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The metacognitive sense of confidence can play a critical role in regulating decision making. In particular, a lack of confidence can justify the explicit, potentially costly, instrumental acquisition of extra information that might resolve uncertainty. Human confidence is highly complex, and recent computational work has suggested a statistically sophisticated tapestry behind the information that governs both the making and monitoring of choices. However, the consequences of the form of such confidence computations for search have yet to be understood. Here, we reveal extra richness in the use of confidence for information seeking by formulating joint models of action, confidence, and information search within a Bayesian and reinforcement learning framework. Through detailed theoretical analysis of these models, we show the intricate normative downstream consequences for search arising from more complex forms of metacognition. For example, our results highlight how the ability to monitor errors or general metacognitive sensitivity impact seeking decisions and can generate diverse relationships between action, confidence, and the optimal search for information. We also explore whether empirical search behavior enjoys any of the characteristics of normatively derived prescriptions. More broadly, our work demonstrates that it is crucial to treat metacognitive monitoring and control as closely linked processes.

Both accurately sensing our own bodily signals and knowing whether we have accurately sensed them may contribute to a successful emotional life, but there is little evidence on whether these physiological perceptual and metacognitive abilities systematically differ between people. Here, we examined whether actors, who receive substantial training in the production, awareness, and control of emotion, and nonactor controls differed in interoceptive ability (the perception of internal bodily signals) and/or metacognition about interoceptive accuracy (awareness of that perception), and explored potential sources of individual differences in and consequences of these abilities including correlational relationships with state and trait anxiety, proxies for acting ability, and the amount of acting training. Participants performed a heartbeat detection task in which they judged whether tones were played synchronously or delayed relative to their heartbeats, and then rated their metacognitive confidence in that judgment. Cardiac interoceptive accuracy and metacognitive awareness of interoceptive accuracy were independent, and while actors' and controls' interoceptive accuracy was not significantly different, actors had consistently superior metacognitive awareness of interoception. Exploratory analyses additionally suggest that this metacognitive ability may be correlated with measures of acting ability, but not the duration of acting training. Interoceptive accuracy and metacognitive insight into that accuracy appear to be separate abilities, and while actors may be no more accurate in reading their bodies, their metacognitive insight means they know better when they're accurate and when they're not. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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.

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.

Individuals with anxiety and depression (AD) exhibit chronic metacognitive biases such as underconfidence. The origin of such biases is unknown. Here we quantified the impact of feedback valence on confidence in two large general population samples (N=230 and N=278). We studied metacognition both locally, as confidence in individual task instances, and globally, as self-performance estimates. Global confidence was sensitive to both local confidence and feedback valence – more frequent positive (negative) feedback increased (respectively decreased) global confidence. Feedback valence impacted confidence in a domain-general fashion and also led to shifts in affective self-beliefs. Notably, global confidence was more sensitive to low (vs. high) local confidence in individuals with greater transdiagnostic anxious-depression symptomatology, despite sensitivity to feedback valence remaining intact. Together, our results reveal a mechanistic basis for chronic underconfidence in AD rooted in distorted interactions between local and global metacognition, while also highlighting potential for restoring confidence through targeted feedback.

Numerous disorders are characterised by fatigue as a highly disabling symptom. Fatigue plays a particularly important clinical role in multiple sclerosis (MS) where it exerts a profound impact on quality of life. Recent concepts of fatigue grounded in computational theories of brain-body interactions emphasise the role of interoception and metacognition in the pathogenesis of fatigue. So far, however, for MS, empirical data on interoception and metacognition are scarce. This study examined interoception and (exteroceptive) metacognition in a sample of 71 persons with a diagnosis of MS. Interoception was assessed by prespecified subscales of a standard questionnaire (Multidimensional Assessment of Interoceptive Awareness [MAIA]), while metacognition was investigated with computational models of choice and confidence data from a visual discrimination paradigm. Additionally, autonomic function was examined by several physiological measurements. Several hypotheses were tested based on a preregistered analysis plan. In brief, we found the predicted association of interoceptive awareness with fatigue (but not with exteroceptive metacognition) and an association of autonomic function with exteroceptive metacognition (but not with fatigue). Furthermore, machine learning (elastic net regression) showed that individual fatigue scores could be predicted out-of-sample from our measurements, with questionnaire-based measures of interoceptive awareness and sleep quality as key predictors. Our results support theoretical concepts of interoception as an important factor for fatigue and demonstrate the general feasibility of predicting individual levels of fatigue from simple questionnaire-based measures of interoception and sleep., European Journal of Neuroscience, ISSN:0953-816X, ISSN:1460-9568

