I grew up watching Star Trek. I love Star Trek. Star Trek made me want to see alien creatures, creatures from a far-distant world. But basically, I figured out that I could find those alien creatures right on Earth.
我看著《星際爭霸戰》長大。 我超愛《星際爭霸戰》。 《星際爭霸戰》讓我想要看外星生物, 從遙遠星球來的生物。 但事實上,我發現我可以在地球上 找到這些外星生物。
And what I do is I study insects. I'm obsessed with insects, particularly insect flight. I think the evolution of insect flight is perhaps one of the most important events in the history of life. Without insects, there'd be no flowering plants. Without flowering plants, there would be no clever, fruit-eating primates giving TED Talks.
我所作的就是研究昆蟲。 我迷上了昆蟲, 尤其是昆蟲飛行。 我認為昆蟲飛行的演化 大概是生命史上最重要的事。 如果沒有昆蟲, 就不會有開花植物。 沒有開花植物, 就不會有聰明、 吃水果的靈長類在TED演講。
(Laughter)
(笑聲)
Now, David and Hidehiko and Ketaki gave a very compelling story about the similarities between fruit flies and humans, and there are many similarities, and so you might think that if humans are similar to fruit flies, the favorite behavior of a fruit fly might be this, for example -- (Laughter) but in my talk, I don't want to emphasize on the similarities between humans and fruit flies, but rather the differences, and focus on the behaviors that I think fruit flies excel at doing.
現在, 大衛、希地可和科踏希 說了一個很令人信服的故事, 故事關於果蠅與人的相似處。 我們真的有許多相似之處, 所以你也許會認為 如果人跟果蠅是相似的, 那麼果蠅最喜歡的行為可能是這個 (笑聲) 但在我的演講中, 我不想強調果蠅與人的相似之處, 我反而要談兩者間不同的部份, 而且我要強調果蠅擅長的行為。
And so I want to show you a high-speed video sequence of a fly shot at 7,000 frames per second in infrared lighting, and to the right, off-screen, is an electronic looming predator that is going to go at the fly. The fly is going to sense this predator. It is going to extend its legs out. It's going to sashay away to live to fly another day. Now I have carefully cropped this sequence to be exactly the duration of a human eye blink, so in the time that it would take you to blink your eye, the fly has seen this looming predator, estimated its position, initiated a motor pattern to fly it away, beating its wings at 220 times a second as it does so. I think this is a fascinating behavior that shows how fast the fly's brain can process information.
所以我想要給你們看一段高速影片, 是在紅外光照明下 以每秒 7 千幅拍攝果蠅飛行的影片, 在右邊螢幕外, 有個電子虛擬獵食者 會飛去捕食果蠅。 果蠅會感受到這個獵食者。 牠會伸長它的腿。 牠會以搖曳生姿飛走 然後多活一天。 我仔細裁剪了這個影片 讓他的速度跟 人類眨眼速度一樣, 所以在你眨眼所需要的時間中, 果蠅會看到這個獵食者、 估計位置、開始運動並飛走, 以每秒拍動翅膀 220 次的速度飛走。 我認為這是一個令人著迷的行為, 這表示果蠅的大腦 可以如此快速地處理資訊。
Now, flight -- what does it take to fly? Well, in order to fly, just as in a human aircraft, you need wings that can generate sufficient aerodynamic forces, you need an engine sufficient to generate the power required for flight, and you need a controller, and in the first human aircraft, the controller was basically the brain of Orville and Wilbur sitting in the cockpit.
飛行需要什麼? 嗯,要能夠飛翔, 就得像人類的飛機一樣, 你需要可以產生 足夠空氣動力的翅膀, 你需要能夠產生 足夠飛行所需能量的發動機, 且你需要一個控制器。 在人類第一架飛機上,控制器基本上是 坐在駕駛艙的奧維爾和威爾伯的大腦。
Now, how does this compare to a fly? Well, I spent a lot of my early career trying to figure out how insect wings generate enough force to keep the flies in the air. And you might have heard how engineers proved that bumblebees couldn't fly. Well, the problem was in thinking that the insect wings function in the way that aircraft wings work. But they don't. And we tackle this problem by building giant, dynamically scaled model robot insects that would flap in giant pools of mineral oil where we could study the aerodynamic forces. And it turns out that the insects flap their wings in a very clever way, at a very high angle of attack that creates a structure at the leading edge of the wing, a little tornado-like structure called a leading edge vortex, and it's that vortex that actually enables the wings to make enough force for the animal to stay in the air. But the thing that's actually most -- so, what's fascinating is not so much that the wing has some interesting morphology. What's clever is the way the fly flaps it, which of course ultimately is controlled by the nervous system, and this is what enables flies to perform these remarkable aerial maneuvers.
