Michael Dickinson: How a fly flies

311,959 views ใƒป 2013-02-22

TED


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

00:00
Translator: Joseph Geni Reviewer: Morton Bast
0
0
7000
๋ฒˆ์—ญ: Surie Lee ๊ฒ€ํ† : Sookjin Hyun
00:15
I grew up watching Star Trek. I love Star Trek.
1
15805
3532
์ €๋Š” ์Šคํƒ€ํŠธ๋ž™์„ ๋ณด๋ฉฐ ์ž๋ž๊ณ  ์ •๋ง๋กœ ์ข‹์•„ํ•ฉ๋‹ˆ๋‹ค.
00:19
Star Trek made me want to see alien creatures,
2
19337
4462
์ด ์˜ํ™”๋ฅผ ๋ณด๋ฉด์„œ ์™ธ๊ณ„ ์ƒ๋ช…์ฒด๋ฅผ ๋ณด๊ณ  ์‹ถ์–ด ํ•˜๊ฒŒ ๋˜์—ˆ์ฃ 
00:23
creatures from a far-distant world.
3
23799
2303
๋จผ ๊ณณ์—์„œ ์˜จ ์ƒ๋ช…์ฒด๋ฅผ ๋ง์ด์ฃ 
00:26
But basically, I figured out that I could find
4
26102
2787
ํ•˜์ง€๋งŒ ๊ธฐ๋ณธ์ ์œผ๋กœ, ์ €๋Š” ๋ฐ”๋กœ ์ด ์ง€๊ตฌ์—๋„
00:28
those alien creatures right on Earth.
5
28889
2977
์™ธ๊ณ„ ์ƒ๋ช…์ฒด๋ฅผ ์ฐพ์„ ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ์•„๋ƒˆ์Šต๋‹ˆ๋‹ค.
00:31
And what I do is I study insects.
6
31866
2653
์ œ๊ฐ€ ์—ฐ๊ตฌํ•˜๊ณ  ์žˆ๋Š” ๋ถ„์•ผ๋Š” ๊ณค์ถฉ์ž…๋‹ˆ๋‹ค.
00:34
I'm obsessed with insects, particularly insect flight.
7
34519
3256
์ €๋Š” ๊ณค์ถฉ์— ๋น ์ ธ ์žˆ์Šต๋‹ˆ๋‹ค. ํŠนํžˆ ๊ณค์ถฉ์˜ ๋น„ํ–‰์—์š”.
00:37
I think the evolution of insect flight is perhaps
8
37775
3141
์ €๋Š” ๊ณค์ถฉ์˜ ๋น„ํ–‰์ด๋ผ๋Š” ์ง„ํ™”์˜ ํ˜๋ช…์€ ์•„๋งˆ๋„
00:40
one of the most important events in the history of life.
9
40916
2742
์ƒ๋ช…์˜ ์—ญ์‚ฌ ์ค‘ ๊ฐ€์žฅ ์ค‘์š”ํ•œ ์‚ฌ๊ฑด์ด๋ผ๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค.
00:43
Without insects, there'd be no flowering plants.
10
43658
2237
๊ณค์ถฉ ์—†์ด๋Š”, ๊ฝƒ ํ”ผ๋Š” ์‹๋ฌผ์ด ์—†์„ ๊ฒ๋‹ˆ๋‹ค.
00:45
Without flowering plants, there would be no
11
45895
1916
๊ฝƒ์ด ํ”ผ๋Š” ์‹๋ฌผ ์—†์—ˆ๋‹ค๋ฉด, TED ๊ฐ•์—ฐ์„ ํ•˜๋Š”
00:47
clever, fruit-eating primates giving TED Talks.
12
47811
3137
์˜๋ฆฌํ•˜๊ณ  ๊ณผ์ผ์„ ์„ญ์ทจํ•˜๋Š” ์˜์žฅ๋ฅ˜๋„ ์—†์„ ๊ฒ๋‹ˆ๋‹ค.
00:50
(Laughter)
13
50948
2300
(์›ƒ์Œ)
00:53
Now,
14
53248
1987
์ด์ œ,
00:55
David and Hidehiko and Ketaki
15
55235
3039
๋ฐ์ด๋น„๋“œ์™€ ํžˆ๋ฐํžˆ์ฝ”(Hidehiko) ๊ทธ๋ฆฌ๊ณ  ์ผ€ํƒ€ํ‚ค(Ketaki)์”จ๊ฐ€
00:58
gave a very compelling story about
16
58274
3445
์ดˆํŒŒ๋ฆฌ์™€ ์ธ๊ฐ„์‚ฌ์ด์˜ ์œ ์‚ฌ์„ฑ์— ๋Œ€ํ•ด์„œ
01:01
the similarities between fruit flies and humans,
17
61719
2805
์•„์ฃผ ์„ค๋“๋ ฅ์žˆ๋Š” ์ด์•ผ๊ธฐ๋ฅผ ํ•ด์ฃผ์…จ์Šต๋‹ˆ๋‹ค.
01:04
and there are many similarities,
18
64524
1489
๋งŽ์€ ์œ ์‚ฌ์ ์ด ์žˆ๋Š”๋ฐ,
01:06
and so you might think that if humans are similar to fruit flies,
19
66013
3002
๋งŒ์•ฝ ์ดˆํŒŒ๋ฆฌ์™€ ์ธ๊ฐ„์ด ๋น„์Šทํ•˜๋‹ค๋ฉด
01:09
the favorite behavior of a fruit fly might be this, for example --
20
69015
3797
์—ฌ๋Ÿฌ๋ถ„์ด ๊ฐ€์žฅ ์ข‹์•„ํ•˜๋Š” ์ดˆํŒŒ๋ฆฌ์˜ ํ–‰๋™์€ ์ด๊ฒƒ์ด๋ผ๊ณ  ์ƒ๊ฐํ• ์ง€๋„ ๋ชจ๋ฆ…๋‹ˆ๋‹ค.
01:12
(Laughter)
21
72812
2282
(์›ƒ์Œ)
01:15
but in my talk, I don't want to emphasize on the similarities
22
75094
3191
ํ•˜์ง€๋งŒ ์ €๋Š” ์ธ๊ฐ„๊ณผ ์ดˆํŒŒ๋ฆฌ์˜ ์œ ์‚ฌ์„ฑ์ด ์•„๋‹ˆ๋ผ
01:18
between humans and fruit flies, but rather the differences,
23
78285
3067
์ธ๊ฐ„๊ณผ ์ดˆํŒŒ๋ฆฌ ์‚ฌ์ด์˜ ์ฐจ์ด์ ์ธ
01:21
and focus on the behaviors that I think fruit flies excel at doing.
24
81352
5287
์ดˆํŒŒ๋ฆฌ๊ฐ€ ์ž˜ ํ•˜๋Š” ํ–‰๋™์— ๋Œ€ํ•ด ์ง‘์ค‘ํ•˜์—ฌ ์ด์•ผ๊ธฐํ•˜๋ ค๊ณ  ํ•ฉ๋‹ˆ๋‹ค.
01:26
And so I want to show you a high-speed video sequence
25
86639
2856
๊ทธ๋ž˜์„œ ์ดˆ๋‹น 7,000 ์žฅ์˜ ํ”„๋ ˆ์ž„์„ ์ฐ์€
01:29
of a fly shot at 7,000 frames per second in infrared lighting,
26
89495
3935
์ ์™ธ์„  ๊ณ ์† ๋น„๋””์˜ค ์ดฌ์˜ ๊ฒฐ๊ณผ๋ฅผ ๋ณด์—ฌ๋“œ๋ฆฌ๊ฒ ์Šต๋‹ˆ๋‹ค.
01:33
and to the right, off-screen, is an electronic looming predator
27
93430
4210
์˜ค๋ฅธ์ชฝ ์Šคํฌ๋ฆฐ ๋ฐ”๊นฅ์—๋Š” ๊ธฐ๊ณ„์ ์œผ๋กœ ๋งŒ๋“  ํฌ์‹์ž๋ฅผ ๋ถˆ์‘ฅ ๋‚˜ํƒ€๋‚˜๊ฒŒ ํ–ˆ์Šต๋‹ˆ๋‹ค.
01:37
that is going to go at the fly.
28
97640
1435
๊ธฐ๊ณ„๊ฐ€ ๋‹ค๊ฐ€์„œ๋ ค ํ•˜์ž,
01:39
The fly is going to sense this predator.
29
99075
1838
ํŒŒ๋ฆฌ๊ฐ€ ํฌ์‹์ž๋ฅผ ๊ฐ์ง€ํ•˜๊ณ ์„ ,
01:40
It is going to extend its legs out.
30
100913
2455
๋‹ค๋ฆฌ๋ฅผ ์ญ‰ ๋ป—์–ด
01:43
It's going to sashay away
31
103368
1613
๋ฏธ๋„๋Ÿฌ์ง€๋“ฏ์ด
01:44
to live to fly another day.
32
104981
2565
๋„๋ง๊ฐ‘๋‹ˆ๋‹ค.
01:47
Now I have carefully cropped this sequence
33
107546
2362
์ด ์—ฐ์†์  ํ–‰๋™์„ ์ธ๊ฐ„์ด ๋ˆˆ์„ ๊นœ๋ฐ•์ด๋Š” ์‹œ๊ฐ„์—
01:49
to be exactly the duration of a human eye blink,
34
109908
3160
์ •ํ™•ํžˆ ๋งž์ถฐ ์ด ์—ฐ์†์ ์ธ ๊ณผ์ •์„ ์ž˜๋ผ๋ƒˆ์Šต๋‹ˆ๋‹ค.
01:53
so in the time that it would take you to blink your eye,
35
113068
2834
์šฐ๋ฆฌ๊ฐ€ ๋ˆˆ์„ ๊นœ๋ฐ•์ด๋Š” ์‹œ๊ฐ„ ๋™์•ˆ์—
01:55
the fly has seen this looming predator,
36
115902
3265
ํŒŒ๋ฆฌ๋Š” ์ด ๋ฌด์‹œ๋ฌด์‹œํ•œ ํฌ์‹์ž๋ฅผ ๋ณธ ํ›„,
01:59
estimated its position, initiated a motor pattern to fly it away,
37
119167
6168
์œ„์น˜๋ฅผ ์ถ”์ •ํ•˜์—ฌ, 1์ดˆ์— 220๋ฒˆ ๋‚ ๊ฐœ์ง“ํ•˜๋Š”
02:05
beating its wings at 220 times a second as it does so.
38
125335
4464
๋น„ํ–‰ ํŒจํ„ด์„ ์ž‘๋™์‹œ์ผœ ๋‚ ์•„๊ฐ”์Šต๋‹ˆ๋‹ค.
02:09
I think this is a fascinating behavior
39
129799
1973
์ €๋Š” ์ด ๋น„ํ–‰์ด ํŒŒ๋ฆฌ์˜ ๋‡Œ๊ฐ€ ์ •๋ณด๋ฅผ
02:11
that shows how fast the fly's brain can process information.
40
131772
3921
์–ผ๋งˆ๋‚˜ ๋นจ๋ฆฌ ์ฒ˜๋ฆฌํ•  ์ˆ˜ ์žˆ๋Š”์ง€ ๋ณด์—ฌ์ฃผ๋Š” ๋งค๋ ฅ์ ์ธ ํ–‰๋™์ด๋ผ๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค
02:15
Now, flight -- what does it take to fly?
41
135693
2842
์ž, ๋น„ํ–‰ -- ๋ฌด์—‡์ด ๋น„ํ–‰ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ• ๊นŒ์š”?
