Here you have a retina.

So you have an image, a retina, and a brain.

The image projected in the retina is inverted.

The retina chip extracts four different kinds of information.

In other words, we're not literally replacing the components of the retina.

We've just abstracted what the retina's doing with a set of equations.

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.

But when it's moving back and forth, the retina picks up these changes.

The retina chip that we designed sits behind this lens here.

This experience taught me to empathize more with my patients, and especially those with retinal diseases.

Can we reconstruct what the retina was seeing from the responses from the firing patterns?

So what we did is we took a moment in time from these recordings and asked, what was the retina seeing at that moment?

What you notice here is that these snapshots taken from the output of the retina chip are very sparse, right?

When this first came out, it was just a really exciting thing, the idea that you even make a blind retina respond at all.

And I'm going to show you a system that we designed to model the retina, which is a piece of brain that lines the inside of your eyeball.

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 on the left is the encoder alone, and on the right is from an actual blind retina, so the encoder and the transducer.

Images will be written directly to our retina, providing full immersion virtual reality, augmented real reality. We'll be interacting with virtual personalities.

But sometime ago, through the help of an opthamologist colleague of mine, Carmen Puliafito, who developed a laser scanner of the retina, I found out the the following.

Heart disease, stroke, diabetes, spinal cord injury, muscular dystrophy, retinal eye diseases are any of these conditions relevant, personally, to you?

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.

Light enters, hits the back of the retina, and is circulated, most of which is streamed to the very back of the brain, at the primary visual cortex.

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 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.

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And the chip I'm going to show you a video that the silicon retina put out of its output when it was looking at Kareem Zaghloul, who's the student who designed this chip.

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.

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.

Instead of doing this in software, or doing those kinds of algorithms, we went and talked to neurobiologists who have actually reverse engineered that piece of brain that's called the retina.

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.

The SBS hypothesis attributed the triad of symptoms to the physical rupture of blood vessels on the brain s surface and in the retina, and the tearing of nerve fibers within the brain.

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, 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 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.

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.

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.

And this is the same thing you see when people compress video to send they want to make it very sparse, because that file is smaller. And this is what the retina is doing, and it's doing it just with the circuitry, and how this network of neurons that are interacting in there, which we've captured on the chip.