[Decoding the Retina: Neural Engineering and the Future of Vision Restoration]-[Dr. E.J. Chichilnisky: How the Brain Works, Curing Blindness & How to Navigate a Career Path]
Huberman Lab · C1 · 2024-03-18
Health
📋 Summary
Decoding the Retina: Neural Engineering and the Future of Vision Restoration
In this episode of the Huberman Lab, Dr. Andrew Huberman hosts Dr. E.J. Chichilnisky, a pioneer in neurosurgery and neuroscience, to discuss the mechanisms of visual perception and the revolutionary potential of neural prosthetics.
The Architecture of Vision: The Retina as a Neural Processor
Dr. Chichilnisky highlights the retina as the "best understood piece of the brain," serving as the primary gateway for visual information. The process begins with photoreceptor cells, which act as "pixel detectors," transforming light energy into electrical signals. This information then passes to a second layer responsible for mixing, matching, and comparing signals. Finally, the retinal ganglion cells (RGCs) act as the "messengers," transmitting these processed signals to the brain.
Dr. Chichilnisky explains that there are approximately 20 distinct types of RGCs in humans. He uses a "Photoshop filter" analogy to describe how these cells function: each type represents the entire visual scene but extracts specific features, such as movement, color, or spatial detail. The brain then assembles these disparate "movies" into a cohesive visual experience.
Neuroengineering and Vision Restoration
A central focus of the discussion is the application of this knowledge to neural prostheses. Current retinal implants are limited, often providing only crude sensations of light. Dr. Chichilnisky argues that these devices fail because they ignore the complex, cell-type-specific nature of the retina. He likens the current approach to an orchestra where the conductor has scattered the sheet music, resulting in "cacophony" rather than a symphony.
To bridge this gap, Dr. Chichilnisky’s lab utilizes a high-density, 512-electrode array—a "bed of nails" that records electrical activity from the retina. By using "random garbage" (flickering checkerboard patterns) as an unbiased stimulus, his team can identify how specific RGC types respond to the world. Their goal is to build a "smart device" that:
- Records electrical activity to identify cell types in a specific patient.
- Calibrates by establishing how electrodes interact with those cells.
- Stimulates the RGCs with high precision, mimicking natural signals to restore high-quality vision.
Beyond Restoration: Visual Augmentation and Future Frontiers
The potential for this technology extends beyond medical rehabilitation. Dr. Chichilnisky discusses the prospect of neural augmentation, where prosthetic devices could allow humans to perceive information currently invisible to the biological eye, such as infrared light or enhanced resolution. He draws a parallel to the ability to drive while listening to a conversation, suggesting that if we can independently modulate parallel neural pathways, we could stream additional visual information into the brain without cognitive interference.
The Importance of Precision in Neuroscience
Dr. Huberman and Dr. Chichilnisky contrast this high-precision approach with non-specific interventions like traditional pharmaceuticals or electroconvulsive therapy. While the latter can provide a "reboot" for the brain, they lack the specificity required for refined cognitive enhancement. By focusing on the retina, researchers are establishing the foundational tools for the future of neuroengineering, eventually hoping to apply these techniques to other complex brain regions like the hippocampus for memory enhancement.
Ultimately, Dr. Chichilnisky emphasizes the responsibility of scientists to develop these technologies thoughtfully. As the field moves from "sci-fi" to "sci," the goal remains to harness our understanding of the nervous system to improve human health and expand the boundaries of human experience, ensuring that such powerful tools are used for the benefit of society.
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📖 Transcript
Welcome to the Huberman Lab podcast where we discuss science and science-based tools for everyday life.
I'm Andrew Huberman and I'm a professor of neurobiology and ophthalmology at Stanford School of Medicine.
My guest today is Dr. E.J. Chicholnysky.
Dr. E.J. Chicholnysky is a professor of neurosurgery, ophthalmology, and neuroscience at Stanford University.
He is one of the world's leading researchers trying to understand how we see the world around us,
that is how visual perception occurs, and then applying that information directly to the design of neural prostheses,
literally robotic eyes that can allow blind people to see once again.
Today's discussion is a very important one for anyone who wants to understand how their brain works.
Indeed, E.J. spells out in very clear terms exactly how the world around us is encoded by the neuron
and the nerve cells within our brain in order to create these elaborate visual images that we essentially see within our minds.
And with that understanding, he explains how that can be applied to engineer specific robotic AI and machine learning devices
that can allow human brains not only to see once again in the blind, but also to perceive things that typical human brains can't,
and indeed for memory to be enhanced and for cognition to be enhanced. This is the direction that neuroscience is going.
And in the course of today's discussion, we have the opportunity to learn from the world expert in these topics
where the science is now and where it is headed.
During today's discussion, we also get heavily into the topic of how to select one's professional and personal path.
And indeed, you'll learn from Dr. Chicholnicki that he has a somewhat unusual path, both into science and through science.
So for those of you that believe that everyone that's highly accomplished in their career always knew exactly what they wanted to do at every stage,
you'll soon learn that that is absolutely not the case with E.J.
He describes wandering through three different graduate programs, taking several years off from school in order to dance.
Yes, you heard that correctly, to dance, and how that wandering, and indeed dancing, helped him decide exactly what he wanted to do with his professional life,
and exactly what specific problems to try and tackle in the realm of neuroscience and medicine.
It's a discussion that I'm certain that everybody, scientist or no, young or old, can benefit from, and can apply the specific tools that E.J. describes in their own life and pursuits.
Before we begin, I'd like to emphasize that this podcast is separate from my teaching and research roles at Stanford.
It is, however, part of my desire and effort to bring zero cost to consumer information about science and science-related tools to the general public.
In keeping with that theme, I'd like to thank the sponsors of today's podcast.
Our first sponsor is 8-Sleep.
8-Sleep makes smart mattress covers with cooling, heating, and sleep tracking capacity.
I've spoken many times before on this another podcast about the fact that sleep is the foundation of mental health, physical health, and performance.
One of the key aspects to getting a great night's sleep is to control the temperature of your sleeping environment.
That's because in order to fall and stay deeply asleep, your body temperature actually has to drop by about 1-3 degrees,
and in order to wake up in the morning feeling refreshed, your body temperature actually has to increase by about 1-3 degrees.
8-Sleep makes it extremely easy to control the temperature of your sleeping environment at the beginning, middle, and throughout the night and when you wake up in the morning.
I've been sleeping on an 8-Sleep mattress cover for nearly three years now, and it has dramatically improved my sleep.
If you'd like to try 8-Sleep, you can go to 8-Sleep.com slash Huberman to save $150 off their pod-3 cover.
8-Sleep currently ships to the USA, Canada, UK, select countries in the EU, and Australia.
Again, that's 8-Sleep.com slash Huberman.
Today's episode is also brought to us by Roka.
Roka makes eyeglasses and sunglasses that are of the absolute highest quality.
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Today's episode is also brought to us by BetterHelp.
BetterHelp offers professional therapy with a licensed therapist carried out online.
