Psychtoolbox-3 Tutorial


It would be great if someone could extend this tutorial for new features and standard operating procedures for version 3.

Until then, the following downloadable PDF file may give you a coarse overview over PTB-3's new features:
Talk slides of Psychtoolbox presentation, given at ECVP 2007 Arezzo

Strengths of Matlab & Psychtoolbox


Interpretive general language & a good interface to hardware

Unlike most software packages for experimental psychology and visual psychophysics, the Psychtoolbox is very general. It doesn't contain specific support for generating gratings, running trials, etc. Rather, it provides the user of a high-level interpreted language (Matlab) with a well-defined interface to the graphics hardware (frame buffer and lookup table) that drives the display. In this sense, it is a very generic tool. The power comes from the fact that once you can write arbitrary matrices into the frame buffer and lookup table as fast as the machine can go, everything else is easy to program in Matlab.

Matlab is a high level interpreted language with extensive support for numerical calculation (The MathWorks, 1993). The Psychophysics Toolbox provides a Matlab interface to the computer’s hardware. The core Psychtoolbox routines provide access to the display frame buffer and color lookup table, allow synchronization with the vertical blanking, support millisecond timing, and facilitate the collection of observer responses.

The Psychtoolbox doesn't limit the user—if the experiment can be run on the hardware, it can be run with the Psychtoolbox. In comparison, other environments for creating perception experiments provide very evolved support for specific experiments. Our experience with software packages not based on a general-purpose programming language has been that the very first thing we wanted to do turned out to be impossible.

We think the Matlab-Psychtoolbox combination has four winning features that we’d recommend for any experiment-design environment:
The Psychtoolbox also provides interfaces for timing, sound, keyboard, and the serial port. And it includes many useful Matlab routines, such as color space transformations (Brainard, 1995; Brainard, Pelli, and Robson, 2002) and the QUEST (Watson and Pelli, 1983; Pelli and Farell, 1995) threshold seeking algorithm.
2. Transforming numbers into movies

Using a high-level platform-independent language like Matlab, it's easy to produce a matrix of numbers specifying the desired luminances of all the pixels in the displayed image. Today's off-the-shelf personal computers can copy those numbers from memory to video memory quickly enough to show a new image on every frame of a CRT monitor. However, high-level languages generally provide only rudimentary control of the vital transformations from number to color, and of the rate at which successive images are displayed.

That is where the Psychtoolbox comes in, providing simple but powerful functions to control the pixel transformation and timing synchronization of the computer-display interface.

Here’s a quick sketch of how computers display images. (See Brainard, Pelli, and Robson, 2002, for a fuller treatment.) Once the matrix of numbers has been loaded into frame buffer memory, the subsequent transformation from number to luminance (or color) is complicated, but usefully simplified to three steps. First, at video rates (e.g. 100 million pixels per second), each number passes through a lookup table, typically one 8-bit number in and three 8-to-10-bit numbers out, each driving an 8-to-10-bit digital-to-analog converter. Second, the three analog video signals drive the three guns of a color CRT. The luminance of light emitted by each monitor phosphor is proportional to the corresponding gun's beam current, which is an accelerating function of drive voltage; this is called the monitor's "gamma" function. Third, the luminous image is blurred by the point spread function of the beam.

Most graphics cards have adjustable pixel size, typically 8, 16, or 32 bits per pixel. Furthermore, while most have 8-bit Digital to Analog Converters (DACs), a few have 9- or 10-bit DACs. Many users write to ask what these numbers of bits mean. In the pixmap, each pixel is assigned a certain number of bits, 8, 16 or 32. The number of bits per pixel determines how many different colors you can have in one frame: 256, thousands, or millions. When you actually display an image, the pixel value is used as in index into a lookup table on your graphics card. The values in the lookup table are typically 8 bits per channel, but some cards have 9 or 10 bits per channel. Those values, output from the lookup table then drive digital to analog converters (DACs) with a corresponding precision, 8 to 10 bits. In 8-bit mode you can select any 256 colors. Within the lookup table, each color is specified by three 8-10 bit numbers. If instead you use the 32-bit mode (millions of colors) then the pixel is considered to be made up of three 8 bit values, one per channel (plus 8 bits of padding), each of which goes through a one-channel lookup table, again with 8-10 bit outputs. 16-bit mode is rarely useful. In that mode 5 bits are assigned to each channel (plus 1 bit of padding), allowing only 32 values per gun. Again, we have a longer treatment of this issue in our Display Characterization chapter (Brainard, Pelli, and Robson, 2002).
3. Toolbox overview

The basic idea is that you use Matlab to compute images or movies, and use new Matlab functions provided by the Psychtoolbox for accurate display. The Psychtoolbox routines treat the computer (Mac or Windows) as a display device: a frame buffer with a color lookup table. (To read about how to use frame buffers for visual psychophysics, see our psychophysics bibliography.)

