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Big Ideas
Cartographers of the Brain: Mapping the Connectome

Imagine navigating the globe with a map that only sketched out the continents. That’s pretty much how neuroscientists have been operating for decades. But one of the most ambitious programs in all of neuroscience, the Human Connectome Project, has just yielded a “network map” that is shedding light on the intricate connectivity in the brain. Join leading neuroscientists and psychologists as they explore how the connectome promises to revolutionize treatments for psychiatric and neurological disorders, answer profound questions regarding the electrochemical roots of memory and behavior, and clarify the link between our upbringing and brain development. This program is part of the Big Ideas Series, made possible with support from the John Templeton Foundation.Learn More

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RADIO: Roger command, request navigation…

NARRATOR: Imagine this: your aircraft has state of the art avionics. But your map is from the 15th century.

RADIO: Command, this chart says we’re going to go over the edge of the earth please advise, please advise.

NARRATOR: Neuroscientists are stuck in this harrowing predicament as they try to make their way around the human brain.

VAN ESSEN: The first classical map made about a century ago is still widely used today.

NARRATOR: Published in 1909, it defined regions on the pinkish grey organ that control our actions and functions.

VAN ESSEN: The fundamental unit of brain organization for the cerebral cortex is what we call a cortical area.

NARRATOR: So on the map you could say there’s a country called ‘Speech’ and a country called ‘Short-term memory,’ another, ‘Hand movement.’ Identifying every one of these cortical areas became a major objective of the Human Connectome Project, the HCP, needing the effort of a master mapmaker.

VAN ESSEN: I consider myself a cortical cartographer.

NARRATOR: By July of last year, the HCP completed its first phase: a 21st century world map of the brain.

VAN ESSEN: We reported the presence of 180 distinct cortical areas.

NARRATOR: 97 of them were new to brain science.

TOTTENHAM: The Connectome gives us this opportunity, a really great tool to be able to navigate the human brain.

NARRATOR: Navigating the brain is more than just naming cities and states. You need to know about the connections between them.

LICHTMAN: The word ‘connectome’ implies that the fundamentally important thing about brains is connections.

NARRATOR: This evening, we’ll be talking and learning about two different kinds of  connections.

BARCH: Structural connections in the brain versus functional connections in the brain. By structural connections, we’re really talking about the physical connections.

LICHTMAN: The wires that connect nerve cells.

NARRATOR: So, structural connectivity looks at the regions and the pathways connecting them.

BARCH: Functional connectivity though is more about how different parts of the brain work together on an ongoing basis.

TOTTENHAM: Brain function arises from conversations that different brain regions are having with each other.

NARRATOR: A functional map must track living data, conversations flowing through the pathways between brain regions.

BARCH: We collected data from 1200 individuals. We had them do different tasks in the scanner, things like memory tasks, emotions on faces. Those same regions of the brain seem to be forming networks.

LICHTMAN: Brain structure is wired by it’s experience but we have no idea in what form that wiring diagram has that information.

NARRATOR: And that’s the big puzzle. To see how that translates into individual nerve connections, you’d need to look much closer than David or Deanna’s technology can go.

VAN ESSEN: Down to the level of individual neurons.

LICHTMAN: Two quadrillion times smaller.

NARRATOR: What exactly is two quadrillion times smaller? Well if the scale of David’s brain map is the big picture.

VAN ESSEN: Equivalent to a map of the whole earth…

NARRATOR: Then the area that Jeff’s covering would be a city about the size of say, Sheboygan Wisconsin.    

VAN ESSEN: That little blur that little blob that there might be Sheboygan, or we’re not sure.

NARRATOR: That little blob is a one-millimeter cube of brain tissue. And it contains a staggering number of neurons.

LICHTMAN: 50 thousand nerve cells and about one billion synapses.

NARRATOR: So right now there’s no to model an entire human brain by diagramming its micro-wiring. Scientifically for now, we’re lost in the foggy limits of brain science.

LICHTMAN: You would need more digital information than is the actual digital content of the world.

JOHN HOCKENBERRY, JOURNALIST: We are going to have the most wonderful scientists in the world talk to us about their experience with mapping, with mapmaking, with map conceptualizing, with brain understanding. Our first guest is Professor of Neurobiology at Washington University in St. Louis, Principal investigator for the Human Connectome Project.  A fellow of the American Association for the Advancement of Science, he is internationally known for his research on the structure, functions, connectivity, evolution, and development of the cerebral cortex in human and nonhuman primates, please welcome David Van Essen.

[00:00:04:50] HOCKENBERRY: Our next participant is a Professor of Psychological and Brain Sciences at Washington University St. Louis and an investigator with the Human Connectome Project. She’s on the scientific board of the Brain and Behavior Research Foundation and the Stanley Foundation.  A fellow of the Association for Psychological Science and a member of the American College of Neuropsychopharmacology, please welcome Deanna Barch.

