Engineering the Brain: Deploying a New Neural Toolkit

So. I'm guy makan as I said I'm a neurosurgeon. At Columbia I one, of the things I get to do is I specialize, in awake brain surgery so I get to operate on patients while, we're looking, at their brain while they're awake while they're functioning, and the, more you do that the more you realize how little we understand, and actually know about the brain so, without further ado we're really privileged, today to have a tremendous, group of participants. First. We've got our, first guest is professor of biomedical engineering, and radiology, at Columbia University, a member. Of the Zuckerman, mind brain behavior Institute, and Kathleen, stitute for brain science, please, welcome Elizabeth, Hillman. Our. Next participant, is an assistant, professor of psychiatry, neuroscience. And physiology, at the NYU Langone, Medical Center. Who, investigates, the neural circuitry, of mating and aggression in mice, please, welcome dye you Lynne. Also. Joining us is a neuroscientist. And psychiatrist. At Weill Cornell Medical, College as a psychiatrist, specializing in. The treatment of complex, mood disorders, please, say hello to Connor listed. On. Our file participant. Is a neuroscientist. Director. Of Neuroscience at Cold Spring Harbor Laboratory, who, is interested in how brain circuits, give rise to behavior. Please welcome Tonys, aider. Maybe. First we could talk about a little bit the history of where did optogenetics, come about from memory you guys can talk about how you're using it a little bit. So. Interestingly actually. The history of optogenetics, can be traced back to an, idea that Francis, Crick who's. Famous for the double helical structure of DNA. First. Came, up with he proposed, that it would be really convenient if we, could activate, neurons with, light he, proposed that something like 30 years, ago, and, it. Was people, have tried different approaches. And, were. Developing, different strategies, for trying. To make it work. And it, was really the. Fortuitous. Recognition. That, a protein. From. Algae. Could, be expressed, in neurons and, endow. Them with the ability to respond. Immediately to to. To. Light and that. Happened, I guess about a little over 10 years ago and it. Transformed. How we do neuroscience, when I started in neuroscience. Everything. In terms of trying to understand behavior was correlational. We, saw neurons fire and we. Saw the behavior and we. Put, them together and we, we, we of course, all recognized, that correlation is not cause a lady but, with without, the ability to sort. Of dis excerpt. That were responsible, for the behavior all we could do is keep trying to find those associations. And. So that happened about I guess 2005. And within. A couple years, lots. Of other lots of labs it happened with it was a paper from Karl Deisseroth and ed Boyden and within. A couple years. Dozens. And soon hundreds of labs who are using it so that that's really the the basic, history right, so, Connor you spent, time in the Ross lab before moving. To Cornell so tell. Us about how, you've gotten without, the genetics to what you're doing with it and some of the potential applications. As you see it within your world yeah, so. As. You guys heard I'm a psychiatrist clinically, and, one. Of the things that really excites me about optogenetics. Is this potential. Opportunity, to understand, the neurobiological. Basis. For men, health and mental illness and hopefully, develop new. Treatments and, I think a big limitation in psychiatry, is that the, drugs we use I always like to emphasize that the drugs we use they do work and, they've been a great benefit for a lot of people but they're blunt tools they, bathe the brain and. They. They. Change. Some aspects of brain function, in a way that that helps but, they probably have lots of other unintended. Side effects and optogenetics. Affords, us this really unique opportunity, to really precisely, manipulate. Specific brain, circuits, figure. Out what's going wrong and and, try to fix it and that's that's one thing that really excites me so, give, us an example of how you've done that yeah specific, circuit that you've targeted and what you've been able to find from that yes so during. My time at Stanford this, is like a collaborative. Work with several, other investigators, there we were really interested, in understanding how, the brain, supports.

Reward. Seeking behavior that's a thing that's obviously, altered, in the brains of of, many, depressed patients, and we. Were able to precisely. Manipulate. The. Activity. Patterns of specific, cells in a region of the brain called the prefrontal cortex and, begin to understand, how how. It how it regulates, the processing, of of. Reward. Related cues and, motivates. And, animals and presumably, something. Similar is happening in people's brains. Motivates. Their, their their desire to work to obtain rewards. And. Interestingly. What, we found. Looks. A lot like what what goes wrong in the brains of depressed people there's, this abnormal, pattern of of. Increased. Connectivity, in this brain circuit, and that seems to be driving, some of the the. Reward. Processing deficits, that these that these rats have and possibly, also people. Using. So, what, are you using it for and what types of questions are you able to ask without their genetics yeah, so I, was, lucky enough actually, to be one not the first person who benefits from the optogenetics, I remember, it. Was a still in. The days when I was a postdoc and I, have to say optogenetics although, it's, a new technique, but the concept, of wise is. Is. Not new. In the sense that, neuroscientists. That have tried very hard for, centuries are trying to manipulate, to, the brains in, order to see will happen so, but. The conventional, manipulation. Is bypassing some currents, into the brain so the electrical, stimulation and, that's, where I started. And when I trying to study the brain before, the optogenetic, era electrical. Stimulation there is a1. Deficits. Of that which is that neurons. They're not just a cell, which are ball but they actually have a lot of processes coming, out so. When we electrically. Stimulate, it we're not only stimulated. The cell body. This, ball but, also all the processes, coming from it so. Potentially, the cells which is a far away can. Also be activated because. Of this electrical stimulation and. Optogenetics. Is. Advantageous. Because it, allows you to really target the, cells are interesting, without. Affecting. Those, cells are just the sending processes, to it that's the specificity. That makes, it is to really, unique and now. We're putting up the genetics, into. Those cells and a, stimulate, so, why don't we look at if we have the aggression video so this is a mouse there. Was this part of the brain it's a very deep very, ventral, and we. Turn down this. Area and, you'll see that he start to attack this cloth. And, he, really you know that's. Not what. Mouse typically, do so they don't, usually attack a glove so but in. This particular case when the lighter activated. You, repeatedly, sink. His teeth into this. Glove in fact when we take it out this glove is in fact a deflated, so. And. It's, not. Only gloves in fact they will attack other, con specifics, including. A, female, Mouse that, a male will typically, would not attack, at all.