The software has three layers. First, there is Matlab code that you write and some Matlab utilities that we supply, e.g. to compute color lookup tables and implement the QUEST staircase procedure. Second, there are a set of Matlab extensions (MEX or DLL files) that are written in C but callable from within Matlab. Third, the extension files, in turn, use OpenGL for graphics output and operating system facilities for other input and output.

The Screen mex file is the heart of the Psychophysics Toolbox, providing many subfunctions (selected by a text argument) that control the display screen(s). Experiments typically begin with a call to Screen('OpenWindow') and end with a call to Screen('CloseAll'). Anywhere in between, you may copy an image from a Matlab matrix onto the screen using Screen('PutImage') and change the lookup table using Screen('LoadClut') or (even better) Screen('LoadNormalizedGammaTable'). Typically you'll create a window on each screen that you're using in your experiment. Copying within or between windows is very fast. And you can create an unlimited number of offscreen windows (in memory, not visible) that can then be shown, one after another, as a movie, by copying to an onscreen window. Other Screen functions display text and dialogs and provide frame-accurate timing.

You can use the Screen function to write Matlab scripts that intermix graphics operations, calculations, and wait for observer responses. If you run the routines interactively from the command window, there will be a certain level of chaos as Matlab's windows overwrite parts of the experimental window. Still, this mode can be useful for debugging, especially if you restrict the window sizes to avoid overlap, or you have a second monitor.

Operations such as synching to vertical blanking and writing color lookup tables depend on the kind of video card(s) you have, and their video drivers. New versions of the computer operating system often include new video drivers. The Psychtoolbox provides a uniform interface, but you should check the timing on your computer, by running ScreenTest.m.

Note that Matlab has a number of built-in graphics commands, like BAR, that can draw into Matlab "figure" windows. Those commands won't draw into a Screen window. Use Matlab commands to draw into Matlab figures; use Screen to draw into Screen windows. For example, if you have an open Screen window, you can draw a black filled rectangle (10x25) in it by saying: Screen(window,'FillRect',BlackIndex(window),[0,0,25,10]). You can erase the whole window by overwriting with white: Screen(window,'FillRect').

Priority

A major challenge in doing psychophysics on modern personal computers is that operating systems are becoming more and more aggressive about stealing time away from your display code to do other things. Priority is a function that allows to protect your Matlab code (to some degree) from interruption. This allows you to keep your computer running more or less normally, with lots of background processes, yet grab complete control for the periods of time that it takes to present your stimuli.

Other Psychophysics routines

In addition to Screen and Priority, there are routines to satisfy all the needs of psychophysical experiments: Unbuffered keyboard i/o via KbCheck, KbWait, KbStrokeWait, KbName etc., mouse i/o via SetMouse, GetMouse and GetClicks, serial i/o via IOPort, timing via GetSecs and WaitSecs, sounds via PsychPortAudio and Snd, and threshold-estimation via the Quest staircase procedure. Other routines interface to the PhotoResearch PR-650 color meter, save images as EPS files, interface with Eyetrackers or EEG systems. An overview of the basic routines can be found by typing help PsychBasic. A high level overview over all categories of functions can be found by typing help PsychToolbox.

4. Displaying a grating with Screen.mex

Let's write a program to display a grating. We’ll open up a window on the screen, write a Matlab matrix into our window (i.e. into the frame buffer), and then close the window. These functions, Screen('OpenWindow'), Screen('PutImage'), and Screen('Close'), along with functions to load the lookup table and sync to the vertical blanking, are the heart of the Psychtoolbox.

First we open a full-screen window on screen 0 (the main monitor):
whichScreen = 0;
window = Screen(whichScreen, 'OpenWindow');


This full-screen window contains the entire screen, every pixel. There is no menu bar, title bar or border. You can ask Screen to open as many windows as you like, on as many monitors as you have, but usually you’ll want just a full-screen window on one monitor.

