ABOUT THE SPEAKER
Ed Boyden - Neuroengineer
Ed Boyden is a professor of biological engineering and brain and cognitive sciences at the MIT Media Lab and the MIT McGovern Institute.

Why you should listen

Ed Boyden leads the Synthetic Neurobiology Group, which develops tools for analyzing and repairing complex biological systems such as the brain. His group applies these tools in a systematic way in order to reveal ground truth scientific understandings of biological systems, which in turn reveal radical new approaches for curing diseases and repairing disabilities. These technologies include expansion microscopy, which enables complex biological systems to be imaged with nanoscale precision, and optogenetic tools, which enable the activation and silencing of neural activity with light (TED Talk: A light switch for neurons). Boyden also co-directs the MIT Center for Neurobiological Engineering, which aims to develop new tools to accelerate neuroscience progress.

Amongst other recognitions, Boyden has received the Breakthrough Prize in Life Sciences (2016), the BBVA Foundation Frontiers of Knowledge Award (2015), the Carnegie Prize in Mind and Brain Sciences (2015), the Jacob Heskel Gabbay Award (2013), the Grete Lundbeck Brain Prize (2013) and the NIH Director's Pioneer Award (2013). He was also named to the World Economic Forum Young Scientist list (2013) and the Technology Review World's "Top 35 Innovators under Age 35" list (2006). His group has hosted hundreds of visitors to learn how to use new biotechnologies and spun out several companies to bring inventions out of his lab and into the world. Boyden received his Ph.D. in neurosciences from Stanford University as a Hertz Fellow, where he discovered that the molecular mechanisms used to store a memory are determined by the content to be learned. Before that, he received three degrees in electrical engineering, computer science and physics from MIT. He has contributed to over 300 peer-reviewed papers, current or pending patents and articles, and he has given over 300 invited talks on his group's work.

More profile about the speaker
Ed Boyden | Speaker | TED.com
TED2011

Ed Boyden: A light switch for neurons

Ed Bojden: Svetlosni okidač neurona

Filmed:
1,005,031 views

Ed Bojden pokazuje kako, umečući gene za svetlosno osetljive proteine u moždane ćelije, može selektivno aktivisati ili deaktivisati specifične neurone s implantima od optičkih vlakana. S tom neprikosnovenom razinom kontrole, on je uspeo izlečiti miša od PTSP-a i određenih formi slepoće. Na horizontu: neuralna prostetika. Voditelj seanse Huan Enrikez vodi kratak Q&A nakon govora.
- Neuroengineer
Ed Boyden is a professor of biological engineering and brain and cognitive sciences at the MIT Media Lab and the MIT McGovern Institute. Full bio

