Author and journalist Carl Zimmer talks about the search for the physiological and biological basis of intelligence, the subject of his article in the October issue of Scientific American magazine. And Editor in Chief John Rennie discusses other articles in the issue, including the cover story on the possibility of a big bounce instead of the big bang and the science of the World Wide Web. Plus, we'll test your knowledge about some recent science in the news. Web sites mentioned in this episode include www.SciAm.com/sciammag; www.carlzimmer.com
Welcome to Science Talk, the weekly podcast of Scientific American for the seven days starting October 1st, 2008. I'm Steve Mirsky and you're intelligent. My evidence is that you listen to this podcast. Well, Carl Zimmer is the author of an article in the October issue of Scientific American called "The Search for Intelligence'". The issue has numerous other fascinating articles. We'll talk with editor in chief, John Rennie, about some of those later. First up though: Carl Zimmer. We talked after a public lecture he gave at the Stevens Institute of Technology in Hoboken, New Jersey.
Steve: So, Carl how are you? Other than, I know, you've a cold, but you're looking all right.
Zimmer: Other than the cold I am doing great, thanks.
Steve: So you got this article in the current Scientific American on intelligence—the search for intelligence—what, really, is intelligence?
Zimmer: Well there are a lot of different ways of testing intelligence, and you can find them on IQ tests and other kinds of tests; and they tend to correlate together and so that people who score a certain way on one intelligence test will test similarly in another test and so these scores, kind of, hang together.
Steve: But in some ways intelligence is the like the famous Supreme Court ruling on obscenity, right? It's hard to define but you know it when you're around it.
Zimmer: Yeah, we all have a sense of people who are really smart and people who aren't so smart. And it's true we have this gut sense about it. And, you know, psychologists can actually turn that into a pretty solid statistical measure and, you know, IQ scores are turned out to be very predictive in the sense that you can take someone's IQ score as a chi-square in predicting about their lives. You can even predict how long they live. So there's something there about intelligence but that doesn't tell you what it really is.
Steve: Yeah, you get into the search for intelligence genes. This was a natural thing. It seems
to be [as soon as we] started to be able to figure out what genes were and what certain genes did,
it became natural to look for the genes associated with intelligence, but that search has proven to be much more treacherous than probably the people in the field ever imagined.
Zimmer: Yeah, that to me is the really fascinating part of this story, and this isn't a really great success story in science. This is a story of science struggling on. So, psychologists know that there is definitely a genetic component to intelligence. There are lots and lots of studies on twins that show that identical twins tend to have the same intelligence or closer score in intelligence tests than non-twins.
Steve: These are even twins raised apart.
Steve: Separated at birth and raised in completely different environments.
Zimmer: That's right, so this is a very strong result that keeps coming up again and again. So you figure that at least some of the differences in people's intelligence scores has something to do with their genes. So, hey, let's go and look in the genes. What turns out [is] that scientists are having [a] really, really hard time finding them, and what that tell[s] us is that there are these genes that influence intelligence but each particular gene is responsible for a tiny, tiny amount of variation—like a fraction of 1 percent. So, probably hundreds upon hundreds of genes
that together produce these differences on intelligence tests.
Steve: And there's one of the researchers you quote in the article talks about, there may be genes that are not directly responsible for some aspect of brain function even at a biochemical cascade level; there might be a gene that is responsible for the width of the birth canal and that that could be associated with ultimately with intelligence.
Zimmer: What scientists point out is that just because you find a gene that correlates with intelligence doesn't mean that it's necessarily doing something we think of it having anything to do with intelligence. So, for example, just to say for the sake of argument, that there's a gene that influences the width of the birth canal, and lets say that some versions of the gene leave women more likely to have trouble giving birth, so that their children have loss of oxygen and that could lead to changes in the brain that lead to lower intelligence scores. Well it's not really an intelligence gene that has anything to do with the brain; it just has to do with actually the mother. So it could be really complicated, and so even when scientists actually identify these intelligence genes—and they haven't really yet—but even when they do, that still doesn't necessarily tell us what those genes actually do for us.
