Carl Schoonover: How to look inside the brain

75,202 views ・ 2012-05-17

TED


μ•„λž˜ μ˜λ¬Έμžλ§‰μ„ λ”λΈ”ν΄λ¦­ν•˜μ‹œλ©΄ μ˜μƒμ΄ μž¬μƒλ©λ‹ˆλ‹€.

λ²ˆμ—­: Woo Hwang κ²€ν† : han soo yeon
00:15
This is a thousand-year-old drawing of the brain.
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이 그림은 μ²œλ…„μ „μ— λ‡Œμ˜ λͺ¨μ–‘을 κ·Έλ¦° κ·Έλ¦Όμž…λ‹ˆλ‹€.
00:19
It's a diagram of the visual system.
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이것은 μ‹œκ°κ³„μ˜ λ‹€μ΄μ–΄κ·Έλž¨ μΈλ°μš”.
00:21
And some things look very familiar today.
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μ˜€λŠ˜λ‚  봐도 λΉ„μŠ·ν•œ 뢀뢄이 많죠.
00:24
Two eyes at the bottom, optic nerve flowing out from the back.
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밑에 λ‘κ°œμ˜ μ•ˆκ΅¬κ°€ 있고, μ‹œμ‹ κ²½μ΄ λ’€λ‘œλΆ€ν„° 흐λ₯΄κ³  있죠.
00:28
There's a very large nose
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맀우 큰 코도 μžˆλŠ”λ°μš”.
00:30
that doesn't seem to be connected to anything in particular.
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νŠΉλ³„νžˆ λ‹€λ₯Έ μ–΄λ–€ 것과도 μ—°κ²°λ˜ 보이지 μ•Šλ„€μš”.
00:34
And if we compare this
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μš°λ¦¬κ°€ 이것을 μ΅œκ·Όμ—
00:35
to more recent representations of the visual system,
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λ§Œλ“€μ–΄μ§„ μ‹œκ°κ³„μ˜ κ·Έλ¦Όκ³Ό λΉ„κ΅ν•˜λ©΄,
00:37
you'll see that things have gotten substantially more complicated
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μ—¬λŸ¬λΆ„μ€ λ‡Œ ꡬ쑰가 μƒλ‹Ήνžˆ λ³΅μž‘ν•΄μ§„ 것을 μ•Œ 수 μžˆμŠ΅λ‹ˆλ‹€.
00:40
over the intervening thousand years.
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κ·Έ 사이 μˆ˜μ²œλ…„ λ™μ•ˆ 말이죠.
00:42
And that's because today we can see what's inside of the brain,
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그건 μ˜€λŠ˜λ‚ μ— μš°λ¦¬κ°€ λ‡Œμ˜ λ‚΄λΆ€λ₯Ό λ³Ό 수 있기 λ•Œλ¬Έμž…λ‹ˆλ‹€.
00:45
rather than just looking at its overall shape.
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λ‡Œμ˜ κ·Έλƒ₯ 전체적인 ν˜•νƒœ λ§κ³ λ„μš”.
00:47
Imagine you wanted to understand how a computer works
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이제 μ—¬λŸ¬λΆ„λ“€μ΄ μ»΄ν“¨ν„°μ˜ μž‘λ™μ›λ¦¬λ₯Ό μ•Œκ³  μ‹Άμ–΄ν•œλ‹€κ³  상상해보죠,
00:51
and all you could see was a keyboard, a mouse, a screen.
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그리고 λ³Ό 수 μžˆλŠ” κ²ƒμ΄λΌκ³ λŠ” ν‚€λ³΄λ“œ, 마우슀, 슀크린이라고 μƒκ°ν•΄λ΄…μ‹œλ‹€.
00:54
You really would be kind of out of luck.
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그럼 정말 운이 μ—†λŠ”κ±°μ£ .
00:57
You want to be able to open it up, crack it open,
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μ—¬λŸ¬λΆ„μ€ 컴퓨터λ₯Ό μ—΄μ–΄ 볼수있기λ₯Ό 바라고,
00:59
look at the wiring inside.
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λ‚΄λΆ€μ˜ 전선듀을 보고 μ‹Άμ–΄ ν•©λ‹ˆλ‹€.
