Jeff Lichtman: Connectomics: Mapping the Brain | Harvard Department of Physics

I I'm Alyssa Franklin I teach physics here and I we have a new new lecture series once a month Wednesday's public lectures from the Harvard faculty Harvard including science faculty faculty from the Medical School that's it and anyhow I'm really really glad you came it's a terrible day it's windy and rainy and horrible and it's a wonderful turnout for that kind of day so I just want you to know that the reason we had you sign in was just so we could figure out who you are and maybe you want to come again to different lectures in this series which hopefully will go for the next 30 or 40 years until we're all no longer able to come anyway I want to introduce professor Jeff Lichtman he's going to give a fantastic talk I've seen it I've seen it anyway he I just wanted to tell you a little bit about him he was younger and then he got older when he got older he moved he went to Bowdoin College that's in in a in a state north of here and then after he graduated from there he went to Washington University which is in st. Louis where he did an MD PhD and the PhD was in something like neuroscience then he liked it so much in st. Louis that he stayed there for 30 years then when his hair turned white he came to Harvard I actually I don't know that it's true where he where he started up this great neuroscience initiative and he's going to talk about I think he's interested in how information gets stored in the brain and a lot of people are interested in that and then what happens to it after it gets stored and then what happens to your brain after the information is there the thing I find incredibly fascinating about this field is that nobody knows which approach to trying to figure it is going to work so it's really really exciting and so Jeff is going to talk about his particular approach and here he is thank you very much for braving the elements tonight I consider myself a very dedicated scientist but I wouldn't have come so I am impressed and grateful that there's my wife is here but I'm grateful that everyone else is here as well in fact I'm not even sure she feels it's appropriate to come given the weather I am a neuroscientist and I've been one for most of my adult life and because of that the language I speak has words in it that may be unfamiliar to you and and I strongly suggest that if I say something and you just don't understand what I'm saying just shout out a question interrupt me so that I make sure I'm not saying something that you can't can't follow neuro scientists of course study the nervous system and I think you're all aware just that the if you read the newspapers or listen to the State of the Union address or know what's going on in Europe there's a huge amount of interest in the brain right now and it's a fair question why the nervous system gets so much attention you know there's like three or four departments in every medical school associated with the brain psychiatry neurology there's usually a neuroscience department for the medical students there's just a really remarkable amount of interest in it but there's not like a kidney department or a lung department or a liver department and it's worth considering why why this might be a special organ system and I want to begin by saying that all organs all parts of the body have the same general relationship but in a physical organ a structure and what the organ does its function and this is a theme that biologists are very interested in that the relationship between the physical structure of something and its function in fact the state of the art in biology right now is a field called structural biology it sounds like a very broad field but it's actually quite a narrow field it's a field that focuses in on the atomic structure where the atoms are in single molecules to explain how that molecule does its function so molecules like enzymes that tear up other molecules or molecules that bind to DNA our molecules where their physical structure is analyzed at the level of single atoms to understand how that structure gives rise to function and this is where a lot of state-of-the-art biology is taking place of course there was a time when humans were interested in the relation between structure and function but it was long before we knew anything about atoms I think the first time people began thinking about this is probably when they opened up the carcasses of animals they were going to eat or looked inside the carcasses of human beings and notice that there are all these aggregations of tissue that had a kind of a familiar look because the same aggregation could be found in individual after individual even in different species all vertebrates have a liver all vertebrates have lungs all vertebrates on the land at least have lungs and there was a time when you could see these organs but what their structure was was not so well understood and certainly their function was not understood either there was at those early times probably the first organ that kind of got a structure function explanation that is the structure explained the function was the heart we're without anything but a naked eye looking at a frog heart beating perhaps the heart of another animal beating near at the time of death last few beats you could tell that this was a pumping organ that was moving blood around the body but but the liver or the kidneys it wasn't so easy to to relate the structure of those organs to their function and the big breakthrough in understanding the relation between structure and function was the invention of microscopes because with microscopes one could see for the first time and this is hundreds of years ago now that each of the organs had its own cellular motif that is the cells were put together in a particular way that was so standard that once you saw that cellular motif and understood it you could find it again and again in any animal so if I know what the liver of a human being looks like I also know what the liver of a zebra looks like or even a frog they have a similar relationship of nerves of cells not nerve cells and in each organ there was a special cellular motif in the kidneys which filter the blood there is this complicated tubules system and once you understand that tube you'll system it's kind of easy to infer what is going on in kidneys as a filtering system in the lungs there's this vessels that carry air that get very close to vessels that carry blood and that allows gas exchange between the outside atmosphere and the lungs so for each of these organ systems we've made tremendous progress in understanding the cellular motifs that underlie function and with that came a huge bonus which is that for most of these organs all or of these organs except except for one which I'll talk about in a moment not only did you understand the normal structure function relationship but you discovered that diseases of those organs almost always had an abnormality in the cellular motif there was something wrong with the cellular motif so when people's livers aren't working well if you look at a little biopsy of liver you will find it's either a cirrhotic liver or another kind of disease of the liver in other diseases like hepatitis inflammation of the liver in kidney there are many diseases of kidney each of them have their own particular appearance of a cellular motif and so we've not only learned the normal structure function but for diseases of these organs we have an underpinning of what's wrong and that leads to ways of thinking about therapy now let's think about the brain where all of what I've just told you is not so true the brain has lots of diseases and these diseases believe it or not many of them are incurable not simply because they're hard to cure but because we have no idea what's wrong we don't know what's wrong because the underpinning of the cellular structure of the brain is not well understood at all this is a tremendous challenge for human beings and it means that the nervous system is for some reason much harder to understand than any of the other organs and I'd like to start this conversation with you by going through some of the reasons why the nervous system compared to all the other organ systems in the body why the relationship between the structure and the function of the nervous system is much more complicated I'm doing this because I want to justify what will seem to you a kind of crazy goal which is to actually get the structure of the brain at a level that we could understand things that seem like they're