So. This. Animated. Object, probably shows the extreme of this behaviors. That this, control. Of this areas, just, turn on this attacking. Instinct immediately. There's some specificity, to the aggression, it does, it does in fact a one of the big questions we are trying to ask in the lab is when we do activate, this area is this just. The abiding events, oh it's, actually increasing. This aggressive, motivation. Of the. Animals and that's. Why we're designing, different Aviva tasks in order to dissociate at this part but, that's exactly trying to ask is it to just make them bite oh actually they, are become has, this urge to, a class a cat. All. Of you guys are talking about technique. Where you're, able to select out a very, small, specific, part of the brain to try to isolate and look for behaviors, Elizabeth. You've been focusing. On the one hand on using imaging, techniques, to look at much broader patterns, of activity and and, larger, connectivity, patterns between the brain and even whole, brain activity, and various types of animals. Can you fill, us in on some of the things you've been doing along those lines, well so we we. Did a lot of technique development in the lab and I was trained as a physicist so I did a lot of optics, and and so. You know these technologies. When they come along they, don't just come along wonderful, people conceive. Of them and piece them together but then using them and figuring out how to do that is is really challenging as well and that's a really important factor here so the little mouse had, a thing on its head and that was actually holding an optical fiber that, was allowing you to put laser light into the actual brain to turn these cells on and off and so. In. An hour we're really interested, in you know how can you how can you do. That better I mean it's not just that you can turn, cells on but you can actually turn cells off as well and the dream is to have many many different colors, so that you can be, very selectively, turning, one thing on and turning one thing off and.

That Really lets you you, know figure, out what part each one of those things is playing I was thinking of the analogy of sort of what is my role in getting my kids out of the house in the morning right, well how do you tell that do you just throw me in there and make me flash no but if you take me away and see what happens when I'm not there you, know it's quite quite, helpful way of figuring out what it is exactly but. So. Figuring. All of this out I mean for me you know we do our own we do our own experiments, as well and I will talk about that more but but figuring, out you know working, working, with you guys you know what what exactly experiment. Do you want to do what behavior, do you want to do now which areas of the brain do we have to get to and how do we have to make that all work together so that we don't have to have ten, lasers, and all, of this stuff happening at the same time is is, one of the things that really gets. Me going and then and then, and then we combine that with imaging, because you know what, you've seen mostly there is is the, readout you know you change something in the brain and you look at the way that the person's actions, change or the animal's actions, change but. We can also simultaneously. Be looking at what effect that has then on the firing of the other neurons and so, we, do a lot of work trying, to capture activity, at, the level of a few cells at the level of the whole brain we, look at that activity, in in, flies, and and. Worms and and little. Fish and then we, also do, it up at the scale of mice and then sort of project, that up to the scale of the human brain also, so. It's. Very different from, exciting, a few neurons with one fibre you're, looking at what the brain is doing spontaneously. In its own. So. What you're seeing here is actually that the, entire top surface, of a mouse's brain and that reveals a whole ton of different, areas of the brain that we can look at all at the same time.

We're Using something called gcamp which is a calcium sensitive, fluorescent, protein so what we were just talking about was, optogenetics. Where you express, based. On the. Genetics, of the cell you make the cell produce, this light-sensitive, protein, and, one of the other major, tools that has really revolutionized neuroscience. In the last five to ten years has, been these. Fluorescent proteins, like the glowing jellyfish, that you've probably seen, or the newspapers with the glowing mice right. So. These are calcium sensitive. Fluorophores which means that actually when the neurons fire they, look that, they actually flash, and we can read that out okay so it's sort of the opposite so we've, been observing this in the mice and we've, found these amazing patterns of spontaneous. Activity that tick around in the brain and what, I thought be fun to show you today is that we do a lot of quantitative analysis on this trying to understand the cadence of these patterns and the locations, of these patterns and what do they mean and one of the things that we just were able to do if you go to the next slide so, we, we. Found that. Again. It's hard to see with these patents so on the top left is is just a still of these kind of weird patterns of activity that we really see coursing through the whole brain and we found that they were sort, of coming on and off in different regions of the brain and so I'm gonna play a movie here where what we've done is rather, than just showing you the movie of these patterns that seem to kind of roll around in the brain because, there's different regions that are lighting up one after the other we've, actually encoded. Them in color and also as notes on a piano so what you're going to hear is kind of what it sounds like in the brain of a mouse as a mouse is just sitting there resting and this is over pretty much the entire surface of the brain so all the regions responsible, for seeing. And hearing and motor. Actions, this was all done by my, student Nick here who is a, biomedical. Engineer slash composer so if you want to just click, the, I'm. Not kidding there you go. Every. Time it region lights up you. Hear a note. Give. It a say. So. We use this method just as a way to try to just really, capture. Is. The relationship, between the brain activity and the music fully automated, or is there yes this is actually using the nmf non, non-negative. Matrix factorization algorithm. On this data and then taking the factors and then putting them into musical notes and then if you go to the next slide so then. Tony. Tony was saying before the. At rest at. Least based on the music pattern and mice are quite calm well. After, I started, doing this analysis, I I remember I had, a big grant on this that I submitted right before Thanksgiving and I was sitting there and Thanksgiving, and, I was I just kept, feeling this rhythm, of my brain you know and thinking you. Know if I could just sort of calm down watch some television if I just watch you know ten Things I Hate About You one more time maybe, I get. Myself into this state you know what I mean and and so this drew us on to the to the next part which is we then gave the animal caffeine okay. Go. To the next slide and play the movie, on the left so it's. It's. Not so, different it's, a little faster, has some gaps. Okay. And then so we gave it an ketamine. So, ketamine, is a is a drug some people use it recreationally and, they shouldn't and it's, an anesthetic, which. Really makes you basically, unconscious makes you high has, various, effects. Of. Making you forget and so on so that's the one on the right here and you'll see it.