Psychological therapies are among the most effective treatments for a range of common mental health problems – however, we still know relatively little about how exactly they improve symptoms. Here, we demonstrate the power of combing theory with computational methods to parse effects of different components of cognitive-behavioural therapies on to underlying mechanisms. Specifically, we present data from a series of randomized-controlled experiments testing the effects of components of behavioural and cognitive therapies on different cognitive processes, using well-validated behavioural measures and associated computational models (total N=807). We found that a goal-setting intervention, based on behavioural activation therapy, reliably and selectively reduced sensitivity to effort when deciding how to act to gain reward. By contrast, we found that a cognitive restructuring intervention, based on cognitive therapy, reliably and selectively reduced the tendency to attribute negative everyday events to self-related causes. Importantly, the effects of each intervention were specific to these respective measures. Our approach provides a basis for understanding how different elements of common psychotherapy programs work, which may enable theoretically-informed treatment targeting in the future.

Metacognition refers to a capacity to reflect on and control other cognitive processes, commonly quantified as the extent to which confidence tracks objective performance. There is conflicting evidence about how metacognition changes across the lifespan and it is unknown whether “local” metacognition (monitoring of individual judgments) and “global” metacognition (estimates of self-ability) change. Additionally, the degree to which metacognition generalises across cognitive domains may itself change over time due to increased experience with one’s own abilities. Using a gamified metacognitive task we measured local and global metacognition during performance-controlled memory and visual perception tasks in an age-stratified sample of 304 healthy volunteers (18-83 years; N=50 in each of 6 age groups). We calculated both local and global metrics of metacognition and charted domain-generality with age. Task performance was stable with age. Global self-performance estimates and local metacognitive bias decreased with age, indicating overall lower confidence. Local metacognitive efficiency was unrelated to age and remained correlated across the two cognitive domains. A stability of local metacognition indicates distinct mechanisms contributing to local and global metacognition. Our study provides both a profile of local and global metacognition across the lifespan and a benchmark against which disease-related changes in metacognition can be compared.

Accounting for why sensitivity to perceptual input (as assayed by discrimination judgments) is not always accompanied by conscious awareness (as assayed by detection judgments) remains a challenge for theories of perception. Here we test a hypothesis that awareness is supported by higher-order inferences within generative models of perceptual content. We develop a novel visual perception paradigm that probes such inferences by orthogonally manipulating expectations about stimulus content (discrimination) and awareness of content (detection). In line with model simulations we show that both detection and discrimination expectations influence reaction times on a categorisation task. By combining a no-report version of our task with functional neuroimaging we reveal a neural dissociation between prediction errors (PEs) on content (discrimination) and awareness of content (detection): content PEs are tracked in posterior sensory cortex while awareness PEs are tracked in prefrontal cortex. Together, our results reveal a hierarchical structure supporting visual detection and discrimination, consistent with a proposal that awareness reflects a higher-order inference within perceptual generative models.

