The nature of metacognitive inefficiency in perceptual decision making

2020 ◽  
Author(s):  
Medha Shekhar ◽  
Dobromir Rahnev
Keyword(s):  
Decision Making ◽  
Mechanistic Model ◽  
Perceptual Decision Making ◽  
Large Dataset ◽  
Substantial Body ◽  
Confidence Levels ◽  
Continuous Scale ◽  
Competing Models ◽  
Metacognitive Ability ◽  
Confidence Ratings

Humans have the metacognitive ability to judge the accuracy of their own decisions via confidence ratings. A substantial body of research has demonstrated that human metacognition is fallible but it remains unclear how metacognitive inefficiency should be incorporated into a mechanistic model of confidence generation. Here we show that, contrary to what is typically assumed, metacognitive inefficiency depends on the level of confidence. We found that, across five different datasets and four different measures of metacognition, metacognitive ability decreased with higher confidence ratings. To understand the nature of this effect, we collected a large dataset of 20 subjects completing 2,800 trials each and providing confidence ratings on a continuous scale. The results demonstrated a robustly nonlinear zROC curve with downward curvature, despite a decades-old assumption of linearity. This pattern of results was reproduced by a new mechanistic model of confidence generation, which assumes the existence of lognormally-distributed metacognitive noise. The model outperformed competing models either lacking metacognitive noise altogether or featuring Gaussian metacognitive noise. Further, the model could generate a measure of metacognitive ability which was independent of confidence levels. These findings establish an empirically-validated model of confidence generation, have significant implications about measures of metacognitive ability, and begin to reveal the underlying nature of metacognitive inefficiency.

scholarly journals Overlapping and unique neural circuits are activated during perceptual decision making and confidence

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jiwon Yeon ◽  
Medha Shekhar ◽  
Dobromir Rahnev
Keyword(s):  
Decision Making ◽  
Functional Mri ◽  
Neural Circuits ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Initial Decision ◽  
Brain Circuits ◽  
Confidence Ratings

AbstractThe period of making a perceptual decision is often followed by a period of rating confidence where one evaluates the likely accuracy of the initial decision. However, it remains unclear whether the same or different neural circuits are engaged during periods of perceptual decision making and confidence report. To address this question, we conducted two functional MRI experiments in which we dissociated the periods related to perceptual decision making and confidence report by either separating their respective regressors or asking for confidence ratings only in the second half of the experiment. We found that perceptual decision making and confidence reports gave rise to activations in large and mostly overlapping brain circuits including frontal, parietal, posterior, and cingulate regions with the results being remarkably consistent across the two experiments. Further, the confidence report period activated a number of unique regions, whereas only early sensory areas were activated for the decision period across the two experiments. We discuss the possible reasons for this overlap and explore their implications about theories of perceptual decision making and visual metacognition.

scholarly journals Overlapping and unique neural circuits are activated during perceptual decision making and confidence

2018 ◽  
Author(s):  
Jiwon Yeon ◽  
Medha Shekhar ◽  
Dobromir Rahnev
Keyword(s):  
Decision Making ◽  
Functional Mri ◽  
Neural Circuits ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Initial Decision ◽  
Brain Circuits ◽  
Confidence Ratings

AbstractThe period of making a perceptual decision is often followed by a period of confidence generation where one rates the likely accuracy of the initial decision. However, it remains unclear whether the same or different neural circuits are engaged during periods of perceptual decision making and confidence generation. To address this question, we conducted two functional MRI experiments in which we dissociated the periods related to perceptual decision making and confidence report by either separating their respective regressors or asking for confidence ratings only in the second half of the experiment. We found that perceptual decision making and confidence reports gave rise to activations in large and mostly overlapping brain circuits including frontal, parietal, posterior, and cingulate regions with the results being remarkably consistent across the two experiments. Further, the confidence report period activated a number of unique regions, whereas there was no evidence for the decision period activating unique regions not involved in the confidence period. We discuss the possible reasons for this overlap and explore their implications about theories of perceptual decision making and confidence generation.

scholarly journals Metacognitive impairments extend perceptual decision making weaknesses in compulsivity

2017 ◽  
Author(s):  
Tobias U. Hauser ◽  
Micah Allen ◽  
Geraint Rees ◽  
Raymond J. Dolan ◽  
Keyword(s):  
Decision Making ◽  
Computational Models ◽  
Large Population ◽  
Computational Modelling ◽  
Population Based ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Metacognitive Abilities ◽  
Adaptive Decision Making ◽  
Metacognitive Ability

AbstractAwareness of one’s own abilities is of paramount importance in adaptive decision making. Psychotherapeutic theories assume such metacognitive insight is impaired in compulsivity, though this is supported by scant empirical evidence. In this study, we investigate metacognitive abilities in compulsive participants using computational models, where these enable a segregation between metacognitive and perceptual decision making impairments. We examined twenty low-compulsive and twenty high-compulsive participants, recruited from a large population-based sample, and matched for other psychiatric and cognitive dimensions. Hierarchical computational modelling of the participants’ metacognitive abilities on a visual global motion detection paradigm revealed that high-compulsive participants had a reduced metacognitive ability. This impairment was accompanied by a perceptual decision making deficit whereby motion-related evidence was accumulated more slowly in high compulsive participants. Our study shows that the compulsivity spectrum is associated with a reduced ability to monitor one’s own performance, over and above any perceptual decision making difficulty.

