Visual Confidence

Distinct basal ganglia contributions to learning from implicit and explicit value signals in perceptual decision-making

Metacognitive evaluations of confidence provide an estimate of decision accuracy that could guide learning in the absence of explicit feedback. We examine how humans might learn from this implicit feedback in direct comparison with that of explicit feedback, using simultaneous EEG-fMRI. Participants performed a motion direction discrimination task where stimulus difficulty was increased to maintain performance, with intermixed explicit- and no-feedback trials. We isolate single-trial estimates of post-decision confidence using EEG decoding, and find these neural signatures re-emerge at the time of feedback together with separable signatures of explicit feedback. We identified these signatures of implicit versus explicit feedback along a dorsal-ventral gradient in the striatum, a finding uniquely enabled by an EEG-fMRI fusion. These two signals appear to integrate into an aggregate representation in the external globus pallidus, which could broadcast updates to improve cortical decision processing via the thalamus and insular cortex, irrespective of the source of feedback.

Abstract deliberation by visuomotor neurons in prefrontal cortex

During visually guided behavior, the prefrontal cortex plays a pivotal role in mapping sensory inputs onto appropriate motor plans. When the sensory input is ambiguous, this involves deliberation. It is not known whether the deliberation is implemented as a competition between possible stimulus interpretations or between possible motor plans. Here we study neural population activity in the prefrontal cortex of macaque monkeys trained to flexibly report perceptual judgments of ambiguous visual stimuli. We find that the population activity initially represents the formation of a perceptual choice before transitioning into the representation of the motor plan. Stimulus strength and prior expectations both bear on the formation of the perceptual choice, but not on the formation of the action plan. These results suggest that prefrontal circuits involved in action selection are also used for the deliberation of abstract propositions divorced from a specific motor plan, thus providing a crucial mechanism for abstract reasoning.

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

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

Measuring the perception and metacognition of time

The ability of humans to identify and reproduce short time intervals (in the region of a second) may be affected by many factors ranging from the gender and personality of the individual observer, through the attentional state, to the precise spatiotemporal structure of the stimulus. The relative roles of these very different factors are a challenge to describe and define; several methodological approaches have been used to achieve this to varying degrees of success. Here we describe and model the results of a paradigm affording not only a first-order measurement of the perceived duration of an interval but also a second-order metacognitive judgement of perceived time. This approach, we argue, expands the form of the data generally collected in duration-judgements and allows more detailed comparison of psychophysical behavior to the underlying theory. We also describe a hierarchical Bayesian measurement model that performs a quantitative analysis of the trial-by-trial data calculating the variability of the temporal estimates and the metacognitive judgments allowing direct comparison between an actual and an ideal observer. We fit the model to data collected for judgements of 750 ms (bisecting 1500 ms) and 1500 ms (bisecting 3000 ms) intervals across three stimulus modalities (visual, audio, and audiovisual). This enhanced form of data on a given interval judgement and the ability to track its progression on a trial-by-trial basis offers a way of looking at the different roles that subject-based, task-based and stimulus-based factors have on the perception of time.

Human-like dissociations between confidence and accuracy in convolutional neural networks

Prior research has shown that manipulating stimulus energy by changing both stimulus contrast and variability results in confidence-accuracy dissociations in humans. Specifically, even when performance is matched, higher stimulus energy leads to higher confidence. The most common explanation for this effect is the positive evidence heuristic where confidence neglects evidence that disconfirms the choice. However, an alternative explanation is the signal-and-variance-increase hypothesis, according to which these dissociations arise from low-level changes in the separation and variance of perceptual representations. Because artificial neural networks lack built-in confidence heuristics, they can serve as a test for the necessity of confidence heuristics in explaining confidence-accuracy dissociations. Therefore, we tested whether confidence-accuracy dissociations induced by stimulus energy manipulations emerge naturally in convolutional neural networks (CNNs). We found that, across three different energy manipulations, CNNs produced confidence-accuracy dissociations similar to those found in humans. This effect was present for a range of CNN architectures from shallow 4-layer networks to very deep ones, such as VGG-19 and ResNet -50 pretrained on ImageNet. Further, we traced back the reason for the confidence-accuracy dissociations in all CNNs to the same signal-and-variance increase that has been proposed for humans: higher stimulus energy increased the separation and variance of the CNNs' internal representations leading to higher confidence even for matched accuracy. These findings cast doubt on the necessity of the positive evidence heuristic to explain human confidence and establish CNNs as promising models for adjudicating between low-level, stimulus-driven and high-level, cognitive explanations of human behavior.

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.

Dopamine precursor depletion affects performance and confidence judgements when events are timed from an explicit, but not an implicit onset

Dopamine affects processing of temporal information, but most previous work has tested its role in prospective tasks, where participants know in advance when the event to be timed starts. However, we are often exposed to events whose onset we do not know in advance. We can evaluate their duration after they have elapsed, but mechanisms underlying this ability are still elusive. Here we contrasted effects of acute phenylalanine and tyrosine depletion (APTD) on both forms of timing in healthy volunteers, in a within-subject, placebo-controlled design. Participants were presented with a disc moving around a circular path and asked to reproduce the duration of one full revolution and to judge their confidence in performance. The onset of the revolution was either known in advance (explicit onset) or revealed only at the end of the trial (implicit onset). We found that APTD shortened reproduced durations in the explicit onset task but had no effect on temporal performance in the implicit onset task. This dissociation is corroborated by effects of APTD on confidence judgements in the explicit task only. Our findings suggest that dopamine has a specific role in prospective encoding of temporal intervals, rather than the processing of temporal information in general.

Confidence judgments are associated with face identification accuracy: Findings from a confidence forced-choice task

Confidence is assumed to be an indicator of identification accuracy in legal practices (e.g., forensic face examination). However, it is not clear whether people can evaluate the correctness of their face-identification decisions reliably using confidence reports. In the current experiment, confidence in the correctness of the perceptual decision was measured with a confidence forced-choice methodology: Upon completion of two perceptual face-identity matching trials, the participants were asked to compare the two decisions and to select the trial on which they felt more confident. On each face-identity matching trial, participants viewed three face images (two same-identity images, one different-identity image) and were instructed to select the image of the different identity. In order to measure the extent to which difficulty level informs confidence decisions, we selected face-image triads using item-difficulty estimates extracted from psychometric modeling applied in a prior study. The difference in difficulty between the paired face-image triads predicted the proportion of high-confidence judgments allocated to the easier trial of the pair. Consistent with the impact of difficulty monitoring on confidence judgments, performance was significantly more accurate on trials associated with higher confidence. Overall, the results suggested that people reliably evaluate the correctness of their perceptual face-identity matching decisions and use trial difficulty to evaluate confidence.