Has A really, profound, effect. What's. What's really interesting about this is it you. Know it's this is a very odd modality. That we came up whether we actually just take the state to using LEDs and cameras it's it's, it's, very low-key, compared, to the really high-tech stuff that we also do in lab but the. Reason why I'm really excited about this is I think neuroscience. For a long time has. Zoomed really, far in on just just the cells you know looking at single cells and how does interact, with each other and when we discovered, this activity, that's really, everywhere. It. Really changes, the way that I'm now trying to think about you know the, brain is just sort of talking to it's like the internet right it's it's not just you and you sitting there it's you connected, to all your Facebook friends and all of those things kind of interacting, together and so we're, just um we're, having fun with this of course but we're. Really using this now to try to understand, how that's. Sort of the whole brain and contributes, to behavior, and particularly, here we're thinking about state so, a state, of being anxious, a state of being calm and and really, what does that look like and then how. Was each one of these react differently if you presented, it with an. Aggressive glove, you. Know you're. Showing these amazing, patterns. Of how, the brain connects, and what connects to what you know Tony you've taken a totally, different. Approach to try to study, major. Areas. And how the what, actually, connects, to what and how we unravel, that maybe can you can you explain, that for us yeah so sort, of to put in perspective, when, there's when. The optogenetics. Revolution. Hit, my. Lab jumped, in whole-hog we were, already. Training, mice. Or at that time rats to. Perform, what we thought were cognitive. Tasks, and we could talk more about that but, we were training them to listen to sounds and make decisions based, on the sounds they heard to, get rewards, and we were trying to understand, the, circuits, that were involved, in making, those decisions, and we, had identified certain.

Subsets, Of neural using optogenetics later, we'd. Gone beyond simply, recording, the activity of these neurons and, actually shown that one, set of neurons turns. Out that projector the auditory, straight and were actually really, important in carrying, information about a sound toward. Driving, movement, but, what. I realized, from that was that you know we can make guesses about the circuits, involved, and using. Optogenetics, we. Can actually, test. Whether our guesses are right for, the first time like we could test at the circuit level well, which subset, of neurons within, a particular area are driving, this behavior, versus that behavior, and what roles they play but, the prowl was that. We. We, just had to make educated guesses and. One. Of my students was really fantastic, and made a really educated, guess and and. Guessed right and and showed. This this, particular pathway but other students, made, less. Successful. Guesses, and the. Cost of guessing wrong is, a, couple, years of work you, you, do a set of experiments, and if. You guessed wrong the answer is nope, I have, Todd that wasn't the right guess and you learn very little and career. There. Used to tell people I, still tell them who entered my lab I quote from Shrek always. There's. A there's, a for. Those of you might my son, at that when he was younger watched Shrek over and over again and there's a scene, where Lord Farquhar. Sends. His Knights. Out to find the princess and he, says this, mission is dangerous, many. Of you may die but. That's a risk I'm prepared to, take. Come. Up empty-handed so anyway. How. Did you make it better so the, so the idea was that we needed a way to, to. Screen, through, the guesses, we, needed to know what the circuit was in, order, to know what was a reasonable, guess it knowing the circuit, would not tell us how it. Actually works but it would rule out all sorts, of possibilities and, the, problem, was that the, tools that were available were.

Either Not, high enough resolution didn't, have single neuron resolution. Or they, were incredibly. Slow so that what, we needed to know was. Whether, there are neurons let's say in mike is in the auditory cortex that, send their axons to this region and that region and, whether, there are other neurons that send their neurons here and there and the. Problem was there was no way of knowing in sort, of a high-throughput. Way what. The. Millions. And billions of neurons well, millions, and emmaus billions, in a human where they send their axons and so, the traditional methods for asking. Those questions were, all based on microscopy. The typical, high. Resolution method is to take one neuron in one, animal, fill, it with a with, a fluorescent tracer, or some other kind of tracer and then. Track. That trace all throughout the brain the, problem is you. Know one neuron, per Mouse lots, of neurons that's very slow. If, you try to do more than one neuron the problem is that the that, the, processes. Start overlapping, and you, can't resolve where the individual. Processes. From these neurons go and so, the idea that I had. Eight. Years. Ago now but. It's finally working was. To replace, the usual, way of, visualizing. The. Neurons which, is just to look at a fluorescent, dye with, what. Has turned out to be a fantastic, marker. Which, is, DNA. Or in fact RNA, so, what we do is we we. Cause. Each neuron to, express a unique, random, sequence, of. RNA. Which, then gets transported, all throughout, the cell so how, do you do that why does a neuron walk so real neural RNA, yeah and in real life most, neurons do not express. Random, in, general, you don't have a lot of random labels, floating, around your body in fact the only case in our body that we know of where we have random, labels is your immune system, where the genetic. Material gets scrambled each time to make antibodies so, we thought about actually trying and we're still kind of working on trying to trick neurons into scrambling their DNA but an easier, way to do that is we, can make viruses. That, are that. Each express a unique random. 30. Nucleotide. 30 letter string, of. DNA. And then, we just squirt. That into the brain and each neuron takes up one viral particle, sometimes. They take up two and we could talk about technically, whether it's it's not a really a problem and. Then those, that, it, gets amplified within, the neuron and gets transported, out to the axon, so now we. No longer have, to carefully. Trace each little, process we. Can just use. DNA. Sequencing, technology. Where, has transformed. Other. Fields of biology we can just, just, piggyback, off of these, tremendous. Advances, and DNA sequencing, technology, which have driven the price of sequencing our genome down to below a thousand, bucks we, can we can use literally. That same technology, to figure out where all these neurons project so every, neuron has its owns its own individual, every neuron has its own individual. Label, and it's, actually. I should have shown this picture it's. Inspired, actually by an idea that. Scientists. At Harvard Josh, Saenz and Jeff Lichtman came up with about 10 years ago called, brain bow where, they cause each neuron to express, not one color but a rainbow, of colors and so.

