TEDGlobal 2009
Henry Markram: A brain in a supercomputer
Henry Markram gradi mozak u superračunalu
Filmed:
Readability: 3.8
1,469,354 views
Henry Markram kaže kako se tajne uma mogu razotkriti - uskoro. Mentalna oboljenja, pamćenje, percepcija: tvore ih neuroni i električni signali te ih on planira otkriti pomoću superračunala koje modelira svih 100.000.000.000.000 sinapsi u mozgu.
Henry Markram - Neuroscientist
Henry Markram is director of Blue Brain, a supercomputing project that can model components of the mammalian brain to precise cellular detail -- and simulate their activity in 3D. Soon he'll simulate a whole rat brain in real time. Full bio
Henry Markram is director of Blue Brain, a supercomputing project that can model components of the mammalian brain to precise cellular detail -- and simulate their activity in 3D. Soon he'll simulate a whole rat brain in real time. Full bio
Double-click the English transcript below to play the video.
00:18
Our mission is to build
0
0
3000
Naša zadaća je izraditi
00:21
a detailed, realistic
1
3000
2000
detaljan, realističan
00:23
computer model of the human brain.
2
5000
2000
računalni model ljudskog mozga.
00:25
And we've done, in the past four years,
3
7000
3000
Postigli smo, u protekle četiri godine,
00:28
a proof of concept
4
10000
2000
dokaz koncepta
00:30
on a small part of the rodent brain,
5
12000
3000
na djeliću mozga glodavca,
00:33
and with this proof of concept we are now scaling the project up
6
15000
3000
i s dokazanim konceptom sada dižemo projekt na višu razinu
00:36
to reach the human brain.
7
18000
3000
kako bismo dosegnuli do ljudskog mozga.
00:39
Why are we doing this?
8
21000
2000
Zašto to činimo?
00:41
There are three important reasons.
9
23000
2000
Tri su važna razloga.
00:43
The first is, it's essential for us to understand the human brain
10
25000
4000
Prvo, ključno je da razumijemo ljudski mozak
00:47
if we do want to get along in society,
11
29000
2000
ako želimo uspjeti u društvu,
00:49
and I think that it is a key step in evolution.
12
31000
4000
i mislim kako je to ključni korak u evoluciji.
00:53
The second reason is,
13
35000
2000
Drugi je razlog taj,
00:55
we cannot keep doing animal experimentation forever,
14
37000
6000
što ne možemo zauvijek eksperimentirati na životinjama,
01:01
and we have to embody all our data and all our knowledge
15
43000
4000
i moramo objediniti sve podatke i sve naše znanje
01:05
into a working model.
16
47000
3000
u djelatni model.
01:08
It's like a Noah's Ark. It's like an archive.
17
50000
4000
To je poput Noine korablje. Poput arhiva.
01:12
And the third reason is that there are two billion people on the planet
18
54000
3000
I treći je razlog što na svijetu ima dvije milijarde ljudi
01:15
that are affected by mental disorder,
19
57000
4000
koji su pogođeni mentalnim bolestima,
01:19
and the drugs that are used today
20
61000
2000
a lijekovi koji se danas koriste
01:21
are largely empirical.
21
63000
2000
su pretežito empirijski.
01:23
I think that we can come up with very concrete solutions on
22
65000
3000
Mislim kako možemo iznaći neka vrlo konkretna rješenja
01:26
how to treat disorders.
23
68000
3000
za tretman tih poremećaja.
01:29
Now, even at this stage,
24
71000
3000
Čak i u ovoj fazi
01:32
we can use the brain model
25
74000
2000
možemo upotrijebiti model mozga
01:34
to explore some fundamental questions
26
76000
3000
istražujući neka fundamentalna pitanja
01:37
about how the brain works.
27
79000
2000
funkcioniranja mozga.
01:39
And here, at TED, for the first time,
28
81000
2000
Ovdje, na TED-u, po prvi puta,
01:41
I'd like to share with you how we're addressing
29
83000
2000
podijelio bih s vama način na koji pristupamo
01:43
one theory -- there are many theories --
30
85000
3000
jednoj teoriji – ima mnogo teorija --
01:46
one theory of how the brain works.
31
88000
4000
jednoj teoriji o funkcioniranju mozga.
01:50
So, this theory is that the brain
32
92000
4000
Ova teorija kaže da mozak
01:54
creates, builds, a version of the universe,
33
96000
6000
stvara, gradi verziju svemira,
02:00
and projects this version of the universe,
34
102000
3000
i projicira tu verziju svemira,
02:03
like a bubble, all around us.
