Confidence in consciousness research

Product, not process: Metacognitive monitoring of visual performance during sustained attention

The performance of the human visual system exhibits moment-to-moment fluctuations influenced by multiple neurocognitive factors. To deal with this instability of the visual system, introspective awareness of current visual performance (metacognitive monitoring) may be crucial. In this study, we investigate whether and how people can monitor their own visual performance during sustained attention by adopting confidence judgments as indicators of metacognitive monitoring - assuming that if participants can monitor visual performance, confidence judgments will accurately track performance fluctuations. In two experiments (N = 40), we found that participants were able to monitor fluctuations in visual performance during sustained attention. Importantly, metacognitive monitoring largely relied on the quality of target perception, a product of visual processing ("I lack confidence in my performance because I only caught a glimpse of the target"), rather than the states of the visual system during visual processing ("I lack confidence because I was not focusing on the task").

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

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

Consciousness Under the Spotlight: The Problem of Measuring Subjective Experience

The study of consciousness is considered by many one of the most difficult contemporary scientific endeavors and confronts several methodological and theoretical challenges. A central issue that makes the study of consciousness so challenging is that, while the rest of science is concerned with problems that can be verified from a "third person" view (i.e., objectively), the study of consciousness deals with the phenomenon of subjective experience, only accessible from a "first person" view. In the present article, we review early (starting during the late 19th century) and later efforts on measuring consciousness and its absence, focusing on the two main approaches used by researchers within the field: objective (i.e., performance based) and subjective (i.e., report based) measures of awareness. In addition, we compare the advantages and disadvantages of both types of awareness measures, evaluate them according to different methodological considerations, and discuss, among other issues, the possibility of comparing them by transforming them to a common sensitivity measure (d'). Finally, we explore several new approaches-such as Bayesian models to support the absence of awareness or new machine-learning based decoding models-as well as future challenges-such as measuring the qualia, the qualitative contents of awareness-in consciousness research.

The role of selective attention in implicit learning: evidence for a contextual cueing effect of task-irrelevant features

With attentional mechanisms, humans select and de-select information from the environment. But does selective attention modulate implicit learning? We tested whether the implicit acquisition of contingencies between features are modulated by the task-relevance of those features. We implemented the contingencies in a novel variant of the contextual cueing paradigm. In such a visual search task, participants could use non-spatial cues to predict target location, and then had to discriminate target shapes. In Experiment 1, the predictive feature for target location was the shape of the distractors (task-relevant). In Experiment 2, the color feature of distractors (task-irrelevant) cued target location. Results showed that participants learned to predict the target location from both the task-relevant and the task-irrelevant feature. Subsequent testing did not suggest explicit knowledge of the contingencies. For the purpose of further testing the significance of task-relevance in a cue competition situation, in Experiment 3, we provided two redundantly predictive cues, shape (task-relevant) and color (task-irrelevant) simultaneously, and subsequently tested them separately. There were no observed costs of single predictive cues when compared to compound cues. The results were not indicative of overshadowing effects, on the group and individual level, or of reciprocal overshadowing. We conclude that the acquisition of contingencies occurs independently of task-relevance and discuss this finding in the framework of the event coding literature.

Metacognitive Sensitivity on the Iowa Gambling Task Reveals Awareness as a Necessary Condition for Advantageous Performance

The Somatic Marker Hypothesis (SHM) proposes that human decision-making under uncertainty is advantageously guided by affective signals before developing awareness of which courses of action are better. However, this claim has been questioned due to the limitations of the methods used to measure awareness, with alternative measures yielding conflicting results. To address this issue, we apply metacognitive sensitivity, a reliable method based on confidence ratings that outperform previous awareness measures, in an online nonclinical sample (N = 44) to assess awareness in the Iowa Gambling Task (IGT). Using this approach, we found that awareness and advantageous decision-making are not independent processes; an increase in metacognitive sensitivity strongly predicted an improvement in task performance in nearly all blocks of the task. A lab-based preregistered replication (N = 47) confirmed these findings. Interestingly, some participants demonstrated awareness without advantageous decision-making, suggesting that awareness is a necessary - but not sufficient - condition for optimal performance. Overall, this study highlights the challenges of measuring awareness in the IGT and introduces a novel alternative method that questions a key postulate of the SMH.

