Huberman Lab - How the Brain Works, Curing Blindness & How to Navigate a Career Path | Dr. E.J. Chichilnisky

Episode Date: March 18, 2024

In this episode, my guest is Dr. E.J. Chichilnisky, Ph.D., a professor of neurosurgery and ophthalmology at Stanford University. He studies how we see and uses that information to build artificial eyes that restore vision to the blind.  We discuss how understanding the retina (the light-sensing brain tissue that lines the back of our eyes) is critical to knowing how our brain works more generally.  We discuss brain augmentation with biologically informed prostheses, robotics, and AI and what this means for medicine and humanity.  We also discuss E.J.’s unique journey into neuroscience and how changing fields multiple times, combined with some wandering, taught him how to guide his decision-making in all realms of life.  This episode ought to be of interest to anyone interested in learning how the brain works from a world-class neuroscientist, those interested in the future of brain therapeutics and people seeking inspiration and tools for navigating their own professional and life journey. For show notes, including referenced articles and additional resources, please visit hubermanlab.com. Thank you to our sponsors AG1: https://athleticgreens.com/huberman LMNT: https://drinklmnt.com/hubermanlab Waking Up: https://wakingup.com/huberman Timestamps (00:00:00) Dr. E.J. Chichilnisky (00:02:47) Sponsors: LMNT & Waking Up (00:06:06) Vision & Brain; Retina (00:11:23) Retina & Visual Processing (00:18:37) Vision in Humans & Other Animals, Color (00:23:01) Studying the Human Retina (00:26:33) Sponsor: AG1 (00:31:16) Cell Types (00:36:00) Determining Cell Function in Retina (00:43:39) Retinal Cell Types & Stimuli (00:49:27) Retinal Prostheses, Implants (01:00:25) Artificial Retina, Augmenting Vision (01:07:12) Neuroengineering, Neuroaugmentation & Specificity (01:17:01) Building a Smart Device, AI (01:20:02) Neural Prosthesis, Paralysis; Specificity (01:25:21) Neurodegeneration; Adult Neuroplasticity; Implant Specificity (01:34:00) Career Journey, Music & Dance, Neuroscience  (01:42:55) Self-Understanding, Coffee; Self-Love, Meditation & Yoga (01:47:50) Body Signals & Decisions; Beauty (01:57:49) Zero-Cost Support, Spotify & Apple Reviews, Sponsors, YouTube Feedback, Momentous, Social Media, Neural Network Newsletter Disclaimer Learn more about your ad choices. Visit megaphone.fm/adchoices

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. Chicholnicki. Dr. E.J. Chicholnicki 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, EJ spells out in very clear terms exactly how the world around us is

encoded by the neurons, 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. Chicholniewski 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 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. And now for my discussion with Dr. E.J. Chicholnicki. Dr. E.J. Chicholniewski. Welcome. Good to see you. For the audience, we are friends, we go way back. EJ has been a few years or more ahead of me in the science game. And the best way to describe you and your work, EJ, is you're an 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 of neural tissue at the rear of the eye, that captures the light that is incident on the eye that comes in 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, 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 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 have 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. It'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 when it's lost. That to me is just deeply satisfying. 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 in 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 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, it comes into the eye, the 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.

So 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. They're 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 in 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. So that second layer is receiving the input from that sheet of photoreceptor. receptors 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 viewers and listeners, these retinal gangland 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. They are the messengers, if you will, from the retina to the brain. The retinal gangland 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 sort of think of them as Photoshop filters, each cell type in the retina. again, about 20 different ganglangen 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 thereby giving us our sensations of color. and probably more things in those 20 different gang and 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 somehow, these filters send the information to many different targets in the brain, and then 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. Amazing. Is it fair for those that don't work with Photoshop to think about these different Photoshop 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 represented as blobs. Another movie is just the color in the environment. Another movie. 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 one way to think about? That's exactly how I think about it. Maybe it's a better way to say. 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 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 responsible for and capable 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, the sound world is represented also in specialized cells that capture sound energy and transduce that into neural signals. And then subsequent stages of processing in the auditory system pick out different features of our auditory world. Like the frequency, how high or how low a tone is, the direction it's coming from. Right. The movement of it, how loud it is, different features are extracted. So we think the visual system is just an example of how the external world is represented in our brain. And of course, in some sense, 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, how the 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 identify objects by smelling, and they navigate with their whiskers to a large extent. We don't do any of that. You don't navigate with your whiskers, at least I don't think you do. You don't recognize me when I walk in the room by my smell. No, you use vision for all that. And we humans use vision,

so it's a really fundamental aspect of who we are as biological creatures. I wonder if just for sake of entertainment, we could think about how the human retina and therefore vision in our species differs a little bit from some extreme examples of vision in other species, not to make this a comparative or zoological exploration, but just to really illustrate the fact that the specific cell types within our retinas create. create a visual representation of the outside world that can be and often is very different from that of other species. For instance, or at least my understanding, is that the mantis shrimp sees, I don't know, 60 to 100 different variations of each color that we are essentially blind to because their photoreceptors can detect very subtle differences in red, for instance, long wavelengths of light. what most people refer to as red.

Pit vipers can sense heat emissions, essentially with their eyes, but also other organs, and on and on. You know, it's, I raise this because I think the, the human neural retina is such an incredible example of extracting features from the visual world that then we recreate, but I think it's also worth reminding everyone and ourselves

that it's not a complete representation of what's out there. Like, there's a lot of, lot in light that we don't see because our neural retina just can't turn it into electrical signals. Do you want to give some examples of what we can't see? And if any particular examples from the animal kingdom delight you, feel free to throw those out. Well, one thing, you mentioned color. We experience a rich sensation of color when we look at the world and say, wow, I see all these colors. That's immediate. And that's just how we talk about it. But in fact, we have very little information about color.

