Enhance Your Learning Speed & Health Using Neuroscience Based Protocols | Dr. Poppy Crum
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My guest is Dr. Poppy Crum, PhD, adjunct professor at Stanford, former Chief Scientist at Dolby Laboratories and expert in neuroplasticity—our brain’s ability to change in response to experience. She explains how you can learn faster and ways to leverage your smartphone, AI and even video games to do so. We also discuss “digital twins” and the future of health technology. This episode will change the way you think about and use technology and will teach you zero-cost protocols to vastly improve your learning, health and even your home environment.
Articles
- Somatic motor and sensory representation in the cerebral cortex of man as studied by electrical stimulation (Brain)
- Enhancing the contrast sensitivity function through action video game training (Nature Neuroscience)
- Improved probabilistic inference as a general learning mechanism with action video games (Current Biology)
- Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task (arXiv)
- Navigation-related structural change in the hippocampi of taxi drivers (Proceedings of the National Academy of Sciences of the United States of America)
- Cinema audiences reproducibly vary the chemical composition of air during films, by broadcasting scene specific emissions on breath (Scientific Reports)
- Sensitive periods for visual calibration of the auditory space map in the barn owl optic tectum (Journal of Neuroscience)
- Experience-dependent plasticity in the inferior colliculus: a site for visual calibration of the neural representation of auditory space in the barn owl (Journal of Neuroscience)
Other Resources
- Poppy's Cheat Sheet
- PassiveLogic
- Introducing Perplexity Labs
- Replit
- Pison
- Poppy Crum: Technology that knows what you’re feeling
- Free Solo
- The Hunger Games
- The Sound of Silence
Huberman Lab Episodes Mentioned
People Mentioned
- Wilder Penfield: Canadian-American neurosurgeon, known for homunculus
- Sam Golden: professor of neurobiology and biophysics, University of Washington
- Eric Knudsen: professor emeritus of neurobiology, Stanford University
- Sam Altman: CEO, Open AI
- Oliver Sacks: British neurologist, author

About this Guest
Dr. Poppy Crum
Poppy Crum, PhD, is an adjunct professor at Stanford, former Chief Scientist at Dolby Laboratories and an expert in neuroplasticity.
This transcript is currently under human review and may contain errors. The fully reviewed version will be posted as soon as it is available.
Andrew Huberman: Welcome to the Huberman Lab podcast, where we discuss science, and science-based tools for everyday life.
Andrew Huberman: I'm Andrew Huberman, and I'm a professor of neurobiology and ophthalmology at Stanford School of Medicine. My guest today is Dr. Poppy Crum. Dr. Poppy Crum 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.
Andrew Huberman: You've no doubt heard about, and perhaps use, wearables and sleep technologies that can monitor your sleep, tell you how much slow wave 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.
Andrew Huberman: 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-of-the-box thinker and scientist.
Andrew Huberman: 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 zero-cost 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.
Andrew Huberman: 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. Poppy Crum.
Andrew Huberman: Dr. Poppy Crum, welcome.
Poppy Crum: Thanks, Andy. It's great to be here.
Andrew Huberman: 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, et cetera. 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.
Andrew Huberman: In particular, I want to know, do you think our brains are much more plastic than most of us believe? 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 going to have to, I don't know, create robots or something to do the work that we're not able to do because our brains are fixed?
Andrew Huberman: But let's start off by just getting your take on what neuroplasticity is, and what you think the limits on it are.
Poppy Crum: I do think we're much more plastic than we talk about or we realize in our daily lives. And, just to your point about creating robots, the more we create robots, there's neuroplasticity that comes with using robots as humans, when we use them in partnerships or as tools to accelerate our capabilities.
Andrew Huberman: Mm-hmm.
Poppy Crum: So, neuroplasticity, the way that I resonate with it a lot is trying to understand, 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.
Poppy Crum: Everything we engage with in our daily lives, whether it's the statistics of our environments and our context, or the technologies we use on a daily basis, are shaping our brains through neuroplasticity. 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 changing.
Poppy Crum: 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 or architecting our brains as we move forward. You go to any neuroscience 101 medical school textbook, and there's something, you'll see a few pages on something called the homunculus. Now, what is the homunculus?
Poppy Crum: It's a data representation, but it'll be this sort of funny-looking creature when you see it. But that picture of this sort of distorted human that you're looking at is really just a data representation of how many cells in your brain are helping, coding, and representing information for your sense of touch, right?
Poppy Crum: And 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 somatosensory cells of patients just before they were to have surgery for epilepsy and such. And since we don't have pain receptors in our cortex, you could have this awake human and be able to touch different parts of their brain and ask them to report what sensation they felt on their bodies.
Poppy Crum: And so, he mapped that part of their cortex, and then that's how we ended up with the homunculus. And you'll see, it'll have bigger lips, it'll have smaller parts of your back, and 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, "What's wrong with this image?" This is an image from 1940 that is still in every textbook.
Poppy Crum: And, any Stanford 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 ankles are the same size, 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.
Poppy Crum: And in a few years, we probably won't be driving, and those resources get optimized elsewhere. So, what the homunculus 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.
Poppy Crum: And 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.
Poppy Crum: They develop more specificity so that, I might have suddenly a lot more cells in my brain devoted to helping me. You know, I'm a violinist, and well, my left hand, my right hemisphere, and on my somatosensory cortex, I'm going to have a lot more cells that are helping me feel with my fingers, and the tips of everything so that I can be fluid and more virtuosic. But that means I have more cells, but they're more specified.
Poppy Crum: 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, my practice as a musician versus my practice playing video games, all of these things influence our brain, and influence our plasticity.
Poppy Crum: Now, where things get kind of interesting to me and sort of my obsession on that side is, every time we engage with the technology, it's going to shape our brain, right? It's both our environments, but our environments are changing. Those are shaping who we are. I think you can look at people's hearing thresholds and predict what city they live in.
Andrew Huberman: Really?
Poppy Crum: Absolutely, yes.
Andrew Huberman: Can you just briefly explain hearing thresholds and why that would be?
Poppy Crum: Why that would be?
Andrew Huberman: I was visiting the city of Chicago a couple years ago. Beautiful city, 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."
Poppy Crum: Yeah.
Poppy Crum: Mm-hmm.
Andrew Huberman: And I grew up in the suburbs, got out as quickly as I could, don't like the suburbs.
Poppy Crum: Yeah.
Andrew Huberman: Sorry, suburb dwellers, not for me. I like the wilderness, and I like cities. 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?
Poppy Crum: In part, it can be both, right? Because cities have sonic imprints, types of noise, things that are very loud cities, but also what's creating that noise, right? That's often unique. The inputs, the types of vehicles, the types of density, people, and even the construction in those environments. It is changing what noise exists. That's shaping people's hearing thresholds.
Poppy Crum: At the lowest level, it's also shaping their sensitivities. If you're used to hearing certain animals in your environment and they come with, you know, 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 to... I hear chickens. I have a neighbor who has chickens in the city.
Andrew Huberman: Roosters too?
Poppy Crum: Yes. Yes.
Andrew Huberman: Okay. I grew up near a rooster.
Poppy Crum: In San Francisco.
Poppy Crum: There you go.
Andrew Huberman: I can still hear that rooster.
Poppy Crum: Yeah.
Andrew Huberman: Those sounds are embedded deeply in my mind.
Poppy Crum: There's the semantic context and then just the sort of spectrum, right? And the intensity of that spectrum, meaning, when I say spectrum, I mean the different frequency amplitudes, and what that shaping's like.
Andrew Huberman: High pitch, low pitch, this kind of thing.
Poppy Crum: Yeah. And that affects how your neural system is changing, even at the lowest level of what your ear, your brain, your cochlea is getting exposed to, but then also that would be the lower level, what sort of noise damage might exist, what exposures, but then also then there's the amplification of coming from your higher level areas that are helping you know that these frequencies are more important in your context, in your environment.
Andrew Huberman: Mm-hmm.
Poppy Crum: There's a funny, like this is kind of funny, there was a film called, I think it's "The Sound of Silence," and I love Peter Sarsgaard, he was one of the actors in it, and it was sort of meant to be a bit fantastical, or is that word? Is that the right word? But in fact, to me... So, the filmmakers had talked to me a lot, and to inform this 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 film.
Poppy Crum: He ends up being this person who tunes people's lives. He'll walk into their environments and be like, "Oh, things are going badly at work or your relationships because you've got this tritone. Your water heater is making this pitch, and your teapot is at this, and you have to."
