The Impact of Feedback on Perceptual Decision-Making and Metacognition: Reduction in Bias but No Change in Sensitivity

More than the sum of its parts: investigating episodic memory as a multidimensional cognitive process

Why do we remember some events but forget others? Previous studies attempting to decode successful vs. unsuccessful brain states to investigate this question have met with limited success, potentially due, in part, to assessing episodic memory as a unidimensional process, despite evidence that multiple domains contribute to episodic encoding. Using a novel machine learning algorithm known as "transfer learning", we leveraged visual perception, sustained attention, and selective attention brain states to better predict episodic memory performance from trial-to-trial encoding electroencephalography (EEG) activity. We found that this multidimensional treatment of memory decoding improved prediction performance compared to traditional, unidimensional, methods, with each cognitive domain explaining unique variance in decoding of successful encoding-related neural activity. Importantly, this approach could be applied to cognitive domains outside of memory. Overall, this study provides critical insight into the underlying reasons why some events are remembered while others are not.

The neural representation of metacognition in preferential decision-making

Humans regularly assess the quality of their judgements, which helps them adjust their behaviours. Metacognition is the ability to accurately evaluate one's own judgements, and it is assessed by comparing objective task performance with subjective confidence report in perceptual decisions. However, for preferential decisions, assessing metacognition in preference-based decisions is difficult because it depends on subjective goals rather than the objective criterion. Here, we develop a new index that integrates choice, reaction time, and confidence report to quantify trial-by-trial metacognitive sensitivity in preference judgements. We found that the dorsomedial prefrontal cortex (dmPFC) and the right anterior insular were more activated when participants made bad metacognitive evaluations. Our study suggests a crucial role of the dmPFC-insula network in representing online metacognitive sensitivity in preferential decisions.

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

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

Think twice: Re-assessing confidence improves visual metacognition

Metacognition is a fundamental feature of human behavior that has adaptive functional value. Current understanding of the factors that influence metacognition remains incomplete, and we lack protocols to improve metacognition. Here, we introduce a two-step confidence choice paradigm to test whether metacognitive performance may improve by asking subjects to reassess their initial confidence. Previous work on perceptual and mnemonic decision-making has shown that (type 1) perceptual sensitivity benefits from reassessing the primary choice, however, it is not clear whether such an effect occurs for type 2 confidence choices. To test this hypothesis, we ran two separate online experiments, in which participants completed a type 1 task followed by two consecutive confidence choices. The results of the two experiments indicated that metacognitive sensitivity improved after re-evaluation. Since post-decisional evidence accumulation following the first confidence choice is likely to be minimal, this metacognitive improvement is better accounted for by an attenuation of metacognitive noise during the process of confidence generation. Thus, here we argue that metacognitive noise may be filtered out by additional post-decisional processing, thereby improving metacognitive sensitivity. We discuss the ramifications of these findings for models of metacognition and for developing protocols to train and manipulate metacognitive processes.

Introspective inference counteracts perceptual distortion

Introspective agents can recognize the extent to which their internal perceptual experiences deviate from the actual states of the external world. This ability, also known as insight, is critically required for reality testing and is impaired in psychosis, yet little is known about its cognitive underpinnings. We develop a Bayesian modeling framework and a psychophysics paradigm to quantitatively characterize this type of insight while people experience a motion after-effect illusion. People can incorporate knowledge about the illusion into their decisions when judging the actual direction of a motion stimulus, compensating for the illusion (and often overcompensating). Furthermore, confidence, reaction-time, and pupil-dilation data all show signatures consistent with inferential adjustments in the Bayesian insight model. Our results suggest that people can question the veracity of what they see by making insightful inferences that incorporate introspective knowledge about internal distortions.

The impact of feedback on metacognition: Enhancing in easy tasks, impeding in difficult ones

Metacognition refers to the ability to monitor and introspect upon cognitive performance. Abundant research suggests that individual metacognition is easily affected by feedback in daily life, but how feedback affects metacognition in perceptual decision-making remains unclear. Here we investigated how trial-by-trial feedback shapes perceptual metacognition in two experiments with either high (n = 82) or low difficulty (n = 90). Participants were randomly divided into a feedback group in which participants received trial-by-trial performance feedback or a no-feedback group. Results showed that, in the high-difficulty task, participants in the feedback group revealed inferior metacognitive performance than the no-feedback group, manifested as decreased metacognitive efficiency while controlling for performance sensitivity. In the low-difficulty task, however, participants in the feedback group had higher metacognitive efficiency than the no-feedback group. The distinct patterns of findings in the two experiments indicate that whether feedback promotes or impedes metacognition is adjusted by task difficulty.

