football team jerseys cheap A Connectionist Explanation of the Stroop Effect
Suppose an individual is presented with the names of different colors, written in colored inks, and then asked to either read the word or name the color of the print. In such tasks, called Stroop tasks, it is easy to set up a situation where the color words may be written in different colored inks, which in some cases will conflict. For example, the word might be written in red ink, or the word RED might be written in green ink. An interesting empirical question is whether the processes involved in reading words and naming colors interfere. The basic Stroop effect involves a set of empirical findings, demonstrating that there is an asymmetry in the observed interference between color word reading and color naming. When reading the names of colors, the background color of the word is relatively easy to ignore. However, in color naming, the meaning of the word tends to influence how quickly we respond with the correct color. For example, identifying a background color, such as red, is quicker when the word is RED than when the word is . In the later case, the word interferes with the process of identifying the red ink. Overall, word reading is quicker than color naming.
The Stroop effect illustrates an important aspect of selective attention: It is easy to ignore some features of the environment, but not others. One explanation for the Stroop effect is that it reflects a difference in processing speed: word reading is faster than color naming, so color naming simply does not have the opportunity to interfere with word reading. Hypothetical differences in processing speed, suggested by Stroop interference, are consistent with a distinction between two types of cognitive processes: controlled and automatic (Shiffrin Schneider, 1977). Controlled processes are assumed to be voluntary, to require attention, and to be relatively slow, whereas automatic processes are assumed to be involuntary, to not require attention, and to be relatively fast.
Based of the processing speed explanation, the Stroop task has gained wide acceptance as a method for distinguishing between controlled and automatic processes. If process A interferes with process B, but process B does not interfere with process A, then process A is automatic and process B is controlled. An interesting challenge arises when a task such as color naming is identified as both controlled and automatic, by varying the other task involved. Color naming is identified as a controlled process when the other task is word reading, but as an automatic process when the other task is shape naming (MacLeod and Dunbar, 1988).
Cohen, Dunbar and McClelland (1990) proposed an alternative connectionist explanation of the Stroop effect, which does not distinguish between automatic and controlled processing. Instead, they proposed that automaticity is a continuum, and that Stroop interference depends on the relative degree of learning of the respective tasks, not on processing speed. According to this view, asymmetries in performance such as those observed in the Stroop task can be accounted for by differences in experience.
The architecture of the Cohen, Dunbar, and McClelland (1990) model is shown in Figure 1. It is a backpropagation network with three layers. The input layer consists of six units: two task units representing the color naming and word reading tasks, two color units representing red ink and green ink, and two word units representing the words RED and . The middle (or hidden) layer consists of four units. Two of the hidden layer units represent the color naming pathway, while the other two units represent the word reading pathway. The task units are used to gate (or selectively attend) to the appropriate pathway. The extent that the network is able to selectively attend to either the color naming or word reading pathway depends on the relative strength of the weights in the to be ignored pathway. The output layer consists of two units: one for the response “red” and one for the response “green”.
While the network is a multilayer architecture the weights
between the input units and hidden units and the
biases of the hidden units are fixed (indicated by the pink arrows)
to implment the selection mechanism.
Exercise 1: Examine the weights between the input units and the hidden units
as well as the biases of the hidden units. Describe how the network is
implementing the selection mechanism with reference to the sigmoid activation function.
Exercise 2: The patterns in the training set are designed to capture
in a simplified form the learning that people undergo before doing the
Stroop task (with the dashes corresponding to either the neutral word
(noncolor word or nonword) or the neutral color (black)).
Examine each of the training patterns and describe the
experience that is represented by each different pattern. Why are there
more multiple copies of the word naming patterns?
Exercise 3: The patterns in the test set are designed to
capture the conditions within a Stroop experiment.
Which patterns in the test set represent the control, congruent, and conflict conditions in the Stroop experiment?