35
105000
4000
poput mjehura, svuda oko nas.
02:07
Now, this is of course a topic of philosophical debate for centuries.
36
109000
4000
Naravno, ovo je tema filozofske debate već stoljećima.
02:11
But, for the first time, we can actually address this,
37
113000
3000
No, po prvi puta možemo tom pitanju pristupiti
02:14
with brain simulation,
38
116000
2000
simulacijom mozga,
02:16
and ask very systematic and rigorous questions,
39
118000
4000
i postaviti sustavska i rigorozna pitanja,
02:20
whether this theory could possibly be true.
40
122000
4000
kako bismo utvrdili može li ta teorija biti točna.
02:24
The reason why the moon is huge on the horizon
41
126000
3000
Mjesec je velik na obzoru iz razloga
02:27
is simply because our perceptual bubble
42
129000
3000
što se naš perceptivni mjehur
02:30
does not stretch out 380,000 kilometers.
43
132000
4000
ne proteže 380.000 kilometara.
02:34
It runs out of space.
44
136000
2000
Nedostaje mu prostora.
02:36
And so what we do is we compare the buildings
45
138000
4000
I zato mi uspoređujemo zgrade
02:40
within our perceptual bubble,
46
142000
2000
u okviru našeg perceptivnog mjehura,
02:42
and we make a decision.
47
144000
2000
i donosimo odluku.
02:44
We make a decision it's that big,
48
146000
2000
Donosimo odluku da je on toliko velik,
02:46
even though it's not that big.
49
148000
2000
premda nije toliko velik.
02:48
And what that illustrates
50
150000
2000
Ovo pokazuje
02:50
is that decisions are the key things
51
152000
2000
kako su odluke ključne stvari
02:52
that support our perceptual bubble. It keeps it alive.
52
154000
5000
koje podržavaju naš perceptivni mjehur. One ga održavaju na životu.
02:57
Without decisions you cannot see, you cannot think,
53
159000
2000
Bez odluka ne možete vidjeti, ne možete razmišljati,
02:59
you cannot feel.
54
161000
2000
ne možete osjećati.
03:01
And you may think that anesthetics work
55
163000
2000
Mogli biste pomisliti da anestetici djeluju
03:03
by sending you into some deep sleep,
56
165000
3000
tako da vas pošalju u duboki san,
03:06
or by blocking your receptors so that you don't feel pain,
57
168000
3000
ili da blokiraju receptore kako ne biste osjetili bol,
03:09
but in fact most anesthetics don't work that way.
58
171000
3000
no, zapravo, većina anestetika ne djeluje tako.
03:12
What they do is they introduce a noise
59
174000
3000
Oni uvode šum u mozak
03:15
into the brain so that the neurons cannot understand each other.
60
177000
3000
tako da neuroni ne razumiju jedan drugoga.
03:18
They are confused,
61
180000
2000
Zbunjeni su,
03:20
and you cannot make a decision.
62
182000
3000
i ne možete donijeti odluku.
03:23
So, while you're trying to make up your mind
63
185000
3000
Pa, dok vi pokušavate odlučiti
03:26
what the doctor, the surgeon, is doing
64
188000
2000
što liječnik, kirurg čini
03:28
while he's hacking away at your body, he's long gone.
65
190000
2000
dok vas reže, on je odavno završio.
03:30
He's at home having tea.
66
192000
2000
Kod kuće je i pije čaj.
03:32
(Laughter)
67
194000
2000
(Smijeh)
03:34
So, when you walk up to a door and you open it,
68
196000
3000
Kad priđete vratima i otvorite ih,
03:37
what you compulsively have to do to perceive
69
199000
3000
ono što obavezno morate učiniti da biste opažali
03:40
is to make decisions,
70
202000
2000
je donošenje odluka,
03:42
thousands of decisions about the size of the room,
71
204000
3000
na tisuće odluka o veličini prostorije,
03:45
the walls, the height, the objects in this room.
72
207000
3000
zidovima, visini, predmetima u sobi.
03:48
99 percent of what you see
73
210000
3000
99 posto onoga što vidite
03:51
is not what comes in through the eyes.
74
213000
4000
nije ono što primite očima.
03:55
It is what you infer about that room.
75
217000
4000
Već ono što zaključite o toj sobi.
