TEDMED 2011
Sheila Nirenberg: A prosthetic eye to treat blindness
Sheila Nirenberg: Prostetično oko za zdravljenje slepote
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Na TEDMED-u Sheila Nirenberg predstavi drzen način vrnitve vida osebam z določenimi tipi slepote. Metoda zavzema povezavo na optični živec in pošiljanje signalov iz kamere neposredno v možgane.
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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Pri svojem delu preučujem, kako možgani
00:17
information. That is, how it takes
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obdelujejo podatke oz. kako podatke
00:19
information in from the outside world, and
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iz zunanjega sveta spremenijo
00:21
converts it into patterns of electrical activity,
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v vzorce električne dejavnosti
00:23
and then how it uses those patterns
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in kako nam preko teh vzorcev
00:25
to allow you to do things --
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omogočajo, da vidimo,
00:27
to see, hear, to reach for an object.
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slišimo ali sežemo po predmetu.
00:29
So I'm really a basic scientist, not
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Moje preučevanje je zastavljeno osnovno,
00:31
a clinician, but in the last year and a half
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ne klinično, a v zadnjem letu in pol
00:33
I've started to switch over, to use what
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sem se preusmerila v uporabo
00:35
we've been learning about these patterns
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ugotovitev o teh vzorcih delovanja
00:37
of activity to develop prosthetic devices,
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za razvoj prostetičnih naprav
00:40
and what I wanted to do today is show you
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in danes bi vam rada predstavila
00:42
an example of this.
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primer take naprave.
00:44
It's really our first foray into this.
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To je naš prvi tak podvig.
00:46
It's the development of a prosthetic device
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Gre za razvoj prostetične naprave
00:48
for treating blindness.
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za zdravljenje slepote.
00:50
So let me start in on that problem.
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Naj začnem s tem problemom.
00:52
There are 10 million people in the U.S.
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V ZDA je 10 milijonov ljudi,
00:54
and many more worldwide who are blind
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po svetu pa še mnogo več, ki so slepi
00:56
or are facing blindness due to diseases
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ali pa se s slepoto soočajo zaradi
00:58
of the retina, diseases like
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bolezni očesne mrežnice,
01:00
macular degeneration, and there's little
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kot je degeneracija rumene pege,
01:02
that can be done for them.
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a zanje ni veliko upanja.
01:04
There are some drug treatments, but
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Obstajajo sicer zdravila, ki pa
01:06
they're only effective on a small fraction
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učinkujejo le na majhnem delu ljudi.
01:08
of the population. And so, for the vast
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Za veliko večino bolnikov je torej
01:10
majority of patients, their best hope for
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največ upanja za obnovo vida
01:12
regaining sight is through prosthetic devices.
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prav v prostetičnih napravah.
01:14
The problem is that current prosthetics
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Težava pa je, da trenutno obstoječe
01:16
don't work very well. They're still very
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protetične naprave niso zelo učinkovite.
01:18
limited in the vision that they can provide.
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Podobe, ki jih omogočajo, so še vedno zelo omejene.
01:20
And so, you know, for example, with these
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Preko takih naprav lahko
01:22
devices, patients can see simple things
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bolniki vidijo preproste stvari, kot so
01:24
like bright lights and high contrast edges,
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močna svetloba ali visoki kontrasti,
01:26
not very much more, so nothing close
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a ne veliko več, zato ne omogočajo
01:28
to normal vision has been possible.
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primerljivosti z normalnim vidom.
01:31
So what I'm going to tell you about today
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Danes vam bom pripovedovala o napravi,
01:33
is a device that we've been working on
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ki jo razvijamo in za katero menim,
01:35
that I think has the potential to make
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da lahko predstavlja napredek
01:37
a difference, to be much more effective,
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in je precej bolj učinkovita,
01:39
and what I wanted to do is show you
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zato bi vam rada pokazala, kako deluje.
