The Daily Monthly

The last day, the last month

2010-05-28T14:19:56Z

It’s been a good four-month run, but I’ve decided to end my experiment with The Daily Monthly. There have been some tremendously satisfying moments in this process, but in the end, there were too many problems with the model to make it sustainable.

Originally, I was hoping that each month’s topic would evolve into a story, that each day’s post would add depth and layers of understanding to the narrative. In some ways, that worked, but I’ve never been really happy at the end of a month with what I’ve produced. Perhaps that’s because I chose topics that were so open-ended that it was difficult to come to a satisfying conclusion, but I think it has more to do with the limitations of the format.

The very title of this blog indicates that there will be something new every day, and with each month, we’ll move on to another topics. In real life, narratives don’t work that way. Some days are slow, and some days have tremendous revelations. Some topics can be covered in a month, and some can be covered in a week. Some might not be adequately addressed in a lifetime.

That said, I think there’s some neat stuff on this blog, and so I’ll try to keep it up and functioning. I’ll continue to allow commenting, spam permitting. If you haven’t checked out all the topics, I encourage you to do so. There is some compelling stuff in each month’s coverage:

In case that seems a little too overwhelming, here are some of the most-notable posts:

AIDS in America

World Population

Fitness

Illusions

At this point, I don’t have a plan for what’s next. I’ll probably take a couple months off from daily blogging, and then we’ll just have to see.

Lightness and contrast illusions help illuminate the visual system

2010-05-25T20:58:20Z

You may not have noticed that the banner artwork for this month’s topic is itself an illusion, based on a design by Stuart Anstis:

Each diamond is identical, yet each row of diamonds appears to be darker than the row above it.

I can construct a simpler version of the illusion with just two squares:

Again, the squares are identical, but the square on the left looks darker (although this illusion isn’t as strong as the diamond illusion). Why?

The reason is that our visual system actually has to do a lot of processing to create a coherent picture of the world. In order to do it needs to make a lot of assumptions. The well-known checkershadow illusion can help you see why:

This illusion, designed by Edward Adelson, shows how our perception of lightness is affected by context. The squares marked A and B are identical, yet appear to be dramatically different. Why? Because our visual system is doing something much more complex than simply comparing absolute color values. In fact, it automatically adjusts for the amount of light it guesses must be falling on an object in order to come to a better assessment of where one object ends and the next one begins.

Unless you’re solving optical puzzles, the important thing to note about the image above is not that A and B are actually the same shade of gray, but that the whole image represents two objects: a green cylinder and a gray-and-white checkerboard. Our visual system automatically accounts for the fact that dark square A is illuminated and light square B is in a shadow, so as to build a coherent representation of the object. In everyday life, it doesn’t help us to know that the luminance of the two squares is the same.

But perceiving a “shadow” and “light” aren’t the only things we use to judge the “real” colors we see. Take a look at this image, known as the Koffka ring:

The image on the right is simply formed by splitting the left-hand image apart. The right half of the “donut” suddenly seems darker than the left half, even though its luminance is the same, and even though we don’t see it as a “real” object.

Now take a look at this:

The effect is even more dramatic, perhaps because we group the right half of the ring with the dark left-background, while grouping the left half with the lighter background on the right.

Vision scientists have systematically manipulated images like this to determine what parts of an image are more likely to be combined by the visual system. Corners and other junctions are critical, perhaps because in three-dimensional objects they often represent portions of an object that are likely to be lit differently.

By combining known effects, truly dramatic illusions can be created:

Amazingly, the four small tilted rectangles in this figure are all identical! Once again, it’s not necessary to see the object as three-dimensional, though some people do — the illusion persists either way. It can all be explained as a side effect of the way our visual system processes everyday objects. Nearly all the time, the system functions perfectly, and the real world corresponds to what we think we’re seeing. But often, an illusion can say more about how the visual system works than an accurate perception of the world.

For a really nice presentation of these and other illusions, be sure to try the demo on Edward Adelson’s web page.

Adelson, E.H. (2000). Lightness perception and lightness illusions. In The New Cognitive Neurosciences, 2nd. Ed., M. Gazzaniga, ed. Cambridge, MA: MIT Press, 339-351.

How do we know what historical figures really looked like?

2010-05-20T15:27:00Z

Compare these two pictures of George Washington. Which one is more accurate?