Joining us is a professor of molecular and cellular biology and the Ramón y Cajal Professor of the Faculty of Arts and Sciences at Harvard University.  Developmental Neurobiologist, member of the National Academy of Sciences, Jeff Lichtman.


Our final guest is an associate professor of psychology at Columbia University and director of the Developmental Affective Neuroscience Laboratory. She’s a recipient of the Institution of Mental Health Bio-Behavioral Research Award for Innovative Science, the American Psychological Association’s distinguished Scientific award for early career contributions to psychology and the Developmental Science Early Career Researcher Prize, Nim Tottenham.

Jeff, what’s the Connectome?

JEFF LICHTMAN, BIOLOGIST: Well, on this stage you have four people who would probably have a slightly different idea of what the Connectome is.

HOCKENBERRY: That’s what we like.

LICHTMAN: Yeah, so from my perspective, the Connectome is a project to map the connections between the nerve cells and synapses, at the level of synapses which is doable but the price we pay is this extraordinary amount of data we need so that doing a cubic millimeter is for us a triumph, and we’re not done with a cubic millimeter I should say. That’s two thousand terabytes of raw data.  

HOCKENBERRY: That’s not a zip drive, that’s–  

LICHTMAN: Yeah, but in terms of the other realms, and maybe you guys can talk about this, a cubic millimeter is your voxel size.  That’s the smallest thing you ever see.

HOCKENBERRY: Nim, what do you– how would you describe the Connectome project to someone who asked you, “so what do you do” at a party?

NIM TOTTENHAM, PSYCHOLOGIST: I think, building on that answer, there are so many levels to address when you’re thinking about connections in the brain. So there’s the very, very small levels that have tremendous meaning and contain an incredible amount of information, but then you can look at more macro levels that we can use with FMRI that tell us about a different level of representation of information within the brain. So it’s going to take a lot of data to be able to map out all of those various levels.

HOCKENBERRY: And Deanna, how would you describe the Connectome?  

DEANNA BARCH, PSYCHOLOGIST: I think I would agree with Nim in the sense that there’s really connectomes at many levels of analysis: at the level that Jeff is working on, and then at the level that says ‘okay, all those different cubic millimeters in the brain, how are they wired up and how do they work together, and how do all of those conversations, to use a term Nim used, kind of support all the different behaviors, and thinking and emotions that humans are able to do? So I think we really need all of those across all of those scales eventually to really understand the full human connectome.

HOCKENBERRY: And David, would it be fair to say, and I deliberately left you last here, that you’re the most macro here?

DAVID VAN ESSEN, NEUROSCIENTIST: I think it’s fair to say that Deanna and Nim all work at a very macroscopic level, the luxury of working on the entire brain of living individuals but, and the other part of what drives us is the need for not only as much information as we can but as rich across different types of imaging, magnetic resonance imaging is the dominant one that we’ll talk about here but there are other, what we call modalities, magnetoencephalography, electroencephalography, give a richer information in the rapid time course of the signals they follow, but not as good in terms of the resolution and space. So all of these types of information can work hand in glove to give us deeper insights into an incredibly challenging and exciting set of problems.

HOCKENBERRY: Jeff. I mean, in many ways, you’re the astronaut in the suit, sort of untethered from the mothership, way out there. What inspired you to do the work that you do?

[00:09:30] LICHTMAN: You know the history of neurobiology began with this guy, Cajal who made this rather remarkable leap of faith from looking at structure that has more or less stood the test of time, this idea of a directional network.  And I think that just as going from Gregor Mendel and his peas to the atomic structure of DNA to the human genome, going down and then back up again, I think neurobiology has to do the same thing. You have these ideas that nerve cells are connected in a wiring diagram, that’s what Cajal said. And now it’s up to our generation and the generations following to get those wiring diagrams, to really know what they are.


LICHTMAN: Many people would say the birth of neuroscience came with the absolutely groundbreaking work of Santiago Ramón y Cajal, a Spanish physician, pathologist, and ultimately neuroscientist, who used a technique called the Golgi stain, that allowed Cajal to stain brains in ways that very small numbers of nerve cells would be rendered dark and all the other cells would be clear. Cajal was a gifted visual genius. He had ink, a paintbrush. That’s what he did. He just drew pictures on paper.  They are absolutely beautiful. And not only beautiful, but he inferred this very dynamic view of the way information flows. There’s a network of cells and the cells are of various types and they talk to each other. And he was right almost always. And it was such a radical idea that Golgi, who invented the stain, absolutely did not believe that that was true. Even at the Nobel Prize, Golgi kept saying that Cajal was an idiot that he just screwed this up entirely. But time has allowed him to win out here.

HOCKENBERRY: Let’s see the tools that you use to get beyond.

