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.
Ja izučavam kako mozak procesuira informacije. Tj, kako preuzima informaciju iz spoljašnjeg svijeta i prevodi je u obrazac električne aktivnosti, i kako zatim koristi ostale obrasce i dopušta vam da vidite, čujete, posežete za predmetima. Ja sam u suštini naučnik, ne kliničar, ali posljednjih godinu i po dana počela sam da se prebacujem, da koristim to što smo naučili o ovim obrascima aktivnosti kako bismo razvili proteze, i ono što danas želim da vam pokažem je primjer toga. Ovo je zapravo naš prvi upad na ovu teritoriju. To je razvoj proteze za liječenje sljepila.
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.
Pa da vas uputim u tu problematiku. U Sjedinjenim Državama živi 10 miliona ljudi i još više širom svijeta koji su slijepi ili se suočavaju sa nekom drugom vrstom oboljenja retine, oboljenja kao [to je makularna degeneracija, i jako malo se može za njih učiniti. Postoje neki farmakološki tretmani, ali su oni uspješni na malom broju populacije. I tako je za većinu pacijenata najbolja nada za povratak vida upravo proteza. Problem je u tome što postojeće proteze ne rade baš najbolje. Još uvijek su dosta ograničene u pogledu vizuelnih mogućnosti koje obezbjeđuju. Na primjer, sa ovim uređajem, pacijent može vidjeti jednostavne stvari kao jasno osvjetljenje i jake kontrastne ivice, nešto više vrlo teško, tako da za sad ništa što je blisko normalnom vidu.
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.
Tako da ono što hoću danas da vam pokažem je uređaj na kome smo radili za koji smatram da ima potencijala da premosti razliku, da bude mnogo efikasniji i htjela sam da vam pokažem kako radi. U redu, dozvolite mi da se malo povučem i pokažem vam kako normalna retina radi kako biste uvidjeli problem koji smo pokušavali da riješimo. Ovdje imate retinu Dakle imate sliku, retina i mozak. Kad gledate u nešto, kao u ovu sliku ili bebino lice, to ulazi u vaše oko i pada na vašu retinu, na ćelije prvog reda, fotoreceptore. Zatim se uključuje retinalno električno kolo, srednji dio, obrađuje to i ono zapravo izvodi operaciju pri kojoj obrađuje informaciju i prevodi je u kod. A taj kod je u obliku mreže električnih impulsa koji se šalju u mozak tako da je ključna stvar da slika na kraju bude prevedena u kod. Kada kažem kod ja bukvalno mislim kod. Kao ova mreža signala ovdje koja u stvari znači "bebino lice" i kada mozak primi ovaj obrazac signala, odmah zna šta je tamo, tamo je bebino lice i kad bi dobilo drugačiji obrazac znalo bi da se tamo nalazi recimo pas ili neki drugi obrazac koji bi predstavljao kuću. Kako bilo, znate na šta mislim.
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.
Naravno, u stvarnom životu je to dinamičnije u smislu da se konstantno mijenja pa se i obrasci mijenjaju svo vrijeme jer se i svijet koji gledamo stalno mijenja. Tako da je to dosta komplikovana stvar. Imate ovu mrežu signala koji dolaze iz vašeg oka svake milisekunde kazujući vašem mozgu šta to zapravo gleda. Šta se dešava kada osoba dobije oboljenje retine kao što je makularna degeneracija? Ono što se dešava je da umiru ćelije prednjeg reda fotoreceptori umiru, i nakon nekog vremena sve druge ćelije i električno kolo koje je povezano sa njima, takođe umire. I sve tako dok ne ostanu jedino ove ćelije ovdje, output ćelije koje šalju signale u mozak ali zbog te degeneracije one ne šalju više nikakve signale jer ne primaju nikakve dolazne informacije i onda mozak više ne dobija nikakve vizuelne informacije, to jest, on ili ona je slijepa.
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.
Dakle rješenje problema bi bilo da se napravi uređaj koji imitira rad kola prvog reda i šalje signale retinalnim ćelijama trećeg reda kako bi one mogle da nastave svoj posao slanja signala mozgu. To je ono na čemu smo mi zapravo radili i to je ono šta radi naša proteza. Dakle ona se sastoji iz dva dijela, koja zovemo koder i konvertor. I tako koder radi ovo o čemu sam pričala: imitira rad ćelija prednjeg reda, dakle uzima slike i konvertuje ih u retinalni kod. A onda konvertor preko ćelija trećeg reda šalje kod gore u mozak, i rezultat je retinalna proteza koja može da izvršava normalnu funkciju retine. Dakle potpuno slijepa retina, čak i ona koja uopšte nema ćelije prednjeg reda, nema fotoreceptore, može sada slati normalne signale, signale koje mozak razumije. Nijedan drugi uređaj nije bio u stanju da ovo odradi.
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.
U redu, sada ću samo u par rečenica da kažem nešto o koderu i šta on radi, jer je zaista bitno i vrlo interesantno i nekako kul. Možda "kul" nije prava riječ, ali znate na šta mislim. Dakle, ono šta on radi jeste da zamjenjuje retinalno kolo sa setom jednačina koje možemo implementirati na čipu. Dakle to je samo matematika. Drugim riječima, mi ne zamjenjujemo bukvalno djelove retine. Niti pravimo neki mini uređaj za jedan ili drugi tip ćelija. Mi samo rezimiramo šta retina radi sa setom jednačina. I tako, jednačine služe kao neka šifrovana knjiga. Slika ulazi, prolazi kroz jednačine, i izlazi kao električni signal, kakav bi normalna retina proizvela.
