How a fly flies Michael Dickinson

I grew up watching Star Trek I love Star

Trek Star Trek wanted me it 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 and what

I do is I study insects I’m obsessed

with insects particularly insect flight

I think the I think the evolution of

insect flight is perhaps one of the most

important events in the history of life

without insects there be no flowering

plants without flowering plants there

would be no clever of fruit eating

primates giving TED talks now David and

he Co and kotaki 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 might be this for example but

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 and so I want

to show you a high-speed video sequence

of a fly shot at 7,000 frames per second

and 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 human eye blinks

and the time that it would take you to

blink your eye the fly has has seen this

this looming predator estimated its

position it initiated a 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

now 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 for

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 that the brain of Orville and

Wilbur I’m sitting in the cockpit 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 that that bumble

bees couldn’t fly well the problem was

in thinking that the insect wings

function the way that aircraft wings

work but they don’t and and we tackled

this problem by building giant

dynamically scaled model robot insects

that would flap in in giant pools of

mineral oil where we could study the

aerodynamic forces and it turns out that

the insects flapped 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 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 wing that the fly rather

flaps it which of course ultimately is

controlled by the the nervous system and

this is what enables flies to perform

these remarkable aerial maneuvers now

what about the engine the engine of the

flies 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 specialized to

generate the 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 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 the changes and

aerodynamic forces which change its its

flight trajectory and of course the role

of the nervous system is to control all

this 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 a sensors on their on their their

wing the wing is covered with with

sensors including sensors that sense the

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 hall tears the hall

tears 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 the sensory

information has to be processed by a

brain and yes indeed flies have a brain

a brain of about a hundred thousand

neurons 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 and let’s let’s explore 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 a

hundred billion neurons it has a hundred

thousand 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 we have to compare

the size of the brain with what the

brain can true can do so I propose we

have a trump number and the Trump number

is the ratio of of this man’s behavioral

repertoire to the number of neurons in

his brain will calculate the Trump

number for the fruit fly now how many

people here think the Trump number is

higher for the for the fruit fly it’s

it’s a very smart smart audience yes the

inequality goes in this direction or I

would posit it now I realized that it is

a little bit absurd to compare the

behavioral repertoire of a human to a

fly but let’s take take another animal

just as an example here’s that here’s a

mouse a mouse has about a thousand times

as many neurons as a fly I used to study

mice when I study mice I used to talk

really slowly and then something

happened when I started to work on flies

and I think if you compare if you

compare it the natural history of flies

and mice it’s really comparable they

have to forage for food they have to

engage in courtship they they they they

have sex they hide from predators they

do a lot of the similar things but but I

would argue that flies do more so for

example I’m going to show you a sequence

so they 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 ok 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

so at least you’ll admit that if fruit

flies are not as clever as mice they’re

at least as clever as pigeons now I want

to get across that it’s not just a

matter of numbers but but also the

challenge for a fly to compute

everything that brain has to compute

with such tiny neurons so this is a

beautiful image of a visual interneuron

from a mouse that came from from Jeff

Lichtman a lab and you could see that

the wonderful images of brains that he

showed in his in his talk but up in the

corner in the right corner you’ll see at

the same scale of 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 how small can neurons get well

look at this interesting insect it looks

sort of like a fly it has wings that has

eyes it has antennae its legs

complicated life history it’s a parasite

it has to fly around and find

caterpillars to parasitize but not only

is its brain the size of a salt brain

which is comparable for a fruit fly it

is the size of a salt brain

so a salt brain 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 a front

one frontier in neuroscience is to

figure out how the brain of that thing

works but let’s think about this how can

you make a small number of neurons do a

lot and I think if 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 and and one idea

comes from lessons from chewing crabs

and I don’t mean chewing the crabs and I

I grew up in Baltimore and I chew crabs

very very well but I’m talking about the

crabs I

like 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 of this this this 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 the this little

tiny ganglion in the crab is actually

inundated by many many neuromodulators

you heard about neuromodulators earlier

they’re more neuromodulators that that

alter that that innervate this structure

then actually neurons in the structure

and they’re able to generate a

complicated set set of patterns and this

is the work by yves martyr and her many

colleagues who’ve been studying this

fascinating system that show how a small

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

and 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 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 and 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 ply it fly play a little video

game by letting it fly around and in a

visual display so let me show you a

little tiny sequence of this here’s a

fly and enlarged infrared view of the

fly in the flight simulator and this is

the game the Flies love to play you

allow them to steer towards a 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

physiology so this is the preparation

that one of my former postdocs gabby

Mayman who’s now at Rockefeller

developed and it’s basically a flight

simulator but under conditions where you

actually can stick and elect

in the brain of the fly and record from

a genetically I identified neuron in the

fly’s brain and this is what one of

these experiments looks like it was a

sequence taken from another postdoc 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 flies 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 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 engaged in active

behaviors like flying and walking and so

forth and why is the the physiology

different well it turns out it’s these

neuromodulators just like the

neuromodulators in that little tiny

ganglion in the crab so here’s a picture

of the october immune system octo

commune as 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 we

learn more it’s going to turn out that

the whole fly brain is just like a large

version of the stomatogastric ganglion

and that’s one of the reasons why it can

do so much with so few neurons

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 invertebrate a

human pyramidal neuron from rimoni cahal

and and another a cell to the right a

non spiking inner neuron 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 somes