這跟果蠅比較起來是如何呢? 嗯,我早期的研究 花了很多時間試圖找出 昆蟲翅膀如何生成 足夠的能量使果蠅得以維持在空中。 你也許聽說過工程師如何證明 熊蜂飛不起來。 嗯,這個思考邏輯的問題是 認為兩者翅膀的運作方式一樣。 但事實上不然。 我們研究的方法是建造巨大模型, 按動態比例建造巨大機器昆蟲 並在礦物油巨型池當中拍打翅膀, 這樣我們可以研究空氣動力。 我們發現昆蟲以 一種非常聰明的方法拍動翅膀, 有非常大的攻角, 使翅膀前沿產生一個像龍捲風的結構 叫作前緣渦, 而且正是這個翅膀上的前緣渦 讓動物能夠產生足以停留在空中的動力。 但是實際上迷人的 並不是這個構造有多稀奇。 而是聰明的果蠅如何拍打它, 這當然最終是 受中樞神經系統控制, 而這也是果蠅可以執行 這些高超飛行技巧的原因。
Now, what about the engine? The engine of the fly is absolutely fascinating. They have two types of flight muscle: so-called power muscle, which is stretch-activated, which means that it activates itself and does not need to be controlled on a contraction-by-contraction basis by the nervous system. It's specialized to generate the enormous power required for flight, and it fills the middle portion of the fly, so when a fly hits your windshield, it's basically the power muscle that you're looking at. But attached to the base of the wing is a set of little, tiny control muscles that are not very powerful at all, but they're very fast, and they're able to reconfigure the hinge of the wing on a stroke-by-stroke basis, and this is what enables the fly to change its wing and generate the changes in aerodynamic forces which change its flight trajectory. And of course, the role of the nervous system is to control all this.
那麼引擎呢? 果蠅的引擎絕對令人著迷。 牠們有兩種類型的飛行肌: 所謂的能量肌肉,這是牽張啟動, 也就是說它可以自我啟動 不需要中樞神經 不斷收縮來控制。 這是由飛行所需 巨大的力量所專一化出來的, 這肌肉充滿了果蠅中間的部分, 所以當一隻果蠅撞到你的擋風玻璃時, 基本上你看到的 就是這些能量肌肉的動作。 但在機翼的基部 有一套小小的微型控制肌肉, 它們不大有力但速度非常快, 它們能夠以每一拍擊為基礎 重新配置機翼轉軸, 這使果蠅得以調整翅膀 來產生及更改空氣動力, 並連帶改變其飛行軌跡。 當然,中樞神經系統控制這一切。
So let's look at the controller. Now flies excel in the sorts of sensors that they carry to this problem. They have antennae that sense odors and detect wind detection. They have a sophisticated eye which is the fastest visual system on the planet. They have another set of eyes on the top of their head. We have no idea what they do. They have sensors on their wing. Their wing is covered with sensors, including sensors that sense deformation of the wing. They can even taste with their wings. One of the most sophisticated sensors a fly has is a structure called the halteres. The halteres are actually gyroscopes. These devices beat back and forth about 200 hertz during flight, and the animal can use them to sense its body rotation and initiate very, very fast corrective maneuvers. But all of this sensory information has to be processed by a brain, and yes, indeed, flies have a brain, a brain of about 100,000 neurons.
