0:00:00.545,0:00:04.077 I grew up watching Star Trek. I love Star Trek. 0:00:04.077,0:00:08.539 Star Trek made me want to see alien creatures, 0:00:08.539,0:00:10.842 creatures from a far-distant world. 0:00:10.842,0:00:13.629 But basically, I figured out that I could find 0:00:13.629,0:00:16.606 those alien creatures right on Earth. 0:00:16.606,0:00:19.259 And what I do is I study insects. 0:00:19.259,0:00:22.515 I'm obsessed with insects, particularly insect flight. 0:00:22.515,0:00:25.656 I think the evolution of insect flight is perhaps 0:00:25.656,0:00:28.398 one of the most important events in the history of life. 0:00:28.398,0:00:30.635 Without insects, there'd be no flowering plants. 0:00:30.635,0:00:32.551 Without flowering plants, there would be no 0:00:32.551,0:00:35.688 clever, fruit-eating primates giving TED Talks. 0:00:35.688,0:00:37.988 (Laughter) 0:00:37.988,0:00:39.975 Now, 0:00:39.975,0:00:43.014 David and Hidehiko and Ketaki 0:00:43.014,0:00:46.459 gave a very compelling story about 0:00:46.459,0:00:49.264 the similarities between fruit flies and humans, 0:00:49.264,0:00:50.753 and there are many similarities, 0:00:50.753,0:00:53.755 and so you might think that if humans are similar to fruit flies, 0:00:53.755,0:00:57.552 the favorite behavior of a fruit fly might be this, for example -- 0:00:57.552,0:00:59.834 (Laughter) 0:00:59.834,0:01:03.025 but in my talk, I don't want to emphasize on the similarities 0:01:03.025,0:01:06.092 between humans and fruit flies, but rather the differences, 0:01:06.092,0:01:11.379 and focus on the behaviors that I think fruit flies excel at doing. 0:01:11.379,0:01:14.235 And so I want to show you a high-speed video sequence 0:01:14.235,0:01:18.170 of a fly shot at 7,000 frames per second in infrared lighting, 0:01:18.170,0:01:22.380 and to the right, off-screen, is an electronic looming predator 0:01:22.380,0:01:23.815 that is going to go at the fly. 0:01:23.815,0:01:25.653 The fly is going to sense this predator. 0:01:25.653,0:01:28.108 It is going to extend its legs out. 0:01:28.108,0:01:29.721 It's going to sashay away 0:01:29.721,0:01:32.286 to live to fly another day. 0:01:32.286,0:01:34.648 Now I have carefully cropped this sequence 0:01:34.648,0:01:37.808 to be exactly the duration of a human eye blink, 0:01:37.808,0:01:40.642 so in the time that it would take you to blink your eye, 0:01:40.642,0:01:43.907 the fly has seen this looming predator, 0:01:43.907,0:01:50.075 estimated its position, initiated a motor pattern to fly it away, 0:01:50.075,0:01:54.539 beating its wings at 220 times a second as it does so. 0:01:54.539,0:01:56.512 I think this is a fascinating behavior 0:01:56.512,0:02:00.433 that shows how fast the fly's brain can process information. 0:02:00.433,0:02:03.275 Now, flight -- what does it take to fly? 0:02:03.275,0:02:06.139 Well, in order to fly, just as in a human aircraft, 0:02:06.139,0:02:08.874 you need wings that can generate sufficient aerodynamic forces, 0:02:08.874,0:02:12.420 you need an engine sufficient to generate the power required for flight, 0:02:12.420,0:02:14.129 and you need a controller, 0:02:14.129,0:02:16.755 and in the first human aircraft, the controller was basically 0:02:16.755,0:02:21.067 the brain of Orville and Wilbur sitting in the cockpit. 0:02:21.067,0:02:23.820 Now, how does this compare to a fly? 0:02:23.820,0:02:27.071 Well, I spent a lot of my early career trying to figure out 0:02:27.071,0:02:31.407 how insect wings generate enough force to keep the flies in the air. 0:02:31.407,0:02:33.017 And you might have heard how engineers proved 0:02:33.017,0:02:35.651 that bumblebees couldn't fly. 0:02:35.651,0:02:38.271 Well, the problem was in thinking that the insect wings 0:02:38.271,0:02:41.390 function in the way that aircraft wings work. But they don't. 0:02:41.390,0:02:44.244 And we tackle this problem by building giant, 0:02:44.244,0:02:47.676 dynamically scaled model robot insects 0:02:47.676,0:02:51.012 that would flap in giant pools of mineral oil 0:02:51.012,0:02:53.286 where we could study the aerodynamic forces. 