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Hans Strasburger - One of the best experts on this subject based on the ideXlab platform.
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a generalized cortical magnification rule predicts low contrast letter recognition in the visual field
Journal of Vision, 2010Co-Authors: Hans StrasburgerAbstract:Harvey L O Jr (1997). Efficient estimation of sensory thresholds with ML-PEST. Spatial Vision 11(1), 121-128. Strasburger H (1997). R_Contrast: Rapid measurement of recognition contrast thresholds. Spatial Vision 10, 495-498. Strasburger H (2001). Converting between measures of slope of the Psychometric Function. Perception & Psychophysics 63, 1348-1355. Strasburger H (2001). Invariance of the Psychometric Function for letter recognition across the visual field. Perception & Psychophysics 63, 1356-1376. Strasburger H & Rentschler I (1996). Contrast-dependent dissociation of visual recognition and detection fields. European Journal of Neuroscience 8, 1787-1791. Strasburger H, Rentschler I & Harvey L O Jr (1994). Cortical magnification theory fails to predict visual recognition. European Journal of Neuroscience 6, 1583-1588. Strasburger H (2002). Indirektes Sehen. Formerkennung im zentralen und peripheren Gesichtsfeld. Hogrefe: Gottingen, Bern, Toronto, Seattle. A generalized cortical magnification rule predicts low-contrast letter recognition in the visual field Hans Strasburger Generation Research Program, Human Studies Center, University of Munchen strasburger@uni-muenchen.de —— www.hans.strasburger.de .
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converting between measures of slope of the Psychometric Function
Attention Perception & Psychophysics, 2001Co-Authors: Hans StrasburgerAbstract:The Psychometric Function's slope provides information about the reliability of psychophysical threshold estimates. Furthermore, knowing the slope allows one to compare, across studies, thresholds that were obtained at different performance criterion levels. Unfortunately, the empirical validation of Psychometric Function slope estimates is hindered by the bewildering variety of slope measures that are in use. The present article provides conversion formulas for the most popular cases, including the logistic, Weibull, Quick, cumulative normal, and hyperbolic tangent Functions as analytic representations, in both linear and log coordinates and to different log bases, the practical decilog unit, the empirically based interquartile range measure of slope, and slope in a d' representation of performance.
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invariance of the Psychometric Function for character recognition across the visual field
Attention Perception & Psychophysics, 2001Co-Authors: Hans StrasburgerAbstract:The Psychometric Function for recognition of singly presented digits as a Function of digit contrast was measured at 2° steps across the horizontal meridian of the visual field, under monocular and binocular viewing conditions. A maximum-likelihood staircase procedure was used in a 10-alternative forcedchoice recognition paradigm to gather the data. Both the Weibull and the logistic Psychometric Functions provide excellent fits to the observed data. The slopes of these Functions at their point of inflection ranged from 4.0 to 5.0 proportion-correct/log10-unit contrast, for both monocular and binocular viewing and for all loci in the visual field. These slope values correspond to short-term measurements (around 30 trials, or 1 min) and do not include performance variations of longer duration; the latter are estimated to increase slope by a factor of about 1.5. A single Psychometric Function shape, centered around a threshold value, therefore describes recognition performance at all retinal loci and binocularity. An empirical comparison of slope results across the literature shows that the Function’s slope is about twice that reported for a number of detection tasks. The comparison of recognition contrast thresholds, percentage correct values, and other performance measures across studies requires the knowledge of the Psychometric Function’s slope, and our results thus provide a firm basis for the study of low-contrast character recognition
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Fitting the Psychometric Function.
Attention Perception & Psychophysics, 1999Co-Authors: Bernhard Treutwein, Hans StrasburgerAbstract:A constrained generalized maximum likelihood routine for fitting Psychometric Functions is proposed, which determines optimum values for the complete parameter set—that is, threshold and slopeas well as for guessing and lapsing probability. The constraints are realized by Bayesian prior distributions for each of these parameters. The fit itself results from maximizing the posterior distribution of the parameter values by a multidimensional simplex method. We present results from extensive Monte Carlo simulations by which we can approximate bias and variability of the estimated parameters of simulated Psychometric Functions. Furthermore, we have tested the routine with data gathered in real sessions of psychophysical experimenting.