I've been going to therapy for well over 30 years. Initially, I didn't have a choice. It was a condition of being allowed to stay in school.
But pretty soon, I realized that therapy is extremely valuable. In fact, I consider doing regular therapy just as important as getting regular exercise, including cardiovascular exercise and resistance training, which, of course, I also do every week.
The reason I know therapy is so valuable is that if you can find a therapist with whom you can develop a really good rapport, you not only get terrific support for some of the challenges in your life, but you also can derive tremendous insights from that therapy.
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So, I think that's a good idea.
If you'd like to try BetterHelp, go to BetterHelp.com slash huberman to get 10% off your first month. Again, that's BetterHelp.com slash huberman.
And now for my discussion with Dr. E.J. Chicholnysky.
Welcome. Good to see you. For the audience, we are friends. We go way back. E.J. has been a few years or more ahead of me in the science game.
And the best way to describe you and your work, E.J. is here in astronaut. You go places. No one else has been willing to go before. He developed new technologies in order to do that.
All with the bold mission of trying to understand how the nervous system, which, of course, includes the brain, works and how to make it better with engineering.
So today, we are going to get into all of that, but just to start off and get everybody on the same page, maybe we could just take a moment and talk about the brain and nervous system.
And what it consists of that allows it to do all the sorts of things that we're going to get into, like see things in our environment and respond to those things in our environment.
So at risk of throwing too much at you right out the gate, what's your one to five minute version of how the brain works?
Oh, I don't have a one to five minute version of how the brain works, but I can tell you how I think vision is initiated in the brain.
And you and I go back a long way. So we have a lot of common understanding about this, but I'll narrate it from scratch if that makes sense.
So vision is initiated in the retina of the eye, which is a sheet neural tissue at the rear of the eye that captures the light that is incident on the eye that comes in through the through the eye transforms that light into electrical signals processes those electrical signals in interesting ways and changes them up.
And then sends that visual information to the brain where it is used to bring about our sense of vision.
And you asked me about the one to five minute version of how the brain works. I don't know, but I do know that the brain receives all these patterns of electrical activity coming out of these nerve cells in the retina and somehow assembles that into our visual experience, whether that be responding to things coming at us or our circadian rhythms.
That that govern our sleep and behavior or identifying objects for prey or avoiding predators or appreciating beauty.
And what we know is that the brain receives a fantastically complex set of signals from the retina and puts that all together into our visual experience. And we are very visual creatures, obviously.
So I think that's a big part of how the brain works because so much of what we do revolves around vision revolves around how the brain puts together these signals coming out of the retina.
And I would love to understand how that works at the moment. I don't. And what we're trying to do is get a really complete understanding of how that begins in the retina and then how we can restore it in those who've lost sight.
Why focus on this issue in the retina? This thin set of layers of neurons that line the back of the eye. Why explore vision there? I mean, obviously there are centers within the brain that of course contain neurons, nerve cells that are involved in vision.
If one wants to understand visual perception, and I agree, by the way, that visual perception is one of the most dominant forces in the quality and experience of our life.
Why focus on the retina? Why not focus on the visual cortex or the visual thalamus? I mean, what's so special about the retina?
Well, we have to focus on all of it because understanding the retina won't give us a full understanding of how all this works, obviously.
And if you don't have your visual cortex and visual thalamus, you won't see. But if you don't have your retina, you also won't see.
You won't even have a chance to see. So I focus on the retina because I enjoy the possibility that we can really understand a piece of the nervous system in my lifetime, in our lifetimes.
We can understand it so well that we can build it, replace it, restore its function. That's farther off in the central regions of the brain. That's going to be quite a bit harder.
I find satisfaction in really understanding something so well that I can write down in a mathematical formula what it's doing that I can test my hypotheses up and down.
And yes, we really get how this little machine works and that I can engineer devices to replace the function of that circuit. It's lost that to me is just deeply satisfying.
But there also has is a really fundamental role for people who want to go and do more exploratory work in the visual brain, as you mentioned in the visual cortex and the thalamus and other places.
Because ultimately those retinal signals won't lead to anything if those areas aren't putting it all together to govern our perception and our ultimately our behavior.
So let's talk about the retina in its full beauty and detail.
Three layers of cells that line the back of the eye like a pie crust.
Somehow take light comes into the eye lens focuses that light if it doesn't do that well we put lenses in front of our eyes such as contact lenses or spectacles.
And somehow takes that light and transforms it as you said into neural signals and processes that within the retina.
Let's take a deep dive into the retina and do so with the understanding at least my understanding is that in part thanks to your work and the work of others this is perhaps the best understood piece of the brain.
Yes, I think it's a solid argument that it's the best understood piece of the brain and we'll turn back to that in a minute.
So the retina begins with a sheet of cells called the photoreceptor cells that are highly specialized these are cells that essentially don't exist anywhere else in the brain.
And what they do is transform light energy into electrical signals in neurons very specialized very demanding cells they require a lot of maintenance and they die relatively easily which is what gives rise to some of the forms of blindness.
Those are the you might call them pixel detectors or tiny cells called photoreceptors that each one captures light from a particular location in the world.
That sheet of cells has done that initial transduction process where light is converted into neural signals that the brain can then begin to work with.
The second layer is responsible for processing adjusting changing mixing and matching comparing signals and different neurons many complex operations that we're still trying to understand and consists of dozens of distinct cell types that extract features if you will of the visual world from the elementary pixels represented in the photoreceptor cells.
The second layer is receiving the input from that sheet of photoreceptors and picking stuff out of it.
The third layer of cells is the so called retinal ganglion cells that's the only term that I'd like to probably will come up repeatedly in this conversation.
So for your for your viewers and listeners these retinal ganglion cells are the ones who are responsible for taking the signals that are there in the retina and sending them to the brain so that the process of vision can begin.
The messenger's if you will from the retina to the brain.
The retinal ganglion cells and there are about 20 different types in humans are again feature extractors they pick out different bits and pieces of the visual scene and send interesting stuff to the brain trying to leave out the uninteresting stuff.
And the 20 or so cell types all pick out different types of information from the visual scene you can a sort of think of them as photoshop filters each cell type in the retina.
Again about 20 different ganglion cell types each type represents the full scene the entire visual world but picks out different features such as some cells pick out spatial detail tiny little points of light almost.
Some cells pick out and signal information about things that are moving in the visual world some cells pick out information that's been captured about different wavelengths from the photoreceptor cells.
And they're there by giving us our sensations of color and probably more things in those 20 different ganglion cell types that we don't fully understand.
The result then is that the retina has this sort of a representation of the visual world but it has 20 different representations not one it's not one picture that comes out of the retina and gets sent to the brain no no no it's 20 different pictures and you can think of maybe as 20 different photoshopped pictures but one of them has the edges highlighted one of them has the colors highlighted one of them has movement.
Encoded in it and these somehow these filters send the information to many different targets in the brain and our brain puts it all together and then we have a cohesive sense of the visual world which is the remarkable feature that we really don't understand.
