Enhance Your Learning Speed & Health Using Neuroscience Based Protocols | Dr. Poppy Crum

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 opthalmology at Stamford School of Medicine. My guest today is Dr. Poppyrum. Dr. Poppyrum is a neuroscientist, a professor at Stanford, and the former chief scientist at Dolby Laboratories. Her work focuses on how technology can accelerate neuroplasticity and learning and generally enrich our life experience. You've no doubt heard about and perhaps use wearables and sleep technologies that can monitor your sleep, tell you how much slowwave sleep you're getting, how much REM sleep, and technologies that can control the temperature of your sleep environment and your room environment. Well, you can soon expect wearables and hearable technologies to be part of your life. Hearable technologies are, as the name suggests, technologies that can hear your voice and the voice of other people and deduce what is going to be best for your immediate health and your states of mind. Believe it or not, these technologies will understand your brain states, your goals, and it will make changes to your home and working and other environments so that you can focus better, relax more thoroughly, and connect with other people on a deeper level. As Poppy explains, all of this might seem kind of space age and maybe even a little aversive or scary now. But she explains how it will vastly improve life for both kids and adults and indeed increase human human empathy. During today's episode, you'll realize that Poppy is a true out ofthe- box thinker and scientist. She has a really unique story. She discovered she has perfect pitch at a young age. She explains what that is and how that shaped her worldview and her work. Poppy also graciously built a zerocost step-by-step protocol for all of you. It allows you to build a custom AI tool to improve at any skill you want and to build better health protocols and routines. I should point out that you don't need to know how to program in order to use this tool that she's built. Anyone can use it and as you'll see, it's extremely useful. We provide a link to it in the show note captions. Today's conversation is unlike any that we've previously had on the podcast. It's a true glimpse into the future and it also points you to new tools that you can use now to improve your life. 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, today's episode does include sponsors. And now for my conversation with Dr. Poppyrum. Dr. Poppyrum, welcome. >> Thanks, Andy. It's great to be here. >> Great to see you again. We should let people know now we were graduate students together, but that's not why you're here. You're here because you do incredibly original work. You've worked in so many different domains of technology, neuroscience, etc. Today I want to talk about a lot of things, but I want to start off by talking about neuroplasticity. This incredible ability of our nervous systems to change in response to experience. I know how I think about neuroplasticity, but I want to know how you think about neuroplasticity. In particular, I want to know, do you think our brains are much more plastic than most of us believe? Like, can we change much more than we think? and we just haven't accessed the ways to do that. Or do you think that our brains are pretty fixed and in order to make progress as a species, we're gonna have to, I don't know, create robots or something to to do the work that we're not able to do because our brains are fixed. Let's start off by just getting your take on what neuroplasticity is and what you think the limits on it are. I do think we're much more plastic than and and and then than than we talk about or we realize in our daily lives and and just to your point about creating robots, the more we create robots, there's neuroplasticity that comes with comes with using robots as humans when we use them in partnerships or as you know tools to accelerate our capabilities. So neuroplasticity the way the the where I resonate with it a lot is uh trying to understand and and this is what I've done a lot of in my career is thinking about building and developing technologies but with an understanding of how they shape our brain. Everything we engage with in our daily lives, whether it's the statistics of our environments and our contexts or the technologies we use on a daily basis are shaping our brains in ways through neuroplasticity. Um, some more than others. Some we know as we age are very dependent on how attentive and engaged we are as opposed to passively just consuming and and mo and and changing. But we are in a place where everyone I believe needs to be thinking more about how the technologies they're using, especially in the age of AI and immersive technologies, how they are shaping, you know, or architecting our brains as we move forward. You go to any neuroscience 101 medical school textbook and there's something you'll you'll see a few pages on something called the homunculus. Now, what is the homunculus? It's a data representation, but it it'll be this sort of funnyl looking creature when you see it. But that picture of this sort of distorted human that you're looking at is really just um a data representation of how many cells in your brain are helping or coding and representing information for your sense of touch, right? And that that image though and this is where things get kind of funny. That image comes from Wilder Penfield back in the 40s. He recorded the he would semataensory cells of uh of patients just before they were to have you know surgery for epilepsy and such. And you know since we don't have pain receptors in our cortex he could have this awake human and be able to touch different parts of their brain and ask them you know to report what sensation they felt on their bodies. And so he mapped that part of their their cortex and then that that's how we ended up with the homunculus and you'll see you know it'll have bigger lips. It'll have you know smaller parts of your back in the areas where you just don't have the same sensitivities. Well fast forward to today when you look at that homunculus one of the things I always will ask people to think about is you know what's wrong with this image? You know, this is an image from 1940 that is still in every textbook. And you know, any Stamford student will look at it and they'll immediately say, "Well, the thumb should be bigger because we do this all day long and I've got more sensitivity in my fingers because I'm always typing on my mobile device." Which is absolutely true. Or maybe they'll say something like, "Well, the the ankles are the same size and and we drive cars now a lot more than we did in the 40s." or maybe if I live different part of the world I drive on one side versus the other and in in a few years you know we probably won't be driving and those resources get optimized elsewhere. So what the hunculus is is it's a representation of how our brain has allocated resources to help us be successful and those resources are the limited cells we have that support whatever we need to flourish in our world. And the the beauty of that is when you develop expertise, you develop more support, more resources go to helping you do that thing. But they also get more specific. They develop more specificity. So that you know I might have suddenly a lot more cells in my brain devoted to helping me yet you know I'm a violinist and my well my left hand my right hemisphere on my semata sensory cortex I'm going to have a lot more cells that are helping me you know feel my fingers and and the the tips of everything so that I can you know be fluid and and more virtuosic but that means I have more cells but they're more specified they're giving me more sensitivity they're giving me more data that's differentiated and that's what my brain needs and that's what my brain's responding to. And so when we think about that, you know, my practice as a musician versus my practice playing video games, all of these things influence our brain um in and influence our our plasticity. Now, where things get kind of interesting to me and sort of my obsession on that side is every time we engage with a technology, it's going to shape our brain, right? It's both, you know, our environments, but our environments are changing. Those are shaping who we are. You know, I think you can look at um people's hearing thresholds and predict what city they live in. Then absolutely. Yes. >> Can you just briefly explain explain thresholds and why that would be? I mean, I was visiting the city of Chicago a couple years ago. Beautiful city. Yeah. Amazing food. Love the people. >> Very loud city. >> Wide downtown streets. Not a ton of trees >> compared to what I'm used to. >> And I was like, "Wow, it's really loud here." And I grew up in the suburbs. Got out as quickly as I could. Don't like the suburbs. Sorry. Suburb dwellers not for me. Um I like the wilderness and I like cities. Um, but you're telling me that you can actually predict people's hearing thresholds for loudness simply based on where they were raised or where they currently live. >> In part, it can be both, right? Because cities have sonic imprints, types of noise, things that are very, you know, very loud cities, but also what's creating that noise, right? That's often unique. the the the inputs, the types of vehicles, the types of density of people or and and um con you even the construction in those environments, it is changing what noise exists. That's shaping, you know, people's hearing thresholds at the lowest level. It's also shaping their sensitivities. If you're used to hearing, you know, certain animals in your environment and they come with, you know, uh, you should be heightened to a certain response in that, you're going to develop increased sensitivity to that, right? Whereas, if it's really abnormal, you know, to I hear chickens. I have a neighbor who has chickens in the city, but roosters, too. >> Yes. Yes. >> I grew up near a rooster. I can still hear that rooster. >> Yeah. >> Those those sounds are embedded deeply in my mind. There's the semantic context and then just the sort of spectrum, right? And the intensity of that spectrum. And meaning when I say spectrum, I mean the different frequency, amplitudes and and what that shaping is like. >> High pitch, low pitch, the same. >> Yeah. Yeah. And that affects how your neural system is is changing even at the lowest level of what you know what it's your your ear is your brain your cookia is getting exposed to. But then also where you know so that would be the lower level you know what what sort of noise damage might exist what exposures but then also then there's the amplification of you know coming from your higher level areas that are helping you know that these are frequencies are more important in your context in your environment there is a a funny like this is kind of funny um there was a film called I think it's the sound of silence and it started I I love Peter Sarsgard he was one of the the actors in it And um it was sort of meant to be a bit fantastical or is that a word? Is that the right word? But in fact to me so the the filmmakers had inter you talked to me a lot as had um and to to inform the sort of main character and the way he behaved because I have absolute pitch and there were certain things that they were trying to emulate in this um in this film. He he ends up being this person who tunes people's lives. He'll walk into their environments and be like, "Oh, you know, things are going badly at work or your relationships because your your you know, you've got this tritone, your or your your water heater is making this, you know, pitch and your teapot is at this." >> Oh my god, this would go over so well in LA. People would pay millions of dollars in Los Angeles. >> Totally funny. >> Do you do this for people? >> Um, no. >> Okay. Okay. >> I I will tell you I I will walk into hotel rooms and immediately if I hear something, I'm I've moved. And so you know that is I >> because you have perfect pitch. Could you define perfect pitch? Does that mean that you can always hit a note perfectly with your voice? >> There is no such thing as perfect pitch. there's absolute pitch and so think only because uh the idea of so like that would be a equal 440 hertz right but that's a standard that we use in modern time and the you know different what a is has actually changed throughout the our lives with aesthetic with what people liked with the tools we used to create music and you know in the broke era a was 415 hertz and that >> you hit that >> awesome And um in any case, so that's why it's it's absolute because you know, guess what? As my uh Basler membrane gets more rigid as I might age or my temporal processing slows down, my brain's going to still think I'm in, you know, I'm singing 440 Hz, but it might not be. It's >> baselor membrane is a portion of the internal ear that uh converts sound waves into electrical signals, right? Yeah. Okay, fair enough. Well, >> I'm talking to an auditory physiologist that help I I teach auditory physiology, but I want to just make sure because I'm I'm sitting across from an expert. >> I'd like to take a quick break and acknowledge one of our sponsors, David. David makes a protein bar unlike any other. It has 28 g of protein, only 150 calories, and zero gram of sugar. That's right, 28 g of protein, and 75% of its calories come from protein. This is 50% higher than the next closest protein bar. David protein bars also taste amazing. Even the texture is amazing. My favorite bar is the chocolate chip cookie dough. But then again, I also like the new chocolate peanut butter flavor and the chocolate brownie flavored. Basically, I like all the flavors a lot. They're all incredibly delicious. In fact, the toughest challenge is knowing which ones to eat on which days and how many times per day. I limit myself to two per day, but I absolutely love them. 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Again, that's helixleep.com/huberman to get up to 27% off. >> Okay, so our brains are customized to our experience. Yeah. >> Especially our childhood experience, but also our adult experience. >> Yes. >> You mentioned the homunculus, this representation of the body surface. And you said something that I just have to pick up on and ask some questions about, which is that um >> this hypothetical Stanford student could be any student anywhere says, "What? Wait, nowadays, uh, we spend a lot of time writing with our thumbs and thinking as we write with our thumbs and emoting, right? I mean, when we text with our thumbs, we're sometimes involved in an emotional exchange. >> Yeah. >> My question is this. The last 15 years or so have represented an unprecedented time of new technology integration, right? I mean, the smartphone, >> um, texting. And when I text, I realized that I'm hearing a voice in my head as I text, which is my voice. Because if I'm texting outward, I'm sending a text. But then I'm also internalizing the voice of the person writing to me if I know them. >> But it's coming through filtered by my brain. Right. So it's like I'm not trying to micro dissect something here for the sake of micro dissection but the conversation that we have by text it's all happening in our own head but there are two or more players group text was too complicated to even consider right now but what is that transformation really about previously I would write you a letter would send you a letter I'd write you an email I'd send you an email and so the process was really slowed now you can be in a conversation with somebody that's fast back and forth, >> right? Some people can type fast. You can email fast, but nothing like what you can do with text, right? I can even know when you're thinking because it's dot dot dot or you're writing, right? And so is it possible that we've now allocated an entire region of the homunculus or of some other region of cortex brain to conversation that prior to 2010 or so the brain just was not involved in conversations of any sort. In other words, we now have the integration of writing with thumbs. That's new. hearing our own voice, hearing the hypothetical voice of the other person at the other end and doing that all at rapid speed. Are we talking about like a new brain area or are we talking about using old brain areas and just trying to find and push the overlap in the ven diagram? Because I remember all of this happening very quickly and very seamlessly. I remember like texting showed up and it was like, "All right, well, it's a little slow, a little clunky." Pretty soon it was autofill. Pretty soon it was learning us. Now we can do voice recognition. And it's it's it you know people picked this up very fast. So the question is are we taking old brain areas and combining them in new ways or is it possible that we're actually changing the way that our brain works fundamentally in order to be able to carry out something as what seems to be nowadays trivial but as uh as basic to everyday life as texting. What's going on in our brain? we aren't developing new resources. we've got the same cells that are or I mean there's neurogenesis of course but um it's how those are getting allocated and you know just one one quick comment from what we said before when we talk about the monculus the homunculus is an example of a map in the brain a cortical map and maps are important in the brain because they you know allow cells that need to interact to give us specificity to make us fast to have you know tight reaction times and things you know because you got shorter distance and you know things that belong together. Also there's a lot of motility in terms of you know what those cells respond to potentially dependent on our inputs. So the homunculus might be one map but there are maps all over our brain and those maps still have a lot of cross input. So what you're talking about is are you having areas where we didn't used to allocate and differentiate in you specificity of what those cells were doing that are now quite related to the different ways my brain is having to interpret a text message and the subtlety and the nuance of that that actually now I'm I get faster at I have faster reaction times I also have faster interpretations. So am I allocating cells that used to do something else to allow me to have that? Probably. But I'm also building, you know, where like think about me as a multi-ensory object that has, you know, I have to integrate information across sight, sound, smell to form a holistic, you