The Confidence Database

Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence studies spanning a broad set of paradigms, participant populations and fields of study. The data from each study are structured in a common, easy-to-use format that can be easily imported and analysed using multiple software packages. Each dataset is accompanied by an explanation regarding the nature of the collected data. At the time of publication, the Confidence Database (which is available at https://osf.io/s46pr/) contained 145 datasets with data from more than 8,700 participants and almost 4 million trials. The database will remain open for new submissions indefinitely and is expected to continue to grow. Here we show the usefulness of this large collection of datasets in four different analyses that provide precise estimations of several foundational confidence-related effects

The Confidence Database

Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence studies spanning a broad set of paradigms, participant populations and fields of study. The data from each study are structured in a common, easy-to-use format that can be easily imported and analysed using multiple software packages. Each dataset is accompanied by an explanation regarding the nature of the collected data. At the time of publication, the Confidence Database (which is available at https://osf.io/s46pr/) contained 145 datasets with data from more than 8,700 participants and almost 4 million trials. The database will remain open for new submissions indefinitely and is expected to continue to grow. Here we show the usefulness of this large collection of datasets in four different analyses that provide precise estimations of several foundational confidence-related effects

Common computations for metacognition and meta-metacognition

Recent evidence shows that people have the meta-metacognitive ability to evaluate their metacognitive judgments of confidence. However, it is unclear whether meta-metacognitive judgments are made by a different system and rely on a separate set of computations compared to metacognitive judgments. To address this question, we asked participants (N = 36) to perform a perceptual decision-making task and provide (i) an object-level, Type-1 response about the identity of the stimulus; (ii) a metacognitive, Type-2 response (low/high) regarding their confidence in their Type-1 decision; and (iii) a meta-metacognitive, Type-3 response (low/high) regarding the quality of their Type-2 rating. We found strong evidence for the existence of Type-3, meta-metacognitive ability. In a separate condition, participants performed an identical task with only a Type-1 response followed by a Type-2 response given on a 4-point scale. We found that the two conditions produced equivalent results such that the combination of binary Type-2 and binary Type-3 responses acts similar to a 4-point Type-2 response. Critically, while Type-2 evaluations were subject to metacognitive noise, Type-3 judgments were made at no additional cost. These results suggest that it is unlikely that there is a distinction between Type-2 and Type-3 systems (metacognition and meta-metacognition) in perceptual decision-making and, instead, a single system can be flexibly adapted to produce both Type-2 and Type-3 evaluations recursively

On the Conservative Influence of Attention on Subjective Perceptual Decision Making

Current models suggest that perception is a decision process: given noisy perceptual signals, the brain has to decide what they represent. While attention is known to enhance the perceptual signal, it has been unclear how it modulates the decision mechanism itself. Here we explored this issue in a series of studies. We used a spatial cuing paradigm to manipulate the attentional focus of observers, and found that attention leads to a conservative detection criterion such that attended stimuli are reported less often than unattended ones (Chapter 1). We investigated whether this effect would generalize to situations that do not involve detection tasks by using the same cuing paradigm, but instead asking observers to discriminate between two stimulus categories. We found that attention leads to low subjective ratings of visibility (Chapter 2). In both sets of experiments, the results were strongest when detection or discrimination capacity d' was equated between different levels of attention, or when stimuli had low contrast. To account for these results, we developed a variance reduction (VR) model of attention in which attention is postulated to reduce the variability of the perceptual signal, while keeping the decision criteria constant (Chapter 3). The VR model provided a good fit to the data observed in Chapters 1 and 2. We tested critical assumptions of the model using functional magnetic resonance imaging (Chapter 4). We found that high activity in the dorsal attention network (DAN) in the brain, which is indicative of a high attentional state, led to lower variability in the evoked signal in motion sensitive area MT+, thus supporting the idea that attention reduces perceptual variability. Further, high DAN activity resulted in lower confidence ratings, which confirmed that the findings from Chapter 2 generalize to exogenous attentional fluctuations and are not limited to spatial cuing. We tested the VR model further by extending it beyond the realm of attention (Chapter 5). We used transcranial magnetic stimulation (TMS) to directly increase the variability of the perceptual signal. The effects mirrored the effect of lack of attention: TMS led to decreased performance but increased subjective ratings. Finally, we explored the influence of attention on the amount of information carried by one's subjective ratings. We found that attention made subjective ratings more predictive of accuracy (i.e., attention improved metacognitive sensitivity) despite the fact that it decreased the overall magnitude of the subjective ratings (Chapter 6). To account for this finding, we developed a simple extension to the VR model - the "variance and criterion jitter reduction" (VCJR) model of attention which postulates that attention reduces the amount of trial-to-trial criterion jitter. Computational modeling shows that this reduction of criterion jitter leads to improved metacognitive sensitivity. We discuss these findings in relation to current debates related to attention and subjective perception, and speculate how they may account for our impression that we clearly see everything in our visual fields, including unattended objects that receive little processing

Probabilistic Model of Onset Detection Explains Paradoxes in Human Time Perception