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.
A sada mi dozvolite da sa riječi pređem na djela i pokažem vam da zapravo možemo stvoriti normalan output i koje bi bile njegove implikacije. Ovdje imamo 3 seta okidajućih obrazaca. Gornji je iz zdrave životinje, srednji je iz slijepe životinje koja je liječena sa koder - konvertor uređajem i donja je iz slijepe životinje liječene običnom protezom. Dakle donja je proizvod uređaja koji se trenutno koristi a zapravo je napravljena od svjetlosnog detektora ali ne i kodera. Tu smo zapravo prikazivali film sa svakodnevnim stvarima ljudima, bebama, klupama iz parkova znate već, obične stvari i snimali smo odgovore sa retine ovih 3 grupa životinja. Čisto da vas orjentišem, svaka slika pokazuje mrežu od par ćelija i baš kao na prethodnom slajdu svaki red je druga ćelija, i ja sam malo smanjila signale i istanjila ih kako bih vam pokazala duži niz podataka.
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?
I kao što vidite, mreže kod slijepih životinja koje imaju koder-konvertor prilično se podudaraju sa normalnim mrežama - nije baš savršeno ,ali je dosta dobro - a kod slijepih životinja sa običnom protezom odgovori nisu baš dobri. Tako da kod obične proteze ćelije šalju signale, ali ne toliko uspješno kao normalne jer ne posjeduju pravi kod. Koliko je ovo važno? Šta je potencijalni uticaj na pacijentovu sposobnost vida? Pokazaću vam jedan eksperiment koji nudi odgovor na to, ali naravno imam još puno podataka o tome pa ako da ste zainteresovani, sa zadovoljstvom ću vam pokazati još. Dakle, eksperiment je nazvan rekonstruktivni eksperiment. Uzeli smo jedan vremenski period iz ovih snimaka i tražili da vidimo šta je retina zapravo vidjela u tom periodu. Da li možemo rekonstruisati šta je retina vidjela iz odgovora mreže signala?
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.
I tako smo uporedili odgovore iz obične proteze i odgovore sa koder-konvertor proteze. Pokazaću vam, i prvo ću početi sa običnom protezom. Vidite da je prilično ograničavajuće, jer mreža signala nije pravilno kodirana, oni su vrlo ograničavajući u tome šta vam mogu reći šta je tamo vani. Možete vidjeti nešto tamo, ali nije jasno šta je to u stvari, i to nas zapravo vraća nazad na moju priču na početku da sa običnom protezom pacijenti mogu vidjeti kontrastne ivice, mogu vidjeti svjetlost ali ništa više od toga. Pa kakva je to slika? To je bilo bebino lice. A kakva je bila sa našom metodom uz pomoć kodiranja? Vidite da je mnogo bolja. Ne samo da možete prepoznati bebino lice, već prepoznajete da je to lice tačno ove bebe, što je izuzetno zahtjevan zadatak. Dakle lijevo je koder sam a desno je sa slijepe retine dakle koder i konverter. Ali u stvari koder je bitan jer možete koristiti koder sa različitim konverterom.
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.
Ovo je zapravo prvi sa kojim smo pokušali. Želim samo nešto reći o običnoj protezi. Prvi put kada je izašla, bila je uzbudljiva sama ideja da da uopšte dobijete neki odgovor sa slijepe retine. Ali postojao je taj ograničavajući faktor, problematika šifre i kako dobiti bolji odgovor ćelije, dobiti normalni odgovor, i to je bio naš doprinos. Sada samo da rezimiram kao što sam ranije spomenula ja imam i drugih podataka ako ste zainteresovani, ali sam htjela da vam izložim osnovnu ideju o sposobnosti komunikacije sa mozgom njegovim jezikom i o mogućnosti da se to uopšte ostvari. To je drugačije od motorne proteze kada komunikacija ide iz mozga ka uređaju. Ovdje moramo da komuniciramo iz spoljašnje sredine ka mozgu i da to ima smisla, da ga mozak razumije.
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.
I na kraju sam htjela da istaknem da generalizujem ideju. Dakle sama strategija koju smo mi ovdje koristili, da nađemo kod za retinu, možemo je koristiti i za kodiranje drugih polja, na primjer za auditorni sistem i za motorni sistem, to jest za liječenje gluvoće i za motorne poremećaje. Na isti način na koji smo uspjeli da prevaziđemo oštećenje rada retine i dođemo do njenih unutrašnjih ćelija, možemo prevazići oštećenje kohlee uha kako bismo došli do slušnog nerva ili oštećenja polja u motornom korteksu, premošćavajući praznine nastale šlogom.
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.
Željela bih da završim sa porukom da razumijevanje koda je zaista vrlo važno i ako razumijemo kod, to jest jezik mozga, stvari postaju moguće iako to ranije nijesu bile. Hvala vam.
(Applause)
(Aplauz)