Crowding-Effekt
English
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Overview
Quelle: Labor von Jonathan Flombaum, Johns Hopkins University
Menschlichen Auges hängt von lichtempfindlichen Nervenzellen, die auf der Rückseite das Auge auf ein Gewebe namens die Netzhaut angeordnet sind. Die Neuronen, die Stäbchen und Zapfen genannt, weil ihre Formen sind nicht gleichmäßig auf der Netzhaut verteilt. Stattdessen gibt es eine Region in der Mitte der Netzhaut, genannt die Makula wo Zapfen dicht gepackt sind, und vor allem so in einen zentralen Teilbereich der Makula genannt die Fovea. Außerhalb der Fovea gibt es praktisch keine Zapfen und Stab Dichte sinkt erheblich mit größerer Entfernung von der Fovea. Abbildung 1 schematizes dieser Anordnung. Diese Art der Anordnung wird auch in der Sehrinde repliziert: viel mehr Zellen repräsentieren Stimulation der Fovea im Vergleich zu der Peripherie.
Abbildung 1. Schematische Darstellung des menschlichen Auges und die Verteilung von Licht-sensitiven Rezeptor Zellen auf der Netzhaut. Die Pupille ist die Öffnung an der Vorderseite des Auges, das Licht zu betreten erlaubt. Licht konzentriert sich dann auf die Netzhaut, Nervengewebe im hinteren Teil des Auges, die Stäbchen und Zapfen, lichtempfindlichen Zellen besteht. In der Mitte der Netzhaut ist die Makula, und in der Mitte der Makula ist die Fovea. Der Graph schematizes die Dichte der Rute und Kegel-Rezeptoren auf der Netzhaut in Abhängigkeit von ihrer Position. Zapfen, die für die Farbwahrnehmung verantwortlich sind, befinden sich fast ausschließlich in der Fovea. Stäbe, welche Unterstützung in Low-Light Bedingungen zu sehen sind ebenso stärker in der Nähe von der Fovea, mit Cluster schnell fallen dichten außerhalb der Makula.
Das Ergebnis: Wir sehen sehr wohl in dem Teil des Universums, die unsere Augen anvisiert werden direkt, die Teil des Raumes, die Stimulierung der Fovea; aber wir tatsächlich sehen nicht sehr gut in der Peripherie. Wir beachten nicht wirklich es zwar, weil unsere Augen ständig bewegen, bauen eine Darstellung des Raums aus vielen einzelnen Fixierungen.
Eine Möglichkeit, die Eigenschaften des peripheren Sehens zu studieren ist mit einem Phänomen bekannt als Verdrängung. 1 Crowding bezieht sich auf die Unfähigkeit, Objekte in Unordnung erkennen und erleben wir besonders stark drängen, wenn Objekte in der Peripherie angezeigt werden. Abbildung 2a ist ein Beispiel, in denen sollte man crowding erleben: Blick auf das Kreuz in der Mitte, und siehe, wenn Sie den Brief melden können, die in der Mitte der Packung auf der rechten Seite ist. Es ist wahrscheinlich ziemlich schwer. Jetzt in Figur 2 b versuchen, den Buchstaben auf der linken Seite melden. Viel einfacher! In dieser Abbildung ist der Brief nicht überfüllt und gibt es keine Unordnung um ihn herum, so dass es leichter zu erkennen ist.
Abbildung 2a. Voll Reiz. Fixieren Sie das Kreuz in der Mitte zu, und sehen Sie, ob Sie die Buchstaben in der Mitte der Packung auf der linken Seite erkennen können. Es sollte schwierig sein, weil die Buchstaben in der Peripherie sind und der zentralen Buchstaben sich durch die Buchstaben um ihn herum drängten.
Abb. 2 b. Nicht überlaufen Reiz. Dieser Reiz ist identisch mit Abbildung 2a, außer, dass der Buchstabe G nicht überlaufen-keine andere Buchstaben umgeben. Auch beim Fixieren des Kreuzes, sollte das Schreiben leicht zu erkennen, sein, obwohl es genauso wie in der Peripherie wie das G in Figur 2a ist.
Dieses Video demonstriert, wie entwerfen und implementieren eine crowding Experiment mit Buchstaben als Stimuli.