worth understanding but once you start seeing what we have to do to get that structure you're going to say this is crazy and so I have to justify it I think by giving you a sense of why the nervous system is such a special case the first thing about the nervous system that is different from other organ systems is that the cellular motifs are insanely complicated in part because the number of different kinds of cells that make up the brain far exceed the total number of different kinds of cells in the rest of the body for example there is a state of the art question right now about how many kinds of cells there are in the retina not how many cells total but how many different kinds of cells make up the retina which part of the nervous system and as nervous system goes it's perhaps the most organized part of the nervous system everything is laid out in Nice layers everything is distributed in a nice tiled way and yet it is a research question of many of my colleagues to count how many different kinds of cells there are and this huge structural diversity I'm going to give you a sense of just how many types of cells are on the retina in the next slide that generates a not only a large number of cells that you have to sort of figure out how they're connected to each other but because of that what the nervous system can do is much greater than what other organs can do you can imagine you could write a chapter you couldn't but most some physiologists could probably write a chapter and tell you everything that a kidney does it may be a hundred pages or so it wouldn't tell you every disease of the kidney but the normal function of a kidney could probably be described in in a hundred maybe 150 pages how big a book would you have to write if you wanted to say everything a human brain could do could you write a book like that you couldn't it in part because every every week we're doing things with our brains that were never done before my children are a good example of this they're using their brains to do things with tools that I can't use the you know their brains are constantly kind of evolving especially human brains to do new tasks and this is partly related to the fact that the structure of the brain is much more complicated so so let's start by looking at the kinds of cells in the retina so this is a a menagerie if you will of about 50 different kinds of cells in the retina that everyone accepts is there and they fall into photoreceptors there are some that respond best to green light some best to red light some best to blue light so there are three kinds of photoreceptors then there's a kind of cell called horizontal cells and the structure of these cells show you that there are different kinds some that are sort of symmetrical and some that are very asymmetrical the cell bodies of these cells are these little swellings here then there's another kind of cell called bipolar cells so you can see by where the cell body is relative to these branches there's many different varieties of bipolar cells it's not a continuum each of these is a class and this is the number of classes that people have seen then there's a kind of cell called a Makran and look at those there just over a wide variety this is all in one retina and then ganglion cells which is the cells of the retina that go into the brain and send visual information into the thalamus there's a wide range of those as well so here's 50 cell types and no one believes that's the total number everyone believes there will be more cell types that some of these can be broken into 2 3 4 maybe 10 categories someday we will know how many cells there are in the retina but that's not going to help us one bit with the cerebral cortex where it has its own complete menagerie of cells or the cerebellum or the brain stem or the amygdala or the spinal cord so this is a big problem about getting the cellular motifs and getting the structure that underlies function so that's problem number one problem number two is that the brain is very different from other organs in another very interesting way some of you probably know people who have donated a kidney to let other people live why does a person donate a kidney because they can without killing themselves because if you've got one kidney you've got kidney enough in fact you don't even need one kidney you can do with even less than a whole kidney you can do with one lung you can lose a lung you can lose part of your liver it doesn't matter you can survive that fine but if I take half of your brain any half no matter how you want to cut it you're going to notice and that is because what is the difference between the brain and these other organs that if you look at a kidney you find it's very boring once you see that cellular motif its iterated hundreds of thousands of times over and over and over again one part of the kidney does the same thing as another part the lung is made up of these alveoli that come up right close to blood vessels one part of the lung does the same thing as another part you lose part of your lung you still can breathe but the brain is different because it's organized at many different size scales there's importantly different information every single part of the brain and I want to just go through that with you by sort of zooming in from the most macroscopic picture of the brain down to the most nanoscopic or microscopic picture so we'll start with a brain this is a human brain in cross-section this is the back of the brain and this is the front of the brain and this is about 10 centimeters maybe 20 inches 25 inches 2 feet about 10 centimeters wide here and even at this level we know that the brain has many many different parts for example if you're trying to plan for what you're going to do to get back home after this lecture and you're thinking about that rather than about what I'm saying your frontal cortex is being involved as you're looking at what I'm showing you here we're activating the occipital lobe where vision is when you get up so you don't fall over your cerebellum is working on balance each of these parts has specific roles to play in your function you lose the front part of the brain you may see fine but you can't plan for the future you lose your cerebellum as an adult you can't balance and the brainstem we're breathing takes place is also essential obviously the spinal cord where motor activities are so at this gross level already the brain is divided into very different functions and this is of course a miniscule portion of the thousands and thousands of things brains do if we go down an order of magnitude from 10 centimeters to a little piece of brain now we're looking maybe at about a centimeter of brain you find that the cerebral cortex itself which is just shown here is divided into an outer part where the nerve cells are and an inner part where the cables that connect nerve cells from one part of the brain to another part are the inner part is called the white matter made pink here just to confuse you and the grayish white outer part is the gray matter and so even in in this little area there's nothing uniform about it the outer part of the brain has a different function than the inner part if we zoom in on the outer part the cerebral cortex as it's called and go now from a centimeter down to a millimeter so this is like say a millimeter by a millimeter and then label a single nerve cell and there are many many there's hundreds of billions of nerve cells in your brain but if we look at one nerve cell in a region like that this is what it looks like these cells are crazy they're just way way more complicated than the cells anywhere else in the body the cell has a cell body like cells elsewhere but these cells have huge numbers of what you might think of as antennas these are their dendrites that collect information from other cells and the fact that this cell is distributed over more than a millimeter of length that's just for its reception of information from other cells but the cell also has a process sticking out of it called an axon which then sends this cell's information to other cells and that axon can spread its branches all the way to the other hemisphere or down the spinal cord or to the thalamus it can go centimeters so this one cell covers huge areas of the brain and every brain cell has a similar kind of distributed network and this allows cells to receive and send information to a vast number of other cells if we zoom up from a millimeter to a tenth of a millimeter which would be a hundred microns and just look at the dendrites of