Brains Like Computers? (artwork by Ricard Solé)
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  2. Transcript

Vijay Balasubramanian:

There's a jellyfish that gets older, and then when it gets tired of getting older, it gets younger for a good while, and then it starts to get older again, and it'll never die unless it's eaten. Now, why can't I do that?


Abha Eli Phoboo: So Chris —

Chris Kempes: Abha —

Abha: The person we just heard from was Vijay Balasubramanian, and we’ll hear more from him later on. But what he said makes me wonder, why aren’t humans like this jellyfish that gets to just decide if it ages? Why can’t we all be Benjamin Buttons?

Chris: Well, to be honest I don’t know too much about this jellyfish, which is called turritopsis dorhnii. But I do know something about the laws of physics. And basically, physics is what makes us age. Turritopsis seems to have found some sort of loophole for aging, but our guests today will help us understand what it’s like for the rest of us: physical laws, like entropy and size, make us get older, not younger. And, they’ll help us understand why we evolved to be this way.

Abha: Long time listeners of Complexity will have noticed that this show has been on a break. We’re relaunching with a bit of a new approach: we’re breaking the show into seasons, and in each season we’ll dive into a new area of complexity research. 

Chris: And in this season, we’ll explore my field of research, the physics of life. I’m Chris Kempes, professor at the Santa Fe Institute, and I’m interested in uncovering the laws of life in the universe.

Abha: And I’m Abha Eli Phoboo, director of communications at the Santa Fe Institute. Today, we’re going to look at what physics can tell us about life and evolution — in three parts. 


Abha: Part One: Breaking the walls of academia


Abha: Before we launch into our two guests, Chris, tell us a little bit about your work in this area. How did you become interested in science, and were you always interested in both physics and life?

Chris: Yeah, I grew up in a tiny town in rural northern New Mexico, and that town had an amazing night sky, where you could see the Milky Way every night and tons and tons of stars were visible. And it was home to an amazingly rich fossil bed where the state dinosaur Coelophysis was found and many other dinosaurs have been found since. And for me, I was sort of fascinated by both stars and dinosaurs. There was something about the depth of time, the largeness of what both of them conveyed to me, it brought out something deep in me. And that was really how I got into science. And I'd go around telling people I want to be both a paleontologist and an astronomer. And then when it went time to apply for grad school, I realized I wanted to do this intersection of things that I called physical biology, and I actually designed my own course of study once I was admitted to MIT focused on exactly that. And then I eventually did some work that got me invited to an astrobiology conference. And I went there and I said, “Right, I am an astrobiologist! Right, I am this paleontologist astronomer, and I've been doing it all along. I just forgot what to call it.” 

Abha: So your work has been very interdisciplinary because that's sort of how we work at SFI. And I wonder, what's your experience been like as a researcher whose expertise doesn't fit squarely into one category, like physics of biology?

Chris: So, there's a sociologist and philosopher I really like who says the disciplines are really a practical concern. There are ways to organize people and funding and so forth, but they don't really have intellectual merit. And I think that's very much the way SFI sees the world. We're much more driven by questions, overarching questions, than we are by someone's particular history of training or the field that they might have quote unquote “grown up in.” Because SFI has no departments, it’s a really unique feature. And for me, that's a relief because I want to think about all of those things and understand where the connections are between different frameworks of thought. And in fact, there's not much of an organizational structure beyond just the fact that we have researchers who mix together and exchange ideas and who share sort of a common view on the world. And I think this is at one point how science was done. A deeper way to think about it might also be to say a lot of the ways the disciplines have evolved are purely dependent on happenstance, and they're sort of arbitrary in lots of ways. For example, biology could have become much more interested in the social phenomena of humans, and we could find that sociology had never become its own field, and it always sort of situated itself as a subfield of biology. And that tells us that a lot of the trajectory of a discipline is based on the particularities of history. And so if we get away from that, we might be able to make huge amounts of progress because we get away from things that are sort of arbitrary, and that’s part of why people find this exchange between disciplines so useful. 