Procedure
Results
Figure 5 graphs accuracy as a function of relative spacing. As relative spacing got bigger, performance improved by a lot. What this means is that performance benefits when the inter-stimulus spacing is at least half as big as the eccentricity. In fact, the idea that spacing needs to be half as big as eccentricity to prevent crowding is known as Bouma's Rule, after the scientist who discovered how the ratio between inter-stimulus spacing and eccentricity controls crowding. When the ratio is 0.5, as shown in the graph, performance is usually around 75% or better. Below 0.5, accuracy is often close to chance. Note that even with a relative spacing of 0.4, performance in this experiment was less than 25%, and with a relative spacing of 0.25, it was close to random. There are 21 consonants in English, so guessing would produce the right answer nearly 5% of the time.
Figure 5. Results of the crowding experiment. Recognition accuracy was very poor, and at times close to chance in trials with a relative spacing less than 0.5. But for trials with spacing of 0.5 or greater, recognition was usually better than 75% accurate. 0.5 is generally the critical relative spacing that prevents crowding.
Variations
Now that you know the basics of running a crowding experiment, you can run an experiment to show that relative spacing is the crucial determinant of crowding. Here is how: Pick four eccentricity values, say 50, 100, 200, and 250 px. For each, identify the four inter-stimulus spacing values that will give you the relative spacing values from the previous experiment, i.e. 0.25, 0.4, 0.5, and 0.75. Now you have four different ways of producing the same relative spacing values but with different eccentricities. That's 16 conditions in total. Run an experiment with 50 trials of all 16 conditions, and plot the data as shown in the Figure 6. You should find that relative spacing is the crucial determinant of performance (as opposed to eccentricity).
Figure 6. Results of a second crowding experiment designed to contrast the effects of eccentricity and relative spacing on performance. The x-axis displays the four relative spacing values used, and the different color icons represent the different eccentricities. If eccentricity were the primary constraint on recognition, then icons with the same color would tend to group together in terms of recognition accuracy. But instead, accuracy seemed to be governed by relative spacing.
Applications and Summary
One reason that understanding crowding is important has to do with macular degeneration. Macular degeneration is a condition that mostly affects older adults, involving the degeneration of the macula, the densely populated part of the retina that includes the fovea. Macular degeneration is the leading cause of blindness in the US among people over 65. It leaves people heavily reliant on peripheral vision. Thus, research on crowding can help scientists to understand the limitations and affordances of peripheral vision, how to improve it, and generally how to design the environment to prevent crowding in important situations.
Understanding how crowding works also plays a role in how engineers, graphic designers, and web developers arrange many of the displays that people engage with on a daily basis. For example, when a pop-up or banner ad appears in your web-browser, it is often designed to catch your attention, but not be 100% readable or resolvable because of crowding-the people behind the scenes want you to move your eyes and look at the ad after it catches your attention.
Acknowledgements
1. Whitney, D., & Levi, D. M. (2011). Visual crowding: A fundamental limit on conscious perception and object recognition. Trends in cognitive sciences,15(4), 160-168.
Transcript
We don’t always see objects in our surroundings clearly, especially if they are located in the periphery of our visual field.
Throughout the day, an individual will move their eyes to look directly at different, distinct items—like elements of a painting in a museum.
When this happens, the object being closely studied—like an apple—is positioned in the middle of the observer’s field of view, and as a result is seen clearly.
In contrast, an item far off to the side of the apple—in this instance, a dog—is located in the periphery of the visual field, and is perceived as fuzzy.
Such haziness can actually worsen in a phenomenon called visual crowding. Here, if the peripheral object is surrounded by “clutter”—like more canines a rogue artist decided to paint—it will be unrecognizable.
In this video, we explore how to investigate crowding using a letter-based approach. We not only explain how to design stimuli and collect and interpret peripheral vision data, but we also note how researchers are studying the concept in other contexts—like how it affects driving safety.
In this experiment, participants are asked to identify letters that are delivered to their peripheral visual field.
This is accomplished by first having them focus on a small fixation cross presented in the middle of a computer monitor, after which the letter stimuli appear.
During this phase, a row of three equally-spaced, capitalized English consonants—like JXW—are shown to one side of the cross, and thus are seen only with peripheral vision. Vowels are specifically excluded, as they could form short words that might interfere with data collection.
Although all of these characters are in the same size and type of font, two key variables are manipulated in these stimuli—eccentricity and inter-stimulus spacing—to better understand the factors that affect crowding.
The first, eccentricity, is the distance in pixels from the central letter to the intersection of the lines in the cross, which relates to where in the periphery of the visual field stimuli are delivered; the higher the eccentricity, the more peripheral the presentation of the letters.
In contrast, inter-stimulus spacing is defined as the distance—also in pixels—between the central consonant and each of the letters that abut it. This measurement assesses how close the flankers need to be to the middle character, to provide the clutter necessary for visual crowding.