Color is a very high dimensional, complex thing, or wavelength, I should say, wavelength information really is about how much energy there is in the light around us at different wavelengths. We only have three sort of snapshots of that in our retinas with the three different types of photoreceptor cells that are sensitive to different wavelength, different bands of the wavelength spectrum. three is not a lot. As you just said, other creatures have many more ways of capturing wavelength information. And one way you can verify for yourself that we just have three is to realize that if you look at your TV, there are only three primaries on your TV.

There's a red, there's a green, and there's a blue. That's it. And from those three primaries, the entire richness of the experience on your TV set is composed. So with just those three things, you basically are able to create any human visual sensation. Well, the mantis shrimp would be like, that's nothing. There's so much more stuff out there that's not represented on this TV, if you could speak to the mantis shrimp. Another thing we maybe don't see another example of a difference in the animal kingdom is, so again, taking rodents as an example, one of the things that rodents have to do is to not be hunted by birds that are coming down toward them. And so it appears that there are cells in the retina that are seem to be quite sensitive to looming, to something dark that's getting bigger, like a shadow coming from a bird coming down at you. We don't know for sure that this is exactly what causes animals to avoid being eaten by birds, but there's interesting evidence in that direction. That's not really a big thing for us for humans.

as far as I know, we're not typically hunted by huge birds. So that's not a thing we need. And I think that's where comes back to where you're headed, if I understand, right, which is we occupy different biological niches. We and the mantis shrimp and the rodents, and our visual systems reflect that. We have different stuff that we're looking for in our visual environment than other creatures are. And so our eyes are different. And that's one of the reasons that we emphasize work on the human retina, as opposed to other.

certain other animal species that would be less clearly relevant to the visual experience you and I have. So let's talk about these incredible experiments that your laboratory has been doing for several decades now. I've had the privilege of sitting in on some of these experiments and they are very involved, to say the least. If you could just walk us through one of these experiments, I think the audience would appreciate understanding what goes into, quote unquote, trying to understand what's going on in the electrical activity of these specific retinal cell types, the retinal gangling cells in particular. What does this look like? You know, you're in your laboratory at Stanford and you get a phone call. Someone says, I got a retina. What happens next?

We scramble like crazy. We drop everything we're doing, cancel all our appointments and get ourselves ready for 48 hours of nonstop work down in the lab, getting as much data as we possibly can from the retina. The most exciting example of what you just said is when we get a human retina. When, for example, there's a donor who has died and the retina is available for research. We jump at that opportunity. How soon after the person is deceased do you need to get the eye globe, the eyeball, in order to get the retina in a condition that would allow you to record electrical signals from it? A few minutes. So you're waiting in the hospital? The way we typically get these eyes is from brain dead individuals, so people who are legally and medically dead, but their hearts are

still pumping and therefore their retinas are still alive and functioning. When those individuals are used, the bodies of those individuals are used for organ donations, we can benefit from that organ donation setup that organ distribution centers do to save many people's lives and also to promote research. So we sometimes get those retinas, and that begins the experiment for us. I'm going to ask for a few more details here just to put the picture in people's minds. And not to be gruesome, I just really want people to understand what's involved here. So you'll get a call.

We've got a patient who is soon to be deceased. They've consented to giving their eye globes, their eyeballs, for research so that you can study the human retina. Yeah. Is it you who goes over and takes the eyes out? Does somebody do that? or hand them to you in a bucket of ice. I'm sorry if I'm making people queasy at all, but this is folks how one goes about trying to understand how the human brain works.

Absolutely. And this is also how you go about donating your heart so that you can save somebody else's life who needs a heart transplant. The same incredible organizations that do the harvesting of the tissue for us, their primary goal is to do that for organ donations to save lives. They save lives every day. These people are incredible. Donor Network West is one of those organizations,

the one that we work with. They're really amazing. So their technicians or a retinal surgeon will take the eye out, give it to myself or somebody from my lab who will bring it back to the lab. And we have a way to keep the eye alive and functioning just the eye by itself. Is this always at Stanford or do you sometimes travel elsewhere? Local hospitals up to an hour away. So then you drive them back?

We drive them back. It's the retina express. And when we're bringing back the retina express, it's again, it's all hands-on-de-end. in our lab. We are scrambling, setting up all of our equipment, getting everything ready. You've been at these experiments. They're intense. And they really are 48-hour marathons of incredible activity by really dedicated individuals. So we might get those eyes sometimes again with two in the morning. That's common. And from that two-in-the-morning time begins the experiment. So we bring the eyes back. We open them up and we have access to the rear of the eye, which is where the retina is. It's a thin, of neural tissue at the back part of the eye. We hemisect the eye, cut it in half so that we can see the back. It's like half of a blob, if you will. And then we put in relaxing cuts and lay it out flat so we can see what we're working

with. And we take little segments of retina out in the subsequent 48 hours, cut them out, maybe a three by three millimeter piece of the retina, a little chunk of retinal tissue, and bring it into an electrophysiology recording and stimulation apparatus that allows us to interact with it. And we do two types of experiments with that. 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 in the retina. That's what we specialize in in my lab. just ask a question about this device.