02:18
Well, in order to fly, just as in a human aircraft,
42
138535
2864
์ธ๊ฐ„์ด ๋งŒ๋“  ๋น„ํ–‰๊ธฐ์ฒ˜๋Ÿผ ๋‚ ๊ธฐ ์œ„ํ•ด์„œ๋Š”
02:21
you need wings that can generate sufficient aerodynamic forces,
43
141399
2735
์ถฉ๋ถ„ํ•œ ์–‘๋ ฅ์„ ๋งŒ๋“ค๊ธฐ ์œ„ํ•œ ๋‚ ๊ฐœ,
02:24
you need an engine sufficient to generate the power required for flight,
44
144134
3546
์ถฉ๋ถ„ํžˆ ๋‚  ์ˆ˜ ์žˆ์„ ์ •๋„์˜ ํž˜์„ ์ถœ๋ ฅํ•ด ๋‚ผ ๋งŒํ•œ ์—”์ง„,
02:27
and you need a controller,
45
147680
1709
๊ทธ๋ฆฌ๊ณ  ์ œ์–ด ์žฅ์น˜๊ฐ€ ํ•„์š”ํ•ฉ๋‹ˆ๋‹ค.
02:29
and in the first human aircraft, the controller was basically
46
149389
2626
์ธ๊ฐ„์ด ๋งŒ๋“  ์ฒซ ๋น„ํ–‰๊ธฐ์˜ ์ œ์–ด ์žฅ์น˜๋Š”
02:32
the brain of Orville and Wilbur sitting in the cockpit.
47
152015
4312
์กฐ์ข…์„์— ์•‰์•„ ์žˆ๋Š” ๋ผ์ดํŠธ ํ˜•์ œ์˜ ๋‡Œ์˜€์Šต๋‹ˆ๋‹ค.
02:36
Now, how does this compare to a fly?
48
156327
2753
์ž, ํŒŒ๋ฆฌ์™€ ๋น„๊ตํ•ด๋ณด๋ฉด ์–ด๋–จ๊นŒ์š”?
02:39
Well, I spent a lot of my early career trying to figure out
49
159080
3251
์ €๋Š” ์ œ ๋ถ„์•ผ์— ์ž…๋ฌธํ•œ ์ผ์ฐ๋ถ€ํ„ฐ ์–ด๋–ป๊ฒŒ ๊ณค์ถฉ์˜ ๋‚ ๊ฐœ๊ฐ€
02:42
how insect wings generate enough force to keep the flies in the air.
50
162331
4336
๊ณต์ค‘์„ ๋‚  ์ˆ˜์žˆ๋Š” ์ถฉ๋ถ„ํ•œ ํž˜์„ ๋งŒ๋“ค์–ด ๋‚ผ ์ˆ˜ ์žˆ๋Š”์ง€ ์•Œ์•„๋‚ด๋Š”๋ฐ ์‹œ๊ฐ„์„ ๋ณด๋ƒˆ์Šต๋‹ˆ๋‹ค.
02:46
And you might have heard how engineers proved
51
166667
1610
์—ฌ๋Ÿฌ๋ถ„์€ ์—”์ง€๋‹ˆ์–ด๋“ค์ด ํ˜ธ๋ฐ•๋ฒŒ์ด
02:48
that bumblebees couldn't fly.
52
168277
2634
๋‚  ์ˆ˜์—†๋‹ค๋Š” ๊ฒƒ์„ ์–ด๋–ป๊ฒŒ ์ฆ๋ช…ํ–ˆ๋Š”์ง€ ๋“ค์–ด๋ณด์…จ์„ ๊ฒ๋‹ˆ๋‹ค.
02:50
Well, the problem was in thinking that the insect wings
53
170911
2620
๋ฌธ์ œ๋Š” ๊ณค์ถฉ์˜ ๋‚ ๊ฐœ๋Š” ๋น„ํ–‰๊ธฐ ๋‚ ๊ฐœ์ฒ˜๋Ÿผ
02:53
function in the way that aircraft wings work. But they don't.
54
173531
3119
๊ธฐ๋Šฅํ•˜์ง€๋งŒ ํ˜ธ๋ฐ•๋ฒŒ์€ ๊ทธ๋ ‡์ง€ ์•Š๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
02:56
And we tackle this problem by building giant,
55
176650
2854
๊ทธ๋ž˜์„œ ์šฐ๋ฆฌ๋Š” ์ด ๋ฌธ์ œ๋ฅผ
02:59
dynamically scaled model robot insects
56
179504
3432
์›€์ง์ด๋Š” ๊ฑฐ๋Œ€ํ•œ ๋กœ๋ด‡ ๊ณค์ถฉ์„ ๋งŒ๋“ค์–ด
03:02
that would flap in giant pools of mineral oil
57
182936
3336
๊ฑฐ๋Œ€ํ•œ ๊ด‘๋ฌผ ์˜ค์ผ ์†์—์„œ ๋‚ ๊ฐœ์ง“์„ ์‹œ์ผœ๋ด„์œผ๋กœ์จ
03:06
where we could study the aerodynamic forces.
58
186272
2274
์œ ์ฒด์—ญํ•™์„ ์—ฐ๊ตฌํ–ˆ์Šต๋‹ˆ๋‹ค.
03:08
And it turns out that the insects flap their wings
59
188546
2158
๊ทธ ๊ฒฐ๊ณผ ๊ณค์ถฉ์€ ๋‚ ๊ฐœ์ง“์„
03:10
in a very clever way, at a very high angle of attack
60
190704
2592
๋งค์šฐ ํ˜„๋ช…ํ•œ ๋ฐฉ๋ฒ•์œผ๋กœ ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.
03:13
that creates a structure at the leading edge of the wing,
61
193296
3121
๋‚ ๊ฐœ ๋์—์„œ ์•ž์ „์™€๋ฅ˜(leading edge vortex)๋ผ ๋ถˆ๋ฆฌ๋Š”
03:16
a little tornado-like structure called a leading edge vortex,
62
196417
3199
ํ† ๋„ค์ด๋„ ๊ฐ™์€ ๊ตฌ์กฐ๋ฅผ ๋งŒ๋“ค๊ณ 
03:19
and it's that vortex that actually enables the wings
63
199616
2954
์ด ์™€๋ฅ˜๋Š” ๊ณค์ถฉ์ด ๊ณต๊ธฐ ์ค‘์— ๋จธ๋ฌด๋ฅผ ์ˆ˜ ์žˆ๋Š”
03:22
to make enough force for the animal to stay in the air.
64
202570
3359
์ถฉ๋ถ„ํ•œ ํž˜์„ ๋‚ ๊ฐœ์— ์‹ค์–ด์ค๋‹ˆ๋‹ค.
03:25
But the thing that's actually most -- so, what's fascinating
65
205929
2428
ํ•˜์ง€๋งŒ ์‚ฌ์‹ค ๊ฐ€์žฅ ๋ฉ‹์ง„ ๊ฒƒ์€
03:28
is not so much that the wing has some interesting morphology.
66
208357
2975
๋‚ ๊ฐœ๊ฐ€ ์žฌ๋ฏธ์žˆ๋Š” ํ˜•ํƒœ๋ฅผ ๊ฐ€์กŒ๋‹ค๋Š” ์ ์ž…๋‹ˆ๋‹ค.
03:31
What's clever is the way the fly flaps it,
67
211332
3645
ํŒŒ๋ฆฌ๊ฐ€ ๋‚ ๊ฐœ์ง“์„ ํ•˜๋Š” ๋ฐฉ๋ฒ•์—์„œ ํ˜„๋ช…ํ•œ ์ ์€
03:34
which of course ultimately is controlled by the nervous system,
68
214977
3136
๋ฌผ๋ก  ์‹ ๊ฒฝ๊ณ„ํ†ต์„ ํ†ตํ•ด ์™„๋ฒฝํ•˜๊ฒŒ ์กฐ์ข…์ด ๋œ๋‹ค๋Š” ์ ์ด๊ณ ,
03:38
and this is what enables flies to perform
69
218113
2647
์ด๊ฒƒ์ด ๋ฐ”๋กœ ํŒŒ๋ฆฌ๊ฐ€
03:40
these remarkable aerial maneuvers.
70
220760
2807
์ธ์ƒ์ ์ธ ๊ณต์ค‘ ๊ธฐ๋™์„ ๋ณด์—ฌ์ฃผ๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค.
03:43
Now, what about the engine?
71
223567
2097
์—”์ง„์€ ์–ด๋–ค๊ฐ€์š”?
03:45
The engine of the fly is absolutely fascinating.
72
225664
2492
ํŒŒ๋ฆฌ์˜ ์—”์ง„๋„ ๋ฌผ๋ก  ํ™˜์ƒ์ ์ž…๋‹ˆ๋‹ค.
03:48
They have two types of flight muscle:
73
228156
1898
๋‘ ์ข…๋ฅ˜์˜ ๋น„ํ–‰ ๊ทผ์œก์„ ๊ฐ€์ง€๊ณ  ์žˆ๋Š”๋ฐ,
03:50
so-called power muscle, which is stretch-activated,
74
230054
2985
ํž˜ ๊ทผ์œก์œผ๋กœ ๋ถˆ๋ฆฌ๋Š” ๊ณณ์€ ์‹ ์ถ• ํ™œ์„ฑํ™”๋ฉ๋‹ˆ๋‹ค.
03:53
which means that it activates itself and does not need to be controlled
75
233039
3726
์ฆ‰ ์Šค์Šค๋กœ ์ž‘๋™ํ•˜๋ฉฐ ์‹ ๊ฒฝ๊ณ„ํ†ต์„ ํ†ตํ•œ ๊ทผ์œก ์ˆ˜์ถ•์œผ๋กœ
03:56
on a contraction-by-contraction basis by the nervous system.
76
236765
3339
์›€์ง์—ฌ์งˆ ํ•„์š”๊ฐ€ ์—†๋‹ค๋Š” ๋œป์ž…๋‹ˆ๋‹ค.
04:00
It's specialized to generate the enormous power required for flight,
77
240104
4609
์ด ๊ทผ์œก์€ ๋น„ํ–‰์— ํ•„์š”ํ•œ ํฐ ํž˜์„ ๋ฐœ์ƒ์‹œํ‚ค๋Š”๋ฐ ์ตœ์ ํ™”๋˜์—ˆ๊ณ ,
04:04
and it fills the middle portion of the fly,
78
244713
2079
ํŒŒ๋ฆฌ์˜ ์ค‘๊ฐ„ ๋ชธ์ฒด๋ฅผ ์ „๋ถ€ ์ฐจ์ง€ํ•ด์„œ
04:06
so when a fly hits your windshield,
79
246792
1547
๋งŒ์•ฝ ํŒŒ๋ฆฌ๊ฐ€ ์ž๋™์ฐจ ์•ž ์œ ๋ฆฌ์ฐฝ์— ๋ถ€๋”ช์น˜๋ฉด
04:08
it's basically the power muscle that you're looking at.
80
248339
2406
์—ฌ๋Ÿฌ๋ถ„์ด ๋ณด๋Š” ๊ฑด ๋ฐ”๋กœ ๊ทธ ํž˜ ๊ทผ์œก์ž…๋‹ˆ๋‹ค.
04:10
But attached to the base of the wing
81
250745
2146
ํ•˜์ง€๋งŒ ๋‚ ๊ฐœ ๊ธฐ์ €์— ๋ถ™์€
04:12
is a set of little, tiny control muscles
82
252891
2638
์•„์ฃผ ์ž‘์€ ์กฐ์ข… ๊ทผ์œก์ด ์žˆ์Šต๋‹ˆ๋‹ค.
