TEDMED 2011
Sheila Nirenberg: A prosthetic eye to treat blindness
Šila Nirenberg (Sheila Nirenberg): Očna proteza za liječenje sljepila
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Na TEDMED, Šila Nirenberg na hrabar način predstavlja novinu u izlječenju sljepila: povezujući se preko očnog živca i šaljući signale preko uređaja u mozak.
Sheila Nirenberg - Neuroscientist
Sheila Nirenberg studies how the brain encodes information -- possibly allowing us to decode it, and maybe develop prosthetic sensory devices. Full bio
Sheila Nirenberg studies how the brain encodes information -- possibly allowing us to decode it, and maybe develop prosthetic sensory devices. Full bio
Double-click the English transcript below to play the video.
00:15
I study how the brain processes
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Ja izučavam kako mozak procesuira
00:17
information. That is, how it takes
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informacije. Tj, kako preuzima
00:19
information in from the outside world, and
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informaciju iz spoljašnjeg svijeta i
00:21
converts it into patterns of electrical activity,
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prevodi je u obrazac električne aktivnosti,
00:23
and then how it uses those patterns
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i kako zatim koristi ostale obrasce
00:25
to allow you to do things --
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i dopušta vam da
00:27
to see, hear, to reach for an object.
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vidite, čujete, posežete za predmetima.
00:29
So I'm really a basic scientist, not
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Ja sam u suštini naučnik, ne kliničar,
00:31
a clinician, but in the last year and a half
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ali posljednjih godinu i po dana
00:33
I've started to switch over, to use what
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počela sam da se prebacujem,
da koristim
da koristim
00:35
we've been learning about these patterns
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to što smo naučili o ovim obrascima
00:37
of activity to develop prosthetic devices,
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aktivnosti kako bismo razvili proteze,
00:40
and what I wanted to do today is show you
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i ono što danas želim da vam pokažem
00:42
an example of this.
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je primjer toga.
00:44
It's really our first foray into this.
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Ovo je zapravo naš prvi upad na ovu teritoriju.
00:46
It's the development of a prosthetic device
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To je razvoj proteze
00:48
for treating blindness.
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za liječenje sljepila.
00:50
So let me start in on that problem.
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Pa da vas uputim u tu problematiku.
00:52
There are 10 million people in the U.S.
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U Sjedinjenim Državama živi 10 miliona ljudi
00:54
and many more worldwide who are blind
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i još više širom svijeta koji su slijepi
00:56
or are facing blindness due to diseases
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ili se suočavaju sa nekom drugom vrstom oboljenja
00:58
of the retina, diseases like
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retine, oboljenja kao
01:00
macular degeneration, and there's little
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[to je makularna degeneracija,
i jako malo
i jako malo
01:02
that can be done for them.
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se može za njih učiniti.
01:04
There are some drug treatments, but
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Postoje neki farmakološki tretmani, ali
01:06
they're only effective on a small fraction
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su oni uspješni na malom
01:08
of the population. And so, for the vast
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broju populacije. I tako je za većinu
01:10
majority of patients, their best hope for
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pacijenata najbolja nada za
01:12
regaining sight is through prosthetic devices.
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povratak vida upravo proteza.
01:14
The problem is that current prosthetics
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Problem je u tome što postojeće proteze
01:16
don't work very well. They're still very
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ne rade baš najbolje.
Još uvijek su dosta ograničene
Još uvijek su dosta ograničene
01:18
limited in the vision that they can provide.
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u pogledu vizuelnih mogućnosti
koje obezbjeđuju.
koje obezbjeđuju.
01:20
And so, you know, for example, with these
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Na primjer, sa ovim
01:22
devices, patients can see simple things
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uređajem, pacijent može
vidjeti jednostavne stvari
vidjeti jednostavne stvari
01:24
like bright lights and high contrast edges,
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kao jasno osvjetljenje
i jake kontrastne ivice,
i jake kontrastne ivice,
01:26
not very much more, so nothing close
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nešto više vrlo teško,
tako da za sad ništa
tako da za sad ništa
01:28
to normal vision has been possible.
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što je blisko normalnom vidu.
