The idiosyncratic nature of confidence

Navajas, Joaquín Fernández-Crehuet; Hindocha, Chandni; Foda, Hebah; Keramati, Mehdi; Latham, Peter E.; Bahrami, Bahador

doi:10.1038/s41562-017-0215-1

Cited by 109 publications

(124 citation statements)

References 45 publications

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“…the orientation of the stimulus (Rausch et al, 2015;Rausch & Zehetleitner, 2016). However, previous studies indicated (Navajas et al, 2017;Rausch et al, 2018) and Exp. 2 corroborated the view that sensory evidence about identity-irrelevant features of the stimulus are involved in the calculation of decisional confidence, too.…”

Section: Discussionmentioning

confidence: 87%

Modelling visibility judgments using models of decision confidence

Rausch¹,

Zehetleitner²

2018

Preprint

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How can we explain the regularities in subjective reports of human observers about their subjective visual experience of a stimulus? The present study tests if a recent model of decisional confidence, the weighted evidence and visibility model, can be generalized from confidence to subjective visibility. In a masked orientation identification task, observers reported the subjective visibility of the stimulus after each single identification response. Cognitive modelling revealed that the weighted evidence and visibility model provided a superior fit to the data compared to the standard signal detection model, the signal detection model with unsystematic noise superimposed on ratings, the postdecisional accumulation model, the two-channel model, the response-congruent evidence model, the two-dimensional Bayesian model, and the constant noise and decay model. A comparison between subjective visibility and decisional confidence revealed that visibility relied more on the strength of sensory evidence about features of the stimulus irrelevant to the identification judgment and less on evidence for the identification judgment. It is argued that at least two types of evidence are required to account for subjective visibility, one related to the identification judgment, and one related to the strength of stimulation.

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Section: Discussionmentioning

confidence: 87%

Modelling visibility judgments using models of decision confidence

Rausch¹,

Zehetleitner²

2018

Preprint

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“…In our noreport conditions, instead, responses were completely absent and may have shifted participant's global strategies for the computation of confidence. In other words, we contest that while first-order reaction time information is, under some experimental settings used by participants to generate a confidence judgement, when motor information is not available at all, it may be replaced by other, equally precise sources of information, closer to the strength of evidence (such as the probability of being correct (Sanders et al, 2016), the internal signal noise (Navajas et al, 2017) and the evidence in favour of the chosen response alternative (Peters et al, 2017). This admittedly speculative account is compatible with our capacity to form confidence estimates about decisions that are not directly linked to a transient motor action, for instance when controlling a brain machine interface (Schurger, Gale, Gozel, & Blanke, 2017) or when making global confidence judgments in ecological contexts (Rouault, Dayan, & Fleming, 2019).…”

Section: Differences With the Existing Literaturementioning

confidence: 99%

Response-related signals increase confidence but not metacognitive performance

Filevich

Koß

Faivre³

2019

Preprint

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AbstractConfidence judgements are a central tool for research in metacognition. In a typical task, participants first perform perceptual (first-order) decisions and then rate their confidence in these decisions. The relationship between confidence and first-order accuracy is taken as measure of metacognitive performance. Confidence is often assumed to stem from decision-monitoring processes alone, but processes that co-occur with the first-order decision may also play a role in confidence formation. In fact, across a broad range of tasks, trials with quick reaction times to the first-order task are often judged with relatively higher confidence than those with slow responses. This robust finding suggests that confidence could be informed by a readout of reaction times in addition to decision-monitoring processes. To test this possibility, we assessed the contribution of response-related signals to confidence and, in particular, to metacognitive performance (i.e., a measure of the adequacy of these confidence judgements). In a factorial design, we measured the effect of making an overt (vs. covert) decision, as well as the effect of pairing a motor action to the stimulus about which the first-order decision is made. Against our expectations, we found no differences in overall confidence or metacognitive performance when first-order responses were covert as opposed to overt. Further, actions paired to visual stimuli presented led to higher confidence ratings, but did not affect metacognitive performance. These results suggest that some of the relationships between first-order decisional signals and confidence might indeed be correlational, and attributable to an upstream cognitive process, common to the two of them.

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“…on the posterior probability of being correct. Although one study found that confidence ratings are consistent with computations based on the posterior probability (Sanders et al 2016; but see Adler & Ma 2018b), others showed that either some (Aitchison et al 2015;Navajas et al 2017) or most (Adler & Ma 2018a;Denison et al 2018) observers are described better by heuristic models in which confidence depends on uncertainty but not on the actual posterior probability of being correct.…”

Section: Confidence Does Not Simply Reflect the Posterior Probabilitymentioning

confidence: 92%

Excess of individual variability of priors prevents successful development of general models

Bachmann

2018

Behav Brain Sci

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Perceptual judgments are influenced by a multitude of factors in addition to the perceptual input. Particularly, the widely varying individual neurobiological endophenotypes and individual differences in the propensity for expectation-based illusory percepts make it unlikely that optimality is possible to define and defend by the type of abstract modeling approach criticized by Rahnev & Denison (R&D).

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The idiosyncratic nature of confidence

Cited by 109 publications

References 45 publications

Modelling visibility judgments using models of decision confidence

Modelling visibility judgments using models of decision confidence

Response-related signals increase confidence but not metacognitive performance

Excess of individual variability of priors prevents successful development of general models

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