ABOUT THE SPEAKER
Sebastian Seung - Computational neuroscientist
Sebastian Seung is a leader in the new field of connectomics, currently the hottest space in neuroscience, which studies, in once-impossible detail, the wiring of the brain.

Why you should listen

In the brain, neurons are connected into a complex network. Sebastian Seung and his lab at MIT are inventing technologies for identifying and describing the connectome, the totality of connections between the brain's neurons -- think of it as the wiring diagram of the brain. We possess our entire genome at birth, but things like memories are not "stored" in the genome; they are acquired through life and accumulated in the brain. Seung's hypothesis is that "we are our connectome," that the connections among neurons is where memories and experiences get stored.

Seung and his collaborators, including Winfried Denk at the Max Planck Institute and Jeff Lichtman at Harvard University, are working on a plan to thin-slice a brain (probably starting with a mouse brain) and trace, from slice to slice, each neural pathway, exposing the wiring diagram of the brain and creating a powerful new way to visualize the workings of the mind. They're not the first to attempt something like this -- Sydney Brenner won a Nobel for mapping all the 7,000 connections in the nervous system of a tiny worm, C. elegans. But that took his team a dozen years, and the worm only had 302 nerve cells. One of Seung's breakthroughs is in using advanced imagining and AI to handle the crushing amount of data that a mouse brain will yield and turn it into richly visual maps that show the passageways of thought and sensation.

More profile about the speaker
Sebastian Seung | Speaker | TED.com
TEDGlobal 2010

Sebastian Seung: I am my connectome

Sebastian Seung: 我是我的连接体

Filmed:
1,131,223 views

Sebastian Seung 正在绘制一组宏大的大脑模型,着重凸显各个神经元之间的连接。他称之为“连接体”。它和我们的基因组一样,是独一无二的-如果能够解开它的奥秘,那么我们就开辟了研究大脑与思维的新途径。
- Computational neuroscientist
Sebastian Seung is a leader in the new field of connectomics, currently the hottest space in neuroscience, which studies, in once-impossible detail, the wiring of the brain. Full bio

Double-click the English transcript below to play the video.