A Shared Intuitive (Mis)understanding of Psychophysical Law Leads Both Novices and Educated Students to Believe in a Just Noticeable Difference (JND)

Humans are both the scientists who discover psychological laws and the thinkers who behave according to those laws. Oftentimes, when our natural behavior is in accord with those laws, this dual role serves us well: our intuitions about our own behavior can serve to inform our discovery of new laws. But, in cases where the laws that we discover through science do not agree with the intuitions and biases we carry into the lab, we may find it harder to believe in and adopt those laws. Here, we explore one such case. Since the founding of psychophysics, the notion of a Just Noticeable Difference (JND) in perceptual discrimination has been ubiquitous in experimental psychology-even in spite of theoretical advances since the 1950's that argue that there can be no such thing as a threshold in perceiving difference. We find that both novices and psychologically educated students alike misunderstand the JND to mean that, below a certain threshold, humans will be unable to tell which of two quantities is greater (e.g., that humans will be completely at chance when trying to judge which is heavier, a bag with 3000 grains of sand or 3001). This belief in chance performance below a threshold is inconsistent with psychophysical law. We argue that belief in a JND is part of our intuitive theory of psychology and is therefore very difficult to dispel.

Metacognitive awareness in the sound-induced flash illusion

Hundreds (if not thousands) of multisensory studies provide evidence that the human brain can integrate temporally and spatially discrepant stimuli from distinct modalities into a singular event. This process of multisensory integration is usually portrayed in the scientific literature as contributing to our integrated, coherent perceptual reality. However, missing from this account is an answer to a simple question: how do confidence judgements compare between multisensory information that is integrated across multiple sources, and multisensory information that comes from a single, congruent source in the environment? In this paper, we use the sound-induced flash illusion to investigate if confidence judgements are similar across multisensory conditions when the numbers of auditory and visual events are the same, and the numbers of auditory and visual events are different. Results showed that congruent audiovisual stimuli produced higher confidence than incongruent audiovisual stimuli, even when the perceptual report was matched across the two conditions. Integrating these behavioural findings with recent neuroimaging and theoretical work, we discuss the role that prefrontal cortex may play in metacognition, multisensory causal inference and sensory source monitoring in general. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Metacognition in the audiovisual McGurk illusion: perceptual and causal confidence

Almost all decisions in everyday life rely on multiple sensory inputs that can come from common or independent causes. These situations invoke perceptual uncertainty about environmental properties and the signals' causal structure. Using the audiovisual McGurk illusion, this study investigated how observers formed perceptual and causal confidence judgements in information integration tasks under causal uncertainty. Observers were presented with spoken syllables, their corresponding articulatory lip movements or their congruent and McGurk combinations (e.g. auditory B/P with visual G/K). Observers reported their perceived auditory syllable, the causal structure and confidence for each judgement. Observers were more accurate and confident on congruent than unisensory trials. Their perceptual and causal confidence were tightly related over trials as predicted by the interactive nature of perceptual and causal inference. Further, observers assigned comparable perceptual and causal confidence to veridical 'G/K' percepts on audiovisual congruent trials and their causal and perceptual metamers on McGurk trials (i.e. illusory 'G/K' percepts). Thus, observers metacognitively evaluate the integrated audiovisual percept with limited access to the conflicting unisensory stimulus components on McGurk trials. Collectively, our results suggest that observers form meaningful perceptual and causal confidence judgements about multisensory scenes that are qualitatively consistent with principles of Bayesian causal inference. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Metacognitive bias resulting from trade-off between local and global motion signals

Visual confidence generally depends on performance in targeted perceptual tasks. However, it remains unclear how factors unrelated to performance affect confidence. Given the hierarchical nature of visual processing, both local and global stimulus features can influence confidence, but their strengths of influence remain unknown. To address this question, we independently manipulated the local contrast signals and the global coherence signals in a multiple-aperture motion pattern. The drifting-Gabor elements were individually manipulated to give rise to a coherent global motion percept. In both dichotomous direction-discrimination task (Experiment 1) and analog direction-judgment task (Experiment 2), we found stimulus-dependent biases in metacognition despite matched perceptual performance. Specifically, participants systematically gave higher confidence ratings to an incoherent pattern with clear elements (i.e., strong local but weak global signals) than a coherent pattern with noisy elements (i.e., weak local but strong global signals). We did not find any systematic effects of local/global stimulus features on metacognitive sensitivity. Model comparisons show that variation in local/global signals in the stimulus should be considered a factor influencing confidence, even after controlling for the effects of performance. Our results suggest that the metacognitive system, when generating confidence for a perceptual task, puts more weights on local than global signals.

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.

Common computations in automatic cue combination and metacognitive confidence reports

Appropriate perceptual decision making necessitates the accurate estimation and use of sensory uncertainty. Such estimation has been studied in the context of both low-level multisensory cue combination and metacognitive estimation of confidence, but it remains unclear whether the same computations underlie both sets of uncertainty estimation. We created visual stimuli with low vs. high overall motion energy, such that the high-energy stimuli led to higher confidence but lower accuracy in a visual-only task. Importantly, we tested the impact of the low- and high-energy visual stimuli on auditory motion perception in a separate task. Despite being irrelevant to the auditory task, both visual stimuli impacted auditory judgments presumably via automatic low-level mechanisms. Critically, we found that the high-energy visual stimuli influenced the auditory judgments more strongly than the low-energy visual stimuli. This effect was in line with the confidence but contrary to the accuracy differences between the high- and low-energy stimuli in the visual-only task. These effects were captured by a simple computational model that assumes common computational principles underlying both confidence reports and multisensory cue combination. Our results reveal a deep link between automatic sensory processing and metacognitive confidence reports, and suggest that vastly different stages of perceptual decision making rely on common computational principles.