Most Americans would probably guess the picture on the left. (Left-image: Gilbert Stuart “Vaughan” portrait of George Washington. Source: Wikimedia Commons. Right-image: Charles Wilson Peale portrait of George Washington. Source: Metropolitan Museum.) But how would you really know? Gilbert Stuart is a more famous portraitist than Peale, having painted the famous incomplete Athenaeum portrait of Washington. Are you just biased because you’re more familiar with Stuart’s work?

It might seem that there is no way to know—after all, there are no photographs of Washington—but Eric Altschuler and Ahmed Meleis believe they have come up with a method to assess a portrait artist’s accuracy in representing his or her subjects. While there are no photographs of the first five U.S. presidents, John Quincy Adams was photographed. He also had his portrait painted by both Stuart and Peale. Unfortunately, the photograph was taken late in Adams’ life, much later than the portraits were made. So Altshuler and Meleis used computer software to artificially “age” the portraits:

The Stuart portrait turned out to be much closer to the photograph than the Peale portrait. Other Stuart portraits similarly match with photos, while Peale’s work consistently falls short. Altschuler and Meleis say that Stuart is a sort of “Rosetta Stone” for images, and we can use Stuart’s portraits to learn what historical figures really looked like. Stuart was a prolific painter, who indeed painted many presidents and other historical figures, so this is a valuable insight.

Altschuler and Meleis go even further, suggesting that older painters who use a style similar to Stuart’s might also be relied on to give accurate representations of their subjects. You could potentially go back quite far in history, comparing portraits of individuals that both Stuart and another artist painted. If the portraits offered similar depictions, then you could say that other artist was also an accurate portraitist. The process could be repeated indefinitely. Of course, it could be problematic as you went further back in history, since the connection between the portraits and the photographic record would be progressively more remote.

Altschuler, E.L, & Meleis, Ahmed (2010). What Did the Early United States Presidents Really Look Like?: Gilbert Stuart Portraits as a “Rosetta Stone” to the Pre- Photography Era. Poster presented at the Vision Sciences Society Meeting, Naples, FL.

Daniel Simons interview, continued: Change Blindness

2010-05-18T17:39:19Z

Last week I interviewed Daniel Simons for Seed Magazine. But the interview that ran there actually only included a little over half of our discussion. In addition to his work on inattentional blindness, Simons is also a leading figure in a different line of research, called change blindness.

Here’s a quick video demonstrating the phenomenon of change blindness:

It’s uncanny how difficult it can be to spot changes occurring right before our eyes. In this case, it seems impossible that anyone would miss it, but Simons and Daniel Levin found people missed this sort of change around 50 percent of the time!

Simons and Christopher Chabris’ book The Invisible Gorilla, which covers both change blindness and inattentional blindness, comes out today (Amazon, Barnes & Noble, Powell’s). I’ve read an advance copy provided by the publisher, and I highly recommend it.

Munger: You’ve studied change blindness for over 13 years. Tell me a bit about that field and your contributions.

Simons: I got into it indirectly. I was studying how kids can categorize different kinds of objects, and I was trying to see if they would notice some kinds of changes more than others. It turned out they weren’t noticing anything. Adults too. I was also studying motion picture perception with Dan Levin, and we were looking at whether people notice editing mistakes in movies. There was kind of a convergence of research on it in the early days. Ron Rensink was starting to use his flicker task, we were starting to do motion picture perception research, and most of it built on some work by George McConkey some years earlier.

Ron Rensink’s work was triggered by a presentation at a conference in Vancouver in 1991 that involved making changes as people were moving their eyes from one place to another. John Grimes showed his demo to illustrate the changes, but of course you can’t have eye tracking for everybody in the audience. They were showing how the stimuli changed, and on occasion, somebody in the audience would miss the change. For Rensink, that suggested that maybe you could do this without eye tracking. So he developed his flicker task as a way of doing that.

That was happening when I was in grad school; I didn’t know anything about that presentation, I didn’t know anything about those studies. I was doing object recognition work, and motion picture perception work independently, and Levin and I started pushing this idea that we don’t notice changes in movies, which people had known for decades in movies.

The early days, I think, of the change blindness work, were much more of a demo nature: It was, how big an effect could you make, how much could you make people miss? The more parametric studies started in the mid to late 1990s, when people were interested in how much you were actually retaining from one moment to the next, or what kinds of things would you miss, what kinds of things wouldn’t you miss, what role would attention play, and that sort of thing. So that was all in the change blindness world.