Thomas J T P Van Den Berg - One of the best experts on this subject based on the ideXlab platform.
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reliability of the compensation comparison method for measuring retinal stray light studied using monte carlo simulations
Journal of Biomedical Optics, 2006Co-Authors: Joris E Coppens, Luuk Franssen, Thomas J T P Van Den BergAbstract:Recently the psychophysical compensation comparison method was developed for routine measurement of retinal stray light. The subject's responses to a series of two-alternative-forced-choice trials are analyzed using a maximum-likelihood (ML) approach assuming some fixed shape for the Psychometric Function (PF). This study evaluates the reliability of the method using Monte-Carlo simulations. Various sampling strategies were investigated, including the two-phase sampling strategy that is used in a commercially available instrument. Results are given for the effective dynamic range and measurement accuracy. The effect of a mismatch of the shape of the PF of an observer and the fixed shape used in the ML analysis was analyzed. Main outcomes are that the two-phase sampling scheme gives good precision (Standard deviation=0.07 logarithmic units on average) for estimation of the stray light value. Bias is virtually zero. Furthermore, a reliability index was derived from the responses and found to be effective.
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reliability of the compensation comparison stray light measurement method
Journal of Biomedical Optics, 2006Co-Authors: Joris E Coppens, Luuk Franssen, L J Van Rijn, Thomas J T P Van Den BergAbstract:The compensation comparison (CC) method is a psychophysical technique to measure retinal stray light. It uses a two alternative forced choice (2AFC) measurement paradigm. The 25 binary (0 and 1) responses resulting from the 2AFC test are analyzed using maximum likelihood estimates. The likelihood Function is used to give two quantities: the most likely stray-light level of the eye under investigation, and the accuracy of this estimate [called expected standard deviation (ESD)]. The CC method is used in 2422 subjects of the GLARE study. Each eye is tested twice to allow analysis of measurement repeatability. Furthermore, the large amount of responses is used to evaluate the shape of the Psychometric Function, for which a mathematical model is used. The shape of the Psychometric Function found by averaging the 0 and 1 responses fit well to the model Function. Data sorted according to ESD show differences in the shape of the Psychometric Function between good and bad observers. These different shapes for the Psychometric Function are used to reanalyze the data, but the stray-light results remain virtually identical. ESD proves to be an efficient tool to detect unreliable measurements. In clinical practice, ESD may be used to decide whether to repeat a measurement.
Joris E Coppens - One of the best experts on this subject based on the ideXlab platform.
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reliability of the compensation comparison method for measuring retinal stray light studied using monte carlo simulations
Journal of Biomedical Optics, 2006Co-Authors: Joris E Coppens, Luuk Franssen, Thomas J T P Van Den BergAbstract:Recently the psychophysical compensation comparison method was developed for routine measurement of retinal stray light. The subject's responses to a series of two-alternative-forced-choice trials are analyzed using a maximum-likelihood (ML) approach assuming some fixed shape for the Psychometric Function (PF). This study evaluates the reliability of the method using Monte-Carlo simulations. Various sampling strategies were investigated, including the two-phase sampling strategy that is used in a commercially available instrument. Results are given for the effective dynamic range and measurement accuracy. The effect of a mismatch of the shape of the PF of an observer and the fixed shape used in the ML analysis was analyzed. Main outcomes are that the two-phase sampling scheme gives good precision (Standard deviation=0.07 logarithmic units on average) for estimation of the stray light value. Bias is virtually zero. Furthermore, a reliability index was derived from the responses and found to be effective.
