## QuestDemo

##### >Psychtoolbox>Quest

One of the great contributions of psychophysics to psychology is the

notion of measuring threshold, i.e. the signal strength required for a

criterion level of response by the observer (Pelli & Farell, 1994;

Farell & Pelli, 1999). Watson and Pelli (1983) described a maximum

likelihood procedure, which they called QUEST, for estimating threshold.

The Quest toolbox in the Psychtoolbox is a set of MATLAB functions

that implement all the original QUEST functions, plus several others.

You can think of it as a Bayesian toolbox for testing observers and

estimating their thresholds. This QUEST toolbox is self-contained,

and runs on any computer with MATLAB 5 or better.

web http://psychtoolbox.org/

web http://psych.nyu.edu/pelli/software.html#quest

By commenting and uncommenting five lines below, you can use this file

to implement three QUEST-related procedures for measuring threshold.

QuestMode: In the original algorithm of Watson & Pelli (1983), each

trial is at the MODE of the posterior pdf. Their final estimate is

maximum likelihood, which is the MODE of the posterior pdf after

dividing out the prior pdf. (Subsequent experience has shown that it’s

better not to divide out the prior, simply using MODE of posterior pdf

throughout.)

QuestMean: In the improved algorithm of King-Smith et al. (1994), each

trial and the final estimate are at the MEAN of the posterior pdf.

QuestQuantile & QuestMean: In the ideal algorithm of Pelli (1987), each

trial is at the best QUANTILE, and the final estimate is at the MEAN of

the posterior pdf.

You begin by calling QuestCreate, telling Quest what is your prior

knowledge, i.e. a guess and associated sd for threshold. Then you run

some number of trials, typically 40. For each trial you ask Quest to

recommend a test intensity. Then you actually test the observer at some

intensity, not necessarily what Quest recommended, and then you call

QuestUpdate to report to Quest the actual intensity used and whether the

observer got it right. Quest saves this information in your Quest struct,

which we usually call “q”. This cycle is repeated for each trial. Finally,

at the end, when you’re done, you ask Quest to provide a final threshold

estimate, usually the mean and sd (of the posterior pdf).

It is important to realize that Quest is merely a friendly adviser,

cataloging your data in your q structure, and making statistical

analyses of it, but never giving you orders. You’re still in charge. On

each trial, you ask Quest (by calling QuestMode, or QuestMean, or

QuestQuantile)) to suggest the best intensity for the next trial. Taking

that as advice, in your experiment you should then select the intensity

yourself for the next trial, taking into account the limitations of your

equipment and experiment. Typically you’ll impose a maximum and a

minimum, but your equipment may also restrict you to particular discrete

values, and you might have some reason for not repeating a value.

Typically you’ll choose the available intensity closest to what Quest

recommended. In some cases the process of producing the stimulus is so

involved that the exact stimulus intensity is known only after it’s been

shown. Having run the trial, you then report the new datum,

the actual intensity tested and the observer’s response, asking Quest to

add it to the database in q.

To use Quest you must provide an estimated value for beta. Beta

controls the steepness of the Weibull function. Many vision studies use

Michelson contrast to control the visibility of the stimulus. It turns

out that psychometric functions for 2afc detection as a function of

contrast have a beta of roughly 3 for a remarkably wide range of targets

and conditions (Nachmias, 1981). However, you may want to estimate beta

for the particular conditions of your experiment. QuestBetaAnalysis is

provided for that purpose, but please think of it as a limited optional

feature. It allows only two free parameters, threshold and beta. You may

prefer to use a general-purpose maximum likelihood fitting program to

allow more degrees of freedom in fitting a Weibull function to your

psychometric data. However, once you’ve done that it’s likely that

you’ll settle on fixed values for all but threshold and use Quest to

estimate that.

Note that data collected to estimate threshold usually are not

good for estimating beta. The psychometric function is sigmoidal, with a

flat floor, a rise, and a flat ceiling. To estimate threshold you want

all your trials near the steepest (roughly speaking) part of the rise.

To estimate beta, the steepness of the rise, you want to have most of

your trials at the corners, where the rise begins and where it ends. The

usual way to achieve this is to first estimate threshold and then to

collect a large number of trials (e.g. 100) at each of several

intensities chosen to span the domain of the rise. These data can

be plotted, making a nice graph of the psychometric function and

they can be fed to QuestBetaAnalysis, to estimate threshold and beta.

References

Farell, B., & Pelli, D. G. (1999). Psychophysical methods, or how to

measure threshold, and why. In J. G. Robson & R. H. S. Carpenter (Eds.),

A Practical Guide to Vision Research (pp. 129-136). New York: Oxford

University Press.

King-Smith, P. E., Grigsby, S. S., Vingrys, A. J., Benes, S. C., and

Supowit, A. (1994) Efficient and unbiased modifications of the QUEST

threshold method: theory, simulations, experimental evaluation and

practical implementation. Vision Res, 34 (7), 885-912.

Nachmias, J. (1981). On the psychometric function for contrast detection.

Vision Res, 21(2), 215-223.

Pelli, D. G. (1987) The ideal psychometric procedure. Investigative

Ophthalmology & Visual Science, 28 (Suppl), 366.

Pelli, D. G., & Farell, B. (1994). Psychophysical methods. In M. Bass,

E. W. Van Stryland, D. R. Williams & W. L. Wolfe (Eds.), Handbook of

Optics, 2nd ed. (Vol. I, pp. 29.21-29.13). New York: McGraw-Hill.

Watson, A. B. and Pelli, D. G. (1983) QUEST: a Bayesian adaptive

psychometric method. Percept Psychophys, 33 (2), 113-20.

All the papers of which I’m an author can be downloaded as PDF files

from my web site:

web http://psych.nyu.edu/pelli/

Try “help Quest”.

`Psychtoolbox/Quest/QuestDemo.m`