01:31
So what I'm going to tell you about today
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Tako da ono što hoću danas da vam pokažem
01:33
is a device that we've been working on
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je uređaj na kome smo radili
01:35
that I think has the potential to make
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za koji smatram da ima
potencijala da premosti
potencijala da premosti
01:37
a difference, to be much more effective,
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razliku, da bude mnogo efikasniji
01:39
and what I wanted to do is show you
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i htjela sam da vam pokažem
01:41
how it works. Okay, so let me back up a
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kako radi. U redu,
dozvolite mi da se malo povučem
dozvolite mi da se malo povučem
01:43
little bit and show you how a normal retina
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i pokažem vam kako
normalna retina radi
normalna retina radi
01:45
works first so you can see the problem
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kako biste uvidjeli problem
01:47
that we were trying to solve.
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koji smo pokušavali da riješimo.
01:49
Here you have a retina.
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Ovdje imate retinu
01:51
So you have an image, a retina, and a brain.
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Dakle imate sliku, retina i mozak.
01:53
So when you look at something, like this image
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Kad gledate u nešto,
kao u ovu sliku
kao u ovu sliku
01:55
of this baby's face, it goes into your eye
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ili bebino lice, to ulazi u vaše oko
01:57
and it lands on your retina, on the front-end
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i pada na vašu retinu, na ćelije
01:59
cells here, the photoreceptors.
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prvog reda, fotoreceptore.
02:01
Then what happens is the retinal circuitry,
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Zatim se uključuje
retinalno električno kolo,
retinalno električno kolo,
02:03
the middle part, goes to work on it,
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srednji dio, obrađuje to
02:05
and what it does is it performs operations
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i ono zapravo izvodi operaciju
02:07
on it, it extracts information from it, and it
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pri kojoj obrađuje informaciju
02:09
converts that information into a code.
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i prevodi je u kod.
02:11
And the code is in the form of these patterns
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A taj kod je u obliku mreže
02:13
of electrical pulses that get sent
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električnih impulsa koji se šalju
02:15
up to the brain, and so the key thing is
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u mozak tako da je ključna stvar
02:17
that the image ultimately gets converted
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da slika na kraju bude prevedena
02:19
into a code. And when I say code,
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u kod. Kada kažem kod
02:21
I do literally mean code.
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ja bukvalno mislim kod.
02:23
Like this pattern of pulses here actually means "baby's face,"
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Kao ova mreža signala ovdje
koja u stvari znači "bebino lice"
koja u stvari znači "bebino lice"
02:26
and so when the brain gets this pattern
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i kada mozak primi ovaj obrazac
02:28
of pulses, it knows that what was out there
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signala, odmah zna šta je tamo,
02:30
was a baby's face, and if it
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tamo je bebino lice i kad bi dobilo
02:32
got a different pattern it would know
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drugačiji obrazac znalo bi
02:34
that what was out there was, say, a dog,
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da se tamo nalazi recimo pas
02:36
or another pattern would be a house.
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ili neki drugi obrazac koji bi predstavljao kuću.
02:38
Anyway, you get the idea.
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Kako bilo, znate na šta mislim.
02:40
And, of course, in real life, it's all dynamic,
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Naravno, u stvarnom životu je to dinamičnije
02:42
meaning that it's changing all the time,
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u smislu da se konstantno mijenja
02:44
so the patterns of pulses are changing
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pa se i obrasci mijenjaju
02:46
all the time because the world you're
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svo vrijeme jer se i svijet
02:48
looking at is changing all the time too.
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koji gledamo stalno mijenja.
02:51
So, you know, it's sort of a complicated
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Tako da je to dosta komplikovana stvar.
02:53
thing. You have these patterns of pulses
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Imate ovu mrežu signala
02:55
coming out of your eye every millisecond
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koji dolaze iz vašeg oka svake milisekunde
02:57
telling your brain what it is that you're seeing.
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kazujući vašem mozgu šta to zapravo gleda.
02:59
So what happens when a person
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Šta se dešava kada osoba
03:01
gets a retinal degenerative disease like
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dobije oboljenje retine kao što je
03:03
macular degeneration? What happens is
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makularna degeneracija?
