3.1 2.0This figure summarizes data collected with a Quest staircase. The sequence of trial values and outcomes are shown by the green (correct) and red (incorrect) dots. The blue bars are the histogram of the distribution of trials over values. The gray region is the Bayesian posterior probability density for threshold. The back dots are the percent correct, and the vertical gray lines are binomial 95% confidence limits. The curve is the maximum likelihood version of a Weibull psychometric function. The legend indicates estimated parameters and error of this function. Click to see a movie of the trial history.
Psychophysica is a collection of Mathematica Notebooks containing functions for collecting and analyzing data in psychophysical experiments. The components at this time are Quest.ma, Psychometrica.ma, and Cinematica. These are described briefly below. In each case the user with a properly configured browser and a copy of Mathematica or the free MathReader can examine these notebooks online. Each includes a brief tutorial.
3.1 2.0Psychometrica.nb contains functions for fitting and plotting psychometric data, as well as definitions of LogWeibull, Logistic, and Normal psychometric functions.
7.0 5.0QUEST is an adaptive psychometric procedure for use in psychophysical experiments. The motivation for adaptive methods, the basis of the QUEST algorithm, and some descriptions of alternative methods are avaliable in the publications listed at the end of this document.
Cinematica is a software package for producing calibrated grayscale displays from within Mathematica, written by Josh Solomon and Andrew Watson.
1.0CinematicaPsychophysics.nb is a notebook that contains high-level psychophysical procedures using displays based on Cinematica. It relies on Quest.m, Psychometrica.m, and Cinematica.
Emerson, P. L. (1986). Observations on maximum likelihood and Bayesian methods of forced-choice sequential threshold estimation. Perception & Psychophysics 39, 151-153.
King-Smith, P. E., Grigsby, S. S., Vingrys, A. J., Benes, S. C. & Supowit, A. (1994). Efficient and unbiased modifications of the QUEST threshold method: Theory, simulations, experimental evaluation, and practical implementation. Vision Research 34(7), 885-912.
Treutwein, B. (1995). Adaptive psychophysical procedures. Vision Research 35(17), 2503-2522.
QUEST: A Bayesian adaptive psychometric method
(1983) Andrew B. Watson & Denis G. Pelli, Perception and Psychophysics
33(2), 113-120.
The method
of constant stimuli is inefficient (1990) Andrew B. Watson &
Fitzhugh, A., Perception & Psychophysics 47(1), 87-91.
Probability summation over time (1979) Andrew
B. Watson, Vision Research 19, 515-522.
NASA Ames Vision
Group