Quantifying body ownership information processing and perceptual bias in the rubber hand illusion

Bodily illusions have fascinated humankind for centuries, and researchers have studied them to learn about the perceptual and neural processes that underpin multisensory channels of bodily awareness. The influential rubber hand illusion (RHI) has been used to study changes in the sense of body ownership - that is, how a limb is perceived to belong to one's body, which is a fundamental building block in many theories of bodily awareness, self-consciousness, embodiment, and self-representation. However, the methods used to quantify perceptual changes in bodily illusions, including the RHI, have mainly relied on subjective questionnaires and rating scales, and the degree to which such illusory sensations depend on sensory information processing has been difficult to test directly. Here, we introduce a signal detection theory (SDT) framework to study the sense of body ownership in the RHI. We provide evidence that the illusion is associated with changes in body ownership sensitivity that depend on the information carried in the degree of asynchrony of correlated visual and tactile signals, as well as with perceptual bias and sensitivity that reflect the distance between the rubber hand and the participant's body. We found that the illusion's sensitivity to asynchrony is remarkably precise; even a 50 ms visuotactile delay significantly affected body ownership information processing. Our findings conclusively link changes in a complex bodily experience such as body ownership to basic sensory information processing and provide a proof of concept that SDT can be used to study bodily illusions.

Metacognitive Effort Regulation across Cultures

Success in cognitive tasks is associated with effort regulation and motivation. We employed the meta-reasoning approach to investigate metacognitive monitoring accuracy and effort regulation in problem solving across cultures. Adults from China, from Israel, and from Europe and North America (for simplicity: "Western countries") solved nonverbal problems and rated their confidence in their answers. The task involved identifying geometric shapes within silhouettes and, thus, required overcoming interference from holistic processing. The Western group displayed the worst monitoring accuracy, with both the highest overconfidence and poorest resolution (discrimination in confidence between the correct and wrong solutions). The Israeli group resembled the Western group in many respects but exhibited better monitoring accuracy. The Chinese group invested the most time and achieved the best success rates, demonstrating exceptional motivation and determination to succeed. However, their efficiency suffered as they correctly solved the fewest problems per minute of work. Effort regulation analysis based on the Diminishing Criterion Model revealed distinct patterns: the Western participants invested the least amount of time regardless of item difficulty and the Israelis invested more time only when addressing the hardest items. The Chinese group allocated more time throughout but particularly in moderate to difficult items, hinting at their strategic determination to overcome the challenge. Understanding cultural differences in metacognitive processes carries implications for theory (e.g., motivational factors) and practice (e.g., international teams, education). The present findings can serve as a foundation for future research in these and other domains.

Confidence response times: Challenging postdecisional models of confidence

Even though the nature of confidence computations has been the topic of intense interest, little attention has been paid to what confidence response times (cRTs) reveal about the underlying confidence computations. Several previous studies found cRTs to be negatively correlated with confidence in the group as a whole and consequently hypothesized the existence of an intrinsic relationship of cRT with confidence for all subjects. This hypothesis was further used to support postdecisional models of confidence that predict that cRT and confidence should always be negatively correlated. Here we test the alternative hypothesis that cRT is driven by the frequency of confidence responses such that the most frequent confidence ratings are inherently made faster regardless of whether they are high or low. We examined cRTs in three large data sets from the Confidence Database and found that the lowest cRTs occurred for the most frequent confidence rating. In other words, subjects who gave high confidence ratings most frequently had negative confidence-cRT relationships, whereas subjects who gave low confidence ratings most frequently had positive confidence-cRT relationships. In addition, we found a strong across-subject correlation between response time and cRT, suggesting that response speed for both the decision and the confidence rating is influenced by a common factor. Our results show that cRT is not intrinsically linked to confidence and strongly challenge several postdecisional models of confidence.