Munger: Can you briefly explain what a parametric study is?

Simons: Sure. So in change blindness, there are really two different kinds of phenomena that are probably related but they might be somewhat different. There’s incidental change blindness, where the change happens unexpectedly, you’re not looking for it, and you’re asked whether you noticed it after the fact. A lot of my early studies worked that way: we showed someone a movie, then we unexpectedly changed something in the movie, say someone’s clothes, or the actual actor in the scene, and find that people didn’t notice, and we asked them immediately afterwards to describe what they’d seen, and they didn’t know anything had gone wrong. With those sorts of studies you just get one shot, it’s just one trial. But you can also do studies when you intentionally change something in the scene, where people know there’s going to be a change, they do their best to find what’s changing, and they still sometimes miss it. The nice thing about that is you can do it over and over again, and systematically vary the nature of the change, the size of the change, the location of the change, across trials to see what factors matter.

Rensink’s flicker task fits that bill, where you have two images that alternate repeatedly with a blank between them. It takes a while to find the changes in most contexts. And you can look to see if there are systematic differences in who notices which change, how quickly people notice different kinds of changes. You can systematically or parametrically vary how long the displays are on, how long the gap is between them, how many things there are on the display. It’s hard to do that with an incidental task because you really only get one trial per subject. So you could do it but you’d need thousands of subjects to do the same thing that you could do in a thousand trials with one subject.

[Here's an example of the "flicker" paradigm]

Munger: So how has that work changed over the years?

Simons: The early days of this sort of research in the 90s was very much of this demo character: Can we change the person you’re talking to in an interview? That phase for change blindness is done now. We spent about four years or so in my lab and in lots of other labs one-upping, showing what you could miss. But the theoretical implications of that were no longer quite as critical. We now knew people would certainly miss things they were not focusing attention on, but they also missed things they were focusing attention on if they weren’t actively comparing it to something else that had changed. But the demo phase of change blindness more or less wrapped up in the early 2000s. There are still occasional demo, one-trial change blindness studies out there, but for the most part that field has moved toward more systematic studies of how much information is preserved when people fail to notice changes, or, are there systematic individual or group differences that determine what people notice or what they don’t. Or, are there individual differences in attention, personality, or memory, that will predict whether people will notice. What role does salience in the scene play in whether or not people are drawn to the change?

So those are the sorts of things people are looking at now. As with any phenomenon like this there’s the underlying phenomenon, and the phenomenology of failing to notice change. And there’s still work on that, but there’s a lot more studying of the task too. Also, because it’s easy to do, I think some people who don’t really know the literature and the methods have started trying to do these experiments and publish the results. There’s more work that’s less theoretically interesting. And there’s still plenty that is.

Munger: What are some real-world applications of this research?

Simons: We all experience this sort of stuff. For example, an experience I have all the time is that I’m working on my computer, I’ve got multiple applications open, and I don’t realize that I’ve actually switched applications, and I don’t realize the menu has changed. That’s just a simple practical example that doesn’t have any consequence, but the same sort of mechanism is at play there.

Munger: In someways change blindness is similar to inattentional blindness studies like your “Gorillas in our Midst” study because you’re not noticing something, but as you pointed out they are different because it’s a one-shot deal with inattentional blindness—

Simons: —and sometimes with change blindness, too

Munger: Yes, but are there similarities as well? Do you think there are some cognitive processes that are the same between the two phenomena?

Simons: Yes. I’m sure. Change blindness is more complicated in many ways. Inattentional blindness is in some ways a purer example of a failure of perception, or awareness of perception. It’s a cleaner example of the mechanisms involved—it is due to attention being focused on something wrong, or in a limited way. Change blindness is more complicated because it can happen for any number of reasons. In change blindness, you’re failing to notice that something is different from the way it was a moment ago, which means you have to encode it in the first place, then you have to remember what it was that you encoded, and then you have to compare what’s there later to what was there before. Any one of those stages could break down. When you fail to notice a change, you don’t know whether people never encoded it in the first place, or forgot it, or remembered it perfectly and never bothered to make the right comparison. So it makes it much more difficult to say exactly what went wrong. It also makes it interesting to study. But I think both are typically attributed to limits of attention in some form. The interesting question for change blindness is how much actually is represented. How much have have you actually stored but just not bothered to access? Or not compared? Or stored in the wrong format to access, that would have allowed you to detect the change? Say you look at a scene. If you look at the pre-change scene, there’s nothing about that scene that tells you what changed. If you look at the post-change scene there’s nothing about that scene that tells you there’s anything wrong, so it has to be a comparison between the two.