Basically, The idea is to replace a rainbow of colors it's. Hard to read out more, than a couple of colors so there wasn't such a big win but it makes beautiful pictures, to. Replace those with these, sequences, and so now what we do is we inject in to, one side in the brain or in fact we can now tile the entire brain with. This virus and figure. Out where all the, neurons in the, cortex, projective. So in fact I was looking at your pictures and one, of the we're just now starting to analyze this whole brain connectivity, map and it, turns out that, there. Are sort of communities. Of neurons that talk preferentially. To each other, and. In fact the, the communities. That we find based. On these connectivity. Actually are very reminiscent, of the, sort. Of different cords especially in the ketamine brain where, it looks like there's they're sort of within, a community there's, a lot of conversation, then it passes the message to the next community so it's possible that you may be seeing with nerve, axon, or labeling, some of the same I think I think actually the substrate, for what you're seeing is precisely. We. Should hang out yeah so. How, do you so how do you take that to the next a, different. Level and say now, we know how things all communicate. How do you start studying what's normal and what's Admiral right so so, the the the, the idea here is that we. Can now for, a, couple, thousand, bucks figure out the whole connectivity. Of a brain. There. Are some issues about resolution. It. Single, neuron resolution. But, the spatial resolution is, limited. We. Have some ideas and actually we're working on methods that give you higher resolution but, the real interesting idea, is that. We. We can now compare, the wiring diagram, of a. Normal, Mouse to. A mouse that has a genetic. Deficit. That has been associated with a human disease and there are now dozens, or hundreds of these mice, these so called animal models of autism. And schizophrenia and. Depression, so, we know that that. There are genes that cause that, are associated with human conditions, we, know that. When. You put those when you disrupt those genes in mice they disrupt, behavior in ways that are sometimes similar sometimes not. But. We in many cases we think that, what's going on is that disruption. Of those. Genes causes, some kind of change in the neural circuit but once again the, traditional, approach to figuring. Out what that change is is to take an educated guess burn. Up a couple of grad students and if you guessed right. Then, well, but that it that is how these things go it's it's incredibly frustrating and so the idea is now we can we can actually take one of these mice, and, say. Look here is the disruption, we're not sure which of these disruptions, are, causal. In the behavior but this totally, sort, of constrains, the set of hypotheses, that now. Physiologist. Like me and the, other people on this stage have, to consider so you're taking a lot of the guesswork, for the grad students, out of picking a project that's right that's right that's really my goal is to sacrifice. Fewer, grad, students on the altar, of bad. Guesses which, is very, we. Would all agree Conor, Conor you've taken, a different approach to, try to look at populations. Of neurons by putting little prisms, in the brain and combining it with optogenetics King can you talk about that and what it allows you to do that's different from, traditional. Opto. Genetics yeah, so. This. Work is really similar to what.

Elizabeth Was just describing, but it's kind of on a more microscopic scale, so, we're using the same kind of calcium, sensors that. That, fluoresce in proportion. To their activity, like, you saw most beautiful videos. That Elizabeth showed us a few minutes ago but, we. Are looking, with. Single cell precision, on a much smaller area. Of the brain one. Of the functions that we're really interested, in is. Working. Memory this. This, basic. Kind of fundamental, form of short-term memory that, we all use all the, time like. If we decided we wanted to take a break now and order some pizza working, memory is like what would enable us to kind of look up our favorite pizza place on your phone and. Store. The memory of the, phone number are long enough to dial it but it goes away rapidly. And. Teamwork. And. And. It's disrupted, in depression and in schizophrenia and, in many other, psychiatric, conditions, in different and interesting ways so we think it's kind of a fundamental process we. Could show that video. Yeah that video, so. So, what you're seeing here are cells, in the prefrontal cortex those, black those. Blacks kind of bands. Are blood vessels but. These are individual. Neurons, brain cells that are expressing this, this. Fluorescent. Calcium, sensor and that. Starry night effect is, is basically a a readout, of how active each one of these cells is over time and what you what you don't see is. That this, mouse is awake and it's behaving it's performing, a working. Memory task, while. We're getting this this readout and so what we hope to be able to do is test hypotheses, about how. Particular. Cell types in. This, image that you're seeing here how, they interact, to, encode. And maintain, a trace. Of the working memory during a delay period during, the time it would take us to dial. The phone number in. That analogy and. How these different cell types interact to kind of imbue working memory with with interesting, properties, and then once we understand, that. Like. Like we were just discussing a minute ago we can we, can formulate, hypotheses. Guesses. And actually, test them using optogenetics to, manipulate, the activity, of specific, cell types and test, whether our, predictions. Are actually, true or not so, everybody. Here, is using different animal models to study these, things to try to come up with information that can help us fundamentally. Understand, human behavior so, maybe, as, a group whoever, wants to can talk a little bit about about, how do we best do that how, do we best do that in a way that we are you. Know minimizing. Use of animals, being, compassionate in that you know but yet understanding, what we need to understand, so. What are your guys thoughts on that. We. Recently started using fruit flies and I, don't. Feel bad about that at all. What. Can you learn. The. Beauty. Of the fruit fly model is that you. Can breed them really really quick and so these genetic, techniques now that are really the core, of, neuroscience. That let us label these cells different colors and change, them introduce genetic diseases. Make. Them up express, up to genetic. Channelrhodopsins. You. Can do that in the space of a week you can just cross two flies and and then you have another fly and it's got rainbows in its brain and it doesn't have this stuff for, me what's really nice because I when, I build microscopes, what you show what you saw there was a about. A 10 millimeter field, of view. Which. Is what we needed but we couldn't see single cells but if you if you have a fly's brain we, can fit that whole thing within our microscopes, field of view and so we can see every single cell in the entire brain and so, we do these completely, crazy things where we get the fly and we actually have it walking on a ball and we're, imaging its whole brain while it's on a ball and then you can actually puff odors and and and, odors, of Lady flies and then you can see what it does and you can see where it crawls and then you're seeing all of this activity in the brain you know as it's doing that and so our. Flies, the same as humans probably not I mean they can fly which we can't so, I don't. Know but, what. We're trying to, do on so many different levels is understand, building, blocks understand, basic, principles, understand. You. Know how, does behavior. Emerge from, all of these little cells. Flashing, on and off and so doing. It in that system is a is a very efficient, very good, nice way of understanding, something. At, that level and then scaling, it up so there's there's people in neuroscience working at every single level what, we really need to do is all talk to each other and. And sort of piece together all of those clues and, we also do the maggots as well I mean it's it's gross that. Diet. You you you you. Work on aggression but you also work on maternal. Instincts, so another thing that's across, the animal kingdom but, that we all think of it as an incredibly human, thing but obviously it's, it's it's it's much.