所以讓我們來看看控制器。 果蠅在這方面 有各種非常精巧的感應器。 牠們有天線可以感受氣味和風向。 牠們有複雜的眼睛, 是這個星球上最快的視覺系統。 牠們在頭頂上有另一對眼睛, 但目前我們還不清楚它們的用處。 牠們的翅膀上有感應器。 牠們的翅耪上充滿了感應器, 包括感應機翼變形的感應器。 牠們甚至可以 用翅膀偵測味道。 果蠅最複雜的感應器之一 是一種被稱為「平衡棒」的構造。 平衡棒其實就是陀螺儀。 這個構造在飛行時 大約以 200 赫茲的速度擺動 使動物可以用它們偵測身體旋轉, 並啟動非常、非常快速地糾正動作。 但所有感官資訊 都需要經由大腦處理, 是的,果蠅有大腦的, 一個大約有 10 萬神經元的大腦。
Now several people at this conference have already suggested that fruit flies could serve neuroscience because they're a simple model of brain function. And the basic punchline of my talk is, I'd like to turn that over on its head. I don't think they're a simple model of anything. And I think that flies are a great model. They're a great model for flies. (Laughter)
已經有一些人在這次會議中 提出果蠅可以作為神經科學的模型, 因為牠們具有簡單的大腦。 然後我的演講的結語會是: 我想要直接反駁它。 我不認為牠們是任何東西的簡單模型。 我認為果蠅是一個偉大的模型。 牠們是為飛行而生的偉大模型。 (笑聲)
And let's explore this notion of simplicity. So I think, unfortunately, a lot of neuroscientists, we're all somewhat narcissistic. When we think of brain, we of course imagine our own brain. But remember that this kind of brain, which is much, much smaller — instead of 100 billion neurons, it has 100,000 neurons — but this is the most common form of brain on the planet and has been for 400 million years. And is it fair to say that it's simple? Well, it's simple in the sense that it has fewer neurons, but is that a fair metric? And I would propose it's not a fair metric. So let's sort of think about this. I think we have to compare -- (Laughter) — we have to compare the size of the brain with what the brain can do. So I propose we have a Trump number, and the Trump number is the ratio of this man's behavioral repertoire to the number of neurons in his brain. We'll calculate the Trump number for the fruit fly. Now, how many people here think the Trump number is higher for the fruit fly?
且讓我們研究一下這種簡單的想法。 所以我認為很多的神經學家 都不幸地有些自戀。 當我們想到大腦時, 我們當然想自己的大腦。 但請記住這種腦, 體積小很多很多的腦 — 它沒有 1 千億神經元,它只有 1 萬神經元 — 但這是這個星球上最常見的大腦形式 而且已經存在 4 億年了。 說它簡單公平嗎? 嗯,以神經元數量來說是簡單的, 但這是一個公平的指標嗎? 我認為這不是一個公平的指標。 讓我們來想一想。 我們必須進行比較 —— (笑聲) —— 我們要比較大腦大小 與大腦可以做什麼。 假設我們有王牌數, 王牌數是這個男人可以做的事 跟大腦中神經元數目的比值。 我們也可以計算出果蠅的王牌號。 現在,有多少人在這裡覺得果蠅的 王牌數會比較高?
(Applause)
(掌聲)
It's a very smart, smart audience. Yes, the inequality goes in this direction, or I would posit it.
真是很聰明、很聰明的觀眾。 雖然這比較不完全恰當, 但至少我認為是這樣的。
Now I realize that it is a little bit absurd to compare the behavioral repertoire of a human to a fly. But let's take another animal just as an example. Here's a mouse. A mouse has about 1,000 times as many neurons as a fly. I used to study mice. When I studied mice, I used to talk really slowly. And then something happened when I started to work on flies. (Laughter) And I think if you compare the natural history of flies and mice, it's really comparable. They have to forage for food. They have to engage in courtship. They have sex. They hide from predators. They do a lot of the similar things. But I would argue that flies do more. So for example, I'm going to show you a sequence, and I have to say, some of my funding comes from the military, so I'm showing this classified sequence and you cannot discuss it outside of this room. Okay? So I want you to look at the payload at the tail of the fruit fly. Watch it very closely, and you'll see why my six-year-old son now wants to be a neuroscientist. Wait for it. Pshhew. So at least you'll admit that if fruit flies are not as clever as mice, they're at least as clever as pigeons. (Laughter)
好,我知道比較人和果蠅的行為 是有點荒謬。 但讓我們看另一種動物:一隻小鼠。 一隻小鼠的神經元數目大約是果蠅的 1 千倍。 我以前研究過小鼠。 當我還在研究小鼠時, 我講話速度慢很多。 這在當我開始研究果蠅時產生了變化。 (笑聲) 我覺得如果你比較果蠅和小鼠的自然史, 它們是可比的。 牠們都要覓食。 牠們都要求愛。 牠們都會發生性關係。 牠們都要躲避獵食者。 牠們做很多類似的事情。 但我想說果蠅做更多。 例如,我要給你們看一段影片, 我不得不說, 我的一些資金來源來自軍方, 所以,我給你們這部機密影片, 請你們離開這裡後必須絕口不提。好嗎? 所以想要你們看看果蠅尾巴 的有效載荷。 仔細看, 你們會懂為什麼我的六歲兒子 現在想要成為一個神經學家。 等一下。 噓。 所以至少你們得承認, 如果果蠅沒有小鼠聰明, 牠們至少達到鴿子的等級。 (笑聲)
Now, I want to get across that it's not just a matter of numbers but also the challenge for a fly to compute everything its brain has to compute with such tiny neurons. So this is a beautiful image of a visual interneuron from a mouse that came from Jeff Lichtman's lab, and you can see the wonderful images of brains that he showed in his talk. But up in the corner, in the right corner, you'll see, at the same scale, a visual interneuron from a fly. And I'll expand this up. And it's a beautifully complex neuron. It's just very, very tiny, and there's lots of biophysical challenges with trying to compute information with tiny, tiny neurons.
