Hi, I'm Whitney Espich, the CEO of the MIT Alumni Association and I hope
you enjoy this digital production created for alumni and friends like you.
MIT and alumni and friends who are just tuning in, welcome.
We're in our second of two tech day sessions
spotlighting four great MIT thinkers in today's program,
Geniuses and Game Changers.
If you missed our first speaker, note that all of these talks
will be available on the MIT Tech Review website.
You can take a look at them later.
If you have questions for our speakers today,
please use the Q&A feature on the Livestream page, where
you can also upload others that you would like to hear
answered.
So just click the thumbs up icon next to your favorites.
Please welcome now our second speaker, Ed Boyden,
class of '99 in MEng '99.
Ed is Professor of Biological Engineering in Brain
and Cognitive Sciences at the MIT Media Lab,
and is the McGovern Institute Y. Eva Tan
Professor of Neurotechnology.
You can read Ed's full bio on the Tech Reunions website.
Thank you and welcome, Ed.
Hello.
I'm going to start my screen sharing here.
The world of Zoom, right?
Great.
Well, it's really wonderful to talk to today.
I'm going to tell you a bit about where
the science of engineering the brain is headed.
I got interested in this, tangentially, a long time ago.
I was very philosophical as a kid,
and really wanted to understand the meaning of life.
What does it mean to be human.
And eventually, through a long and meandering path,
I ended up as an undergrad at MIT.
And was very interested in sciences
that bordered upon the philosophical
and the mysterious.
I ended up studying quantum computing a bit
when I was an undergrad and later a master's student.
And many years later I came back to MIT
to try to set up a group that would put together engineering
approaches to these mysteries of how to understand,
and also to repair, the brain.
So I've been trained as an engineer.
One of the first things that's always interesting
is, well, why is this system that we're trying to understand
and fix so hard to deal with?
And for the brain, I think there are
two features that make it really hard to understand and fix.
One is space and one is time.
So what do I mean by that?
Well, brain cells, neurons are gigantic cells
that can be centimeters in spatial extent.
But if you zoom in into the brain,
you see these tiny connections called
synapses that connect to cells.
And you see these tiny biomolecules,
nanometers in dimension.
The human genome has, what, 30,000 or so genes,
and all those gene products are nanoscale building blocks
organized with nanoscale precision.
So how can we help to understand such a thing?
And the other angle is time.
If you care about learning or Alzheimer's disease or aging,
these are processes that take years, even decades.
But the elementary building blocks of how the brain works
are these millisecond time-scale electrical events
within neurons, and these millisecond time-scale chemical
exchanges between neurons.
So how can we understand and repair
such a complex thing, from nano to centimeter, from millisecond
to decade?
Well, the answer that we proposed
was, well, we need to build tools to let us see and control
the brain across these very divergent scales.
If we could, maybe we could understand
how the brain generates things like thoughts and feelings.
And of course there are many practical implications
of this quest.
We're not just here to try to understand
the brain for its own sake, although I
think that's very important.
But there are also lots of urgent and pressing
medical needs.
Perhaps a billion people around the world
suffer from some kind of brain condition, addiction,
Alzheimer's disease, epilepsy.
List goes on and on.
My own grandmother has Alzheimer's.
And I think all of us, if we live long enough,
will encounter one of these, or a loved one will.
So what can we do about it?
Well, currently none of these conditions can be fully cured,
and the treatments are pretty partial.
And a lot of the treatments have side effects.
And I would argue that this is because
of the very same complexity that challenges us
for understanding the basic operation of the brain.
So today I want to tell you about two technological arenas
that we've been exploring, one about space and one about time.
And in both cases, I want to tell you
a little bit about how we go about thinking
about the problem.
Many research groups will specialize in a specific area,
like a certain kind of material, or a certain kind of device,
or certain kind of algorithm.
Their group tries to specialize in a way
of approaching problems as complex as the brain.
We try to think backwards from these problems,
and we survey all these different disciplines
of science and engineering, chemistry and physics,
electrical engineering, computer science,
and then we try to develop an invention that
confronts the spatial and temporal complexity
of the brain.
And then we try to deploy this technology
to help many people solve problems.
And then finally, we take these discoveries
and try to get them into the world.
So let's start with space.
How can we understand how brain cells are organized
into these vast networks?
And how these tiny nanoscale molecules
are organized into brain cells?
Well, I think we've all seen some brain scans, things that
look like this picture here.
This is an MRI scan, and you see these blobs,
or voxels as they're known, that light up.
And those are an indirect measure of neural activity.
They're measuring blood flow, not neural activity directly.
And furthermore, these blobs or voxels are pretty large.
They can contain millions or billions of brain cells.
And we know from basic neuroscience
that even two brain cells next to each other
can be doing very different things.