03:59
So I can say, with some certainty,
76
221000
4000
Zato mogu reći, s određenom sigurnošću,
04:03
"I think, therefore I am."
77
225000
3000
"Mislim, dakle jesam."
04:06
But I cannot say, "You think, therefore you are,"
78
228000
4000
Ali ne mogu reći, "Ti misliš, dakle ti jesi,"
04:10
because "you" are within my perceptual bubble.
79
232000
5000
jer si "ti" dio mog perceptivnog mjehura.
04:15
Now, we can speculate and philosophize this,
80
237000
3000
Možemo špekulirati i filozofirati o tome,
04:18
but we don't actually have to for the next hundred years.
81
240000
3000
ali zapravo i ne moramo, u sljedećih stotinu godina.
04:21
We can ask a very concrete question.
82
243000
2000
Možemo postaviti vrlo konkretno pitanje.
04:23
"Can the brain build such a perception?"
83
245000
4000
"Može li mozak izgraditi takvu percepciju?"
04:27
Is it capable of doing it?
84
249000
2000
Je li on to u stanju učiniti?
04:29
Does it have the substance to do it?
85
251000
2000
Ima li osnovu da to učini?
04:31
And that's what I'm going to describe to you today.
86
253000
3000
I to je ono što ću vam danas opisati.
04:34
So, it took the universe 11 billion years to build the brain.
87
256000
4000
Svemiru je trebalo 11 milijardi godina da izgradi mozak.
04:38
It had to improve it a little bit.
88
260000
2000
Morao ga je malo poboljšati.
04:40
It had to add to the frontal part, so that you would have instincts,
89
262000
3000
Morao je dodati frontalni režanj kako biste imali nagone,
04:43
because they had to cope on land.
90
265000
3000
jer su potrebni na kopnu.
04:46
But the real big step was the neocortex.
91
268000
4000
Ali stvarno veliki korak je bio neokorteks.
04:50
It's a new brain. You needed it.
92
272000
2000
To je novi mozak. Trebao vam je.
04:52
The mammals needed it
93
274000
2000
Sisavci su ga trebali
04:54
because they had to cope with parenthood,
94
276000
4000
jer su se morali nositi s roditeljstvom,
04:58
social interactions,
95
280000
2000
društvenim interakcijama,
05:00
complex cognitive functions.
96
282000
3000
složenim kognitivnim funkcijama.
05:03
So, you can think of the neocortex
97
285000
2000
Na neokorteks možete gledati
05:05
actually as the ultimate solution today,
98
287000
5000
kao na današnje definitivno rješenje
05:10
of the universe as we know it.
99
292000
3000
svemira kakav nam je poznat.
05:13
It's the pinnacle, it's the final product
100
295000
2000
On je vrhunac, konačni proizvod
05:15
that the universe has produced.
101
297000
4000
kojega je svemir stvorio.
05:19
It was so successful in evolution
102
301000
2000
Evolucijski je bio toliko uspješan
05:21
that from mouse to man it expanded
103
303000
2000
da je od miša do čovjeka narastao
05:23
about a thousandfold in terms of the numbers of neurons,
104
305000
3000
tisuću puta, u smislu broja neurona,
05:26
to produce this almost frightening
105
308000
3000
kako bi stvorio taj gotovo zastrašujući
05:29
organ, structure.
106
311000
3000
organ, strukturu.
05:32
And it has not stopped its evolutionary path.
107
314000
3000
I nije završio svoj evolucijski put.
05:35
In fact, the neocortex in the human brain
108
317000
2000
Zapravo, neokorteks ljudskog mozga
05:37
is evolving at an enormous speed.
109
319000
3000
evolvira ogromnom brzinom.
05:40
If you zoom into the surface of the neocortex,
110
322000
2000
Ako uvećate površinu neokorteksa,
05:42
you discover that it's made up of little modules,
111
324000
3000
otkrit ćete kako se sastoji od malenih modula,
05:45
G5 processors, like in a computer.
112
327000
2000
G5 procesora, kao u računalu.
05:47
But there are about a million of them.
113
329000
3000
Ali ima ih oko milijun.
05:50
They were so successful in evolution
114
332000
2000
Toliko su evolucijski uspješni
05:52
that what we did was to duplicate them
115
334000
2000
da smo ih duplicirali
05:54
over and over and add more and more of them to the brain
116
336000
2000
još i još i dodavali sve više mozgu
05:56
until we ran out of space in the skull.