For inattentional blindness you can look right at that scene and the thing that’s odd is right there. So there’s nothing to compare to, there’s no memory demand. I think there are common processes, there are limits on awareness, there are limits on attention, that contribute to both, but there are more mechanisms that can go wrong to cause change blindness.

The change blindness studies, the gorilla studies, they do the same thing. When we change the person you’re talking to in the middle of an interaction, that’s not something that ever happens. But if we didn’t make that change we’d have no way of knowing whether you were actually encoding details about that person before or afterwards. We’d have no way of knowing how much information you were retaining. So it’s a way of seeing what the default assumptions are of attention and awareness. Metaphorically it’s the same approach. You break the system, in this case the cognitive parts of the system, not vision, but you’re breaking down what typically happens in order to see what happens by default. Do you, by default keep track of the height, sex, hair color of the person you’re talking to? Does that happen automatically? Do you keep track of their identity? We’d really have no way of knowing that unless we test whether or not you had.

Munger: But there are changes in individuals that people do notice pretty readily, right?

Simons: Yes. We tried changing the sex of a person you’re interacting with, or the race, and those are almost always noticed. I think that’s interesting. When people successfully detect a change, it tells you what sorts of information they’re keeping track of. When they fail, you don’t quite know. If you detect a change to the race of a person, but not other sorts of changes, that tells you something about what was encoded.

Munger: I always think it’s interesting that parents of little kids, so small that you really can’t tell what sex they are just looking at them, tend get really offended if you don’t get the sex right.

Simons: I always find that really funny. That’s why people dress their kids in pink or blue.

The hollow mask gets a nose ring!

2010-05-15T02:48:42Z

The hollow face mask illusion is a great three-dimensional effect that’s remarkable because it not only works in movies, it also works in real life. Check this out:

This is a computer-generated image (from the Max-Planck-Institut für biologische Kybernetik in Tübingen), but it can just as easily be perceived with a real hollow mask. Here’s Thomas Papathomas’s 2008 illusion of the year, produced with a physical mask on a turntable. This works best if you sit back a bit from your computer monitor (or watch on a small display like an iPhone).

I met Papathomas and saw the mask live at the VSS conference this week, and the illusion is even more dramatic in person. When you see it in real life, it does require you to stand back a bit, and often people don’t see it unless they close one eye. Why?

Papathomas has a theoretical explanation for not only the hollow face illusion, but a number of similar effects. The problem is that when we’re looking at a three-dimensional object, an individual eye only gets two-dimensional information about it — an inverted image much like a slide — projected on the retina (the inside of the back of the eye). This information could correspond to several possible objects. It could, for example, be a flat photograph of a face. Or it could be a real, three-dimensional face. More rarely, it could be the back side of a mask. Most of the time, without further information to the contrary, we assume it’s a three-dimensional face. But when we move or the mask moves, it appears to do things that are impossible for a real face. This image shows why:

The Hollow Mask at the top is what you’re looking at. But since the perceptual system assumes the mask to be convex like a normal face, when your eye is at Position 1, you perceive Face 1. Just look at the dotted lines extending from the eye to the mask — you can see that they pass through the perceived face and end up on the hollow mask at the same position on both faces. Indeed, you might perceive the face in other ways too — with a long pointy nose but otherwise flat, for example. The only reason you perceive the convex “normal” face is because that’s the sort of face you’ve seen other times.

The key to the illusion occurs when you move to Position 2. Although the mask hasn’t moved at all, since you perceive it as a convex face, your perceived face does move — it seems to follow you as you move around the room. Or, as in the movie, you could stand in the same place while the face appears to change the direction it rotates in.

By adding a nose ring to the mask, Papathomas highlights how bizarre the hollow face illusion is. Since the nose ring, unlike the rest of the mask, is convex, it doesn’t appear to turn along with the rest of our illusory perception. Even though it’s the only “real” part of the display, it seems to move almost magically in the opposite direction of the rest of the mask.