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

00:15
Think about your day for a second.
0
0
2000
Razislite o svom danu jedan trenutak.
00:17
You woke up, felt fresh air on your face as you walked out the door,
1
2000
3000
Probudili ste se. Osetili ste svež vazduh na licu izlazeći iz kuće,
00:20
encountered new colleagues and had great discussions,
2
5000
2000
sreli ste nove kolege i imali sjajne razgovore,
00:22
and felt in awe when you found something new.
3
7000
2000
i osetili strahopoštovanje kada ste otkrili nešto novo.
00:24
But I bet there's something you didn't think about today --
4
9000
2000
Ali kladim se da postoji stvar na koju danas niste pomislili --
00:26
something so close to home
5
11000
2000
nešto svima tako blisko
00:28
that you probably don't think about it very often at all.
6
13000
2000
da verovatno o tome ne mislite uopšte.
00:30
And that's that all the sensations, feelings,
7
15000
2000
A mislim na to da u svemu što zapazite, osetite,
00:32
decisions and actions
8
17000
2000
odlučite i uradite
00:34
are mediated by the computer in your head
9
19000
2000
posreduje kompjuter u vašoj glavi
00:36
called the brain.
10
21000
2000
koji zovemo mozak.
00:38
Now the brain may not look like much from the outside --
11
23000
2000
Znam da mozak ne izgleda bog zna kako spolja --
00:40
a couple pounds of pinkish-gray flesh,
12
25000
2000
par kilograma ružičasto-sive mase,
00:42
amorphous --
13
27000
2000
amorfne --
00:44
but the last hundred years of neuroscience
14
29000
2000
ali poslednjih stotinjak godina neuronauke
00:46
have allowed us to zoom in on the brain,
15
31000
2000
su nam omogućile da "zumiramo" mozak
00:48
and to see the intricacy of what lies within.
16
33000
2000
i vidimo komplikovanost onoga što se nalazi unutra.
00:50
And they've told us that this brain
17
35000
2000
Oni nam govore da je mozak
00:52
is an incredibly complicated circuit
18
37000
2000
neverovatno komplikovano ispovezivan
00:54
made out of hundreds of billions of cells called neurons.
19
39000
4000
sačinjen od stotina milijardi ćelija zvanih neuroni.
00:58
Now unlike a human-designed computer,
20
43000
3000
Nasuprot kompjuteru koji su napravili ljudi,
01:01
where there's a fairly small number of different parts --
21
46000
2000
koji čini relativno mali broj različitih delova --
01:03
we know how they work, because we humans designed them --
22
48000
3000
za njih znamo kako rade jer smo ih mi, ljudi, dizajnirali --
01:06
the brain is made out of thousands of different kinds of cells,
23
51000
3000
mozak se sastoji od hiljada različitih vrsta ćelija,
01:09
maybe tens of thousands.
24
54000
2000
možda desetina hiljada.
01:11
They come in different shapes; they're made out of different molecules.
25
56000
2000
Te ćelije su različitih oblika; čine ih različiti molekuli;
01:13
And they project and connect to different brain regions,
26
58000
3000
i one projektuju i povezuju se sa različitim regijama mozga.
01:16
and they also change different ways in different disease states.
27
61000
3000
One se i menjaju na različite načine u različitim stadijumima bolesti.
01:19
Let's make it concrete.
28
64000
2000
Da konkretizujem.
01:21
There's a class of cells,
29
66000
2000
Postoji klasa ćelija,
01:23
a fairly small cell, an inhibitory cell, that quiets its neighbors.
30
68000
3000
prilično mala ćelija, inhibitorna ćelija, koja umiruje susedne.
01:26
It's one of the cells that seems to be atrophied in disorders like schizophrenia.
31
71000
4000
Čini se da te ćelije atrofiraju u stanjima kao što je šizofrenija.
01:30
It's called the basket cell.
32
75000
2000
Zovu je korpasta ćelija.
01:32
And this cell is one of the thousands of kinds of cell
33
77000
2000
Ta ćelija je jedna od hiljada vrsta ćelija
01:34
that we are learning about.
34
79000
2000
o kojima učimo.
01:36
New ones are being discovered everyday.
35
81000
2000
Nove otkrivaju svakoga dana.
01:38
As just a second example:
36
83000
2000
Evo drugog primera:
01:40
these pyramidal cells, large cells,
37
85000
2000
ove piramidalne ćelije, velike ćelije,
01:42
they can span a significant fraction of the brain.
38
87000
2000
one se mogu prostirati značajnim delom mozga.
01:44
They're excitatory.
39
89000
2000
One su pobuđujuće.
01:46
And these are some of the cells
40
91000
2000
I to su samo neke od ćelija
01:48
that might be overactive in disorders such as epilepsy.
41
93000
3000
koje bi mogle biti previše aktivne u poremećajima kao što je epilepsija.
01:51
Every one of these cells
42
96000
2000
Svaka od ovih ćelija
01:53
is an incredible electrical device.
43
98000
3000
je neverovatna električna naprava.
01:56
They receive input from thousands of upstream partners
44
101000
2000
One primaju podatke od hiljada prethodećih partnera
01:58
and compute their own electrical outputs,
45
103000
3000
i proračunavaju njihov sopstveni električni izlaz,
02:01
which then, if they pass a certain threshold,
46
106000
2000
koji onda, ako pređu određeni prag,
02:03
will go to thousands of downstream partners.
47
108000
2000
nastavlja ka hiljadama narednih partnera.
02:05
And this process, which takes just a millisecond or so,
48
110000
3000
Taj proces, koji traje praktično samo milisekundu,
02:08
happens thousands of times a minute
49
113000
2000
odvija se hiljadama puta u minuti
02:10
in every one of your 100 billion cells,
50
115000
2000
u svakoj od vaših 100 milijardi ćelija,
02:12
as long as you live
51
117000
2000
dok ste živi
02:14
and think and feel.
52
119000
3000
i mislite i osećate.
02:17
So how are we going to figure out what this circuit does?
53
122000
3000
I kako ćete da odgonetnete šta to kolo radi?
02:20
Ideally, we could go through the circuit
54
125000
2000
U idealnoj varijanti, mogli bi da prođemo tim kolom
02:22
and turn these different kinds of cell on and off
55
127000
3000
i tom prilikom da te raznorazne ćelije aktiviramo i deaktiviramo
02:25
and see whether we could figure out
56
130000
2000
i vidimo da li tako možemo da zaključimo
02:27
which ones contribute to certain functions
57
132000
2000
koje učestvuju u određenim funkcijama
02:29
and which ones go wrong in certain pathologies.
58
134000
2000
a koje se kvare usled nekih patologija.
02:31
If we could activate cells, we could see what powers they can unleash,
59
136000
3000
Ako bismo mogli da aktiviramo ćelije, mogli bi videti energiju koju one oslobađaju,
02:34
what they can initiate and sustain.
60
139000
2000
šta mogu da iniciraju i podrže.
02:36
If we could turn them off,
61
141000
2000
Ako bismo mogli da ih isključimo,
02:38
then we could try and figure out what they're necessary for.
62
143000
2000
onda bi mogli da pokušamo da odgonetnemo za šta su neophodne.
02:40
And that's a story I'm going to tell you about today.
63
145000
3000
E to je priča koju ću vam danas ispričati.
02:43
And honestly, where we've gone through over the last 11 years,
64
148000
3000
Iskreno, kuda smo prošli u prethodnih 11 godina,
02:46
through an attempt to find ways
65
151000
2000
pokušavajući da nađemo načine
02:48
of turning circuits and cells and parts and pathways of the brain
66
153000
2000
da kola i ćelije i delove i putanje u mozgu
02:50
on and off,
67
155000
2000
aktiviramo i deaktiviramo
02:52
both to understand the science
68
157000
2000
i da bi razumeli nauku,
02:54
and also to confront some of the issues
69
159000
3000
ali i da bi se suočili sa nekim pitanjima
02:57
that face us all as humans.
70
162000
3000
koja se tiču svih nas, ljudskih bića.
03:00
Now before I tell you about the technology,
71
165000
3000
Sada, pre priče o tehnologiji,
03:03
the bad news is that a significant fraction of us in this room,
72
168000
3000
loša vest je da će značajan broj nas u ovoj prostoriji,
03:06
if we live long enough,
73
171000
2000
ako poživimo dovoljno dugo,
03:08
will encounter, perhaps, a brain disorder.
74
173000
2000
verovatno, doživeti neki moždani poremećaj.
03:10
Already, a billion people
75
175000
2000
Već sada, milijarda ljudi
03:12
have had some kind of brain disorder
76
177000
2000
pati od neke vrste moždanog poremećaja
03:14
that incapacitates them,
77
179000
2000
koja ih onesposobljava.
03:16
and the numbers don't do it justice though.
78
181000
2000
A brojevi nam nisu naklonjeni.
03:18
These disorders -- schizophrenia, Alzheimer's,
79
183000
2000
Ti poremećaji -- šizofrenija, Alchajmer,
03:20
depression, addiction --
80
185000
2000
depresija, zavisnosti --
03:22
they not only steal our time to live, they change who we are.
81
187000
3000
ne samo da nam skraćuju životni vek, oni nas menjaju;
03:25
They take our identity and change our emotions
82
190000
2000