Steve: Yeah, so basically we still don't know hardly anything about genes and intelligence.
Zimmer: We do hardly know anything about genes that have to do with intelligence and what['s] surprising is that this ignorance is taking place even when we have really sophisticated tools. So scientists can now use the so called gene chips to scan people's DNA for hundreds of thousands of genes and different variants of genes. You think that if there were some big intelligence genes with these kinds of gene chips we would catch them; and you might imagine that this would be a done deal, but it is not. Even with this incredibly powerful technology the scientists have now, they are still coming up with these genes that may or may not have a tiny, tiny influence on intelligence. You know, in a way, that's the result
s of a viral genome studies [study] on complex traits. So, like, complex diseases like diabetes or cancer or schizophrenia, the keep coming up with these same results. So in a sense we shouldn't be surprised that intelligence turns out to be so complex, but it is a little frustrating.
Steve: Some really interesting material in the article on brain imaging as a child grows from infancy into adolescence really and the thickness of parts of the brain. Let's talk about that and what that actually kind of ends up meaning.
Zimmer: So there have been some scientists who have been keeping track of the development of children's brains. Year after year, they scan these kids and they are also keeping track of other things like, do they develop schizophrenia? They give them intelligence tests and they do all sorts of things to try to look at whether there is a link between certain changes of the brain and things about human behavior. And so one scientist named Phil Shaw has been looking at whether there is a difference in how the brain in children who score high on intelligence tests developed compared to children who scored low, and it turns out there is. So in the outer layer of the brain, the cerebral cortex gets thicker faster in intelligent kids, and it gets thinner compared to an average kid. And so this is a distinct difference in how the brain is developing. The problem is that it's very hard to know what that means about the biology of intelligence. So why would that have anything to do with you doing [well] on an intelligence score? Really scientists have no clue, I mean they really just have the point of pinpointing real patterns that you can link to intelligence; then the challenge becomes to say, "Well how does A cause B?"
Steve: And that the thickness is networks of nerve cells joining together and then the thinness is discarding of some of those connections when the brain figures out they don't need them.
Zimmer: Yeah, so the neurons are growing in the child's brain and they are making more and more of these connections and then cutting them back, so you know, it's possible that they are cutting back these connections to produce a very efficient network. There is a lot of ideas about how intelligence might have something to do with speed, sort of mental speed; you know, if signals go back and forth around your brain really quickly, maybe that has something to do with intelligence; and so maybe what's happening is that these networks are being built for speed in kids who score high in intelligence tests. Again it's all a speculation, but that's the kind of stuff the scientists are thinking about now.
Steve: There's apparently some kind of balance in there between processing power and speed and two different people who are equally intelligent—if you can even say such [a] thing and
having to [have it] be meaningful, one might have a lot of processing power and one might have a lot of speed but you wind up with the same results.
Zimmer: Yeah, that's another interesting thing that comes out of these brain studies. People who score high in intelligence tests, they don't all have the same brain. So some of them tend to have well-developed connections between different regions of the brain; that's where the white matter—the cables connecting different processors in the brain. The other people have certain parts of the cerebral cortex—the gray matter—that are well developed and those are like the processors. So in some cases maybe I would like to say having well developed processors has something to do with intelligence and maybe in other cases having fast connections between different parts of the brain has something to do with it. Again, the patterns are there and now the challenge is to make sense of them.
Steve: So what's next to this field? What are people going to be looking for and why? Why does it matter that we understand where intelligence comes from biologically?
Zimmer: I think that one of the most promising things would be to identify children with particular learning disabilities. You could say, for example, if someone has a certain combination of a whole bunch of genes that might make them more at risk, for example, having trouble learning how to read. And so in the sense you know ultimately what's going to have to happen is intelligence is going to have to be better understood as a whole bunch of different processes in the brain. But once scientists
to do that, they may be able to help pinpoint the best ways to help people learn by understanding how intelligence develops in the brain. On the other hand, you know, some psychologists say, "Look, this is just interesting." I mean it's just a fascinating fact that we can measure this thing called intelligence that has this incredible predict of [predictive] power though we still don't really have a clue what it is, and so they just want to understand it as a basic scientific question.