these cells we find that the dendrites themselves are divided into two categories and that is you zoom in on one dendrite you find that the dendrite has these little spines sticking out of it and then there are regions in between where there are no spines and it turns out that the spines are the place where cells receive information via synapses from neurons that are trying to excite this cell and make the cell talk to other cells and when there are other kinds of inputs in the brain that try to shut this sell off called inhibitory inputs and those are mostly connections made on the shafts the non spiny part of dendrites so there's this other division of labor that's very important that you see when you start looking at 1/10 of a millimeter now if we want to zoom in on one dendritic spine and go down to 10 microns we see that again there is a remarkable amount of interesting structure so let's look at that region there and to see that we have to now go to an electron microscope we're now looking at things where the resolution limits of light microscopes get in the way the diffraction limit of light makes it difficult to resolve all the information so this region here I just color it in for you this is one of these dendritic spines there's a dendrite and it has a little process coming out and a little swollen end and it has this little thing in here you probably wouldn't have noticed if I didn't point it out called the spine apparatus which is in there and it's an important part of the spine so that's the spine that's receiving information from an axon from another cell and the axon is shown here in cross-section this is an electron micrograph so this is just cut sliced through a thin piece of brain and here this thing is an axon and it's filled with these little circles and those circles are synaptic vesicles and each of those vesicles is filled with neurotransmitter and when the neuron that this axon came from is excited it dumps the chemical neurotransmitter in these vesicles right against the membrane of the dendrite right here at the synaptic connection and so this is a synapse in the brain this is where all the communication between one cell and another takes place there are about a trillion or more synapses in the brain so there's many of them and you can see that they're not bi-directional they're uni-directional most of them the axon sends information to the dendrite so here is one little place where one neuron is making a connection with another neuron to communicate some information to it and the brain is just filled with that and this is one of the challenges of neuroscience just to understand what all these synapses are doing now I want to give you one sense of why this is such an extraordinary problem if we look at this kind of resolution up at the brain level there are tools like functional magnetic resonance imaging some of you may have heard of this it's a technique that measures local blood flow in the brain to see what parts of the brain are working when you do particular tasks fMRI is done with a resolution of about a cubic millimeter that is the smallest spot you can resolve with fMRI is about one cubic millimeter millimeter on each side a little box that's a cubic millimeter on a side and we have learned very important information about the brain using this technique because as I said the brain is distributed so functions are distributed to different places this is a very powerful approach and a lot of people when they see these images say oh that explains how the brain works but let's think about the resolution of an electron micrograph it is its voxel size is a hundred cubic nanometers nanometers are a thousandth of a micron a single nanometer and this box the voxels the resolution of this image is a trillion fold smaller than the resolution of this image and if you want to understand the brain you've got to understand details at the level of the electron microscope at the level of the light microscope all the way up to the level of the fMRI that's a trillion fold range and no matter how you slice it that is a big number and that's just to get the information about how the brain is organized you have to deal with a trillion fold range in resolutions so those are the easy problems yeah there's a harder problem and and this is the one that I'm most interested in and it is related to something that I'm sure most of you know which is that all structure that we think about when we think about bodies and organs are are built based on a genetic blueprint your genes build the structure and the structure generates the function that's how kidneys livers all the organs work with one notable exception again and it's the brain and let me give you an example of why this is not entirely this whole story and why it's so hard to understand how brains work and for this I need to know is there anyone here who learned to ride a bicycle or tried to learn to ride a bicycle as an adult who never had experience with bicycle riding as a child anyone here who was tried to ride a bicycle as an adult for the first time I suspect there is someone but they don't want to admit it because it's not a pretty story they would be telling I have a neighbor who grew up in another country and she moved to Cambridge number of years ago started a family it's two daughters one couple summers ago one was like nine and the other 11 and they were beginning to ride their bicycles around our street which is pretty quiet and the mother did not ride a bicycle but I think either she was jealous because they seemed to be having so much fun or it's just amazing how quickly a kid can get out of the view of the parent on a bicycle for one reason another she decided she was going to learn to ride a bicycle so a couple of summers ago she decided to ride a bicycle as an adult and I watched this I didn't watch all the time a job but when I was home I paid attention and watching it was very interesting as far as I can tell this woman is neurologically normal in all respects except when she gets on a bicycle where she looks like she doesn't have a cerebellum she just cannot balance the thing you know her arms are going backwards and forwards and her kids are you know literally riding circles around her and making fun of her it's very embarrassing I'm sure and and for reasons I think related to the incentive of wanting to be with her kids doing this she she worked on it all summer but I noticed as the summer went on she was doing it less and less and by the end of the summer I didn't see her on a bicycle and I haven't seen her on a bicycle since so that says her kids learned how to ride a bicycle and she didn't but let me tell you another story which is about me and I like most of you learned to ride a bicycle as a child and then we moved to st. Louis where I just didn't have opportunity to use a bicycle and so I walked I wrote a car alot and says nothing about st. Louis there's lots of people ride bicycles there but I didn't write a bicycle and then in 2004 we moved back east to Cambridge and in 2005 my wife told me I was growing I was very excited which is not this way you're going this way and maybe uh you know it's time for you I think she said we we should we should exercise she meant me but and we decided bicycle so she decided bicycles would be a good idea so we went to a bicycle store I'd been our bicycle in a very long time and you know how it is at bicycle stores they give you a bicycle to try out where you go outside and you take this road trip only a block long and they watch you very carefully and so you know if you're a nervous person it's a little harrowing anyway to have somebody watch you ride a bicycle for the first time and I hadn't ridden a bicycle in a very long time and I got on the bicycle and and sure enough I was having trouble with balance but it was only for about eight seconds and then suddenly it all came back and I was riding perfectly fine now what is the difference between me and the woman who cannot ride a bicycle as an adult it's not that I've been practicing bicycle riding for years I there were many years a decade or so or more when I wasn't riding a bicycle at all and yet somehow it was still there my bicycle riding and and so the question I would ask you is what is the difference between the brain of a person who can ride a bicycle and the brain of a person who can't what do I have that she doesn't have where is she got something that I don't have that by getting rid of it I can now ride a bicycle nobody really knows this is a fundamental question but to bring it back