Engineering the Brain: Deploying a New Neural Toolkit

So I’m Guy McKhann: 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
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 Kavli Institute 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 Dayu Lin. 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 Conor Liston. And our final 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 Tony Zador. So maybe first we could talk about a little
bit the history of where did optogenetics come about from. Then you guys could talk
about using 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 had 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 ten 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 of course all recognize that correlation
is not causality, but with without the ability to sort of dissect out the circuits 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 of years lots of other, lots
of labs it happened. It was a paper from Karl Deisseroth and Ed Boyden. And within a couple
of years. Dozens and soon hundreds of labs were using it. So that’s really the basic
history. So Conor you spent time in Deisseroth lab
before moving to Cornell so tell us about how you’ve gotten with optogenetics to what
you’re doing with it, 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 mental 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 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 try to fix it. And that’s that’s one thing that really excites me. So give us give us an example of how you’ve
done that, a specific circuit that you’ve targeted and what you’ve been able to find
from that. Yeah, 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 many depressed patients. And we were able
to precisely manipulate the activity patterns of specific cells in the region of the brain
called the prefrontal cortex and begin to understand how, how it how it regulates the
processing of reward related cues and motivates 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 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 then possibly also people Dayu you’re using a lot optogenetics so what
are you using it for and what types of questions are you able to ask with optogenetics. Yeah. So I was lucky enough actually to be
of the first person that will benefit from the optogenetics. I remember it was still
in the days when there was a postdoc. And I had to say optogenetics, although it’s a
new technique but the concept wise is is not new. In the sense that neuroscientist have
tried very hard for centuries, of trying to manipulate the brains in order to see what
happened. So but the conventional manipulation is by passing some currents into the brain
so the electrical stimulation and that’s where I started when I trying to study the brain
before the optogenetic era. Electrical stimulation, there is one deficit
of that which is that neurons are not just a cell, which a ball, but they actually have
a lot of processes coming out. So when we electrically stimulate it we’re not only stimulated
to 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 electric stimulation. And optogenetics
is advantages because it allows you to really target the cells interesting without affecting
those cells it just sending processes to it. That’s just the specificity that makes this
tool really unique. And now we’re putting optogenetics into those cells and stimulate. So why don’t we look at it if we have the
aggression video first Yeah. So this is a mouse. There was this part
of the brain. It’s a very deep very Ventrell. And we turned down this area and you’ll see
that he start to attack this glove. And he really you know that’s not what mouse typically
do, so they don’t usually attack with gloves but in this particular case when the light
activated it he repeatedly sinks his teeth into this glove. In fact when we take it out
this glove is in fact deflated. So and it’s not only gloves. In fact that they would attack
other conspecifics including a female mouse that a male will typically would not attack
at all. So this inanimate object probably shows the extreme of misbehaviors that this
control of this area is just a turn on this attacking instinct immediately. So there’s some specificity to the aggression. It does. It does. In fact, one of the big
questions that we are trying to ask in the lab is when we do activate this area, is this
just a biting instinct or it’s actually increasing this aggressive motivation. Of the animals
and that’s why we’re designing different behavior task in order to dissociate this part. But
that’s exactly to ask is it to just make them bite or actually they are become has this
urge to aggress. Can you get them to attack a cat? I haven’t tried that, attack a cat or a
rat. That’s a much more complicated question. So all of you guys are talking about a technique
where you’re able to select out a very small specific part of the brain to try to isolate
and look for behaviors. Now Elizabeth you’ve been focusing on the one hand on using imaging
techniques to look at much broader patterns of activity and larger connectivity patterns
between the brain and even whole brain activity in various types of animals. Can you fill
us in on some of the things you’ve been doing along those lines? We do a lot of technique development in the
lab and I was trained as a physicist so I did a lot of optics 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 really
challenging as well and that’s a really important fact to hear so that 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 our work
what 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. All right well how do you
tell that you just throw me in there and make me flash. No but if you take me away and then
see what happens when I’m not there. You know it’s quite, quite a helpful way of figuring
out what it is exactly that I contribute. And so you know it’s not that much actually But so so so figuring all of this out I mean
for me you know we do our own we do our own experiments as well and we’ll talk about that
more. But but figuring out you know working working with you guys you know 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 10 lasers and all of this stuff happening at the same time as 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 read out 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 flies 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 cells. So this would be a good time to look at the
video that you have in terms of patterns of activity because it’s very different from
exciting a few neurons with one fiber. You’re looking at what the brain is doing spontaneously
in its own pattern of pattern of activity. so this is work that we’ve been doing. All
