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I spoke at TED in NYC in December of 2012 on my grand unified theory of illusions. For more information, see my earlier book, The Vision Revolution. (For those with a strong stomach, see this journal article.)

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Mark Changizi is Director of Human Cognition at 2AI, a managing director of O2Amp, and the author of HARNESSED: How Language and Music Mimicked Nature and Transformed Ape to Man and THE VISION REVOLUTION. He is finishing up his new book, HUMAN 3.0, a novel about our human future, and working on his next non-fiction book, FORCE OF EMOTION.

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The O2Amp amplifies perception of emotions, moods and health. Really.

One of the “7 Major Health Innovations of 2012 that Matter”.

And, no, they’re not merely tinted glasses. …gray (non-pink) versions coming soon.

O2Amps by 2AI

As seen in TIME Magazine, Technology Review, and WIRED, the world’s first eyewear designed to enhance the visibility of blood beneath the skin, giving doctors, nurses and other medical personnel a clearer view of vasculature, oxygenation, and trauma.

The O2Amp furnishes superior powers of clinical assessment and diagnosis, better visualizations for procedures and blood work, and is a central piece of medicine’s next-generation toolkit. Eye protection, but with an enhanced perception of health.

Comfortably wear it all day, or quickly pull it out as needed, whether it’s emergency medicine, surgery, dermatology, neonatology or elsewhere.

“It looks like my vision is compensated with Photoshop,” says neurosurgeon Dr. Kei Nomura, Chief of Center for Brain and Spine Surgery, Aoyama General Hospital.

We at 2AI Labs are excited to have our first spin-off company, O2Amps, the home of our patented eyewear and light filtering technology that amplifies one’s view of the emotions and health visible in the color and pallor of other people’s skin.

The technology comes out of my research while at Caltech on the evolution of color vision in primates, where I provided evidence that color vision evolved to sense oxygenation modulations in the hemoglobin under the skin. Once one understands the connection between our color vision and blood physiology, it’s possible to build filters that further amplify our perception of the blood and the signals it provides (a patented invention by myself and my co-director, Tim Barber).

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Because color vision evolved for everyday wear, so to speak, one of our largest markets is for everyday-wear sunglasses, to enhance one’s perception of the emotion, mood and health signals we evolved to detect with our color vision. For example, typical sunglasses shade the world but also end up shading one’s connections to other people; this is exemplified by the way people tip up their sunglasses to get a better look at someone. Our technology shades the world but not the social; for the O2Amps, one sees other people better by keeping them on, rather than tipping them up.

There are also applications in security, sports, poker, and dating. (See projects in development.)

And there are applications in medicine, which is where we believe we can make the greatest impact. In fact, for medicine we have developed three different technologies, and they can be described as…

– (i) Oxy-Iso: An oxygenation-isolator that amplifies perception of oxygenation modulations under the skin (and eliminates perception of variations in the concentration of hemoglobin),

– (ii) Hemo-Iso: A trauma-detector, or hemoglobin-concentration-isolator, that amplifies perception of hemoglobin concentrations under the skin (and eliminates perception of variations in oxygenation), and

– (iii) Oxy-Amp: A general clinical enhancer, or oxygenation-amplifier, that combines the best features of the first two; it eliminates neither signal (i.e., it retains perception of both variation in hemoglobin oxygenation and concentration), and only amplifies perception of oxygenation. It provides a strict enhancement to exactly the thing primate color vision evolved to sense.

We’ve received great interest from medical professionals interested in trying out the O2Amp, and we’re moving now to get them in hospitals and among clinical staff everywhere.

We’re also moving into lighting, where entire spaces can be filled with the same filtered light. …no eyewear needed.

We believe our Oxy-Amp is the new starting point for lens blanks.

Colorblind folk have found that the Oxy-Iso provides a big help for their red-green blindness.

See the O2Amp site for all our projects in development.

Note that good light is needed for the technology, by which we mean outdoor lighting or a head lamp.