LICHTMAN: So the first thing we tried is if the Golgi technique is good and every small subset of cells are labeled black and you can learn something about the circuits, what if we could see every single cell and instead of black, we made every cell a different color? We called this technique BrainBow and it’s been extraordinarily popular as screensavers for those of you… yeah it’s a very powerful technique of labeling every cell a different color and in certain parts of the nervous system, it really does reveal circuits. But when you get to the cerebral cortex, guess what? There’s just so many wires there that you can’t actually tell the colors apart because even at the finest resolution of the light microscope and there’s a picture of those big blobs are nerve cells and all that stuff in between, that felt work, are the bazillion wires that attach them and you can’t resolve them as individuals. So yeah we have to go to a different technique. So that’s plan A, so plan B is what we’re working on now which is to do this, not with light and color, but use electrons which have a much shorter wavelength and give us the ability to resolve every one of those wires. And the way we do this is we take a block of the brain and we fill it with a metal called osmium.  And we take that block of brain filled with Osmium, that little black spot in there and then we put it in plastic, really hard plastic and we put it on a chuck and we move it up and down, against a diamond knife. That’s what’s going on in that second picture, and then from there, out comes one section after another. They’re about a thousandth as thick as a human hair so it has a thousandth of a hair thickness. Then we pick them up on a tape and then we take a picture of each and every one of them with a very high-resolution microscope. And the pictures are 250,000 pixels by 250,000 pixels for each image. And then we need to take 33,333 sections like that to do a cubic millimeter. So that’s what—-

HOCKENBERRY: So you take that level of resolution in 2D and do 33,333 to make it 3D.

LICHTMAN: Right. So it’s basically a film strip, and you take those pictures and you stack them up and you get a stack of images that are now a three dimensional image of the brain and then you color in the objects using deep convolutional neural nets to generate the structures of the brain. Here is a dendrite of a nerve cell and an axon talking to that cell in green and that’s just one piece of an area we did, which is just so discouraging. It’s so depressing. There’s just so much stuff in these brains!  There’s 1500 nerve cells. This is three billionths of a mouse brain. It took us five years to do three billionths of a mouse brain when we started. It’s just extraordinary: there’s a synapse every cubic micron so there are 1500 synapses in there so… yeah…

[00:15:36] HOCKENBERRY: I mean… I could say this to all four of you but really, my response is just ‘I am not worthy. I am not worthy.’ I mean, do you ever think about how fifty years from now, a hundred years from now, how they will look back on this work and—

LICHTMAN: As primitive and stupid.  It’s like the early days of genomics when people actually used their thumbs and pipette men to get the DNA sequence of a virus. And now we have these robots who can do a whole genome in a day or two for a few thousand dollars. We are now back at the virus stage. We’re just starting.

HOCKENBERRY: Nim, where would you say, in terms of the two parts that we’re going to be discussing, functional and structural sort of aspects of the macro-brain. Where are the scientific disagreements within that? What are the arguments, what are the big questions?

TOTTENHAM: Yeah, I mean I think when just looking at the people we have on the panel here, one question we want to know is are the data that we’re getting on the level that Jeff’s seeing comparable to the types of level we’re getting with FMRI and what is FMRI measuring and…

HOCKENBERRY: What does that stand for, FMRI?

TOTTENHAM: Functional Magnetic Resonance Imaging so it’s the-

HOCKENBERRY: So what’s that taking a picture of?

TOTTENHAM: It’s the data that gives you the activation patterns on the brain, so what we commonly think of as the blobs on the brain.

HOCKENBERRY: And is that… the pictures of the neuron electricity?

TOTTENHAM: So it’s not electricity, it’s an area of active inquiry to try and understand what is the bold signal? So when you’re seeing those colored pictures, what you’re getting is a statistical map of a signal called Bold, which is giving us an index of where oxygen is being distributed differentially across the brain as the brain is engaging in a particular task.

HOCKENBERRY: So its data that presumes that a mapping of blood activity and oxygenated blood activity in the brain is comparable to neuronal and cognitive, well I mean not cognitive, that’s too much to say but electrochemical activity in the brain, is that fair to say?

TOTTENHAM: Right, it’s an inference. We can only make an inference with those data.

HOCKENBERRY: How good is that inference, Jeff?

LICHTMAN: The challenge is in one little blob of the FMRI image, you have fifty thousand nerve cells and a billion synapses from hundreds of different cell types over many different layers of cerebral cortex. Each part of the cerebral cortex is layered and there are different kinds of things going on in each layer and all that is compacted into a single dot.


LICHTMAN: Yes, so it is a global average. I would say if you tried to do the equivalent of an FMRI on the United States, you would be looking at energy use in cities. Perhaps.


LICHTMAN: Yeah Sheboygan maybe. You might be able to get a little bit of Sheboygan data. You’d get more data from bigger cities. And these cities have a lot of energy use in the daytime.  They fall off at night, but it’s not like nothing is going on. But you would not be looking at each individual person or each individual activity. You would be looking at essentially all the lights on in a particular part of the brain at a particular time.  And so you can infer something, I’m not saying you can’t infer something, but there is still a chasm between the machine that’s doing the work that is very, very intricate, and these rather global macroscopic techniques that can work in a living human brain. I can’t-if you want me to do this to your brain, I have to kill you. So.