oni nam oduzimaju identitet i menjaju naša osećanja --
03:27
and change who we are as people.
83
192000
3000
i menjaju nas kao osobe.
03:30
Now in the 20th century,
84
195000
3000
Sada, u 20. veku,
03:33
there was some hope that was generated
85
198000
3000
postojala je nada koju je generisao
03:36
through the development of pharmaceuticals for treating brain disorders,
86
201000
3000
razvoj farmaceutskih proizvoda za tretiranje moždanih poremećaja.
03:39
and while many drugs have been developed
87
204000
3000
Dok su razvijani mnogi lekovi
03:42
that can alleviate symptoms of brain disorders,
88
207000
2000
koji ublažavaju simptome moždanih poremećaja,
03:44
practically none of them can be considered to be cured.
89
209000
3000
praktično nijedan od njih nije moga biti izlečen.
03:47
And part of that's because we're bathing the brain in the chemical.
90
212000
3000
Deo razloga je što preplavljujemo mozak hemikalijama.
03:50
This elaborate circuit
91
215000
2000
Ovo složeno kolo
03:52
made out of thousands of different kinds of cell
92
217000
2000
sačinjeno od hiljada različitih vrsta ćelija
03:54
is being bathed in a substance.
93
219000
2000
počinje da biva preplavljeno supstancama.
03:56
That's also why, perhaps, most of the drugs, and not all, on the market
94
221000
2000
Možda je to razlog zašto većina lekova, ali ne svi, koji su na tržištu
03:58
can present some kind of serious side effect too.
95
223000
3000
ima ozbiljne neželjene efekte.
04:01
Now some people have gotten some solace
96
226000
3000
Neki ljudi nalaze utehu
04:04
from electrical stimulators that are implanted in the brain.
97
229000
3000
od električnih stimulatora koji su im ugrađeni u mozak.
04:07
And for Parkinson's disease,
98
232000
2000
Ili u slučaju Parkinsonove bolesti,
04:09
Cochlear implants,
99
234000
2000
kohlearni implanti,
04:11
these have indeed been able
100
236000
2000
koji su zaista uspeli
04:13
to bring some kind of remedy
101
238000
2000
da donesu neku vrstu poboljšanja
04:15
to people with certain kinds of disorder.
102
240000
2000
ljudima sa određenim vrstama poremećaja.
04:17
But electricity also will go in all directions --
103
242000
2000
Ali elektricitet ide u svim pravcima --
04:19
the path of least resistance,
104
244000
2000
putem manjeg otpora,
04:21
which is where that phrase, in part, comes from.
105
246000
2000
što je, delom, i poreklo fraze.
04:23
And it also will affect normal circuits as well as the abnormal ones that you want to fix.
106
248000
3000
A uticaće i na normalna kola baš kao i na abnormalna koja želite da popravite.
04:26
So again, we're sent back to the idea
107
251000
2000
I tako smo se vratili ideji
04:28
of ultra-precise control.
108
253000
2000
ultra precizne kontrole.
04:30
Could we dial-in information precisely where we want it to go?
109
255000
3000
Možemo li poslati informaciju precizno tamo gde želimo da ona ode?
04:34
So when I started in neuroscience 11 years ago,
110
259000
4000
I tako, kada sam ja počeo da se bavim neuronaukom pre 11 godina,
04:38
I had trained as an electrical engineer and a physicist,
111
263000
3000
posedovao sam znanja električnog inženjera i fizičara,
04:41
and the first thing I thought about was,
112
266000
2000
a prva stvar koju su me naučili je bila
04:43
if these neurons are electrical devices,
113
268000
2000
da ako su neuroni električni sklopovi,
04:45
all we need to do is to find some way
114
270000
2000
sve što treba da uradimo je da nađemo način
04:47
of driving those electrical changes at a distance.
115
272000
2000
da izvedemo električne promene sa daljine.
04:49
If we could turn on the electricity in one cell,
116
274000
2000
Ako bi mogli da izazovemo elekticitet u jednoj ćeliji,
04:51
but not its neighbors,
117
276000
2000
ali ne i u susednoj,
04:53
that would give us the tool we need to activate and shut down these different cells,
118
278000
3000
to bi nam dalo alat koji nam treba da aktiviramo i deaktiviramo te različite ćelije,
04:56
figure out what they do and how they contribute
119
281000
2000
da otkrijemo šta one rade i kako doprinose
04:58
to the networks in which they're embedded.
120
283000
2000
mreži u koju su smeštene.
05:00
And also it would allow us to have the ultra-precise control we need
121
285000
2000
To bi nam omogućilo i da imamo ultra precizne kontrole koje nam trebaju
05:02
in order to fix the circuit computations
122
287000
3000
da bi mogli da popravimo rezultate kola
05:05
that have gone awry.
123
290000
2000
koja su zastranila.
05:07
Now how are we going to do that?
124
292000
2000
Kako ćemo to da uradimo?
05:09
Well there are many molecules that exist in nature,
125
294000
2000
Pa, u prirodi postoje mnogi molekuli
05:11
which are able to convert light into electricity.
126
296000
3000
koji su sposobni da pretvore svetlost u elektricitet.
05:14
You can think of them as little proteins
127
299000
2000
Možete o njima misliti kao o malim proteinima
05:16
that are like solar cells.
128
301000
2000
koji su kao solarne ćelije.
05:18
If we can install these molecules in neurons somehow,
129
303000
3000
Ako bi nekako mogli da instaliramo te molekule u neurone
05:21
then these neurons would become electrically drivable with light.
130
306000
3000
onda bi ti neuroni postali elektro-upravljivi svetlom.
05:24
And their neighbors, which don't have the molecule, would not.
131
309000
3000
A njihovi susedi, koji nemaju dodate molekule, ne bi bili.
05:27
There's one other magic trick you need to make this all happen,
132
312000
2000
Postoji još jedan magični trik koji vam treba da bi se sve ovo desilo
05:29
and that's the ability to get light into the brain.
133
314000
3000
a to je načičn da uvedete svetlost u mozak.
05:32
And to do that -- the brain doesn't feel pain -- you can put --
134
317000
3000
Da bi to uradili -- mozak ne oseća bol -- možete ugraditi --
05:35
taking advantage of all the effort
135
320000
2000
zahvaljujući svemu što je uloženo
05:37
that's gone into the Internet and communications and so on --
136
322000
2000
u razvoj internet i komunikacije i slično --
05:39
optical fibers connected to lasers
137
324000
2000
optička vlakna prikopčana na lasere
05:41
that you can use to activate, in animal models for example,
138
326000
2000
koja možete koristiti za aktiviranje, na primer u životinjskim modelima,
05:43
in pre-clinical studies,
139
328000
2000
u predkliničkim studijama,
05:45
these neurons and to see what they do.
140
330000
2000
ovih neurona i tako videti šta rade.
05:47
So how do we do this?
141
332000
2000
Pa kako ćemo to da izvedemo?
05:49
Around 2004,
142
334000
2000
U 2004. godini,
05:51
in collaboration with Gerhard Nagel and Karl Deisseroth,
143
336000
2000
u saradnji sa Gerhardom Najdželom i Karlom Deiserotom,
05:53
this vision came to fruition.
144
338000
2000
ova vizija je dala plodove.
05:55
There's a certain alga that swims in the wild,
145
340000
3000
Postoji alga koja obitava u divljini,
05:58
and it needs to navigate towards light
146
343000
2000
i ona se kreće prema svetlu
06:00
in order to photosynthesize optimally.
147
345000
2000
da bi optimalno obavljala fotosintezu.
06:02
And it senses light with a little eye-spot,
148
347000
2000
Ona oseća svetlost malom tačkom-okom,
06:04
which works not unlike how our eye works.
149
349000
3000
koja funkcioniše ne bitno različito od našeg oka.
06:07
In its membrane, or its boundary,
150
352000
2000
U membrani, ili na njenoj granici,
06:09
it contains little proteins
151
354000
3000
sadrži male proteine
06:12
that indeed can convert light into electricity.
152
357000
3000
koji zaista pretvaraju svetlost u elektricitet.
06:15
So these molecules are called channelrhodopsins.
153
360000
3000
Ti molekuli se zovu channelrhodopsin-i
06:18
And each of these proteins acts just like that solar cell that I told you about.
154
363000
3000
I svaki od tih proteina deluje kao solarna ćelija o kojoj sam vam pričao.
06:21
When blue light hits it, it opens up a little hole
155
366000
3000
Kada je pogodi plavo svetlo, otvori se mala rupa
06:24
and allows charged particles to enter the eye-spot,
156
369000
2000
i čestica sa nabojem uđe u tačku-oko.
06:26
and that allows this eye-spot to have an electrical signal
157
371000
2000
Time tačka-oko dobija električni impuls
06:28
just like a solar cell charging up a battery.
158
373000
3000
baš kao solarna ćelija koja puni bateriju.
06:31
So what we need to do is to take these molecules
159
376000
2000
Znači, ono što treba da uradimo je da uzmemo te molekule
06:33
and somehow install them in neurons.
160
378000
2000
i nekako ih instaliramo u neurone.
06:35
And because it's a protein,
161
380000
2000