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reliability of the compensation comparison stray light measurement method
Journal of Biomedical Optics, 2006Co-Authors: Joris E Coppens, Luuk Franssen, L J Van Rijn, Thomas J T P Van Den BergAbstract:The compensation comparison (CC) method is a psychophysical technique to measure retinal stray light. It uses a two alternative forced choice (2AFC) measurement paradigm. The 25 binary (0 and 1) responses resulting from the 2AFC test are analyzed using maximum likelihood estimates. The likelihood Function is used to give two quantities: the most likely stray-light level of the eye under investigation, and the accuracy of this estimate [called expected standard deviation (ESD)]. The CC method is used in 2422 subjects of the GLARE study. Each eye is tested twice to allow analysis of measurement repeatability. Furthermore, the large amount of responses is used to evaluate the shape of the Psychometric Function, for which a mathematical model is used. The shape of the Psychometric Function found by averaging the 0 and 1 responses fit well to the model Function. Data sorted according to ESD show differences in the shape of the Psychometric Function between good and bad observers. These different shapes for the Psychometric Function are used to reanalyze the data, but the stray-light results remain virtually identical. ESD proves to be an efficient tool to detect unreliable measurements. In clinical practice, ESD may be used to decide whether to repeat a measurement.
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compensation comparison method for assessment of retinal straylight
Investigative Ophthalmology & Visual Science, 2006Co-Authors: Luuk Franssen, Joris E Coppens, Thomas BergAbstract:METHODS. The psychophysical technique of the “direct compensation” method was adapted to make it suitable for routine clinical assessment. In the new approach, called “compensation comparison, ” the central test field is subdivided into two half fields: one with and one without counterphase compensation light. The subject’s task is a forced-choice comparison between the two half fields, to decide which half flickers more strongly. A theoretical form for the respective Psychometric Function was defined and experimentally verified in a laboratory experiment involving seven subjects, with and without artificially increased light scattering. The method was applied in a separate multicenter study. Its reliability was additionally tested with a commercial implement (C-Quant; Oculus Op
Michael Bach - One of the best experts on this subject based on the ideXlab platform.
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the freiburg visual acuity test variability unchanged by post hoc re analysis
Graefes Archive for Clinical and Experimental Ophthalmology, 2007Co-Authors: Michael BachAbstract:The Freiburg Visual Acuity and Contrast Test (FrACT) has been further developed; it is now available for Macintosh and Windows free of charge at http://www.michaelbach.de/fract.html . The present study sought to reduce the test-retest variability of visual acuity on short runs (18 trials) by post-hoc re-analysis. The FrACT employs advanced computer graphics to present Landolt Cs over the full range of visual acuity. The sequence of optotypes presented follows an adaptive staircase procedure, the Best-PEST algorithm. The Best-PEST threshold obtained after 18 trials was compared to the result of a post-hoc re-analysis of the acquired data, where both threshold and slope of the Psychometric Function were estimated via a maximum-likelihood fit. Testing time was 1.7 min per run on average. Test-retest reproducibility was ±2 lines (or ±0.2 logMAR) for a 95% confidence band (using 18 optotype presentations per test run). Post-hoc Psychometric fitting reproduced the Best-PEST result within 1%, although the individual slopes varied widely; test-retest reproducibility was not improved. The FrACT offers advantages over traditional chart testing with respect to objectivity and reliability. The similarity between the results of the Best-PEST vs. post-hoc analysis, fitting both slope and threshold, suggest that there is no disadvantage to the constant slope assumed by Best PEST. Furthermore, since variability was not reduced by post-hoc analysis, for high reliability more trials should be employed than the 18 trials per run used here.
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the freiburg visual acuity test automatic measurement of visual acuity
Optometry and Vision Science, 1996Co-Authors: Michael BachAbstract:The Freiburg Visual Acuity test is an automated procedure for self-administered measurement of visual acuity. Landolt-Cs are presented on a monitor in one of eight orientations. The subject presses one of eight buttons, which are spatially arranged on a response box according to the eight possible positions of the Landolt-Cs' gap. To estimate the acuity threshold, a best PEST (best Parameter Estimation by Sequential Testing) procedure is used in which a Psychometric Function having a constant slope on a logarithmic acuity scale is assumed. Measurement terminates after a fixed number of trials. With computer monitors, pixel-discreteness artifacts limit the presentation of small stimuli. By using anti-aliasing, i.e., smoothing of contours by multiple gray levels, the spatial resolution was improved by a factor of four. Thus, even the shape of small Landolt-Cs with oblique gaps is adequate and visual acuities from 5/80 (0.06) up to 5/1.4 (3.6) can be tested at a distance of 5 m.
