1 00:00:00,359 --> 00:00:04,355 This is a thousand-year-old drawing of the brain. 2 00:00:04,355 --> 00:00:06,267 It's a diagram of the visual system. 3 00:00:06,267 --> 00:00:09,017 And some things look very familiar today. 4 00:00:09,017 --> 00:00:13,384 Two eyes at the bottom, optic nerve flowing out from the back. 5 00:00:13,384 --> 00:00:15,504 There's a very large nose 6 00:00:15,504 --> 00:00:18,821 that doesn't seem to be connected to anything in particular. 7 00:00:18,821 --> 00:00:20,521 And if we compare this 8 00:00:20,521 --> 00:00:22,595 to more recent representations of the visual system, 9 00:00:22,595 --> 00:00:25,552 you'll see that things have gotten substantially more complicated 10 00:00:25,552 --> 00:00:27,125 over the intervening thousand years. 11 00:00:27,125 --> 00:00:30,090 And that's because today we can see what's inside of the brain, 12 00:00:30,090 --> 00:00:32,571 rather than just looking at its overall shape. 13 00:00:32,571 --> 00:00:36,550 Imagine you wanted to understand how a computer works 14 00:00:36,550 --> 00:00:39,729 and all you could see was a keyboard, a mouse, a screen. 15 00:00:39,729 --> 00:00:42,125 You really would be kind of out of luck. 16 00:00:42,125 --> 00:00:44,167 You want to be able to open it up, crack it open, 17 00:00:44,167 --> 00:00:46,011 look at the wiring inside. 18 00:00:46,011 --> 00:00:47,875 And up until a little more than a century ago, 19 00:00:47,875 --> 00:00:49,875 nobody was able to do that with the brain. 20 00:00:49,875 --> 00:00:51,755 Nobody had had a glimpse of the brain's wiring. 21 00:00:51,755 --> 00:00:54,707 And that's because if you take a brain out of the skull 22 00:00:54,707 --> 00:00:56,396 and you cut a thin slice of it, 23 00:00:56,396 --> 00:00:58,894 put it under even a very powerful microscope, 24 00:00:58,894 --> 00:01:00,075 there's nothing there. 25 00:01:00,075 --> 00:01:01,688 It's gray, formless. 26 00:01:01,688 --> 00:01:04,292 There's no structure. It won't tell you anything. 27 00:01:04,292 --> 00:01:07,146 And this all changed in the late 19th century. 28 00:01:07,146 --> 00:01:11,021 Suddenly, new chemical stains for brain tissue were developed 29 00:01:11,021 --> 00:01:13,833 and they gave us our first glimpses at brain wiring. 30 00:01:13,833 --> 00:01:15,846 The computer was cracked open. 31 00:01:15,846 --> 00:01:18,702 So what really launched modern neuroscience 32 00:01:18,702 --> 00:01:20,667 was a stain called the Golgi stain. 33 00:01:20,667 --> 00:01:22,548 And it works in a very particular way. 34 00:01:22,548 --> 00:01:25,658 Instead of staining all of the cells inside of a tissue, 35 00:01:25,658 --> 00:01:28,690 it somehow only stains about one percent of them. 36 00:01:28,690 --> 00:01:32,032 It clears the forest, reveals the trees inside. 37 00:01:32,032 --> 00:01:34,704 If everything had been labeled, nothing would have been visible. 38 00:01:34,704 --> 00:01:36,750 So somehow it shows what's there. 39 00:01:36,750 --> 00:01:39,417 Spanish neuroanatomist Santiago Ramon y Cajal, 40 00:01:39,417 --> 00:01:42,262 who's widely considered the father of modern neuroscience, 41 00:01:42,262 --> 00:01:46,159 applied this Golgi stain, which yields data which looks like this, 42 00:01:46,159 --> 00:01:49,917 and really gave us the modern notion of the nerve cell, the neuron. 43 00:01:49,917 --> 00:01:52,531 And if you're thinking of the brain as a computer, 44 00:01:52,531 --> 00:01:54,542 this is the transistor. 45 00:01:54,542 --> 00:01:56,617 And very quickly Cajal realized 46 00:01:56,617 --> 00:01:58,954 that neurons don't operate alone, 47 00:01:58,954 --> 00:02:00,792 but rather make connections with others 48 00:02:00,792 --> 00:02:03,298 that form circuits just like in a computer. 49 00:02:03,298 --> 00:02:06,689 Today, a century later, when researchers want to visualize neurons, 50 00:02:06,689 --> 00:02:09,456 they light them up from the inside rather than darkening them. 51 00:02:09,456 --> 00:02:10,606 And there's several ways of doing this. 52 00:02:10,606 --> 00:02:12,333 But one of the most popular ones 53 00:02:12,333 --> 00:02:14,425 involves green fluorescent protein. 54 00:02:14,425 --> 00:02:16,084 Now green fluorescent protein, 55 00:02:16,084 --> 00:02:19,229 which oddly enough comes from a bioluminescent jellyfish, 56 00:02:19,229 --> 00:02:20,467 is very useful. 