Efficient estimation of stereo thresholds: What slope should be assumed for the psychometric function?
Autoři:
Ignacio Serrano-Pedraza aff001; Kathleen Vancleef aff003; William Herbert aff002; Nicola Goodship aff002; Maeve Woodhouse aff002; Jenny C. A. Read aff002
Působiště autorů:
Faculty of Psychology, Universidad Complutense de Madrid, Madrid, Spain
aff001; Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
aff002; Cognitive Neuropsychology Centre, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
aff003
Vyšlo v časopise:
PLoS ONE 15(1)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0226822
Souhrn
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 log10 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 log10 arcsec for 2AFC (slope β = 4.3 /log10 arcsec), and around σ = 1.5 log10 arcsec for 4AFC (β = 4.9 /log10 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.
Klíčová slova:
Simulation and modeling – Analysis of variance – Probability distribution – Normal distribution – Psychophysics – Bayesian method – Luminance
Zdroje
1. Treutwein B. Adaptive psychophysical procedures. Vision Res. 1995;35(17):2503–22. doi: 10.1016/0042-6989(95)00016-s 8594817.
2. Emerson PL. Observations on a maximum likelihood method of sequential threshold estimation and a simplified approximation. Percept Psychophys. 1984;36(2):199–203. doi: 10.3758/bf03202680 6514529.
3. Madigan R, Williams D. Maximum-likelihood psychometric procedures in two-alternative forced-choice: evaluation and recommendations. Percept Psychophys. 1987;42(3):240–9. doi: 10.3758/bf03203075 3671049.
4. Green DM. Stimulus selection in adaptive psychophysical procedures. J Acoust Soc Am. 1990;87(6):2662–74. doi: 10.1121/1.399058 2373801.
5. Alcala-Quintana R, Garcia-Perez MA. The role of parametric assumptions in adaptive Bayesian estimation. Psychol Methods. 2004;9(2):250–71. doi: 10.1037/1082-989X.9.2.250 15137892.
6. King-Smith PE, Grigsby SS, Vingrys AJ, Benes SC, Supowit A. Efficient and unbiased modifications of the QUEST threshold method: theory, simulations, experimental evaluation and practical implementation. Vision Res. 1994;34(7):885–912. doi: 10.1016/0042-6989(94)90039-6 8160402.
7. Watson AB, Pelli DG. QUEST: a Bayesian adaptive psychometric method. Percept Psychophys. 1983;33(2):113–20. doi: 10.3758/bf03202828 6844102.
8. Pentland A. Maximum likelihood estimation: the best PEST. Percept Psychophys. 1980;28(4):377–9. doi: 10.3758/bf03204398 7465322.
9. Emerson PL. Observations on maximum-likelihood and Bayesian methods of forced-choice sequential threshold estimation. Percept Psychophys. 1986;39(2):151–3. doi: 10.3758/bf03211498 3725540.
10. Anderson AJ. Utility of a dynamic termination criterion in the ZEST adaptive threshold method. Vision Res. 2003;43(2):165–70. doi: 10.1016/s0042-6989(02)00396-6 12536138.
11. Snoeren PR, Puts MJH. Multiple Parameter Estimation in an Adaptive Psychometric Method: MUEST, an Extension of the QUEST Method. J Math Psychol. 1997;41(4):431–9. doi: 10.1006/jmps.1997.1188 9473404.
12. King-Smith PE, Rose D. Principles of an adaptive method for measuring the slope of the psychometric function. Vision Res. 1997;37(12):1595–604. doi: 10.1016/s0042-6989(96)00310-0 9231226.
13. Kontsevich LL, Tyler CW. Bayesian adaptive estimation of psychometric slope and threshold. Vision Res. 1999;39(16):2729–37. doi: 10.1016/s0042-6989(98)00285-5 10492833.
14. Prins N. The psi-marginal adaptive method: How to give nuisance parameters the attention they deserve (no more, no less). J Vis. 2013;13(7):3. doi: 10.1167/13.7.3 23750016.
15. Watson AB. QUEST+: A general multidimensional Bayesian adaptive psychometric method. J Vis. 2017;17(3):10. doi: 10.1167/17.3.10 28355623.
16. Pelli DG. The VideoToolbox software for visual psychophysics: transforming numbers into movies. Spat Vis. 1997;10(4):437–42. doi: 10.1163/156856897x00366 9176953.