Testing the Social Function of Metacognition for Common-Pool Resource Use

Metacognition, the ability to monitor and evaluate our own cognitive processes, confers advantages to individuals and their own judgment. A more recent hypothesis, however, states that explicit metacognition may also enhance the collective judgment of groups, and may enhance human collaboration and coordination. Here, we investigate this social function hypothesis of metacognition with arguably one of the oldest collaboration problems humans face, common-pool resource use. Using an agent-based model that simulates repeated group interactions and the forming of collective judgments about resource extraction, we show that (1) in "kind" environments (where confidence and judgment accuracy correlate positively), explicit metacognition may allow groups to reach more accurate judgments compared to groups exchanging object-level information only; while (2) in "wicked" environments (where confidence and judgment accuracy correlate negatively), explicit metacognition may protect groups from the large judgment errors yielded by groups using metacognitive information for individual-level learning only (implicit metacognition). With explicit metacognition, this research highlights a novel mechanism which, among others, provides a testable explanation of the often-observed finding that groups all over the world communicate to enhance common property use.

Removal of reinforcement improves instrumental performance in humans by decreasing a general action bias rather than unmasking learnt associations

Performance during instrumental learning is commonly believed to reflect the knowledge that has been acquired up to that point. However, recent work in rodents found that instrumental performance was enhanced during periods when reinforcement was withheld, relative to periods when reinforcement was provided. This suggests that reinforcement may mask acquired knowledge and lead to impaired performance. In the present study, we investigated whether such a beneficial effect of removing reinforcement translates to humans. Specifically, we tested whether performance during learning was improved during non-reinforced relative to reinforced task periods using signal detection theory and a computational modelling approach. To this end, 60 healthy volunteers performed a novel visual go/no-go learning task with deterministic reinforcement. To probe acquired knowledge in the absence of reinforcement, we interspersed blocks without feedback. In these non-reinforced task blocks, we found an increased d’, indicative of enhanced instrumental performance. However, computational modelling showed that this improvement in performance was not due to an increased sensitivity of decision making to learnt values, but to a more cautious mode of responding, as evidenced by a reduction of a general response bias. Together with an initial tendency to act, this is sufficient to drive differential changes in hit and false alarm rates that jointly lead to an increased d’. To conclude, the improved instrumental performance in the absence of reinforcement observed in studies using asymmetrically reinforced go/no-go tasks may reflect a change in response bias rather than unmasking latent knowledge.

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.

Across-subject correlation between confidence and accuracy: A meta-analysis of the Confidence Database

If one friend confidently tells us to buy Product A while another friend thinks that Product B is better but is not confident, we may go with the advice of our confident friend. Should we? The relationship between people's confidence and accuracy has been of great interest in many fields, especially in high-stakes situations like eyewitness testimony. However, there is still little consensus about how much we should trust someone's overall confidence level. Here, we examine the across-subject relationship between average accuracy and average confidence in 213 unique datasets from the Confidence Database. This approach allows us to empirically address this issue with unprecedented statistical power and check for the presence of various moderators. We find an across-subject correlation between average accuracy and average confidence of R = .22. Importantly, this relationship is much stronger for memory than for perception tasks ("domain effect"), as well as for confidence scales with fewer points ("granularity effect"). These results show that we should take one's confidence seriously (and perhaps buy Product A) and suggest several factors that moderate the relative consistency of how people make confidence judgments.

Response Bias Reflects Individual Differences in Sensory Encoding

Humans exhibit substantial biases in their decision making even in simple two-choice tasks, but the origin of these biases remains unclear. I hypothesized that one source of bias could be individual differences in sensory encoding. Specifically, if one stimulus category gives rise to an internal-evidence distribution with higher variability, then responses should optimally be biased against that stimulus category. Therefore, response bias may reflect a previously unappreciated subject-to-subject difference in the variance of the internal-evidence distributions. I tested this possibility by analyzing data from three different two-choice tasks (ns = 443, 443, and 498). For all three tasks, response bias moved in the direction of the optimal criterion determined by each subject's idiosyncratic internal-evidence variability. These results demonstrate that seemingly random variations in response bias can be driven by individual differences in sensory encoding and are thus partly explained by normative strategies.