Dynamic influences on static measures of metacognition

Confidence reports during perceptual decision making dissociate from changes in subjective experience

In noisy perceptual environments, people frequently make decisions based on non-perceptual information to maximize rewards. Therefore, a central problem in psychophysics, metacognition and consciousness research is to distinguish between decisions resulting from changes in subjective experience and those arising from non-perceptual information. It has recently been proposed that confidence reports can be used to discriminate between changes in subjective experience and those arising from non-perceptual information. Here we use a Bayesian ordinal modelling framework combined with an explicit measure of subjective experience to show across two experiments (N = 204) and three bias manipulations that confidence during perceptual decision-making does not uniquely reflect subjective experience. Instead, non-perceptual manipulations affecting response bias 'leak' into perceptual confidence reports. This occurs not only for biases resulting from changes in the base rate of stimuli ('cognitive' priors), but also when biasing information does not inform decision correctness (asymmetric payoff matrix). The relative strength of biases in first-order responses and confidence may help disentangle whether a given bias manipulation is perceptual in nature or not.

The influence of tDCS on the speed-accuracy tradeoff and metacognitive decision making

A fundamental tradeoff exists between speed and accuracy when performing a decision (speed-accuracy tradeoff, SAT). Metacognition allows for the adjustment, monitoring, and evaluation of one's own decisions and strategies. While these aspects of cognition are central to human behavioural performance, their respective causal neural underpinnings are not well understood. Here, we used transcranial direct current stimulation (tDCS) to investigate the causal roles of the prefrontal cortex (PFC), superior medial frontal cortex (SMFC), and posterior parietal cortex (PPC) in the SAT and metacognition. Subjects received active or sham tDCS before completing a perceptual task with explicit SAT cues and reported confidence in their decisions. We fit the linear ballistic accumulator model to behavioural data to extract latent decision variables and used confidence judgments to compute two common indices of metacognition: meta-d' and m-ratio. Stimulation influenced performance on the perceptual task but there was no meaningful evidence for an effect on metacognition. Specifically, PFC stimulation reduced subjects' response caution, especially when accuracy was emphasised; SMFC stimulation decreased response caution and increased the discriminability between choices; and PPC stimulation increased both response caution and discriminability. These results show that the impact of tDCS on the SAT critically depends on the frontoparietal region stimulated. In addition, there was little to no evidence of any effect of tDCS on metacognition, hinting at potential differences in the neural circuitry supporting aspects of object-level computation and meta-level processing. In sum, our findings provide further evidence that tDCS can alter decision making and strategic processes in the human brain.

Does age affect metacognition? A cross-domain investigation using a hierarchical Bayesian framework

According to previous research, the accuracy of metacognitive judgments in aging depends on the cognitive domain involved in the task, the experimental design, and the metacognitive index used. Older adults are frequently less accurate than younger adults in judging their episodic memory, while no difference is typically observed for semantic metamemory. In addition, age-related changes in metaperception appear to be highly task-dependent. Other metacognitive domains (such as metacognition of executive functioning) have been seldom explored. This study aimed to integrate methodological and theoretical advances in the study of metacognition to answer the question of whether metacognition is impaired in healthy aging. Data were collected in a large sample (n = 443) of participants aged 18 to 79. Participants provided retrospective confidence judgments in four domains: episodic memory, semantic memory, executive functioning, and visual perception. Our measure of accuracy, metacognitive efficiency, was estimated using a hierarchical Bayesian implementation of the meta-d' model. Results showed that metacognitive efficiency decreased with age in the episodic task and increased with age in the semantic task. There was no effect of age on metacognitive efficiency in the executive and perception tasks. Moreover, metacognitive efficiency appeared to rely on a domain-general process in older adults. Explaining the episodic metamemory deficit in aging could help understand the difficulties of older adults to use inferential processes for memory search and retrieval as well as their difficulties to implement memory strategies.

Neural mechanisms of metacognitive improvement under speed pressure

The ability to accurately monitor the quality of one's choices, or metacognition, improves under speed pressure, possibly due to changes in post-decisional evidence processing. Here, we investigate the neural processes that regulate decision-making and metacognition under speed pressure using time-resolved analyses of brain activity recorded using electroencephalography. Participants performed a motion discrimination task under short and long response deadlines and provided a metacognitive rating following each response. Behaviourally, participants were faster, less accurate, and showed superior metacognition with short deadlines. These effects were accompanied by a larger centro-parietal positivity (CPP), a neural correlate of evidence accumulation. Crucially, post-decisional CPP amplitude was more strongly associated with participants' metacognitive ratings following errors under short relative to long response deadlines. Our results suggest that superior metacognition under speed pressure may stem from enhanced metacognitive readout of post-decisional evidence.