know, object experience. That same sort of, you know, integration and and pattern is happening now when we communicate in ways that it didn't used to. So what does that mean? It means there's a lot more repeatability, a lot faster pattern matching, a lot more integration that is allowing us to go faster. >> I completely agree. I feel like there's an entire generation of people who grew up with smartphones, >> uh, for which it's just part of life. I think one of the most impactful statements I ever heard in this kind of general domain was I gave a talk down at Santa Clara University one evening to some students. >> Um, and I made a comment about putting the phone away and how much easier it is to focus when you put the phone away and how much better life is when you take space from your smartphone and all of this kind of thing. And afterwards, this young guy came up to me. He's probably in his early 20s and he said, "Listen, you don't get it at all." Said, "What do you And he said, "You adopted this technology into your life and after your brain had developed." He said, "When," he's speaking for himself. He said, "When my phone runs out of charge, I feel the life drain out of my body and it is unbearable or nearly unbearable until that phone pops back on." And then I feel life returned to my body. And it's because I can communicate with my friends again. I don't feel alone. I don't feel cut off from the rest of the world. And I was thinking to myself, wow. Like his statements really stuck with me because I realized that his brain, as he was pointing out, is indeed fundamentally different than mine in terms of social context, communication, feelings of safety, and on and on. And I don't think he's alone. I think for some people it might not be quite as extreme, >> but for many of us um to see that dot dot dot in the midst of a conversation where we really want the answer to something um or it's an emotionally charged conversation can be uh a very intense human experience. >> That's interesting. So we've we've sped up the rate that we transfer information between one another. But even about trivial things, it doesn't have to be an argument or like is it, you know, stage four cancer or is it benign, right? Like these are those are extreme conditions, right? Are they alive? Are they dead? You know, did they find him or her or did they not? You know, those are extreme cases. But there's just the everyday life of um and I noticed this like if I go um up the coast sometimes or I'll go to Big Su and I I will intentionally have time away from my phone. It takes about a an hour or two or maybe even a half day to really drop into the local environment where you're not looking for stimulation coming in through the smartphone. And I don't think I'm unusual in that regard either. So I guess the question is do you think that the technology is good, bad, neutral or are you agnostic as to how the technologies are shaping our brain? >> It goes in lots of different directions. Um, one thing I did want to say though with what with smartphones specifically and sort of everything, you know, in in audio, you know, that our ability to have, you know, carry uh our lifetime of music and and content with us has been because of, you know, huge advances in the last 25, 30 years and maybe maybe even slightly more around um compression algorithms that have enabled us to have really effective what we call perceptual compression, lossy perceptual algorithms and things like MP3 and and you know my my past work with companies like Dolby. But whenever you're talking about what's the goal of content compression algorithms, it's to translate the entirety of the experience, the entirety of a signal in, you know, with with a lot of the information removed, right? But in intelligent ways. When you look at the way someone is communicating with acronyms and the shorthand that the next generations use to communicate, it is such a rich communication. Even though they might just say LOL, I mean, it's like or they might you you know, it's it's it's actually a lossy compression that's triggering a huge cognitive experience, right? >> Can you explain lossy for people who might not be familiar with it? Lossy means that in your encoding and decoding of that information, there is actually information that's lost when you decode it. But hopefully that information is not impacting the perceptual experience. Imagine I have, you know, a song and I want to represent that song. I could take out to make my file smaller. I could take out every other, you know, every 500 milliseconds of that and it would sound really horrible, right? or I could be a lot more intelligent and instead basically, you know, if you look at early models like MP3, they're they're they're kind of like computational models of the brain. They stop, you know, they might stop at like the auditory nerve, but they're trying to put a model of how our brain would deal with sound, what we would hear, what we wouldn't. If this sound's present, and it's present at the same time as this sound, then this sound wouldn't be heard, but this sound would be. So we don't need to spend any of our our bits coding this sound. Instead, we just need to code this one. And so it becomes an intelligent way for the model and the algorithm of deciding what information needs to be represented and what doesn't to create the same, you know, the best ex perceptual experience which perceptual meaning what we get to you know take home. I think one of the things that's important then why I think whenever I had used to have to teach some of you know what it means to represent a rich experience with minimal data you think with minimal information um some of the acronyms that exist in in like mobile texting they've taken on a very rich life in internal >> yeah well those are simplistic ones but I think people can have communication now that we can't understand entirely This is because you have a 10-year-old daughter. Does she does she have communication by acronym that to you is cryptic >> sometimes. But I I have to figure it out then. But yes, but but the point is it that is an example of a lossy compression algorithm that actually has a much richer perceptual experience, right? And it often needs context, but it's still, you know, you're using few bits of information to try to represent a much richer feeling in a much richer state, right? And you know, if you look at different people, they're going to have, you know, bigger physiological experience dependent on, you know, how how they've grown up with that kind of context. >> It sounds to me, >> yeah, >> uh I don't want to um project here, but it sounds to me like you see the great opportunity of the of data compression. Like let's just stay with the use of acronyms in texting. That's a that's a vast data compression compared to the kind of speech and direct exchange that people uh engaged in 30 years ago. So there's less data being exchanged. Um but the experience is just as rich if not more rich is what you're saying, which implies to me that you look at it as generally neutral to to benevolent. Like it's good. >> It's just different. >> I'm coming up on 50 in a couple months. as opposed to somebody saying, "Well, you know, when I was younger, we'd write our boyfriend or girlfriend a letter. Uh, you know, I would um I would actually write out a birthday card. I would um go You'd have a face tof face conversation." And you got this younger generation that are saying, "Yeah, whatever." You know, this is like what we heard about, I used to trudge to school in the snow kind of thing. It's like, well, we have heated school buses now and we've got uh you driverless cars. So um I think this is important and useful for people of all ages to hear that the richness of an experience can be maintained even though the there are data or some elements of the exchange are being completely removed. >> Absolutely. But it's maintained because of the neural connections that are built in those individuals. Right. and that generation. I I always think of okay and the nervous system likes to code um along a continuum but like yum yuck or meh like do you think that that that a technology is kind of neutral like yeah you lose some things you gain some things or do you think like this is bad these days we hear a lot of AI fear we'll talk about that um or you hear also people who are super excited about what AI can do what smartphones can do I mean some people uh like my sister and her daughter love smartphones because they can communicate it gives a feeling of safety at a distance like quick communications are easier. It's hard to sit down and write write a letter. Um she's going off to college soon. So the question is like how often will you be in touch? It raises expectations about frequency but it reduces of contact but it reduces expectations of depth >> because you can do like a hey was thinking about you this morning and that can feel like a lot but a letter if I sent a letter home you know during college to my own like hey was thinking about you this morning love Andrew and be like okay like I don't know how that would be like well that didn't take long right so I think that there's a it's a seessaw you know >> you get more frequency and then it comes with different levels of you know expectation Sean those my daughter's at camp right now and we were only allowed to write letters for two weeks. >> Handwritten letters. >> Handwritten letters. How did that get over that? It's happening. I mean, >> I'd lost their home in a flood years ago. And um one of the only things I saved out of the flood, which is this >> and and I just brought these back because I I got them for my brother is the the they're this communication between one of my ancestors, you know, during the Civil War, like they were courting and that was all saved these letters back and forth between the women and you know, and it's, you know, with these it's like 1865. And >> you have those letters? >> I do. I do. I had them in my in my computer bag until flew up here and um but you know they were on parchment and even though they went through a flight they they you know they didn't run they say and it's this very different era of communication and it's wonderful to have that preserved because that doesn't translate right through um and without um that history in any case I am a hu huge advocate for integration of technology but it's for me the world is data and and I I do think that way. It's, you know, and and I I look at what the way my daughter behaves. I'm like, okay, well, what data is coming in? Why did she, you know, respond that way? And, you know, there's this an example I I can give. But, you know, you think we were talking about neuroplasticity. It's like we are the creatures of sort of three things. One is uh you know our sensory systems how they've evolved and be it from by you know the intrinsic noise that is you know causing our sensory receptors or the external stren you know I my brain is going to have access to about the same amount of information as someone with hearing loss if I'm in a very noisy environment and so suddenly you've induced you know you've compromised the data I have access to and then also our sort of experientially established priors right our prior is being if you think about the brain as sort of a basian model you things aren't always deterministic for us like they are for some creatures our brains having to take data and make decisions about it and respond >> basian we should just explain for people deterministic would be input A leads to output B yeah >> Beijian is it depends on the statistics of what's happening externally and internally yeah >> these are probabilistic models like there's a likelihood of A >> becoming B or there's a likelihood of A driving B but there's also a probability that A will drive C, D or F. >> Absolutely. And you know Frank and we should get into I mean some of the things that make us the most effective in our environments and just in interacting in the world is how fast and effective we are with dealing with those probabilistic you know situations. Those things where your brain it's it's like probabilistic inference is a great indicator of success in an environment. And you know, be it a work environment, be it just, you know, walking down the street and um how that's how do we deal with this like data that doesn't just tell us we have to go right or left, but there's a lot of different inputs and it's our sort of situational intelligence in the world. And there you we can break that down into a lot of different ways. In any case, we are the products of our, you know, our sensory systems, our experience, our priors, which are the statistics that and data we've had up until that moment that our brain's using to wait how it's going to behave in the decisions it makes, but also then our expectations, the context of that, you know, that have shaped where we are. And so there's this funny story like my daughter when she was two and a half, we're in the planetarium at the Smithsonian and we're watching, I think, one typical film you might watch in a planetarium. We started in LA, zoom out on our way to the sun, and we pass that sort of, you know, quintessential NASA image of the Earth, and it's totally dark and silent. And my daughter, as loud as she possibly could, yells, "Minions." And I'm like, "What's going on?" I'm like, "Oh, yes, of course." Her experientially established prior of that image is coming from the Universal logo. And you know, she never, you know, that says Universal. It was totally valid, but it was this very uh you know honest and true part of what it is to be human. Like each of us is experiencing very different you know having very different experiences of the same physical information and we need to recognize that but it is driven by our exposures and our priors and our sensory systems. It's sort of that trifecta and our expectations of the moment. And once you unpack that, you really start to rep and and appreciate the influence of technology. Now I am a huge advocate for technology improving us as humans, but also improving the data we have to make better decisions and the sort of insights that drive us. At the same time, I think sometimes we're pennywise pound foolish with how we use technology and the quick things that make us faster can also make us dumber and take away our cognitive capabilities. And you know where you'll end up with those that are using the technologies might be to to you know to write papers all the time are maybe well and we we we can talk about that more are putting themselves in a place where they are going to be compromised trying to do anything without that technology and also in terms of their their learning of that data that information. And so you start even ending up with bigger differentiations and cognitive capabilities by whether how you use a tool a a technology tool to make you better or faster or not. One of my sort of things I've always done is teach at Stanford that thus we also have that in common. >> I need to sit in on one of your lectures >> and you know but my my class there has been is called neuroplasticity and video gaming and um I'm a neurohysiologist but I'm I'm really a technologist. I like buildings. I like you know innovation across many domains and while that class says video gaming it's really more well video games are powerful in the sense that there's this sort of closed loop environment you give feedback you get data on your performance but you get to control that and know what you randomize how you build and what our aim is in that class is to build technology and games with an understanding of the neural circuits you're impacting and how you want to what you want to train I'll have um students that are musicians. I'll have students that are computer scientists. I'll have students that are, you know, some of Samford's top athletes. I've had a number of their top athletes go through my my course and um it's always focused on okay, there's some aspect of human performance I want to dissect and I want to really amplify the sensitivity or the the access to that type of learning in a closed loop way. Just for anyone that isn't familiar with the role or the history of gaming in the neuroscience space, you know, there's been some great papers in the past. Um, take a gamer versus a non-gamer just to start with someone self-identified. a typical gamer um actually has what we would call um more sensitive and this is your domain so you can counter me on this anytime but you know contrast sensitivity functions and like a contrast sensitivity function is um you know ability to see uh edges and differentiation um in a visual landscape. Okay, they can see uh faster and uh you know more they're more sensitive to that sort of differentiation. So than someone who says I'm not a video game player or or selfidentifies that way >> because they've trained it >> like like a first person shooter game which I've played occasionally in an arcade or something like that. Uh I didn't play a lot of video games growing up. I don't these days either but um yeah a lot of it is based on contrast sensitivity knowing are is that a friend or foe are you supposed to shoot them or not? Yeah. you have to make these decisions very fast. Yeah. Um like right on the threshold of of what you would call like reflexive like no no thinking involved but but it's just it's just rapid rapid iteration and decision-m and then the rules will switch. Yeah. >> Right. Like suddenly you're supposed to uh turn other other things into targets and other things into into >> you're spot on because then you take someone who that selfidentified non-gamer, make them play 40 hours of Call of Duty and now their contrast sensitivity looks like a video game player and it persists. You know, go back, measure them a year later, but you know, 40 hours of playing Call of Duty and I see the world differently, not just in my video game. I actually have foundational shifts in how I experience the world that give me more greater sensitivity to my situational awareness, my situational intelligence, real life. >> Yeah. Yeah. >> Yeah. Because that's a low-level processing capability. I love intersecting those when you can. But what's even I think more interesting is you also and there these were some this was a great study by Alex Puge um and Daphne um devel uh where it's not just the contrast sensitivity it's let's go to that next level where we were talking about basian like probabilistic decisions where