to this point I don't have a gene for bicycle riding I didn't get bicycle riding from genes where did I get the bicycle riding from I got the bicycle riding from practice from the use of my nervous system rehearsal and practice I've changed somehow the structure of the brain and that structure then has given me a new function it this is a loop biologists hate these things we like these linear things because you knock out a gene it changes the structure change of the function but in a situation like this cause and effect are very confusing and we don't like this but this is true this is happening all of you if you can button your shirt if you can speak a language you can ride a bicycle your brain has stabili changed itself based on experience and what is the form that experience has taken in your brain is a deep question but because it can last for such long periods of time even without rehearsal one argument might be it's related somehow to the structure of the brain which is the interconnections of nerve cells so if you want to understand something like that you're going to have to map out the connections at some deep level I don't think like a brain of somebody who rides their bicycle it has a big pathway connecting to parts of the brain that someone who doesn't ride a bicycle has it's probably very subtle and to map out these subtle differences one would need to map all the connections humans have a penchant for mapping things and the big map we've made for humans is the human genome project where with genomics we've mapped out our DNA yes I would say if this way that it's not that an adult can't learn new things at least I hope that's not the case although my children would argue with me about this they seem to think I don't learn as much I'm not as adaptable as them it's certainly harder for adults to learn than children and if you want to learn a new language as an adult without an accent it's almost impossible for a child they don't even have to work at it at all it's natural so they're our ability to learn difficult tasks becomes more and more limited as adults I know you don't want to hear this people my age hate hearing this we like to think we're plastic our brains are constantly changing but what we're learning as adults is a miniscule fraction of what we learned as children and we it's much harder for us to learn new things now my kids don't ask me too many questions anymore in part because they say there's no point because they know exactly what my answers will be and and that's a very depressing thing to hear but I remember thinking the same about my parents that there was a point when it's just no point in telling them or maybe telling them but asking them they would almost always react the same way and so yeah I wouldn't want to make it as black and white that adults can't learn anything obviously I read the newspaper I feel like I know something today that I didn't know yesterday but I think I filter everything I learned through what I already expect the world to be like it's very hard to make an adult Republican into a Democrat you would agree with that or vice versa you agree with it no okay so if we want to map out these connections we would need a no mix like genomics but it wouldn't be genomics it would be connect omics this is a new term probably for most of you I brought the dictionary definition and this word here is just how you would make a function into a structure you'd make a physical Engram of it so I made up this word in Graham at ization it's not a real word but that would be this process of turning experience into physical structures you in grama ties your structure your functions into physical structure this is a deep mystery what does bicycle-riding look like what does your grandmother your memory of your grandmother look like in your brain nobody knows but I think if one wants to know that one's going to have to map the connections at the level of individual connections and that would be connect omics so here is the dictionary definition of connectomics or connectomics it's a plural noun but singular in construction like economics is something this is for Merriman Webster's unabridged dictionary 2019 it's a branch of biotechnology when I first made this it was 2014 and I've keep having to push this number up it's going to depressing a branch of biotechnology important to see that this is biology but it's technology you can't just say oh I'll map that on you know I'll come in and map it you have to do this in an industrial way so it's really a technology just like the human genome was done by a bunch of machines concerned with applying the techniques of computer assisted image acquisition computers are essential for this process and analysis of the structural mapping of sets of neural circuits or to the complete either to map some neural circuits or perhaps even map the complete nervous system of an organism using high-speed methods you've got to do this fast or you'll never finish as you'll see and organizing the results in databases and by databases I don't mean you know Excel spreadsheets this is a really a different kind of data this is you know very large data big data maybe and with applications of the data as in neurology and psychiatry so I began by saying there are all these diseases of the nervous system that don't not only don't we have a cure we don't even know what's wrong and that's because their diseases where we don't have a physical underpinnings of many psychiatric diseases and adults at some neurological diseases where we mainly see abnormal behavior or a patient complains of like migraine headaches but there's no blood tests there's nothing you can do to confirm that other than looking at the patient there's no physical instantiation not that there isn't it's just we can't find it until we have I think a deeper understanding of the brain so you might say there are pathologies of the wiring diagram connect tapa thiis that one would like to get at and that's going to require connectomics if one wants to get the proximate cause of those diseases and fundamental neuroscience questions such as what does bicycle riding look like and and it may be also the word connectome would be like a genome the full wiring diagram in the brain so that is the goal and I'm going to tell you just two approaches we've taken the first was to try to do the nervous system wiring diagram with a light microscope and this is a to take advantage of the idea that if every nerve cell were a different color and the whole brain were lit up maybe you could get the wiring diagram just by looking at the color of cells connected to each other this may seem fanciful but some of you may know that thanks to a jellyfish that bioluminesce is a green color because of a protein in it that's fluorescent that as you shine blue light on it and at fluoresce is green this green fluorescent protein gave rise to a revolution in the use of fluorescent proteins to understand things and and one of the things that came out of the discovery of the green fluorescent protein which got a Nobel Prize in Chemistry few years back was that then it was clear that there were certain corals that were red fluorescent proteins were in them and other corals that had blue fluorescent proteins so you know when people put black lights on their aquarium and get these beautiful corals to oh this is because of the fluorescent proteins in these animals so there are red fluorescent proteins green fluorescent proteins and blue fluorescent proteins and you may know that if there's a protein that's fluorescent there's a gene that makes that protein and once these fluorescent proteins were their structure was understood it was not long before clones of the genes for these proteins were found so we now have genes for red fluorescent proteins green fluorescent proteins and blue fluorescent proteins so we have a dream for a green a red and a blue fluorescent protein and that is really all you need to get all the colors a human being can see because we only have three kinds of photoreceptors in our eye one for red one for green one for blue so if you could make every cell have a randomly different amount of red green and blue relative to every other cell each cell would have its own hue you know this is the way color television works there are only three colors in this projector but all the colors you see are mixtures of the amount of red green and blue that are coming out here and we filter it all through our own eyes so RGB is all you really need so I won't tell you that the molecular trick we