現在,我想要傳達的不只是數字, 還有果蠅大腦要用少量神經元 計算這所有資訊所面臨的挑戰。 這是小鼠視覺中間神經元的美麗影像, 這來自傑夫·歷之曼的實驗室, 你們可以看到他在他的演講中 使用的精彩大腦影像。 在右上角你們將看到, 在同樣的比例之下 一隻果蠅的視覺中間神經元。 我把這展開。 它是一個精美複雜的神經元。 它真是非常、 非常地小, 這必須克服許多生物物理的挑戰, 才能用極為微小的神經元來計算資訊。
How small can neurons get? Well, look at this interesting insect. It looks sort of like a fly. It has wings, it has eyes, it has antennae, its legs, complicated life history, it's a parasite, it has to fly around and find caterpillars to parasatize, but not only is its brain the size of a salt grain, which is comparable for a fruit fly, it is the size of a salt grain. So here's some other organisms at the similar scale. This animal is the size of a paramecium and an amoeba, and it has a brain of 7,000 neurons that's so small -- you know these things called cell bodies you've been hearing about, where the nucleus of the neuron is? This animal gets rid of them because they take up too much space. So this is a session on frontiers in neuroscience. I would posit that one frontier in neuroscience is to figure out how the brain of that thing works.
神經元能有多小? 那麼,讓我們看看這個有趣的昆蟲。 牠看起來有點像果蠅。牠有翅膀,牠有眼睛, 牠有天線,牠有腿, 也有複雜的生活史。 牠是一種寄生蟲, 牠要到處飛,並尋找毛毛蟲 當作寄主, 牠的大腦很小, 跟果蠅可相比較, 它也只有鹽粒大小。 所以這裡是一些其它類似規模的物種。 這個動物是草履蟲和變形蟲大小, 牠的大腦大約有 7 千神經元 — 你知道有種叫做細胞體的東西, 就是神經元的細胞核所在的地方? 這種動物沒有細胞體, 因為它們太佔空間了。 這是神經科學研究的新領域。 我認為神經科學其中 一個新領域就是要研究這類大腦的運作。
But let's think about this. How can you make a small number of neurons do a lot? And I think, from an engineering perspective, you think of multiplexing. You can take a hardware and have that hardware do different things at different times, or have different parts of the hardware doing different things. And these are the two concepts I'd like to explore. And they're not concepts that I've come up with, but concepts that have been proposed by others in the past.
但讓我們想一想。 如何讓少量的神經元做很多事? 我認為,從工程的角度看, 要多功能。 你們可以拿一個硬體,並用該硬體 在不同的時間做不同的事情 或用不同部分的硬體做不同的事情。 這些是我想要探討的兩個概念。 但不是我想出來的概念, 而是過去由其他人提出的概念。
And one idea comes from lessons from chewing crabs. And I don't mean chewing the crabs. I grew up in Baltimore, and I chew crabs very, very well. But I'm talking about the crabs actually doing the chewing. Crab chewing is actually really fascinating. Crabs have this complicated structure under their carapace called the gastric mill that grinds their food in a variety of different ways. And here's an endoscopic movie of this structure. The amazing thing about this is that it's controlled by a really tiny set of neurons, about two dozen neurons that can produce a vast variety of different motor patterns, and the reason it can do this is that this little tiny ganglion in the crab is actually inundated by many, many neuromodulators. You heard about neuromodulators earlier. There are more neuromodulators that alter, that innervate this structure than actually neurons in the structure, and they're able to generate a complicated set of patterns. And this is the work by Eve Marder and her many colleagues who've been studying this fascinating system that show how a smaller cluster of neurons can do many, many, many things because of neuromodulation that can take place on a moment-by-moment basis. So this is basically multiplexing in time. Imagine a network of neurons with one neuromodulator. You select one set of cells to perform one sort of behavior, another neuromodulator, another set of cells, a different pattern, and you can imagine you could extrapolate to a very, very complicated system.