Differences in the detail: Metacognition is better for seen than sensed changes to visual scenes

Metacognition is the process by which we know what we know. Knowing has both declarative and sensed components. Differences exist in the information that moves to our conscious awareness and how it is synthesised with existing knowledge. The current study measured metacognition by extending a visual change detection paradigm that promoted explicit or implicit detection by either a local or global manipulation of a scene. A within-subjects design was used to investigate how 91 participants detected change and made metacognitive judgements. Cognitive modelling, based on confidence judgements, estimated the relative contributions of discrete and continuous cognitive processes to change detection, and to metacognition. Metacognition was sensitive to both the discrete and continuous processes underlying change detection, but was more sensitive to the discrete process. These results demonstrate that metacognition attunes confidence differentially to explicit and implicit processes, and support direct-access theories for discrete processing and meta-representation theories for continuous processing.

Cross-modal metacognition: Visual and tactile confidence share a common scale

Humans can judge the quality of their perceptual decisions-an ability known as perceptual confidence. Previous work suggested that confidence can be evaluated on an abstract scale that can be sensory modality-independent or even domain-general. However, evidence is still scarce on whether confidence judgments can be directly made across visual and tactile decisions. Here, we investigated in a sample of 56 adults whether visual and tactile confidence share a common scale by measuring visual contrast and vibrotactile discrimination thresholds in a confidence-forced choice paradigm. Confidence judgments were made about the correctness of the perceptual decision between two trials involving either the same or different modalities. To estimate confidence efficiency, we compared discrimination thresholds obtained from all trials to those from trials judged to be relatively more confident. We found evidence for metaperception because higher confidence was associated with better perceptual performance in both modalities. Importantly, participants were able to judge their confidence across modalities without any costs in metaperceptual sensitivity and only minor changes in response times compared to unimodal confidence judgments. In addition, we were able to predict cross-modal confidence well from unimodal judgments. In conclusion, our findings show that perceptual confidence is computed on an abstract scale and that it can assess the quality of our decisions across sensory modalities.

The presence of irrelevant alternatives paradoxically increases confidence in perceptual decisions

Confidence in perceptual decisions is thought to reflect the probability of being correct. According to this view, confidence should be unaffected or minimally reduced by the presence of irrelevant alternatives. To test this prediction, we designed five experiments. In Experiment 1, participants had to identify the largest geometrical shape among two or three alternatives. In the three-alternative condition, one of the shapes was much smaller than the other two, being a clearly incorrect option. Counter-intuitively, confidence was higher when the irrelevant alternative was present, evidencing that confidence construction is more complex than previously thought. Four computational models were tested, only one of them accounting for the results. This model predicts that confidence increases monotonically with the number of irrelevant alternatives, a prediction we tested in Experiment 2. In Experiment 3, we evaluated whether this effect replicated in a categorical task, but we did not find supporting evidence. Experiments 4 and 5 allowed us to discard stimuli presentation time as a factor driving the effect. Our findings suggest that confidence models cannot ignore the effect of multiple, possibly irrelevant alternatives to build a thorough understanding of confidence.

Re-evaluating frontopolar and temporoparietal contributions to detection and discrimination confidence

Previously, we identified a subset of regions where the relation between decision confidence and univariate functional magnetic resonance imaging (fMRI) activity was quadratic, with stronger activation for both high and low compared with intermediate levels of confidence. We further showed that, in a subset of these regions, this quadratic modulation appeared only for confidence in detection decisions about the presence or absence of a stimulus, and not for confidence in discrimination decisions about stimulus identity (Mazor et al. 2021). Here, in a pre-registered follow-up experiment, we sought to replicate our original findings and identify the origins of putative detection-specific confidence signals by introducing a novel asymmetric-discrimination condition. The new condition required discriminating two alternatives but was engineered such that the distribution of perceptual evidence was asymmetric, just as in yes/no detection. We successfully replicated the quadratic modulation of subjective confidence in prefrontal, parietal and temporal cortices. However, in contrast with our original report, this quadratic effect was similar in detection and discrimination responses, but stronger in the novel asymmetric-discrimination condition. We interpret our findings as weighing against the detection-specificity of confidence signatures and speculate about possible alternative origins of a quadratic modulation of decision confidence.

Underestimation of the number of hidden objects

The perceptual representation of our environment does not only involve what we actually can see, but also inferences about what is hidden from our sight. For example, in amodal completion, simple contours or surfaces are filled-in behind occluding objects allowing for a complete representation. This is important for many everyday tasks, such as visual search, foraging, and object handling. Although there is support for completion of simple patterns from behavioral and neurophysiological studies, it is unclear if these mechanisms extend to complex, irregular patterns. Here, we show that the number of hidden objects on partially occluded surfaces is underestimated. Observers did not consider accurately the number of visible objects and the proportion of occlusion to infer the number of hidden objects, although these quantities were perceived accurately and reliably. However, visible objects were not simply ignored: estimations of hidden objects increased when the visible objects formed a line across the occluder and decreased when the visible objects formed a line outside of the occluder. Confidence ratings for numerosity estimation were similar for fully visible and partially occluded surfaces. These results suggest that perceptual inferences about what is hidden in our environment can be very inaccurate und underestimate the complexity of the environment.

Can individual subjective confidence in training questions predict group performance in test questions?

When people have to solve many tasks, they can aggregate diverse individuals' judgments using the majority rule, which often improves the accuracy of judgments (wisdom of crowds). When aggregating judgments, individuals' subjective confidence is a useful cue for deciding which judgments to accept. However, can confidence in one task set predict performance not only in the same task set, but also in another? We examined this issue through computer simulations using behavioral data obtained from binary-choice experimental tasks. In our simulations, we developed a "training-test" approach: We split the questions used in the behavioral experiments into "training questions" (as questions to identify individuals' confidence levels) and "test questions" (as questions to be solved), similar to the cross-validation method in machine learning. We found that (i) through analyses of behavioral data, confidence in a certain question could predict accuracy in the same question, but not always well in another question. (ii) Through a computer simulation for the accordance of two individuals' judgments, individuals with high confidence in one training question tended to make less diverse judgments in other test questions. (iii) Through a computer simulation of group judgments, the groups constructed from individuals with high confidence in the training question(s) generally performed well; however, their performance sometimes largely decreased in the test questions especially when only one training question was available. These results suggest that when situations are highly uncertain, an effective strategy is to aggregate various individuals regardless of confidence levels in the training questions to avoid decreasing the group accuracy in test questions. We believe that our simulations, which follow a "training-test" approach, provide practical implications in terms of retaining groups' ability to solve many tasks.