A pošto su to proteini,
06:37
it's encoded for in the DNA of this organism.
162
382000
3000
kodirani su za DNK tih organizama.
06:40
So all we've got to do is take that DNA,
163
385000
2000
Sve što treba da uradimo je da uzmemo tu DNK
06:42
put it into a gene therapy vector, like a virus,
164
387000
3000
ubacimo je u okviru genske terapije, kao virus,
06:45
and put it into neurons.
165
390000
3000
i ugradimo je u neuron.
06:48
So it turned out that this was a very productive time in gene therapy,
166
393000
3000
Ispostavilo se da je ovo veoma produktivno vreme u smislu genske terapije,
06:51
and lots of viruses were coming along.
167
396000
2000
i mnogi virusi su se pojavljivali.
06:53
So this turned out to be very simple to do.
168
398000
2000
Tako je ovo postalo lako izvodivo.
06:55
And early in the morning one day in the summer of 2004,
169
400000
3000
Ranim jutrom jednog dana u septembru 2004.
06:58
we gave it a try, and it worked on the first try.
170
403000
2000
pokušali smo i proradilo je iz prve.
07:00
You take this DNA and you put it into a neuron.
171
405000
3000
Uzmete ovu DNK i stavite je u neuron.
07:03
The neuron uses its natural protein-making machinery
172
408000
3000
Neuroni su koristili prirodan proces za pravljenje proteina
07:06
to fabricate these little light-sensitive proteins
173
411000
2000
da bi prizveli ove male fotoosetljive proteine
07:08
and install them all over the cell,
174
413000
2000
i instalirali ih svuda po ćeliji,
07:10
like putting solar panels on a roof,
175
415000
2000
kao što se postavljaju solarni paneli na krov.
07:12
and the next thing you know,
176
417000
2000
I tek tako,
07:14
you have a neuron which can be activated with light.
177
419000
2000
imate neuron koji može da se aktivira pomoću svetla.
07:16
So this is very powerful.
178
421000
2000
To je tako moćno.
07:18
One of the tricks you have to do
179
423000
2000
Jedna od stvari koje treba da uradite
07:20
is to figure out how to deliver these genes to the cells that you want
180
425000
2000
je da odgonetnete kako da isporučite te gene u ćelije koje ste odredili
07:22
and not all the other neighbors.
181
427000
2000
a ne u sve ćelije u okolini.
07:24
And you can do that; you can tweak the viruses
182
429000
2000
I to može da se uradi; moguće je "oblikovati" viruse
07:26
so they hit just some cells and not others.
183
431000
2000
tako da pogode samo određene ćelije a ne neke druge.
07:28
And there's other genetic tricks you can play
184
433000
2000
A postoje i drugi genetičarski trikovi koje možete primeniti
07:30
in order to get light-activated cells.
185
435000
3000
da bi dobili ćelije koje se aktiviraju svetlom.
07:33
This field has now come to be known as optogenetics.
186
438000
4000
Ova oblast je sada poznata kao optogenetika.
07:37
And just as one example of the kind of thing you can do,
187
442000
2000
Evo jedan primer onoga što možete da uradite,
07:39
you can take a complex network,
188
444000
2000
možete uzeti kompleksnu mrežu i
07:41
use one of these viruses to deliver the gene
189
446000
2000
upotrebiti neki od virusa da isporučite gen
07:43
just to one kind of cell in this dense network.
190
448000
3000
samo jednoj vrsti ćelija u toj gustoj mreži.
07:46
And then when you shine light on the entire network,
191
451000
2000
Kada obasjate svetlom celu mrežu
07:48
just that cell type will be activated.
192
453000
2000
aktiviraće se samo odabrana vrsta ćelija.
07:50
So for example, lets sort of consider that basket cell I told you about earlier --
193
455000
3000
Na primer, hajde da vidimo one korpaste ćelije o kojima sam ranije pričao --
07:53
the one that's atrophied in schizophrenia
194
458000
2000
one koje atrofiraju u šizofreniji
07:55
and the one that is inhibitory.
195
460000
2000
koje su inhibitorne.
07:57
If we can deliver that gene to these cells --
196
462000
2000
Ako možemo da isporučimo odabrane gene tim ćelijama --
07:59
and they're not going to be altered by the expression of the gene, of course --
197
464000
3000
naravno, to ih neće, u genetskom smislu, promeniti --
08:02
and then flash blue light over the entire brain network,
198
467000
3000
i ako onda obasjamo plavom svetlošću kompletnu moždanu mrežu,
08:05
just these cells are going to be driven.
199
470000
2000
samo će se odabrane ćelije pokrenuti.
08:07
And when the light turns off, these cells go back to normal,
200
472000
2000
Kada ugasimo svetlo, te ćelije će se vratiti u normalu
08:09
so they don't seem to be averse against that.
201
474000
3000
tako da nisu trajno izmenjene.
08:12
Not only can you use this to study what these cells do,
202
477000
2000
Ne samo da ovo možete da koristite da bi studirali šta ove ćelije rade,
08:14
what their power is in computing in the brain,
203
479000
2000
koji je njihov značaj u proračunima mozga,
08:16
but you can also use this to try to figure out --
204
481000
2000
nego možete koristiti ovo da bi pokušali da odgonetnete --
08:18
well maybe we could jazz up the activity of these cells,
205
483000
2000
možda bi mogli da oživimo aktivnosti ovih ćelija,
08:20
if indeed they're atrophied.
206
485000
2000
ako one zaista atrofiraju.
08:22
Now I want to tell you a couple of short stories
207
487000
2000
Sada bih želeo da vam ispričam nekoliko kratkih priča
08:24
about how we're using this,
208
489000
2000
o tome kako koristimo ovo,
08:26
both at the scientific, clinical and pre-clinical levels.
209
491000
3000
na naučnom, kliničkom i predkliničkom nivou.
08:29
One of the questions we've confronted
210
494000
2000
Jedno od pitanja sa kojima smo se susreli
08:31
is, what are the signals in the brain that mediate the sensation of reward?
211
496000
3000
je koji signali u mozgu posreduju osećaju nagrade?
08:34
Because if you could find those,
212
499000
2000
Jer ako možemo da pronađemo njih,
08:36
those would be some of the signals that could drive learning.
213
501000
2000
to bi bili neki od signala koji bi mogli da podstiču učenje.
08:38
The brain will do more of whatever got that reward.
214
503000
2000
Mozak bi radio više onoga što se nagrađuje.
08:40
And also these are signals that go awry in disorders such as addiction.
215
505000
3000
Ujedno, to su signali koji oslabe pri poremećajima kao što je zavisnost.
08:43
So if we could figure out what cells they are,
216
508000
2000
Ako bi mogli da odgonetnemo koje su to ćelije,
08:45
we could maybe find new targets
217
510000
2000
možda bi mogli da nađemo nove ciljeve
08:47
for which drugs could be designed or screened against,
218
512000
2000
za koje bi mogli da napravimo lekove ili koje bi mogli da izolujemo,
08:49
or maybe places where electrodes could be put in
219
514000
2000
ili možda mesta u koja bi mogli da uvedemo elektrode
08:51
for people who have very severe disability.
220
516000
3000
ljudima koji pate od ozbiljnih invaliditeta.
08:54
So to do that, we came up with a very simple paradigm
221
519000
2000
Da bi to uradili, smislili smo veoma jednostavan primer
08:56
in collaboration with the Fiorella group,
222
521000
2000
u saradnji sa Fiorela grupom,
08:58
where one side of this little box,
223
523000
2000
u kome na jednoj strani ove male kutije,
09:00
if the animal goes there, the animal gets a pulse of light
224
525000
2000
ako životinja prođe tuda, životinja dobije bljesak svetla
09:02
in order to make different cells in the brain sensitive to light.
225
527000
2000
da bi učinila druge ćelije mozga osetljive na svetlo.
09:04
So if these cells can mediate reward,
226
529000
2000
Ako te ćelije posreduju pri nagradi,
09:06
the animal should go there more and more.
227
531000
2000
životinja će sve više i više ići tuda.
09:08
And so that's what happens.
228
533000
2000
I to se i desilo.
09:10
This animal's going to go to the right-hand side and poke his nose there,
229
535000
2000
Ova životinja će ići ka desnoj strani i promoliće nos tamo,
09:12
and he gets a flash of blue light every time he does that.
230
537000
2000
i dobiti bljesak plavog svetla svaki put kada to učini.
09:14
And he'll do that hundreds and hundreds of times.
231
539000
2000
I ona će to učiniti stotine i stotine puta.
09:16
These are the dopamine neurons,
232
541000
2000
Ovo su neuroni dopamina,
09:18
which some of you may have heard about, in some of the pleasure centers in the brain.
233
543000
2000
o kojima su neki od vas možda čuli, u nekim od centara za zadovoljstvno u mozgu.
09:20
Now we've shown that a brief activation of these
234
545000
2000
Pokazali smo da je njihova kratka aktivacija
09:22
is enough, indeed, to drive learning.
235
547000
2000
dovoljna, zaista, da bi podstakla učenje.
09:24
Now we can generalize the idea.
