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Efficient estimation of stereo thresholds: What slope should be assumed for the psychometric function?

Bayesian staircases are widely used in psychophysics to estimate detection thresholds. Simulations have revealed the importance of the parameters selected for the assumed subject’s psychometric function in enabling thresholds to be estimated with small bias and high precision. One important paramete...

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Autores principales: Serrano-Pedraza, Ignacio, Vancleef, Kathleen, Herbert, William, Goodship, Nicola, Woodhouse, Maeve, Read, Jenny C. A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6939937/
https://www.ncbi.nlm.nih.gov/pubmed/31895925
http://dx.doi.org/10.1371/journal.pone.0226822
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author Serrano-Pedraza, Ignacio
Vancleef, Kathleen
Herbert, William
Goodship, Nicola
Woodhouse, Maeve
Read, Jenny C. A.
author_facet Serrano-Pedraza, Ignacio
Vancleef, Kathleen
Herbert, William
Goodship, Nicola
Woodhouse, Maeve
Read, Jenny C. A.
author_sort Serrano-Pedraza, Ignacio
collection PubMed
description Bayesian staircases are widely used in psychophysics to estimate detection thresholds. Simulations have revealed the importance of the parameters selected for the assumed subject’s psychometric function in enabling thresholds to be estimated with small bias and high precision. One important parameter is the slope of the psychometric function, or equivalently its spread. This is often held fixed, rather than estimated for individual subjects, because much larger numbers of trials are required to estimate the spread as well as the threshold. However, if this fixed value is wrong, the threshold estimate can be biased. Here we determine the optimal slope to minimize bias and maximize precision when measuring stereoacuity with Bayesian staircases. We performed 2- and 4AFC disparity detection stereo experiments in order to measure the spread of the disparity psychometric function in human observers assuming a Logistic function. We found a wide range, between 0.03 and 3.5 log(10) arcsec, with little change with age. We then ran simulations to examine the optimal spread using the empirical data. From our simulations and for three different experiments, we recommend selecting assumed spread values between the percentiles 60–80% of the population distribution of spreads (these percentiles can be extended to other type of thresholds). For stereo thresholds, we recommend a spread around the value σ = 1.7 log(10) arcsec for 2AFC (slope β = 4.3 /log(10) arcsec), and around σ = 1.5 log(10) arcsec for 4AFC (β = 4.9 /log(10) arcsec). Finally, we compared a Bayesian procedure (ZEST using the optimal σ) with five Bayesian procedures that are versions of ZEST-2D, Psi, and Psi-marginal. In general, for the conditions tested, ZEST optimal σ showed the lowest threshold bias and highest precision.
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spelling pubmed-69399372020-01-10 Efficient estimation of stereo thresholds: What slope should be assumed for the psychometric function? Serrano-Pedraza, Ignacio Vancleef, Kathleen Herbert, William Goodship, Nicola Woodhouse, Maeve Read, Jenny C. A. PLoS One Research Article Bayesian staircases are widely used in psychophysics to estimate detection thresholds. Simulations have revealed the importance of the parameters selected for the assumed subject’s psychometric function in enabling thresholds to be estimated with small bias and high precision. One important parameter is the slope of the psychometric function, or equivalently its spread. This is often held fixed, rather than estimated for individual subjects, because much larger numbers of trials are required to estimate the spread as well as the threshold. However, if this fixed value is wrong, the threshold estimate can be biased. Here we determine the optimal slope to minimize bias and maximize precision when measuring stereoacuity with Bayesian staircases. We performed 2- and 4AFC disparity detection stereo experiments in order to measure the spread of the disparity psychometric function in human observers assuming a Logistic function. We found a wide range, between 0.03 and 3.5 log(10) arcsec, with little change with age. We then ran simulations to examine the optimal spread using the empirical data. From our simulations and for three different experiments, we recommend selecting assumed spread values between the percentiles 60–80% of the population distribution of spreads (these percentiles can be extended to other type of thresholds). For stereo thresholds, we recommend a spread around the value σ = 1.7 log(10) arcsec for 2AFC (slope β = 4.3 /log(10) arcsec), and around σ = 1.5 log(10) arcsec for 4AFC (β = 4.9 /log(10) arcsec). Finally, we compared a Bayesian procedure (ZEST using the optimal σ) with five Bayesian procedures that are versions of ZEST-2D, Psi, and Psi-marginal. In general, for the conditions tested, ZEST optimal σ showed the lowest threshold bias and highest precision. Public Library of Science 2020-01-02 /pmc/articles/PMC6939937/ /pubmed/31895925 http://dx.doi.org/10.1371/journal.pone.0226822 Text en © 2020 Serrano-Pedraza et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Serrano-Pedraza, Ignacio
Vancleef, Kathleen
Herbert, William
Goodship, Nicola
Woodhouse, Maeve
Read, Jenny C. A.
Efficient estimation of stereo thresholds: What slope should be assumed for the psychometric function?
title Efficient estimation of stereo thresholds: What slope should be assumed for the psychometric function?
title_full Efficient estimation of stereo thresholds: What slope should be assumed for the psychometric function?
title_fullStr Efficient estimation of stereo thresholds: What slope should be assumed for the psychometric function?
title_full_unstemmed Efficient estimation of stereo thresholds: What slope should be assumed for the psychometric function?
title_short Efficient estimation of stereo thresholds: What slope should be assumed for the psychometric function?
title_sort efficient estimation of stereo thresholds: what slope should be assumed for the psychometric function?
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6939937/
https://www.ncbi.nlm.nih.gov/pubmed/31895925
http://dx.doi.org/10.1371/journal.pone.0226822
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