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Jon Kaas on brain evolution and neocortex

Episode 11 14.03.2012

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Season 2012

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Why does a duck-billed platypus have electroreception, and what does that tell us about how 250 million years of evolution sculpted the six-layered cortex that makes you human? Jon Kaas traces the entire arc of mammalian brain evolution from stem reptiles to primates.

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Kaas argues that understanding brain evolution is essential for understanding what we are. All mammals share a six-layered neocortex that evolved from a simpler one-layered dorsal cortex in stem reptiles, a structure likely involved in habituation and short-term memory rather than sensory processing. The transition to six layers gave early mammals extraordinary flexibility: the ability to replicate cortical areas, specialize them for different functions, and modify sensory representations by enlarging what matters most, whether whisker maps, nose representations, or echolocation frequencies.

The interview reconstructs the ecological pressures that drove early mammalian brain evolution. Small, nocturnal, and hunted by dinosaurs, the first mammals developed high-frequency hearing through the dissociation of jaw bones into inner ear ossicles, enabling mother-offspring communication at frequencies predators could not detect. Olfaction dominated the forebrain, essential for nocturnal foraging. Sensory hairs, likely the precursors of whiskers, provided tactile information before physical contact, a critical advantage in poor light. Kaas emphasizes that the brain’s hyperplasticity, its ability to automatically reorganize when peripheral inputs change, was the key innovation enabling rapid diversification.

The primate chapter of this story centers on the shift to diurnal, arboreal life after the dinosaur extinction 60 million years ago. Visual processing expanded massively, with the temporal and occipital lobes growing to cover the midbrain. Eye-hand coordination became critical for catching insects on moving branches, driving the development of grasping forepaws and eventually freeing the hand from the mouth. Social group living, essential for ground-dwelling primates facing predators, drove frontal lobe expansion. Throughout, Kaas stresses that cortical and subcortical structures co-evolved, with changes in cortex driving modifications in spinal cord circuitry, thalamic inputs, and midbrain organization.

Tagged as:
brain evolution Cortex Essential Mammalian Brain neocortex Stem Reptiles

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Both the triumphs of humanity and its most evil deeds have resulted from collaboration. In a time where humanity is required to aspire to the former and minimize the latter, the question arises of how collaboration arises and why it fails. Surprisingly, this phenomenon, so central to who we are, is not well understood. Hence, a collaborative effort is required to understand collaboration in its full biological, psychological, sociological, cultural, and economic complexity and to translate this understanding into operational impact. This series of podcasts is one step toward achieving these complementary goals. The Collaboration Podcast presents interviews with people who are central orchestrators of collaboration in various domains including business, government, science, art, health, sustainability, and the military. The discussions were conducted by Prof. Dr. Paul F.M.J. Verschure and members of the Program Advisory Committee of the Ernst Strungmann Forum on Collaboration (https://www.esforum.de/forums/ESF32_Collaboration.html) during 2021 and had the goal to sketch a map of opportunities, challenges, and obstacles in human collaboration. The forum took place in May 2022, and now we would like to share this series of interviews with a broader audience. The full report of the Forum will be published in 2023 by MIT Press. The podcast was produced by the Convergent Science Network (https://www.convergentsciencenetwork.org/). Context: The stability of social systems depends critically on realizing sustainable methods of “collaboration,” yet how and by which means collaboration is achieved is not clearly understood; neither are the conditions or processes that lead to its breakdown or failure. Collaboration can be understood as cooperation between agents toward mutually constructed goals. Part of the reason for our lack of understanding is that the phenomenon of collaboration is, by nature, a highly multidisciplinary problem, and effective research into its complexities has been difficult to achieve across the broad range of scientific and technical disciplines involved. The need for a fundamental understanding of collaboration, however, has become increasingly important. Not only does humankind demand answers as it attempts to address critical challenges at multiple scales (e.g., climate change, migration, enhanced automation, social and economic inequality), but ever-increasing technological and economic means of interconnecting people and societies are disrupting long-established, familiar patterns of how we interact. Radical technological changes that are ongoing have the potential to reshape collaboration in ways that are currently hard to predict or influence (e.g., by altering configurations in interaction, information creation, and modes of communication). On one hand, such changes could disrupt hitherto stable forms of collaboration by affecting critical communication channels and traditional roles, as can be observed in the rapidly changing patterns in governance, commerce, and social interaction. Conversely, technology could lead to the emergence of novel, successful forms of collaboration that deviate from traditional “hierarchical” architectures. Evidence of this can be seen in areas as diverse as highly automated manufacturing plants, the open science movement, collaborative software repositories, user-centered services, and the sharing of economy-based modes of organization. Without a fundamental understanding of the mechanisms, processes, and boundary conditions of collaboration, it is not possible to evaluate or predict which of these possible scenarios are sustainable or even plausible. The Forum “How Collaboration Arises and Why it Fails” (May 8–13, 2022, Location: Frankfurt am Main, Germany) Chairs: Andreas Roepstorff and Paul Verschure Program Advisory Committee: Jenna Bednar, Julia R. Lupp, Bhavani R. Rao , Andreas Roepstorff, Ferdinand von Siemens, and Paul Verschure

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00:00:03 - This is the Convergent Science Network podcast.
00:00:08 - Leading researchers in the domain of neuroscience, brain theory and technology
00:00:13 - are interviewed by Paul Vershoor and Tony Prescott.
00:00:19 - This is Paul Vershoor with our summer school, again, together with Tony Prescott,
00:00:26 - co-chair of summer school, and John Kass, one of our speakers.
00:00:30 - And John gave a talk about the evolution of the brain.
00:00:37 - And you showed this incredible overview and insight in how brains have evolved.
00:00:43 - So why is evolution, this evolutionary perspective on the brain so essential to you?
00:00:52 - Well, part of it I went in my talk, and that is that we had a curiosity of how
00:01:00 - we got here, what we are, who we are.
00:01:02 - And you can think of it in development, or you can think of in religious terms,
00:01:09 - but you can also think about an evolutionary past, from where we started and now we got here.
00:01:16 - And for a neuroscientist, I think the perspective of how our brains got to be
00:01:22 - the way they are is the most informative and interesting.
00:01:29 - Given that what we are is so much different than what other species are in terms
00:01:35 - of abilities, in terms of what they do, and so on.
00:01:38 - And one of the statements I remember is, if you're criticizing someone, are you a man or a mouse?
00:01:48 - The real difference, the main important difference between a man and a mouse
00:01:52 - is the brain, I think. The things that the brain can do.
00:01:56 - Of course, there are some slight morphological differences. They have a body
00:02:01 - that's appropriate for the brain as well. Yeah.
00:02:05 - But then you define, let's say, you identify evolution and let's say the phylogeny
00:02:12 - of brains as a phenomenon in and of itself.
00:02:15 - So this is one perspective. But do you see it also contribute to,
00:02:20 - let's say, extracting these fundamental principles along which any brain is
00:02:25 - organized? Yeah, so the same sort of thing.
00:02:28 - I take the evolution of the human brain because it'd be the most interesting
00:02:32 - for the most number of people. but you could pick anything.
00:02:37 - How would you get to an unusual brain such as in a duck-billed platypus?
00:02:41 - How would you ever get a brain like that? Why is it organized the way it is?
00:02:47 - And it applies if you're talking about rats.
00:02:50 - Why do they have such a wonderful vibrancy system and so on?
00:02:53 - You can start asking questions of how any mammal's brain got the way it is from
00:03:01 - the early beginning. any.
