Allan Jones: A map of the brain

164,945 views ใƒป 2011-11-10

TED


์•„๋ž˜ ์˜๋ฌธ์ž๋ง‰์„ ๋”๋ธ”ํด๋ฆญํ•˜์‹œ๋ฉด ์˜์ƒ์ด ์žฌ์ƒ๋ฉ๋‹ˆ๋‹ค.

๋ฒˆ์—ญ: Davis Bae ๊ฒ€ํ† : Bianca Lee
00:15
Humans have long held a fascination
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์ธ๊ฐ„์€ ์•„์ฃผ ์˜ค๋žซ๋™์•ˆ ์ธ๊ฐ„์˜ ๋‡Œ์˜ ์‹ ๋น„์—
00:17
for the human brain.
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๋งค๋ฃŒ๋˜์–ด ์™”์Šต๋‹ˆ๋‹ค.
00:19
We chart it, we've described it,
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์šฐ๋ฆฌ๋Š” ๋‡Œ๋ฅผ ํ‘œ๋กœ ๊ทธ๋ฆฌ๊ณ , ์„ค๋ช…์„ ๋ง๋ถ™์ด๊ณ ,
00:22
we've drawn it,
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๊ทธ๋ฆผ์œผ๋กœ ํ‘œํ˜„ํ•˜์˜€์œผ๋ฉฐ,
00:24
we've mapped it.
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์ง€๋„๋กœ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค.
00:27
Now just like the physical maps of our world
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์ด์ œ ์˜ค๋Š˜๋‚ ์˜ ๊ธฐ์ˆ ์— ์˜ํ–ฅ์„ ๋ฐ›์•„
00:30
that have been highly influenced by technology --
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๋ณ€ํ™”ํ•˜๋Š” ์‹ค์ œ ์ง€๋„๋“ค์„ ์ƒ๊ฐํ•ด๋ณด์‹œ์ฃ 
00:33
think Google Maps,
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๊ตฌ๊ธ€ ์ง€๋„๋ฅผ ๋– ์˜ฌ๋ ค ๋ณด์‹œ๊ณ ,
00:35
think GPS --
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GPS ๋ฅผ ์ƒ๊ฐํ•ด ๋ณด์„ธ์š”
00:37
the same thing is happening for brain mapping
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์ด๋Ÿฐ ๊ธฐ์ˆ ์˜ ๋ณ€ํ™”๊ฐ€ ๋‘๋‡Œ ์ง€๋„ ์ƒ์„ฑ์—๋„
00:39
through transformation.
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์‘์šฉ๋˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
00:41
So let's take a look at the brain.
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์ž ์ด์ œ ๋‡Œ๋ฅผ ๊ด€์ฐฐํ•ด ๋ด…์‹œ๋‹ค.
00:43
Most people, when they first look at a fresh human brain,
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๋Œ€๋ถ€๋ถ„์˜ ์‚ฌ๋žŒ๋“ค์€ ์ธ๊ฐ„์˜ ๋‡Œ๋ฅผ ์‹ค์ œ๋กœ ๋ณด๊ณ ๋‚˜์„œ
00:46
they say, "It doesn't look what you're typically looking at
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์ด๋ ‡๊ฒŒ ๋งํ•ฉ๋‹ˆ๋‹ค, "์ด์ „์— ๋ณด์•˜๋˜ ๋‘๋‡Œ์™€๋Š”
00:49
when someone shows you a brain."
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๋ญ”๊ฐ€ ๋‹ฌ๋ผ ๋ณด์—ฌ์š”."
00:51
Typically, what you're looking at is a fixed brain. It's gray.
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๋ณดํ†ต, ์—ฌ๋Ÿฌ๋ถ„์ด ๋ณด์•„ ์™”๋˜ ๋‘๋‡Œ๋Š” ๋ฉˆ์ถฐ ์žˆ๋Š” ๋‘๋‡Œ์ž…๋‹ˆ๋‹ค. ํšŒ์ƒ‰์ด์ฃ .
00:54
And this outer layer, this is the vasculature,
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๊ทธ๋ฆฌ๊ณ  ์ด ๋ฐ”๊นฅ๋ง‰์€, ๋‘๋‡Œ๋ฅผ ๋‘˜๋Ÿฌ์‹ธ๊ณ  ์žˆ๋Š”
00:56
which is incredible, around a human brain.
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๊ฒƒ์€ ๋งฅ๊ด€๊ตฌ์กฐ๋กœ์„œ ๋Œ€๋‹จํ•œ ์กด์žฌ์ž…๋‹ˆ๋‹ค.
00:58
This is the blood vessels.
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์ด๊ฒƒ์€ ํ˜ˆ๊ด€๋“ค ์ž…๋‹ˆ๋‹ค.
01:00
20 percent of the oxygen
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์—ฌ๋Ÿฌ๋ถ„์˜ ํ์—์„œ ๋‚˜์˜จ
01:03
coming from your lungs,
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20%์˜ ์‚ฐ์†Œ์™€
01:05
20 percent of the blood pumped from your heart,
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์—ฌ๋Ÿฌ๋ถ„์˜ ์‹ฌ์žฅ์—์„œ ๋งŒ๋“ค์–ด๋‚ธ 20%์˜ ํ˜ˆ์•ก์ด
01:07
is servicing this one organ.
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์ด ์žฅ๊ธฐ ํ•œ๊ฐœ๋ฅผ ์ง€์›ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
01:09
That's basically, if you hold two fists together,
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์‰ฝ๊ฒŒ๋งํ•ด, ๋‘ ์ฃผ๋จน์„ ์ฅ์–ด๋ณด์‹œ๋ฉด
01:11
it's just slightly larger than the two fists.
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๋‡Œ๋Š” ๊ทธ ๋‘ ์ฃผ๋จน๋ณด๋‹ค ์•ฝ๊ฐ„ ๋” ํฐ ํฌ๊ธฐ์ž…๋‹ˆ๋‹ค.
01:13
Scientists, sort of at the end of the 20th century,
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20์„ธ๊ธฐ ๋ง๊ฒฝ ๊ณผํ•™์ž๋“ค์€
01:16
learned that they could track blood flow
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ํ˜ˆ์•ก์˜ ํ๋ฆ„์„ ๋น„์นจ๋ฒ”์ ์œผ๋กœ ์ถ”์ ํ•˜์—ฌ
01:18
to map non-invasively
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์—ฌ๋Ÿฌ ํ™œ๋™๋“ค์ด ์ด๋ค„์ง€๊ณ  ์žˆ๋Š” ๋‘๋‡Œ ๋‚ด๋ถ€์˜ ์ง€๋„๋ฅผ
01:21
where activity was going on in the human brain.
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๊ทธ๋ฆด ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌ ํ•˜์˜€์Šต๋‹ˆ๋‹ค.
01:24
So for example, they can see in the back part of the brain,
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์˜ˆ๋ฅผ ๋“ค์–ด, ๊ทธ๋“ค์€ ๋‘๋‡Œ์˜ ๋’ท ๋ถ€๋ถ„์„ ๋ณผ ์ˆ˜ ์žˆ์—ˆ์œผ๋ฉฐ
01:27
which is just turning around there.
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๋ฐ”๋กœ ์ด ๋ถ€๋ถ„์ด์ฃ . ์—ฌ๋Ÿฌ๋ถ„์ด ๋˜‘๋ฐ”๋กœ ์„œ ์žˆ์„์ˆ˜ ์žˆ๊ฒŒ
01:29
There's the cerebellum; that's keeping you upright right now.
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๋„์™€์ฃผ๋Š” ์ด๊ฒƒ์€ ์†Œ๋‡Œ์ด๋ฉฐ
01:31
It's keeping me standing. It's involved in coordinated movement.
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์กฐํ™”๋กœ์šด ๋™์ž‘์„ ํ–‰ํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค.
01:34
On the side here, this is temporal cortex.
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์ด ์˜†๋ถ€๋ถ„์€ ์ธก๋‘์—ฝ ํ”ผ์งˆ ์ž…๋‹ˆ๋‹ค.
01:37
This is the area where primary auditory processing --
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์—ฌ๊ธฐ์„œ ์ผ์ฐจ ์ฒญ๊ฐ ์ฒ˜๋ฆฌ๊ฐ€ ์ด๋ค„์ง€๊ฒŒ ๋˜๋ฉฐ
01:40
so you're hearing my words,
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์—ฌ๋Ÿฌ๋ถ„๋“ค์ด ์ œ ๋ง์„ ๋“ฃ๊ณ  ๋‚œ ๋’ค, ๊ทธ๊ฒƒ์„
01:42
you're sending it up into higher language processing centers.
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๋” ๋†’์€ ์ˆ˜์ค€์˜ ์ค‘์•™ ์–ธ์–ด์ฒ˜๋ฆฌ ์žฅ์น˜๋กœ ๋ณด๋‚ด๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค.
01:44
Towards the front of the brain
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๋‘๋‡Œ์˜ ์•ž ๋ฐฉํ–ฅ์—์„œ๋Š”
01:46
is the place in which all of the more complex thought, decision making --
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๋” ๋ณต์žกํ•œ ์ƒ๊ฐ๊ณผ ๊ฒฐ์ •์„ ๋‚ด๋ฆฌ๋Š” ๋ถ€๋ถ„์ด
01:49
it's the last to mature in late adulthood.
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์œ„์น˜ํ•˜๋ฉฐ ์„ฑ์ธ๊ธฐ ๋ง์— ๋งˆ์ง€๋ง‰์œผ๋กœ ์„ฑ์ˆ™ํ•ด์ง€๋Š” ๋ถ€๋ถ„ ์ž…๋‹ˆ๋‹ค.
01:53
This is where all your decision-making processes are going on.
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๋ชจ๋“  ์˜์‚ฌ ๊ฒฐ์ •์„ ์—ฌ๊ธฐ์„œ ๋‚ด๋ฆฝ๋‹ˆ๋‹ค.
01:56
It's the place where you're deciding right now
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ํ˜„์žฌ ์—ฌ๋Ÿฌ๋ถ„์ด ๊ฒฐ์ •์„ ๋‚ด๋ฆฌ๊ณ  ์žˆ๋Š” ๋ถ€๋ถ„์ด๋ฉฐ
01:58
you probably aren't going to order the steak for dinner.
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์˜ค๋Š˜ ์ €๋…์—” ์Šคํ…Œ์ดํฌ๋ฅผ ๋จน์ง€ ๋ง์•„์•ผ์ง€ ๋ผ๋Š” ๊ฒฐ์ •๋„ ๋‚ด๋ฆฝ๋‹ˆ๋‹ค.
02:01
So if you take a deeper look at the brain,
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์ž ์ด์ œ ๋” ๊นŠ๊ฒŒ ๋‘๋‡Œ๋ฅผ ๋“ค์—ฌ๋‹ค ๋ณด๋ฉด
02:03
one of the things, if you look at it in cross-section,
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์•„์‹œ๊ฒ ์ง€๋งŒ, ๋‘๋‡Œ์˜ ๋‹จ๋ฉด์„ ํ†ตํ•˜์—ฌ
02:05
what you can see
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์ œ๋Œ€๋กœ ๋œ ๋‘๋‡Œ์˜ ๊ตฌ์กฐ๋ฅผ
02:07
is that you can't really see a whole lot of structure there.
