What well learn about the brain in the next century Sam Rodriques
I want to tell you guys
something about neuroscience.
I’m a physicist by training.
About three years ago, I left physics
to come and try to understand
how the brain works.
And this is what I found.
Lots of people are working on depression.
And that’s really good,
depression is something
that we really want to understand.
Here’s how you do it:
you take a jar and you fill it up,
about halfway, with water.
And then you take a mouse,
and you put the mouse in the jar, OK?
And the mouse swims around
for a little while
and then at some point,
the mouse gets tired
and decides to stop swimming.
And when it stops swimming,
that’s depression.
OK?
And I’m from theoretical physics,
so I’m used to people making
very sophisticated mathematical models
to precisely describe physical phenomena,
so when I saw that this
is the model for depression,
I though to myself, “Oh my God,
we have a lot of work to do.”
(Laughter)
But this is a kind of general
problem in neuroscience.
So for example, take emotion.
Lots of people want to understand emotion.
But you can’t study emotion
in mice or monkeys
because you can’t ask them
how they’re feeling
or what they’re experiencing.
So instead, people who want
to understand emotion,
typically end up studying
what’s called motivated behavior,
which is code for “what the mouse does
when it really, really wants cheese.”
OK, I could go on and on.
I mean, the point is, the NIH
spends about 5.5 billion dollars a year
on neuroscience research.
And yet there have been almost
no significant improvements in outcomes
for patients with brain diseases
in the past 40 years.
And I think a lot of that
is basically due to the fact
that mice might be OK as a model
for cancer or diabetes,
but the mouse brain
is just not sophisticated enough
to reproduce human psychology
or human brain disease.
OK?
So if the mouse models are so bad,
why are we still using them?
Well, it basically boils down to this:
the brain is made up of neurons
which are these little cells that send
electrical signals to each other.
If you want to understand
how the brain works,
you have to be able to measure
the electrical activity of these neurons.
But to do that, you have to get
really close to the neurons
with some kind of electrical
recording device or a microscope.
And so you can do that in mice
and you can do it in monkeys,
because you can physically
put things into their brain
but for some reason we still
can’t do that in humans, OK?
So instead, we’ve invented
all these proxies.
So the most popular one is probably this,
functional MRI, fMRI,
which allows you to make these
pretty pictures like this,
that show which parts
of your brain light up
when you’re engaged
in different activities.
But this is a proxy.
You’re not actually measuring
neural activity here.
What you’re doing
is you’re measuring, essentially,
like, blood flow in the brain.
Where there’s more blood.
It’s actually where there’s more oxygen,
but you get the idea, OK?
The other thing that you can do
is you can do this –
electroencephalography – you can put
these electrodes on your head, OK?
And then you can measure your brain waves.
And here, you’re actually measuring
electrical activity.
But you’re not measuring
the activity of neurons.
You’re measuring
these electrical currents,
sloshing back and forth in your brain.
So the point is just
that these technologies that we have
are really measuring the wrong thing.
Because, for most of the diseases
that we want to understand –
like, Parkinson’s is the classic example.
In Parkinson’s, there’s one particular
kind of neuron deep in your brain
that is responsible for the disease,
and these technologies just don’t have
the resolution that you need
to get at that.
And so that’s why
we’re still stuck with the animals.
Not that anyone wants
to be studying depression
by putting mice into jars, right?
It’s just that there’s this pervasive
sense that it’s not possible
to look at the activity of neurons
in healthy humans.
So here’s what I want to do.
I want to take you into the future.
To have a look at one way in which
I think it could potentially be possible.
And I want to preface this by saying,
I don’t have all the details.
So I’m just going to provide you
with a kind of outline.
But we’re going to go the year 2100.
Now what does the year 2100 look like?
Well, to start with, the climate
is a bit warmer that what you’re used to.
(Laughter)
And that robotic vacuum cleaner
that you know and love
went through a few generations,
and the improvements
were not always so good.
(Laughter)
It was not always for the better.
But actually, in the year 2100
most things are surprisingly recognizable.
It’s just the brain is totally different.
For example, in the year 2100,
we understand the root causes
of Alzheimer’s.
So we can deliver targeted
genetic therapies or drugs
to stop the degenerative process
before it begins.
So how did we do it?
Well, there were essentially three steps.
The first step was
that we had to figure out
some way to get electrical
connections through the skull
so we could measure
the electrical activity of neurons.
And not only that,
it had to be easy and risk-free.
Something that basically anyone
would be OK with,
like getting a piercing.
Because back in 2017,
the only way that we knew of
to get through the skull
was to drill these holes
the size of quarters.
You would never let
someone do that to you.
So in the 2020s,
people began to experiment –
rather than drilling these gigantic holes,
drilling microscopic holes,
no thicker than a piece of hair.
And the idea here
was really for diagnosis –
there are lots of times in the diagnosis
of brain disorders
when you would like to be able to look
at the neural activity beneath the skull
and being able to drill
these microscopic holes
would make that much easier
for the patient.
In the end, it would be
like getting a shot.
You just go in and you sit down
and there’s a thing
that comes down on your head,
and a momentary sting and then it’s done,
and you can go back about your day.
So we’re eventually able to do it
using lasers to drill the holes.
And with the lasers,
it was fast and extremely reliable,
you couldn’t even tell
the holes were there,
any more than you could tell
that one of your hairs was missing.