00:03:03 - But then if you let's take the platypus which is sort of very close to the common
00:03:08 - ancestors of our brain why is my brain not exactly like the brain of a platypus?
00:03:14 - What are the differences and why are these differences there?
00:03:18 - Well first there are some amazing similarities,
00:03:25 - and so all mammals will have this layered cortis which is quite different from
00:03:30 - any non-mammal And that's something we share in common.
00:03:34 - So one of the points I try to make is that given a six-layered cortex,
00:03:38 - it can be changed and modified in a number of ways to fulfill the needs of all
00:03:45 - kinds of different species and depending on what they need to do.
00:03:50 - A lot of species have a high reproductive rate and a short life.
00:03:56 - And if you're going to have a short life, you need a high reproductive rate,
00:04:00 - you need to reproduce early and so on.
00:04:02 - So you can't really invest under those circumstances in a complex brain.
00:04:07 - It takes too long to build, too much energy.
00:04:12 - So we happen to be one of those lucky species that has figured out how to live a long time.
00:04:19 - And so we can have a brain that takes 20 years to really fully develop.
00:04:25 - And that's almost unique, that luxury.
00:04:31 - But it leads to a very complicated brain that a whole range of other species never invest in.
00:04:37 - They just want to get reproducing within a few months, and they're unlikely
00:04:43 - to live more than a year or two.
00:04:46 - So you have those kind of brains. But a duck-billed platypus has taken a very
00:04:53 - unusual tact, and that is that it lives in water and feeds in water.
00:05:00 - Some other animals have done that, mammals have done that.
00:05:03 - But in this case, they were able to develop from mucous glands electroreception.
00:05:12 - And at high levels of current, I guess we all have electroreception,
00:05:18 - but to get the high level of sensitivity,
00:05:22 - it's not clear exactly how that's come about, but it's happened independently
00:05:26 - in several fish and so on.
00:05:31 - And once you have that, you can exploit this environment
00:05:37 - of turbid, muddy water that you can't see in, you can't really hear when you're
00:05:43 - adapted as a mammal to be above on land part of the time.
00:05:48 - So you can touch things, but then you're already up there.
00:05:55 - So electroreception is what makes them unique. It makes them different as getting electroreception.
00:06:00 - They refine that to a tremendous degree, come their most important sense.
00:06:07 - So the duck-billed platypus is interesting because it split from the main line
00:06:12 - of mammalian evolution a very long time ago and followed a very distinctive
00:06:16 - path, so it's almost now a unique creature.
00:06:20 - Now the common ancestor that the duck-billed platypus has with other mammals
00:06:24 - lived around 250 million years ago.
00:06:27 - And what is your view of what that animal was like, why it evolved to be different
00:06:33 - from a reptile, and how the evolution of that first animal changed the brain in such a dramatic way.
00:06:42 - Well, you're asking a tough question because of the lack of intermediates.
00:06:52 - But when it was proper to talk about the non-mammalian ancestors of mammals,
00:06:58 - they talked about them being mammal-like reptiles.
00:07:04 - And, uh.
00:07:06 - Their brains were bigger, but it wasn't clear whether they had a neocortex or just a dorsal cortex,
00:07:13 - and it's not clear how dorsal cortex of a single layer of pyramidal cells with
00:07:19 - a different kind of wiring diagram and processing of information and sending information back out,
00:07:26 - how that kind of cortex changed to the neocortex.
00:07:31 - And in my talk, I emphasize neocortex because because this structure is not new.
00:07:38 - A lot of people complain it shouldn't be called neocortex, and some people have
00:07:42 - called it isocortex, but it's new in the sense that it's a six-layered structure
00:07:46 - that evolved from something that was a one-layered structure with fiber layers on each side,
00:07:52 - so you could really call it three if you wanted to.
00:07:56 - But it's one layer of cells that gets the input, and the same cells provide
00:08:01 - the output, So it's very simple in kind of the wiring diagram it is.
00:08:07 - Changing from that into six layers gave the great flexibility and possibilities
00:08:15 - to early mammals to diverge and develop in so many different ways.
00:08:20 - A lot of the ways were just simply modifying the way sensory inputs were represented,
00:08:28 - enlarging what was important, putting more neurons into what seemed to be behaviorally important.
00:08:35 - So you get large vibrisci representations, for example, or large nose representations,
00:08:41 - or large mouth representations. All these are common variations in the somatosensory system. them.
00:08:47 - A lot devoted to vision, little devoted to vision, these kind of things.
00:08:51 - I'd say these are what we'd say is rather modest modifications,
00:08:57 - echolocating bats devoting a tremendous amount of space and cortex to the echo frequency.
00:09:05 - Another example. So would it be true to say that the dorsal cortex of the stem
00:09:12 - reptiles from which these first mammals evolved was a relatively simple layered
00:09:19 - structure, just three layers,
00:09:20 - but was it also doing sensory processing?
00:09:24 - I would say it had more to do with something like memory or something like there's
00:09:32 - evidence that had to do with habituation, which would be a kind of learning, short-term learning.
00:09:38 - And this would be very valuable, but it wouldn't be very useful in detecting
00:09:43 - a bug from a ball or making discriminations of what kind of sensory information this was.
00:09:52 - That information would be done subcortically. So the auditory and the tactile
00:09:58 - and the visual brain of the stem reptile would be a midbrain,
00:10:03 - and then in the first mammals,
00:10:06 - this dorsal cortex would suddenly start
00:10:08 - to take over or be involved in the representation of these modalities.
00:10:13 - Yeah, midbrain and parts of the forebrain that would be now considered basal
00:10:18 - ganglion mammal, and certainly the amygdala was a large part of this subcortical processing,
00:10:27 - and still is for a lot of kind of behaviors.
00:10:31 - And the pressure to develop that new function for dorsal cortex,
00:10:36 - would that be to do with the lifestyle of those first mammals and how that had shifted?
00:10:41 - Well, it's presumed that the lifestyle would have been a little precarious for
00:10:45 - them because you had all these very vast reptiles, dinosaurs all around, many of them predators.
00:10:53 - And so it was assumed that they would be nocturnal. Their skeletal features
00:10:58 - suggest that they were nocturnal. They were small.
00:11:02 - They were living on insects or maybe some of the meeting some of the infants
00:11:07 - of smaller reptiles and things like that, eggs perhaps, but mainly on insects
00:11:13 - and scurrying around and hiding at night.
00:11:15 - And a couple things became important.
00:11:19 - One was the change in the auditory system in which the bones of the jaw became
00:11:25 - dissociated from the jaw. So you have the three.
00:11:31 - Bones of the inner ear, which really defines mammals as something unique,
00:11:35 - and that allowed a high-frequency transduction of sounds for the first time.
00:11:43 - So early mammals had a nice advantage over reptiles in that they could communicate
00:11:49 - mother to offspring, or mother.
00:11:53 - Offspring could make a separation call or something at a high enough frequency
00:11:57 - that predator couldn't find them, and they started to exploit this kind of life.
00:12:04 - And now we presume that auditory inputs to dorsal cortex, which would be now
00:12:09 - neocortex at some stage, would have emerged for the first time.
00:12:13 - And that kind of auditory processing at a higher level would emerge with the
00:12:19 - ancestors or with the first mammals.
00:12:23 - Do you see then also a link of olfaction here, because about nocturnal animals,
00:12:28 - so you want to sort of rely on sensory modalities that don't require light.
00:12:33 - Now you emphasize audition.
00:12:35 - Recently there was a paper out where people look at the fossil record,
00:12:39 - making the argument that actually this whole drive towards the cortex was very
00:12:43 - much grounded in olfaction. Do you support that?