01:01
And up until a little more than a century ago,
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ν•œ μ„ΈκΈ° μ „κΉŒμ§€λ§Œν•΄λ„,
01:03
nobody was able to do that with the brain.
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아무도 λ‡Œλ₯Ό κ·Έλ ‡κ²Œ μ—΄μ–΄ λ³Ό 수 μ—†μ—ˆμŠ΅λ‹ˆλ‹€.
01:05
Nobody had had a glimpse of the brain's wiring.
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아무도 λ‡Œμ†μ˜ 신경듀에 λŒ€ν•΄ μ•Œ 수 μ—†μ—ˆμŠ΅λ‹ˆλ‹€.
01:07
And that's because if you take a brain out of the skull
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μ™œλƒν•˜λ©΄ 아무리 λ‘κ°œκ³¨ λ°–μœΌλ‘œ λ‡Œλ₯Ό κΊΌλ‚΄μ„œ
01:09
and you cut a thin slice of it,
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μ–‡κ²Œ λ‡Œλ₯Ό 자λ₯Έ ν›„,
01:11
put it under even a very powerful microscope,
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κ³ μ„±λŠ₯ ν˜„λ―Έκ²½ 밑에 μ˜¬λ €λ΄λ„,
01:14
there's nothing there.
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아무것도 μ•ˆ 보이기 λ•Œλ¬Έμ΄μ£ .
01:15
It's gray, formless.
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κ·Έλƒ₯ νšŒμƒ‰μ—, ν˜•νƒœκ°€ μ—†μ£ .
01:16
There's no structure. It won't tell you anything.
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μ–΄λ–€ ꡬ쑰도 μ•ˆκ°€μ§€κ³  μžˆμ–΄ 배울게 μ—†λ‹€λŠ” λ§μž…λ‹ˆλ‹€.
01:19
And this all changed in the late 19th century.
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κ·ΈλŸ¬λ‹€κ°€ 19세기말에 λͺ¨λ“ κ²ƒμ΄ λ°”λ€Œμ—ˆμŠ΅λ‹ˆλ‹€.
01:22
Suddenly, new chemical stains for brain tissue were developed
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κ°‘μžκΈ° λ‡Œμ‘°μ§μ„ λ³Ό 수 μžˆλŠ” ν™”ν•™ μ°©μƒ‰μ œκ°€ κ°œλ°œλœκ²ƒμ΄μ£ .
01:26
and they gave us our first glimpses at brain wiring.
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그리고 λ‡Œμ†μ˜ 신경듀을 처음 λ³Ό 수 있게 ν•΄μ£Όμ—ˆμŠ΅λ‹ˆλ‹€.
01:29
The computer was cracked open.
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컴퓨터 λ‚΄λΆ€λ₯Ό λ³Ό 수 있게 된거죠.
01:31
So what really launched modern neuroscience
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κ·Έλž˜μ„œ ν˜„λŒ€ 신경과학을 λΆ€ν₯μ‹œν‚¨ 것은
01:33
was a stain called the Golgi stain.
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골지(Golgi) μ°©μƒ‰μ œλΌκ³  λΆˆλ¦¬μš°λŠ” μž¬λ£Œμž…λ‹ˆλ‹€.
01:35
And it works in a very particular way.
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이 μ°©μƒ‰μ œλŠ” νŠΉλ³„ν•œ λ°©λ²•μœΌλ‘œ μž‘μš©ν•˜κ²Œ λ˜λŠ”λ°μš”.
01:37
Instead of staining all of the cells inside of a tissue,
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μ‘°μ§λ‚΄μ˜ λͺ¨λ“  세포에 μ°©μƒ‰ν•˜μ§€ μ•Šκ³ ,
01:40
it somehow only stains about one percent of them.
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μ•½ 1%μ •λ„μ—λ§Œ μ°©μƒ‰ν•˜κ²Œ λ©λ‹ˆλ‹€.
01:43
It clears the forest, reveals the trees inside.
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μˆ²μ„ μΉ˜μ›Œ 버리고 κ·Έ μ•ˆμ˜ λ‚˜λ¬΄λ₯Ό 보이게 ν•˜λŠ” κ²ƒμ²˜λŸΌ 말이죠.
01:47
If everything had been labeled, nothing would have been visible.