236
549000
2000
Iz toga možemo da generalizujemo ideju.
09:26
Instead of one point in the brain,
237
551000
2000
Umesto jedne tačke u mozgu,
09:28
we can devise devices that span the brain,
238
553000
2000
možemo izmisliti napravu koja može obuhvatiti mozak,
09:30
that can deliver light into three-dimensional patterns --
239
555000
2000
koja može dopremiti svetlo u trodimenzionalnom obliku --
09:32
arrays of optical fibers,
240
557000
2000
nizovi optičkih vlakana,
09:34
each coupled to its own independent miniature light source.
241
559000
2000
svaki uparen sa njegovim nezavisnim minijaturnim izvorom svetla.
09:36
And then we can try to do things in vivo
242
561000
2000
I tada možemo da pokušamo stvari na živo
09:38
that have only been done to-date in a dish --
243
563000
3000
koje su do sada rađene samo u posudama --
09:41
like high-throughput screening throughout the entire brain
244
566000
2000
kao što je visoko-propusno nadgledanje kompletnog mozga
09:43
for the signals that can cause certain things to happen.
245
568000
2000
zbog signala koji mogu prouzrokovati dešavanje određenih stvari.
09:45
Or that could be good clinical targets
246
570000
2000
Ili bi mogli da budu dobre kliničke ciljane grupe
09:47
for treating brain disorders.
247
572000
2000
za tretmane poremećaja mozga.
09:49
And one story I want to tell you about
248
574000
2000
Evo još jedne priče koju želim da vam ispričam
09:51
is how can we find targets for treating post-traumatic stress disorder --
249
576000
3000
o tome kako možemo naći mete za tretman PTSP --
09:54
a form of uncontrolled anxiety and fear.
250
579000
3000
oblik nekontrolisane anksioznosti i straha.
09:57
And one of the things that we did
251
582000
2000
Jedna od stvari koje smo uradili
09:59
was to adopt a very classical model of fear.
252
584000
3000
je bila da smo usvojili veoma klasičan model straha.
10:02
This goes back to the Pavlovian days.
253
587000
3000
Ovo je iz vremena Pavlova.
10:05
It's called Pavlovian fear conditioning --
254
590000
2000
Naziva se Pavlovljevim uslovljavanjem --
10:07
where a tone ends with a brief shock.
255
592000
2000
tu se zvuk završava kratkim šokom.
10:09
The shock isn't painful, but it's a little annoying.
256
594000
2000
Šok nije bolan ali je neprijatan.
10:11
And over time -- in this case, a mouse,
257
596000
2000
Tokom vremena -- u ovom slučaju miš --
10:13
which is a good animal model, commonly used in such experiments --
258
598000
2000
koji je dobar životinjski model, obično se koristi u ovakvim eksperimentima --
10:15
the animal learns to fear the tone.
259
600000
2000
životinja uči da se plaši zvuka.
10:17
The animal will react by freezing,
260
602000
2000
Životinja reaguje kočenjem,
10:19
sort of like a deer in the headlights.
261
604000
2000
nešto kao jelen uhvaćen u farove.
10:21
Now the question is, what targets in the brain can we find
262
606000
3000
Pitanje je koju metu možemo da nađemo u mozgu
10:24
that allow us to overcome this fear?
263
609000
2000
koja bi nam omogućila da prevlada strah?
10:26
So what we do is we play that tone again
264
611000
2000
Stoga smo ponovo proizvodili ton
10:28
after it's been associated with fear.
265
613000
2000
nakon što je povezan sa strahom.
10:30
But we activate targets in the brain, different ones,
266
615000
2000
Ali aktiviramo ciljeve u mozgu, neke druge,
10:32
using that optical fiber array I told you about in the previous slide,
267
617000
3000
koristeći nizove optičkih vlakana o kojima sam vam pričao uz prethodni slajd,
10:35
in order to try and figure out which targets
268
620000
2000
u cilju da probamo da odredimo koji ciljevi
10:37
can cause the brain to overcome that memory of fear.
269
622000
3000
mogu da učine da mozak prevaziđe sećanje na strah.
10:40
And so this brief video
270
625000
2000
I tako ovaj kratki video snimak
10:42
shows you one of these targets that we're working on now.
271
627000
2000
pokazuje jedan od tih ciljeva na kojima mi sada radimo.
10:44
This is an area in the prefrontal cortex,
272
629000
2000
Ovo je oblast u prefrontalnom korteksu,
10:46
a region where we can use cognition to try to overcome aversive emotional states.
273
631000
3000
region u kome koristimo spoznato da pokušamo da prevaziđemo averzivna emocionalna stanja.
10:49
And the animal's going to hear a tone -- and a flash of light occurred there.
274
634000
2000
Životinja će čuti ton -- bljesak svetla se pojavio tamo.
10:51
There's no audio on this, but you can see the animal's freezing.
275
636000
2000
Ovaj snimak nema ton ali možete videti da se životinja ukočila.
10:53
This tone used to mean bad news.
276
638000
2000
Ovaj ton je značio najavu lošeg.
10:55
And there's a little clock in the lower left-hand corner,
277
640000
2000
U donjem levom uglu vidite mali sat,
10:57
so you can see the animal is about two minutes into this.
278
642000
3000
tako da možete da vidite da je životinja u ovom stanju oko dva minuta.
11:00
And now this next clip
279
645000
2000
A sada sledeći video snimak
11:02
is just eight minutes later.
280
647000
2000
koji je napravljen samo osam minuta kasnije.
11:04
And the same tone is going to play, and the light is going to flash again.
281
649000
3000
Isti ton je proizveden i svetlo će bljesnuti ponovo.
11:07
Okay, there it goes. Right now.
282
652000
3000
OK, evo ga. Baš sad.
11:10
And now you can see, just 10 minutes into the experiment,
283
655000
3000
I sada možete videti, nakon samo deset minuta eksperimenta,
11:13
that we've equipped the brain by photoactivating this area
284
658000
3000
da smo mozgu omogućili fotoaktiviranjem oblasti
11:16
to overcome the expression
285
661000
2000
da prevaziđe iskazivanje
11:18
of this fear memory.
286
663000
2000
sećanja na strah.
11:20
Now over the last couple of years, we've gone back to the tree of life
287
665000
3000
Tokom poslednjih par godina vrativši se stablu života,
11:23
because we wanted to find ways to turn circuits in the brain off.
288
668000
3000
pošto smo želeli da nađemo način da isključimo kola u mozgu.
11:26
If we could do that, this could be extremely powerful.
289
671000
3000
Ako bi mogli to da uradimo to bi bilo izuzetno moćno.
11:29
If you can delete cells just for a few milliseconds or seconds,
290
674000
3000
Ako možete da izbrišete ćelije na samo nekoliko milisekundi ili sekundi,
11:32
you can figure out what necessary role they play
291
677000
2000
možete da otkrijete koju to neophodnu ulogu one imaju
11:34
in the circuits in which they're embedded.
292
679000
2000
u kolu u koje su smeštene.
11:36
And we've now surveyed organisms from all over the tree of life --
293
681000
2000
Pregledom organizama širom stabla života --
11:38
every kingdom of life except for animals, we see slightly differently.
294
683000
3000
svako životno carstvo osim životinjskog jer mi vidimo nešto drugačije.
11:41
And we found all sorts of molecules, they're called halorhodopsins or archaerhodopsins,
295
686000
3000
I našli smo svakojake vrste molekula, zovu se halorhodopsini i arherohodopsini,
11:44
that respond to green and yellow light.
296
689000
2000
koje odgovaraju na zeleno i žuto svetlo.
11:46
And they do the opposite thing of the molecule I told you about before
297
691000
2000
Oni rade nešto različito od molekula o kojima sam vam pričao ranije
11:48
with the blue light activator channelrhodopsin.
298
693000
3000
sa channelrhodopsin-om koji se aktivira plavim svetlom.
11:52
Let's give an example of where we think this is going to go.
299
697000
3000
Evo primera o tome šta mislimo kuda ovo vodi.
11:55
Consider, for example, a condition like epilepsy,
300
700000
3000
Uzmimo na primer stanje kao što je epilepsija,
11:58
where the brain is overactive.
301
703000
2000
gde je mozak previše aktivan.
12:00
Now if drugs fail in epileptic treatment,
302
705000
2000
Ako lekovi ne uspevaju da tretiraju epilepsiju,
12:02
one of the strategies is to remove part of the brain.
303
707000
2000
jedna od strategija je da se odstrani deo mozga.
12:04
But that's obviously irreversible, and there could be side effects.
304
709000
2000
Ali to je očigledno nepovratna akcija i moglo bi da bude neželjenih efekata.
12:06
What if we could just turn off that brain for a brief amount of time,
305
711000
3000
Šta ako možemo da jednostavno isključimo taj mozak na tren,
12:09
until the seizure dies away,
306
714000
3000
dok napad ne prođe,
12:12
and cause the brain to be restored to its initial state --
307
717000
3000
i tako uspemo da mozak obnovi svoje početno stanje --
12:15
sort of like a dynamical system that's being coaxed down into a stable state.
308
720000
3000