04:15
that are not very powerful at all, but they're very fast,
83
255529
3301
ํž˜์€ ์ „ํ˜€ ์„ธ์ง€ ์•Š์ง€๋งŒ, ๋Œ€์‹  ๋ฌด์ฒ™ ๋น ๋ฅด์ฃ .
04:18
and they're able to reconfigure the hinge of the wing
84
258830
3206
๊ทธ๋ฆฌ๊ณ  ๋‚ ๊ฐœ๊ฐ€ ์ ‘ํžˆ๋Š” ์ •๋„๋ฅผ ๋ฐ”๊ฟ€ ์ˆ˜ ์žˆ๊ฒŒ ํ•ด์ค๋‹ˆ๋‹ค.
04:22
on a stroke-by-stroke basis,
85
262036
1762
๊ทธ๊ฒƒ๋„ ๋‚ ๊ฐœ์ง“์„ ํ•  ๋•Œ๋งˆ๋‹ค์š”.
04:23
and this is what enables the fly to change its wing
86
263798
3142
์ด๊ฒƒ์ด ํŒŒ๋ฆฌ๊ฐ€ ๋‚ ๊ฐœ๋ฅผ ๋ฐ”๊ฟ”
04:26
and generate the changes in aerodynamic forces
87
266940
2971
๊ณต๊ธฐ์—ญํ•™์  ํž˜์„ ๋ณ€ํ™”์‹œํ‚ด์œผ๋กœ์จ
04:29
which change its flight trajectory.
88
269911
2573
๋น„ํ–‰๊ถค์ ์„ ๋ฐ”๊พธ๋Š” ๋ฐฉ๋ฒ•์ž…๋‹ˆ๋‹ค.
04:32
And of course, the role of the nervous system is to control all this.
89
272484
3563
๊ทธ๋ฆฌ๊ณ  ๋ฌผ๋ก , ์‹ ๊ฒฝ๊ณ„ํ†ต์ด ์ด ๋ชจ๋“  ๊ฒƒ์„ ํ†ต์ œํ•ฉ๋‹ˆ๋‹ค.
04:36
So let's look at the controller.
90
276047
1512
์ œ์–ด ์žฅ์น˜๋ฅผ ํ•œ ๋ฒˆ ๋ณผ๊นŒ์š”.
04:37
Now flies excel in the sorts of sensors
91
277559
2647
ํŒŒ๋ฆฌ๋Š” ์ด ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋Š”๋ฐ
04:40
that they carry to this problem.
92
280206
2284
๋ฌด์—‡๋ณด๋‹ค ๋›ฐ์–ด๋‚œ ์„ผ์„œ๋“ค์„ ๊ฐ€์ง€๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
04:42
They have antennae that sense odors and detect wind detection.
93
282490
4127
๋ƒ„์ƒˆ์™€ ๋ฐ”๋žŒ์„ ๊ฐ์ง€ํ•  ์ˆ˜ ์žˆ๋Š” ๋”๋“ฌ์ด๊ฐ€ ์žˆ์ง€์š”.
04:46
They have a sophisticated eye which is
94
286617
1675
์ง€๊ตฌ์ƒ์—์„œ ๊ฐ€์žฅ ๋น ๋ฅธ ์‹œ๊ฐ ์ฒ˜๋ฆฌ๊ฐ€ ๊ฐ€๋Šฅํ•œ
04:48
the fastest visual system on the planet.
95
288292
2456
๋งค์šฐ ์„ฌ์„ธํ•œ ๋ˆˆ์„ ๊ฐ€์ง€๊ณ  ์žˆ๊ณ ,
04:50
They have another set of eyes on the top of their head.
96
290748
2036
๋จธ๋ฆฌ ๊ผญ๋Œ€๊ธฐ์— ๋˜๋‹ค๋ฅธ ๋ˆˆ๋“ค์ด ์žˆ์–ด์š”.
04:52
We have no idea what they do.
97
292784
2052
๊ทธ ๋ˆˆ๋“ค์ด ์–ด๋–ค ์—ญํ• ์„ ํ•˜๋Š”์ง€๋Š” ๋ชจ๋ฆ…๋‹ˆ๋‹ค.
04:54
They have sensors on their wing.
98
294836
2954
๋‚ ๊ฐœ์— ์„ผ์„œ๋„ ์žˆ์ง€์š”.
04:57
Their wing is covered with sensors, including sensors
99
297790
3760
ํŒŒ๋ฆฌ์˜ ๋‚ ๊ฐœ๋Š” ์„ผ์„œ๋กœ ๋’ค๋ฎํ˜€ ์žˆ๋Š”๋ฐ,
05:01
that sense deformation of the wing.
100
301550
2046
๋‚ ๊ฐœ์˜ ๋ณ€ํ˜•์„ ๊ฐ์ง€ํ•˜๋Š” ์„ผ์„œ๋„ ์žˆ์Šต๋‹ˆ๋‹ค.
05:03
They can even taste with their wings.
101
303596
2109
์‹ฌ์ง€์–ด ๋‚ ๊ฐœ๋กœ ๋ง›๋„ ๋ณผ ์ˆ˜ ์žˆ์ง€์š”.
05:05
One of the most sophisticated sensors a fly has
102
305705
2555
ํŒŒ๋ฆฌ๊ฐ€ ๊ฐ€์ง„ ๊ฐ€์žฅ ์„ฌ์„ธํ•œ ์„ผ์„œ๋Š”
05:08
is a structure called the halteres.
103
308260
1807
ํ‰ํ˜•๊ณค(halteres)๋ผ ๋ถˆ๋ฆฌ๋Š” ๊ธฐ๊ด€์ž…๋‹ˆ๋‹ค.
05:10
The halteres are actually gyroscopes.
104
310067
1879
ํ‰ํ˜•๊ณค์€ ์‹ค์ œ๋กœ ์ž์ด๋กœ์Šค์ฝ”ํ”„์ž…๋‹ˆ๋‹ค.
05:11
These devices beat back and forth about 200 hertz during flight,
105
311946
4449
์ด ๊ธฐ๊ด€์€ ๋น„ํ–‰ ์ค‘์— 200Hz๋กœ ์•ž๋’ค๋กœ ์›€์ง์ด๋ฉฐ
05:16
and the animal can use them to sense its body rotation
106
316395
2673
ํŒŒ๋ฆฌ๊ฐ€ ๋ชธ์˜ ํšŒ์ „์„ ๊ฐ์ง€ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•ฉ๋‹ˆ๋‹ค.
05:19
and initiate very, very fast corrective maneuvers.
107
319068
3968
๊ทธ๋ฆฌ๊ณ  ์•„์ฃผ ๋น ๋ฅด๊ฒŒ ๋น„ํ–‰ ๊ฒฝ๋กœ๋ฅผ ์ˆ˜์ •ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜์ง€์š”.
05:23
But all of this sensory information has to be processed
108
323036
2329
ํ•˜์ง€๋งŒ ๋ชจ๋“  ์ด๋Ÿฐ ๊ฐ๊ฐ ์ •๋ณด๋“ค์€ ๋‡Œ์— ์˜ํ•ด ์ฒ˜๋ฆฌ๋˜์–ด์•ผ ํ•ฉ๋‹ˆ๋‹ค.
05:25
by a brain, and yes, indeed, flies have a brain,
109
325365
3720
๋„ค, ์ •๋ง์ž…๋‹ˆ๋‹ค, ํŒŒ๋ฆฌ์—๊ฒŒ๋„ ๋‡Œ๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค.
05:29
a brain of about 100,000 neurons.
110
329085
3159
10๋งŒ ๊ฐœ ๊ฐ€๋Ÿ‰์˜ ๋‰ด๋ก ์ด ์žˆ๋Š” ๋‡Œ๊ฐ€ ์žˆ์ง€์š”.
05:32
Now several people at this conference
111
332244
2193
์—ฌ๊ธฐ ๊ณ„์‹œ๋Š” ๋ช‡๋ช‡ ๋ถ„๋“ค์€
05:34
have already suggested that fruit flies could serve neuroscience
112
334437
4808
์ดˆํŒŒ๋ฆฌ๊ฐ€ ์‹ ๊ฒฝ ๊ณผํ•™ ์—ฐ๊ตฌ ๋Œ€์ƒ์ด ๋˜์–ด์•ผ ํ•œ๋‹ค๊ณ  ์ œ์•ˆํ•˜๊ธฐ๋„ ํ•˜์…จ์ฃ .
05:39
because they're a simple model of brain function.
113
339245
3247
์™œ๋ƒํ•˜๋ฉด ๊ฐ€์žฅ ๊ฐ„๋‹จํ•œ ๋‡Œ ๊ธฐ๋Šฅ ๋ชจ๋ธ์ด๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.
05:42
And the basic punchline of my talk is,
114
342492
2077
๊ทธ๋ฆฌ๊ณ  ์ €๋Š” ์ œ ๊ฐ•์—ฐ์˜ ํ•ต์‹ฌ์„
05:44
I'd like to turn that over on its head.
115
344569
2658
ํŒŒ๋ฆฌ์˜ ๋จธ๋ฆฌ์— ๋‘๊ณ  ์‹ถ์Šต๋‹ˆ๋‹ค.
05:47
I don't think they're a simple model of anything.
116
347227
2628
ํŒŒ๋ฆฌ๊ฐ€ ์–ด๋–ค ๊ฒƒ์ด๋“ ์ง€ ๊ฐ„๋‹จํ•œ ๋ชจ๋ธ์ด๋ผ ์ƒ๊ฐํ•˜์ง€ ์•Š์Šต๋‹ˆ๋‹ค.
05:49
And I think that flies are a great model.
117
349855
2477
์ €๋Š” ํŒŒ๋ฆฌ๊ฐ€ ๊ต‰์žฅํ•œ ๋ชจ๋ธ์ด๋ผ๊ณ  ์ƒ๊ฐํ•ด์š”.
05:52
They're a great model for flies.
118
352332
2516
ํŒŒ๋ฆฌ๋Š” ๋น„ํ–‰์˜ ๊ต‰์žฅํ•œ ๋ชจ๋ธ์ด์ฃ .
05:54
(Laughter)
119
354848
2481
(์›ƒ์Œ)
05:57
And let's explore this notion of simplicity.
120
357329
3003
์ด ๊ฐ„๋‹จํ•œ ๊ฐœ๋…์„ ์ƒ๊ฐํ•ด๋ณผ๊นŒ์š”.
06:00
So I think, unfortunately, a lot of neuroscientists,
121
360332
2431
๋ถˆํ–‰ํžˆ๋„ ๋งŽ์€ ์‹ ๊ฒฝ ๊ณผํ•™์ž๋“ค์€
06:02
we're all somewhat narcissistic.
122
362763
1832
์–ด๋–ป๊ฒŒ ๋ณด๋ฉด ์ž๊ธฐ ๋„์ทจ์ ์ด์—์š”.
06:04
When we think of brain, we of course imagine our own brain.
123
364595
3433
๋‡Œ์— ๋Œ€ํ•ด ์ƒ๊ฐํ•  ๋•Œ, ๋‹น์—ฐํžˆ ์šฐ๋ฆฌ ์ž์‹ ์˜ ๋‡Œ์— ๋Œ€ํ•ด ์ƒ๊ฐํ•˜์ง€์š”.