did but we built these animals we call brain bow animals that have lots of colors in them I'll just give you a sense of what these what parts of the brain look like these are nerve fibers cut in cross-section these are ones running along the plane of focus these are the ones in cross-section you can see there are lots of colors this is in the auditory pathway and here's a zoom up of a another region of that you're very pretty they almost look like paintings of some sort if we zoom up on that little region you can see the individual fibers these are axons that are very big that are taking auditory information from your ear and sending it in to your brain stem and because they're big the information travels very quickly and that's an essential part of hearing and then if you focus up and down on a little data set like this you just focus in and out you see this kind of remarkable fact that if you look at any one of these objects you can kind of follow it as you're as you're going up and down these things are not really moving in the sense that you're just looking at one slice after another with a laser scanning confocal microscope a particular kind of microscope but this allows you to trace out branches over long distances some of them are running into the plane and out and others are running across the plane so this is in the brainstem where the axons as these little branches are all axons are very big in other parts of the brain like the cerebellum a very special kind of cell called the Purkinje cell a very large cell again they all come in different colors and if we view this by focusing up and down from this direction turning this on its side and focusing up and down you see these kind of remarkable cellular details of how individual cells dendrites these each color is a different cell are running parallel to each other but they interfere with each other slightly and I don't this looks to me like fabric or something I don't really know exactly what it is that it looks like but it's pretty to look at and here one more example is this may look like a butterfly but this is actually the spinal cord and these are the neurons in the spinal cord that send information to your muscle fibers to cause them to contract they're called motor neurons spinal motor neurons and this particular line of Brainbow mice these are genetically these animals inherit these colours so that each animal will have the same kind of color distribution from one generation to the next these cells are then connected to muscle fibers so if you look at the nerves coming out of the spinal cord going to a muscle you find that the axons coming out again are all different colors and this was very gratifying to see because it meant we could follow them long distances and but it's important to realize we did not invent this idea this was invented by people trying to figure out how computers work they put colored wires inside computer hookups so you could trace a wire from one place to another and that's basically the same thing that was done here here's just one more picture of these wires so over very long distances you can follow each individual wire going to the periphery if you look at these axons where they get two muscle fibers you can see the synapses and this again is a three-dimensional data set but now rather than folk sing through I'm just spinning it for you and what you are looking at here take a moment to get used to seeing this is that these axons end in these pretzel shaped objects that appear to be clasping invisible cylinders the invisible cylinders would be running up and down those are the muscle fibers which are not labeled in these Brainbow mice but these are the neuromuscular junctions where nerve cells connect to muscle fibers and the color tells you the origin which particular nerve cell gave rise to each of them there's no significance to the color except that when the color is the same those two neuromuscular junctions came from the same neuron in the spinal cord which could be a centimeter away but I don't have to trace it all the way back because the colors are the same and I know equally certainly that this is a different neuron and that's a different neuron and that's a different neuron because the color is different in each case using techniques like this we can get the whole connectome of a little piece of an animal like the muscle we can get every wire connected to a muscle so this is a very small part of a muscle but this is a slightly larger muscle it's a muscle that wiggles the ear of a mouse it's called the inter-school Alerus muscle it has only 15 different axons that come into the muscle and what we just looked at in the previous picture was an area about this big so these are the individual neuromuscular junctions the muscle fibers are running up and down like this and this is one animal where we've analyzed the branching of every single axon in this muscle that's just a joke up there but this is the wiring diagram of that muscle and the color is each representing a different nerve cell they're about 15 axons in here and this immediately allowed us to do something that we had never do before which was asked is this wiring diagram stereotyped animals use the muscle the same way with the left ear and the right ear there's no aridness and in mice which is what animal we're using here the left ear does the same thing as the right ear the nerve comes in in a mirror symmetric way into both muscles the muscles are bilaterally symmetric they're pulling the ear back towards the mid-line so the question is is this wiring diagram the same in the left side and the right side and if it's different is the left side of one animal look like the left side wiring diagram of another animal is there any stereo Tippi so I ask you are we going to find a stereotyped wiring diagram here anyone want to guess same obviously same genes on both sides and I should tell you if you did this kind of experiment in an insect you would almost certainly find a highly stereotyped branching pattern so how about in a mammal our wiring diagram is going to be stereotyped no anybody say yes you say yes yeah well you're wrong every instantiation was unique every wiring diagram we looked at every left was different from every left every left was different from every right every one was different despite the fact that genes are the same in the left and right side somehow the wiring here has been unfettered from the tyranny of the genes and I'd like to put it in that positive way that somehow genes tyrannize nervous systems they make nervous systems do the same thing from animal to animal except for things like mammals where a lot of the wiring diagram is kind of figured out on the fly it's figured out as the animal is developing and therefore there's no genetic regulation of exactly where individual branches go some evidence to support this is that this wiring diagram in muscle is extraordinarily inefficient it has lots of sub optimality in it Lieut useless loops premature branch I'll give you a quick example of this this is the a wiring diagram julu was a graduate student when he did this and and he's labeled one of the axons here different colors so you can see it clearly I'm just going to focus in on this box right here this is the nerve coming into the muscle and this blue are all the axons running this way there are two axons however that take this left branch one of them goes both ways this blue one here is a branch of an axon that goes both ways but this red axon in this particular muscle this this particular animals muscle decides only to go the left branch and you know I am NOT judgmental who am I to judge anyway this seems like okay if it wants to do that it can but look what it does it goes all the way up here and then it makes a hairpin turn now it's going backwards in the wrong direction it goes any further it's going to leave the muscle then it makes a hairpin turn and goes out again and especially notice this branch here which generates this synapse here there was an easy way to get there just there but it's not there so and here's another example this neuromuscular Junction here is due to this branch point here so it seems like it should branch here and just go that way but it doesn't it branches here and then it co fasciculus with itself all the way up here then it peels off crosses over itself to innervate that Junction and this is one example of things we saw in every animal every one was different every one had its own particular peculiarities but they all had peculiarities like this and it