About the guest: Robert Barton, PhD is an evolutionary anthropologist and Professor at Durham University. He studies the evolution of the brain and behavior across species, including humans.
Episode summary: Nick and Dr. Barton discuss: mammalian brain evolution; how brain and body size scale across mammals; how metabolism relates to brain size and function; the evolution of the neocortex & cerebellum in primates & humans; the concept of “intelligence” and whether it relates to brain size; and more.
Related episodes:
Evolution of Complex Behavior, Perception, Cognition, Consciousness & the Brain | Paul Cisek | #107
Organisms, Cities, Companies & the Science of Scale | Geoffrey West | #12
*This content is never meant to serve as medical advice.
Support M&M if you find value in this content.
Full audio only version: [Apple Podcasts] [Spotify] [Elsewhere]
Episode transcript below.
Full AI-generated transcript below. Beware of typos & mistranslations!
Robert Barton 3:42
Yeah, so my name's Rob Barton. I'm an evolutionary anthropologist, but that means that I have a pretty diverse background. I started in zoology, but also did psychology, and have always been interested in the kind of intersection between those two disciplines. Went on to do biological anthropology for a masters, and started to get interested in questions to do with the evolution of the brain. And I've been, you know, I've resided in psychology departments and interacted with cognitive scientists and neuroscientists, but wound up in an anthropology department, and that's really why I call myself an evolutionary anthropologist. It's a matter of taste as much as anything else. But broadly, I'm interested in evolutionary theory and what it can tell us about the evolution of our own species, but particularly in relation to the brain and cognitive abilities.
Nick Jikomes 4:51
Yeah, I actually started out myself. I was a zoology major in college, and I was studying evolutionary biology and. Before I went into neuroscience. And one of the things that I value a lot about that kind of educational trajectory is when you study Comparative Zoology and evolutionary biology and evolutionary genetics, you really it really teaches you. It taught me at least the value in the comparative approach, that even if you're interested in humans, say you can actually learn a lot by studying other creatures and understanding how and why they're different, and that's very much what you seem to do. So we're going to talk about a lot of different species and comparative biology here, but I think a lot of it will be anchored in the human brain and understanding humans. What I wanted to start out with is a very simple question, how big is the human brain in absolute terms and compared to other creatures?
Robert Barton 5:47
Well, it's not necessarily the largest brain in absolute terms, because there are whales that have larger brains, but in relative terms, it's generally considered, when you take account of the overall size of the animal, relate the size of the brain to the size of the body that amongst currently living species and any fossils that have been discovered so far, humans have the largest brains relative to their body size. So if you compare us to our phylogenetically closest relatives, the other great apes, such as chimpanzees and gorillas, our brains about our bodies are not that much different. In fact, we're smaller than gorillas, but our brains are up to about three times larger. So something happened in this sort of approximately 7 million years after the divergence of the hominin line leading eventually to us on one hand, and the line that ended up in modern living chimpanzees, something pretty unusual happened On the branch leading to our own species.
Nick Jikomes 7:02
And if we look at all of the fossil humans and pre humans, between the divergence from chimpanzees up until present day, Homo sapiens was was the increase in cranial volume and brain size? Was that uniform? Was it non uniform over time. I often hear things not necessarily from scientists or anthropologists. People often say things like, the human brain doubled in size in a million years, a sense for what did that tempo of change look like?
Robert Barton 7:31
I mean, that's a really good question, and one which is still being debated. And actually, my co authors have a paper under review at the moment that has something new to say about that, so I can't really talk too much about that, but in general terms, what we see when we look at the hominin fossil record reflects what we see when we look more broadly across the Tree of Life, which is that the tempo. Patterns and tempo of evolution are tremendously variable. So you don't see a single kind of uniform pattern. You see variation in rates of change at different things happening on different branches of the tree. And you know, we've, we've tended in the past to think of human evolution, certainly about when I was a student, you know, the story was pretty simple. You had a few Australopithecines, and then the advent of our own genus, the genus Homo and then eventually, sort of archaic homo sapiens. And the things were, you know, just kind of increasing, changing gradually over the last 7 million years in a fairly sort of linear sort of way. But now the fossil record is so much richer what we have now, we can see that there were lots of different things happening on different branches of that part of the tree of life and brain size, you know, didn't change much initially, but it then started to expand quite rapidly. And so the overall pattern that we see is one of accelerating increase towards the present. So and that's kind of suggestive of some kind of positive feedback process. We don't really know why though there was escalating acceleration in increase in brain size, but it is consistent with ideas about positive feedback of some kind, for example, possibly between between cultural change and biological change, some feedback between biology and culture. But we've also now, we've also just just quickly. We've also now got. Fossils that tell us that, you know, none of this was uniform. So there are relatively recent hormones with small brains, and possibly we see brain size reduction happening in some lineages. So there was nothing kind of inexorable and inevitable about the pattern. It was tremendously variable. And that's one sort of big lesson that over my career, the data has taught me, is that patterns are very complicated.
Nick Jikomes 10:32
Yeah, yeah. So different patterns on different branches, even the pattern presumably changes on the same branch at some point, if you just look long enough when you say a positive feedback mechanism that accounts for this sort of accelerating increase in brain size in our lineage. I understand that we may not know exactly what that is, but in principle, what could that look like? Would that be? Would one way to think about that be like? Maybe there was selection, for some reason, for a larger brain this sort of unlocked our ability to have richer social interactions and develop a richer culture, which then creates a social additional selection pressure for an even larger brain. Would that be like one way to start thinking about that? Yeah,
Robert Barton 11:13
and that is the kind of classic Machiavellian intelligence hypothesis, kind of arms race in socio cognitive abilities. You know, the smarter the other individuals in your group are, them, the smarter you need to be. And, you know, and that's one possibility. For many years, the so called, sort of social brain hypothesis really held sway. It's been somewhat more questioned in recent years as a kind of the explanation of everything, but it's a distinct possibility that social life was a really important factor in the evolution of the brain, and it could that kind of feedback could account for the acceleration we see on the hominin line. But, yeah, we don't know, and it's always going to be difficult, because behavior doesn't fossilize, is going to be, yeah, to say what it was.
Nick Jikomes 12:06
The other aspect of human brain evolution I want to talk about is, obviously our brains got bigger. But to what extent did the brain just sort of uniformly scale up in size, versus to what extent that certain areas become larger relative to other brain areas.