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 inter

digitated and there’s no single action

potential that drives all the the

outputs at the same time so there’s a

possibility that you have computational

compartments that allow the different

different neurons to do different of

different parts of the neuron to do

different things at the same time so

these basic concepts of of multitasking

and time a multitask 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

you

我是看着星际迷航长大的 我爱星际

迷航 星际迷航想要我 它让我

想看到来自

遥远世界的外星生物,但基本上我

发现我可以

在地球上找到那些外星生物,

我所做的就是学习 昆虫 我痴迷

于昆虫 尤其是昆虫飞行

我认为

昆虫飞行的进化可能

是生命史上最重要的事件之一

没有昆虫

就没有开花植物 吃

灵长类动物现在做 TED 演讲 David and

he Co 和 kotaki 讲述了一个非常引人入胜的

故事,关于果蝇和人类之间的相似之处,

并且有

很多相似之处,所以你可能会认为

,如果人类与果蝇相似,那么

果蝇最喜欢的行为

例如可能是这样,

但在我的演讲中,我不想强调

人类和果蝇之间的相似之处,

而是强调差异

和重点 s 关于我认为

果蝇擅长做的行为,所以我想

向你展示一个高速视频

序列,它以每秒 7,000 帧的速度拍摄

并使用红外照明,

屏幕右侧是一个电子隐约

可见的捕食者,它是 要去

飞苍蝇 苍蝇会感觉到这个捕食者

它会伸出它的腿 它

离开 活着再飞一天 现在我已经

仔细裁剪了这个序列,以

准确地显示人类眨眼的持续时间

你眨眼的时间 苍蝇已经看到了

这个迫在眉睫的捕食者估计了它的

位置 它启动了一个运动模式

让它以每秒 220 次拍打翅膀飞走

所以我认为

这是一个迷人的 表现

出飞行的大脑现在处理信息的速度有多快的行为

现在飞行需要什么才能飞

得好才能飞行就像在人类

飞机上一样,您需要能够

产生足够空气动力的机翼,以满足

您的需求 gine 足以

产生飞行所需的动力

,你需要一个控制器,在

第一架人类飞机中,控制器

基本上是 Orville 和 Wilbur 的大脑

我现在坐在驾驶舱里

,这与我

花了 我早期的很多职业生涯都在试图

弄清楚昆虫翅膀如何产生

足够的力量来让苍蝇保持在

空中,你可能已经听说过

工程师如何证明大

黄蜂不能很好地飞行问题

在于认为昆虫翅膀的

功能 飞机机翼的工作方式,

但它们不工作,我们

通过构建巨大的

动态缩放模型机器人昆虫来解决这个问题,这些机器人昆虫

会在巨大的矿物油池中扑腾,在

那里我们可以研究

空气动力,结果

发现昆虫拍打着 他们的机翼以一种

非常巧妙的方式以非常高的迎角

在机翼的前缘形成了一个

类似龙卷风的结构,称为

前缘涡旋 正是

那个漩涡实际上使翅膀

能够产生足够的力量让动物

留在空中,但

实际上最令人着迷的

并不是翅膀有一些

有趣的形态而是聪明的是

翅膀的方式 苍蝇宁愿

拍打它,这当然最终是

由神经系统控制的,

这就是使苍蝇能够进行

这些非凡的空中机动的原因,现在

引擎呢?苍蝇的引擎

绝对令人着迷,它们有

两种类型的飞行肌肉所谓

被拉伸激活的动力肌肉,

这意味着它可以自行激活,

不需要神经系统在收缩的基础上进行控制,

它专门

产生飞行所需的巨大力量

,它填充了苍蝇的中间

部分,所以 当一只苍蝇撞到

你的挡风玻璃时,它基本上

是你看到的动力肌肉,但

附着在机翼底部的是

一组微小的控制肌肉,

它们根本不是很强大,

但它们非常快,它们能够一次又一次

地重新配置机翼的铰链

,这

就是使苍蝇能够改变其机翼的原因

产生改变其

飞行轨迹的变化和空气动力,当然

神经系统的作用是控制

这一切,所以让我们看看控制器

现在在他们携带的各种传感器中表现出色,

他们有这个问题

能够感知气味和

检测风的触角 他们有一个

复杂的眼睛,这是地球上最快的

视觉系统

他们的头顶上有另一组眼睛

我们不知道他们在做什么 他们的身上

有一个传感器

机翼 机翼上覆盖着

传感器,包括感知

机翼变形的传感器,它们甚至可以

用翅膀尝到味道

苍蝇拥有的最复杂的传感器之一是一种

称为 t 的结构 大厅的眼泪 大厅的

眼泪实际上是陀螺仪 这些

设备

在飞行过程中来回摆动大约 200 赫兹,动物可以

用它们来感知身体的旋转并

启动非常快速的纠正

动作,但所有的感觉

信息都必须由

大脑处理 是的,果蝇确实有

一个大脑,一个大约有十万个

神经元的大脑现在在这个

会议上已经有几个人已经提出

果蝇可以为神经科学服务,

因为它们是大脑功能的简单模型,

而我演讲的基本要点

是“我”

想把它颠倒过来 我

认为不幸的是,很多

神经科学家

当我们想到大脑时,我们都有点自恋,

我们当然会想象自己的大脑,但

请记住,这种大脑

非常多 maller 而不是一

千亿个神经元,它有

十万个神经元,但这是

地球上最常见的大脑形式,

已经存在了 4 亿年,

公平地说它很简单吗?