Confidence reflects a noisy decision reliability estimate

Decisions vary in difficulty. Humans know this and typically report more confidence in easy than in difficult decisions. However, confidence reports do not perfectly track decision accuracy, but also reflect response biases and difficulty misjudgements. To isolate the quality of confidence reports, we developed a model of the decision-making process underlying choice-confidence data. In this model, confidence reflects a subject's estimate of the reliability of their decision. The quality of this estimate is limited by the subject's uncertainty about the uncertainty of the variable that informs their decision ('meta-uncertainty'). This model provides an accurate account of choice-confidence data across a broad range of perceptual and cognitive tasks, investigated in six previous studies. We find meta-uncertainty varies across subjects, is stable over time, generalizes across some domains and can be manipulated experimentally. The model offers a parsimonious explanation for the computational processes that underlie and constrain the sense of confidence.

The development of audio-visual temporal precision precedes its rapid recalibration

Through development, multisensory systems reach a balance between stability and flexibility: the systems integrate optimally cross-modal signals from the same events, while remaining adaptive to environmental changes. Is continuous intersensory recalibration required to shape optimal integration mechanisms, or does multisensory integration develop prior to recalibration? Here, we examined the development of multisensory integration and rapid recalibration in the temporal domain by re-analyzing published datasets for audio-visual, audio-tactile, and visual-tactile combinations. Results showed that children reach an adult level of precision in audio-visual simultaneity perception and show the first sign of rapid recalibration at 9 years of age. In contrast, there was very weak rapid recalibration for other cross-modal combinations at all ages, even when adult levels of temporal precision had developed. Thus, the development of audio-visual rapid recalibration appears to require the maturation of temporal precision. It may serve to accommodate distance-dependent travel time differences between light and sound.

Calibrating Vision: Concepts and Questions

The idea that visual coding and perception are shaped by experience and adjust to changes in the environment or the observer is universally recognized as a cornerstone of visual processing, yet the functions and processes mediating these calibrations remain in many ways poorly understood. In this article we review a number of facets and issues surrounding the general notion of calibration, with a focus on plasticity within the encoding and representational stages of visual processing. These include how many types of calibrations there are - and how we decide; how plasticity for encoding is intertwined with other principles of sensory coding; how it is instantiated at the level of the dynamic networks mediating vision; how it varies with development or between individuals; and the factors that may limit the form or degree of the adjustments. Our goal is to give a small glimpse of an enormous and fundamental dimension of vision, and to point to some of the unresolved questions in our understanding of how and why ongoing calibrations are a pervasive and essential element of vision.

Optimal integration of kinematic and ball-flight information when perceiving the speed of a moving ball

In order to intercept a moving target such as a baseball with high spatio-temporal accuracy, the perception of the target's movement speed is important for estimating when and where the target will arrive. However, it is unclear what sources of information are used by a batter to estimate ball speed and how those sources of information are integrated to facilitate successful interception. In this study, we examined the degree to which kinematic and ball-flight information are integrated when estimating ball speed in baseball batting. Thirteen university level baseball batters performed a ball-speed evaluation task in a virtual environment where they were required to determine which of two comparison baseball pitches (i.e., a reference and comparison stimuli) they perceived to be faster. The reference and comparison stimuli had the same physical ball speed, but with different pitching movement speeds in the comparison stimuli. The task was performed under slow (125 km/h) and fast (145 km/h) ball-speed conditions. Results revealed that the perceived ball-speed was influenced by the movement speed of the pitcher's motion, with the influence of the pitcher's motion more pronounced in the fast ball-speed condition when ball-flight information was presumably less reliable. Moreover, exploratory analyses suggested that the more skilled batters were increasingly likely to integrate the two sources of information according to their relative reliability when making judgements of ball speed. The results provide important insights into how skilled performers may make judgements of speed and time to contact, and further enhance our understanding of how the ability to make those judgements might improve when developing expertise in hitting.

Metacognition tracks sensitivity following involuntary shifts of visual attention

Salient, exogenous cues have been shown to induce a temporary boost of perceptual sensitivity in their immediate vicinity. In two experiments involving uninformative exogenous cues presented at various times before a target stimulus, we investigated whether human observers (N = 100) were able to monitor the involuntary increase in performance induced by such transients. We found that an increase of perceptual sensitivity (in a choice task) and encoding precision (in a free-estimation task) occurred approximately 100 ms after cue onset, and was accompanied by an increase in confidence about the perceptual response. These simultaneous changes in sensitivity and confidence resulted in stable metacognition across conditions. These results suggest that metacognition efficiently tracks the effects of a reflexive attentional mechanism known to evade voluntary control, and illustrate a striking ability of high-level cognition to capture fleeting, low-level sensory modulations.

Consensus Goals in the Field of Visual Metacognition

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

Confidence at the limits of human nested cognition

Metacognition is the ability to weigh the quality of our own cognition, such as the confidence that our perceptual decisions are correct. Here we ask whether metacognitive performance can itself be evaluated or else metacognition is the ultimate reflective human faculty. Building upon a classic visual perception task, we show that human observers are able to produce nested, above-chance judgements on the quality of their decisions at least up to the fourth order (i.e. meta-meta-meta-cognition). A computational model can account for this nested cognitive ability if evidence has a high-resolution representation, and if there are two kinds of noise, including recursive evidence degradation. The existence of fourth-order sensitivity suggests that the neural mechanisms responsible for second-order metacognition can be flexibly generalized to evaluate any cognitive process, including metacognitive evaluations themselves. We define the theoretical and practical limits of nested cognition and discuss how this approach paves the way for a better understanding of human self-regulation.

