ArticleJournal of neurophysiology2016
A quantitative confidence signal detection model: 1. Fitting psychometric functions.
Article in Journal of neurophysiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Noisy galvanic vestibular stimulation induces stochastic resonance in vestibular perceptual thresholds assessed efficiently using confidence reports.Experimental brain research · 2024Article
- Your Vestibular Thresholds May Be Lower Than You Think: Cognitive Biases in Vestibular Psychophysics.American journal of audiology · 2023Article
- Vestibular Precision at the Level of Perception, Eye Movements, Posture, and Neurons.Neuroscience · 2021Review
- Are you sure? The relationship between response certainty and performance in visual detection using a perimetry-style task.Journal of vision · 2020Article
- Frontal scalp potentials foretell perceptual choice confidence.Journal of neurophysiology · 2020Article
- The Confidence Database.Nature human behaviour · 2020Article
- A quantitative confidence signal detection model: 2. Confidence analysis.Journal of neurophysiology · 2019Article
- When uncertain, does human self-motion decision-making fully utilize complete information?Journal of neurophysiology · 2018Article
- Unbounded evidence accumulation characterizes subjective visual vertical forced-choice perceptual choice and confidence.Journal of neurophysiology · 2017Article
- Perception of combined translation and rotation in the horizontal plane in humans.Journal of neurophysiology · 2016Article
Corrections and comments
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Authors and funding
2 authors.
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Abstract
Perceptual thresholds are commonly assayed in the laboratory and clinic. When precision and accuracy are required, thresholds are quantified by fitting a psychometric function to forced-choice data. The primary shortcoming of this approach is that it typically requires 100 trials or more to yield accurate (i.e., small bias) and precise (i.e., small variance) psychometric parameter estimates. We show that confidence probability judgments combined with a model of confidence can yield psychometric parameter estimates that are markedly more precise and/or markedly more efficient than conventional methods. Specifically, both human data and simulations show that including confidence probability judgments for just 20 trials can yield psychometric parameter estimates that match the precision of those obtained from 100 trials using conventional analyses. Such an efficiency advantage would be especially beneficial for tasks (e.g., taste, smell, and vestibular assays) that require more than a few seconds for each trial, but this potential benefit could accrue for many other tasks.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.