So of course, the advantage here is
it's non-invasive, but doesn't have the spatial precision that
gets down to these building blocks.
At the other extreme, are microscopes.
That's how brain cells were discovered in the first place
over a century ago.
But light has a finite size, or wavelength,
and you can't see things a lot smaller
than that wavelength, which happens to be a few nanometers.
Frustratingly close to where we want to be,
but about 100 times too course to see
individual nanoscale building blocks.
So we start thinking backwards from this problem.
How do you see across scales?
And we were inspired, actually, by a physicist at MIT, Toyoichi
Tanaka, who had been one of the pioneers
of the study of responsive polymers, smart gels.
So in this cartoon is little animation
of the kind of polymer you might find in a baby diaper.
You add water, and the polymer threads,
shown as little white lines, swell apart from each other
as you absorb the water, an experiment that millions
of kids do every day.
Now, this is very practical if you want to absorb liquid
in a baby diaper.
And it's also been used for a lot
of other interesting problems, like drug delivery.
But we started wondering, what if you could chemically
weave this dense spider web like mesh
of baby diaper like polymer throughout a brain
cell, or even an entire brain.
Could you weave this dense spider web like mesh
so it went around biomolecules and between biomolecules?
If you could do that just right, then when you add water,
the swelling of the polymer should actually physically make
the brain bigger.
This is very different from how people imaged stuff
for hundreds of years.
You zoom in with a lens and the light is magnified.
But here we actually want to magnify the object itself.
So that's a basic question.
Can we install this polymer spider web
like mesh of baby diaper material
around and inside cells and tissues densely and evenly.
So getting to the punch line, to our surprise actually,
this is kind of a cool discovery in a way, we could do that.
In panel B in the top middle of the slide
is a small piece of the brain of a mouse, one
of the most common species used in neuroscience.
And in panel C on the right is the same piece of mouse brain
tissue, let's say about a day and a half later,
and we physically modified it by about 100 times
in volume, about 4 and 1/2 fold in each direction.
And the left hand side are some sketches
of what the polymer might look like when it's densely
winding its way around the brain cells, inside the brain cells,
between the biomolecules, and around the biomolecules.
And the lower left is when it's swollen with water,
but of course it's pushing the brain bigger as well.
Here's a little time lapse movie that I'll show you,
which hopefully will show you an actual piece
of brain growing before your very eyes.
This movie is sped up by about 50 folds,
so the whole process takes more like an hour than a minute.
And we just added the water there.
So this piece of brain had had the baby diaper
polymer, sodium polyacrylate for the aficionados,
synthesized throughout the brain earlier.
And then we added water, and I hope
you can see that this piece of brain tissue
is growing right as you watch.
So I'm sure it's only a matter of time
before a Hollywood screenwriter makes a horror movie out
of this.
But of course, what do we want to do with it?
Well, we want to understand how the brain works.
Now importantly, this expansion process is very, very even.
We're turning a cell like the one on the left
into a cell like the one on the right.
Remember those nanoscales biomolecules I told you about?
We're pulling them apart with nanoscale precision,
so that the biomolecules are like a constellation of stars
hovering in space, but with their relative organization,
meaning the biological information, preserved.
That means that what we have is basically
a large replica of the brain, physically much larger,
but with all the biological information locked in place.
So of course this won't work on a living brain,
but it will allow us to magnify reserve tissues.
And so here's a piece of the brain
of a mouse that's involved with, amongst other processes,
memories.
These cells are expressing different fluorescent proteins.
These are proteins from jellyfish and coral
and other critters that glow.
And we expanded this piece of brain tissue.
And I hope you can see here, is we can actually
see the fine wires of the brain, those nanoscale conduits
of electricity that I mentioned earlier.
So our hope is someday, maybe in the coming years,
we could be able to make maps of the brain
so detailed that we could actually
try to look at the circuitry.
How is information flowing and being transformed by the brain?
Could you someday have a map of the brain so detailed
that you could try to simulate things like decisions
and feelings?
Now as I mentioned earlier, we also
try to deploy these inventions and help people use them.
And so one of the things that people talked to us about
was about detecting diseases early.
How do you do that?
Well, early in a disease the changes are really subtle.
And so what we realized is that if we physically magnified
a tissue like this breast cancer biopsy you see in the movie
here, in the image here, maybe we
could take those tiny invisible changes
and make them large and obvious.
And so we collaborated with a bunch of doctors
from different institutions, and found that we could actually
do early disease detection.
We could take a piece of tissue from a human patient,
magnify it, and turn the early invisible changes of a disease
into big obvious ones.
So it gives you an example of how we are inventing,
we're making discoveries, and then
we are designing and deploying these into the world.
So that short story's about space.
