Following is the full transcript of neuroengineer Sam Rodriques’ TED Talk titled “What We’ll Learn About the Brain in the Next Century.”
Listen to the MP3 audio while reading the transcript:
Sam Rodriques – Neuroengineer
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. I mean 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 thought to myself, “Oh my God, we have a lot of work to do.”
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 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.