00:17
We live生活 in in a remarkable卓越 time,
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我们生活在一个伟大的时代
00:20
the age年龄 of genomics基因组学.
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基因组学时代
00:23
Your genome基因组 is the entire整个 sequence序列 of your DNA脱氧核糖核酸.
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基因组是你的整套DNA序列
00:26
Your sequence序列 and mine are slightly different不同.
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你我的序列稍有不同
00:29
That's why we look different不同.
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所以我们看上去不太一样
00:31
I've got brown棕色 eyes眼睛;
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我的眼睛是棕色的
00:33
you might威力 have blue蓝色 or gray灰色.
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你的眼睛可能是蓝色或灰色的
00:36
But it's not just skin-deep肤浅的.
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但这序列的作用可没这么肤浅
00:38
The headlines新闻头条 tell us
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新闻头条告诉我们
00:40
that genes基因 can give us scary害怕 diseases疾病,
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基因可能产生可怕的疾病,
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maybe even shape形状 our personality个性,
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甚至可能决定了我们的性格
00:46
or give us mental心理 disorders障碍.
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让我们神经错乱
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Our genes基因 seem似乎 to have
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我们的基因似乎有着
00:52
awesome真棒 power功率 over our destinies命运.
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主宰我们命运的神奇力量
00:56
And yet然而, I would like to think
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但是, 我希望
00:59
that I am more than my genes基因.
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我胜过我的基因。
01:04
What do you guys think?
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你们怎么想?
01:06
Are you more than your genes基因?
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你们认为你们胜过自己的基因吗?
01:09
(Audience听众: Yes.) Yes?
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(观众:是的)是吗?
01:13
I think some people agree同意 with me.
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我看有一些人同意我的观点
01:15
I think we should make a statement声明.
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我觉得我们应该做个声明
01:17
I think we should say it all together一起.
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我们应该一起大声喊
01:20
All right: "I'm more than my genes基因" -- all together一起.
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来吧:“我胜过我的基因”-预备起
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Everybody每个人: I am more than my genes基因.
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众人:我胜过我的基因。
01:27
(Cheering打气)
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(众人欢呼)
01:30
Sebastian塞巴斯蒂安 Seung: What am I?
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Sebastian Seung:那我是什么?
01:32
(Laughter笑声)
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(众人笑)
01:35
I am my connectome连接组.
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我是我的连接体
01:40
Now, since以来 you guys are really great,
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现在,既然大家万众一心
01:42
maybe you can humor幽默 me and say this all together一起 too.
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那么你们一起说这一句话,让我开开心
01:44
(Laughter笑声)
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(众人笑)
01:46
Right. All together一起 now.
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来吧,预备起
01:48
Everybody每个人: I am my connectome连接组.
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众人:我是我的连接体
01:53
SSSS: That sounded满面 great.
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Sebastian Seung:太棒了!
01:55
You know, you guys are so great, you don't even know what a connectome连接组 is,
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你们真是太合作了,你们连什么是连接体都不知道
01:57
and you're willing愿意 to play along沿 with me.
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就愿意听从我的指挥
01:59
I could just go home now.
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我现在就可以回家歇着了
02:02
Well, so far only one connectome连接组 is known已知,
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目前我们仅认识了一个连接体
02:05
that of this tiny worm.
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就是这条小虫
02:08
Its modest谦虚 nervous紧张 system系统
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它简单的神经系统
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consists of just 300 neurons神经元.
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仅由300个神经元组成
02:12
And in the 1970s and '80s,
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二十世纪七八十年代
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a team球队 of scientists科学家们
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一群科学家
02:16
mapped映射 all 7,000 connections连接
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绘制了神经元之间的
02:18
between之间 the neurons神经元.
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7000个连接
02:21
In this diagram, every一切 node节点 is a neuron神经元,
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在这幅图里,每个结都是一个神经元
02:23
and every一切 line线 is a connection连接.
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每一条线都是一个连接
02:25
This is the connectome连接组
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这就是线虫的
02:27
of the worm C. elegans线虫.
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连接体
02:31
Your connectome连接组 is far more complex复杂 than this
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你的连接体比这复杂多了
02:34
because your brain
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因为你的大脑
02:36
contains包含 100 billion十亿 neurons神经元
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由一千亿个神经元组成
02:38
and 10,000 times as many许多 connections连接.
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连接数是线虫的一万倍
02:41
There's a diagram like this for your brain,
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人脑也有类似的一张图
02:43
but there's no way it would fit适合 on this slide滑动.
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但是这张幻灯片可放不下
02:47
Your connectome连接组 contains包含 one million百万 times more connections连接
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你连接体中的连接数比你基因组中的字母
02:50
than your genome基因组 has letters.
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还要多100万倍
02:53
That's a lot of information信息.
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信息量非常大
02:55
What's in that information信息?
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里面的信息有什么意义?
02:59
We don't know for sure, but there are theories理论.
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我们还不得而知,但是有一些相关理论
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Since以来 the 19th century世纪, neuroscientists神经学家 have speculated推测
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自十九世纪以来,神经元学家们就开始推测
03:05
that maybe your memories回忆 --
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或许你的记忆-
03:07
the information信息 that makes品牌 you, you --
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那决定你是谁的信息-
03:09
maybe your memories回忆 are stored存储
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也许你的记忆就储存在
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in the connections连接 between之间 your brain's大脑的 neurons神经元.
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你大脑神经元之间的连接里
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And perhaps也许 other aspects方面 of your personal个人 identity身分 --
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也许你个人身份的其它方面-
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maybe your personality个性 and your intellect智力 --
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你的个性与智力-
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maybe they're also encoded编码
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或许它们
03:22
in the connections连接 between之间 your neurons神经元.
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也被编译在你神经元的连接里
03:26
And so now you can see why I proposed建议 this hypothesis假设:
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现在你们明白我为什么提出这个假设了:
03:29
I am my connectome连接组.
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我是我的连接体
03:32
I didn't ask you to chant it because it's true真正;
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我让大家一起喊并不是因为这是事实
03:35
I just want you to remember记得 it.