A key goal of consciousness science is identifying neural signatures of being aware vs. unaware of simple stimuli. This is often investigated in the context of near-threshold detection, with reports of stimulus awareness being linked to heightened activation in a frontoparietal network. However, due to reports of stimulus presence typically being associated with higher confidence than reports of stimulus absence, these results could be explained by frontoparietal regions encoding stimulus visibility, decision confidence or both. In an exploratory analysis, we leverage fMRI data from 35 human participants (20 females) to disentangle these possibilities. We first show that, whereas stimulus identity was best decoded from the visual cortex, stimulus visibility (presence vs. absence) was best decoded from prefrontal regions. To control for effects of confidence, we then selectively sampled trials prior to decoding to equalize confidence distributions between absence and presence responses. This analysis revealed striking differences in the neural correlates of subjective visibility in prefrontal cortex regions of interest, depending on whether or not differences in confidence were controlled for. We interpret our findings as highlighting the importance of controlling for metacognitive aspects of the decision process in the search for neural correlates of visual awareness.Significance statementWhile much has been learned over the past two decades about the neural basis of visual awareness, the role of the prefrontal cortex remains a topic of debate. By applying decoding analyses to functional brain imaging data, we show that prefrontal representations of subjective visibility are contaminated by neural correlates of decision confidence. We propose a new analysis method to control for these metacognitive aspects of awareness reports, and use it to reveal confidence-independent correlates of perceptual judgments in a subset of prefrontal areas.

Foundational work in the psychology of metacognition identified a distinction between metacognitive knowledge (stable beliefs about one’s capacities) and metacognitive experiences (local evaluations of performance). More recently, the field has focused on the latter half of the construct in the form of confidence estimates, developing tasks and metrics that seek to identify metacognitive capacities from momentary estimates of confidence in performance, and providing precise computational accounts of metacognitive failure. However, progress in formalising models of metacognitive judgments may have come at a cost of ignoring broader elements of the psychology of metacognition – such as how stable meta-knowledge is formed, how social cognition and metacognition interact, and how we evaluate affective states that do not have an obvious ground truth. We propose that construct breadth in metacognition research can be restored while maintaining rigour in measurement (for example, through computational modelling) and highlight promising avenues for extending both temporality and scope in the study of metacognition. Such a research programme is well placed to recapture qualitative features of metacognitive knowledge and experience that were part of the original construct, while maintaining the psychophysical rigor that characterises modern research on confidence and performance monitoring.

To survive, organisms constantly make decisions to avoid danger and maximize rewards in information-rich environments. As a result, decisions about sensory input are not only driven by sensory information, but also by other factors, such as the expected rewards of a decision (known as the payoff matrix) or by information about temporal regularities in the environment (known as cognitive priors or predictions). However, it is unknown to what extent these different types of information affect subjective experience, or whether they merely result in non-perceptual response criterion shifts. To investigate this question, we used three carefully matched manipulations that typically result in behavioral shifts in decision criteria: a visual illusion (Müller-Lyer condition), a punishment scheme (payoff condition), and a change in the ratio of relevant stimuli (base rate condition). To gauge shifts in subjective experience, we introduce a novel task in which participants not only make decisions about what they have just seen, but are also asked to reproduce their experience of a target stimulus. Using Bayesian ordinal modeling, we show that each of these three manipulations affects decision criterion as intended, but that the visual illusion uniquely affects sensory experience as measured by reproduction. In a series of follow-up experiments, we use computational modeling to show that although the visual illusion result in a distinct drift-diffusion (DDM) parameter profile relative to non-sensory manipulations, reliance on DDM parameter estimates alone is not sufficient to ascertain whether a given manipulation is perceptual or non-perceptual.

Some conscious experiences are more vivid than others. Although perceptual visibility is a familiar component of human consciousness, how variation in visibility is registered by the human brain is unknown. In particular, it is unknown whether the vividness of experience is encoded in a “rich” manner, via the strengthening or broadcast of content-specific perceptual representations, or a “sparse” manner, in which content-invariant signals track the reliability or precision of perceptual contents. Here we reanalysed existing MEG and fMRI data from two distinct studies, operationalising perceptual visibility as subjective ratings of awareness and visibility. Using representational similarity and decoding analyses, we find evidence supporting a proposal that perceptual visibility is associated with content-invariant neural signatures distributed across visual, parietal, and frontal cortices. Our findings are consistent with content-invariant neural substrates supporting the strength of perceptual experience and offer a novel methodology for examining the neural correlates of perceptual awareness.Significance StatementThe vividness of experience varies across different stimuli and contexts. Despite being a fundamental feature of human conscious awareness, it remains debated as to how perceptual vividness is encoded in the brain. Here we investigate whether the neural correlates of perceptual visibility are specific to the content of an experience and/or whether they generalize over different stimuli. By reanalysing data from two different neuroimaging studies, we describe evidence in support of a content-invariant neural code for perceptual visibility. We find temporally dynamic content-invariant neural signatures of visibility localised to visual, parietal, and frontal cortices. Our approach to dissociating content-specific and content-invariant neural signatures of awareness offers a new framework within which to distinguish between rich vs. sparse models of consciousness.