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λ§Œμ•½ λͺ¨λ“  쑰직에 착색이 λœλ‹€λ©΄, 아무것도 보지 λͺ»ν–ˆμ„ κ²λ‹ˆλ‹€.
01:49
So somehow it shows what's there.
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κ·Έλž˜μ„œ 이런 λ°©λ²•μœΌλ‘œ 쑰직내 신경듀을 보여주기 μ‹œμž‘ν•œκ±°μ£ .
01:52
Spanish neuroanatomist Santiago Ramon y Cajal,
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슀페인의 μ‹ κ²½ν•΄λΆ€ν•™μž μ‚°ν‹°μ•„κ³  라λͺ¨λ‹ˆ 카할은
01:54
who's widely considered the father of modern neuroscience,
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ν˜„λŒ€ μ‹ κ²½κ³Όν•™μ˜ μ•„λ²„μ§€λ‘œ λΆˆλ¦¬μš°λŠ”λ°μš”,
01:57
applied this Golgi stain, which yields data which looks like this,
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골지 μ°©μƒ‰μ œλ₯Ό μ΄μš©ν•΄μ„œ μ΄λ ‡κ²Œ λ³΄μ΄λŠ” 자료λ₯Ό λ§Œλ“€μ–΄λƒˆμŠ΅λ‹ˆλ‹€.
02:01
and really gave us the modern notion of the nerve cell, the neuron.
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그리고 신경세포와 λ‰΄λŸ°μ— λŒ€ν•œ ν˜„λŒ€μ μΈ κ°œλ…μ„ μ •λ¦½ν–ˆμŠ΅λ‹ˆλ‹€.
02:05
And if you're thinking of the brain as a computer,
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κ·Έλž˜μ„œ μ—¬λŸ¬λΆ„λ“€μ΄ λ‡Œλ₯Ό 컴퓨터에 λΉ„μœ ν•œλ‹€λ©΄,
02:07
this is the transistor.
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이건 νŠΈλžœμ§€μŠ€ν„°κ°€ λ˜λŠ”κ±°μ£ .
02:09
And very quickly Cajal realized
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그리고 카할은 λ‰΄λŸ°λ“€μ€ ν˜Όμžμ„œ
02:11
that neurons don't operate alone,
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μž‘λ™ν•˜μ§€ μ•ŠλŠ”λ‹€λŠ” 것을 κΈˆμƒˆ μ•Œκ²Œ λ˜μ—ˆμŠ΅λ‹ˆλ‹€.
02:14
but rather make connections with others
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λŒ€μ‹ μ— μ»΄ν“¨ν„°μ•ˆμ˜ νšŒλ‘œλ„ 처럼
02:16
that form circuits just like in a computer.
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μ„œλ‘œ μ—°κ²°λ˜μ–΄ μž‘λ™ν•œλ‹€λŠ”κ²ƒμ„ μ•Œκ²Œ 된 것이죠.
02:18
Today, a century later, when researchers want to visualize neurons,
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ν•œμ„ΈκΈ°κ°€ μ§€λ‚œ μ˜€λŠ˜λ‚ , 연ꡬ원듀이 λ‰΄λŸ°μ„ 보고자 ν•˜λ©΄,
02:21
they light them up from the inside rather than darkening them.
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λ‰΄λŸ°λ“€μ„ μ–΄λ‘‘κ²Œ ν•˜μ§€ μ•Šκ³  λ°κ²Œν•΄μ„œ 보게 λ©λ‹ˆλ‹€.
02:24
And there's several ways of doing this.
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μ΄λŸ°κ±°μ—λŠ” μ—¬λŸ¬κ°€μ§€ 방법이 μžˆλŠ”λ°μš”.
02:25
But one of the most popular ones
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많이 μ“°λŠ” 방법쀑 ν•˜λ‚˜λŠ”
02:27
involves green fluorescent protein.
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λ…Ήμƒ‰μ˜ ν˜•κ΄‘ λ‹¨λ°±μ§ˆμ„ μ°©μƒ‰ν•˜λŠ”κ²λ‹ˆλ‹€.
02:29
Now green fluorescent protein,
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생체 λ°œκ΄‘ ν•΄νŒŒλ¦¬λ‘œ λΆ€ν„°
02:31
which oddly enough comes from a bioluminescent jellyfish,
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많이 얻을 수 μžˆλŠ” 녹색 ν˜•κ΄‘ λ‹¨λ°±μ§ˆμ€
02:34
is very useful.