117
338000
3000
dok nam nije ponestalo mjesta u lubanji.
05:59
And the brain started to fold in on itself,
118
341000
2000
I mozak se počeo preklapati na sebe,
06:01
and that's why the neocortex is so highly convoluted.
119
343000
3000
i zato je neokorteks toliko naboran.
06:04
We're just packing in columns,
120
346000
2000
Mi gomilamo stupce,
06:06
so that we'd have more neocortical columns
121
348000
3000
kako bismo imali više stupaca neokorteksa
06:09
to perform more complex functions.
122
351000
3000
za izvođenje složenih funkcija.
06:12
So you can think of the neocortex actually as
123
354000
2000
Možete na neokorteks gledati i kao na
06:14
a massive grand piano,
124
356000
2000
ogromni veliki glasovir,
06:16
a million-key grand piano.
125
358000
3000
glasovir s milijun dirki.
06:19
Each of these neocortical columns
126
361000
2000
Svaki od tih stupaca neokorteksa
06:21
would produce a note.
127
363000
2000
proizvodi jedan ton.
06:23
You stimulate it; it produces a symphony.
128
365000
3000
Vi ga stimulirate; on stvara simfoniju.
06:26
But it's not just a symphony of perception.
129
368000
3000
Ali nije to samo simfonija opažanja.
06:29
It's a symphony of your universe, your reality.
130
371000
3000
To je simfonija vašeg svemira, vaše stvarnosti.
06:32
Now, of course it takes years to learn how
131
374000
3000
Naravno, trebaju godine da biste naučili
06:35
to master a grand piano with a million keys.
132
377000
3000
upravljati glasovirom s milijun dirki.
06:38
That's why you have to send your kids to good schools,
133
380000
2000
Zato morate slati djecu u dobre škole,
06:40
hopefully eventually to Oxford.
134
382000
2000
na kraju, nadajmo se i u Oxford.
06:42
But it's not only education.
135
384000
3000
Ali nije riječ samo o obrazovanju.
06:45
It's also genetics.
136
387000
2000
Tu je i genetika.
06:47
You may be born lucky,
137
389000
2000
Možete imati sreće pri rođenju,
06:49
where you know how to master your neocortical column,
138
391000
4000
pa znate kako upravljati vašim neokorteksom,
06:53
and you can play a fantastic symphony.
139
395000
2000
i znate svirati fantastičnu simfoniju.
06:55
In fact, there is a new theory of autism
140
397000
3000
U stvari, postoji nova teorija autizma
06:58
called the "intense world" theory,
141
400000
2000
zvana teorija intenzivnog svijeta,
07:00
which suggests that the neocortical columns are super-columns.
142
402000
4000
koja predlaže da su stupci neokorteksta super-stupci.
07:04
They are highly reactive, and they are super-plastic,
143
406000
4000
Oni su visoko reaktivni, super-plastični,
07:08
and so the autists are probably capable of
144
410000
3000
i autisti su vjerojatno u stanju
07:11
building and learning a symphony
145
413000
2000
stvarati i učiti simfoniju
07:13
which is unthinkable for us.
146
415000
2000
koja je nama nezamisliva.
07:15
But you can also understand
147
417000
2000
Ali također možete shvatiti
07:17
that if you have a disease
148
419000
2000
da ako imate poremećaj
07:19
within one of these columns,
149
421000
2000
u jednom od tih stupaca,
07:21
the note is going to be off.
150
423000
2000
ton će biti pogrešan.
07:23
The perception, the symphony that you create
151
425000
2000
Opažanje, simfonija koju stvarate
07:25
is going to be corrupted,
152
427000
2000
će biti oštećena,
07:27
and you will have symptoms of disease.
153
429000
3000
i imat ćete simptome bolesti.
07:30
So, the Holy Grail for neuroscience
154
432000
4000
Dakle, sveti Gral za neuroznanost
07:34
is really to understand the design of the neocoritical column --
155
436000
4000
je razumijevanje dizajna stupca neokorteksa --
07:38
and it's not just for neuroscience;
156
440000
2000
i ne samo za neuroznanost;
07:40
it's perhaps to understand perception, to understand reality,
157
442000
3000
bitno je za razumijevanje percepcije, razumijevanje stvarnosti,
07:43
and perhaps to even also understand physical reality.
158
445000
4000
i možda čak i za razumijevanje fizičke stvarnosti.
