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  • 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.