00:12:45 - Well, clearly the first mammals emphasized olfaction a lot.
00:12:51 - And this is a really old idea, going back to Herrick.
00:12:54 - A hundred years ago, the evidence from looking at mammals in a comparative way,
00:13:02 - but also some of the fossil evidence, suggested that olfaction was very important.
00:13:08 - They used mainly comparison of living mammals, but it's been substantiated by
00:13:14 - everything that's been learned since then, so that if you had to look at the
00:13:19 - forebrain, it was dominated
00:13:21 - by olfactory processing.
00:13:23 - And this would be very handy for a nocturnal animal to find their food,
00:13:27 - find their mates, not use vision, not really use sound so much because that
00:13:34 - would lead predators to find you.
00:13:39 - So the olfaction is obviously crucial. But another interesting thing with the
00:13:44 - first mammals is the emergence of hair.
00:13:48 - And I think it's presumed that before hair could have a thermoregulation function,
00:13:54 - it would probably have had a function as a touch sensor.
00:13:57 - And of course, that was probably in the form of the whiskers,
00:14:01 - the fibrissi of the first mammals.
00:14:03 - And so then you also have somatosensory cortex.
00:14:07 - Yeah, it's very important.
00:14:11 - The sensory hairs probably were the most important feature of early hairs.
00:14:17 - They can touch something before they quite touch it. The longer the hair, the better.
00:14:25 - And this would be especially a great advantage in poor light or bad light,
00:14:30 - where vision wouldn't be so useful.
00:14:32 - You'd touch something and you could back away before it was too late or decide
00:14:37 - what kind of behavior you might initiate.
00:14:40 - And a good example of that would be in naked mole rats, which have been studied
00:14:46 - at Vanderbilt and other places.
00:14:48 - And they're not naked. They have these sensory hairs, but the other ones are
00:14:52 - gone because they don't need them for thermoregulation.
00:14:55 - And they're very driven by what hairs you touch.
00:15:00 - So they don't see you, You touch with a little stick or something,
00:15:03 - one part of the body, they go forward.
00:15:07 - Another part of the body, they go backwards because where they're touched determines
00:15:12 - what direction they're going to move in.
00:15:14 - So now we have sort of a sketch of this early mammal.
00:15:21 - But it also then had to develop a brain that would match these capabilities.
00:15:25 - And then the idea would be this would contribute from this step towards a six-layer cortex, right?
00:15:31 - It would just sort of highlight the isocortex in this case.
00:15:35 - But still then within that, so now there will be two questions at least.
00:15:41 - Or the one of this, okay, how do I get from a one-layer sheet of cells performing
00:15:45 - some very simple, possibly memory function, learning function,
00:15:50 - to a six-layer structure, and also so fairly rapidly?
00:15:53 - But then how do I make that match all these variations on morphology,
00:15:59 - on mixing of different sensor modalities?
00:16:04 - Efficiently and rapidly? Because now we're talking K-min explosion roughly,
00:16:08 - so we have all these different types of animals emerging.
00:16:12 - So how do you see the six-layer cortical sheet being rapidly adjusted in its
00:16:20 - details to then the specific requirements?
00:16:22 - So how do we get from one layer to six? And then once we have six,
00:16:25 - how do we tune it actually to the specifics of the specific organism in which
00:16:29 - you want to have that cortex working?
00:16:32 - Well, the speculation of how you get to more layers would be that the original
00:16:39 - organization really corresponded to layer 5 pyramidal cells.
00:16:46 - They get inputs on their apical dendrites and they send outputs subcortically,
00:16:52 - and this is what dorsal cortex does with a few inner neurons.
00:16:56 - How those other layers came about and any ball is really rather uncertain.
00:17:03 - People working on development probably will come up with and are coming up with
00:17:08 - some good suggestions about cell migration, cell division, changing the cell
00:17:13 - replication cycle, and so on.
00:17:16 - But it's really uncertain because we don't have examples of intermediate forms.
00:17:22 - Once you get to the six layers, you can modify the sensory representations representations
00:17:28 - that are there, as I already mentioned, in all kinds of ways.
00:17:32 - But the real powerful advantage of cortex is that you can start to replicate
00:17:38 - cortical areas and increase the numbers.
00:17:41 - One idea that we talked about a long time ago is just you duplicate areas that
00:17:48 - are already there and then modify them differently for different functions.
00:17:52 - I don't know if this is the way new areas emerge or where they emerge gradually
00:17:56 - by internal differentiation,
00:17:58 - but the idea of duplicating is
00:18:01 - something that's an old advantage in evolution
00:18:04 - where you duplicate body parts and as you
00:18:06 - can see in segmented creatures that have more segments and more body parts that
00:18:11 - were originally all alike and then you start specializing them as in a lobster
00:18:16 - with different of the appendages modified for different functions you can think
00:18:21 - of cortex with more areas doing something similar,
00:18:25 - is that you're now modifying different parts that might have been quite similar
00:18:29 - in anatomy and connections and,
00:18:33 - making them more and more specialized for different kinds of functions.
00:18:38 - If you don't have a number of areas, you can't specialize for different functions
00:18:43 - with one area very easily.
00:18:44 - You can subdivide an area into more layers and get some of that in a single structure.
00:18:51 - By having layer differences, but really the best way to add is to get more areas
00:18:59 - and then specialize them.
00:19:01 - And you specialize them in terms of what their inputs and outputs are,
00:19:05 - but you specialize them also in adjusting them to what they're best at doing
00:19:12 - or what you want them to do.
00:19:13 - So you can have dendritic arbors that are large or small, and they collect information
00:19:19 - from a few neurons or a lot of different other neurons.
00:19:23 - You can use different neurotransmitters. You can have different neuromodulators
00:19:27 - that will affect them in a different way.
00:19:30 - And you can end up, as we hear in all these talks, with neurons that are sensitive
00:19:35 - to very particular kinds of combinations of sensory information.
00:19:43 - In my mind, there's sort of a gap still in that answer Because while I'm changing
00:19:50 - my morphology, it's not like I can just change my morphology and I flop around
00:19:53 - for a few generations and at some point in time I have a brain that matches my morphology.
00:19:57 - These changes have to happen in a very coordinated fashion, right?
00:20:00 - So that means I would hope that you have an answer, just to satisfy my own ignorance,
00:20:07 - that would mean something like, well, there is a very specific genetic control
00:20:10 - that allows you to change body parts and in some sense change also matching
00:20:15 - neural structures in some coordinated fashion. Yes, absolutely.
00:20:20 - So one thing that you can imagine is that you change brain parts without changing
00:20:27 - peripheral morphology at all and get more out of the kind of information that's coming in.
00:20:31 - But there is a cascading sort of modification that occurs in any system. So.
00:20:41 - The whole system is changed by that, at least in development,
00:20:44 - but also in mature animals.
00:20:46 - And that's due to the plasticity or the flexibility of the system to always adjust to change.
00:20:53 - And so one of the major mechanisms of evolution is that you change the sensory inputs.
00:21:01 - Say, you change the cochlea so that you can now send signals at higher frequencies.
00:21:08 - The whole system, If you did that in any animal that didn't hear high frequencies,
00:21:13 - if you gave them the possibility of high frequencies, the whole system in development
00:21:18 - would adjust to that and have neural space devoted to this.
00:21:23 - If you doubled the number of receptors that come from the face,
00:21:28 - the whole system would adjust to that and you would have more processing throughout.