right to take takes a little bit of explaining. 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
G camp, which is a calcium sensitive fluorescent protein. So what we’re just talking about
was optogenetics where you express based on the genetics of the cells 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 10 years has been these fluorescent proteins
like the glowing jellyfish that 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 that they actually flash and we can read
that out. OK so it’s sort of the opposite. So anyway 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 would 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
patterns. So on the top left 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 going to play a 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 are responsible for seeing and hearing and motor actions.
This is 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 getting… there you go. So every time a region lights
up you hear a note. Give it a second So we use this method just as a way to try
to just really capture Is that fully automated? Sorry? Is the relationship between the brain activity
and the music fully automated or. Yes this is actually using the NAM. Non-active
matrix factorization algorithm on this stator and then taking the factors and then putting
them into musical notes And then if you go to the next slide. So then Just before you go there, I would argue relative
to what Tony Tony was saying before At rest, at least based on the music pattern
the mice are quite calm. Well after I started doing this analysis I
remember I had a big grant on this that I submitted right before Thanksgiving and I
was sitting there in 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 10 Things I hate about you one more time I thought maybe I
could get myself into this state. You know what I mean. And so this drew us onto to the
next part which is we then gave the animal caffeine. OK. So go to the next slide and play the movie
on the left so, it takes a minute. So we could we could play this music to a
mouse listening to its own brain. We talked about that just recently actually
if you can use that as a way to actually. So you want to quickly pay the caffeine one
It’s not so different. It’s a little faster. Has some gaps. Feels a little different. OK and then so we gave it ketamine. So ketamine
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 that this is a very odd modality that we came up with. we actually just take the data
using LEDs and camera.. It’s very low key compared to the really high tech stuff that
we also do in the 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 cells 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. It’s like the Internet. Right. 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 dumb. We’re having fun with this of course but we’re
really using this now to try to understand how that sort of whole brain contributes to
behavior. And particularly here we think about state so a state of being anxious a state
of being calm. And really what does that look like and then. How would each one of these
react differently if you presented it with an aggressive glove. So 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 what actually connects to what and
how we unravel that maybe can you can you explain that for us. Yeah so to sort of put it in perspective.
When the 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 neurons,
using optogenetics later we had gone beyond simply recording the activity of these neurons
and actually shown that one set of neurons, turns out that project to the auditory striatum,
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 which subset of neurons within a particular
area are driving this behavior versus that behavior and what roles they play. But the problem was that, we just have to
make educated guesses. And one of my students was really fantastic and made a really educated
guess and guessed right. And chose 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 was nope. That wasn’t the right
guess. And you learn very little Time for a new career. Not my career. As I told you I used to tell
people I still tell them who enter my lab I quote from Shrek always there’s a there’s
a for those of you my son 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. So,
If we guessed wrong there still ones who come up empty handed. So anyway. So how did you make it better for them? 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. 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 a single neuron resolution or
they were incredibly slow. So that what we needed to know was whether there are neurons,
let’s say in my case and 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 a mouse 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 with a fluorescent tracer or some other kind of tracer and then track that
trace all throughout the brain. The problem is…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 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 but how do you do that why does a neuron
want, not want real neural RNA. Yeah, 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 thirty nucleotide, thirty 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 not 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, which has transformed other fields
of biology. We can just just piggyback off of these tremendous advances in 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 we… Every neuron has its owns its own individual.. Every neuron has its own individual label,
and it actually I should have shown this picture. It’s inspired actually by an idea that scientists
at Harvard, Josh Staines and Jeff Lichtman came up with about 10 years ago, called ‘brainbow’
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 sight
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 project to. So in fact I was looking at your pictures
and one of them, we were 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 the sort of different chords especially in the ketamine brain where
it looks like there’s there’s sort of within their community there’s a lot of conversation
and then it passes the message to the next community. So it’s possible that you may be seeing with
nerve axonal labeling some of the same things I think actually the substrate for what you’re
seeing is precisely… We should hang out. Yeah. So how do you say how do you take that to
the next or a different level and say Now we know how things all communicate. How do
you start studying what’s normal and what’s abnormal? Right. So so the idea here is that we can
now for a couple thousand bucks figure out the whole connectivity of our brain at, there