0:02:53.286,0:02:55.444 And it turns out that the insects flap their wings 0:02:55.444,0:02:58.036 in a very clever way, at a very high angle of attack 0:02:58.036,0:03:01.157 that creates a structure at the leading edge of the wing, 0:03:01.157,0:03:04.356 a little tornado-like structure called a leading edge vortex, 0:03:04.356,0:03:07.310 and it's that vortex that actually enables the wings 0:03:07.310,0:03:10.669 to make enough force for the animal to stay in the air. 0:03:10.669,0:03:13.097 But the thing that's actually most -- so, what's fascinating 0:03:13.097,0:03:16.072 is not so much that the wing has some interesting morphology. 0:03:16.072,0:03:19.717 What's clever is the way the fly flaps it, 0:03:19.717,0:03:22.853 which of course ultimately is controlled by the nervous system, 0:03:22.853,0:03:25.500 and this is what enables flies to perform 0:03:25.500,0:03:28.307 these remarkable aerial maneuvers. 0:03:28.307,0:03:30.404 Now, what about the engine? 0:03:30.404,0:03:32.896 The engine of the fly is absolutely fascinating. 0:03:32.896,0:03:34.794 They have two types of flight muscle: 0:03:34.794,0:03:37.779 so-called power muscle, which is stretch-activated, 0:03:37.779,0:03:41.505 which means that it activates itself and does not need to be controlled 0:03:41.505,0:03:44.844 on a contraction-by-contraction basis by the nervous system. 0:03:44.844,0:03:49.453 It's specialized to generate the enormous power required for flight, 0:03:49.453,0:03:51.532 and it fills the middle portion of the fly, 0:03:51.532,0:03:53.079 so when a fly hits your windshield, 0:03:53.079,0:03:55.485 it's basically the power muscle that you're looking at. 0:03:55.485,0:03:57.631 But attached to the base of the wing 0:03:57.631,0:04:00.269 is a set of little, tiny control muscles 0:04:00.269,0:04:03.570 that are not very powerful at all, but they're very fast, 0:04:03.570,0:04:06.776 and they're able to reconfigure the hinge of the wing 0:04:06.776,0:04:08.538 on a stroke-by-stroke basis, 0:04:08.538,0:04:11.680 and this is what enables the fly to change its wing 0:04:11.680,0:04:14.651 and generate the changes in aerodynamic forces 0:04:14.651,0:04:17.224 which change its flight trajectory. 0:04:17.224,0:04:20.787 And of course, the role of the nervous system is to control all this. 0:04:20.787,0:04:22.299 So let's look at the controller. 0:04:22.299,0:04:24.946 Now flies excel in the sorts of sensors 0:04:24.946,0:04:27.230 that they carry to this problem. 0:04:27.230,0:04:31.357 They have antennae that sense odors and detect wind detection. 0:04:31.357,0:04:33.032 They have a sophisticated eye which is 0:04:33.032,0:04:35.488 the fastest visual system on the planet. 0:04:35.488,0:04:37.524 They have another set of eyes on the top of their head. 0:04:37.524,0:04:39.576 We have no idea what they do. 0:04:39.576,0:04:42.530 They have sensors on their wing. 0:04:42.530,0:04:46.290 Their wing is covered with sensors, including sensors 0:04:46.290,0:04:48.336 that sense deformation of the wing. 0:04:48.336,0:04:50.445 They can even taste with their wings. 0:04:50.445,0:04:53.000 One of the most sophisticated sensors a fly has 0:04:53.000,0:04:54.807 is a structure called the halteres. 0:04:54.807,0:04:56.686 The halteres are actually gyroscopes. 0:04:56.686,0:05:01.135 These devices beat back and forth about 200 hertz during flight, 0:05:01.135,0:05:03.808 and the animal can use them to sense its body rotation 0:05:03.808,0:05:07.776 and initiate very, very fast corrective maneuvers. 