00:21:33 - Out and so your answer is essentially say
00:21:36 - look the first trick was maybe to develop a brain or
00:21:39 - cortex as well that is let's say hyper plastic or hyper adaptive and then after
00:21:45 - that you can start to play with your morphology to to sort of see how you can
00:21:48 - optimize yourself to a specific niche yeah yeah you have things that will happen
00:21:53 - automatically and and one of the.
00:21:59 - Papers from Van der Loos was how the periphery instructs the brain how to build itself.
00:22:07 - And I think that paper was not as influential as it could have been,
00:22:12 - in part because he was looking for genetic reasons as well at the same time,
00:22:18 - and he deleted his own message that way.
00:22:20 - The powerful thing was working with mice, if they're born with an extra whisker
00:22:25 - or a whisker short or a couple whiskers extra or a couple short,
00:22:30 - you still have a whole vibrancy system that incorporates that new information
00:22:36 - or that lack of information into the number of barrels or barrelettes or whatever
00:22:41 - in different parts of the somatosensory system.
00:22:43 - So the system developed to accommodate the change in the periphery.
00:22:50 - And even that change in the periphery is somewhat indirect because it depends
00:22:55 - a bit on how folds in the face occur in development, and that determines how
00:23:00 - many whiskers there's going to be.
00:23:03 - So we have this early mammal brain, which is plastic and allows quite a lot
00:23:08 - of diversity to happen, but it's still really quite a small brain.
00:23:12 - And then you mentioned in your talk something that was very interesting,
00:23:16 - that around 60 million years ago, the reptile disappeared,
00:23:22 - and that this was an opportunity for a new radiation of mammals to diversify
00:23:26 - into a whole new set of niches in which they could live.
00:23:32 - And that there were then some really quite dramatic changes in the brain as
00:23:36 - a result of that for some groups of mammals.
00:23:38 - And one of those, obviously, is the group of mammals that led towards primates
00:23:43 - and eventually to ourselves.
00:23:45 - So what do you see as the most important changes from those earlier mammals
00:23:50 - to, say, the early primates?
00:23:54 - Well, that did give an opportunity for animals to become diurnal.
00:24:00 - It became a lot of opportunities for different kinds of environments that they could occupy and so on.
00:24:06 - Their risk of being preyed upon changed from these very efficient reptilian
00:24:13 - predators to the mammals that had to evolve into becoming efficient predators
00:24:19 - and opening up that predator environment for them.
00:24:23 - But early primates developed apparently from animals that were emphasizing vision
00:24:32 - more and living in bushes or trees and trying to go into the fine branch environment
00:24:37 - and live on insects and find food there.
00:24:40 - And it gave them an advantage of escaping some predators by being away from them.
00:24:46 - But it put demands on visual processing in dim light that were very powerful
00:24:54 - and so they had to devote more to vision.
00:24:58 - So eyes were big, a lot of receptors, but the whole visual system started to
00:25:04 - expand and devote more neurons and more cortical areas for sequential processing.
00:25:10 - Processing, and already in the ancestors of present-day primates,
00:25:15 - the temporal lobe would have been expansive.
00:25:18 - The fossil record shows the temporal lobe and occipital region are both expansive.
00:25:24 - Both of them are thought to be completely devoted to vision,
00:25:27 - and so the cortex now is going over and covering the whole midbrain and much of the cerebellum.
00:25:34 - You can get that from the fossil And, of course, if you're going around and
00:25:39 - catching things rapidly and find branches, insects that could hide or escape or die.
00:25:50 - Defend themselves in some sense, but you have to be agile. You have to be able to,
00:26:00 - hold on to a branch that may be moving up and down and reach and get something
00:26:05 - that may be on another branch and isn't moving or is moving in a different way.
00:26:09 - And you have to use visual guidance for these kind of movements.
00:26:13 - And grasping things with a forepaw would be something to be important and new,
00:26:21 - sort of, instead of grabbing things with your mouth, grabbing them with a forepaw.
00:26:25 - So, eye-hand coordination would start to become important.
00:26:28 - And so, all primates then, all living primates, have a huge investment at the
00:26:37 - cortical level in processing visual information,
00:26:40 - but also in processing sensory information relative relative to simple motor skills.
00:26:50 - So, yeah, and I think that's quite important, the idea of the hand,
00:26:54 - and also the hand being away from the mouth, so you can look where you want
00:26:59 - to eat something or pursue something and go with your hand for it.
00:27:02 - And in a way, also, that frees you from having the need for the whiskers quite
00:27:06 - so much because you now use your hand as this organ for touching further away in the world.
00:27:12 - But one of the things about primates, I think, that people notice is that they
00:27:18 - live in large social groups,
00:27:19 - and that the development of these societies of primates was possibly one of
00:27:25 - the important factors in their success.
00:27:28 - And is that reflected in the changes in the primate brain? Not all primates
00:27:33 - live in social groups, and a number of the prosimians don't.
00:27:36 - So it's uncertain, I think, if the first primates were social or not.
00:27:41 - There'd have to be some kind of evidence one way or other, and I'm not aware of any.
00:27:45 - They might have been solitary and nocturnal. The suggestion would be that they're nocturnal.
00:27:51 - But if you're going to go to the ground, or you're going to be out in the daylight
00:27:56 - and the ground, it's a tremendous advantage to be in a social group,
00:28:02 - because then you can be detected visually by a lot of different predators.
00:28:06 - You need a lot of sentinels. You have to have somebody warning you that there's
00:28:10 - danger and you're not too distracted by trying to find food or other things.
00:28:15 - So a social group then becomes very important.
00:28:19 - And a side benefit of a social group is you can defend a territory against other
00:28:24 - social groups or non-social animals and drive them out.
00:28:27 - And that would then impact on the sort of non-motor or less motor and less sensory
00:28:33 - areas of the brain and the way that they would change.
00:28:35 - This would impact on, I think, especially frontal cortex and enlarging frontal cortex.
00:28:42 - And you see in the monkeys and all the anthropoid primates that the frontal
00:28:48 - lobe is really well developed, but it's not very well developed in the prosimian
00:28:54 - primates by comparison to monkeys.
00:28:57 - By comparison to most other animals, the frontal lobes are quite well developed
00:29:03 - in even prosimian primates.
00:29:05 - So now we went with our cortex from the first vertebrates, and.
00:29:14 - Up now to the primates. But in some sense, that's not the only part of the brain
00:29:20 - that evolved or that changed, right?
00:29:22 - There's, let's say, also an underlying architecture.
00:29:25 - And also in your talk, you mentioned the McLean proposal of the triune brain,
00:29:29 - which might be considered a bit naive.
00:29:32 - But it was like one of these attempts to try to say like, okay,
00:29:35 - but these are the different parts of, let's say, an overall neural architecture,
00:29:39 - that we have to consider when we think about this evolutionary perspective.
00:29:44 - So what's your view on then these key ingredients of that architecture that
00:29:50 - actually leads to a successful brain?
00:29:54 - Well, every mammal or every animal has a successful brain in some sense.
00:30:01 - It has to be successful or they wouldn't be here.
00:30:04 - Well, I share features. That's the point, right? But you're right in pointing
00:30:11 - out that it's just not neocortex,
00:30:14 - but the whole brain is being modified in each line depending on what the requirements are.
00:30:19 - But they interact
00:30:22 - and I'll give a couple examples
00:30:26 - one example of course is optic tectum or
00:30:28 - superior colliculus as you're talking about mammals you don't
00:30:32 - get a cortical input to the optic tectum in non-mammals but you get a cortical
00:30:40 - input to the tectum but the regions that project to the cortex or the tectum
00:30:47 - superior colliculus in mammals is variable across mammals.