Robert Barton 12:24
So you've hit upon, you know, something that is another sort of big debate in the field of evolutionary neuroscience. You've pinpointed it exactly. And I've become identified with a position that, you know, broadly, you can characterize as the mosaic brain hypothesis, which is that you know, and again, it goes back to what I was saying about things being complicated. It's quite interesting that often people like there to be simple patterns that explain large swathes of data in with a simple model. And one of those models was the idea that just everything, as you say, just scales up together. And that's basically the story of brain evolution, that all the different systems and structures within the brain expanded together. Now that is partly true and but interpretations of what's going on with that coordinated increase vary. So one idea about that is there's some kind of developmental constraint that the easiest way to grow a big brain is just to carry on growing it for longer along the same developmental pathway, and that leads to everything getting bigger. But there are other reasons why you might get those patterns of coordinated change, and that's because functionally, the different parts of the brain are, you know, highly interconnected and functionally interdependent. And you know, one of the things that you know, we've realized is that when you look at the comparative data, it can be a little bit misleading, because the easiest way to get data on brain structure and brain size and the size the volumes of or numbers of neurons in in different parts of the brain, is to Just segment the brain in, you know, sort of anatomically, relatively straightforward ways into the traditional kind of segments of the cortex and the midbrain and the hindbrain structures and so on. But that segmentation doesn't really capture the way that the functional systems are organized because they cut across those those crude segments. And when you start to look at things more in terms of specific pathways and networks that cut across those systems, you see more evidence for Mosaic change. So for example, i. My work on the evolution of the primate brain, I got very interested in the role of visual specialization. I don't know if this is a good moment to talk about that, but yeah. So again, this was something that really sort of just came out of the data at me. It wasn't necessarily something I was looking for, expecting to find, but it gradually emerged from the data, and it kind of tied up with what we know about primate biology and Behavioral Ecology and the importance of vision. And what we found is that a lot of the variation in the size of the brain in primates and in the size of different brain structures within primates is accounted for by expansion of the visual system. So primates have, compared to other mammals, incredible visual acuity. Some species have particularly good color vision. Primates do all sorts of different things with their visual system, in particular, visually guided manipulation, which ultimately, in hominins, led to our ability to make and use tools and that kind of thing. And so when you look at it in those terms, we see, you know, structures within the neocortex of the brain, but also in the midbrain, the visual relays all the way back to the peripheral anatomy, to the eyes, to the degree of binocularity and stereopsis that that facilitates, and you can look at it in terms of the volumes of the optic nerve, or visual structures in the brain, the numbers of neurons in those structures, and in all these cases, what we see is relative change, relative expansion of the visual system relative to other systems in the brain. But you'd kind of miss that if you just looked at the growth segments of the brain. So to some extent, you know, that debate has kind of moved on, and I think we have a richer understanding that what's going on, and it's a combination of coordinated and Mosaic change. Yeah,
Nick Jikomes 17:12
I would imagine that because we have a lot longer lifespan humans do compared to many other creatures, because we have a longer developmental period, early developmental period, some much of the change of brain size can be accounted for by just having more time to build more brain. But as you said, there's also seems to be some mosaicism here, where we belong to a lineage of creatures that use vision a lot. So our brain is very visual, I guess you could say, and I guess one way to quantify that, or think about that, is just to look at how much real estate in the cortex is dedicated to that sense versus other senses. Stepping back from the visual cortex and the visual system for a moment at least, what about the whole cerebral cortex? Sort of a classic, I guess, cartoon story that you often hear about why certain animals, like primates, are very smart, is that the cerebral cortex is really the important part of the brain that got bigger. To what extent is that true? Can
Robert Barton 18:16
I Can I just preface my answer with a more general point, which is that it's really important to distinguish between explanations for, you know, human evolution and for macro evolutionary patterns more generally and often we conflate them. When I'm talking about things like visual specialization, what I'm talking about is a macro evolutionary pattern that explains, you know, some a good proportion of the variation in something like brain size across the whole primate order, as I mentioned at the beginning. However, different things happened on different branches, and so that's only a part of the story, that lots of other interesting things going on as well, and it doesn't necessarily tell you that much about human brain evolution specifically, it turns out actually there is. There are some really interesting data suggesting that there are visual specializations that occurred in the hominin lineage as well, but different kinds of specializations. But to go to your question, which was about the forebrain and the neocortex, I you know, and again, to sort of rewind to where I started, when I started looking at these things, I accepted conventional wisdom. I started out with the same kind of assumptions that there is an intelligent part of the brain, you know, which is where all the all the action happened, evolutionarily speaking, that expanded most and. During evolution and endowed humans with our intelligence, and then that, you know, that's the basic story. And really, you know, what I could do with comparative data is go out and test a few ideas about why that might have happened, but over the years, the patterns that emerge from the data again, you know, indicated that there's much more complexity to the story. And actually it's much more, a much more interesting story, because biology is really, I mean, it's gloriously messy, I always think, and so it's too and it's too messy and complicated for these kinds of simple notions to really stand up to to close scrutiny. So you will still see in, you know, reviews in the literature, in a lot of the literature, statements about the neocortex being the intelligent part of the brain that expanded most. I've even seen eminent neuroscientists referring to it as the pinnacle of evolution. And actually this, this portrays another interesting thing about the culture in this field, which is the kind of scar and naturae perspective that looks at humans and takes humans as a kind of an end point of a process, and then projects back and expects everything, all the data, to be sort of simply explained by a model that accounts for how you get from, you know, a chimpanzee to a human, or from a shrew to a human, and as I say, that underplays the variability and the complexity. So anyway, that's a kind of slightly conceptual issue, but your question, I think more importantly, relates to empirical questions. And as I say, I started with the same kinds of assumptions, but the data led me down interestingly different tracks, and we started to find sort of slightly unanticipated patterns and kind of the first one of the first clues to this was when we found that the forebrain, in particular, the neocortex, and an area of the hindbrain, the cerebellum, exhibit a very strong pattern, relatively strong pattern, coordinated evolution. So once you've accounted for change in the rest of the brain, in other brain structures, this supposedly sort of basic kind brain structure, the cerebellum, that has been associated with, you know, basic regulation of motor functions, balance coordination and was kind of dismissed as being an interesting evolutionarily and cognitively seemed to expand in close coordination with neocortical areas. So that goes back to what I was saying about the patterns that we see reflecting very distributed neural pathways are distributed widely across the brain. What it suggested was that neural systems that cut across those structures, that integrate those structures, have been really important. And we found that in mammalian brain evolution, generally in primate brain evolution in particular. So that meant we started to get really interested in the cerebellum and what the cerebellums doing, and at the same time, rather sort of satisfyingly, or similar, sort of similar timing in cognitive neuroscience, people were starting to get interested in the cerebellum and say, Hang on, like it's this is an interesting structure. It does some it's involved in some very, you know, complex aspects of cognition and behavior. And we can't just write it off as something that, you know, a structure that's not involved in cognitive processes. And now, I think it's very widely accepted that the cerebellum has crucial functions in all manner of of cognitive processes. And it it's partly well, to a large extent, it's serving those functions by communicating with the neocortex and particular cortical region. So we see these, these reciprocal cortico cerebellar networks loops that have. That project to different areas of the neocortex, different functional areas and different functional areas of the cerebellum, but have a very similar kind of architecture, designed in a very similar way across those different subsections of those structures, as though there's some kind of general computational process that those different loops with different functional kind of implications carry out. So there's both kind of functional divergence, but but also some commonalities. And so that's that's kind of something that people, both in cognitive neuroscience and evolutionary neuroscience, have become increasingly interested in.
