- At this time, I am delighted to bring out the host of "The Future Of Everything" and his guest, Karl Deisseroth. Please join me in welcoming Russ Altman, the Kenneth Fong Professor
of Bioengineering, Genetics, Medicine, Biomedical Data Science, and by courtesy, of Computer Science. Russ was also one of our past
chairman for bioengineering. So please give me a warm Stanford welcome to Russ Altman and Karl Deisseroth! (audience applauding and cheering) - Thank you everybody,
it's great to see you. Before we get started, a couple of things. I haven't spoken for four
days with laryngitis. I am heavily medicated, so I
think I'll be able to speak, but I wanna apologize if
my voice seems strange. I'm okay at the lows,
but I lost all the highs. So I'm gonna try to keep it really low. Thanks to Karl. That's the first thing I wanted to say. Well, we'll talk more
about Karl in a second. It's all about Karl. The second thing I wanted to say is, yes, this is a live recording of a podcast that does air on your
favorite iTunes podcast or other applications. And please, if you enjoy today,
please consider listening. I'm gonna say that again
on the air in a moment. Right now we're off the air, so it's a little intimate
moment with all of you as we warm up. Everything okay? - Everything's great,
thanks for having me. - Okay, and are our volumes okay? I'm just gonna keep speaking a little bit so that the volumes can be connected. But we're gonna do about a
25 minute normal episode, and after that we're
gonna have a little break and then we're gonna have a discussion, a wide ranging discussion with
Karl about many, many things. I want to apologize a little bit that normally I have a teleprompter. It makes me look super suave
and like I don't need any help. I don't have a teleprompter today, so I will do a little tiny bit of reading. I will try to minimize it and
I ask for your forgiveness. So with that, are we videotaping this? Awesome. Where's the camera? I just, I always need to
know where the cameras are. Thank you, okay. All right, so ready? We'll get going just about now. This is Stanford Engineering's
"The Future Of Everything", and I'm your host Russ Altman. If you enjoy "The Future Of Everything", please follow or subscribe it wherever you listen to podcasts. This will guarantee that
you never miss an episode. Today, Karl Deisseroth will tell us about technology development
for neuroscience, how to use that technology
for discovery in neuroscience, and how we can take that
technology and those discoveries and improve the mental health of patients. It's the future of neuroscience. Before we jump into this episode, I want to ask you all to
rate and review the podcast. It will help fellow listeners discover us and it'll help us improve. Okay. So when you think about the brain, one of the things you might
think of is that in 2013, the National Institutes of
Health of the United States created a roadmap. It was called BRAIN 2025, I think. And it was in 2013 or roundabout there. And it was a roadmap about
how we could crack or solve important questions in neuroscience. Neuroscience, of course, has been making progress
for hundreds of years, but there was a sense that
there was an opportunity that we needed to take advantage of in order to accelerate our understanding. And that plan led to a beautiful document, which I recommend you read. There was actually a
follow up five years later. But the thing that I remember
about it is one thing. They said, the first five years of this
effort should be focused on technology development. We need to create new technologies because we simply don't have what we need. After that, we then need to
get serious about solving major problems in neuroscience that have been vexing us for decades. So that led to a big
push, and in many ways is a beautiful summary of
what we're about to talk to with Karl Deisseroth. Karl is a professor of bioengineering and psychiatry and behavioral
sciences at Stanford. His lab does those three things. They develop technologies,
they apply them for discovery, and they are driven by the
need and the desire to improve the state of mental health care and psychiatric care in all patients. So Karl, welcome. - Thanks Russ. - And I really wanna say
that my first question is how did you respond to these challenges of the Brain Project as it came out, just around the time you were still a young
and promising scientist. How do you trade off the
desire to develop technologies with the desire to just
get on with the science? - This is a absolutely crucial
point because many times people will have a self
image of themselves as, oh, I'm a technology developer,
or I'm a pure biologist. And people have these
narratives about themself and where they get them,
it's almost random. And then they end up being constraining. And from the very beginning, you know, I came to neuroscience from,
I was trained in biochemistry, but I got interested in
neuroscience from the, all the way at the other
level, the psychiatric level. And there's a vast chasm there. And it's very clear that new technologies had to be developed. And so, from the very
beginning, from my perspective, it was all about even
if your basic science, even if you were a pure biologist, you had to develop technologies