Andrew Huberman: Oh my god, this would go over so well in LA. People would pay millions of dollars in Los Angeles.
Poppy Crum: It's totally funny.
Andrew Huberman: Do you do this for people?
Poppy Crum: No.
Andrew Huberman: Okay, okay.
Poppy Crum: But I will tell you, I will walk into hotel rooms and immediately if I hear something, I'm moved. And so, that is...
Andrew Huberman: Because you have perfect pitch. Could you define perfect pitch? Does that mean that you can always hit a note perfectly with your voice?
Poppy Crum: There is no such thing as perfect pitch. There's absolute pitch. And so the thing, only because, the idea of...
Andrew Huberman: Mm-hmm.
Poppy Crum: So, like, "Ah." That would be A equal 440 hertz, right? But that's a standard that we use in modern time, and the different... What A is has actually changed throughout our lives, with aesthetic, with what people liked, with the tools we used to create music, and in the Baroque era, A was 415 hertz, and that...
Andrew Huberman: Can you hit that?
Poppy Crum: "Ah"
Andrew Huberman: Awesome.
Poppy Crum: And, in any case... So that's why it's absolute, because guess what? As my basilar membrane gets more rigid as my age or my temporal processing slows down, my brain's going to still think I'm singing 440 hertz, but it might not be.
Andrew Huberman: Basilar membrane is a portion of the internal ear that convert sound waves into electrical signals, right?
Poppy Crum: Yeah.
Andrew Huberman: Okay, fair enough?
Poppy Crum: Well, mechanically. It moves the hair cells that help...
Andrew Huberman: I'm talking to an auditory physiologist here.
Andrew Huberman: Right, right, right.
Poppy Crum: Yeah, yeah.
Andrew Huberman: I teach auditory physiology, but I want to just make sure, because I'm sitting across from an expert.
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Andrew Huberman: Okay, so our brains are customized to our experience.
Poppy Crum: Yeah.
Andrew Huberman: Especially our childhood experience, but also our adult experience.
Poppy Crum: Yes.
Andrew Huberman: You mentioned the homunculus.
Poppy Crum: Yes.
Andrew Huberman: The 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 this hypothetical Stanford student, could be any student anywhere, says, "Wait, nowadays, we spend a lot of time writing with our thumbs and thinking as we write with our thumbs."
Poppy Crum: Mm-hmm.
Poppy Crum: Mm-hmm.
Andrew Huberman: And emoting, right? When we text with our thumbs, we're sometimes involved in an emotional exchange.
Poppy Crum: Yeah.
Andrew Huberman: My question is this. The last 15 years or so have represented an unprecedented time of new technology integration, right? I mean, the smartphone.
Poppy Crum: Mm-hmm.
Andrew Huberman: 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.
Poppy Crum: Mm-hmm.
Andrew Huberman: 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 texts was too complicated to even consider right now. But what is that transformation really about? Previously, I would write you a letter, I would send you a letter, or I'd write you an email, I'd send you an email.
Andrew Huberman: And so, the process was really slowed. Now, you can be in a conversation with somebody that's really fast back and forth.
Poppy Crum: Mm-hmm.
Andrew Huberman: Right? Some people can type fast, and even 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?
Poppy Crum: Yeah.
Andrew Huberman: 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.
Poppy Crum: Mm-hmm.
Andrew Huberman: 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 Venn diagram? Because I remember all of this happening very quickly and very seamlessly. I remember texting showed up, and it was all right, well, it's a little slow, a little clunky.
Andrew Huberman: Pretty soon, it was autofill. Pretty soon, it was learning us. Now, we can do voice recognition, and people pick this up very fast.
Poppy Crum: Yeah.
Andrew Huberman: 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 basic to everyday life as texting?
Poppy Crum: Mm-hmm.
Andrew Huberman: What's going on in our brain?
Poppy Crum: We aren't developing new resources. We've got the same cells that are... Or, I mean, there's neurogenesis, of course, but it's how those are getting allocated, and just one quick comment from what we said before when we talk about the homunculus.
Poppy Crum: The homunculus is an example of a map in the brain, a cortical map, and maps are important in the brain because they allow cells that need to interact to give us specificity, to make us fast, to have tight reaction times, and things, because you got shorter distance, and things that belong together. Also, there's a lot of motility in terms of what those cells respond to, potentially dependent on our input. 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.
Poppy Crum: So, what you're talking about is, are you having areas where we didn't use to allocate and differentiate in the 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?
Poppy Crum: And the subtlety and the nuance of that, that actually now 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 where... Think about me as a multi-sensory object that I have to integrate information across sight, sound, smell, to form a holistic object experience.
Poppy Crum: That same sort of integration and pattern is happening now when we communicate in ways that it didn't use 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.
Andrew Huberman: I completely agree. I feel like there's an entire generation of people who grew up with smartphones, for which it's just part of life.
Poppy Crum: Mm-hmm.
Andrew Huberman: I think one of the most impactful statements I ever heard in this general domain was, I gave a talk down at Santa Clara University one evening to some students, 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.
Poppy Crum: Yeah.
Andrew Huberman: And afterwards, this young guy came up to me, he was probably in his early 20s, and he said, "Listen, you don't get it at all." I said, "What do you mean?" 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 return 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."
Andrew Huberman: And I was thinking to myself, "Wow." 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.
Poppy Crum: Mm-hmm.
Andrew Huberman: And I don't think he's alone. I think for some people, it might not be quite as extreme?
Poppy Crum: Mm.
Andrew Huberman: But for many of us, to see that dot, dot, dot in the midst of a conversation where we really want the answer to something, or it's an emotionally charged conversation, can be a very intense human experience.
Poppy Crum: That's interesting, yeah.
Andrew Huberman: So, we've sped up the rate that we transfer information between one another, but even about trivial things.
Poppy Crum: Yeah.
Andrew Huberman: It doesn't have to be an argument or a stage four cancer, or is it benign, right? Those are extreme conditions, right? Are they alive or are they dead? Did they find him or her, or did they not? Those are extreme cases, but there's just the everyday life of... And I notice this, if I go up the coast sometimes, or I'll go to Big Sur, and I will intentionally have time away from my phone.
Andrew Huberman: It takes about 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.
Poppy Crum: Yeah.
Andrew Huberman: 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?
Poppy Crum: It goes in lots of different directions.
Poppy Crum: One thing I did want to say, though, with smartphones specifically and sort of everything, in audio, our ability to carry our lifetime of music and content with us has been because of huge advances in the last 25, 30 years, and maybe even slightly more, around compression algorithms that have enabled us to have really effective what we call perceptual compression, lossy perceptual algorithms, and things like MP3, and 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 with a lot of the information removed, right? But in intelligent ways.
Poppy Crum: 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...
Andrew Huberman: Mm-hmm.
Poppy Crum: It's actually a lossy compression that's triggering a huge cognitive experience, right?
Andrew Huberman: Can you explain lossy for people who might not be familiar with it?
Poppy Crum: 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 a song and I want to represent that song. To make my file smaller, I could take out every other 500 milliseconds of that, and it would sound really horrible, right?
Poppy Crum: Or, I could be a lot more intelligent, and instead, basically, if you look at early models like MP3, they're kind of like computational models of the brain. They might stop at 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 bits coding this sound. Instead, we just need to code this one.
Poppy Crum: 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 best perceptual experience, which perceptual meaning what we get to take home.
Poppy Crum: I think one of the things that's important then, why I think, whenever I used to have to teach some of what it means to represent a rich experience with minimal data, you think with minimal information, some of the acronyms that exist in mobile texting, they've taken on a very rich life in internal life.
Andrew Huberman: LOL.
Andrew Huberman: OMG.
Poppy Crum: Yeah, well those are simplistic ones.
Andrew Huberman: Right.
Andrew Huberman: Yeah.
Poppy Crum: But I think people can have communication now that we can't understand entirely.
Andrew Huberman: Is this because you have a 10-year-old daughter? Does she have communication by acronym that, to you, is cryptic?
Poppy Crum: Yes.
Poppy Crum: Sometimes. But I have to figure it out then.
Andrew Huberman: Mm-hmm.
Poppy Crum: But, yes.
Andrew Huberman: Mm-hmm.
Poppy Crum: But the point is, 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're using few bits of information to try to represent a much richer feeling and a much richer state, right? And if you look at different people, they're going to have bigger physiological experience dependent on how they've grown up with that kind of context.