Is it fair for those that don't work with photoshopped to think about these different photoshopped filters perhaps as like different movies of the visual world one movie contains the outlines of objects and people and things another movie is showing the motion of blobs in the environment meaning whatever's moving environment is kind of just represent as blobs another movie is just the color in the environment another move and then all of those.
What I'm calling movies are sent into the brain and then the brain somehow combines those in ways that allow us to see each other and see cars and objects and recognize faces is that is that one way that's exactly how I think about it maybe it's a better way to say and no I like the photoshop filter analogy I just for those that don't work with photoshop you know I just think that the movie analogy might might be a decent alternative.
How the retina works is an example we think of how all sensory systems work there's an initial representation in a specialized cell type that is that is responsible for incapable of extracting physical features from the world.
And then neural circuits in the brain use that information in different ways to grab stuff out of the visual world in the auditory system there's the sound world is represented also in specialized cells that capture sound energy and transduce that into neural signals and then subsequent.
And then the stages of processing in the auditory system pick out different features of our auditory world like the frequency how higher how low a tone is right the direction it's coming from right the movement of that how loud it is different features are extracted so.
Visual system is just an example of how the external world is represented in our brain and of course in some sense in a philosophical approach to the brain is really saying well there's the sensory world.
And then there's the actions we take and there's almost nothing else that we really know other than those two things have a sensory world comes in and then finally it results in our action that's what our brain is about.
Because vision is so important for people I find it absolutely compelling and fascinating I mean as an example as you know well many people study rodents to understand how different aspects of the brain work and you know rodents are interesting animals and do all sorts of really cool things but they interact with the world differently than we do they in a lot of ways they sense by smelling they they identify objects by smelling and they navigate with their whiskers into the brain.
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and we do two types of experiments with that and so this electrophysiological recording and stimulation apparatus is very custom built by our physics collaborators who have developed high-end equipment. It allows us to record and stimulate through 512 channels simultaneously at very high density. This is pretty high-end stuff in terms of technology for interrogating and manipulating the electrical signals and the retina that's what we specialize in in my lab. I just asked a question about this device.
I've seen it before. It's very small. As you mentioned, you're recording from a few millimeter square of the retina from this recently deceased patient. It looks a little bit like a bed of nails, tiny little micro wires, all arranged very closely to one another. You got the retina laying down on top of it. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right. That's right.
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That allows us to study how the retina works normally. What we also do with that same electrical apparatus is turn around and pass current through those electrodes in order to see if we can activate those ganglion cells directly with no light just electrodes. Why do we do that? We do that because it allows us to design future methods of restoring vision by electrical stimulation of the retina, which we'll probably talk about in a few minutes. We do that because it allows us to design future methods of restoring vision by electrical stimulation of the retina, which we'll probably talk about in a few minutes. We do that because it allows us to design future methods of restoring vision by electrical stimulation of the retina, which we'll probably talk about in a few minutes. We do that because it allows us to design future methods of restoring vision by electrical stimulation of the retina, which we'll probably talk about in a few minutes. We do that because it allows us to design future methods of restoring vision by electrical stimulation of the retina, which we'll probably talk about in a few minutes.
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So you mentioned there are about 20 different types of these retinal ganglion cells, what we may refer to in brief as RGCs. So retinal ganglion cells are GCs, same thing.
And as you mentioned, these cover the entire retina so that if each cell type is extracting a different set of features from the visual or motion, color, specific colors, etc.
That essentially no location in the world around us fails to be represented by these cells. Put differently, these cells are looking everywhere. Each cell type is looking everywhere so that if movement occurs in any region of our visual world, we are in a position to detect it.
But maybe we could talk a little bit about cell types. Cell types is such an important theme in the field of neuroscience and indeed in all of biology. But it's actually not something we have talked about very much on this podcast before either in solo episodes or in guest episodes.
I don't have any specific reason for that. We've talked about brain area, as prefrontal cortex, basal ganglia, anterior mentally cortex and on and on. We've talked about neural circuits. But we've never really talked about cell types.
So the ganglion cells rather you let me down. I'm talking about cell types. Well, but that's why you're here. That's why I'm here. That's why you're here.
Tell us about cell types. How do you figure out if you have a cell type? How do you know if it's a cell type or, you know, is it the shape? Is it how it responds? How do you know if you have a cell type?
What's this about? I want to just put in the back of this question or rather in the back of people's minds that this issue of cell types is not just an issue pertinent to the retina. This is an issue that is critical to understanding how the brain works.
It's critical to understanding consciousness. I know a lot of people like what is consciousness? We're not going there just yet. But what are cell types? How do you determine if you have a cell type and why is this so important to understanding how the brain works?
Yeah, I mean, as you said, as far as we understand, every single brain circuit is full of very distinct cell types. Those cell types are distinguished by their genetic expression, their shapes and sizes, which other cells they do contact and which cells they don't contact, where they send their information to in other parts of the brain, and what they represent.
And as far as we know, this is true throughout the brain. And it's true in the retina, the different ganglion cell types, retinal ganglion cell types, about 20 of them, each of which is looking at the whole visual scene, extracts different stuff.
This cell type one extracts one thing, cell type two extracts something else, but they all represent the entire visual scene.
But those cell types we know from lots of beautiful work, work that you're closely connected to and some of which you've done, those cell types have different morphology, different shapes and sizes, different patterns of gene expression, different targets in the brain, they send their outputs to different places in the brain.
So really to study the retina without understanding cell types, you're kind of lost right away, you have to know what's going on with the cell types otherwise you can't make sense of this retinal signal.
The way we identify them in two ways and they're different for different purposes. The basic way we identify the different cell types is their function, because we study their function.
We study how they respond to light images and we can clearly separate them out. In fact, it's a simple thing to say, but it's really true. Our 512 electrode array technology, which you've seen in our lab and stuff that we developed with collaborators about 20 years ago, was crucial for this.
Because with that 512 electrode technology, we could see many cells of each type and we could clearly parse them apart from one another, whereas previous studies working on one cell at a time had great difficulty doing that.
So with our technology with 512 electrodes, we record hundreds of cells simultaneously. So we say, oh, there's 20 of these, there are 50 of those, there are 26 of those.
And here they are, we can just set them in different bins and say, okay, this is what's present in this retina, just what the information is they're extracting.
There's another purpose, again, referring forward to the neuroengineering aspect. We need to identify the cell types, not just based on what visual information they carry, but based on their electrical features, properties, electrical properties of the cells.
As you know, neurons are electrical cells. They fundamentally receive and transmit electrical information and the way that they do that has a distinctive electrical signature. That turns out to be super important for developing devices to restore vision.
Could you explain how you determine what a given cell type does. It's electrical properties.
And let's just draw a mental image for people. The retina is taken out of this deceased individual, put down on this bed of nails of electrodes. Those electrodes can detect electrical signals within the ganglion cells.
You are able to shine light onto the retina and see how the retinal ganglion cells respond, meaning what electrical signals they would transmit to the brain if they were still connected to a brain.