as a primary goal, honestly. And so I've tried to instill that in the folks who come through
my lab, you know, probably, I think even the people
who consider themselves pure biologists who are in my lab, at least 1/4 and up to half of their time is spent on technology development. It's actually best that you
unify those two threads, not just in the same
lab, in the same person. So for me, it was never a
trade off or a conflict. In fact, it was a way to help move things where it should go. And it was, for us, it
made a lot of sense. - So let's take an example. I think one of the things
you're very famous for is the technologies
associated with optogenetics. So you have lots of
things you can work on. Tell us the story about how
the optogenetics technology became clear to you as
something worth a big push as opposed to the many other things you could have pushed on. - Well, like a lot of things, you don't really know until you try. If you're getting the
green light from nature and you just have to try it. It's like you're walking
through Manhattan, you know, you know where you're going, but you gotta take the
lights that are there. And there's no way to know until you look. And so that's kind of the perspective. And honestly, if you want
to, what optogenetics is, it's a way of controlling
specific cells with light. You can turn them on or
turn them off with light, even in complex behaving
mammals doing intricate tasks. So if you have that goal, how
do you set about doing it? Well, there's a lot of ways you
might turn things on or off. You might use different
ways of delivering energy. You might use genes that help
cells increase or decrease their excitability. And that was how it started. I said, let's try a
bunch of different things and see where we get the green light. - So the goal, tell me if
I'm getting this right, the goal was to precisely
control individual cells. And there was a severe need
for this because even I know that in the olden days
it was plunge electrodes into neural tissue and have
a huge electric field applied that was not very precise. - Yeah, and that's for stimulating. It's even worse for inhibiting. The technology for inhibiting was scoop out that part
of the brain, you know? - So tell me a little bit more. Okay, so you say we have to
get precise control of neurons. You already, you indicated to us, you were already were creating a checklist of what might work,
what might be possible. What made light the winner? And then how do you take a
great idea and turn it into something that is a practical tool that can be exported to others? - Yeah, and that's where
being in bioengineering was so important. Because I had, not just myself, but the people around me,
the department, in the air, in the water was this
desire to not just discover, but to create. And that's really what it was. It was let's discover what might work and then let's put in the years of work to actually make it work. And so from the first
principles, test some things, see where you're getting the first clues that something might work. And then put in the substantial
effort that came after that, after the first, you know, promising signs to actually build something
that's functional. And that, you know, that said, in the backdrop of academia
is kind of interesting because as someone running a lab, you can't always just take
the 10 year viewpoint. You have to think about
the careers and the papers of the people who work with you. And so then you have to set
up checkpoints and milestones where the papers can come, and the steps that are partway to the goal are clear and discrete. And so the way I approached that was, now we're at a point, I'll
just jump right to the end to give you a perspective
where things are going. Now we can play in single cell control to hundreds or thousands of
individually specified cells. We can literally circle them and say, I want to drive these 1000 cells with this particular sequence and rhythm. But that took until really just this year to get to that point. So, but early on, what
were the achievable steps? There was a list of control cell types. First let's control all the
cells that have one genetic type or one anatomical type, the cells that live here and
send a connection to there. And so establishing
those early milestones, which were actually honestly
great in themselves, a lot of discoveries can happen that way. Understanding the biology of cells that have certain projections
or certain genetic identities that allowed us to make sure
the students and the postdocs got their papers and kept us going toward the goal and where we are now. - So for people who are not
familiar with optogenetics, and I'm going to, this is a big mistake, but I'm gonna try to summarize
and you will then correct. But basically you found proteins, channels that can be put
into cells artificially. These channels are
amazing because they come from widely disparate
organisms found on earth who have the need, basically,
to sense where there's light often to then travel
towards it to get nutrients or sunshine for a living. So, and then you put
these into these cells and then when you expose
light to the cells, something which normally doesn't happen in an enclosed skull, you
can change the behavior. Is that a fair summary? - That's perfect.