Andrew Huberman: It sounds to me, I don't want to project here, but it sounds to me like you see the great opportunity of data compression.
Poppy Crum: Yeah.
Andrew Huberman: Let's just stay with the use of acronyms in texting.
Poppy Crum: Mm-hmm.
Andrew Huberman: That's a vast data compression compared to the kind of speech and direct exchange that people engaged in 30 years ago. So, there's less data being exchanged, 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 benevolent.
Poppy Crum: Yeah.
Andrew Huberman: It's good.
Poppy Crum: It's just different.
Andrew Huberman: I'm coming up on 50 in a couple months, and as opposed to somebody saying, "Well, you know, when I was younger, we'd write our boyfriend or girlfriend a letter."
Poppy Crum: Yes.
Andrew Huberman: "I would actually write out a birthday card. I would go... You'd have a face-to-face conversation," and you've got this younger generation that are saying, "Yeah, whatever," this is what we heard about, "I used to trudge to school in the snow," kind of thing.
Andrew Huberman: It's like, "Well, we have heated school buses now, and we've got driverless cars."
Poppy Crum: Yeah.
Andrew Huberman: So, 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 there are data or some elements of the exchange are being completely removed.
Poppy Crum: Absolutely. But it's maintained because of the neural connections that are built in those individuals, right? And that generation.
Andrew Huberman: I always think of, okay, and the nervous system likes to code, along a continuum, but yum, yuck, or meh. Do you think that technology is kind of neutral? Yeah, you lose some things, you gain some things. Or, do you think, this is bad? These days, we hear a lot of AI fear. We'll talk about that. Or you hear also people who are super excited about what AI can do, what smartphones can do.
Andrew Huberman: I mean, some people, like my sister and her daughter, love smartphones because they can communicate, it gives a feeling of safety at a distance. Quick communications are easier, it's hard to sit down and write a letter. She's going off to college soon, so the question is like, "How often will you be in touch?" It raises expectations about frequency of contact, but it reduces expectations of depth.
Poppy Crum: Mm.
Andrew Huberman: 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, during college to my mom, like, "Hey, was thinking about you this morning. Love, Andrew." It'd be like, "Okay." I don't know how that would be. They'd be, "Well, that didn't take long," right?
Andrew Huberman: So, I think that there's a... It's a see-saw, you know?
Poppy Crum: You can get more frequency.
Andrew Huberman: Mm-hmm.
Poppy Crum: And then it comes with different levels of expectation on those.
Andrew Huberman: Mm-hmm.
Poppy Crum: And my daughter's at camp right now, and we are only allowed to write letters for two weeks.
Andrew Huberman: Handwritten letters?
Poppy Crum: Handwritten letters.
Andrew Huberman: How did that get over?
Poppy Crum: It's happening. I mean, I'd lost another home in a flood years ago.
Andrew Huberman: Mm-hmm.
Andrew Huberman: Mm-hmm.
Poppy Crum: And one of the only things I saved out of the flood, which is this... And I just brought these back because I got them from my brother, is they're this communication between one of my ancestors during the Civil War, like, they were courting, and that was all saved, these letters back and forth between the woman.
Andrew Huberman: Wow.
Poppy Crum: And it's with these, it's like 1865, and...
Andrew Huberman: You have those letters?
Poppy Crum: I do. I do.
Andrew Huberman: Wow.
Poppy Crum: I had them in my computer bag until I flew up here.
Andrew Huberman: Wow.
Poppy Crum: But they were on parchment, and even though they went through a flood, they didn't run. And it's this very different era of communication, and it's wonderful to have that preserved because that doesn't translate, right, through, and without that history.
Poppy Crum: In any case, I am a huge advocate for the integration of technology, but for me, the world is data. And I do think that way. And I look at the way my daughter behaves, I'm like, "Okay, well, what data's coming in?" And that's like, you know... "And why did she respond that way?" And there's an example I can give, but you think... We were talking about neuroplasticity. It's like we are the creatures of sort of three things.
Poppy Crum: One is our sensory systems, how they've evolved, and be it by the intrinsic noise that is degrading our sensory receptors, or the... You know, 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?
Poppy Crum: Our priors being, if you think about the brain as sort of a Bayesian model, things aren't always deterministic for us like they are for some creatures. Our brain's having to take data and make decisions about it and respond to it.
Andrew Huberman: Which is Bayesian. We should just explain it for people.
Poppy Crum: Yes.
Andrew Huberman: Deterministic would be input A leads to output B.
Poppy Crum: Yeah.
Andrew Huberman: Bayesian is, it depends on the statistics of what's happening externally and internally.
Poppy Crum: Yeah.
Andrew Huberman: These are probabilistic models.
Poppy Crum: Yes.
Andrew Huberman: 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.
Poppy Crum: Absolutely. 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 situations. Those things where your brain... It's like probabilistic inference is a great indicator of success in an environment. And be it a work environment, be it just walking down the street.
Poppy Crum: And that's how 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 we can break that down into a lot of different ways.
Poppy Crum: In any case, we are the products of our sensory systems, our priors, which are the statistics and data we've had up until that moment that our brain is using to weight how it's going to behave and the decisions it makes, but also then our expectations, the context that have shaped where we are.
Andrew Huberman: Mm-hmm.
Poppy Crum: And so, there's this funny story. Like, my daughter, when she was two and a half, we were in the planetarium at the Smithsonian, and we were watching, I think, a typical film you might watch in a planetarium. We started in LA, zoom out on our way to the sun, and we passed that sort of 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?"
Poppy Crum: And I'm like, "Oh, yes, of course." Her experientially established prior of that image is coming from the Universal logo. And she never... You know, that says Universal.
Andrew Huberman: Yeah. No, I love it.
Poppy Crum: It was totally valid, but it was this very 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.
Poppy Crum: And once you unpack that, you really start to understand 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.
Poppy Crum: At the same time, I think sometimes we're penny-wise, 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.
Poppy Crum: And where you'll end up with those that are using the technologies might be to write papers all the time, or maybe... Well, and 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 learning of that data, that information.
Andrew Huberman: Mm-hmm.
Poppy Crum: And so, you start even ending up with bigger differentiations in cognitive capabilities by how you use a tool, a technology tool, to make you better or faster, or not. One of my sorts of things I've always done is teach at Stanford. We also have that in common.
Andrew Huberman: Mm-hmm. I need to sit in on one of your lectures.
Poppy Crum: You know, but my class there is called "Neuroplasticity and Video Gaming." And I'm a neurophysiologist, but I'm really a technologist. I like building. I like innovation across many domains. And while that class says video gaming, it's really more a... Well, video games are powerful in the sense that there's this sort of closed-loop environment. You get feedback, you get data on your performance, but you get to control that and know what you randomize, how you build.
Poppy Crum: 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 students that are musicians, I'll have students that are computer scientists, I'll have students that are some of Stanford's top athletes. I've had a number of their top athletes go through my course.
Poppy Crum: And 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 access to that type of learning in a closed-loop way.
Poppy Crum: Just for anyone that isn't familiar with the role or the history of gaming in the neuroscience space, there's been some great papers in the past. Take a gamer versus a non-gamer, just to start with, someone self-identified.
Poppy Crum: A typical gamer actually has what we would call more sensitive... And this is your domain, so you can counter me on this anytime, but contrast sensitivity functions.
Andrew Huberman: Mm-hmm.
Poppy Crum: And like, a contrast sensitivity function is the ability to see edges and differentiation in a visual landscape, okay?
Poppy Crum: They can see faster, and they're more sensitive to that sort of differentiation than someone who says, "I'm not a video game player," or self-identifies that way.
Andrew Huberman: Because they've trained it.
Poppy Crum: Yeah, they've trained it.
Andrew Huberman: Right? Like, a first-person shooter game, which I've played occasionally, in an arcade or something like that.
Poppy Crum: Yeah.
Poppy Crum: Yeah.
Poppy Crum: Yeah.
Andrew Huberman: I didn't play a lot of video games growing up. I don't these days either. But, yeah, a lot of it is based on contrast sensitivity, knowing if that is a friend or foe.
Poppy Crum: Absolutely.
Andrew Huberman: Are you supposed to shoot them or not?
Poppy Crum: Yeah.
Andrew Huberman: You have to make these decisions very fast.
Poppy Crum: Yeah.
Andrew Huberman: Like, right on the threshold of what you would call, like, reflexive.