06:08
But remember that this kind of brain,
124
368028
1960
ํ•˜์ง€๋งŒ ์ด๋Ÿฐ ์ข…๋ฅ˜์˜ ๋‡Œ,
06:09
which is much, much smaller
125
369988
1768
์ฆ‰ ํ›จ์”ฌ ์ž‘์€
06:11
โ€” instead of 100 billion neurons, it has 100,000 neurons โ€”
126
371756
2678
-- ์ฒœ์–ต ๊ฐœ์˜ ๋‰ด๋ก ๋Œ€์‹  10๋งŒ ๊ฐœ์˜ ๋‰ด๋ก ์ด ์žˆ๋Š” --
06:14
but this is the most common form of brain on the planet
127
374434
2882
ํ•˜์ง€๋งŒ ์ด๋Ÿฐ ๋‡Œ๊ฐ€ ์ง€๊ตฌ์ƒ์˜ ๊ฐ€์žฅ ํ”ํ•œ ํ˜•ํƒœ์ด๊ณ 
06:17
and has been for 400 million years.
128
377316
2904
4์–ต ๋…„ ์ „๋ถ€ํ„ฐ ์žˆ์—ˆ์ง€์š”.
06:20
And is it fair to say that it's simple?
129
380220
2288
๊ทธ๋ ‡๋‹ค๋ฉด ์ด๋Ÿฐ ๋‡Œ๊ฐ€ ๊ฐ„๋‹จํ•˜๋‹ค๊ณ  ๋งํ•˜๋Š”๊ฒŒ ์˜ณ์„๊นŒ์š”?
06:22
Well, it's simple in the sense that it has fewer neurons,
130
382508
2095
๊ธ€์Ž„์š”, ๋” ์ ์€ ๋‰ด๋ก ์ด ์žˆ๋‹ค๋Š” ์˜๋ฏธ์—์„œ๋Š” ๊ฐ„๋‹จํ•˜์ง€๋งŒ
06:24
but is that a fair metric?
131
384603
1754
๊ณผ์—ฐ ๊ณต์ •ํ•œ ๊ธฐ์ค€์ผ๊นŒ์š”?
06:26
And I would propose it's not a fair metric.
132
386357
2276
์ €๋Š” ๊ทธ๋ ‡๊ฒŒ ์ƒ๊ฐํ•˜์ง€ ์•Š์Šต๋‹ˆ๋‹ค.
06:28
So let's sort of think about this. I think we have to compare --
133
388633
3100
์ด ๊ฒƒ์— ๋Œ€ํ•ด ํ•œ ๋ฒˆ ์ƒ๊ฐํ•ด๋ณผ๊นŒ์š”.
06:31
(Laughter) โ€”
134
391733
1559
์ œ ์ƒ๊ฐ์—๋Š” ์ด๋ ‡๊ฒŒ ๋น„๊ต๋ฅผ -- (์›ƒ์Œ) --
06:33
we have to compare the size of the brain
135
393292
5121
๋‡Œ์˜ ํฌ๊ธฐ๋ฅผ ๋น„๊ตํ•ด ๋ด์•ผํ•  ๊ฒƒ ๊ฐ™์•„์š”.
06:38
with what the brain can do.
136
398413
2030
๊ทธ๋ฆฌ๊ณ  ๋‡Œ๊ฐ€ ๋ฌด์—‡์„ ํ•  ์ˆ˜ ์žˆ๋Š”์ง€๋„์š”.
06:40
So I propose we have a Trump number,
137
400443
2881
ํŠธ๋Ÿผํ”„ ์ˆซ์ž๊ฐ€ ์žˆ๋‹ค๊ณ  ํ•ด๋ณด์ฃ .
06:43
and the Trump number is the ratio of this man's
138
403324
2865
๊ทธ ์ˆซ์ž๋“ค์€ ํ•œ ์‚ฌ๋žŒ์˜ ๋‡Œ์— ์žˆ๋Š” ๋‰ด๋ก ์˜ ์ˆซ์ž์™€
06:46
behavioral repertoire to the number of neurons in his brain.
139
406189
3679
๊ทธ ์‚ฌ๋žŒ์˜ ์ „์ฒด ํ–‰๋™ ๋ชฉ๋ก์˜ ๋น„์œจ์ž…๋‹ˆ๋‹ค.
06:49
We'll calculate the Trump number for the fruit fly.
140
409868
2668
์ดˆํŒŒ๋ฆฌ์˜ ํŠธ๋Ÿผํ”„ ์ˆซ์ž๋„ ๊ณ„์‚ฐํ•ด ๋ด…์‹œ๋‹ค.
06:52
Now, how many people here think the Trump number
141
412536
2684
์ž, ๋ช‡ ๋ถ„์ด๋‚˜ ์ดˆํŒŒ๋ฆฌ๋ณด๋‹ค ๋†’์€
06:55
is higher for the fruit fly?
142
415220
2489
์ˆซ์ž๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค๊ณ  ์ƒ๊ฐํ•˜์‹œ๋‚˜์š”?
06:57
(Applause)
143
417709
2431
(๋ฐ•์ˆ˜)
07:00
It's a very smart, smart audience.
144
420140
3428
์•„์ฃผ ๋˜‘๋˜‘ํ•œ ์ฒญ์ค‘๋“ค์ด๊ตฐ์š”.
07:03
Yes, the inequality goes in this direction, or I would posit it.
145
423568
3327
๋งž์•„์š”. ๋ถ€๋“ฑํ˜ธ๋Š” ์ด์ชฝ ๋ฐฉํ–ฅ์œผ๋กœ ํ–ฅํ•ฉ๋‹ˆ๋‹ค. ์•„๋‹ˆ๋ฉด ๊ทธ๋ ‡๋‹ค๊ณ  ๊ฐ€์ •ํ• ๊ฒŒ์š”.
07:06
Now I realize that it is a little bit absurd
146
426895
2382
์ด์ œ ์ƒ๊ฐํ•ด๋ณด๋‹ˆ ์‚ฌ๋žŒ๊ณผ ํŒŒ๋ฆฌ์˜ ํ–‰๋™ ๊ฐ€์ง“์ˆ˜๋ฅผ
07:09
to compare the behavioral repertoire of a human to a fly.
147
429277
3558
๋น„๊ตํ•œ๋‹ค๋Š”๊ฒŒ ์ข€ ํ„ฐ๋ฌด๋‹ˆ ์—†๋Š” ๊ฒƒ ๊ฐ™๋„ค์š”.
07:12
But let's take another animal just as an example. Here's a mouse.
148
432835
4143
๊ทธ๋ ‡๋‹ค๋ฉด ๋‹ค๋ฅธ ๋™๋ฌผ์„ ์˜ˆ๋กœ ๋“ค์–ด๋ณด์ง€์š”. ์—ฌ๊ธฐ ์ƒ์ฅ๊ฐ€ ์žˆ์–ด์š”.
07:16
A mouse has about 1,000 times as many neurons as a fly.
149
436978
4305
์ƒ์ฅ๋Š” ํŒŒ๋ฆฌ๋ณด๋‹ค ์ฒœ ๋ฐฐ๋‚˜ ๋” ๋งŽ์€ ๋‰ด๋ก ์„ ๊ฐ€์ง€๊ณ  ์žˆ์ง€์š”.
07:21
I used to study mice. When I studied mice,
150
441283
2027
์ €๋Š” ์ƒ์ฅ๋ฅผ ์—ฐ๊ตฌํ–ˆ์—ˆ์Šต๋‹ˆ๋‹ค. ์ œ๊ฐ€ ์ƒ์ฅ๋ฅผ ์—ฐ๊ตฌํ–ˆ์„ ๋•Œ๋Š”,
07:23
I used to talk really slowly.
151
443310
2837
์ •๋ง ๋Š๋ฆฌ๊ฒŒ ๋งํ•˜๊ณค ํ–ˆ์ง€์š”.
07:26
And then something happened when I started to work on flies.
152
446147
2576
ํŒŒ๋ฆฌ์— ๋Œ€ํ•ด ์—ฐ๊ตฌ๋ฅผ ์‹œ์ž‘ํ–ˆ์„ ๋•Œ ๋ญ”๊ฐ€ ์ผ์–ด๋‚ฌ์–ด์š”.
07:28
(Laughter)
153
448723
2412
(์›ƒ์Œ)
07:31
And I think if you compare the natural history of flies and mice,
154
451135
3460
ํŒŒ๋ฆฌ์™€ ์ƒ์ฅ์˜ ์ž์—ฐ์‚ฌ๋ฅผ ๋น„๊ตํ•ด ๋ณด๋ฉด
07:34
it's really comparable. They have to forage for food.
155
454595
3313
์•„์ฃผ ์œ ์‚ฌํ•ฉ๋‹ˆ๋‹ค. ๋‘˜ ๋‹ค ๋จน์ด๋ฅผ ์ฐพ์•„๋‹ค๋‹ˆ๊ณ ,
07:37
They have to engage in courtship.
156
457908
2447
๊ตฌ์• ๋ฅผ ํ†ตํ•ด ์ด์„ฑ์„ ์œ ํ˜นํ•˜์ง€์š”.
07:40
They have sex. They hide from predators.
157
460355
3471
์„ฑ์„ ๊ฐ€์ง€๊ณ  ์žˆ๊ณ , ์ฒœ์ ์œผ๋กœ๋ถ€ํ„ฐ ์ˆจ์–ด ์ง€๋ƒ…๋‹ˆ๋‹ค.
07:43
They do a lot of the similar things.
158
463826
1980
์„œ๋กœ ๋น„์Šทํ•œ ์ ๋“ค์„ ๋งŽ์ด ๊ฐ€์ง€๊ณ  ์žˆ์–ด์š”.
07:45
But I would argue that flies do more.
159
465806
1718
ํ•˜์ง€๋งŒ ํŒŒ๋ฆฌ๊ฐ€ ๋” ๋งŽ์€ ์ผ์„ ํ•œ๋‹ค๊ณ  ๋งํ•˜๊ณ  ์‹ถ์–ด์š”.
07:47
So for example, I'm going to show you a sequence,
160
467524
3378
์˜ˆ๋ฅผ ๋“ค์–ด, ํ•œ ์—ฐ์† ์‚ฌ์ง„์„ ๋ณด์—ฌ๋“œ๋ฆดํ…๋ฐ,
07:50
and I have to say, some of my funding comes from the military,
161
470902
4205
๊ทธ ์ „์— ์ œ ์—ฐ๊ตฌ ๊ธฐ๊ธˆ ์ค‘์— ์ผ๋ถ€๋Š” ๊ตฐ๋Œ€์—์„œ ์ง€์›๋ฐ›๋Š”๋‹ค๋Š” ๊ฒƒ์„ ๋ง์”€๋“œ๋ ค์•ผ๊ฒ ๊ตฐ์š”.
07:55
so I'm showing this classified sequence
162
475107
2072
์ž, ์—ฌ๋Ÿฌ๋ถ„์—๊ฒŒ ๋Œ€์™ธ๋น„ ์‚ฌ์ง„์„ ๋ณด์—ฌ๋“œ๋ฆด๊ฑฐ์—์š”.
07:57
and you cannot discuss it outside of this room. Okay?
163
477179
4093
์ด ๊ฐ•์—ฐ์žฅ ๋ฐ–์—์„œ ์ด๊ฒƒ์— ๋Œ€ํ•ด ์–˜๊ธฐํ•˜์‹œ๋ฉด ์•ˆ๋˜์š”. ์•„์‹œ๊ฒ ์ฃ ?