things aren't deterministic um and 40 a video game player and I can train this they're going to make the same decisions as a nonvideo game player in those you know probabilistic envir inferential situations, but they're going to do it a lot faster. And so that edge, that ability to get access to that information is phenomenal, I think. And and and when you can tap into that, that becomes a very powerful thing. So like probabilistic inference goes up when I've, you know, played 40 hours of Call of Duty. But then what I like to do is take it and say, okay, here's, you know, a training environment. You know, I had a couple of uh de of Stanford's top soccer players on my in my course this this year and we got um our focus was okay, what data do you not have and how can we build a closed loop environment and make it something so that you're gaining better neurological access to your performance based on data like my acceleration, my velocity, not at the end of my, you know, two-hour practice, but in real time and getting auditory feedback. back so that I am actually tapping into more neural training. So, we had uh sensors, you know, like on on their calves that were measuring acceleration velocity and give able to g give us um feedback in real time as they were doing, you know, a sort of somewhat gamified training. I I don't want to use gamified, it's so overused, but let's say it's it felt like fun environment, but it's also based on computation of that acceleration data and what their targets were. It's feeding them different sonic cues so that they're building um they're building that resolution. When I say resolution, what I mean is, especially as a novice, I can't tell the difference between whether I've accelerated successfully or not. But if you give me more gradation in the feedback that I get, with that sort of that closed loop behavior, I start to my my neural representation of that is going to start differentiating more. So with that, that's where the auditory feedback. So they're getting that in real time and we you build that kind of closed loop environment that helps build that, you know, create greater resolution in the brain and greater sensitivity to differentiation. >> I'd love for you to uh share the story about your daughter um improving her swimming stroke, right? because she's not a D1 athlete yet. Maybe she will be someday, but she's a swimmer, right? And in the past, if you wanted to get better at swimming, you needed a swimming coach. And if you wanted to get really good at swimming, you'd have to find a really good swimming coach and you'd have to work with them repeatedly. Uh, you took a slightly different direction that really points to just how beneficial and inexpensive this technology can potentially be or relatively inexpensive. >> First, I'll say this. Number one is having good swimming coaches. >> Okay, sure. I'm not trying to do away with swimming coaches. parents who are uh data centric and and really like building technologies are sometimes maybe can be red herring distractions but hopefully not. >> Okay. All right. Well, yes, >> that's one of them. >> Let's keep the swimming coaches uh h happy. >> Yeah. So, for example, like you go and train with elite athletes and um if you go to a lot of um swimming camps where you're you or training programs, it's always about under you know work with cameras and and you know what what they're they're recording you. they're, you know, assessing your strokes. But the point is what I mean I you can use and I did this uh you know knowing the things that the coaches you or frankly you can go online and learn some of those things that matter to different strokes. You can use you know use perplexity labs use replet use some of these >> these are online resources. >> Yeah. Yeah. And you can build quickly build a computer vision app that is giving you data analytics on your strokes and in real time. >> So how's that work? You you're taking the phone underwater analyzing the stroke. >> In this case I'm using mobile phone so I'm doing everything above you know. >> Okay. So you're you're filming if you could walk us through this. So you film your daughter doing freestyle stroke for right or breast stroke or butterfly. There's a lot of core things that you know maybe you want to care about backstroke and freestyle. What's the you know and I am not a I was we used to run like I know you're a good runner but I am a runner I'm a rock climber less a swimmer but um you know things like the roll or how high they're coming above the water what's your you know what what's your velocity on a you know you can get actually very sophisticated once you have the data right and you know what's your velocity on entrance how much you know where how far in front of your your head is your arm coming in how you know what is um maybe There's again maybe there are things that you you know are obvious which is you want to know you know how consistent are your strokes and your cadence across you know the pool. Um so you don't just have your speed you suddenly have access to what I would call and and you'll hear me use this a lot better resolution but also a lot more analytics that can give you insight. Now, important thing here is, you know, my 10-year-old is not going to resp I'm not going to go tell my 10-year-old that she needs to change her her velocity on this head or stroke, but it gives me information that I can at least understand and help her know how something is going and how consistent she is on certain things that her coaches have told her to do. um you know and and what I love about the idea is look this isn't just for the ease of getting access to the type of data and information that would previously and I mean I do code in in a lot of areas but you don't have to do that anymore to build these apps in fact you shouldn't you should leverage you know AI for development of these types of tools >> you you tell AI to write a code so that it would analyze you know trajectory jumping into the pool how that could be improved if the goal is to swim faster. >> You you'd use AI to build an app that would allow you to do that so that you would have then access to that whatever the data is that you want to do. Yeah. So in that case you're trying to do better stroke analytics and and understand things as you move forward. Um you could do the same thing for running for gate for uh you could do you know in a work environment you can understand a lot more about where vulnerabilities are where weaknesses are. There are sort of two different places where I see this type of um AI acceleration and tool building really having major impact. It's on sort of democratizing data, analytics and information that would normally be reserved for the elite to everyone that's really engaged and that has a huge impact on improving performance because that kind of data is really you know useful in understanding um learning. It also has applications for, you know, when you're in a work environment and you're trying to better understand um success in that environment ac in in some process or skill of, you know, what you're doing. Um you you can gain different analytics than you otherwise would in ways that are become much more uh successful but also give you um new data to think about with regard to what I would call a digital twin. And when I use the word digital twin, the goal of a digital twin is not to digitize and represent a physical system in its entirety. It's to gain use different interoperable meaning data sets coming from different sources to gain insights you know digitized data of a physical system or a physical environment or physical world be it a hospital be it airplanes be it my body be it my fish tank to give me insights that are you know continuous and in real time that I otherwise wouldn't be able to gain access to >> we've known for a long time that there are things that we can do to improve our leap and that includes things that we can take things like magnesium thrienate, theanine, chamomile extract and glycine along with lesserk known things like saffron and valyan root. 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If you'd like to try Rora, you can go to roora.com/huberman and get an exclusive discount. Again, that's r o r a.com/huberman. We will definitely talk more about digital twins and but what I'm hearing is that it can be very um as nerd speak but domain specific. I mean, like the lowest level example I can think of, which would actually be very useful to me, would be a digital twin of my refrigerator that would place an order for the things that I need, not for the things I don't need. Um, eliminate the the need for a shopping list. Um, it would just keep track of like, hey, like you usually run out of strawberries on this day and this day. And it would just keep track of it in the background and the stuff would just arrive and it would just be there. And like eliminate what seemed like like, well, gosh, isn't going to the store nice? Yeah, this morning I walked to the corner store, bought some produce. I had the time to do that, the the eight minutes to do that, but really I I would like the fridge to be stocked with the things that I like and need, and I could hire someone to do that, but that's expensive. This could be done trivially and probably will be done trivially soon, and I don't necessarily need to even build an app into my phone. >> So, I like to think in terms of kind of lowest level, but highly useful >> and easily available now >> type technologies. There are a couple of areas like when it comes to students learning information. We've heard that, you know, AI, we we've heard of AI generally as like this really bad thing like, oh, they're just going to use AI to write essays and things like that. But there's a use of AI for learning. I know this cuz I'm still learning. I teach and learn all the time for the podcast, which is I've been using AI to take large volumes of text from papers. So this is an AI hallucinating just take like just take large volumes of text verbatim from from papers. >> Yes, >> I've read those papers literally printed them out, taken notes, etc. And then I've been using AI to design tests for me of what's in those papers because I learned uh you know about eight eight months ago when researching a podcast on how to study and learn best. The data all point to the fact that when we self test >> Yes. Especially when we self test away from the material like when we're being we're thinking oh yeah like what what is the cascade of hormones driving the cortisol negative feedback loop when I have to think about that on a walk. >> Yes. >> As opposed to just looking it up. It's the it's the self- testing that is really most impactful for memory because most of memory is anti-forgetting. This is kind of one way to think about it. So, what I've been doing is is having AI build tests for me and having ask me questions like, you know, uh what is the the the you know, the signal between the pituitary and the adrenals uh that drives the release of cortisol and and what layer of the adrenals does cortisol come from? >> And I love that >> and and so it's it's I'm sure that the information it's drawing from is is accurate, at least to the best of science and medicine's knowledge now. >> And it's just testing me and it's learning. This is what's so incredible about AI and I don't consider myself like extreme on AI technology at all. It's learning where I'm weak and where I'm strong at remembering things because I'm asking it where am I weak and where am I strong and they'll say oh like like naming and this and like like like third order conceptual links here need a little bit of work and I go test me on it and it starts testing me on it. It's amazing like I'm blown away that the technology can do this and I'm not building apps with AI or anything. I'm just using it to try and learn better. Whether you're building naps or you're building a tool, you're you're using it as a tool that's helping you optimize your cognition and find your weaknesses, but also give you feedback on your performance and and and accelerate your learning in this, right? Because it's the goal, but you're still putting in the effort to learn. And I think even the the ways that I'm using it to you with your computer vision with mobile devices, AI is a huge opportunity and tool that like using the cameras and the data that you've collected to, you know, have much more sophisticated input is is huge. Um, but in both of those cases, you're shaping cognition. You're shaping you're using data to enrich what you can know. and AI is just, you know, incredibly powerful and uh a great opportunity in those spaces. The the place where I think it is um and I I sort of separate it into literally just two categories. Maybe that's too simplistic. It's am I using and and this is true for any tool not just AI but am I using the tool am I using the technology in a way to make me smarter about in a and and let me have more information and make me more effective but also cognitively more effective gain different insights or am I using it to replace replace a cognitive skill I've done before to be faster and it doesn't mean you don't want to do those things I mean GPS in our car is a perfect example of a place where we're replacing a cognitive tool of, you know, to make me faster and more effective. And frankly, you know, you take away your GPS and in a city you drive around and and we're not very good. And >> I remember paper maps. I remember the early studies of the Hippoc campus were based on London taxi drivers that had mental maps of the city. >> Absolutely. >> That you know at with all due respect to London taxi drivers up until GPS like that those mental maps are not necessary anymore. >> No. And I mean they had more gray matter in their hippocampus and we know that and you look at them today and they they don't have to have that because the people in their back seats have more data have more information have eyes from the sky. I mean satellite data is so huge in our success in the future and you know it can anticipate the things that locally you can't and so it's been replaced but it it still means when you lose that data you don't don't expect yourself to have the same spatial navigation of that environment without it right >> I love your two your two batches right you're either using it to make you cognitively better or you're using it to speed you up but you have to be here's where I think >> cognitively or physically But you're still trying to gain insight and data and information that's making me a more effective human. >> Right. And I think that the the place where people are concerned >> Yes. >> including myself is when we use these technologies that eliminate steps, make things faster. >> Yeah. >> But we fill in the additional time or mental space with things that are neutral to detrimental. It's sort of like saying, "Okay, I can get all the nutrients I need from a drink that's 8 ounces." This is not true. But then the question is like, how do I make up the rest of my calories, right? Am I making up with also nutritious food, right? Um, let's just say that keeps me at a neutral health status or am I eating stuff that because I need calories that I'm not necessarily gaining weight, but I'm bringing in a bunch of bad stuff with those calories. is or in the mental version of this um things are sped up but people are filling the space with things that are making them dumber in some cases. There was a recent paper from MIT that I I actually it it was it is very much what I spend a lot of my time talking about but and and thinking about but um >> yeah could you describe that study? >> The upshot of the paper first was that people there's a lot less uh mental process or cognitive process that goes on for people when they use LLMs to write papers and they have they don't have the same transfer and they don't really learn the information. Surprise surprise. So, so that to just to briefly describe the study even though it got a lot of popular press, it's you know um MIT students writing papers using AI versus writing papers the oldfashioned way where you think and write. >> So there were three different categories. People who had to write the papers uh you know just with their using their brain only. Uh and that that would be case one. Case two would be I get to use search engines which would be sort of a middle ground. Again these are you know rough categories. And then a third would be I use LLMs to write my paper. And they're looking at you know sort of what kind of transfer happened what you know what kind of they were measuring neural response. So they were using EEG to look at neural patterns of uh across the brain to understand how much neural engagement happened during the writing of the papers and during the the whole process and then what they could do with that what they knew about that information down down the road. It's a really nice paper, so I don't want to want to diminish it in any way by summarizing it. But what I think is a really important upshot of that paper and also just how we talk about it that I liked was um they I I talk a lot about cognitive load always. And you can measure cognitive load and the diameter of your pupil and body posture and how people are thinking. It's really how hard is my brain working right now uh to solve a problem or just in my context. And there are a lot of different cues we give off as humans that tell us when we're under states of different load and cognitively and whether we are aware of it or not. And there's something called cognitive load theory that breaks down sort of what happens when our brains are under states of uh you know load. And that load can come from sort of three different places. It might be coming from intrinsic uh what you would call intrinsic information which is what and this is all during learning the intrinsic load cognitive load load would be from uh you know the difficulty of the material I'm trying to understand how you know really some things are easy to learn some things are a lot harder and that's intrinsic load extraneous load would be the load that comes from how the information is presented uh is it poorly taught is it poorly organized or also in the environment. If it's I'm trying to learn something auditorially and it's noisy, that's introducing extraneous cognitive load, right? It's it just it's not the information itself, but it's because of everything else happening with that data. And then the third is germaine cognitive load. And