0:05:07.776,0:05:10.105 But all of this sensory information has to be processed 0:05:10.105,0:05:13.825 by a brain, and yes, indeed, flies have a brain, 0:05:13.825,0:05:16.984 a brain of about 100,000 neurons. 0:05:16.984,0:05:19.177 Now several people at this conference 0:05:19.177,0:05:23.985 have already suggested that fruit flies could serve neuroscience 0:05:23.985,0:05:27.232 because they're a simple model of brain function. 0:05:27.232,0:05:29.309 And the basic punchline of my talk is, 0:05:29.309,0:05:31.967 I'd like to turn that over on its head. 0:05:31.967,0:05:34.595 I don't think they're a simple model of anything. 0:05:34.595,0:05:37.072 And I think that flies are a great model. 0:05:37.072,0:05:39.588 They're a great model for flies. 0:05:39.588,0:05:42.069 (Laughter) 0:05:42.069,0:05:45.072 And let's explore this notion of simplicity. 0:05:45.072,0:05:47.503 So I think, unfortunately, a lot of neuroscientists, 0:05:47.503,0:05:49.335 we're all somewhat narcissistic. 0:05:49.335,0:05:52.768 When we think of brain, we of course imagine our own brain. 0:05:52.768,0:05:54.728 But remember that this kind of brain, 0:05:54.728,0:05:56.496 which is much, much smaller 0:05:56.496,0:05:59.174 — instead of 100 billion neurons, it has 100,000 neurons — 0:05:59.174,0:06:02.056 but this is the most common form of brain on the planet 0:06:02.056,0:06:04.960 and has been for 400 million years. 0:06:04.960,0:06:07.248 And is it fair to say that it's simple? 0:06:07.248,0:06:09.343 Well, it's simple in the sense that it has fewer neurons, 0:06:09.343,0:06:11.097 but is that a fair metric? 0:06:11.097,0:06:13.373 And I would propose it's not a fair metric. 0:06:13.373,0:06:16.473 So let's sort of think about this. I think we have to compare -- 0:06:16.473,0:06:18.032 (Laughter) — 0:06:18.032,0:06:23.153 we have to compare the size of the brain 0:06:23.153,0:06:25.183 with what the brain can do. 0:06:25.183,0:06:28.064 So I propose we have a Trump number, 0:06:28.064,0:06:30.929 and the Trump number is the ratio of this man's 0:06:30.929,0:06:34.608 behavioral repertoire to the number of neurons in his brain. 0:06:34.608,0:06:37.276 We'll calculate the Trump number for the fruit fly. 0:06:37.276,0:06:39.960 Now, how many people here think the Trump number 0:06:39.960,0:06:42.449 is higher for the fruit fly? 0:06:42.449,0:06:44.880 (Applause) 0:06:44.880,0:06:48.308 It's a very smart, smart audience. 0:06:48.308,0:06:51.635 Yes, the inequality goes in this direction, or I would posit it. 0:06:51.635,0:06:54.017 Now I realize that it is a little bit absurd 0:06:54.017,0:06:57.575 to compare the behavioral repertoire of a human to a fly. 0:06:57.575,0:07:01.718 But let's take another animal just as an example. Here's a mouse. 0:07:01.718,0:07:06.023 A mouse has about 1,000 times as many neurons as a fly. 0:07:06.023,0:07:08.050 I used to study mice. When I studied mice, 0:07:08.050,0:07:10.887 I used to talk really slowly. 0:07:10.887,0:07:13.463 And then something happened when I started to work on flies. 0:07:13.463,0:07:15.875 (Laughter) 0:07:15.875,0:07:19.335 And I think if you compare the natural history of flies and mice, 0:07:19.335,0:07:22.648 it's really comparable. They have to forage for food. 0:07:22.648,0:07:25.095 They have to engage in courtship. 0:07:25.095,0:07:28.566 They have sex. They hide from predators. 0:07:28.566,0:07:30.546 They do a lot of the similar things. 0:07:30.546,0:07:32.264 But I would argue that flies do more. 0:07:32.264,0:07:35.642 So for example, I'm going to show you a sequence, 0:07:35.642,0:07:39.847 and I have to say, some of my funding comes from the military, 0:07:39.847,0:07:41.919 so I'm showing this classified sequence 0:07:41.919,0:07:46.012 and you cannot discuss it outside of this room. Okay? 0:07:46.012,0:07:47.920 So I want you to look at the payload 0:07:47.920,0:07:50.946 at the tail of the fruit fly. 0:07:50.946,0:07:53.047 Watch it very closely, 0:07:53.047,0:07:57.344 and you'll see why my six-year-old son 0:07:57.344,0:08:02.073 now wants to be a neuroscientist. 