scholarly journals Humans exhibit discrete confidence levels in perceptual decision-making

2016 ◽  
Vol 16 (12) ◽  
pp. 979
Author(s):  
Matteo Lisi ◽  
Gianluigi Mongillo ◽  
Andrei Gorea
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Confidence Levels

Metacognition-related regions modulate the reactivity effect of confidence ratings on perceptual decision-making

2020 ◽  
Vol 144 ◽  
pp. 107502
Author(s):  
Wei Lei ◽  
Jing Chen ◽  
Chunliang Yang ◽  
Yiqun Guo ◽  
Pan Feng ◽  
...  
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Reactivity Effect ◽  
Perceptual Decision ◽  
Confidence Ratings

scholarly journals Alexithymia is associated with lower confidence in both perceptual and emotion recognition tasks

2020 ◽  
Author(s):  
Nathan Torunsky ◽  
Iris Vilares
Keyword(s):  
Decision Making ◽  
Emotion Recognition ◽  
Community Sample ◽  
Emotional Awareness ◽  
Poor Mental Health ◽  
Perceptual Decision Making ◽  
Affective Component ◽  
Increased Risk ◽  
Task Types ◽  
Metacognitive Ability

Emotions play an important role in everyday decision-making, but emotional awareness can vary greatly between people. Alexithymia, a trait characterized by little or no awareness of one’s emotions, is broadly associated with poor mental health and increased risk of suicide. Alexithymia is fairly common, affecting as much as 10% of people in Western cultures. Understanding how alexithymia relates to decision-making may therefore have wide-reaching impacts on the quality of life for many individuals. We designed and preregistered a study that examined the relationship between alexithymia and decision-making across different task-types. Data were collected from a community sample (N = 123) and participants completed a social, an emotional, and a perceptual decision-making task, as well as a short alexithymia questionnaire. For each task, we considered multiple aspects of the decision-making process, examining participants’ accuracy, confidence, and metacognitive ability (i.e. the ability to retrospectively distinguish between correct and incorrect responses). We found no relationship between alexithymia and performance or metacognitive ability in any task. However, alexithymia was negatively correlated with confidence in both the perceptual and emotional tasks. Furthermore, confidence in one’s decision was strongly, positively correlated across task types, but both accuracy and metacognitive ability showed no relationship between tasks. These results suggest that confidence may be a trait-like, affective component of decision-making, while performance and metacognitive sensitivity appear more task-specific. Furthermore, our results challenge the current limitations of the alexithymia construct, suggesting that alexithymia may have consequences on cognitive processes beyond emotion recognition alone.

Discarding optimality: Throwing out the baby with the bathwater?

2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Standard Observer ◽  
Rate Maximization ◽  
Reward Rate Maximization ◽  
Descriptive Standard ◽  
Observer Model

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.

LPCD framework: Analytical tool or psychological model?

2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks
Keyword(s):  
Decision Making ◽  
Analytical Tool ◽  
Mathematical Framework ◽  
Bayesian Decision ◽  
Perceptual Decision Making ◽  
Psychological Model ◽  
Psychological Reality ◽  
Psychological Theories ◽  
Target Article ◽  
Bayesian Decision Making

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.

scholarly journals Flexible categorization in perceptual decision making

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Genís Prat-Ortega ◽  
Klaus Wimmer ◽  
Alex Roxin ◽  
Jaime de la Rocha
Keyword(s):  
Decision Making ◽  
Network Models ◽  
Drift Diffusion Model ◽  
Perceptual Decision Making ◽  
Drift Diffusion ◽  
Perceptual Decision ◽  
Attractor Dynamics ◽  
Attractor Model ◽  
Sensory Evidence ◽  
Winner Take All

AbstractPerceptual decisions rely on accumulating sensory evidence. This computation has been studied using either drift diffusion models or neurobiological network models exhibiting winner-take-all attractor dynamics. Although both models can account for a large amount of data, it remains unclear whether their dynamics are qualitatively equivalent. Here we show that in the attractor model, but not in the drift diffusion model, an increase in the stimulus fluctuations or the stimulus duration promotes transitions between decision states. The increase in the number of transitions leads to a crossover between weighting mostly early evidence (primacy) to weighting late evidence (recency), a prediction we validate with psychophysical data. Between these two limiting cases, we found a novel flexible categorization regime, in which fluctuations can reverse initially-incorrect categorizations. This reversal asymmetry results in a non-monotonic psychometric curve, a distinctive feature of the attractor model. Our findings point to correcting decision reversals as an important feature of perceptual decision making.

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