Ono što se dešava je
Ono što se dešava je
03:05
is that, the front-end cells die,
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da umiru ćelije prednjeg reda
03:07
the photoreceptors die, and over time,
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fotoreceptori umiru,
i nakon nekog vremena
i nakon nekog vremena
03:09
all the cells and the circuits that are
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sve druge ćelije i električno kolo koje je
03:11
connected to them, they die too.
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povezano sa njima, takođe umire.
03:13
Until the only things that you have left
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I sve tako dok ne ostanu jedino
03:15
are these cells here, the output cells,
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ove ćelije ovdje, output ćelije
03:17
the ones that send the signals to the brain,
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koje šalju signale u mozak
03:19
but because of all that degeneration
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ali zbog te degeneracije
03:21
they aren't sending any signals anymore.
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one ne šalju više nikakve signale
03:23
They aren't getting any input, so
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jer ne primaju nikakve
dolazne informacije i onda
dolazne informacije i onda
03:25
the person's brain no longer gets
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mozak više ne dobija
03:27
any visual information --
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nikakve vizuelne informacije,
03:29
that is, he or she is blind.
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to jest, on ili ona je slijepa.
03:32
So, a solution to the problem, then,
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Dakle rješenje problema
03:34
would be to build a device that could mimic
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bi bilo da se napravi uređaj koji imitira
03:36
the actions of that front-end circuitry
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rad kola prvog reda
03:38
and send signals to the retina's output cells,
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i šalje signale retinalnim
ćelijama trećeg reda
ćelijama trećeg reda
03:40
and they can go back to doing their
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kako bi one mogle da nastave svoj
03:42
normal job of sending signals to the brain.
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posao slanja signala mozgu.
03:44
So this is what we've been working on,
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To je ono na čemu smo mi zapravo radili
03:46
and this is what our prosthetic does.
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i to je ono šta radi naša proteza.
03:48
So it consists of two parts, what we call
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Dakle ona se sastoji iz dva dijela,
koja zovemo
koja zovemo
03:50
an encoder and a transducer.
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koder i konvertor.
03:52
And so the encoder does just
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I tako koder radi
03:54
what I was saying: it mimics the actions
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ovo o čemu sam pričala: imitira rad
03:56
of the front-end circuitry -- so it takes images
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ćelija prednjeg reda,
dakle uzima slike
dakle uzima slike
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in and converts them into the retina's code.
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i konvertuje ih u retinalni kod.
04:00
And then the transducer then makes the
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A onda konvertor preko ćelija
04:02
output cells send the code on up
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trećeg reda šalje kod gore
04:04
to the brain, and the result is
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u mozak, i rezultat je
04:06
a retinal prosthetic that can produce
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retinalna proteza koja može da izvršava
04:09
normal retinal output.
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normalnu funkciju retine.
04:11
So a completely blind retina,
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Dakle potpuno slijepa retina,
04:13
even one with no front-end circuitry at all,
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čak i ona koja uopšte nema
ćelije prednjeg reda,
ćelije prednjeg reda,
04:15
no photoreceptors,
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nema fotoreceptore,
04:17
can now send out normal signals,
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može sada slati normalne signale,
04:19
signals that the brain can understand.
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signale koje mozak razumije.
04:22
So no other device has been able
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Nijedan drugi uređaj nije bio u stanju
04:24
to do this.
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da ovo odradi.
04:26
Okay, so I just want to take
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U redu, sada ću samo u par rečenica
04:28
a sentence or two to say something about
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da kažem nešto o
04:30
the encoder and what it's doing, because
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koderu i šta on radi, jer
04:32
it's really the key part and it's
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je zaista bitno i
04:34
sort of interesting and kind of cool.
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vrlo interesantno i nekako kul.
04:36
I'm not sure "cool" is really the right word, but
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Možda "kul" nije prava riječ, ali
04:38
you know what I mean.
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znate na šta mislim.
04:40
So what it's doing is, it's replacing
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Dakle, ono šta on radi jeste da zamjenjuje
04:42
the retinal circuitry, really the guts of
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retinalno kolo
04:44
the retinal circuitry, with a set of equations,
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sa setom jednačina
04:46
a set of equations that we can implement
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koje možemo implementirati
04:48
on a chip. So it's just math.
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na čipu. Dakle to je samo matematika.