57 00:02:20,467 --> 00:02:23,105 Because if you can get the gene for green fluorescent protein 58 00:02:23,105 --> 00:02:24,780 and deliver it to a cell, 59 00:02:24,780 --> 00:02:26,527 that cell will glow green -- 60 00:02:26,527 --> 00:02:30,273 or any of the many variants now of green fluorescent protein, 61 00:02:30,273 --> 00:02:31,937 you get a cell to glow many different colors. 62 00:02:31,937 --> 00:02:33,458 And so coming back to the brain, 63 00:02:33,458 --> 00:02:37,258 this is from a genetically engineered mouse called "Brainbow." 64 00:02:37,258 --> 00:02:38,808 And it's so called, of course, 65 00:02:38,808 --> 00:02:42,420 because all of these neurons are glowing different colors. 66 00:02:42,420 --> 00:02:45,871 Now sometimes neuroscientists need to identify 67 00:02:45,871 --> 00:02:48,915 individual molecular components of neurons, molecules, 68 00:02:48,915 --> 00:02:50,713 rather than the entire cell. 69 00:02:50,713 --> 00:02:52,419 And there's several ways of doing this, 70 00:02:52,419 --> 00:02:53,888 but one of the most popular ones 71 00:02:53,888 --> 00:02:56,083 involves using antibodies. 72 00:02:56,083 --> 00:02:57,420 And you're familiar, of course, 73 00:02:57,420 --> 00:03:00,371 with antibodies as the henchmen of the immune system. 74 00:03:00,371 --> 00:03:02,789 But it turns out that they're so useful to the immune system 75 00:03:02,789 --> 00:03:05,339 because they can recognize specific molecules, 76 00:03:05,339 --> 00:03:07,458 like, for example, the coat protein 77 00:03:07,458 --> 00:03:09,846 of a virus that's invading the body. 78 00:03:09,846 --> 00:03:11,891 And researchers have used this fact 79 00:03:11,891 --> 00:03:16,216 in order to recognize specific molecules inside of the brain, 80 00:03:16,216 --> 00:03:18,856 recognize specific substructures of the cell 81 00:03:18,856 --> 00:03:21,100 and identify them individually. 82 00:03:21,100 --> 00:03:24,125 And a lot of the images I've been showing you here are very beautiful, 83 00:03:24,125 --> 00:03:26,031 but they're also very powerful. 84 00:03:26,031 --> 00:03:27,667 They have great explanatory power. 85 00:03:27,667 --> 00:03:29,757 This, for example, is an antibody staining 86 00:03:29,757 --> 00:03:33,277 against serotonin transporters in a slice of mouse brain. 87 00:03:33,277 --> 00:03:34,958 And you've heard of serotonin, of course, 88 00:03:34,958 --> 00:03:37,785 in the context of diseases like depression and anxiety. 89 00:03:37,785 --> 00:03:39,193 You've heard of SSRIs, 90 00:03:39,193 --> 00:03:42,090 which are drugs that are used to treat these diseases. 91 00:03:42,090 --> 00:03:44,980 And in order to understand how serotonin works, 92 00:03:44,980 --> 00:03:48,056 it's critical to understand where the serontonin machinery is. 93 00:03:48,056 --> 00:03:49,652 And antibody stainings like this one 94 00:03:49,652 --> 00:03:53,198 can be used to understand that sort of question. 95 00:03:53,198 --> 00:03:55,756 I'd like to leave you with the following thought: 96 00:03:55,756 --> 00:03:58,366 Green fluorescent protein and antibodies 97 00:03:58,366 --> 00:04:01,373 are both totally natural products at the get-go. 98 00:04:01,373 --> 00:04:04,152 They were evolved by nature 99 00:04:04,152 --> 00:04:06,719 in order to get a jellyfish to glow green for whatever reason, 100 00:04:06,719 --> 00:04:11,102 or in order to detect the coat protein of an invading virus, for example. 101 00:04:11,102 --> 00:04:14,119 And only much later did scientists come onto the scene 102 00:04:14,119 --> 00:04:16,142 and say, "Hey, these are tools, 103 00:04:16,142 --> 00:04:18,255 these are functions that we could use 104 00:04:18,255 --> 00:04:20,263 in our own research tool palette." 105 00:04:20,263 --> 00:04:23,891 And instead of applying feeble human minds 106 00:04:23,891 --> 00:04:25,775 to designing these tools from scratch, 107 00:04:25,775 --> 00:04:28,679 there were these ready-made solutions right out there in nature 108 00:04:28,679 --> 00:04:31,915 developed and refined steadily for millions of years 109 00:04:31,915 --> 00:04:33,615 by the greatest engineer of all. 110 00:04:33,615 --> 00:04:34,877 Thank you. 111 00:04:34,877 --> 00:04:37,415 (Applause)