are some issues about resolution. It’s a 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 can now compare the wiring diagram
of a normal mouse to a mouse that has a genetic deficit that has been associated with the
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 or sometimes
not. But 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 to take an educated guess. Burn up a couple of grad students
and if you guess right then… well but that is how these things go 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 physiologists like me
and the other people on this stage have to consider. So you’re taking a lot of guesswork for the
grad students out of picking your 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 admirable. We would all agree Connor. Connor 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. Can you talk about that and what it allows you to do that’s different
from traditional optogenetics. Yes 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 fluoresce in proportion to their activity. Like you
saw on those 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 basic kind of fundamental form of short
term memory that we all use all the time like if we decided we wanted to take 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 long
enough to dial it. But it goes away rapidly It’s already gone away with cell phones. Yeah exactly. Teamwork. 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 can show that, Can we see this Video that video. So so what you’re seeing here
are cells in the prefrontal cortex those black, those black 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 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 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 delayed period during the time it would take us to
dial the phone number in that analogy and how these different cell types interact to
imbue working memory 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 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 minimizing the
use of animals, being compassionate in that you know, but yet understanding what we need
to understand. So what are your thoughts on that? We recently started using fruit flies and
I don’t feel bad about that at all. So tell us what can you learn out of a fruit
fly? 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
at the core of neuroscience that let us label the cells different colors and change them,
introduce genetic diseases, make them express optogenetic options. You can do that in the
space of a week. You can just cross two flies and then you have another fly and it’s got
rainbows in its brain and it does all this stuff. For me what’s really nice because I
when I build microscopes is what you showed what you saw there was about a ten millimeter
field of view which is what we need, 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 it’s whole brain while it’s
on a ball and then you can actually puff odors 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, are flies the same as humans ? Probably
not. They they can fly which we can’t. So I don’t know. 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 very efficient very good nice way of understanding something at that level
and then scaling it up so. So there’s these people in neuroscience working at every single
level. What we really need to do is all talk to each other and sort of piece together all
of those clues. And we also do the maggot’s as well. I mean it’s gross. Dayu. Dayu, you showed us that you work on
aggression but you also work on maternal instinct so another thing that’s across the animal
kingdom but that we all think of as an incredible human thing but actually 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 optogenetics. You know they are in my views a lot of social
behaviors instinctive behaviors that they’re all controlled by those ancient structures
that the mechanisms is very conserved. And the maternal and paternal behaviors and in
fact parental behaviors in general in fact is also highly sexual dimorphism. I’m all
for them and I’m one of the regions we study is controlling the maternal behaviors. So
I to show you a video here just to say that we are not only looking at the years which
is fighting but also this is like just a heartwarming videos and look at it. So this was this is a virgin female that date
she doesn’t really care about the pups so much and she doesn’t have much experience
with the pups. So this is called a sham sham stimulation. In those imitation there were
just the endless areas that we put a puppy in the corner and she basically ignored the
pups. The pups is a whipping around probably making other boys sound. Tried to get her
attention. So. So this part will be sixty seconds which I guess was just trying to convince
you that there’s really nothing happened. So now pay attention. So now we start to stimulate
this part of the brain Right here. And then. Walked right out. And to bring the PAP .Back
home. So they are part of the brain regions which are really just controlling those maternal
instincts when it turns out they should be instamom mom. So supermom do this all day long. Yeah. So before we move because 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
to optogenetics out of the Deisseroth lab, another great development has been this technique
CLARITY, the ability to take the brain which is in oblique structure and essentially turned
it into a window pane. 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 is 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 fat 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 Deisseroth 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 have less to do with the actual tissue and more to do with microscopy. I think that really is making it a lot easier
to quickly see what the circuitry is how different parts of the brain are connected, 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 tissue but simultaneously to expand it. So some of the structures we’re
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. A lot of grad students. It’s more it’s a, it’s a it’s a million dollar
machine and it’s it’s it’s a nightmare at least on this scale first for for applying
electron microscopy to sort of macroscopic structures. And so what he had, I mean Ed
is actually the co-developer of channel and along with Karl Deisseroth, what Ed realized
was that instead of getting, making microscopy better so you could see smaller things. It
would be just as good 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 had liquid will say water to a diaper and it expands. And so he imbeds this
this this diaper stuff in between the bits of neuron and then binds every little protein
to a bit of it and then expands every protein isotropically in all directions. And so you