Perceptual confidence of visual stimulus features is associated with duration perception

It has been shown that the perceived duration of an object in the subsecond range is closely associated with its nontemporal perceptual properties, the mechanism under which remains unclear. Previous studies have revealed a modulatory effect of early visual feature processing on the apparent duration. Here, we further examined the relationship between perceptual confidence and subjective time by asking participants to simultaneously perform temporal and nontemporal perceptual judgments. The results revealed a significant effect on confidence levels. When participants' confidence in judging the coherent motion direction or relative dot numerosity increases, their perceived duration of the stimulus also appears longer. These results are discussed in the context of perceptual evidence accumulation and evaluation for the decision-making of perceptual properties. They suggest a profound contribution of object processing to the computation of subjective time and provide further insights into the mechanism of event timing.

Suprathreshold perceptual decisions constrain models of confidence

Perceptual confidence is an important internal signal about the certainty of our decisions and there is a substantial debate on how it is computed. We highlight three confidence metric types from the literature: observers either use 1) the full probability distribution to compute probability correct (Probability metrics), 2) point estimates from the perceptual decision process to estimate uncertainty (Evidence-Strength metrics), or 3) heuristic confidence from stimulus-based cues to uncertainty (Heuristic metrics). These metrics are rarely tested against one another, so we examined models of all three types on a suprathreshold spatial discrimination task. Observers were shown a cloud of dots sampled from a dot generating distribution and judged if the mean of the distribution was left or right of centre. In addition to varying the horizontal position of the mean, there were two sensory uncertainty manipulations: the number of dots sampled and the spread of the generating distribution. After every two perceptual decisions, observers made a confidence forced-choice judgement whether they were more confident in the first or second decision. Model results showed that the majority of observers were best-fit by either: 1) the Heuristic model, which used dot cloud position, spread, and number of dots as cues; or 2) an Evidence-Strength model, which computed the distance between the sensory measurement and discrimination criterion, scaled according to sensory uncertainty. An accidental repetition of some sessions also allowed for the measurement of confidence agreement for identical pairs of stimuli. This N-pass analysis revealed that human observers were more consistent than their best-fitting model would predict, indicating there are still aspects of confidence that are not captured by our modelling. As such, we propose confidence agreement as a useful technique for computational studies of confidence. Taken together, these findings highlight the idiosyncratic nature of confidence computations for complex decision contexts and the need to consider different potential metrics and transformations in the confidence computation.

The feeling of confidence in what we perceive can influence our future behaviour and learning. Understanding how the brain computes confidence is an important goal of researchers. As such, researchers have identified a host of potential models. Yet, rarely are a wide range of models tested against each other to find those that best predict choice behaviour. Our study had human participants compare their confidence for pairs of easy perceptual decisions, reporting if they had higher confidence in the first or second decision. We tested twelve models, covering all three types of models proposed in previous studies, finding strong support for two models. The winning Heuristic model combines all three factors affecting choice uncertainty with an idiosyncratic weighting to compute confidence. The other winning model uses a transformation where the strength of the sensory signal is scaled according to sensory uncertainty. We also assessed the agreement of confidence reports in identical decision scenarios. Humans had higher agreement than almost all model predictions. We propose using confidence agreement intentionally as a second performance benchmark of model fit.

Age-related differences in visual confidence are driven by individual differences in cognitive control capacities

Visual perception is not only shaped by sensitivity but also by confidence, i.e., the ability to estimate the accuracy of a visual decision. Younger observers have been reported to have access to a reliable measure of their own uncertainty when making visual decisions. This metacognitive ability might be challenged during ageing due to increasing sensory noise and decreasing cognitive control resources. We investigated age effects on visual confidence using a visual contrast discrimination task and a confidence forced-choice paradigm. Younger adults (19–38 years) showed significantly lower discrimination thresholds than older adults (60–78 years). To focus on confidence sensitivity above and beyond differences in discrimination performance, we estimated confidence efficiency that reflects the ability to distinguish good from bad perceptual decisions. Confidence efficiency was estimated by comparing thresholds obtained from all trials and trials that were judged with relatively higher confidence, respectively. In both age groups, high confidence judgments were associated with better visual performance, but confidence efficiency was reduced in older adults. However, we observed substantial variability across all participants. Controlling for age group, confidence effciency was closely linked to individual differences in cognitive control capacities. Our findings provide evidence for age-related differences in confidence efficiency that present a specific challenge to perceptual performance in old age. We propose that these differences are driven by cognitive control capacities, supporting their crucial role for metacognitive efficiency.

Humans represent the precision and utility of information acquired across fixations

Our environment contains an abundance of objects which humans interact with daily, gathering visual information using sequences of eye-movements to choose which object is best-suited for a particular task. This process is not trivial, and requires a complex strategy where task affordance defines the search strategy, and the estimated precision of the visual information gathered from each object may be used to track perceptual confidence for object selection. This study addresses the fundamental problem of how such visual information is metacognitively represented and used for subsequent behaviour, and reveals a complex interplay between task affordance, visual information gathering, and metacogntive decision making. People fixate higher-utility objects, and most importantly retain metaknowledge about how much information they have gathered about these objects, which is used to guide perceptual report choices. These findings suggest that such metacognitive knowledge is important in situations where decisions are based on information acquired in a temporal sequence.

Subjective confidence reflects representation of Bayesian probability in cortex

What gives rise to the human sense of confidence? Here, we tested the Bayesian hypothesis that confidence is based on a probability distribution represented in neural population activity. We implemented several computational models of confidence, and tested their predictions using psychophysics and fMRI. Using a generative model-based fMRI decoding approach, we extracted probability distributions from neural population activity in human visual cortex. We found that subjective confidence tracks the shape of the decoded distribution. That is, when sensory evidence was more precise, as indicated by the decoded distribution, observers reported higher levels of confidence. We furthermore found that neural activity in the insula, anterior cingulate, and prefrontal cortex was linked to both the shape of the decoded distribution and reported confidence, in ways consistent with the Bayesian model. Altogether, our findings support recent statistical theories of confidence and suggest that probabilistic information guides the computation of one’s sense of confidence.