- Okay. So how did you know about
these proteins that, in these weird little floating
algae in the Sargasso Sea or wherever they live? - Well, so these proteins
is a class of protein called microbial rhodopsins. And the genes that encode them are, are called microbial opsins. This family of proteins had
been known for about 50 years. And it was in biochemistry textbooks, my biochemistry textbook, Lubert Stryer's third
edition of "Biochemistry", there's a beautiful
page on the photo cycle of bacteria rhodopsin, and how when the light hits the protein, a charged particle gets
translocated across the membrane. So, known for a long time. But as you said, these
come from weird species, very, very far afield from
animals, even, certainly mammals. And people who had, as I had, expressed different proteins
from different species and neurons. Neurons are very sensitive,
they're very vulnerable. This particular kind of protein, it lives in the membrane of the cell. And that itself is a very
disruptive part of the cell to pack full of foreign protein. You know, this is the barrier between the inside and
outside of the cell. It's very easy to kill a cell by putting too much of the wrong
stuff in its membrane. And I knew this, I had done work like this
putting in membrane proteins into cells, and I'd seen
how toxic it could be. And that was even with mammalian proteins. What about taking something
from a single cell microbe, billions of years removed
from us evolutionarily? So it was unlikely to work,
extremely unlikely to work. And other issues, there were many other
issues to not even try it. The currents would be very small. The rate at which charged
particles would translocate across the membrane would be very small. There were questions about
how do you get the light in, how do you target the
gene to the cell type that you care about? A host of other issues. And if you add 'em all up,
you look at it and say, nah, just it's not worth it. - Yes, but it was worth it.
- It was worth it. - Okay, so thank you. And so this is great
because it kind of shows that in retrospect
everything is fun and games and everything works. But at the time you were making a big bet. And you were putting
resources into a project that could have come up empty. So I'm sure what one of the
things that people are thinking is, this is a great discovery tool. You can do this now, you can study neurons at a precision that was not possible before. Are we ever going to be putting
lights into human brains to take advantages of this technology for diagnostic or therapeutic uses? - Well, first of all, it's already actually being done, at least into the central
nervous system of human beings. So two years ago, my colleague
and sometimes collaborator Botond Roska in Switzerland, he was able to take a blind person and make them be able to see again, at least to be able to
identify objects on a table and to reach out to them, someone who was completely blind before and didn't have that level of vision. - Had they been a seer previously? - Yes. - So their brain knew what
to do with light signals. - Yes, this was someone
with retinitis pigmentosa, a late onset degenerative disease. So the brain knew what to do. And other things that
made it more accessible than some harder problems
you might imagine. The retina's very accessible. The retina's used to dealing with light. And it was initially
just a simple experiment, just give the person the ability to see what's in front of them, that there is something in front of them. But still, that's pretty good. And it answered so many
questions, human beings, like the rats, mice, fish, worms, monkeys that it's been tested in before can tolerate these microbial
proteins perfectly well and that they work. And so it is possible to do direct, what you might
call direct optogenetics in human beings. And now the question is, as you get to more
mysterious parts of the brain than the retina you better
know what you're doing. 'Cause you've gotta put in a
gene and you probably have to get light in somehow. And so probably good to
not be doing your guesswork in the human beings, do the
basic discovery in the animals, and work in structures that are ancestral and conserved phylogenetically
across animal species. And then you might be in good shape. So a lot of my work in the
lab has been devoted to that sort of work, is saying, you know, as a psychiatrist I think
about motivation and energy and anxiety and primary
survival drives like hunger. When do we not eat when we're hungry? These are things that
all can go horribly wrong in human beings. And so I study the cells
and the connections that, if you intervene,
you can change them. And so that's been a
thread all the way through. Building that knowledge
of what actually matters in the long run may help
with direct optogenetics. But the final thing is
that's not even necessary for there to be a therapeutic impact. You don't ever have to
put these genes in people for something to matter for human health. And that's because understanding
what matters opens the door to any kind of treatment. Once you know the cells that matter for causing or correcting a symptom, then it opens the door
to looking at the genes those cells express, the molecular targets that might be there for drugs, the ways of accessing
their far-flung projections across the brain. And so once you know what matters, the therapy can be anything. - Fantastic. Okay, so this leads really nicely into what I wanted to spend