can get expansion factors that are two and four and now even twenty times the original.
So you can take a synapse which is below the resolution of light point below point two
microns and make it a three micron, five micron structure which we can easily resolve and
I think that that technique is really on the verge of transforming a lot of what we can
do. Can think, you merge that? So we are we are actively working with lab
to merge our approach. So all of this just to be clear is in fixed tissue and tissue
from the brain and after it’s out of the skulls. 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 sort of these methods so we are barcoding neurons in all the animals
you know regenerate 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 bar codes are still inside the brain
and it gives us the spatial resolution to actually see which barcodes are at a synapse
and actually figure out which neurons are connected to each other neurons. So there
are some engineering issues, throughputs, throughput issues but conceptually we can
expand an entire brain and figure out the wiring diagram of an entire brain at synoptic
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 in 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 cause 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. So we’re talking a lot about you know mouse
mice have human behaviors and things. You know, Elizabeth you talk a little bit that
you have done a very strong proponent of that we’ve already got great human imaging techniques
that you’re using. But also in humans in trying to trying to study the differences and 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 you know anybody here had an MRI scan? Have you ever volunteered for a functional
MRI scan where they showed you how to do tasks and things like this? OK. So I’ve done lots
of them, I fall asleep I’m terrible subject. So we, so 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 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. The puppy area And so you know I did 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’s noninvasive,
any one of you can go sit and do one of these studies and pretend to be a mouse, you know
tapping your fingers or 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 neurons fire. And so I’ve spent, in addition to 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 when you’re
seeing blood. We wanted to understand what that meant in terms of neurons I could talk
about this all day but it CT cause 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 or 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 that 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 going to happen you’re going to 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 I mean the 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 and 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 ,there were we’re 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 in your neural activity, it gives us a way to
really better use functional MRI and it has, this method 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 detailed 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 MRI and then
can we use fMRI in a much more guided way to get to those conditions in human brain.
So sounds a little circuitous but it keeps me busy. I think we all agree it’s something there’s
a huge need for, to understand what is it we’re seeing and how do we learn from it.
You know you’ve done some of the same thing in trying to tease apart subtypes of depression
using, using functional imaging. Can you tell us kind of how you approach 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 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 like
little background story. So our DSM, this book that we use for diagnosis is kind of
seeped into the public lexicon right, you read about in 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 yet 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 are our diagnostic
system at that time was not very reproducible and very prone to bias. So social psychologist
at Stanford very cleverly designed a set of experiments where he sent his investigators
into hospitals around the country presenting with a fake symptom. 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 were really shocking to everybody. They got different diagnoses in different
places and later work showed that your socioeconomic background and your ethnic background were
could bias the way people assigned diagnoses 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
judgment in that way. And then in the second part of this study,
and this is kind of the clincher, in the second part of the study the lead of 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 can 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 is a real patient. Twenty percent
of people were identified as definite impostures and other twenty percent were identified as
probable impostures. So fully two out of every five people who came to the hospital had,
were thought to be possible impostures. And the truth was that he hadn’t sent any impostors
and that they were all real patients. So you could bias people’s judgments in both ways. And so getting to that point here, the DSM3
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 it did a really good job of that. The diagnoses are much more
reproducible than they used to be, less prone to bias. But the problem is they don’t correspond
to 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 two hundred
fifty six ways you can be depressed. And some of them are almost opposites of one another
like sleeping nineteen hours a day, can’t get out of bed. Not enjoying any activities,
very slowed, gained a lot of weight. That person is depressed. So is a person who’s
sleeping three hours a day anxious, weight loss, almost the opposite. And they get the
same diagnoses but they probably don’t have the same biological problem and it’s a miracle
really that treatments work as well as they do in these in these very different people.
So what we’re trying to do with fMRI is figure out whether we can identify clusters of patients
that have similar biological problems as indexed by fMRI and which can be used to map functional
connections in the brain. And if so then maybe we can then maybe we can target specific treatments
to individual people who are most likely to benefit from that. And can you find different patterns of patients
based on fMRI? Yeah. So we’ve found, I always emphasize I
don’t think this is the best or final solution to this problem but it’s it’s a it’s one solution
that works well we’ve found, that we can identify four very different patterns of abnormal functional
