Feeds:
Posts
Comments

Posts Tagged ‘organization’

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.

Read Full Post »

Jay Ingram’s Daily Planet television show on Discovery Channel has a  piece on my cities-are-shaped-like-brains research (the paper which recently appeared in the journal Complexity, with co-author Marc Destefano). The clip begins about half way through the segment (7 minutes and 30 seconds.)

See these posts at my blog (and also one at ScienceDaily) for more information about the research.

Mark Changizi is Professor of Cognitive Science at RPI, the author of The Vision Revolution (Benbella, 2009) and The Brain from 25,000 Feet (Kluwer, 2003).

Read Full Post »

RPI’s press release on my and Marc Destefano’s city-brain paper just came out, written by science-writer Michael Mullaney. I have included a copy of it here as well…

Ego City: Cities Organized Like Human Brains

Credit: Rensselaer/Mark Changizi

New study shows striking similarity in the evolution of brains, cities

Cities are organized like brains, and the evolution of cities mirrors the evolution of human and animal brains, according to a new study by researchers at Rensselaer Polytechnic Institute.

Just as advanced mammalian brains require a robust neural network to achieve richer and more complex thought, large cities require advanced highways and transportation systems to allow larger and more productive populations. The new study unearthed a striking similarity in how larger brains and cities deal with the difficult problem of maintaining sufficient interconnectedness.

“Natural selection has passively guided the evolution of mammalian brains throughout time, just as politicians and entrepreneurs have indirectly shaped the organization of cities large and small,” said Mark Changizi, a neurobiology expert and assistant professor in the Department of Cognitive Science at Rensselaer, who led the study. “It seems both of these invisible hands have arrived at a similar conclusion: brains and cities, as they grow larger, have to be similarly densely interconnected to function optimally.”

As brains grow more complex from one species to the next, they change in structure and organization in order to achieve the right level of interconnectedness. One couldn’t simply grow a double-sized dog brain, for example, and expect it to have the same capabilities as a human brain. This is because, among other things, a human brain doesn’t merely have more “dog neurons,” but, instead, has neurons with a greater number of synapses than that of a dog – something crucial in helping to keep the human brain well connected.

As with brains, interconnectedness is also a critical component of the overall function of cities, Changizi said. One couldn’t put together three copies of Seattle (surface area of 83.9 sq. miles) and expect the result to have the same interconnectedness and efficiency as Chicago (surface area of 227.1 sq. miles). There would be too many highways with too few exits and lanes that are too narrow.

In exploring this topic, Changizi discovered evidence linking the size of a city or a brain to the number and size of its supporting infrastructure. He investigated and documented how the infrastructures scale up as the surface area of brains and cities increase.

As cities and the neocortex grow in surface area, the number of connectors – highways in cities and pyramidal neurons in brains – increases more slowly, as surface area to the 3/4 power, Changizi found. This means the number of connectors increases in both brains and cities as S3/4, where S = surface area. Similarly, as cities and brains grow, the total number of highway exits and synapses — which share a similar function as terminal points along highways and neurons — increases with an exponent of about 9/8. The number of exits per highway and synapses per neuron were also closely aligned, with an exponent of approximately 3/8.

These and other findings are detailed in the paper “Common Scaling Laws for City Highway Systems and the Mammalian Neocortex,” published this week in the journal Complexity. The complete paper may be viewed online at the Complexity Web site.

“When scaling up in size and function, both cities and brains seem to follow similar empirical laws,” Changizi said. “They have to efficiently maintain a fixed level of connectedness, independent of the physical size of the brain or city, in order to work properly.”

Marc Destefano, clinical assistant professor in the Department of Cognitive Science at Rensselaer, co-authored the paper.

Earlier this summer, Changizi’s new eye-opening book, The Vision Revolution: How the Latest Research Overturns Everything We Thought We Knew About Human Vision, hit store shelves. Published by BenBella Books, The Vision Revolution investigates why vision has evolved as it has over millions of years, and challenges theories that have dominated the scientific literature for decades.

For more information on Changizi’s research, visit Changizi’s Web site and read a recent magazine story on his work. See Rensselaer’s recent news release for more information on The Vision Revolution.

Published September 3, 2009

Contact: Michael Mullaney
Phone: (518) 276-6161
E-mail: mullam@rpi.edu

[See it in ScienceDaily.]

Read Full Post »

The following piece was written for ScientificBlogging.com on my new paper on the brain-like organization of cities…

The brain-like organization of cities. (Or, is it, the city-like organization of brains?)

Mark Changizi

You may recall the “China Brain” thought experiment about consciousness, which goes something like this: if each person in China were to mimic the activity of a neuron using cell phones to communicate with one another, would this China-sized brain like Chinese food? I may be missing some of the philosophical nuances in the question, but as a one-time philosopher, I know enough about consciousness to know I have nothing remotely worthwhile to say about it.

So let me set consciousness aside. Here’s a different kind of “China Brain” question more up my alley: Are the people of China actually organized in a brain-like fashion? This is not a thought experiment, but a genuine question. A silly question, you might say. But countries do tend to be cohesive complex systems that function via the movement of people, goods and information.  In fact, cities are more cohesively organized than countries, and the same question can be asked of them: Are cities organized like brains?

Cities shaped like brains.

Cities shaped like brains.