17. Brainard DH. The Psychophysics Toolbox. Spat Vis. 1997;10(4):433–6. 9176952.
18. Kleiner M, Brainard D, Pelli D. What's new in Psychtoolbox-3? Perception. 2007;36:14.
19. Serrano-Pedraza I, Vancleef K, Read JC. Avoiding monocular artifacts in clinical stereotests presented on column-interleaved digital stereoscopic displays. J Vis. 2016;16(14):13. doi: 10.1167/16.14.13 27846341.
20. Sierra-Vazquez V, Serrano-Pedraza I, Luna D. The effect of spatial-frequency filtering on the visual processing of global structure. Perception. 2006;35(12):1583–609. doi: 10.1068/p5364 17283927.
21. Garcia-Perez MA, Alcala-Quintana R. Sampling plans for fitting the psychometric function. Span J Psychol. 2005;8(2):256–89. doi: 10.1017/s113874160000514x 16255393.
22. Wichmann FA, Hill NJ. The psychometric function: I. Fitting, sampling, and goodness of fit. Percept Psychophys. 2001;63(8):1293–313. doi: 10.3758/bf03194544 11800458.
23. Cooper J, Feldman J, Medlin D. Comparing stereoscopic performance of children using the Titmus, TNO, and Randot stereo tests. J Am Optom Assoc. 1979;50(7):821–5. 500993.
24. Fox R, Patterson R, Francis EL. Stereoacuity in young children. Invest Ophthalmol Vis Sci. 1986;27(4):598–600. 3957579.
25. Ciner EB, Schanel-Klitsch E, Herzberg C. Stereoacuity development: 6 months to 5 years. A new tool for testing and screening. Optom Vis Sci. 1996;73(1):43–8. doi: 10.1097/00006324-199601000-00007 8867681.
26. Serrano-Pedraza I, Manjunath V, Osunkunle O, Clarke MP, Read JC. Visual suppression in intermittent exotropia during binocular alignment. Invest Ophthalmol Vis Sci. 2011;52(5):2352–64. doi: 10.1167/iovs.10-6144 21220559.
27. Serrano-Pedraza I, Herbert W, Villa-Laso L, Widdall M, Vancleef K, Read JC. The Stereoscopic Anisotropy Develops During Childhood. Invest Ophthalmol Vis Sci. 2016;57(3):960–70. doi: 10.1167/iovs.15-17766 26962692.
28. Zaroff CM, Knutelska M, Frumkes TE. Variation in stereoacuity: normative description, fixation disparity, and the roles of aging and gender. Invest Ophthalmol Vis Sci. 2003;44(2):891–900. doi: 10.1167/iovs.02-0361 12556426.
29. Garnham L, Sloper JJ. Effect of age on adult stereoacuity as measured by different types of stereotest. Br J Ophthalmol. 2006;90(1):91–5. doi: 10.1136/bjo.2005.077719 16361675.
30. Kingdom FAA, Prins N. Psychophysics: A Practical Introduction. London: Elsevier2010.
31. Read J, Vancleef K, Serrano-Pedraza I, Morgan G, Sharp C, Clarke M. ASTEROID: Accurate STEReoacuity measurement in the eye clinic. Perception. 2015;44:75–6.
32. Vancleef K, Serrano-Pedraza I, Sharp C, Slack G, Black C, Casanova T, et al. ASTEROID: A New Clinical Stereotest on an Autostereo 3D Tablet. Transl Vis Sci Technol. 2019;8(1):25. doi: 10.1167/tvst.8.1.25 30834173.
33. Kim W, Pitt MA, Lu ZL, Steyvers M, Myung JI. A hierarchical adaptive approach to optimal experimental design. Neural Comput. 2014;26(11):2465–92. doi: 10.1162/NECO_a_00654 25149697.
34. Vancleef K, Read JCA, Herbert W, Goodship N, Woodhouse M, Serrano-Pedraza I. Two choices good, four choices better: For measuring stereoacuity in children, a four-alternative forced-choice paradigm is more efficient than two. PLoS One. 2018;13(7):e0201366. doi: 10.1371/journal.pone.0201366 30059524.
35. Alcala-Quintana R, Garcia-Perez MA. A comparison of fixed-step-size and Bayesian staircases for sensory threshold estimation. Spat Vis. 2007;20(3):197–218. doi: 10.1163/156856807780421174 17524255.
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