08:01
So I want you to look at the payload
164
481272
1908
์ดˆํŒŒ๋ฆฌ์˜ ๊ผฌ๋ฆฌ์—
08:03
at the tail of the fruit fly.
165
483180
3026
๋‹ฌ๋ ค์žˆ๋Š” ๊ฒƒ์„ ๋ณด์‹œ๊ธฐ ๋ฐ”๋ž๋‹ˆ๋‹ค.
08:06
Watch it very closely,
166
486206
2101
์ž์„ธํžˆ ๋ณด์„ธ์š”.
08:08
and you'll see why my six-year-old son
167
488307
4297
๊ทธ๋Ÿฌ๋ฉด ์ œ ์—ฌ์„ฏ ์‚ด ๋‚œ ์•„๋“ค์ด
08:12
now wants to be a neuroscientist.
168
492604
4729
์‹ ๊ฒฝ ๊ณผํ•™์ž๊ฐ€ ๋˜๊ณ  ์‹ถ์–ดํ•˜๋Š” ์ด์œ ๋ฅผ ์ดํ•ดํ•˜์‹ค ๊ฑฐ์—์š”.
08:17
Wait for it.
169
497333
1179
์ž ์‹œ๋งŒ์š”.
08:18
Pshhew.
170
498512
1569
ํœด-
08:20
So at least you'll admit that if fruit flies are not as clever as mice,
171
500081
3084
์ดˆํŒŒ๋ฆฌ๊ฐ€ ์ƒ์ฅ๋ณด๋‹ค ๋˜‘๋˜‘ํ•˜์ง€ ์•Š๋‹คํ•ด๋„
08:23
they're at least as clever as pigeons. (Laughter)
172
503165
4916
์ ์–ด๋„ ๋น„๋‘˜๊ธฐ๋ณด๋‹ค๋Š” ๋˜‘๋˜‘ํ•˜๋‹ค๋Š” ๊ฒƒ์„ ์ธ์ •ํ•˜์‹ค๊ฑฐ์—์š” (์›ƒ์Œ)
08:28
Now, I want to get across that it's not just a matter of numbers
173
508081
3967
๋‹จ์ง€ ์ˆซ์ž์˜ ๋ฌธ์ œ๊ฐ€ ์•„๋‹ˆ๋ผ
08:32
but also the challenge for a fly to compute
174
512048
2598
ํŒŒ๋ฆฌ๊ฐ€ ๊ทธ๋ ‡๊ฒŒ ์ž‘์€ ๋‰ด๋ก ์„ ๊ฐ€์ง€๊ณ 
08:34
everything its brain has to compute with such tiny neurons.
175
514646
2849
๋ชจ๋“  ๊ฒƒ์„ ๊ณ„์‚ฐํ•˜๋Š”๊ฒŒ ํŒŒ๋ฆฌ์—๊ฒŒ๋Š” ๋„์ „์ด๋ผ๋Š” ๊ฒƒ์„ ๋ง์”€๋“œ๋ฆฌ๊ณ  ์‹ถ์–ด์š”.
08:37
So this is a beautiful image of a visual interneuron from a mouse
176
517495
2988
์ œํ”„ ๋ฆญ๋งŒ(Jeff Lichtman) ์—ฐ๊ตฌ์‹ค์—์„œ ์ดฌ์˜ํ•œ
08:40
that came from Jeff Lichtman's lab,
177
520483
2768
์ƒ์ฅ์˜ ์•„๋ฆ„๋‹ค์šด ์‹œ๊ฐ ๊ฐœ์žฌ๋‰ด๋ก (interneuron) ์‚ฌ์ง„์ž…๋‹ˆ๋‹ค.
08:43
and you can see the wonderful images of brains
178
523251
3247
๊ทธ๊ฐ€ ๊ฐ•์—ฐ์—์„œ ์–˜๊ธฐํ•œ
08:46
that he showed in his talk.
179
526498
3193
๋ฉ‹์ง„ ๋‡Œ ์‚ฌ์ง„์„ ๋ณด์‹ค ์ˆ˜ ์žˆ์ง€์š”.
08:49
But up in the corner, in the right corner, you'll see,
180
529691
2368
ํ•˜์ง€๋งŒ ์ €๊ธฐ ๊ฐ€์žฅ์ž๋ฆฌ์—, ์˜ค๋ฅธ์ชฝ ์œ„์—์š”.
08:52
at the same scale, a visual interneuron from a fly.
181
532059
4112
๊ฐ™์€ ์ถ•์ฒ™์˜ ํŒŒ๋ฆฌ์˜ ์‹œ๊ฐ ๊ฐœ์žฌ๋‰ด๋ก ์„ ๋ณด์„ธ์š”.
08:56
And I'll expand this up.
182
536171
1841
ํ™•๋Œ€ํ•ด๋ณผ๊นŒ์š”.
08:58
And it's a beautifully complex neuron.
183
538012
2170
์•„๋ฆ„๋‹ต๊ฒŒ ์–ฝํžŒ, ๋ณต์žกํ•œ ๋‰ด๋ก ์ด์ง€์š”.
09:00
It's just very, very tiny, and there's lots of biophysical challenges
184
540182
3485
์ •๋ง ์ •๋ง ์ž‘์•„์š”. ์—„์ฒญ๋‚œ ์ƒ๋ฌผ๋ฌผ๋ฆฌํ•™์ ์ธ ๋„์ „์ด ์žˆ์Šต๋‹ˆ๋‹ค.
09:03
with trying to compute information with tiny, tiny neurons.
185
543667
3623
์ด ์ž‘๊ณ  ์ž‘์€ ๋‰ด๋ก ๋“ค์„ ๊ฐ€์ง€๊ณ  ์ •๋ณด๋ฅผ ๊ณ„์‚ฐํ•ด์•ผ ํ•˜์ง€์š”.
09:07
How small can neurons get? Well, look at this interesting insect.
186
547290
3537
๋‰ด๋ก ์ด ์–ผ๋งˆ๋‚˜ ์ž‘์•„์งˆ ์ˆ˜ ์žˆ์„๊นŒ์š”? ์ž, ์ด ์žฌ๋ฐŒ๋Š” ๊ณค์ถฉ์„ ํ•œ ๋ฒˆ ๋ด…์‹œ๋‹ค.
09:10
It looks sort of like a fly. It has wings, it has eyes,
187
550827
2212
ํŒŒ๋ฆฌ์˜ ์ผ์ข…์ด์—์š”. ๋‚ ๊ฐœ๊ฐ€ ์žˆ๊ณ , ๋ˆˆ์ด ์žˆ๊ณ ,
09:13
it has antennae, its legs, complicated life history,
188
553039
2799
๋”๋“ฌ์ด์™€ ๋‹ค๋ฆฌ๊ฐ€ ์žˆ์–ด์š”. ์‚ถ์ด ๋ณต์žกํ•˜์ฃ .
09:15
it's a parasite, it has to fly around and find caterpillars
189
555838
3096
๊ธฐ์ƒ์„ ํ•˜๋Š”๋ฐ, ๋‚ ์•„๋‹ค๋‹ˆ๋ฉด์„œ
09:18
to parasatize,
190
558934
1382
๊ธฐ์ƒํ•  ์• ๋ฒŒ๋ ˆ๋ฅผ ์ฐพ์Šต๋‹ˆ๋‹ค.
09:20
but not only is its brain the size of a salt grain,
191
560316
4115
ํ•˜์ง€๋งŒ ์ด ๋…€์„์˜ ๋‡Œ๊ฐ€ ์ดˆํŒŒ๋ฆฌ์ฒ˜๋Ÿผ
09:24
which is comparable for a fruit fly,
192
564431
1969
์†Œ๊ธˆ ์•Œ๊ฐฑ์ด๋งŒํ•œ๊ฒŒ ์•„๋‹ˆ๋ผ
09:26
it is the size of a salt grain.
193
566400
2926
๋ชธ ์ž์ฒด๊ฐ€ ์†Œ๊ธˆ ์•Œ๊ฐฑ์ด๋งŒํ•ฉ๋‹ˆ๋‹ค.
09:29
So here's some other organisms at the similar scale.
194
569326
3635
๊ฐ™์€ ์ถ•์ฒ™์˜ ๋‹ค๋ฅธ ๊ธฐ๊ด€๋“ค์„ ๋ณด์‹œ์ฃ .
09:32
This animal is the size of a paramecium and an amoeba,
195
572961
4130
์งš์‹ ๋ฒŒ๋ ˆ์™€ ์•„๋ฉ”๋ฐ” ํฌ๊ธฐ์˜ ์ƒ๋ฌผ์ด์—์š”.
09:37
and it has a brain of 7,000 neurons that's so small --
196
577091
3880
7์ฒœ๊ฐœ์˜ ๋‰ด๋ก ์„ ๊ฐ€์ง„ ๋‡Œ๊ฐ€ ์žˆ์ง€์š”. ์ •๋ง ์ž‘์•„์š”.
09:40
you know these things called cell bodies you've been hearing about,
197
580971
2456
์„ธํฌ์ฒด๋ผ ๋ถˆ๋ฆฌ๋Š” ์ด๊ฒƒ๋“ค์„ ๋“ค์–ด๋ณด์…จ์„๊ฑฐ์—์š”.
09:43
where the nucleus of the neuron is?
198
583427
1651
๋‰ด๋ก ์˜ ํ•ต์ด ์–ด๋”” ์žˆ๋Š”๊ฑธ๊นŒ์š”?
09:45
This animal gets rid of them because they take up too much space.
199
585078
3460
์ด ์ƒ๋ฌผ๋“ค์€ ํ•ต์ด ์ž๋ฆฌ๋ฅผ ๋„ˆ๋ฌด ๋งŽ์ด ์ฐจ์ง€ํ•ด์„œ ์—†์• ๋ฒ„๋ ธ์Šต๋‹ˆ๋‹ค.
09:48
So this is a session on frontiers in neuroscience.
200
588538
2473
์‹ ๊ฒฝ ๊ณผํ•™์˜ ๋ฏธ๊ฐœ์ฒ™ ๋ถ„์•ผ๋ผ ํ•  ์ˆ˜ ์žˆ์–ด์š”.
09:51
I would posit that one frontier in neuroscience is to figure out how the brain of that thing works.
201
591011
5360
์‹ ๊ฒฝ ๊ณผํ•™์˜ ๋ฏธ๊ฐœ์ฒ™ ๋ถ„์•ผ ์ค‘ ํ•˜๋‚˜๊ฐ€ ์ด๊ฒƒ๋“ค์ด ์–ด๋–ป๊ฒŒ ์ผํ•˜๋Š”์ง€๋ฅผ ์ดํ•ดํ•˜๋Š” ๊ฒƒ์ด๋ผ๊ณ  ์ œ์•ˆํ•˜๊ณ  ์‹ถ์–ด์š”.
09:56
But let's think about this. How can you make a small number of neurons do a lot?
202
596371
5633
ํ•˜์ง€๋งŒ ์ƒ๊ฐํ•ด ๋ด…์‹œ๋‹ค. ์–ด๋–ป๊ฒŒ ์ ์€ ์ˆ˜์˜ ๋‰ด๋ก ์ด ๋งŽ์€ ์ผ์„ ํ•  ์ˆ˜ ์žˆ์„๊นŒ์š”?
10:02
And I think, from an engineering perspective,
203
602004
2522
์ œ ์ƒ๊ฐ์—๋Š” ๊ณตํ•™์ ์ธ ๊ด€์ ์—์„œ
10:04
you think of multiplexing.