connectivity in the brains of different depressed people. We can assign individual people to
those categories based just on their brain scan 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, I mean it
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 circuits. TCS
works in much the same way and it’s and it’s much more effective in one of these subtypes
than in than in the others. And do you think if you look for those patterns
in mice you could find out for Tony if mice are depressed. Yeah where we’re working on that. One thing
I think that’s really nice about the mice is that you can, you know, Elizabeth talked
about this. The the one of the limits of MRI is it’s fundamentally kind of correlational
in nature. You observe this change in the brain scan and it seems to correlate with
a particular behavior or a 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, we want to leave a little bit of time
for questions, but so, one final thought for anyone here, so looking down the road, five
years down the road what’s your wish list or what’s your vision of where you think we’re
going to be or where do you think is going to be the next? What are we going to do to
unlock this and take it the next step and what are what are we going to 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 behavior to the neural activity to the actual wiring diagram for
me is sort of the Holy Grail. To to reduce, it’s not even to reduce, 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 in a neuroscientist for several decades it remains just as mysterious.
I don’t think we’re any closer to… A little bit? No sadly. But I mean the core question, why does it
how does it…. why are we conscious? How do we even 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 going to 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 right next question which I currently
don’t have. My Ph.D. adviser was Christof Koch who has
spent most of his career trying to understand consciousness. And I think 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 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, that
you’re smiling because you’re a neurosurgeon or 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 as as humans evolved in the last
couple of hundred thousand, maybe million years as primates over the last couple of
million. I mean most of the work was done I think by the time we evolved as mammals.
We split off from mice seventy, eighty million years ago. The basic building blocks I think
are there for us to understand. And once we get those, than 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 learn a little bit of time of
questions for 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 informatic techniques
that might be advancing the field you mentioned NMF for dimensionality reduction. There have
been issues with, you know far more specifically with sort of the kernels and statistics that
are going on there. But how has you know Big Data, data science, machine learning also
influenced the field Thank you. Well I’ll just say that I started off in
machine learning neural networks as a grad student and I think that those that field
has affected it 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 of 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 data sets and, 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, 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 these these big data techniques transform,
have are in the process of transforming how we sort of generate scientific hypotheses
that then we can go out and test. 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 big data to
understand the brain. Right. Because it is a computer right? And again the insights you
get from people who who who know that are really critical. What’s really fascinating
we’ve got Amazon and Google and all of those big companies now really interested in brain
research. They’re hiring our graduate students, right? 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 going to be a path towards getting where we need
to go. Part of the difficulty is to understand, actually
the behaviors. And the behaviors, it turned that a machine can do a better job than humans
in order to determine how many forms of a behaviors they are. Actually Bob Datta in
Harvard, they are creating a syllable of the behaviors and they’re trying to find a neural
correlate to that, which turned out, you actually finding exact in neural correlate to the syllables
of the behaviors, which we as a human observer you could have completely missing it. So I
think that’s kind of how these two things are neuroscience and machine learning aspects
are really assisting each other. Another question? Depressed lab animals produce, developed isolated,
do you alter the genetics? How do you produce a depressed animal? Yeah I can take that one. The real challenge
you mentioned like th, 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 environment. But it’s probably the result 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 a,
there’s a model of learned…one model of depression as a model of cold 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 fifteen, twenty
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 bred these rats that were genetically
distinct and showed this trait of learned helplessness and they, he and others have
gone on to dissect some of the circuitry that is disrupted in these and identified the lateral
habenula, the particularly important circuit in this. Now that’s one particular type of
depression. But I think it just shows how the kinds of behaviors that we have can actually
often be modeled in a rodent.. And I’ll just 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
and particular types of neurons that seem to encode an animal’s confidence and confidence
is for example one of the things that can be easily disrupted in depression. So I think
that when you actually really think hard about how to probe that 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. 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 optogenetics
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 anything
that I might not even be able to understand from your answer to this. Thank you. I think getting back to the transcranial magnetic
stimulation thing as one example of a treatment that’s based on stimulating a brain region
is, electroconvulsive therapy is 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 yet it also has a lot of undesirable side effects. And so
we reserve it for 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 with 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 antidepressant
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.