04:50
In other words, we're not literally replacing
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Drugim riječima,
mi ne zamjenjujemo
mi ne zamjenjujemo
04:53
the components of the retina.
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bukvalno djelove retine.
04:55
It's not like we're making a little mini-device
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Niti pravimo neki mini uređaj
04:57
for each of the different cell types.
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za jedan ili drugi tip ćelija.
04:59
We've just abstracted what the
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Mi samo rezimiramo šta
05:01
retina's doing with a set of equations.
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retina radi sa setom jednačina.
05:03
And so, in a way, the equations are serving
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I tako, jednačine služe
05:05
as sort of a codebook. An image comes in,
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kao neka šifrovana knjiga.
Slika ulazi,
Slika ulazi,
05:07
goes through the set of equations,
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prolazi kroz jednačine,
05:10
and out comes streams of electrical pulses,
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i izlazi kao električni signal,
05:12
just like a normal retina would produce.
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kakav bi normalna retina proizvela.
05:16
Now let me put my money
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A sada mi dozvolite da sa riječi
05:18
where my mouth is and show you that
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pređem na djela i pokažem vam
05:20
we can actually produce normal output,
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da zapravo možemo stvoriti normalan output
05:22
and what the implications of this are.
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i koje bi bile njegove implikacije.
05:24
Here are three sets of
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Ovdje imamo 3 seta
05:26
firing patterns. The top one is from
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okidajućih obrazaca. Gornji je
05:28
a normal animal, the middle one is from
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iz zdrave životinje, srednji je
05:30
a blind animal that's been treated with
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iz slijepe životinje koja je liječena
05:32
this encoder-transducer device, and the
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sa koder - konvertor uređajem i
05:34
bottom one is from a blind animal treated
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donja je iz slijepe životinje liječene
05:36
with a standard prosthetic.
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običnom protezom.
05:38
So the bottom one is the state-of-the-art
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Dakle donja je proizvod
05:40
device that's out there right now, which is
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uređaja koji se trenutno koristi
05:42
basically made up of light detectors,
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a zapravo je napravljena
od svjetlosnog detektora
od svjetlosnog detektora
05:44
but no encoder. So what we did was we
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ali ne i kodera.
Tu smo zapravo
Tu smo zapravo
05:46
presented movies of everyday things --
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prikazivali film sa svakodnevnim stvarima
05:48
people, babies, park benches,
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ljudima, bebama, klupama iz parkova
05:50
you know, regular things happening -- and
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znate već, obične stvari i
05:52
we recorded the responses from the retinas
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snimali smo odgovore sa retine
05:54
of these three groups of animals.
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ovih 3 grupa životinja.
05:56
Now just to orient you, each box is showing
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Čisto da vas orjentišem,
svaka slika pokazuje
svaka slika pokazuje
05:58
the firing patterns of several cells,
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mrežu od par ćelija
06:00
and just as in the previous slides,
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i baš kao na prethodnom slajdu
06:02
each row is a different cell,
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svaki red je druga ćelija,
06:04
and I just made the pulses a little bit smaller
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i ja sam malo smanjila signale
06:06
and thinner so I could show you
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i istanjila ih kako bih vam pokazala
06:09
a long stretch of data.
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duži niz podataka.
06:11
So as you can see, the firing patterns
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I kao što vidite, mreže
06:13
from the blind animal treated with
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kod slijepih životinja koje imaju
06:15
the encoder-transducer really do very
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koder-konvertor prilično se
06:17
closely match the normal firing patterns --
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podudaraju sa normalnim mrežama -
06:19
and it's not perfect, but it's pretty good --
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nije baš savršeno ,ali je dosta dobro -
06:21
and the blind animal treated with
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a kod slijepih životinja sa
06:23
the standard prosthetic,
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običnom protezom
06:25
the responses really don't.
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odgovori nisu baš dobri.
06:27
And so with the standard method,
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Tako da kod obične proteze
06:30
the cells do fire, they just don't fire
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ćelije šalju signale, ali ne
06:32
in the normal firing patterns because
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toliko uspješno kao normalne
06:34
they don't have the right code.
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jer ne posjeduju pravi kod.
06:36
How important is this?
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Koliko je ovo važno?
06:38
What's the potential impact
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Šta je potencijalni uticaj
06:40
on a patient's ability to see?