Reduced Context Updating but Intact Visual Priors in Autism

A general consensus persists that sensory-perceptual differences in autism, such as hypersensitivities to light or sound, result from an overreliance on new (rather than prior) sensory observations. However, conflicting Bayesian accounts of autism remain unresolved as to whether such alterations are caused by more precise sensory observations (precise likelihood model) or by forming a less precise model of the sensory context (hypo-priors model). We used a decision-under-uncertainty paradigm that manipulated uncertainty in both likelihoods and priors. Contrary to model predictions we found no differences in reliance on likelihood in autistic group (AS) compared to neurotypicals (NT) and found no differences in subjective prior variance between groups. However, we found reduced context adjustment in the AS group compared to NT. Further, the AS group showed heightened variability in their relative weighting of sensory information (vs. prior) on a trial-by-trial basis. When participants were aligned on a continuum of autistic traits, we found no associations with likelihood reliance or prior variance but found an increase in likelihood precision with autistic traits. These findings together provide empirical evidence for intact priors, precise likelihood, reduced context updating and heightened variability during sensory learning in autism.

A robust confidence-accuracy dissociation via criterion attraction

Many studies have shown that confidence and accuracy can be dissociated in a variety of tasks. However, most of these dissociations involve small effect sizes, occur only in a subset of participants, and include a reaction time (RT) confound. Here, I develop a new method for inducing confidence-accuracy dissociations that overcomes these limitations. The method uses an external noise manipulation and relies on the phenomenon of criterion attraction where criteria for different tasks become attracted to each other. Subjects judged the identity of stimuli generated with either low or high external noise. The results showed that the two conditions were matched on accuracy and RT but produced a large difference in confidence (effect appeared for 25 of 26 participants, effect size: Cohen's d = 1.9). Computational modeling confirmed that these results are consistent with a mechanism of criterion attraction. These findings establish a new method for creating conditions with large differences in confidence without differences in accuracy or RT. Unlike many previous studies, however, the current method does not lead to differences in subjective experience and instead produces robust confidence-accuracy dissociations by exploiting limitations in post-perceptual, cognitive processes.

Effective Plug-Ins for Reducing Inference-Latency of Spiking Convolutional Neural Networks During Inference Phase

Convolutional Neural Networks (CNNs) are effective and mature in the field of classification, while Spiking Neural Networks (SNNs) are energy-saving for their sparsity of data flow and event-driven working mechanism. Previous work demonstrated that CNNs can be converted into equivalent Spiking Convolutional Neural Networks (SCNNs) without obvious accuracy loss, including different functional layers such as Convolutional (Conv), Fully Connected (FC), Avg-pooling, Max-pooling, and Batch-Normalization (BN) layers. To reduce inference-latency, existing researches mainly concentrated on the normalization of weights to increase the firing rate of neurons. There are also some approaches during training phase or altering the network architecture. However, little attention has been paid on the end of inference phase. From this new perspective, this paper presents 4 stopping criterions as low-cost plug-ins to reduce the inference-latency of SCNNs. The proposed methods are validated using MATLAB and PyTorch platforms with Spiking-AlexNet for CIFAR-10 dataset and Spiking-LeNet-5 for MNIST dataset. Simulation results reveal that, compared to the state-of-the-art methods, the proposed method can shorten the average inference-latency of Spiking-AlexNet from 892 to 267 time steps (almost 3.34 times faster) with the accuracy decline from 87.95 to 87.72%. With our methods, 4 types of Spiking-LeNet-5 only need 24–70 time steps per image with the accuracy decline not more than 0.1%, while models without our methods require 52–138 time steps, almost 1.92 to 3.21 times slower than us.

Perceptual confidence judgments reflect self-consistency

Each perceptual decision is commonly attached to a judgment of confidence in the uncertainty of that decision. Confidence is classically defined as the estimate of the posterior probability of the decision to be correct, given the evidence. Here we argue that correctness is neither a valid normative statement of what observers should be doing after their perceptual decision nor a proper descriptive statement of what they actually do. Instead, we propose that perceivers aim at being self-consistent with themselves. We present behavioral evidence obtained in two separate psychophysical experiments that human observers achieve that aim. In one experiment adaptation led to aftereffects, and in the other prior stimulus occurrences were manipulated. We show that confidence judgments perfectly follow changes in perceptual reports and response times, regardless of the nature of the bias. Although observers are able to judge the validity of their percepts, they are oblivious to how biased these percepts are. Focusing on self-consistency rather than correctness leads us to interpret confidence as an estimate of the reliability of one's perceptual decision rather than a distance to an unattainable truth.

Confidence guides priority between forthcoming tasks

Humans can estimate confidence in their decisions, and there is increasing interest on how this feeling of confidence regulates future behavior. Here, we investigate whether confidence in a perceptual task affects prioritizing future trials of that task, independently of task performance. To do so, we experimentally dissociated confidence from performance. Participants judged whether an array of differently colored circles was closer to blue or red, and we manipulated the mean and variability of the circles' colors across the array. We first familiarized participants with a low mean low variability condition and a high mean high variability condition, which were matched in performance despite participants being more confident in the former. Then we made participants decide in which order to complete forthcoming trials for both conditions. Crucially, prioritizing one condition was associated with being more confident in that condition compared to the other. This relationship was observed both across participants, by correlating inter-individual heterogeneity in prioritization and in confidence, and within participants, by assessing how changes in confidence with accuracy, condition and response times could predict prioritization choices. Our results suggest that confidence, above and beyond performance, guides prioritization between forthcoming tasks, strengthening the evidence for its role in regulating behavior.

Metacognitive blindness in temporal selection during the deployment of spatial attention

How does orienting attention in space affect the quality of our confidence judgments? Orienting attention to a particular location is known to boost visual performance, but the deployment of attention is far from being instantaneous. Whether observers are able to monitor the time needed for attention to deploy remains largely unknown. To address this question, we adapted a "Wundt clocks" paradigm, asking observers (N=140) to reproduce the phase of a rotating clock at the time of an attentional cue, and to evaluate their confidence in their responses. Attention affected the latency between objective and perceived events: the average reported phase was delayed in accordance with the known latencies of voluntary and involuntary attention. Yet, we found that confidence remains oblivious to these attention-induced perceptual delays, like a 'metacognitive blind spot'. In addition, we observed weaker metacognition specifically during the deployment of voluntary attention, suggesting a tight relationship between the attentional and metacognitive systems. While previous work has considered how visual confidence adjusts to fully attended versus unattended locations, our study demonstrates that the very process of orienting attention in space can alter metacognition.