Metacognitive confidence and affect - two sides of the same coin?

Decision confidence is a prototypical metacognitive representation that is thought to approximate the probability that a decision is correct. The perception of being correct has also been associated with affective valence such that being correct feels more positive and being mistaken more negative. This suggests that, similarly to confidence, affective valence reflects the probability that a decision is correct. However, both fields of research have seen very little interaction. Here, we test if affect, similarly to confidence reflects probability that a decision is correct in two perceptual decision-making experiments where we compare the relationships of theoretically relevant variables (e.g. evidence, accuracy, and expectancy) with both confidence and affect ratings. The findings indicate that confidence and affect ratings are similarly sensitive to changes in accuracy, evidence, and expectancy, indicating that both track the subjective probability that a decision is correct. We identify various mechanisms that can explain these results. We also envision future research for clarifying the role of cognitive and affective aspects of metacognition relying on deeper integration of the respective research fields.

A comprehensive assessment of current methods for measuring metacognition

One of the most important aspects of research on metacognition is the measurement of metacognitive ability. However, the properties of existing measures of metacognition have been mostly assumed rather than empirically established. Here I perform a comprehensive empirical assessment of 17 measures of metacognition. First, I develop a method of determining the validity and precision of a measure of metacognition and find that all 17 measures are valid and most show similar levels of precision. Second, I examine how measures of metacognition depend on task performance, response bias, and metacognitive bias, finding only weak dependences on response and metacognitive bias but many strong dependencies on task performance. Third, I find that all measures have very high split-half reliabilities, but most have poor test-retest reliabilities. This comprehensive assessment paints a complex picture: no measure of metacognition is perfect and different measures may be preferable in different experimental contexts.

No gender difference in confidence or metacognitive ability in perceptual decision-making

Prior research has found inconsistent results regarding gender differences in confidence and metacognitive ability. Different studies have shown that men are either more or less confident and have either higher or lower metacognitive abilities than women. However, this research has generally not used well-controlled tasks or used performance-independent measures of metacognitive ability. Here, we test for gender differences in performance, confidence, and metacognitive ability using data from 10 studies from the Confidence Database (total N = 1,887, total number of trials = 633,168). We find an absence of strong gender differences in performance and no gender differences in either confidence or metacognitive ability. These results were further confirmed by meta-analyses of the 10 datasets. These findings show that it is unlikely that gender has a strong effect on metacognitive evaluation in low-level perceptual decision-making and suggest that previously observed gender differences in confidence and metacognition are likely domain-specific.

Confidence control for efficient behaviour in dynamic environments

Signatures of confidence emerge during decision-making, implying confidence may be of functional importance to decision processes themselves. We formulate an extension of sequential sampling models of decision-making in which confidence is used online to actively moderate the quality and quantity of evidence accumulated for decisions. The benefit of this model is that it can respond to dynamic changes in sensory evidence quality. We highlight this feature by designing a dynamic sensory environment where evidence quality can be smoothly adapted within the timeframe of a single decision. Our model with confidence control offers a superior description of human behaviour in this environment, compared to sequential sampling models without confidence control. Using multivariate decoding of electroencephalography (EEG), we uncover EEG correlates of the model's latent processes, and show stronger EEG-derived confidence control is associated with faster, more accurate decisions. These results support a neurobiologically plausible framework featuring confidence as an active control mechanism for improving behavioural efficiency.

Pharmacological Elevation of Catecholamine Levels Improves Perceptual Decisions, But Not Metacognitive Insight