They're not connected to a brain in the experiment. They're sitting there.
They're trying. I could imagine playing those cells a movie of a checkerboard going wherever square on the checkerboard goes from white to black to gray. You could do that.
I could play a cartoon. I could show it this year's Academy Award winner for best picture. How do you decide what to show the retina?
This is a human beings retina after all. Presumably it looked at things that are relevant to human beings until that person died.
But how do you determine cell type electrical signals? If you don't know what specific things to show it. I mean, you're going to show it. I don't know, Disney movies. What do you show it?
What we show now reflects the fact that we've built up a lot of information and our work stands on the shoulders of many scientists who have studied the retina for decades to figure out what different cell types respond to.
We know that certain cell types respond primarily to increments of light. When light gets brighter than it was. A change from a certain brightness to a higher brightness, this particular cell type fires.
Another cell type fires or sends spikes to the brain when it gets darker. Some cell types respond primarily to large targets in the visual world. Other cell types respond better to small targets in the visual world.
Some cell types respond to different wavelengths of light that we can identify. There are exists certain cell types that are still poorly understood that respond to movement.
We can tailor visual stimuli to types that we kind of already know about because of much preceding research. That's not actually how we do it in our experiments for the most part. Instead, we use a very unbiased flickering checkerboard pattern as it turns out, which is a really efficient unbiased way to sample many cells simultaneously.
So that in a half hour of electrical recording from a retina, we can figure out what all the 512th or so cells are that we're recording and know all of their types.
And the way we do that is to play essentially random garbage TV snow type image to the ratnafer a period of time and determine which bits of brightening or darkening or moving or whatever in that random garbage activated this particular cell by looking at average of cross the half hour recording and saying, oh, it looks like this cell was always firing when it became bright in this region of the screen. That must be an on cell sensitive to light in this region of the screen and so on.
So we have sophisticated efficient ways of doing it, but it all comes back to these basic things about what features in the visual world tend to cause a given cell to send a signal to the brain.
Yeah, that makes a lot of sense. So you take essentially what you called random garbage snow white black and gray pixels on a screen.
The retina views that and then the cells in the red note will respond every once in a while with an electrical potential the fire as we say spike sometimes called.
And then you take sort of a forensic approach.
A bit later you look back in time and you say, you know, what was the arrangement of pixels in this random garbage right before this cell fired in electrical potential that's right spike and then from that you can reconstruct the preferred stimulus.
And you can say, oh, this cell and cells around it seem to like motion of things going in a particular direction, for instance. And how do you know that the cell doesn't also like a bunch of other stuff that you didn't pick up on using this.
Random garbage. Yeah, two things for let me just say for the record, we don't record from these cells that signal motion in particular directions.
They are an elusive cell type that is best understood in rodents and other creatures and not well understood in the primate as you know, although some people are discovering potential cells of that type now have have recently discovered them.
Okay, so let's say cells that respond to small spots that are red.
You know, that go from dim red to bright red, right? Yeah, so we can go through that colored TV snow and pick out the cells that responded to a transition of the kind you described from darker to lighter or from greener to redder or something like that.
And so we can pick that stuff up, but you ask the question, well, G is the TV snow going to capture everything about what these cells are doing. That's a really important question that I want to just mention more.
Not that's a scientific instrument. It's an unbiased way to sample a whole bunch of cells, you know, first cut, look at, you know, generally speaking, what are they up to. But that doesn't mean we've really captured their role in natural visual perception because actually you don't go through the world perceiving visual snow, you go through the world perceiving objects and meals and mates and targets and all these things right.
So the study of how the retina responds to more naturalistic visual stimuli in my lab and in many other labs around the world is really getting getting off the ground now. And I would say we have limited understanding.
I would say we know that our simple laboratory experiments with the TV snow don't capture the whole story. There's more. There are about 20 different cell types in the retina. We have basic characterizations of seven of them, if you count a certain way.
We know that there are another 15 or so lurking right behind the curtain that we've started to sample. We don't know what naturalistic targets they respond to in the visual life of the animal. That's work that's underway, exciting, interesting work because this.
We know that the retina they got to be there for something one one way to think of it. I'm pretty sure you think of it this way too is that the retina is a highly evolved organ with a lot of evolutionary pressure for it to be efficient to have a small optic nerve sending to the brain.
It's probably the case that there's no accidental stuff sitting around the retina that's vestigial and sending information to the brain. It's probably the case that those signals are all doing something important for our visual behavior, for our well-being, for our sleep, all sorts of stuff.
And I think and the field is still trying to figure that out. These are the big mysteries I think in terms of the retina. What are those signals exactly in all those different cell types? What different behaviors and aspects of our life do they control?
What is the wildest cell type you've ever encountered? Like what did it do? What did it respond to? That's what I mean when I say wildest.
You know, it sells retinal ganglion cells that respond to increasingly red portions of the visual scene or decreasingly green portions of the visual scene. Like, okay, cool, that's seem cool. Like get some, you know, around the time of Christmas that that's useful and it's useful in other days of the year as well.
But you know, given that the retina is indeed the best understood piece of the brain and given that you have 20 cell types, 20 is in 20 million. It seems tractable.
How it gets understanding it in its entirety or understanding them in their entirety, excuse me. One would like to know, what stuff are we paying attention to at the level of the retina?
Are they like spiral cells that like spiral stuff in the environment or there's cells that like emojis like what's going on in there? You spend a lot of time doing this.
We do. We spend a lot of time. After all, you give up two night sleep, which is kind of incredible way. I'll just do a little take a moment here and just say, you know, for a guy that's been doing this for this long with these sleepless nights, you look pretty good. You look pretty rested.
I tend to go home. I go home before the graduate students do. They stay up. I used to stay up until my mid 40s. I was in there doing the all nighter type things.
And maybe you can help me figure out my sleep patterns.
Yeah, we can talk about that. We talk about how to pull all nighters and still survive.
We've done plenty of those. But yeah, like what's lots at stake here. There's a human retina, you know, meaning a human gave up their eyeballs to for this experiment after they died, of course.
Yeah, you've got many people on this. These are these sorts of experiments are very expensive. A lot of fancy equipment, a lot of salaries to try and figure this stuff out. This is the chief mission of the National Institute. There's a lot of tax dollars.
This is in my opinion, as important as the space program, probably more important in my opinion, you know, restoring vision to the blind.
So what are you finding in there?
Yeah. And we have the privilege of being on the front lines of that funded by the National Institute and other institutions to be out there figuring out what's going on in this human retina. I'm with you on that.
So I'll tell you how we go bad at these days. There are about seven cell types that we understand pretty well what they're doing. They're not complicated. They just have different properties color size, this kind of thing, temporal properties, their timing of their signals.
And those seven cell types, we understand pretty well, but we're trying to really nail down the details. Why? Because of neuroengineering for vision restoration.
Then there's another, I'm going to say 15 or so. And we and the anatomists, the people who study the shapes and sizes of the cells have long known that there were more cell types lurking in the retinal circuitry, but their function has not been known.
