WEBVTT 00:00:00.359 --> 00:00:03.663 This is a thousand-year-old drawing of the brain. 00:00:03.663 --> 00:00:05.667 It's a diagram of the visual system. 00:00:05.667 --> 00:00:08.125 And some things look very familiar today. 00:00:08.125 --> 00:00:12.292 Two eyes at the bottom, optic nerve flowing out from the back. 00:00:12.292 --> 00:00:14.750 There's a very large nose 00:00:14.750 --> 00:00:17.667 that doesn't seem to be connected to anything in particular. NOTE Paragraph 00:00:17.667 --> 00:00:19.583 And if we compare this 00:00:19.583 --> 00:00:21.333 to more recent representations of the visual system, 00:00:21.333 --> 00:00:24.583 you'll see that things have gotten substantially more complicated 00:00:24.583 --> 00:00:27.125 over the intervening thousand years. 00:00:27.125 --> 00:00:28.875 And that's because today we can see what's inside of the brain, 00:00:28.875 --> 00:00:31.833 rather than just looking at its overall shape. NOTE Paragraph 00:00:31.833 --> 00:00:35.458 Imagine you wanted to understand how a computer works 00:00:35.458 --> 00:00:38.083 and all you could see was a keyboard, a mouse, a screen. 00:00:38.083 --> 00:00:42.125 You really would be kind of out of luck. 00:00:42.125 --> 00:00:44.167 You want to be able to open it up, crack it open, 00:00:44.167 --> 00:00:45.042 look at the wiring inside. 00:00:45.042 --> 00:00:47.875 And up until a little more than a century ago, 00:00:47.875 --> 00:00:49.875 nobody was able to do that with the brain. 00:00:49.875 --> 00:00:51.417 Nobody had had a glimpse of the brain's wiring. NOTE Paragraph 00:00:51.417 --> 00:00:54.292 And that's because if you take a brain out of the skull 00:00:54.292 --> 00:00:56.042 and you cut a thin slice of it, 00:00:56.042 --> 00:00:58.125 put it under a very powerful microscope, 00:00:58.125 --> 00:00:59.875 there's nothing there. 00:00:59.875 --> 00:01:00.750 It's gray, formless. 00:01:00.750 --> 00:01:04.292 There's no structure. It won't tell you anything. NOTE Paragraph 00:01:04.292 --> 00:01:06.208 And this all changed in the late 19th century. 00:01:06.208 --> 00:01:09.667 Suddenly, new chemical stains for brain tissue were developed 00:01:09.667 --> 00:01:13.833 and they gave us our first glimpses at brain wiring. 00:01:13.833 --> 00:01:15.000 The computer was cracked open. NOTE Paragraph 00:01:15.000 --> 00:01:17.333 So what really launched modern neuroscience 00:01:17.333 --> 00:01:20.667 was a stain called the Golgi stain. 00:01:20.667 --> 00:01:22.333 And it works in a very particular way. 00:01:22.333 --> 00:01:24.750 Instead of staining all of the cells inside of a tissue, 00:01:24.750 --> 00:01:27.306 it somehow only stains about one percent of them. 00:01:27.306 --> 00:01:31.017 It clears the forest, reveals the trees inside. 00:01:31.017 --> 00:01:34.042 If everything had been labeled, nothing would have been visible. 00:01:34.042 --> 00:01:36.750 So somehow it shows what's there. NOTE Paragraph 00:01:36.750 --> 00:01:39.417 Spanish neuroanatomist Santiago Ramon y Cajal, 00:01:39.417 --> 00:01:40.708 who's widely considered the father of modern neuroscience, 00:01:40.708 --> 00:01:44.667 applied this Golgi stain, which yields data which looks like this, 00:01:44.667 --> 00:01:49.917 and really gave us the modern notion of the nerve cell, the neuron. 00:01:49.917 --> 00:01:51.500 And if you're thinking of the brain as a computer, 00:01:51.500 --> 00:01:54.542 this is the transistor. 00:01:54.542 --> 00:01:55.417 And very quickly Cajal realized 00:01:55.417 --> 00:01:58.323 that neurons don't operate alone, 00:01:58.323 --> 00:02:00.792 but rather make connections with others 00:02:00.792 --> 00:02:03.298 that form circuits just like in a computer. 00:02:03.298 --> 00:02:04.458 Today, a century later, when researchers want to visualize neurons, 00:02:04.458 --> 00:02:08.625 they light them up from the inside rather than darkening them. 00:02:08.625 --> 00:02:10.375 And there's several ways of doing this. 00:02:10.375 --> 00:02:12.333 But one of the most popular ones 00:02:12.333 --> 00:02:13.917 involves green florescent protein. 00:02:13.917 --> 00:02:14.792 Now green florescent protein, 00:02:14.792 --> 00:02:17.167 which oddly enough comes from a bioluminescent jellyfish, 00:02:17.167 --> 00:02:18.765 is very useful. 