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์•Œ์•„๋ณด๊ธฐ๊ฐ€ ์‰ฝ์ง€ ์•Š๋‹ค๋Š” ๊ฒƒ ์ž…๋‹ˆ๋‹ค.
02:10
But there's actually a lot of structure there.
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์‚ฌ์‹ค, ์ด๊ณณ์—๋Š” ๋งŽ์€ ์กฐ์ง๋“ค์ด ์กด์žฌํ•˜๊ณ  ์žˆ์œผ๋ฉฐ
02:12
It's cells and it's wires all wired together.
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์„ธํฌ๋“ค๊ณผ ์„ ๋“ค์ด ๋‹ค๊ฐ™์ด ์—ฐ๊ฒฐ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค.
02:14
So about a hundred years ago,
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๊ทธ๋ž˜์„œ ์•ฝ 100๋…„ ์ „,
02:16
some scientists invented a stain that would stain cells.
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๋ช‡๋ช‡ ๊ณผํ•™์ž๋“ค์€ ์„ธํฌ ์—ผ์ƒ‰์ œ๋ฅผ ๊ฐœ๋ฐœํ–ˆ์Šต๋‹ˆ๋‹ค.
02:18
And that's shown here in the the very light blue.
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๋ณด์‹œ๋Š” ๋ฐ์€ ํŒŒ๋ž€์ƒ‰์ด ๊ทธ๊ฒƒ์ž…๋‹ˆ๋‹ค.
02:21
You can see areas
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์ •์ƒ์ ์ธ ์„ธํฌ๊ธฐ๊ด€๋“ค์ด ์—ผ์ƒ‰๋˜๋Š”
02:23
where neuronal cell bodies are being stained.
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๋ถ€๋ถ„๋“ค์„ ์ง€๊ธˆ ๋ณด์‹œ๊ณ  ๊ณ„์‹ญ๋‹ˆ๋‹ค.
02:25
And what you can see is it's very non-uniform. You see a lot more structure there.
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๋งค์šฐ ์ผ๊ด€์„ฑ์ด ์—†์–ด ๋ณด์ด์ฃ . ํ›จ์”ฌ ๋” ๋งŽ์€ ์กฐ์ง์ด ๋ณด์ž…๋‹ˆ๋‹ค.
02:28
So the outer part of that brain
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์ง€๊ธˆ ๋ณด์‹œ๋Š” ๋‘๋‡Œ์˜ ๋ฐ”๊นฅ๋ถ€๋ถ„์€
02:30
is the neocortex.
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์‹ ํ”ผ์งˆ ์ด๋ผ๊ณ  ํ•ฉ๋‹ˆ๋‹ค.
02:32
It's one continuous processing unit, if you will.
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์ง€์†์ ์ธ ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•˜๋Š” ๋‹จ์ผ์ฒด๋ผ๊ณ  ์ƒ๊ฐํ•˜์‹œ๋ฉด ๋ฉ๋‹ˆ๋‹ค.
02:35
But you can also see things underneath there as well.
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ํ•˜์ง€๋งŒ ๊ทธ ์•„๋ž˜์— ์žˆ๋Š” ๊ฒƒ๋“ค๋„ ๊ฐ™์ด ๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
02:37
And all of these blank areas
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๊ทธ๋ฆฌ๊ณ  ์ด ๋น„์–ด์žˆ๋Š” ์˜์—ญ๋“ค ์—ญ์‹œ
02:39
are the areas in which the wires are running through.
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๋งŽ์€ ๊ฒƒ๋“ค์ด ์—ฐ๊ฒฐ๋˜์–ด ์žˆ๋Š” ์˜์—ญ๋“ค ์ž…๋‹ˆ๋‹ค.
02:41
They're probably less cell dense.
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์„ธํฌ ๋ฐ€๋„๊ฐ€ ์ข€ ๋” ๋‚ฎ๊ฒ ์ฃ .
02:43
So there's about 86 billion neurons in our brain.
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์ธ๊ฐ„์˜ ๋‡Œ์—๋Š” ์•ฝ 860์–ต๊ฐœ์˜ ๋‰ด๋Ÿฐ์ด ์žˆ์Šต๋‹ˆ๋‹ค.
02:47
And as you can see, they're very non-uniformly distributed.
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๋ณด์‹œ๋‹ค์‹œํ”ผ, ๋งค์šฐ ๋น„๊ท ์ผ์ ์œผ๋กœ ๋ถ„ํฌ๋˜์–ด ์žˆ์œผ๋ฉฐ
02:50
And how they're distributed really contributes
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์–ด๋–ป๊ฒŒ ๋ถ„ํฌ๋˜์–ด ์žˆ๋Š”์ง€๊ฐ€ ๊ทธ๋“ค์˜
02:52
to their underlying function.
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๊ธฐ๋ณธ์ ์ธ ๊ธฐ๋Šฅ์— ์ค‘์š”ํ•œ ๊ธฐ์—ฌ๋ฅผ ํ•ฉ๋‹ˆ๋‹ค.
02:54
And of course, as I mentioned before,
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๊ทธ๋ฆฌ๊ณ  ๋ฌผ๋ก , ์ œ๊ฐ€ ๋งํ–ˆ๋‹ค์‹œํ”ผ,
02:56
since we can now start to map brain function,
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๋‡Œ ๊ธฐ๋Šฅ์„ ์ง€๋„๋กœ ๊ทธ๋ ค๋‚ด๋Š” ๊ฒƒ์ด ๊ฐ€๋Šฅํ•˜๊ธฐ์—,
02:59
we can start to tie these into the individual cells.
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๊ฐ๊ฐ์˜ ์„ธํฌ์— ์—ฐ๊ด€์ง€์–ด ๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
03:02
So let's take a deeper look.
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์ž ๊ทธ๋Ÿผ ํ•œ๋‹จ๊ณ„ ๋” ๋“ค์–ด๊ฐ€ ๋ณผ๊นŒ์š”.
03:04
Let's look at neurons.
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๋‰ด๋Ÿฐ์„ ์‚ดํŽด๋ด…์‹œ๋‹ค.
03:06
So as I mentioned, there are 86 billion neurons.
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๋ง์”€๋“œ๋ ธ๋‹ค์‹œํ”ผ, 860์–ต๊ฐœ์˜ ๋‰ด๋Ÿฐ์ด ์กด์žฌํ•˜๊ณ  ์žˆ์œผ๋ฉฐ
03:08
There are also these smaller cells as you'll see.
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๊ทธ๋ณด๋‹ค ๋” ์ž‘์€ ์„ธํฌ๋“ค๋„ ์—ฌ๋Ÿฌ๋ถ„์€ ๋ณด์‹œ๊ฒŒ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค.
03:10
These are support cells -- astrocytes glia.
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์•„๊ต์„ธํฌ ๋ผ๊ณ  ๋ถˆ๋ฆฌ๋Š” ์ง€์›์„ธํฌ๋“ค ์ž…๋‹ˆ๋‹ค.
03:12
And the nerves themselves
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๊ทธ๋ฆฌ๊ณ  ์‹ ๊ฒฝ๋“ค ์ž์ฒด๊ฐ€
03:15
are the ones who are receiving input.
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์ž…๋ ฅ์„ ๋ฐ›๊ณ  ์žˆ๋Š” ์ค‘์ด๋ฉฐ
03:17
They're storing it, they're processing it.
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๋ณด๊ด€ํ•˜๊ณ , ์ฒ˜๋ฆฌํ•˜๋Š” ์ž‘์—…๋„ ํ•ฉ๋‹ˆ๋‹ค.
03:19
Each neuron is connected via synapses
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๊ฐ ๋‰ด๋Ÿฐ์€ ์—ฐ์ ‘์„ ํ†ตํ•ด ๋‘๋‡Œ์˜
03:23
to up to 10,000 other neurons in your brain.
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์ตœ๋Œ€ 1๋งŒ๊ฐœ ๊นŒ์ง€์˜ ๋‹ค๋ฅธ ๋‰ด๋Ÿฐ๋“ค๊ณผ ์—ฐ๊ฒฐ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค.
03:26
And each neuron itself
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๊ทธ๋ฆฌ๊ณ  ๊ฐ๊ฐ์˜ ๋‰ด๋Ÿฐ์€
03:28
is largely unique.
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๋งค์šฐ ํŠน์ดํ•ฉ๋‹ˆ๋‹ค.
03:30
The unique character of both individual neurons
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๊ฐ๊ฐ์˜ ๋‰ด๋Ÿฐ๋“ค๊ณผ ๋‘๋‡Œ ์•ˆ์—
03:32
and neurons within a collection of the brain
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์œ„์น˜ํ•œ ๋‰ด๋Ÿฐ์ง‘ํ•ฉ์˜ ํŠน์„ฑ์€
03:34
are driven by fundamental properties
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์ƒํ™”ํ•™ ๊ณ ์œ ์˜ ์„ฑ์งˆ์— ๋”ฐ๋ผ
03:37
of their underlying biochemistry.
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ํ–‰๋™ํ•˜๊ฒŒ ๋ฉ๋‹ˆ๋‹ค.
03:39
These are proteins.
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์ด๊ฒƒ๋“ค์€ ๋‹จ๋ฐฑ์งˆ ์ž…๋‹ˆ๋‹ค.
03:41
They're proteins that are controlling things like ion channel movement.
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์ด ๋‹จ๋ฐฑ์งˆ๋“ค์€ ์ด์˜จ ์ฑ„๋„์˜ ์›€์ง์ž„์„ ํ†ต์ œํ•˜๋ฉฐ
03:44
They're controlling who nervous system cells partner up with.
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์‹ ๊ฒฝ์‹œ์Šคํ…œ ์„ธํฌ์™€ ๋ˆ„๊ฐ€ ๊ต์‹ ์„
03:48
And they're controlling
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์ด๋ฃจ๋Š”๊ฐ€๋ฅผ ํ†ต์ œํ•จ๊ณผ ๋”๋ถˆ์–ด
03:50
basically everything that the nervous system has to do.
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๋‹ค๋ฅธ ๋ชจ๋“  ์‹ ๊ฒฝ ์‹œ์Šคํ…œ์ด ํ•˜๋Š”์ผ์„ ๊ด€์žฅํ•ฉ๋‹ˆ๋‹ค.
03:52
So if we zoom in to an even deeper level,
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์ž ์—ฌ๊ธฐ์„œ ํ•œ๋‹จ๊ณ„ ๋” ๊นŠ์€ ๋ ˆ๋ฒจ๋กœ ํ™•๋Œ€ํ•ด์„œ ๋ณด๋ฉด,
03:55
all of those proteins
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์ด ๋ชจ๋“  ๋‹จ๋ฐฑ์งˆ์ด
03:57
are encoded by our genomes.
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๊ฐ์ž์˜ ๊ฒŒ๋†ˆ์— ์˜ํ•˜์—ฌ ์•”ํ˜ธํ™” ๋ฉ๋‹ˆ๋‹ค.
03:59
We each have 23 pairs of chromosomes.
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์—ฌ๋Ÿฌ๋ถ„์€ ๊ฐ๊ฐ 23์Œ์˜ ์—ผ์ƒ‰์ฒด๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
04:02
We get one from mom, one from dad.