And because we didn't have many recordings from them, we didn't have electrical recordings in response to light that would tell us what they naturally do.
We've actually had a breakthrough in the last few years led by a senior researcher in my lab named Alexandra Kling, who has figured out that there's another 15 or so cell types lurking in those recordings that if we look more carefully, they're there.
And they have crazy properties. And so the crazy properties I can tell you about have to do with the spatial region of the visual world that they respond to.
The well known cell types that you know and I know from the textbooks kind of respond to a circular spot in the visual world. If there's light in this little circular area, they'll fire a spike. If there's no light there, they don't care.
Well, okay, some cells is not quite circular. Some cells respond to the light that's there and the difference from the light that's around it. So if it's brighter than the light that's nearby, then you get a big response.
The new cell types are more puzzling than that. Some of them respond to three or four blobs in the visual world. That's kind of strange, unexpected, definitely unexpected based on the textbooks.
And the newest ones are weirder yet. Some of them, their visual response profiles, that is the region of the visual world that they are sensitive to light in.
Almost has a spidery shape, almost like the dendrites of a cell, like the processes of a cell. And some of them have blobby light sensitivity. They're sensitive to light increments here and decrements there and increments here and decrements there and some blue light over here and blue light over here.
We don't understand these cells. To be clear, the seven that we understand reasonably well, they're not trying to just pin down and really nail for vision restoration, the sort of first cut at cell type specific vision restoration.
Those ones don't have these weird properties. They're a little simpler to understand. So we're just working out all the details of the timing of the responses and all that. These new ones, we don't know what's going on with them. So we're doing experiments.
Those seven cell types constitute maybe 70% of all the neurons that send visual information from the eye to the brain. So we think it's a really solid target for vision restoration to work with the simple ones.
And so, so when I say that I think that the retina is the best understood circuit and nervous system, I'm talking about those seven cell types, which we know a lot about what they do. We really do know a lot. It's not done, but we know a lot.
I'm not talking about the other 15 cell types, which are a minority of the population, but seem to be doing very strange and surprising things that are yet to be determined. So it's a mix.
We know some really good stuff, and then there's really some deep mysteries out there about these other cell types.
So we've been talking a lot about how to understand the signals that the retina is sending the brain. And I know your lab has done incredible work in this arena and figured out a number of the different signals as you described some of the features that the different cell types are extracting just a moment ago. These blobs of different colors, etc.
What good is this to, you know, the everyday person, right? What what in addition to wanting to understand how we see, you know, what sort of sorts of medical applications can this provide in terms of potentially restoring vision to the blind.
But perhaps even larger theme is this notion of neuroengineering, right? Taking this information and creating devices that can help us help our nervous system function better, maybe even function at super physiological levels.
I know there's a lot of interest in this these days. In part due to neural link, right? Because Elon's out there front facing very vocal about his vision of the nopun intended of chips being implanted in people's brains that would allow them to be in conversation with, you know, 100 people at the same time just by hearing those voices in the head, maybe filtering things out so it doesn't sound like a clamor of 100 different voices.
Perhaps giving people super memory, I mean, you know, sky's the limit. No one really knows where this is all headed. You're working in what we call a very constrained system where it has specific properties that you're trying to understand.
And once you understand those, you can start to think about real applications of like what's possible? Like could you create a visual system that can extract more color features from the world that no other human can see?
Can you restore pattern vision to somebody who is essentially blind, independent on a cane or a dog or, you know, God forbid, can't even leave their house because they can't see anything at all.
You know, where is this headed? What is the information useful for? And perhaps we should frame that first within the medical rehabilitative context of repairing or restoring vision rather and then get into the more kind of sci-fi type neuroengineering stuff.
Absolutely. Yeah, this, this really is my passion these days, turning that corner, continuing to figure out the mysteries in the retina, but also saying, wait a second, we actually know quite a lot about this.
Shouldn't this be the first place that we can solve problems like restoring vision, restoring function or augmenting our function? I think it should be.
The concept of how to do this is straightforward and not invented by us in any way. And that is the following. One of the major sources of blindness in the Western world is loss of the photoreceptor cells that capture light, macular degeneration and red knight is pigmentosa or two well known elements that give rise to vision loss.
And the vision loss is because the cells that capture light in the first place that we talked about earlier die off. So you're no longer sensitive to light and then your blind.
The concept is that you may be able to bypass those early sections of the retina that capture the light and process the signals and instead build an electronic implant that connects up directly to the retinal ganglion cells.
And this electronic implant would do the following. It would capture the light using a camera, which is relatively easy.
It would process the visual information in a manner similar to the way that the retina normally does as similar as possible. And then it would electrically activate the retinal ganglion cells by passing current and causing the ganglion cells to fire spikes and send those spikes to the brain.
And if we do this really well, we can essentially replace those first two layers of the retina and piggyback on to the third layer and say, okay, we'll just jump right into that third layer.
We're going to force those ganglion cells to send reasonable visual signals to the brain and then the brain is going to think that got a natural visual signal and proceed accordingly. That's the concept.
This is not our idea. People have had this concept for decades and some people have even started to make it work in human patients.
And what I mean by that is implanting electrodes on the retina, stimulating and causing people who have been profoundly blind for decades to see visual sensation, blobs and streaks of light in their visual world that are reproducible.
So that's happening now. That's happened. People who were at once blind are able to see objects are able to see crude blobs and flashes of light in ways that allow them to navigate their world a little bit.
Avoid a coffee table. Maybe or at least see a bright window in a dark wall and be able to point to that bright window or the bright doorway in a dark wall, something like that.
So it's a glass half full half empty story that I want to turn that I'd like to turn attention to in this conversation, because I think it's very exciting.
Yes, you can see stuff by artificially electrically stimulating the gang themselves and you can see stuff that actually helps you interact with your world, a tiny little bit. So great. That's the glass half full.
The glass half empty is it's nothing remotely resembling what we understand as naturalistic vision where we see spine spatial detail and color and objects and can navigate complex environments and all that stuff. No chance. You can't do anything remotely like that.
You can see that there's a bright doorway over that way and turn toward it, which is a helpful step in your human experience, but there's a long way to go.
So the question is, why does this existing technology fail to give us high quality vision? What's needed to give us high quality vision?
And this is the piece I'm really passionate about.
It turns out that the devices that have been implanted in humans so far by pioneering bioengineers who did really hard stuff were fairly simple devices.
And they created the retinas if it's a camera that is just a grid of pixels and they put a grid of electrodes down there and they stimulated according to the pixels in the visual world and thought, well, hopefully that will cause the retina to do the right thing and send a nice visual piece of visual information to the brain initiate vision.
Unfortunately, they left the science on the table.
And this is actually what I'm dedicating the next phase of my career to bringing the science that we know that we talked about to the table for vision engineering.
And in particular, the fact that there are there really are 20 or so distinct cell types and they send different types of visual information to the different targets in the brain.
I like to think of them a little bit as an orchestra playing a symphony.
Each different cell type has its particular score. The violins do one thing. The obos do something else.