Poppy Crum: Yes.
Andrew Huberman: Like, no thinking involved. But it's just rapid iteration and decision-making. And then the rules will switch.
Poppy Crum: Yeah.
Andrew Huberman: Right? Like, suddenly you're supposed to turn other things into targets and other things into friends.
Poppy Crum: Yeah.
Poppy Crum: Well, you're spot on, because then you take someone who self-identified as a non-gamer, make them play 40 hours of Call of Duty, and now their contrast sensitivity looks like a video game player's. And it persists. You know, go back, measure them a year later. But 40 hours of playing Call of Duty, and I see the world differently, not just in my video game.
Andrew Huberman: Mm-hmm.
Poppy Crum: I actually have foundational shifts in how I experience the world that give me greater sensitivity to my situational awareness, my situational intelligence.
Andrew Huberman: In real life.
Poppy Crum: Yeah.
Andrew Huberman: Yeah.
Poppy Crum: Yeah, because that's a low-level processing capability, and I love intersecting those when you can. But what's even, I think, more interesting is you also... And these were some... This was a great study by Alex Paget and Daphne Bavelier, where it's not just the contrast sensitivity. Let's go to that next level where we were talking about Bayesian, like, probabilistic decisions where things aren't deterministic.
Poppy Crum: And for a video game player, and I can train this, they're going to make the same decisions as a non-video game player in those probabilistic inferential situations, but they're going to do it a lot faster.
Poppy Crum: And so, that edge, that ability to get access to that information, is phenomenal, I think.
Andrew Huberman: Mm-hmm.
Poppy Crum: And when you can tap into that, that becomes a very powerful thing. So, like, probabilistic inference goes up when I've played 40 hours of Call of Duty, but then what I like to do is take it and say, "Okay, here's a training environment."
Poppy Crum: You know, I had a couple of Stanford's top soccer players in my course this year, and 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 two-hour practice, but in real time, and getting auditory feedback so that I am actually tapping into more neural training?
Poppy Crum: So, we had sensors, like, on their calves that were measuring acceleration velocity and able to give us feedback in real time as they were doing a sort of somewhat gamified training. I don't want to use the word gamified. It's so overused, but let's say it felt like a fun environment.
Andrew Huberman: Mm-hmm.
Poppy Crum: 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 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 closed-loop behavior, I start to... My neural representation of that is going to start differentiating more.
Andrew Huberman: Mm-hmm.
Poppy Crum: So, with that, that's where the auditory feedback. So, they're getting that in real time, and you build that kind of closed-loop environment that helps build that, creating greater resolution in the brain and greater sensitivity to differentiation.
Andrew Huberman: I'd love for you to share the story about your daughter improving her swimming stroke, right? Because she's not a D1 athlete yet. Maybe she will be someday. But she's a swimmer, right?
Poppy Crum: Yes.
Andrew Huberman: 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. You took a slightly different direction that really points to just how beneficial and inexpensive this technology can potentially be, or relatively inexpensive.
Poppy Crum: Yeah.
Poppy Crum: Well, first I'll say this. Number one is having good swimming coaches.
Andrew Huberman: Okay. Sure, I'm not trying to do away with swimming coaches.
Poppy Crum: Parents who are data-centric and really like building technologies are sometimes, maybe, can be red herring distractions, but hopefully not.
Andrew Huberman: Okay. All right. Well, yes.
Poppy Crum: That's one of them.
Andrew Huberman: Yeah.
Poppy Crum: But, no.
Andrew Huberman: Let's keep the swimming coaches happy.
Poppy Crum: Yeah. So, for example, like, you go and train with elite athletes, and if you go to a lot of swimming camps where you're, you know... Or training programs, it's always about work with cameras. And they're recording you, they're assessing your strokes, but the point is... I mean, you can use... And I did this knowing the things that the coaches... You know, or frankly, you can go online and learn some of those things that matter to different strokes. You can use Perplexity Labs, use some of these...
Andrew Huberman: These are online resources?
Poppy Crum: 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.
Andrew Huberman: So, how does that work? You're taking the phone underwater, analyzing the stroke?
Poppy Crum: In this case, I'm using a mobile phone, so I'm doing everything above.
Andrew Huberman: Okay, so you're filming... If you could walk us through this. So, you film your daughter doing the freestyle stroke for, you know...
Poppy Crum: Right, right.
Poppy Crum: Or breaststroke or butterfly.
Andrew Huberman: Sure.
Poppy Crum: There's a lot of core things that maybe you want to care about in backstroke and freestyle. What's their-- You know, and I am not a... We used to run. Like, I know you're a good runner, but I am a runner, I'm a rock climber, less so a swimmer. But things like the roll, or how high they're coming above the water. What's your velocity on a... You know, you can get actually very sophisticated once you have the data, right?
Poppy Crum: And what's your velocity on entrance? You know, how far in front of your head is your arm coming in? You know, what is... Again, maybe there are things that, you know, are obvious, which is you want to know how consistent your strokes and your cadence are across the pool. So, you don't just have your speed, you suddenly have access to what I would call, and you'll hear me use this a lot, a better resolution, but also a lot more analytics that can give you insight.
Poppy Crum: Now, the important thing here is my 10-year-old is not going to... I'm not going to go tell my 10-year-old that she needs to change 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.
Poppy Crum: 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 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 AI for the development of these types of tools.
Andrew Huberman: You tell AI to write a code so that it would analyze trajectory, jumping into the pool, how that could be improved if the goal is to swim faster.
Poppy Crum: 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 understand things as you move forward. You could do the same thing for running, for gait. You know, in a work environment you can understand a lot more about where vulnerabilities are, where weaknesses are.
Poppy Crum: There are sort of two different places where I see this type of AI acceleration and tool building really having a 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.
Andrew Huberman: Mm-hmm.
Poppy Crum: And that has a huge impact on improving performance, because that kind of data is really useful in understanding learning.
Andrew Huberman: Mm-hmm.
Poppy Crum: It also has applications for when you're in a work environment and you're trying to better understand success in that environment, in some process or skill of what you're doing. You can gain different analytics than you otherwise would in ways that become much more successful but also give you new data to think about with regard to what I would call a digital twin.
Poppy Crum: 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 use different interoperable, meaning datasets coming from different sources to gain insights into digitized data of a physical system, or a physical environment, or the physical world, be it a hospital, be it airplanes, be it my body, or be it my fish tank, to give me insights that are continuous and in real time that I otherwise wouldn't be able to gain access to.
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Andrew Huberman: We will definitely talk more about digital twins, but what I'm hearing is that it can be very, and this is nerd speak, but domain specific.
Poppy Crum: Yeah, yeah.
Andrew Huberman: 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, eliminate the need for a shopping list.
Andrew Huberman: It would just keep track of, like, "Hey, you usually run out of strawberries on this day and this day." And it would just keep track of it in the background, and then stuff would just arrive, and it would just be there and, like, eliminate what seemed 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 eight minutes to do that. But really, 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.
Poppy Crum: Yeah.
Poppy Crum: Yeah.
Andrew Huberman: So, I like to think in terms of the kind of lowest-level but highly useful and easily available now type of technologies.
Poppy Crum: Mm-hmm.
Andrew Huberman: There are a couple of areas, like, when it comes to students learning information, we've heard that AI... We've heard of AI generally as 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 because 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 isn't AI hallucinating. Just take large volumes of text verbatim from papers.
Poppy Crum: Yes.
Andrew Huberman: I've read those papers. Literally printed them out, taken notes, et cetera, and then I've been using AI to design tests for me of what's in those papers, because I learned, you know, about 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, especially when we self-test away from the material, like when we're being... When we're thinking, "Oh, yeah, like, what is the cascade of hormones driving the cortisol negative feedback loop?"
Poppy Crum: Yes.
Andrew Huberman: When I have to think about that on a walk, as opposed to just looking it up, it's the self-testing that is really most impactful for memory, because most of memory is anti-forgetting.
Poppy Crum: Yes.
Andrew Huberman: This is kind of one way to think about it. So, what I've been doing is having AI build tests for me and having it ask me questions, like, you know, "What is the signal between the pituitary and the adrenals that drives the release of cortisol, and what layer of the adrenals does cortisol come from?"
Poppy Crum: And I love that.
Andrew Huberman: You know? And so, I'm sure that the information it's drawing from is accurate, at least to the best of science and medicine's knowledge now.
Poppy Crum: Yes.