Across The animal kingdom so maybe you could talk, to us about how you study. That sort of thing with something like that yeah. They are my. Views a lot of social behaviors instinctive, behaviors, that they're all controlled, by those Asian structures that the, mechanisms, very conserved. And. The. The, maternal, and the paternal. Behaviors in fact a parental behaviors, in general, in fact is also highly sexual dimorphism and, one, of the regions we study is. Controlling. The maternal behaviors so like, to show you a video here. Just, to. Say that we're not only looking at the behaviors, which is a fighting but also this like just, a heartwarming video, so when you look at it so this, mouse, this, is a virgin female, that they, she, doesn't really care about it a pups so much and. She. Doesn't have much experience with, the pups so, this is a called a sham sham, stimulation, basically no stimulation with just the Indus, areas, then, we put in a puppy in the corner and she basically the, nor the pups that the pups is or whipping around and probably making any bit sana trying. To get her attention and, so, so, this partner will be 60, seconds, which I guess we're just trying to convince you that there's, really nothing happens so now pay attention so. Now we start to stimulate, to just part of the brain. Right. Here and. Then. She'll walk the right out and, I. Bring the path back, home so. So, they are part. Of the brain regions, which really, just taurine dose and maternal instinct and when it turns out they. Should. Become instant mom. And. Do this all day long yeah. So before, we move cuz, a lot of you guys are doing not. Just mouse modeling, but also doing, human work too can, you all comment, on because because I don't know if anyone here is actually working with it in addition optogenetics. You're, out of the Dicer off lab another great development, has been this technique, clarity, the, ability, to take the brain which is an oblique structure. And essentially. Turn it into a, windowpane. So. Can, you all talk about how you see, that, as a tool the strength of it and can you potentially, merge it with some of these other techniques. Well. I think that so, for those of you who haven't heard there's, a technique, that allows, so. We'd like to see where all the neurons are we'd like to see how they're all connected. And. What limits it is the fact that the, neurons are embedded, in all sorts of fab.

And, Extracellular stuff. And when. You do microscopy it's very difficult to see clearly what's, going on and so. For several. Decades people, have been trying various, methods, for clearing. Tissue for making it transparent, and, there. Have been a couple of major advances. In the. Last couple of years including the clarity, technique, from. DICE. Roth's lab and some other techniques. That. Have made it much. Easier to see a lot of the. Brain clearly. To be able to image, down one to three, millimeters, in fact as the, limits now of less, to do with the actual. Tissue. And more to do with microscopy. I. Think. That that really, is making, it a lot easier, to quickly, see what the circuitry, is how different. Parts of the brain are connected where we're, using sort, of, related. Techniques, in fact we're using a technique, developed. By a guy, named ed Boyden. At. MIT. Which. In. Some sense goes one step further it, allows you to not only clear. The the tissue but. Simultaneously, to, expand, it so, some of the structures were interested, in it's called expansion microscopy surprisingly. Enough so. Some of the structures we're interested, in are below, the resolution, of light and the usual approach. To resolving a structure that's below the resolution. Of visible light is to. Use. Electron microscopy which, is a, lot, of work. My. Grad students, it's. More it's it's a it's, a million-dollar machine. And, just that's it's it's a nightmare. At least on this scale for c4 for, applying. Electron microscopy to, sort of macroscopic structures. And. So what he had I mean ed is actually the. Co-developer. Of channelrhodopsin. Along with Carl dice Roth what. Edie realized was, that instead, of getting, making. Microscopy better, so, you could see smaller things it would be just as good is if you could make the smaller things bigger and so. He. Developed a technique, that was really that was inspired, by and, actually uses, literally, the, stuff. That they make diapers out of and, you. Know how you for, those of you who are, familiar with diapers you add liquid, we'll say water to, a diaper and it expands, and so. He. Embeds. This this this, diaper. Stuff, in between, the. Bits, of. Of. Neuron, and then, binds every, little protein to a bit of it and then expands. Every. Protein. Isotopically. In all directions and, so, you can get expansion, factors, that are 2 & 4 and now, even 20, times the original so, you can take a synapse, which is below the resolution. Of light, point below, point 2 microns and make it a. 3. Micron 5 micron structure. Which we can easily resolve, and I. Think that that technique. Is is. Really on the verge of transforming a lot of what we can do and. Can you merge that so we are we are actively working with Ed's. Lab to merge our. Approach so all of this is to be clear is in. You. Know fix tissue and tissue from the brain after it's out of the skull so the optogenetics. Is fantastic. For working with a live. Animal but. Then to figure out the circuitry, of that, animal, that, what. You have to do is take it out and then use one of these methods so we are barcoding.