01:41
how it works. Okay, so let me back up a
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Za začetek pa naj pokažem,
01:43
little bit and show you how a normal retina
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kako deluje zdrava očesna mrežnica,
01:45
works first so you can see the problem
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da boste videli težavo,
01:47
that we were trying to solve.
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ki jo poskušamo rešiti.
01:49
Here you have a retina.
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V sredini je očesna mrežnica.
01:51
So you have an image, a retina, and a brain.
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Imamo sliko, mrežnico in možgane.
01:53
So when you look at something, like this image
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Ko nekaj vidite, v tem primeru sliko
01:55
of this baby's face, it goes into your eye
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otroškega obraza, se podoba projicira
01:57
and it lands on your retina, on the front-end
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na vaši mrežnici, na prvi vrsti celic
01:59
cells here, the photoreceptors.
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oz. fotoreceptorjih.
02:01
Then what happens is the retinal circuitry,
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Nato živčno vezje na mrežnici
02:03
the middle part, goes to work on it,
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oz. srednji del to podobo obdela,
02:05
and what it does is it performs operations
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z njo upravlja
02:07
on it, it extracts information from it, and it
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in iz nje zbere podatke,
02:09
converts that information into a code.
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ki jih spremeni v kodo.
02:11
And the code is in the form of these patterns
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Koda se v obliki vzorcev
02:13
of electrical pulses that get sent
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električnih signalov prenese v možgane,
02:15
up to the brain, and so the key thing is
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ključnega pomena je torej,
02:17
that the image ultimately gets converted
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da se podoba pretvori v kodo.
02:19
into a code. And when I say code,
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Izraz kodo v tem primeru
02:21
I do literally mean code.
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pomeni dobesedno to.
02:23
Like this pattern of pulses here actually means "baby's face,"
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Ta vzorec signalov pomeni "otroški obraz"
02:26
and so when the brain gets this pattern
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in ko ga možgani sprejmejo,
02:28
of pulses, it knows that what was out there
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izvejo, da smo videli
02:30
was a baby's face, and if it
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otroški obraz
02:32
got a different pattern it would know
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in bi ob drugačnem vzorcu izvedeli,
02:34
that what was out there was, say, a dog,
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da smo videli, na primer, psa,
02:36
or another pattern would be a house.
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ob spet drugačnem pa morda hišo.
02:38
Anyway, you get the idea.
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Razumete, kaj želim povedati.
02:40
And, of course, in real life, it's all dynamic,
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V resničnem življenju je seveda vse gibljivo
02:42
meaning that it's changing all the time,
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in se stalno spreminja,
02:44
so the patterns of pulses are changing
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zato se tudi vzorci signalov nenehno spreminjajo
02:46
all the time because the world you're
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hkrati s svetom, ki ga gledamo
02:48
looking at is changing all the time too.
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in ki se prav tako stalno spreminja.
02:51
So, you know, it's sort of a complicated
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Gre torej za zapleteno stvar.
02:53
thing. You have these patterns of pulses
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Ti vzorci signalov iz vaših oči
02:55
coming out of your eye every millisecond
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vsako milisekundo sporočajo
02:57
telling your brain what it is that you're seeing.
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vašim možganom, kaj vidite.
02:59
So what happens when a person
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Kaj pa se zgodi, ko oseba zboli za
03:01
gets a retinal degenerative disease like
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degenerativno boleznijo,
03:03
macular degeneration? What happens is
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kot je degeneracija rumene pege?
03:05
is that, the front-end cells die,
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V tem primeru celice v ospredju
03:07
the photoreceptors die, and over time,
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oz. fotoreceptorji odmrejo
03:09
all the cells and the circuits that are
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in sčasoma odmrejo tudi vse celice
03:11
connected to them, they die too.
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in vezja, ki so z njimi povezana.