I've seen it before. It's very small. As you mentioned, you're recording from a few millimeters square of the retina from this recently deceased patient. It looks a little bit like a bed of nails, right? Like tiny little micro wires all arrange very closely to one another. You've got the retina laying down on top of it. And that bed of nails can extract, meaning record the electrical signals that are coming

out of the retinal ganglion cells. That's right. And the retina is still alive, so you are in a position to shine light on it and essentially make it behave in the same way it would if it were still lining the back of a healthy, alive person's mind. That is the beauty of these experiments. So because we can keep the retina alive and happy, and because the retinal ganglin cells, the cells that are the ones that message the visual information to the brain are on the

surface, we can put them right next to the electrodes and we can record their electrical activity. In other words, we record the signal that those cells would have sent to the brain if they were still in the living person. And at the same time, as you said, we can focus an image that we create on a computer display onto the retina. So we're treating the retina, if you will, as a little electronic circuit, which it almost is, honestly, delivering light to the photoreceptor cells so that they are electrically excited and then recording the electrical activity that the retina is sending out, if you will. 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 gangland 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. I'd like to take a quick break and acknowledge one of our sponsors, Athletic Greens. Athletic Greens now called AG1 is a vitamin mineral probiotic drink that covers all of your foundational nutritional needs. I've been taking Athletic Green since 2012, so I'm delighted that they're sponsoring the podcast. The reason I started taking Athletic Greens and the reason I still take athletic greens once or usually twice a day is that it gets to be the probiotics that I

need for gut health. Our gut is very important. It's populated by gut microbiota that communicate with the brain, the immune system, and basically all the biological systems of our body to strongly impact our immediate and long-term health. And those probiotics and athletic greens are optimal and vital for microbiotic health. In addition, athletic greens contains a number of adaptogens, vitamins and minerals that make sure that all of my foundational nutritional needs are met, and it tastes great. If you'd like to try athletic greens, you can go to athletic greens.com slash Huberman, and they'll give you five free travel packs that make it really easy to mix up athletic greens

while you're on the road in the car, on the plane, et cetera, and they'll give you a year's supply of vitamin D3K2. Again, that's athletic greens.com slash Huberman to get the five free travel packs and the year's supply of vitamin D3K2. Let's take this moment to talk a little bit about cell types. So you mentioned there are about 20 different types of these retinal gangland cells, what we may refer to in brief as RGCs. So retinal gangland cells RGC, 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 word 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 type. 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 areas, prefrontal cortex, basal ganglia, anterior mid-signal cortex, and on and on. We've talked about neural circuits, but we've never really talked about cell types. So the gangling cells... Brother, you let me down.

No 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? And 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. And 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 ganglain cell types, about 20 of them, each of which is looking at the whole visual scene, extracts different stuff.

This cell type 1 extracts one thing, cell type 2 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 what 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 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. And 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 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 50012 electrodes, we record hundreds of cells simultaneously. We can say, oh, there's 20 of these, there are 50 of those, there's 26 of those, and here they are, and 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. 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. Let's just draw a mental image for people. The retina's 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. But they're trying. But they're trying. I could imagine playing those cells a movie of, I don't know, a checkerboard going where every square on the checkerboard goes from white to black to gray. We could do that. I could play a cartoon.

I could show it this year's Academy Award winner for Best Picture. But 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? Like, what do you show it? So 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. And we know that certain cell types respond primarily to increments of light

when light gets brighter than it was. So a change from a certain brightness to a higher brightness, this particular cell type fires. Another cell type fires are send 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 exist certain cell types that are still poorly understood that respond to movement. So 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 in 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 retina for a period of time and determine which bits of brightening or darkening or movement or whatever in that random garbage activated this particular cell by looking at average across 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 of 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, shh, the retina views that. And then the cells in the retina will respond every once in a while with an electrical potential. They'll fire, as we say. Spike, sometimes called. And then you take sort of a forensic approach a bit later. You'll

look back in time and you say, you know, what was the arrangement of pixels in this random garbage right before this cell fired an electrical potential? That's right. A spike. And then from that, you can reconstruct the preferred stimulus. Yeah. 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. 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 and have recently discovered them. Okay, so let's say cells that respond to

small, like 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. Cells tend to respond to transitions in the visual scene rather than static imagery. And so we can pick that stuff out, but you ask the question, well, gee, 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. Quite likely not.

That's a scientific instrument. It's an unbiased way to sample a whole bunch of cells, 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 off the ground now.

And I would say we have limited understanding. I would say we know that. We know that that are 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 we know that the retina, they got to be there for something. 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 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 cells, retinal gangling cells that respond to, you know, increasingly red portions of the visual scene or decreasingly green portions of the visual scene. Like, okay, cool, that seems cool. Like, get some, you know, around the time of Christmas, 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 isn't 20 million. It seems tractable. It probably gets understanding it in its entirety or understanding them in their entirety.

Excuse me. One would like to know, like, what stuff is, are we paying attention to at the level of the retina? I mean, are there like spiral, cells that like spiral stuff in the environment? Or there sells it like emojis? Like, what's going on in there? You spent 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, by the 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. Oh, they stay up. They stay up. You used to stay up. I used to step up until my mid-40s. I was in there doing the all-nighter type things.

Got it. And maybe you can help me figure out my sleep patterns better. Yeah, yeah, we can talk about that this episode. We can talk about how to pull all-nighters instead. still survive. Exactly. 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 Eye Institute. There's a lot of tax dollars.

Like, this is, in my opinion, as important, is the space program, probably more important, in my opinion, you know, restoring vision to the blind, obviously. So what are you finding in there? Yep. 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 property.

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 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 research 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 I expected 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. 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 are 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, but 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 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, et cetera. What good is this to the everyday person, right? 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, the...