Some useful links:
- The start-up for this technology… o2amp.com
- Video from Daily Planet television show, Discovery Channel.
- ABC News’ This Could Be Big Television.
- Introductory video (by filmmaker Emon Hasson)… Intro video
- Some testimonials… Testimonials
- More testimonials
- What one sees… Illustration, Description
- Train yourself… in five steps (text only version).
- The research article on the evolution of color vision… Journal article

Some of the press interest in o2amp.com:
MSNBC, Sciencebase, Tech Rev, Betabeat, PopSci, ExameInformatica, Smithsonian, LiveScience/Yahoo, WIRED, NZ Herald, Investors, DesignBoom, Mobiledia, Discovery, PSFK, Neoteo, Earthsky, Good, Wissenundkonzepte, Stuff, Forbes, Actualidad, Geek, Gizmodo, PSFK, Neatorama, TIME, Oprah, BBC, DarkDaily; Lost At E Minor, ZenniOptical. Prevention Magazine, Scientific American / Txchnologist, Slashdot, Diffusion Radio, io9, The Times UK [subscription], BBC, Discovery News, Daily Mail UK, New Scientist, Smart Planet, CBC, Unexplained Mysteries, Telegraph, Voice of Russia, Geek Chic Mama, NY Daily News, GizMag, The Argus, Elite Daily, Columbia Chronicle, Under the Gun, Today, PopSci,
ABC News’ This Could Be Big.

Also, listed as one of the “7 Major Health Innovations of 2012 that Matter”.

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Mark Changizi is Director of Human Cognition at 2AI, and the author of Harnessed: How Language and Music Mimicked Nature and Transformed Ape to Man and The Vision Revolution. He is finishing up his new book, HUMAN 3.0, a novel about our human future.

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You’ve heard that space is curved – that’s gravity. You’ve also been told that you cannot really understand curved space. Sure, you can come to know curvy mathematics by studying general relativity or differential geometry, but you cannot grasp curved space in your bones…for the obvious reason that, in our everyday human-level world, space is flat, and so we have a brain for thinking flat.

Or, at least, that’s what they say.

But there is at least one variety of curvy mathematics that your brain comprehends so completely that you don’t even know you know it. It concerns your visual field, and your innate understanding of the directions from you to all the objects in your environment.

In thinking about your visual field, it is best to imagine a sphere around your head, recording the directions to all objects in one’s environment. Call it the “projection sphere,” since it records in which directions objects project light toward us.

So, if you are standing in front of a row of six vertical poles, then they will project onto your sphere as shown below. In this figure, one imagines that you, the observer, are at the center of the sphere, looking in the direction of the cross.

Consider now the way these poles project…

First, notice that each pole appears straight in your visual field. They are not straight in the figure above, but remember that the observer in the figure is at the center of the sphere looking out. Each pole is straight on this projection sphere — and thus in your visual field — because each is what is called a “great circle,” extending in this case from the bottom to the top of the sphere like lines of longitude.

Second, observe that the poles are parallel to one another at the equator.

Yet, despite being straight lines that are parallel to one another, they intersect! Namely, the lines intersect at the top and bottom of the sphere.

Can this really be?

It can really be, and it is possible because of the non-Euclidean nature of the geometry of the visual field.   The geometry that is appropriate for the visual field is the surface of a projection sphere, and the surface of a sphere is not flat / Euclidean, but, well, spherical.

There are three main kinds of geometry for space: elliptical (including spherical), Euclidean (or flat), and hyperbolic.  How does one tell them apart? One way is to simply measure the sum of the angles in a square drawn in that space.

In Euclidean geometry, the sum of the angles in a square is 360 degrees. But for elliptical geometry the sum adds up to more than 360 degrees. In hyperbolic geometries, on the other hand, the sum comes to less than 360 degrees.  Back to the visual field, then, let’s “draw” a square on it and sum up its angles.

The figure above shows a square in your visual field. Why does it count as a square? Because (i) it has four sides, (ii) each side is a straight line (being part of a great circle), (iii) the lines are the same length, and (iv) the four angles are the same.

Although it is a square, notice that each of its angles is larger than 90 degrees, and thus the square has a sum of angles greater than 360 degrees.  The visual field is therefore elliptical, and spherical in particular.

One does not need to examine figures like those above to grasp this. If you are inside a rectangular room at this moment, look up at the ceiling. The ceiling projects toward you as a four-sided figure. Namely, you perceive its four edges to project as straight lines. Now, ask yourself what each of its projected angles is. Each of its angles projects toward you at greater than 90 degrees (a corner would only project as exactly 90 degrees if you stood directly under it).

Thus, you are perceiving a figure with four straight sides, and where the sum of the angles is greater than 360 degrees.

Your visual field conforms to an elliptical geometry!

(The perception I am referring to is your perception of the projection, not your perception of the objective properties. That is, you will also perceive the ceiling to objectively, or distally, be a rectangle, each angle having 90 degrees. Your perception of the objective properties of the ceiling is Euclidean.)