Nick Jikomes 25:47
So it was noticed that there's this evolutionary relationship between the neocortex and the cerebellum. They seem to be sort of coupled together in our lineage. I guess one explanation for that might have been that, well, maybe there's just, developmentally, there's no good way to grow the neocortex without growing the cerebellum, and it's just sort of a side effect. What you're saying is, over time, just in the neuroscience literature, neuroscientists have changed their view of the cerebellum. It used to be thought of as purely like a motor coordination structure. It wasn't doing the cognitive stuff. But over time, we've come discovered that, in fact, is and then it would perhaps make more sense that if it's actually participating in cognitive functions, if it's hooked up to the neocortex in very interesting and to a large extent, in interesting ways, that maybe there's a functional reason why these things are coupled
Robert Barton 26:39
absolutely and I think it's, it's a, I can't remember the date, but it goes back quite a long way that people had dissected, just dissecting out the human brain. Had actually observed that the fibers connecting those two structures are so big they're visible with the naked eye. I mean, these massive connections between them. So it absolutely, you know, makes some kind of functional sense that they should evolve together if they're working together to that extent. And, you know, I think so. So there's a couple of other implications in relation to what you're saying. One is that the whole distinction, I think, between sensory motor processes, as you know, some kind of basic fundamental thing that you know, is separate from cognition and cognitive processes, which, you know, we tend to associate with humans. And I always think of Rodin sculpture of the thinker, the guys sitting on the rock contemplating the mysteries of life, the universe and everything. But actually, you know, our brains didn't evolve to enable us to sit on a rock contemplating mysteries of life, the universe and everything. That's kind of a side effect of the capacities that we have. It evolved to enable us to interact physically in complicated ways with our world and to plan our activities. And we now know that the cerebellum is really importantly involved in planning process is not just planning a movement, a grasping movement, for example, but in planning beyond that, planning patterns, complicated sequences of behavior. There's a theory called the cerebellar sequencing hypothesis, which suggests that the cerebellum has a particular role in organizing complicated sequences of actions, and obviously you know that that could relate quite nicely to what we know about the evolution of tool making and tool use and dominance. So that whole sort of distinction between cognitive on one hand and sensory motor on the other, I think is interestingly breaking down, and has been for some time. And I'm particularly interested in notions of embodied cognition, which is really about, you know that cognitive systems evolved from the systems that were originally there to control the body, and that that's the way to understand the evolution of neuro cognitive systems, is how they enable the individual to sort of interact usefully with its physical world. Then the second thing that I wanted to pick you up on was where you talked about patterns might just be, where you might be able to explain them by development as so that's an alternative and to me, that's not an alternative hypothesis, and that it's true that it has sometimes been construed in that kind of way. And going back to what we're talking about covid. Coordinated versus mosaic evolution. You know, one idea about the coordinated evolution of brain structures as you as you mentioned, is that just the, you know, it's easier to develop a big brain, but by growing everything together. And there was this idea around for quite a while that there might be developmental constraints on how brains evolve, and that if you the if you just tweak developmental timing, then all kinds of things change together, and that, that might be why you see correlations between, for example, brain size and longevity, and the juvenile period maturation time, and all of those life history variables that you were referring to. But I actually think that's putting things the wrong way around. So we published a paper about 10 years ago, looking at mammalian brain size and development, looking at the patterns, there's been a lot of kind of focus on lifespan and longevity and and the possible role of longer lives in cognition and brain size, but what we found was that there were fairly sort of straight forward connections between developmental processes. So for example, the growth of the brain in utero in mammals and the size of the brain of the newborn animal, and that that already set some of the variation in adult brain size. And then after birth, there was further variation in the time taken to grow and develop. And together, those two periods, the prenatal period and the postnatal growth period, could really adequately account for variation in brain size, and that once you accounted for those life history variables, there was no correlation with lifespan anymore. So the lifespan correlation seems to be a side effect of development, and that emphasizes that there is a close connection between developmental processes and the evolution of large brains, but I would tend to see that as Being a case of when selection selects for particular capacities that has, you know, consequences in terms of brain systems, neurons in within particular systems, and perhaps overall brain size, And that works by selecting for particular developmental processes. So when the selection on brain size, to put it simply, then development has to change as well. And in fact, evolution is working through the developmental processes to produce brain adaptations, rather than, you know, brains being a side effect in some sense of those developmental processes that change for other reasons, and we actually came to the conclusion that selection on the brain is an important determinant of developmental time across man.
Nick Jikomes 33:42
Why? One more thing about just sort of brain size and Mosaic evolution, I want to ask you about for our lineages. When we talk about mosaic evolution, we talk about certain regions of the brain, like the neocortex, say, or the cerebellum, growing more than other regions or becoming larger in relative terms. This begs the question of relative to what and I'm wondering if they're in our lineage, if there are actually structures in the brain? Because I've never really heard about this. People like to talk about what got big. Did anything get particularly small and less functionally important in our lineage?
Robert Barton 34:17
Well, relatively speaking, the and this is a trend in primates, the olfactory system releasing. In monkeys and apes, the old factory system reduced, whilst the visual system increased. And that's partly because, you know, as diurnal animals, vision becomes, you know, much more useful. You could do more things with it. If you're a nocturnal animal, smell can be really useful. So that's perhaps the most obvious example, having said that the differences we see are. Pretty much entirely relative differences. So compared to the expansion of other systems, the olfactory system, you know, it didn't change much. So relatively speaking, it looks small, but I wouldn't like to give the impression that it became completely unimportant. So we've actually got no really good, clear examples of where something got smaller that might be, you know, and it's a good question. I don't think people have looked for it specifically. It could be one of these biases that people are looking for things that got bigger. So there aren't, yeah, at the moment, there aren't any really clear examples of that. Again, you know, if you look at the primary visual cortex in humans, this, you know, just that small area at the back of the cortex that looks relatively small compared to the rest of of the cortex, and some people had interpreted that as meaning that, you know, things other than vision, were where all the action was in human brain evolution. But it is a more complicated story in that partly because some of the areas that did expand relative to primary visual cortex are areas to which primary visual cortex projects. So it looks like those, those other cortical regions that do interesting things with the visual input have undergone interesting evolutionary change. And again, you know, just a slightly more complex story than just vision. Vision is relatively unimportant. So yeah, not a clean answer for you there. I'm afraid
Nick Jikomes 36:57
I want to ask you some some questions about the comparative biology here. So obviously there's a relationship between body size and brain size. You can tend to see bigger brains in animals with bigger bodies, because they can actually accommodate a bigger brain. But also we know that that's it's not a straightforward, perfectly linear story here. I know that you studied this to some extent, so obviously a whale is going to have a large brain in absolute terms, because it's so huge, and a bat is going to have a smaller brain because it's so tiny. But also, I know that certain lineages, including primates and others, the brain grew larger than you would expect, purely from the size of the body of that creature compared to other creatures. Can you sort of talk a little bit about what we understand about the scaling, the precise scaling relationships between body size and brain size and mammals, and where certain lineages start to deviate from the norm.