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 neuralink, right, because Elon's out there front-facing, very vocal about his vision of the, no pun intended,

of chips being implanted in people's brains that would allow them to be in conversation with 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 a hundred 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 and dependent 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 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, 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 retinitis pigmentosa are two well-known ailments 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 you're 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 ganglens cells by passing current and causing the ganglens cells to fire the 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 onto the third layer and say, okay, we're just jumping right into that third layer. We're going to force those ganglan cells to send reasonable visual signals to the brain and then the brain is going to think it 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. 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 our. artificially electrically stimulating the gangland cells, 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 find 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 that treated the retina as 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 piece of visual information to the brain and 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 oboes do something else. It's a very organized signal coming out of the music.

the retina, presenting to the brain this complex pattern of electrical activity that 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, 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 epirotinetinal 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 Eye Institute in 1968 is incorporated into the existing retinal implants. Nothing. We've learned a ton about the retina. Your research was funded by the National Eye Institute. My research is funded by National Eye 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 spinoffs 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 than 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 better figure out how to interface to the retina first. That's what we're all about doing in my life. lap 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 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 seeing twice as far, getting hawk-like resolution of the visual world. Yep. Which that would be cool.

Yep. Could be distracting. Yep. Like, I'm not sure I want to see the fine movements of a piece of paper in 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

by your choice, you might be like, yeah, that'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 for. and do that quite safely, pretty safely, right? And why? Because you're tapping in, you've got two types of signals coming into your brain. Your visual signal of the cars on the freeway, anyone 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 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. I see 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 you can't do well. You probably talk him. Yeah, 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 at the, the car next to you. Yeah, look where they're looking. And people are 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 has caused the deaths of many people. Yeah, change lanes. Get away from them. And 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. Called midget cells, by the way, folks, because they're very, very small. Yes. And named by anatomous decades ago. So we carry that nomenclature forward. And the parasol cells, which are different cells, 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 and vision, maybe we can do those two things safely at the same time. Now, 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 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. Not the same implant I'm telling you about that can restore vision to people because it's an electronic device that can dial up in the activity in the 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 ourselves to have new revision 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. 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 that whole.

Two and a half decades. It's your robustness that matters, EJ, 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 neuroengineering 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 shmooy, like crazy representation of the outside world. That's right. 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 does 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, you know, you can 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 and vice 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 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 Eye 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 leveraging 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 ill. 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 in our brains to do stuff. Yeah, well, we will. It's pretty much clear that humanity will do that. And 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 developments 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. How's it going to go? Well, I think I think as scientists, 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 a very close field to mine. I know you speak with all sorts of scientists on this podcast, but this is pretty much your field, not the neuroengineering 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? one did many years ago, et cetera, is an area that I think anytime the conversation about neuroprosthetics or neuroengineering or neural augmentation comes up, people think, oh, wouldn't it be cooled out, 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. While that's an attractive idea,

I think it's worth pointing out right now that, sure, there's a lot. 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, 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, seroton, 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 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 and 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 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 if we were going to think about

levels of specificity for manipulating the human brain to get an effect, you would say, 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, you know, 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, 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 ask me a question on this podcast. I love that answer. Long answer. Yeah. And specificity is what you're talking about.

And we need technology to do that, to modulate neural circuits in a highly specific way. We've got to start with the piece of the neural circuit we understand best and we have best access to. That's the retina. It's sitting right there on the surface. We can get right into it and install devices. We know so much about it. That's the place to start, the place that we understand. build electronics 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 first figures out who it's talking to and then learns to speak the language of the nearby neural circuitry. So a smart device.

A smart device. Let's push on that a little bit. So put a little chip onto 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 contact with? 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 eye. 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's step one. Step two. Stimulate and record. So you figure out, oh, this electrode activates cell number 14 with 50% probability. This electrode activates cell number 12, if you pass a microamp of current, with this probability and so on. You make a big table that tells you how these electrodes talk to these cells in your circuit. That's step two. Calibrate the stimulation by stimulation and 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 bing, bing, bing, bing, bing, activate them in the correct sequence. That's what I think of as a smart device, a device that records, stimulates, and 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. It's not easy to write down just a few lines of code or a few equations. It's

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. It's just an engineering tool that helps us to capture what this thing normally does and then go ahead and execute and make the 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. A very, you know, on the face of it, barbaric. treatment, but effective in certain conditions. It's still used for a reason. But it can appear

barbaric, right? You know, people have like a bite device, you know, so they don't bite through their tongue or their lips. They're, you know, they're strapped down and they stimulate all neurons in the brain, essentially. There's a huge dump of neurotransmitters and neuromodulators. It's like drugs. It's completely nonspecific 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, pharmacotivism. 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 prostheses 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 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 the language cortex in order to help people to communicate or to move cursors on screens in order to interact with devices. These are paralyzed people. Yes, excuse me, paralyzed people who can't interact with technology the way that we do. 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. The work of Krishna Shinoi and Jamie Henderson at Stanford is one beautiful example. Eddie Chang doing stuff now. You know, Neurlink doing this kind of stuff that built on the work of Chenoy and Henderson and stuff. So that's great. You know, stimulating in spinal circuits, as you said, for creating rhythmic movements. That's happening. So this is an enormous space. And in each case, what you said, I think is really highly relevant, that electroshock therapy, you can think of that as, look, 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? It gets a little inconvenient to be rebooting your computer every five minutes. Maybe you 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. It's at that level. So we want to intervene more specifically. How do you do that?

Well, 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 particular thing. that's going wrong. You've got to interfere with that and change it and modulate it. Well, that's what understanding the neural circuit is about. That's what building specific hardware that can activate specific cells is about. That's in the case of the retina, 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. 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 want to, they draw a line more or less at saying, look, we're trying to 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 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 it won't help you very much, whatever. I'm just trying to say, as soon as you start building devices to restore, sensations building electronic devices. Augmentation is right around the corner. It'll creep up on you real fast. So I think you can't even really draw a line. Throughout today's discussion, we've been thinking of the brain as kind of a,

the rest of the brain, I should say, because the neural retina is two pieces of the brain extruded out into the eye globes during development. I like to remind people of that over and over. When you're looking at somebody's eyes, you are looking at two pieces of their brain. There's no debate about that. but most people don't realize that. You'll never look at anyone the same way again. But this is the reason why you can tell so much about people's inner state from their, from their eyes.

