Recently I was interviewed Jovana Grbic of ScriptPhD about The Vision Revolution. She has a great knack for asking unusual questions, taking me out of my standard responses and making me think. (To find the podcast itself, scroll down within this link until you see it.) I also wrote a guest piece for them on idea-mongering and non-genius that you’ll find there.
Posted in Color & bare skin, Illusions, Interviews, Origins of language, The Vision Revolution, tagged David DiSalvo, Illusions, neuronarrative, The Vision Revolution, writing on May 12, 2010 | 2 Comments »
He recently interviewed me about my book, The Vision Revolution…
Benchfly’s Alan Marnett hit me with an in-depth interview Dec 16, 2009. In addition to getting into the science, the nice thing about the interview was the opportunity to talk about different ways of being a scientist. As you’ll see, I suggest being an aloof son-of-a-bitch, something I also talk about in this piece titled “How Not to Get Absorbed in Someone Else’s Abdomen“.
As research scientists, many of us spend a very large amount of time working on a very small subject. In fact, it’s not unusual for a biochemist to go through their entire career without ever physically observing the protein or pathway they work on. As we hyper-focus on our own niche of science, we run the risk of forgetting to take the blinders off to see where our slice of work fits in to the rest of the pie.
For Dr. Mark Changizi, assistant professor and author of The Vision Revolution, science starts with the pie. We spoke with Dr. Changizi about why losing focus on the big picture can hurt our research, how autistic savants show us the real capacity of the brain and what humans will look like a million years from now.
Mark Changizi: I sometimes distinguish between two motivations for going into science. First there’s the “radio kid,” the one who takes apart the radio, is always fascinated with how things work, and is especially interested in “getting in there” and manipulating the world. And then there’s the “Carl Sagan kid,” the one motivated by the romantic what-does-it-all-mean questions. The beauty of Sagan’s Cosmos series is that he packaged science in such a way that it fills the more “religious” parts of one’s brain. You tap into that in a kid’s mind, and you can motivate them in a much more robust way than you can from a here’s-how-things-work motivation. I’m a Carl Sagan kid, and was specifically further spurred on by Sagan’s Cosmos. As long as I can remember, my stated goal in life has been to “answer the questions to the universe.”
While that aim has stayed constant, my views on what counts as “the questions to the universe” have changed. As a kid, cosmology and particle physics were where I thought the biggest questions lied. But later I reasoned that there were even more fundamental questions; even if physics were different than what we have in our universe, math would be the same. In particular, I became fascinated with mathematical logic and the undecidability results, the area of my dissertation. With those results, one can often make interesting claims about the ultimate limits on thinking machines. But it is not just math that is more fundamental than physics – that math is more fundamental than physics is obvious. In a universe without our physics, the emergent principles governing complex organisms and evolving systems may still be the same as those found in our universe. Even economic and political principles, in this light, may be deeper than physics: five-dimensional aliens floating in goo in a universe with quite different physics may still have limited resources, and may end up with the same economic and political principles we fuss over.
So perhaps that goes some way to explaining my research interests.
This is science we’re talking about, of course, not math, so nothing in science is proven in the strong mathematical sense. It is all about data supporting one’s hypothesis, and all about the parsimonious nature of the hypothesis. Parsimony aims for explaining the greatest range of data with the simplest amount of theory. That’s what I aim for.
But it can, indeed, be difficult to find data for the kinds of questions I am interested in, because they often make predictions about a large swathe of data nobody has. That’s why I typically have to generate 50 to 100 ideas in my research notes before I find one that’s not only a good idea, but one for which I can find data to test it. You can’t go around writing papers without new data to test it. If you want to be a theorist, then not only can you not afford to spend the time to become an experimentalist to test your question, but most of your questions may not be testable by any set of experiments you could hope to do in a reasonable period of time. Often it requires pooling together data from across an entire literature.
A lot of people believe that by going straight to the parts – to the mechanism – they can eventually come to understand the organism. The problem is that the mechanisms in biology were selected to do stuff, to carry out certain functions. The mechanisms can only be understood as mechanisms that implement certain functions. That’s what it means to understand a mechanism: one must say how the physical material manages to carry out a certain set of functional capabilities.
And that means one must get into the business of building and testing hypotheses about what the mechanism is for. Why did that mechanism evolve in the first place? There is a certain “reductive” strain within the biological and brain sciences that believes that science has no role for getting into questions of “why”. That’s “just so story” stuff. Although there’s plenty of just-so-stories – i.e., bad science – in the study of the design and function of biological structure, it by no means needs to be. It can be good science, just like any other area of science. One just needs to make testable hypotheses, and then go test it. And it is not appreciated how often reductive types themselves are in the business of just-so-stories; e.g., computational simulators are concerned just with the mechanisms and often eschew worrying about the functional level, but then allow themselves a dozen or more free parameters in their simulation to fit the data.
