Processing information in a rapidly changing environment is demanding, and visual attention is necessary for object recognition to occur.

For example, to recognize how a group of features comprises an object, like this football, visual attention is required, and sustaining it takes considerable effort.

In dynamic situations where items move rapidly—like a football and players on the field during a game—the attentional effort involved causes a momentary lapse in attention once it is disengaged, such as when the quarterback is looking for a receiver.

This lapse is referred to as an attentional blink—as if the brain blinks for a moment, shutting down attention for a rest—in which stimuli, such as an opponent, are not perceived.

Based on the methods pioneered by Raymond, Shapiro and Arnell in 1992, this video demonstrates how to implement the phenomenon of Attentional Blink by discussing the steps required to design the stimuli and execute the paradigm, as well as how to analyze the data and interpret the results describing the accuracy of responses across trials with varying levels of attentional engagement.

In this experiment, a series of images, such as large black lower case letters and numbers in Helvetica font, are presented for 50 ms one after the other—an experimental procedure called Rapid Serial Visual Presentation, RSVP for short.

Each trial is programmed to display 30 characters in total, whereby two of the images are different numbers between 1 and 9.

The first is randomly placed somewhere between the eighth and twentieth RSVP position, while the second digit is randomly inserted in a spot immediately after the first number, to six places after it. This spacing is called the lag position, which can range from 1 to 6.

Over the course of the experiment, there are 180 trials, 30 at each of the 6 lag positions.

After each trial, participants are asked to report the numbers, in the order that they appeared, during the RSVP. The dependent variable is recorded as the number of correct responses across lag positions.

The logic behind the paradigm is that the first number will grab the participant’s attention, leading to a very high accuracy in naming the first ones. However, depending on the lag position, performance is expected to vary when reporting the second number.

If it appears immediately after the first, performance should still be very high—a concept called lag 1 sparing.

Accuracy should be affected most dramatically when the second number is in the second and third lag positions—because of the attentional blink phenomenon—and accuracy will be less affected at the later lag positions, those that occur after the short attentional blink window.

Before the experiment, set up the program to generate an output spreadsheet that reports all of the relevant data for subsequent analysis, including the trial number, the position of the first digit in the RSVP stream and the lag, the true identity of the first and second numbers, and the responses given.

To begin, greet the participant in the lab and guide them into the experimental room. Have them sit comfortably in front of the computer, with their chair back approximately 60 cm away.

Now, explain the task instructions: The screen will display the word “Ready?”until the space bar is pressed, after which a series of letters and numbers will immediately and rapidly appear.

Direct the participant to indicate what numbers they saw by pressing the corresponding keys in the same order they saw them. Remind them that if they are not sure what numbers they saw, to just guess.

After answering any questions, leave the room and allow them to complete the 30 trials at all lag positions, for a total of 180. When they are finished, thank them for taking part in the experiment.

To begin data analysis, open the spreadsheet with the data output from the experiment. Add two columns, named ‘Accuracy 1’ and ‘Accuracy 2’, to indicate whether the participant correctly identified the number in each position.

For each trial, in the column labeled ‘Accuracy 1’, indicate whether or not they identified the first number correctly by placing a 1 or incorrectly by assigning a 0. Duplicate this for the column labeled ‘Accuracy 2’.

Next graph the mean accuracy across all trials for the first, along with the averages for the second numbers reported—’Accuracy 2’—by lag positions.

Notice that the response for the first number—’Accuracy 1’—was very high, which demonstrates that even though the number appears very briefly, in an unpredictable location and embedded between letters, focused attention can support detailed processing and recognition.

As predicted, when the second number immediately followed the first, accuracy remained high due to lag 1 sparing. Thus, focused attention triggered by the first number remains engaged, allowing for the capture of the second number.

However, for lag positions 2 and 3, mean accuracy values decreased dramatically, reflecting the phenomenon of attentional blink. That is, after processing the first number, attention becomes temporarily disengaged, thereby reducing processing and recognition.

Though, the attentional blink did not last long, as shown by the improved performance for lag positions 4, 5, and 6.

Now that you are familiar with the phenomenon, let’s look at how the paradigm is used to investigate the basic limitations of visual attention in more detail, including the kinds of things that may capture it automatically, and even how anxiety and other mental health problems may divert it.

In a similar RSVP task using photographs, participants were asked to identify a target image—one that was rotated in an unusual position. For example, an upside-down room was included as the target, and participants reported if it was an indoor or an outdoor scene.

In some trials, researchers added a picture of a spider to the stream in a position preceding the target. They hypothesized that this might automatically capture attention because of the fear it induces. In this case, they reasoned that it should produce an attentional blink—leading the rotated target to be missed.

Indeed, participants responded inaccurately when a spider preceded the target, demonstrating that fear-inducing objects can automatically capture attention and produce attentional blinks.

Researchers have also used the same paradigm to investigate differences between people with severe phobias and those with just a typical dislike of spiders.

In this instance, the task is reversed: the rotated room is shown beforehand, presenting the spider in the lag 2 position. For most participants then, the perception of the spider is blocked by the attentional blink.

Interestingly, individuals with severe arachnophobia did not show an attentional blink, as they reported seeing the spider—suggesting that at times, emotional stimuli have a very strong pull on attention, when it would otherwise be disengaged.

You’ve just watched JoVE’s introduction to the attentional blink. Now you should have a good understanding of how to design and execute an attention-engagement task, as well as analyze and assess the results.

Thanks for watching!