that's the load that is used in my brain to build mental schemas to build to organize that information to to really develop a representation of what that information is that I'm taking in. And that germaine cognitive load that's that's the work right and if you don't have gerine cognitive load you don't have learning really and what they found is basically the germaine cognitive load is what gets impacted most by using LLMs which is I mean it that it's a very obvious thing like that's >> meaning you don't engage quite as high levels of germanine cognitive load >> using LLMs you're not engaging the mental effort to build cognitive schema to build neural schemas and you sort of the mental representation of the information that you can interact with it later and you have access it to access to it later and this is really important because without that you won't be as intelligent on that topic that's for sure down the road let me give two examples I have a doctor I have a lawyer and both of them use LLMs extensively for searches say or for building information in one case it's for patient aggregation of patient data and in another case it's for you know history of case files and that is the GPS that's happening in those spaces and because those are the tools that are quickly adopted where you have someone that is maybe came you know from a different world has learned that information has gone and worked with data in a different way worked their representation of that information is going to be better at extrapolation it's going to be better at generalization it's going to be better at seeing patterns that you know would exist the brain that has done everything through LLMs is going to be in a place where they will get the answer for that relevant task or using the tools they have. But you're not the same level of um richness and depth of information or generalization or extrapolation for those topics as someone that has learned in a different way. There's a generational difference in understanding, not because they don't have the same information, but there is an an acknowledgement that there's a gap even though we're getting to the same place as as fast. And that's because of the learning that's happened. >> The gerine cognitive load. >> Absolutely. The cognitive load like you've got to do the work. your brain has to and you know what was beautiful about your descriptions Andy is when you were talking about how you were using it which I I love you know to test yourself find your weak vulnerabilities is you know and and actually in the paper in MIT which I think again these are things that are somewhat obvious but we just have to name I think we have to talk about them more is people with higher competency on the topic use the tools in ways that still engage more germaine cognitive load but helped accelerate their their learning it's you know where is the biggest vulnerability and gap. It's when it's especially in areas and topics where you're you're trying to learn a new domain fast or you're under pressure and you're not putting in the domain effort or you're not using the tools that you have access to that AI can enable. >> You're not using them to amplify your cognitive, you know, gain, but instead to deliver something faster, more rapid, and then walking away from it. I'm going to try and present two parallel scenarios >> in order to go further into this question of how to use AI to our best advantage to enrich our brains as opposed to diminish our brains. >> Mhm. >> So I could imagine a world because we already live in it where there's this notion of slow food like you cook your food, you get great ingredients from the farmers market like like a peach that quote unquote really tastes like a peach this kind of thing. you um you you make your own food. You you cook it and you taste it. It's just delicious. And and um I can also imagine a world where you order a peach pie online, it shows up and you take a slice and you eat it. And you could take two different generations of people, maybe people that are currently now 50 or older and people that are 15 or younger, and the older generation would say, "Oh, isn't that the peach pie that you made so much better? Like these peaches are amazing." And I could imagine a real scenario where the younger person 15 to 30 let's say would say like I don't know I actually really like the other pie. I like it just as well. And the older generation is like this like what are you talking about? Like this is how it's done. What's different? Well sure experience is different etc. But from a neural standpoint, from a neuroscience standpoint, it very well could be that it tastes equally good to the two of them, just differs based on their experience. Meaning that the person isn't lying. It's not like this kid um, you know, isn't as fine-tuned to taste. It's that their neurons acclimated to like what sweetness is and what contrast between sweet and saltiness is and what a peach should taste like cuz damn it, they had peach gummies and that tastes like a peach, you know. And so we can be disparaging of the kind of what we would call the lower level or diminished sensory input. >> Yeah. >> But it depends a lot on the neural what those neural circuits were weaned on. >> Couple of comments. I love the peach pie example. Making bread is another example of that. And in the 90s, everyone I knew when they graduated from high school got a bread maker that was shaped like a box and, you know, created this >> like loaf of bread with a giant, you know, rod through it. And it was just it was the graduation gift for many years. >> And um, you know, you don't see those anymore. And you know if you even look at what happened with like the millennial generation in the la you know in the last 5 years especially during the pandemic suddenly breadmaking sourdough that became a thing. What's the difference? You know, you've got bread. It's warm. It's, you know, with the bread maker, it's fresh and it is not at all desired relative to bread that takes a long period of time and is tactile and in the process and the making of it and you know is clearly much more ownorous than the other in its process of development. I think the key part is it's in in the appreciation of the bread. it. The process is part of it and that process is development of sort of the germaine knowledge and the commitment and connection to that humanness of development but also the tactile uh commitment the work that went into it is really appreciated in the same way that that peach pie for one comes with that whole time series of data that wasn't just about my taste but was also smell also physical also visual and saw the process you know evolve and build a different prior going into that experience and that is I think part of richness of human experience will it be part of the richness of how humans interact with AI absolutely or interact with robots absolutely so it's what are the relationships we're building and how are they you know how integrated are these tools these you know companions whatever they may be in our existence will shape us in different ways. What I am particularly I guess bullish on and excited for is the robot that optimizes my health, my comfort, my intent in my environment, in my you know be it in the cabin of a car, be it in the my my rooms, my spaces. >> So what would that look like if you uh could you give me the lowest level example? um like like would it be an assistant that helps you travel today when you head back to the Bay Area? Would it like what is this non-physical robot? >> And I think we already have some of these like it's the point where HVAC systems actually get sexy, right? Not sexy in that sense, but they're actually really interesting because they are the heart of, you know, >> HVAC systems, >> heating ventilation AC, >> but you think about a thermostat. You know, a thermostat right now is optimizing for you an AI thermostat optimizing for my behavior, but it's trying to save me resources, trying to save me money, but it's not doesn't know if I'm hot or cold. It doesn't know to your point, it my intent, what I'm trying to do at that moment where and this is, you know, speaks more to a lot of the the things you've studied in the past. You know, it doesn't know what my optimal state is for my goal in that moment in time, >> but it can very easily, frankly, you know, it can talk to me, but it can also know how my state of my body right now and what is going, you know, it's if it's 1:00 a.m. and I really need to work on a paper. >> You you know, my house should not get cold, but it also should be very, it should >> for me it shouldn't. I know for some people it should. >> Yeah. My my eight sleep mattress, which I love, love, love. And yes, they're a podcast sponsor, but I would use one anyway. It knows what temperature adjustments need to be made, >> right, >> across the course of the night. I put in what I think it it is best, but it's updating all the time now because it has updating sensors, like dynamically updating sensors. I'm getting close to two hours of REM sleep a night, which is outrageously good for me. >> Much more deep sleep, and that's a little micro environment. You're talking about integrating that into an entire home environment. >> Home vehicle. Yes. Because it needs to treat me as a dynamic time series. It needs to understand the context of everything that's driving my state internally. There's everything that's driving my state in my local environment, meaning my home or my car. And then there's what's driving my state externally, my in from, you know, my external environment. And we're in a place where those things are rarely treated, you know, interacting together for the optimization and the, you know, the dynamic interactions that happen. But we can know these things. We can know so much about the human state from non-cont sensors. >> Yeah. And we're right at the point where the sensors can start to feed information to AI to be able to deliver what effectively again a lower level example would be like the the cooling the dynamically cooling mattress or dynamically heating mattress. Like I discovered through the AI that my mattress was applying that and I was told that heating your sleep environment toward the end of the night >> yes >> increases your REM sleep dramatically whereas cooling it at the beginning of the night increases your deep sleep has been immensely beneficial for me to be able to shorten my total sleep need which is something that for me is like awesome because I I like sleep a lot but I don't want to need to sleep so much in order to feel great. Well, you you want to have your own choice about how you sleep. Yeah. Given the date, it's helping you have that. >> Sometimes I have six hours, sometimes I have eight hours, this kind of thing. >> Here's where I'm I get stuck and I've been wanting to have a conversation about this with someone, ideally a neuroscientist who's interested in building technologies for a very long time. So, I feel like this moment is a moment I've been waiting for for a very long time, which is the following. I'm hoping you can solve this for all of us, Bobby. >> We're talking about sleep and we know a lot about sleep. You got slow wave sleep, deep sleep, growth hormone release at the beginning of the night. You have less metabolic need then. Then you have rapid eye movement sleep which consolidates learning from the previous day. It removes the emotional load of previous day experiences. We can make temperature adjustments. You do all these things. Avoid caffeine too late in the day. Lots of things to optimize these known states that occupy this thing that we call sleep. And AI and technology is, I would say, is doing a really great job, as is pharmarmacology, to try and enhance sleep. Sleep's getting better. We're getting better at sleeping despite more forces um uh potentially disrupting our sleep, >> like smartphones and noise and city noise, etc. Okay, >> here's the big problem in my mind is that we have very little understanding or even names for different awake states. We have names for the goal like I want to be able to work. Okay, what's work? What kind of work? Uh I want to write a chapter of a book. What kind of book? A non-fiction book based on what? But like we don't we talk about alpha, beta waves, theta waves, but I feel like as neuroscientists, we have done a pretty poor job as a field of defining different states of wakefulness. And so the like the technology AI and other technologies are don't really have they don't know what to to shoot for. They don't know what to help us optimize for. Whereas with slow wave sleep and REM sleep like we've got it. I ask questions of myself all the time like is my brain and what it requires in the first three hours of the day anything like what my brain requires in the last three hours of the day if I want to work in each one of those three-hour compartments. like and so I think like we don't really understand what to try and uh adjust to. So here's my question. Do you think AI could help us understand the different states that our brain and body go through during the daytime? Give us some understanding of what those are in terms of body temperature, focus ability, etc. And then help us optimize for those the same way that we optimize for sleep. Because whether it's a conversation with your therapist, whether or not it's a podcast, whether or not it's playing with your kids, whether or not it's Netflix and chill, whatever it is, the the goal and what people have spent so much time, energy, money, etc. And whether or not they're drinking alcohol, caffeine, taking rolin or aderall, or running or what, like humans have have spent their entire existence trying to build technologies to get better at doing the things that they need to do. And yet we still don't really understand waking states. So can AI teach it to us? Can AI teach teach us a goal that we don't even know we have? >> Can AI teach it to us? I would say AI is part of the story. But before we get AI, we need better more data. Not just me, right? So maybe I am very focused right now, but without my belief and this is my perspective is imagine I I'm very focused right now. I need to know the context of my environment that's driving that. Like what are what what's in that environment? Is it internal focus that's gotten me there? What what is my environment? What is that external environment? So the understanding my awake state for me is very dependent on the data and interactions that happen from these different environments. Let me give an example like if I'm in my home or I'm in a say I'm in a vehicle, all right, and you are measuring information about me and you know I'm under stress or you know I'm uh experiencing joy or I'm or heightens attention right now. Some different states you may want to uh have my home or my system react to mitigate. Well, like if you get sleepy in a self-driving in in a smart vehicle, >> it will make adjustments >> potentially. It will make adjustments, but not necessarily right for you. That's an important part is optimizing for you personalization and how a system responds. And you know, it can make adjust any home, an HVAC system or the the internal state of a vehicle is going to adjust, you know, sound, background sound, music. It's going to adjust, you know, whatever whether it can haptic feedback, temperature, lighting, you know, any number of, you know, position of your, you know, your chair dynamics of what's in your space. All of these different systems in my home or my my other what what my vehicle if it or some other system can react, right? But the important thing is how you react is going to shift me. And the goal is to not measure me but to actually intersect with my state and move it in some direction right some >> yeah I always think of devices as good at measurement or uh modification >> right >> measurement or modification measurement is critical and that's yeah meas but measurement not just of my me but also of like my environment and understanding of the external environment this is where like things like Earth observation and understanding, you know, we're getting to a place where we're getting uh image, you know, really good image quality data from sat the the satellites that are going in the sky at at much lower um uh lower distances so that you now have, you know, faster reaction times between technologies and the information they have to understand and be dynamic with them. Right? Can you give me an example where that impacts everyday life? Are we talking about like weather analysis? >> Sure. Weather predictions, uh, car environ, you know, things happening. >> And what about traffic? Why haven't they solved traffic yet given all the knowledge of of um object flow and how to optimize for object flow? And we've got satellites that can basically look at at traffic and I mean and open up roads dynamically like change number of lanes. What why isn't that happening? The traffic problem gets resolved when you have autonomous vehicles in ways that don't have like the the human side of things. >> That gets resolved. >> It does like >> autonomous vehicles. >> Only autonomous vehicles. You would probably you don't have traffic in the ways that you do with >> goodness. That's reason alone. >> That's reason alone to to shift to autonomous vehicles. >> It is that injection from human the human system that you know is interrupting all the models. I think the world right now we think about wearables a lot. Wearables track us. You have smart mattresses um which are wonderful for understanding. So there's so much you learn while you know from a smart mattress and ways of also both measuring as well as intervening to optimize your sleep which is the beauty uh and it's this nice incredible period of time where you can measure so many things. Um but you know in our home so I was I use the example of a thermostat right? it it's pretty, you know, frankly dumb about what my goals are or what I'm trying to do at that moment in time, but it doesn't have to be. And there are, you know, there's a company, Passive Logic. I love them. Uh they actually have, I think, some of the smartest uh digital twin HVAC systems, but you know, their sensors measure things like sound. They measure carbon dioxide, uh your carbon, your CO2 levels, like when when we breathe, we give off CO2, you know. So imagine, you know, there's a dynamic mixture of acetone, isoprene, and carbon dioxide that's constantly exchanging when my, you know, when I get stressed or