Robert Barton 37:49
Yeah, so this turns out to be a really interesting question, and I think you know, in particular, the advent of sophisticated statistical methods have uncovered new patterns in what people had assumed was a fairly well known and worked out simple story about the way brain and body size scale in relation to each other. And it's also a nice example where I always think it's it's really important not to come with too much baggage, to even even the questions you think are relatively resolved, because it can lead you to to miss important details, important patterns that change your perspective. And I mean, and in fact, you know, sort of to set back a moment, if you, if you allow me, I think we said one of the most liberating things that I found in science is actually being wrong. And we sometimes forget about that, and we think we're building. You know, the point of our scientific work is to build incrementally within a particular discipline and but sometimes something comes out of the data that just indicates that you have to re evaluate a lot. So for for many years, actually for over 100 years, since people like Huxley first plotted the size of the brain against the size of the body and showed that there was a relationship. We've known you know that brain size is closely related to body size across species, and that's true of mammals. It's true of birds. It's true of of everything, really, and furthermore, but you know, back then, they established a pretty simple statistical framework for studying brain size, scaling and deviations that you also refer to variability that's in brain size. It's not explained by body size. And essentially, you know that means taking logarithmic transformations of brain size and of body size, and when you do that and plot the data that the log data on a graph, it looks like you have a fairly straightforward linear relationship. And that indicates a power, a straightforward power relationship between the two variables. And that's how brain science was studied for many years. Well, as I say, for over 100 years. And it's partly because, you know people, people saw that pattern, because they assumed that that pattern was true. And so whenever people did a study, they said, Well, what you have to do is you have to log, transform your data and do a linear regression, and then you can find out interesting things. And until very, very recently, I assumed that that was correct, and there were, there was a slew of papers in the past few years that have used that approach, that basic approach, but applied a much more sophisticated statistical framework for examining evolutionary change in a variable like brain size on phylogenetic trees. So to use sophisticated methods for kind of reconstructing evolutionary change and looking at rates of change on individual branches of a phylogenetic tree and studying variability in rates of change and patterns of evolution and but these papers also still made this, this basic assumption, and one of the fine well, there are a number of sort of findings that came out of that approach. One is that the way that the brain size, brain size and body size scale with each other, varies from one group of mammals to another, for example, one group of birds to another. In some cases, the relationship is much steeper than in other cases, apparently. And they're also sort of shifts in the size of the brain relative to the size of the body in different groups, different orders of mammals, for example. And so this seemed to be a story of the kind of thing I was talking about earlier, of biology being complicated different patterns in different groups, and I'd be quite happy with that. That kind of makes sense to me, except that when my my collaborators sent me the sort of latest analysis one day, and in particular, some scatter plots of the data, I kind of squinted at it, and when, well, it doesn't look to me like if you look at the big pattern across all mammals, it looks like logarithmic transformation of the data hasn't actually linear, aligned, linearized the relationship. It looks curved. It looks like there's still a curve in those data. And my collaborators are sort of geniuses with these very sophisticated methods, and can, like, take about 10 minutes to test any ideas that I come up with. So I that they said, you know, my collaborator, in particular, Chris Venditti, who should take a lot of credit for this work, and Joe Baker as well, he's done some of the analyzes as well, has been very involved in this. They said, well, we can take a look at that. And they came back and said, Yeah, you're right. It's, it's not linear, it's a quadratic relationship. So we we went, well, that's quite interesting, because that's not what people have been saying for 100 years. And the first thing is to well, why? Why is that the case? And so far, we don't know. We haven't managed to pin down a reason for that particular shape of relationship, but what we have done is find that it's also true in birds as well as mammals. So it might be quite general, at least in homeothermic, you know, warm blooded creatures. But the other thing that it does is greatly simplify the patterns. So here's an example where, you know, my kind of standard position is biology. Evolutionary Biology is really messy and complicated. No reason to expect one kind of model to explain everything. And I've had to kind of recant a bit on that in this particular case, but only in this particular case of brain size gaining because various. Sort of puzzling complexities in the way in which brain size and body size scale seem to disappear once we account for this curvilinear relationship. So for example, for many years, there was a problem. It was called the tax on level. Problem was quite an esoteric, esoteric thing in sort of evolutionary neuroscience. But what it basically says is, if you compare different species of mammals or different species of birds within a closely related group, so for example, within a genus or within a family of mammals, the slope of the line relating brain to body size is flatter than if you compare more distantly related species, For example, across different orders of mammals, from, you know, bats to whales, and the various theories were put forward to try and explain this. One sort of popular idea is that there's some kind of lag in the evolution of the size of the brain, that body size can change relatively rapidly, and brain size takes a while to catch up, in some sense, for the you know, the developmental mechanisms to make that happen, so that when there's rapid evolutionary change in body size that differentiates closely related species, the correlation with brain size is sort of flatter. It hasn't caught up yet various kinds of explanations like that, but all of this disappears when you account for the quadratic nature of that relationship and the variability and slopes of the relationship between different groups of mammals also completely disappears. It doesn't
Nick Jikomes 47:03
seem it's a natural consequence of the curvilinear relationship that you guys defined, but if you make the linear assumptions of the people ringing historically, you have to come up with all of these other explanations to layer on top of
Robert Barton 47:16
it. Yeah. So what we found was that the if you fit linear relationships to the different orders of mammals, if you properly controlled for the effects of body size what you you shouldn't find any correlation between the slope of the relationship and the over the average size of That group of mammals. So large mammals like whales should have the same kind of slope, or shouldn't particularly predict the slope that they have compared to small bodied animals like shrews and so on. But we found there was a strong correlation between the overall size of the group, the average size of the group, and the slope of the line indicating there was something wrong there that size hadn't been properly controlled for. And so that's where the variability in the slope of the line came from. It was a side effect of not controlling properly for size through fitting linear models. So
Nick Jikomes 48:18
for decades, over a century, people were, you know, for statistical reasons, for historical reasons, people would log transform the data. When they're looking at brain size, body size, stuff, they would plot it. You see a scatter plot of data, and then they would fit straight lines to that, which is the default way people often do statistical analyzes. And you're saying that those those lines, those straight lines, fit that log, transform data pretty well, pretty good, if. But if you looked at it closely, it actually looked the data looked curve. And it sounds like just no one ever bothered to try and see if something fit the data better. And when you guys did that work, you did, in fact, find that something could fit the data
Robert Barton 49:02
better. That's exactly it. And it was a kind of an accident. And I love these accidents, and I and but I also think it's really important to be open to these accidents and to what the data are telling you. And you know, maybe we sometimes we just like, it's so embedded this idea that the relationship must be linear, that we just, like, don't let ourselves see something. And so we fit more complex models with, you know, lots of different groupings within, within it, to try and account for it, you know. And maybe it's, maybe it was my bad eyesight that, like, made when I was looking at the screen, because I'm quite sure sighted and I don't, don't always have my glasses on when I'm looking at the screen, you know, sort of made it sufficiently blurry that I could see, like, see that curve there? And then you have to be open to it and go, Okay, so Well, it's worth following that up. I might it might, might be nothing there. But. But, you know, let's, let's have a look. And so I do think in science, there is, you know, a tendency for us to be, you know, too influenced by the conventions in our field, to the extent that we sometimes lose that sort of playful exploratoriness That you know, can allow us to question something that's really embedded, that, like, just seems, you know, it must be true, or it's very likely to be true.