It's a very organized signal coming out of the retina presenting to the brain this complex pattern of electrical activity at the brain assembles into our visual experience.
Well, current retinal implants unfortunately are too crude to do anything like that.
The conductor has just scattered the sheet music everywhere and people are playing whatever it's cacophony. You can maybe recognize a tune in there a little bit sometimes navigate toward a doorway.
But you're not going to get the full richness of the experience by ignoring the different cell types.
And I'm so passionate about this in part for reasons that a little bit are similar to your reasons for doing this kind of work that you do, which I think is great.
Which is I feel we have a mission to give back as scientists to take all this stuff we've been talking about because we find it so interesting and cool.
And to deliver something to the society that has allowed us to explore these fascinating areas.
And in our case, it's in the case of my lab and what we've done. It's to turn around and say, wait a second.
We understand that there's these different cell types. We understand a lot about what they do. None of this information appears in current retinal implants.
Can't we do better by using the science to restore vision in a way that respects the circuitry of the retina? That's what we're trying to do.
And the mismatch is intense. I told you when we were chatting before that nothing that we have learned about the retina since the founding of the National High Institute in 1968 is incorporated into the existing retinal implants.
We've learned a ton about the retina. Your research was funded by the National Institute. My research is funded by National Institute. A fantastic organization that allows us to learn all these things.
How is this showing up in the neuroengineering to restore vision to people? Well, currently it's not. And so we're trying to do that.
Now doing that turns out to be hard. And maybe we'll talk about that. It's a technological feat that's really challenging.
You have to build a device that you can implant in a human that can recognize the distinct cell types. See where they are.
Stimulate them separately from one another and conduct this orchestra to create a musical score that reasonably closely resembles the natural one.
That's what we're all about doing. And as it turns out, and maybe we'll talk about that separately, that mission of being able to restore the patterns of activity that the retina normally creates also has extremely exciting spin-offs in three directions.
One of them is understanding better how the brain puts the signals together. That's research for the brain.
The second one is augmenting vision, creating novel types of visual sensations that weren't possible before and maybe doing something along the Elon Musk lines of delivering more visual information that was ever possible.
And third, figuring out how to interface to the brain more broadly. Because as you and I know, the structure of the retina is very much representative of the structure of many brain areas.
And if we're going to figure out how to interface to the visual cortex, we darn well, but are figure out how to interface to the retina first.
That's what we're all about doing in my lab these days is figuring out how to do that well. That's a mixed science and engineering effort.
We've done about 15 years of basic science on that. How do we stimulate cells? How do we recognize cells? How are we going to build a device that does all this and talks to the cells in this way?
And I can go into lots of gory detail about it. But that's what we've been doing the basic research on. And the last few years we've worked at Stanford with fantastic engineers from various disciplines, electrical engineers, material scientists, others to figure out how to put together the pieces and build an implant that can do this in a living human.
So is the idea to build a robotic retina to build a essentially an artificial retina that could be put into the eye of a blind person or even put into the eye of a sighted person that would fundamentally change their ability to see or in the latter case enhance their ability to extract things from the visual world that they would otherwise not be able to see like like seeing twice as far getting, you know, hawk like resolution of the brain.
And then the evolution of the visual world. Yep. Which that would be cool. Yep. Could be distracting. Yeah. I'm not sure I want to see the fine movements of a piece of paper and somebody's notebook from across a cafe as they flutter the pages.
But you might want to for a moment. There might be a moment when you want to and if you have an electronic device that you can control that you can dial in to sense different aspects of the visual world. And you know by your choice, you might be like, yeah, it's pretty cool. I want to be able to do that right now.
There's an example I like to give which I think maybe is helpful for interpreting what we're talking about when we say being able to do more things with the optic nerve.
You gave the example of many voices and stuff. Here's an example that I like. We know that we can drive down the road and have a phone call.
Hands free and do that quite safely. Pretty safely, right? And you're big why? Because you're tapping in there. You've got two types of signals coming into your brain.
Your visual signal of the cars on the freeway, anyone who which could kill you in an instant. So it's important.
And the sound coming into your ears, which carries the voice of your girlfriend that's telling who's telling you something that you're interested in hearing.
And these are different parts of the brain processing this information. And so you can do both of these things at the same time because there's no interference.
One part of the brain's working doing one thing. Another part's doing something else. You're good.
What you can't do is to read your texts and drive down the freeway at the same time. That's not good because now that visual system of yours that needs to be detecting these fast moving dangerous objects is being distracted by looking at the text.
And you might die and some other people might die with you. So a lot of people texting and driving.
Yeah, that's why I like to point out this example to remind people you can't do it well. It's like it's like you can't do well.
It used to be, you know, I will just take a brief tangent here into this topic a few years back there were a lot of news articles, a lot of discussion about texting and driving, a lot of attention to getting people to stop texting and driving.
I've seen a few people pulled over for texting and driving before, but I would say texting and driving is rampant reading what's on one's phone while driving is rampant.
All you have to do is be on the freeway here in Los Angeles, look in the car next to you.
Yeah, look where they're looking and be willing to be reading and texting while driving presumably when they're doing that, they're just using their peripheral vision to detect any kind of motion and no doubt this is caused the deaths of many people.
Yeah, change lanes get away from them. That's, you know, just like that other driver. So, so here's the thing.
And this is, this is, I say this a bit tongue in cheek, but it's sort of a real example. It may be that if we harness the different cell types in the retina
to deliver different visual information to different cell types.
Like the image of the text on your screen to a certain cell type that you know the so-called midget cells or the motion of the objects in the visual scene, the cars to a different cell type.
The midget cells, by the way, folks, because they're very, very small.
Yes. And by named by an atomist decades ago, so we carry that nomenclature forward.
And the parasol cells, which are different cells that you can potentially encode the movement of the cars in the parasol cells.
And if those two systems are operating independently, which we sort of think they may be from research that you know very well from your extensive studies in vision, maybe we can do those two things safely at the same time.
Not by the way, that's not my research goal to text and drive at the same time just to be clear, but it's a very tangible real world of example of if we do really have parallel pathways that can be modulated and controlled independently of one another.
This opens the door to streaming all kinds of visual information in parallel into our very high bandwidth visual systems that wasn't possible during evolution because we didn't have control over the cell types.
So I think of that as the world of visual augmentation, and it starts to get interesting if the different cell types are behaving in an independent way when they transmit visual information to the brain.
Now, how are we going to figure that out? Well, we need a device that can stimulate the different cells independently and then study that to see whether people can do this kind of thing.
Right. What's that device, the artificial right now the same implant I'm telling you about that can restore vision to people because it's an electronic device that can dial up and the activity in different cell types.
That same device is what we can use as a research instrument to understand if the different pathways are parallel, if the signals interact with one another and explore how the brain receives that information and then we can use that to explore can we augment vision and allow allow ourselves to have new or visual sensations that we don't even know what that would look like.
We don't even understand what it would look like to us to see those sensations, but it might be able to deliver lots of information to our brain.