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我只是想让你们记住这句话
03:37
And in fact事实, we don't know if this hypothesis假设 is correct正确,
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事实上,我们不知道这假设是否正确
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because we have never had technologies技术
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因为我们的技术还没有发展到
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powerful强大 enough足够 to test测试 it.
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足以测试其正确与否的程度
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Finding查找 that worm connectome连接组
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光是找出那条小虫的连接体
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took over a dozen years年份 of tedious乏味 labor劳动.
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就花了十几年的艰苦劳动
03:50
And to find the connectomesconnectomes of brains大脑 more like our own拥有,
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而找到人脑的连接体
03:53
we need more sophisticated复杂的 technologies技术, that are automated自动化,
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我们需要更加精尖的自动化技术
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that will speed速度 up the process处理 of finding发现 connectomesconnectomes.
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以提高寻找连接体的速度
03:59
And in the next下一个 few少数 minutes分钟, I'll tell you about some of these technologies技术,
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下面的几分钟里,我将向大家介绍其中一些技术
04:02
which哪一个 are currently目前 under development发展
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这些技术尚处于研发状态
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in my lab实验室 and the labs实验室 of my collaborators合作者.
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在我和我同事的实验室里进行
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Now you've probably大概 seen看到 pictures图片 of neurons神经元 before.
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你们可能已经见过神经元的照片
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You can recognize认识 them instantly即刻
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你们可以通过它们奇特的形状
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by their fantastic奇妙 shapes形状.
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一眼就认出它们
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They extend延伸 long and delicate精巧 branches分支机构,
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它们延伸出长而纤细的枝条
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and in short, they look like trees树木.
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简单说,它们看起来像树一样
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But this is just a single neuron神经元.
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而这只是一个神经元
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In order订购 to find connectomesconnectomes,
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想找到连接体
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we have to see all the neurons神经元 at the same相同 time.
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我们必须同时看到所有神经元
04:30
So let's meet遇到 Bobby鲍比 Kasthuri卡斯特里,
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下面我们请出波比. 卡斯特里
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who works作品 in the laboratory实验室 of Jeff杰夫 Lichtman利希特曼
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他在哈佛大学
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at Harvard哈佛 University大学.
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利希曼实验室工作
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Bobby鲍比 is holding保持 fantastically飞驰 thin slices
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波比拿在手里的是一片极薄的
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of a mouse老鼠 brain.
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小鼠大脑切片
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And we're zooming缩放 in by a factor因子 of 100,000 times
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我们把它放大了十万倍
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to obtain获得 the resolution解析度,
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达到所需分辨率
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so that we can see the branches分支机构 of neurons神经元 all at the same相同 time.
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这样我们就可以同时看到所有神经元的分枝
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Except, you still may可能 not really recognize认识 them,
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但是,你可能还是无法真正识别它们
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and that's because we have to work in three dimensions尺寸.
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我们必须在三维的效果下进行工作
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If we take many许多 images图片 of many许多 slices of the brain
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如果我们给许多大脑切片拍照
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and stack them up,
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再把它们叠在一起
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we get a three-dimensional三维 image图片.
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我们会得到一个三维图像
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And still, you may可能 not see the branches分支机构.
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然而,你可能还是看不到那些分枝
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So we start开始 at the top最佳,
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我们从上至下
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and we color颜色 in the cross-section横截面 of one branch in red,
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把一个分枝的交叉部位涂成红色
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and we do that for the next下一个 slice
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我们对下一张切片进行同样处理
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and for the next下一个 slice.
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接着再下一张
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And we keep on doing that,
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我们持续这么处理
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slice after slice.
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一张接着一张
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If we continue继续 through通过 the entire整个 stack,
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如果对一整叠切片进行处理
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we can reconstruct重建 the three-dimensional三维 shape形状
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我们就能重塑这一小段
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of a small fragment分段 of a branch of a neuron神经元.
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神经元分枝的三维图形
05:26
And we can do that for another另一个 neuron神经元 in green绿色.
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我们还可以把另一个神经元涂成绿色
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And you can see that the green绿色 neuron神经元 touches触摸 the red neuron神经元
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你们可以看到绿色神经元与红色神经元
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at two locations地点,
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在两处接触了
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and these are what are called synapses突触.
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这两个就是神经突触
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Let's zoom放大 in on one synapse突触,
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我们把一个神经突触放大
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and keep your eyes眼睛 on the interior室内 of the green绿色 neuron神经元.
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大家注意看绿色的内部
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You should see small circles --
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你们可以看到一些小圆圈
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these are called vesicles囊泡.
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这些被称为囊泡
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They contain包含 a molecule分子 know as a neurotransmitter神经递质.
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它们包含了被称为神经递质的分子
05:47
And so when the green绿色 neuron神经元 wants to communicate通信,
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当绿色神经元想进行沟通