00:30:52 - So the inputs from frontal motor areas, for example, frontal eye fields and so on.
00:30:59 - That's unique to primates and maybe a few independently involved in a few other
00:31:03 - animals such as some carnivores and so on that are highly visual.
00:31:08 - So you're modifying a structure that has been important for vision through all
00:31:13 - vertebrates, basically. But you're modifying it by adding complexity to it and
00:31:19 - adding other ways of influencing its functions.
00:31:23 - But do you see this adding of complexity mainly occurring at this level of this isocortex?
00:31:29 - Or is it then also matched by the addition of complexity at these supporting
00:31:35 - midbrain and lower structures?
00:31:38 - So the midbrain will be modified, and architectonically it's modified.
00:31:44 - You can see it's changed greatly in different lines in terms of architectonic
00:31:48 - complexity, so its functions will be changed as well.
00:31:51 - The important feedback into the thalamus is very old,
00:31:58 - that there's a projection from the optic tectum into the thalamus,
00:32:03 - but how that's distributed to cortex has changed, its cortex has changed,
00:32:08 - its downstream projections become more important because they're influenced by other inputs,
00:32:16 - and so they're not really doing the same thing as they did before.
00:32:20 - And you could think of almost any structure.
00:32:23 - The amygdala would be responsive to direct inputs from the thalamic inputs to
00:32:32 - the amygdala that wouldn't depend on cortex at all,
00:32:35 - and they're highly important in a lot of mammals, but certainly non-mammals.
00:32:40 - Do you see, let's say that, because in some sense,
00:32:44 - the simple view on the phylogeny of the human brain would be like,
00:32:53 - okay, you have all these subcortical structures and they were sort of a constant
00:32:56 - and then this magnificent isocortex grew on top of that and that added all these
00:33:01 - amazing functionalities.
00:33:02 - An alternative view would be to say no actually it's a bit like we discussed
00:33:06 - earlier morphology and brain has to match and it's something you could say okay oh isocortex and.
00:33:13 - Subcortical structures have to match as well so it's always a co-development
00:33:16 - and change in these structures as opposed to these subcortical structures remaining
00:33:21 - constant and then your isocortex exploding,
00:33:23 - so where do you position yourself in that debate how should we look upon that well,
00:33:32 - So you're talking about systems that include cortical parts and other parts
00:33:37 - of the forebrain and parts of midbrain, hindbrain, spinal cord,
00:33:43 - and they all have to be coordinated and interrelated.
00:33:46 - But a lot of what happens depends on the changes in cortex to sort of drive
00:33:53 - these other changes, in my view.
00:33:58 - As motor centers in the cortex become important for controlling digit movements
00:34:03 - in hand and so on, you have to modify the circuitry in the cervical spinal cord
00:34:08 - that will deal with this control of muscles.
00:34:12 - Muscles, but deciding when to do something or how to do something and so on would depend on cortex.
00:34:21 - So it would be a series of gradual changes, I think, over many,
00:34:29 - many generations that would modify different parts but always together so that
00:34:35 - it would be pointless to have some function you couldn't use.
00:34:41 - But then if we now reduce a bit the level of granularity in that discussion,
00:34:48 - so now we look at, let's say, this brain with its different parts,
00:34:52 - we might have to sort of define what the key subdivisions are there.
00:34:59 - Co-evolving with the morphology, but now these larger chunks like isocortex
00:35:05 - and its underlying structure, like thalamus or basal ganglia or amygdala,
00:35:10 - again, consists of the subcircuits.
00:35:13 - And these subcircuits also will have some invariant features and also some variable features.
00:35:18 - So what's your view on that? What are the invariant features of such an isocortex
00:35:22 - and what are the variable features as such a brain is changing phylogenetically
00:35:28 - but also changing across the different modalities where it has to deal with?
00:35:33 - Well, tough question, but I've tried to emphasize some of the things that all mammals would have.
00:35:40 - It seems unlikely that we would involve any mammal without a somatosensory system
00:35:47 - that had somatosensory cortex involved in it.
00:35:50 - There are several divisions, but at least one division because we depend on
00:35:54 - this sort of sensory information so clearly.
00:35:57 - And once you relegate it to the cortical level, it seems like you're unlikely
00:36:02 - to change that and do those functions some other place.
00:36:10 - I can imagine the visual structures completely being lost in animals that no
00:36:19 - longer have functional form vision, as we see that those systems can be greatly reduced.
00:36:26 - Auditory could be lost. I can imagine it's not so important in some animals
00:36:31 - that live underground in tunnels, for example. You know what direction the sound
00:36:36 - is coming from because your body is blocking it or not and muffling.
00:36:41 - So sound localization as reduced sound is still important.
00:36:44 - You can imagine things being lost. lost in terms of higher order functions.
00:36:52 - You could go in any direction, I think.
00:36:58 - It could be modified in any way.
00:37:01 - It'd be easy for midbrain structures such as the superior colliculus to become
00:37:08 - completely auditory or completely somatosensory in function and not use vision at all anymore.
00:37:14 - It is already multimodal, and so you can just change functions.
00:37:21 - But the motor functions might be always very similar towards orienting towards
00:37:27 - a stimulus or something like that.
00:37:30 - Relay of sensory information as another route to cortex might be completely
00:37:35 - used in a quite different way.
00:37:37 - Right. So, a little procedure-wise.
00:37:41 - So, Tony wants to discuss with you a little bit developments in certain domains
00:37:48 - of science, like comparative neuroscience and so on, but then he has another appointment.
00:37:55 - So, then after that, I want to go back to some more specific questions and then
00:37:59 - later we just we added the interview that sort of these concluding questions
00:38:03 - go towards the end so that you're not sort of all right shocked by tony leaving
00:38:08 - and if you want to stop for lunch then tell him because otherwise he'll talk to you until it gets dark,
00:38:15 - exactly i will have to go and get my wife for lunch pretty soon okay um so well
00:38:22 - a couple of things if um the first thing i wanted to ask about multi-sensory areas in cortex.
00:38:29 - So it's clear that these early mammals have these new areas or sort of radically reduced.
00:38:38 - More sophisticated areas for analyses of the auditory and visual and spatiosensory inputs.
00:38:46 - Now, at what stage and whereabouts in their brains do they fuse these inputs?
00:38:51 - And how does the multisensory system evolve as mammals diversify?
00:39:00 - Opinions on this have changed a lot in recent times. When we were working early
00:39:04 - on in mapping visual areas 40 years ago, it was popular,
00:39:11 - and we believed it, to talk about visual areas or auditory areas or somatosensory areas.
00:39:17 - And we said, you know, most of the processing is done within a modality,
00:39:21 - and only at the very end, when things are very sophisticated,
00:39:25 - do you start to integrate modalities.
00:39:27 - And this partly was due to the methods of recording from anesthetized animals,
00:39:33 - where you really have dampened the responsiveness of neurons tremendously.
00:39:38 - And so you're getting this dominant input and say, yes, that's visual.
00:39:43 - And now when the anatomical methods and recording methods have been improved,
00:39:50 - you'll start to see people saying, it's multisensory everywhere.
00:39:55 - And Barry Stein had a book, is the editor of a book a few years ago on and multisensory systems.
00:40:05 - And you could say then it's amazing how fast multisensory processing evolved
00:40:13 - because it wasn't there very long ago, and now it's everywhere.
00:40:18 - But it depends on what you're looking at.
00:40:23 - Clearly, people are talking about in primates that even primary visual cortex
00:40:31 - gets auditory input, maybe somatosensory input, maybe not so directly, but...
