Sample from Lab Manual
This project demonstrates a number of important concepts and methods in the study of visual perception. The theoretical orientation is feature integration theory, developed by Anne Treisman and her colleagues (Treisman and Gelade, 1980). The basic idea is that visual information processing occurs in two stages, an initial preattentive stage in which visual features are processed more or less automatically and in parallel, and a second feature integration stage in which visual features are processed via the conscious focusing of attention and in a serial fashion.
The project employs the important reaction time methodology developed by Sternberg (1969) for the study of memory search. In the visual attention experiment, the participant is presented with a target stimulus and, after a brief pause, is presented with an array of characters that may contain the target character. The participant's task is to report, as quickly as possible, whether or not the second stimulus array contained the same character as the target stimulus. There are two types of tasks possible in the experiment: (1) A disjunctive task, in which the target stimulus has a unique feature (such as color or shape) that is not shared by any characters in the second array, and (2) a conjunctive task, in which the target character has a unique combination of color and shape features (the second array may include characters of similar color or shape). Analysis of the reaction time results enables the experimenter to draw conclusions about the nature of the stages of visual processing and also about whether visual search is essentially parallel or serial, and self-terminating or exhaustive.
You need to decide how many trials per block and how many blocks (conditions) of trials there will be in the experiment. You also have to decide on the sequence of conditions for those blocks. For example, you might wish to run a total of four blocks of 20 trials each. The first and third block might be the conjunction task and the second and fourth block the disjunction task. The number of characters in the array are set by a random number generator in the program, so you don't have to worry about setting that parameter. If you are concerned about the effects of order, you could run more blocks with fewer trials per block and randomize the order of task type. After SET-ting the parameters for each condition, it's a good idea to review all the blocks by stepping through them with the STEP button.
It's a good idea to run at least four blocks of trials, either alternating or randomizing the task type in the different blocks (see Parameters section). The total number of trials you need depends on how extensive your analysis will be. If you're not going to examine the effect of color vs. shape, or of array position, etc., you probably can get by with a total of 80 trials or fewer. If you like, you can split the total trials among a number of blocks in which the order of task (conjunction or disjunction) is randomized.
The participant presses key 1 for a "no" response (the fixation target was not present in the array) and key 2 for a "yes" response (the fixation target was present in the array). If you get some responses with 0 ms reaction times, discard them. The participant should have a small amount of practice with the conditions prior to the experimental runs. Make sure that the participant understands that the appropriate strategy is accuracy first, speed second: the error rate should be less than 1 error in 30 or 40 trials. Pushing the PEEK key resets the trial counter to the end of the block.
The task is to respond, as accurately and as quickly as possible, about whether the first stimulus (the "target") is also present in the second stimulus (the "array"). You will see that there are two kinds of tasks in this experiment. During one type of task (the "conjunction" task), the target stimulus will be one of the following characters: a green T, a green X, a brown T, or a brown X. Look to see if exactly the same character appears as part of the array of characters; if so, respond by pressing the 2 key. If the same character is not present in the array, press the 1 key. During the other type of task (the "disjunction" or "feature" task), the target character will be one of the following characters: a blue T, a blue X, a brown S, or a green S. Again, see if exactly the same character appears in the array. If it does, press 2, otherwise press 1. Try not to make many errors (fewer than 1 every 30 or 40 trials). The array will (randomly) consist of 1, 5, 15, or 30 characters. To start a block of trials, press either the START button or the ENTER key or SPACE bar.
The analysis of this experiment is much simpler than might first appear. The basic analysis consists of considering array size as the independent variable and average reaction time as the dependent variable. You need to partition the trials by task type, array size, and response (yes/no). Then you examine how average reaction time (RT) increases with array size for the different tasks and response. A major interest is the slope of the RT vs array size function. More extensive analyses can test the effects of color vs. shape or of spatial position or of task order.
The data will be in the following form:
stype task type (conj, feat)
block block number
trial trail number
dsize array size
tcolo target color
tchar target character
tposi array position of target (whether or not present)
targ target (0-no, 1-yes)
resp response (0-no, 1-yes)
rxn time reaction time
c/e correct/error
A typical line of data would be of the form:
stype block trial dsize tcolo tchar tposi targ resp rxn time c/e
conj 1 4 5 green T 2 1 1 992 c
(Note: The data file is written with commas between all entries. You may have to tell your spreadsheet program to use comma delimiters.)
To analyze the results you would first remove trials on which there were errors and then calculate what the error rate was in different conditions. Then, to perform a basic analysis of the data, you would sort the data file by stype, by dsize, and by targ (in that order). A subset of the data would then look like the following set of trials that has all the same stype, dsize, and target condition (target absent):
stype block trial dsize tcolo tchar tposi targ resp rxn time c/e
conj 1 4 5 green T 2 0 0 1992 c
conj 1 7 5 green T 1 0 0 1342 c
conj 1 11 5 brown T 2 0 0 1252 c
conj 1 13 5 green X 5 0 0 507 c
Averaging the obtained reaction times for this block of trials would yield the RT for the conj, array size=5, and target absent condition. Repeat the process for the other conditions. Once you have the RTs, you can plot them as a function of array size. If you are doing more complex analyses, such as examining the effects of color versus shape, you will need to do more detailed sorts of the data.
TECHNICAL DETAILS
There are some differences between the Treisman & Gelade (1980) experiment and the current program. In this program, there are two background stimuli: T's and X's; these can be either brown or green, respectively, with a probability of 0.5. The possible targets on the conjunction trials are brown T or green T (probability of 0.5 each). The possible targets on a feature trial are brown S, blue X, blue T, or green S (probability of 0.25 each). The stimulus array is composed of either 1, 5, 15, or 30 characters, again with a probability of 0.25 on any trial. The resolution of the reaction timer is 3 ms. The trial sequence is as follows: ready cue of 1 s, fixation cue of 500 ms, blank 250 ms, array display for up to 3 s, followed by a feedback-rest period of 1 s.
REFERENCES
Levine, G. & Parkinson, S. (1994). Experimental Methods in Psychology, Hillsdale, N.J.:Erlbaum, Chapters 10 & 11.
Printzmetal, W. Presti, D. E., & Posner, M. I. (1986). Does attention affect visual feature integration? Journal of Experimental Psychology: Human Perception & Performance, 12, 361-369.
Sternberg, S. (1969). The discovery of processing stages: extensions of Donders' method. In W. G. Koster (Ed.), Attention and Performance II. Acta Psychologica, 30, 276-315.
Treisman, A. & Gelade, G. (1980). A feature integration theory of attention. Cognitive Psychology, 12, 97-136