03:13
Until the only things that you have left
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Na koncu ostanejo le še te celice,
03:15
are these cells here, the output cells,
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izhodne celice, ki pošiljajo
03:17
the ones that send the signals to the brain,
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signale možganom,
03:19
but because of all that degeneration
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a zaradi neaktivnih celic pred njimi
03:21
they aren't sending any signals anymore.
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ni več niti signalov.
03:23
They aren't getting any input, so
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Ker ničesar ne sprejemajo,
03:25
the person's brain no longer gets
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tudi možgani ne prejmejo
03:27
any visual information --
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nobenih vizualnih podatkov,
03:29
that is, he or she is blind.
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kar povzroči slepoto.
03:32
So, a solution to the problem, then,
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Rešitev tega problema bi torej bil
03:34
would be to build a device that could mimic
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razvoj naprave, ki bi posnemala
03:36
the actions of that front-end circuitry
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dejanja živčnih vezij v ospredju
03:38
and send signals to the retina's output cells,
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in pošiljala signale izhodnim celicam mrežnice,
03:40
and they can go back to doing their
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ki bi lahko nadaljevale z običajnim
03:42
normal job of sending signals to the brain.
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pošiljanjem signalov možganom.
03:44
So this is what we've been working on,
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S tem smo se torej ukvarjali
03:46
and this is what our prosthetic does.
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in tako deluje naša prostetična naprava.
03:48
So it consists of two parts, what we call
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Sestavljena je iz dveh delov, ki jim pravimo
03:50
an encoder and a transducer.
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kodirnik in pretvornik.
03:52
And so the encoder does just
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Naloga kodirnika je torej, kot rečeno,
03:54
what I was saying: it mimics the actions
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posnemanje dejavnosti sprednjih
03:56
of the front-end circuitry -- so it takes images
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vezij mrežnice -- sprejemanje podob
03:58
in and converts them into the retina's code.
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in njihovo pretvarjanje v kodo na mrežnici.
04:00
And then the transducer then makes the
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Pretvornik nato omogoči
04:02
output cells send the code on up
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izhodnim celicam,
04:04
to the brain, and the result is
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da pošljejo kodo v možgane,
04:06
a retinal prosthetic that can produce
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rezultat tega je torej prostetična mrežnica,
04:09
normal retinal output.
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ki lahko izvede običajen prenos podatkov na mrežnici.
04:11
So a completely blind retina,
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To omogoči tudi popolnoma slepi mrežnici,
04:13
even one with no front-end circuitry at all,
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celo taki brez sprednjih vezij,
04:15
no photoreceptors,
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brez fotoreceptorjev,
04:17
can now send out normal signals,
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da v možgane pošlje normalne signale,
04:19
signals that the brain can understand.
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ki jih lahko možgani razumejo.
04:22
So no other device has been able
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Nobena druga naprava
04:24
to do this.
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še ni tega omogočala.
04:26
Okay, so I just want to take
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Rada bi povedala še
04:28
a sentence or two to say something about
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stavek ali dva
04:30
the encoder and what it's doing, because
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o kodirniku in njegovem delu,
04:32
it's really the key part and it's
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saj gre za ključen del,
04:34
sort of interesting and kind of cool.
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ki je zanimiv in na nek način kul.
04:36
I'm not sure "cool" is really the right word, but
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Morda "kul" ni ravno prava beseda,
04:38
you know what I mean.
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a vseeno razumete, kaj želim povedati.
04:40
So what it's doing is, it's replacing
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Naloga kodirnika je torej, da nadomesti
04:42
the retinal circuitry, really the guts of
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bistvo živčnih vezij na mrežnici
04:44
the retinal circuitry, with a set of equations,
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z vrsto enačb,
04:46
a set of equations that we can implement
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ki jih lahko vnesemo na čip.
04:48
on a chip. So it's just math.
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Gre torej za čisto matematiko.
04:50
In other words, we're not literally replacing
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Z drugimi besedami, ne gre dobesedno za
04:53
the components of the retina.