Abha: So we’re making the case that physics is a fundamental part of life. It’s a huge, broad area of study, and today we'll zoom in and land on just a couple examples of how physics and life are intertwined. We’ll explore how physics limits the way we humans think — how our brains work and how much we're able to comprehend. And we’ll investigate the way physics limits our human lifespans. 

Chris: If you could start by introducing yourself —

Vijay: Sure, my name is Vijay Balasubramanian and I'm a theoretical physicist by trade. I work broadly in the field on everything from the quantum theory of gravity to biophysics and complex systems with bits of condensed matter physics and occasionally things involving cosmology on the way. So yeah, that's what I do.

Abha: Vijay takes a pretty broad approach to his work, and he tells us how his curiosity about the world led him be to a scientist.

Vijay: When I was seven, we were living in Calcutta at the time and Calcutta has this very big culture of sort of booksellers who, you know, small booksellers who have books in little closets in the wall, my parents got me a big thick volume written by somebody named Arkady Leokum —  I remember his name — called Tell Me Why and the book consisted of a very large number of questions and I flipped the thing open and the first question I saw was, “Why is the sky blue?” And I thought “Yeah! Right on! Why is the sky blue!” And the guy explained it with scattering of nitrogen molecules and everything. Wow. Then I flipped another page somewhere. And it said, “Why does the moon follow you as you drive around?” I was like, “Yeah, yeah! Why does the moon follow you as you drive around?” And then he explained it as because the moon's very big and far away and stuff like this. And I was completely hooked. I think I knew I would want to be a scientist, but you know, when you're seven, you can't articulate these things particularly clearly, whether it's physics or neuroscience or whatever. It's all the same. You know, you want to work out the way the world works.

Chris: He may say that it’s all the same now. But when Vijay was younger, his focus was much narrower.

Vijay: So I was one of these students. So when you're growing up in India, you didn't have access as much in those days to sort of biological laboratories and things like that. Smart kids typically wanted to go into physics and math. In many cases, my own inclinations lay towards physics and math because I always perceived those fields as having this sort of... pristine beauty where there's a very small number of principles that you've got to remember you can derive everything else.

Abha: Vijay saw biology as more qualitative — all these things to memorize, rather than that pristine beauty of a few core laws. He managed to argue his way out of every biology class he could until it was —

Vijay: Towards the end of my PhD in physics that my PhD advisor said, “Well, you know, there's this whole field of systems neuroscience.”

Abha: He had been studying computers, and he loved programming and machines. The machines had limits to what they could do and how much they could compute, which got him thinking —

Vijay: That there was something about the thinking machine inside my head that would constrain the way I thought. That is to say, a cat thinks too, but it can't do calculus. So I assume that whatever algorithms my brain can implement, there are many things I can't do because of the nature of the computer inside my head and its constraints.

Abha: Basically, how do we know what we don’t know? What are the limits of the brain? Suddenly, for Vijay, biology was looking much more appealing.

Vijay: But the fourth year of your PhD is not a good time to switch into something else. You need to finish something. So I got my PhD. And then as a postdoc, I began to moonlight the evenings in a neuroscience lab, read more papers, learn more, you know, it's a... very big field with an enormous amount to learn, especially for somebody who made the mistake of skipping all the biology classes all those years.

Chris: So Vijay’s love of science started when he was a kid, but he felt like he was behind when he realized he liked biology, not just physics, as a late-stage PhD student. But, he’s not the only one who felt like he arrived late.

Abha: Could you tell me about why you wanted to look into life when you were really a physicist to begin with?

Geoffrey West: Well, yes, it wasn't so much life, it was more death, to be honest.

Chris: That’s Geoffrey West, theoretical physicist, former president of the Santa Fe Institute, and founder of the high energy physics group at Los Alamos National Laboratory. In the early ‘90s, Geoffrey was working on something called —

Geoffrey: The Superconducting Super Collider, this big particle machine being built in Texas.

