Sheila Nirenberg: A prosthetic eye to treat blindness

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.

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.

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.

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.

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.

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.

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.

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?

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.

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.

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 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.

(Applause)