更少的

神经元,但这是一个公平的指标,

我建议这不是一个公平的指标,所以

让我们考虑一下我认为

我们必须比较我们必须将

大脑的大小与

大脑可以做到的事情进行比较,所以我建议 我们

有一个特朗普数字,特朗普数字

是这个人的行为

曲目与他大脑中神经元数量的比率,

现在将计算果蝇的特朗普数字,

这里有多少人认为特朗普数字

更高 果蝇,

它是一个非常

聪明的听众 另一个

动物 举个例子 这是一只

老鼠 一只老鼠

的神经元数量大约是苍蝇的一千倍

我认为如果你比较如果你

比较苍蝇

和老鼠的自然历史真的可以比较它们

必须觅食它们必须

进行求爱它们它们

有性行为它们躲避掠食者它们

做很多类似的事情 但我

会争辩说苍蝇做得更多,

例如我要给你看一个序列,

所以他们不得不说我的一些资金

来自军方,所以我要展示

这个机密序列,你不能

在这个之外讨论它 房间还可以,所以我

想让你看看果蝇尾部的有效载荷

仔细观察,你会明白为什么我

六岁的儿子现在想成为一名

神经科学家 等一下

,至少你会 承认如果

果蝇不是 像老鼠一样聪明,它们

至少和鸽子一样聪明现在我想表达

的是,这

不仅仅是数字的问题,

也是苍蝇

计算大脑必须

用如此微小的神经元计算的一切的挑战,所以这是 来自 Jeff Lichtman 实验室的老鼠

的视觉中间神经元的美丽图像

,你可以

看到他在演讲中展示的大脑的精彩图像,

在右上角的角落里,你会看到

与苍蝇相同规模的视觉中间神经元

,我将其扩展,

它是一个非常复杂的神经元,

它非常非常小

,尝试

用微小的

神经元计算信息存在许多生物物理挑战,神经元能看清多小

这种有趣的昆虫它看起来

有点像苍蝇它有翅膀有

眼睛它有触角它的腿

复杂的生活史它是一种寄生虫

它必须飞来飞去寻找

毛虫寄生但它不仅

是 大脑 盐脑的大小

与果蝇相当 它

是盐脑的大小

所以是盐脑 所以这里有一些其他

类似规模的生物 这种

动物有草履虫

和变形虫的大小 它有 由 7,000 个

神经元组成的大脑 非常小 你知道这些

叫做细胞体的东西 你

听说过神经元的细胞核在

哪里 这种动物会

因为它们占用太多空间而摆脱它们 所以

这是一个关于神经科学前沿的会议

我 会假设

神经科学的一个前沿前沿是

弄清楚那个东西的大脑是如何

工作的,但让我们考虑一下,你如何才能

让少数神经元做

很多事情,我认为如果从工程学的

角度来看,你想多路复用

你 可以使用硬件并让该

硬件在不同时间做不同的事情,

或者让

硬件的不同部分做不同的事情

,这是我想探索的两个概念

,它们不是概念 在

我提出了

但过去其他人提出的概念,

并且一个想法

来自咀嚼螃蟹的教训

,我不是说咀嚼螃蟹

,我在巴尔的摩长大,我咀嚼螃蟹

非常好 但我说的是

喜欢的螃蟹 咀嚼螃蟹

真的很迷人 螃蟹

在它们的甲壳下有一个复杂的结构,

叫做胃磨,

它以各种

不同的方式研磨食物

,这是一部关于这个的内窥镜电影 这个

这个这个结构 令人惊奇的

是它是由一组非常

小的神经元控制的,大约有两打神经元

,可以产生各种各样

不同的运动模式,

它能够做到这一点的原因是这个

小小的神经节在 螃蟹实际上

被许多神经调节剂淹没了,

你之前听说过神经调节剂,

它们是更多的神经调节剂,可以

改变支配这种结构的神经调节剂,

然后实际上 结构中的 y 个神经元

,它们能够生成一

组复杂的模式,这

是 yves martyr 和她的许多同事的工作

许多

事情是因为神经调节