And I know it might sound crazy,
using lasers to drill holes in your skull,
but back in 2017,
people were OK with surgeons
shooting lasers into their eyes
for corrective surgery
So when you’re already here,
it’s not that big of a step.
OK?
So the next step,
that happened in the 2030s,
was that it’s not just about
getting through the skull.
To measure the activity of neurons,
you have to actually make it
into the brain tissue itself.
And the risk, whenever
you put something into the brain tissue,
is essentially that of stroke.
That you would hit
a blood vessel and burst it,
and that causes a stroke.
So, by the mid 2030s,
we had invented these flexible probes
that were capable of going
around blood vessels,
rather than through them.
And thus, we could put
huge batteries of these probes
into the brains of patients
and record from thousands of their neurons
without any risk to them.
And what we discovered,
sort of to our surprise,
is that the neurons that we could identify
were not responding
to things like ideas or emotion,
which was what we had expected.
They were mostly responding
to things like Jennifer Aniston
or Halle Berry
or Justin Trudeau.
I mean –
(Laughter)
In hindsight, we shouldn’t
have been that surprised.
I mean, what do your neurons
spend most of their time thinking about?
(Laughter)
But really, the point is that
this technology enabled us to begin
studying neuroscience in individuals.
So much like the transition to genetics,
at the single cell level,
we started to study neuroscience,
at the single human level.
But we weren’t quite there yet.
Because these technologies
were still restricted
to medical applications,
which meant that we were studying
sick brains, not healthy brains.
Because no matter how safe
your technology is,
you can’t stick something
into someone’s brain
for research purposes.
They have to want it.
And why would they want it?
Because as soon as you have
an electrical connection to the brain,
you can use it to hook
the brain up to a computer.
Oh, well, you know, the general public
was very skeptical at first.
I mean, who wants to hook
their brain up to their computers?
Well just imagine being able
to send an email with a thought.
(Laughter)
Imagine being able to take
a picture with your eyes, OK?
(Laughter)
Imagine never forgetting anything anymore,
because anything
that you choose to remember
will be stored permanently
on a hard drive somewhere,
able to be recalled at will.
(Laughter)
The line here
between crazy and visionary
was never quite clear.
But the systems were safe.
So when the FDA decided to deregulate
these laser-drilling systems, in 2043,
commercial demand just exploded.
People started signing their emails,
“Please excuse any typos.
Sent from my brain.”
(Laughter)
Commercial systems
popped up left and right,
offering the latest and greatest
in neural interfacing technology.
There were 100 electrodes.
A thousand electrodes.
High bandwidth for only 99.99 a month.
(Laughter)
Soon, everyone had them.
And that was the key.
Because, in the 2050s,
if you were a neuroscientist,
you could have someone come into your lab
essentially from off the street.
And you could have them engaged
in some emotional task
or social behavior or abstract reasoning,
things you could never study in mice.
And you could record
the activity of their neurons
using the interfaces
that they already had.
And then you could also ask them
about what they were experiencing.
So this link between
psychology and neuroscience
that you could never make
in the animals, was suddenly there.
So perhaps the classic example of this
was the discovery
of the neural basis for insight.
That “Aha!” moment, the moment
it all comes together, it clicks.
And this was discovered
by two scientists in 2055,
Barry and Late,
who observed, in the dorsal
prefrontal cortex,
how in the brain of someone
trying to understand an idea,
how different populations of neurons
would reorganize themselves –
you’re looking at neural
activity here in orange –
until finally their activity aligns
in a way that leads to positive feedback.
Right there.
That is understanding.
So finally, we were able to get
at the things that make us human.
And that’s what really opened the way
to major insights from medicine.
Because, starting in the 2060s,
with the ability to record
the neural activity
in the brains of patients
with these different mental diseases,
rather than defining the diseases
on the basis of their symptoms,
as we had at the beginning of the century,
we started to define them
on the basis of the actual pathology
that we observed at the neural level.
So for example, in the case of ADHD,
we discovered that there are
dozens of different diseases,
all of which had been called ADHD
at the start of the century,
that actually had nothing
to do with each other,
except that they had similar symptoms.
And they needed to be treated
in different ways.
So it was kind of incredible,
in retrospect,
that at the beginning of the century,
we had been treating
all those different diseases
with the same drug,
just by giving people amphetamine,
basically is what we were doing.
And schizophrenia and depression
are the same way.
So rather than prescribing drugs to people
essentially at random,
as we had,
we learned how to predict
which drugs would be most effective
in which patients,
and that just led to this huge
improvement in outcomes.
OK, I want to bring you back now
to the year 2017.
Some of this may sound satirical
or even far fetched.
And some of it is.
I mean, I can’t actually
see into the future.
I don’t actually know
if we’re going to be drilling hundreds
or thousands of microscopic holes
in our heads in 30 years.
But what I can tell you
is that we’re not going
to make any progress
towards understanding the human brain
or human diseases
until we figure out how to get
at the electrical activity of neurons
in healthy humans.
And almost no one is working
on figuring out how to do that today.
That is the future of neuroscience.
And I think it’s time for neuroscientists
to put down the mouse brain
and to dedicate the thought
and investment necessary
to understand the human brain
and human disease.
Thank you.
(Applause)