suggests there's something unfinished about our nervous system relative to the nervous system of animals that have been around much longer than mammals where things are maybe more perfect or less there's less sub optimality but of course the nervous system always does the same thing they're not going to learn new things and so an interesting question is why is this variability exists and the answer and I'm not going to spend any time on this at all just a quick moment is to tell you it's the main research in my lab but I don't have time to talk about it tonight is that this wiring diagram one sees in the adult is the product of a developmental period at the time animals are learning to walk and humans are learning to ride bicycles where the right wiring diagram and muscles and probably elsewhere in the nervous system is far different than the adult wiring diagram and different in the weirdest way possible it's not that there's less connectivity it's that in these young wiring diagrams everything is connected to everything every nerve cell has made branches almost everywhere so here is a sort of cartoon of this that the neurons in the spinal cord which end up each innervating a separate neuromuscular Junction with a single branch in babies every single neuromuscular Junction has got lots of innervation from every neuron and I'm only showing four neurons here but there could be 15 or even more neurons and hundreds of muscle fibers and you have this kind of all-to-all connectivity everybody is talking to everybody and then as development proceeds and Anna Mouse this is only a couple of weeks the vast majority of these branches permanently disappear and you end up with this simple-minded nervous system so you could think of it this way that when a child is young anything is possible and then through practice television parents teachers experience with gravity the vast majority of what the person could become is totally eliminated and you're left with a kind of simple system where each nerve cell has a particular task to do but how it turns out is different in every animal and every person so this is a very destructive view of education that says education is there to kind of eliminate alternative ways of thinking and that the more we know the more narrow-minded we are and you know most children would tell you adults seem to be much more like this and they are much more open and so maybe this is a good metaphor for what's going on elsewhere but most people are not interested in muscle but you're interested in brains and memory and including me and so could we use the same kind of techniques to study this in the cerebral cortex so here is a brain bow of the cerebral cortex the nerve cells of different colors but what matters is the connections between them which is all this felt work here if we zoom up to look at that felt work at a little higher resolution you see it's really hopeless there's just wait surprise there's way too many wires to trace the problem in a more specific way is that the kind of imaging we're doing here the thinnest focal section we can look at this which is called an optical section the thinnest optical section is so thick that many wires are running on top of each other in our finest focus so we can't we follow every wire in most parts of the brain I showed you those giant axons you could follow but where there are dendrites and fine axons it becomes much too difficult now we can make brain bow animals we're only a subset of brain cells are labeled this is for example a technique where only the inhibitory neurons in the brain are labeled now the density is much less these big black blobs are the pyramidal neurons that are receiving inhibitory synapses so you you can see you could trace out most of the inhibition in an animal like this but that's not what we want what if we want to see all the connections what do we have to do so what we realize is we have to kind of give up for the time being on this brain bow approach and go to a higher resolution technique which is electron microscopy and cut brains thinner than the optical section thickness and I want to show you our slicer for the brain it's a weird contraption it looks like a movie projector and you'll see it has some analogies to a movie projector this is a film tape and this is a piece of brain here and and what we're doing is collecting the brain section by section I'll just show you what's actually happening here piece of brain is put into a block of plastic it's hard and then the brain is sliding up and down like this on this big Chuck against a diamond knife and the diamond knife slices off a section that's about 30 nanometers thick that's about a thousandth the thickness of a hair so these are just about invisible and they float on water and then a conveyor belt is picking them up one by one so you take a three-dimensional block of brain and you turn it into a linear array of single sections then you take the array and of those tape and you cut the tape into pieces you paste the pieces onto a flat silicon wafer and you keep doing that until you have the whole brain piece in a library of wafers so here's what a wafer a library looks like of ten thousand three hundred sections of the thalamus this dataset is about a hundred terabytes a terabyte is a thousand gigabytes some of you may already be you in terabytes so this is a pretty big data set and I'll show you what these wafers look like Bobbie kes thorry is helped develop a way of imaging these using an electron microscope and I asked him to show one of these wafers to you by holding his hand really still so Bobby's holding his hands still here and we're going to zoom in on one of these wafers and each of these is a section of brain as we zoom in we're going to get to a piece of cerebral cortex he has to step into the electron microscope at about this moment these are blood vessels these big white things these little white circles are the nerve cells of the brain and these white streaks you're seeing our dendrites the black enclosed objects are myelinated axons and as we zoom up further and further and further finally we get to the point where we have a synaptic terminal and axon making a synapse onto a dendritic spine with a spine apparatus and so that's one section but this is thousands of sections and if I just give you a sense of this this plays yeah so here is a one section after another of several thousand nothing seems to be happening in this movie even though each is a picture of a next section and that's because these are 30 nanometers thick so only gradually are you going to see that blood vessel slowly disappear it takes about a thousand sections to get through a single nerve cell each of these white things as a single nerve cell at this level you can't really see the wiring diagram but you can appreciate that the same data is appearing in section after section we have to zoom up higher and this is what it looks like if you zoom up higher you can see these myelinated axons moving again they're not really moving this is a nerve cell here and there's another couple of nerve cells that will appear such as this one right in the middle these things moving around are the wires that are running through the volume and because they're moving at different angles through the volume they appear to be moving in directions this is a big dendrite moving off of that cell there these little gray objects inside these cells are that are sort of oval and shape are called mite Kandra at this level you see all these wires moving you also see that this looks like it was made in 1903 and and that's because the tape is not very good yet you know it's not this is a blood vessel by the way you know we have a little further to go to make the quality better but you really have to zoom up higher because at that level although you get a box of brain you can't really see all the synapses these are nerve cells here we have to go higher resolution and if we look at that data at higher resolution and that's what's shown here you start to see that in between the large objects moving are lots of little objects moving those are axons and little dendritic spines and there are synapses all over the place those little things with the little gray circles in them are synapses and they're everywhere in this data set the kind of data we're taking now is approximately a terabyte a day our images are about a hundred thousand K a hundred thousand by a hundred thousand each image and we take about a hundred images a day so it we're moving but it's still a slow process but what