Andrew Huberman: And it's just testing me, and it's learning... This is what's so incredible about AI, and I don't consider myself 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?"
Andrew Huberman: And it'll say, "Oh, like, naming and this," and like, "Third-order conceptual links here need a little bit of work."
Poppy Crum: Mm-hmm.
Andrew Huberman: 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.
Poppy Crum: Whether you're building apps or you're building a tool, 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 accelerate your learning in this, right?
Andrew Huberman: Mm-hmm.
Poppy Crum: Because it's...
Andrew Huberman: Well, that's the goal.
Poppy Crum: But you're still putting in the effort to learn. And I think even the ways that I'm using it to... You know, computer vision with mobile devices, AI is a huge opportunity and tool. Like using the cameras and the data that you've collected to have much more sophisticated input is huge. But in both of those cases, you're shaping cognition. You're using data to enrich what you can know.
Andrew Huberman: Mm-hmm.
Poppy Crum: And AI is just incredibly powerful and a great opportunity in those spaces. You know, the place where I think it is... And I sort of separate it into literally just two categories. Maybe that's too simplistic. It's, am I using... 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 it 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 a cognitive skill I've done before to be faster? And it doesn't mean you don't want to do those things.
Poppy Crum: I mean, GPS in our car is a perfect example of a place where we're replacing a cognitive tool to make me faster and more effective. And frankly, you take away your GPS in a city you drive around in, and we're not very good, and...
Andrew Huberman: I remember paper maps. I remember the early studies of the hippocampus were based on London taxi drivers that had mental maps of the city.
Poppy Crum: Yeah.
Poppy Crum: Absolutely.
Andrew Huberman: You know, with all due respect to London taxi drivers, up until GPS, like, those mental maps are not necessary anymore.
Poppy Crum: No. And I mean, they had more gray matter in their hippocampus, and we know that, and you look at them today and 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 it can anticipate the things that locally you can't. And so, it's been replaced. But it still means when you lose that data, you don't expect yourself to have the same spatial navigation of that environment without it, right?
Andrew Huberman: Mm-hmm.
Andrew Huberman: Mm-hmm.
Andrew Huberman: I love 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 people...
Poppy Crum: Cognitively or physically.
Andrew Huberman: Cognitively or physically.
Poppy Crum: But you're still trying to gain insight and data and information that's making me a more effective human.
Andrew Huberman: Right.
Andrew Huberman: Right. And I think that the place where people are concerned, including myself, is when we use these technologies that eliminate steps, make things faster, but we fill in the additional time or mental space with things that are neutral to detrimental.
Poppy Crum: Yes.
Poppy Crum: Yeah.
Andrew Huberman: It's sort of like saying, "Okay, I can get all the nutrients I need from a drink that's eight 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 it up with also nutritious food? Right? Let's just say that it keeps me at a neutral health status.
Andrew Huberman: 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? And so, in the mental version of this, things are sped up, but people are filling the space with things that are making them dumber, in some cases.
Poppy Crum: There was a recent paper from MIT that I actually... It was very much what I spend a lot of my time talking about and thinking about, but...
Andrew Huberman: Yeah, could you describe that study?
Poppy Crum: The upshot of the paper, first, was that people... There's a lot less mental process or cognitive process that goes on for people when they use LLMs to write papers, and they don't have the same transfer, and they don't really learn the information. Surprise, surprise.
Andrew Huberman: So, just to briefly describe the study, even though it got a lot of popular press, it's, you know, MIT students writing papers using AI, versus writing papers the old-fashioned way, where you think and write.
Poppy Crum: Yeah.
Poppy Crum: So, there were three different categories. People who had to write the papers just using their brain only. And 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 rough categories. And then a third would be I use LLMs to write my paper. And they're looking at sort of what kind of transfer happened, what kind of...
Poppy Crum: They were measuring neural response, so they were using EEG to look at neural patterns across the brain to understand how much neural engagement happened during the writing of the papers and during the whole process, and then what they could do with that and what they knew about that information down the road. It's a really nice paper so I don't want to diminish it in any way by summarizing it.
Poppy Crum: But what I think is a really important upshot of that paper, and also just how we talk about it, that I liked was they... I talk a lot about cognitive load always, and you can measure cognitive load in the diameter of your pupil, and body posture, and how people are thinking. It's really, how hard is my brain working right now 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, cognitively, and whether we are aware of it or not.
Poppy Crum: And there's something called cognitive load theory that breaks down sort of what happens when our brains are under states of load. And that load can come from sort of three different places. It might be coming from what you would call intrinsic information, which is what... And this is all during learning.
Poppy Crum: The intrinsic load, or cognitive load, would be from the difficulty of the material I'm trying to understand. 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's presented. Is it poorly taught? Is it poorly organized? Or also even the environment. If I'm trying to learn something auditorily and it's noisy, that's introducing extraneous cognitive load, right? It's not the information itself, but it's because of everything else happening with that data.
Poppy Crum: And then the third is germane cognitive load, and that's the load that is used in my brain to build mental schemas, to organize that information, to really develop a representation of what that information is that I'm taking in. And that germane cognitive load, that's the work, right? And if you don't have germane cognitive load, you don't have learning, really.
Poppy Crum: And what they found is basically the germane cognitive load is what gets impacted most by using LLMs, which is, I mean, it's a very obvious thing. Like, that's...
Andrew Huberman: Meaning you don't engage quite as high levels of germane cognitive load.
Poppy Crum: Using LLMs, you're not engaging the mental effort to build cognitive schema, to build neural schemas and sort of the mental representation of the information so that you can interact with it later, and you have access to it later.
Andrew Huberman: Mm-hmm.
Poppy Crum: And this is really important, because without that, you won't be as intelligent on that topic down the road, that's for sure. 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.
Poppy Crum: In one case it's for aggregation of patient data. In another case it's for the history of case files, and that is the GPS that's happening in those spaces, because those are the tools that are quickly adopted. Where you have someone that maybe came from a different world, has learned that information, has gone and worked with data in a different way, 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 would exist.
Poppy Crum: 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 at the same level of richness and depth of information, or generalization, or extrapolation for those topics as someone that has learned in a different way.
Andrew Huberman: Mm-hmm.
Poppy Crum: There's a generational difference in understanding, not because they don't have the same information, but there is an acknowledgement that there's a gap, even though we're getting to the same place as fast.
Andrew Huberman: Mm-hmm.
Poppy Crum: And that's because of the learning that's happened.
Andrew Huberman: Mm-hmm. The germane cognitive load.
Poppy Crum: Absolutely. The cognitive load. Like, you've got to do the work. Your brain has to... And what was beautiful about your descriptions, Andy, is when you were talking about how you were using it, which I love to test yourself and find your vulnerabilities is...
Andrew Huberman: Mm-hmm.
Poppy Crum: You know, and actually in the paper at MIT, which I think, again, these are things that are somewhat obvious, but we just have to... I think we have to talk about them more, as people with higher competency on the topic use the tools in ways that still engage more germane cognitive load but help to accelerate their learning.
Andrew Huberman: Mm-hmm.
Poppy Crum: You know, where is the biggest vulnerability and gap? It's when it's especially in areas and topics where you're trying to learn a new domain fast, or you're under pressure and you're not putting in the germane effort, or you're not using the tools that you have access to that AI can enable.
Andrew Huberman: Mm-hmm.
Poppy Crum: You're not using them to amplify your cognitive gain but instead to deliver something faster, more rapid and then walking away from it.
Andrew Huberman: 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.
Poppy Crum: Mm-hmm.
Poppy Crum: Mm-hmm.
Andrew Huberman: 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 farmer's market, like a peach that, quote unquote, "really tastes like a peach," this kind of thing. You make your own food, you cook it, and you taste it, and it's just delicious. And I can also imagine a world where you order a peach pie online, and it shows up, and you take a slice, and you eat it.
Andrew Huberman: 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 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."
Andrew Huberman: And the older generation is like, "What are you talking about?" Like, "This is how it's done." What's different? Well, sure, experience is different, et cetera, 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, 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. Because 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, but it depends a lot on what those neural circuits were weaned on.
Poppy Crum: Yeah.
Poppy Crum: 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 the graduation gift for many years.
Andrew Huberman: I remember this. Yep.
Poppy Crum: And, you know, you don't see those anymore. And, yeah, if you even look at what happened with, like, the millennial generation in the last five years, especially during the pandemic, suddenly bread-making and sourdough, that became a thing. What's the difference, you know?