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์šฐ๋ฆฌ๋Š” ํ•œ๊ฐœ๋Š” ์–ด๋จธ๋‹ˆ๋กœ๋ถ€ํ„ฐ, ํ•œ๊ฐœ๋Š” ์•„๋ฒ„์ง€๋กœ๋ถ€ํ„ฐ ๋ฐ›์Šต๋‹ˆ๋‹ค.
04:04
And on these chromosomes
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๊ทธ๋ฆฌ๊ณ  ์ด ์—ผ์ƒ‰์ฒด์—๋Š”
04:06
are roughly 25,000 genes.
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2๋งŒ 5์ฒœ๊ฐœ์˜ ์œ ์ „์ž๊ฐ€ ์กด์žฌํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
04:08
They're encoded in the DNA.
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DNA ์†์— ์ธ์‹๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค.
04:10
And the nature of a given cell
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๊ทธ๋ฆฌ๊ณ  ๊ธฐ์ดˆ ์ƒํ™”ํ•™
04:13
driving its underlying biochemistry
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์ž‘์šฉ์„ ์ด๋„๋Š” ์„ธํฌ์˜ ๋ณธ์„ฑ์€
04:15
is dictated by which of these 25,000 genes
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2๋งŒ 5์ฒœ๊ฐœ์˜ ์œ ์ „์ž์ค‘ ์–ด๋–ค ์œ ์ „์ž๊ฐ€
04:18
are turned on
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๋ฐ˜์‘ํ•˜๋Š”๊ฐ€์— ๋”ฐ๋ผ
04:20
and at what level they're turned on.
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๊ทธ๋ฆฌ๊ณ  ์–ด๋–ค ๋ ˆ๋ฒจ์—์„œ ๋ฐ˜์‘ํ•˜๋Š”์ง€์— ๋”ฐ๋ผ ์ •ํ•ด์ง€๊ฒŒ ๋ฉ๋‹ˆ๋‹ค.
04:22
And so our project
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๊ทธ๋ž˜์„œ ์šฐ๋ฆฌ์˜ ํ”„๋กœ์ ํŠธ๋Š”
04:24
is seeking to look at this readout,
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์ด๋Ÿฐ 2๋งŒ 5์ฒœ๊ฐœ์˜ ์œ ์ „์ž์ค‘ ์–ด๋–ค ์œ ์ „์ž๊ฐ€ ๋ฐ˜์‘ํ•˜๋Š”์ง€๋ฅผ
04:27
understanding which of these 25,000 genes is turned on.
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์ž๋ฃŒํ•ด๋…์„ ํ†ตํ•˜์—ฌ ์ดํ•ดํ•˜๋Š” ๊ฒƒ์— ์žˆ์Šต๋‹ˆ๋‹ค.
04:30
So in order to undertake such a project,
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์ด๋Ÿฐ ํ”„๋กœ์ ํŠธ์— ์ฐฉ์ˆ˜ํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š”,
04:33
we obviously need brains.
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๋ฌผ๋ก  ๋˜‘๋˜‘ํ•œ ๋‘๋‡Œ๋“ค์ด ํ•„์š”ํ•ฉ๋‹ˆ๋‹ค.
04:36
So we sent our lab technician out.
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๊ทธ๋ฆฌ์„œ ์šฐ๋ฆฌ์˜ ์—ฐ๊ตฌ์›์„ ๋ณด๋ƒˆ์Šต๋‹ˆ๋‹ค.
04:39
We were seeking normal human brains.
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์šฐ๋ฆฌ๋Š” ํ‰๋ฒ”ํ•œ ์ธ๊ฐ„์˜ ๋‡Œ๋ฅผ ์ฐพ๊ณ  ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค.
04:41
What we actually start with
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์šฐ๋ฆฌ๊ฐ€ ์‹ค์ œ๋กœ ์‹œ์ž‘ํ•œ ๊ณณ์€
04:43
is a medical examiner's office.
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ํ•œ ๋ถ€๊ฒ€์†Œ ์˜€์Šต๋‹ˆ๋‹ค.
04:45
This a place where the dead are brought in.
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์ด๊ณณ์€ ์‹œ์ฒด๊ฐ€ ๋ชจ์ด๋Š” ์žฅ์†Œ์ž…๋‹ˆ๋‹ค.
04:47
We are seeking normal human brains.
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์šฐ๋ฆฌ๋Š” ํ‰๋ฒ”ํ•œ ์ธ๊ฐ„ ๋‡Œ๋“ค์„ ์ฐพ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
04:49
There's a lot of criteria by which we're selecting these brains.
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ํ‰๋ฒ”ํ•œ ๋‡Œ๋ž€ ๋งŽ์€ ๊ธฐ์ค€์— ์˜ํ•˜์—ฌ ์ •ํ•ด์ง‘๋‹ˆ๋‹ค.
04:52
We want to make sure
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์šฐ๋ฆฌ๊ฐ€ ํ™•์‹คํžˆ ํ•˜๋ ค๋Š” ๊ฒƒ์€
04:54
that we have normal humans between the ages of 20 to 60,
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20์„ธ๋ถ€ํ„ฐ 60์„ธ ์‚ฌ์ด์˜
04:57
they died a somewhat natural death
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์ž์—ฐ์‚ฌ๋กœ ์ˆจ์กŒ์œผ๋ฉฐ
04:59
with no injury to the brain,
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๋‡Œ์— ์ถฉ๊ฒฉ์„ ๋ฐ›์ง€ ์•Š์•˜์œผ๋ฉฐ
05:01
no history of psychiatric disease,
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์ •์‹ ๋ณ‘๋ ฅ๋„ ์—†์œผ๋ฉฐ
05:03
no drugs on board --
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์•ฝ๋ฌผ ๋ณต์šฉ์ค‘๋„ ์•„๋‹Œ ์ƒํƒœ์—์„œ ์‚ฌ๋งํ•œ ๊ฒฝ์šฐ์ด๋ฉฐ
05:05
we do a toxicology workup.
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๋…๊ทน๋ฌผ์˜ ์กด์žฌ๋„ ํ™•์ธํ•ฉ๋‹ˆ๋‹ค.
05:07
And we're very careful
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๊ทธ๋ฆฌ๊ณ  ์ €ํฌ๋Š” ๋งค์šฐ ์กฐ์‹ฌ์Šค๋Ÿฝ๊ฒŒ
05:09
about the brains that we do take.
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์ด ๋‘๋‡Œ๋“ค์„ ๋‹ค๋ฃจ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
05:11
We're also selecting for brains
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ํ•œํŽธ, ๋‡Œ ์กฐ์ง์„ ์–ป์„์ˆ˜ ์žˆ๋Š”
05:13
in which we can get the tissue,
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๋‘๋‡Œ๋“ค์„ ๊ณจ๋ผ๋‚ด๊ณ  ์žˆ์œผ๋ฉฐ
05:15
we can get consent to take the tissue
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์‚ฌํ›„ 24์‹œ๊ฐ„ ์•ˆ์— ๋‡Œ ์กฐ์ง์„ ์ถ”์ถœํ• ์ˆ˜ ์žˆ๋Š”
05:17
within 24 hours of time of death.
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ํ—ˆ๊ฐ€๋ฅผ ๋ฐ›์€ ํ›„ ์ถ”์ถœ์ด ์ด๋ค„์ง‘๋‹ˆ๋‹ค.
05:19
Because what we're trying to measure, the RNA --
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์œ ์ „์ž์— ์ €์žฅ๋˜์–ด์žˆ๋Š” ๋งค์šฐ ๋ถˆ์•ˆ์ •ํ•œ
05:22
which is the readout from our genes --
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RNA (Ribonucleic Acid: ๋ฆฌ๋ณดํ•ต์‚ฐ) ์„
05:24
is very labile,
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์ธก์ •ํ•ด์•ผ ํ•˜๊ธฐ ๋•Œ๋ฌธ์—
05:26
and so we have to move very quickly.
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๋น ๋ฅธ ์ž‘์—…์ˆ˜ํ–‰์ด ์ด๋ค„์ ธ์•ผ ํ•ฉ๋‹ˆ๋‹ค.
05:28
One side note on the collection of brains:
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ํ•œ๊ฐ€์ง€ ๋‘๋‡Œ๋“ค์˜ ๋ชจ์Œ์— ๊ด€ํ•˜์—ฌ ์ด์•ผ๊ธฐ ๋ง๋ถ™์ด์ž๋ฉด,
05:31
because of the way that we collect,
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์ €ํฌ๊ฐ€ ์ˆ˜์ง‘ํ•˜๋Š” ๋ฐฉ์‹์ด
05:33
and because we require consent,
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๋ฒ•์ ์ธ ๋™์˜๋ฅผ ์š”๊ตฌํ•˜๊ธฐ ๋•Œ๋ฌธ์—,
05:35
we actually have a lot more male brains than female brains.
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์—ฌ์„ฑ๋“ค์˜ ๋‘๋‡Œ๋ณด๋‹ค ์•„์ฃผ ๋งŽ์€ ๋‚จ์„ฑ๋“ค์˜ ๋‘๋‡Œ๋ฅผ ๋ณด์œ ํ•˜๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.
05:38
Males are much more likely to die an accidental death in the prime of their life.
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๋‚จ์„ฑ๋“ค์€ ์—ฌ์„ฑ๋ณด๋‹ค ์ธ์ƒ์˜ ํ™ฉ๊ธˆ๊ธฐ๋•Œ ์‚ฌ๊ณ ์‚ฌ๋กœ ์ˆจ์งˆ ํ™•๋ฅ ์ด ํ›จ์”ฌ ๋” ๋†’๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.
05:41
And men are much more likely
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๊ทธ๋ฆฌ๊ณ  ๋‚จ์ž๋“ค์€ ์—ฌ์ž๋“ค๋ณด๋‹ค
05:43
to have their significant other, spouse, give consent
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์ž์‹ ์˜ ๋ฐ˜๋ ค์ž๋‚˜, ๋ฐฐ์šฐ์ž์—๊ฒŒ ์ž์‹ ์˜ ๋‘๋‡Œ๊ธฐ์ฆ ํ—ˆ๊ฐ€๋ฅผ ํ•  ํ™•๋ฅ ์ด
05:46
than the other way around.
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์›”๋“ฑํžˆ ๋†’๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.
05:48
(Laughter)
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(์›ƒ์Œ)
05:52
So the first thing that we do at the site of collection
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๋‘๋‡Œ์ˆ˜์ง‘์˜ ์ฒซ ๋‹จ๊ณ„๋Š”
05:54
is we collect what's called an MR.
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Magnetic Resonance (์ž๊ธฐ๊ณต๋ช…) ์„ ์ˆ˜์ง‘ํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
05:56
This is magnetic resonance imaging -- MRI.
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์ด๊ฒƒ์€ MRI (Magnetic Resonance Imaging: ์ž๊ธฐ๊ณต๋ช…์˜์ƒ) ์ž…๋‹ˆ๋‹ค.
05:58
It's a standard template by which we're going to hang the rest of this data.
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์ด๊ฒƒ์€ ์šฐ๋ฆฌ๊ฐ€ ์•ž์œผ๋กœ ์ด ์ž๋ฃŒ๋“ค์„ ์˜ฌ๋ ค ๋†“์„ ํ‘œ์ค€ ๊ฒฌ๋ณธ์ž…๋‹ˆ๋‹ค.
06:01
So we collect this MR.