A very basic computational model is proposed to explain two puzzling findings in the time perception literature. First, spontaneous motor actions are preceded by up to 1–2 s of preparatory activity (Kornhuber and Deecke, 1965). Yet, subjects are only consciously aware of about a quarter of a second of motor preparation (Libet et al., 1983). Why are they not aware of the early part of preparation? Second, psychophysical findings (Spence et al., 2001) support the principle of attention prior entry (Titchener, 1908), which states that attended stimuli are perceived faster than unattended stimuli. However, electrophysiological studies reported no or little corresponding temporal difference between the neural signals for attended and unattended stimuli (McDonald et al., 2005; Vibell et al., 2007). We suggest that the key to understanding these puzzling findings is to think of onset detection in probabilistic terms. The two apparently paradoxical phenomena are naturally predicted by our signal detection theoretic model

Low attention impairs optimal incorporation of prior knowledge in perceptual decisions

When visual attention is directed away from a stimulus, neural processing is weak and strength and precision of sensory data decreases. From a computational perspective, in such situations observers should give more weight to prior expectations in order to behave optimally during a discrimination task. Here we test a signal detection theoretic model that counter-intuitively predicts subjects will do just the opposite in a discrimination task with two stimuli, one attended and one unattended: when subjects are probed to discriminate the unattended stimulus, they rely less on prior information about the probed stimulus’ identity. The model is in part inspired by recent findings that attention reduces trial-by-trial variability of the neuronal population response and that they use a common criterion for attended and unattended trials. In five different visual discrimination experiments, when attention was directed away from the target stimulus, subjects did not adjust their response bias in reaction to a change in stimulus presentation frequency despite being fully informed and despite the presence of performance feedback and monetary and social incentives. This indicates that subjects did not rely more on the priors under conditions of inattention as would be predicted by a Bayes-optimal observer model. These results inform and constrain future models of Bayesian inference in the human brain

When visual metacognition fails: widespread anosognosia for visual deficits

Anosognosia for visual deficits—cases where significant visual deficits go unnoticed—challenges the view that our own conscious experiences are what we know best. We review these widespread and striking failures of awareness. Anosognosia can occur with total blindness, visual abnormalities induced by brain lesions, and eye diseases. We show that anosognosia for visual deficits is surprisingly widespread. Building on previous accounts, we introduce a framework showing how apparently disparate forms of anosognosia fit together. The central idea is that, to notice a deficit, individuals need to form expectations about normal vision, compare expectations and visual input, and judge any mismatch at the metacognitive level. A failure in any of these three steps may lead to unawareness of visual deficits

An Informal Internet Survey on the Current State of Consciousness Science

The scientific study of consciousness emerged as an organized field of research only a few decades ago. As empirical results have begun to enhance our understanding of consciousness, it is important to find out whether other factors, such as funding for consciousness research and status of consciousness scientists, provide a suitable environment for the field to grow and develop sustainably. We conducted an online survey on people’s views regarding various aspects of the scientific study of consciousness as a field of research. 249 participants completed the survey, among which 80% were in academia, and around 40% were experts in consciousness research. Topics covered include the progress made by the field, funding for consciousness research, job opportunities for consciousness researchers, and the scientific rigor of the work done by researchers in the field. The majority of respondents (78%) indicated that scientific research on consciousness has been making progress. However, most participants perceived obtaining funding and getting a job in the field of consciousness research as more difficult than in other subfields of neuroscience. Overall, work done in consciousness research was perceived to be less rigorous than other neuroscience subfields, but this perceived lack of rigor was not related to the perceived difficulty in finding jobs and obtaining funding. Lastly, we found that, overall, the global workspace theory was perceived to be the most promising (around 28%), while most non-expert researchers (around 22% of non-experts) found the integrated information theory (IIT) most promising. We believe the survey results provide an interesting picture of current opinions from scientists and researchers about the progresses made and the challenges faced by consciousness research as an independent field. They will inspire collective reflection on the future directions regarding funding and job opportunities for the field

An Informal Internet Survey on the Current State of Consciousness Science

The scientific study of consciousness emerged as an organized field of research only a few decades ago. As empirical results have begun to enhance our understanding of consciousness, it is important to find out whether other factors, such as funding for consciousness research and status of consciousness scientists, provide a suitable environment for the field to grow and develop sustainably. We conducted an online survey on people's views regarding various aspects of the scientific study of consciousness as a field of research. 249 participants completed the survey, among which 80% were in academia, and around 40% were experts in consciousness research. Topics covered include the progress made by the field, funding for consciousness research, job opportunities for consciousness researchers, and the scientific rigor of the work done by researchers in the field. The majority of respondents (78%) indicated that scientific research on consciousness has been making progress. However, most participants perceived obtaining funding and getting a job in the field of consciousness research as more difficult than in other subfields of neuroscience. Overall, work done in consciousness research was perceived to be less rigorous than other neuroscience subfields, but this perceived lack of rigor was not related to the perceived difficulty in finding jobs and obtaining funding. Lastly, we found that, overall, the global workspace theory was perceived to be the most promising (around 28%), while most non-expert researchers (around 22% of non-experts) found the integrated information theory (IIT) most promising. We believe the survey results provide an interesting picture of current opinions from scientists and researchers about the progresses made and the challenges faced by consciousness research as an independent field. They will inspire collective reflection on the future directions regarding funding and job opportunities for the field