Chris: It was receiving funding from multiple sources, including the U.S. government. But over time, the costs ballooned and foreign investment that had been expected never materialized. Eventually, the Clinton administration decided to cut them off.

Geoffrey: And we were left high and dry and there was a sort of a death process associated with it. But it was very threatening to the field of high energy physics, elementary particle physics. And it coincided with me being sort of in my early/mid-50s. And it turns out that I come from a short-lived line of men, people who die young, and I had always expected to die relatively young, meaning in my early 60s, and here I was in my 50s, and here was this machine that was the lifeblood of the field, and it was dying, and in fact died. And I began to be conscious of my own death. But at that time one of the big comments that was bandied around, not just by other scientists, but by people in the Department of Energy and the administration, was that physics was the science of the 19th and 20th century, and biology is clearly gonna be the science of the 21st century, and so to speak, we know enough physics was the corollary, so there's not much point in doing any more.

Chris: Those weren’t the exact words they used, but it was the general attitude.

Geoffrey: I reacted saying, without knowing any biology, by the way, saying if biology were a real science, it would have to incorporate the paradigms, culture and techniques of physics to make real progress and move from something that I perceived as being qualitative into something that was more principled, more mathematical, more computational and more predictive. And of course I knew no biology and it was a very arrogant kind of high energy physics thing to say, but it did get me thinking that, maybe, I should put money where my mouth is. And that's what started this because I thought, well, maybe I should start thinking about why is it that since I have impending from my viewpoint, I had impending mortality that, that human lifespan is in the order of 100 years and not a 1,000 years, 1,000,000 years or ten years. What the hell determines it? And I started looking at the literature and discovered that the whole question of aging and mortality was at that time quite a backwater of biology. And I thought, well, maybe this is a good problem to just start thinking about, get me thinking about some of these questions of death.

Abha: Both Geoffrey and Vijay made this transition from physics to biology because they wanted to understand human limits. Why our brains are limited in how much they can think, why our lifespans are limited to a hundred years, if we’re lucky. Are there underlying laws that explain this?


Abha: Part two: Vijay, the brain, and energy


Chris: Something that fascinated Vijay was the fact that when information becomes too big or complex for us to wrap our heads around, we use shorthands to describe it. In complexity science, this is known as compression, or coarse graining, or effective laws, it goes by a few different names. For example, think of a crowd versus two people sitting in a room. You can picture two individual people having a conversation, but if you think of a crowd —

Vijay: We're not capable, of course, of thinking about the crowd in terms of all of the individuals, it’s too difficult, it requires too much computational power. And so you compress it.

Abha: We compress it because we have to. Vijay uses this story, Funes the Memorius, to show why.

Vijay: … This story called Funes the Memorious by Jorge Luis Borges. I don't know if you know the story, there's a guy Funes who gets kicked on the head by a donkey or something. And when he wakes up, he has this perfect ability to understand and know everything in complete detail. So we see a tree, he sees the tree and all of its individual leaves, and therefore doesn't see why one tree is in the same category as the other tree, because it isn't, right? It's shaped differently, it's got different leaves, and he slowly loses the ability to think, because the ability to think and cognition is really about this process of making effective theories about different things. It's about compressing the complexity of all the detail into these effective concepts.

Abha: In a way, these effective concepts, these shorthands we use to describe complex things, are a form of efficiency. There’s a limit on what we can comprehend, but compressing the details allows us to move through the world anyway. And the brain is surprisingly efficient in the way it uses energy.

Chris: So all biological processes require some amount of energy to function. And so energy budgets, that is how food gets turned into ATP and how ATP eventually gets used for various things, to me is sort of one of the central challenges biology has to deal with, is this finite energy budget that is given to an organism. And that's also true for the brain. The brain gets a certain amount of energy from the body and has to do everything that it does with that energy budget. And so I've been really inspired recently by lots of work showing that the brain in many cases seems to be operating with sort of enormous energetic efficiency. There are certain computations that happen in the brain that seem to be pretty close to the physical limit —

Vijay: Yeah. I think the brain, like everything else in life, is a very constrained organ. It's got only so much space. It's got only so many cells. It's got only so much energy. \\ The brain is the most expensive organ we own in terms of energy consumption. And, you know, it has to conserve all of these things. It's also got only so much time because, you know, if I have to make a decision and I take a day to do it, it'll probably be too late. Things have to be done quickly. So all of these things, I believe, constrain the architecture of circuits. You have to do things quickly. You have to do things efficiently with few components and burn less power.