07:47
So, what we did was, for the past 15 years,
159
449000
3000
U proteklih 15 godina mi smo
07:50
was to dissect out the neocortex, systematically.
160
452000
4000
sustavno secirali neokortekst.
07:54
It's a bit like going and cataloging a piece of the rainforest.
161
456000
4000
To vam je kao izrada kataloga dijela tropske prašume.
07:58
How many trees does it have?
162
460000
2000
Koliko stabala ima?
08:00
What shapes are the trees?
163
462000
2000
Kojeg oblika su stabla?
08:02
How many of each type of tree do you have? Where are they positioned?
164
464000
3000
Koliko broj stabala svake vrste ima? Gdje se nalaze?
08:05
But it's a bit more than cataloging because you actually have to
165
467000
2000
No, i više je od kataloga jer morate
08:07
describe and discover all the rules of communication,
166
469000
4000
opisati i otkriti pravila komunikacije,
08:11
the rules of connectivity,
167
473000
2000
pravila povezivanja,
08:13
because the neurons don't just like to connect with any neuron.
168
475000
3000
jer se neuroni ne vole naprosto povezati s bilo kojim neuronima.
08:16
They choose very carefully who they connect with.
169
478000
3000
Vrlo pažljivo biraju s kim se povezuju.
08:19
It's also more than cataloging
170
481000
3000
Više je to od izrade kataloga i zato
08:22
because you actually have to build three-dimensional
171
484000
2000
što morate izraditi trodimenzionalne
08:24
digital models of them.
172
486000
2000
digitalne modele.
08:26
And we did that for tens of thousands of neurons,
173
488000
2000
Mi smo to učinili za desetke tisuća neurona,
08:28
built digital models of all the different types
174
490000
3000
izradili smo digitalne modele za sve vrste
08:31
of neurons we came across.
175
493000
2000
neurona s kojima smo se susreli.
08:33
And once you have that, you can actually
176
495000
2000
A kad jednom to imate,
08:35
begin to build the neocortical column.
177
497000
4000
onda možete početi graditi stupac neokorteksa.
08:39
And here we're coiling them up.
178
501000
3000
Ovdje ih namatamo.
08:42
But as you do this, what you see
179
504000
3000
Ali možete vidjeti
08:45
is that the branches intersect
180
507000
2000
da se grane presijecaju
08:47
actually in millions of locations,
181
509000
3000
na milijun mjesta,
08:50
and at each of these intersections
182
512000
3000
i na svakom od tih spojeva
08:53
they can form a synapse.
183
515000
2000
mogu stvoriti sinapsu.
08:55
And a synapse is a chemical location
184
517000
2000
Sinapsa je kemijska lokacija
08:57
where they communicate with each other.
185
519000
3000
na kojoj komuniciraju jedan s drugim.
09:00
And these synapses together
186
522000
2000
Te sinapse zajedno
09:02
form the network
187
524000
2000
čine mrežu
09:04
or the circuit of the brain.
188
526000
3000
ili mozgovni sklop.
09:07
Now, the circuit, you could also think of as
189
529000
4000
Taj sklop možete promatrati i kao
09:11
the fabric of the brain.
190
533000
2000
građu mozga.
09:13
And when you think of the fabric of the brain,
191
535000
3000
A što se tiče građe mozga,
09:16
the structure, how is it built? What is the pattern of the carpet?
192
538000
4000
strukture, kako je izgrađena? Koji je uzorak na tepihu?
09:20
You realize that this poses
193
542000
2000
Shvatite da to upućuje
09:22
a fundamental challenge to any theory of the brain,
194
544000
4000
fundamentalni izazov za svaku teoriju mozga,
09:26
and especially to a theory that says
195
548000
2000
a posebno za teoriju koja tvrdi
09:28
that there is some reality that emerges
196
550000
2000
kako postoji neka realnost koja nastaje
09:30
out of this carpet, out of this particular carpet
197
552000
3000
iz tog tepiha, iz tog konkretnog tepiha
09:33
with a particular pattern.
198
555000
2000
s tim konkretnim uzorkom.
09:35
The reason is because the most important design secret of the brain
199
557000
3000
To je tako zato što je najvažnija tajna dizajna mozga
09:38
is diversity.
200
560000
2000
njegova raznolikost.
09:40
Every neuron is different.
201
562000
2000
Svaki neuron je različit.
09:42
It's the same in the forest. Every pine tree is different.
202
564000
2000
Isto je u šumi. Svaki bor je različit.