可以在每时每刻发生,

所以这基本上是多路复用

和时间想象一个神经元网络

与一个神经调节剂你选择一

组细胞来执行一种

行为另一个神经调节剂另一

组细胞 一个不同的模式,你

可以想象你可以推断出一个

非常非常复杂的系统。有

没有证据表明苍蝇

在我的实验室和

世界各地的其他实验室多年来做得很好,我们一直在

研究飞行行为和小型飞行

模拟器,你可以 把苍蝇拴在一根

小棍子上 你可以测量

它产生的空气动力 你可以

让它飞的层 让它玩一个小

游戏 飞来飞去并在

视觉显示中让我向你展示一个

小小的序列 这是飞行模拟器

中的苍蝇和放大的红外视图

这是

苍蝇喜欢玩的游戏 你

让它们转向一点

条纹,他们将永远转向

那个条纹,这是他们

视觉引导系统的一部分,但

最近有可能修改

这些生理学行为领域,

所以

这是我的前博士后之一 gabby

Mayman 现在在做的准备工作 洛克菲勒

开发了它,它基本上是一个飞行

模拟器,但在你

实际上可以

在果蝇的大脑中粘贴和选择并

从基因上识别的果蝇大脑中的神经元记录

的条件下,这就是其中

一个实验看起来像是一个

序列 取自

实验室的另一位博士后 Bettina schnell 底部的绿色迹线

是果蝇大脑中神经元的膜电位,

你会看到 f 谎言开始飞行,

而苍蝇实际上是

通过它自己的翅膀运动来控制视觉模式本身的旋转,你可以看到

这个视觉中间神经元

在苍蝇飞行时对翅膀运动的模式做出反应,

所以我们第一次真正

地 能够在苍蝇执行复杂行为(例如飞行)时从苍蝇大脑中的神经元记录下来,

我们一直在学习的一个教训

,我们多年来一直

在静止苍蝇中研究的细胞生理学是 与

果蝇实际从事

飞行和行走等活动行为时的那些细胞

的生理机能不同,为什么生理机能如此

不同,事实证明,这些

神经调节剂就像螃蟹

那个小

神经节中的神经调节剂一样 所以这是

一张十月免疫系统 octo commune 的图片,它

是一种神经调节剂,似乎

在飞行和其他行为中发挥着重要作用,

但这只是在

果蝇大脑中的许多神经调节剂,

所以我真的认为,随着我们

了解更多,结果会

发现整个果蝇大脑就像一个大

版本的口胃神经节

,这就是它可以

这样做的原因之一 现在神经元如此之少的

另一种想法

是在空间中进行多路复用,

让神经元的不同部分同时做

不同的事情,所以

这里有两种来自脊椎动物的典型神经元

来自 rimoni cahal 的无脊椎动物人类锥体神经元

和 右边的另一个细胞是一个

非尖峰的内部神经元,这是多年前

Alan Watson 和 Malcolm burrows 的工作,

malcolm burrows 提出

了一个非常有趣的想法,

基于蝗虫的这个神经元

不会激发动作电位这一事实

它是一个非尖峰细胞,所以

像我们大脑中的神经元这样的典型细胞有一个

称为树突的区域,它

接收输入并将一些输入一起输入

,然后 产生

沿着轴突向下运行的动作电位,然后激活

神经元的所有输出区域,但非

尖峰神经元实际上非常

复杂,因为它们可以具有输入

突触和输出突触都相互

交错,并且没有单个动作

电位可以驱动所有

输出 同时,有

可能你有计算

隔间,允许

不同的神经元做不同的神经元的

不同部分,同时做

不同的事情,所以

这些多任务处理的基本概念

和时间在空间中的多任务我 认为

这些在我们的大脑中也是真实的,

但我认为昆虫

是这方面的真正主人,所以我希望

你下次对昆虫的看法

有所不同,正如我在这里所说的,

在你打你之前请三思