a few minutes talking about, which is you are an actual
practicing psychiatrist. You care deeply about the
problems that your patients have. And these are complex problems. You were just referring, you know, people think of depression,
bipolar, schizophrenia, terrible diseases with a huge
morbidity in the population. But there are many more subtle
dysfunctions that you see in your patients. And by the way, they're
beautifully described in your book called "Projections". And I want to know, and we've established
in the last few minutes the kind of great
engineering and discovery that you've been able to do. But I know that a lot of this is informed by your clinical practice. So can we go to the
other end of the extreme and tell us, how do you approach the art of medicine as you go
into a room with a patient, with knowing that you have this
amazing set of capabilities back at the lab, but
still looking at a patient who needs help now? Tell me about that experience. - Well, first of all, I've kept doing it just because it's such an experience. It matters. It's become part of my identity,
you know, how I see myself. But it's, I'll be honest, particularly when I do both
inpatient and outpatient work, so outpatients in a clinic
where someone comes in and you know pretty well and you've been seeing them for years and they come in every
month or so, that's great. It's great to really know the person and you can really help them best. But then the inpatient work, that's acute emergency room psychiatry, where people are the most, you know, most vulnerable, most broken
down, need the most help. And things are most confusing,
chaotic, lack of information. Life threatening, you know,
comorbid conditions are present, other diseases that are
present at the same time. And I do that for about one week a year. And I have to admit, when
that week comes close, I start to get kind of anxious myself because I haven't done the
acute stuff for a year. And what if I'm not up to the job? You know, what if things
have advanced in some way? Of course, I stay current. But there's always some question, have I not stayed current enough? But that week is always a
completely invigorating, transformative period for me. And I come out the other side, just new energy, new perspective, and I come back to the
lab with just such joy that each year, it's
like rebooting myself. It's quite remarkable to see. So that's one thing is it actually matters psychologically,
motivationally for me. But it also really helps the science. 'Cause I know many people
who are working in a lab who are interested in a disease process, somebody might be interested in autism or they might be interested
in schizophrenia, but they haven't had a lot of
direct exposure to patients. I think it really helps to
be able to go and talk to, you know, your advisor and say, what is the symptom really like? What does it feel like? What really matters to the patient? Instead of just looking at
a list in a book and saying, oh, okay, repetitive behavior, okay. It matters a lot to think about
how this actually manifests in human beings. And so I try to share that
real world perspective with my students as much as possible. So it helps in that regard. We design a lot of our experiments, keeping in mind what really matters, what challenges people
with psychiatric disorders, what they encounter. And to what extent can we
study those things in the lab, focusing on conserved ancestral
circuits and behaviors. - So I, that's great. And I mentioned the Brain
Project that was kicked off about 10 years ago. And I talked about how it was gonna be technology development, but then they were gonna start
looking at the big problems. And I know you've
thought about this a lot, and in fact there was a
report five years later, and I did look at it in
preparing for our conversation. But then I said, nah, I'd like to hear Karl's take on what are the most pressing
questions in neuroscience that are within reach now that may not have been
in reach 10 years ago because of this technology development? - Yeah, this was a moment,
I remember this very well, the 2013 moment when the group was put together from the White House. And so I was very happy to
play a role in that group. There were a few of us
who organized workshops over the course of a year. We integrated feedback
from neuroscientists and engineers from across the world. And there was a clear sense
that some things were missing, and that the wind was at
our back at that moment. And so it was something
to pay attention to. One was what we've
alluded to a couple times is the cell types. What is the parts list,
effectively, in the brain? And you know, with other
organs like the heart, it's easier to appreciate
the parts list, right? You've got your cardiac myocytes, the muscle cells that contract and they drive the
contraction of the heart. And then you've got your pacemaker cells that time the rhythm. And then you've got your blood
vessel cells in the heart that send the blood around the heart. And that's great. The brain, there are hundreds
if not thousands of cell types in the brain. They're all intermixed with each other. They're all tangled up
in this massive wiring. And we only had the broadest
categorization of cell types. We knew there were excitatory cells and we knew there were inhibitory cells, we knew there were dopamine
cells and serotonin cells, but we didn't know fundamentally