00:40:39 - Some inputs rather directly. If you look at a small-brained animal like a rat
00:40:46 - or a mouse, you're seeing these kind of connections.
00:40:49 - Primary visual cortex will connect it everywhere almost.
00:40:55 - And if you look carefully at striped cortex projections like Henry Kennedy has been doing,
00:41:03 - And 99% of the connections can be accounted for with maybe five areas that you're talking about.
00:41:11 - But that 1% probably goes to 15 other areas and has some influence.
00:41:19 - So I think it's hard to find a neuron in the cortex that's not influenced by more than one modality.
00:41:25 - But whether it's driven by more than one modality, that would reduce the number
00:41:32 - of places. that you would find that.
00:41:36 - To give an example within a modality,
00:41:41 - you'll find in primary somatosensory cortex representing the hand in a monkey,
00:41:46 - neurons with small excitatory receptive fields on different parts of the digits,
00:41:50 - rather small, responding nicely.
00:41:54 - But if you get the neuron responding, and even in an anesthetized animal,
00:41:59 - and now have a second somatosensory input put somewhere else on the hand.
00:42:04 - It'll influence that firing.
00:42:07 - Then you go to the other hand on the other,
00:42:10 - and you will also influence that firing. And there's practically very few direct
00:42:16 - connections between the two hemispheres.
00:42:18 - For the hand areas, more connections would be from higher areas and then feedback connections.
00:42:25 - So it's not clear exactly how this is done, but it is clear that our traditional
00:42:30 - pictures of what neurons are responding to has been greatly constrained by our methods of looking.
00:42:37 - And when you look in other ways, you'll see the neurons are influenced by much
00:42:44 - more outside what's they call the classical receptive field in their own modality,
00:42:49 - but also from other modalities.
00:42:51 - Well, this is something very interesting. There's a caution here for students,
00:42:56 - that if you're reading the older literature,
00:42:59 - you may want to make sure that the opinions on these things haven't changed
00:43:05 - because there's been some really radical changes in methodology here that have
00:43:09 - made us revise our views on some of these fundamental questions.
00:43:14 - I guess another thing would be to say that this question of the multisensory
00:43:19 - cortex is really still open, that there's a lot more we need to know about this.
00:43:23 - And there are recognized areas in primates that are where neurons respond very
00:43:29 - readily, even in anesthetized animals to auditory and vision or vision and tactile and so on.
00:43:37 - And these would be called in earlier times or present times multisensory.
00:43:43 - Some of these areas have been called multisensory for a long time because of these responses.
00:43:51 - But 50 years ago, all the recordings were from a few primary sensory areas because
00:43:59 - anesthetics at that time just blocked everything else.
00:44:02 - So you had no chance of really talking about multisensory.
00:44:06 - So going to the field and how it's developed,
00:44:11 - so you've been in this field for a long time, and I think you were lucky to
00:44:17 - come into it at a time when people had this strong interest in comparative approaches
00:44:22 - and looking at different brains and different species.
00:44:25 - And now we have this fantastic new range of techniques to do this comparative
00:44:31 - study, but how do you feel the field of comparative neuroscience is looking
00:44:37 - in correspondence to the rest of the field?
00:44:40 - I mean, is this work happening, and where would you like the focus to be?
00:44:45 - Well, first, it's true I've been in the field for a long time.
00:44:49 - And this year I got a letter from Science Magazine, where we like to publish
00:44:55 - every once in a while. It's getting harder.
00:44:58 - And they said, you get a free subscription from now on. You don't have to pay
00:45:03 - for it anymore because you have subscribed for 50 years.
00:45:08 - So there are some advantages. I would say not that many, but there are some.
00:45:15 - And your question now is, how
00:45:21 - do I see the changes that have happened in comparative studies of brains?
00:45:26 - Has this field been influenced by technological advances as much as other parts of neuroscience?
00:45:35 - It's how you see the future for comparative neuroscience really more generally.
00:45:39 - So, there's obviously still many questions to be asked here,
00:45:44 - and how should we go about it?
00:45:45 - How should we balance our resources as a community between this comparative
00:45:49 - approach that you've been exploring and other approaches that are maybe focused
00:45:54 - more towards single-model animals?
00:45:57 - Well, I think the model animal approach has been a good one,
00:46:01 - and I wouldn't disparage it.
00:46:04 - Because if you work on a particular animal, you gain a lot of information that
00:46:09 - others have developed for you.
00:46:12 - If you work to another model or another animal, you have to do a lot of things
00:46:15 - over just to get to the point where you can answer the next question.
00:46:19 - So that becomes a problem. And sadly, in some ways, I started off working on
00:46:26 - cats as a model system, and they've been largely abandoned as a model system.
00:46:33 - And there's a tremendous amount of information known about brain organization
00:46:37 - in cats from years and years and years of study that is in some sense now not
00:46:44 - used to its full capacity because people have moved on to other models.
00:46:51 - That said, I think that we should always work on some primate models and some
00:46:57 - rodent models and maybe a few others, simple models.
00:47:00 - But simple models are limited in many ways.
00:47:05 - There was a debate at the Vision Science meeting, a friendly one just for the
00:47:09 - fun of it, and Tony Moshman was going to defend using simple models.
00:47:16 - He works on monkeys, so he was picked to defend using simple models.
00:47:20 - And he said, why stop at the mouse?
00:47:23 - C. elegans would be perfect because they're so cheap, the cost per individual
00:47:27 - is not even worth mentioning.
00:47:29 - They're so cheap, and they can do so many things. You can train them to move,
00:47:33 - turn to the left in a maze, and all kinds of things.
00:47:36 - And he went on for about 15 minutes about their virtues.
00:47:39 - But he said, there are two problems for vision research. They have no eyes, and they have no brain.
00:47:45 - So you have
00:47:49 - to have a model that has the capability or the potential of answering the kind
00:47:56 - of questions you're interested in and that means that we need a range of models
00:48:00 - because you can answer very general questions or very specific ones depending
00:48:05 - on what model you're using.
00:48:09 - But we also have a chance to study now a whole range of species and do it very
00:48:16 - productively because the methods are so powerful. You can learn so much.
00:48:20 - So you could take a new species, something that's never been looked at before,
00:48:26 - and you could know a lot about the brain of that species from one laboratory in three or four years.
00:48:34 - I think you could come up close to having a basic understanding of the brain
00:48:40 - organization in a relatively short time because the methods are so powerful.
00:48:46 - They were so poor when I was starting out. We were so limited in what you could
00:48:52 - do, and they were worse before then.
00:48:55 - And that people came up with such good ideas early on on such limited information is totally amazing.
00:49:03 - And given your vast experience and knowledge of different mammalian brains,
00:49:08 - are there particular animals that you think we should be exploring more?
00:49:12 - Well, from the point of view of evolution, brain evolution, which is of particular
00:49:17 - interest to me, it's important to learn more about the relatives of primates.
00:49:23 - Also, how much variability is in the primate order. We know a lot about a few monkeys.
00:49:29 - We don't know much about the diversity in monkeys. We know very little about apes.
00:49:35 - We're learning quite a bit about humans now from non-invasive methods.
00:49:39 - So there are big gaps that haven't been studied very well.
00:49:45 - Primate studies aren't very frequent. A review of publications over the last
00:49:53 - 15 or so years by Paul Manger showed that almost all the studies are on mice or rats or humans.
00:50:02 - That takes almost all those neuroscience studies.
00:50:06 - Studies, then out of primate studies that aren't human, then you have macaque
00:50:11 - monkeys studied, and then the next would be prosimian galagos,
00:50:16 - and they're only studied in two laboratories that I know of.