09:44
You may have many different types of trees,
203
566000
2000
Imate mnogo različitih vrsta drveća,
09:46
but every pine tree is different. And in the brain it's the same.
204
568000
3000
ali svako stablo bora je različito. Isto je u mozgu.
09:49
So there is no neuron in my brain that is the same as another,
205
571000
3000
Tako da nema neurona u mom mozgu koji je isti kao neki drugi,
09:52
and there is no neuron in my brain that is the same as in yours.
206
574000
3000
i nema neurona u mom mozgu koji je isti kao neki u vašem mozgu.
09:55
And your neurons are not going to be oriented and positioned
207
577000
3000
I vaši neuroni neće biti okrenuti i smješteni
09:58
in exactly the same way.
208
580000
2000
na potpuno jednak način.
10:00
And you may have more or less neurons.
209
582000
2000
A vi možda imate više ili manje neurona.
10:02
So it's very unlikely
210
584000
2000
Zato je mala vjerojatnost
10:04
that you got the same fabric, the same circuitry.
211
586000
4000
da imate istu građu, isti sklop.
10:08
So, how could we possibly create a reality
212
590000
2000
Pa kako onda uopće možemo stvoriti realnost
10:10
that we can even understand each other?
213
592000
3000
u kojoj uopće razumijemo jedni druge?
10:13
Well, we don't have to speculate.
214
595000
2000
No, ne moramo špekulirati.
10:15
We can look at all 10 million synapses now.
215
597000
3000
Sada možemo pogledati svih 10 milijuna sinapsi.
10:18
We can look at the fabric. And we can change neurons.
216
600000
3000
Možemo zaviriti u građu. I možemo promijeniti neurone.
10:21
We can use different neurons with different variations.
217
603000
2000
Možemo koristiti različite neurone u različitim varijacijama.
10:23
We can position them in different places,
218
605000
2000
Možemo ih postaviti na različita mjesta,
10:25
orient them in different places.
219
607000
2000
različito ih okrenuti.
10:27
We can use less or more of them.
220
609000
2000
Možemo ih koristiti više ili manje.
10:29
And when we do that
221
611000
2000
I kad smo to učinili,
10:31
what we discovered is that the circuitry does change.
222
613000
3000
otkrili smo kako se sklop mijenja.
10:34
But the pattern of how the circuitry is designed does not.
223
616000
7000
Ali uzorak prema kojem je sklop oblikovan se ne mijenja.
10:41
So, the fabric of the brain,
224
623000
2000
Znači, građa mozga,
10:43
even though your brain may be smaller, bigger,
225
625000
2000
premda vaš mozak može biti manji, veći,
10:45
it may have different types of neurons,
226
627000
3000
imati različite vrste neurona,
10:48
different morphologies of neurons,
227
630000
2000
različite morfologije neurona,
10:50
we actually do share
228
632000
3000
zapravo nam je zajednička
10:53
the same fabric.
229
635000
2000
ista građa.
10:55
And we think this is species-specific,
230
637000
2000
Mislimo da je to određeno vrstom,
10:57
which means that that could explain
231
639000
2000
što znači da bi to objasnilo
10:59
why we can't communicate across species.
232
641000
2000
zašto ne možemo komunicirati s drugim vrstama.
11:01
So, let's switch it on. But to do it, what you have to do
233
643000
3000
Uključimo ga. Ali da biste to postigli
11:04
is you have to make this come alive.
234
646000
2000
morate ga oživjeti.
11:06
We make it come alive
235
648000
2000
Oživjet ćemo ga
11:08
with equations, a lot of mathematics.
236
650000
2000
s jednadžbama, s puno matematike.
11:10
And, in fact, the equations that make neurons into electrical generators
237
652000
4000
Jednadžbe koje pretvaraju neurone u elektrogeneratore
11:14
were discovered by two Cambridge Nobel Laureates.
238
656000
3000
otkrila su dva dobitnika Nobelove nagrade iz Cambridgea.
11:17
So, we have the mathematics to make neurons come alive.
239
659000
3000
Znači, imamo matematiku koja može oživjeti neurone.
11:20
We also have the mathematics to describe
240
662000
2000
Imamo i matematiku koja može opisati
11:22
how neurons collect information,
241
664000
3000
kako neuroni prikupljaju informacije
11:25
and how they create a little lightning bolt
242
667000
3000
i kako stvaraju malu munju
11:28
to communicate with each other.