do you do with this data you what you can notice is that with your eye you can easily follow an object from one section to the other in fact you could probably get a five-year-old with a good set of crayons and a very large coloring book of these to color the same object in the same color from section to section and if they did that they would be segmenting this out as a wiring diagram and here's basically what you'd like to do and Daniel Berger who's been working on this project has developed a kind of digital coloring book which is basically you go in and you say oh that's an interesting object I'll color it in red on each section I keep doing that and if you keep doing that you can then generate that object in three dimensions as you'll see so there is a dendrite with dendritic spines sticking out of it and here's an axon that happens to innervate two of those spines running across so that is a hand segmentation that as a human being is doing the coloring but they're coloring it in with a computer and and now you have you know that that's the axon that innervates that dendritic spine but you don't just want to do two things you know you basically want to do the entire data set and and so let me just show you that here so here is a entire data set colored in segmented by this program of hand segmentation and and so this is ultimately what would give us wiring diagram information once you have this data you can then render it in three dimensions this is exactly the same data but now just rendered in three dimensions those are the dendrites with all their spines and then we're going to fill in all the axons there you have it totally useless I mean it's useless for many reasons I'm sad to say one is that the material is orphaned in all directions you don't know where anything came from the second is more depressing and that is this piece that took a long time to reconstruct is there in this section and that section sits there in this image in this image sits there in that image and that little green dot I don't know if you can see it it's a smallest dot I can make is bigger than what was reconstructed now you say well what about a cubic millimeter which would be a voxel of an fMRI image how big is that it's that big so there's a problem and and when we started we were taking these images at the pace of about a half a million pixels per second and at that rate to just to take the pictures of the entire cubic millimeter is 2.2 for centuries and 2,000 terabytes I could find no graduate students interested in this project although interestingly a lot of postdocs were interested and I think this just tells you what the job market is like this would be stable employment so that is a problem so you know we have to go faster and now we're not going point five million pixels per second but we're going 20 million pixels per second terabyte a day we can do a cubic millimeter in a PhD thesis time of one PhD thesis unit and soon we're going to have we already have the machine but it's not quite automated yet we'll be able to go 40 million pixels per second with a single beam scanning electron microscope that goes very fast and then we could do a cubic millimeter in 2.8 years that's still pretty slow for one one voxel of an fMRI image we want to go faster still and in a few years probably about a year from the spring we will have a new machine in the lab that goes over a billion pixels per second allowing us to do a cubic millimeter of the mammalian brain in three weeks this machine is worth looking at it's it's like an electron microscope with a single scanning beam except it has 61 beams in it and Zeiss is making this for us it's as if you have one machine that is like 61 microscopes would go 61 times faster and should allow us to do billion pixels per second or faster this looks impressive it's more impressive when you see it next to a normal-sized human being it really is a humongous machine it's gigantic not only in size but in price and this is what it looks like without its clothes on it's a really impressive piece of technology so we are going to be able to get the data pretty quickly but I'm sure some of you are wondering what about the coloring in part the segmentation problem how are you going to get a lot of children to color this in and and this was our problem that we could color it in by hand but it's slow I talked to some engineers here hans-peter Fister as an engineer in the School of Engineering and he said that's just engineering you know really weak we can make make it work and after five years they developed an algorithm that was quite good you know this is colored in entirely now by Machine and it's coloring in the right things and then if you look at this movie it's done here about 8,000 of what a single-segment er could do 8,000 times faster so this took about a day to do it would take a thousand people to the same data so I just want to end by giving you a sense of what one is what we're trying to do with this by just showing you a few little movies so this is a column of nerve cells in the cortex and this is still not all the cells there but we decided to get every single element in one part of one cell and this may look like a miniscule a small area but it's the largest area this is about 700 cubic microns where we have now identified every synapse every axon every synaptic vesicle every dendrite in this little region around the dendritic spines of one dendrite we wanted to see how many other things are in the vicinity of one dendrite and this will show you what's in that little cylinder and it's a quite depressing because there's so much there there's 700 axons there's about fifty five different dendrites that interact in that little region and there's glial cells and every one of these things extend out in all directions this extraordinarily large amount of stuff that we write amaizing and in there are really nuggets of interesting data you know if you just look at the main dendrite you find some of the axons make multiple synapses on multiple spines that's what these blue arrows show for one for for this one dendrite and then because I am surrounded by students undergrads and and high school students who are interested in getting involved in neuroscience and are you know eager for letters of recommendation they're willing to do things that I'm not willing to do and one of those things is to actually look at the synaptic vesicles in every one of these synapses to see is there something common about the synaptic vesicles in one axon versus another and so this is a huge amount of work and I'll show you this is not an artist rendering each of these little yellow dots is a synaptic vesicle in a difference in apps and you know there's a lot of work this is get letter recommendation letter recommendation letter recognition so but it is impressive you see a lot I just show you this one final view of the same data set you know someday my view is that this is the level one is going to have to probably look at the nervous system to see how information is instantiated and stored physically I hope some day diseases like schizophrenia will look like something at this level of resolution of course you know when you look at this you can only feel a certain amount of humility that this is a lot more complicated and certainly a lot more beautiful than most of the thoughts that come out of our brains so it's like the machine is a lot more impressive than what we use it for and I don't know what the lesson is but I think there's some truth to that I just want to end by saying that although it's a made the sound like I did this work this work is industrial and it requires a lot of people working not only a lot of students but a lot of collaborators from other labs other universities and a lot of support from from many different sources so thank you very much for your attention you last night you were showing vesicles on the dendrites right vesicles on axons that are innovating that dendrite that are right synapse on the damaged suit so does it does a geometry of the vesicles matter in terms of function I mean what exactly is the I mean why exactly should we be interested in studying the vesicles I think the nobody knows but but the thought is that some synapses have lots of vesicles other synapses have rather few and it's possible that this is a measure of how potent those synapses are okay that's one thing we're hoping to see thank you so given the projection of the speed increases that are going forward and the endless supply of cheap labor when do you see sort of the