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it wants to send发送 a message信息 to the red neuron神经元,
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想给红色神经元发送信息
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it spits吐奶 out neurotransmitter神经递质.
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它就释放出神经递质
05:54
At the synapse突触, the two neurons神经元
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在神经突触处,这两个神经元
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are said to be connected连接的
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被认为是相互连接起来
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like two friends朋友 talking on the telephone电话.
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就像两个朋友通过电话聊天
06:02
So you see how to find a synapse突触.
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你们了解了如何找到一个神经突触
06:04
How can we find an entire整个 connectome连接组?
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那么我们怎么找到整个完整的连接体呢?
06:07
Well, we take this three-dimensional三维 stack of images图片
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我们把这个图形重叠形成的三维图像
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and treat对待 it as a gigantic巨大 three-dimensional三维 coloring染色 book.
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处理成一本巨大的三维填图
06:13
We color颜色 every一切 neuron神经元 in, in a different不同 color颜色,
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我们把每一个神经元涂成一种颜色
06:16
and then we look through通过 all of the images图片,
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接着从所有图像中
06:18
find the synapses突触
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找到神经突触
06:20
and note注意 the colors颜色 of the two neurons神经元 involved参与 in each synapse突触.
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记录下任意两个组成神经突触的神经元的颜色,
06:23
If we can do that throughout始终 all the images图片,
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如果我们可以对所有图像进行这样的处理
06:26
we could find a connectome连接组.
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我们就能找到整个连接体
06:29
Now, at this point,
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到目前为止
06:31
you've learned学到了 the basics基本 of neurons神经元 and synapses突触.
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大家已经对神经元和神经突触有了基本了解
06:33
And so I think we're ready准备 to tackle滑车
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我想我们已经可以解决
06:35
one of the most important重要 questions问题 in neuroscience神经科学:
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神经学上最重要的问题:
06:39
how are the brains大脑 of men男人 and women妇女 different不同?
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男性与女性的大脑有何不同?
06:42
(Laughter笑声)
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(众人笑)
06:44
According根据 to this self-help自救 book,
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这本自学书上说
06:46
guys brains大脑 are like waffles威化饼;
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男性的大脑像华孚饼
06:48
they keep their lives生活 compartmentalized条块 in boxes盒子.
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他们把自己的生活分别独立包装在盒子里
06:51
Girls'少女时代 brains大脑 are like spaghetti意大利面;
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而女性的大脑像意大利面
06:54
everything in their life is connected连接的 to everything else其他.
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她们生活中的一切与其它所有东西都联系在一起
06:57
(Laughter笑声)
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(众人笑)
06:59
You guys are laughing,
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大家都笑了
07:01
but you know, this book changed my life.
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但是,你们知道吗,这本书改变了我一生
07:03
(Laughter笑声)
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(众人笑)
07:07
But seriously认真地, what's wrong错误 with this?
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说正经的,这错在哪里?
07:10
You already已经 know enough足够 to tell me -- what's wrong错误 with this statement声明?
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你们已经足以回答这个问题了。这个说法错在哪里?
07:20
It doesn't matter whether是否 you're a guy or girl女孩,
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不管你是男是女
07:23
everyone's大家的 brains大脑 are like spaghetti意大利面.
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所有人的大脑都像意大利面
07:26
Or maybe really, really fine capellini卡佩利尼 with branches分支机构.
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或者说像非常非常优质的、带枝条的细面条
07:30
Just as one strand of spaghetti意大利面
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正如一条意大利面
07:32
contacts往来 many许多 other strands on your plate盘子,
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连接着你盘子里的其它面条一样
07:35
one neuron神经元 touches触摸 many许多 other neurons神经元
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一个神经元与许多其它神经元
07:37
through通过 their entangled纠缠 branches分支机构.
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通过它们缠绕的枝条相互接触
07:39
One neuron神经元 can be connected连接的 to so many许多 other neurons神经元,
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一个神经元能够与其它众多神经元连接在一起
07:42
because there can be synapses突触
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是因为在它们的接触点上
07:44
at these points of contact联系.
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形成神经突触
07:49
By now, you might威力 have sort分类 of lost丢失 perspective透视
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现在你们对这个大脑组织块的实际大小
07:52
on how large this cube立方体 of brain tissue组织 actually其实 is.
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可能已经摸不着头脑了
07:55
And so let's do a series系列 of comparisons对比 to show显示 you.
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那么我们通过一系列对比给你们做展示
07:58
I assure保证 you, this is very tiny. It's just six microns微米 on a side.
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我保证,这非常微小,边长仅为6微米
08:03
So, here's这里的 how it stacks up against反对 an entire整个 neuron神经元.
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看,这就是它与一个完整神经元的对比
08:06
And you can tell that, really, only the smallest最少 fragments片段 of branches分支机构
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你们可以看到,真的,只有分枝最小的部分
08:09
are contained inside this cube立方体.
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被包含在这个方块里
08:12
And a neuron神经元, well, that's smaller than brain.
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而一个神经元,比大脑要小多了
08:17
And that's just a mouse老鼠 brain --
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而这还只是一只小鼠的脑
08:21
it's a lot smaller than a human人的 brain.
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比人类的脑小多了
08:25
So when show显示 my friends朋友 this,
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当我给朋友看这张图
08:27
sometimes有时 they've他们已经 told me,
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他们有时会劝我
08:29
"You know, Sebastian塞巴斯蒂安, you should just give up.
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“我说, Sebastian,你应该放弃了
08:32
Neuroscience神经科学 is hopeless绝望."
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神经科学是没有出路的。”
08:34
Because if you look at a brain with your naked eye,
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如果你只用肉眼来看一个大脑
08:36
you don't really see how complex复杂 it is,
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你看不到它有多复杂
08:38
but when you use a microscope显微镜,
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但是,在显微镜之下
08:40
finally最后 the hidden complexity复杂 is revealed透露.
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那隐藏的复杂性就最终显现出来了
08:45
In the 17th century世纪,
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在十七世纪
08:47
the mathematician数学家 and philosopher哲学家, Blaise布莱斯 Pascal帕斯卡尔,
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数学家兼哲学家布莱士. 帕斯卡
08:49
wrote of his dread恐惧 of the infinite无穷,
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在冥想浩瀚的外太空时
08:52
his feeling感觉 of insignificance渺小
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写下了他对无限性的恐惧
08:54
at contemplating考虑 the vast广大 reaches到达 of outer space空间.
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以及自身的微不足道
08:59
And, as a scientist科学家,
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而,作为一个科学家
09:01
I'm not supposed应该 to talk about my feelings情怀 --
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我不应该谈论我的感受
09:04
too much information信息, professor教授.
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太多隐私啊,教授
09:06
(Laughter笑声)
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(众人笑)
09:08
But may可能 I?