The numbers chosen for these two distances in any given stimulus are actually controlled by a third variable defined as the ratio of inter-stimulus spacing to eccentricity—called the relative spacing.
Four different values—0.25, 0.4, 0.5, and 0.75—are tested to specifically assess whether inter-stimulus spacing needs to be a certain size, in relation to eccentricity, to have a crowding effect on peripheral vision.
For example, if a letter trio has a relative spacing value of 0.75, this means that the inter-stimulus distance is three-fourths the size of the eccentricity. So, the flanking consonants would be located relatively far away from the central character.
After the stimulus disappears, a response screen is shown, which prompts participants to type in what they perceived as the central letter.
Two hundred such trials are performed, in which stimuli with different relative spacing values are equally—but randomly—presented.
Here, the dependent variable is the percentage of trials in which the middle letter is correctly identified.
Based on previous work, it is expected that participants will only be able to accurately recognize the central characters in stimuli with a relative spacing of 0.5 or greater.
Importantly, this indicates that inter-stimulus spacing needs to be at least half the size of eccentricity to prevent crowding, a stipulation known as Bouma’s rule.
Greet the participant when they arrive, and have them sign informed consent materials. Then, seat them in front of a computer monitor with a keyboard.
Place their chin in the apparatus positioned approximately 60 cm from the screen.
Continue to explain the task, emphasizing that the experiment is self-paced, and—to proceed—the spacebar must be pressed. Also note that if in any instance the participant is unsure of the identity of the central consonant, they should provide their best guess.
Then, watch as the participant performs several practice trials. For each, ensure that the fixation cross is presented for 500 ms, followed by it and the letters, for the same amount of time. Also check that the participant, when prompted, enters their responses by pressing a consonant button on the keyboard.
Once they understand the task, leave the room, and allow the participant to complete the 200 trials.
To analyze the data, for each relative spacing ratio, compute the percentage of trials in which participants correctly identified the central consonant.
Notice that, as relative spacing increased, accuracy improved. Specifically, when this ratio was 0.5, participants demonstrated a performance of 75%, and this value jumped to approximately 95% when the relative spacing was 0.75.
However, with a ratio of 0.4, participants only accurately recognized the central consonant in 20% of trials, and at 0.25 this value dropped to 5%—a frequency that roughly corresponds to chance, if the central letter was guessed randomly
Collectively, these results indicate that crowding only occurs if the inter-stimulus spacing is less than half the size of eccentricity—for example, either 25% or 40% of this distance, as tested here—an observation supporting Bouma’s rule.
Now that you know how the manipulation of eccentricity and inter-stimulus spacing can be used to study crowding, let’s take a look at other ways aspects of peripheral vision are being explored.
Crowding has also been looked at in relation to automobile safety, and whether the number of objects in an environment can influence what a driver sees.
Such work has determined that crowding—either several cars, traffic cones, or signs in an area—can cause a driver to not effectively perceive a pedestrian.
For example, a person may observe a blurry object amidst cars, and think it is a parked bike—until the item darts out into the street, and turns out to be a man running to catch a train.
Work on the limits of peripheral vision is encouraging researchers to come up with ways to improve pedestrian and driving safety, like creating clear, well-lit crosswalks.
In contrast, web developers are also applying what we know about peripheral vision to create effective pop-up ads.
Due to the effects of crowding on letters, such banners are designed to not contain a lot of text, since these words won’t be distinguishable when they appear on the side of a monitor—in an internet user’s peripheral vision.
Rather, these advertisements contain bright, moving elements that attract someone’s attention, and cause them to move their eyes and fixate on this promotion. Then—hopefully—the person will click on it and order whatever is being sold.
Up until now, we’ve focused on crowding in normal participants; however, researchers are also looking at whether this perceptual phenomenon is related to visual defects associated with certain diseases.
For example, some work has involved the presentation of closely-spaced letter trios to patients diagnosed with a neurodegenerative condition similar to Alzheimer’s. Importantly, these stimuli were shown in the middle of a computer monitor, and thus delivered to the center of the visual field.
Interestingly, fewer patients were able to name the central letter, compared to healthy controls.
Collectively, this work provides evidence for the expansion of crowding—normally only a problem in the periphery—into central vision, and offers a possible explanation for the reading difficulties some neurodegenerative patients experience.
You’ve just watched JoVE’s video on peripheral crowding. By now, you should understand how to manipulate letter spacing to investigate this phenomenon, and collect and interpret vision data. In addition, you should grasp how crowding is being applied to other areas, such as the design of pop-up ads.
Thanks for watching!