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na pacijentovu sposobnost vida?
06:43
So I'm just going to show you one
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Pokazaću vam jedan
06:45
bottom-line experiment that answers this,
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eksperiment koji nudi odgovor na to,
06:47
and of course I've got a lot of other data,
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ali naravno imam još puno podataka o tome
06:49
so if you're interested I'm happy
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pa ako da ste zainteresovani,
sa zadovoljstvom
sa zadovoljstvom
06:51
to show more. So the experiment
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ću vam pokazati još.
Dakle, eksperiment
Dakle, eksperiment
06:53
is called a reconstruction experiment.
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je nazvan rekonstruktivni eksperiment.
06:55
So what we did is we took a moment
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Uzeli smo jedan vremenski period
06:57
in time from these recordings and asked,
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iz ovih snimaka i tražili
da vidimo šta je retina
da vidimo šta je retina
07:00
what was the retina seeing at that moment?
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zapravo vidjela u tom periodu.
07:02
Can we reconstruct what the retina
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Da li možemo rekonstruisati šta je retina
07:04
was seeing from the responses
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vidjela iz odgovora
07:06
from the firing patterns?
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mreže signala?
07:08
So, when we did this for responses
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I tako smo uporedili odgovore
07:11
from the standard method and from
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iz obične proteze i odgovore sa
07:14
our encoder and transducer.
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koder-konvertor proteze.
07:16
So let me show you, and I'm going to
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Pokazaću vam, i prvo ću početi
07:18
start with the standard method first.
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sa običnom protezom.
07:20
So you can see that it's pretty limited,
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Vidite da je prilično ograničavajuće,
07:22
and because the firing patterns aren't
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jer mreža signala nije
07:24
in the right code, they're very limited in
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pravilno kodirana,
oni su vrlo ograničavajući
oni su vrlo ograničavajući
07:26
what they can tell you about
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u tome šta vam mogu reći
07:28
what's out there. So you can see that
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šta je tamo vani. Možete vidjeti
07:30
there's something there, but it's not so clear
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nešto tamo, ali nije jasno
07:32
what that something is, and this just sort of
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šta je to u stvari,
i to nas zapravo vraća nazad
i to nas zapravo vraća nazad
07:34
circles back to what I was saying in the
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na moju priču na početku
07:36
beginning, that with the standard method,
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da sa običnom protezom
07:38
patients can see high-contrast edges, they
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pacijenti mogu vidjeti
kontrastne ivice, mogu
kontrastne ivice, mogu
07:40
can see light, but it doesn't easily go
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vidjeti svjetlost ali ništa više
07:42
further than that. So what was
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od toga. Pa kakva je to slika?
07:44
the image? It was a baby's face.
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To je bilo bebino lice.
07:47
So what about with our approach,
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A kakva je bila sa našom metodom
07:49
adding the code? And you can see
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uz pomoć kodiranja? Vidite
07:51
that it's much better. Not only can you
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da je mnogo bolja.
Ne samo da možete prepoznati
Ne samo da možete prepoznati
07:53
tell that it's a baby's face, but you can
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bebino lice, već prepoznajete
07:55
tell that it's this baby's face, which is a
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da je to lice tačno ove bebe,
07:57
really challenging task.
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što je izuzetno zahtjevan zadatak.
07:59
So on the left is the encoder
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Dakle lijevo je koder sam
08:01
alone, and on the right is from an actual
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a desno je sa slijepe retine
08:03
blind retina, so the encoder and the transducer.
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dakle koder i konverter.
08:05
But the key one really is the encoder alone,
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Ali u stvari koder je bitan
08:07
because we can team up the encoder with
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jer možete koristiti koder sa
08:09
the different transducer.
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različitim konverterom.
08:11
This is just actually the first one that we tried.
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Ovo je zapravo prvi sa kojim smo pokušali.
08:13
I just wanted to say something about the standard method.
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Želim samo nešto reći o običnoj protezi.
08:15
When this first came out, it was just a really
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Prvi put kada je izašla, bila je
08:17
exciting thing, the idea that you
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uzbudljiva sama ideja da
08:19
even make a blind retina respond at all.
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da uopšte dobijete neki odgovor
sa slijepe retine.
sa slijepe retine.