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์ด๋ ‡๊ฒŒ ์ž๊ธฐ๊ณต๋ช… ์ž๋ฃŒ๋ฅผ ์ˆ˜์ง‘ํ•ฉ๋‹ˆ๋‹ค.
06:03
And you can think of this as our satellite view for our map.
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๋งˆ์น˜ ์œ„์„ฑ์—์„œ ๋ณด๋Š” ์ง€๋„์™€ ๊ฐ™์€ ๋งฅ๋ฝ์ž…๋‹ˆ๋‹ค.
06:05
The next thing we do
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๋‹ค์Œ์œผ๋กœ ์šฐ๋ฆฌ๊ฐ€ ์ˆ˜์ง‘ํ•˜๋Š” ๊ฒƒ์€
06:07
is we collect what's called a diffusion tensor imaging.
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Diffusion Tensor Imaging (DTI :ํ™•์‚ฐํ…์„œ์˜์ƒ) ์ด๋ฉฐ
06:10
This maps the large cabling in the brain.
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๋‘๋‡Œ์˜ ํฐ ์—ฐ๊ฒฐ์„ ๋“ค์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค.
06:12
And again, you can think of this
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๊ทธ๋ฆฌ๊ณ , ์ด๊ฒƒ์„ ๋ฏธ๊ตญ์˜ ์ฃผ์™€ ์ฃผ ์‚ฌ์ด๋ฅผ ์ž‡๋Š” ๊ณ ์†๋„๋กœ์—
06:14
as almost mapping our interstate highways, if you will.
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๋น—๋Œ€์–ด ์ƒ์ƒํ•ด ๋ณด์‹ ๋‹ค๋ฉด ์•„๋งˆ ์ดํ•ด๊ฐ€ ๋น ๋ฅด์‹ค ๊ฒ๋‹ˆ๋‹ค.
06:16
The brain is removed from the skull,
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๋‘๋‡Œ๋Š” ๋‘๊ฐœ๊ณจ์—์„œ ๋ถ„๋ฆฌ๋˜์–ด
06:18
and then it's sliced into one-centimeter slices.
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1์„ผํ‹ฐ๋ฏธํ„ฐ ๋‘๊ป˜์˜ ๋‹จ๋ฉด๋“ค๋กœ ์ž˜๋ฆฝ๋‹ˆ๋‹ค.
06:21
And those are frozen solid,
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๊ทธ๋ฆฌ๊ณ  ๋”ฑ๋”ฑํ•˜๊ฒŒ ์–ผ๋ ค์ง€๊ณ  ๋‚œ ๋’ค,
06:23
and they're shipped to Seattle.
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์‹œ์• ํ‹€๋กœ ๋ฐฐ์†ก๋˜์–ด์ง‘๋‹ˆ๋‹ค.
06:25
And in Seattle, we take these --
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๊ทธ๋ฆฌ๊ณ  ์‹œ์• ํ‹€์—์„œ๋Š”, ์ด๊ฒƒ๋“ค์„ ๋ฐ›์•„์„œ --
06:27
this is a whole human hemisphere --
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๋ณด์‹œ๋Š” ๊ฒƒ์€ ์ธ๊ฐ„ ๋ฐ˜๊ตฌ ์ „์ฒด ์ž…๋‹ˆ๋‹ค --
06:29
and we put them into what's basically a glorified meat slicer.
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๊ธฐ๋ณธ์ ์œผ๋กœ ๊ณ ๊ธฐ๋ฅผ ์–‡๊ฒŒ ์ฐ์–ด๋‚ด๋Š” ๊ธฐ๊ตฌ์— ์˜ฌ๋ฆฌ๊ณ 
06:31
There's a blade here that's going to cut across
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์—ฌ๊ธฐ์žˆ๋Š” ์นผ๋‚ ์ด ๋‡Œ ์กฐ์ง์˜
06:33
a section of the tissue
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ํ•œ ๋ถ€๋ถ„์„ ๊ฐ€๋กœ์งˆ๋Ÿฌ ์ž˜๋ผ ๋‚ด์–ด
06:35
and transfer it to a microscope slide.
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ํ˜„๋ฏธ๊ฒฝ ์Šฌ๋ผ์ด๋“œ ์œ„๋กœ ์˜ฎ๊น๋‹ˆ๋‹ค.
06:37
We're going to then apply one of those stains to it,
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๊ทธ๋ฆฌ๊ณ  ์šฐ๋ฆฌ๋Š” ์—ผ๋ฃŒ์ค‘ ํ•œ๊ฐ€์ง€ ์ƒ‰์„ ๊ทธ๊ณณ์— ์ž…ํžˆ๊ณ 
06:39
and we scan it.
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์Šค์บ”์„ ํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค.
06:41
And then what we get is our first mapping.
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๊ทธ๋ฆฌ๊ณ  ๋‚˜๋ฉด ์ฒซ๋ฒˆ์งธ ์ง€๋„์ œ์ž‘์ด ์™„์„ฑ๋ฉ๋‹ˆ๋‹ค.
06:44
So this is where experts come in
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์ด์ œ ์ „๋ฌธ๊ฐ€๋“ค์ด ์ฐธ์—ฌํ•˜์—ฌ
06:46
and they make basic anatomic assignments.
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๊ธฐ๋ณธ์ ์ธ ํ•ด๋ถ€ ๋ช…์นญ์ด ๋ฐฐ์ •๋˜์–ด์ง€๋ฉฐ ์ด๋Ÿฐ
06:48
You could consider this state boundaries, if you will,
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๊ฝค ๊ด‘๋ฒ”์œ„ํ•œ ์œค๊ณฝ์„ ๋“ค์€ ๋ฏธ๊ตญ์˜ ์ฃผ ์‚ฌ์ด์˜
06:51
those pretty broad outlines.
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๊ฒฝ๊ณ„์„ ๋“ค ์ด๋ผ๊ณ ๋„ ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
06:53
From this, we're able to then fragment that brain into further pieces,
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์ด๊ฒƒ์„ ํ†ตํ•˜์—ฌ ๋‡Œ๋ฅผ ๋” ์ž‘์€ ์กฐ๊ฐ์œผ๋กœ ๋‚˜๋ˆˆ ๋’ค์—
06:57
which then we can put on a smaller cryostat.
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๋” ์ž‘์€ ์ €์˜จ์œ ์ง€์žฅ์น˜์— ๋„ฃ์Šต๋‹ˆ๋‹ค.
06:59
And this is just showing this here --
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๊ทธ๋ฆฌ๊ณ  ์ง€๊ธˆ ๋ณด์‹œ๋‹ค์‹œํ”ผ --
07:01
this frozen tissue, and it's being cut.
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์ด ์–ผ์–ด๋ถ™์€ ์กฐ์ง์€ ์ž˜๋ฆฌ๊ณ  ์žˆ๋Š” ์ค‘์ž…๋‹ˆ๋‹ค.
07:03
This is 20 microns thin, so this is about a baby hair's width.
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๋‘๊ป˜๋Š” 20 ๋งˆ์ดํฌ๋ก ์œผ๋กœ ์•„๊ธฐ๋“ค์˜ ๋จธ๋ฆฌ์นด๋ฝ ๋‘๊ป˜ ์ •๋„๋กœ
07:06
And remember, it's frozen.
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์•„์ง ์–ผ์–ด ์žˆ์Šต๋‹ˆ๋‹ค.
07:08
And so you can see here,
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์—ฌ๊ธฐ์„œ ๋ณด์‹œ๋‹ค์‹œํ”ผ
07:10
old-fashioned technology of the paintbrush being applied.
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๋ถ“์„ ์ด์šฉํ•œ ๊ตฌ์‹์ ์ธ ๊ธฐ์ˆ ์˜ ์ž‘์—…์„ ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
07:12
We take a microscope slide.
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ํ˜„๋ฏธ๊ฒฝ ์Šฌ๋ผ์ด๋“œ๋ฅผ ๊ฐ€์ง€๊ณ  ์™€์„œ
07:14
Then we very carefully melt onto the slide.
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๋งค์šฐ ์กฐ์‹ฌ์Šค๋Ÿฝ๊ฒŒ ์Šฌ๋ผ์ด๋“œ ์œ„์— ๋…น์ž…๋‹ˆ๋‹ค.
07:17
This will then go onto a robot
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๊ทธ๋ฆฌ๊ณ  ๋กœ๋ด‡์—๊ฒŒ ๋ณด๋‚ด
07:19
that's going to apply one of those stains to it.
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๊ทธ๊ณณ์—์„œ ์ƒ‰์„ ์ž…ํžˆ๋Š” ์ž‘์—…์ด ์ง„ํ–‰๋ฉ๋‹ˆ๋‹ค.
07:26
And our anatomists are going to go in and take a deeper look at this.
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ํ•ด๋ถ€ํ•™์ž๋“ค์€ ์ด๊ฒƒ์„ ๊ฐ€์ง€๊ณ  ๋” ๊นŠ์€ ๊ด€์ฐฐ์„ ํ•ฉ๋‹ˆ๋‹ค.
07:29
So again this is what they can see under the microscope.
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ํ˜„๋ฏธ๊ฒฝ์œผ๋กœ ๋ณด๋ฉด ์–ด๋ ‡๊ฒŒ ๋ณด์ž…๋‹ˆ๋‹ค.
07:31
You can see collections and configurations
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ํฌ๊ณ  ์ž‘์€ ์„ธํฌ๋“ค์˜ ๋ชจ์Œ๊ณผ ๊ตฌ์„ฑ์ด
07:33
of large and small cells
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์—ฌ๋Ÿฌ ์ง€์—ญ์— ๋ญ‰์ณ์žˆ๋Š” ๊ฒƒ์„
07:35
in clusters and various places.
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๋ณด์‹ค ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
07:37
And from there it's routine. They understand where to make these assignments.
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๊ทธ๋ฆฌ๊ณ  ์—ฌ๊ธฐ์„œ๋ถ€ํ„ฐ๋Š” ๊ณ„์† ๋ฐ˜๋ณต์ž…๋‹ˆ๋‹ค. ํ•ด๋ถ€ํ•™์ž๋“ค์€ ์–ด๋””์— ๋ฌด์—‡์„
07:39
And they can make basically what's a reference atlas.
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๋ฐฐ์น˜ํ•ด์•ผ ํ• ์ง€ ์•Œ๊ณ  ์žˆ์œผ๋ฉฐ ์ด๋ ‡๊ฒŒ ๋‘๋‡Œ ์ง€๋„์ฑ…์ด ์™„์„ฑ๋ฉ๋‹ˆ๋‹ค.
07:42
This is a more detailed map.
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์ด๊ฒƒ์€ ๋”์šฑ ์ž์„ธํ•œ ์ง€๋„์ž…๋‹ˆ๋‹ค.
07:44
Our scientists then use this
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์ €ํฌ ๊ณผํ•™์ž๋“ค์€ ์ด๊ฒƒ์„ ์ด์šฉํ•˜์—ฌ
07:46
to go back to another piece of that tissue
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๊ทธ ์กฐ์ง์˜ ๋‹ค๋ฅธ ์กฐ๊ฐ์œผ๋กœ ๋Œ์•„๊ฐ€์„œ
07:49
and do what's called laser scanning microdissection.
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๋ ˆ์ด์ € ์Šค์บ” ํ˜„๋ฏธํ•ด๋ถ€ ์ž‘์—…์„ ํ•ฉ๋‹ˆ๋‹ค.