much more than that. So that was one goal. And once we knew the cell types, then we could bring in tools
like optogenetics and say, okay, what happens if you turn up or turn down this cell
type in this context? And that was one, probably the first major
goal of the BRAIN Initiative was to get that parts list. And then once we had the parts list, to start bringing the optogenetic tools, which we've been developing along the way, to bear on those parts. - So I know that one of the
things that they talk about and that you talk about, you mentioned it even
earlier in our conversation, is this idea of causality. That perhaps too often people were looking at the correlation of certain
phenomenon in the brain to certain behaviors or certain illnesses. And I think that you implied
before that there's something very concrete about
knowing that a certain cell is driving the normal or
the abnormal behavior. - Yeah, the brain is so
vast and so interconnected. And we've actually done
experiments like this. You can ask a simple question like, of all the cells in the brain, about what fraction are correlated with the simplest possible
action you could imagine? And we did this experiment, published it a couple years ago in 2019, recording effectively from
tens of thousands of cells across the brain electrically while a thirsty mouse
went for a sip of water. Simplest possible thing you can imagine. And more than half of all
the neurons across the brain correlated with that action. - We're all thirsty. - (laughing) Yeah, or something. But, and this was every structure. Structures that weren't
even visual, you know, the parts of the brain
you wouldn't imagine that would be involved. So right away you've got,
the brain is so fast, so interconnected that everything
ends up being correlated more or less. So that's where causality
is so important is to ask, what matters? By the way, I don't mean to dismiss
at all how amazing it is that this information gets around. I think that's very important. I think every part of
the brain needs to know what's being planned by another part so it can make sense of the
new information it's getting and isn't surprised by it. I think the brain is read
into a lot of things, even if those parts that
are getting information are not causally involved
in the immediate action. But if you care about what
matters for something specific, maybe it's a psychiatric disease symptom or maybe it's a memory, or maybe it's a healthy adaptive
drive that we care about, like parenting. These things, to know
what actually matters, you have to bring in a causal-- - So let me ask you about that, because we've been
talking about like, okay, and I know it is true that
in some cases you find one or a small group of cells that
really seems to be driving the thing of interest. But of course there's gonna
be cases where it's a ensemble of cells, maybe even distant in the brain. And how are we gonna get at
that when you're gonna need to do your optogenetic queries, perhaps over several cell types in drastically different
parts of the brain, and maybe even with very exquisite timing? So what is all that? How's that gonna happen? - Well, we're getting there. And in some ways, we are there now. So at least in mice for
example, and in zebrafish, small organisms where we can access many parts of the brain at once, we can now reach into many
different regions simultaneously, see what's happening,
cause things to happen and have millisecond timing resolution, synchrony or asynchrony as we like. So we're now there in principle. And in some studies it's
already starting to be done. There's work done both
here and around the world, people doing things like
recording from cerebellum and frontal cortex at the
same time, for example, you know, front and back of the brain. - So one the thing that
strikes me is that that means that there is an almost infinite number of combinations of cells
that you could look at. So do we need, or do we have a theory for which cells actually should be working together so that our search space
of which combinations can be brought into a manageable range? - So this is very, very important. And this is was another key
pillar of the BRAIN Initiative because we realized this
issue that very clearly, we needed theory guidance to deal with this combinatorial explosion you're alluding to. And it hadn't been as
serious a problem before because we didn't have the
technological abilities to make it a problem. But then all of a sudden
we had this ability and the theory hadn't caught up. The theorists, who are great, many of them we collaborate with and our are dear friends of mine, but that we were not able
to be guided by theory all of a sudden, given where
the technology had brought us. And so that's been a very important part of the BRAIN Initiative. And it's really been wonderful, honestly, to see the new generation
of theorists that have been, you know, fostered by the initiative. - So in the last couple of minutes, I want to go back to
your book "Projections". It's great, I've read it, and
I've read it more than once. And not even in preparation
for this conversation. Why would you write a book? And tell me about any
kind of knock on effects that this has had. Is it what you expected? Was it easier, harder than you expected? And what has been the reception been other than from Russ,
who clearly is a fan? - Well, I'm glad you read
it, I'm glad you liked it. That's why I wrote it. Not for you.