The dual-basis theory of metamemory suggests that people evaluate their memory performance based on both processing experience during the memory process and their prior beliefs about overall memory ability. However, few studies have proposed a formal computational model to quantitatively characterize how processing experience and prior beliefs are integrated during metamemory monitoring. Here, we introduce a Bayesian inference model for metamemory (BIM) which provides a theoretical and computational framework for the metamemory monitoring process. BIM assumes that when people evaluate their memory performance, they integrate processing experience and prior beliefs via Bayesian inference. We show that BIM can be fitted to recall or recognition tasks with confidence ratings on either a continuous or discrete scale. Results from data simulation indicate that BIM can successfully recover a majority of generative parameter values, and demonstrate a systematic relationship between parameters in BIM and previous computational models of metacognition such as the stochastic detection and retrieval model (SDRM) and the meta-d' model. We also show examples of fitting BIM to empirical data sets from several experiments, which suggest that the predictions of BIM are consistent with previous studies on metamemory. In addition, when compared with SDRM, BIM could more parsimoniously account for the data of judgments of learning (JOLs) and memory performance from recall tasks. Finally, we discuss an extension of BIM which accounts for belief updating, and conclude with a discussion of how BIM may benefit metamemory research. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Risk engenders a phenomenologically distinct experience from certainty, often driving people to behave in ostensibly irrational ways, and with potential consequences for our subjective sense of confidence in having made the best choice. While previous work on decision confidence has largely focused on ambiguous perceptual decisions or value-based choices under certainty, it is unclear how subjective confidence reports are formed during risky value-based choice (i.e. those with uncertain outcomes). Accordingly, we sought to examine the effect of risky (versus certain) choice upon confidence ratings in a calibrated economic choice task and explore the well-documented interrelationships between confidence and subjective value (SV) as well as choice response time (RT) in the context of value-based choice. By jointly analyzing choices (risky versus certain), SV of the chosen option, confidence, and RT, we found a systematic effect of risk on subjective confidence: subjective confidence reports were significantly higher when selecting a certain prospect compared with a risky one. Interestingly, risk attenuated the strength of the relationships between confidence and both RTs and difference in subjective value (ΔSV), as well as the relationship between RT and ΔSV. Taken together, these results corroborate how choice, RT, confidence and SV relate in value-based choice under risk, informing both theories of confidence and risk preferences.

Significance Dogmatic individuals are reluctant to seek out new information to refine their views, often skewing political, scientific, and religious discourse in the process. The cognitive drivers of this reluctance are poorly understood. Here, we isolate an influence of uncertainty on information search using a low-level perceptual decision-making task. We show that people with dogmatic views are both less likely to seek information before committing to a decision and to use fluctuations in uncertainty to guide their search. Our results highlight a cognitive mechanism that may contribute to the formation of dogmatic worldviews., When knowledge is scarce, it is adaptive to seek further information to resolve uncertainty and obtain a more accurate worldview. Biases in such information-seeking behavior can contribute to the maintenance of inaccurate views. Here, we investigate whether predispositions for uncertainty-guided information seeking relate to individual differences in dogmatism, a phenomenon linked to entrenched beliefs in political, scientific, and religious discourse. We addressed this question in a perceptual decision-making task, allowing us to rule out motivational factors and isolate the role of uncertainty. In two independent general population samples (n = 370 and n = 364), we show that more dogmatic participants are less likely to seek out new information to refine an initial perceptual decision, leading to a reduction in overall belief accuracy despite similar initial decision performance. Trial-by-trial modeling revealed that dogmatic participants placed less reliance on internal signals of uncertainty (confidence) to guide information search, rendering them less likely to seek additional information to update beliefs derived from weak or uncertain initial evidence. Together, our results highlight a cognitive mechanism that may contribute to the formation of dogmatic worldviews.