204
604526
1729
๋‹ค์ค‘ ์ฒ˜๋ฆฌ๋ฅผ ์ƒ๊ฐํ•ด๋ณด์ฃ .
10:06
You can take a hardware and have that hardware
205
606255
2703
์„œ๋กœ ๋‹ค๋ฅธ ์‹œ๊ฐ„์— ์—ฌ๋Ÿฌ ์ผ์„ ์ฒ˜๋ฆฌํ•  ์ˆ˜ ์žˆ๋Š”
10:08
do different things at different times,
206
608958
1613
ํ•˜๋“œ์›จ์–ด๋ฅผ ์ƒ๊ฐํ•˜์‹ค ์ˆ˜๋„ ์žˆ๊ณ ,
10:10
or have different parts of the hardware doing different things.
207
610571
2995
์—ฌ๋Ÿฌ ์ผ์„ ์ฒ˜๋ฆฌํ•˜๋Š” ์—ฌ๋Ÿฌ ๋ถ€์†์„ ๊ฐ€์ง„ ํ•˜๋“œ์›จ์–ด๋ฅผ ์ƒ๊ฐํ•˜์‹ค ์ˆ˜๋„ ์žˆ์–ด์š”.
10:13
And these are the two concepts I'd like to explore.
208
613566
3271
์ด ๋‘๊ฐ€์ง€ ์ปจ์…‰์ด ์ œ๊ฐ€ ํƒ๊ตฌํ•˜๊ณ ์ž ํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
10:16
And they're not concepts that I've come up with,
209
616837
1658
๊ทธ๋ฆฌ๊ณ  ์ด ์ปจ์…‰์€ ์ œ๊ฐ€ ์ƒ๊ฐํ•ด๋‚ธ ๊ฒƒ์ด ์•„๋‹ˆ๋ผ
10:18
but concepts that have been proposed by others in the past.
210
618495
4545
์ด๋ฏธ ๊ณผ๊ฑฐ์— ๋‹ค๋ฅธ ๋ถ„๋“ค์ด ์ œ์•ˆํ•œ ๊ฒƒ์ž…๋‹ˆ๋‹ค.
10:23
And one idea comes from lessons from chewing crabs.
211
623040
3075
๊ฒŒ์˜ ์ €์ž‘ ์šด๋™์„ ๋ณด๊ณ  ํ•œ ๊ฐ€์ง€ ์•„์ด๋””์–ด๋ฅผ ๋– ์˜ฌ๋ ธ๋Š”๋ฐ,
10:26
And I don't mean chewing the crabs.
212
626115
1867
์ œ๊ฐ€ ๊ฒŒ๋ฅผ ๋จน์—ˆ๋‹ค๋Š” ์–˜๊ธฐ๊ฐ€ ์•„๋‹ˆ์—์š”,
10:27
I grew up in Baltimore, and I chew crabs very, very well.
213
627982
3599
์ „ ๋ณผํ‹ฐ๋ชจ์–ด ์ถœ์‹ ์ด๋ผ ๊ฒŒ๋ฅผ ์ž˜ ์”น์–ด ๋จน๊ธฐ๋Š” ํ•ด์š”.
10:31
But I'm talking about the crabs actually doing the chewing.
214
631581
2857
์‹ค์ œ๋กœ ์Œ์‹๋ฌผ์„ ์”น์–ด ๋จน๋Š” ๊ฒŒ์— ๋Œ€ํ•œ ์–˜๊ธฐ์ธ๋ฐ์š”,
10:34
Crab chewing is actually really fascinating.
215
634438
2030
๊ฒŒ์˜ ์ €์ž‘ ์šด๋™์€ ์‹ค๋กœ ์ธ์ƒ์ ์ž…๋‹ˆ๋‹ค.
10:36
Crabs have this complicated structure under their carapace
216
636468
3259
๊ฒŒ๋Š” ๊ป์งˆ ๋ฐ‘์— ์ด๋Ÿฐ ๋ณต์žกํ•œ ๊ตฌ์กฐ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋Š”๋ฐ
10:39
called the gastric mill
217
639727
1310
์ €์ž‘๊ธฐ(gastric mill)์ด๋ผ ๋ถˆ๋ฆฌ๋Š” ๊ธฐ๊ด€์ž…๋‹ˆ๋‹ค.
10:41
that grinds their food in a variety of different ways.
218
641037
2430
์ด๊ฒƒ์€ ๋‹ค์–‘ํ•œ ๋ฐฉ๋ฒ•์œผ๋กœ ์Œ์‹๋ฌผ์„ ๊ฐˆ์•„๋ƒ…๋‹ˆ๋‹ค.
10:43
And here's an endoscopic movie of this structure.
219
643467
5259
์ด ๊ธฐ๊ด€์˜ ๋‚ด์‹œ๊ฒฝ ์‚ฌ์ง„์„ ๋ณด์„ธ์š”.
10:48
The amazing thing about this is that it's controlled
220
648726
2560
๋†€๋ผ์šด ์ ์€ ์ด๊ฒƒ์ด ๋‹จ์ง€ ๋ช‡ ๊ฐœ์˜ ๋‰ด๋ก ์œผ๋กœ ์ œ์–ด๋œ๋‹ค๋Š” ์ ์ž…๋‹ˆ๋‹ค.
10:51
by a really tiny set of neurons, about two dozen neurons
221
651286
3432
์Šค๋ฌด์—ฌ๊ฐœ ๋‚จ์ง“ํ•œ ๋‰ด๋ก ๋งŒ์œผ๋กœ
10:54
that can produce a vast variety of different motor patterns,
222
654718
4963
์—„์ฒญ๋‚˜๊ฒŒ ๋‹ค์–‘ํ•œ ์šด๋™ ํŒจํ„ด์„ ๋งŒ๋“ค์–ด๋ƒ…๋‹ˆ๋‹ค.
10:59
and the reason it can do this is that this little tiny ganglion
223
659681
4347
๊ฒŒ์˜ ์ด ๋งค์šฐ ์ž‘์€ ์‹ ๊ฒฝ์ ˆ์€ ์‹ค์ œ๋กœ
11:04
in the crab is actually inundated by many, many neuromodulators.
224
664028
4184
๋งค์šฐ ๋งŽ์€ ์‹ ๊ฒฝ ์กฐ์ • ์ธ์ž๋กœ ๊ฐ€๋“ ์ฐจ ์žˆ๊ธฐ ๋•Œ๋ฌธ์— ๊ฐ€๋Šฅํ•ฉ๋‹ˆ๋‹ค.
11:08
You heard about neuromodulators earlier.
225
668212
2141
์•ž์„œ ์‹ ๊ฒฝ ์กฐ์ • ์ธ์ž์— ๋Œ€ํ•ด ๋“ค์–ด๋ณด์…จ์„๊ฑฐ์—์š”.
11:10
There are more neuromodulators
226
670353
2225
์‹ค์ œ๋กœ ๋‰ด๋ก ์„ ๋Œ€์‹ ํ•ด์„œ ์ด ๊ธฐ๊ด€์„
11:12
that alter, that innervate this structure than actually neurons in the structure,
227
672578
5485
์ž๊ทนํ•˜๋Š” ์‹ ๊ฒฝ ์กฐ์ • ์ธ์ž๋“ค์ด ์žˆ์–ด์š”.
11:18
and they're able to generate a complicated set of patterns.
228
678063
4242
๊ทธ๋ž˜์„œ ๋ณต์žกํ•œ ์ข…๋ฅ˜์˜ ์›€์ง์ž„์„ ํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•ด์ฃผ์ฃ .
11:22
And this is the work by Eve Marder and her many colleagues
229
682305
3441
์ด๋ธŒ ๋งˆ๋”(Eve Marder)์™€ ๊ทธ์˜ ๋งŽ์€ ๋™๋ฃŒ ๊ณผํ•™์ž๋“ค์ด
11:25
who've been studying this fascinating system
230
685746
2295
์ด ๋†€๋ผ์šด ์‹œ์Šคํ…œ์— ๋Œ€ํ•ด ์—ฐ๊ตฌํ–ˆ๋Š”๋ฐ,
11:28
that show how a smaller cluster of neurons
231
688041
2152
์–ด๋–ป๊ฒŒ ์ด ์ž‘์€ ๋‰ด๋ก  ์ง‘ํ•ฉ์ฒด๊ฐ€
11:30
can do many, many, many things
232
690193
1825
์—„์ฒญ๋‚˜๊ฒŒ ๋งŽ์€ ์ผ์„ ํ•  ์ˆ˜ ์žˆ๋ƒํ•˜๋ฉด
11:32
because of neuromodulation that can take place on a moment-by-moment basis.
233
692018
4856
์‹ ๊ฒฝ ์กฐ์ ˆ ๊ธฐ์ œ๊ฐ€ ์ˆœ๊ฐ„์ˆœ๊ฐ„ ๋ฐœ์ƒํ•˜๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.
11:36
So this is basically multiplexing in time.
234
696874
2439
์ฆ‰ ๊ธฐ๋ณธ์ ์œผ๋กœ ๋™์‹œ ๋‹ค์ค‘ ์ฒ˜๋ฆฌ๊ฐ€ ์ด๋ฃจ์–ด์ง€๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
11:39
Imagine a network of neurons with one neuromodulator.
235
699313
2785
ํ•œ ๊ฐœ์˜ ์‹ ๊ฒฝ ์กฐ์ ˆ๊ธฐ๋ฅผ ๊ฐ€์ง„ ๋‰ด๋ก ์˜ ๋„คํŠธ์›Œํฌ๋ฅผ ์ƒ์ƒํ•ด๋ณด์„ธ์š”.
11:42
You select one set of cells to perform one sort of behavior,
236
702098
3478
ํ•œ ํ–‰๋™์„ ์œ„ํ•œ ํ•œ ์„ธํฌ ์ง‘ํ•ฉ์ฒด๋ฅผ ์„ ํƒํ•˜๊ณ ,
11:45
another neuromodulator, another set of cells,
237
705576
2618
๋˜ ๋‹ค๋ฅธ ์‹ ๊ฒฝ ์กฐ์ ˆ๊ธฐ์™€ ๋‹ค๋ฅธ ์„ธํฌ๋“ค๊ณผ
11:48
a different pattern, and you can imagine
238
708194
1713
๋‹ค๋ฅธ ์›€์ง์ž„์— ๋Œ€ํ•ด์„œ๋„ ๊ทธ๋ ‡๊ฒŒ ํ•ด๋ณด๋ฉด,
11:49
you could extrapolate to a very, very complicated system.
239
709907
3878
๋งค์šฐ ๋ณต์žกํ•œ ์‹œ์Šคํ…œ์„ ์ถ”๋ก ํ•  ์ˆ˜ ์žˆ์„ ๊ฒ๋‹ˆ๋‹ค.
11:53
Is there any evidence that flies do this?
240
713785
2094
ํŒŒ๋ฆฌ๊ฐ€ ์ด๋ ‡๊ฒŒ ํ•œ๋‹ค๋Š” ์ฆ๊ฑฐ๊ฐ€ ์žˆ์„๊นŒ์š”?
11:55
Well, for many years in my laboratory and other laboratories around the world,
241
715879
3375
๋ช‡ ๋…„๊ฐ„ ์ œ ์—ฐ๊ตฌ์‹ค๊ณผ ์„ธ๊ณ„์˜ ๋‹ค๋ฅธ ์—ฐ๊ตฌ์‹ค์—์„œ๋Š”
11:59
we've been studying fly behaviors in little flight simulators.