It is often said that non-Euclidean geometry, the kind needed to understand general relativity, is beyond our everyday experience, since we think of the world in a Euclidean manner. While we may think in a Euclidean manner for our perception of the objective lines and angles, our perception of projective properties — i.e., the directions from us to the world around us — is manifestly non-Euclidean, namely spherical.

We do have tremendous experience with non-Euclidean geometry, it is just that we have not consciously noticed it. But once one consciously notices it, it is possible to pay more attention to it, and one then sees examples of non-Euclidean geometry at every glance.

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This piece was adapted from my book, The Brain from 25000 Feet (Kluwer), and first appeared so adapted at Sept 30, 2010, in Science 2.0.

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Mark Changizi is Director of Human Cognition at 2AI, and the author of The Vision Revolution (Benbella Books) and the upcoming book Harnessed: How Language and Music Mimicked Nature and Transformed Ape to Man (Benbella Books).

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Daniel Lende from PLoS Blogs’ Neuroanthropology recently interviewed me about the relationship between culture, brain and nature, and the origins of language. See the interview here.

In my view, anthropology — and evolution and culture — are crucial to understanding neuroscience and our origins. …and so their “Neuroanthropology” blog (also by Greg Downey) will be one I follow closely.

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This first appeared on January 10, 2010, as a feature at ScientificBlogging.com.

Joggers love their head phones. If you ask them why, they’ll tell you it keeps them motivated. The right song can transform what is by all rights an arduous half hour of ascetic masochism into an exhilarating whirlwind (or, in my case, into what feels like only 25 minutes of ascetic masochism).

Music-driven joggers may be experiencing a pleasurable diversion, but to the joggers and bikers in their vicinity, they’re Tasmanian Devils.

In choosing to jog to the beat of someone else’s drum rather than their own, headphoned joggers have blinded themselves to the sounds of the other movers around them. Headphones don’t prevent joggers from deftly navigating the trees, stumps, curbs, and parked cars of the world because these things can be seen as one approaches. But when one moves in a world with other movers, things not currently in front of you can quickly come to be in front of you. This is where the headphoned jogger stumbles … and crashes into the crossing jogger, passing biker, or first-time tricycler.

These music-filled movers may be a menace to our streets, but they can serve to educate us all about one of our underappreciated powers: using sound alone, we know where people are around us, and the nature of their movement. I’m sitting in a coffee shop as I write this, and when I close my eyes I sense the movement all around me: a clop of boots just passed to my right; a jingling-key person just walked in front of me from my right to my left, and back; and a pitter patter of a child just meandered way out in front of me. I sense where they are, their direction of motion, and their speed. I also sense their gait, such as whether they are walking or running. And I can often tell more than this, such as a brisk versus shuffling walk, an angry stomp versus a happy prance, or even a complex behavior, like turning and stopping to drop a dirty tray in a bin, slowing to open a door, or reversing direction to get a forgotten coffee. My auditory system carries out these mover-detection computations even when I’m not consciously attending to them. That’s why I’m difficult to sneak up on (although they keep trying!), and that’s why I only rarely find myself saying, “How long has that cheerleading squad been doing jumping jacks behind me?!” That almost never happens to me because my auditory system is keeping track of where people are and roughly what they’re doing, even when I’m otherwise occupied.

We can now see why joggers with their ears unencumbered by headphones almost never crash into feral dogs or runaway wheelchaired grandpas: they may not see the dog or grandpa, but they hear their movement through space, and can dynamically modulate their running to avoid both, and be merrily on their way. Without headphones, joggers are highly sensitive to the sounds of cars, and can track their movement: that car is coming around the bend; the one over there is reversing directly toward me; the one above me is falling; and so on. Headphoned joggers, on the other hand, have turned off their movement-detection system, and should be passed with caution! And although they are a hazard to pedestrians and cyclists, the people they put at greatest risk are themselves. This is because where there are joggers there are often cars nearby, and in collisions between a jogger and an automobile, automobiles typically only need a power-wash to the grill.

How does your auditory system serve as a movement tracking system? In addition to sensing whether a mover is to your left or right, in front or behind, and above or below – something that depends on the shape, position and number of ears you have – you possess specialized auditory software that interprets the sounds of movers and generates a good guess as to the mover’s movement through space. Your software has evolved to give you four kinds of information about a mover: (i) his distance from you, (ii) his directedness toward you, (iii) his speed, and (iv) his behavior or gait. How, then, does your auditory system infer these four kinds of information?