一個想法是來自於咀嚼螃蟹的經驗。 我不是指吃螃蟹。 我在巴爾的摩長大, 我非常、非常會吃螃蟹。 但我說的螃蟹的咀嚼。 螃蟹的咀嚼實在令人著迷。 螃蟹在其甲殼下有個複雜的結構 叫作胃磨機, 以各種不同方式磨牠們的食物。 而這是內鏡下看到的這種結構的影片。 令人驚訝的是它是由一組非常小的神經元控制, 約有 20 多個神經元可以 產生多種不同的運動模式, 它可以這樣做的原因 是這個螃蟹身上的小小神經節 實際上是被許多 神經調節物質所包圍。 你們剛剛已經聽過神經調節物質了。 這個結構中可以改變、支配神經元的 神經調節物質比 構造中的神經元還多, 且它們能夠生成複雜的模式。 這是由伊娃·碼德和 她許多同事們的研究, 他們研究這個有趣的系統, 可以說明一小群神經元如何 可以做很多、 很多、 很多的事情, 由於神經調節可以時時刻刻地進行。 所以這基本上是時間復用。 想像一個只有一個神經調節物質的神經網絡。 你選擇一組細胞執行一個行為、 另一個神經調節物質、另一組細胞、 另一種模式,你可以想像 你可以推到一個非常、 非常複雜的系統。
Is there any evidence that flies do this? Well, for many years in my laboratory and other laboratories around the world, we've been studying fly behaviors in little flight simulators. You can tether a fly to a little stick. You can measure the aerodynamic forces it's creating. You can let the fly play a little video game by letting it fly around in a visual display. So let me show you a little tiny sequence of this. Here's a fly and a large infrared view of the fly in the flight simulator, and this is a game the flies love to play. You allow them to steer towards the little stripe, and they'll just steer towards that stripe forever. It's part of their visual guidance system. But very, very recently, it's been possible to modify these sorts of behavioral arenas for physiologies. So this is the preparation that one of my former post-docs, Gaby Maimon, who's now at Rockefeller, developed, and it's basically a flight simulator but under conditions where you actually can stick an electrode in the brain of the fly and record from a genetically identified neuron in the fly's brain. And this is what one of these experiments looks like. It was a sequence taken from another post-doc in the lab, Bettina Schnell. The green trace at the bottom is the membrane potential of a neuron in the fly's brain, and you'll see the fly start to fly, and the fly is actually controlling the rotation of that visual pattern itself by its own wing motion, and you can see this visual interneuron respond to the pattern of wing motion as the fly flies. So for the first time we've actually been able to record from neurons in the fly's brain while the fly is performing sophisticated behaviors such as flight. And one of the lessons we've been learning is that the physiology of cells that we've been studying for many years in quiescent flies is not the same as the physiology of those cells when the flies actually engage in active behaviors like flying and walking and so forth. And why is the physiology different? Well it turns out it's these neuromodulators, just like the neuromodulators in that little tiny ganglion in the crabs. So here's a picture of the octopamine system. Octopamine is a neuromodulator that seems to play an important role in flight and other behaviors. But this is just one of many neuromodulators that's in the fly's brain. So I really think that, as we learn more, it's going to turn out that the whole fly brain is just like a large version of this stomatogastric ganglion, and that's one of the reasons why it can do so much with so few neurons.