HOCKENBERRY: I’m scared of you most of all Jeff, that’s for sure. And Deanna, FMRI, useful tool but there’s a huge horizon beyond it. That’s fair to say?

BARCH: Yes, absolutely.

HOCKENBERRY: And David, you would go along with that? We don’t need to belabor this point.  

[00:20:05] VAN ESSEN: I would also agree strongly and I would point out there’s another type of information that is very important for the Human Connectome Project and other endeavors which is what we call diffusion imaging and looking at structural connectivity and that is also a very informative method. It relies on the preferred diffusion of water along the length of axons within the white matter and it’s a little bit faster than trying to get across the membranes of each axon. That indirectly informs us about local orientations of fibers bundles that can then be stitched together to estimate long distance connections from one region of grey matter to another. That is also fraught with its own challenges because it’s looking at bundles that are criss-crossing one another to reflect the actual reality of brain circuitry and we can make estimates, but they’re not perfect and so another of the hot debates in the field is what can we infer that we can put confidence in and what do we have to be very careful of and not over-interpret?

HOCKENBERRY: But I have to say David, those are some damn pretty pictures. Those are great. Why spend so much time and money mapping every single connection if we might never be able to finish it? Jeff?  

LICHTMAN: You know I think that everyone probably would agree that the Human Genome Project was worthwhile. This was a descriptive attempt to get the nucleotide sequence down to every single nucleotide in the DNA of a human being. And when that project was first proposed, there were a lot of people who said, “Why should we spend all this money to get all this DNA; we know a lot of it is junk DNA, there’s a lot of things in there we don’t care about. Why do this? This is just going to be impossible to understand.” But no one in the scientific community at least doubts the extraordinary value of actually having a data set that describes the human genome, and not only that, but now that we have the way to do it, we can get your genome and my genome and they’re different. And the genome of people who have diseases are a little different. A profound amount of insight has come from generating that data set and I see connectomics just like how I see genomics: it is a way to describe the brain at enough resolution that we can begin to make reasonable hypotheses about how brains of people who have disease are different from brains of people who don’t have diseases of the brain for example. How baby brains are wired differently than adult brains.

And old people, even old people who don’t have dementia, and my children would count me in this category, are a little different from young people. We’re a little more set in our ways. Why is that? Where does that change take place? Where are all our memories stored?  There are millions and millions of questions where this kind of data would be justifiable.

HOCKENBERRY: By analogy to the genome, how much variability do you expect from in the connectome?” Does that question make sense?

LICHTMAN: Yes, that’s a great question. Obviously there are five of us sitting here and we all have a different set of experiences that have molded us into the adults we are. People like me believe that information is embedded in our wiring diagrams so it would be shocking if our wiring diagrams are very similar. Now, it’s true also that genomes are not identical, otherwise we would all look the same, which would be very scary I think.

HOCKENBERRY: But there’s no way the connectome variability would be on the order of chimps have 99% of the same genetic information it appears that humans do.

LICHTMAN: I think that this is a good question. It may be depending on what level of resolution you look at. If you look at the major pathways that connect parts of the brain, things that come out of the BOLD technique and perhaps at diffusor tensor imaging, you might find that brains actually are 95% similar. I actually don’t know but probably they’re quite similar. If you get down to the wiring of a little piece of cerebral cortex, we would probably see a lot of substantial differences between the brains of different people.  


BARCH: Well I was going to say I think this it’s kind of the glass half empty, glass half full and I think this is one of the interesting things that’s coming out of the data produced by the human connectome project because one of our explicit goals was to look at individual differences and relate them to brain or behavior. And I think we’re seeing exactly that, that there is remarkable similarity in a sort of basic network structure, at the level of Sheboygan and Chicago and New York but there are also really interesting differences, that seem to relate to behavior, including a lot of those sort of high level cognitive and emotional and motivational behaviors. So I think we’re going to see it’s both, that there’s real commonality in key structures, but really important individual differences that link to behavior.  

[00:25:24] LICHTMAN: I think many people use this as a strong argument against doing this. Well if everybody’s brain is different, what are you going to learn from doing just one brain? Well it’s a bit like saying what could you learn, if every city is different—

HOCKENBERRY: Why teach all the kids?

LICHTMAN: Right. There’s another example. But every city is different. But if you studied in detail Paris, I suspect you would get insights that translate to London, to New York—

HOCKENBERRY: David, who inspired you to do this work and what was your original conception of a brain map?