Poppy Crum: You've got bread, it's warm, 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 in the process and the making of it, and, you know, is clearly much more onerous than the other in its process of development.
Poppy Crum: I think the key part is, in the appreciation of the bread, the process is part of it, and that process is development of sort of the germane knowledge and the commitment and connection to that humanness of development, but also the tactile commitment.
Andrew Huberman: Mm-hmm.
Poppy Crum: 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 evolve and build a different prior going into that experience. And that is, I think, part of richness of human experience.
Poppy Crum: 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 integrated are these tools, these, you know, companions, whatever they may be, in our existence will shape us in different ways.
Poppy Crum: 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, you know, be it in the cabin of a car, be it in my rooms, my spaces.
Andrew Huberman: So what would that look like? Could you give me the lowest level example? Like, would it be an assistant that helps you travel today when you head back to the Bay Area? What is this nonphysical robot?
Poppy Crum: 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-
Andrew Huberman: Mm-hmm.
Andrew Huberman: HVAC systems?
Poppy Crum: Heating, ventilation, you know, AC.
Andrew Huberman: Yeah.
Poppy Crum: But you think about a thermostat, you know, a thermostat right now is optimizing for, you know, an AI thermostat, optimizing for my behavior, but it's trying to save me resources, trying to save me money, but doesn't know if I'm hot or cold. It doesn't know, to your point, my intent, what I'm trying to do at that moment, and this, you know, speaks more to a lot of 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.
Andrew Huberman: Mm-hmm.
Poppy Crum: But it can very easily, frankly, you know, it can talk to me, but it can also know my state of my body right now and what is going...
Andrew Huberman: Mm-hmm. Mm-hmm.
Andrew Huberman: Mm-hmm.
Poppy Crum: You know, if it's 1:00 AM and I really need to work on a paper, you know, my house should not get cold, but it also should be very... For me, it shouldn't, I know.
Andrew Huberman: Mm-hmm.
Poppy Crum: For some people it should.
Andrew Huberman: Yeah, my Eight Sleep mattress, which I love, 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 across the course of the night.
Poppy Crum: Mm-hmm.
Poppy Crum: Right.
Andrew Huberman: I put in what I think 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.
Poppy Crum: Mm-hmm.
Andrew Huberman: Much more deep sleep. And that's a little micro environment. You're talking about integrating that into an entire home environment.
Poppy Crum: 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, 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 dynamic interactions that happen. But we can know these things. We can know so much about the human state from non-contact sensors.
Andrew Huberman: 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 dynamically cooling mattress, or dynamically heating mattress. Like, I discovered through the AI that my mattress was applying, and I was told, that heating your sleep environment toward the end of the night increases your REM sleep dramatically, whereas cooling at the beginning of the night increases your deep sleep.
Poppy Crum: Yes.
Poppy Crum: Yes.
Andrew Huberman: It 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 like sleep a lot, but I don't want to need to sleep so much in order to feel great.
Poppy Crum: Mm-hmm.
Poppy Crum: Well, you want to have your own choice about how you sleep, given that it's helping you have that.
Andrew Huberman: Yeah.
Andrew Huberman: Right.
Andrew Huberman: Sometimes I have six hours, sometimes I have eight hours, this kind of thing. Here's where 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, Poppy.
Poppy Crum: Yeah.
Andrew Huberman: We're talking about sleep, and we know a lot about sleep. You've 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, we 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.
Andrew Huberman: And AI and technology, I would say, is doing a really great job, as is pharmacology, to try and enhance sleep. Sleep's getting better. We're getting better at sleeping, despite more forces potentially disrupting our sleep, like smartphones and noise and city noise, et cetera.
Poppy Crum: Mm-hmm.
Andrew Huberman: Okay. Here's the big problem in my mind, is that we have very little understanding or even names for different awake states.
Poppy Crum: Mm.
Andrew Huberman: We have names for the goal, like, "I want to be able to work." Okay, what's work? What kind of work? "I want to write a chapter of a book." What kind of book? "A non-fiction book." Based on what? But, like, 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.
Andrew Huberman: And so the technology, AI and other technologies don't really have... They don't know what 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?"
Andrew Huberman: And so I think, like, we don't really understand what to try and 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, et cetera, and then help us optimize for those the same way that we optimize for sleep?
Andrew Huberman: 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 goal, and what people have spent so much time, energy, money, et cetera on, whether or not they're drinking alcohol, caffeine, taking Ritalin or Adderall, or running, humans 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 us a goal that we don't even know we have?
Poppy Crum: 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 am very focused right now. I need to know the context of my environment that's driving that. Like, what's in that environment? Is it internal focus that's gotten me there? What is my environment?
Poppy Crum: What is that external environment? So 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 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 experiencing joy or heightened attention right now.
Poppy Crum: Some different states you may want to have my home or my system react to mitigate.
Andrew Huberman: Well, like, if you get sleepy in a smart vehicle, it will make adjustments.
Poppy Crum: Mm-hmm.
Poppy Crum: Potentially it will make adjustments, but not necessarily right for you.
Andrew Huberman: Mm-hmm.
Poppy Crum: That's an important part, is optimizing for personalization and how a system responds. And, you know, it can make any home, an HVAC system or the internal state of a vehicle is going to adjust, you know, sound, background sound, music, it's going to adjust whatever whether it can, haptic feedback, temperature, lighting, you know, any number of, you know, position of your chair, dynamics of what's in your space. All of these different systems in my home or my other, you know... 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?
Andrew Huberman: Mm-hmm.
Andrew Huberman: Mm-hmm.
Poppy Crum: Some... Yeah.
Andrew Huberman: Yeah, I always think of devices as good at measurement or modification.
Poppy Crum: Right.
Andrew Huberman: Mm-hmm.
Poppy Crum: Measurement or modification. Measurement is critical, and that's... Yeah. But measurement not just of me, but also of my environment and understanding of the external environment. And this is where things like Earth observation and understanding, you know, we're getting to a place where we're getting, you know, really good image quality data from the satellites that are going in the sky at much 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?
Andrew Huberman: Can you give me an example where that impacts everyday life? Are we talking about, like, weather analysis?
Poppy Crum: Sure. Weather predictions, car environment... You know, things happening.
Andrew Huberman: Uh-huh.
Andrew Huberman: And what about traffic? Why haven't they solved traffic yet given all the knowledge of object flow and how to optimize for object flow? And we've got satellites that can basically look at traffic, I mean, and open up roads dynamically, like change number of lanes. Why isn't that happening?
Poppy Crum: The traffic problem gets resolved when you have autonomous vehicles in ways that don't have, like, the human side of things.
Andrew Huberman: That gets resolved?
Poppy Crum: It does. Like-
Andrew Huberman: Autonomous vehicles can solve traffic?
Poppy Crum: Fully autonomous vehicles. You don't have traffic in the ways that you do with, you know, human behavior. Yeah.
Andrew Huberman: My goodness, that's reason alone. That's reason alone to shift to autonomous vehicles.
Poppy Crum: It is that injection from 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, which are wonderful for understanding. There's so much you learn, you know, from a smart mattress and ways of also both measuring as well as intervening to optimize your sleep, which is the beauty, and it's this nice, incredible period of time where you can measure so many things.
Andrew Huberman: Mm-hmm.
Poppy Crum: But, you know, in our home... I used the example of a thermostat, right? 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. You know, there's a company, PassiveLogic. I love them.
Poppy Crum: They actually have, I think, some of the smartest digital twin HVAC systems but, you know, their sensors measure things like sound. They measure carbon dioxide, your CO2 levels. Like, when we breathe, we give off CO2, you know. So imagine, there's a dynamic mixture of acetone, isoprene, and carbon dioxide that's constantly exchanging when I get stressed or when I'm feeling, you know, happiness or suspense 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 have more information to contribute about how I'm feeling, and can also be part of that solution in ways that I don't have to have things on my body, right?
Poppy Crum: 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 was at Dolby and had them watching "Free Solo," you know, the Alex Honnold movie where they're climbing El Cap.
Andrew Huberman: Stressful.
Poppy Crum: So, carbon dioxide's heavier than air, so we could measure carbon dioxide from, you know, just tubes on the ground, and you could get the real-time differential of CO2 in there, and-
Andrew Huberman: Were they scared throughout?
Poppy Crum: No. Well, but I mean, I like to say we broadcast how we're feeling, right? And we do that wherever we are.
Andrew Huberman: Mm-hmm.
