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