nešto kao dinamički sistem koji potisnemo nadole u stabilno stanje.
12:18
So this animation just tries to explain this concept
309
723000
3000
Ova animacija samo pokušava da objasni koncept
12:21
where we made these cells sensitive to being turned off with light,
310
726000
2000
u kome smo učinili ove ćelije osetljivim na gašenje svetlom,
12:23
and we beam light in,
311
728000
2000
i onda bljesnemo svetlo,
12:25
and just for the time it takes to shut down a seizure,
312
730000
2000
i to samo onoliko vremena koliko je potrebno da se zaustavi napad
12:27
we're hoping to be able to turn it off.
313
732000
2000
u nadi da ćemo biti u stanju da mozak ugasimo.
12:29
And so we don't have data to show you on this front,
314
734000
2000
Nemamo podatke da vam ih sada pokažemo
12:31
but we're very excited about this.
315
736000
2000
ali ovo je veoma uzbudljivo.
12:33
Now I want to close on one story,
316
738000
2000
Želim da završim jednom pričom,
12:35
which we think is another possibility --
317
740000
2000
za koju mislimo da je još jedna od mogućnosti --
12:37
which is that maybe these molecules, if you can do ultra-precise control,
318
742000
2000
a to je da ovi molekuli možda, ako može da se napravi ultra precizno upravljanje,
12:39
can be used in the brain itself
319
744000
2000
mogu da budu upotrebljeni u samom mozgu
12:41
to make a new kind of prosthetic, an optical prosthetic.
320
746000
3000
za pravljenje nove vrste pomagala, optičkih pomagala.
12:44
I already told you that electrical stimulators are not uncommon.
321
749000
3000
Već sam vam rekao da elektirčna stimulacija nije neobična.
12:47
Seventy-five thousand people have Parkinson's deep-brain stimulators implanted.
322
752000
3000
75.000 ljudi ima, duboko u mozgu, ugrađene stimulatore za kontrolu Parkinsonove bolesti.
12:50
Maybe 100,000 people have Cochlear implants,
323
755000
2000
Nekih 100.000 ljudi ima kohlearne implante,
12:52
which allow them to hear.
324
757000
2000
koji im omogućavaju da čuju.
12:54
There's another thing, which is you've got to get these genes into cells.
325
759000
3000
Ima tu još nesšto a to je da morate da ubacite ove gene u ćelije.
12:57
And new hope in gene therapy has been developed
326
762000
3000
Pojavila se nova nada u genskoj terapiji
13:00
because viruses like the adeno-associated virus,
327
765000
2000
jer su virusi poput adeno povezanih virusa,
13:02
which probably most of us around this room have,
328
767000
2000
koje verovatno većina nas u ovoj prostoriji ima,
13:04
and it doesn't have any symptoms,
329
769000
2000
a da pri tom nema nikakve simptome,
13:06
which have been used in hundreds of patients
330
771000
2000
upotrebljeni na stotinama pacijenata
13:08
to deliver genes into the brain or the body.
331
773000
2000
da bi dopremili gene u mozak ili telo.
13:10
And so far, there have not been serious adverse events
332
775000
2000
I za sada još nije bilo ozbiljnih štetnih događaja
13:12
associated with the virus.
333
777000
2000
koji su povezani sa virusom.
13:14
There's one last elephant in the room, the proteins themselves,
334
779000
3000
U sobi se nalazi još jedan slon, sami proteini,
13:17
which come from algae and bacteria and fungi,
335
782000
2000
koje dobijamo od algi i bakterija i plesni,
13:19
and all over the tree of life.
336
784000
2000
sa celog stabla života.
13:21
Most of us don't have fungi or algae in our brains,
337
786000
2000
Većina nas nema plesni ili alge u mozgu,
13:23
so what is our brain going to do if we put that in?
338
788000
2000
i šta će mozak da uradi ako mu ih ubacimo?
13:25
Are the cells going to tolerate it? Will the immune system react?
339
790000
2000
Da li će ih ćelije tolerisati? Da li će reagovati imunološki sistem?
13:27
In its early days -- these have not been done on humans yet --
340
792000
2000
U početku smo -- ovo još nije probano na ljudima --
13:29
but we're working on a variety of studies
341
794000
2000
ali radimo na raznim studijama
13:31
to try and examine this,
342
796000
2000
ispitujući ovo.
13:33
and so far we haven't seen overt reactions of any severity
343
798000
3000
Za sada nismo videli suprotne ili ikakve značajne reakcije
13:36
to these molecules
344
801000
2000
na ove molekule
13:38
or to the illumination of the brain with light.
345
803000
3000
ili na obasjavanje mozga svetlošću.
13:41
So it's early days, to be upfront, but we're excited about it.
346
806000
3000
Rano je, da budemo jasni, ali smo veoma uzbuđeni svim ovim.
13:44
I wanted to close with one story,
347
809000
2000
Želim da završim jednom pričom,
13:46
which we think could potentially
348
811000
2000
za koju mislimo da predstavlja potencijalnu
13:48
be a clinical application.
349
813000
2000
kliničku primenu.
13:50
Now there are many forms of blindness
350
815000
2000
Postoje razne vrste slepila
13:52
where the photoreceptors,
351
817000
2000
gde fotoreceptori,
13:54
our light sensors that are in the back of our eye, are gone.
352
819000
3000
naši svetlosni senzori koji su u dnu naših očiju, više ne postoje.
13:57
And the retina, of course, is a complex structure.
353
822000
2000
A retina je, naravno, kompleksna struktura.
13:59
Now let's zoom in on it here, so we can see it in more detail.
354
824000
2000
Hajde da zumiramo to, da bi mogli da vidimo više detalja.
14:01
The photoreceptor cells are shown here at the top,
355
826000
3000
Fotoreceptorske ćelije su prikazane na vrhu,
14:04
and then the signals that are detected by the photoreceptors
356
829000
2000
a onda se signal koji detektuju fotorecpetori
14:06
are transformed by various computations
357
831000
2000
transformiše različitim proračunima,
14:08
until finally that layer of cells at the bottom, the ganglion cells,
358
833000
3000
dok na kraju taj sloj ćelija na dnu, ganglionske ćelije,
14:11
relay the information to the brain,
359
836000
2000
proslede informaciju mozgu,
14:13
where we see that as perception.
360
838000
2000
gde vidimo opaženo.
14:15
In many forms of blindness, like retinitis pigmentosa,
361
840000
3000
U mnogim vrstama slepila, kao recimo retinska pigmentoza,
14:18
or macular degeneration,
362
843000
2000
ili degeneracija makule,
14:20
the photoreceptor cells have atrophied or been destroyed.
363
845000
3000
fotorecpetorske ćelije su atrofirane ili su uništene.
14:23
Now how could you repair this?
364
848000
2000
Kako je ovo moguće popraviti?
14:25
It's not even clear that a drug could cause this to be restored,
365
850000
3000
Nije jasno da lekovi mogu da uzrokuju obnavljanje,
14:28
because there's nothing for the drug to bind to.
366
853000
2000
pošto ne postoji ništa za šta bi lek mogao da se veže.
14:30
On the other hand, light can still get into the eye.
367
855000
2000
A opet, svetlo i dalje dospeva u oko.
14:32
The eye is still transparent and you can get light in.
368
857000
3000
Oko je i dalje providno i možete da uvedete svetlost unutra.
14:35
So what if we could just take these channelrhodopsins and other molecules
369
860000
3000
Šta ako možemo da uzmemo channelfhodopsin-e i druge molekule
14:38
and install them on some of these other spare cells
370
863000
2000
i instaliramo ih na neke od slobodnih ćelija
14:40
and convert them into little cameras.
371
865000
2000
i tako ih pretvorimo u male kamere.
14:42
And because there's so many of these cells in the eye,
372
867000
2000
A pošto ima mnogo ovih ćelija u oku,
14:44
potentially, they could be very high-resolution cameras.
373
869000
3000
potencijalno, one mogu biti kamere visoke rezolucije.
14:47
So this is some work that we're doing.
374
872000
2000
To je nešto na čemu radimo.
14:49
It's being led by one of our collaborators,
375
874000
2000
Time rukovodi jedan od naših saradnika,
14:51
Alan Horsager at USC,
376
876000
2000
Alan Horsager sa USC-a,
14:53
and being sought to be commercialized by a start-up company Eos Neuroscience,
377
878000
3000
a radi komercijalizacije ga traži start-ap kompanija Eos Neuroscience,
14:56
which is funded by the NIH.
378
881000
2000
koju je osnovao NIH.
14:58
And what you see here is a mouse trying to solve a maze.
379
883000
2000
Ono što vidite ovde je miš koji pokušava da reši lavirint.
15:00
It's a six-arm maze. And there's a bit of water in the maze
380
885000
2000
To je šestokraki lavirint. A ima i nešto vode u lavirintu
15:02
to motivate the mouse to move, or he'll just sit there.
381
887000
2000
da bi motivisali miša da se kreće jer bi u suprotnom on samo sedeo unutra.
15:04
And the goal, of course, of this maze
382
889000
2000
Cilj ovog lavirinta je, naravno,
15:06
is to get out of the water and go to a little platform
383
891000
2000
da izađe iz vode na malu platformu
15:08
that's under the lit top port.