243
670000
2000
da bi komunicirali jedan s drugim.
11:30
And when they get to the synapse,
244
672000
2000
A kad dođu u sinapsu
11:32
what they do is they effectively,
245
674000
2000
oni učinkovito,
11:34
literally, shock the synapse.
246
676000
3000
doslovno, stvore šok u sinapsi.
11:37
It's like electrical shock
247
679000
2000
To je kao električni šok
11:39
that releases the chemicals from these synapses.
248
681000
3000
koji dovodi do otpuštanja kemikalija u sinapsi.
11:42
And we've got the mathematics to describe this process.
249
684000
3000
Poznata nam je matematika koja opisuje taj proces.
11:45
So we can describe the communication between the neurons.
250
687000
4000
Pa možemo opisati komunikaciju između neurona.
11:49
There literally are only a handful
251
691000
3000
Doslovno postoji samo pregršt
11:52
of equations that you need to simulate
252
694000
2000
jednadžbi potrebnih za simuliranje
11:54
the activity of the neocortex.
253
696000
2000
aktivnosti neokorteksa.
11:56
But what you do need is a very big computer.
254
698000
3000
Ali treba vam vrlo veliko računalo.
11:59
And in fact you need one laptop
255
701000
2000
Zapravo, treba vam jedan laptop
12:01
to do all the calculations just for one neuron.
256
703000
3000
za sve izračune samo za jedan neuron.
12:04
So you need 10,000 laptops.
257
706000
2000
Znači, trebate 10.000 prijenosnih računala.
12:06
So where do you go? You go to IBM,
258
708000
2000
Pa gdje se obratiti? Odete u IBM,
12:08
and you get a supercomputer, because they know how to take
259
710000
2000
i dobijete superračunalo, jer oni znaju kako spojiti
12:10
10,000 laptops and put it into the size of a refrigerator.
260
712000
4000
10.000 laptopa na veličinu jednog hladnjaka.
12:14
So now we have this Blue Gene supercomputer.
261
716000
3000
Pa imamo ovo superračunalo Blue Gene.
12:17
We can load up all the neurons,
262
719000
2000
Možemo učitati sve neurone,
12:19
each one on to its processor,
263
721000
2000
svaki na vlastiti procesor,
12:21
and fire it up, and see what happens.
264
723000
4000
pokrenuti računalo, i vidjeti što se zbiva.
12:25
Take the magic carpet for a ride.
265
727000
3000
Povest ćemo se letećim tepihom.
12:28
Here we activate it. And this gives the first glimpse
266
730000
3000
Ovdje ga aktiviramo. Ovo nam daje prvi uvid
12:31
of what is happening in your brain
267
733000
2000
u ono što se događa u mozgu
12:33
when there is a stimulation.
268
735000
2000
kad dođe do stimulacije.
12:35
It's the first view.
269
737000
2000
Ovo je prvi pogled.
12:37
Now, when you look at that the first time, you think,
270
739000
2000
Kad to gledate prvi puta, mislite,
12:39
"My god. How is reality coming out of that?"
271
741000
5000
"Zaboga. Kako stvarnost nastaje iz toga?"
12:44
But, in fact, you can start,
272
746000
3000
No, možete početi,
12:47
even though we haven't trained this neocortical column
273
749000
4000
premda nismo istrenirali ovaj stupac neokorteksa
12:51
to create a specific reality.
274
753000
2000
da stvara neku određenu realnost.
12:53
But we can ask, "Where is the rose?"
275
755000
4000
Ali možemo se upitati, "Gdje je ruža?"
12:57
We can ask, "Where is it inside,
276
759000
2000
Možemo pitati, "Gdje je u ovome,
12:59
if we stimulate it with a picture?"
277
761000
3000
ako ga stimuliramo sa slikom?"
13:02
Where is it inside the neocortex?
278
764000
2000
Gdje je unutar neokorteksa?
13:04
Ultimately it's got to be there if we stimulated it with it.
279
766000
4000
Mora biti ondje ako smo ga stimulirali time.
13:08
So, the way that we can look at that
280
770000
2000
Tome možemo pristupiti tako da
13:10
is to ignore the neurons, ignore the synapses,
281
772000
3000
ignoriramo neurone, ignoriramo sinapse,
13:13
and look just at the raw electrical activity.
282
775000
2000
i gledamo samo osnovnu električnu aktivnost.
13:15
Because that is what it's creating.
