Signal Detection Theory Analysis of Type 1 and Type 2 Data: Meta-d′, Response-Specific Meta-d′, and the Unequal Variance SDT Model

Maniscalco, Brian; Lau, Hakwan

doi:10.1007/978-3-642-45190-4_3

Cited by 165 publications

(234 citation statements)

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“…A similar procedure was used to simulate sensory samples and behavioral responses for the second block half of 250 trials. Now that each trial was associated with a true stimulus configuration as well as the simulated subject's perceptual and metacognitive judgments, we were able to compute dЈ and meta-dЈ for the first and second block halves for each simulated subject using standard SDT analyses (Macmillan and Creelman, 2005;Lau, 2012, 2014).…”

Section: Monte Carlo Sdt Simulationsmentioning

confidence: 99%

“…If a single process generates perceptual and metacognitive decisions, we should expect declines in perceptual sensitivity to be associated with declines in metacognitive sensitivity Lau, 2012, 2014). Conversely, if distinct processes generate perceptual and metacognitive decisions, we might expect vigilance decrements in perception and metacognition to be dissociable.…”

Section: Introductionmentioning

confidence: 99%

“…Recent work has developed a signal detection theory (SDT) analysis of confidence ratings (Galvin et al, 2003;Lau, 2012, 2014), allowing for a bias-free measure of metacognitive sensitivity (i.e., an observer's ability to discriminate between her own correct and incorrect judgments, regardless of her tendency to report high confidence). Of particular interest is how such measures of metacognition are related to perceptual performance.…”

Section: Introductionmentioning

confidence: 99%

“…Of particular interest is how such measures of metacognition are related to perceptual performance. A tacit assumption of the classical SDT analysis of confidence rating data is that perceptual decisions and confidence rating are based on the same underlying process (Galvin et al, 2003;Macmillan and Creelman, 2005;Lau, 2012, 2014), and this view has received some empirical support (Kepecs et al, 2008;Kiani and Shadlen, 2009;Kepecs and Mainen, 2012). Other findings suggest that metacognition is subserved by high-level prefrontal mechanisms and is therefore partially dissociable from perceptual performance (Fleming et al, 2010(Fleming et al, , 2014Pleskac and Busemeyer, 2010;Rounis et al, 2010;McCurdy et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Conversely, if distinct processes generate perceptual and metacognitive decisions, we might expect vigilance decrements in perception and metacognition to be dissociable. Importantly, according to SDT, for an ideal observer, perceptual performance should be related to metacognitive performance such that dЈ ϭ meta-dЈ Lau, 2012, 2014). However, deviations from this expectation caused by sampling error and suboptimal metacognitive performance are to be expected, so a comparison between real data and an SDT model assuming no differences between these two measures may result in spurious findings attributable to an overly conservative null hypothesis.…”

Section: Introductionmentioning

confidence: 99%

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Limited Cognitive Resources Explain a Trade-Off between Perceptual and Metacognitive Vigilance

Maniscalco

McCurdy

Odegaard³

et al. 2016

J. Neurosci.

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Why do experimenters give subjects short breaks in long behavioral experiments? Whereas previous studies suggest it is difficult to maintain attention and vigilance over long periods of time, it is unclear precisely what mechanisms benefit from rest after short experimental blocks. Here, we evaluate decline in both perceptual performance and metacognitive sensitivity (i.e., how well confidence ratings track perceptual decision accuracy) over time and investigate whether characteristics of prefrontal cortical areas correlate with these measures. Whereas a single-process signal detection model predicts that these two forms of fatigue should be strongly positively correlated, a dual-process model predicts that rates of decline may dissociate. Here, we show that these measures consistently exhibited negative or near-zero correlations, as if engaged in a trade-off relationship, suggesting that different mechanisms contribute to perceptual and metacognitive decisions. Despite this dissociation, the two mechanisms likely depend on common resources, which could explain their trade-off relationship. Based on structural MRI brain images of individual human subjects, we assessed gray matter volume in the frontal polar area, a region that has been linked to visual metacognition. Variability of frontal polar volume correlated with individual differences in behavior, indicating the region may play a role in supplying common resources for both perceptual and metacognitive vigilance. Additional experiments revealed that reduced metacognitive demand led to superior perceptual vigilance, providing further support for this hypothesis. Overall, results indicate that during breaks between short blocks, it is the higher-level perceptual decision mechanisms, rather than lower-level sensory machinery, that benefit most from rest.

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Section: Monte Carlo Sdt Simulationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Limited Cognitive Resources Explain a Trade-Off between Perceptual and Metacognitive Vigilance

Maniscalco

McCurdy

Odegaard³

et al. 2016

J. Neurosci.

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Multilingualism and Metacognitive Processing

Bright¹,

Ouzia²,

Filippi³

2019

The Handbook of the Neuroscience of Multilingualism

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Neural correlates of metacognition: Disentangling the brain circuits underlying prospective and retrospective second‐order judgments through noninvasive brain stimulation

Saccenti,

Moro,

Sassaroli

et al. 2024

J of Neuroscience Research

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Metacognition encompasses the capability to monitor and control one's cognitive processes, with metamemory and metadecision configuring among the most studied higher order functions. Although imaging experiments evaluated the role of disparate brain regions, neural substrates of metacognitive judgments remain undetermined. The aim of this systematic review is to summarize and discuss the available evidence concerning the neural bases of metacognition which has been collected by assessing the effects of noninvasive brain stimulation (NIBS) on human subjects' metacognitive capacities. Based on such literature analysis, our goal is, at first, to verify whether prospective and retrospective second‐order judgments are localized within separate brain circuits and, subsequently, to provide compelling clues useful for identifying new targets for future NIBS studies. The search was conducted following the preferred reporting items for systematic reviews and meta‐analyses guidelines among PubMed, PsycINFO, PsycARTICLES, PSYNDEX, MEDLINE, and ERIC databases. Overall, 25 studies met the eligibility criteria, yielding a total of 36 experiments employing transcranial magnetic stimulation and 16 ones making use of transcranial electrical stimulation techniques, including transcranial direct current stimulation and transcranial alternating current stimulation. Importantly, we found that both perspective and retrospective judgments about both memory and perceptual decision‐making performances depend on the activation of the anterior and lateral portions of the prefrontal cortex, as well as on the activity of more caudal regions such as the premotor cortex and the precuneus. Combining this evidence with results from previous imaging and lesion studies, we advance ventromedial prefrontal cortex as a promising target for future NIBS studies.

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Signal Detection Theory Analysis of Type 1 and Type 2 Data: Meta-d′, Response-Specific Meta-d′, and the Unequal Variance SDT Model

Cited by 165 publications

References 20 publications

Limited Cognitive Resources Explain a Trade-Off between Perceptual and Metacognitive Vigilance

Limited Cognitive Resources Explain a Trade-Off between Perceptual and Metacognitive Vigilance

Multilingualism and Metacognitive Processing

Neural correlates of metacognition: Disentangling the brain circuits underlying prospective and retrospective second‐order judgments through noninvasive brain stimulation

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