Next we figure out what numbers will produce white, gray, and black, and fill the whole window with gray.
white = WhiteIndex(window); % pixel value for white
black = BlackIndex(window); % pixel value for black
gray = (white+black)/2;
inc = white-gray;
Screen(window, 'FillRect', gray);


Now we use Matlab functions to compute a gabor patch (a grating vignetted by a gaussian envelope), and put that image into our window.
[x,y] = meshgrid(-100:100, -100:100);
m = exp(-((x/50).^2)-((y/50).^2)) .* sin(0.03*2*pi*x);
Screen(window, 'PutImage', gray+inc*m);


Now we ask the system to make our stimulus image visible at the beginning of the next video refresh interval, by "Flipping" it onto the visible display:
Screen(window, 'Flip');


Now we pause, displaying the grating until the observer presses any key, and finally close the window.
KbWait;
Screen('CloseAll');


That’s a complete program that will run on any computer with Matlab and the Psychtoolbox. It’s a slightly abbreviated version of GratingDemo.m, which is included in the Psychtoolbox.

In the above, the call to Screen('PutImage') slowly translates the Matlab double precision matrix into the pixmap format of the frame buffer. You won't want to do that while showing a movie. In that case you’d create a texture, which is allocated in your computer’s memory, and store the Matlab image matrix into it:
w = Screen(window, 'MakeTexture', gray+inc*m);


Now, whenever you like, you can blit (i.e. copy) very quickly (up to 80 GB/s depending on your graphics hardware—run ScreenTest to time your hardware) from the texture to onscreen graphics memory:
Screen('DrawTexture', window, w);


If you create multiple textures in advance, then you can show them, one after another, one per frame, to create a movie. The 'Flip' command will automatically synchronize to the vertical blanking of your display device:
for i = 1:100
    Screen('DrawTexture', window, w(i));
    Screen(window,'Flip');
end


The Psychtoolbox program MovieDemo.m illustrates this.

Incidentally, if you display stimuli on the main screen, as we often do, then the Screen window will hide the main menu bar and obscure Matlab’s command window. That can be a problem if your program stops (perhaps due to an error) before closing the window. The keyboard will seem to be dead because its output is directed to the front most window, which belongs to Screen not Matlab, so Matlab won’t be aware of your typing. It’s ok. Remain calm. Typing Ctrl-C will stop your program if hasn't stopped already. Typing command-zero (on the Mac) or Alt-Tab (on Windows) will bring Matlab’s command window forward. That will restore keyboard input. The screen might still be hard to make out, if you’ve been playing with the lookup table. Typing
clear Screen


will cause Matlab to flush Screen.mex. Screen.mex, as part of its exit procedure, cleans up everything it did, closing all its windows and restoring the lookup table of all its displays. And everything will be hunky dory again. Remember the magic incantations: command-zero (Mac) or ALT-tab (Win) to bring the command window forward, and "clear screen" to restore the displays to normal.

5. Examples

You got yourself a computer, bought Matlab, and installed the Psychtoolbox. Now you want to get your experiment running. Where to begin?

George Sperling pointed out to us recently that writing software from scratch is hard. It's much easier to edit an already working program that does something similar. The PsychDemos folder includes a variety of short programs that show how to do various specific things, including synthesizing and displaying a movie. Type
help PsychDemos

at the Matlab prompt for a list.

The Psychtoolbox website includes a Library page with links to programs written by other users. We invite everyone to send software to the Psychtoolbox forum, which automatically archives your message and enclosure. (Please include the keyword DONATE in the subject, so we can all search the forum for software.) We add links on the Library page to programs in the forum that appear to have enduring value.

By the way, don’t shortchange yourself. Buy enough memory ($0.4/MB) and disk space ($3/GB) as well as a recent graphics card to work comfortably.

6. Online help

The Psychtoolbox has no manual. Matlab has manuals, but we hardly ever use them. Instead we use the HELP command. Typing
will list a variety of broad topics on which Matlab offers help. You can ask for help on any function, including Matlab’s functions and any function in the Psychtoolbox. For example,
help help/techdoc/ref/meshgrid.html">meshgrid


will explain how the Matlab function meshgrid works. Similarly,
help Screen


will give a brief synopsis of Screen. If you type
help Psychtoolbox


you will get an overview of the hierarchical organization of the Psychtoolbox. For any of the subdirectories listed, you can get a synopsis of the functions in that subdirectory. So
help PsychBasic


will give you a synopsis of the core toolbox routines. The HELP facility is a fast way to explore Matlab and the Psychtoolbox, and we use it all the time.