Somebody who's sleep deprived, it's not just about the droopiness of their eyelids or the circles under their eyes. There's an aliveness to the eyes. The yogis talk about people that sort of show up at the level of their eyes as opposed to sunk back into their brain. You know, these are very kind of abstract concepts. And there's some very non-abstract stuff these days looking at, looking through the eye at the retina the way the ophthalmologists do. And there's a lot of diagnostic capability just in those images of the retina. Oh, right. I'm glad you brought this up.

There's some interesting and increasing evidence that looking at the neural retina, because it is a piece of the brain with neurons that have the potential to both thrive or degenerate, that looking at the neural retina, which one can do with these new technologies, can provide a window into whether or not there are forms of degeneration just. such as Alzheimer's and other forms of neurodegeneration, a deeper within the brain that one can't image directly because of the thick opacity of the skull. So in other words, imaging the eye in order to determine if someone is developing Alzheimer's. Because you have a direct view into a little piece of the brain. It's a good signal.

It can help you figure stuff out about what's going on in your brain, even beyond the sunken eyes. Absolutely. Amazing. So I think the rest of the brain piece is also really interesting. and maybe here we can go like semi-neurophilosophical. You know that there are clearly parts of the brain that are involved in essential what I call housekeeping functions,

regulating respiration, you know, keeping us breathing, keeping our heart beating, digestion, responding to threats in some sort of basic way, like through the secretion of adrenaline and giving us the potential to move. But a lot of the brain is capable of plasticity. And one wonders if you were to, for instance, develop a retinal prosthesis that would allow me to see with twice the level of detail

that I currently can. Would my adult brain be capable of dealing with that information? We're talking about twice as much information coming in. Same brain tissue on the receiving end. Can it make sense of it? Do we have any idea if it can make sense of it? Are there experiments that speak to that? Yeah, that's a fantastic and interesting question. It makes you think about neural development all over again, right? And I take some inspiration on that from the work of someone you know, Eric Knudson, who discovered that there is plasticity beyond the periods of time. He discovered many wonderful things, but there's plasticity well beyond the period of time

that we thought that there was plasticity in certain animals. And in particular, that if you make gradual adjustments to the sensory world, you can exhibit plasticity that you can't see if you make an abrupt adjustment. So plasticity is there. It just has to be brought on by more subtle manipulations that take you from A to B in little incremental steps. And if you take those incremental steps, you can see the adult plasticity. So coming to your question, is the brain capable of receiving the kind of extra information we provided? It could be that if we just show up on day one, bam, try to deliver twice the visual resolution

or whatever in your visual system, it could be that if we try to deliver twice the visual resolution on day one, it won't work. You'll see, it'll, you know, it won't look sensible to you. But if we gradually introduce it by the way that we're dialing up the resolution, we may be able to get there. And there are fascinating studies to be done. You think about spike timing dependent plasticity, a term that your viewers may not all know, but is related to how neurons adjust their strength of connectivity to one another

according to the timing of the signals in those cells. Mechanisms like that tell us, wow, the brain really cares about the very precise timing of stuff and to the degree that that influences the way that neurons do or don't strengthen their connections to one another. It's so fundamental in everything from memory to visual function, what have you. This relates to fire together, wire together, although it highlights the together part. How closely in time do two neurons need to be active in order for them to subsequently increase their connectivity? And indeed, one of them needs to be active a little bit before the other one in order for it to work optimally, right? So what I envision is that when we have full control of the neural code with an electronic implant that can talk to the cells and do all the things that I said and we can really control the neural code coming out of the retina, we can then see. start to play games and dial up that neural code very slowly and teach the remaining brain how to

understand these signals. Not introduce some crazy thing from day one, no, just gradually teach. Isn't that how we do everything well? Isn't that how plasticity works? I love the subtlety and the rationality of your example because so much of what we see in the internet and on the news is like chips inserted into the brain to create supermembers. or conversations between 50 people at the same time without anyone speaking, you know, just hearing other people's thoughts by way of, you know, neural signals being passed from one to the next. But yet another reason why you're here today is because you represent the realistic, grounded incremental approach to really parsing this whole thing of how the brain

works and how one then goes about engineering devices to augment the human brain. And as you just pointed out, it's not going to be done by just sticking electrodes in and stimulating and seeing what happens. In fact, those experiments were done in the 1960s. People like Robert Heath would put electrodes into the brain during neurosurgery, stimulate and just see what the patient would do or what they reported thinking. Nowadays, that's done still, but with a lot more precision and intention. And we've moved far beyond that.

By the way, I just want to say, those were important first experiments. Yeah, that's the first thing you've got to do. Heath was a rather, let's be honest, not the most savory character. He embarked on some experiments that had a social agenda to them and was a pretty, at least by my read, was not the kind of person I'd want to spend time with to say the least. But you're right, those experiments were critical because like electric shock therapy, like the formulation of drugs that can massively increase certain neuromodulators or decrease them, they led to some level, crude, but some level of understanding about how the brain works, which is what we're really talking about today. But you represent the, uh, As I said, the astronauts of this, astronauts don't go into space and just kind of blast off and see where they end up. There's math. There's physics. There's computer science.

Sensors. Censors? Cameras. That's right. Where are we about to land here on the moon? Is there a crater here or not? What's around us? We should sense what's there and then make our decisions accordingly. And our electronic implants in the brain, really, we should make them smart.