So why does the illusion require us to stand back a bit, especially when viewing in person? Because we get three-dimensional information from other sources. At a close enough distance, we can use two eyes to triangulate the distance to objects — we can directly perceive that the nose is farther away than the cheeks, and the illusion fails. That’s also why closing one eye can often restore the illusion. How far away do we need to be to perceive the illusion? We discussed one study of the effect on Cognitive Daily, and the answer was “it depends” — upright, recognizable objects preserve the illusion at a closer distance, seemingly overriding the depth information given by our eyes. For a teddy-bear, viewers could be standing as close as 1.5 meters and still see the illusion.

Papathomas, T. (2007). Art pieces that ‘move’ in our minds — an explanation of illusory motion based on depth reversal Spatial Vision, 21 (1), 79-95 DOI: 10.1163/156856807782753958

Can Kids Ken Kanizsa?

2010-05-12T18:22:30Z

The Kanizsa Illusion is one of the best-known and simplest visual phenomena:

Most adults readily see not only the three “pac-men,” but also the triangle formed by their “mouths.” This effect can be used to create virtual rectangles, stars, and other more complicated shapes. What’s less clear is at what age children are first able to see the illusion. Some research suggests that infants are able to perceive it, but other studies find that kids as old as five or six still have difficulty recognizing the shapes suggested by the pac-men.

So a team led by Kimberly Feltner developed a test that could be administered to kids as young as three years old. They trained children ranging from age three to nine, as well as adults, in three phases: comparing shapes, comparing orientation, and finally comparing real shapes to shapes suggested by Kanizswa contours. In each case, they first saw a model shape, then chose between two choices to identify matching shapes, presented as real shapes or Kanizswa illusions depending on the training phase.

Every age group could complete the first two tasks at 80 percent accuracy, but children age three to four had difficulty with the Kanizswa task, only getting about 70 percent correct. This is still better than random guessing, so in some senses these young kids can do the task, but the researchers suspected that younger kids were taking a different approach to the problem.

Using eye tracking software, the researchers analyzed where the kids (and adults) were pointing. Here are the results:

When looking at real shapes, both adults and children looked mostly at the middle and edges of the shapes. But when looking the shapes presented in the form of Kanizsa illusions, younger children looked primarily at the corners of the pac-men, suggesting they may have been perceiving the illusion in a different way from the adults.

Since selections were made with a touch screen, the researchers also tracked where the kids were pointing. Pointing matched looking behavior — even when the youngest children selected the correct Kanizsa figure, they were significantly more likely than adults to point at the corners or pac-men rather than the center of the shapes. Three- and four-year-olds actually tried to touch all the corners of the Kanizsa figure simultaneously. While it’s unclear from this experiment exactly what these young children were perceiving, it seems likely that they were processing the Kanizsa figures differently from older kids and adults.

Could they literally not be seeing an illusion that’s dramatic and clear for most adults? It’s hard to tell from this study. The fact that they look at the corners rather than the center of the shape does seem to indicate that they perceive it differently. It may be that the ability to perceive an illusion like this is acquired gradually.

Feltner, K., Mayar, K., Adolph, K.E., & Kiorpes, L. (2010). Kanizsa illusory contour perception in children: A novel approach using eye-tracking. Poster presented at Vision Sciences Society Meeting, Naples, FL.

Live from VSS: When you make a bad tennis shot, the ball seems faster

2010-05-11T17:11:21Z

Pro golfers say the hole seems bigger when they’re putting well. Baseball players say the ball seems bigger when they’re hitting well. But what about the perceived speed of the baseball?

Today at the VSS (Vision Sciences Society) conference I saw a great poster where the researchers measured real-world perception of the speed of a tennis ball. Mila Sugovic and Jessica Witt asked players enrolled in beginning, intermediate, and expert tennis lessons to return balls launched by a serving machine at 50 to 80 miles per hour. After each shot, the players walked to a computer showing an animated ball moving toward them. They pressed a button to launch the ball, and again after they estimated the ball had been in the air for the same amount of time as the ball they had just hit.

Did the advanced players see the ball as moving slower than the beginners? Actually, the ability of the players didn’t predict their estimates. But when the players made a better shot, they saw the ball as taking more time to get to them.

Sugovic and Witt videotaped each shot and measured the actual time the ball took to travel to the players. They compared this to the players’ estimates. In general, players overestimated the speed of the balls, saying they took about 70 percent as long in the air as they actually did. But when players subsequently hit the balls out of bounds, their estimates of ball speed were significantly faster than when they hit a good shot. The difference in perception corresponded to about a 5 mile-per-hour difference in speed.