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nadomeščanje sestavnih delov mrežnice.
04:55
It's not like we're making a little mini-device
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Ne razvijamo majčkene napravice
04:57
for each of the different cell types.
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za vsako od različnih tipov celic.
04:59
We've just abstracted what the
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Le povzeli smo način,
05:01
retina's doing with a set of equations.
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kako mrežnica upravlja vrsto enačb.
05:03
And so, in a way, the equations are serving
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Na nek način te enačbe predstavljajo
05:05
as sort of a codebook. An image comes in,
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neke vrste kodirno knjigo.
05:07
goes through the set of equations,
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Ko podoba vstopi, gre preko vrste enačb,
05:10
and out comes streams of electrical pulses,
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njen izid pa so tokovi električnih signalov,
05:12
just like a normal retina would produce.
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taki, kot bi nastali na zdravi mrežnici.
05:16
Now let me put my money
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Naj zdaj preidem od besed k dejanjem
05:18
where my mouth is and show you that
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in vam pokažem,
05:20
we can actually produce normal output,
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da lahko dejansko ustvarimo običajen podatek
05:22
and what the implications of this are.
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in kako lahko to uporabimo.
05:24
Here are three sets of
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Tu imamo tri različne vzorce signalov.
05:26
firing patterns. The top one is from
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Zgornji predstavlja signale pri zdravi živali,
05:28
a normal animal, the middle one is from
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srednji signale pri slepi, ki jo zdravimo
05:30
a blind animal that's been treated with
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z našo napravo s kodirnikom in pretvornikom,
05:32
this encoder-transducer device, and the
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spodnja pa predstavlja
05:34
bottom one is from a blind animal treated
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signale pri slepi živali, ki jo zdravimo
05:36
with a standard prosthetic.
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z običajno prostetično napravo.
05:38
So the bottom one is the state-of-the-art
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Gre za najsodobnejšo prostetično
05:40
device that's out there right now, which is
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napravo, ki je trenutno na voljo,
05:42
basically made up of light detectors,
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in ki jo sestavljajo detektorji svetlobe,
05:44
but no encoder. So what we did was we
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ne pa tudi kodirnik.
05:46
presented movies of everyday things --
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Predvajali smo posnetke vsakdanjih stvari --
05:48
people, babies, park benches,
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ljudi, otrok, klopi v parku --
05:50
you know, regular things happening -- and
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stvari okoli nas
05:52
we recorded the responses from the retinas
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in beležili odzive mrežnic
05:54
of these three groups of animals.
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teh treh skupin živali.
05:56
Now just to orient you, each box is showing
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Za boljšo predstavo, vsak okvir prikazuje
05:58
the firing patterns of several cells,
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vzorce signalov večih celic
06:00
and just as in the previous slides,
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in tako kot ste videli prej,
06:02
each row is a different cell,
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vsaka vrsta predstavlja drugačne celice,
06:04
and I just made the pulses a little bit smaller
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signali pa so nekoliko skrajšani in zoženi,
06:06
and thinner so I could show you
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da lahko prikažem
06:09
a long stretch of data.
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širši obseg podatkov.
06:11
So as you can see, the firing patterns
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Kot vidite, vzorci signalov pri
06:13
from the blind animal treated with
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slepi živali, ki jo zdravimo s sistemom
06:15
the encoder-transducer really do very
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kodirnika in pretvornika,
06:17
closely match the normal firing patterns --
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so zelo podobni običajnim vzorcem --
06:19
and it's not perfect, but it's pretty good --
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niso identični, a je podobnost velika --
06:21
and the blind animal treated with
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medtem ko se signali pri živali,
06:23
the standard prosthetic,
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zdravljeni z običajnimi prostetiki,
06:25
the responses really don't.
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od zdravih precej razlikujejo.