08:22
But there was this limiting factor,
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Ali postojao je taj ograničavajući faktor,
08:25
the issue of the code, and how to make
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problematika šifre i kako dobiti
08:27
the cells respond better,
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bolji odgovor ćelije,
08:29
produce normal responses,
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dobiti normalni odgovor,
08:31
and so this was our contribution.
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i to je bio naš doprinos.
08:33
Now I just want to wrap up,
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Sada samo da rezimiram
08:35
and as I was mentioning earlier
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kao što sam ranije spomenula
08:37
of course I have a lot of other data
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ja imam i drugih podataka
08:39
if you're interested, but I just wanted to give
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ako ste zainteresovani,
ali sam htjela da vam izložim
ali sam htjela da vam izložim
08:41
this sort of basic idea
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osnovnu ideju
08:43
of being able to communicate
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o sposobnosti komunikacije
08:46
with the brain in its language, and
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sa mozgom njegovim jezikom i o
08:48
the potential power of being able to do that.
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mogućnosti da se to uopšte ostvari.
08:51
So it's different from the motor prosthetics
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To je drugačije od motorne proteze
08:53
where you're communicating from the brain
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kada komunikacija ide iz mozga
08:55
to a device. Here we have to communicate
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ka uređaju. Ovdje moramo
da komuniciramo
da komuniciramo
08:57
from the outside world
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iz spoljašnje sredine
08:59
into the brain and be understood,
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ka mozgu i da to ima smisla,
09:01
and be understood by the brain.
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da ga mozak razumije.
09:03
And then the last thing I wanted
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I na kraju sam htjela
09:05
to say, really, is to emphasize
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da istaknem
09:07
that the idea generalizes.
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da generalizujem ideju.
09:09
So the same strategy that we used
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Dakle sama strategija koju smo mi ovdje koristili,
09:11
to find the code for the retina we can also
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da nađemo kod za retinu, možemo
09:13
use to find the code for other areas,
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je koristiti i za kodiranje drugih polja,
09:15
for example, the auditory system and
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na primjer za auditorni sistem i
09:17
the motor system, so for treating deafness
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za motorni sistem, to jest za liječenje gluvoće
09:19
and for motor disorders.
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i za motorne poremećaje.
09:21
So just the same way that we were able to
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Na isti način na koji smo uspjeli da
09:23
jump over the damaged
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prevaziđemo oštećenje
09:25
circuitry in the retina to get to the retina's
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rada retine i dođemo do
09:27
output cells, we can jump over the
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njenih unutrašnjih ćelija,
možemo prevazići
možemo prevazići
09:29
damaged circuitry in the cochlea
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oštećenje kohlee uha
09:31
to get the auditory nerve,
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kako bismo došli do slušnog nerva
09:33
or jump over damaged areas in the cortex,
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ili oštećenja polja
09:35
in the motor cortex, to bridge the gap
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u motornom korteksu,
premošćavajući praznine
premošćavajući praznine
09:38
produced by a stroke.
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nastale šlogom.
09:40
I just want to end with a simple
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Željela bih da završim
09:42
message that understanding the code
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sa porukom da razumijevanje koda
09:44
is really, really important, and if we
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je zaista vrlo važno
09:46
can understand the code,
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i ako razumijemo kod,
09:48
the language of the brain, things become
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to jest jezik mozga, stvari postaju
09:50
possible that didn't seem obviously
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moguće iako to ranije nijesu bile.
09:52
possible before. Thank you.
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Hvala vam.
09:54
(Applause)
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(Aplauz)
ABOUT THE SPEAKER
Sheila Nirenberg - NeuroscientistSheila Nirenberg studies how the brain encodes information -- possibly allowing us to decode it, and maybe develop prosthetic sensory devices.
Why you should listen
Sheila Nirenberg is a neuroscientist/professor at Weill Medical College of Cornell University, where she studies neural coding – that is, how the brain takes information from the outside world and encodes it in patterns of electrical activity. The idea is to be able to decode the activity, to look at a pattern of electrical pulses and know what an animal is seeing or thinking or feeling. Recently, she’s been using this work to develop new kinds of prosthetic devices, particularly ones for treating blindness.
Sheila Nirenberg | Speaker | TED.com