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还是让我说说吧?
09:10
(Laughter笑声)
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(众人笑)
09:12
(Applause掌声)
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(众人鼓掌)
09:14
I feel curiosity好奇心,
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我感觉好奇
09:16
and I feel wonder奇迹,
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我感觉迷惑,
09:18
but at times I have also felt despair绝望.
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但我也常常感觉绝望
09:22
Why did I choose选择 to study研究
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为什么我会选择
09:24
this organ器官 that is so awesome真棒 in its complexity复杂
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学习这个复杂到绝美
09:27
that it might威力 well be infinite无穷?
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但也复杂到无限的器官呢?
09:29
It's absurd荒诞.
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太荒唐了
09:31
How could we even dare to think
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我们怎敢想像
09:33
that we might威力 ever understand理解 this?
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有一天我们能把大脑了解清楚
09:38
And yet然而, I persist坚持 in this quixotic不切实际 endeavor努力.
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但是,我坚持进行这项愚侠的事业
09:41
And indeed确实, these days I harbor港口 new hopes希望.
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而实际上,这些天我见到了一些新希望
09:45
Someday日后,
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总有一天
09:47
a fleet舰队 of microscopes显微镜 will capture捕获
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会有一大批显微镜
09:49
every一切 neuron神经元 and every一切 synapse突触
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能够捕捉到每一个神经元与每一个神经突触
09:51
in a vast广大 database数据库 of images图片.
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得到一个巨大的图像数据库
09:54
And some day, artificially人为 intelligent智能 supercomputers超级计算机
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总有一天,人工智能超级计算机
09:57
will analyze分析 the images图片 without human人的 assistance帮助
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能够对这些图像进行自主分析
10:00
to summarize总结 them in a connectome连接组.
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把它们总结成连接体
10:04
I do not know, but I hope希望 that I will live生活 to see that day,
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我不知道,但我希望我能在有生之年看到那一天
10:08
because finding发现 an entire整个 human人的 connectome连接组
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因为,找到一个完整的人类连接体
10:10
is one of the greatest最大 technological技术性 challenges挑战 of all time.
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是历史上最重大的技术挑战之一
10:13
It will take the work of generations to succeed成功.
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这要求许多代人的共同努力才能完成
10:17
At the present当下 time, my collaborators合作者 and I,
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在现今,我和我的同事们
10:20
what we're aiming瞄准 for is much more modest谦虚 --
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我们的奋斗目标没有那么远大-
10:22
just to find partial局部 connectomesconnectomes
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只是力求找到在小鼠大脑
10:24
of tiny chunks of mouse老鼠 and human人的 brain.
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和人类大脑微小切片中的部分连接体
10:27
But even that will be enough足够 for the first tests测试 of this hypothesis假设
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而这已经足够用来进行“我是我的连接体”
10:30
that I am my connectome连接组.
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这个假设的初期测试
10:35
For now, let me try to convince说服 you of the plausibility合理性 of this hypothesis假设,
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到此,我想告诉大家这个假设的合理性
10:38
that it's actually其实 worth价值 taking服用 seriously认真地.
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这是值得严肃对待的
10:42
As you grow增长 during childhood童年
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你在童年时成长
10:44
and age年龄 during adulthood成年,
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在成年之后逐渐变老
10:47
your personal个人 identity身分 changes变化 slowly慢慢地.
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你个人身份慢慢地变化
10:50
Likewise同样, every一切 connectome连接组
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同理,每个连接体
10:52
changes变化 over time.
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都会随着时间而变化
10:55
What kinds of changes变化 happen发生?
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发生什么样的变化呢?
10:57
Well, neurons神经元, like trees树木,
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神经元,像树
10:59
can grow增长 new branches分支机构,
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能够长出新的枝条
11:01
and they can lose失去 old ones那些.
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也会换下旧的枝条
11:04
Synapses突触 can be created创建,
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神经突触会产生
11:07
and they can be eliminated淘汰.
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也会消失
11:10
And synapses突触 can grow增长 larger,
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神经突触能够长大
11:12
and they can grow增长 smaller.
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也能变小
11:15
Second第二 question:
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第二个问题:
11:17
what causes原因 these changes变化?
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是什么促成了这些变化?
11:20
Well, it's true真正.
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如人所说,
11:22
To some extent程度, they are programmed程序 by your genes基因.
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在某种程度上,它们是由你的基因决定的
11:25
But that's not the whole整个 story故事,
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但并不完全如此
11:27
because there are signals信号, electrical电动 signals信号,
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因为有许多信号,电子信号
11:29
that travel旅行 along沿 the branches分支机构 of neurons神经元
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沿着神经元的枝条游动
11:31
and chemical化学 signals信号
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还有化学信号
11:33
that jump across横过 from branch to branch.
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在枝条的交界处跳跃
11:35
These signals信号 are called neural神经 activity活动.
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这些信号被称为神经活动
11:38
And there's a lot of evidence证据
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有许多证据证明
11:40
that neural神经 activity活动
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神经活动
11:43
is encoding编码 our thoughts思念, feelings情怀 and perceptions看法,
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决定了我们的思想,感受与知觉
11:46
our mental心理 experiences经验.
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还有我们的精神经历
11:48
And there's a lot of evidence证据 that neural神经 activity活动
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还有很多证据证明神经活动
11:51
can cause原因 your connections连接 to change更改.
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能够促使你的连接体发生变化
11:54
And if you put those two facts事实 together一起,
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如果你把两个因素放在一起
11:57
it means手段 that your experiences经验
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它就意味着你的经历
11:59
can change更改 your connectome连接组.
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能够改变你的连接体
12:02
And that's why every一切 connectome连接组 is unique独特,
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这就是为什么每个人的连接体都是独一无二的
12:04
even those of genetically基因 identical相同 twins双胞胎.
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即使是同卵双胞胎也不例外
12:08
The connectome连接组 is where nature性质 meets符合 nurture培育.
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连接体是先天与后天的共同产物
12:12
And it might威力 true真正
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这很有可能是真的
12:14
that just the mere act法案 of thinking思维
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一个小小的思维动作
12:16
can change更改 your connectome连接组 --
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就能改变你的连接体——
12:18
an idea理念 that you may可能 find empowering授权.
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你可能感觉这个概念很强势。
12:24
What's in this picture图片?
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这幅图是什么?
12:28
A cool and refreshing清爽 stream of water, you say.
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你会说是一条清凉的溪流
12:32
What else其他 is in this picture图片?
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图上还有什么?
12:37
Do not forget忘记 that groove in the Earth地球
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别忘了那地表的深漕