when I'm feeling, you know, happiness or suspense in my my in my state. And that dynamic sort of cocktail mixture that's in my breath is both an indicator of my state, but it's also something that, you know, it's just the spaces around me, you know, have more information to contribute about how I'm feeling and can also be part of that solution in ways that don't I don't have to have things on my body, right? So, I have sensors now that can measure CO2. You can watch my TED talk. I have given examples. We brought people in when I when I was at Dolby and had um had them watching Free Solo, you know, the Alex Hold movie where they're climbing LCAP >> stressful. >> So carbon dioxide's heavier than air. So we can measure we could measure carbon dioxide from s, you know, just tubes on the ground and you could get the real-time differential of CO2 in there. And >> were they scared throughout? >> No. Well, but it's I mean I like to say we broadcast how we're feeling, right? And we do that wherever we are. And in this uh you could look at the time series of carbon dioxide levels and be able to you know know what what was happening in the film or in the movie without actually having it annotated. You could tell where he summited where he had to abandon his climb where he hurt his ankle. >> Absolutely. There's another study I forget who the authors are and they're you know they've got different audiences watching Hunger Games and you know different days different people you can tell exactly where Katniss's dress catches on fire and uh you know it's like we really are sort of you know it's like digital exhaust of how we're feeling but you know and and our thermals we you know radiate the things we're feeling um I'm very um bullish on the power of you know our eye or in in representing our cognitive load our stressors >> our Okay. >> Our eye. Yes. Like the diameter. >> Our eye. >> Our >> Yeah. Our eye. Sorry. Our our literally our eyes. Our pupil pupil size. >> Yes. Yes. Yes. I you know back when I was a physiologist I always you were I've worked with a lot of species on in you know understanding information processing internally in cells but also then I you would very often use pupilometry as an indicator of you know perceptual engagement and experience. >> Yeah. Bigger pupil mean more arousal higher levels of alertness. >> Yeah. more arousal, cognitive load or you know obviously lighting changes but the the thing that's changing from you know >> 20 years ago 15 years ago it was very expensive to track the kind of resolution and data to you know leverage all of those autonomic nervous system you know deterministic responses because those ones are deterministic and not probabilistic right those are the ones that it's like the body's reacting even if the brain doesn't say anything about >> detection and uh but Today we can do that with I mean do it well we can do it right now with a you know open source software on our laptops or our mobile devices right and every pair of smart glasses will be tracking this information when we wear them uh so it is becomes a channel of data and you know you it may be an ambiguous signature in the sense that there's you know changes in lighting there's changes am I aroused or am I >> those can be adjusted for right like if you you can you can literally take a measurement wear eyeglasses that are measuring pupil size. >> Um, the eyeglasses could have a sensor that detects levels of illumination in the room >> at the level of my eyes. >> Um, it could measure how dynamic that is and we just make that the denominator in a fraction, right? And then we just look at changes in pupil size as the numerator in that fraction, right? Um, more or less you just have to have other sensors. >> All you need to do is cancel. So as as you walk from a shadowed area to a brighter area, sure the pupil size changes, but then you can adjust for that change, right? just like normalize for that and you end up with an index of arousal, >> right? >> Which is amazing. You could also use the index of of illumination as a useful measure of like are you getting uh compared to your vitamin D levels uh to your levels of maybe you need more illumination in order to get more arousal. Like it could tell all of this. It could literally say hey take a 5minute walk outside in to the left after work and you will um get your your require your photon requirement for the day. you know, this kind of thing, not just measuring steps. All this stuff is possible now. >> I just don't know why it's not being integrated into single devices more quickly >> because you'd love to also know that person's blood sugar instead of like drawing their blood, taking it down to like you think in the with with the resident that's been up for for 13 hours because that's the standard in the field and they're making mistakes on a on a on a chart. It's like I think at some point we're just going to go I can't believe we used to do it that way. It's crazy. >> Yeah. No, and it's a lot of the consumer devices and just computation we can do from you know whether it's cameras or excalent or you know other data in our environments that tell us about our physical state and some of these situations that you're talking about a lot of the I mean why isn't it happening a lot of reasons are simply the regulatory process is antiquated and not up to keeping up with the acceleration of innovation that's happening you know getting things through the FDA even if they're you deemed uh you know in the same ballpark and supposed to move fast. you know, uh, with the regulatory costs and processes is really high. And >> you know you end up many years you know down the road from when the capability and the data and technology actually you know should have arisen to be used in a hospital or to be used in a place where you actually have that kind of appreciation for the data you know appreci and use. The consumer grade devices for tracking of data of our biological processes are on par and in many cases surpassed the medical grade devices. And that's because they they just have but then they will have to bill what they do and what they're tracking in some way that is consumer you know is not making the medical claims to allow them to be able to be you know continue to move forward in those spaces. But there's no question that that's that's a big part of what can you know holds back the uh availability of a lot of these devices and capabilities. I'd like to take a quick break and acknowledge one of our sponsors, Function. Last year, I became a Function member after searching for the most comprehensive approach to lab testing. Function provides over 100 advanced lab tests that give you a key snapshot of your entire bodily health. This snapshot offers you with insights on your heart health, hormone health, immune functioning, nutrient levels, and much more. 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There's so many things related to your mental and physical health that can only be detected in a blood test. The problem is blood testing has always been very expensive and complicated. In contrast, I've been super impressed by function simplicity and at the level of cost, it is very affordable. As a consequence, I decided to join their scientific advisory board and I'm thrilled that they're sponsoring the podcast. If you'd like to try Function, you can go to functionhealth.com/huberman. Function currently has a wait list of over 250,000 people, but they're offering early access to Huberman podcast listeners. Again, that's functionhealth.com/huberman to get early access to function. Okay, so I agree that we need more data and that there are a lot of different sensors out there that can measure blood glucose and sleep and um temperature and breathing and all sorts of things, which raises the question of are we going to need tons of sensors? I mean, are we going to be just wrapped in sensors as clothing? Are we going to be wearing 12 watches? Uh what's this going to look like? >> I'm an advocate for fewer things on, you know, not having all this stuff on our bodies. I'm, you know, there's so much we can get out of the computer vision side, you know, from how, you know, the cameras in our spaces and how they're supporting us in our rooms, in our the sensors on our in our um you know, I brought up HVAC systems earlier. So now you've got you effectively a digital twin that's track, you know, and sensors that are tracking my metabolic rates just in my space. They're tracking uh carbon dioxide. They're tracking sound. You're getting context because of that. You're getting intelligence. And now you're able to start having more information from, you know, what's happening in my environment. The same is true in my my vehicle. You can tell how I'm whether I'm stressed or how I'm feeling just by the posture I have it sitting in my car, right? And you need AI. This is AI interpretation of data. But what's driving that posture might be coming from also an understanding of what else is happening in that environment. So it's suddenly this con with contextual intelligence uh AIdriven understanding of what's happening in that space that's driving you know the state of me and how do I you know I keep leaning to the side because I'm talking thinking about you know my the way I move and sit is you know it's a proxy for what's actually happening inside me and then you've also got data around me coming from my environment what's happening you know if I'm driving a car or what's happening in my home in my you know in in the weather in not threats that might be outside in noise that's happening not inside the space but things that give context to have more intelligence with the systems we have so I'm a a huge believer in you don't we aren't anywhere until we have integration of those systems between the body the local environment and the external environment And we're finally at a place where AI can help us start integrating that data. Um, in terms of wearables though, uh, you so obviously some of the big companies, we've got the watch we have on our hand has a lot of information that is very relevant to our bodies. Um the devices we put in our ears. You may not realize but you know a dimesized patch in your in in your consc we can use we can know heart rate pul blood oxygen level uh because of the the electrical signature that your eye produces when it moves back and forth. we can know what you're looking at just you know in from uh measuring a signature measuring um your um electrocul ocular in your ear we can measure EEG electronogs you can also get you know eye movements out of electronograms but you can get attention you can know what people are attending to based on signatures in their ear so our earbuds you know that become sort of a window to our state um and you've got a number of companies working on that right now. Uh, you know, so do we need to wear lots of different sensors? No. Do we need to have the sensors, the data we have, whether it's on our bodies or off our bodies, be able to, you know, work together and not be proprietary to just one company, but to be able to integrate great with other companies. That that becomes really important. You need integrative systems so that the the data they have can interact with the systems that surround surround you or surround my spaces or the mattress I'm sleeping on. Right. >> Um because you've had a lot of specialty of design come from different developers and that's partly been a product of again the the FDA and the regulatory pathways because of the cost of development. It tends to move companies towards specialization unless they're very large. >> But where we're at today is you're going, you know, we're getting to a point where you're going to start seeing a lot of this data get integrated. I I think and and by all means, hopefully we're not going to be wearing a lot of things on our bodies. I sure as heck won't. You know, the more we put on our bodies, it affects our gate. It affects it has ramifications in so many different ways. Uh when I got here, I was talking to some of the people that work with you and they're like, "Well, what what wearables do you wear?" And I actually don't wear many at all. And you know, I I have worn rings, I've worn watches at different times, but for me, the importance is the point at which I get insights that, you know, I am a big believer in um as little on my body as possible when it comes to wearables. One interesting company that I think is uh worth mentioning is Pyson. and Python, you know, again, they've got a form factor that's, you know, like a Timex watch or they're partnered with Timex, but they're measuring um are you familiar with Python? >> No. >> Okay. So, they're ma measuring psycho motor vigilance. So you know really trying to understand it's like a ENG electron neurom modulation and they're trying to understand fatigue and and neural attentiveness in a way that is you know continuous and useful for say high-risk operations or uh training uh you whether be it in sport but what I like about it is it's actually trying to get at a higher level cognitive state from the biometrics or the that you're measuring. And that to me is an exciting really exciting direction is when you're actually doing something that you could make a decision about how I engage in my work or how I engage in my training or my life based on that data about my cognitive state and how effective I'm going to be. >> And then I can start associating that data with the other data to make better to have better decisions, better insights at a certain point in time. And that becomes that's really your digital twin. >> It's interesting earlier you said you don't like the word gamification. >> But um one thing that I think has really been effective in the sleep space has been this notion of a sleep score where people aspire to get a high sleep score. >> Um and if they don't they don't see that as a um a disparagement of them but rather that they need to adjust their behavior. So, it's not like, oh, I'm a terrible sleeper and I'll never be a good sleeper. It gives them something to aspire to on a night by basis. >> Yes. >> And I feel like that's been pretty effective. When I say gamification, I don't necessarily mean competitive uh with others, but I mean um encouraging of oneself, right? So I could imagine uh this showing up in other domains too um for wakeful states like you know like I spend the I had very few highly distracted you know work bouts or something like that like I'd love to know at the end of my day I had three really solid work bouts >> um of an hour each at least um that would feel good like that was day well spent even if you know I didn't accomplish what I wanted to in its entirety like I I put in some really good solid work. Right now, it's all very subjective. Uh we know that gamification of steps was very effective as a public messaging. You know, 10,000 steps a day. We now know you want to get somewhere exceeding 7,000 as a threshold. But if you think about it, we could have just as easily said, hey, you want to walk at a at a reasonable pace for you for 30 minutes per day. But somehow the counting steps thing was more effective because people I know who are not fanatic about exercise at all will tell me I make sure I get my 11,000 steps per day. Like people tell me this. I'm like oh okay. Like so apparently it's a meaningful thing for people. Um so I think quantification of performance um creates this aspirational state. Mhm. >> Um so I think that can be very useful >> data and and h understanding the quantification that you're working towards is really important. Those are, you know, summary summary statistics effectively that maybe they're good on some level to aim for. If it means that people move more, >> all for it, right? And it's something that if I didn't move as much before and I didn't get up and I didn't do something, then you know, and this is making me do it. That's awesome or that's great. But it's also great when now through like a computer vision app I can understand it's not just 10,000 steps but maybe there's you know an you know a small battery of things I'm trying to perform against that are helping shape me neurally with the feedback and the targets that I'm getting so that there's a little more there's more nuance towards achieving the goal I'm aiming for which is what I'm all about from a neuroplasticity perspective. So I just don't like the word gamification. I believe everything should be fun or everything training can be fun and gamified in some ways. Um, you know, again, like my life has been predominantly in industry, but I've always, you know, I love teaching and I've always been at Stanford to, you know, really there I try to it's it's how do I use technology and and merge it with the human system in a way that does help optimize learning in and training in a way that is from a sort of neural circuit first perspective. you know, how do we think about the neural system and use, you know, this more enjoyable, understandable target to to engage with it. One of my favorite examples though is there was a a period it was right around 2018 2020 and from 2018 to 2020 20 and into the pandemic where you know there became uh the students I I noticed had a much more uh there there were a lot of projects their final project they can build whatever they want um and you know they've had to do projects where they build neural brain computer interfaces they've had to build projects in VR they've had to build AR projects they've had to build projects that you know use um any sort of input device you know they have to use different sensor driven input devices and that's all part of what they develop and around 2018 2020 I started to see almost every project had a wellness component to it which I loved I thought that was and it was a very notable shift in like the student body and maybe you've seen that too but I still got this like one of my favorite games today it was this VR game where I'm you in a morg. I wake up. I've got to solve an escape room. I've got zombies that are coming out of me and they're climbing out of the morg and they're getting closer and there's people breathing on my neck and you know and everything. And it's a wellness app. Go figure. It was their idea of look, this is what I feel like. I've got to because I'm also measuring my breath and heart rate and I've got to keep those biological signatures. like everything about how the zombies in solving my escape room problems, they're going to get closer to me if my breath rate