(audience chuckling) But the immediate stimulus
right around the time I started writing it in earnest was I wanted to communicate with everybody, I wanted to share with everybody both the inner worlds
of psychiatric patients, which I think are mysterious and opaque to many people, understandably. I wanted to share that perspective. And so, and I thought about
that hard, how to do that. And each chapter deals with a different
psychiatric disorder. And each chapter's written, colored by what I know
about the inner worlds of these patients. So the chapter on mania is written in an over-exuberant style. The chapter on schizophrenia is written in a fragmented style. And so I wanted to help use the language as well as the content to illustrate what was
going on, just to share, just so people knew. That was one goal. Another goal was to bring the science. I wanted everybody to know where the science had brought us too, to know that the basic
science and engineering has been good. It's been helpful. People who don't necessarily
have any exposure to science or engineering in their everyday life, I thought it would be great for them to see what's happening. So that was the immediate precipitant. But I've always loved writing,
I've always loved words. That was actually what led me to think about the brain first. And I'd been writing all along the way. When I saw a patient, I would
write about the patient. When I saw words or phrases that to me captured an
emotion well, a feeling, I would write those down. And so in some ways the
book is 20 years of that. So, and bringing it together was hard because I set some
ground rules for myself. I wanted to be, no matter how creative I
wanted to get with language, which I did, but I set a rule. I had to be absolutely
grounded in the science. Like, I couldn't stray even
in iota from rock solid truth. And so that was the fundamental
balance in writing it. How do I allow literary flights and stay anchored firmly in science? And so threading that was a challenge. But what I do know is I
didn't offend any scientist, which was very important,
as far as I know. Both the scientists and the literary folks seem to like it. - Have you gotten feedback from the world? - So I've got amazing feedback from people from all over the world. You know, for example,
things I didn't expect. Because a lot of this
was me trying to capture the inner worlds of these people based on my experiences with 'em. A lot of these are very
mysterious still to me, having treated many people
with these disorders. For example, there's a chapter on borderline personality disorder and there's a chapter on eating disorders. And these are very mysterious. Even to this day, I don't
claim to understand them, but I've seen many patients with them. I know psychiatry still
doesn't understand them in a fundamental way. But I knew something about these patients, and I was able to try to capture something about their state
in the best way I could. And from both sets of patients, borderline and eating disorder patients, I got spontaneous emails
from people, you know, thanking me for, you know, people saying that you've captured it better than I've heard anybody capture. And for me just to be able to share that, that was so important
to get because honestly, I didn't know. I was doing my best, but I didn't know. And for the people who
really were suffering to say that was, for me,
it made it all worthwhile, as hard as it was. - Fantastic. Well, I want to thank Karl Deisseroth for the last few minutes. That was the future of neuroscience. You've been listening to
"The Future Of Everything" with Russ Altman. If you enjoyed the
podcast, please subscribe. Please rate and review. We have more than 200
episodes in the back archives. Please listen to them. You can connect with me on
Twitter at @rbaltman, or X, or on Threads at @russbaltman. And you can follow Stanford
Engineering at @StanfordENG. Thank you.
(audience applauding)