intersection of all this getting to the whole brain of a mammalian subject so I think a mouse brain or even a smaller mammals brain like a European tree shrew is something that we're going to be thinking about in the next four or five years a human brain is a thousand times bigger than a mouse brain and that these techniques can't do a whole human brain at that resolution yet oh of course it could it would just require a lot of money but you need to genetically modify the human to do that right you'd have to kill the human right so you'd need a volunteer and not only do you have to kill them you'd have to kill them and start infusing them with glutaraldehyde and formaldehyde the moment of death you know so you wouldn't want to kill somebody what you would want is is a human who decided to dedicate their body to science and are willing at the moment a doctor declares them dead to infuse them with something that would certainly kill them if they were still alive and there's a lot of problems with doing that in a hospital for example of B if I was in the bed next door literally research so I'd say what is always European research right so but but you know there is a there are brain banks of diseased human brains that are fixed in formaldehyde that usually there's several hours between the moment of death in the time the brain was taken out we're going to start looking at those pretty soon and then I have colleagues who are working in neurosurgery who are neuro pathologists who often get pieces of brain that they can dunk not whole brains but little pieces of human brain that can be dunked into formaldehyde very quickly so we'll get a sense of what human brains look like long before we try to do something as amazingly difficult to imagine now you know it would be about two million petabytes of data a human brain and that that's much larger I think than the digital content of the world right now so we're not ready at least in my lab or anything that big I mean I think when you get your full wiring diagram if you ever do it's going to be like Bohr has is Universal library where all the facts in the world are represented but you can't find anything of interest or meaning because there's so much of it I mean as a neurophysiologist I I'm always a little back when people talk about the brain and don't even mention spike trains or information in the spike trains there's an informational order that's somewhat not not completely but somewhat independent of the structure and if you look in the early auditory system and in the mntb where where you showed a slide the action and all the coding of the information is in the spike train and the structure of the spike trains and we know you know we know the the wiring diagram to a first approximation so the question is and the thing I'm always frustrated with is you know if we could read the anatomy in a way that could tell us how the system works what what could we learn so what what how we're going to figure out how the system works from a wiring diagram right so this is of course a very obvious and important question I don't want to make make light of it or say this is trivial I didn't talk about the neuromuscular Junction enough to show you an example where the wiring diagram in development which is very different from the adult actually is highly ordered and it's ordered in a linear order connectional matrix that is the physical instantiation of the size principle that is the firing order turns out to be played out in the wiring connectivity once we made that decoding any muscle I go to in principle I can understand the firing pattern just by looking at the wiring diagram now now you say well that's a special case and I say no all the things you learn simple must be put in to a form that you can read it out again based on connections there has to be a connection alundra pinning so that's what I'm searching for which are these sort of motifs where the subtle differences from one to another are not as important as the principle of the way information is organized if you could decode like that you would be able to read out information now the challenge is of course information coming into the auditory system is coming in from the outside it's not in the nervous system but if you have a memory of a voice or a memory of a melody that is in the nervous system and it has to be in the connectivity it's not in the firing trains if you haven't been thinking of a song for a year and then you play and then you sing the song it's not because you've been playing that firing train over that time it's that somehow the connectivity between the cells allows that firing train to well I actually teach psychology of music and the neuro psychology music and and there are notions of temporal memory traces which are also mediated by structure but that could be a way that you could dredge up a melody after several decades the thing is is that we have to think about both the informational order and the spike trains and the structure of the thing in a complimentary complimentary ways that mutually affect each other so the loop I mentioned is what I literally mean that but I'm not saying structures more important than function function generates structure and structure generates function it's a loop you can't ignore structure and you can't ignore function one has to be able to decode one relative to them but the spike trains are it's like it's like what if we were going to study the molecular genetics and we didn't know about the genetic code and we were going to go in and look at the molecular structure of chromosomes and then further and further in without knowing what the nature of the code was there's an informational order there that's complementary to the structure it function is another aspect of that but but we have to always be thinking about about the nature of the informational order visa vie the structure so I agree with that yeah I agree thank you yeah yes I have a more general question but it was inspired by your very nice introduction to this subject I mean how does the brain evolve how does it evolve yeah since I have the impression that genes can create everything since the beginning so and of course what you learn in your life is not it cannot be given a to to your sons so I added the impression that apart from increasing the size of the of the brain there is no other way to to evolve well I think humans show that there's a very weird way to evolve which is to jettison most of the fundamental information that other animals are imbued with at birth and require that to come in through experience humans are interesting in that we come into the world knowing less about the world than other animals and we take far longer to reach mature state well you know what is it it's a year till a baby walks 15 more years to the driver's license three more years before they leave the nest you know they're 18 when they leave the nest what other animal leaves the nest at the age of 18 so so the the magic of being a human being it's not that we've evolved all this fancy stuff said we come in with this huge brain and we can take advantage of experience to mold the circuitry such that we have skills that are related to the world we find ourselves in rather than to our genetic heritage whereas most other animals are kind of stuck we we don't transmit these to to other generation so I think of Darwinian evolved evolution so well of course we I mean you your kids speaker in my life I don't I don't get to my to my son so don't what your son I don't give to my son so it's new don't give to your sons what a layer kind of parent are you of course you give to your sons so I don't make the jeans of my my so my son's bet there's this is the magic of the human nervous system you give to your son's experience that gives them a structural brain that evolves much faster than genetic evolution that's why humans today are doing different things than your parents were doing or your grandparents were doing there's no other animal like us it's because we are so slow and growing up we have all this information that makes our structure as opposed to our genes it's that loop between structure and functions is and gromit ization in my view that makes us so special

Channel: Harvard University

Views: 35,220

Rating: 4.8961039 out of 5

Keywords: harvard, brain, imaging, organ systems, science research lecture, physics, research, molecular biology, cell biology, cellular biology, brain function, nerves, memory

Id: 82tQ4ID-xNg

Length: 75min 33sec (4533 seconds)

Published: Wed Jul 17 2013