00:02:18.765 --> 00:02:22.167 Because if you can get the gene for green florescent protein 00:02:22.167 --> 00:02:24.227 and deliver it to a cell, 00:02:24.227 --> 00:02:25.434 that cell will glow green -- 00:02:25.434 --> 00:02:30.273 or any of the many variants now of green florescent protein, 00:02:30.273 --> 00:02:31.937 you get a cell to glow many different colors. NOTE Paragraph 00:02:31.937 --> 00:02:33.458 And so coming back to the brain, 00:02:33.458 --> 00:02:36.750 this is from a genetically engineered mouse called Brainbow. 00:02:36.750 --> 00:02:38.208 And it's so called, of course, 00:02:38.208 --> 00:02:42.420 because all of these neurons are glowing different colors. NOTE Paragraph 00:02:42.420 --> 00:02:45.625 Now sometimes neuroscientists need to identify 00:02:45.625 --> 00:02:48.500 individual molecular components of neurons, molecules, 00:02:48.500 --> 00:02:50.375 rather than the entire cell. 00:02:50.375 --> 00:02:51.250 And there's several ways of doing this, 00:02:51.250 --> 00:02:52.125 but one of the most popular ones 00:02:52.125 --> 00:02:56.083 involves using antibodies. 00:02:56.083 --> 00:02:56.958 And you're familiar, of course, 00:02:56.958 --> 00:02:57.833 with antibodies and the henchmen of the immune system. 00:02:57.833 --> 00:03:01.958 But it turns out that they're so useful to the immune system 00:03:01.958 --> 00:03:03.708 because they can recognize specific molecules, 00:03:03.708 --> 00:03:07.458 like, for example, the code protein 00:03:07.458 --> 00:03:09.708 of a virus that's invading the body. 00:03:09.708 --> 00:03:10.583 And researchers have used this fact 00:03:10.583 --> 00:03:14.708 in order to recognize specific molecules inside of the brain, 00:03:14.708 --> 00:03:17.333 recognize specific substructures of the cell 00:03:17.333 --> 00:03:20.500 and identify them individually. NOTE Paragraph 00:03:20.500 --> 00:03:24.125 And a lot of the images I've been showing you here are very beautiful, 00:03:24.125 --> 00:03:25.000 but they're also very powerful. 00:03:25.000 --> 00:03:27.667 They have great explanatory power. 00:03:27.667 --> 00:03:28.542 This, for example, is an antibody staining 00:03:28.542 --> 00:03:33.277 against serotonin transporters in a slice of mouse brain. NOTE Paragraph 00:03:33.277 --> 00:03:33.958 And you've heard of serotonin, of course, 00:03:33.958 --> 00:03:36.708 in the context of diseases like depression and anxiety. 00:03:36.708 --> 00:03:37.583 You've heard of SSRI's, 00:03:37.583 --> 00:03:40.875 which are drugs that are used to treat these diseases. 00:03:40.875 --> 00:03:44.042 And in order to understand how serotonin works, 00:03:44.042 --> 00:03:47.625 it's critical to understand where the serontonin machinery is. 00:03:47.625 --> 00:03:49.375 And antibody staining like this one 00:03:49.375 --> 00:03:52.167 can be used to understand that sort of question. NOTE Paragraph 00:03:52.167 --> 00:03:54.125 I'd like to leave you with the following thought. 00:03:54.125 --> 00:03:57.566 Green florescent protein and antibodies 00:03:57.566 --> 00:03:58.958 are both totally natural products at the get-go. 00:03:58.958 --> 00:04:04.152 They were evolved by nature 00:04:04.152 --> 00:04:05.750 in order to get a jellyfish to glow green for whatever reason, 00:04:05.750 --> 00:04:09.917 or in order to detect the code protein of an invading virus, for example. 00:04:09.917 --> 00:04:12.750 And only much later did scientists come onto the scene 00:04:12.750 --> 00:04:13.250 and say, "Hey, these are tools, 00:04:13.250 --> 00:04:16.917 these are functions that we could use 00:04:16.917 --> 00:04:18.667 in our own research tool pallet." 00:04:18.667 --> 00:04:22.583 And instead of applying feeble human minds 00:04:22.583 --> 00:04:23.458 to designing these tools from scratch, 00:04:23.458 --> 00:04:26.833 there were these ready-made solutions right out there in nature 00:04:26.833 --> 00:04:30.500 developed and refined steadily for millions of years 00:04:30.500 --> 00:04:31.929 by the greatest engineer of all. 00:04:31.929 --> 00:04:34.000 Thank you. 00:04:34.000 --> 00:04:37.415 (Applause)