Perceptual decisions are often accompanied by a feeling of decision confidence. Where the parietal cortex is known for its crucial role in shaping such perceptual decisions, metacognitive evaluations are thought to additionally rely on the (pre)frontal cortex. Because of this supposed neural differentiation between these processes, perceptual and metacognitive decisions may be divergently affected by changes in internal (e.g., attention, arousal) and external (e.g., task and environmental demands) factors. Although intriguing, causal evidence for this hypothesis remains scarce. Here, we investigated the causal effect of two neuromodulatory systems on behavioral and neural measures of perceptual and metacognitive decision-making. Specifically, we pharmacologically elevated levels of catecholamines (with atomoxetine) and acetylcholine (with donepezil) in healthy adult human participants performing a visual discrimination task in which we gauged decision confidence, while electroencephalography was measured. Where cholinergic effects were not robust, catecholaminergic enhancement improved perceptual sensitivity, while at the same time leaving metacognitive sensitivity unaffected. Neurally, catecholaminergic elevation did not affect sensory representations of task-relevant visual stimuli but instead enhanced well-known decision signals measured over the centroparietal cortex, reflecting the accumulation of sensory evidence over time. Crucially, catecholaminergic enhancement concurrently impoverished neural markers measured over the frontal cortex linked to the formation of metacognitive evaluations. Enhanced catecholaminergic neuromodulation thus improves perceptual but not metacognitive decision-making.

Confidence biases in problem gambling

Background and aims

Subjective confidence plays an important role in guiding behaviour, especially when objective feedback is unavailable. Systematic misjudgements in confidence can foster maladaptive behaviours and have been linked to various psychiatric disorders. In this study, we adopted a transdiagnostic approach to examine confidence biases in problem gamblers across three levels: local decision confidence, global task performance confidence, and overall self-esteem. The importance of taking a transdiagnostic perspective is increasingly recognised, as it captures the dimensional nature of psychiatric symptoms that often cut across diagnostic boundaries. Accordingly, we investigated if any observed confidence biases could be explained by transdiagnostic symptom dimensions of Anxiety-Depression and Compulsive Behaviour and Intrusive Thought. This approach allows us to gain a more comprehensive understanding of the role of metacognitive processes in problem gambling, beyond the constraints of traditional diagnostic categories.

Methods

Thirty-eight problem gamblers and 38 demographically matched control participants engaged in a gamified metacognition task and completed self-report questionnaires assessing transdiagnostic symptom dimensions.

Results

Compared to controls, problem gamblers displayed significantly elevated confidence at the local decision and global task levels, independent of their actual task performance. This elevated confidence was observed even after controlling for the heightened symptom levels of Anxiety-Depression and Compulsive Behaviour and Intrusive Thought among the problem gamblers.

Discussion

The results reveal a notable disparity in confidence levels between problem gamblers and control participants, not fully accounted for by the symptom dimensions Anxiety-Depression and Compulsive Behaviour and Intrusive Thought. This suggests the contribution of other factors, perhaps linked to gambling-specific cognitive distortions, to the observed confidence biases.

Conclusion

The findings highlight the intricate link between metacognitive confidence and psychiatric symptoms in the context of problem gambling. It underscores the need for further research into metacognitive biases, which could enhance therapeutic approaches for individuals with psychiatric conditions.

The influence of irrelevant emotionally negative stimuli on early and late retrospective metacognitive judgements

It is well established that negative emotions influence a range of cognitive processes. How these emotions influence the metacognitive judgement individuals make about their own performance and whether this influence is similar depending on the conditions under which metacognition is assessed, however, is far less understood. The primary aim of this study was to determine whether exposure to emotional stimuli could influence metacognitive judgements made under short or long time constraints. A total sample of 144 young adults (aged 18-35 years) was recruited and asked to complete an arithmetic strategy selection task under emotional or neutral condition. Following each strategy selection trial, participants also provided a retrospective confidence judgement (RCJ). Both strategy selection and RCJ were collected under short or long time constraints (1,500 vs. 2,500 ms for strategy selection and 800 vs. 1,500 ms for RCJ). In addition to replicating previous findings showing lower rates of better strategy selection under negative emotions compared with neutral condition, an effect of negative stimuli on the accuracy of participants' confidence judgements was found, but only if participants had a short time limit to make their second-level evaluation. Such findings are consistent with the hypothesis that exposure to emotional stimuli disturbs early, but not late metacognitive processes and have important implications to further our understanding of the role of emotions on metacognition.

Metacognitive evaluation of postdecisional perceptual representations

Perceptual confidence is thought to arise from metacognitive processes that evaluate the underlying perceptual decision evidence. We investigated whether metacognitive access to perceptual evidence is constrained by the hierarchical organization of visual cortex, where high-level representations tend to be more readily available for explicit scrutiny. We found that the ability of human observers to evaluate their confidence did depend on whether they performed a high-level or low-level task on the same stimuli, but was also affected by manipulations that occurred long after the perceptual decision. Confidence in low-level perceptual decisions degraded with more time between the decision and the response cue, especially when backward masking was present. Confidence in high-level tasks was immune to backward masking and benefitted from additional time. These results can be explained by a model assuming confidence heavily relies on postdecisional internal representations of visual stimuli that degrade over time, where high-level representations are more persistent.