VAN ESSEN: I’ve been fascinated by the cerebral cortex for forty years and when I started working on the problem I was looking at the visual cortex of an animal model, the macaque monkey.  It has a sheet of tissue that is convoluted to get it to fit inside the skull of a monkey and one of the challenges I faced was in order to get information about the brain and the connections, it was necessary to take slices of the brain and look one slice at a time. I was compelled by the analogy with maps of the earth, that two dimensional of a convoluted sheet are very informative, so at that time, I actually used pencil and tracing paper to make crude but useful maps of the visual cortex and then the entire cerebral cortex of the macaque monkey. I knew this was a job better suited for a computer and when I moved to Caltech in 1976, we started working on that problem. But it literally took two decades to get the computer horsepower but more importantly the algorithms into operational shapes for others to lead the way. A number of groups have worked on that effort so now we can make computerized maps of the monkey’s cerebral cortex but more excitingly, of the human cerebral cortex, which is even more complicated and convoluted.

HOCKENBERRY: When you were kicking around back as an advanced science student in high school and maybe college, what were the visuals that you could see that would show you what the map of the brain or the functionality of the brain supposedly was all about?

VAN ESSEN: They were pictures in books and it’s nice that you brought forward exhibit A which is the classic, century old map of the human cerebral cortex by the great German anatomist Korbinian Brodmann who published…

HOCKENBERRY: This is the 1909 map you were talking about.

VAN ESSEN: That’s right. I learned about it in college and it’s still taught today as one representation but it’s analogous to maps of the earth’s surface from the mid sixteenth century for intents which were quaint and colorful. Brodmann, there’s a colorful version of his but this is the map that he used and it was actually accurate to this day for a few of the fifty other regions he identified but there was reason to suspect that this was not the whole story and it’s been a century long endeavor to make better maps of the human cortex.

HOCKENBERRY: (speaking German)

VAN ESSEN: Your German is impeccable.

HOCKENBERRY: 1907. So, getting from these maps, you had to, and you alluded to it a moment ago, you had to really begin to describe the meaning of the folds in the brain. Right?

VAN ESSEN: That’s correct. I think of the folds in the human cerebral cortex as analogous to the crumpling of the earth’s surface into mountains and valleys and other geographic features. And that’s of course very important as part of the physical substrate for understanding the lay of the land quite literally. The cerebral cortex contains about sixteen billion neurons in each individual and it’s the interactions and communications of local and long distance connections and functions of those neurons, that determine what we call the parcels or cortical areas in the human cortical sheet.

HOCKENBERRY: So is it the case that in the beginning, the brain is smooth in an embryo and then development…

VAN ESSEN: In an embryo and even into the first two trimesters of human embryonic and fetal development, its very smooth—it just gets slightly curved in its shape.

[00:30:09] HOCKENBERRY: Alright so this is first trimester.


HOCKENBERRY: No real crinkling there at all.

VAN ESSEN: So by the beginning of the second trimester, things have gotten into a somewhat curved shape, but in the explosion of cortical growth in the last, the third trimester of human gestation, things get really wild and crumples up like that. Yours is good for one individual and mine is even more crumpled, so it’s pretty severe.

HOCKENBERRY: So the more of this, the more of this.

VAN ESSEN: Well the more that can fit inside the skull, it has to get through the birth canal. That’s one of the reasons we have to have a highly convoluted cortex to get a pizza like sheet of tissue for each hemisphere crumpled up to fit inside a compact skull that can get through the birth canal. But by birth, the cortical convolutions are nearly as complex as they are in an adult, even though the brain is only one third the size of an adult brain.

HOCKENBERRY: It only goes to show how important the brain is in terms of creating more complexity in a confined space. Right? You’re limited in the space. You’re unlimited in the level of complexity that you can do. There are other limitations but this is how the brain solves its own problem of dynamics.

Nim, would you say that the maps that we have now, the visual or tools that we have now are helping us to pose new questions or answer more questions than they pose?

TOTTENHAM: Both, for sure. I mean, I think that as a developmental psychologist, the reason why I came into this is because I was very interested in behavior and where behavior comes from, and being able to get some tool that gives us structure and function to attach these behaviors to changes everything. It starts to answer the question that you raised which is: how does the environment get under the skin so to speak, right? So to use an analogy from the heart, our cardiac tissue is the tissue and our heartbeat is the behavior that’s associated with that tissue. So likewise, our brain is the tissue and behavior is the output of that tissue. So if you want to understand and be able to ask deeper questions about behaviors and where they come from and why am I different from you and why are we similar in other ways, then being able to have this tool changes the game.

HOCKENBERRY: Deanna can you explain for us the great pictures that we have of the twin, identical twin brains? These are identical twins.

BARCH: Well I think that the twin data does a wonderful job of illustrating what Nim talked about in terms of both how the environment gets into the brain and how genetics shape the brain. So when you look at the brains of twins, there are things especially identical twins who share the vast majority, 99% of their genetic makeup, there are clear similarities, things that are more similar about those twins than other ones. But there are also fascinating differences.

HOCKENBERRY: I mean, they don’t look identical. Identical is not even a word I would begin to use.