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맀우 μœ μš©ν•©λ‹ˆλ‹€.
02:35
Because if you can get the gene for green fluorescent protein
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μ™œλƒν•˜λ©΄ 녹색 ν˜•κ΄‘ λ‹¨λ°±μ§ˆμ—μ„œ μœ μ „μžλ₯Ό 채취해
02:38
and deliver it to a cell,
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세포에 μ£Όμž…ν•˜λ©΄,
02:40
that cell will glow green --
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κ·Έ μ„Έν¬λŠ” λ…Ήμƒ‰μœΌλ‘œ λ°œκ΄‘ν•˜κ²Œ λ©λ‹ˆλ‹€. --
02:41
or any of the many variants now of green fluorescent protein,
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λ˜λŠ” 녹색 ν˜•κ΄‘ λ‹¨λ°±μ§ˆμ˜ λ‹€μ–‘ν•œ λ³€μ’…μœΌλ‘œ λ˜κ±°λ‚˜μš”.
02:45
you get a cell to glow many different colors.
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κ·Έλž˜μ„œ λ‹€μ–‘ν•œ μƒ‰κΉ”λ‘œ λΉ›λ‚˜λŠ” 세포λ₯Ό 얻을 수 있기 λ•Œλ¬Έμ— μœ μš©ν•©λ‹ˆλ‹€.
02:47
And so coming back to the brain,
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λ‹€μ‹œ λ‡Œ μ΄μ•ΌκΈ°λ‘œ λŒμ•„μ™€μ„œμš”,
02:48
this is from a genetically engineered mouse called "Brainbow."
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이 사진은 "Brainbow"라고 λΆˆλ¦¬λŠ” μœ μ „μž μ‘°μž‘λœ μ₯μ—μ„œ λ‚˜μ˜¨ κ²ƒμž…λ‹ˆλ‹€.
02:52
And it's so called, of course,
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μ΄λ¦„μ—μ„œ λ§ν•˜λ“―μ΄
02:54
because all of these neurons are glowing different colors.
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이 λ‰΄λŸ°λ“€μ΄ μ„œλ‘œ λ‹€λ₯Έ μƒ‰κΉ”λ‘œ λ°œκ΄‘ν•˜κ²Œ λ©λ‹ˆλ‹€.
02:57
Now sometimes neuroscientists need to identify
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μ‹ κ²½κ³Όν•™μžλ“€μ€ λ•Œλ‘œλŠ” 전체 μ„Έν¬λ³΄λ‹€λŠ”
03:01
individual molecular components of neurons, molecules,
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λ‰΄λŸ°μ˜ 각각의 λΆ„μž 성뢄을
03:04
rather than the entire cell.
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ν™•μΈν•˜κ³  μ‹Άμ„λ•Œκ°€ μžˆμŠ΅λ‹ˆλ‹€.
03:05
And there's several ways of doing this,
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λͺ‡κ°€μ§€ λ°©λ²•μœΌλ‘œ 확인 ν•  수 μžˆλŠ”λ°μš”,
03:07
but one of the most popular ones
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κ°€μž₯ 보편적인 방법쀑에 ν•˜λ‚˜λŠ”
03:09
involves using antibodies.
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항체λ₯Ό μ΄μš©ν•˜λŠ” κ²ƒμž…λ‹ˆλ‹€.
03:11
And you're familiar, of course,
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λ¬Όλ‘  λ©΄μ—­μ²΄κ³„μ—μ„œ
03:12
with antibodies as the henchmen of the immune system.
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μ€‘μš”ν•œ 역할을 ν•˜λŠ”κ±Έλ‘œ μΉœμˆ™ν•˜μ£ .
03:15
But it turns out that they're so useful to the immune system
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ν•­μ²΄λŠ” 면역체계에 μ•„μ£Ό μœ μš©ν•œκ±Έλ‘œ μ•Œλ €μ‘ŒλŠ”λ°μš”,
03:18
because they can recognize specific molecules,
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νŠΉλ³„ν•œ λΆ„μžλ₯Ό 인지 ν•  수 있기 λ•Œλ¬Έμž…λ‹ˆλ‹€.