384
893000
2000
koja je pod osvetljenim gornjim otvorom.
15:10
Now mice are smart, so this mouse solves the maze eventually,
385
895000
3000
Miševi su pametni, i tako ovaj miš konačno reši lavirint,
15:13
but he does a brute-force search.
386
898000
2000
ali on primenjuje pretragu putem pokušaja i promašaja.
15:15
He's swimming down every avenue until he finally gets to the platform.
387
900000
3000
On upliva u svako udubljenje dok na kraju ne nađe platformu.
15:18
So he's not using vision to do it.
388
903000
2000
Znači ne koristi vid da bi to obavio.
15:20
These different mice are different mutations
389
905000
2000
Ovi razni miševi imaju raličite mutacije
15:22
that recapitulate different kinds of blindness that affect humans.
390
907000
3000
koje prikazuju različite vrste slepila koje pogađa ljude.
15:25
And so we're being careful in trying to look at these different models
391
910000
3000
Pažljivo smo se trudili da sagledamo ove različite modele,
15:28
so we come up with a generalized approach.
392
913000
2000
i tako smo došli do generalizovanog pristupa.
15:30
So how are we going to solve this?
393
915000
2000
Kako ćemo da rešimo ovo?
15:32
We're going to do exactly what we outlined in the previous slide.
394
917000
2000
Pokušaćemo da uradimo baš ono što smo predstavili prethodnim slajdom.
15:34
We're going to take these blue light photosensors
395
919000
2000
Uzećemo ove fotosenzore za plavo svetlo
15:36
and install them on a layer of cells
396
921000
2000
i instaliraćemo ih na sloj ćelija
15:38
in the middle of the retina in the back of the eye
397
923000
3000
u sredini retine, u dnu oka
15:41
and convert them into a camera --
398
926000
2000
i pretvorićemo ih u kamere.
15:43
just like installing solar cells all over those neurons
399
928000
2000
Baš kao što se instaliraju solarne ćelije svuda po ovim neuronima
15:45
to make them light sensitive.
400
930000
2000
da bi ih učinili osetljivim na svetlost.
15:47
Light is converted to electricity on them.
401
932000
2000
Svetlo se pretvara u elektricitet na njima.
15:49
So this mouse was blind a couple weeks before this experiment
402
934000
3000
Ovaj miš je bio slep nekoliko nedelja pre ovog eksperimenta
15:52
and received one dose of this photosensitive molecule in a virus.
403
937000
3000
i primio je jednu dozu ovih fotoosetljivih molekula u virusu.
15:55
And now you can see, the animal can indeed avoid walls
404
940000
2000
Kao što možete videti, životinja zaista može da izbegne zidove
15:57
and go to this little platform
405
942000
2000
i dođe do male platforme
15:59
and make cognitive use of its eyes again.
406
944000
3000
ponovo upotrebivši oči za tu spoznaju.
16:02
And to point out the power of this:
407
947000
2000
A da bih naglasio značaj ovoga:
16:04
these animals are able to get to that platform
408
949000
2000
ove životinje su bile u stanju da dođu na platformu
16:06
just as fast as animals that have seen their entire lives.
409
951000
2000
istom brzinom kao i životinje koje vide celog života.
16:08
So this pre-clinical study, I think,
410
953000
2000
Ova predklinička studija je, mislim,
16:10
bodes hope for the kinds of things
411
955000
2000
dobar predznak za vrstu stvari
16:12
we're hoping to do in the future.
412
957000
2000
za koje se nadamo da ćemo raditi u budućnosti.
16:14
To close, I want to point out that we're also exploring
413
959000
3000
Za kraj, želim da naglasim da mi istražujemo i
16:17
new business models for this new field of neurotechnology.
414
962000
2000
nove poslovne modele za ovo novo polje neurotehnologije.
16:19
We're developing these tools,
415
964000
2000
Razvijamo oruđa,
16:21
but we share them freely with hundreds of groups all over the world,
416
966000
2000
ali ih razmenjujemo slobodno sa stotinama grupa širom sveta,
16:23
so people can study and try to treat different disorders.
417
968000
2000
tako da ljudi mogu da proučavaju i pokušavaju da tretiraju različite poremećaje.
16:25
And our hope is that, by figuring out brain circuits
418
970000
3000
Nadamo se da, shvativši kola u mozgu
16:28
at a level of abstraction that lets us repair them and engineer them,
419
973000
3000
na apstraktnom nivou koji nam dopušta da ih popravimo i da ih stvaramo,
16:31
we can take some of these intractable disorders that I told you about earlier,
420
976000
3000
možemo neke od ovih tvrdoglavih poremećaja o kojima sam ranije pričao,
16:34
practically none of which are cured,
421
979000
2000
od kojih nijedan praktično nije izlečen,
16:36
and in the 21st century make them history.
422
981000
2000
da pošaljemo u istoriju.
16:38
Thank you.
423
983000
2000
Hvala.
16:40
(Applause)
424
985000
13000
(Aplauz)
16:53
Juan Enriquez: So some of the stuff is a little dense.
425
998000
3000
Huan Enrikez: Nešto od ovoga je malo previše.
16:56
(Laughter)
426
1001000
2000
(Smeh)
16:58
But the implications
427
1003000
2000
Ali implikacije
17:00
of being able to control seizures or epilepsy
428
1005000
3000
ideje da je moguće kontrolisati napade ili epilepsiju
17:03
with light instead of drugs,
429
1008000
2000
svetlom umesto lekovima,
17:05
and being able to target those specifically
430
1010000
3000
i mogućnosti da se baš one naciljaju
17:08
is a first step.
431
1013000
2000
je prvi korak.
17:10
The second thing that I think I heard you say
432
1015000
2000
Druga stvar koju mislim da sam čuo da si rekao
17:12
is you can now control the brain in two colors,
433
1017000
3000
je da je sada moguće kontrolisati mozak dvema bojama.
17:15
like an on/off switch.
434
1020000
2000
Nešto kao prekidač za uključivanje i isključivanje.
17:17
Ed Boyden: That's right.
435
1022000
2000
Ed Boyden: Tako je.
17:19
JE: Which makes every impulse going through the brain a binary code.
436
1024000
3000
HE: To svaki impuls koji ide kroz mozak čini binarnim kodom.
17:22
EB: Right, yeah.
437
1027000
2000
EB: Da, tako je.
17:24
So with blue light, we can drive information, and it's in the form of a one.
438
1029000
3000
Plavim svetlom možemo slati informacije, i to je recimo jedinica.
17:27
And by turning things off, it's more or less a zero.
439
1032000
2000
A isključivanje je nešto kao nula.
17:29
So our hope is to eventually build brain coprocessors
440
1034000
2000
Tako da se mi nadamo da ćemo moći da stvorimo koprocesore u mozgu
17:31
that work with the brain
441
1036000
2000
koji će raditi sa mozgom,
17:33
so we can augment functions in people with disabilities.
442
1038000
3000
tako da ćemo moći da povećamo funkcije ljudima sa invaliditetom.
17:36
JE: And in theory, that means that,
443
1041000
2000
HE: U teoriji to znači da,
17:38
as a mouse feels, smells,
444
1043000
2000
kao što miš oseća, omiriše,
17:40
hears, touches,
445
1045000
2000
čuje, dodirne,
17:42
you can model it out as a string of ones and zeros.
446
1047000
3000
vi možete da napravite model u vidu jedinica i nula.
17:45
EB: Sure, yeah. We're hoping to use this as a way of testing
447
1050000
2000
EB: Naravno, da. Nadamo se da to upotrebimo kao način testiranja.
17:47
what neural codes can drive certain behaviors
448
1052000
2000
koji su prirodni kodovi koji upravljaju određenim ponašanjima
17:49
and certain thoughts and certain feelings,
449
1054000
2000
i određenim mislima i određenim osećanjima,
17:51
and use that to understand more about the brain.
450
1056000
3000
i da to upotrebimo za bolje spoznavanje mozga.
17:54
JE: Does that mean that some day you could download memories
451
1059000
3000
HE: Da li to znači da ćemo jednog dana moći da daunlodujemo sećanja
17:57
and maybe upload them?
452
1062000
2000
i možda ih aploudujemo?
17:59
EB: Well that's something we're starting to work on very hard.
453
1064000
2000
EB: Pa to je nešto na čemu počinjemo da radimo intenzivno.
18:01
We're now working on some work
454
1066000
2000
Sada radimo na radu
18:03
where we're trying to tile the brain with recording elements too.
455
1068000
2000
gde pokušavamo da popločamo mozak i elementima za beleženje.
18:05
So we can record information and then drive information back in --
456
1070000
3000
Tako da možemo da zabeležimo informacije i onda da možemo da upravimo informacije nazad --
18:08
sort of computing what the brain needs
457
1073000
2000
nešto kao proračunavanje onoga što je mozgu potrebno
18:10
in order to augment its information processing.
458
1075000
2000
da bi poboljšali njegov informacioni proces.
18:12
JE: Well, that might change a couple things. Thank you. (EB: Thank you.)
459
1077000
3000
HE: To bi moglo da izmeni neke stvari. Hvala ti. (EB: Hvala.)
18:15
(Applause)
460
1080000
3000
(Aplauz)
Translated by BAW Beograd
Reviewed by Tilen Pigac - EFZG