07:51
So the technician takes the instructions.
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์ง€์‹œ๋ฅผ ๋ฐ›์€ ํ›„, ๊ธฐ์ˆ ์ž๊ฐ€
07:54
They scribe along a place there.
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ํ•œ ์ง€์—ญ์„ ํ‘œ์‹œํ•˜๊ฒŒ ๋˜๋ฉด
07:56
And then the laser actually cuts.
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์‹ค์ œ๋กœ ๊ทธ ๋ถ€๋ถ„์ด ๋ ˆ์ด์ €๋กœ ์ž˜๋ฆฝ๋‹ˆ๋‹ค
07:58
You can see that blue dot there cutting. And that tissue falls off.
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์ €๊ธฐ ํŒŒ๋ž€ ์ ์ด ์ง€๊ธˆ ์กฐ์ง์„ ์ž๋ฅด๊ณ , ์ž˜๋ฆฐ ์กฐ์ง์€ ๋–จ์–ด์ง€๊ฒŒ ๋ฉ๋‹ˆ๋‹ค.
08:01
You can see on the microscope slide here,
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์—ฌ๊ธฐ ํ˜„๋ฏธ๊ฒฝ ์Šฌ๋ผ์ด๋“œ ์œ„์—์„œ ๋ณด์‹ค ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
08:03
that's what's happening in real time.
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์ง€๊ธˆ ์‹ค์‹œ๊ฐ„์œผ๋กœ ๋ณด์‹œ๊ณ  ๊ณ„์‹ญ๋‹ˆ๋‹ค.
08:05
There's a container underneath that's collecting that tissue.
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์กฐ์ง์„ ๋ชจ์œผ๋Š” ์šฉ๊ธฐ๊ฐ€ ์•„๋ž˜์— ์žˆ๊ณ 
08:08
We take that tissue,
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๊ฑฐ๊ธฐ์„œ ๊ทธ ์กฐ์ง์„ ๊ฐ€์ ธ์™€์„œ
08:10
we purify the RNA out of it
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๊ฐ„๋‹จํ•œ ๊ธฐ์ˆ ์„ ํ†ตํ•ด
08:12
using some basic technology,
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๋ฆฌ๋ณดํ•ต์‚ฐ์„ ์ •ํ™”์‹œํ‚จ ํ›„
08:14
and then we put a florescent tag on it.
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ํ˜•๊ด‘ ํƒœ๊ทธ๋ฅผ ๊ทธ ์œ„์— ๋ถ™์ž…๋‹ˆ๋‹ค.
08:16
We take that tagged material
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์šฐ๋ฆฌ๋Š” ๊ทธ ํƒœ๊ทธ๊ฐ€ ๋ถ™์€ ๋ฌผ์งˆ์„ ๊ฐ€์ ธ๋‹ค๊ฐ€
08:18
and we put it on to something called a microarray.
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๋ฏธ์„ธ๋ฐฐ์—ด๊ธฐ ์œ„์— ์˜ฌ๋ ค๋†“์Šต๋‹ˆ๋‹ค.
08:21
Now this may look like a bunch of dots to you,
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์˜๋ฏธ์—†๋Š” ์  ๋ฌถ์Œ ๊ฐ™์•„ ๋ณด์ด์ง€๋งŒ
08:23
but each one of these individual dots
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์ด ๊ฐ๊ฐ์˜ ์ ๋“ค์€
08:25
is actually a unique piece of the human genome
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์Šฌ๋ผ์ด๋“œ ์œ„์—์„œ ๋ณด์•˜๋˜
08:27
that we spotted down on glass.
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์ธ๊ฐ„ ๊ฒŒ๋†ˆ ๊ณ ์œ ์˜ ์กฐ๊ฐ ์ž…๋‹ˆ๋‹ค.
08:29
This has roughly 60,000 elements on it,
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์•ฝ 6๋งŒ๊ฐœ์˜ ์š”์†Œ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๊ธฐ ๋•Œ๋ฌธ์—,
08:32
so we repeatedly measure various genes
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์ €ํฌ๋Š” ๋ฐ˜๋ณตํ•˜์—ฌ 2๋งŒ 5์ฒœ๊ฐœ์˜ ์œ ์ „์ž์ค‘
08:35
of the 25,000 genes in the genome.
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์—ฌ๋Ÿฌ๊ฐ€์ง€ ์œ ์ „์ž๋“ค์„ ์ธก์ • ํ›„
08:37
And when we take a sample and we hybridize it to it,
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์ƒ˜ํ”Œ์„ ์ฑ„์ทจํ•˜์—ฌ ํ˜ผํ•ฉ๋ฌผ์„ ๋งŒ๋“ค์—ˆ๊ณ 
08:40
we get a unique fingerprint, if you will,
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๋‹ค์‹œ๋งํ•ด, ๋…ํŠนํ•œ ์ง€๋ฌธ์„ ๋งŒ๋“ค์–ด ๋ƒˆ์œผ๋ฉฐ ์–‘์ ์œผ๋กœ
08:42
quantitatively of what genes are turned on in that sample.
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์–ด๋–ค ์œ ์ „์ž๋“ค์ด ๊ทธ ์ƒ˜ํ”Œ๋‚ด์—์„œ ๋ฐ˜์‘ํ•˜๋Š”์ง€ ์•Œ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
08:45
Now we do this over and over again,
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์ด์ œ ์šฐ๋ฆฌ๋Š” ์ด ์ž‘์—…์„ ์–ด๋–ค ๋‘๋‡Œ๊ฐ€ ์ฃผ์–ด์ ธ๋„
08:47
this process for any given brain.
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๊ณ„์† ๋ฐ˜๋ณตํ•ด์„œ ์ง„ํ–‰ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
08:50
We're taking over a thousand samples for each brain.
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๊ฐ๊ฐ์˜ ๋‘๋‡Œ์—์„œ๋Š” ์ฒœ๊ฐœ๊ฐ€ ๋„˜๋Š” ์ƒ˜ํ”Œ์„ ์ฑ„์ทจํ•ฉ๋‹ˆ๋‹ค.
08:53
This area shown here is an area called the hippocampus.
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์ง€๊ธˆ ๋ณด์‹œ๋Š” ๋ถ€๋ถ„์€ ํ•ด๋งˆ๋ผ๊ณ  ๋ถˆ๋ฆฌ๋Š” ๋ถ€๋ถ„์ž…๋‹ˆ๋‹ค.
08:56
It's involved in learning and memory.
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ํ•™์Šต๊ณผ ๊ธฐ์–ต๋ ฅ์— ๊ด€์—ฌ ํ•˜๋Š” ๋ถ€๋ถ„์ด์ฃ .
08:58
And it contributes to about 70 samples
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๊ทธ๋ฆฌ๊ณ  ์ฒœ๊ฐœ์˜ ์ƒ˜ํ”Œ์ค‘
09:01
of those thousand samples.
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70๊ฐœ ์ •๋„์˜ ๊ฒฌ๋ณธ์„ ์ฐจ์ง€ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
09:03
So each sample gets us about 50,000 data points
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๊ทธ๋ž˜์„œ ๊ฐ๊ฐ์˜ ์ƒ˜ํ”Œ์€ ๋ฐ˜๋ณต ์ธก์ •์„ ํ†ตํ•˜์—ฌ ์•ฝ 5๋งŒ๊ฐœ์˜
09:07
with repeat measurements, a thousand samples.
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์ž๋ฃŒํฌ์ธํŠธ์™€ ์ฒœ๊ฐœ์˜ ์ƒ˜ํ”Œ์„
09:10
So roughly, we have 50 million data points
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์ œ๊ณต ํ•ฉ๋‹ˆ๋‹ค. ์ธ๊ฐ„์˜ ๋‘๋‡Œ๋ณ„๋กœ
09:12
for a given human brain.
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์•ฝ 500์–ต๊ฐœ์˜ ์ž๋ฃŒ ํฌ์ธํŠธ๊ฐ€ ์ƒ๊ธฐ๊ฒŒ ๋ฉ๋‹ˆ๋‹ค.
09:14
We've done right now
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์ €ํฌ๋Š” ํ˜„์žฌ ๋‘๊ฐœ์˜ ์ธ๊ฐ„ ๋‘๋‡Œ์— ํ•ด๋‹นํ•˜๋Š”
09:16
two human brains-worth of data.
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์ž๋ฃŒ๋ฅผ ์ˆ˜์ง‘ํ•˜์˜€์Šต๋‹ˆ๋‹ค.
09:18
We've put all of that together
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๊ทธ๋ฆฌ๊ณ  ๊ทธ ์ž๋ฃŒ๋“ค์„ ๋‹ค ๋ชจ์•„์„œ
09:20
into one thing,
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ํ•˜๋‚˜์˜ ํ†ตํ•ฉ๋œ ์ž๋ฃŒ๋กœ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค.
09:22
and I'll show you what that synthesis looks like.
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์ด์ œ ์ €๋Š” ์—ฌ๋Ÿฌ๋ถ„์—๊ฒŒ ํ†ตํ•ฉ๋œ ์ž๋ฃŒ๋ฅผ ๋ณด์—ฌ๋“œ๋ฆฌ๊ฒ ์Šต๋‹ˆ๋‹ค.
09:24
It's basically a large data set of information
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๊ธฐ๋ณธ์ ์œผ๋กœ ์ด๊ฒƒ์€ ๋งŽ์€ ์ •๋ณด์˜ ๋ชจ์Œ ์ด๋ฉฐ
09:27
that's all freely available to any scientist around the world.
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์ „์„ธ๊ณ„์˜ ๋ชจ๋“  ๊ณผํ•™์ž๋“ค์—๊ฒŒ ๋ฌด๋ฃŒ๋กœ ์—ด๋ ค์žˆ์Šต๋‹ˆ๋‹ค.
09:30
They don't even have to log in to come use this tool,
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์ด ๋„๊ตฌ๋ฅผ ์‚ฌ์šฉํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ๋กœ๊ทธ์ธ ํ•  ํ•„์š”๋„ ์—†์œผ๋ฉฐ,
09:33
mine this data, find interesting things out with this.
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์ด ์ž๋ฃŒ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ƒˆ๋กญ๊ณ  ํฅ๋ฏธ๋กœ์šด ๋ฐœ๊ฒฌ๋„ ํ•˜์‹ค ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
09:37
So here's the modalities that we put together.
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์—ฌ๊ธฐ ์šฐ๋ฆฌ๊ฐ€ ๊ตฌ์„ฑํ•ด๋ณธ ์–‘์ƒ๋“ค์ด ์žˆ์Šต๋‹ˆ๋‹ค.
09:40
You'll start to recognize these things from what we've collected before.
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์ข€์ „์— ์ €ํฌ๊ฐ€ ๋ชจ์€ ์ž๋ฃŒ๋“ค์„ ํ†ตํ•ด ๋ณด์…จ๋“ฏ์ด
09:43
Here's the MR. It provides the framework.
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์ž๊ธฐ๊ณต๋ช…๊ณผ ํ•จ๊ป˜ ๊ด€๋žŒํ‹€์ด ์ œ๊ณต๋ฉ๋‹ˆ๋‹ค.