Steve: You can read Carl's intelligent article online just go to www.SciAm.com/SciAmmag. Carl has a new book out all about, believe it or not, E. coli, many of which are swimming around in your gut right now. He will be on again soon to talk about those usually beneficent bacteria. I sat down at the office with editor in chief, John Rennie, last week to talk about some of the other offerings in the October issue.
Steve: You know, John, I am biased because I do get a check from Scientific American. I thought this was a particularly strong issue.
Rennie: Thank you, Steve.
Steve: Lets start with the cover: the big bounce. I mean, this is just, you're going to blow people's minds with this.
Rennie: That's right. Well this is an article which is about cosmology, the origin of the universe, and this means a lot of fun because it examines one new idea that has been emerging about the model for how the universe started and that answered that question of where did it all come from. We know that there was a big bang because all the evidence shows that basically the entire universe is expanding all the time. If you, of course, go back in time what that tells you is that at some point, in theory, everything should have gone back to a little singularity; a point where basically all the matter and energy in the universe was crammed down into one infinite decimal point. Here's the problem what that, though.
Steve: Here's the problem with that.
Rennie: Yeah, that's right. (laughs) The problem is that under general relativity that's not possible, because you have a bunch of things, basically various numbers in equation go to infinity, and that should not be possible. So that's always been a problem and something has to change that. An answer may come from the attempts the people are making to try to develop a theory of quantum gravity because under one of the models for this called up loop quantum gravity spacetime itself almost consists of, like, you can think of it is like a little a atom of spacetime; and one possibility is that when you start to cram everything very close together when space itself is packed down into a small enough point that it can't keep shrinking it, it can't keep compacting it. At some point, you have passed a maximum energy that you can pack into that space and will then start to push everything back out again. So, in effect,
with[what] that means is gravity—which we normally think of is[as] an attractive force—under those conditions, it suddenly starts to operate as a repulsive force.
Steve: And the article uses this sponge analogy. If you have a dry sponge in your water, it will suck up the water, but once the sponge is full then, it will start to repel water; if you try to add in more water, the water will just spill away. And it's a more, the analogy falls flat a little bit because it's an actual repulsive force rather than just a saturation point but you can understand the concept.
Rennie: Right, and so what that means is that, one possibility then, is that what happens is that our universe is oscillating in a way that there was a universe that existed before the one that we know of now on the other side of this point of maximum density. The weird things about that are that, of course, time in, say, this universe and in that preceding universe, they would have run in opposite directions. So there was never theoretically for somebody who was in, say, this universe or in the universe that would have preceded this one there is never a moment when it all turns around and comes back in. Some listeners may remember that there was an old cosmological theory about an oscillating universe where the idea was that the big bang sort of threw the universe—it
outward expanded outward, but at some point, gravity would cause everything to slow down and then it would start to collapse again. This is different from that, and you never have the same kind of collapse. It just means that before the beginning of this universe, there would have been another universe and what was the beginning of this one was in essence the end of that one from our perspective.
Steve: One man's ceiling is another man's floor.
Rennie: There you go.
Steve: And for those of you who are very uncomfortable with this singularity idea of basically an infinite amount of matter and energy in an infinitesimally small point of space, again, this does away with that and you only have to deal with the concept of the massive, a trillions suns in a volume of space the size of a proton.
Steve: Much easier to get it around.
Rennie: Much easier to picture and much easier to imagine that that's how things look like.
Steve: So there is that, then we have a really interesting article, one of the authors is Tim Berners-Lee, famous Webmatician.
Rennie: Well, we usually refer to [him] as the father of the World Wide Web.
Steve: Father of the World Wide Web, about Web science and this is particularly interesting because the Web has sort of come in to existence and evolved on its own, but now there are properties of it that are emerging that researchers can actually study to find a science of the Web.