03:20
like, for example, the coat protein
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예λ₯Όλ“€μ–΄, 인체에 μΉ¨νˆ¬ν•˜λŠ”
03:22
of a virus that's invading the body.
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λ°”μ΄λŸ¬μŠ€μ˜ λ‹¨λ°±μ§ˆ μ½”λ“œ 같은 것 말이죠.
03:25
And researchers have used this fact
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κ·Έλž˜μ„œ 연ꡬ원듀이 λ‡Œμ†μ˜ νŠΉλ³„ν•œ λΆ„μžλ₯Ό
03:27
in order to recognize specific molecules inside of the brain,
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μ°Ύμ•„λ‚΄κΈ° μœ„ν•΄ 이런 사싀을 μ΄μš©ν•˜κ²Œ 된 κ²ƒμž…λ‹ˆλ‹€.
03:31
recognize specific substructures of the cell
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그리고 μ„Έν¬μ˜ ν•˜λΆ€ ꡬ쑰듀 각각을
03:34
and identify them individually.
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κ΅¬λΆ„ν•˜λŠ”λ° μ΄μš©ν•˜κΈ°λ„ ν•©λ‹ˆλ‹€.
03:36
And a lot of the images I've been showing you here are very beautiful,
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였늘 μ—¬λŸ¬λΆ„λ“€μ—κ²Œ λ³΄μ—¬λ“œλ¦° λ§Žμ€ 사진듀은 정말 아름닡기도 ν•˜μ§€λ§Œ,
03:39
but they're also very powerful.
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맀우 κ°•λ ₯ν•œ 의미λ₯Ό 가지고 μžˆμŠ΅λ‹ˆλ‹€.
03:41
They have great explanatory power.
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ꡉμž₯히 섀득λ ₯μžˆλŠ” μ΄λ―Έμ§€λ“€μž…λ‹ˆλ‹€.
03:42
This, for example, is an antibody staining
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μ˜ˆλ“€λ“€μ–΄, 이것은 μ₯μ˜ λ‡Œμ‘°μ§μ—μ„œ μ„Έλ‘œν‹΄μ—
03:45
against serotonin transporters in a slice of mouse brain.
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λ°˜μ‘ν•˜λŠ” 항체 착색 μ‚¬μ§„μž…λ‹ˆλ‹€.
03:48
And you've heard of serotonin, of course,
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λ¬Όλ‘  μ—¬λŸ¬λΆ„λ“€μ€ 우울증과 λΆˆμ•ˆκ³Ό κ΄€λ ¨λœ
03:50
in the context of diseases like depression and anxiety.
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μ„Έλ‘œν‹΄μ— λŒ€ν•΄μ„œ 많이 λ“€μ–΄ 보셨을 κ²λ‹ˆλ‹€.
03:53
You've heard of SSRIs,
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이런 병듀을 μΉ˜λ£Œν•˜λŠ”
03:54
which are drugs that are used to treat these diseases.
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우울증치료제(SSRI)도 λ“€μ–΄ 보셨을 κ²λ‹ˆλ‹€.
03:57
And in order to understand how serotonin works,
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μ„Έλ‘œν‹΄μ΄ μ–΄λ–»κ²Œ μž‘μš©ν•˜λŠ”μ§€ μ•ŒκΈ° μœ„ν•΄μ„œ,
04:00
it's critical to understand where the serontonin machinery is.
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μ„Έλ‘œν‹΄μ΄ λΆ„λΉ„λ˜λŠ” 곳이 μ–΄λ”˜μ§€λ₯Ό μ•„λŠ”κ²ƒμ€ 맀우 μ€‘μš”ν•©λ‹ˆλ‹€.
04:03
And antibody stainings like this one
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κ·Έλž˜μ„œ 이와 같은 항체 착색은
04:04
can be used to understand that sort of question.
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이런 μ§ˆλ¬Έμ— λŒ€ν•œ 닡을 μ–»λŠ”λ° 이용 될 수 μžˆμŠ΅λ‹ˆλ‹€.
04:08
I'd like to leave you with the following thought:
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μ €λŠ” μ—¬λŸ¬λΆ„λ“€μ΄ 이런 생각듀을 ν•΄μ£Όμ…¨μœΌλ©΄ ν•©λ‹ˆλ‹€ :
04:11
Green fluorescent protein and antibodies
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녹색 ν˜•κ΄‘ λ‹¨λ°±μ§ˆκ³Ό 항체 착색은
04:13
are both totally natural products at the get-go.