Evidence suggests that (i) distance is gleaned from loudness, (ii) directedness toward you can be cued by pitch (due to subtle but detectable Doppler shifts), (iii) speed is inferred by the number of footsteps per second, and (iv) behavior and gait are read from the pattern of footsteps. Four fundamental parameters of human movement, and four kinds of auditory cue: (i) loudness, (ii) sound frequency, (iii) step rate, and (iv) gait pattern.

Your auditory system has evolved to track these cues because of the supreme value in knowing where and what everyone is doing nearby.

This is where things get interesting… Even though joggers without headphones are not listening to music, their auditory systems are listening to fundamentally music-like constituents. Consider the four auditory movement cues mentioned just above (and shown on the right of Figure 2). Loudness? That’s just pianissimo versus piano versus forte and so on. Sound frequency? That’s roughly pitch. Step rate? That’s tempo. And the gait pattern? That’s akin to rhythm and beat. The four fundamental auditory cues for movement are, then, awefully similar to (i) loudness, (ii) pitch, (iii) tempo, and (iv) rhythm.

These are the most fundamental ingredients of music, and yet, there they are in the sounds of human movers. The most informative sounds of human movers are the fundamental building blocks of music!

The importance of loudness, pitch, tempo and rhythm to both music and movement is, I believe, more than a coincidence. The similarity runs deep – something speculated on ever since the Greeks. Research in my lab has been providing evidence that music is built not just with the building blocks of movement, but is actually organized like movement, thereby harnessing our movement-recognition auditory mechanisms. The story this leads to for music is this: Music has been culturally selected to sound like people moving, just the kinds of sounds your auditory system evolved to be great at processing. …and just the kinds of sounds that can possess emotional content that makes music evocative and worth listening to.

Music is evocative because it is made with people, something I also wrote about here [ http://bit.ly/rcKVh ], and something I will discuss further in the future.

Headphoned joggers, then, aren’t merely missing out on the real movement around them – they pipe into their ears a fictional movement, making them even more hazardous than a jogger wearing earplugs.

Mark Changizi is a professor of cognitive science at Rensselaer Polytechnic Institute, and the author of The Vision Revolution (Benbella Books).


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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“.

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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.

Changizi

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.

BenchFly: Your book presents theories on questions ranging from why our eyes face forward to why we see in color.  Big questions.  As a kid, was it your attraction to the big questions that drew you into science?

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.

Tell us a little about both the scientific and thought processes when tackling questions that are very difficult to actually prove beyond a shadow of a doubt.

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.

In basic research we are often hyper-focused on the details.  To understand a complex problem, we start very simple and then assume we will eventually be able to assemble the disparate parts into a single, clear picture.  In essence, you think about problems in the opposite direction- asking the big questions up front.  Describe the philosophical difference between the two approaches, as well as their relationship in the process of discovery.

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.

In explaining why we see in color, you suggest that it allows us to detect the subtleties of complex emotions expressed by humans – such as blushing.  Does this mean colorblind men actually have a legitimate excuse for not understanding women?!

…..to see my answer, and the rest of the interview, go to Benchfly.

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Have you ever noticed that Santa’s rosy cheeks are visible despite his furry face? It is as if his facial hair “purposely” keeps out of the way of his color signals. I have argued in my research that some of us primates evolved bare faces (and rumps) in order to color signal. In fact, our color vision appears to be optimized for sensing these blood-modulated color signals. I talk about this in detail in Chapter 1 of The Vision Revolution, and you can also find a variety of pieces related to this on my ChangiziBlog.

Santa's rosy cheeks are not obscured by his beard.

In this light, here is an excerpt from a piece Roger Highfield wrote about Santa’s beard before he became editor of New Scientist.

Research by Dr Mark Changizi of America’s Rensselaer Polytechnic Institute has suggested that we may have evolved our particular brand of colour vision to discriminate between slight changes in skin tone due to blushing, rage and blanching.

A survey of our primate relatives suggests that this kind of vision is only found in those with bare faces, such as humans, and is tuned precisely to detect changes in skin tone.

But even a beard as luxuriant as Santa’s should not hinder his ability to send out a colour signal, such as a healthy glow. After all, says Dr Changizi, we could have evolved to sprout hair anywhere – for example, on the cheeks, forehead and nose, which are the first areas to go red.

“But facial hair doesn’t end up there,” he points out. “You can really appreciate what beards don’t do by looking at men with the condition of hypertrichosis, when their faces are covered with hair.

“In terms of Father Christmas, note how the songs mention his rosy cheeks. Even Santa can colour-signal, despite his facial hair, because evolution has made sure that his beard and moustache got out of the way.”