09:45
There's an operator side on the right that allows you to turn,
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์šฐ์ธก์—๋Š” ๋‡Œ๋ฅผ ๋Œ๋ ค๋ณผ ์ˆ˜ ์žˆ๋Š” ๊ธฐ๋Šฅ๋„ ์žˆ๊ณ 
09:48
it allows you to zoom in,
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ํ™•๋Œ€ํ•ด์„œ ๋ณผ ์ˆ˜๋„ ์žˆ๊ณ 
09:50
it allows you to highlight individual structures.
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๊ฐ๊ฐ์˜ ๊ตฌ์กฐ๋ฌผ์„ ๋ฐ๊ฒŒ ํ‘œ์‹œํ•  ์ˆ˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค.
09:53
But most importantly,
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ํ•˜์ง€๋งŒ ์ œ์ผ ์ค‘์š”ํ•œ ๊ฒƒ์€,
09:55
we're now mapping into this anatomic framework,
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ํ•ด๋ถ€ํ•™์ ์ธ ํ‹€์„ ์ง€๋„ํ™” ํ•œ๋‹ค๋Š” ๊ฒƒ์ด๋ฉฐ
09:58
which is a common framework for people to understand where genes are turned on.
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์ด๊ฒƒ์„ ํ†ตํ•ด ์œ ์ „์ž์˜ ๋ฐ˜์‘๋“ค์„ ํ•œ๋ˆˆ์— ํŒŒ์•…ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
10:01
So the red levels
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๊ทธ๋ž˜์„œ ๋นจ๊ฐ„์ƒ‰์œผ๋กœ ํ‘œ์‹œ๋œ ๋ถ€๋ถ„์€ ์œ ์ „์ž์˜
10:03
are where a gene is turned on to a great degree.
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๋ฐ˜์‘์ด ํ›จ์”ฌ ๋” ํ™œ๋ฐœํ•˜๋‹ค๋Š” ํ‘œ์‹œ์ด๋ฉฐ
10:05
Green is the sort of cool areas where it's not turned on.
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์ดˆ๋ก์ƒ‰์€ ์นจ์ฐฉํ•œ ๋ถ€๋ถ„๋“ค๋กœ ๋งŽ์€ ๋ฐ˜์‘์ด ๋ณด์ด์ง€ ์•Š๋Š” ๋ถ€๋ถ„์ž…๋‹ˆ๋‹ค.
10:08
And each gene gives us a fingerprint.
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๊ทธ๋ฆฌ๊ณ  ๊ฐ๊ฐ์˜ ์œ ์ „์ž๋Š” ์ง€๋ฌธ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค.
10:10
And remember that we've assayed all the 25,000 genes in the genome
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์ค‘์š”ํ•œ ๊ฒƒ์€, ์ €ํฌ๊ฐ€ ๊ฒŒ๋†ˆ๋‚ด์˜ 2๋งŒ 5์ฒœ๊ฐœ์˜ ๋ชจ๋“  ์œ ์ „์ž๋ฅผ ๋ถ„์„ํ•˜์˜€์œผ๋ฉฐ
10:15
and have all of that data available.
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๊ทธ ๋ฐฉ๋Œ€ํ•œ ์ž๋ฃŒ๋ฅผ ๋ชจ๋‘์—๊ฒŒ ์—ด์–ด ๋†“์•˜๋‹ค๋Š” ๊ฒƒ ์ž…๋‹ˆ๋‹ค.
10:19
So what can scientists learn about this data?
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๊ณผํ•™์ž๋“ค์€ ์ด ์ž๋ฃŒ๋ฅผ ํ†ตํ•ด ๋ฌด์—‡์„ ๋ฐฐ์šธ ์ˆ˜ ์žˆ์„๊นŒ์š”?
10:21
We're just starting to look at this data ourselves.
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์ €ํฌ๋„ ์ด์ œ ์ด ์ž๋ฃŒ๋ฅผ ๋ถ„์„ํ•˜๊ธฐ ์‹œ์ž‘ํ•˜์˜€์Šต๋‹ˆ๋‹ค.
10:24
There's some basic things that you would want to understand.
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์—ฌ๋Ÿฌ๋ถ„์ด ์•„์…”์•ผํ•  ๋ช‡๊ฐ€์ง€ ๊ธฐ์ดˆ์ ์ธ ๊ฒƒ๋“ค์ด ์žˆ์Šต๋‹ˆ๋‹ค.
10:27
Two great examples are drugs,
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ํ›Œ๋ฅญํ•œ ์˜ˆ๋กœ์จ ๋‘๊ฐ€์ง€ ์•ฝ,
10:29
Prozac and Wellbutrin.
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ํ”„๋กœ์žญ๊ณผ ์›ฐ๋ถ€ํŠธ๋ฆฐ์ด ์žˆ์Šต๋‹ˆ๋‹ค.
10:31
These are commonly prescribed antidepressants.
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์ด๋“ค์€ ์ผ๋ฐ˜์ ์œผ๋กœ ์ฒ˜๋ฐฉ๋˜๋Š” ํ•ญ์šฐ์šธ์ œ ์ž…๋‹ˆ๋‹ค.
10:34
Now remember, we're assaying genes.
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๊ธฐ์–ตํ•˜์‹ค ๊ฒƒ์€, ์šฐ๋ฆฌ๋Š” ์œ ์ „์ž๋ฅผ ์ธก์ •ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ
10:36
Genes send the instructions to make proteins.
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์œ ์ „์ž๋“ค์€ ๋‹จ๋ฐฑ์งˆ์„ ๋งŒ๋“ค๋ผ๋Š” ์ง€์‹œ๋ฅผ ๋‚ด๋ฆฝ๋‹ˆ๋‹ค.
10:39
Proteins are targets for drugs.
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์•ฝ๋“ค์€ ๋‹จ๋ฐฑ์งˆ์„ ๋Œ€์ƒ์œผ๋กœ ํ•˜๊ธฐ๋•Œ๋ฌธ์—
10:41
So drugs bind to proteins
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๋‹จ๋ฐฑ์งˆ๊ณผ ๊ฒฐํ•ฉ์„ ํ•˜๊ฒŒ๋˜๊ณ 
10:43
and either turn them off, etc.
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๊ทธ๋“ค์„ ํ•ด์ œํ•˜๊ฑฐ๋‚˜ ๋‹ค๋ฅธ ๋ฐ˜์‘์„ ํ•ฉ๋‹ˆ๋‹ค.
10:45
So if you want to understand the action of drugs,
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๊ทธ๋ž˜์„œ ์•ฝ์ด ์–ด๋–ป๊ฒŒ ์ž‘์šฉํ•˜๋Š”์ง€ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•˜์—ฌ์„œ๋Š”
10:47
you want to understand how they're acting in the ways you want them to,
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๊ทธ ์•ฝ๋“ค์ด ์–ด๋–ป๊ฒŒ ๋‹น์‹ ์ด ์›ํ•˜๋Š”๋Œ€๋กœ ์ž‘์šฉํ•˜๋Š”์ง€ ์ดํ•ดํ•ด์•ผ ํ•˜๊ณ 
10:50
and also in the ways you don't want them to.
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๋˜ํ•œ ์›ํ•˜์ง€ ์•Š๋Š”๋Œ€๋กœ ์ž‘์šฉํ•˜๋Š”์ง€๋„ ๋ง์ž…๋‹ˆ๋‹ค.
10:52
In the side effect profile, etc.,
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๋ถ€์ž‘์šฉ ๋ฐ ์—ฌ๋Ÿฌ๊ฐ€์ง€ ์ƒํ™ฉ์— ๋”ฐ๋ผ
10:54
you want to see where those genes are turned on.
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์–ด๋–ค ์œ ์ „์ž๊ฐ€ ๋ฐ˜์‘ํ•˜๋Š”์ง€ ๋งค์šฐ ์•Œ๊ณ  ์‹ถ์œผ์‹ค ๊ฒ๋‹ˆ๋‹ค.
10:56
And for the first time, we can actually do that.
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๊ทธ๋ฆฌ๊ณ  ์‚ฌ์ƒ ์ตœ์ดˆ๋กœ, ๊ทธ๊ฒƒ์ด ๊ฐ€๋Šฅํ•ด์กŒ์Šต๋‹ˆ๋‹ค.
10:58
We can do that in multiple individuals that we've assayed too.
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์ €ํฌ๊ฐ€ ์ธก์ •ํ–ˆ๋˜ ๋งŽ์€ ๊ฐœ์ธ๋“ค์˜ ๋ฐ˜์‘๋„ ๊ด€์ฐฐ์ด ๊ฐ€๋Šฅํ•ฉ๋‹ˆ๋‹ค.
11:01
So now we can look throughout the brain.
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์ด์ œ ๋‘๋‡Œ๋‚ด๋ถ€๋ฅผ ์„ธ์„ธํžˆ ๋ณผ ์ˆ˜ ์žˆ์œผ๋ฉฐ
11:04
We can see this unique fingerprint.
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๊ณ ์œ ์˜ ์ง€๋ฌธ์„ ๋ณผ์ˆ˜ ์žˆ๊ณ 
11:06
And we get confirmation.
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ํ™•์ธ๋„ ๊ฐ€๋Šฅ ํ•ฉ๋‹ˆ๋‹ค.
11:08
We get confirmation that, indeed, the gene is turned on --
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๊ทธ ์œ ์ „์ž๊ฐ€ ์ •๋ง ๋ฐ˜์‘ํ•˜๊ณ  ์žˆ๋‹ค๋Š” ํ™•์ธ์„ ๋ง์ด์ฃ 
11:11
for something like Prozac,
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ํ”„๋กœ์žญ๊ณผ ๊ฐ™์€ ๊ฒฝ์šฐ์—๋„
11:13
in serotonergic structures, things that are already known be affected --
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์„ธ๋กœํ† ๋‹Œ์„ฑ ๊ตฌ์กฐ๋ฐ ์ด๋ฏธ ์˜ํ–ฅ์„ ๋ฐ›๋Š”๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ง„ ๋‹ค๋ฅธ๊ฒƒ๋“ค๊ณผ ํ•จ๊ป˜
11:16
but we also get to see the whole thing.
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์ „์ฒด์ ์ธ ๋ฐ˜์‘๋„ ๊ด€์ฐฐํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
11:18
We also get to see areas that no one has ever looked at before,
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์•„๋ฌด๋„ ๋ณผ ์ˆ˜ ์—†์—ˆ๋˜ ๋ถ€๋ถ„๋“ค๋„ ๊ด€์ฐฐ์ด ๊ฐ€๋Šฅํ•˜๋ฉฐ,
11:20
and we see these genes turned on there.
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์œ ์ „์ž๋“ค์ด ๊ทธ๊ณณ์—์„œ ๋ฐ˜์‘ํ•˜๋Š” ๊ฒƒ์„ ๋ณผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
11:22
It's as interesting a side effect as it could be.
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์ด๋ณด๋‹ค ๋” ํฅ๋ฏธ๋กœ์šด ๋ถ€์ž‘์šฉ์ด ์žˆ์„๊นŒ์š”.
11:25
One other thing you can do with such a thing
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๋˜ ํ•˜๋‚˜ ๋” ๊ฐ€๋Šฅํ•˜๊ฒŒ ๋œ ๊ฒƒ์€
11:27
is you can, because it's a pattern matching exercise,
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ํŒจํ„ด ๋งค์นญ ์ž‘์—…์„ ํ†ตํ•˜์—ฌ
11:30
because there's unique fingerprint,
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๊ณ ์œ ์˜ ์ง€๋ฌธ์ด ์กด์žฌํ•˜๊ธฐ์—
11:32
we can actually scan through the entire genome
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์‹ค์ œ๋กœ ์ „์ฒด ๊ฒŒ๋†ˆ์„ ์Šค์บ”ํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ
11:34
and find other proteins
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๋น„์Šทํ•œ ์ง€๋ฌธ์„ ๊ฐ€์ง„
11:36
that show a similar fingerprint.