Functional cognitive disorder is common but underlying mechanisms remain poorly understood. Metacognition, an individual’s ability to reflect on and monitor cognitive processes, is likely to be relevant. Local metacognition refers to an ability to estimate confidence in cognitive performance on a moment-to-moment basis, whereas global metacognition refers to long-run self-evaluations of overall performance. Using a novel protocol comprising task-based measures and hierarchical Bayesian modelling, we compared local and global metacognitive performance in individuals with functional cognitive disorder. Eighteen participants with functional cognitive disorder (mean age = 49.2 years, 10 males) were recruited to this cross-sectional study. Participants completed computerized tasks that enabled local metacognitive efficiency for perception and memory to be measured using the hierarchical meta-d’ model within a signal detection theory framework. Participants also completed the Multifactorial Memory Questionnaire measuring global metacognition, and questionnaires measuring anxiety and depression. Estimates of local metacognitive efficiency were compared with those estimated from two control groups who had undergone comparable metacognitive tasks. Global metacognition scores were compared with the existing normative data. A hierarchical regression model was used to evaluate associations between global metacognition, depression and anxiety and local metacognitive efficiency, whilst simple linear regressions were used to evaluate whether affective symptomatology and local metacognitive confidence were associated with global metacognition. Participants with functional cognitive disorder had intact local metacognition for perception and memory when compared with controls, with the 95% highest density intervals for metacognitive efficiency overlapping with the two control groups in both cognitive domains. Functional cognitive disorder participants had significantly lower global metacognition scores compared with normative data; Multifactorial Memory Questionnaire-Ability subscale (t = 6.54, P

Significance Momentary feelings of confidence accompany many of our actions and decisions. In addition to such “local” feelings of confidence, we also construct “global” confidence estimates about our skills and abilities (global self-performance estimates or SPEs). Distorted SPEs may have a pervasive impact on motivation and self-evaluation, for instance affecting estimates of our competitiveness at work or in a sports team. Here, we found that components of a brain network previously implicated in the tracking of local confidence was additionally modulated by SPE level, whereas ventral striatum tracked SPEs irrespective of confidence. Our findings of a neurocognitive basis for global SPEs lay the groundwork for understanding how distorted SPEs arise in educational and clinical settings., Humans create metacognitive beliefs about their performance across many levels of abstraction—from local confidence in individual decisions to global estimates of our skills and abilities. Despite a rich literature on the neural basis of local confidence judgements, how global self-performance estimates (SPEs) are constructed remains unknown. Using functional magnetic resonance imaging, we scanned human subjects while they performed several short blocks of tasks and reported on which task they think they performed best, providing a behavioral proxy for global SPEs. In a frontoparietal network sensitive to fluctuations in local confidence, we found that activity within ventromedial prefrontal cortex and precuneus was additionally modulated by global SPEs. In contrast, activity in ventral striatum was associated with subjects’ global SPEs irrespective of fluctuations in local confidence, and predicted the extent to which global SPEs tracked objective task difficulty across individuals. Our findings reveal neural representations of global SPEs that go beyond the tracking of local confidence, and lay the groundwork for understanding how a formation of global self-beliefs may go awry in conditions characterized by distorted self-evaluation.