▲Back to top

ABOUT THE SPEAKER
Ed Boyden - Neuroengineer
Ed Boyden is a professor of biological engineering and brain and cognitive sciences at the MIT Media Lab and the MIT McGovern Institute.

Why you should listen

Ed Boyden leads the Synthetic Neurobiology Group, which develops tools for analyzing and repairing complex biological systems such as the brain. His group applies these tools in a systematic way in order to reveal ground truth scientific understandings of biological systems, which in turn reveal radical new approaches for curing diseases and repairing disabilities. These technologies include expansion microscopy, which enables complex biological systems to be imaged with nanoscale precision, and optogenetic tools, which enable the activation and silencing of neural activity with light (TED Talk: A light switch for neurons). Boyden also co-directs the MIT Center for Neurobiological Engineering, which aims to develop new tools to accelerate neuroscience progress.

Amongst other recognitions, Boyden has received the Breakthrough Prize in Life Sciences (2016), the BBVA Foundation Frontiers of Knowledge Award (2015), the Carnegie Prize in Mind and Brain Sciences (2015), the Jacob Heskel Gabbay Award (2013), the Grete Lundbeck Brain Prize (2013) and the NIH Director's Pioneer Award (2013). He was also named to the World Economic Forum Young Scientist list (2013) and the Technology Review World's "Top 35 Innovators under Age 35" list (2006). His group has hosted hundreds of visitors to learn how to use new biotechnologies and spun out several companies to bring inventions out of his lab and into the world. Boyden received his Ph.D. in neurosciences from Stanford University as a Hertz Fellow, where he discovered that the molecular mechanisms used to store a memory are determined by the content to be learned. Before that, he received three degrees in electrical engineering, computer science and physics from MIT. He has contributed to over 300 peer-reviewed papers, current or pending patents and articles, and he has given over 300 invited talks on his group's work.

More profile about the speaker
Ed Boyden | Speaker | TED.com