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Overview
출처: 조나단 플롬바움 연구소 -존스 홉킨스 대학
인간의 시력은 망막이라고 불리는 조직에 눈의 뒤쪽에 배치되는 빛에 민감한 뉴런에 달려 있습니다. 그들의 모양 때문에 막대와 원두에게 불린 뉴런은 망막에 균일하게 분포되지 않습니다. 대신, 망막의 중심에 는 콘이 조밀하게 포장되는 황반이라고 불리는 지역이 있으며, 특히 포베아라고 불리는 황반의 중앙 하위 영역에서는 특히 있습니다. 포베아 외부에는 콘이 거의 없으며, 막대 밀도는 포베아에서 더 큰 거리로 상당히 감소합니다. 그림 1은 이 배열을 스키마화합니다. 배열의 이 종류는 또한 시각적 인 피질에서 복제됩니다 : 많은 세포가 주변에 비해 포베아에서 자극을 나타냅니다.
그림 1. 인간의 눈의 회로도 묘사및 망막에 빛에 민감한 수용체 세포의 분포. 동공은 빛이 들어갈 수 있도록 눈 앞의 개구부입니다. 빛은 그 때 막대와 원추, 빛에 민감한 세포로 만들어진 눈의 뒤쪽에 있는 신경 조직인 망막에 집중됩니다. 망막의 중심에는 황반이 있으며 황반의 중심에는 포베아가 있습니다. 그래프는 그들의 위치의 함수로 망막에 막대와 원뿔 수용체의 밀도를 스키마화합니다. 색상 비전을 담당하는 콘은 거의 독점적으로 포베아에서 발견됩니다. 저조도 조건에서 볼 수 있는 막대도 마찬가지로 포베아 근처에 더 무겁게 군집되어 있으며, 황반 밖에서 밀도가 빠르게 떨어지는다.
결과: 우리는 우리의 눈이 직접 가리키는 공간의 부분에서 아주 잘 볼 수 있습니다, 포베아를 자극 공간의 부분; 그러나 우리는 실제로 주변에서 잘 보이지 않습니다. 우리의 눈이 끊임없이 움직이기 때문에 우리는 많은 개별 고정에서 공간을 표현하기 때문에 실제로 그것을 알지 못합니다.
주변 시력의 특성을 연구하는 한 가지 방법은 혼잡으로 알려진 현상입니다. 1 군중은 어수선하게 물체를 인식하지 못하는 것을 의미하며, 주변에 물체가 표시될 때 특히 강하게 혼잡을 경험합니다. 그림 2a는 혼잡을 경험할 수 있어야 하는 예입니다: 중앙의 십자가를 살펴보고 오른쪽 팩 의 중간에 있는 문자를 보고할 수 있는지 확인합니다. 그것은 아마 꽤 어렵다. 이제 그림 2b에서 왼쪽에 있는 편지를 보고하려고 합니다. 훨씬 쉽게! 이 그림에서 편지는 혼잡하지 않고 주변에 혼란이 없으므로 인식하기가 쉽습니다.
그림 2a. 혼잡 한 자극. 중앙에 십자가를 고정하고 왼쪽팩 중간에 있는 문자를 인식할 수 있는지 확인합니다. 편지가 주변에 있고 중앙 문자가 주변 의 편지로 붐비기 때문에 어려울 것입니다.
그림 2b. 혼잡하지 않은 자극. 이 자극은 그림 2a와 동일하며, 문자 G가 혼잡하지 않은 다른 문자가 둘러싸여 있지 않다는 것을 제외합니다. 십자가를 고정하는 동안에도 그림 2a의 G만큼 주변에 있지만 문자는 쉽게 인식 할 수 있어야합니다.
이 비디오는 문자로 군중 실험을 자극으로 설계하고 구현하는 방법을 보여줍니다.
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!