And if we can do all those things, then we can take that same set of tools and engineering technologies into the brain to access different cell types as well.
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So to just summarize a little bit of the linear flow here of what you've done.
You started off with the understanding that the neural retina is perhaps the best place to try and understand how the brain works because of its arrangement, the cell types etc.
You spend a number of decades doing these wild experiments on human retinas and other retinas recording the different cell types with these high density, what I call bed of nails.
Two and a half decades, not bad at all.
Two and a half decades.
It's your robustness that matters, you know, and you have plenty of it.
You figure out what the cell types are. So then you gained an understanding of how light is transformed into different types of electrical signals that encode different features in the visual scene.
Then comes the challenge of developing neural engineering tools to try and stimulate the specific cell types in a way that more or less mimics their normal patterns of activation, like not activating a huge piece of retina so that, you know, the cells that like increases in redness
are also being stimulated with the cells that like, you know, edges in a way that would create some shmooey like crazy representation of the outside world.
No, you want the same precision that light stimulation of these cells in the intact human eye provides in this explanted retina, this retina on this bed of nails.
But then a device that essentially can mimic what the retina does and you needed to do all that earlier work, understanding like, what does the normal retina do?
What is the healthy retina do in order to try and develop this prosthetic device to either restore vision or because it puts you in the position of being able to stimulate cells however you want.
In theory, you could create a situation in a human where the cells that respond to, I don't know, outlines of objects are hyperactive.
So that, you know, the person could effectively see objects in one's environment better than anyone else could perceive, I know, motion is a tricky one, but motion better than anyone else could see detail in the visual world that no one else could detect.
We're not talking about turning people into mantis shrimp, but the analogy works because mantis shrimp can see things that we can't advise versa.
And so what you're talking about here is neural augmentation through the use of engineering.
Yep. And we often do talk about it as sci-fi because the sci-fi writers have been talking, you know, writing about this for decades.
It's not sci-fi anymore. It's sci. It's straight up sci right now.
It's really, we just need to build the instrumentation and start working with those experiments to figure out how to make it work.
I think we have a responsibility to do this because this is the way we take this kind of information, all that's been learned about the visual system by the National Institute since 1968 and all the people that it's funded to do this research and turn the corner and make a difference for humanity with it.
And I assume and think that humanity will be leverage nervous system knowledge to build all sorts of devices that we can interface to the world with.
I think, you know, I don't know Elon Musk, but I think he's right about that. That that's where we're headed.
It should be done well. It's important to do it well.
We will hopefully be more connected to truth in the world. If we're able to build devices that give us better sensations, more acute understanding of what's going on out there, better abilities to make decisions and all that, let alone just see stuff.
So that frontier of developing technologies to allow our brains and our visual systems initially and then other parts of our brains to do things better is unbelievably exciting. It is sci fi, but I just want to emphasize, I think it's the responsible way to go to think about how to do that well.
All technologies that we develop can be used for good or for real. And I'm sure some of your listeners who are a lot of very passionate thinking people out there thinking about neuroscience and the implications worry what does this mean we're going to be introducing electronic circuits and our brains to do stuff.
Yeah, well, we will pretty much clear the humanity will do that.
So in any technology development, you have to think about, well, how do you do it well? How do you do it for good? There are popular movies right now about technology development such as understanding the structure of the atom.
And that technology development can be used for good or for ill to blow up cities or to save civilizations.
So I think that scientists were responsible for advancing that in a thoughtful and meaningful way. I think we can do this in the retina. It is the place to start.
I'm curious what you think actually as a scientist your background is in this field or very close field to mine. I know you speak with all sorts of scientists on this podcast, but this is pretty much your field or very close, not the neural engineering part but understanding the retina. And I'm curious if you agree that this is the place to start doing this stuff.
The first guest ever asked me a question on this podcast during a guest interview. I think this would be a fun place to both answer and riff on this a little bit because first of all, I think the retina is absolutely the place to start because we understand so much of what it does, what the cell types are.
But maybe by comparison, a different brain region, the hippocampus, which is involved in the formation of memories and other stuff, but formation of memories about what one did the previous day, what one did many years ago, etc.
Is an area that I think any time the conversation about neural prosthetics or neuroengineering or neural augmentation comes up, people think when to be cool that like a little stimulating device in the hippocampus. And then if I want to remember a bunch of information from a page or from a lecture, I just stimulate and then voila, all the information is batched in there.
Well, that's an attractive idea. I think it's worth pointing out right now that sure there is a pretty decent understanding of the different cell types in terms of their shapes, some of their electrical properties of the hippocampus.
But there is in no way shape or form the depth of understanding about the hippocampus and what the individual cell types do and what the different layers of it do that one has for the neural retina.
So what we're really saying is if you stimulate the hippocampus, you'll likely get an effect, but it's unclear what the effect is and it's not clear how to stimulate.
That's to me the best reason to focus on the retina because you know what the cell types are. Thanks to the work of your laboratory and many other laboratories, you know what sorts of stimulation matter.
And it provides the perfect test bed for this whole business of neural augmentation, neuroengineering. I think there's also a bigger discussion to just frame this in which is so much of what we discuss on this podcast with guests and in solo episodes relates to things like dopamine, neuromodulator, serotonin.
And everyone is interested in these things because they can profoundly change the way that we perceive and interact with the world. But one only has to look to the various pharmaceuticals that increase or decrease these neuromodulators and know that indeed those pharmaceuticals can be immensely beneficial to certain individuals.
I want to be clear about that. But that whatever quote unquote side effects one sees or lack of effect over time is because those receptors are like everywhere over the around the brain.
So you can't just increase dopamine in the brain and expect to only get one specific desired effect. So the reason you're here today is not because we both worked on the retina.
It's not because we happen to also be friends. It's because to my mind your laboratory represents the apex of precision in terms of trying to figure out what a given piece of the brain in your case the neural retina does.
And then we can parse all its different components and then use that knowledge to create a real world technology that can actually tickle and probe and stimulate that piece of the brain in a way that's meaningful.
Right not just like sending electrical activity in and that to me is so important. I think we were going to think about levels of specificity from manipulating the human brain to get it an effect.
Okay, crudest would be drugs take a drug increases serotonin which might bind to particular receptors.
Take the drug psilocybin a lot of excitement about psilocybin. We know that can lead to increased connectivity between different brain regions at rest.
There's probably there is some demonstrate clinical benefit. There's also some potential hazards. But it's very broad scale.
We don't know what's happening when the person is thinking about a piece of moss expanding into an image and a memory of their childhood.
It's like a million different things are happening there. And then at the other far extreme is the kind of experiment that you're talking about stimulating one known type of retinal cell.
Seeing what that means for visual processing or modeling what that means for visual processing and then building a device that can do exactly that and then maybe ramp it up 20% 50% because I think that represents the first step into okay how would you stimulate the hippocampus to create a super memory.
Would you stimulate a particular cell type in a particular way and to my knowledge there's you know despite the immense excitement about the hippocampus and understandably so there just isn't that precision and of understanding yet.