00:50:20 - So a single person or a few people could make a big difference by filling in
00:50:26 - gaps in particular areas.
00:50:28 - It doesn't take many, but we have a lot of gaps. I think.
00:50:34 - To study animals like the monotremes would be very important because they're so unusual.
00:50:38 - We don't know anything about the brains, practically nothing about any of the larger marsupial.
00:50:45 - We know a lot about opossums because they're available in this country.
00:50:49 - In South America, they're small.
00:50:50 - You can get them in the laboratory, but we don't know anything about the red
00:50:54 - kangaroo, giant kangaroo brain, how it's similar, how it's different.
00:50:58 - We don't even know very much about carnivores at different sizes.
00:51:01 - So you could pick, almost in any order, animals that are just a mystery.
00:51:08 - And someone studying them would be bound to find something interesting and informative
00:51:13 - just by falling in and trying to do this.
00:51:17 - So one of the things that could be done in a lot of different countries,
00:51:21 - and there's been a tendency to do this in Brazil, take the native animals that
00:51:26 - are there and try to understand their brain organization.
00:51:30 - So they're looking at say the very large rodents and so on how their brains are organized,
00:51:37 - so then to follow up on that so you also showed in your talk an earlier map
00:51:44 - of the cortex and most of it was actually white so by now.
00:51:51 - How much of this map of the cortex do you feel have you really filled in can
00:51:56 - we say look these are areas that But we really have understanding how they're
00:52:01 - organized, how structure maps to function, and how big are the gaps.
00:52:08 - There are major gaps, but depending on who you ask, people will feel,
00:52:15 - well, we've got the gaps pretty well filled in or not.
00:52:18 - So you can look at Brodmann's maps. There are no gaps.
00:52:23 - Right. But there are a lot of errors and different kinds of errors.
00:52:32 - We can make complete maps
00:52:35 - at any time and it depends on a tolerance of ambiguity or we can say well we're
00:52:42 - basing this on a very limited amount of evidence and so on and the kind of map
00:52:47 - that for example that Thelman and Van Essen did had a lot of uncertainty which
00:52:53 - they recognized and talked about,
00:52:55 - and I think it's important to talk about uncertainty so people don't get the
00:53:00 - impression that we really understand all the little divisions and subdivisions
00:53:05 - of the brain and where they are and how they're organized and how they interact.
00:53:10 - But if you would have to give this a number, would you say, look,
00:53:13 - 20% is reasonably well explored, so uncertainty is low for these areas,
00:53:19 - let's say primary visual, primary motor.
00:53:22 - There we know what we're talking about. Association areas is,
00:53:26 - let's say, synonymous with saying we have no clue.
00:53:28 - So out of the proposed about 100 areas in a macaque brain, I would say we probably
00:53:37 - have a good understanding of about 20, so that'd be about 20% in that brain.
00:53:43 - But it depends on what you mean. I would say that you can find good evidence
00:53:50 - for a functionally distinct region,
00:53:52 - but to define it precisely in terms of boundaries becomes a real problem.
00:53:59 - So if we talked about VIP today in the talk today.
00:54:05 - People are very uncertain about what you're talking about. You know roughly
00:54:09 - where you are, and you say, if I'm in this region, it must be VIP.
00:54:14 - But it's hard to pin down exactly where there he is, what the boundaries are.
00:54:20 - Are the boundaries variable across different individuals and so on?
00:54:25 - So I'd say that's a subdivision of the brain that's reasonably well understood,
00:54:31 - but it's not understood to the extent that you can say, I know I'm in it or
00:54:36 - I don't, I'm not sure whether I'm in it, those kind of questions.
00:54:39 - You don't know what all the connections are because we don't know how to define the area precisely.
00:54:45 - Right. But then in some sense, also in your recent work, I think this also illustrated
00:54:51 - maybe this issue a little bit.
00:54:54 - Because if you look at motor areas, then in some sense, the standard knowledge
00:54:58 - would be that you have a fairly abstract representation of, let's say,
00:55:03 - the direction of movements, acceleration of movements.
00:55:06 - We're close to the kinematics of the whole of the body that we're then controlling.
00:55:12 - But in your recent work, you showed that if you stimulate in these motorized
00:55:15 - areas, you actually can get whole coordinated movement pattern.
00:55:19 - So how do you then link or compare that to our standard understanding of these
00:55:25 - areas we thought we knew?
00:55:27 - We said, okay, there's something like a population response that gives you some kinematic control.
00:55:31 - But now it seems that in your recent results, you're saying,
00:55:34 - look, actually, we're talking about highly coordinated control of stereotype behavioral patterns.
00:55:42 - So where are we going with that?
00:55:44 - Well, motor cortex, even primary motor cortex, is especially interesting because
00:55:49 - the early maps didn't quite give the details of the way that they're organized.
00:55:54 - So you'll have a hand area, you'll have a foot area, a face area, tongue area even.
00:56:00 - But within the hand area, you'll
00:56:02 - get multiple representation of the digits movements, the same digits.
00:56:07 - You'll get a digit movement that the very next site where you stimulate it next
00:56:12 - to it, you'll get a wrist movement, or you might even get a movement at the elbow, or you might get,
00:56:20 - and the same digit movement would be paired with other digit movements or just
00:56:24 - that single digit movement, but that would be repeated over a large region of cortex.
00:56:29 - You would find the same movement again, and this seems to be different than
00:56:34 - some of the sensory representations.
00:56:36 - Why are you repeating these things.
00:56:39 - And you can say, well, it's important because any particular movement might
00:56:45 - be conjoined with any other kind of movement, and you want to have them close and interconnected.
00:56:50 - I think now that the long-term stimulation with showing more purposeful,
00:56:56 - behaviors or movements can be elicited from primary motor cortex or premotor
00:57:02 - cortex context is starting to give another perspective on this issue.
00:57:08 - Part of a cortical area of M1, of the hand area, will be involved in some kind
00:57:14 - of behavior with the hand.
00:57:15 - Another part will be involved in another kind of behavior with the hand and
00:57:20 - joined with arm movements and so on, depending on what it is.
00:57:24 - And so this adds a complexity as if parts of the area are.
00:57:31 - Are working somewhat independently from other parts of the hand area.
00:57:36 - You're not involving the whole hand area in one task.
00:57:39 - You're involving part of it, and other parts will be involved in other tasks.
00:57:44 - That's what seems to be suggested by these kind of stimulation experiments.
00:57:50 - So it's more complicated than it seemed originally.
00:57:55 - So are you saying with that, that in these motor areas,
00:57:58 - You would have like a library of discrete behaviors that are then sort of biased
00:58:06 - with respect to the limbs that are being involved in these behaviors.
00:58:11 - Should I look at it like that?
00:58:13 - I think you can look at it that there's an organization, a gross organization
00:58:19 - of foot to tongue from medial to lateral.
00:58:23 - And then within that, there's a more complex organization. but that organization
00:58:28 - is similar across individuals of the same species and even across members of
00:58:35 - the same family, different species.
00:58:37 - So you have this preserved, and the reason it's preserved must be that it in
00:58:42 - some way is specified during development to come out in a particular way every time.
00:58:48 - On top of that, you must have a tremendous amount of being able to modify these
00:58:55 - circuits by experience and training so that you not only want to be able to
00:59:01 - do some tasks that every animal has to do, every person has to pick up something,
00:59:06 - but you want to be able to develop specific skills that for a human may be making
00:59:14 - pottery or something like you practice and you get good at it,
00:59:17 - but it could be anything that you practice and get good at.
00:59:21 - For many species Species I practice in modifying the system may not be that important.