Nick Jikomes 50:31
Yeah. I mean, when I look at the data, and I try and I try and remove some of my statistical education, you know, this curvilinear line. It isn't that curved, right? It's like almost straight. And, yes, it looks to the untrained eye like there's not It looks like a straight line, basically. Yeah, it looks like quite a subtle thing. In some sense it is, but it turns out to be very significant, if I'm reading it correctly, you're saying that, you know, if you basically plot body size versus brain size on a graph across a bunch of different orders of mammals, the relationship between body and brain size the sloper line gradually, gradually, gradually gets shallower as you go up in body size.
Robert Barton 51:11
Yeah. I mean, you know, you're absolutely right. It's very subtle, but it's statistically significant, highly, highly significant. Because, you know, we've got about one and a half 1000 data points in there, and it does account for these other statistical patterns that people have puzzled over and scratched their heads over for a long time. So, you know, I one one way of, sort of indicating how subtle this curve is is I was interested in, well, does that mean, like, if it's if it's quadratic, is there a body size at which brain size stops increasing that, you know, like, if animals got bigger and bigger, their brain size would just stay the same. And what is that size? And basically, Chris Venditti poured cold water on that. He did it, he did the analysis, and he said, Yeah, that's true, but you'd have to be about over a billion tons for that to happen. So that tells you how subtle the curve is, but still, it's there, and it accounts for these other things
Nick Jikomes 52:27
and so. So after you guys fit the data in this way and made this discovery this it had a simplifying effect on lots of puzzles. It sounds like you had all of these things that needed extra explanation of before you needed to generate auxiliary hypotheses, because you got all of these mysterious questions that were emerging, and many of those, it sounds like, disappeared after you fit the data better,
Robert Barton 52:54
yeah, yeah. And I'm not, no, I'm not normally a fan of that approach. So in ecology, there's this thing called the metabolic theory of ecology, which says that you can explain all sorts of evolutionary and ecological relationships by simple energetics. The way that metabolic rate scales, and there's a magic scaling parameter is three quarters point seven, five, and I just don't believe that. But, you know, I might be wrong, and generally I don't, because I generally, I don't see any reason why there should be some simple underlying relationship that explains, you know, lots of complex patterns. So I was surprised. I was very surprised by this. But, you know, it's good to be surprised, isn't it? I mean, it's makes your day more interesting.
Nick Jikomes 53:59
So, you know, give everything you just told us, when you guys fit the data properly with these non linear models, and you look at brain versus body size, you've got an interesting graph here that I would hope you could unpack for us. So base, essentially, you're plotting a measure of brain size versus body size, and you're looking at which orders of mammals sort of fall outside the norm. In other words, where does body size get bigger more than you would expect from the increase in body size in that lineage? What are the types of mammals where that's true?
Robert Barton 54:34
Okay, so there are various ways of looking at that. One is to ask, what which groups of mammals, which orders of mammals? So when talking about mammalian orders, I mean things. Well, there are different ways of defining orders, but the primates are is our own order. So. And ungulates would be another group, although there, as I say, there are different ways of grouping these. I'm trying to use terms that people might have heard of. So hoofed animals, but cetaceans are closely related to those as well. So one question we asked was whether there is a general trend through time, like we know there is for body size, for increase. Is there a general trend for brain size to increase over and above the change attributed to body size? In other words, for relative brain size to consistently increase more than you would expect by random chance. Very the various different ways of looking at that. The simplest way is just to ask, you know, how many branches on the phylogenetic tree do we see increases in relative brain size, and on how many branches are the decreases, or, you know, change and we do find across mammals a signature of a trend in general, but it's restricted to a couple of groups. Well, at a stretch three, but I think really two, and the most prominent group in which we see this trend is our own order, the primates, so the other two are the rodents and the carnivores, and in both those groups, there were slightly more branches of the tree on which brain size increased than branches on which body size increased, suggesting a general trend. And looking at it other ways as well, we see a bit of a signature of a trend in those groups. But in primates, it's really quite dramatic. So in primates, on 80% of the phylogenetic branches on the tree, we see increases in brain size, and only about 6% of branches we see increases in body size, and overall, we find a strong signature of a trend for increase in relative brain size in primates. And again, this was a surprise to me. I mean, I saw no reason generally for what you know, why there should be a trend at all? In particular, I saw no reason why, if there is, it should be particularly confined to our own order, the order primings, but it's that, that's what the data tell us. And you know this, this seemingly set the stage for the increase we see on on the hominin branch, which, you know, carried on this trend, but accelerated it again. You know this is This opens a whole tranche of new questions, like about why? Why should you see a trend. Why should you see a trend at all when evolution is, you know, fundamentally a random process? Yeah, it's no kind of I'm against teleology. I'm against the idea there's some kind of final cause dragging everything in a particular direction. Inevitably. There's no reason why brain size shouldn't decrease. And in, you know, in some cases, it does, but in primates, very rarely. So why is that the case?
Nick Jikomes 58:30
I guess, just maybe to set this up a little bit like when I look at this relationship, you know, naively, one of the simplistic ways you might think about this data that a lot of people naturally do is okay if we're talking about outsized increases in brain size compared to body size, let's just call that something that's driven by intelligence, or how smart the creature is. And then you see primates up here. You're like, okay, that fits, but yeah, you don't see cetaceans, dolphins and whales with this pattern. You don't see elephants with this pattern, so that clearly isn't what's driving this,
Robert Barton 59:04
no, and, but there are groups within those orders where you do see rapid increases in brain. So, so, so trends is one story, and that's, you know, that's a distinct phenomenon, is, does a group show an overall trend in a particular direction? But then the other side of this is just looking across all the branches. Can we identify where there has been rapid change in one direction or another? And when we ask that question, we see rapid changes in brain size scattered right throughout the mammalian tree of life. So there are some. So elephants are one example where there was a rapid increase in brain size on one branch, it's just the. Across the branches of that group of man. There was no consistent trend for that to
Nick Jikomes 1:00:05
happen. So it's sort of like all primates, or most primates, you saw this trend. But for something like whales and dolphins, there's many different species of whales, many different species of dolphins. Some of them may have exhibited this trend, but on average, all of them did not.
