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Archive for the ‘Brain’ Category

I’ve argued there’s no imminent singularity, and I’ve thrown water on the idea that the web will become smart or self-aware. But am I just a wet blanket, or do I have a positive vision of our human future?

I have just written up a short “manifesto” of sorts about where we humans are headed, and it appeared in Seed Magazine. It serves not only as guidepost to our long-term future, but also one for how to create better technologies for our brains (part of the aim of the research institute, 2ai, I co-direct with colleague Tim Barber).

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Mark Changizi is Director of Human Cognition at 2AI, and the author of The Vision Revolution (Benbella Books, 2009) and the upcoming book Harnessed: How Language and Music Mimicked Nature and Transformed Ape to Man (Benbella Books, 2011).

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Jeremy Hsu recently interviewed me for a piece in LiveScience (picked up at MSNBC and Yahoo) about brain evolution and its relationship to the prospects for AI.  His piece was in reaction to a Brain, Behavior and Evolution piece I wrote, and also to the following featured SB piece I wrote…

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There are currently two ambitious projects straddling artificial intelligence and neuroscience, each with the aim of building big brains that work. One is The Blue Brain Project, and it describes its aim in the following one-liner:

“The Blue Brain Project is the first comprehensive attempt to reverse-engineer the mammalian brain, in order to understand brain function and dysfunction through detailed simulations.”

The second is a multi-institution IBM-centered project called SyNAPSE, a press release which describes it as follows:

“In an unprecedented undertaking, IBM Research and five leading universities are partnering to create computing systems that are expected to simulate and emulate the brain’s abilities for sensation, perception, action, interaction and cognition while rivaling its low power consumption and compact size.”

Oh, is that all!

The difficulties ahead of these groups are staggering, as they (surely) realize. But rather than discussing the many roadblocks likely to derail them, I want to focus on one way in which they are perhaps making things too difficult for themselves.

In particular, each aims to build a BIG brain, and I want to suggest here that perhaps they can get the intelligence they’re looking for without the BIG.

Why not go big? Because bigger brains are a pain in the neck, and not just for the necks that hold them up. As brains enlarge across species, they must modify their organization in radical ways in order to maintain their required interconnectedness. Convolutedness increases, number of cortical areas increases, number of synapses per neuron increases, white-to-gray matter ratio rises, and many other changes occur in order to accommodate the larger size. Building a bigger brain is an engineering nightmare, a nightmare you can see in the ridiculously complicated appearance of the dolphin brain relative to that of the shrew brain below – the complexity you see in that dolphin brain is due almost entirely to the “scaling backbends” it must do to connect itself up in an efficient manner despite its large size. (See http://www.changizi.com/changizi_lab.html#neocortex )

dolphin brain size  versus shrew brain

If the only way to get smarter brains was to build bigger brains, then these AI projects would have no choice but to embark upon a pain-in-the-neck mission. But bigger brains are not the only way to get smarter brains. Although for any fixed technology, bigger computers are typically smarter, this is not the case for brains. The best predictor of a mammal’s intelligence tends not to be its brain size, but its relative brain size. In particular, the best predictor of intelligence tends to be something called the encephalization quotient (a variant of a brain-body ratio), which quantifies how big the brain is once one has corrected for the size of the body in which it sits. The reason brain size is not a good predictor of intelligence is that the principal driver of brain size is body size, not intelligence at all. And we don’t know why. (See my ScientificBlogging piece on brain size, Why Doesn’t Size Matter…for The Brain?)

This opens up an alternative route to making an animal smarter. If it is brain-body ratio that best correlates with intelligence, then there are two polar opposite ways to increase this ratio. The first is to raise the numerator, i.e., to increase brain size while holding body size fixed, as the vertical arrow indicates in the figure below. That’s essentially what the Blue Brain and SyNAPSE projects are implicitly trying to do.

But there is a second way to increase intelligence: one can raise the brain-body ratio by lowering the denominator, i.e., by decreasing the size of the body, as shown by the horizontal arrow in the figure below. (In each case, the arrow shifts to a point that is at a greater vertical distance from the best-fit line below it, indicating its raised brain-body ratio.)

brain weight best fit  line primates

Rather than making a bigger brain, we can give the animal a smaller body! Either way, brain-body ratio rises, as potentially does the intelligence that the brain-body combo can support.

We’re not in a position today to understand the specific mechanisms that differ in the brains of varying size due to body size, so we cannot simply shrink the body and get a smarter beast. But, then again, we also don’t understand the specific mechanisms that differ in the brains of varying size! Building smarter via building larger brains is just as much a mystery as the prescription I am suggesting: to build smarter via building smaller bodies. And mine has the advantage that it avoids the engineering scaling nightmare for large brains.

For AI to actually somehow take this advice, though, they have to answer the following question: What counts as a body for these AI brains in the first place? Only after one becomes clear on what their bodies actually are (i.e., what size body the brains are being designed to support) can one begin to ask how to get by with less of it, and hope to eke out greater intelligence with less brain.

Perhaps this is the ace in the AI hole: perhaps AI researchers have greater freedom to shrink body size in ways nature could not, and thereby grow greater intelligence. Perhaps the AI devices that someday take over and enslave us will have mouse brains with fly bodies. I sure hope I’m there to see that.

This first appeared on March 9, 2010, as a feature at ScientificBlogging.com.

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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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I was recently interviewed about brain and city evolution by “Gladelic: A Quarterly Magazine of Intuitive Intelligence”. Here’s the beginning…

Mark, why have you chosen to focus your study on the neocortex (its importance in the aspect of human evolution) how did you come to comparing cities and brains?