goes up, if my heart rate goes up. I've got to keep >> So, it was about stress control basically. >> Exactly. Yes. But it was in that environment and it was, you know, realized for them how they felt, but Yeah. And you can do it in much simpler ways, but at least I I'm a huge fan of how do we use the right quantification to develop the right habits, the right skills, the right acuity or resolution in a domain we might not or an area where we might not be able to break it into the pieces we need, but it's going to help us get there because my brain actually needs to now learn to uh understand that different, you know, that sophistication. Yeah, it's clear to me that in the health space, giving people information that scares them is great for getting them to not do things, but it's very difficult to scare people into doing the right things. You need to incentivize people do the right things by making it engaging and fun and quantifiable and yeah. Um, you know, I like the example of the zombie game. Um, okay. So, fortunately, we won't have to wear uh dozens of sensors. Um, they'll be more integrated over time. I'm I'm happy to walk through a cheat sheet later after you know for building out like a computer vision app if if you know for quantifying some of you you know some of these more personalized domain related things that people might want to do if >> that would be awesome. Yeah. Yeah. And then we can we can post a link to it in the show not captions because I think that the example you gave of of you know creating an app that can analyze swimming performance running gate focus what you know focused work bouts I think that's really intriguing to a lot of people but I think there's a at least for me there's a a gap there between hearing about it thinking it's really cool and and how to implement. So I would certainly appreciate it. I know the audience would too. >> I mean just in >> that's very generous of you. Thank you. >> Yes. Absolutely. and and you know we're in an era where everyone all you hear about is AI and AI tools and there are tools that absolutely accelerate our capabilities as humans but you know we we gave the examples of talking about some you know some of the LLMs I mean I I sat next to for we we went to Cal I sat next I was at a a film premiere and I was sitting it there I was sitting next to a few students who happened to be from Berkeley and they said to me you know they were computer science students and double engineering and one of them when he knew what I talk about or care about he's like you know I'm really worried my my peer group like my peers can't start a paper without chat GPT and you know it was a truth but it was also a concern so they understand the implications of what's happening and you know that's on one level we're in an era of agents everywhere and you know I think Reed has said that there's you know a number of people have said you we won't we'll be using agents AI agents for everything at work in in the next five years and um some of those things we need to use agents will accelerate um they will accelerate capability they will accelerate short-term revenue but they also will diminish workforce capab you know cognitive uh cognitive skill and as a user of agents in any environment as a you know an owner of companies employing agents you have to think hard about whi what the near-term and long-term ramifications. Doesn't mean you don't use your agents in places where you need to, but you need to without the gerine cognitive load. There there is a different dependence now that you have to have down the road. But also you have to think about how do you how do you engage with the right competence to keep your humans that are in you know engaged with you know developing their cognitive skills and their gerine cognit their their mental schemas to be able to support your systems down the road. >> Let's talk more about digital twins. >> Sure. Um, I don't think this concept has really landed uh squarely in people's minds as as like a specific thing. I think people hear AI, they know what AI is more or less. They hear about a smartphone, they obviously know what a smartphone is. Everyone uses one, it seems, but um, what is a digital twin? I think when people hear the word twin, they think it's a twin of us. Earlier you pointed out that's not necessarily the case. It can be a useful tool for some area of our life but it's not a replica of us. Correct. >> Not at all in the ways that I think are most relevant. Maybe you know there are some you know side cases that think about that. And so like first two things to think about. One when I talk about digital twins to companies and such I I like to frame it on um how it's being used how the immediiacy of the data from the digital twin. So, let's go back 50 years. An example of a digital twin that we still use, air traffic controllers. When an air traffic controller sit down sits down and looks at, you know, a screen, they're not looking at a spreadsheet. They're looking at a digitization of information about physical objects. That is meant to give them fast reaction times, make them understand the landscape as effectively as possible. We would call that situational awareness. I've got to take in data about the environment around me and I've got to be able to action on it as rapidly as quickly as possible to make the right decisions that mitigate any potential you know things that I you know are determined to be pro you know problems or risks right and so that's what you're trying to engage a human system you know the visualization of that data is important or doesn't have to be visualization the interpretation of it right and it's not the raw data it's again it's how is that data you know represented you want the key information in a way that the salient most important information in this case you know about planes h is able to be acted on by that human or even autonomous system right >> could you give me an example where in like a more typical home environment >> we're both into uh reefing and um you know I built a aquacultured reef in my kitchen partly because I have a a child and I wanted her to understand I I love I I of it myself. So don't get that wrong. It wasn't just all but to understand sort of the fragility of the ecosystems that happen in the ocean and things we need to to worry about, care about and and and all. And um you know initially when I started and maybe you know this was is not something you encountered, but when you build aqua a reef or a reef tank and and do saltwater fish, you're uh a couple things. you're doing chemical measurements by hand usually um you know weekly bi-weekly uh there's a whole you know like 10 different chemicals that you're measuring and I would have my daughter doing that so that she would do the science part of it and you're trying to you know you know the ranges the tolerances you have and you're also observing this ecosystem and looking for problems and by the time you see a problem you're reacting to that problem and I can tell you it was very unsuccessful. I mean there's lots of error and noise and human measurements. There's you don't have the right resolution of measurements. When resolution I mean I I'm every other you know every few days is not enough to track a problem. Uh you also have the issue of you know you're reactive instead of being proactive. It's just you're not sensing things that where you're the point at which it's visible to you. It's probably too late to do anything about it. So if you look at my fish tank right now or my reef tank right now um I have a number of digital sensors in it. I have dashboards. I can track a huge chemical assay that is tracked in real time so that I can go back and look at the data. I can understand I can see oh there was a water change there. Oh the the rod tank you my my I can tell what's happening by looking at the data. I have you know and you know this you've got your spe the spectrum of your lights is on a cycle of effect that's representative of the environment that the corals you're aquaculturing would you know that their their systems their deterministic systems are looking for right and so you've built this ecosystem that when I look at my dashboards I have a digital twin of that system and it it my tank is very stable my tank knows what's wrong what's happening I can look at the data and understand that import an event happens somewhere that could have been mitigated or some I can understand that something's wrong quickly before it even shows up. >> It's amazing. I mean I think for people who aren't into reefing um might ask like you know I know people that are and multiple people in my life are soon to have kids. Um most everybody nowadays has a has a camera on the the sleeping environment of their kids so that if their kid wakes up in the middle of the night they can see it, they can hear it. Um so camera and microphone do you think we're either have now or soon we'll have AI tools that will help us um better understand the health status of infants like parents learn intuitively over time based on um diaper changes based on um all sorts of things cries frequency of illnesses etc and their kids how well their kids are doing before they kids can communicate that do you think AI can help parents be better parents by giving real-time feedback on the health information of their kids. Not just if they're awake or asleep or if they're in some sort of uh trouble, but really help us adjust our care of our young like what's more important for our species than, you know, supporting the the growth of our uh next generation. >> No, absolutely. But I' I'd even more on the biological side. I mean, so think about digital twins. There's and I'll get to babies in a moment, but just you if you've ever bought a plane ticket, which any of us have today, that's a very sophisticated digital twin. Not the, you know, not the air traffic controllers looking at planes, but the pricing models for what data is going into driving that price in uh real time, right? you you might be trying to buy a ticket and you go back an hour later or half hour later and it's like double or maybe it's gone up in you and that's because it's using constant data from environments from things happening in the world from geopolitical issues from things happening in the that's driving that price and that is very much an AIdriven digital twin that's driving you know the sort of value of that that ticket and so there there are places where we use digital twin so that would sort of the example of something that's affecting our lives, but we don't think about it as a digital twin, but it is a digital twin. >> And then you think about a different example where you've got a whole sandbox model. The NFL might have a a digital twin of every player that's in the NFL, right? They're they know data. They they they're tracking that information. They know how people are going to perform many times. What do they care about? They want to anticipate if someone might be, you know, high risk for an injury so that they, you know, can mitigate it. >> They're using those kind of data. >> Absolutely. Yeah. >> Interesting. I think the word twin is the misleading part. I feel like digital twin I feel like >> soon that nomenclature needs to be replaced because people hear twin they think a duplicate of yourself. >> Yes. >> I I feel like these are are um >> well it's a duplicate of relevant data and information about yourself but not just trying to like what's the purpose in emulating myself? It's to emulate key. So imagine me as a physical system. I'm going to digitize some of that data, right? And whatever, you know, data I have, I'm it's how that data I interact with it to make intelligent insights and feedback loops in the digital environment about how that physical system is going to behave. Right. >> Okay. So, it's a digital representative. >> Yes. >> More than a digital twin. Yes. I think I'm I'm not trying to >> There are many digital twins in any digital twin. So like even you know you've got data you live with lots of digital what I would I think the world would the digital twin whatever nomenclature would say is a digital twin but I like a digital representative and it's it's informing some aspect of decision- making and it's many feedback so I'm digitizing different things I'm you know and and in that situational awareness model like just can I give a quick example so imagine I so I I can digitize an environment right I can digitize are the the space we're in right now and would that be a digital twin? So first there in situational awareness there's the state of okay so what's the sort of sensor you know limitations the acuity of the data I've actually brought in okay so that's like perception same with our sensory systems and then there's comprehension so comprehension would be like okay that's a table that's a chair that's a person now I'm in those sort of semantic units of relevance that the digitization takes then there's the insight so what's happening in that environment. What do I do with that? What is, you know, and and that's that's where things get interesting and that's where a lot of, you know, I think the future of AI products is because then it's the feedback loops of what's happening with those, you know, that input and that data. And it it becomes interesting and important when you start having multiple layers of relevant data that are interacting that can give you the right insights about what's happening, what to anticipate and you know in that space. But that's all about our situational awareness and intelligence in that environment. >> Yeah, I I can see where uh these technologies could take us. I think for the general public right now, AI is super scary because we hear most about AI developing its own forms of intelligence that turn on us. >> I think people are gradually getting on board the idea that AI can be very useful. We have digital representatives already out there for for us in these different domains. >> Absolutely. And >> I think being able to customize them for our unique challenges and to and our unique goals is really what's most exciting to me. >> I love that because I I mean I think what I was trying to say is exactly what you said. Look, there they are out there and these are effectively digital twins. Every company that's you're interacting with social media has an effectively a digital twin of you in some place. It's not to emulate your body but it's to emulate your behaviors. So to you know in those spaces or you're using tools that are optim you know have digital twins you for things you do in your daily life. So the question is how do we harness that for our success for individual success for understanding and agency of what that can mean for you? If the NFL is using it for a player, you can use it as an athlete, meaning as an athlete at any level, right? And it's that digitization of information that can feed you. For my baby, you can better understand a great deal about how they're successful or what isn't successful about them. and you know some of not not your baby's always successful I don't want to say but what is maybe not you know working well for them you know the things that but um I would tend to say uh the the exciting places about digital twins come in and really once you start integrating the data from different places that tell us about the success of our systems and those are anchored with actual successes right I think You used an example of your mattress and sleep and or even like you one I liked was I had three good very focused work sessions. You may have used different words Andy but the idea is okay you've had those but it's when you can correlate it with other systems and other outputs that it becomes powerful. That's the way a digital representative or a digital twin becomes more useful is thinking about not you know the resolution of the data where the data source where the data is coming from meaning whether is it biometric data is it environmental data you know is it the context of the state of what else was happening during those work sessions and how is that something that I don't have to think about but AI can help me understand where I'm successful and what else drove that success or what drove that state because it's not just my success, it's intelligence. It's I like to call it situational intelligence is sort of the overarching goal that we want to have and that involves you know my body and systems having situational awareness but it's really you know a lot of um integration of data that you know AI is very powerful for thinking about how does it optimize and give us the the insights it doesn't have to do just have systems behave but it can give us the insights of how effectively we can act in those environments >> yeah I think of AI as being able to see what we can't see. Yes. So, for instance, if I had some sort of AI representative that, you know, paid attention to my work environment and to my ability to focus as I'm trying to do focused work. >> And it turned out, obviously I'm making this up, but it turned out that every time my um my air conditioner clicked over to silent or back to on that it would break my focus for the next 10 minutes. Yes. >> And I wasn't aware of that. And by the way, this for people listening, this is entirely plausible because so many of our states of mind are triggered by cues that we're just fundamentally unaware of >> or that it's always at the 35 minute mark that my eyes start to have to reread words or lines um because somehow my attention is drifting um or that it's paragraphs of longer than a certain length. It's a near infinite space for us to explore on our own, but for AI to explore it, it's straightforward. And so it it can see through our literal our cognitive blind spots and our functional blind spots. I and I think of where people pay a lot of money right now to get information to get around their blind spots are things like um when you have a pain and you don't know what it is, you go to this thing called a doctor. >> Or when you have um a uh a problem and you don't know how to sort it out, you might talk to a therapist, right? People pay a lot of money for that. I'm not saying AI should replace all of that, but I do think AI can see things that we can't see. >> Two examples to your point, which I I love the, you know, the reading potentially you're, you know, there's a point at which you're experiencing fatigue and you want, you know, you ideally, much like the fish tank, you want to be not reactive. You