283
777000
2000
Jer je to ono što nastaje.
13:17
It's creating electrical patterns.
284
779000
2000
Nastaju električni uzorci.
13:19
So when we did this,
285
781000
2000
Kad smo to učinili,
13:21
we indeed, for the first time,
286
783000
2000
doista smo, po prvi puta,
13:23
saw these ghost-like structures:
287
785000
3000
ugledali ove sablasne strukture:
13:26
electrical objects appearing
288
788000
3000
električni objekti se pojavljuju
13:29
within the neocortical column.
289
791000
3000
u stupcu neokorteksa.
13:32
And it's these electrical objects
290
794000
3000
I ti električni objekti
13:35
that are holding all the information about
291
797000
3000
sadržavaju sve informacije
13:38
whatever stimulated it.
292
800000
3000
o onome što ih je stimuliralo.
13:41
And then when we zoomed into this,
293
803000
2000
A kad ovo uvećamo,
13:43
it's like a veritable universe.
294
805000
4000
to je kao pravi svemir.
13:47
So the next step
295
809000
2000
Sljedeći korak je
13:49
is just to take these brain coordinates
296
811000
4000
uzeti te mozgovne koordinate
13:53
and to project them into perceptual space.
297
815000
4000
i projicirati ih u prostor percepcije.
13:57
And if you do that,
298
819000
2000
A ako to učinite,
13:59
you will be able to step inside
299
821000
2000
moći ćete stupiti u unutrašnjost
14:01
the reality that is created
300
823000
2000
stvarnosti koja je stvorena
14:03
by this machine,
301
825000
2000
u ovom uređaju,
14:05
by this piece of the brain.
302
827000
3000
u ovom dijelu mozga.
14:08
So, in summary,
303
830000
2000
Ukratko,
14:10
I think that the universe may have --
304
832000
2000
mislim kako je svemir --
14:12
it's possible --
305
834000
2000
moguće je --
14:14
evolved a brain to see itself,
306
836000
3000
razvio mozak da bi sebe vidio,
14:17
which may be a first step in becoming aware of itself.
307
839000
5000
što bi mogao biti prvi korak u stjecanju svijesti o sebi.
14:22
There is a lot more to do to test these theories,
308
844000
2000
Još ima puno posla na testiranju ovih teorija,
14:24
and to test any other theories.
309
846000
3000
i na testiranju svih drugih teorija.
14:27
But I hope that you are at least partly convinced
310
849000
3000
Ali nadam se da ste barem djelomice uvjereni
14:30
that it is not impossible to build a brain.
311
852000
3000
da nije nemoguće izgraditi mozak.
14:33
We can do it within 10 years,
312
855000
2000
Možemo to postići u narednih 10 godina,
14:35
and if we do succeed,
313
857000
2000
i ako uspijemo,
14:37
we will send to TED, in 10 years,
314
859000
2000
poslat ćemo TED-u, za 10 godina,
14:39
a hologram to talk to you. Thank you.
315
861000
3000
hologram da vam održi govor. Hvala vam.
14:42
(Applause)
316
864000
6000
(Pljesak)
ABOUT THE SPEAKER
Henry Markram - NeuroscientistHenry Markram is director of Blue Brain, a supercomputing project that can model components of the mammalian brain to precise cellular detail -- and simulate their activity in 3D. Soon he'll simulate a whole rat brain in real time.
Why you should listen
In the microscopic, yet-uncharted circuitry of the cortex, Henry Markram is perhaps the most ambitious -- and our most promising -- frontiersman. Backed by the extraordinary power of the IBM Blue Gene supercomputing architecture, which can perform hundreds of trillions of calculations per second, he's using complex models to precisely simulate the neocortical column (and its tens of millions of neural connections) in 3D.
Though the aim of Blue Brain research is mainly biomedical, it has been edging up on some deep, contentious philosophical questions about the mind -- "Can a robot think?" and "Can consciousness be reduced to mechanical components?" -- the consequence of which Markram is well aware: Asked by Seed Magazine what a simulation of a full brain might do, he answered, "Everything. I mean everything" -- with a grin.
Now, with a successful proof-of-concept for simulation in hand (the project's first phase was completed in 2007), Markram is looking toward a future where brains might be modeled even down to the molecular and genetic level. Computing power marching rightward and up along the graph of Moore's Law, Markram is sure to be at the forefront as answers to the mysteries of cognition emerge.
Henry Markram | Speaker | TED.com