Despite the brain’s complexity, our gray matter is essentially a surface, albeit convoluted in our case. Bigger brains expand the surface area of the gray matter, with only a meager increase in the thickness of gray matter. Cities, too, are surfaces, because they lie on the Earth. Our cortex has ample white matter wiring that “leaps” out of the gray matter to faraway parts of the brain, and these long-range connections are crucial to keeping the entire cortex closely connected. For cities, highways are the white matter axons, leaving the surface streets to efficiently connect to faraway spots. I began to follow these leads, and to flesh out further analogies: synapses and highway exits; axon wire thickness and number of highway lanes; axon propagation velocity and average across-city transit speed.

I found similar scaling laws governing how network properties increase as surface area increases. For example, in each case, the number of conduits (highways and white matter axons) increases as surface area to approximately the 3/4 power, and the total number of “leaves” (exits and synapses) increases as surface area to approximately the 9/8 power.

Despite the radically different kind of network, they are in some respects similar enough, and each has been under selection pressure over time to become more efficiently wired. The selection pressure for brains was, of course, natural selection, which involved lots and lots of being eaten. And the selection pressure for cities was teems of political decisions over many decades to steer a city to work better and better as it grew.

The rest of the interview is at Gladelic (half way down). More about my city-brain research can be found here: http://changizi.wordpress.com/category/cities-shaped-like-brains/

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 December 14, 2009, as a feature at ScientificBlogging.com.

Daniel Tammet is an autistic savant and author of the recent book Embracing the Wide Sky: A Tour Across the Horizons of the Mind (Free Press). You may have heard of him. For example, most people first became aware of the existence of Iceland upon hearing that Tammet learned Icelandic in a week.

This is also the fellow that rattled off the first 22,514 digits of pi in five hours, enough for even the most exacting civil engineer, and far more accurate than the 19th century Texas town that passed an ordinance that pi would be approximated as 4. If ever there were a real human with superpowers, then Tammet fits the bill. Although stricken with adversity, his brain nevertheless is in certain respects blessed with something extra, smarter, almost magical.


But I don’t believe that the moral of extraordinary people like Tammet is that they are extraordinary. No doubt they ARE extraordinary – doing *anything* 22,514 times is amazing, especially when a transcendental number is involved. The moral of Daniel Tammet is not that he’s extraordinary, but that it follows that we must ALL be extraordinary. In fact, it follows that we must all have powers even greater than the ones in the savant repertoire.

You might be responding, “Extraordinary powers! Me? No, you must be mistaken.” And that does seem like a reasonable response, because if we really had mind-boggling powers, wouldn’t we be the first to know? The answer is, “No.” Your own powers are perhaps the most difficult for you to notice. Your capabilities were selected over evolutionary time to work effortlessly as intended, but there was no selection pressure to brag to your consciousness about how exceptionally cool your hardware is.

You have employed your natural capabilities your whole life, and you have seen them in action in everyone you know; that leads to a “nothing to see here, folks, please go home” mentality about your own capabilities. The only time you are likely to notice your capabilities is when something goes wrong with them. But that still falls quite short of appreciating just how powerful the mechanisms are when they are up and running.

And this is where Daniel Tammet’s brain, and that of other savants, becomes useful . (I knew there was a reason for your brain, Daniel!) His brain allows us to begin to appreciate the true extent of our own non-savant capabilities. The savant brain is just like our brain, but with a twist. And because giving a (metaphorical) twist to neural tissue can only hinder its workings, the powers of savants are an underestimate to the power we have inside us.

Why? Consider what cannot be underlying the talents of savants. It is NOT the case that their brain possesses mechanisms, or algorithms, fundamentally different from those found in our brains. That’s the impression one might get by watching television shows or movies about savants: their brains are endowed with some altogether fancy qualitatively new design enabling them to implement their power. But savants are savants because of a disorder; their brains do not end up as they “should” be.

Their brains have undergone a “twist”. And when mistakes happen in the construction of any machine – biological or otherwise – the chances of getting efficiently designed and altogether new functionality is essential zero. Evolution gets fancy new functionality by virtue of countless generations of tiny changes. Evolution does not design new gadgets in one go.

What must, then, be going on is that one of the fancy gadgets that is inside all of us is being directed, in savants, in a manner in which it wasn’t selected for. For example, Tammet describes his internal experience of what it’s like to determine the digits of pi as something like visualizing a complex landscape. His brain ended up with a “twist” that gave him the ability to harness the computational power of his visual system for calculating the digits of pi, something his visual system was not designed to do. (As an aside, see my own attempt to harness our visual system for computation)

The beauty of savant cases is that once the power of the brain is redirected in an utterly unusual direction, then we who observe these savant powers in action have a much better ability to judge the true extent of their power. Whereas we are nearly incapable of gauging how superbly capable the mechanisms are when directed as evolution intended, we see clear-as-day the brawny power of our mechanisms when twisted to point in a strange direction.

When we see Daniel Tammet reaching the 22,500th digit of pi, and we’re reeling with wonder, we should pause and realize that what Tammet has done is provide a lens through which you can see the superpower hidden inside your own brain.

In fact, because Tammet’s pi-calculating machinery wasn’t designed for that, the machinery is probably nowhere near as sophisticated as a pi-calculating biological machine would be were pi-calculation to have been selected for.

The machinery Tammet harnesses for pi-calculation – machinery you have as well, but without the “twist” you can’t harness it as he does – is much more well designed for what it is supposed to do (something having to do with seeing) than for pi-calculating, so the power of Tammet’s superpower pales in comparison to what’s going inside of all of us (including Tammet when he uses his visual system as “intended”).

Daniel, thanks for illustrating to the world the amazing power of our brains! And thanks for being a good sport!

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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