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μ›λž˜λΆ€ν„° μ²œμ—° λ¬Όμ§ˆμž…λ‹ˆλ‹€.
04:16
They were evolved by nature
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그것듀은 μžμ—°μ μœΌλ‘œ μ§„ν™”ν–ˆλŠ”λ°,
04:19
in order to get a jellyfish to glow green for whatever reason,
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뭐 예λ₯Ό λ“€λ©΄, ν•΄νŒŒλ¦¬κ°€ μ΄ˆλ‘μƒ‰μœΌλ‘œ 보이게 ν•˜κ±°λ‚˜,
04:21
or in order to detect the coat protein of an invading virus, for example.
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μΉ¨νˆ¬ν•œ λ°”μ΄λŸ¬μŠ€μ˜ λ‹¨λ°±μ§ˆ μ½”λ“œλ₯Ό νƒμ§€ν•˜κΈ° μœ„ν•΄μ„œ λ§μž…λ‹ˆλ‹€.
04:26
And only much later did scientists come onto the scene
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그리고 ν•œμ°Έν›„μ— κ³Όν•™μžλ“€μ΄ λ‚˜νƒ€λ‚˜μ„œ λ§ν•˜μ£ .
04:29
and say, "Hey, these are tools,
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"이야~ μ—¬κΈ° 쒋은 도ꡬ듀이 μžˆλ„€!!
04:31
these are functions that we could use
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이 λ„κ΅¬μ˜ κΈ°λŠ₯듀은 우리의
04:33
in our own research tool palette."
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연ꡬ에 μ‚¬μš©ν•΄λ„ λ¬μ—ˆμ„ 텐데.."
04:35
And instead of applying feeble human minds
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λ³΄μž˜κ²ƒ μ—†λŠ” μΈκ°„μ˜ 생각을 ν™œμš©ν•˜κΈ° λ³΄λ‹€λŠ”
04:39
to designing these tools from scratch,
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이런 도ꡬ듀을 λ§Œλ“€μ–΄ λ‚΄κΈ° μœ„ν•΄,
04:41
there were these ready-made solutions right out there in nature
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μœ„λŒ€ν•œ 기술자(μžμ—°)에 μ˜ν•΄μ„œ
04:43
developed and refined steadily for millions of years
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μˆ˜λ°±λ§Œλ…„λ™μ•ˆ 잘 개발되고 닀듬어진
04:47
by the greatest engineer of all.
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μžμ—°μ μΈ 도ꡬ듀이 μ‘΄μž¬ν•œλ‹€λŠ” 것이죠.
04:48
Thank you.
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κ°μ‚¬ν•©λ‹ˆλ‹€.
04:50
(Applause)
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(λ°•μˆ˜)
이 μ›Ήμ‚¬μ΄νŠΈ 정보

이 μ‚¬μ΄νŠΈλŠ” μ˜μ–΄ ν•™μŠ΅μ— μœ μš©ν•œ YouTube λ™μ˜μƒμ„ μ†Œκ°œν•©λ‹ˆλ‹€. μ „ 세계 졜고의 μ„ μƒλ‹˜λ“€μ΄ κ°€λ₯΄μΉ˜λŠ” μ˜μ–΄ μˆ˜μ—…μ„ 보게 될 κ²ƒμž…λ‹ˆλ‹€. 각 λ™μ˜μƒ νŽ˜μ΄μ§€μ— ν‘œμ‹œλ˜λŠ” μ˜μ–΄ μžλ§‰μ„ 더블 ν΄λ¦­ν•˜λ©΄ κ·Έκ³³μ—μ„œ λ™μ˜μƒμ΄ μž¬μƒλ©λ‹ˆλ‹€. λΉ„λ””μ˜€ μž¬μƒμ— 맞좰 μžλ§‰μ΄ μŠ€ν¬λ‘€λ©λ‹ˆλ‹€. μ˜κ²¬μ΄λ‚˜ μš”μ²­μ΄ μžˆλŠ” 경우 이 문의 양식을 μ‚¬μš©ν•˜μ—¬ λ¬Έμ˜ν•˜μ‹­μ‹œμ˜€.

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