After the study was over, the researchers also asked players to estimate the height of the net. Players who had hit more shots into the net were significantly more likely to make higher net-height estimates!

Sugovic, M., & Witt, J. (2011). Performance affects perception of ball speed in tennis. Poster presented at Vision Sciences Society meeting, Naples, FL.

Best Illusion of the Year 2010

2010-05-15T13:56:28Z

I’m here at the Illusion of the year contest, which is held at the symphony hall here in Naples, Florida. It’s an enormous room, just now beginning to fill with some of the pre-eminent vision scientists in the world.

Since I have journalist credentials for this conference, I was able to get a sneak peak at the illusions that will be presented. Unfortunately, there’s no wifi here, so I won’t be able to live-blog the proceedings, but I’ll try to get this post up as soon as possible after the event.

The contest winner was Koukichi Sugihara, who has created a remarkable three-dimensional physical illusion: Impossible motion: magnet-like slopes.

Four ramps appear to ascend up to a central junction. Then a hand appears and rolls marbles “up” each ramp, with each marble stopping at the top of the hill. They seem to inhabit a bizarre world with reverse gravity. Perhaps it’s done with magnets—except the balls are made of wood! Then the camera pans around the device and it becomes clear how it was done—the ramps are actually all downhill!

There’s a long movie with more illusions here.

Another great illusion, which didn’t end up winning a prize: Peter Tse’s illusion is Attention-based after-image rivalry. It’s based on a couple different perceptual phenomena, but combined in a unique way. To see the illusion, you stare at the image on the left, two superimposed rectangles, each with colored strips along the longest dimension. After staring for 60 seconds, you then look at the image on the right. The after-image appears over the two outlines, and you can easily shift your perception to see two different after-images, one corresponding to each rectangle.

I’ll have another post about the contest tomorrow.

Live Blogging at VSS

2010-05-08T16:46:18Z

I’m here at the Vision Sciences Society 2010 convention in Naples, Florida — a fantastic meeting of vision scientists from around the world. So far the wifi is working well, so I’m going to try liveblogging a session. The session I’m at is “Motion: Perception,” moderated by Scott Stevenson.

First speaker: Albert van den Berg: The vestibular frame for visual perception of head rotation

When you move through a scene, there are two aspects of movement: translation, and rotation.

Did an fMRI study. simulating the rotation of the head while participants were still in the fMRI machine.

Participants had to wear a special contact lens to see the screen because it was extremely close to the head.

“rotated” at varying speeds, around three different axes. The display looks sort of like what you see in sci-fi movies, when a ship is about to enter into warp speed and the stars are moving by.

They were able to identify the brain activity associated with each type of rotation. For each individual, this occurred in a slightly different region of the brain.

Second Speaker: Scott Stevenson: Suppression of retinal image motion due to fixation jitter is directionally biased

Cool, a live animation of the human retina! — Extremely jerky motion, but the eye is fixated steadily on an object.

Question: why don’t we normally see the jitter in our eye? Our eyes are sensitive enough to perceive it.

Suggestion: somehow the visual system actively suppresses this jitter.

In their study, they took the motion of the eye, and fed it back into the stimulus as the viewer perceived it. A small target is moving as the viewer watches.

It’s not perfect stabilization, but it does break down when the eyes make dramatic movements.

When the target perfectly matches eye movement, it fades due to Troxler effect.

So they changed the direction of target motion relative to the eye.

Then they asked the subjects what they perceived.

As the difference between the motion and the eye motion increased, perceived motion decreased!

Third Speaker: Satoshi Shioiri, Comparing the static and flicker MAEs with a cancellation technique in adaptation stimuli

[Lost wifi during this session, sorry!]

Wow, really cool motion after-effect. The top part of the screen is moving in the opposite direction of the bottom.

Basically this is done by moving part of the display (fat vertical bars) left-to-right, and part right-to-left (skinny vertical bars). The right-to-left portion has decreasing contrast from top-to-bottom. Then when the animation is stopped, there’s a really bizarre contortion. I may see if I can contact this guy to get his demo online.

Fourth Speaker: Deborah Apthorp, The neural correlates of motion streaks: an fMRI study

Motion streaks — those streaks added by artists to show motion in a picture — may be a part of our visual system.

When you look at actual motion, your perceptual system responds in a similar way to how it responds to motion streaks in pictures.