So, you have got to attack the functional level in order to understand organisms, and you really need to do that before, or at least in parallel with, the study of the mechanisms.
But in order to understand the functional level, one must go beyond the organism itself, to the environment in which the animal evolved. One needs to devise and test hypotheses about what the biological structure was selected for, and must often refer to the world. One can’t just stay inside the meat to understand the meat.
Looking just at the mechanisms is not only not sufficient, but will tend to lead to futility. An organism’s mechanisms were selected to function only when the “inputs” were the natural ones the organism would have encountered. But when you present a mechanism with an utterly unnatural input, the meat doesn’t output, “Sorry, that’s not an ecologically appropriate input.” (In fact, there are results in theoretical computer science saying that it wouldn’t be generally possible to have a mechanism capable of having such a response.) Instead, the mechanism does something. If you’re studying the mechanism without an appreciation for what it’s for, you’ll have teems and teems of mechanistic reactions that are irrelevant to what it is designed for, but you won’t know it.
The example I often use is the stapler. Drop a stapler into a primitive tribe, and imagine what they do to it. Having no idea what it’s for, they manage to push and pull its mechanisms in all sorts of irrelevant ways. They might spend years, say, carefully studying the mechanisms underlying why it falls as it does when dropped from a tree, or how it functions as crude numchucks. There are literally infinitely many aspects of the stapler mechanism that could be experimented upon, but only a small fraction are relevant to the stapler’s function, which is to fasten paper together.
…..to see my answer, and the rest of the interview, go to Benchfly.
Posted in Color & bare skin, Interviews, The Vision Revolution, tagged bare skin, binocular vision, changizi, Color & bare skin, Evolution, Illusions, stereo, The Vision Revolution, writing on December 9, 2009 | Leave a Comment »
Today I was on LateNightLive (of ABC Radio National) with host Phillip Adam. In addition to divulging my enjoyment at running over pigeons, I got a chance to talk about sex, blood, the blind, writing, rabbit-heads and other topics from The Vision Revolution.
Recently I was interviewed by Pouria Nazemi, Science Editor of the Jam-e-Jam Daily Newspaper. Jam-e-Jam is the principal Iranian newspaper and is controlled by the government. In the wake of Iran shutting down its leading business newspaper last week and three pro-reform newspapers in October I thought this would be interesting to readers, since it appeared between these two events.
If your Farsi is up to par, here is the link (and pdf version here). The interview was done via email in English so I have corrected some minor grammar but otherwise it is as we corresponded. This originally appeared in English at ScientificBlogging.com .
By the way, before the piece appeared I didn’t realize that Jam-e-Jam was a major newspaper in Iran, much less the state-run newspaper. To my ears, and given that I do not know Farsi, the name sounds “light”, reminiscent of BoingBoing. Do not take this piece as an endorsement of the dictatorship!
Pouria Nazemi : Cognitive science is a new science that we hear more about every day. Can you briefly describe what it is?
Mark Changizi : Cognitive Science likes to define itself at the intersection of many disciplines, including psychology, neuroscience, linguistics, philosophy and computer science. But, in reality, you’d be hard pressed to pin us down. …other than to say that we’re all interested in understanding the principles underlying thinking, seeing, and other complex brain powers.
Pouria Nazemi : The brain is an amazing thing. We understand the world around us using it but how much do we know about brain itself?
Mark Changizi : Not much – in fact, I wrote a recent blog story titled “We don’t know jack” (Does that translate well?!). There are many avenues for being pessimistic about what we know – or don’t know – about the brain, but one that I often focus on is our powers, or functions. If some alien stumbled upon a calculator or a stapler, would you say that the alien understood these artifacts if the alien did not know that calculators are for math and staplers are for binding paper together? The aliens can take apart, catalog, and watch the workings of calculators and staplers for eternity, and if they haven’t figured out their function, we will be confident they haven’t come to understand them.
We’re in a similar situation as these aliens for our brains. We’ve had significant successes in taking apart the brain and watching its mechanistic workings, but the problem is that much of what our brain can do – most of the functions it is capable of carrying out – are simply not known by us. We’ll be in a good position to make sense of all our mushy meat only when we have a good idea about the functions the meat was selected to implement. And in order to do that, we have to study the human animal in a more ecological setting – that is, we must understand not just the brain, but the complexity of the environment for which it evolved, and how the brain (and body) fit the environment (often) like a glove. For example, my own research often focuses on showing that we have powers no one has noticed. You can be sure that if I’m finding new powers, then there must be tens of thousands more!
Pouria Nazemi: According to Scientific American : “Although many neuroscientists are trying to figure out how the brain works, Mark Changizi is bent on determining why it works that way”; so do you think we can learn why the brain works by having a better understanding of its structure?