0:08:02.073,0:08:03.252 Wait for it. 0:08:03.252,0:08:04.821 Pshhew. 0:08:04.821,0:08:07.905 So at least you'll admit that if fruit flies are not as clever as mice, 0:08:07.905,0:08:12.821 they're at least as clever as pigeons. (Laughter) 0:08:12.821,0:08:16.788 Now, I want to get across that it's not just a matter of numbers 0:08:16.788,0:08:19.386 but also the challenge for a fly to compute 0:08:19.386,0:08:22.235 everything its brain has to compute with such tiny neurons. 0:08:22.235,0:08:25.223 So this is a beautiful image of a visual interneuron from a mouse 0:08:25.223,0:08:27.991 that came from Jeff Lichtman's lab, 0:08:27.991,0:08:31.238 and you can see the wonderful images of brains 0:08:31.238,0:08:34.431 that he showed in his talk. 0:08:34.431,0:08:36.799 But up in the corner, in the right corner, you'll see, 0:08:36.799,0:08:40.911 at the same scale, a visual interneuron from a fly. 0:08:40.911,0:08:42.752 And I'll expand this up. 0:08:42.752,0:08:44.922 And it's a beautifully complex neuron. 0:08:44.922,0:08:48.407 It's just very, very tiny, and there's lots of biophysical challenges 0:08:48.407,0:08:52.030 with trying to compute information with tiny, tiny neurons. 0:08:52.030,0:08:55.567 How small can neurons get? Well, look at this interesting insect. 0:08:55.567,0:08:57.779 It looks sort of like a fly. It has wings, it has eyes, 0:08:57.779,0:09:00.578 it has antennae, its legs, complicated life history, 0:09:00.578,0:09:03.674 it's a parasite, it has to fly around and find caterpillars 0:09:03.674,0:09:05.056 to parasatize, 0:09:05.056,0:09:09.171 but not only is its brain the size of a salt grain, 0:09:09.171,0:09:11.140 which is comparable for a fruit fly, 0:09:11.140,0:09:14.066 it is the size of a salt grain. 0:09:14.066,0:09:17.701 So here's some other organisms at the similar scale. 0:09:17.701,0:09:21.831 This animal is the size of a paramecium and an amoeba, 0:09:21.831,0:09:25.711 and it has a brain of 7,000 neurons that's so small -- 0:09:25.711,0:09:28.167 you know these things called cell bodies you've been hearing about, 0:09:28.167,0:09:29.818 where the nucleus of the neuron is? 0:09:29.818,0:09:33.278 This animal gets rid of them because they take up too much space. 0:09:33.278,0:09:35.751 So this is a session on frontiers in neuroscience. 0:09:35.751,0:09:41.111 I would posit that one frontier in neuroscience is to figure out how the brain of that thing works. 0:09:41.111,0:09:46.744 But let's think about this. How can you make a small number of neurons do a lot? 0:09:46.744,0:09:49.266 And I think, from an engineering perspective, 0:09:49.266,0:09:50.995 you think of multiplexing. 0:09:50.995,0:09:53.698 You can take a hardware and have that hardware 0:09:53.698,0:09:55.311 do different things at different times, 0:09:55.311,0:09:58.306 or have different parts of the hardware doing different things. 0:09:58.306,0:10:01.577 And these are the two concepts I'd like to explore. 0:10:01.577,0:10:03.235 And they're not concepts that I've come up with, 0:10:03.235,0:10:07.780 but concepts that have been proposed by others in the past. 0:10:07.780,0:10:10.855 And one idea comes from lessons from chewing crabs. 0:10:10.855,0:10:12.722 And I don't mean chewing the crabs. 0:10:12.722,0:10:16.321 I grew up in Baltimore, and I chew crabs very, very well. 0:10:16.321,0:10:19.178 But I'm talking about the crabs actually doing the chewing. 0:10:19.178,0:10:21.208 Crab chewing is actually really fascinating. 0:10:21.208,0:10:24.467 Crabs have this complicated structure under their carapace 0:10:24.467,0:10:25.777 called the gastric mill 0:10:25.777,0:10:28.207 that grinds their food in a variety of different ways. 0:10:28.207,0:10:33.466 And here's an endoscopic movie of this structure. 