So they placed viewers in an fMRI machine, and showed them both dots in motion and streaks (in separate blocks).

Same areas of the brain (V1-V3) show activity with fast motion and streaks. Slow motion has a different activity pattern from both.

Voxels of the brain that responded to particular orientations of an object, also responded to fast motion in the same direction.

Fifth Speaker: Peter Scarfe, Perception of motion from the combination of temporal luminance ramping and spatial luminance gradients

The researchers created a complex stimulus that led to a strong motion aftereffect, even though the stimulus itself wasn’t moving.

Very complicated stimuli, difficult to explain — but a very cool study!

Sixth Speaker: Andrew Rider, Position-variant perception of a novel ambiguous motion field

Question: We often perceive motion with limited information, but depending on information, we perceive it differently. How?

Basically, it seems that when we see a bunch of different moving things, we analyze the motion, then pick the simplest way to integrate all the motion.

But this could be done in a bunch of different ways — how do we actually do it?

They developed an interesting stimulus whose apparent motion depends on where you look. Hard to explain.

Room now filling up for Stuart Antsis’s presentation

Seventh Speaker: Stuart Anstis, Perceptual grouping of ambiguous motion

How do we detect motion of groups of spots?

He’s showing bunches of spots of different shapes, and asking when we see the motion of the spots as a big group rather than small groups.

Overall, tend to parse maximum number of items into minimum number of items!

Very cool, very funny demos.

And now, everyone sings “happy birthday” to Stuart

He says “I’m not looking forward to being 60″

Spinning ellipses perplex the visual system

2010-05-07T16:53:39Z

Take a look at this video (Click on the image to play, QuickTime required):

Which ellipse is rotating faster?

While at first it seems quite obvious that the ellipse on the right is rotating faster, if you download the movie and play in loop mode, by counting rotations you should be able to convince yourself that they are actually rotating at the same speed.

The next question, of course, is why. Gideon Caplovitz, Po-Jang Hsieh, and Peter Tse systematically studied the question in a paper they published in 2005. They showed viewers dozens of movies like the one above, with one ellipse always the same fatness always rotating at the same speed (126 degrees per second). In each movie, the width and speed of the second ellipse was systematically varied, and viewers judged which ellipse seemed to be rotating faster. This graph shows the results:

There’s a lot going on here, so I’m going to take some time to explain it. The four ellipses at the bottom are the different shapes used in the study. One of the two ellipses being shown was always like ellipse a, outlined in green. Sometimes both ellipses were the same shape (a), and sometimes the second ellipse was skinnier (b, c, or d). Angular velocity is the rotational speed of the second ellipse. The first ellipse always rotated at 126 degrees per second. The graph charts how frequently the second ellipse was perceived as spinning faster than the first ellipse. The color of the line corresponds to the shape of the ellipse — a is green, b is black, and so on. As you can see, when the green ellipse was spinning at 126 degrees per second, it was judged to be spinning faster than the reference ellipse 50 percent of the time (participants weren’t allowed to say the ellipses were spinning the same speed — they had to choose faster or slower). For ellipse b, this threshold occurred at a slower speed — even when it was spinning at just 105 degrees per second, most respondents saw it as moving faster than the fatter reference ellipse spinning at 126 degrees per second. The thinner ellipses were seen as spinning even faster, as you can clearly see in the example movie.

Does the illusion work for any shape? The researchers repeated the study with rectangles and found no effect — respondents were accurate at judging which rectangle spun faster, regardless of how fat or skinny it was.

But when they used rectangles with rounded corners rather than true ellipses, the illusion returned. The less rounded the corners, the faster the rectangles seemed to rotate.

Caplovitz’s team also tried adding dots to the end points of the ellipses, like this:

While the effect was diminished, skinnier ellipses were still perceived as spinning faster. So even when there is a readily-trackable part of the ellipse, viewers still see skinny ones as spinning faster than fat ones.

So we must not base estimates of rotational speed solely on trackable features like corners or dots on an image. Instead, the researchers conclude, we probably combine inputs from multiple sources. Fortunately, we don’t see a lot of spinning ellipses in day-to-day life, or we’d have a lot of trouble making sense of their movements.

Caplovitz, G., Hsieh, P., & Tse, P. (2006). Mechanisms underlying the perceived angular velocity of a rigidly rotating object Vision Research, 46 (18), 2877-2893 DOI: 10.1016/j.visres.2006.02.026