Abha: The fact that there are physical limits constraining the brain, and the fact our brains are so good at using what they’ve got, is pretty amazing. Studying the brain this way also blurs the line between old-school physics and old-school biology, because it’s a living organ that’s always using energy.

Vijay: You know, historically, the systems that have been easy to study in physics that have been historically studied are either at equilibrium or close to equilibrium. They're at rest and they move a little bit and so on and so forth. Now, what's very interesting about anything living is it's inherently out of equilibrium. If you are at equilibrium as a living thing, you're dead, right? So really the way life works is it brings in energy on one side and funnels it through the system and uses that energy to do all kinds of crazy things, like talk about physics. So there's this whole field of something called active matter in physics, whose goal is to understand systems like that, where you funnel energy through it and you can get completely crazy dynamics things that violate Newton's laws, for example, because they're burning energy on the way. So the inspiration from all of these kinds of biological systems is now fueling, you know, a minor revolution in parts of physics and soft matter and living matter physics to study these kinds of complex systems, which are inherently out of equilibrium. 

Geoffrey: The laws of physics are universal. I mean, the fundamental laws have this kind of universality to them, this immutability, namely that, you know, it is assumed they apply everywhere, something that was first postulated discovered by Newton to recognize that his laws of motion that deal with balls running down little hills or horses pulling carts or whatever, are the same laws that determine the motion of the moon around the earth and the planets around the sun and everything else in the universe. That's what's kind of extraordinary. And so therefore, they obviously apply to life. And I think one of the interesting questions is how far can you take that? In understanding life and biological phenomena.  


Abha: With Vijay, we learned that the size of the brain and the way it uses energy create limits on our ability to think, to literally, compute. And we also learned that although living organisms are not at equilibrium, the way, for example, a rock is, there are still physical laws that apply. Next up: we’ll look at the limits on our lives. Why humans die at age 100 and not 1,000, why trees don’t grow forever and ever up to the sky, and why sleep is so important. 

Abha: This is Part Three: Geoffrey and the scales


Abha: By now, you’ve probably noticed that Geoffrey sounds like he’s outside. And Chris was actually there with him. 

Chris: Geoffrey West and I have been in South Africa together for a week. We're both teaching at the Complexity Global School. When we sat down for this conversation, it was on a deck overlooking a dry riverbed where the savannah gives way to slightly denser forest. And just across this dry riverbed is a watering hole. We've seen all manner of animals, zebras, impalas, baboons, monkeys. And there's a hyena around, although neither of us have seen it. 

Geoffrey: …this big particle machine that was being built in Texas. And sorry, I have to stop. Listen, you know why? We're hearing the roars of lions just below. Yeah, there's a baboon right here. Is that what it is? Yeah, it's a baboon, yeah. 

Chris: There’s some mongoose.

Geoffrey: Ahh the little mongoose. That's great. Oh, that's wonderful. Look at them. What do they eat? They must be eating little insects.

Chris: I think they're after the insects.

Geoffrey: The insects that. Oh, they're probably eating all these.  

Chris: All these insects 

Geoffrey: All these little insects

Abha: But anyway, back to the laws of physics. How do they apply to these baboons and mongoose and animals that are all around? Since Geoffrey began studying life, one physical limit he’s examined in depth is the concept of scaling laws. He’s written a book called Scale and co-authored multiple papers with Chris. And he’s thought about how it applies to everything from animals to entire cities and societies. 

Chris: Why is it that these regular patterns emerge like scaling laws? I think you and I have talked a lot about this, about why is it that physics should show up in evolutionary biology? 