Although most cities don’t at first glance look much like brains, there are some initial similarities.

First, unless you buy a thousand acres of land and have your own city built to order, cities get their shapes via (political and economic) selection forces over many decades. Like brains, cities evolve: ones that are not well organized wilt (people move away over time) or modify themselves to become more efficient.

Second, cities interconnect themselves with highways, and are under selection pressure to connect themselves efficiently. Highways break out of the two dimensional street grid, and “pull” the city’s edges closer to one another. Brains, too, have highways: white matter axons. The pyramidal neurons in the cortex send their axons out of the gray matter to faraway parts of the cortex.

I long ago stopped my subscription to the Flat Earth Society newsletter, but I still have reason to believe that cities are flat, and this is a third similarity between cities and brains. Even if you live in San Francisco, your city lies on the surface of the Earth, rather than, say, being built in a three-dimensional array below ground, or like the Borg cube. Our cortex is also flat, and if you’re lucky enough to be used in an experiment, researchers will flatten your gray matter onto the nearest cold metal table.

Having noticed these prima facie city / brain similarities, and having long had an interest in understanding why brains are shaped as they are, I thought I would take a closer look. I asked, Given what we know about how brains change when they get larger, do we find that cities change in similar ways as they get larger? So graduate student Marc Destefano and I took data from U.S. cities varying in population from about 10 thousand to about 10 million, and determined how city organization changed as city size increased. Our paper just appeared in the journal Complexity.

We found that cities and brains are quantitatively very similar in how they change their organization as a function of size. For example, the number of highways increases more slowly than does the surface area of a city, something already known to be the case for our brain’s highways (i.e., our white-matter-projecting neurons); in particular, in each case the number increases at about the 3/4 power of surface area. And the total number of highway exits in a city increases faster than the land area of the city, also the case for the total number of synapses in the brain; in fact, in each case the number increases at about the 9/8 power of surface area. Our paper discusses a number of other similarities – and discusses differences – e.g., for the diameter of highways, their propagation velocity (i.e., cross-city travel time), and the number of compartments (akin to cortical areas).

One notable problem with the analogy is people. What does population mean for the cortex? We’re not sure, but we found that the population of cities increases very fast as a function of land area, namely nearly as the 3/2 power of land area. That means population density in cities tends to increase as the 1/2 power, or as the square root, of land area. Bigger cities seem to demand that people really get up close and personal. That’s too bad for your and my kids, because cities are growing ever larger, and I don’t want anyone getting up close and personal to my wee girl.

Why do larger cities demand greater population density? Well, our measurements show that the total surface area of highways in a city also increases approximately as the 3/2 power of land area. Perhaps an efficiently running city highway system requires that each person in the city gets an invariant swathe of highway, so that no matter the size of the city, the total number of people per unit area of highway is a constant.  Our data suggest that this is, indeed, roughly a constant across cities, although whether this is itself one of the evolutionary drivers of city highway organization is unclear.

Given our findings that city highway systems tend to obey certain quantitative scaling laws, and presuming that they obey these scaling laws because they have been selected over time for greater efficiency, then one way to diagnose the health of a city highway system is to see whether a city’s data point is where it should be for its land area. For example, if one plots total number of highway exits versus land area for many cities, and one sees a city that does not fall on the line (e.g., maybe it has too many exits), then one would know how to purposely get a city into line, rather than waiting for selective forces to work over the decades to come.

Cities are a lot smarter than we have thought. And that, I contend, is true about most complex systems that are under selection pressure for considerable periods of time. If we can understand the organization of cities, then we might have a leg up in understanding the brain. And cities make it easy, because relative to the size of these city-brains, we are nano-particles traveling through them like the characters from Fantastic Voyage.

Mark Changizi is Professor of Cognitive Science at RPI, and the author of The Vision Revolution (Benbella, 2009) and The Brain from 25000 Feet (Kluwer, 2003).

[A ScienceDaily piece.]

Read Full Post »

cities

Could the organization of our cities be smarter than we think? Here’s the abstract of my and Marc Destefano’s new paper in the journal Complexity…

Cities and the mammalian neocortex may seem to have little in common, but each is approximately a surface with a network of conduits (roads and neurons, respectively) connecting its disparate parts. Because both cities and brains are under selection pressures to make their connections efficiently, we investigate the hypothesis that the organization of city highway networks and the mammalian neocortex may be governed by common principles. Here we measure how city highway networks vary with city size and find that, consistent with the hypothesis, highway networks scale with exponents nearly identical to those found for the analogous quantities in the neocortex. As a function of surface area, the number of conduits scales approximately as the 3/4 power, the number of “leaves” (highway exits and synapses) scales approximately as the 9/8 power, propagation velocity scales approximately as the 1/8 power, and total conduit surface area scales approximately as the 11/8 power. We also find that city population scales as the 1.46 power of surface area, potentially driven by the total surface area of highways. We discuss the extent to which explanations for neocortical scaling can be extended to cities.

The paper is here

Here’s a little piece at ScientificBlogging.com

<!–[if gte mso 9]> Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 <![endif]–><!–[if gte mso 9]> <![endif]–> <!–[endif]–>
.
Mark Changizi is Professor of Cognitive Science at RPI, and the author of The Vision Revolution (Benbella, 2009) and The Brain from 25000 Feet (Kluwer, 2003).

Read Full Post »