12:39
called the stream bed.
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我们叫它河床
12:42
Without没有 it, the water would not know in which哪一个 direction方向 to flow.
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没有了它,水就不知道往那个方向流了
12:45
And with the stream,
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对于溪流
12:47
I would like to propose提出 a metaphor隐喻
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我想做一个暗喻
12:49
for the relationship关系 between之间 neural神经 activity活动
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来形容神经活动与连接体活动
12:51
and connectivity连接.
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之间的关系
12:54
Neural神经 activity活动 is constantly经常 changing改变.
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神经活动不停地在变化
12:57
It's like the water of the stream; it never sits坐镇 still.
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就像溪流一样;永不停息
13:00
The connections连接
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而脑部神经网络的
13:02
of the brain's大脑的 neural神经 network网络
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连接处
13:04
determines确定 the pathways途径
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决定了神经活动
13:06
along沿 which哪一个 neural神经 activity活动 flows流动.
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流动的路线
13:08
And so the connectome连接组 is like bed of the stream;
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所以,连接体就像河床一样
13:13
but the metaphor隐喻 is richer更丰富 than that,
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但这暗喻的内容比这丰富得多
13:16
because it's true真正 that the stream bed
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因为尽管河床
13:19
guides导游 the flow of the water,
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是流水的导向
13:21
but over long timescales时间表,
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但经过很长的时期
13:23
the water also reshapes重塑 the bed of the stream.
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流水也会对河床进行重塑
13:26
And as I told you just now,
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我刚才说过
13:28
neural神经 activity活动 can change更改 the connectome连接组.
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神经活动能够改变连接体
13:33
And if you'll你会 allow允许 me to ascend
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如果大家允许我
13:35
to metaphorical隐喻 heights高度,
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更进一步使用暗喻
13:38
I will remind提醒 you that neural神经 activity活动
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我会提醒大家,神经活动
13:41
is the physical物理 basis基础 -- or so neuroscientists神经学家 think --
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至少神经学家是这么认为的-
13:43
of thoughts思念, feelings情怀 and perceptions看法.
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是思想,感受以及感知的生理基础
13:46
And so we might威力 even speak说话 of
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这样我们甚至可以探讨
13:48
the stream of consciousness意识.
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意识的溪流
13:50
Neural神经 activity活动 is its water,
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神经活动是水
13:53
and the connectome连接组 is its bed.
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连接体是河床
13:57
So let's return返回 from the heights高度 of metaphor隐喻
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我们从暗喻中
13:59
and return返回 to science科学.
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回到科学上
14:01
Suppose假设 our technologies技术 for finding发现 connectomesconnectomes
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假设我们寻找连接体的技术
14:03
actually其实 work.
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起到了作用
14:05
How will we go about testing测试 the hypothesis假设
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我们如何对假设进行测试
14:07
"I am my connectome连接组?"
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证明“我是我的连接体”呢?
14:10
Well, I propose提出 a direct直接 test测试.
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我提出一个直接的测试
14:13
Let us attempt尝试
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我们尝试
14:15
to read out memories回忆 from connectomesconnectomes.
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通过连接体来解读记忆
14:18
Consider考虑 the memory记忆
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记忆是
14:20
of long temporal sequences序列 of movements运动,
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长期有序发生的动作
14:23
like a pianist钢琴家 playing播放 a Beethoven贝多芬 sonata奏鸣曲.
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就像一个在弹奏贝多芬奏鸣曲的钢琴家
14:26
According根据 to a theory理论 that dates日期 back to the 19th century世纪,
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根据十九世纪时提出的理论
14:29
such这样 memories回忆 are stored存储
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这些记忆以神经键链条的形式
14:31
as chains of synaptic突触 connections连接 inside your brain.
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被储存在你的大脑里
14:35
Because, if the first neurons神经元 in the chain are activated活性,
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因为,如果链条中第一批神经元被激活
14:38
through通过 their synapses突触 they send发送 messages消息 to the second第二 neurons神经元, which哪一个 are activated活性,
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它们会通过神经突触向第二批被激活的神经元发出信息
14:41
and so on down the line线,
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以此类推,一直往下
14:43
like a chain of falling落下 dominoes骨牌.
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就像是一路倒下的多米诺骨牌
14:45
And this sequence序列 of neural神经 activation激活
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这有序的神经激活
14:47
is hypothesized假设 to be the neural神经 basis基础
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被猜想为那些有序动作的
14:50
of those sequence序列 of movements运动.
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神经基础
14:52
So one way of trying to test测试 the theory理论
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所以,检验这一理论的一种途径
14:54
is to look for such这样 chains
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就是在连接体中
14:56
inside connectomesconnectomes.
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寻找这样的链条
14:58
But it won't惯于 be easy简单, because they're not going to look like this.
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但这并非易事,因为它们可不像这样
15:01
They're going to be scrambled up.
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它们会相互纠结成一团
15:03
So we'll have to use our computers电脑
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所以我们就必须使用我们的计算机
15:05
to try to unscramble解读 the chain.
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把这些链条解开
15:08
And if we can do that,
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如果我们成功了
15:10
the sequence序列 of the neurons神经元 we recover恢复 from that unscrambling解读
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我们解开的神经元序列
15:13
will be a prediction预测 of the pattern模式 of neural神经 activity活动
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能够预测大脑中记忆回放时
15:16
that is replayed重播 in the brain during memory记忆 recall召回.
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神经活动的模式
15:19
And if that were successful成功,
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如果成功了
15:21
that would be the first example of reading a memory记忆 from a connectome连接组.
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这将是由连接体读取记忆的第一例
15:28
(Laughter笑声)
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(众人笑)
15:30
What a mess食堂 --
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真复杂
15:33
have you ever tried试着 to wire线 up a system系统
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你们有没有尝试过
15:35
as complex复杂 as this?
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连接一个类似的复杂系统?
15:37
I hope希望 not.
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但愿没有
15:39
But if you have, you know it's very easy简单 to make a mistake错误.
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但是如果尝试过,你知道这很容易出错
15:45
The branches分支机构 of neurons神经元 are like the wires电线 of the brain.
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神经元的枝条就像是大脑的电线一样
15:47
Can anyone任何人 guess猜测: what's the total length长度 of wires电线 in your brain?
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谁能猜一猜:你大脑里神经元的总长有多少?
15:54
I'll give you a hint暗示. It's a big number.
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给你一个提示:这个数字很大
15:56
(Laughter笑声)
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(众人笑)
15:59