Robert Barton 1:00:19
So overall, there was no trend. When you look at it at the level of the group or the order. There was no consistent pattern across all of those branches for change in a particular direction. But at the same time, there were some isolated branches where rapid change did happen and resulted in big changes in brain size. So then, you know, you can ask whether there's something that links all of those different cases of rapid brain size change in different on different branches of the mammalian tree of life. And I mean, I people talk about intelligence, and I'm not. I'm not a great fan of the concept of intelligence, which I think is, like, really culturally loaded and essentially comes out of Western notions about individual differences, and doesn't translate particularly well to understanding evolution and what natural selection was working on. I don't think you know. I suspect that in those different groups of mammals, all sorts of different things explain those similar, you know, superficially similar, patterns in terms of brain size increases. And I suspect if you look below the surface of the brain in those different groups of mammals, you will see different systems changing. So presumably in cetaceans, you know the systems that are involved in echolocation, in sonar and navigate, auditory navigation, probably very sophisticated and expanded whereas, as I've said, in primates, it's more to do with the visual system and visual motor capacities. And I don't think intelligence really captures that very well. You can call it intelligence, you know, you can look for the commonalities in, you know the behaviors that that and perhaps the behavioral flexibility that that supports. But biologically, I think you know that sort of conceals an interesting variation in in which systems are involved.
Nick Jikomes 1:02:38
When we think about the the major variables on which natural selection is acting, when we look at these relationships between brain size, body size, and how they're evolving in different lineages, different individual branches of the tree of life, are there any major I'll just call them ecological factors, or life history life style factors that do seem to play an outsized role in explaining some of these trends. So for example, predators versus prey, animals, aquatic versus terrestrial animals. Like, are there any clear factors that do seem to push a lineage in a certain direction here
Robert Barton 1:03:22
and so this, this question has been quite, quite debated in recent years. I'll give you, you know, one example of this and and the difficulties, I think you know not, not necessarily insurmountable difficulties, challenges, shall we say, for science here. So if we look at primates, and you know, we mentioned this earlier, for many years, the idea that social life was the key selective factor held sway and the variability in brain size across primates was, you know, apparently well explained by differences in social complexity, and that seemed to be, you know, fairly consistent with the data that we had. But more recent studies trying to expand, you know, the data set and look at it in more detail didn't really support that strongly. And went back to some previous ideas about the foraging niche that different primate groups have, and ideas about foraging for fruit being demanding cognitively, having a large home range that you have to navigate around, find your way around, possibly what's called extractive foraging. And again, this would be put. Much important in hominins, the ability to extract nutritious resources from food stuff, unpromising food stuff, so that you have to crack open or dig up, extract in some way, from some kind of substrate and process in various different ways. Now, I think all of these ideas do, do have merit, and I suspect that they've all been factors in different groups, but there's no clear pattern from the broad scale analyzes of brain size. And this is partly, I think, due to what we're talking about at the beginning to do with mosaic brain evolution, that ultimately brain cell you know, you can ask interesting questions about the evolution of brain size and its relationship to body size, and how relative brain size has changed in different groups, but ultimately, you have to get a bit more down and dirty with the data and ask about neural systems, because I was talking about nocturnal and diurnal primates earlier in the fact that you see expansion of olfactory systems in nocturnal animals, but In diurnal animals, you see expansion of visual systems. Well, the result of that is that nocturnal and diurnal species don't really differ in brain size. If there is a difference, it's minimal, and you only pick it up in some data sets, because different things are changing in kind of opposite ways. So if you're just asking what selection pressures drove brain cells, you're kind of missing an important part of the story, and you're maybe to some extent, focusing on, well, an unanswerable question, because there isn't going to be a single factor that drove brain size, is going to be lots of different factors. And so where we are at the moment with that is, there's disagreement, but my take on it is, it's not surprising that you get different results using different data sets. That's one of the things we found. If you just use different data sets, you get different correlations. So that's a problem, and that's partly because the data is really messy. So if you're trying to characterize the diet or the home range area or the social group size of a particular species. There's a lot of within species variation in that, and if you use different data sets, you get different results out. But also this problem of Mosaic brain evolution that it's probably more interesting to ask questions about how particular systems changed in response to particular selection pressures. And then you can ask whether that had implications for brain size, but it won't necessarily always have been associated with differences in brain size. So the question is slightly different there, and clearly, you know, whatever explains the evolution of large brain size in some groups of primates is quite likely to be very different to what explains the evolution of brain size in different groups of dolphins and whales. You know, it could be sociality in both cases. That's, you know, one argument that people have put. But equally, it could be a load a bunch of other things that differs between those groups in quite dramatic ways with you know, if you compare an animal that you know like a primate that explores its world, learns about its world through essentially visually guided manipulation of its world with one that doesn't have hands, swims around and explores its world using sonar, then you know, you're likely to see quite different things going on in their brains. And to me, that's the kind of more interesting question is, what was different? Yes, and
Nick Jikomes 1:09:24
then I think what you were saying before that has to do with this, is, when we look at animals like primates and dolphins as we meaning human beings with with our language, the language biases and concepts that we have, we can say, okay, a dolphin is intelligent. Chimpanzee is intelligent, and that is in we all know what that means. It's intuitive, but obviously they do different things in different ways. And what you're saying is that might be an intuitive concept to use, that we can all mutually communicate with and make it sensible to our minds. Science, but it's actually obscuring the biological processes on which natural selection is actually acting. And it's sort of, it's masking the variation that matters here when we want to explain this biologically.