  1. Vannic Wolf said:

    Hey, that was a good talk. Juicy. I like how they showed interest in working together.

    January 8, 2019
  2. Chris Mccullough said:

    Thanks for the info…Cool concept with the music and fruit flys

    January 8, 2019
  3. vicki kondylas said:

    Thank You πŸ™Œ

    January 8, 2019
  4. D Man said:

    Hey Psychiatrist guy. The drugs are terrible. First try to differentiate between depression and anxiety. Both are treated as the same thing currently. I think psychiatrists are barbaric as they ever were. Still no brain scanning. Wild speculations made on people, Worryingly corporations are now using psychiatrists to attach mental disorders to employees in cases of bullying complaints just in case there is a court case, Also with a recent focus on children and teenage mental health, People are being medicated with drugs that cause mental disorders, for instance they focus on neutering a person's emotions with a drug like Zoloft, Psychiatrists are getting too much respect, They are comparable to witch doctors. And dangerously they can be used to damage an individual's reputation, Lately aspergers was created because aspergers people have great imaginations and therefore during a court case they imagine past reality, These guys should be banned from labelling people, that's where the abuse is happening, Psychiatrists have been turned into legal support tools for discrediting individuals and supporting corporations, Hopefully science bypasses these people in time, Their business is based on the customer feeling like they need help, True this is an opportunity but not an opportunity to support psychiatrists to brand people with rubbish disorders. I'm concerned about the goal of psychiatric "professionals" in general. They like repeat customers after all.

    January 8, 2019
  5. 12vinyl said:

    So they can make a perfect soldier?

    January 8, 2019
  6. Justice Blue said:

    I don't think 'wrong' and 'fix' are the right way to think about brain function.

    January 8, 2019
  7. Sanja Jovanovic said:

    Justice for 🐁!!!

    January 8, 2019
  8. USERNAMEfieldempty said:

    Good talk, but this discussion really needed Kanye West's input πŸ˜‰

    January 8, 2019
  9. Anton Mies said:

    Would love to hear and see mice brain on LSD

    January 8, 2019
  10. Zangief The Red said:

    Interesting. Although I felt the urge to vote down on behalf of all those poor mice and rats that cannot vote by themselves. 🐁🐁🐁

    January 8, 2019
  11. RoGeorgeRoGeorge said:

    Good re-upload, looking forward for new talks

    January 9, 2019
  12. Toxis said:

    how accurate is that metaphor @ 16:37 – because if the brain is similar to the internet – is vice versa true? If yes, have we unintentionally build a brain just without all the goodies of our neuro-soup? Could we build artificial neurotransmitters on a standard TCP/IP maybe?= ) (god damnit, don't tell me blockchains are that:). Great work btw, please give more psy stuff to mice. Because a)they deserve some fun and 2)the interpretation of the data in this way is awesome. And a bonus question – when will I be able to play my thoughts to people, preferably without an om4 cable dangling from the back of my head like cyberpunk Cyrax from Mortal Kombat?

    January 9, 2019
  13. gail lilly said:

    Am disappointed that the neural doctrine has dominated this presentation. White matter which is 85 to 90% of the brain was not mentioned. Nothing re: the role of calcium ions, calcium waves, glia, e.g. astrocytes, their role in creativity, thought and more basically, more fundamentally, their role in the stimulation or activation of neurons, their production of neurotransmitters. Hope white matter will be the subject of more research; it is key to understanding the brain.

    January 12, 2019
  14. Adam Hicks said:

    Any chance of uploading the full video of the mouse brain visualizations with music like indicators? It was really calming, and it would be interesting to observe longer periods of the recordings.

    January 20, 2019
  15. stuntard said:

    This is my new favorite channel πŸ‘ŒπŸ‘Œ

    February 8, 2019
  16. Why bother? said:

    Terrible audio as always.

    March 24, 2019
  17. The Koran has scientific accuracy said:

    see my channel

    May 13, 2019

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