Why make them dumb? We're smarter than that. We can build implants that can sense what's around them and change their patterns of activity accordingly. I use a metaphor sometimes if you go as an American who doesn't speak Chinese to China and you start yelling in English, maybe somebody will to learn which way to go on the street. Somebody might understand you at some point and help you out, but it's going to be a, it's going to be a, you know, not very effective way to get around. It's way better if you speak the language. you talk to people and ask them where to go.

So that's what we need to know. We need to say, look, we have the science. We have incredible devices we can engineer. We have AI now that even helps us to do this query of the outside world and turn it into a smarter instrument. Make our instruments smart. Make them so they know how to talk to the brain. Don't expect that the brain is just going to wrap itself around your simple electronic device.

No, make a smart device. That's what we want to make, a smart rental implant. Maybe we could just take a couple of minutes and talk a little bit about you and some of the things that have led to your choice to go in this direction. So did you always know you want to be a neuroscientist from the time you started college? What was your trajectory? I should know this. You were an undergraduate at Princeton. At Princeton.

That right. Studying math. Math. So you could have just done all your work with a piece of paper and a pen, but you had to try and engineer all these electronics. Okay, that's a pen and paper pen. I took a very random route. I studied math as an undergrad. I spent a few years running around playing music and traveling and living a bohemian life.

Tell me more about that. Oh, I basically just told you all I'm going to tell. Following the Grateful Dead. No, not quite following them, but that was an important part of the story. Was that an important part of your personal development? Yes, very much so. free expression, dance, music, creative, exploratory music, all that kind of stuff. Such a contrast to the EJ that comes forward when we're talking about the precision of neural

stimulation in the specific retinal cell types. But I think it's useful for people to hear both young and old, like that one's nervous system can be partitioned into these different abilities to go and dance and travel. And you weren't doing anything academic at that time. No, for a few years, I wasn't doing that programming. computers to make a to make a living and then I started I started three different PhD programs at Stanford before I settled no no no my goodness in sequence I started in the math PhD program I learned that was not really for me and I started in the economics PhD program in the business school there

and I realized after after less than a year that was not for me I worked in a startup company for a while I did a lot of stuff for a few years and took some settling but then I decided to go into neuroscience. And there were a couple formative things. One is that I had gotten a really formative experience as an undergraduate from a wonderful guy called Don Reddy who taught an introductory neuroscience course, who was really an inspiring mentor. And then when I was at Stanford, I met Brian Wendell, my PhD advisor,

and I was inspired by him. I thought, I didn't know why he was studying, what he was studying, but I just knew I wanted to learn from this man. and I wanted to study with him. I just knew this was this was the person who should be my mentor. Based on something about him. Yes. Can I ask you about these three PhD programs?

Because I think people here, you know, or see what you're doing and probably imagine a very linear trajectory. But now I'm hearing you, you like toured around playing music. Then you start a PhD program. Nope. Then another one. Nope. Then another one without getting into all the details. I mean, were there nights spent lying awake thinking like, what am I going to

to do with my life, or did you have the sense that you knew you wanted to do something important? You just hadn't found the right fit for you. Like how much anxiety on a scale of 1 to 10, 10 being total panic did you experience at the apex of your anxiety in that kind of wandering? Am I allowed to go above 10, like turning up the app to 11? Sure. I just think it's really important for people to hear, whether or not they want to be scientists or not, this idea that people that are doing important things in the world, in my view,

rarely, if ever, understood that that's the thing that they were going to be doing. There was some wandering about. That sure seems like it, doesn't it? Yeah, I experienced the same when I talked to other people, and it seems like that. And for sure, for me. It just took a while of trying different things to see, number one, what I was really good at and where I felt I could make a difference. And I realized I studied math, and I was okay at math.

but I know I have known mathematicians who are really talented, gifted mathematicians, the one who really make a difference. I wasn't going to be one of those people. Likewise, playing music, I don't have that intrinsic talent. It's fun. I can play songs in front of people and do stuff. I like it and stuff like that. But I don't have that kind of talent.

In fact, I'll say something that I say to friends sometimes, and you're a good friend of mine. If I had the talent to get a few thousand people on their feet dancing by playing music, I'd probably just do that. Really? As long as we've been friends, I knew none of this. I'd like do none of this. Most of because I think we always end up talking about neuroscience or other aspects of our life.

Yes. But I didn't know. I mean, I know a great many things about you, but I had no idea. It's so interesting. Do you still do dance? We had Eric Jarvis on the podcast, by the way, Professor Rockefeller, who studies at one point was studying speech in birds, as in song in birds. And then he's done a great many other things now in genetics of vocalization.

And, you know, he actually danced with or was about to dance with the Alvinalee Dance Company. So, he had really, really talented dancer. And so, you know, dance seems to be like a theme that comes up on one of the neuroscience guests on this podcast. Do you still dance? Yeah, I love to dance. I'm a free-form dancer. I'm not a skilled dancer, but I love music. I love dancing.

I think it's part of the human spirit. I someday will understand the neuroscience behind dancing, right? Dancing is a universal human thing in all cultures. What is this dancing thing? Why do we do this and other creatures don't? Well, Jarvis thinks that perhaps it's one of the more early forms of language and that song came before spoken language. It's sort of interesting that birds that can actually recreate human beings.

speech oftentimes have the ability to dance as well. Oh, wow. And so there's some commonality of circuitry there. We'll provide a link to that episode. Jarro's a really interesting guy. I would love to hear that. I mean, but if I may, I'd like to riff on that in a different way. I did spend some time wandering around as many people do. And I think particularly for your young listeners and viewers who don't know, wow, you know, could I ever be a scientist and develop new things like that? Yes, you can. And if you're messing around your life, trying this, trying that, trying the other thing, definitely stick with it. Keep looking for the thing that works for you. I really deeply believe that. You got to play around. You got to find what it is that works for you. Interestingly enough, at least it's interesting for me,

I spent a lot of years studying the retina in a pure basic science, just curiosity-driven research way, as you and I have both done in the past. And as it turned out, I learned all the stuff I needed to know about the retina to do, to develop a high fidelity adaptive retinal implant of the type that I'm talking about in that process. The technology, the stimulation, recording, figuring out the cell types, how do you stimulate all the stuff? I learned all that stuff.