Neurons. In. All the animals you, know. We're. Getting ready to perform a task and then we, expand. The tissue and do the sequencing, in. Situ, so we can actually sequence the barcodes, while. The barcodes, are still inside the brain and it, gives us the spatial, resolution to. Actually see which barcodes, are out of synapse and actually figure out which neurons are connected to which other neurons so, there's. There are some engineering. Issues, throughputs, but throughput, issues but conceptually, we, can expand. An entire, brain and figure out the wiring diagram of an entire brain at, synaptic. Resolution, and while, we're at it we can also figure out which genes are, being expressed so. This. Is you know. One. Of one of the people and Ed's lab calls it the Rosetta, project because, basically we, can figure out everything, about a brain all. The way from activity. While the animal is performing, a task the behavior. And. Then the circuitry, and gene expression that caused those things so that that's where we're hoping to, go. With them that's pretty amazing to think about so. But, as you say that's finding, out everything about, a mouse brain yeah, and so we're talking a lot about you, know do mouse mice have human behaviors, and things you, know Elizabeth can you talk a little bit about you've, been. A very strong. Proponent of, that we've already got great, human, imaging techniques, that you're you're using, but. Also in humans and trying to trying, to study the differences, in similarities, and what we can gain more out of our MRI techniques, we already have and how you're going about that and helping translate ideas. Sure. So. So. I touched, on this a little bit before but I use, anybody. Here had an MRI scan. Yeah. Have you have you ever volunteered, for a, MRI. Scan where they you had to do tasks, and things like this, okay. So I've done lots of them they're very I fall asleep I'm terrible subject. So. We so, the you, go into an MRI scanner, it makes this beautiful image of your brain and. What they discovered about 30 years ago now is if you actually took a sequence, of images over, time that. You could see small changes, in the signal in different regions of the brain while. You were doing things so like if you actually moved your hand you, could find a region, of the brain that would have some sort of correlated, change in the MRI signal, while, you were doing that task and we call that the bold signal the blood oxygen, level dependent signal, and it's, what generates, those beautiful movies images, that you see on the front of the New York Times saying this is the area of the human brain that reacts. When you see a picture of a puppy or something and. And. So you, know I didn't my I did my postdoc up. In Boston. In one of the centers. That actually, developed this method and, so. Right now you know this is the best method that we have for looking at the human brain it it's. Non-invasive any. One of you can go sit and do one of these studies and pretend, to be a mouse, you. Know tapping. Your fingers are being shown pictures and and, it does a pretty good job it points to this.

Area Here this something, happened here, right, the. Problem is that that signal, actually. Comes about because there was a change in blood flow in that area so there's. Not really a change in the MRI signal, when a neuron fires but, there's a change in the magnetic, properties, of blood when it becomes, oxygenated. Or deoxygenated, and so that, little signal change that you see is actually coming from a change in blood flow to, the area and that's, why it gets a little bit confusing because, it's. A little slower than the neural activity because it takes a while for blood, flow to change after neuro neurons, fire and so, I've spent in addition, to the the other work I've done I spent a long time studying, this the relationship between neural. Activity, in the brain and the blood flow activity, that that kind of accompanies, it partly. Initially, to, help with understanding, those fMRI, images, better functional, MRI, because. We, knew using blood but, we wanted to understand what that meant in terms of neurons. I could talk about this all day, but it chords caused us to have to develop a lot of imaging methods to go in and use microscopes, to simultaneously, look at neurons firing and blood vessels next to them and I, got very interested in it from the standpoint. Of, it's. Actually quite surprising, that every time, a region, of your brain has. Some neural activity, that there's, actually a big increase in blood flow in that area and that. Has to happen for a reason and there has to be an important part of brain health and so, now my work has sort of moved towards, not. Just trying to understand the fMRI signal better, but also, recognizing. That there, might be situations in, which that relationship, between neural activity and blood flow gets disrupted and if, every, time you're hungry you, try to eat a sandwich but you miss, something's. Gonna happen you're gonna lose weight you're not going to perform as well and so. What. All. That stuff I showed you with the coffee and the ketamine they're really the core of that study in the beginning was, looking at how that, neural activity, actually was coupled to blood flow changes and, we've, got ways now we actually can give drugs that disrupt. The, relationship between, neural activity, in blood flow and we can then see what, effects do they actually have in real time on neural activity what effects they have on behavior, so, we're training the animals to sit and actually push, a lever this is one of Nick's other projects right flick their whisker try and get them to push a lever disrupt.

This Blood flow relationship, and see whether they actually become slower. At pushing the lever. Simply. Because this is just another aspect of the brain that we really don't understand. Stepping. Back. If. We, can get a better handle on this, relationship, between blood flow and neural activity, it, gives us a way to really better use functional, MRI and it has this. Method it has kind of an image problem right. We all agree. Because. It's not so clear what it means and in fact when you do it in someone who just had a stroke you might, see huge activity, in an area where they're paralyzed, or you might see no. Activity, at all and they go on to be to, have a great. Recovery. And so. Sort of my mission is to to, use these methods more in the mice where we can do this very detail, imaging but, to try to disambiguate, all of this try to find is there an early signature, of Alzheimer's, is there something that happens in stroke that, we can actually understand. In terms of what it's going to look like in, fMRI and then can we use fMRI, and much more guided way to. Get to those conditions in human brain so. It's a little sounds a little circuitous, but. It. Keeps me busy I think, we all agree it's something there's a huge need for you know to understand, what is it we're seeing and how do we learn from it you know car you've done some of the same thing and trying to tease apart, subtypes. Of depression, using using. Functional, imaging can you tell us kind. Of how you've approached that and what you've found and, what you think the potential for that kind of analysis, is yeah yeah, we're, really excited about this is another area we're really excited about in my lab the the. Opportunity, to potentially use brain. Imaging, to rethink, the way we diagnose, psychiatry, if you make. Diagnoses in psychiatry, if you'll bear with me for like two minutes I'll tell you an interesting historical, Dyk like, little background story so our, DSM. This book. That we use for diagnosis, it's kind of seeped into the public lexicon, right you read about and the times a lot of people are familiar with it and the. Whole way we diagnose, mental illness is, really not very old it was completely, changed, in 1980, I was born in 1980, you can't say that about. Very many other areas of Medicine and, and. Yet and yeah it's the truth everything, we do in psychiatry, is quite different from before 1980, due in part to this kind. Of controversial, study that was published in science seven years before that just. Showed essentially. That our our, diagnostic. System at that time was not very, reproducible and, very prone to bias so a social. Psychologist at Stanford very, cleverly designed a set of experiments, where he sent his, investigators. Into hospitals, around the country presenting. With a a fake, symptom, they were they said I'm experiencing. Voices, saying. The words empty hollow or thud and otherwise. They were supposed to answer all questions honestly, truthfully, and and. The results they just followed them and the results really shocking to everybody they, got different diagnoses in different places. Later, work showed that your. Socio-economic background, and your, ethnic background were could. Bias the way people assigned. Diagnosis, to you and. And. It. Was really hard to detect that these were fake patients, basically that's that's what he showed you could bias people's judgement in that way and then in a second part of the study and. This is kind of the clincher, in, the second part of the study he the, the Leda, on this study had met. The director of a famous hospital at the time and he said you know this, is this, is an. Anomaly, what you found is not representative, of the way we do business come. To my hospital see, if you see if you'll get different results and so, they agreed he would send an unknown number of people into his hospital over the next few. Months and during, that time their, job was to figure out who is a fake patient who's a real patient twenty percent of people were identified as definite imposters, another, twenty percent were identified, as probable. Imposters, so fully, two. Out of every five people who came to the hospital had were thought to be possible imposters. And the truth was that he hadn't sent any Impostors and they, were all real patients, so, you could bias people's judgments in both ways and, so, getting, to the point here, the. DSM, 3, which was released in 1980, and very similar to the one we use today was really designed to lump. Lots of people together with very different problems, in big diagnostic. Categories, that we could all agree on and and, it did a really good job of that the. The diagnoses. Are much more reproducible than, they used to be less, prone to bias but, the problem is they don't correspond, in biology very well so. Depression. Is a great example of that you, have this like choose, five.