Now I'm going to tell you one short story about time.
As mentioned earlier, brain cells
use these high speed electrical events to compute.
How can we actually understand them?
Well one idea is, what if you could control individual brain
cells?
Now there are many ways to do that.
You can use electricity, for example.
Or you could try to use pharmacology.
But those are not very precise.
And so we started wondering, could you actually
control brain cells with lights?
How would you do that?
Well, suppose you could install a little solar panel in a brain
cell.
The solar panels convert light to electricity.
The brain cells compute using electricity.
We could then control brain cells with light.
Now you can also get light into the brain.
The brain doesn't feel pain, so you can bring light
in with an optical fiber.
If you could do this, you could turn brain cells on or off,
and see what they do.
Then the question became, how do you make
those little tiny solar panels?
It turns out that all over the tree of life
you can find organisms like this single-celled green algae that
contain photoreceptors, molecules that convert light
into electrical signals.
So green algae swim around in bodies of water.
And we can actually take a small protein
called an opsin, which converts light into electrical signals.
And these are found in a tiny part of the algae called an eye
spot.
This small molecule converts light into electrical signals.
And here's where we got lucky.
A lot of serendipity plays a role in neuroscience,
and here we got really lucky that this is a protein encoded
for by a small snippet of DNA.
So what does that mean?
Well, it means you can take the small snippet of DNA,
transplant it into a gene therapy vector or a virus,
and of course gene therapies are actually already
in use in humans.
So this is something where we can build off
of a different field.
We can take that small snippet of DNA,
put it into a gene therapy vector or a virus,
much like the kind that are approved for use in humans,
and deliver that gene therapy vector into a living brain.
So this is all currently being used
to study the brain in animals, although a few people are
doing human trials for conditions like blindness.
Although the data is still being collected.
Anyway we got really, really lucky here.
Brain cells, we found, would take up these viruses
and manufacture these proteins from algae
and other small critters.
And amazingly, this is a sheer dumb luck, when
we shine light on the brain cells,
those proteins would allow light to be
converted into those tiny electrical signals.
And we could then actually activate cells in the brain,
and make them do what we want.
So this is very cool.
We can activate brain cells and drive them,
and have them trigger changes in the brain.
And we can see whether those changes could trigger
a behavior, or a computation, or maybe whether you
could actually drive a pattern of activity that could overcome
a brain disease condition.
So one thing we did of course, as I mentioned, is we
invented a tool, and then we deployed to many people
and help them use it.
And Li-Huei Tsai's group at MIT used this tool
to activate one kind of cell in the brain,
these little star-shaped cells called interneurons.
If you put this molecule from algae
into the interneurons using a gene therapy vector that's
carefully designed, then you shine light, blue light
in this case, it'll activate just those cells and not
their neighbors.
Their group went on to make a really stunning discovery.
They used mice that are engineered to develop
Alzheimer's-like symptoms, and they found that if you activate
these brain cells at a special frequency, 40 times a second,
these brains actually got better.
They would clean up the molecular pathology
of Alzheimer's.
And this is really incredible, right?
Because Alzheimer's again, is one
of those diseases for which we have no cure and really
no treatments that can stop the disease.
The teams went on, under Li-Huei's leadership,
to also find that you could deliver
this brainwave, this special frequency pattern,
without using our technology.
So they used our technology to make their initial discovery,
but went on to show that you could use just our eyes
and ears to deliver these brainwave patterns
into the brain.
So they took these mice that have Alzheimer's-like symptoms,
and they would just exposed them to a flickering light
or clicking sound, and these animals would get better.
So we're actually are now doing human trials of flickering
lights and clicking sounds with actual Alzheimer's patients.
So I gave you two examples today, one about space
and one about time, about how we tried
to invent new tools that get to fundamental scientific insights
about how the brain works.
We can help people make discoveries
about how the brain works or can be repaired.
And then we try to help design practical implementations that
can get out into the world, whether it's
for early detection of cancer, or in the project that Li-Huei
is leading, ways to potentially treat Alzheimer's disease.
And I think that really illustrates a take home message
here, which is, when you have a problem as complex
as the brain, whether it's understanding or repairing it,
you need to bring together every parts of the sciences
and engineering disciplines to confront it.
And this slide is really dense and too many
people listed on it to read out loud,
but I just wanted to end on this note,
that you hear a lot about interdisciplinary research
right now, bringing two fields together.
Neurotechnology is becoming an omni-disciplinary science.
We need every part of the sciences and engineering
disciplines to work together, if we really
want to understand and repair the brain.
So stay in touch.
We're very excited to always let out new problems to work on,
and help people use tools to solve it.
Thanks for joining us and for more information on how to connect
with the MIT Alumni Association please visit our website.