And I have come to a point in my life where I realize, wow, if somebody's going to do what I think needs to be done, which is to take everything we've learned about, about the retina and instantiate that in smart technology that can restore vision and do all the things we've been talking about. Who are the people in the world who have the right training and background and know how to do that stuff? I'm one of them. I know that.

And it's totally by chance that I picked up and learned, or it seems by chance, that I picked up and learned the things that I need to know for this. But I definitely have the right know how to do this based on all my training and the research that I've done. And it feels accidental sometimes. I look back on my own history. I'm like, how did I get here where this is obviously the thing I need to do? Was this on purpose? It didn't seem like it was on purpose. But now I got to do this because I know what needs to be done and it's something that needs to be done. So that's my mission for the coming decade or so. I mean, I knew you had this engineer, math, geeky, geeky neuroscience. I don't want to say geeky,

because I'm, well, because it may sound like I'm not right there in the same, same raft with you. But I didn't know about this more free-spirited move in all directions, depending on what one feels in the moment, dancing, E.J. It's very cool. Are you still an absolute level 11 coffee snob? Yes. Okay. Yeah, I used to go to meetings and E.J. would bring his own coffee maker and coffee to meetings. We're not talking about an espresso machine. We're talking about like, extreme levels of coffee snobbery. Press pot, the correct ground coffee, the correct kind of press pot. Good, good, good. I expect nothing less. Proof that not all circuits in the brain are neuroplastic, nor should they be. That's right.

But to bridge off of that in a more serious way, despite the free, you know, free exploration aspect to yourself and that hopefully other people don't suppress, it seems like you really are good at developing, like knowing your taste. Like it seems like the, I think it was the great Marcus Meister, a colleague of ours who, you know, has also worked on the neural retina extensively, of course, who once said, you know, that there's a coding system in the brain that leads to either the perception, the feeling of, um, yum, yuck, or me. And that's so much of life as being able to register that in terms of who you interact with and how and, um, the, the choices. of problems to work on it. It seems like you have a very keen sense of like, yes, that. And you move toward that. You've always been very goal directed since the time I've known you. So, and you've picked such a huge problem, but going about it in such a precise way, hence the analogy to the space

mission. So, like, when you experience that, may I ask, is it, does it come about as like a thought? like, oh yeah, that has to be the thing, or is it like a whole body sensation? What a great question. I love that question. I have two things to say that. The first is that for me, it's all feeling. I don't make hardly any decisions out of thoughts. I think, I process, I put it all into the hopper, and the hopper comes out and spits out a feeling. And feelings like, yeah, that's the thing to do. 100%. And I know not everybody's like me. Lots of people aren't like me. And particularly lots of scientists aren't like me, you know, but I definitely roll that way.

That is absolutely how I work. There's something that's related to that I think is, you know, philosophically in terms of personal development and spiritual development stuff, I think is quite relevant that I think you'll relate to. My favorite aphorism is know thyself. The Oracle. And I think because if you don't know yourself, you can't. do anything. You don't even know where to go. You can't even, you know, orient yourself at the next thing in your life. And I think it deserves to have two corollaries that go with it or addenda. Know thyself, be thyself, which is not easy. It's not easy to really be yourself

in this world. There are all sorts of things telling us to be something other than what we are. and the third one is love thyself and it's you know having gone through much exploration of yourself and your life and your values and me too and all the things we've talked about over time that's not easy some of us are not necessarily programmed to love ourselves and it's a skill i and i really I try my best to be with those three things all the time, know thyself, pee thyself, love thyself. Could you elaborate a little bit more on your process for the third? This is a concept that has been very challenging for me and I think for many other people.

And it gets kind of opaque when it starts getting complained with like self-respect and etc. are like loving thyself. Do you have practices? Do you meditate? Do you journal? Do you spend time trying to cultivate a love for self? Yeah. Yeah, I meditate in an informal way in the morning with my coffee. Every morning I make a fantastic cup of coffee. And I sit with it for five or ten minutes and take in my world as it's coming toward me and start to be, as I come into the day and come into consciousness, I meditate like that. And I have a ashtanga related yoga practice. Many of you, many of your viewers and listeners will know about ashtanga yoga. It's a very physical, spiritual, traditional yoga practice that has a deep meditative and breath-focused component. I know you've

had lots of episodes and discussion about the breath and the importance of that for awareness. You know, at the end of many Western yoga practices, you end with Namasas. which is expressing your respect and for the connectedness of what is in front of you to the whole universe and what's common to all of us and everything. And I usually practice yoga by myself. When I say namaste at the end of my yoga practice, a part of that is to myself. Earlier when I asked you about how you guide your decisions, you said, it's all feel. And you provide a beautiful description as to how we're.

and why that occurs for you and your trust in that. I don't recall you saying whether or not the feeling is in your head or it's a whole body feeling. Does it have a particular signature to it that you'd be willing to share? Is it excitement that makes you want to get up and move or is it a stillness? I think I ask because we've been talking throughout today's episode about the precision of neural coding and the signals that are at the level of individual cells. And yet when it comes to feeling, we actually have a pretty.

crude map and certainly a deficit in language to explain what this feeling thing is. And I know that people experience life and feelings differently, but I think it's often insightful when somebody with your understanding of the nervous system and yourself can share a bit. What does it feel like? I love that question. And it relates to something you said to me years ago. What it feels like is ease. And I remember years ago when we were talking about challenging things that each of us was facing in our lives, you said to me something like,

I wish for you some ease with all of this. It was very moving, touching. That's what a good friend does, is to give that to somebody who they love. And it sticks with me probably 10 years later. So the feeling I feel when I'm on the path that makes sense for me is ease. It's there's just nothing. It's just, okay, this is it.