00:59:27 - If your average lifespan is eight months, you don't want to spend a lot of time modifying it.
00:59:35 - But for a long-lived species, this modification can be very important.
00:59:40 - So our motor cortex part of the motor system is greatly expanded. banded.
00:59:47 - It's got all these premotor areas and cingulate motor areas in it.
00:59:53 - So there's a tremendous amount of cortex involved.
00:59:55 - And exactly what this means isn't so clear, but.
01:00:00 - There's a big investment in motor control at the cortical level that interacts
01:00:05 - with posterior parietal cortex, frontal cortex, sensory inputs of various sorts.
01:00:10 - Right. But do you see these behavioral primitives now? So we're not talking motor primitives.
01:00:15 - We're talking behavioral primitives matching the ones that are represented and
01:00:20 - controlled at subcortical levels, like in areas like the central grave, for instance.
01:00:24 - Do you see some matching there between these primitives? So that means the motor
01:00:28 - cortex provides you an interface to the subcortical areas on which you can then
01:00:32 - start to play using, let's say, your planning and learning mechanisms you have
01:00:35 - at cortex. Or should I look at this differently?
01:00:38 - No, I think you're looking at it in a good way because it has been unpopular
01:00:45 - to talk about primitives or built-in sort of things in a human brain, for example,
01:00:50 - and say it's all learning or almost all learning.
01:00:57 - But then if you start looking at mammals in general, you see that there's so
01:01:02 - many things that would be too costly to learn,
01:01:07 - costly in that you wouldn't live long enough to learn them if you didn't know
01:01:11 - how to run away or escape or recognize a dangerous situation or to find your mother or whatever.
01:01:18 - There could be so many different things. There might be very rapid learning
01:01:21 - in the kinds of imprinting,
01:01:23 - first many things that would allow a pre-adapted system to rapidly congeal into
01:01:33 - eliciting a kind of behavior that's hard to rule that out.
01:01:39 - But then you have a whole system of levels of, say, a sensory motor,
01:01:47 - system that would have to be working in concert, pre-adapted for certain primitives, modifiable,
01:01:58 - hopefully in some ways, and on top of that then completely learned and modifiable
01:02:05 - sorts of motor behaviors that
01:02:07 - would be unique to the individual if they bothered to learn them. Right.
01:02:11 - So, John, to get to the finish line with our discussion, I have two questions.
01:02:19 - So, as you already indicated yourself, you got awarded this free subscription
01:02:23 - now to science because you have been paying enough money to this.
01:02:28 - I haven't gotten the first issue free yet, though.
01:02:31 - Exactly. We'll see. So, based on this broad experience you have in the study
01:02:35 - of brains and this comparative study of brains,
01:02:37 - what would you now see as the law of John Kass in our attempts to understand the brain? A law? Yeah.
01:02:47 - I'm not sure what a law is. We
01:02:51 - used to talk about laws and science quite a bit, but not so much anymore.
01:02:56 - So, this is your chance. Yeah, so I could make a law.
01:03:01 - John Ullman and I, when we started defining visual areas, thought,
01:03:05 - maybe they'll name a visual area after us sometime, but it never happened.
01:03:09 - Or an asteroid, maybe. So now is the chance for a law. Yeah, exactly.
01:03:13 - I don't think I can think of something that would fit the law.
01:03:20 - What I would like to take from other people that have made studies in development
01:03:28 - is that one level of the system will specify what the next level,
01:03:36 - a lot of its organization,
01:03:38 - so that you have this chain naturally that starts with sensory inputs and modifies
01:03:45 - the system to adjust to whatever the sensory inputs happen to be.
01:03:48 - This principle probably works anywhere in the nervous system.
01:03:53 - You make a change at any level in a complex network and in development,
01:03:59 - and the rest of the system will develop to accommodate that.
01:04:02 - And this makes brain evolution and change...
01:04:08 - Fantastically more easy, because you can imagine if it's, in some sense,
01:04:13 - based on genetic change,
01:04:15 - that you wouldn't want something that you had to change the genes at 10 different
01:04:22 - places, or the gene expression at 10 different places to get what you wanted.
01:04:26 - You would like to be able to make a change one place by some fortuitous accident of genetics,
01:04:33 - and that dies out because it didn't work well or it's propagated,
01:04:38 - but for it to work at all, it has to propagate itself through the whole system.
01:04:43 - So the John Kars law would be that when we look at the brain,
01:04:48 - its power is actually its ability to adjust to many different kinds of sensory
01:04:53 - inputs, also across different morphologies, right?
01:04:57 - So it's very much a very general design of many possible brains as opposed to a single one.
01:05:04 - And that the driving force is really how am I changing the inputs to this hyper,
01:05:11 - plastic control system I don't know how we can summarize it in three words.
01:05:19 - So then the second question would be,
01:05:23 - if we're going to get you back here five years from now and we do a similar
01:05:27 - interview I want to ask you okay did your prediction work out or not so what's
01:05:31 - the one prediction you would like to make today day that you're most enthusiastic about,
01:05:36 - that you have the strongest confidence in?
01:05:40 - I think that we're going to have, at the cellular level, a much better understanding
01:05:45 - of a whole range of brains.
01:05:47 - And one of the surprises that's coming out of looking at just counting neurons
01:05:53 - is a whole change from views that were made 20 years ago.
01:05:57 - And the view then was that all cortical areas are basically the same in the
01:06:05 - sense that their hardware is the same.
01:06:07 - Their neurons are the same. If you run a pin down through cortex,
01:06:11 - you'll count the same number of neurons no matter where you are and so on.
01:06:14 - The variability is turning out to be really tremendous, and it's possible to
01:06:19 - look at different aspects of that variability now.
01:06:23 - And one thing that's true that's going back to the early studies,
01:06:26 - They said that the one exception is primary visual cortex in primates,
01:06:32 - that the number of neurons is twice as many per unit volume of tissue than other places. It turns out.
01:06:43 - That statement is absolutely true for humans and for monkeys.
01:06:49 - It's less true for prosimian primates.
01:06:52 - It's less true for new-world monkeys and old-world monkeys and so on.
01:06:55 - So it's variable for primary visual cortex, but it's also variable in many other areas.
01:07:03 - And we don't know completely for humans yet, but macaque monkeys have variable
01:07:09 - numbers of neurons or neuron densities for different cortical areas.
01:07:14 - So they're specialized by changing the density of neurons, which implies changing
01:07:20 - the sizes of neurons, bigger or smaller, because that affects the density that you can pack them.
01:07:26 - And that wasn't appreciated, and it's just starting to become known as a big
01:07:33 - variable. But this variable is very...
01:07:36 - It is a major variable in macaque monkeys. It's going to turn out,
01:07:40 - I predict, to be a major variable in the human brain.
01:07:44 - And it's not going to be a major variable for most mammals.
01:07:48 - The neuron densities and neuron shapes and neuron functions are going to be
01:07:52 - more standard for most mammals, including prosimian primates.
01:07:56 - Okay, great. Well, John Goss, thank you very much for this conversation.
01:08:00 - Okay. That was great, John. Thank you.
01:08:04 - The CSN podcast was produced by the Convergent Science Network of Biometrics
01:08:10 - and Biohybrid Systems, a project funded by the European Sevens Research Framework Programme.
01:08:18 - For more interviews, recorded lectures or upcoming conferences in the field
01:08:23 - of biometrics and biohybrid systems, go to csnnetwork.eu.
01:08:30 - And thank you for listening. Thank you.
01:08:30 - Music.

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Jon Kaas on brain evolution and neocortex

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