Some of the Psychtoolbox functions, like Screen, have a large number of subfunctions, making it impractical to include all the information in the HELP display. Simply typing
Screen


will give you a synopsis of all the Screen subfunctions. For more detail on a specific subfunction, call Screen itself, adding a question mark to the sub function name.
Screen('CopyWindow?')


will type out helpful text for 'CopyWindow'. You can omit the parentheses and quote marks, because Matlab considers this
Screen CopyWindow?

equivalent to the above.

In our help text for specific functions, we've mostly followed Mathworks's help-text conventions. But note that we designate optional arguments to function calls by embracing them with square brackets. You're not meant to include these brackets when you actually call the function. For example, "help Snd" will tell you this:err = Snd(command,[sig],[rate]). What this means is that the "command" argument is required and the "sig" and "rate" arguments are optional. Thus, a typical call to Snd looks like this, and has no brackets: Snd('Play','Quack'). If you would like to force an optional argument explicitly to its default, you can typically pass the empty matrix. This is useful for functions with more than one optional argument where you'd like to (e.g.) accept the default on the first but explicitly pass the second.

Matlab usually ignores case (at least on Mac and Win platforms), except in variable names and built-in functions. The Psychtoolbox, by default, ignores case, but this is a user-settable preference. Although lazy typists can type everything in lower case, keep in mind that this practice may lead to portability problems somewhere down the line.


Another helpful tool is lookfor. Suppose you want to convert a variable of cell type to something else, such as a matrix. However, you have no idea what the function might be called. generates a list of all the functions with cell in the name. cell2mat is an obvious choice, and inspecting the list quickly teaches you about various cell related functions while you are working with the cell type.

7. Parallelize

Matlab is quick. Running on a 250 MHz PowerBook G3, the loop overhead is only 1 microsecond per iteration (after the first). Because it’s an interpreted language, it takes time (7 microseconds) to process each statement. However, one statement can perform a large number of elementary operations, e.g. adding two 100 element matrices requires 100 adds. Matlab does the elementary operations very efficiently. The large 76:1 ratio of the 7 microsecond statement overhead to the 0.09 microseconds per elementary operation (~ + - * / = = & | sin sign) is a defining characteristic of the language. You can run the Psychtoolbox program SpeedTest to assess these parameters for your own computer.

The implication, worth remembering, is that the run time of statements that operate on fewer than 76 elements is mostly spent processing the statement, not the elements. An example may help.
x = ones(10);
y = ones(10);


This creates two 100 element arrays. (They’re 10x10 square matrices.) In languages, like C or BASIC, that lack matrix operations, one would add x and y by writing a loop.
for i = 1:100
    z(i) = x(i) + y(i);
end


That works in Matlab too, but it runs very slowly, taking 800 microseconds (i.e. 8 microseconds per iteration, for 100 iterations). The right way to do this in Matlab is to operate on the whole matrix at once,
z = x + y;


which takes just 16 microseconds. That’s 50 times faster!

Again, the thing to remember is that the run time of statements that operate on fewer than 76 elements is mostly spent processing the statement, not the elements. An important part of learning Matlab is learning how to operate on lots of elements at once, as in the above example.

All of the timing above is for compiled code. Matlab compiles functions and loops before executing them, so you’ll usually benefit from the compilation without having to think about it. The one case you should avoid is calling a script (i.e. not a function) repeatedly; you should convert that script into a function.

8. Use the debugger

Matlab has a great built-in debugger, allowing you to step through your program, examine and modify variables, and set breakpoints. However, in the Mac version, the way you start it up is confusing, at least the first time you do it, which discourages many people enough that they never discover how useful the debugger is.

Be warned that, on the Mac, the debugger has slight difficulties with files that are in the Matlab toolbox folder (which includes the Psychtoolbox) and that the debugger may give a spurious error beep if you choose to debug a file whose name has any uppercase characters. For best results, debug a file outside the toolbox folder with a filename that’s entirely lowercase. Later on, once you've got the hang of using the debugger, you can ignore this restriction, but, as a beginner, it'll be less confusing to respect it.

