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