Contrasting contributions of movement onset and duration to self-evaluation of sensorimotor timing performance

Movement execution is not always optimal. Understanding how humans evaluate their own motor decisions can give us insights into their suboptimality. Here, we investigated how humans time the action of synchronizing an arm movement with a predictable visual event and how well they can evaluate the outcome of this action. On each trial, participants had to decide when to start (reaction time) and for how long to move (movement duration) to reach a target on time. After each trial, participants judged the confidence they had that their performance on that trial was better than average. We found that participants mostly varied their reaction time, keeping the average movement duration short and relatively constant across conditions. Interestingly, confidence judgements reflected deviations from the planned reaction time and were not related to planned movement duration. In two other experiments, we replicated these results in conditions where the contribution of sensory uncertainty was reduced. In contrast to confidence judgements, when asked to make an explicit estimation of their temporal error, participants' estimates were related in a similar manner to both reaction time and movement duration. In summary, humans control the timing of their actions primarily by adjusting the delay to initiate the action, and they estimate their confidence in their action from the difference between the planned and executed movement onset. Our results highlight the critical role of the internal model for the self‐evaluation of one's motor performance.

Multitasking costs on metacognition in a triple-task paradigm

Multitasking situations, such as using one's phone while driving, are increasingly common in everyday life. Experimental psychology has long documented the costs of multitasking on task performance; however, little is known of the effects it has on the metacognitive processes that monitor such performance. The present study is a step toward filling this void by combining psychophysical procedures with complex multitasking. We devised a multimodal paradigm in which participants performed a sensorimotor tracking task, a visual discrimination task, and an auditory 2-back working memory task, either separately or concurrently, while also evaluating their task performance every ~15 s. Our main finding is that multitasking decreased participants' awareness of their performance (metacognitive sensitivity) for all three tasks. Importantly, this result was independent of the multitasking cost on task performance, and could not be attributed to confidence leak, psychological refractory period, or recency effects on self-evaluations. We discuss the implications of this finding for both metacognition and multitasking research.

Underconfidence in peripheral vision

Our visual experience appears uniform across the visual field, despite the poor resolution of peripheral vision. This may be because we do not notice that we are missing details in the periphery of our visual field and believe that peripheral vision is just as rich as central vision. In other words, the uniformity of the visual scene could be explained by a metacognitive bias. We deployed a confidence forced-choice method to measure metacognitive performance in peripheral as compared to central vision. Participants judged the orientation of gratings presented in central and peripheral vision, and reported whether they thought they were more likely to be correct in the perceptual decision for the central or for the peripheral stimulus. Observers were underconfident in the periphery: higher sensory evidence in the periphery was needed to equate confidence choices between central and peripheral perceptual decisions. When performance on the central and peripheral tasks was matched, observers were still more confident in their ability to report the orientation of the central gratings over the one of the peripheral gratings. In a second experiment, we measured metacognitive sensitivity, as the difference in perceptual sensitivity between perceptual decisions that are chosen with high confidence and decisions that are chosen with low confidence. Results showed that metacognitive sensitivity is lower when participants compare central to peripheral perceptual decisions compared to when they compare peripheral to peripheral or central to central perceptual decisions. In a third experiment, we showed that peripheral underconfidence does not arise because observers based confidence judgments on stimulus size or contrast range rather than on perceptual performance. Taken together, results indicate that humans are impaired in comparing central with peripheral perceptual performance, but metacognitive biases cannot explain our impression of uniformity, as this would require peripheral overconfidence.

Global visual confidence

Visual confidence is the observers’ estimate of their precision in one single perceptual decision. Ultimately, however, observers often need to judge their confidence over a task in general rather than merely on one single decision. Here, we measured the global confidence acquired across multiple perceptual decisions. Participants performed a dual task on two series of oriented stimuli. The perceptual task was an orientation-discrimination judgment. The metacognitive task was a global confidence judgment: observers chose the series for which they felt they had performed better in the perceptual task. We found that choice accuracy in global confidence judgments improved as the number of items in the series increased, regardless of whether the global confidence judgment was made before (prospective) or after (retrospective) the perceptual decisions. This result is evidence that global confidence judgment was based on an integration of confidence information across multiple perceptual decisions rather than on a single one. Furthermore, we found a tendency for global confidence choices to be influenced by response times, and more so for recent perceptual decisions than earlier ones in the series of stimuli. Using model comparison, we found that global confidence is well described as a combination of noisy estimates of sensory evidence and position-weighted response-time evidence. In summary, humans can integrate information across multiple decisions to estimate global confidence, but this integration is not optimal, in particular because of biases in the use of response-time information.

Are children's judgments of another's accuracy linked to their metacognitive confidence judgments?

The world can be a confusing place, which leads to a significant challenge: how do we figure out what is true? To accomplish this, children possess two relevant skills: reasoning about the likelihood of their own accuracy (metacognitive confidence) and reasoning about the likelihood of others' accuracy (mindreading). Guided by Signal Detection Theory and Simulation Theory, we examine whether these two self- and other-oriented skills are one in the same, relying on a single cognitive process. Specifically, Signal Detection Theory proposes that confidence in a decision is purely derived from the imprecision of that decision, predicting a tight correlation between decision accuracy and confidence. Simulation Theory further proposes that children attribute their own cognitive experience to others when reasoning socially. Together, these theories predict that children's self and other reasoning should be highly correlated and dependent on decision accuracy. In four studies (N = 374), children aged 4-7 completed a confidence reasoning task and selective social learning task each designed to eliminate confounding language and response biases, enabling us to isolate the unique correlation between self and other reasoning. However, in three of the four studies, we did not find that individual differences on the two tasks correlated, nor that decision accuracy explained performance. These findings suggest self and other reasoning are either independent in childhood, or the result of a single process that operates differently for self and others.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11409-021-09263-x.