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๋‹ค๋ฅธ ๋‹จ๋ฐฑ์งˆ๋“ค์„ ์ฐพ์„ ์ˆ˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค.
11:38
So if you're in drug discovery, for example,
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์˜ˆ๋ฅผ๋“ค์–ด ์‹ ์•ฝ์„ ๊ฐœ๋ฐœํ•ด์•ผ ํ•˜๋Š” ์ž„๋ฌด๊ฐ€ ์ฃผ์–ด์ง„๋‹ค๋ฉด,
11:41
you can go through
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๊ฒŒ๋†ˆ์ด ๋ณด์—ฌ์ค„ ์ˆ˜ ์žˆ๋Š”
11:43
an entire listing of what the genome has on offer
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์ „์ฒด ๋ชฉ๋ก์„ ๋‹ค ํ™•์ธํ•˜์—ฌ
11:45
to find perhaps better drug targets and optimize.
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์•ฝ์˜ ๋ชฉํ‘œ๋ฌผ๋“ค์„ ์„ค์ •ํ•˜๊ณ  ์ตœ์ ํ™” ์‹œํ‚ฌ ์ˆ˜ ์žˆ์„ ๊ฒƒ ์ž…๋‹ˆ๋‹ค.
11:49
Most of you are probably familiar
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์—ฌ๋Ÿฌ๋ถ„ ์ค‘ ๋Œ€๋ถ€๋ถ„์€ ์•„๋ž˜ ๋ฌธ๊ตฌ์™€ ๊ฐ™์€ ๋ฐฉ์‹์˜
11:51
with genome-wide association studies
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๊ฒŒ๋†ˆ๋ถ„์•ผ ์—ฐ๊ตฌ์ž๋ฃŒ๋ฅผ ๋‰ด์Šค๋ฅผ ํ†ตํ•ด ์ ‘ํ•ด ๋ณด์…จ์„ ๊ฒ๋‹ˆ๋‹ค.
11:53
in the form of people covering in the news
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โ€œ๊ณผํ•™์ž๋“ค์€ ์ตœ๊ทผ X ๋ผ๋Š” ์ฃผ์ œ์—
11:56
saying, "Scientists have recently discovered the gene or genes
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์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์œ ์ „์ž๋‚˜ ์œ ์ „์ž๋“ค์„
11:59
which affect X."
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๋ฐœ๊ฒฌ ํ•˜์˜€์Šต๋‹ˆ๋‹คโ€
12:01
And so these kinds of studies
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์ด๋Ÿฐ ํ•™๋ฌธ์€ ์ •๊ทœ์ ์œผ๋กœ ๊ณผํ•™์ž๋“ค์— ์˜ํ•ด
12:03
are routinely published by scientists
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๋ฐœํ‘œ๋˜๋ฉฐ ๊ฝค ๊ดœ์ฐฎ์€ ๋‚ด์šฉ์„
12:05
and they're great. They analyze large populations.
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ํฌํ•จํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋“ค์€ ๋งŽ์€ ์–‘์˜
12:07
They look at their entire genomes,
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์ง‘๋‹จ์„ ๋ถ„์„ํ•˜๋ฉฐ ์ „์ฒด ๊ฒŒ๋†ˆ๋“ค์„
12:09
and they try to find hot spots of activity
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๊ด€์ฐฐํ•จ๊ณผ ๋™์‹œ์— ๋œจ๊ฑฐ์šด ๋ฐ˜์‘์ด
12:11
that are linked causally to genes.
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์ผ์–ด๋‚˜๊ณ  ์žˆ๋Š” ๊ณณ์„ ์ฐพ์Šต๋‹ˆ๋‹ค.
12:14
But what you get out of such an exercise
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ํ•˜์ง€๋งŒ ์ด๋Ÿฐ ์ž‘์—…์„ ํ†ตํ•ด ์–ป๋Š” ๊ฒƒ์€
12:16
is simply a list of genes.
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๋‹จ์ง€ ์œ ์ „์ž ๋ชฉ๋ก์— ๋ถˆ๊ณผํ•ฉ๋‹ˆ๋‹ค.
12:18
It tells you the what, but it doesn't tell you the where.
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๋ฌด์Šจ์ผ์ด ์ผ์–ด๋‚ฌ๋Š”์ง€๋Š” ๋งํ•ด์ฃผ๊ฒ ์ง€๋งŒ, ์–ด๋””์„œ ์ผ์–ด๋‚˜๋Š”์ง€ ์•Œ ์ˆ˜ ์—†์Šต๋‹ˆ๋‹ค.
12:21
And so it's very important for those researchers
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๊ทธ๋ž˜์„œ ์—ฐ๊ตฌ์›๋“ค์—๊ฒŒ๋Š” ์ด๋Ÿฐ ์ž๋ฃŒ๋ฅผ ๋งŒ๋“ค์—ˆ๋‹ค๋Š”๊ฒŒ
12:24
that we've created this resource.
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๋งค์šฐ ์ค‘์š”ํ•˜๊ฒŒ ๋‹ค๊ฐ€์˜ต๋‹ˆ๋‹ค.
12:26
Now they can come in
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๊ทธ๋“ค์€ ์ด์ œ ์–ด๋–ค ํ™œ๋™๋“ค์„ ๋ณด๊ณ 
12:28
and they can start to get clues about activity.
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์‰ฝ๊ฒŒ ๋‹จ์„œ๋ฅผ ์ฐพ์„์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
12:30
They can start to look at common pathways --
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๋จผ์ € ๋ณดํ†ต ์“ฐ์ด๋Š” ํ™œ๋™ ๊ฒฝ๋กœ๋ถ€ํ„ฐ ํ™•์ธํ•  ์ˆ˜ ์žˆ์œผ๋ฉฐ
12:32
other things that they simply haven't been able to do before.
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์ „์—๋Š” ๊ทธ์ € ๋ถˆ๊ฐ€๋Šฅ ํ–ˆ๋˜ ๋ฐฉ์‹๋“ค์„ ์ด์ œ๋Š” ์‹œ๋„ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
12:36
So I think this audience in particular
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๊ทธ๋ž˜์„œ ์ €๋Š” ์˜ค๋Š˜ ์ฒญ์ค‘ ์—ฌ๋Ÿฌ๋ถ„์ด ๋”์šฑ
12:39
can understand the importance of individuality.
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๊ฐ์ž์˜ ์ฐจ์ด์˜ ์ค‘์š”์„ฑ์„ ์ž˜ ์ดํ•ดํ•˜์‹œ๋ฆฌ๋ผ ์ƒ๊ฐ๋ฉ๋‹ˆ๋‹ค.
12:42
And I think every human,
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๊ทธ๋ฆฌ๊ณ  ๋ชจ๋“  ์ธ๊ฐ„์€
12:44
we all have different genetic backgrounds,
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๊ฐ๊ฐ ๋‹ค๋ฅธ ์œ ์ „์ ์ธ ๋ฐ”ํƒ•์„ ๊ฐ€์ง€๊ณ  ์žˆ์œผ๋ฉฐ,
12:48
we all have lived separate lives.
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๊ฐ๊ธฐ ๋‹ค๋ฅธ ์‚ถ์„ ์‚ด์•„์™”์Šต๋‹ˆ๋‹ค.
12:50
But the fact is
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ํ•˜์ง€๋งŒ ์žฌ๋ฏธ์žˆ๋Š” ์‚ฌ์‹ค์€
12:52
our genomes are greater than 99 percent similar.
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์šฐ๋ฆฌ์˜ ๊ฒŒ๋†ˆ๋“ค์€ 99ํผ์„ผํŠธ ์ด์ƒ ์ผ์น˜ํ•œ๋‹ค๋Š” ๊ฒƒ ์ด๊ณ 
12:55
We're similar at the genetic level.
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์šฐ๋ฆฌ๊ฐ€ ์œ ์ „์  ๋ ˆ๋ฒจ์—์„œ๋„ ๋น„์Šทํ•ฉ๋‹ˆ๋‹ค.
12:58
And what we're finding
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๊ทธ๋ฆฌ๊ณ  ์šฐ๋ฆฌ๊ฐ€ ๋ฐœ๊ฒฌํ•œ ๊ฒƒ์€
13:00
is actually, even at the brain biochemical level,
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์ƒํ™”ํ•™์ ์ธ ๋‘๋‡Œ ๋ ˆ๋ฒจ์—์„œ๋„
13:02
we are quite similar.
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์šฐ๋ฆฌ๋Š” ๋งค์šฐ ๋น„์Šทํ•ฉ๋‹ˆ๋‹ค.
13:04
And so this shows it's not 99 percent,
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99ํผ์„ผํŠธ๋Š” ์•„๋‹ˆ์ง€๋งŒ
13:06
but it's roughly 90 percent correspondence
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๊ฑฐ์˜ 90ํผ์„ผํŠธ์˜ ์ผ์น˜ํ•จ์„ ๋ณด์ž…๋‹ˆ๋‹ค
13:08
at a reasonable cutoff,
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๊ทธ๋ž˜์„œ ๋ฏธ์ง€์†์˜ ๋ชจ๋“  ์ž๋ฃŒ๋“ค์€
13:11
so everything in the cloud is roughly correlated.
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๋Œ€๋ฝ์ ์ธ ๊ด€๋ จ์„ฑ์„ ๋ณด์ž…๋‹ˆ๋‹ค.
13:13
And then we find some outliers,
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๊ทธ๋ฆฌ๊ณ  ๋ช‡ ๊ฐ€์ง€ ํŠน์ˆ˜ํ•œ ํ‰๊ท ๋ฐ–์˜
13:15
some things that lie beyond the cloud.
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์ž๋ฃŒ๋“ค์„ ์ฐพ๊ธฐ๋„ ํ•˜์ฃ .
13:18
And those genes are interesting,
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์ด๋Ÿฐ ์œ ์ „์ž๋“ค์€ ๋งค์šฐ ํฅ๋ฏธ๋กญ์Šต๋‹ˆ๋‹ค๋งŒ,
13:20
but they're very subtle.
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๋™์‹œ์— ๋งค์šฐ ๋ฏผ๊ฐํ•ฉ๋‹ˆ๋‹ค.
13:22
So I think it's an important message
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๊ทธ๋ž˜์„œ ์˜ค๋Š˜ ์—ฌ๋Ÿฌ๋ถ„์—๊ฒŒ ๋ณด๋‚ด๋Š” ์ค‘์š”ํ•œ ๋ฉ”์‹œ์ง€๋Š”
13:25
to take home today
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์šฐ๋ฆฌ๋Š” ์„œ๋กœ์˜ ๋‹ค๋ฅธ์ ๋“ค์— ๋Œ€ํ•ด
13:27
that even though we celebrate all of our differences,
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์ฆ๊ฑฐ์›Œ ํ•˜๊ธฐ๋„ ํ•˜์ง€๋งŒ
13:30
we are quite similar
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๋‘๋‡Œ ๋ ˆ๋ฒจ์—์„œ๋„ ์šฐ๋ฆฌ๋Š” ๋ชจ๋‘
13:32
even at the brain level.