Suppose you just wrote a function called foo.m, and you’ve got the file open, in a window called "foo.m". Click on the debugger icon (a green bug) in the window’s title bar. This will open the debugger window, which (confusingly) is also called "foo.m". Note the debugger's flow control icons at the left end of the title bar. Now set a breakpoint somewhere in your program by clicking one of the dashes "—" that appear in the left margin of the window, next to each statement. Clicking the dash turns it into a red dot , a breakpoint. (You can set multiple breakpoints, if you like.)

Sometimes when you try to set a breakpoint, you'll get a beep and no red dot. This usually means that Matlab is having trouble finding your file. (Which is sad, considering that it's got the file open.) Setting a breakpoint seems to be implemented in effect by issuing a command like "dbstop foo 17". This will fail if foo is neither in Matlab's path (a list of folders of likely places to find stuff) nor the current directory. You fix this by using the Matlab CD command to set the current directory to be the folder that contains the file your debugging, foo.m. If that succeeded, you should be able to open foo by typing "edit foo" in the command window. Now you should be able to set breakpoints without difficulty.

Now you’re ready to run your program. You’d have thought that you could just click something to say "Go!". No such luck. You must now go back to the Matlab command window. Using the keyboard shortcut, type command-zero (on a Mac) or xxx (on Win) to bring the command window forward. Now run foo, by typing its name:
foo


The program will begin execution and halt when it gets to your breakpoint. The command window will display a special prompt
K>>


indicating that you’re in the debugger. You can issue any Matlab command you like. Mostly you’ll simply type variable names to see what values they have. You can resume execution by typing
but, instead, you’ll probably find it more convenient to go back to the debugger window by typing the shortcut command-4 (Mac) or xxx (Win), and use the flow-control icons in the title bar. You can single step , descend into a subroutine , ascend to the calling program , continue , or stop . You can also add or remove breakpoints . When you’re done, you should remove all the breakpoints.

It seems that in new version of matlab (I'm running 7.9 (r2009b)) debugging is not this troublesome, on Windows at least. Just play with it and you'll get the hang of it quickly. There is no need to boot up seperate debuggers and such, just click on the grey area between the line numbers and the code itself. A red dot will appear, signifying the break point. With F5 you can jump from one breakpoint to the next, shift-F5 stops debugging, F10 gets you to the next statement (line of interpretable code) that matlab finds, F11 allows you to enter a function so you can see what happens inside, shift-F11 exits the function again to go back to the higher level in the call stack.

Other debugging tips are: 1) look at the function
PsychDebugWindowConfiguration


which allows you to make your PTB windows transparent for both your eyes and mouse interaction on OSX, Vista and Windows 7 (not XP!) so that when errors occur you can see the matlab GUI below your stimulus window and interact with matlab.

A second tip is to call
on top of your script, which causes matlab to enter debug mode at the point of error instead of stop execution. This allows you to quickly diagnose why the error occured. Also note you can navigate through the call stack and thus examine the
content of variables at each level of invocation. Great aid in diagnosing problems with your script, especially if it goes through a bunch of function call layers. Do be sure to put
at the end of your script though, or you are permanently enabling this feature for the current and later matlab sessions...

9. Measuring threshold

You can measure whatever you like, but it is often useful to measure the stimulus intensity that yields a criterion level of observer performance (Pelli and Farell, 1995). The Psychtoolbox includes Matlab code implementing the QUEST procedure for estimating threshold.

Experiments are usually organized as a run (e.g. 40 to 100) of trials. Each trial presents stimuli to the observer and waits for a response. Each trial takes several seconds. To measure threshold you’ll write a loop, with one iteration per trial.

Before starting the loop, you’ll initialize QUEST, giving it a rough guess for the value of threshold. You may also want to ask for the observer’s name and so on.

Within that loop are the guts of your experiment. Typically you might call QUEST to ask it to suggest a good contrast to test at, based on the initial guess and all the observer’s responses so far. Then you’d compute an appropriate stimulus and display it briefly in a window. If you’re using a two-interval forced choice paradigm you’ll have two intervals, announce by beeps, and display the signal in only one of them. Then you’ll wait for the observer’s response, typically a keypress or mouse click. Finally, tell QUEST what contrast you actually tested at and whether the observer’s response was right or wrong. The Psychtoolbox demo program QuestDemo illustrates how QUEST is used in the toolbox environment. We recommend discarding the observer’s first response, just in case he or she wasn’t quite ready.

Finally, after the last trial, you’ll report QUEST’s threshold estimate and confidence interval.