Or More of nine, symptoms. So, there's at least 256. Ways you can be depressed and, some of them are almost opposites, of one another like sleeping. 19, hours a day can't, get out of bed not, enjoying any activities. Very. Slowed. Gained. A lot of weight that, person's depressed so as a person who is sleeping three hours a day. Anxious. Weight. Loss almost, the opposite and, they get the same diagnosis, but they probably don't have the same biological, problem and it's a miracle really that our treatments work as well as they do in, these in these very different people so, what we're trying to do with FMR is figure. Out whether we can identify clusters. Of. Patients, that have similar biological. Problems, as indexed, by fMRI. And and, which. Can be used to map. Functional. Connections, in the brain and and. If so then maybe we can then maybe we can target specific treatments. To individual, people who are most likely to benefit from them and can you find different patterns. Yeah. So we found, Ella's. Emphasize I don't think this is the the, best. Or final, solution to this problem but it's it's a it's it's one solution, that works well we found we can identify four very different patterns of of. Abnormal. Functional, connectivity in the brains of different, depressed people we can assign, individual, people to those categories, based just on their brain skin and then, those. Those categories, predict different kinds of symptoms and a, different, likelihood of responding, to transcranial. Magnetic stimulation. Which is a. Brain. Stimulation, based. Treatment. That you, could imagine it I mean it's, on a much coarser scale, but the, goal is the same as with optogenetics where, you're trying to stimulate, a particular, circuit, to to, modify, the activity, of that circuit, TMS. Works in much the same way and, it's and it's much more effective in one of these subtypes, than in then and the others and, you think if you look for those patterns in mice you can find out for Tony if mice are depressed yeah, we're we're working on that one, thing I think that's that's, really nice, about the mice is that you can you, know Elizabeth.

Talked About this, the. One. Of the limits of fMRI is it's fundamentally, kind of correlational. In nature you, you observe this, change. In in the brain scan and and it seems to correlate with a particular, behavior or symptom but there are many changes in these brain scans and it's really hard to pinpoint which, one if any is causally. Related to, particular. Behaviors, and mice. Afford us that that opportunity so that's that's one thing we're trying to do in the, brains of our of our mice so, because. We want a little bit of time for questions but so kind, of for one final thought. For anyone here so looking. Down the road five, ten years down the road what's. Your wish list or, what's your vision, of where you think we're gonna be or what, do you think is gonna be the next, what. We're what are we gonna do to unlock this and take it the next step and what are what are we gonna be talking about a decade from now. Well. I can tell you what we're trying to do I laid it out it's the rosetta brain I think, being. Able to understand. Behavior. All the way through from the the, behavior to, the neural activity to, the actual wiring diagram, for me as sort of the Holy Grail - to, reduce. It's. Not even reduced it's to provide the foundation, I went, into neuroscience, because, I, wanted to understand how three. Pounds, of. Stuff. Gives everything, that we see hear and feel and, it, just seemed incredibly, mysterious to me and after. Being a neuroscientist, for several decades it remains just as mysterious, I, don't, think we're any closer, to. Limit no. Sadly. We. But we I mean the core question why does it how does it why. Are we conscious how do we how, does it, feel. How, is it that we feel the way we do I don't think we're any closer to understanding, and. I sat there thinking about it for a long time and decided that thinking about it wasn't gonna get us anywhere further. But. I'm hoping that if we actually see, an example. Where we can go all the way from the, neural activity, to. The through the behavior to the circuitry, it'll, at least provide, us a way of maybe formulating. The the right next question which I currently. Don't. Have my, my. PhD. Adviser was Christoph call who has spent most of his career trying. To understand consciousness and. I. Think. And now he he's, the scientific. Director at, the Allen Institute where. Their goals are very similar to the goals of the people here which is to tease, apart the, circuitry, of a. Mouse, and so, I my my feeling is that although. The. The circuitry. Of a mouse is clearly, different from the circuitry of a human. Basically. The, building blocks are already there by the time you get to the cortex if you look at a piece, of Mouse cortex, and you. Change the scale bar and you, put, it next to a piece of human cortex they are indistinguishable, so. The basic, building blocks we, think even you a you're smiling, because you're a nursery but you will not be able to tell the difference if, I change the scale bar. Even, the neuroanatomists, at the Allen Institute were. Fooled by this this, pair. Of pictures so I. Think that you, know we we. As as. Humans. Evolved, in the last couple hundred thousand, maybe million, years as primates. Over the last couple million I mean most of the work was done I think, by the time we evolved, as mammals, we split off from mice. 7080. Million years ago the. Basic, building blocks I think are there, for us to understand, and once we get those then I think we're off to the races to figure out what makes us human but, I would be I, would be pretty happy if we could get an understanding of what makes us mammal so, we want to leave a little bit of time to questions we've got two microphones going around so if you have a question, please wait till somebody brings you a microphone. Thank. You very much to the, panel, you've given a really great overview of some. Of the genetic. And biochemical, techniques. That have advanced, the field in the last decade, or so but. Can you talk more to some of the informatics. Techniques. That. Might be advancing the field you, mentioned, and. A math for dimensionality, reduction there. Have been issues with you, know fMRI. Specifically. With sort of the kernels and statistics, that are going on there but, how has you know big data a data science, machine learning also, influence the field thank you. Well. I'll just say that I started, off in machine. Learning and neural networks as, a, grad student. And. I. Think. That those that. Field has, affected and in two ways first of all it inspires us how. To think about how the brain works trying, to build something, is one of the best ways of figuring out how something works, beyond. That in the last couple. Years machine, learning techniques, have. Transformed. Big data in, neuroscience, just like they've they're transforming, it in all other in many other fields so, that our, ability I mean we're now collecting, huge.