want to be proactive. You want to mitigate it. you know stop or you could have your devices can have that integration of data and respond to give you feedback when your either your mental acuity your vigilance or your just effectiveness has waned right but also on the level of health uh a we know AI is you know huge for uh identifying a lot of different pathologies out of you know data that as humans we're just not that good at at discerning you know our voice in the last 10 years we've become come much more aware of the different pathologies that are um can be discerned from AI app, you know, assessments of our speech and not what we say, but how we say it. >> Yeah, there's a lab up in University of Washington, um I think it's Sam Golden's lab who um uh working on some really impressive algorithms to analyze speech patterns as a way to predict suicidality. >> Oh, interesting. and to great success where people don't realize that they're drifting in that direction. >> Um and phones can potentially warn people, >> warn them themselves, right? Um that they're drifting in a particular direction. People who have um cycles of depression or mania can know whether or not they're drifting into that. That can be extremely useful. Um they can discern who else gets that information. Um I think it and it's all based on tonality uh at different times of day stuff that even in a close close relationship with a therapist over many years they might not be able to detect if the person becomes reclusive or something of that sort. >> Absolutely. I mean um neural degeneration it shows up and you know short assessment of how people speak uh they've definitely been able to show potential likelihood of psychosis. um you know and and that's with uh syntactic completion and and how people read read read paragraphs. Um neural degeneration though things like Alzheimer's show up in speech because of the you know linguistic cues can show up but you know sometimes 10 years before a typical clinical uh uh symptom would show up that would be identified and and what I what I think is important for people to realize is it's not someone saying I don't remember. It's nothing like that. It's not those cues that you think are actually relevant. It's more like an individual says something like that. What I just did, which was I purposely stuttered. I started a word again, right? And it's, you know, what we might call a stutter in how we're speaking. Sometimes duration of spaces between starting one sentence to the next. These are things that as humans we've adapted to not p not pick up on because it makes us you know it makes us ineffective in communication or and and but an algorithm can do so very well. Um diabetes, heart disease both show up in voice. diabetes shows up because uh you can pick up on uh dehydration uh in the in the voice uh you much again I'm I'm a sound person in my heart in my past and if you look at the spectrum of sound you're going to see changes that show up you know there are very consistent things in a voice that show up with dehydration in the spectral you know salance as well as with heart disease you get sort of flutter that shows up it's a proxy for things happening inside your body you know with problems cardiovascular issues, but you're going to see them as certain like modulatory fluctuations in certain frequency bands. And again, we don't walk around as as, you know, a partner or a spouse or a or a child, you know, you you caretaking our parents and listening for, you know, like the the 4 kHz modulation, but an algorithm can. And you know, all of these are places where you can identify something that is potentially, you know, mitigate something proactively before there's, you know, a problem. And especially with like neural degeneration, we're really just getting to a place where there's pharmacological, you know, opportunities to slow something down. And you want to find that as quick as possible. So where do you you want to you want to have that input so that you can do something about it. You asked me about the babies, you know, like before we the type of coughs we have tell us a lot about different pathologies. So for a baby their cry their you know if I'm thinking you asked me about a digital tomb where would I be most interested in using that information if I had you know children or I mean I do have a child but from you know in the sort of lowest touch most opportunity it's to identify potential you know pathologies or issues early based on you know the the natural sounds and the natural utterances and call you know that are happening to understand if there is something that you know there's a way it could be helped. It could be you know need you could proactively um make something much better. >> Let's talk about you. >> Oh boy. >> And how you got into all of this stuff because you're highly unusual in the neuroscience space. I recall when we were graduate students who when you were working on auditory perception and physiology and then years later uh now you're involved with in AI neuroplasticity you were at Dolby. the what is to you the most of interesting question that's driving all of this like what what guides your choices about what to work on >> human technology intersection and perception is my core right I say perception but the world is data and you know how our brains take in the data that we consume to optimize how we experience the world is is what I care about across all of what I've spent my time doing and for me technology is such a huge part of that >> that it is you know I I like to innovate I like to build things but I also like to think about how do we improve human performance core to improving human performance is understanding how we're different not just how similar but you know the nuances of how our brains are shaped and how they're influenced and thus why I care you know I've spent so much time in neuroplasticity and it is at the intersection of everything is how are we changing and how do we harness that how Do we make it something that we have agency over? Whether it's from the technologies we build and we innovate to the point of I want to feel better. I want to be successful. I don't want that to be something left to surprise me. Right? >> So you asked me how do I get there? One thing that so I was violinist back in the day. I'm still a violinist and music's a part of my life. But I was studying viol music and engineering a uh when I was in undergrad and I think we alluded to the fact I have uh absolute pitch and absolute pitches for anyone that doesn't know it's not it it's not anything that means I always sing in tune. What it means is I hear the world uh like I hear sound like people see color. Okay. Um and I can't turn it off really. I can kind of push it back. >> Wait, sorry. Don't we all hear sound like we see? I mean, I hear sounds and I see colors. Could you clarify what you mean? >> When you Okay. So, when you walk down the street, your brain is going, "Oh, that's red, that's black, that's blue, that's green." My brain's going, "That's an A, that's a B, that's a G, that's an F." >> I see. You're cate your You're your category. >> There's a categorical perception about it. And because of the nature of I think my exposure to sound in my life, I also know what frequency it is, right? You know, so I can say that's, you know, 350 Hz or that's 400 Hz or that's 442 hertz. And um it has different applications. I mean, I can transcribe a jazz solo when I listen to it. That's a great party trick. But but it doesn't mean that it's not necessarily a good thing for a musician, right? you know as well as I do that um you know categorical perception is we all have different forms of it usually for speech and language like the units of vowels or phonetic units will especially vowels will you can hear many different versions of a an e and still hear it as an e and that's what we would call categorical perception and I my brain does the same thing for you a sort of set of frequencies to hear it as an a and um that's that that can be good at times, but when you're actually a musician, there's a lot more subtlety that goes into how you play with other people. And um what what key you're in or what you know the the details like if you ask me to sing happy birthday, I'm always going to sing it in the key of G if I am left to my own devices and I will I will get you there somehow if we start somewhere else. M so what happened to me when I was in music school when I was in conservatory and also engineering school is um I was taking two things happened. I knew that I had to override my brain because it was not allowing me the subtlety I wanted to play my shots or play my chamber music in the ways that were that I was having to work too hard to override what you know these these sort of categories of sounds I was hearing. So I started playing early music. Early music, Baroque music for anyone. I I said I think I said earlier A has is a social construct. Today we typically as a set as a standard A is 440 hertz. Um if you go back to like the 1700s, A was uh 415 hertz in the Baroque era and 415 hertz is effectively a G sharp. So it's the difference between H and H. Okay. And um what would happen to me when I was trying to override this is I was playing in an early music ensemble and I would tune my violin up and I would see a on the page and I'd hear G#arp in my brain and it was completely it it was it was I was terrible. I was like always it was really hard for my brain to override and uh I mean wind brass and wind players do this all the time. It's like transposition and they modulate to the key that they're in and they doesn't their brains have evolved, you know, through their training and neuroplasticity to be able to not have the same sort of experience I had. Anyhow, long story long, I uh was also taking a neuroscience course. This neuroscience course, we were reading papers about sort of different mapmaking and neuroplasticity. And I read this paper by a professor at Stanford named Eric Kudson. And Eric Kudson did these amazing well he did a lot of seminal work for how we understand the auditory pathways as well as how we form multiensory objects and and the way the brain integrates um you know cells data from across our modalities meaning you know sight and sound. Um but in this paper what he was doing was he had identified cells in the brain that optimally responded their receptive fields. You know receptive field being that sort of like in all of that giant data set of the world it's that you know it's the the set of data that optimally causes that cell to respond. And for these cells, they cared about a particular location in auditory and visual space, which you know, frankly, for mammals, we don't have the same sort of like cells because we can move our eyes back and forth in our sockets unlike owls. And he studied owls. And owls have a very hardwired map of auditory visual space. >> On the other hand, if I hear click off to my right, I turn my head to the right. >> You turn your head it triggers a different, you know, vestibular ocular response that moves, you know, all of that. Yes. But in this case, he had these beautiful hardwired maps of auditory visual space. And then he would rear and raise these owls with prism glasses that effectively shifted their their visual system by 15 degrees. And um then he would put them key to developing neuroplasticity. He would put them in high, you know, important, you know, high not stress, but let's say situations where they had to do something critical to their, you know, their survival or their their well-being. And so they would hunt and they would feed and do things like that with with the um this 15 degree shift, you know. And consequently, he saw the cells, the auditory neurons, he saw their their denderrites realigned to the now 15 degree visually shifted cells. And and it was this realization that they developed a secondary map that was now aligned with the 15 degree shift of the prism glasses as well as their original map was was super interesting for understanding how our brains integrate data and the feedback and neuroplasticity. So I go back to my Baroque violin where I'm always out of tune and I'm tuning up with, you know, tuning up my vi my baroque violin and I realize I had developed absolute pitch at A415. So I developed a secondary absolute pitch map and then I would go play Shastikovich right after it A440 and I had that map and I have nothing in between but I could modulate between the two and that's like the point at which I said I I I think I just you know my brain is a little weird and I just did something that I need to go better understand. So that's how I like ended up here as a neuroscientist. >> I know Eric's work really well. Um our labs were next door. Yes, our offices were next door. He's retired now, but um >> I I've he knows I told him the story. >> He's he's wonderful. I I think one of my favorite things about those studies I think people will find interesting is that um if an animal, human or owl, you know, has a displacement in the world, something's different, something changes and you need to adjust to it. could be like new information coming to you that you need to learn in order to perform your sport correctly or to perform well in class or or an emotionally challenging situation that you need to adjust to. All of that >> can happen, but it happens much much faster if your life depends on it. >> Yes. >> And we kind of intuitively know this, but one of my favorite things about his work is where he said, "Okay, well, yeah, these owls can adjust to the prism shift. their maps in the brain can change, but they sure as heck form much faster if you say, "Hey, in order to eat, in other words, in order to survive, these maps have to change." You know, and I I like that study so much because, you know, we hear all the time, you know, it takes 29 days to form a new habit or it takes 50 days to form a new habit or whatever it is. Actually, you can form a new habit as quickly as is necessary to form that new habit. And so the limits on neuroplasticity are really set by how critical it is. >> Yeah. >> And you know, of course, if you put a gun to my head right now and you said, "Okay, remap your your auditory world." I mean, there are limits at the at the other end, too. I mean, I can't do that quickly. But I I think um it's a reminder to me anyway, and thank you for bringing up Eric's work. It's a reminder to me that neuroplasticity is always in reach. If the incentives are high enough, we can do it. Yeah. >> And so I think with AI it's going to be very interesting or with technology generally. You know our ability to form these new maps of experience at least with smartphones has been pretty gradual. I really see 2010 as kind of the beginning of the smartphone and then now by 2025 >> we're in a place where most everyone young and old has integrated this new technology. I think AI is coming at us very fast and it's not unclear what form it's coming at us and and where and as you said it's already here. And I think um we will adapt >> for sure. We'll form the necessary maps. I think uh being very conscious of which maps we're are changing is so key. I mean I think we're still doing a lot of cleanup >> of the kind of detrimental aspects of smartphones. Short wavelength light late at night. >> Um you know being in contact with so many people all the time maybe not so good. I mean, I think what scares people, certainly me, is the idea that, you know, we're going to be doing a lot of error correction over the next 30 years because we're going so fast with technology because maps can change really, really fast. >> Well, they they do change. Sam Alman had um I I I saw him say this and I actually thought was really good description. It's like, you know, PE Gen X or you know, there's a group that is using AI as a tool that's sort of novel, interesting. Then you you know you've got a different millennials or are using it as you know a search algorithm and maybe that's even Genex but you know it's it's a little more deeply integrated but then you go back you know to to younger generations and it's an operating system and it already is and that has major changes in neural structure for how not just you know maps but also neural processes for how we deal with information how we learn. uh you know the idea that we are very plastic under pressure. Absolutely. And that's where it gets interesting to talk about different species too. I mean we're talking about owls and that was under pressure but you know what is successful human performance in training and all of these things. It's to make those probabilistic situations more deterministic. Right? That's when you are, if you're training as an athlete, you're really trying to not have to think and to have the fastest reaction time to very complex behaviors given complex stimula, complex situations and contexts, but you're you know that situational awareness or physical behavior in those environments. You you want that as fast as possible with as little cognitive, you know, load as possible. And you know, it's like that execution is critical. You love looking across species. So do I. and looking for these ways where you know we we are a brain is changing or you've got a species that can do something that is absolutely not what you would predict or it's incredible in its you know how it can evade a predator how it can find a target you find a a mate and you know it's doing things that are critical to it being able to survive much as you said like I if I make it something that is absolutely necessary for success. It's going to do it. You know, one of my favorite examples is a particular moth that bats predate on um echolocating bats and and you know, frankly, echolocating bats are sort of nature's engineered amazing predatory species. You know, their their brains when you look at them, you know, are are just incredible. They have huge amounts of their their brain just dedicated to what's called a FM constant frequency FM sort of sweep that some of the bats you know elicit a call that's sort of likeoo but really high >> so we so we can't hear it what does that do for them >> it's doing two things one that constant frequency portion is allowing them to sort of track the Doppler in a moving object so and and they're they're even so uh I mean It's such clever and sophisticated. They're not changing um they're changing subtly how what frequencies they elicit the call at so that it always comes back in the same frequency range because