Judging from email queries we’ve received from users, the most common beginner’s mistake is to forget to leave things in the same state at the end of the trial as they were at the beginning. If you open a window at the beginning of the trial (on- or off-screen) then close it at the end. Otherwise you’ll eat up memory fast, adding yet another window on each trial. The symptom of this programming error is that the experiment works perfectly for a few trials but eventually fails, when it runs out of memory.

We suggest that you avoid opening and closing windows (whether on- or off-screen) within a trial because it’s slow. It’s better to open all the windows you’ll need ahead of time and then just use them on each trial. Finally, after the last trial, you should close them all.

10. Calibration

Everyone says that you should calibrate your monitor so that you’ll know what you’re displaying, but rarely is software and a photometric instrument provided to help you do it. The Psychtoolbox, being free software, doesn’t include the instrument, but it does include software, in PsychCal, which should help, though it still isn’t as well documented as we’d like. Our measure page has some suggestions on what to buy. You may wish to read our chapter on display calibration (Brainard, Pelli, and Robson, 2002).

11. use psychotoolbox and fMRI

There are many ways you can interface matlab with your EEG or MRI system. Here is an example on how to make it work in fMRI.

A - How the MRI is set

The MRI trigger is converted via a ForpInterface unit (Current Designs) into a TTL send to the mouse port.
The subject response is received via the same Forpinterface and plugged into your computer. Responses are perceived as keyboard keys.

B - Basis of the program

Make sure responses, MRI trigger (mousse) and timing are correct using the priorityLevel function
e.g. priorityLevel=MaxPriority(['GetSecs'],['KbCheck'],['KbWait'],['GetClicks']);

Get the starting point of the MRI with GetSecs, load your stimuli after each MRI pulse (mouse click) and record the timing
e.g.
MRIstart = GetSecs;
WaitTTL = GetClicks;
if WaitTTL == 1
    t = GetSecs; t = t-MRIstart;
    % .. do something here ..
end


in the core of the experiment one can collect responses with KbCheck
e.g.
start = GetSecs;
timeSecs = KbWait;
[keyDown, secs, keyCode] = KbCheck;
stop = GetSecs;
rt_catch(nbtrial_catch) = stop - start;
         
success = 0;
while success == 0
    pressed = 0;
    while pressed == 0
        [pressed, secs, kbData] = KbCheck;
    end
    for i = 1:length(keysWanted)
        if kbData(keysWanted(i)) == 1
            success = 1;
            keyPressed = keysWanted(i);
            break;
        end
    end
end


Finally, depending on your TR, the PPT will return an error message related to timing issues (too long delays)
One can use WaitSecs between events (and after you collect the subject response) to make sure everything is ok
e.g. WaitSecs(TR-TA); % given that you set the acquisition time (time to acquire a volume - TA) and repetition time (time between volumes - TR)

ATTENTION: for an unknown reason FlushEvents overloads so it is not used here.

12. Good luck!

References

Brainard, D. H. (1995) Colorimetry. In Handbook of Optics: Volume 1. Fundamentals, Techniques, and Design. M. Bass (ed.). McGraw-Hill, New York, 26.1-54.

Brainard, D. H. (1997) The Psychophysics Toolbox. Spatial Vision 10:433-436 (PDF)

Brainard, D. H., Pelli, D.G., and Robson, T. (2002). Display characterization. In the Encyclopedia of Imaging Science and Technology. J. Hornak (ed.), Wiley. 172-188. (PDF)

The MathWorks (1993) Matlab User's Guide. The MathWorks, Inc., Natick, MA.

Pelli, D.G. (1997) The VideoToolbox software for visual psychophysics: Transforming numbers into movies. Spatial Vision 10:437-442. (HTML)

Pelli, D. G. and Farell, B. (1995) Psychophysical methods. In Handbook of Optics: Volume 1. Fundamentals, Techniques, and Design. M. Bass (ed.). McGraw-Hill, New York, 29.1-13.

Pelli, D. G. and Zhang, L. (1991) Accurate control of contrast on microcomputer displays. Vision Research 31, 1337-1350. [pdf]

Watson, A. B. and Pelli, D. G. (1983) QUEST: a Bayesian adaptive psychometric method. Perception and Psychophysics 33, 113-120

To read PDF files you may want to download the free Acrobat reader from Adobe.

Thanks to George Sperling for suggesting that a tutorial and examples would be useful.


David Brainard, Denis Pelli & Allen Ingling.
psychtoolbox@yahoogroups.com

19 September 2000
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