Physical effort modulates perceptual awareness judgment independent of level of processing

Recent studies have emphasized the association between action and perceptual awareness, suggesting that action-related information can contribute to perceptual awareness. Given that the Level of Processing (LoP) hypothesis proposes that the emergence of awareness depends on the level of stimulus processing, the current study examines whether action impacts perceptual awareness across different processing levels. In Experiment 1, participants identified target stimuli's color (low-level task) or category (high-level task) via mouse clicks, followed by visual awareness ratings. Experiment 2 replicated the tasks using hand-grip dynamometers. Results from Experiment 1 support the LoP theory, showing a more gradual emergence of awareness for low-level features and a more dichotomous emergence for high-level features. In Experiment 2, higher reported visual awareness ratings were observed at greater physical effort, regardless of task type. These results suggest that action-related information influences reported awareness of stimuli in the same way at low- and high-level stimulus processing.

Neural Signatures of Evidence Accumulation Encode Subjective Perceptual Confidence Independent of Performance

Confidence is an adaptive computation when environmental feedback is absent, yet there is little consensus regarding how perceptual confidence is computed in the brain. Difficulty arises because confidence correlates with other factors, such as accuracy, response time (RT), or evidence quality. We investigated whether neural signatures of evidence accumulation during a perceptual choice predict subjective confidence independently of these factors. Using motion stimuli, a central-parietal positive-going electroencephalogram component (CPP) behaves as an accumulating decision variable that predicts evidence quality, RT, accuracy, and confidence (Experiment 1, N = 25 adults). When we psychophysically varied confidence while holding accuracy constant (Experiment 2, N = 25 adults), the CPP still predicted confidence. Statistically controlling for RT, accuracy, and evidence quality (Experiment 3, N = 24 adults), the CPP still explained unique variance in confidence. The results indicate that a predecision neural signature of evidence accumulation, the CPP, encodes subjective perceptual confidence in decision-making independent of task performance.

Tactile shape discrimination for moving stimuli

In this study, we explored spatial-temporal dependencies and their impact on the tactile perception of moving objects. Building on previous research linking visual perception and human movement, we examined if an imputed motion mechanism operates within the tactile modality. We focused on how biological coherence between space and time, characteristic of human movement, influences tactile perception. An experiment was designed wherein participants were stimulated on their right palm with tactile patterns, either ambiguous (incongruent conditions) or non-ambiguous (congruent conditions) relative to a biological motion law (two-thirds power law) and asked to report perceived shape and associated confidence. Our findings reveal that introducing ambiguous tactile patterns (1) significantly diminishes tactile discrimination performance, implying motor features of shape recognition in vision are also observed in the tactile modality, and (2) undermines participants' response confidence, uncovering the accessibility degree of information determining the tactile percept's conscious representation. Analysis based on the Hierarchical Drift Diffusion Model unveiled the sensitivity of the evidence accumulation process to the stimulus's informational ambiguity and provides insight into tactile perception as predictive dynamics for reducing uncertainty. These discoveries deepen our understanding of tactile perception mechanisms and underscore the criticality of predictions in sensory information processing.

The cognitive reality monitoring network and theories of consciousness

Theories of consciousness abound. However, it is difficult to arbitrate reliably among competing theories because they target different levels of neural and cognitive processing or anatomical loci, and only some were developed with computational models in mind. In particular, theories of consciousness need to fully address the three levels of understanding of the brain proposed by David Marr: computational theory, algorithms and hardware. Most major theories refer to only one or two levels, often indirectly. The cognitive reality monitoring network (CRMN) model is derived from computational theories of mixture-of-experts architecture, hierarchical reinforcement learning and generative/inference computing modules, addressing all three levels of understanding. A central feature of the CRMN is the mapping of a gating network onto the prefrontal cortex, making it a prime coding circuit involved in monitoring the accuracy of one's mental states and distinguishing them from external reality. Because the CRMN builds on the hierarchical and layer structure of the cerebral cortex, it may connect research and findings across species, further enabling concrete computational models of consciousness with new, explicitly testable hypotheses. In sum, we discuss how the CRMN model can help further our understanding of the nature and function of consciousness.

Masked priming under the Bayesian microscope: Exploring the integration of local elements into global shape through Bayesian model comparison

To investigate whether local elements are grouped into global shapes in the absence of awareness, we introduced two different masked priming designs (e.g., the classic dissociation paradigm and a trial-wise probe and prime discrimination task) and collected both objective (i.e., performance based) and subjective (using the perceptual awareness scale [PAS]) awareness measures. Prime visibility was manipulated using three different prime-mask stimulus onset asynchronies (SOAs) and an unmasked condition. Our results showed that assessing prime visibility trial-wise heavily interfered with masked priming preventing any prime facilitation effect. The implementation of Bayesian regression models, which predict priming effects for participants whose awareness levels are at chance level, provided strong evidence in favor of the hypothesis that local elements group into global shape in the absence of awareness for SOAs longer than 50 ms, suggesting that prime-mask SOA is a crucial factor in the processing of the global shape without awareness.