Geoffrey: Scaling law basically says that in terms of almost anything that you can measure about the physiology and life history of a mouse can be related by a simple mathematical formula to those same physiological phenomena and life history events in an elephant or a human being or giraffe and so on. And they are connected all together in a simple way. But the important thing is, the thing that distinguishes conceptually the biological from the physics from that viewpoint, is that, when it's applied to physical phenomena — the planets around the sun, etc. — those laws have a certain precision and exactness that we believe. That is a different character in biology because it is in fact an evolving adaptive system. It's continually changing in variance. And one of the interesting questions I think about scaling is how much are you allowed to deviate from the scaling laws? You know, how much variance, so to speak, are you allowed and still be functional and still be competitive?

Abha: If you were to plot the size and organ functions of all different animals, you’d see that there is a pattern, a law underlying all organisms. But as you move up in size and complexity, the pattern isn’t a simple, straight line.

Geoffrey: What happens if you take some object or some system and you scale it up, meaning double its size, triple its size and so on. What happens to it? Does, you know, you double a city, does it have...twice as many roads? Double the size of an animal? Does it have twice as fast a heartbeat and so on? How do the systems respond? That question, which was one of the first questions in modern science to be asked, has opened up all kinds of vistas. And indeed, the first person to ask it was the founding father of modern science, Galileo, who asked the question. “Why can't we have infinitely,” I mean, didn't use these words, but “infinitely tall trees or buildings? What stops us?” And he used a scaling argument and the scaling argument was the scaling of, you know, if you double the size you double the weight, but he realized if you double the size you don't strengthen strength. Strength of beams or legs or limbs in general do not increase linearly, and this is the point, they increase nonlinearly, and eventually weight crushes the strength. 

Abha: Think about the metabolism of an animal, how much energy it uses.

Geoffrey: You know, everything is evolved by natural selection. And so you would think that an animal that is twice the size of another, that is a different animal, you know, things would be quite different because they have a completely different environmental niche, they have a different history and so on. And one of the things the data showed, is that an elephant is actually not just a scaled up mouse but a scaled down whale and a scaled up giraffe, which is a scaled up human being, biologically, which was sort of mind blowing actually. And to understand that in terms of the underlying dynamics, that's what got me and ultimately you very excited about working on these issues and using that as a window onto underlying principles.

Chris: The idea is that basically, if you took a mouse and blew it up to be the size of an elephant, it would behave surprisingly similar to the elephant. Now, obviously it wouldn’t grow a trunk or suddenly get giant, floppy ears. But its metabolism would slow down, and it would sleep less, and both would happen in a predictable, but nonlinear way. Geoffrey, and one of his co-authors, Van Savage, have actually created a theory that predicts how much an animal should sleep based on the way its metabolism scales up or down.

Geoffrey: We got this result one day and we were very excited. And we had it on the board. And I said, “That's great.” But I said, “You know, there's a real problem here. If you put in the numbers, as I did on the blackboard, an elephant should only sleep for about three or four hours, which is obviously nuts!” And so I went away, we went away, there must be something we’re missing here, and then I got a call from Van, who said, “Hey, guess what? I looked up the data. Elephants sleep for three or four hours,” in fact, two to three hours, in fact, is what they do sleep. So that was fantastic. And so this explained why it was that elephants sleep for such a short time, and why mice, for example, sleep from 16, 17 hours, and also why you and me, used to sleep for 16 or 17 hours, you know, when we were babies. And as we grew... ontogenetically, we needed less and less until we settled down at eight, which this theory explains.

Abha: Remember Geoffrey’s original question, as he was expecting death? Why do humans live on a scale of 100 years, and not 1,000? It turns out, sleep is a big part of the answer.

Geoffrey: Sleep is like death, or maybe one can console oneself at my age that death is like sleep.

Abha: And sleep is crucial to life.