BARCH: No, because there are also environmental factors that get under the skin and into the brain that are going to shape you know how the brain wires up, how those convolutions over time and the twins’ behavior will probably follow and be similarly different or the same depending on how much they’ve experienced the environment differently.

HOCKENBERRY: And even if you take identical twins, and no one would actually do this, and put them in identical green rooms and fed them identical green food and gave them identical glasses of water at the exact same time everyday for eight years, you would still get differences.

BARCH: You would get some differences for sure, yeah.

HOCKENBERRY: But it would be less.

BARCH: It might be less. I mean, that’s actually a great question. We don’t know-

HOCKENBERRY: It’s not a good experiment though

BARCH: We’re not going to do that experiment. But I think obviously to the degree that we believe environment also shapes brain development, the more similar the environment, the more likely it is that those things will be shaped, you know, in a similar way. But again, we can’t really do that experiment to deliberately manipulate how similar or not similar the environments are.

HOCKENBERRY: Go ahead, David.

[00:34:54] VAN ESSEN: But since most of the cortical folding, the development of the convolutions occur before birth, that’s actually occurring in not quite identical but in the same womb and very similar environmental influences. So the fact that the outcome at birth of newborn identical twins, their brains are very different, that tells us that a lot of this is driven by subtle, perhaps epigenetic influences, and perhaps small differences in environment lead to perturbations that lead to different folding outcomes. But the other part of what’s important here is that even though the newborn twins or any other individual has a relatively, highly convoluted and relatively mature looking cortex, during the expansion that occurs by a factor of three, especially in early afterbirth, post natal development, the regions that change the most are the regions that we associate with higher cognitive functions. So that’s where our plasticity, our ability to learn and develop and emerge with sophisticated concepts like drive this conversation, that’s occurring in specialized regions of the cortex that are more plastic. They are also more vulnerable to abnormal experience and perturbed development. So this relationship to disorders and disease comes into play in that regard as well.

HOCKENBERRY: During this rapid period, things like the autism spectrum might emerge because it is such a complicated and rapid developmental period that is not well understood physiologically.

VAN ESSEN: That is correct, although we know that there is a certain genetic heritability to autism in terms of the likelihood of having an individual, a child somewhere in the autism spectrum disorder. But it’s called the spectrum for good reason because there’s tremendous diversity in many ways and that’s where the experience, particularly in early childhood development is likely to shape the trajectory of individuals and where we desperately want to understand how can we decipher what’s going on and perhaps better treat and modify the outcome.

HOCKENBERRY: Nim can you describe, lets extend this developmental discussion because a clock begins, as David was sort of saying at birth and there are various kinds of developmental pathways that are emerging at different times, and we’ve started to separate them a little bit and really understand what race takes place at what time.  

TOTTENHAM: Yeah so human brain development is one of the most fascinating things right? Because we start off, all of us, as a single celled organism and then we all go through this miracle of development where we create the most complicated three pounds in the universe. And we all do it more or less the same and yet we all have beautiful, individual differences. So where did those come from? So why would mother nature go through that whole process? Because that’s really inefficient.  Metabolically, arguably, that’s incredibly inefficient. And the reason is that it gives us what David was talking about earlier: this incredible plasticity during development. It’s like throwing a big fishing net into the ocean and then pulling back what you need. Because when we’re new on this planet, when we just land on this planet, we don’t know what household we’re going to land in, we don’t know what the climate’s going to be, we don’t know what language we’re going to have to learn and yet we all do it. And so in many ways, in order to understand the mature human brain, you want to understand the brain through infancy and childhood because that’s what gives us that end product where we’re all exquisitely adapted to our environments in which our brain grew up.

HOCKENBERRY: But the profile of the adaptation process, the becoming an adult, the maturation and the development of a personality, et cetera, is actually a subtractive process.

TOTTENHAM: It’s a series of progressive and subtractive or regressive processes.  So if we look in the back of the brain where the visual cortex is, you see this overshoot which I described and then this pruning away like you prune your rose bushes, this pruning away of the synapses that your brain realizes it doesn’t need. It’s inefficient to keep those.

HOCKENBERRY: What are the two functions here that are being looked at?

TOTTENHAM: So in the pinkish line is where we’re looking at the back of the brain, the visual cortex, and you see that increase in synaptic density—the density of the connections and then you get this pruning back as we get older.  And then if you look at that blue line, that’s the frontal cortex in the front of the brain and it does the same thing but you can see that that whole curve is shifted over. So that’s reflecting that we have these processes of increase in synapses and regression that’s happening in our brain but in hierarchical fashion where we go from the back of the brain to the front of the brain which really reflects the way these behaviors emerge over development, right? So we—

[00:40:35] HOCKENBERRY: Professor Nim, does this mean that evolutionarily, cognitively we require visual information to inform our cognitive selves and so that’s why cognitive development might lag behind visual?