06:27
And so with the standard method,
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Pri običajni metodi
06:30
the cells do fire, they just don't fire
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celice širijo signale,
06:32
in the normal firing patterns because
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ki pa ne tvorijo običajnega vzorca signalov,
06:34
they don't have the right code.
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ker nimajo prave kode.
06:36
How important is this?
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Kako pomembno je to?
06:38
What's the potential impact
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Kako lahko to odkritje vpliva
06:40
on a patient's ability to see?
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na bolnikove možnosti, da spet vidi?
06:43
So I'm just going to show you one
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Namesto odgovora vam bom pokazala
06:45
bottom-line experiment that answers this,
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bistveni poskus,
06:47
and of course I've got a lot of other data,
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seveda pa imam še veliko drugih podatkov,
06:49
so if you're interested I'm happy
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ki jih z veseljem delim z vami,
06:51
to show more. So the experiment
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če vas zanimajo.
06:53
is called a reconstruction experiment.
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Gre za poskus rekonstrukcije.
06:55
So what we did is we took a moment
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Pri tem smo se osredotočili na
06:57
in time from these recordings and asked,
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določen trenutek v teh posnetkih in se vprašali,
07:00
what was the retina seeing at that moment?
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kaj v tem trenutku mrežnica zaznava?
07:02
Can we reconstruct what the retina
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Ali lahko obnovimo podatke,
07:04
was seeing from the responses
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ki jih mrežnica zazna
07:06
from the firing patterns?
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iz odziva na vzorce signalov?
07:08
So, when we did this for responses
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Zanimali so nas odzivi
07:11
from the standard method and from
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pri običajni metodi
07:14
our encoder and transducer.
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ter pri našem kodirniku in pretvorniku.
07:16
So let me show you, and I'm going to
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Za začetek naj vam pokažem
07:18
start with the standard method first.
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izsledke pri običajni metodi.
07:20
So you can see that it's pretty limited,
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Vidite, da je podoba zelo nejasna
07:22
and because the firing patterns aren't
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in ker vzorci signalov
07:24
in the right code, they're very limited in
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niso v pravi kodi,
07:26
what they can tell you about
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možganom zelo omejeno poročajo o videnem.
07:28
what's out there. So you can see that
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Vidite, da gre za nek predmet,
07:30
there's something there, but it's not so clear
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a ne veste, za kaj točno gre,
07:32
what that something is, and this just sort of
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kar zopet povzema to,
07:34
circles back to what I was saying in the
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o čemer sem govorila na začetku,
07:36
beginning, that with the standard method,
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namreč da pri običajni metodi
07:38
patients can see high-contrast edges, they
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bolniki zaznavajo le visoke kontraste
07:40
can see light, but it doesn't easily go
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in svetlobo, največkrat pa je to vse.
07:42
further than that. So what was
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Kaj je torej na sliki?
07:44
the image? It was a baby's face.
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Otroški obraz.
07:47
So what about with our approach,
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Kaj pa se zgodi pri našem pristopu
07:49
adding the code? And you can see
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in uporabi dodane kode?
07:51
that it's much better. Not only can you
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Vidite, da je dosti bolje. Ne samo,
07:53
tell that it's a baby's face, but you can
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da zaznate, da gre za otroški obraz,
07:55
tell that it's this baby's face, which is a
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pač pa, da gre za točno določenega otroka,
07:57
really challenging task.
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kar je še posebej zahtevna naloga.
07:59
So on the left is the encoder
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Slika v sredini na levi predstavlja le kodirnik,
08:01
alone, and on the right is from an actual
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desna slika pa dejanski prikaz na slepi mrežnici,
08:03
blind retina, so the encoder and the transducer.
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torej kombinacijo kodirnika in pretvornika.
08:05
But the key one really is the encoder alone,
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Ključen pa je predvsem kodirnik,
08:07
because we can team up the encoder with
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saj ga lahko priključimo na
08:09
the different transducer.
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drugačen pretvornik.
08:11
This is just actually the first one that we tried.