See the entire piece here.  Roger Highfield has a book about the science of Christmas, in fact: Can Reindeer Fly?: The Science of Christmas (Orion).

Merry Christmas!

Mark Changizi is a professor of cognitive science at Rensselaer Polytechnic Institute, and the author of The Vision Revolution (Benbella Books).

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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.

Late Night Live

Late Night Live

Check out the segment here. (Download the mp3.)

Mark Changizi is a professor of cognitive science at Rensselaer Polytechnic Institute, and the author of The Vision Revolution (Benbella Books).

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This first appeared on November 16, 2009, as a feature at ScientificBlogging.com

No one draws pictures of heads with little gears or hydraulics inside any more. The modern conceptualization of the brain is firmly computational. The brain may be wet, squooshy, and easy to serve with an ice cream scooper, but it is nevertheless a computer.

However, there is a rather blaring difficulty with this view, and it is encapsulated in the following question: If our brains are computers, why doesn’t size matter? In the real world of computers, bigger tends to mean smarter. But this is not the case for animals: bigger brains are not generally smarter. Most of the brain size differences across mammals seem to make no behavioral difference at all to the animal.

Instead, the greatest driver of brain size is not how smart the animal is, but how big the animal is. Brain size doesn’t much matter – instead, it is body size that matters. That is not what one would expect of a computer in the head. Brain scientists have long known this. For example, take a look at the plot below showing how brain mass varies with body mass. You can see how tightly correlated they are. If one didn’t know that the brain was the thinking organ and consequently lobbed it into the same pile as the liver, heart and spleen (FYI, I keep my pile of organs in the crawl space), then one would not find it unusual that it increases so much with body size. Organs do that.

But the brain is supposed to be a computer of some strange kind. And yet it is acting just like a lowly organ. It gets bigger merely because the animal’s body is bigger, even though the animal may be no smarter. The plot below, from a 2007 article of mine (in Kaas JH (ed.) Evolution of Nervous Systems. Oxford, Elsevier) shows how behavioral complexity varies with brain mass. There is no correlation. Bigger and bigger brains, and seemingly doing nothing for the animal!

It has long been clear to neuroscientists that what does correlate nicely with animal intellgence is how high above the best-fit line a point is in the brain-versus-body plot we saw earlier. This is called the encephalization quotient, or EQ. It is simply a measure of how big the brain is once one has controlled for body size. EQ matches our intuitive ranking of mammalian intelligence, and in a 2003 paper (in the Journal of Theoretical Biology) I showed that it also matches quantitative measures of their intelligence (namely, the number of items in ethograms as measured by ethologists). The plot is shown below, where you can see that the number of behaviors in each of the mammalian orders rises strongly with EQ.

But although this is well known by neurobiologists, there is still no accepted answer to why brains get bigger with body size. Why should a cow have a brain 200 times larger than a roughly equally smart rat, or 10 times larger than a clearly-smarter house cat? One of my older research areas, in fact, aimed to explain why brains change in the ways they do as they grow in size from mouse to whale (http://www.changizi.com/changizi_lab.html#neocortex), and yet, embarrassingly, I have no idea why these brains are increasing with body size at all. If a dull-witted cow could just stick a tiny rat brain into its head and get all the behavioral complexity it needs, then brains would come in just one size, and I would have had no research to work on concerning the manner in which brains scale up in size.

So, here’s a plan. I would like to hear your hypotheses for why brains increase so quickly with body mass (namely as the 3/4 power). I will let you know if the idea is new, and I will see if I can give your idea a good thrashing. What’s at stake here is our very framework for conceptualizing what the brain is. Perhaps you can say why it is a computer, and that greater body size brings in certain subtle computational demands that explain why brain volume should increase as it does with body mass. Or, more exciting, perhaps you can propose an altogether novel framework for thinking about the brain, one that makes the enigmatic “size matters” issue totally obvious.

To the comments!…

This is where the fun of the piece begins, because at ScientificBlogging.com there were more than 70 comments, all quite productive (no trolls). So, go here and scroll down to the comments.  …and leave one!

Mark Changizi is a professor of cognitive science at Rensselaer Polytechnic Institute, and the author of The Vision Revolution (Benbella Books).

o one draws pictures of heads with little gears or hydraulics inside any more. The modern conceptualization of the brain is firmly computational. The brain may be wet, squooshy, and easy to serve with an ice cream scooper, but it is nevertheless a computer.
However, there is a rather blaring difficulty with this view, and it is encapsulated in the following question: If our brains are computers, why doesn’t size matter? In the real world of computers, bigger tends to mean smarter. But this is not the case for animals: bigger brains are not generally smarter. Most of the brain size differences across mammals seem to make no behavioral difference at all to the animal.