I estimate估计, millions百万 of miles英里,
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我估计,有几百万英里
16:02
all packed打包 in your skull头骨.
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全部装在你头颅里
16:05
And if you appreciate欣赏 that number,
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如果你惊叹于这个数字
16:07
you can easily容易 see
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你不难看到
16:09
there is huge巨大 potential潜在 for mis-wiring误接线 of the brain.
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大脑中接错线的可能性极大
16:11
And indeed确实, the popular流行 press loves headlines新闻头条 like,
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确实,大众媒体特别青睐这样的头版头条
16:14
"Anorexic厌食症 brains大脑 are wired有线 differently不同,"
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“”厌食症患者大脑结构与众不同
16:16
or "Autistic自闭症 brains大脑 are wired有线 differently不同."
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或者“孤独症患者大脑结构与众不同”
16:18
These are plausible似是而非 claims索赔,
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这听起来似乎有道理
16:20
but in truth真相,
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但事实上
16:22
we can't see the brain's大脑的 wiring接线 clearly明确地 enough足够
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我们不能够清楚地看到大脑中的连接情况
16:24
to tell if these are really true真正.
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来证实这些说法正确与否
16:26
And so the technologies技术 for seeing眼看 connectomesconnectomes
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因此,显示连接体的科技
16:29
will allow允许 us to finally最后
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最终能够让我们
16:31
read mis-wiring误接线 of the brain,
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解读大脑中的连接错误
16:33
to see mental心理 disorders障碍 in connectomesconnectomes.
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看到连接体中的精神错乱
16:40
Sometimes有时 the best最好 way to test测试 a hypothesis假设
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有时候,检验假设的最佳方式
16:43
is to consider考虑 its most extreme极端 implication意义.
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是考虑最极端的情况
16:46
Philosophers哲学家 know this game游戏 very well.
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哲学家对这一招特别在行
16:50
If you believe that I am my connectome连接组,
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如果你相信我是我的连接体
16:53
I think you must必须 also accept接受 the idea理念
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我认为你就必须接受这个观点
16:56
that death死亡 is the destruction毁坏
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那就是:死亡就是
16:58
of your connectome连接组.
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你连接体的消亡
17:02
I mention提到 this because there are prophets先知 today今天
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我提出这一点是因为现今有一些预言家
17:05
who claim要求 that technology技术
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声称科技
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will fundamentally从根本上 alter改变 the human人的 condition条件
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将会从根本上改变人类的身体条件
17:11
and perhaps也许 even transform转变 the human人的 species种类.
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甚至使人类发生变异
17:14
One of their most cherished珍爱的 dreams
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他们最崇高的梦想之一
17:17
is to cheat作弊 death死亡
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就是躲避死亡
17:19
by that practice实践 known已知 as cryonics人体冷冻.
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使用一种叫做人体冷冻的做法
17:21
If you pay工资 100,000 dollars美元,
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如果你出十万美元
17:23
you can arrange安排 to have your body身体 frozen冻结的 after death死亡
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你就可以安排在你死后把你的身体冷冻起来
17:26
and stored存储 in liquid液体 nitrogen
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储存在液态氮中
17:28
in one of these tanks坦克 in an Arizona亚利桑那 warehouse仓库,
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装进这样一个罐子里保存在亚利桑那州的一个仓库里
17:30
awaiting等待 a future未来 civilization文明
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等待未来的先进文明
17:32
that is advanced高级 to resurrect复活 you.
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来为你解冻
17:36
Should we ridicule嘲笑 the modern现代 seekers求职者 of immortality不朽,
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我们应对这种寻求永生的现代人嗤之以鼻
17:38
calling调用 them fools傻瓜?
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叫他们疯子?
17:40
Or will they someday日后 chuckle暗笑
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还是他们有朝一日
17:42
over our graves坟墓?
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对着我们的墓碑发笑
17:45
I don't know --
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我不知道
17:47
I prefer比较喜欢 to test测试 their beliefs信仰, scientifically科学.
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我更想通过科学的方法检验他们的信仰
17:50
I propose提出 that we attempt尝试 to find a connectome连接组
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我提议我们争取找到
17:52
of a frozen冻结的 brain.
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一个冷冻大脑的连接体
17:54
We know that damage损伤 to the brain
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我们知道脑部的损伤
17:56
occurs发生 after death死亡 and during freezing冷冻.
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是在死后以及冷冻期间发生的
17:58
The question is: has that damage损伤 erased擦除 the connectome连接组?
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问题是:这种损伤是否已将连接体抹去?
18:01
If it has, there is no way that any future未来 civilization文明
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若果真如此,那么任何未来先进文明
18:04
will be able能够 to recover恢复 the memories回忆 of these frozen冻结的 brains大脑.
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都无法使这些冷冻大脑的记忆复原
18:07
Resurrection复活 might威力 succeed成功 for the body身体,
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复活术也许能对身体奏效
18:09
but not for the mind心神.
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但对思想却无能为力
18:11
On the other hand, if the connectome连接组 is still intact完整,
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另一方面,如果连接体依旧完整
18:14
we cannot不能 ridicule嘲笑 the claims索赔 of cryonics人体冷冻 so easily容易.
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我们就不能轻易说人体冷冻术是谬论了
18:20
I've described描述 a quest寻求
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我已经描述了
18:22
that begins开始 in the world世界 of the very small,
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在微观世界开始的探视
18:25
and propels推动 us to the world世界 of the far future未来.
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并驱使我们去探寻未来的世界
18:28
ConnectomesConnectomes will mark标记 a turning车削 point in human人的 history历史.
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连接体会成为人类历史的转折点
18:32
As we evolved进化 from our ape-like类人猿 ancestors祖先
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我们是从非洲大草原上的
18:34
on the African非洲人 savanna稀树草原,
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人猿祖先进化而来的
18:36
what distinguished杰出的 us was our larger brains大脑.
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而我们与他们之间的不同之处在于我们的脑体积更大
18:40
We have used our brains大脑 to fashion时尚
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我们已经利用大脑
18:42
ever more amazing惊人 technologies技术.
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创造了更为辉煌的科技成果
18:45
Eventually终于, these technologies技术 will become成为 so powerful强大
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最后,这些科技的力量变得如此强大
18:48
that we will use them to know ourselves我们自己
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以至于我们能利用它们
18:51
by deconstructing解构 and reconstructing重建
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来拆析并重组我们的大脑
18:54
our own拥有 brains大脑.
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以此了解我们自身
18:57
I believe that this voyage航程 of self-discovery自我发现
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我相信这一自我发现的旅程
19:00
is not just for scientists科学家们,
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不仅只为了科学家
19:03
but for all of us.
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更为了我们所有人
19:05
And I'm grateful感激 for the opportunity机会 to share分享 this voyage航程 with you today今天.
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我很感谢能有这次机会与大家共享这一旅程
19:08
Thank you.
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感谢大家
19:10
(Applause掌声)
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(热烈鼓掌)
Translated by Lili Liang
Reviewed by Alison Xiaoqiao Xie