Robert Barton 1:10:16
Yeah, and you know, I agree with you. I think it's okay to to talk about the evolution of intelligence, as long as you bear in mind that that can mean very different things in in different groups of animals, and it's that it is not an explanation in itself. And the problem comes when people start to sort of assume that there is a thing that we call intelligence, and it's fundamentally the same kind of thing as we measure in IQ tests in different humans. And you know which characterizes different species of mammals to greater or lesser extent. So it's seeing other species as kind of lesser versions of ourselves that's the problem here. I think instead of seeing them in terms of their own ecological niche and evolutionary history, and I think it's a very limited and limiting ways of understanding other species and understanding evolution as kind of inferior versions, as runs on the ladder leading inexorably to human superiority. It's a very impoverished kind of take on on things that we teach our students in first year that like we've rejected that notion, but it's still very implicit in a lot of the ways that people think about cognitive evolution and brain evolution. And one you know, example is you'll know about the marshmallow test. That's human developmental psychology, and supposedly so. This is the idea that inhibitory control, or executive control, as measured by this thing called the Marsh mallow test in kids, which is like, you know, if you can inhibit your response of grabbing the reward that's there in front of you now, because if you do that, you'll get a greater reward further down the line, and that shows you've got good executive control, and that's associated with intelligence and all kinds of good outcomes. Now that idea has actually been exported into comparative psychology and used to explain macro evolutionary patterns across species, as though so executive control, which is, I mean, I think there's a really interesting and very loaded cultural history behind these ideas that we could talk about. I think it's very western kind of notion of intelligence, in fact. And I actually think it's, it's just not a very useful way of understanding other species to to ask about how much executive control they have and and how that's associated with their intelligence and brain size. People have tried to do that, but I don't think it's, it's the answer. So I think, you know, it's sort of the idea that, like, if only you know chimpanzees could, you know, resist the urge to act on impulse, then you know they could, too. Could have built space rockets and gone to the moon. And clearly, that's not the case. You know, however long, however long they sat and thought about things and inhibited their initial reaction, they were never going to come up with the technology that allows you to go to the moon. So it's not going to explain those sorts of complexities. And you know, our technological wizardry,
Nick Jikomes 1:14:02
one thing I want to talk about, too, and come back to you mentioned this earlier, is metabolism considerations here. Because, on the one hand, you know one thing that you've told us here, one theme here, is heterogeneity and variation. You know, different lineages. There's many different ways to build a bigger brain. There's many different factors that could drive one branch of the evolutionary tree of life towards a bigger brain of one kind or another. So there may not be, you know, one ecological variable that sort of unifies a lot of this stuff, one thing that does seem to cut across all the branches, as far as I can tell when we think about brain size, overall, brain size is metabolism, because neurons are very expensive metabolically. We know that, you know, the the amount of energy our brains use is, is very large for the brain. I forget what the exact number is. The brain is, you know, it's using 20% 25% of the energy of. Of the human body, I think something like that. And we know, you know, we know that neural tissue is very expensive. Extra potentials require a lot of ATP. And you mentioned earlier that there are these scaling laws which apparently explain how metabolism relates to body size. And I've had Jeffrey west on the podcast a number of years ago, and he's one of those,
Robert Barton 1:15:23
sorry, I should not have been rude about the metabolic theory of ecology in that case,
Nick Jikomes 1:15:27
no, no, it's okay, but, but you know, according to that body of work, you can fit these power laws that relate body size to metabolic rate. And you mentioned that there's this, this three quarters power law that that a lot of people are fond of, and it basically says is used to explain why metabolic rate is lower for larger bodied animals, and why you get sort of an economies of scale that comes in there. And this can maybe explain why larger animals tend to live longer and so forth. But given, given that we know in physiological terms, that you know, neural tissue is expensive. It does require more energy, I would think that there's usually, in most branches, where you get an outsized amount of brain growth, there must be some, some metabolic factors there involved in how animals are acquiring food that are ensuring they're getting more energy dense foods, because it they no matter why their brain got bigger and what's driving that ecologically, you do have to pay for it energy and so what do you have to say about the role of metabolism here?
Robert Barton 1:16:35
So this is a really nice, another nice example of where views have changed over time and kind of flip flopped to some extent, and also, example, where I've changed, I've had to change my views based on data, and I should here credit My old mentor and Master's supervisor. Way back when I was a master's student, I was taught and supervised and inspired by Bob Martin, who came up with this idea called the maternal energy hypothesis. So there were various ideas linking scaling of brain size to metabolism, and his particular idea, which I think turns out to to hold a lot of water, but which for a while I was very skeptical about, was, is that the growth of the brain is constrained by the rate of delivery of nutrients from The mother to the fetus, and then during lactation, to the to the to the infant, as it grows and suckles. And so he was interested in the fact that seemed to be some relationship between metabolic rate and brain size. And I am among some other people for years, kind of rejected that and said the data don't seem to support that, but more data and better methods seem to have vindicated Bob's position. And so one of the papers we did, I shall mentioned a bit earlier, looked at the looked at this in terms of development, and we found that in addition to the gestation period, the period of pregnancy across mammal species having an influence on the size of the brain in the newborn, So did metabolic rate. So species with higher relative metabolic rates grow their brains faster in utero, leading to larger brain size in the newborn, and that may that seems to have consequences for subsequent brain growth after birth as well, and then in our more recent paper, but also other people have shown this more recently as well. So this is not attributable to us in particular, but we found it too. Is that, you know, when you have lots of data and good methods, you find that metabolic rate and brain size are correlated with each other, and that's after accounting for the relationship that each has with with body size. So relative brain size and relative metabolic rate are associated. You know, just as as Bob Martin had predicted. So I think what that indicates is that brains, as you say, are metabolically expensive. I wouldn't interpret it necessarily as a constraint. That, you know, if there's some reason why metabolic rate can increase that allows you to increase brain size, and it's generally advantageous to have the big brain, so you do, I think it makes more sense to see it in terms of when selection selects for something that requires a larger brain for it to happen that it also has to increase metabolism. And so it's a constraint in that sense, but it's a constraint that natural selection works through, and it's kind of the increase in metabolism is, is probably a side effect of selection on the cognitive capacities that are associated with larger brains.
Nick Jikomes 1:20:51
And when we think about things like maternal investment and life history strategies, so thinking about our lineage, primates in primates in general, but But humans in particular. We have long lives, but we also have these, these, you know, famously long childhoods, where they require a lot of maternal and paternal investment, a lot of care, to allow the child an environment where a lot of training can happen. If you think of it in terms of almost like in machine learning terms, we've got this extended period in which we get to play our brains, get exposed to these training data sets, and there's a lot of time that our brains spend learning things that simply require time to learn complex social behaviors and so forth. How unique is that to our lineage and and what are some of the key things there, in terms of really, really the what characterizes the post natal developmental period of our
Robert Barton 1:21:55
lineage? Yeah, no. I mean, I think what you say is is absolutely correct, certainly for mammals, I think there are strong relationships between, you know, the need to grow brains postnatally to and that's associated with, you know, species having generally A large brain, and it getting wired up through learning processes, through input from the environment. You know, large brains take longer to wire up and to function effectively, so extended period of maternal investment is probably necessary to enable that to be supported. And I think we do see that in so we see, you know, we mentioned elephants as one group where there are large brains, particularly massive cerebellum, I should point out in elephants. And they also have, you know, extended juvenile development, extended period for learning some citations as well, again, extended period of maternal investment and relatively slow growth. So this does seem to be a pretty consistent pattern, and it is consistent with the hypothesis that, you know, having a large brain is associated with these extended postnatal developmental periods and extended learning periods and maturational periods. So I think you know, behavioral sort of learning is intimately associated with physical maturation or processes going on in the brain. Whether the extent to which that applies more broadly is less clear. So octopuses a really interesting counter example to almost everything we know about brain evolution from mammals. So octopuses have large brains for their body size, and amongst mollusks, because octopus is a kind of mollusk, but they don't have any of the kind of ecological factors that are associated with large brains in mammals. They don't like giving social groups. Generally, they don't have complex social lives. They, I mean, they do do extractive foraging, so that that might be a kind of a similarity. They don't take a long time to develop, and they don't have long lifespan. So in that sense, they deviate markedly. So they grow their large brains pretty quickly, and then they don't live very long. So something different going on there with octopuses, some people have tried to. Squeeze. I mean, octopuses are pretty squeezy, but you shouldn't try to squeeze everything into the same. Theory is my take on this. So they're radically different. They're kind of they've been described as like aliens, and of course, they evolved their brains entirely independently from the vertebrate brain. Their closest relatives don't really have brains. They barely have, you know, they have very simple nervous systems, and they tend to be, you know, stuck to rocks for most of their lives. So, so So all of that is a rather long winded way of saying that, yes, there amongst mammals, I think there are consistent patterns in terms of life history and opportunities to learn and wire, wire up your brain. But that doesn't necessarily always relate to brain size in all groups. And you know, birds, there might be some parallel cases, example, parrots and crows, but they don't really have the same extended juvenile periods that you see in mammals. So again, you know, interesting complexity that we're only just beginning to kind of get some kind of a handle on,
Nick Jikomes 1:26:21
another area that I think is interesting, where there's a lot of evolutionary variation, there's a lot of developmental variation that potentially links some of these things together, because there are learning and memory considerations, there are metabolic considerations and so forth, is sleep, and I believe you're doing some work on the evolutionary diversity of Sleep in different lineages. Can you give us maybe just a bird's eye view here? Bird's eye view in mammals, maybe, or even across mammals and birds say, of how sleep seems to vary in different branches of the tree of life for animals, how that might relate to body size, how that might relate to brain size and things like that.