that's where their heightened sensitivity is. >> So otherwise you you know so they're modifying their vocal cords to make sure that the call comes back in the same range and then they're tracking how much they've had to modify their their the call >> just so that people are on board. Yeah. Bats echoloccate. They're sending out sound and they can measure distance and sh they can essentially >> see in their mind's eye. They can sense distance. They can uh sense speed of objects. They can sense shape of objects by virtue of sounds being sent out and coming back. Absolutely. >> And they're shaping those the sounds going out differently so that they can look at multiple objects simultaneously. >> But also so they're shaping the sounds they send out so that whatever comes back is in their optimal neural like range. so that they don't have to go through more neuroplasticity that they already have like circuits that are really dedicated to these certain frequency ranges. And so they send it out and then they're keeping track of the deltas. They're keeping track of how much they've had to change it and that's what's in, you know, tells them the speed. So that constant frequency is a lot like you know the ambulance sound going by. That's the compression of sound waves that you hear as a when when things move past you at speed. That's the Doppler effect. And then there also it has usually a really fast FM frequency modulated sweep and that lets me take kind of a an imprint of you know so one's telling me the speed of the object another one's telling me sort of what the surface structure looks like right that FM sweep lets me get uh you know a sonic imprint of what's there so I can tell topography I can tell if there's a you know a moth on a a hard surface right so what's beautiful about other species is you've got a little moth and you've got nature's predatory marvel and 80% of the time about that moth gets away >> how >> multiple things I call it almost an acoustic arms race that's happening between the two and there's a lot of acoustic sub subtrifuge between the moth you know but there's also beautiful deterministic responses that they have and um so first uh deterministic behaviors again be it an athlete be it you know effectiveness being fast, quick in making good decisions that get you the right answer are always important. So, you know, moss have just a few neurons. When that echolocating bat is flying, you know, at a certain point, uh, when those neurons start firing, they will start, you know, they'll start flying in more of a random pattern. You'll see the same thing with seals when there are great white sharks around, right? It's decreasing the probability that, you know, it's easy for them to continue to track you. So they'll f fly in a random pattern and then when their neurons saturate you when when the when it gets those calls get close enough the moth will drop to the ground with the idea that yeah in assuming we don't live in cities in a natural world the ground is you know wheat grass it's a difficult environment for an echo locating back to locate you right so that is just a deterministic behavior that will happen regardless but then the interesting part is their body is reflecting metarlectors effectively so that the bat may put out its call and it deflects the you know the energy of the call away from its body. So you're deflecting it away from critical critical areas and you know this is all like happening and that's the the changes in the physi physical body are interesting but then it's the behavioral differences they're really key right it's how fast does that moth react if it has to question you know or if it were cognitively responsive instead of being deterministic in its behavior it wouldn't escape right but it gets Yeah, I've never thought about bats and and moths. I I um I never got the insect I was about to say I never got the insect bug that that then no pun intended. I I never got the insect bug because um I I don't think of things in the auditory domain. I think of things in the visual domain. And some insects are very visual. But um it's it's it's good for me to think about that. You know, one of my favorite people, although I never met him, was Oliver Saxs, like the neurologist and writer. And he claimed to have spent a lot of time imagining, just sitting in a chair and trying to imagine what life would be like as a bat as a way to enhance his um clinical abilities with patients suffering from different neurologic disorders. >> Huh. So when he would interact with somebody with Parkinson's or with severe autism or with lockin syndrome or uh any number of different deficits of the of the nervous system, he would um he felt that he could go into their mind a bit to understand what their experience was like. He could empathize with them and that would make him more effective at treating them. And he certainly was very effective at storing out their um their experience in ways that brought about a lot of compassion and understanding. Like he never presented a a neural condition in a way that made you feel sorry for the person. It was always the opposite. >> Um and I should point out, not trying to be politically correct here, but when I say autistic, I meant the patients he worked with were severely autistic to the point of, you know, never being able to take care of themselves. This is we're not talking about along a spectrum. We're talking about the far end of the spectrum of uh needing assisted living their entire lives and being sensory very uh from a sensory standpoint extremely sensitive, couldn't go out in public, that kind of thing. That we're not talking about people that are uh functioning uh with autism. So um apparently thinking in the auditory domain was useful for him. So I should probably do that. So I have one final question for you. Uh which is what's really two questions. First question, why did you sing to spiders? And second, what does that tell us about spiderw webs? Because uh I confess I know the answers to these questions, but I was absolutely blown away to learn what spiderw webs are actually for. Um and you singing to spiders reveals what they're for. So why did you sing to spiders? >> Two things. And um you can watch me sing to a spider on a TED talk I gave a few years ago. We'll put it >> here back. Okay. And um no uh so maybe this comes back to I have absolute pitch so I know what frequencies I'm singing but I also recognize by having absolute pitch I know my brain is just a little different. Again what you ask me what threads drive me. It's always been we we do experience the world differently. And I believe that our success, everyone's success and the success of our growth as humans is is partly dependent on how we use technology to help you know improve and optimize each of us with you know the different variables we need. Right? So different species and how they respond to sound is very interesting to me. And as much as you I know Andy you look at how different species respond to color and to information in the world be it cuttlefish or such I have jellyfish too and I can see how they you know their pulsing rates change with their photo receptors when they uh you know with different light colors it's very obvious that some clearly make you know that they are under when they're under stress versus when they're in a a more calming state. And so it's like understanding the stimula in our world that shape us, those changes is a huge part of being human. In my perspective, in this case, this happens to be an orb spider, the one I sing to. And when I hit about 880 hertz, uh you will see the spider kind of dances. But what this particular species and not all spiders will do this is predated on by echolocating bats and birds which makes sense that then you know it tunes its web effectively and and the orb weavers are all over California. It's what they they show up a lot in around uh Thanksgiving if you are October, November for anyone that's on the you know out here on the west coast. Um they're not bad spiders. They they are not spiders you need to get rid of. They're totally happy spiders. or some, you know, that maybe you're should worry about more. Anyhow, they tune their webs to resonate like a violin. And when, you know, you'll see it as I hit a certain frequency, it'll effectively tell me to to to go away. And uh it's it's it's a pretty interesting sort of deterministic response. Other insects do different things. Uh the one kind of uh funny for that was when my daughter was I think at the time she was about two and a half or three and she kind of adopted uh asking me when we would see spiders if it was the kind we would we should sing to or the kind we shouldn't touch. >> Those were the two classes. >> So uh amazing. So if I understand correctly, these orb spiders use their web. >> Yes. more or less as an instrument to detect certain sound frequencies in their environment. >> Resonances absolutely >> so that they can respond appropriately. Yeah. >> Either by raising their legs to protect themselves or to attack or whatever it is that that the spiderweb is a functional thing not just for catching prey. It's it's a detection device also. And we know that because when prey are in caught in a spiderweb, they wiggle and then the spider goes over to it and wraps it and and eats it. But um but the idea that it would be tuned to particular frequencies is really wild. >> Yeah. Not just any vibration, right? You know, there's the idea that there's any vibration, I know I've got, you know, food somewhere, I should go to that food source, but instead it's something that if I experience a threat or something, I'm going to behave. And that is a more selective, you know, response that I've tuned it towards. >> It's so interesting because if I just transfer it to the visual domain, it's like, yeah, of course, like if an animal, including us, sees something like a looming object coming at us. >> Yeah. uh closer to dark, we our immediate response is to either freeze or flee. Like that's just what we do. The looming response is one of the most fundamental responses, but that's in the visual domain. So the fact that there would be auditory cues that would bring about what you said the sort of deterministic responses seems very real. I feel like that there the whale of a of somebody in pain. >> Yes. >> Evokes a certain response. the um yesterday there was a lot of noise outside my window at night and I there was a moment where I couldn't tell were these um shouts of glee or shouts of fear >> and I like I can't do and then I heard this like kind of like uh highpitch um fluttering that came after the scream and I realized these were kids playing in the in the alley outside my house and I went and looked I was like oh yeah they're they're definitely playing but I knew even before I went and looked based on the kind of the the flutter of sound that came after the like the the shriek. It was like and then it was it was like I can't I can't reproduce the sound at that high frequency. >> That's that's um >> so the idea that this would be true all the time is uh is super interesting. We just don't tend to focus just on our hearing unless of course somebody's blind in which case they have to rely on it much more. >> So two interesting things to go with that. So like crickets for example, crickets um have biodal neurons that have sort of peaks in two different frequency ranges for the same neuron. And each frequency range will elicit a completely different behavior to when when so you've got a peak at 6k and you've got a peak at 40k and cricket and this is the same neuron. cricket hears 40k from a speaker, run over to it because that's got to be my bait or some you know that and you hear 40k and they run away and you know it's very predictive behavior. Uh I spend a lot of well I spent a good period of time working with non- primate non-human primate species marmicetses. Marmicetses are very interesting when you get to a more sophistic you know you know a more sophisticated neural system. Um, but they're you marmicetses are very social. You know, it's critical to their happiness. If you ever see a single marmicet in the zoo or something, that's a very unhappy uh animal. But they're they're native to the Amazon. You know, new world monkeys native to Brazil and the Amazon, but they're aroreal. They live in trees and they're very social. So that kind of can, you know, be in conflict with each other because you're, you know, in dense foliage, but yet you need to communicate. So they've evolved very interesting systems to be able to you know achieve what they needed to which one um they if you ever see a marmicetses they're very stoic unlike macac monkeys that you know often have a lot of visual you know expression of how they're feeling. Armicetses always look about the same and um but their their vocalizations are almost like bird song and they're very rich in the information that they're you know communicating. They also have a f pherommonal system like you know they um thought you can have a dominant female in the colony who may not be because you have to have ways of communic when one sense is compromised the other senses sort of rise up to help assure that the success of what that s you know that that species or system needs is going to be you know thrive. And in the case of marmicetses, you can have the dominant female effectively causes the ovulation of like the biology to change of all the other females and you can have a female that you put just in the same proximity but now as part of a different group and her biology will change. I mean it's very powerful the pherommonal interactions that happen in the because those are things that can travel even when I can't see you. One thing when I was working with them, you know, that I thought was and and I never I like writing pads more than publishing papers. So, but these things are real because I was studying pupilometry is is understanding the power of the you know their sacads. I could know what they were hearing based on their eye movements, right? So, if I play marmicetses have, you know, call some of their calls are really antipinal. They're to see, hey, are you out there? Am I alone? Who else is around? >> Texting for humans. Yeah. >> Yeah. And sometimes it's light or sometimes it might be like oh you know from be careful there's you know there's somebody you know around that we got to watch out for maybe there's a leopard on the ground or somebody something right and then sometimes it's like you're in my face get out of here now right and those are three different things and I can play that to you and I can tell you without hearing it and I know exactly what's being heard in the case of the antipol hey are you out there you see like the the eye will just start scanning back and forth right because that's the right movement I'm looking for where's this coming from? >> Yeah. They paired the right eye movement with the right sound. >> Exactly. In the case of, you know, look, it's um you know, there's something to be scar threatened of. You're going to see dilation and you're also going to see some scanning, but it's not as slow. It's a lot faster because there's a threat to me. I my you know, my autonomic system and my cognitive system are like be reacting differently. And in the case of you're in my face, it's going to be, you know, without even so without seeing you, if I hear another, you know, sort of aggressive sound, I'm going to react. I'm going to be, you know, I'm not scanning anywhere, but I my dilation is going to be fast and, you know, my and I'm also going to be much more on top of things. But we do this as, you know, humans too, right? And it's like I you can you walk into a business meeting, you walk into a conference room and you know it's these subtle cues that are con you we can't don't always suppress them. We show them whether we think we do or we don't. But you know when you look at species like that it's very much like okay you know there's there's a lot of you know sophistication in and how their bodies are helping them be successful even in a world or an environment that has a lot of things that that could maybe you know come after them. So interesting to think about that in terms of um our own human behavior and what we're optimizing for, especially as all these technologies come on board and are sure to come on board even more quickly. Um Poppy, thank you so much for coming here today to educate us about what you've done, what's here now, what's to come. We covered a lot of different territories and I I'm glad we did because um you have expertise in a lot of areas and I love that you are constantly thinking about technology development and I you know I drew a little diagram for myself that I'll just describe for people because um if I understood correctly one of the reasons you got into neuroscience and research at all is about this um interface between inputs and us and what sits in between those two things is this incredible feature of our nervous systems which is neuroplasticity or what I sometimes like to refer to as self-directed plasticity because unlike other species we can decide what we want to change and make the effort to adopt a second map of the auditory world or visual world or or take on a new uh a new set of learnings in any domain and we can do it if we put our mind to it if the incentives are high enough we can do it and at the same time neuroplasticity is always occurring based on the things we're bombarded with new technology. So, we have to be aware of how we are changing and we need to intervene at times and and leverage those things for our health. So, thank you so much for doing the work that you do. Thank you for coming here to educate us on them and um keep us posted. We'll provide links to you singing to uh spiders and and all the rest. My mind's blown. Thank you so much. >> Thank you, Eddie. Great to be here. >> Thank you for joining me for today's discussion with Dr. Poppyrcum. To learn more about her work and to find links to the various resources we discussed, please see the show note captions. If you're learning from and or enjoying this podcast, please subscribe to our YouTube channel. That's a terrific zerocost way to support us. In addition, please follow the podcast by clicking the follow button on both Spotify and Apple. And on both Spotify and Apple, you can leave us up to a five-star review. And you can now leave us comments at both Spotify and Apple. 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