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ABOUT THE SPEAKER
Sebastian Seung - Computational neuroscientist
Sebastian Seung is a leader in the new field of connectomics, currently the hottest space in neuroscience, which studies, in once-impossible detail, the wiring of the brain.

Why you should listen

In the brain, neurons are connected into a complex network. Sebastian Seung and his lab at MIT are inventing technologies for identifying and describing the connectome, the totality of connections between the brain's neurons -- think of it as the wiring diagram of the brain. We possess our entire genome at birth, but things like memories are not "stored" in the genome; they are acquired through life and accumulated in the brain. Seung's hypothesis is that "we are our connectome," that the connections among neurons is where memories and experiences get stored.

Seung and his collaborators, including Winfried Denk at the Max Planck Institute and Jeff Lichtman at Harvard University, are working on a plan to thin-slice a brain (probably starting with a mouse brain) and trace, from slice to slice, each neural pathway, exposing the wiring diagram of the brain and creating a powerful new way to visualize the workings of the mind. They're not the first to attempt something like this -- Sydney Brenner won a Nobel for mapping all the 7,000 connections in the nervous system of a tiny worm, C. elegans. But that took his team a dozen years, and the worm only had 302 nerve cells. One of Seung's breakthroughs is in using advanced imagining and AI to handle the crushing amount of data that a mouse brain will yield and turn it into richly visual maps that show the passageways of thought and sensation.

More profile about the speaker
Sebastian Seung | Speaker | TED.com