TOTTENHAM: Right so brain development makes sense evolutionarily but also within one individual’s lifetime.  So first you have the sensory systems coming on line because you need to be able to take in information from the environment. Then you’ve got motor systems to allow you to interact with the environment. And those are necessary prerequisites in order to do all of the cool, higher level stuff that we can do like plan for the future or fall in love or control our emotions.

HOCKENBERRY: Or even be blind, I mean blind people are going through an adaptive process.

TOTTENHAM: Right. So we have multiple sensory systems, right? So we have this plasticity early on in life, where we can shift resources to where it suits us best.

HOCKENBERRY: How does learning multiple languages early on affect brain development? Any knowledge about that?

TOTTENHAM: Yeah, so there’s a lot of excitement in this area. So one is, it just speaks to the behavior of language.  So your brain will undergo Neural-Darwinism during development. It learns based on who’s being activated, which synapses are being activated or not.  If they’re being activated, then I’m going to keep them and if not, then I’m going to prune them away. So if I’m being exposed to both English and Japanese as a six month old, then my brain is going to hang on to both of those.

HOCKENBERRY: Is that what happened to you?  Is that your experience?

TOTTENHAM: That was, no, I don’t speak Japanese. I wish!

TOTTENHAM: That in and of itself is amazing, that we’re that plastic. So I can’t speak Japanese. There are many sounds, phonemes in Japanese that I will never be able to process. But when I was five months old, I could. But my brain decided that it didn’t need to hang on to those anymore. So that, in and of itself is amazing. And then the second thing is that there are all of these cascading functions, all these cascading benefits that you get. So children who can speak two language, two languages fluently also have this amazing benefit in their prefrontal cortex. So they’re able to switch very easily in terms of cognitive functions because they’ve had a lifetime of switching what languages their speaking and understanding what the other person is expecting of them in terms of language.

HOCKENBERRY: I’ve also heard that somebody from South Asia who spoke I think 7 languages. Her experience was that once you get past two, three, four and five are easy. Is that… is that what the brain tells you?

TOTTENHAM: Right so the brain starts picking up on what are the common principles that I need to extract from a language so as you gather three or four, if that’s the magic number, you get a broader sense of what are the generalized principles here that you can apply to new languages. So yeah I would say probably the second language is the hardest to learn and then yeah after that, it’s nothing to brag about.

HOCKENBERRY: You’re sort of just feasting.

TOTTENHAM: It’s nothing to brag about after that.

BARCH: John, one thing that’s important too is that those effects don’t just last through childhood. There’s evidence they last for your entire life and actually may be protective later on in life against things like cognitive decline, even dementia. More work is needed there, but they have a lot of evidence that it has very beneficial, long lasting effects.

HOCKENBERRY: Is free will an illusion? In other words, is the brain the be all and end all… this is sophisticated, the be all and end all to our decision making? When you get to the connectome, will you be looking at a deterministic image? Anyone want to take that on?

LICHTMAN: I would like to because one of the great surprises for me when we actually began reconstructing brains at the level of resolution of the wiring diagram is the insane density of wires and synapses in the brain. It might as well be called free will because it is so darn complicated. It’s not that you have to find that one place where there’s a switch which you can just flip or roll dice and you’re going to go left or right.  The whole brain is made up of billions of elements, trillions of synapses actually that each have a certain amount of stochastic behavior so you might as well call this free will. It is free will for us. We believe we have free will. You look down from an airplane at New York City at night, you’ll see most people on the highways are leaving the city. You look in the morning and those people are coming in. That doesn’t seem like free will.  To someone up there, it looks like we’re doing exactly what we’re supposed to do to make our city to work.

HOCKENBERRY: Anyone else want to say anything on free will?

VAN ESSEN:  I agree with Jeff, it’s in our control.  What does control mean? That’s part of what we want to decipher. Will we ever understand it? Perhaps not but fundamentally the richness of brain circuitry gives us, in practical terms, “free will” that is our handle on that concept.

HOCKENBERRY: Do you believe brain data including but not limited to the connectome can be faithfully recreated in a Von Neumann machine. Now a Von Neumann machine, is something like a Turing machine, a theoretical idea of a computer that would reach a level of complexity that would be able to behave comparably to what we’d think of as autonomous.

LICHTMAN: I get this question a lot, that if you get the wiring diagram, aren’t you 90% of the way there to having a thinking machine? The wiring diagram is a static entity at the moment you take it and it doesn’t tell you the way information is flowing through those wires. This was one of the great discoveries of neurobiology: that information flows in a direction through individual nerve cells. That information is often stimulated by things from the outside that are activating your retina or cells in your ear or skin. None of that is build into these wiring diagrams. That’s coming from the outside. And so when we look at the wiring diagram, we don’t see what is actually going on. At the level of fMRI, at least you see areas of the brain lighting up, but at the fine level of the way the machine works, we haven’t found a way of putting information into those wires in a way that simulates the way actual experience goes into the brain.

HOCKENBERRY: David, you were going to say something. Do you remember what it is here you were going to say?