Affective valence does not reflect progress prediction errors in perceptual decisions

Affective valence and intensity form the core of our emotional experiences. It has been proposed that affect reflects the prediction error between expected and actual states, such that better/worse-than-expected discrepancies result in positive/negative affect. However, whether the same principle applies to progress prediction errors remains unclear. We empirically and computationally evaluate the hypothesis that affect reflects the difference between expected and actual progress in forming a perceptual decision. We model affect within an evidence accumulation framework where actual progress is mapped onto the drift-rate parameter and expected progress onto an expected drift-rate parameter. Affect is computed as the difference between the expected and actual amount of accumulated evidence. We find that expected and actual progress both influence affect, but in an additive manner that does not align with a prediction error account. Our computational model reproduces both task behavior and affective ratings, suggesting that sequential sampling models provide a promising framework to model progress appraisals. These results show that although affect is sensitive to both expected and actual progress, it does not reflect the computation of a progress prediction error.

The future of metacognition research: Balancing construct breadth with measurement rigor

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 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, this notable progress in formalising models of metacognitive judgments may 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, and highlight promising avenues for expanding the scope of metacognition research. Such a research programme is well placed to recapture qualitative features of metacognitive knowledge and experience while maintaining the psychophysical rigor that characterises modern research on confidence and performance monitoring.

Metacognition and Confidence: A Review and Synthesis

Determining the psychological, computational, and neural bases of confidence and uncertainty holds promise for understanding foundational aspects of human metacognition. While a neuroscience of confidence has focused on the mechanisms underpinning subpersonal phenomena such as representations of uncertainty in the visual or motor system, metacognition research has been concerned with personal-level beliefs and knowledge about self-performance. I provide a road map for bridging this divide by focusing on a particular class of confidence computation: propositional confidence in one's own (hypothetical) decisions or actions. Propositional confidence is informed by the observer's models of the world and their cognitive system, which may be more or less accurate-thus explaining why metacognitive judgments are inferential and sometimes diverge from task performance. Disparate findings on the neural basis of uncertainty and performance monitoring are integrated into a common framework, and a new understanding of the locus of action of metacognitive interventions is developed.

Unskilled, underperforming, or unaware? Testing three accounts of individual differences in metacognitive monitoring

Many studies show that competence (e.g., skill, expertise, natural ability) influences individuals' capabilities of monitoring their item-level performance. However, debate persists about how best to explain these individual differences in metacognition. The competence-based account ascribes differences in monitoring to individuals' objective ability level, arguing that the same skills necessary to perform a task are required to effectively monitor performance. The performance-based account attributes differences in monitoring to changes in overall task performance - no individual differences in competence required. Finally, the metacognitive awareness account proposes that alignment between an individuals' self-assessed and objective ability leads to differences in monitoring. In this study, 603 participants completed a self-assessment of face recognition ability, a lineup identification task, and an objective assessment of face recognition ability. We manipulated the number of encoding repetitions and delay between encoding and test to produce varying levels of task performance across objective face recognition ability. Following each lineup decision, participants provided both a numeric confidence rating and a written expression of verbal confidence. We transformed verbal confidence into a quantitative value using machine learning techniques. When matched on overall identification accuracy, objectively stronger face recognizers used numeric and verbal confidence that a) better discriminates between correct and filler lineup identifications than weaker recognizers, and b) shows better calibration to accuracy. Participants with greater self-assessed ability used higher levels of confidence, irrespective of trial accuracy. These results support the competence-based account.

Self-motion perception and sequential decision-making: where are we heading?

To navigate and guide adaptive behaviour in a dynamic environment, animals must accurately estimate their own motion relative to the external world. This is a fundamentally multisensory process involving integration of visual, vestibular and kinesthetic inputs. Ideal observer models, paired with careful neurophysiological investigation, helped to reveal how visual and vestibular signals are combined to support perception of linear self-motion direction, or heading. Recent work has extended these findings by emphasizing the dimension of time, both with regard to stimulus dynamics and the trade-off between speed and accuracy. Both time and certainty-i.e. the degree of confidence in a multisensory decision-are essential to the ecological goals of the system: terminating a decision process is necessary for timely action, and predicting one's accuracy is critical for making multiple decisions in a sequence, as in navigation. Here, we summarize a leading model for multisensory decision-making, then show how the model can be extended to study confidence in heading discrimination. Lastly, we preview ongoing efforts to bridge self-motion perception and navigation per se, including closed-loop virtual reality and active self-motion. The design of unconstrained, ethologically inspired tasks, accompanied by large-scale neural recordings, raise promise for a deeper understanding of spatial perception and decision-making in the behaving animal. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

