Subtitles section Play video Print subtitles 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.