A prominent source of polarised and entrenched beliefs is confirmation bias, where evidence against one’s position is selectively disregarded. This effect is most starkly evident when opposing parties are highly confident in their decisions. Here we combine human magnetoencephalography (MEG) with behavioural and neural modelling to identify alterations in post-decisional processing that contribute to the phenomenon of confirmation bias. We show that holding high confidence in a decision leads to a striking modulation of post-decision neural processing, such that integration of confirmatory evidence is amplified while disconfirmatory evidence processing is abolished. We conclude that confidence shapes a selective neural gating for choice-consistent information, reducing the likelihood of changes of mind on the basis of new information. A central role for confidence in shaping the fidelity of evidence accumulation indicates that metacognitive interventions may help ameliorate this pervasive cognitive bias., People often ignore evidence that disconfirms their prior beliefs. Here, the authors investigate the underlying cognitive, computational and neuronal mechanisms of such confirmation bias, and show that high confidence induces a selective neural processing of choice-consistent information.

Thinking about our own death and its salience in relation to decision making has become a fruitful area of multidisciplinary research across the breadth of psychological science. By bringing together experts from philosophy, cognitive and affective neuroscience, clinical and computational psychiatry we have attempted to set out the current state of the art and point to areas of further enquiry. One stimulus for doing this is the need to engage with policy makers who are now having to consider guidelines on suicide and assisted suicide so that they may be aware of their own as well as the wider populations’ cognitive processes when confronted with the ultimate truth of mortality.

Internally generated imagery and externally triggered perception rely on overlapping sensory processes. This overlap poses a challenge for perceptual reality monitoring: determining whether sensory signals reflect reality or imagination. In this study, we used psychophysics to investigate how imagery and perception interact to determine visual experience. Participants were instructed to detect oriented gratings that gradually appeared in noise while simultaneously either imagining the same grating, a grating perpendicular to the to-be-detected grating, or nothing. We found that, compared to both incongruent imagery and no imagery, congruent imagery caused a leftward shift of the psychometric function relating stimulus contrast to perceptual threshold. We discuss how this effect can best be explained by a model in which imagery adds sensory signal to the perceptual input, thereby increasing the visibility of perceived stimuli. These results suggest that, in contrast to changes in sensory signals caused by self-generated movement, the brain does not discount the influence of self-generated sensory signals on perception.

As a general rule, if it is easy to detect a target in a visual scene, it is also easy to detect its absence. To account for this, models of visual search explain search termination as resulting either from counterfactual reasoning over second-order representations of search efficiency, automatic extraction of ensemble statistics of a display, or heuristic adjustment of a search termination strategy based on previous trials. Traditional few-subjects/many-trials lab-based experiments render it impossible to disentangle the unique contribution of these different processes to absence pop-out - the immediate recognition that a feature is missing from a display. In 2 preregistered large-scale online experiments (N1 = 1187; N2 = 887) we show that search termination times are already aligned with target identification times in the very first trials of the experiment before any experience with target presence. Exploratory analysis reveals that explicit metacognitive knowledge about search efficiency is not necessary for efficient search termination. We conclude that for basic stimulus properties, efficient inference about absence is independent of task experience and of explicit metacognitive knowledge about visual search. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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.

People have better metacognitive sensitivity for decisions about the presence compared to the absence of objects. However, it is not only objects themselves that can be present or absent, but also parts of objects and other visual features. Asymmetries in visual search indicate that a disadvantage for representing absence may operate at these levels as well. Furthermore, a processing advantage for surprising signals suggests that a presence/absence asymmetry may be explained by absence being passively represented as a default state, and presence as a default-violating surprise. It is unknown whether the metacognitive asymmetry for judgments about presence and absence extends to these different levels of representation (object, feature, and default violation). To address this question and test for a link between the representation of absence and default reasoning more generally, here we measure metacognitive sensitivity for discrimination judgments between stimuli that are identical except for the presence or absence of a distinguishing feature, and for stimuli that differ in their compliance with an expected default state.

Doerig et al. point out a number of shortcomings with existing theories of consciousness and argue they should be systematically constrained by empirical data. In this commentary I suggest a further constraint - the potential functions of (the contents of) consciousness. One such candidate function in humans is the social sharing of reportable mental states. The social function of consciousnessprovides a general framework within which to understand the evolution and neurobiology of conscious awareness.