Poppy Crum: And in this, you could look at the time series of carbon dioxide levels and be able to know 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.
Andrew Huberman: Really?
Poppy Crum: Absolutely. There's another study, I forget who the authors are, and you know, they've got different audiences watching "Hunger Games," and different days, different people. You can tell exactly where Katniss's dress catches on fire. And it's like we really are sort of... You know, it's like digital exhaust of how we're feeling. And our thermals, we radiate the things we're feeling. I'm very bullish on the power of, you know, our eye in representing our cognitive load, our stressors-
Andrew Huberman: RI?
Poppy Crum: Our eye, yes.
Andrew Huberman: Mm-hmm.
Poppy Crum: Like, the diameter-
Andrew Huberman: Oh, our eye.
Poppy Crum: Our... Yes.
Andrew Huberman: Yeah, our eye. Sorry, literally our eyes.
Poppy Crum: Yes.
Andrew Huberman: Our pupil size.
Poppy Crum: Yes, yes, yes.
Andrew Huberman: Yeah, yeah.
Poppy Crum: You know, back when I was a physiologist, I always... You know, where I've worked with a lot of species in understanding information processing internally in cells, but also then I would very often use pupillometry as an indicator of, you know, a perceptual engagement and experience.
Andrew Huberman: Mm-hmm.
Andrew Huberman: Mm-hmm.
Andrew Huberman: Yeah, bigger pupils mean more arousal, higher levels of alertness.
Poppy Crum: Yeah.
Andrew Huberman: And we should know this.
Poppy Crum: More arousal, cognitive load, or, you know, obviously lighting changes. But 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 leverage all of those autonomic nervous system, 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 it.
Andrew Huberman: Mm-hmm.
Andrew Huberman: Below conscious detection.
Poppy Crum: Yeah.
Andrew Huberman: Yeah.
Poppy Crum: But today we can do that with a... I mean, 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. So it becomes a channel of data. And it may be an ambiguous signature in the sense that there are changes in lighting, am I aroused or am I, you know-
Andrew Huberman: But those can be adjusted for, right? Like, you can literally take a measurement, wear eyeglasses that are measuring pupil size.
Poppy Crum: Mm-hmm.
Andrew Huberman: The eyeglasses could have a sensor that detects levels of illumination in the room at the level of my eyes.
Poppy Crum: Mm-hmm.
Poppy Crum: Mm-hmm.
Andrew Huberman: It could measure how dynamic that is, and we can just make that the denominator in a fraction, right? And then we can just look at changes in pupil size as the numerator in that fraction, right?
Poppy Crum: Yep.
Andrew Huberman: More or less.
Poppy Crum: You just have to have other sensors.
Andrew Huberman: And then, all you need to do is cancel... So 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?
Andrew Huberman: You just, like, normalize for that, and you end up with an index of arousal.
Poppy Crum: Yep.
Poppy Crum: Right.
Andrew Huberman: Which is amazing. You could also use the index of illumination as a useful measure of, like, are you getting, compared to your vitamin D levels, to your levels of... Maybe you need more illumination in order to get more arousal. Like, it could tell you all of this. It could literally say, "Hey, take a five-minute walk outside to the left after work, and you will get your photon requirement for the day." You know, this kind of thing, not just measuring steps.
Poppy Crum: Mm-hmm.
Andrew Huberman: All this stuff is possible now.
Poppy Crum: Mm-hmm.
Andrew Huberman: 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 the lab. Like, you think about... With the resident that's been up for 13 hours because that's the standard in the field, and they're making mistakes 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."
Poppy Crum: Yeah. No, and a lot of the consumer devices and just computation, we can do from, you know, whether it's cameras or exhalant 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, I mean, why isn't it happening? A lot of the reasons are simply the regulatory process is antiquated and not up to keeping up with the acceleration of innovation that's happening.
Andrew Huberman: Mm-hmm.
Poppy Crum: You know, getting things through the FDA, even if they're deemed in the same ballpark and supposed to move fast, with the regulatory costs and processes, is really high.
Andrew Huberman: Mm-hmm.
Poppy Crum: You know, you end up many years down the road from when the capability and the data and technology actually should've 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 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.
Poppy Crum: And that's because 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 continue to move forward in those spaces. But there's no question that that's a big part of what holds back the availability of a lot of these devices and capabilities.
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Andrew Huberman: 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 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? What's this going to look like?
Poppy Crum: I'm an advocate for fewer things on, you know, not having all this stuff on our bodies. There's so much we can get out of the computer vision side, you know, the cameras in our spaces and how they're supporting us in our rooms, the sensors in our... You know, I brought up HVAC systems earlier. So, now you've got effectively a digital twin and sensors that are tracking my metabolic rates just in my space.
Poppy Crum: They're tracking 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 vehicle. You can tell whether I'm stressed or how I'm feeling just by the posture I have sitting in my car. Right? And you need AI. This is AI interpretation of data.
Poppy Crum: 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, with contextual intelligence, AI-driven understanding of what's happening in that space that's driving, you know, the state of me, and how do I... I keep leaning to the side because I'm thinking about the way I move and sit. 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.
Poppy Crum: What's happening, you know, if I'm driving a car, or what's happening in my home, in the weather, and not just threats that might be outside, and noise that's happening not inside the space, but things that give context to have more intelligence with the systems we have.
Poppy Crum: So I'm a huge believer in 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. In terms of wearables, though, so obviously some of the big companies. The watch we have on our hand has a lot of information that is very relevant to our bodies.
Poppy Crum: The devices we put in our ears, you may not realize but, you know, a dime-sized patch in your concha, we can know heart rate, blood oxygen level, because the electrical signature that your eye produces when it moves back and forth. We can know what you're looking at just from measuring a signature, measuring your electrooculogram in your ear.
Poppy Crum: We can measure EEG, electroencephalograms. You can also get, you know, eye movements out of electroencephalograms, 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. And you've got a number of companies working on that right now. You know, so do we need to wear lots of different sensors? No.
Poppy Crum: Do we need to have the sensors, the data we have, whether it's on our bodies or off our bodies, be able to work together and not be proprietary to just one company, but to be able to integrate with other companies? That becomes really important. You need integrative systems so that the data they have can interact with the systems that surround you, or surround my spaces, or the mattress I'm sleeping on. Right?
Andrew Huberman: Mm-hmm.
Poppy Crum: Because you've had a lot of specialty of design come from different developers, and that's partly been a product of, again, the FDA and the regulatory pathways because of the cost of development. It tends to move companies towards specialization unless they're very large.
Andrew Huberman: Mm-hmm.
Poppy Crum: But where we're at today is we're getting to a point where you're going to start seeing a lot of this data get integrated, I think. 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 gait, it has ramifications in so many different ways. When I got here, I was talking to some of the people that work with you, and they were like, "Well, what wearables do you wear?" And I actually don't wear many at all. And, you know, I have worn rings, I've worn watches at different times.
Poppy Crum: But for me, the importance is the point at which I get insights that... You know, I am a big believer in as little on my body as possible when it comes to wearables. One interesting company that I think is worth mentioning is Pison. And Pison, you know, again, they've got a form factor that's like a Timex watch, they're partnered with Timex, but they're measuring... Are you familiar with Pison?
Andrew Huberman: No.
Poppy Crum: Okay. So they're measuring psychomotor vigilance. So, you know, really trying to understand, it's like a ENG, electroneuromodulation, and they're trying to understand fatigue and neural attentiveness in a way that is continuous and useful for, say, high-risk operations or training, you know, whether it be in sport.
Poppy Crum: But what I like about it is, it's actually trying to get at a higher level cognitive state from the biometrics that you're measuring. And that, to me, is a 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.
Andrew Huberman: Mm-hmm.
Poppy Crum: And then I can start associating that data with the other data to have better decisions, better insights at a certain point in time. And that's really your digital twin.
Andrew Huberman: It's interesting, earlier you said you don't like the word gamification.
Poppy Crum: Mmm. Yeah.
Andrew Huberman: But, 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.
Poppy Crum: Mm-hmm.
Andrew Huberman: And if they don't, they don't see that as 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 night basis.
Poppy Crum: Yes.
Andrew Huberman: And I feel like that's been pretty effective. When I say gamification, I don't necessarily mean competitive with others, but I mean encouraging of oneself, right? So, I could imagine this showing up in other domains too, for wakeful states. Like, I had very few highly distracted 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 of an hour each at least.
Poppy Crum: Yeah.