Rennie: Right, if you look at the Web that we have today, it's kind of a self-assembled structure. I mean, obviously people were putting it together and there were people who were creating the different elements of that but nobody designed a lot of the networks that in fact linked different people or different devices or different computers to one another. That is something that sort of grew up organically. So in this article, Web science emerges. Tim Berners-Lee and Nigel Shadbolt talk about a movement that has been taking place in recent years to try to establish basically a science of the Web. A brand new science for studying this networked phenomenon, and in effect it's kind of a reverse engineering the World Wide Web that we know and the kinds of networks that we see on that to try to figure out how they took shape and maybe from that we can learn what principles involve and how networks do grow and you might be able to use that sort of thing to be able to develop a better system
s for example being able to create more efficient networks and that could be very valuable in industry, there may be a lot of practical applications, involving protecting privacy, for example, and stopping people from stealing identities; and you should, you know, should be of just an interesting phenomenon. In a sense it's like any kind of science: You don't know what benefits might come out of it until you start to do it.
Steve: One of the things the article talks about is that as the Web has grown, you might expect it to have grown exponentially, but if you examine the fabric of it, the way nodes connect to other nodes and sites connect to other sites, rather than an exponential growth it's really a scale-free growth and I don't think anybody could have expected that. Let's try to explain what that actually means.
Rennie: Yes, scale-free networks are ones in which you can look at them at any scale. You can look at them, say, one little piece or at a larger level of magnification and the level of complexity stays the same at every one of those levels. Basically it's like fractals. There is a scale-free phenomenon for you. It's says that there are some kinds of principles at work affecting how a network like this one take[s] shape and why it probably really is worthwhile for us to study that.
Steve: As opposed to an exponential growth where we start with a whole bunch of stuff in the middle and then other things build up around that at a different kind of pace really.
Rennie: Right, right, that's right, you would, that's probably what most of us would have naively figured—you would see when you would look at the structure of the Web and how things grew up because it seems like things are up online and other things attach themselves and they inspire other things and you might expect that kind of exponential structure, but in fact you are getting this scale-free structure and that says there's something interesting about the way that in effect information wants to be organized within networks.
Steve: And it also says that if a chunk of the Web goes down, the rest of the Web should still function pretty well, whereas in an exponential system, if a chunk goes down you may have a ...
Rennie: A massive failure of some sort that would completely collapse everything. That's right. Obviously back when they were first constructing the underpinnings that preceded the Web, the old Arpanet, that was one of the structural things that they wanted. They wanted to create a communications network for the military and for researchers that would be potentially impervious to destruction from, say, nuclear attack and it would route itself around any kind of damage to the network. On practice of course we have seen that it still happens, but it is showing up, that same kind of routing itself around damaged structure behavior occurs even in parts of the Web that we wouldn't have expected.
Steve: Lots of other interesting stuff. We have an article on bar coding life.
Rennie: Right, right this is a kind of a really interesting idea. This is a way of trying to identify species. It's been determined that if you look at a particular about 650-base-long piece of the DNA from the mitochondria of various animals that you can find that those all tend to, from species to species, those vary enough that you can basically read that little chunk and get a sense of
whether what species an organism belongs to. And that's actually a pretty useful thing to be able to do if you are a biologist and you are faced with the problem of trying to identify what species you want to assign an organism to. You know, think of something like a caterpillar; obviously, your caterpillars look very different from the butterflies that they eventually become and there are lots of different species of butterflies that have caterpillars that look very similar or that look very different. With something like this kind of barcode technique, it could potentially really simplify this kind of aspect of field biology and clarify some of the kind of evolutionary relationships you would see.
Steve: In theory, you could have a handheld device like a glucose meter that a diabetic might use and you just, you know, take a hair of some animal, put it in the device, and you get an instant read up based on the analysis of that little DNA section of what species you're looking at and, you know, take your caterpillar example that might sound like something that just a level-headed field biologist would be interested in. Actually caterpillars do hundreds of millions of dollars worth of damage to crops and to forests. So this is something that field biologists might actually find a good use for. Is this caterpillar I am looking at indicative of an invasion or is it just a harmless thing?