Robert Barton 1:27:00
I have to confess, I'm no longer working on the evolution of sleep. We had a project going a few years ago, but, you know, the other people are following up on some of the work that we did, and we were interested in this idea that sleep plays a role in the consolidation of memories. And it's, it's, actually, it's pretty tricky to study these things across many species of animals, because the data that you need really to study something like memory consolidation are so fine grained that you're unlikely to to have that kind of data for enough species to be able to do these kind of macro Evolutionary analysis. But you know, there are some indications that the amount of sleep is related to the numbers of neurons in the brain, and as I say, other people are following up on this. So some patterns in the data that are consistent with a particular relationship between sleep and the brain, as you would expect, but really, I think at this stage, we're waiting for more and better sort of fine scale data on sleep and perhaps on neuroanatomy across enough species To be able to say anything really definitive about that in the
Nick Jikomes 1:28:43
few minutes we have left. What are some of the things that you're working on right now, questions you're asking in your research today that are sort of at the cutting edge of your thinking and and what's maybe on the horizon that you think is particularly interesting in terms of human evolution and mammalian evolution in general.
Robert Barton 1:29:00
So going back to the curve in brains, you know that, as I say, that was a surprise to us, and so we're following up on that, and first of all, trying to find out how general that is. Asking, you know, if that's a general pattern, then what explains it, and does it have the potential to explain a lot of the complexities in other groups of animals, as well as mammals? And so yeah, we're looking at a variety of different groups now. If that's the case, is it true, particularly for the brain. Is it something special about brains and the way that they scale with body size and the architecture of brains, the way that they change as overall size of the animal changes? Or do we see it in other organs as well? Because if we see it in a bunch of other. Organs, then it must be something really fundamental about the biological scaling of different organs, and not not something specific, you know, special about the brain. So these kind of more general questions trying to follow up on on that we are interested in the molecular mechanisms that underlie evolutionary changes in in brain systems. So how, what sort of genetic changes have facilitated the evolution of cognitive capacities of different kinds, and do we see similar changes in genes across the tree of life? To what extent do we see different changes? So what we call sort of Pheno genotype correlated evolution, and just broadly, more broadly, trying to understand mosaic brain evolution, I have, you know, other colleagues who are working in other groups of animals to help us to understand whether these patterns are similar in other groups, whether they're different to what extent they're different, and to look at in more fine grain detail. And you know, we've still done things in a very broad brush kind of way. So we've talked about brain structures like the neocortex and the cerebellum, but even that is incredibly coarse. And it I mentioned some specific hypotheses that have specific implications for looking at particular systems. So I mentioned this cerebellar sequencing hypothesis. This is the idea that, you know, the cerebellum has a particularly important role in managing, comprehending and organizing and predicting complicated sequences of things that might help us to explain how humans evolve language. Because obviously, you know, when we're engaging in linguistic communication, we're ordering words into extremely complicated, multi layered, hierarchically organized sequences. To what extent is that the same kind of sequencing process that we engage in when we're organizing sequences of actions, and to what extent do they use the same kinds of the same brain systems? Are there particular areas of the cerebellum and the court those cortico cerebellar networks that underpin complicated sequences of actions and complicated language and that will help us to understand sort of the nature of cognitive evolution. I think the extent to which things that we think of as being kind of or would have traditionally thought of as being quite separate, like language, some people have thought of it as a module, actually, is it part of a more generalized capacity for this managing secret.
Nick Jikomes 1:33:24
That's because, yeah, I suppose that would relate to things you were mentioning earlier around embodied cognition. You know, to what extent is language, this quote, unquote, pure cognitive thing that's different and sort of uncoupled from the the circuits underlying action in the world, sensory motor action versus To what extent is it an elaboration of sensory motor systems that would sequence any other behavior? Perhaps. Yeah. And
Robert Barton 1:33:51
traditionally, people have tried to describe the language system, called language system in humans, as being something that is resides in the neocortex, and increasingly, again, you know, with this part of this general trend of finding more functions are more distributed finding, you know, the cerebellum, but other structures, like the basal ganglia, have important functions in language production and language comprehension, and finding that those systems are also closely allied to the systems that are involved in gesture, for example, so vocal Communication is intimately associated with gestural communication and the more general sort of, as you say, embodied organization of activities. So we've got a project running this this autumn in Durham, kind of a slightly crazy blue skies thing, where we're bringing together people from arts and humanities, social science, psychology, cognitive science. Science, evolutionary biology, neuroscience, focusing on this idea of sequences as being, kind of the organization of sequences as being a kind of a very general capacity. Years ago in 1950 something, Carl Lashley said he thought that was what distinguishes humans. So we're kind of following up on this, this old idea, and taking a very interdisciplinary approach to working out its implications for all sorts of areas of human activity, including things like dance, for example.
Nick Jikomes 1:35:36
Well, Rob, this has been fascinating before we go. Is there anything you want to reiterate for people, anything that we talked about before, or any final thoughts you want to leave people with about evolution or human evolution.
Robert Barton 1:35:48
I think you know, if I there was one thing I'd like to emphasize, it's more generally about science, that thing that we forget about wonder and curiosity and not, not necessarily always believe in conventional wisdom, being prepared to question conventional wisdom, because in my own area, this is, this is what has led to, for me, the most sort of excitement and The most interesting, findings and being the most productive thing is, is where I've kind of allowed myself the freedom to, slightly, you know, go against what I had assumed in the past, and so not to always see science as Just an incremental process of building on what we think we already know, but to see it sometimes also usefully as a disruptive thing, to there being a disruptive part of it that sometimes, to make a leap, we need to be a little bit disruptive. And when we do that, we find out all sorts of, you know, there are still interesting things to find out about problems we thought were solved like, you know, scaling, and that's, that's kind of thing. So yeah, be be full of wonder and open to to finding out new things that just come out of the data at you essentially, rather than come out of conventional ways of thinking,
Nick Jikomes 1:37:23
all right. Well, Professor Rob Barton, thank you very much for your time.
Robert Barton 1:37:27
Thank you very much for having me. It's been pleasure.
Comparative Brain Evolution: Mammals, Primates & Humans | Robert Barton | #171