有任何證據說果蠅這麼做嗎? 嗯,多年來在我和其它世界各地實驗室, 我們在研究微小飛行模擬器的飛行行為。 你可以將果蠅綁到小棒子上。 你可以側量牠產生的空氣動力。 你可以讓果蠅玩個小遊戲, 讓牠在視覺影像間飛行。 讓我給你們看一個小小的影片。 這裡是一隻果蠅 和一個大型飛行模擬的紅外視圖 和這個果蠅喜歡玩的遊戲。 你允許牠們飛向小條紋, 牠們就會一直飛向那區。 這是牠們視覺引導的一部份。 但最近,已經可以藉由改變生理 來改變行為的範疇。 這是我之前一個博士後研究員的作法, 蓋柏·買夢,他現在洛克菲勒, 他建造這個基本上是一種飛行模擬器, 在實驗中你可以把電極置入 果蠅大腦中 並從一個已被辨別基因的神經元中紀錄。 這實驗看起來像這樣。 這是另一個 博士後研究員貝蒂娜·靴諾 的實驗影片。 在底部的綠色是果蠅腦內的 一個神經元的膜電位。 你們將看到果蠅開始飛, 且果蠅是靠自身翅膀運動來控制 視覺模式中的旋轉。 你們可以看到這個視覺中間神經元 對果蠅翅膀運動作出回應。 所以我們第一次實際記錄 果蠅執行像是飛行這樣的複雜行為時 腦內的神經元狀況。 我們一直在學習的是 我們多年來在靜止果蠅身上 研究到的細胞生理 與正在做一些像是 飛行或行走等主動行為時的 果蠅細胞生理是不同的。 為什麼細胞生理會不同呢? 事實是就是這些神經調節物質, 就像是在螃蟹神經節上 的神經調節物質一樣。 這是章魚涎胺系統的圖片。 章魚涎胺是一種神經調節物質, 它似乎在飛行和其他行為中具有重要的功用。 但這只是果蠅大腦裡多種 神經調節物質的一種而已。 所以我真的認為,當我們瞭解更多後, 我們會發現整個果蠅大腦 就像這個放大版本的胃腸神經節, 這就是牠可以用 少量神經元執行大量功能的原因之一。
Now, another idea, another way of multiplexing is multiplexing in space, having different parts of a neuron do different things at the same time. So here's two sort of canonical neurons from a vertebrate and an invertebrate, a human pyramidal neuron from Ramon y Cajal, and another cell to the right, a non-spiking interneuron, and this is the work of Alan Watson and Malcolm Burrows many years ago, and Malcolm Burrows came up with a pretty interesting idea based on the fact that this neuron from a locust does not fire action potentials. It's a non-spiking cell. So a typical cell, like the neurons in our brain, has a region called the dendrites that receives input, and that input sums together and will produce action potentials that run down the axon and then activate all the output regions of the neuron. But non-spiking neurons are actually quite complicated because they can have input synapses and output synapses all interdigitated, and there's no single action potential that drives all the outputs at the same time. So there's a possibility that you have computational compartments that allow the different parts of the neuron to do different things at the same time.
現在,另一個想法,另一種多工的方式 是在空間上的多工, 讓神經元的不同部分 在同一時間做不同的事情。 所以這裡是兩種典型的神經元排列, 一個是脊椎動物、 另一個是無脊椎動物, 從拉蒙·卡哈身上來的人類錐體神經元 和在右側的細胞是 無動作電位中間神經元, 這是很多年前, 艾倫 · 華生和瑪律科姆 · 巴路士的研究, 瑪律科姆 · 巴路士有一個很有趣的想法 是基於這個來自於蝗蟲的神經元 不會觸發動作電位。 它是一個無動作電位細胞。 所以一個典型的細胞, 像我們的大腦中的神經元, 有個叫作樹突的部份會接收訊號, 這些訊號加總在一起 會產生動作電位, 這個電位會透過軸突傳遞然後 啓動輸出區域的所有神經元。 但無動作電位神經元其實是相當複雜, 因為它們輸入突觸和輸出突觸合而為一, 但卻沒有單一的動作電位 可以在同一時間產生輸出。 所以你有可能有不同的計算區域 使神經元的不同部分 在同一時間做不同的事情。
So these basic concepts of multitasking in time and multitasking in space, I think these are things that are true in our brains as well, but I think the insects are the true masters of this. So I hope you think of insects a little bit differently next time, and as I say up here, please think before you swat.
這些基本的在時間上、 空間上的多工處理, 我認為在我們的大腦中也成立, 但我認為昆蟲才是真正的行家。 所以,我希望你能對昆蟲另眼相看, 正如我所說: 在打牠前請記得想想牠的神奇之處。
(Applause)
(掌聲)