Mark Changizi : Another way of saying the same thing is that I want to reverse-engineer the brain. That’s what evolutionary types like me aim to do: figure out the principles governing our “design”.
Pouria Nazemi : When I read about you I find that you have many interesting experiments and theory from writing systems to optical illusions and similarity of brain and highway systems. So what is the main goal of your research in these categories?
Mark Changizi : The research on writing systems asks why our brains, which do not have areas specialized for reading, can read so well. Could it be that the symbols and letters used in writing systems have culturally evolved over time to have the shapes our visual brains are innately good at processing? And, what is our visual brain good at processing? The shapes from nature, in particular from objects strewn about in a three-dimensional world. Could letters have come to look like nature, explaining why we’re such capable readers? In fact, that’s what I found: the contour conglomerations found in natural scenes tend to be the same ones found in human writing.
The brain and highway systems research comes from earlier work of mine trying to explain why brains change in the way they do from mouse to whale. My research shows that much of the anatomical changes that occur as brains increase in size (and there are a lot) can be explained by brains “trying” to maintain a fixed level of total-brain interconnectivity. It struck me more recently that cities have some similarities to the cortex: cities lie on the surface of the Earth and the cortex is a flattenable sheet; highways serve a similar role to white-matter-projecting neurons in the cortex; and highway exits a similar role to synapses. With my understanding of brain scaling in hand, I wondered the extent to which city highway systems scale similarly to the brain as a function of size. To my surprise, there were deep similarities in the scaling laws.
Another major research direction concerns color vision, where I have shown that our kind of color vision is nearly optimal for detecting oxygenation changes in blood under the skin. That is, I have been able to provide evidence that color vision is for seeing the emotions and other socio-sexual signals on the faces (and rumps) of others.
Is there anything tying my research together? Yes and no.
“Yes,” in that I tend to focus on “design principles,” i.e., on the fundamental engineering principles explaining why it would have evolved in the first place. I also bring a similar style to my research directions, aiming for broad unifying theories, ones that are rigorous, ones that can be tested, and ones where I can actually do test. (Rather than many physics journals, say, which publish biological theories without any data.)
But, “no,” in the sense that I do not try to build an incremental program of research. I have always actively tried to remain aloof from previous research problems, and from research communities, so that I am psychologically open to stumbling onto new ideas. Thus the crazy suite of research directions I am embarrassed to admit to.
Pouria Nazemi : One of the most interesting things is your research about the brain’s ability to see into the future (1/10th second) so would you please explain more about that and if it is an ability we can hope to develop?
Mark Changizi: Well, you can’t actually see into the future. The point is that your brain has to anticipate a tenth of a second into the future – and generate a perception of it – because by the time it is done with its anticipating, a tenth of a second has elapsed, and so the anticipated future is of the present. That is, in order to at all times try to perceive the world as it is at that time – to “perceive the present” – the brain has to anticipate the near future.
My contribution here was to show how this simple idea is sufficiently rich that whole swathes of illusions can be explained as cases where the brain incorrectly anticipates the future.
Pouria Nazemi : many of us enjoy optical illusions. You are studying illusions as a way to understand how our brain works. I think illusions are the result of some error in our mind. Would you please explain more about how these tricks tell us about our brain.
Mark Changizi: Let me explain one specific case, the Hering illusion shown below, where the two vertical lines are parallel but appear to bow out. Radial lines like those in the illusion do occur very often in real life, in particular whenever you move forward. At these times, the objects in the world flow outward in your visual field away from a center point. In fact, they even often blur on your retina, because your retina is not an infinitely fast “camera”. So, when you fixate on the illusion, your brain sees all those lines emanating from that center point, and says, “When I usually see this kind of radial blur stimulus, it is because I’m moving forward in the direction of the center point.” (I don’t actually mean your brain is saying this! I only mean it has evolved to have mechanisms that figure out where the observer is headed on the basis of blur cues like this.)
Now the brain has a good guess as to where it is headed. Recall that it takes about a tenth of a second to build a perception from the retinal stimulation. The brain wants to generate a perception of the two vertical lines not as they actually projected onto the retina, but as how they will project a tenth of a second later, after the observer has moved forward toward the center a little bit. Think about how the look of two vertical poles, or the sides of a doorway, change their shape as you move forward. When far away they appear vertical in your visual field. But as you near them, to pass between them, they flow outward in your visual field, but do so most quickly at eye level. To see this, imagine walking through a tall cathedral doorway, where when you are close, the upper parts of the door look like they are approaching one another up in the sky (like railroad tracks). That is, when you move forward through a doorway, the sides of the doorway bow outwards in your visual field, just like you perceive the vertical lines in the illusion. You perceive them that way because that is how they would project in the next moment were you moving in the direction your brain has been tricked into thinking it is going. Of course, it is being tricked in this case, so it counts as an illusion. But in real life it typically encounters such radial-line stimuli only when it actually is moving forward toward the center, as I mentioned above.