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Tu vidimo le primer prvega, ki smo ga uporabili.
08:13
I just wanted to say something about the standard method.
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Želela bi povedati nekaj o običajni metodi.
08:15
When this first came out, it was just a really
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Ko so jo razvili, je bila navdušujoča
08:17
exciting thing, the idea that you
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misel, da se lahko omogoči
08:19
even make a blind retina respond at all.
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odzivanje celo slepi mrežnici.
08:22
But there was this limiting factor,
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Obstajala pa je tudi omejitev,
08:25
the issue of the code, and how to make
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in sicer problem kode ter vprašanje,
08:27
the cells respond better,
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kako izboljšati odziv celic,
08:29
produce normal responses,
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da bi bil čim bližje običajnemu
08:31
and so this was our contribution.
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in temu smo se posvetili mi.
08:33
Now I just want to wrap up,
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Želela bi povzeti povedano
08:35
and as I was mentioning earlier
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in -- kot že rečeno --
08:37
of course I have a lot of other data
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lahko z vami delim še veliko drugih podatkov,
08:39
if you're interested, but I just wanted to give
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a danes sem želela le predstaviti
08:41
this sort of basic idea
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to osnovno zamisel
08:43
of being able to communicate
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sposobnosti sporazumevanja
08:46
with the brain in its language, and
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z možgani v njihovem jeziku
08:48
the potential power of being able to do that.
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in pomen te možnosti za bolnike.
08:51
So it's different from the motor prosthetics
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Gre torej za drugačen način od motoričnih prostetikov,
08:53
where you're communicating from the brain
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pri katerih sporazumevanje poteka
08:55
to a device. Here we have to communicate
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od možganov do naprave.
08:57
from the outside world
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V našem primeru pa iz okolice pošiljamo
08:59
into the brain and be understood,
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signale v možgane,
09:01
and be understood by the brain.
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kjer jih dešifriramo in razumemo.
09:03
And then the last thing I wanted
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Kot zaključek
09:05
to say, really, is to emphasize
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sem želela izpostaviti
09:07
that the idea generalizes.
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možnost posplošitve te metode.
09:09
So the same strategy that we used
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Enako strategijo, kot smo jo uporabili
09:11
to find the code for the retina we can also
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za iskanje kode za mrežnico,
09:13
use to find the code for other areas,
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lahko uporabimo za iskanje kode za druga področja,
09:15
for example, the auditory system and
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na primer slušni ali motorični sistem,
09:17
the motor system, so for treating deafness
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torej za zdravljenje gluhosti
09:19
and for motor disorders.
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in motoričnih okvar.
09:21
So just the same way that we were able to
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Na enak način, kot smo
09:23
jump over the damaged
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preskočili okvarjena vezja v mrežnici
09:25
circuitry in the retina to get to the retina's
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in prešli na izhodne celice mrežnice,
09:27
output cells, we can jump over the
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lahko tudi preskočimo
09:29
damaged circuitry in the cochlea
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okvarjena vezja v ušesnem polžu
09:31
to get the auditory nerve,
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in preidemo na slušne živce,
09:33
or jump over damaged areas in the cortex,
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ali pa preskočimo okvarjena področja v
09:35
in the motor cortex, to bridge the gap
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motorični skorji možganov in tako
09:38
produced by a stroke.
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premagamo vrzel, nastalo po možganski kapi.
09:40
I just want to end with a simple
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Želela bi končati s preprostim sporočilom,
09:42
message that understanding the code
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da je razumevanje kode
09:44
is really, really important, and if we
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resnično izjemnega pomena
09:46
can understand the code,
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in če razumemo kodo
09:48
the language of the brain, things become
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oz. jezik možganov, lahko omogočimo stvari,
09:50
possible that didn't seem obviously
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ki se prej niso zdele mogoče.
09:52
possible before. Thank you.
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Hvala lepa.
09:54
(Applause)
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(Aplavz)
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