0:10:33.466,0:10:36.026 The amazing thing about this is that it's controlled 0:10:36.026,0:10:39.458 by a really tiny set of neurons, about two dozen neurons 0:10:39.458,0:10:44.421 that can produce a vast variety of different motor patterns, 0:10:44.421,0:10:48.768 and the reason it can do this is that this little tiny ganglion 0:10:48.768,0:10:52.952 in the crab is actually inundated by many, many neuromodulators. 0:10:52.952,0:10:55.093 You heard about neuromodulators earlier. 0:10:55.093,0:10:57.318 There are more neuromodulators 0:10:57.318,0:11:02.803 that alter, that innervate this structure than actually neurons in the structure, 0:11:02.803,0:11:07.045 and they're able to generate a complicated set of patterns. 0:11:07.045,0:11:10.486 And this is the work by Eve Marder and her many colleagues 0:11:10.486,0:11:12.781 who've been studying this fascinating system 0:11:12.781,0:11:14.933 that show how a smaller cluster of neurons 0:11:14.933,0:11:16.758 can do many, many, many things 0:11:16.758,0:11:21.614 because of neuromodulation that can take place on a moment-by-moment basis. 0:11:21.614,0:11:24.053 So this is basically multiplexing in time. 0:11:24.053,0:11:26.838 Imagine a network of neurons with one neuromodulator. 0:11:26.838,0:11:30.316 You select one set of cells to perform one sort of behavior, 0:11:30.316,0:11:32.934 another neuromodulator, another set of cells, 0:11:32.934,0:11:34.647 a different pattern, and you can imagine 0:11:34.647,0:11:38.525 you could extrapolate to a very, very complicated system. 0:11:38.525,0:11:40.619 Is there any evidence that flies do this? 0:11:40.619,0:11:43.994 Well, for many years in my laboratory and other laboratories around the world, 0:11:43.994,0:11:46.642 we've been studying fly behaviors in little flight simulators. 0:11:46.642,0:11:48.348 You can tether a fly to a little stick. 0:11:48.348,0:11:50.849 You can measure the aerodynamic forces it's creating. 0:11:50.849,0:11:53.395 You can let the fly play a little video game 0:11:53.395,0:11:57.273 by letting it fly around in a visual display. 0:11:57.273,0:11:59.610 So let me show you a little tiny sequence of this. 0:11:59.610,0:12:00.837 Here's a fly 0:12:00.837,0:12:04.274 and a large infrared view of the fly in the flight simulator, 0:12:04.274,0:12:06.229 and this is a game the flies love to play. 0:12:06.229,0:12:08.666 You allow them to steer towards the little stripe, 0:12:08.666,0:12:11.491 and they'll just steer towards that stripe forever. 0:12:11.491,0:12:15.049 It's part of their visual guidance system. 0:12:15.049,0:12:17.394 But very, very recently, it's been possible 0:12:17.394,0:12:22.334 to modify these sorts of behavioral arenas for physiologies. 0:12:22.334,0:12:24.822 So this is the preparation that one of my former post-docs, 0:12:24.822,0:12:27.265 Gaby Maimon, who's now at Rockefeller, developed, 0:12:27.265,0:12:28.951 and it's basically a flight simulator 0:12:28.951,0:12:32.026 but under conditions where you actually can stick an electrode 0:12:32.026,0:12:34.290 in the brain of the fly and record 0:12:34.290,0:12:37.946 from a genetically identified neuron in the fly's brain. 0:12:37.946,0:12:40.244 And this is what one of these experiments looks like. 0:12:40.244,0:12:43.215 It was a sequence taken from another post-doc in the lab, 0:12:43.215,0:12:44.414 Bettina Schnell. 0:12:44.414,0:12:47.806 The green trace at the bottom is the membrane potential 0:12:47.806,0:12:49.836 of a neuron in the fly's brain, 0:12:49.836,0:12:52.778 and you'll see the fly start to fly, and the fly is actually 0:12:52.778,0:12:56.057 controlling the rotation of that visual pattern itself 0:12:56.057,0:12:57.536 by its own wing motion, 0:12:57.536,0:12:59.646 and you can see this visual interneuron 0:12:59.646,0:13:03.554 respond to the pattern of wing motion as the fly flies. 