Instead, the greatest driver of brain size is not how smart the animal is, but how big the animal is. Brain size doesn’t much matter – instead, it is body size that matters. That is not what one would expect of a computer in the head. Brain scientists have long known this. For example, take a look at the plot below showing how brain mass varies with body mass. You can see how tightly correlated they are. If one didn’t know that the brain was the thinking organ and consequently lobbed it into the same pile as the liver, heart and spleen (FYI, I keep my pile of organs in the crawl space), then one would not find it unusual that it increases so much with body size. Organs do that.

But the brain is supposed to be a computer of some strange kind. And yet it is acting just like a lowly organ. It gets bigger merely because the animal’s body is bigger, even though the animal may be no smarter. The plot below, from a 2007 article of mine (in Kaas JH (ed.) Evolution of Nervous Systems. Oxford, Elsevier) shows how behavioral complexity varies with brain mass. There is no correlation. Bigger and bigger brains, and seemingly doing nothing for the animal!

It has long been clear to neuroscientists that what does correlate nicely with animal intellgence is how high above the best-fit line a point is in the brain-versus-body plot we saw earlier. This is called the encephalization quotient, or EQ. It is simply a measure of how big the brain is once one has controlled for body size. EQ matches our intuitive ranking of mammalian intelligence, and in a 2003 paper (in the Journal of Theoretical Biology) I showed that it also matches quantitative measures of their intelligence (namely, the number of items in ethograms as measured by ethologists). The plot is shown below, where you can see that the number of behaviors in each of the mammalian orders rises strongly with EQ.

But although this is well known by neurobiologists, there is still no accepted answer to why brains get bigger with body size. Why should a cow have a brain 200 times larger than a roughly equally smart rat, or 10 times larger than a clearly-smarter house cat? One of my older research areas, in fact, aimed to explain why brains change in the ways they do as they grow in size from mouse to whale (http://www.changizi.com/changizi_lab.html#neocortex), and yet, embarrassingly, I have no idea why these brains are increasing with body size at all. If a dull-witted cow could just stick a tiny rat brain into its head and get all the behavioral complexity it needs, then brains would come in just one size, and I would have had no research to work on concerning the manner in which brains scale up in size.

So, here’s a plan. I would like to hear your hypotheses for why brains increase so quickly with body mass (namely as the 3/4 power). I will let you know if the idea is new, and I will see if I can give your idea a good thrashing. What’s at stake here is our very framework for conceptualizing what the brain is. Perhaps you can say why it is a computer, and that greater body size brings in certain subtle computational demands that explain why brain volume should increase as it does with body mass. Or, more exciting, perhaps you can propose an altogether novel framework for thinking about the brain, one that makes the enigmatic “size matters” issue totally obvious.

To the comments!…

Comments

It seems to me that total brain mass vs. Body size doesn’t account for different parts of the brain.
Intellegence seems to me to be more related to the percentage of brain mass dedicated to the the Frontal cortex vs the total brain mass. Larger Animals may have need for more brain mass to process more nerve receptors in the larger amount of skin for example, or dedicated to processing Smell. But the part of the brain dedicated to higher level functions may be smaller by some measure (either total mass, or percentage of the rest of the brain mass, etc.)

Mark Changizi's picture

Hi Chuck

“to process more nerve receptors in the larger amount of skin”
Nice. That’s one common hypothesis. And not only more skin and thus more sensory receptors, but more musculature, and so on. But *that* would seem to imply that bigger mammals should have disproportionately larger somatosensory and motor areas, but they don’t.

“dedicated to processing Smell”
But why should larger animals need bigger olfactory neural tissue?

The motor processing functions of an animals brain may be proportionate, but the brain as a whole has to take the total motor processing input and output into account; when you are large and have a complex environment to deal with, you need a concordantly larger brain to deal with it.

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I was on the Lionel Show / Air America this morning, which was a blast!  Got to talk about my recent book, and about evolution, autistic savants, intelligent design, color, forward-facing eyes, illusions, and more. I really must get off the elliptical machine next time I do a radio show. Here’s the segment with me (or mp3 on your computer).

Mark Changizi is a professor of cognitive science at Rensselaer Polytechnic Institute, and the author of The Vision Revolution (Benbella Books).

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