0:00 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
0:46 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
1:33 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.
2:19 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
3:04 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
3:50 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
4:36 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
5:23 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?
6:09 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
6:56 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
7:43 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.
8:29 >> 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
9:16 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.
10:02 >> 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
10:48 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,
11:34 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
12:20 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
13:06 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
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15:23 customized to you. Right now, Helix is giving up to 27% off all mattress orders. 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.
16:08 >> 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
16:55 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
17:41 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.
18:26 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
19:12 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
19:58 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,
20:44 >> 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
21:31 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
22:16 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
23:02 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
23:50 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?
24:35 >> 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,
25:22 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
26:08 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
26:54 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.
27:40 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
28:27 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
29:12 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,
29:58 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
30:44 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
31:32 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
32:19 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
33:05 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
33:50 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
34:37 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
35:23 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
36:10 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
36:56 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
37:42 >> 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
38:28 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
39:14 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,
40:00 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
40:48 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
41:34 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
42:20 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
43:06 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
43:54 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
44:40 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
45:26 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
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49:14 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
50:00 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
50:46 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
51:33 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
52:20 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
53:06 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
53:52 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
54:40 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
55:25 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
56:11 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.
56:58 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
57:45 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
58:32 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
59:19 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
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