Pouria Nazemi : Would you please explain about these categories of illusions?
Mark Changizi: The same explanation I just gave concerning the Hering illusion turns out to radically generalize. Radial lines are just one of seven cues I was able to identify for where the observer may be headed in the next moment. And it is not just the visual geometries that can distort in the next moment if you are moving forward; this is just one of four qualities that can distort in the next moment (the others concern speed, brightness contrast, and distances to objects). That is, I eventually realized that the explanation above extended to a 7 by 4 table of 28 predictions, the Hering-type classical geometrical illusions falling in just one of these 28 slots. And I provided evidence that the pattern of illusions predicted by this unified account was, in fact, the case.
Pouria Nazemi : Your recent well-received Book “The Vision Revolution” (that I didn’t have chance to get but would very much like to do) also is about our vision. Would you please tell us about the main focus of this book?
Mark Changizi: The book is about four “powers” of vision. Color vision is for sensing emotion, not for seeing fruit as it has been argued. Forward-facing eyes evolved for seeing better in cluttered forest environments, not for stereo-3D vision as it is usually argued. Illusions are the brain’s (failed) attempt at seeing the future…in order to perceive the present. And letter shapes have culturally evolved to look like nature, turning ancient illiterate visual areas in the brain into capable reading machines.
Pouria Nazemi : We understand our world by our brains. There is nothing out there that we can understand without our brains. Also, we know that our brain sometimes (like in optical illusions) have misunderstandings. Is it possible that some parts of the world that we think we understand are really the result of such misunderstanding? I mean, how we can talk about reality if each brain is that object that determines what reality is?
Mark Changizi: Our brain was selected to provide perceptions that help us survive and reproduce, whether or not those perceptions actually gave us a more objective view of our real universe. The brain could, instead, give us perceptions that are “useful fictions” (which is the term people often use). However, very often the most useful perception to have is the one that actually does truthfully represent the world. As liars know, it takes a lot of work to string together lies in such a way that there are not contradictions. And often the best way to predict the world and not get eaten is to see the world as it is. So much of what we experience is veridical. But not all. For example, as I discuss in The Vision Revolution, color (colors are not out there), stereo vision (we see a single view from a perspective where we have no eye), and illusions (we see a guess) are all cases where useful fictions are at work.
Pouria Nazemi : Your new study show similarity between human brains and highway systems. How can man-made structures can be similar to our brain that evolved during millennia?
Mark Changizi: The idea is that, in each case, there is selection pressure shaping the organization. For the brain it is natural selection, which consists mostly of lots and lots of animals being eaten. For cities, although being eaten does sometimes make the news, the selection pressure is mostly due to multitudes of political and economic forces over many decades, which serve to slowly “push” a city to have a more efficiently functioning highway design.
Pouria Nazemi : Is it possible that someday we can map our brains and understand completely how it works? And, if yes, how long will it take and what our the challenges along the way?
Mark Changizi: Yes. And I’d say hundreds of thousands of years, optimistically. Sorry for the pessimism. I mentioned some of the difficulties above. Another way to put things in context is to consider Caenorhabditis elegans, a little roundworm with 302 neurons, with about a thousand connections, and where we have nearly a “God’s eye view”. It is the most well understood organism on Earth, if not the universe. Despite everything we know about its details, we are a very long way from really understanding how the neural network relates to the complex sets of behaviors it carries out. (Probably because, I would say, we don’t completely understand its behavior.) Our brain has a wee bit more neurons than 302, and is the most complicated machine in the universe. We’re in for a long haul.
Pouria Nazemi : If such a thing happens, everything would change because we could program brains to do many different things. Can you tell us more about the effects of such theoretical mapping in human life?
Mark Changizi: As for programming brains, I have actually thought about that. I wondered whether it may be possible to create images that provoke the visual system to carry out computations. Our visual system would be the hardware, the image would be the software, and the output of the hardware when run on the software would be our perception itself. Why not put our visual brain to work, making it do complicated calculations, and yet it wouldn’t feel like work to us, because all those visual computations are done unconsciously? So I created a class of stimuli called “visual circuits” that can do this, albeit not very well at this point. Here is a Wired story on the research… http://www.wired.com/wiredscience/2008/07/scientists-sugg/
Pouria Nazemi : What is the next step in your studies?
Mark Changizi: For the last year or two I have been studying the origins of language and music. Like letters, I believe that the sounds of speech, and the sounds of music, culturally evolved to sound like nature. Too much to this story to get into here, but they will be the subject of my third book which I hope to finish by the end of the year: HARNESSED: How Language and Music Mimicked Nature and Transformed Ape to Man.