So forgive the long answer but you know you asked me a question on this podcast. I love that.
Yeah and specificity is what you're talking about and we need technology to do that to to modulate neural circuits in a highly specific way we've got to start with the piece of the neural circuit we understand best we have best access to that's the right.
It's sitting right there on the surface we can get right into it and in installed devices we know so much about it that's the place to start the place that we understand build electronics that is that is adaptive but senses what circuit it's embedded in and responds appropriately it's not just electronics you stick in there and it does something and that's it no it it first figures out who it's talking to and then learns to speak the language of the nearby neural circuitry.
So smart device let's push on that a little bit so put a little chip under the retina that can stimulate specific cell types is there a way that it can use AI machine learning that it can learn something about the tissue it happens to be in context.
Absolutely and the simplest possible way the device works in three simple steps step number one record electrical activity which is what we do in our lab in a room full of equipment but this is a two millimeter size chip implanted in your eyes.
Record the electrical activity just recognize what cells are there when they're firing what electrical properties they have to identify the cells and cell types in this specific circuit in this human that step one step two.
Stimulate and record so you figure out this electrode activate cell number 14 with 50% probability this electrode activate cell number 12 with you pass micro app of current with this probability and so on you make a big table tells you how these electrodes talk to these cells in your circuit that step to calibrate the stimulation by stimulation recording then finally when you have a visual image.
And you want to represent it in the pattern of activity of these cells you say okay I know from decades of basic science what these cells ought to be doing with this image that's coming in I know exactly what they ought to be doing that's what the science has been telling us we've been studying the neural code for decades to understand this I know what they should do use my device with my calibration where I know where the cells are I know how the electrodes talk to them and being being being being activate them in the correct sequence that's what I think of as a smart device device that records.
records stimulated records and then finally stimulates yes AI is part of that of course it is because this is a very complex transformation if you will from the external visual world to the patterns of activity of these cells not easy to write down just a few lines of code or a few equations complicated and AI is really helpful for that and learning by stimulating and recording and aggregating information quickly so that you can then use the device that's absolutely a part of the engineering let me be clear the AI
doesn't help us to understand is just an engineering tool that helps us to capture what this thing normally does and then go ahead and execute and make it do thing it should normally do.
I hope people will appreciate this example perhaps not you know not but goodness I don't know 40, 50 years ago but still today one treatment for depression is electric shock therapy.
I'm very up you know on the face of a barbaric treatment but effective in certain conditions it's still used for a reason but it can appear barbaric right you know people are like a bite.
You know bite device you know so they don't bite through their tongue or their lips there you know they're strapped down and they stimulate the whole.
Just like stimulate all neurons in the brain essentially there's a huge dump of neurotransmitters and neuromodulators like drugs it's completely non specific stimulation effectively probably even less specific than drugs and yet.
The clinical outcomes from electric shock therapy in some cases are pretty impressive like people the brain is quote unquote reset they still remember who they are.
But presumably through the release of neuromodulators like dopamine serotonin acetylcholine in a very non specific way there has been some symptom relief in some cases what you're talking about is really the opposite extreme.
You know before I said pharmaceuticals that tickle a particular neuromodulator pathway would be the opposite extreme I think electric shock therapy is probably the most extreme.
Where is this whole business of neural press these these going outside of the visual system like right now I can imagine that there are little stimulators in the spinal cord for sake of restoring movement to paralyze people I realize this is not your field but is are you seeing impressive stuff there or is it still really really early days.
There's absolutely impressive stuff particularly for example people reading out signals from the motor cortex or language cortex in order to help people to communicate or to move cursors on screens in order to interact with devices.
Paralyzed people yes excuse me paralyze people who can't interact with technology the way that we do and but with their thoughts can send signals through an electronic device that can be used to control a mouse on a screen and have them connect to the internet that's a huge deal to be able to have people do that imagine how life changing would be to be able to communicate if you couldn't before so there are wonderful examples of that you know of them so do I work of christian oi and Jamie Henderson at Stanford is.
One beautiful example of the engineers at each and doing stuff now you know no like doing doing this kind of stuff the built on the work of shinoin and Henderson and stuff so that's great you know.
Stimulating in spinal circuits as you said for creating rhythmic movements that's that's happening so this is an enormous space and in each case what you said I think is really highly relevant that electrophysic therapy you can think of that is let's say your computer is not behaving right.
You can reboot it might work then it'll start not working again then you have to reboot it again well how often do you want to reboot your computer gets a little inconvenient to be rebooting computer every five minutes maybe want to go in and actually diagnose this thing and put in a piece of software that fixes the thing that was going wrong.
Instead of rebooting your computer every five minutes right and I think of electric shock therapy a little bit as a reboot that level so we want to intervene more specifically how do you do that what you have to understand the software in order to do that you have to have specificity controlling this thing in your computer not this this this this this this this particular thing that's going wrong you got to interfere with that and change it and modulated well that's what understanding the real circuit is about that's what building specific hardware that activate specific cells is about.
That's in in the case of the right now again it's just so obvious that it's right in front of us to do this stuff and it's right in front of us to take us into augmentation to giving us better senses a fun example I like this is it's an interesting topic because the national institutes of health that funds a lot of research that goes in this direction tends to not be interested in augmenting our senses.
They kind of wanted there they draw a line more or less it's saying look which I'm a restore what we were as humans not create a new kind of human.
And that's an interesting question because I don't think there is a fine there's an actual line a bright line between those things I don't think there's a bright line between those two things.
The the finest example I know is that even in the very crudest visual restoration devices you have to actively suppress the infrared sensitivity of your camera to not have infrared vision why because many cameras are sensitive to infrared light.
So in other words if you don't put an infrared filter in front of your camera you're going to have some infrared vision maybe won't help you very much whatever just trying to say as soon as you start building devices to restore sensations building electronic devices.
The organization is right around the corner you'll creep up on your real fast so I think you can't even really draw a line.
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receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving end of the receiving
when I invited you here today I was absolutely sure that our listeners and viewers were going to get a absolutely world class explanation of how the nervous system works and the the retina and the visual system in particular and that it would be delivered with the utmost clarity which it was so thank you I know there's been so much learning in and around that and you beautifully framed for us what that means in terms of the larger understanding of how the nervous system works and what you and other laboratories are now
in a position to really do with that information and the technologies that are being built and that will be built and the purpose in bringing here today was was just that but not that alone.
You know, I think we hear so much about the brain and how it works and everyone wants to have tools and protocols to function better but it's clear that the work that you're doing is headed in an direction that's going to vastly expand the possibilities for sake of treating human disease and for expanding human
experience I'm certain of that. What I did not expect however was that when I wrote down one bullet point well actually two I wrote still a coffee snob question mark the answer is yes and yoga you know that we would end up in territory where you would share some of your experience that I myself was not aware of about this a bit of a wandering of three different PhD programs and I was going to do that.
I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to
do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I
'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do
that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm
going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that
I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to
do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I'm going to do that. I
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