Miguel A Garciaperez - One of the best experts on this subject based on the ideXlab platform.
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shifts of the Psychometric Function distinguishing bias from perceptual effects
Quarterly Journal of Experimental Psychology, 2013Co-Authors: Miguel A Garciaperez, Rocio AlcalaquintanaAbstract:Morgan, Dillenburger, Raphael, and Solomon have shown that observers can use different response strategies when unsure of their answer, and, thus, they can voluntarily shift the location of the Psychometric Function estimated with the method of single stimuli (MSS; sometimes also referred to as the single-interval, two-alternative method). They wondered whether MSS could distinguish response bias from a true perceptual effect that would also shift the location of the Psychometric Function. We demonstrate theoretically that the inability to distinguish response bias from perceptual effects is an inherent shortcoming of MSS, although a three-response format including also an “undecided” response option may solve the problem under restrictive assumptions whose validity cannot be tested with MSS data. We also show that a proper two-alternative forced-choice (2AFC) task with the three-response format is free of all these problems so that bias and perceptual effects can easily be separated out. The use of a thr...
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Psychometric Functions for detection and discrimination with and without flankers
Attention Perception & Psychophysics, 2011Co-Authors: Miguel A Garciaperez, Russell L Woods, Rocio Alcalaquintana, Eli PeliAbstract:Recent studies have reported that flanking stimuli broaden the Psychometric Function and lower detection thresholds. In the present study, we measured Psychometric Functions for detection and discrimination with and without flankers to investigate whether these effects occur throughout the contrast continuum. Our results confirm that lower detection thresholds with flankers are accompanied by broader Psychometric Functions. Psychometric Functions for discrimination reveal that discrimination thresholds with and without flankers are similar across standard levels, and that the broadening of Psychometric Functions with flankers disappears as standard contrast increases, to the point that Psychometric Functions at high standard levels are virtually identical with or without flankers. Threshold-versus-contrast (TvC) curves with flankers only differ from TvC curves without flankers in occasional shallower dippers and lower branches on the left of the dipper, but they run virtually superimposed at high standard levels. We discuss differences between our results and other results in the literature, and how they are likely attributed to the differential vulnerability of alternative psychophysical procedures to the effects of presentation order. We show that different models of flanker facilitation can fit the data equally well, which stresses that succeeding at fitting a model does not validate it in any sense.
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bayesian adaptive estimation of arbitrary points on a Psychometric Function
British Journal of Mathematical and Statistical Psychology, 2007Co-Authors: Miguel A Garciaperez, Rocio AlcalaquintanaAbstract:Bayesian adaptive methods have been extensively used in psychophysics to estimate the point at which performance on a task attains arbitrary percentage levels, although the statistical properties of these estimators have never been assessed. We used simulation techniques to determine the small-sample properties of Bayesian estimators of arbitrary performance points, specifically addressing the issues of bias and precision as a Function of the target percentage level. The study covered three major types of psychophysical task (yes-no detection, 2AFC discrimination and 2AFC detection) and explored the entire range of target performance levels allowed for by each task. Other factors included in the study were the form and parameters of the actual Psychometric Function Psi, the form and parameters of the model Function M assumed in the Bayesian method, and the location of Psi within the parameter space. Our results indicate that Bayesian adaptive methods render unbiased estimators of any arbitrary point on psi only when M=Psi, and otherwise they yield bias whose magnitude can be considerable as the target level moves away from the midpoint of the range of Psi. The standard error of the estimator also increases as the target level approaches extreme values whether or not M=Psi. Contrary to widespread belief, neither the performance level at which bias is null nor that at which standard error is minimal can be predicted by the sweat factor. A closed-form expression nevertheless gives a reasonable fit to data describing the dependence of standard error on number of trials and target level, which allows determination of the number of trials that must be administered to obtain estimates with prescribed precision.