On why we lack confidence in some signal-detection-based analyses of confidence

Signal-detection theory (SDT) is one of the most popular frameworks for analyzing data from studies of human behavior - including investigations of confidence. SDT-based analyses of confidence deliver both standard estimates of sensitivity (d'), and a second estimate informed by high-confidence decisions - meta d'. The extent to which meta d' estimates fall short of d' estimates is regarded as a measure of metacognitive inefficiency, quantifying the contamination of confidence by additional noise. These analyses rely on a key but questionable assumption - that repeated exposures to an input will evoke a normally-shaped distribution of perceptual experiences (the normality assumption). Here we show, via analyses inspired by an experiment and modelling, that when distributions of experience do not conform with the normality assumption, meta d' can be systematically underestimated relative to d'. Our data highlight that SDT-based analyses of confidence do not provide a ground truth measure of human metacognitive inefficiency. We explain why deviance from the normality assumption is especially a problem for some popular SDT-based analyses of confidence, in contrast to other analyses inspired by the SDT framework, which are more robust to violations of the normality assumption.

Metacognitive Information Theory

The capacity that subjects have to rate confidence in their choices is a form of metacognition, and can be assessed according to bias, sensitivity and efficiency. Rich networks of domain-specific and domain-general regions of the brain are involved in the rating, and are associated with its quality and its use for regulating the processes of thinking and acting. Sensitivity and efficiency are often measured by quantities called meta-d' and the M-ratio that are based on reverse engineering the potential accuracy of the original, primary, choice that is implied by the quality of the confidence judgements. Here, we advocate a straightforward measure of sensitivity, called meta-𝓘, which assesses the mutual information between the accuracy of the subject's choices and the confidence reports, and two normalized versions of this measure that quantify efficiency in different regimes. Unlike most other measures, meta-𝓘-based quantities increase with the number of correctly assessed bins with which confidence is reported. We illustrate meta-𝓘 on data from a perceptual decision-making task, and via a simple form of simulated second-order metacognitive observer.

Feeling lucky? prospective and retrospective cues for sensorimotor confidence

On a daily basis, humans interact with the outside world using judgments of sensorimotor confidence, constantly evaluating our actions for success. We ask, what sensory and motor-execution cues are used in making these judgements and when are they available? Two sources of temporally distinct information are prospective cues, available prior to the action (e.g., knowledge of motor noise and past performance), and retrospective cues specific to the action itself (e.g., proprioceptive measurements). We investigated the use of these two cues in two tasks, a secondary motor-awareness task and a main task in which participants reached toward a visual target with an unseen hand and then made a continuous judgment of confidence about the success of the reach. Confidence was reported by setting the size of a circle centered on the reach-target location, where a larger circle reflects lower confidence. Points were awarded if the confidence circle enclosed the true endpoint, with fewer points returned for larger circles. This incentivized accurate reaches and attentive reporting to maximize the score. We compared three Bayesian-inference models of sensorimotor confidence based on either prospective cues, retrospective cues, or both sources of information to maximize expected gain (i.e., an ideal-performance model). Our findings showed two distinct strategies: participants either performed as ideal observers, using both prospective and retrospective cues to make the confidence judgment, or relied solely on prospective information, ignoring retrospective cues. Thus, participants can make use of retrospective cues, evidenced by the behavior observed in our motor-awareness task, but these cues are not always included in the computation of sensorimotor confidence.

Age-related decreases in global metacognition are independent of local metacognition and task performance

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 "local" metacognition (monitoring of individual judgments) and "global" metacognition (estimates of self-performance) change across the lifespan. Additionally, the degree to which metacognition generalises across cognitive domains may itself change with age due to increased experience with one's own abilities. Using a gamified suite of performance-controlled memory and visual perception tasks, we measured local and global metacognition 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 quantified how and whether domain-generality changes with age. First-order task performance was stable across the age range. People's global self-performance estimates and local metacognitive bias decreased with age, indicating overall lower confidence in performance. In contrast, local metacognitive efficiency was spared in older 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 reveals how local and global metacognition change across the lifespan and provide a benchmark against which disease-related changes in metacognition can be compared.