Rennie: Right, there are a lot of very practical applications for being able to track, for example, which types of mosquitoes are carrying a particular disease; lots of different applications in medicine and agriculture that come out of this. Now it's still [a] somewhat controversial idea among biologists actually, partly because you do have some who are little bit skeptical about how much can you trust that this one little chunk of DNA is really a good indicator of species differentiation. It also works much, much better for animals than it does for plants. Plants have their own complexities about even how you define what constitutes the species in plants they tend to hybridize much more easily than the animals do, but it's in any case a useful tool. A useful kind of technique and this article in the October issue gives you some idea of how it works.
Steve: Lots of good stuff in the October issue. Tell people where can they find the October issue of Scientific American.
Rennie: Steve, you can find the October issue on newsstands everywhere.
Steve: And we are also available in our entirety...
Rennie: That's right.
Steve: ... on that World Wide Web we were talking about before.
Steve: Now it's time to play TOTALL....... Y BOGUS. Here are four science stories; only three are true. See if you know which story is TOTALL....... Y BOGUS.
Story number 1: NASA's Mars Phoenix Lander has spotted snow falling on Mars.
Story number 2: MBA students were more likely to lie in e-mail than when they wrote using pen and paper.
Story number 3: The federal government has funded almost 5 million dollars to study bear DNA. That's b-e-a-r DNA
And story number 4: Researchers have invented a pill that you add to a tank of gas to increase your mileage by 20 percent.
Time is up.
Story number 1 is true. The Mars Lander has indeed seen white flakes falling on the Red Planet. The snow vaporizes though before hitting the ground. The
n Lander was designed for a three-month mission on the surface that's still going in it's fifth month; before the Lander's power dies, an onboard microphone will be activated to see if there's any sound such as a voice saying, "I'm going to tell you one last time, there is no standing in the blue zone."
Story number 2 is true. A study of MBA students found that they lied more in e-mail then when actually writing. Check out the September 29th 60-Second Psych podcast for more details, but I will tell you that the experiment-tested students are given money that they then had to split with someone else who they would inform via e-mail or a handwritten note, one or the other. More than 90 percent of the e-mailers did lie, but only about two-thirds of hand writers lied about the total sum of money. Perhaps another study is in order to find out why regardless of the medium you still had a big majority of MBA candidates lying about money.
And story number 3 is true. The feds have indeed funded bear DNA research—b-e-a-r DNA research—to the tune of almost five million dollars over the last five years, which is way more than the three million dollars that John McCain keep springing up as an example of wasteful government spending. He did so again in the
first debate last week. Actually, however, the money is necessary to study the animals and keep their population healthy in accordance with federal law, not to mention that bears undoubtedly pay for themselves. Lots of people pay lots of money at national parks because they are hoping to get a glimpse of Yogi and Boo Boo. For more info, check out the September 28th article on our Web site called "The Real McCain–Obama Debate Over Bear DNA", unless you are Stephen Cole-Bear.
All of which means that story number 4 about the pill you add to your gas to up your mileage is of course TOTALL....... Y BOGUS. Come on, you have been hearing that one for decades. But what is true is that a researcher at Temple University has created a device that in early testing does appear to boost highway mileage by about 20 percent. The device produces an electric field near the fuel injector and the field thins out the fuel which means that the droplets of fuel that get injected into the engine are smaller, which appears to give more efficient and cleaner combustion. The research was published in the American Chemical Society journal Energy and Fuels, which means that other labs will now have the opportunity to replicate and confirm what would appear to be a pretty big deal on the fuel front.
Well that's it for this edition of the weekly SciAm podcast. Visit http://www.SciAm.com for all the latest science news, discussions and today's science trivia. For Science Talk, the weekly podcast of Scientific American, I'm Steve Mirsky. Thanks for clicking on us.