I love that. I don't actually recall that specific conversation because we had many, many conversations sitting in your yard in San Diego on those plastic chairs with my bulldog Costello hanging out. By the way, folks, E.J. New Costello, my Bulldog Master. it very well. And he was not a huge fan of dogs prior to meeting Costello, but Costello flipped him. He became at least a Costello lover. I love Costello. I'll never forget him. Yeah. He embodied ease. He did nothing but sleep and eat. He embodied energetic efficiency. And everybody loves him. Everybody who gets to be in the same room with him loves him.

The people I just spoke to in your setup here and your colleagues, you know. Yeah. Yeah. Yeah. I could see why. And you have a beautiful photo of him hanging there. Yeah. Yeah. He's a great, great memory. Definitely embedded in my nervouses. I often choke up when I think about him. But I want to be clear because I've already cried once about him on a different podcast. I don't want to do that. They're not tears of sadness. It's this crazy thing. Like I love him so much. I just kind of want to explode. So damn it, Costello got me again and publicly again. So he's a lot. He's someplace laugh. Nothing. So I love that. And I think if I made, you know, do you think it's worth kids and adults learning to recognize those kind of states, those signals that tell them they're on the right path by paying attention to, I don't know, this. Like we said, there's sort of a deficit of language like eases in the body, eases in the mind. It's the release of, I mean, you know, it's not even worth exploring verbally because it's a it's such a whole body, whole, nervous system thing. Yeah, I feel like I actually was thinking about, I was giving advice to a young fellow who is applying to graduate school recently and had a Zoom call with him about stuff. He had received some good advice from some other people, and then I gave him some advice. And I saw him speak and emote and with body language drop into like, oh, yeah, that makes me sense. Yeah, that, that feeling, of course. Kind of the, of course. And I think if you can teach people to do that, I don't know if the verbal communication of that is going to, like you said, is that

going to do anything? But can you at least observe it in them as a teacher, as a mentor, and do things and when you know when you've done it, because you see them drop into ease? Do you think you can detect ease in people by looking at them and seeing their body language and everything? It's got to be a, of different things, the cadence of their breathing, their pupil size. It's not worth dissecting. This is an experiment I would not want to run. But I wouldn't want to bring people into a laboratory and figure out, you know, what pupils of the eye dynamics combined with certain rhythms of breathing, relaxation of the shoulders. It's too beautiful for that, isn't it? It's too beautiful and it's too nuanced and it's different when we're in motion versus when we're lying down. It's like, I mean,

science is capable of a great many things, but I don't think it needs to be pointed at every aspect of human experience. I think some of these things are simply worth allowing to just be. Do you feel the same way about when you have a feeling about a person, you meet somebody, and their energy just captures you? It's like, wow, what a cool person. What amazing energy. Do you want to know the science behind that? I don't. No, I don't. I think the word that comes to mind when I experience somebody like that or something like a beautiful animal or you see something, the movement of something or a beautiful piece of music or something is the word just behold. I just want to stop and take in as much of it as possible.

And here's something I know you've done, but I'm checking to make sure I really got this right because I've done it too. Because we sometimes get human retinas for doing our experiments. The first thing that happens when we get the human retina, we bring it back to our lab. It's a big production. Everybody's getting ready to go, a whole bunch of moving parts going on. We have to open up the eye and look into it to see what, condition that's in. And it's typically with a dissecting scope on a chair. It's open, sitting

on a chair, dissecting scope, looking down, look into the eye. It is so beautiful. It's breathtaking. Each time, I've looked at the retina. I don't know how many times. Each time, wow. This is what's initiating all the visual experiences I've ever had in my life or that person ever had in their life. Right. And the beauty just keeps coming. I love it. And I love it because you're talking about a behold moment that isn't just to entertain your curiosity. Sure, it's that. You want to understand how the brain works. But also a behold moment that leads from that desire to understand to a deep level of understanding now after more than two decades of exploration to a mission and service to human. humanity, restore vision to the blind, develop neuroprostheses and other types of neuroengineering

technologies that will allow the human brain to function better than it would otherwise. So there's real purpose there too. So it represents kind of a perfect ecosystem of it's not just about delighting in something and spending one's time there. There's a real, there's a real mission there. So I love it. Well, E.J., Dr. Chicholnski. Dr. Huberman. I rarely get called that these days. 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 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. 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 you here today was just that, but not that alone. 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 a 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 of this cultivation of an intuitive sense of beauty and taste and preference that the way you described it takes you out of your rational mind and into the aspects of your nervous system that

just really act as a compass toward what is absolutely right for you. And we're also lucky that what's absolutely right for you turns out to also be what's absolutely right and beneficial for the world. So thank you for coming here today. Thank you for sharing your knowledge and your heart and for doing it with such an incredible degree of openness and respect. So thank you so much. Thank you, Andrew. It's a great pleasure. Really appreciate it. Thank you for joining me for today's discussion with Dr. E.J. Chicholminsky. To learn more about the work in the Chicholminsky lab and to find links to EJ's social media handles, please see the links in the show note captions. If you're learning from and or enjoying this podcast,

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