242
719254
2648
์ž‘์€ ๋น„ํ–‰ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ ์•ˆ์—์„œ ํŒŒ๋ฆฌ๋ฅผ ์—ฐ๊ตฌํ•ด์™”์Šต๋‹ˆ๋‹ค.
12:01
You can tether a fly to a little stick.
243
721902
1706
ํŒŒ๋ฆฌ๋ฅผ ์ž‘์€ ๋ง‰๋Œ€์— ์—ฐ๊ฒฐํ•ด์„œ
12:03
You can measure the aerodynamic forces it's creating.
244
723608
2501
ํŒŒ๋ฆฌ๊ฐ€ ๋งŒ๋“ค์–ด๋‚ด๋Š” ๊ณต๊ธฐ ์—ญํ•™์  ํž˜์„ ์ธก์ •ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
12:06
You can let the fly play a little video game
245
726109
2546
์˜์ƒ ํ‘œ์‹œ ์žฅ์น˜ ์•ˆ์—์„œ ๋‚ ์•„๋‹ค๋‹ˆ๊ฒŒ ํ•ด์„œ
12:08
by letting it fly around in a visual display.
246
728655
3878
ํŒŒ๋ฆฌ๊ฐ€ ๋น„๋””์˜ค ๊ฒŒ์ž„์„ ํ•˜๊ฒŒ ํ•  ์ˆ˜๋„ ์žˆ์–ด์š”.
12:12
So let me show you a little tiny sequence of this.
247
732533
2337
์•„์ฃผ ์งง์€ ์—ฐ์† ์‚ฌ์ง„์„ ๋ณด์—ฌ๋“œ๋ฆด๊ป˜์š”.
12:14
Here's a fly
248
734870
1227
์—ฌ๊ธฐ ํŒŒ๋ฆฌ๊ฐ€ ์žˆ๊ณ 
12:16
and a large infrared view of the fly in the flight simulator,
249
736097
3437
๋น„ํ–‰ ์‹œ๋ฎฌ๋ ˆ์ดํ„ฐ ์•ˆ์— ์žˆ๋Š” ํŒŒ๋ฆฌ์˜ ์ ์™ธ์„  ์ดฌ์˜ ์‚ฌ์ง„์ž…๋‹ˆ๋‹ค.
12:19
and this is a game the flies love to play.
250
739534
1955
ํŒŒ๋ฆฌ๊ฐ€ ์ข‹์•„ํ•˜๋Š” ๊ฒŒ์ž„์ธ๋ฐ,
12:21
You allow them to steer towards the little stripe,
251
741489
2437
ํŒŒ๋ฆฌ๊ฐ€ ์ž‘์€ ๋ง‰๋Œ€๋กœ ์กฐ์ข…ํ•ด๋‚˜๊ฐˆ ์ˆ˜ ์žˆ๊ฒŒ ํ•˜๋ฉด
12:23
and they'll just steer towards that stripe forever.
252
743926
2825
๊ณ„์†ํ•ด์„œ ๋ง‰๋Œ€๋ฅผ ํ–ฅํ•ด ๋‚˜์•„๊ฐ‘๋‹ˆ๋‹ค.
12:26
It's part of their visual guidance system.
253
746751
3558
์ด๊ฒƒ์ด ํŒŒ๋ฆฌ์˜ ์‹œ๊ฐ ์œ ๋„ ์žฅ์น˜์ž…๋‹ˆ๋‹ค.
12:30
But very, very recently, it's been possible
254
750309
2345
์•„์ฃผ ์ตœ๊ทผ์—
12:32
to modify these sorts of behavioral arenas for physiologies.
255
752654
4940
์ƒ๋ฆฌํ•™์„ ํ†ตํ•ด ์ด๋Ÿฐ ํ–‰๋™ ์˜์—ญ์˜ ์กฐ์ •์ด ๊ฐ€๋Šฅํ•ด์กŒ์ง€์š”.
12:37
So this is the preparation that one of my former post-docs,
256
757594
2488
์ œ ๋ฐ•์‚ฌํ›„ ๊ณผ์ • ํ•™์ƒ์˜ ํ•˜๋‚˜์˜€๋˜,
12:40
Gaby Maimon, who's now at Rockefeller, developed,
257
760082
2443
์ง€๊ธˆ์€ ๋กํŽ ๋Ÿฌ์—์„œ ์ผํ•˜๋Š” ๊ฐœ๋น„ ๋ฉ”์ด๋จผ(Gaby Maimon)์ด
12:42
and it's basically a flight simulator
258
762525
1686
๊ธฐ๋ณธ์ ์ธ ๋น„ํ–‰ ์‹œ๋ฌผ๋ ˆ์ดํ„ฐ๋ฅผ ๋งŒ๋“ค์—ˆ๋Š”๋ฐ,
12:44
but under conditions where you actually can stick an electrode
259
764211
3075
์‹ค์ œ๋กœ ํŒŒ๋ฆฌ์˜ ๋‡Œ์— ์ „๊ทน์„ ๋ถ™์ด๊ณ 
12:47
in the brain of the fly and record
260
767286
2264
ํŒŒ๋ฆฌ์˜ ๋‡Œ์—์„œ ์œ ์ „์ ์œผ๋กœ ํ™•์ธ๋œ ๋‰ด๋ก ์„ ํ†ตํ•ด
12:49
from a genetically identified neuron in the fly's brain.
261
769550
3656
๊ธฐ๋ก์„ ํ•˜๋Š” ์žฅ์น˜์˜€์Šต๋‹ˆ๋‹ค.
12:53
And this is what one of these experiments looks like.
262
773206
2298
์ด๊ฒƒ์ด ๊ทธ ์‹คํ—˜ ์ค‘ ์ผ๋ถ€์—์š”.
12:55
It was a sequence taken from another post-doc in the lab,
263
775504
2971
์ด ์—ฐ์† ์‚ฌ์ง„์€ ์‹คํ—˜์‹ค์˜ ๋‹ค๋ฅธ ๋˜๋‹ค๋ฅธ ํ•™์ƒ
12:58
Bettina Schnell.
264
778475
1199
๋ฒ ํ‹ฐ๋‚˜ ์Šˆ๋„ฌ(Bettina Schnell)์˜ ์—ฐ๊ตฌ์ธ๋ฐ์š”.
12:59
The green trace at the bottom is the membrane potential
265
779674
3392
์•„๋ž˜์˜ ๋…น์ƒ‰ ๊ทธ๋ž˜ํ”„๊ฐ€ ํŒŒ๋ฆฌ ๋‡Œ์— ์žˆ๋Š”
13:03
of a neuron in the fly's brain,
266
783066
2030
๋‰ด๋ก  ๋ง‰์˜ ์œ„์น˜ ๋ณ€ํ™”๋ฅผ ํ‘œ์‹œํ•œ ๊ฒƒ์ž…๋‹ˆ๋‹ค.
13:05
and you'll see the fly start to fly, and the fly is actually
267
785096
2942
ํŒŒ๋ฆฌ๊ฐ€ ๋‚ ๊ธฐ ์‹œ์ž‘ํ•˜๋ฉด์„œ,
13:08
controlling the rotation of that visual pattern itself
268
788038
3279
ํŒŒ๋ฆฌ๋Š” ์‹ค์ œ์ ์œผ๋กœ ์‹œ๊ฐ ํŒจํ„ด์˜ ํšŒ์ „์„
13:11
by its own wing motion,
269
791317
1479
๋‚ ๊ฐœ์˜ ์›€์ง์ž„์— ๋”ฐ๋ผ ์กฐ์ข…ํ•˜๋Š” ๊ฒƒ์„ ๋ณด์‹ค ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
13:12
and you can see this visual interneuron
270
792796
2110
๊ทธ๋ฆฌ๊ณ  ์ด ์‹œ๊ฐ๊ฐœ์žฌ ๋‰ด๋ก ์ด ํŒŒ๋ฆฌ๊ฐ€ ๋‚  ๋•Œ
13:14
respond to the pattern of wing motion as the fly flies.
271
794906
3908
๋‚ ๊ฐœ์˜ ์›€์ง์ž„ ํ˜•ํƒœ์— ๋ฐ˜์‘ํ•˜๋Š” ๊ฒƒ์„ ๋ณด์‹ค ์ˆ˜ ์žˆ์–ด์š”.
13:18
So for the first time we've actually been able to record
272
798814
2376
๊ทธ๋ž˜์„œ ์ฒ˜์Œ์œผ๋กœ
13:21
from neurons in the fly's brain while the fly
273
801190
2908
ํŒŒ๋ฆฌ๊ฐ€ ๋น„ํ–‰๊ณผ ๊ฐ™์€ ๋ณต์žกํ•œ ํ–‰๋™์„ ํ•˜๋Š” ๋™์•ˆ
13:24
is performing sophisticated behaviors such as flight.
274
804098
4468
๊ทธ ๋‡Œ์˜ ๋‰ด๋ก ์˜ ๋ณ€ํ™”๋ฅผ ๊ธฐ๋กํ•  ์ˆ˜ ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค.
13:28
And one of the lessons we've been learning
275
808566
1855
๋ช‡ ๋…„๊ฐ„ ์„ธํฌ ์ƒ๋ฆฌ ๊ธฐ๋Šฅ์— ๋Œ€ํ•ด
13:30
is that the physiology of cells that we've been studying
276
810421
2420
๋ช‡ ๋…„๊ฐ„์˜ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด
13:32
for many years in quiescent flies
277
812841
2421
ํ•œ ๊ฐ€์ง€ ๋ฐฐ์šด ์ ์€
13:35
is not the same as the physiology of those cells
278
815262
2648
์›€์ง์ž„์ด ์—†๋Š” ํŒŒ๋ฆฌ์˜ ์„ธํฌ์™€
13:37
when the flies actually engage in active behaviors
279
817910
2736
๋‚ ๊ฑฐ๋‚˜ ์•ž๋’ค๋กœ ํ™œ๋ฐœํžˆ ์›€์ง์ด๋Š” ํŒŒ๋ฆฌ์˜
13:40
like flying and walking and so forth.
280
820646
2539
์„ธํฌ ์ƒ๋ฆฌ ๊ธฐ๋Šฅ์ด ๊ฐ™์ง€ ์•Š๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.
13:43
And why is the physiology different?
281
823185
2925
์™œ ์ƒ๋ฆฌ ๊ธฐ๋Šฅ์ด ๋‹ค๋ฅผ๊นŒ์š”?
13:46
Well it turns out it's these neuromodulators,
282
826110
2057
์ด๋Ÿฐ ์‹ ๊ฒฝ ์กฐ์ ˆ ๋ฌผ์งˆ์ด
13:48
just like the neuromodulators in that little tiny ganglion in the crabs.
283
828167
3951
๊ฒŒ์˜ ์ž‘์€ ์‹ ๊ฒฝ์ ˆ์— ์žˆ๋Š” ๊ฒƒ๊ณผ ๊ฐ™์€ ๊ฒƒ์ด๋ผ๋Š” ์‚ฌ์‹ค์ด ๋ฐํ˜€์กŒ์Šต๋‹ˆ๋‹ค.
13:52
So here's a picture of the octopamine system.
284
832118
2550
์ด๊ฒƒ์ด ์˜ฅํ† ํŒŒ๋ฏผ ์‹œ์Šคํ…œ์˜ ์‚ฌ์ง„์ž…๋‹ˆ๋‹ค. (๊ต๊ฐ ์‹ ๊ฒฝ ํฅ๋ถ„์„ฑ ์•„๋ฏผ)
13:54
Octopamine is a neuromodulator
285
834668
1754
์˜ฅํ† ํŒŒ๋ฏผ์€ ์‹ ๊ฒฝ ์กฐ์ ˆ ๋ฌผ์งˆ๋กœ
13:56
that seems to play an important role in flight and other behaviors.
