two variables: belief update size and belief uncertainty. Robust single-trial regression was used to assess how these model-derived variables were related to the amplitudes of the P3 and the stimulus-preceding negativity (SPN), respectively. Results showed a positive relationship between belief update size and P3 amplitude at one fronto-central electrode, and a negative relationship between SPN amplitude and belief uncertainty at a left central and a right parietal electrode. These results provide evidence that belief update size and belief uncertainty have distinct neural signatures that can be tracked in single trials in specific ERP components. This, in turn, provides evidence that the cognitive mechanisms underlying belief updating in humans can be described well within a Bayesian framework.

Losing the rose tinted glasses: neural substrates of unbiased belief updating in depression

Recent evidence suggests that a state of good mental health is associated with biased processing of information that supports a positively skewed view of the future. Depression, on the other hand, is associated with unbiased processing of such information. Here, we use brain imaging in conjunction with a belief update task administered to clinically depressed patients and healthy controls to characterize brain activity that supports unbiased belief updating in clinically depressed individuals. Our results reveal that unbiased belief updating in depression is mediated by strong neural coding of estimation errors in response to both good news (in left inferior frontal gyrus and bilateral superior frontal gyrus) and bad news (in right inferior parietal lobule and right inferior frontal gyrus) regarding the future. In contrast, intact mental health was linked to a relatively attenuated neural coding of bad news about the future. These findings identify a neural substrate mediating the breakdown of biased updating in major depression disorder, which may be essential for mental health.

Neural correlates of informational cascades: brain mechanisms of social influence on belief updating

Informational cascades can occur when rationally acting individuals decide independently of their private information and follow the decisions of preceding decision-makers. In the process of updating beliefs, differences in the weighting of private and publicly available social information may modulate the probability that a cascade starts in a decisive way. By using functional magnetic resonance imaging, we examined neural activity while participants updated their beliefs based on the decisions of two fictitious stock market traders and their own private information, which led to a final decision of buying one of two stocks. Computational modeling of the behavioral data showed that a majority of participants overweighted private information. Overweighting was negatively correlated with the probability of starting an informational cascade in trials especially prone to conformity. Belief updating by private information was related to activity in the inferior frontal gyrus/anterior insula, the dorsolateral prefrontal cortex and the parietal cortex; the more a participant overweighted private information, the higher the activity in the inferior frontal gyrus/anterior insula and the lower in the parietal-temporal cortex. This study explores the neural correlates of overweighting of private information, which underlies the tendency to start an informational cascade.

Depression is related to an absence of optimistically biased belief updating about future life events

BACKGROUND

When challenged with information about the future, healthy participants show an optimistically biased updating pattern, taking desirable information more into account than undesirable information. However, it is unknown how patients suffering from major depressive disorder (MDD), who express pervasive pessimistic beliefs, update their beliefs when receiving information about their future. Here we tested whether an optimistically biased information processing pattern found in healthy individuals is absent in MDD patients.

METHOD

MDD patients (n = 18; 13 medicated; eight with co-morbid anxiety disorder) and healthy controls (n = 19) estimated their personal probability of experiencing 70 adverse life events. After each estimate participants were presented with the average probability of the event occurring to a person living in the same sociocultural environment. This information could be desirable (i.e. average probability better than expected) or undesirable (i.e. average probability worse than expected). To assess how desirable versus undesirable information influenced beliefs, participants estimated their personal probability of experiencing the 70 events a second time.

RESULTS

Healthy controls showed an optimistic bias in updating, that is they changed their beliefs more toward desirable versus undesirable information. Overall, this optimistic bias was absent in MDD patients. Symptom severity correlated with biased updating: more severely depressed individuals showed a more pessimistic updating pattern. Furthermore, MDD patients estimated the probability of experiencing adverse life events as higher than healthy controls.

CONCLUSIONS

Our findings raise the intriguing possibility that optimistically biased updating of expectations about one's personal future is associated with mental health.

Degree of Handedness, but not Direction, is a Systematic Predictor of Cognitive Performance

A growing body of evidence is reviewed showing that degree of handedness (consistent versus inconsistent) is a more powerful and appropriate way to classify handedness than the traditional one based on direction (right versus left). Experimental studies from the domains of episodic memory retrieval, belief updating/cognitive flexibility, risk perception, and more are described. These results suggest that inconsistent handedness is associated with increased interhemispheric interaction and increased access to processes localized to the right cerebral hemisphere.