Confidence Forced-Choice and Other Metaperceptual Tasks

Metaperception is the self-monitoring and self-control of one's own perception. Perceptual confidence is the prototypical example of metaperception. Perceptual confidence refers to the ability to judge whether a perceptual decision is correct. We argue that metaperception is not limited to confidence but includes other judgments such as the estimation of familiarity and the aesthetic experience of sensory events. Perceptual confidence has recently received a surge of interests due in particular to the design of careful psychophysical experiments and powerful computational models. In psychophysics, the use of confidence ratings is the dominant methodology, but other paradigms are available, including the confidence forced choice. In this latter paradigm, participants are presented with two stimuli, make perceptual decisions about these stimuli, and then choose which decision is more likely to be correct. One benefit of confidence forced choice is that it disregards confidence biases to focus on confidence sensitivity. Confidence forced choice might also be a paradigm that will allow us to establish whether confidence is estimated serially or in parallel to the perceptual decision.

Human visual motion perception shows hallmarks of Bayesian structural inference

Motion relations in visual scenes carry an abundance of behaviorally relevant information, but little is known about how humans identify the structure underlying a scene's motion in the first place. We studied the computations governing human motion structure identification in two psychophysics experiments and found that perception of motion relations showed hallmarks of Bayesian structural inference. At the heart of our research lies a tractable task design that enabled us to reveal the signatures of probabilistic reasoning about latent structure. We found that a choice model based on the task's Bayesian ideal observer accurately matched many facets of human structural inference, including task performance, perceptual error patterns, single-trial responses, participant-specific differences, and subjective decision confidence-especially, when motion scenes were ambiguous and when object motion was hierarchically nested within other moving reference frames. Our work can guide future neuroscience experiments to reveal the neural mechanisms underlying higher-level visual motion perception.

Priors and payoffs in confidence judgments

Priors and payoffs are known to affect perceptual decision-making, but little is understood about how they influence confidence judgments. For optimal perceptual decision-making, both priors and payoffs should be considered when selecting a response. However, for confidence to reflect the probability of being correct in a perceptual decision, priors should affect confidence but payoffs should not. To experimentally test whether human observers follow this normative behavior for natural confidence judgments, we conducted an orientation-discrimination task with varied priors and payoffs that probed both perceptual and metacognitive decision-making. The placement of discrimination and confidence criteria were examined according to several plausible Signal Detection Theory models. In the normative model, observers use the optimal discrimination criterion (i.e., the criterion that maximizes expected gain) and confidence criteria that shift with the discrimination criterion that maximizes accuracy (i.e., are not affected by payoffs). No observer was consistent with this model, with the majority exhibiting non-normative confidence behavior. One subset of observers ignored both priors and payoffs for confidence, always fixing the confidence criteria around the neutral discrimination criterion. The other group of observers incorrectly incorporated payoffs into their confidence by always shifting their confidence criteria with the same gains-maximizing criterion used for discrimination. Such metacognitive mistakes could have negative consequences outside the laboratory setting, particularly when priors or payoffs are not matched for all the possible decision alternatives.

Performance monitoring for sensorimotor confidence: A visuomotor tracking study

To best interact with the external world, humans are often required to consider the quality of their actions. Sometimes the environment furnishes rewards or punishments to signal action efficacy. However, when such feedback is absent or only partial, we must rely on internally generated signals to evaluate our performance (i.e., metacognition). Yet, very little is known about how humans form such judgements of sensorimotor confidence. Do they monitor their actual performance or do they rely on cues to sensorimotor uncertainty? We investigated sensorimotor metacognition in two visuomotor tracking experiments, where participants followed an unpredictably moving dot cloud with a mouse cursor as it followed a random horizontal trajectory. Their goal was to infer the underlying target generating the dots, track it for several seconds, and then report their confidence in their tracking as better or worse than their average. In Experiment 1, we manipulated task difficulty with two methods: varying the size of the dot cloud and varying the stability of the target's velocity. In Experiment 2, the stimulus statistics were fixed and duration of the stimulus presentation was varied. We found similar levels of metacognitive sensitivity in all experiments, which was evidence against the cue-based strategy. The temporal analysis of metacognitive sensitivity revealed a recency effect, where error later in the trial had a greater influence on the sensorimotor confidence, consistent with a performance-monitoring strategy. From these results, we conclude that humans predominantly monitored their tracking performance, albeit inefficiently, to build a sense of sensorimotor confidence.

Segregated Co-activation Patterns in the Emergence of Decision Confidence During Visual Perception

Visual metacognition-the introspection and evaluation of one's own visual perceptual processes-is measured through both decision confidence and "metacognitive efficiency." Metacognitive efficiency refers to an individual's ability to accurately judge incorrect and correct decisions through confidence ratings given their task performance. Previous imaging studies in humans and nonhuman primates reported widely distributed brain regions being involved in decision confidence and metacognition. However, the neural correlates of metacognition are remarkably inconsistent across studies concerning spatial outline. Therefore, this study investigates the neural correlates of visual metacognition by examining co-activation across regions that scale with visual decision confidence. We hypothesized that interacting processes of perceptual and metacognitive performance contribute to the arising decision confidence in distributed, but segregable co-activating brain regions. To test this hypothesis, we performed task-fMRI in healthy humans during a visual backward masking task with four-scale, post-decision confidence ratings. We measured blood oxygenation covariation patterns, which served as a physiological proxy for co-activation across brain regions. Decision confidence ratings and an individual's metacognitive efficiency served as behavioral measures for metacognition. We found three distinct co-activation clusters involved in decision confidence: the first included right-centered fronto-temporal-parietal regions, the second included left temporal and parietal regions, and the left basal forebrain (BF), and the third included cerebellar regions. The right fronto-temporal-parietal cluster including the supplementary eye field and the right basal forebrain showed stronger co-activation in subjects with higher metacognitive efficiency. Our results provide novel evidence for co-activation of widely distributed fronto-parieto-temporal regions involved in visual confidence. The supplementary eye field was the only region that activated for both decision confidence and metacognitive efficiency, suggesting the supplementary eye field plays a key role in visual metacognition. Our results link findings in electrophysiology studies and human fMRI studies and provide evidence that confidence estimates arise from the integration of multiple information processing pathways.