Do people have privileged and direct access to their own minds, or do we infer our own thoughts and feelings indirectly, as we would infer the mental states of others? In this study we shed light on this question by examining how mentalizing ability—the set of processes involved in understanding other people’s thoughts and feelings—relates to metacognitive efficiency—the ability to reflect on one’s own performance. In a general population sample (N = 477) we showed that mentalizing ability and self-reported socio-communicative skills are positively correlated with perceptual metacognitive efficiency, even after controlling for choice accuracy. By modelling the trial-by-trial formation of confidence we showed that mentalizing ability predicted the association between response times and confidence, suggesting those with better mentalizing ability were more sensitive to inferential cues to self-performance. In a second study we showed that both mentalizing and metacognitive efficiency were lower in autistic participants (N = 40) when compared with age, gender, IQ, and education-matched non-autistic participants. Together, our results suggest that the ability to understand other people’s minds predicts self-directed metacognition.

Humans are voracious imaginers, with internal simulations supporting memory, planning and decision-making. Because the neural mechanisms supporting imagination overlap with those supporting perception, a foundational question is how reality and imagination are kept apart. Traditional psychology experiments struggle to investigate this issue as subjects can rapidly learn that real stimuli are in play. Here we capitalised on the ability to conduct large-scale, one-trial-per-participant psychophysics via online platforms combined with computational modelling and neuroimaging to investigate perceptual reality monitoring failures in the general population. We find striking evidence for a subjective intermixing of imagination and reality – both behaviourally and neurally. Our data are best explained by a model that evaluates the total strength of intermixed imagined and perceived signals against a “reality threshold” to determine whether it reflects reality. These findings suggest that imagined and perceived signals are not kept separate, nor is the intention to imagine used to identity and discount self-generated signals. Instead, a judgment of reality is based on the intensity of the intermixture between imagination and reality. A striking consequence of this account is that it predicts when virtual or imagined signals are strong enough, they become indistinguishable from reality.

Functional cognitive disorder (FCD) is common but underlying mechanisms remain poorly understood. Metacognition, an individual’s ability to reflect on and monitor cognitive processes, is likely to be relevant. Local metacognition refers to an ability to estimate confidence in cognitive performance on a moment-to-moment basis, whereas global metacognition refers to long-run self-evaluations of overall performance. Using a novel protocol comprising task-based measures and hierarchical Bayesian modelling, we compared local and global metacognitive performance in individuals with FCD and evaluated interactions between these levels of metacognition. We also investigated how local and global metacognition were related to the presence of affective symptomatology.Eighteen participants with FCD were recruited to this cross-sectional study. Participants completed computerised tasks that enabled local metacognitive efficiency for perception and memory to be measured using the hierarchical meta-d’ (HMeta-d) model within a signal detection theory framework. Participants also completed the Multifactorial Memory Questionnaire (MMQ) measuring global metacognition (beliefs about memory performance), and questionnaires measuring anxiety and depression. Estimates of local metacognitive efficiency were compared to those estimated from two control groups who had undergone comparable metacognitive tasks. Global metacognition scores were compared to existing normative data. A hierarchical regression model was used to evaluate associations between global metacognition, depression and anxiety and local metacognitive efficiency, while simple linear regressions were used to evaluate whether affective symptomatology and local metacognitive confidence were associated with global metacognition.Participants with FCD had intact local metacognition for perception and memory when compared to controls, with the 95% highest-density intervals for metacognitive efficiency overlapping with the two control groups in both cognitive domains. FCD participants had significantly lower global metacognition scores compared to normative data; MMQ-Ability (t=6.54, pWe show that local metacognition is intact, whilst global metacognition is impaired, in FCD, suggesting a decoupling between the two metacognitive processes. In a Bayesian model, an aberrant prior (impaired global metacognition), may override bottom up sensory input (intact local metacognition), giving rise to the subjective experience of abnormal cognitive processing. Future work should further investigate the interplay between local and global metacognition in FCD and aim to identify a therapeutic target to recouple these processes.