Geoffrey: The very processes that are keeping you alive, metabolism, the biochemical production of so-called ATP, which is sort of the complex molecule that is our currency of energy, gets of course sent through our various networks, particularly our cardiovascular system, to supply energy to cells —

Abha: And metabolism produces wear and tear on our bodies, just like a car or a washing machine or the pipes in your home get worn out over time. Our bodies are not at physical equilibrium, the way a rock is. 

Geoffrey: We have evolved repair mechanisms to deal with those. But repair is exceedingly costly. Natural selection has evolved us so that the repair is good enough so that we live to at least 35 or 40 so that we can have a dozen or so children, and then natural selection doesn't care, and we die. So that's the relationship to death, and indeed, the expected lifespan of human beings until this last century or so was close to 40 years or even less in many cases. So you don't care that you don't exactly repair your liver or maybe your lungs and so forth, because as long as it lasts for 35, 40 years, great. But there's one organ that you better repair faithfully, and that's your brain because that damage very quickly results in you not being you after a relatively short time, so that the repair mechanisms are very strong in the neural system in your cerebellum, cortex and so forth. And that's why your brain takes proportionately much more energy, metabolic energy than the rest of your body, it's because it's fighting the forces of entropy that are, well, eventually, if you didn't combat them, would, well, you'd die.

Chris: So scaling laws, ultimately, determine our metabolisms, the wear and tear on our bodies, and how much we sleep. And eventually, that wear and tear accumulates so much that we die. Like Vijay said, our brains have physical limits that determine how much thinking we can do, and how much we can understand. There are outliers everywhere of course — in fact, one of the interesting things about life is that it’s incredibly diverse. But these limits and laws do connect everything in the natural world in a natural way. Here’s Vijay again.

Vijay: I don't really recognize a distinction between physics and necessarily the other sciences. I think we should be careful about that. Back in the day of Newton, there was no physics. There was natural philosophy, which was supposed to be the idea that natural philosophers could attempt to quantitatively and precisely describe all the phenomena of the world. And I'm totally confident that if Newton had access to the experiments we have today in biology, he would absolutely be thinking about these and there'd be a Principia Mathematica Biologica or something. So I'm sure of that. I mean, physics didn't develop techniques to really think about systems that look like they're living. But that's going to change very rapidly. I think there are biologists who will just invent the techniques and then there are physicists who will say this stuff is too cool not to be involved in and they will come in and also help to invent the techniques. In fact, that's happening already. Many, I would say both Chris and myself come from that tradition, as do many others.

Chris: The way brains use energy, the limits on our lifespans, and the scaling laws that shape it all — it can feel really abstract if you’re not a scientist. But, I think despite the chaos of our world, it’s comforting to look at life all around us and know that there’s a simple structure holding it all together. 


Geoffrey: I'm just looking here at this forest. And of course, it looks like a bunch of different sized trees, different species. It looks like some arbitrary mess. And the wonderful thing about having done that work, was that it revealed an extraordinary kind of systematic regularity in what superficially appears to be random and chaotic. And I have to say, I'm reluctant to use the word, but sometimes when I'm walking in a forest situation, and sometimes even in a city, I feel almost a spiritual experience. And maybe it's a bit of arrogance that here I am walking and not seeing it as just some very specific individual thing that has sort of, has of course its own unique history. But I can see that it's evolved to obey these extraordinary mathematical equations. And I'm blessed to understand why. 


Geoffrey: So it's a kind of arrogance that exists there, but it's also being part of it, feeling that I'm sort of at one with it.


Abha: That was Vijay Balasubramanian and Geoffrey West. Next time, we’ll ask how life began and what it might look like outside our own planet.

Sara Walker: And so information and time and matter are all kind of the same things in assembly, and they’re manifest in objects that are deep products of evolution.

Abha: That’s next time, on Complexity. Complexity is the official podcast of the Santa Fe Institute. This episode was produced by Katherine Moncure, and our theme song is by Mitch Mignano. Additional sounds from Blue Dot Sessions, Pink House Music, Eardeer, and Craig Smith. I’m Abha, and we’ll see you next time.