Datasets In you, know either, calcium, imaging or. Connectivity. And. You. Know you can't you can't just stare, at it anymore it's the same question of, you. Machine. Learning approaches. Provide ways of generating hypotheses, again, just. Just like knowing, the connectivity, and then it takes a real brain at least so far we're, not quite out of business yet but the these, these big data techniques transform, have, are in the process of transforming how we sort of generate, the scientific, hypotheses, that then we can go out and test that at least for me that's one. Of the big ways I would. Say coming back again to the other point is we, need computer, scientists. And people who understand, code, and and and big, data to. Understand, the brain right, because, it is a computer, right and and I again the insights you get from people who who. Know that are really, critical what's, really fascinating we've, got Amazon and Google and, and all of those big companies now really, interested, in brain research they're. Hiring our graduate, students, right, you this deep learning these algorithms I mean the whole thing is coming together so, so, I think both. Fields, are now really stimulating. Each other and I think you, know that's gonna be a path towards getting where we need to go part. Of the, difficulty. Is to, understand, actually the behaviors, and the behaviors. That turned out to the machine can do a better, job than, humans, in order to determine how many forms of a behaviour that they are actually. Bob data and hover they're creating, there's a syllabus of the behaviors, and they're trying to find a neural correlates, to that would you turned out you, know you actually finding, exactly, the neural correlates into the syllables of the behaviors which, as, a human server you could have completely, missing it so, I think that's kind of how does the two things our neuroscience. Enemy machine. Learning aspects. Are really assisting. Each other another. Question. Depressed. Lab animals, produced, developed, isolated, do you alter the genetics. Howdy. How do you produce. A depressed, yeah. I. Can. Take that one the. Real challenge. You, mentioned like. The like. Animal models of mouse, models of schizophrenia, autism, we. Have a much better handle on the genetics, of some, psychiatric, disorders, like schizophrenia, and. Autism than, we do for depression, what we know about depression is it's it's. It's heritable if, your mom is depressed you're, much more likely to grow up to be depressed yourself, and. That's, not just about environments. But. It's probably the. Results of the. Shared impact, of many many genes, each having a very small influence. On your likelihood of becoming depression, and that interacting. With your experience, so that makes it a lot harder to, have like a, genetically. Based. Model, of depression that. They, just don't exist yet they, may one day I'll, push back on that a little there's uh there's, a model of learned. One, model of depression as a model of called, learned helplessness and. There. Was a guy. Who, bred. Generation. After generation. Rats. That, showed. This this trait. Of learned helplessness and. Over. The last I. Think. It took him a good 15 20 years to breed these. Unfortunately. He started doing this when rats. Seemed like they were going to be the right model system not mice, but, he read he bred these rats that were genetically. Distinct. And showed this trait of learned helplessness and. They. And, he, and others have, gone on to dissect, some of the circuitry, that. Is. Disrupted. In these and identified, the lateral habenula, particularly. Important, circuit. In this now that's one particular, type of depression. But. I think, it just shows, how. The the, kinds, of behaviors, that we have can actually often, be modeled. In a row analogous I'll also add to that to say that you. Can even study things like confidence in. A rat. Or, a mouse it's, not obvious that something. Like confidence, which feels like it's an internal state would have a, neural, correlate, but one of my colleagues at Cold, Spring Harbor is identified. A brain region in, particular types, of nerve that seemed to encode an animal's, confidence, and confidences, for example one of the things that can, be easily disrupted, in.

In. Depression, so I think that when you actually, really. Think. Hard about how, to probe. The behavior, in a way that traditionally, people who work on rats and mice have not but are now starting to you, can actually sort of get more traction on these things than you might have thought the, sort of ridiculous notion of you. Know a depressed, mouse, or rat becomes, less ridiculous so, another. Question. Thank. You for the presentation. You, talked a little bit about. The, advance, how these advances, impact the diagnosis, of mental. Disorders. How. Do you see on the practical, level what, do you see these advances. Such as. Optic. Genetics, or anything, else that you talked about here how do you see them advancing. The treatment, like what can we expect. In the next couple of years with things like. ECT. Or, kind. Of anything, that I might not even be able to understand, from your answer to, this thank you. I. Think. Getting. Back to the the transcranial magnetic stimulation. Thing. As one example of, a treatment that's based on stimulating, a brain region ECT, electroconvulsive therapy. Is, is our. Most effective by far treatment, for depression and it's, basically a big jolt, that, is to the brain that's very, stimulating, to everywhere in the brain right and. And. And yet it also has a lot of undesirable, side-effects and so we reserve it for the people who are most who. Most need it who don't respond well to other treatments, I think one, potentially. Exciting Avenue in future would be figuring out whether there are particular, more focal, brain areas that require, a particular. Kind of stimulation, you, could even imagine maybe, a little further down the road cell type-specific, stimulation. Getting. At what a lot of Tony's work was describing. The. Overall goal being more, precision, in the way where we're stimulating brain regions might lead to more, effective anti, depressed responses, and fewer, side-effects and I think that's a vision that everyone kind of shares so. Unfortunately. We are running out of time we. Really need to thank these amazing, scientists, for being here. You.

2019-01-09 01:06

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