0:13:03.554,0:13:05.930 So for the first time we've actually been able to record 0:13:05.930,0:13:08.838 from neurons in the fly's brain while the fly 0:13:08.838,0:13:13.306 is performing sophisticated behaviors such as flight. 0:13:13.306,0:13:15.161 And one of the lessons we've been learning 0:13:15.161,0:13:17.581 is that the physiology of cells that we've been studying 0:13:17.581,0:13:20.002 for many years in quiescent flies 0:13:20.002,0:13:22.650 is not the same as the physiology of those cells 0:13:22.650,0:13:25.386 when the flies actually engage in active behaviors 0:13:25.386,0:13:27.925 like flying and walking and so forth. 0:13:27.925,0:13:30.850 And why is the physiology different? 0:13:30.850,0:13:32.907 Well it turns out it's these neuromodulators, 0:13:32.907,0:13:36.858 just like the neuromodulators in that little tiny ganglion in the crabs. 0:13:36.858,0:13:39.408 So here's a picture of the octopamine system. 0:13:39.408,0:13:41.162 Octopamine is a neuromodulator 0:13:41.162,0:13:45.498 that seems to play an important role in flight and other behaviors. 0:13:45.498,0:13:47.970 But this is just one of many neuromodulators 0:13:47.970,0:13:49.041 that's in the fly's brain. 0:13:49.041,0:13:51.707 So I really think that, as we learn more, 0:13:51.707,0:13:54.234 it's going to turn out that the whole fly brain 0:13:54.234,0:13:57.323 is just like a large version of this stomatogastric ganglion, 0:13:57.323,0:14:01.683 and that's one of the reasons why it can do so much with so few neurons. 0:14:01.683,0:14:04.470 Now, another idea, another way of multiplexing 0:14:04.470,0:14:06.126 is multiplexing in space, 0:14:06.126,0:14:07.820 having different parts of a neuron 0:14:07.820,0:14:09.942 do different things at the same time. 0:14:09.942,0:14:11.775 So here's two sort of canonical neurons 0:14:11.775,0:14:14.060 from a vertebrate and an invertebrate, 0:14:14.060,0:14:17.310 a human pyramidal neuron from Ramon y Cajal, 0:14:17.310,0:14:21.313 and another cell to the right, a non-spiking interneuron, 0:14:21.313,0:14:25.460 and this is the work of Alan Watson and Malcolm Burrows many years ago, 0:14:25.460,0:14:28.535 and Malcolm Burrows came up with a pretty interesting idea 0:14:28.535,0:14:31.417 based on the fact that this neuron from a locust 0:14:31.417,0:14:33.376 does not fire action potentials. 0:14:33.376,0:14:35.124 It's a non-spiking cell. 0:14:35.124,0:14:37.904 So a typical cell, like the neurons in our brain, 0:14:37.904,0:14:40.656 has a region called the dendrites that receives input, 0:14:40.656,0:14:43.245 and that input sums together 0:14:43.245,0:14:45.541 and will produce action potentials 0:14:45.541,0:14:47.872 that run down the axon and then activate 0:14:47.872,0:14:50.168 all the output regions of the neuron. 0:14:50.168,0:14:53.044 But non-spiking neurons are actually quite complicated 0:14:53.044,0:14:56.156 because they can have input synapses and output synapses 0:14:56.156,0:14:59.819 all interdigitated, and there's no single action potential 0:14:59.819,0:15:02.945 that drives all the outputs at the same time. 0:15:02.945,0:15:06.852 So there's a possibility that you have computational compartments 0:15:06.852,0:15:10.830 that allow the different parts of the neuron 0:15:10.830,0:15:13.390 to do different things at the same time. 0:15:13.390,0:15:18.061 So these basic concepts of multitasking in time 0:15:18.061,0:15:20.422 and multitasking in space, 0:15:20.422,0:15:23.254 I think these are things that are true in our brains as well, 0:15:23.254,0:15:25.831 but I think the insects are the true masters of this. 0:15:25.831,0:15:28.947 So I hope you think of insects a little bit differently next time, 0:15:28.947,0:15:31.882 and as I say up here, please think before you swat. 0:15:31.882,0:15:34.835 (Applause)