VAN ESSEN: It was a follow up to the question about autonomous agents and artificial intelligence. And one thing I’ve learned through my career is never say never too earnestly because some of the things that we’re talking about is everyday scientific experiences. We’re out of the realm of what I could even imagine, let alone say that would be possible someday. Technology advances are driven by the laws of physics but they can make profound advances.

HOCKENBERRY: So some of the things we’re talking about up here right now were impossible to imagine when you were an undergraduate.

VAN ESSEN: That is correct. Even magnetic resonance imagining, I remember thinking about, would there be some way to measure brain activity and talking to experts and it didn’t seem like it was going to go anywhere in the early 1980s. That was lack of vision and insight about how the clever ways into the new technologies could be achieved by physicists and engineers. But I was also going to come back to the point about artificial intelligence. Many people know about entities like Watson and other extraordinarily sophisticated computers which, in some contexts can do impressively well in communicating with humans and giving the appearance of intelligent thought. Arguably there is some degree of intelligence there. I don’t think Watson now would be able to sit at this discussion with a fifth chair or sixth chair and carry his or her digital weight in this kind of free flowing conversation.

HOCKENBERRY: But I’ve heard Watson described one time as a combination of the Library of Congress and sprinter Usain Bolt, running around getting source material—

VAN ESSEN: Right, working in a profoundly different way. So will there be versions of artificial intelligence in the future that are dramatically better than Watson? Unquestionably in my mind. Will that ever come close to the cleverness and insight and perspective of real human beings having a conversation like this? I personally am on the skeptical side. I wouldn’t say impossible, but I’m doubtful. And I think if they are doing it, one of the fascinating challenges is to what degree will computers emulate human-like thought strategies? To what extent will they use principles of neural-circuitry like what Jeff focuses on, to process information in ways that emulate the characteristics that Deanna, Nim and I look at in the living human brain. A huge, open and exciting question and it’ll come back to the next generation of young scientists who carry that ball forward.

[00:50:46] HOCKENBERRY: How can we continue to develop new synaptic responses as an adult?

TOTTENHAM: So we do, we are. The fact that we can learn new things, the fact that we can form more memories depends on these microstructural things happening, otherwise we would have no memory. So we have incredible plasticity early in life. It decreases but it never goes away permanently. Some argue that in some areas of the prefrontal cortex we actually never reach our “full mature state” because we’re constantly exhibiting high levels of plasticity. So, some of the exciting interventions are things like ‘how can exercise boost that even further for individuals who are experiencing cognitive decline? Or how can pharmacological agents increase that plasticity further?”

HOCKENBERRY: Career changing millennials.

TOTTENHAM: Career changing millennials.  Sleep. All of the things we want to know if they’re good for us are probably having an effect on increasing our plasticity.


BARCH: Yeah, I was just going to comment on that and sleep and you know there are fascinating theories on sleep is sort of a way to clean up synapses so you can do more the next day. There’s fascinating work looking at brain injuries and ways that rehabilitation can help with, you know, rewiring the brain. So I think that there’s a lot of hope that it will continue on. It’s less but it still continues.


LICHTMAN: Well, you know, I hate to say this because it’s a downer but being an old person and I’d like to think that I’m infinitely flexible, but I remember when I was young, being impressed at how narrow-minded my parents were when they were my age. And I have a feeling that my children think a little bit about me this way. So although I feel plastic, I think the world is beginning to assume I just always talk about the same thing over and over again. I say it’s because it’s really interesting but it’s probably because all of the other things my circuits could have done have been pruned away.

HOCKENBERRY: Rust. All we are is rust.  But I mean, if you took up the violin or something…

LICHTMAN: I wouldn’t.

HOCKENBERRY: I’m so glad I didn’t end on Jeff.  David?

VAN ESSEN: Well I see a lot of younger faces out in the audience and I would reiterate the point you guys are the future of those of us who are above fifty, to put it mildly. We will continue to work hard and look for opportunities to strengthen in plasticity, in healthy aging. We will continue to chip away at the profound impact of brain disorders and diseases, which is a scourge of society and we desperately need better solutions. And we are excited by the interest in the brain and neuroscience manifested by the wonderful attendance at this session and we look forward to future years and reading and learning about the accomplishments of the next generation, so thanks to all.

Big Ideas
Cartographers of the Brain: Mapping the Connectome

Imagine navigating the globe with a map that only sketched out the continents. That’s pretty much how neuroscientists have been operating for decades. But one of the most ambitious programs in all of neuroscience, the Human Connectome Project, has just yielded a “network map” that is shedding light on the intricate connectivity in the brain. Join leading neuroscientists and psychologists as they explore how the connectome promises to revolutionize treatments for psychiatric and neurological disorders, answer profound questions regarding the electrochemical roots of memory and behavior, and clarify the link between our upbringing and brain development. This program is part of the Big Ideas Series, made possible with support from the John Templeton Foundation.Learn More

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