286
836422
4336
๋น„ํ–‰๊ณผ ๋‹ค๋ฅธ ํ–‰๋™์— ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋ณด์ž…๋‹ˆ๋‹ค.
14:00
But this is just one of many neuromodulators
287
840758
2472
ํ•˜์ง€๋งŒ ์ด๊ฒƒ์€ ํŒŒ๋ฆฌ ๋‡Œ์— ์žˆ๋Š”
14:03
that's in the fly's brain.
288
843230
1071
๋‹จ ํ•˜๋‚˜์˜ ์‹ ๊ฒฝ ์กฐ์ ˆ ๋ฌผ์งˆ์— ๋ถˆ๊ณผํ•ฉ๋‹ˆ๋‹ค.
14:04
So I really think that, as we learn more,
289
844301
2666
๊ทธ๋ž˜์„œ ์ €๋Š” ์—ฐ๊ตฌ๊ฐ€ ์ง„์ฒ™๋จ์— ๋”ฐ๋ผ
14:06
it's going to turn out that the whole fly brain
290
846967
2527
ํŒŒ๋ฆฌ ๋‡Œ ์ „์ฒด๊ฐ€ ๊ฒŒ์˜ ๊ตฌ์œ„์‹ ๊ฒฝ๊ณ„(stomatogastric)
14:09
is just like a large version of this stomatogastric ganglion,
291
849494
3089
์‹ ๊ฒฝ์ ˆ์„ ํ™•๋Œ€ํ•œ ๊ฒƒ๊ณผ ๊ฐ™๋‹ค๋Š” ์ ์„ ๋ฐํ˜€๋‚ผ ์ˆ˜ ์žˆ๋‹ค๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค.
14:12
and that's one of the reasons why it can do so much with so few neurons.
292
852583
4360
์ด๊ฒƒ์ด ํŒŒ๋ฆฌ๊ฐ€ ์ ์€ ์ˆ˜์˜ ๋‰ด๋ก ์„ ๊ฐ€์ง€๊ณ ๋„ ๋งŽ์€ ์ผ์„ ํ•  ์ˆ˜ ์žˆ๋Š” ์ด์œ  ์ค‘ ํ•˜๋‚˜์ž…๋‹ˆ๋‹ค.
14:16
Now, another idea, another way of multiplexing
293
856943
2787
๋‹ค๋ฅธ ์ƒ๊ฐ, ๋‹ค๋ฅธ ๋ฐฉ๋ฒ•์˜ ๋‹ค์ค‘ ์ฒ˜๋ฆฌ๋กœ๋Š”
14:19
is multiplexing in space,
294
859730
1656
๊ณต๊ฐ„ ํ™œ์šฉ์ž…๋‹ˆ๋‹ค.
14:21
having different parts of a neuron
295
861386
1694
๋‰ด๋ก ์˜ ์„œ๋กœ ๋‹ค๋ฅธ ๋ถ€๋ถ„์ด ๋™์‹œ์—
14:23
do different things at the same time.
296
863080
2122
๋‹ค๋ฅธ ์ผ์„ ์ฒ˜๋ฆฌํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜๋Š” ๊ฒƒ์ด์ฃ .
14:25
So here's two sort of canonical neurons
297
865202
1833
์ฒ™์ถ”๋™๋ฌผ๊ณผ ๋ฌด์ฒ™์ถ”๋™๋ฌผ์˜
14:27
from a vertebrate and an invertebrate,
298
867035
2285
์„œ๋กœ ๋Œ€์กฐ๋˜๋Š” ๋‰ด๋ก ๋“ค์ด ์žˆ๋Š”๋ฐ์š”,
14:29
a human pyramidal neuron from Ramon y Cajal,
299
869320
3250
์ธ๊ฐ„์˜ ํ”ผ๋ผ๋ฏธ๋“œ ๋‰ด๋ก ์€ ๋ผ๋ชฌ ์ด ์นดํ• (Ramon y Cajal)์˜ ์—ฐ๊ตฌ์ด๊ณ ,
14:32
and another cell to the right, a non-spiking interneuron,
300
872570
4003
์˜ค๋ฅธ์ชฝ์˜ ๋…ผ-์ŠคํŒŒ์ดํ‚น ๋‰ด๋ก ์€ ์˜ค๋ž˜ ์ „
14:36
and this is the work of Alan Watson and Malcolm Burrows many years ago,
301
876573
4147
์•จ๋Ÿฐ ์™“์Šจ(Alan Watson)๊ณผ ๋ง์ฝค ๋ฒ„๋กœ์šฐ์Šค(Malcolm Burrows)์˜ ์—ฐ๊ตฌ์ž…๋‹ˆ๋‹ค.
14:40
and Malcolm Burrows came up with a pretty interesting idea
302
880720
3075
๋ง์ฝค ๋ฒ„๋กœ์šฐ์Šค๋Š” ์žฌ๋ฏธ์žˆ๋Š” ์•„์ด๋””์–ด๋ฅผ ๋– ์˜ฌ๋ ธ๋Š”๋ฐ,
14:43
based on the fact that this neuron from a locust
303
883795
2882
์ด ๋ฉ”๋šœ๊ธฐ์˜ ๋‰ด๋ก ์ด
14:46
does not fire action potentials.
304
886677
1959
ํ–‰๋™์„ ์œ ๋ฐœํ•˜์ง€ ์•Š๋Š”๋‹ค๋Š” ๊ฒƒ์— ๊ทผ๊ฑฐํ–ˆ์ฃ .
14:48
It's a non-spiking cell.
305
888636
1748
์ด๊ฒƒ์€ ๋…ผ-์ŠคํŒŒ์ดํ‚น ์„ธํฌ์ž…๋‹ˆ๋‹ค.
14:50
So a typical cell, like the neurons in our brain,
306
890384
2780
์šฐ๋ฆฌ ๋‡Œ์— ์žˆ๋Š” ๊ฒƒ์ฒ˜๋Ÿผ ํŠน์ •ํ•œ ์„ธํฌ์—์š”,
14:53
has a region called the dendrites that receives input,
307
893164
2752
์šฐ๋ฆฌ ๋‡Œ์˜ ์ˆ˜์ƒ๋Œ๊ธฐ(dendrite)๋ผ๊ณ  ๋ถˆ๋ฆฌ๋Š”
14:55
and that input sums together
308
895916
2589
์ž…๋ ฅ์„ ๋ฐ›์•„๋“ค์ด๊ณ , ํ†ตํ•ฉํ•ด์„œ
14:58
and will produce action potentials
309
898505
2296
ํ–‰๋™์„ ์œ ๋ฐœํ•˜๋Š” ๊ฒƒ๊ณผ ๊ฐ™์€ ๊ฒƒ์œผ๋กœ
15:00
that run down the axon and then activate
310
900801
2331
์ถ•์ƒ‰๋Œ๊ธฐ๋ฅผ ๋”ฐ๋ผ ๋‚ด๋ ค์™€
15:03
all the output regions of the neuron.
311
903132
2296
๋‰ด๋ก ์˜ ์ถœ๋ ฅ ๋ถ€๋ถ„์„ ํ™œ์„ฑํ™”์‹œํ‚ต๋‹ˆ๋‹ค.
15:05
But non-spiking neurons are actually quite complicated
312
905428
2876
ํ•˜์ง€๋งŒ ๋…ผ-์ŠคํŒŒ์ดํ‚น ๋‰ด๋ก ์€ ์‚ฌ์‹ค ๋งค์šฐ ๋ณต์žกํ•ฉ๋‹ˆ๋‹ค.
15:08
because they can have input synapses and output synapses
313
908304
3112
์™œ๋ƒํ•˜๋ฉด ์ž…๋ ฅ๊ณผ ์ถœ๋ ฅ ์‹œ๋ƒ…์‹œ์Šค๊ฐ€ ์žˆ๋Š”๋ฐ,
15:11
all interdigitated, and there's no single action potential
314
911416
3663
๋ชจ๋‘ ๊ฒฌ๊ณ ํžˆ ์—ฐ๊ฒฐ๋˜์–ด ์žˆ๊ณ , ํ•œ ๊ฐ€์ง€๋งŒ ์ž‘์šฉํ•˜๋Š” ๊ฒƒ์€ ๋ถˆ๊ฐ€๋Šฅํ•ด์„œ
15:15
that drives all the outputs at the same time.
315
915079
3126
๋ชจ๋“  ์ถœ๋ ฅ์„ ๋™์‹œ์— ํ•ด์•ผ๋งŒ ํ•ฉ๋‹ˆ๋‹ค.
15:18
So there's a possibility that you have computational compartments
316
918205
3907
์ฆ‰ ์„œ๋กœ ๋‹ค๋ฅธ ์ผ์„ ๋™์‹œ์— ์ฒ˜๋ฆฌํ•˜๊ธฐ ์œ„ํ•ด
15:22
that allow the different parts of the neuron
317
922112
3978
๋‰ด๋ก ์˜ ์„œ๋กœ ๋‹ค๋ฅธ ๋ถ€๋ถ„์„ ์ด์šฉํ•˜๋Š”
15:26
to do different things at the same time.
318
926090
2560
๊ณ„์‚ฐ ๊ตฌ์—ญ์ด ์žˆ์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
15:28
So these basic concepts of multitasking in time
319
928650
4671
๊ทธ๋ž˜์„œ ๋™์‹œ์— ๊ฐ™์€ ๊ณต๊ฐ„์—์„œ
15:33
and multitasking in space,
320
933321
2361
๋‹ค์–‘ํ•œ ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•˜๋Š” ๊ธฐ๋ณธ์ ์ธ ๊ฐœ๋…์€
15:35
I think these are things that are true in our brains as well,
321
935682
2832
์šฐ๋ฆฌ ๋‡Œ์—์„œ๋„ ์ผ์–ด๋‚œ๋‹ค๊ณ  ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค.
15:38
but I think the insects are the true masters of this.
322
938514
2577
ํ•˜์ง€๋งŒ ๊ณค์ถฉ๋“ค์ด ์ด ์ ์— ์žˆ์–ด์„œ ๋”์šฑ ๋ฐœ๋‹ฌํ•ด์žˆ๋‹ค๊ณ  ๋ด…๋‹ˆ๋‹ค.
15:41
So I hope you think of insects a little bit differently next time,
323
941091
3116
๋‹ค์Œ๋ถ€ํ„ฐ๋Š” ๊ณค์ถฉ๋“ค์„ ์ข€ ๋‹ค๋ฅธ ์‹œ๊ฐ์œผ๋กœ ๋ณด์‹œ๊ธฐ๋ฅผ ๋ฐ”๋ž๋‹ˆ๋‹ค.
15:44
and as I say up here, please think before you swat.
324
944207
2935
๊ทธ๋ฆฌ๊ณ  ๋‹น๋ถ€๋“œ๋ฆฌ๊ณ  ์‹ถ์€ ๊ฒƒ์€, (ํŒŒ๋ฆฌ๋ฅผ) ๋‚ด๋ ค์น˜๊ธฐ ์ „์— ํ•œ ๋ฒˆ ์ƒ๊ฐํ•ด์ฃผ์„ธ์š”.
15:47
(Applause)
325
947142
2953
(๋ฐ•์ˆ˜)
์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.

https://forms.gle/WvT1wiN1qDtmnspy7