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๋น„์Šทํ•œ ์กด์žฌ๋ผ๋Š” ๊ฒƒ ์ž…๋‹ˆ๋‹ค.
13:34
Now what do those differences look like?
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์ด๋Ÿฐ ์ฐจ์ด๋ฅผ ๋ˆˆ์œผ๋กœ ๋ณผ ์ˆ˜ ์žˆ์„๊นŒ์š”?
13:36
This is an example of a study that we did
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๋ณด์‹œ๋Š” ๊ฒƒ์€ ๊ทธ ์ฐจ์ด์ ๋“ค์„ ์ •ํ™•ํžˆ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•ด
13:38
to follow up and see what exactly those differences were --
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์ €ํฌ๋“ค์ด ๋งˆ์นœ ์—ฐ๊ตฌ์˜ ์˜ˆ์ด๋ฉฐ
13:40
and they're quite subtle.
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๊ทธ ์ฐจ์ด์ ๋“ค์€ ๋งค์šฐ ๋ฏธ๋ฌ˜ํ•ฉ๋‹ˆ๋‹ค.
13:42
These are things where genes are turned on in an individual cell type.
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์ด ๋ถ€๋ถ„๋“ค์€ ํ•œ๊ฐ€์ง€ ์„ธํฌ ์œ ํ˜• ์†์˜ ์œ ์ „์ž๋“ค์ด ๋ฐ˜์‘ํ•˜๊ณ  ์žˆ๋Š” ๊ณณ ์ž…๋‹ˆ๋‹ค.
13:46
These are two genes that we found as good examples.
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์ €ํฌ๊ฐ€ ์ฐพ์€ ์ด ๋‘๊ฐœ์˜ ์œ ์ „์ž๋“ค์ด ์ข‹์€ ์˜ˆ ์ž…๋‹ˆ๋‹ค.
13:49
One is called RELN -- it's involved in early developmental cues.
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์ฒซ๋ฒˆ์งธ๋Š” RELN ์ด๋ผ๊ณ  ๋ถˆ๋ฆฌ๋ฉฐ ์ดˆ๊ธฐ ์ง„ํ–‰๋‹จ๊ณ„ ์•”์‹œ์— ๊ด€๊ณ„ ๋˜์–ด์žˆ์Šต๋‹ˆ๋‹ค.
13:52
DISC1 is a gene
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DISC1 ๋Š” ํ•œ ์œ ์ „์ž๋กœ์„œ
13:54
that's deleted in schizophrenia.
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์ •์‹ ๋ถ„์—ด์ฆ์ƒ ์—์„œ๋Š” ๋ˆ„๋ฝ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค.
13:56
These aren't schizophrenic individuals,
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๋ณด์‹œ๋Š” ๊ฒƒ์€ ์ •์‹ ๋ถ„์—ด์ฆ์„ ๊ฒช๋Š” ์‚ฌ๋žŒ๋“ค์ด ์•„๋‹ˆ์ง€๋งŒ,
13:58
but they do show some population variation.
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์ง‘๋‹จ์‚ฌ์ด ํŽธ์ฐจ๊ฐ€ ์กด์žฌํ•˜๊ธฐ๋„ ํ•ฉ๋‹ˆ๋‹ค.
14:01
And so what you're looking at here
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๊ทธ๋ž˜์„œ ์ง€๊ธˆ ๋ณด์‹œ๋Š” ๊ฒƒ์€
14:03
in donor one and donor four,
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์ œ๊ณต์ž 1๋ฒˆ๊ณผ 4๋ฒˆ์˜ ๊ฒƒ์œผ๋กœ
14:05
which are the exceptions to the other two,
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๋‹ค๋ฅธ ๋‘ ์ œ๊ณต์ž๋“ค๊ณผ๋Š” ์˜ˆ์™ธ์ ์œผ๋กœ
14:07
that genes are being turned on
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๋งค์šฐ ํŠน์ •ํ•œ ์กฐ์ง์˜ ๋ถ€๋ถ„์ง‘ํ•ฉ ๋‚ด์—์„œ
14:09
in a very specific subset of cells.
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์œ ์ „์ž๋“ค์ด ๋ฐ˜์‘ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
14:11
It's this dark purple precipitate within the cell
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์ง€๊ธˆ ๋ณด์ด๋Š” ์กฐ์ง๋‚ด์˜ ์–ด๋‘์šด ๋ณด๋ž๋น› ์นจ์ „๋ฌผ์ด
14:14
that's telling us a gene is turned on there.
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์œ ์ „์ž๊ฐ€ ๊ทธ ๊ณณ์—์„œ ๋ฐ˜์‘ํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ๋งํ•ด ์ค๋‹ˆ๋‹ค.
14:17
Whether or not that's due
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์ด๊ฒƒ์ด ๊ทธ ๊ฐœ์ธ์˜ ์œ ์ „์ ์ธ
14:19
to an individual's genetic background or their experiences,
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๋ฐฐ๊ฒฝ์ด๋‚˜ ๊ฒฝํ—˜์— ๋”ฐ๋ฅธ ๊ฒƒ์ธ์ง€ ์•„๋‹Œ์ง€๋Š”,
14:21
we don't know.
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์ €ํฌ๋„ ์•Œ ์ˆ˜ ์—†์Šต๋‹ˆ๋‹ค.
14:23
Those kinds of studies require much larger populations.
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๊ทธ๋Ÿฐ ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•ด์„œ๋Š” ํ›จ์”ฌ ๋งŽ์€ ์ƒ˜ํ”Œ๋“ค์ด ํ•„์š”ํ•ฉ๋‹ˆ๋‹ค.
14:28
So I'm going to leave you with a final note
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๋งˆ์ง€๋ง‰์œผ๋กœ ๋‘๋‡Œ์˜ ๋ณต์žก์„ฑ์— ๋Œ€ํ•ด์„œ์™€
14:30
about the complexity of the brain
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์–ผ๋งˆ๋‚˜ ์•„์ง๋„ ๋งŽ์€ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•œ์ง€์— ๋Œ€ํ•ด์„œ
14:33
and how much more we have to go.
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๋ง์”€๋“œ๋ฆฌ๋ฉฐ ๋ง์„ ๋งˆ์น˜๊ณ  ์‹ถ์Šต๋‹ˆ๋‹ค.
14:35
I think these resources are incredibly valuable.
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์ „ ์ด ์ž๋ฃŒ๋“ค์ด ์—„์ฒญ๋‚œ ๊ฐ€์น˜๋ฅผ ์ง€๋‹Œ๋‹ค๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค.
14:37
They give researchers a handle
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์—ฐ๊ตฌ์›๋“ค์—๊ฒŒ ์–ด๋””๋กœ ๋‚˜์•„๊ฐ€์•ผ ํ• ์ง€๋ฅผ
14:39
on where to go.
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์•Œ๋ ค์ฃผ๋Š” ๋ฐฉํ–ฅํƒ€๊ฐ€ ๋˜์–ด ์ค๋‹ˆ๋‹ค.
14:41
But we only looked at a handful of individuals at this point.
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ํ•˜์ง€๋งŒ ์ง€๊ธˆ๊นŒ์ง€ ์šฐ๋ฆฌ๋Š” ๋งค์šฐ ์†Œ์ˆ˜์˜ ์‚ฌ๋žŒ๋“ค์˜ ์ž๋ฃŒ๋งŒ ํ™•์ธํ•ด ๋ณด์•˜์Šต๋‹ˆ๋‹ค.
14:44
We're certainly going to be looking at more.
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๋ฌผ๋ก  ์•ž์œผ๋กœ๋Š” ํ›จ์”ฌ ๋” ์‚ฌ๋žŒ๋“ค์˜ ์ž๋ฃŒ๋ฅผ ๋ณผ ๊ฒƒ์ž…๋‹ˆ๋‹ค.
14:46
I'll just close by saying
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๋งˆ์ง€๋ง‰์œผ๋กœ ์ œ๊ฐ€ ํ•˜๊ณ  ์‹ถ์€ ๋ง์€
14:48
that the tools are there,
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ํ•„์š”ํ•œ ๋„๊ตฌ๋Š” ์ค€๋น„๋˜์—ˆ์œผ๋ฉฐ
14:50
and this is truly an unexplored, undiscovered continent.
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์ด๊ฒƒ์€ ์•„๋ฌด๋„ ํƒํ—˜ํ•˜์ง€ ์•Š์€ ๋ฏธ์ง€์˜ ๋ถ„์•ผ๋ผ๋Š” ๊ฒƒ ์ž…๋‹ˆ๋‹ค.
14:54
This is the new frontier, if you will.
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๋‹ค์‹œ๋งํ•ด ์ƒˆ๋กœ์šด ๊ตญ๊ฒฝ์ž…๋‹ˆ๋‹ค.
14:58
And so for those who are undaunted,
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๋‘๋‡Œ์˜ ์ƒˆ๋กœ์šด ๋ฐœ๊ฒฌ์„ ๋‘๋ ค์›Œ ํ•˜์ง€ ์•Š์œผ๋ฉฐ
15:00
but humbled by the complexity of the brain,
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๊ทธ ์‹ ๋น„์˜ ์†Œ์ค‘ํ•จ์„ ์•„๋Š” ์ž๋“ค์—๊ฒŒ๋Š”
15:02
the future awaits.
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๋ฐ์€ ๋ฏธ๋ž˜๊ฐ€ ๊ธฐ๋‹ค๋ฆฌ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
15:04
Thanks.
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๊ฐ์‚ฌํ•ฉ๋‹ˆ๋‹ค.
15:06
(Applause)
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(๋ฐ•์ˆ˜)

Original video on YouTube.com
์ด ์›น์‚ฌ์ดํŠธ ์ •๋ณด

์ด ์‚ฌ์ดํŠธ๋Š” ์˜์–ด ํ•™์Šต์— ์œ ์šฉํ•œ YouTube ๋™์˜์ƒ์„ ์†Œ๊ฐœํ•ฉ๋‹ˆ๋‹ค. ์ „ ์„ธ๊ณ„ ์ตœ๊ณ ์˜ ์„ ์ƒ๋‹˜๋“ค์ด ๊ฐ€๋ฅด์น˜๋Š” ์˜์–ด ์ˆ˜์—…์„ ๋ณด๊ฒŒ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๊ฐ ๋™์˜์ƒ ํŽ˜์ด์ง€์— ํ‘œ์‹œ๋˜๋Š” ์˜์–ด ์ž๋ง‰์„ ๋”๋ธ” ํด๋ฆญํ•˜๋ฉด ๊ทธ๊ณณ์—์„œ ๋™์˜์ƒ์ด ์žฌ์ƒ๋ฉ๋‹ˆ๋‹ค. ๋น„๋””์˜ค ์žฌ์ƒ์— ๋งž์ถฐ ์ž๋ง‰์ด ์Šคํฌ๋กค๋ฉ๋‹ˆ๋‹ค. ์˜๊ฒฌ์ด๋‚˜ ์š”์ฒญ์ด ์žˆ๋Š” ๊ฒฝ์šฐ ์ด ๋ฌธ์˜ ์–‘์‹์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ฌธ์˜ํ•˜์‹ญ์‹œ์˜ค.

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