Andrew Huberman: That would feel good. It was like, oh, that was a day well spent, even if I didn't accomplish what I wanted to in its entirety. I put in some really good solid work. Right now, it's all very subjective. 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 the threshold. But if you think about it, we could've just as easily said, "Hey, you want to walk at a reasonable pace for you for 30 minutes per day."
Poppy Crum: Mm-hmm.
Andrew Huberman: 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." So, apparently it's a meaningful thing for people. So, I think quantification of performance creates this aspirational state.
Poppy Crum: Mm-hmm.
Andrew Huberman: So, I think that can be very useful.
Poppy Crum: Data and understanding the quantification that you're working towards is really important. Those are summary statistics effectively that maybe they're good on some level to aim for if it means that people move more.
Andrew Huberman: Mm-hmm.
Poppy Crum: 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 and this is making me do it, that's awesome or that's great.
Poppy Crum: 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 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 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 training can be fun and gamified in some ways.
Andrew Huberman: Mm-hmm.
Andrew Huberman: Mm-hmm.
Poppy Crum: Again, my life has been predominantly in industry but I love teaching and I've always been at Stanford to really... There I try to... It's how do I use technology 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. How do we think about the neural system and use this more enjoyable understandable target to engage with it.
Poppy Crum: One of my favorite examples, though, is there was a period, it was right around 2018, 2020, and from 2018 to 2020, and into the pandemic where... The students, I noticed had a much more... There were a lot of projects. Their final project they can build whatever they want. And you know, they've had to do projects where they build neuro brain computer interfaces. They've had to build projects in VR. They've had to build AR projects.
Poppy Crum: They've had to build projects that use any sort of input device. 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.
Andrew Huberman: Mm.
Poppy Crum: I thought that was...
Andrew Huberman: Interesting.
Andrew Huberman: Mm-hmm.
Poppy Crum: And it was a very notable shift in like the student body, and maybe you've seen that too. But I still got these, like one of my favorite games to date was this VR game where I'm in a morgue, 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 morgue, and they're getting closer and there's people breathing down my neck and they're like, "Ah," you know, and everything.
Andrew Huberman: Mm-hmm.
Andrew Huberman: Mm-hmm.
Poppy Crum: And it's a wellness app. Go figure.
Andrew Huberman: Mm-hmm.
Poppy Crum: 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...
Andrew Huberman: So, it was about stress control, basically.
Poppy Crum: 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'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 understand that different, that sophistication.
Andrew Huberman: 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.
Poppy Crum: Mm-hmm.
Andrew Huberman: But it's very difficult to scare people into doing the right things. You need to incentivize people to do the right things by making it engaging, and fun, and quantifiable, and I like the example of the zombie game.
Poppy Crum: Yeah.
Andrew Huberman: Okay. So, fortunately, we won't have to wear dozens of sensors. They'll be more integrated over time.
Poppy Crum: I'm happy to walk through a cheat sheet later, after... You know, for building out a computer vision app for quantifying some of these more personalized domain-related things that people might want to do, if that's useful.
Andrew Huberman: That would be awesome. Yeah, and then we can post a link to it in the show note captions. Because I think that the example you gave of creating an app that can analyze swimming performance, running gait, focused work bouts, I think that's really intriguing to a lot of people.
Poppy Crum: Sounds good.
Poppy Crum: Mm.
Andrew Huberman: But I think there's a... At least for me, there's a gap there between hearing about it, thinking it's really cool, and how to implement. So, I'd certainly appreciate it. I know the audience would too.
Poppy Crum: I mean, just in...
Andrew Huberman: And that's very generous of you. Thank you.
Poppy Crum: Yes, absolutely. And 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, we gave the examples of talking about some of the LLMs. Of course, we went to Cal. I was at a film premiere, and I was sitting 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 peer group... Like, my peers can't start a paper without ChatGPT." And, it was a truth, but it was also a concern. So, they understand the implications of what's happening.
Andrew Huberman: Mm-hmm.
Poppy Crum: And that's on one level. We're in an era of agents everywhere, and I think we said that there's... A number of people have said, "We'll be using AI agents for everything at work in the next five years."
Andrew Huberman: Mm-hmm.
Poppy Crum: And some of those things we need to use. Agents will accelerate it... They will accelerate capability, they will accelerate short-term revenue, but they also will diminish work first, you know, cognitive skill. And as a user of agents in any environment, as an owner of companies employing agents, you have to think hard about what the near-term and long-term ramifications.
Poppy Crum: Doesn't mean you don't use your agents in places where you need to, but without the germane cognitive load, there is a different dependence now that you have to have down the road, but also, you have to think about how do you engage with the right competence to keep your humans that are engaged with developing their cognitive skills, and their mental schemas to be able to support your systems down the road.
Andrew Huberman: Let's talk more about digital twins.
Poppy Crum: Sure.
Andrew Huberman: I don't think this concept has really landed squarely in people's minds as 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, 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?
Poppy Crum: Not at all, in the ways that I think are most relevant. Maybe, you know, there are some side cases that think about that. And so, first, two things to think about. One, when I talk about digital twins to companies and such, I like to frame it on how it's being used, how... The immediacy 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.
Poppy Crum: When an air traffic controller sits down and looks at 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, things that are determined to be problems or risks, right?
Poppy Crum: And so, that's what you're trying to engage, a human system. The visualization of that data is important, or it doesn't have to be visualization, the interpretation of it, right? And it's not the raw data. It's, again, how is that data represented? You want the key information in a way that the salient, most important information, in this case, about planes, is able to be acted on by that human or even autonomous system, right?
Andrew Huberman: Could you give me an example in a more typical home environment?
Poppy Crum: We're both into reefing, and I built a aqua-cultured reef in my kitchen partly because I have a child, and I wanted her to understand. I love 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 worry about, care about, and all. And initially, when I started, and maybe this is not something you encountered, but when you build a reef or a reef tank and do saltwater fish, a couple of things. You're doing chemical measurements by hand usually, weekly, biweekly. There's a whole, 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...
Poppy Crum: 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 in human measurements. You don't have the right resolution of measurements. And by resolution, I mean, every few days is not enough to track a problem. 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.
Poppy Crum: So, if you look at my fish tank right now, or my reef tank right now, 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, or oh, the RO/DI tank... I can tell what's happening by looking at the data.
Poppy Crum: And you know this, you've got the spectrum of your lights is on a cycle of effect that's representative of the environment that the corals you're aqua-culturing would... You know, that 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 my tank is very stable. My tank knows what's wrong, what's happening. I can look at the data and understand that an event happened somewhere that could have been mitigated, or I can understand that something's wrong quickly before it even shows up.
Andrew Huberman: Mm-hmm. It's amazing. I mean, I think for people who aren't into reefing, they might ask, like, I know people that are... I know multiple people in my life are soon to have kids, most everybody nowadays has a camera on 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.
Poppy Crum: Yes.
Andrew Huberman: So, camera and microphone. Do you think we either have now or soon will have AI tools that will help us better understand the health status of infants? Like, parents learn intuitively over time based on diaper changes, based on all sorts of things, cries, frequency of illnesses, et cetera, in their kids, how well their kids are doing before 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?
Andrew Huberman: Not just if they're awake or asleep or if they're in some sort of trouble, but really help us adjust our care of our young? What's more important for our species than supporting the growth of our next generation?
Poppy Crum: No, absolutely. But I'd even... More on the biological side. So, think about digital twins. And I'll get to babies in a moment, but if you've ever bought a plane ticket, which any of us have today, that's a very sophisticated digital twin. Not the air traffic controllers looking at planes, but the pricing models for what data is going into driving that price in real time, right?
Poppy Crum: 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... 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 AI-driven digital twin that's driving the sort of value of that ticket.
Poppy Crum: And so, there are places where we use digital twins. So, that would be 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.
Andrew Huberman: Mm-hmm.
Poppy Crum: And then you think about a different example where you've got a whole sandbox model. The NFL might have a digital twin of every player that's in the NFL, right? They know the data. 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 at high risk for an injury, so that they can mitigate it, or...
Andrew Huberman: They're using those kind of data?
Poppy Crum: Absolutely, yeah.
Andrew Huberman: 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.
Poppy Crum: Yeah.
Poppy Crum: Yes.
Andrew Huberman: I feel like these are...
Poppy Crum: Well, it's a duplicate of relevant data and information about yourself, but not just trying to... What's the purpose in emulating myself?
Andrew Huberman: Mm-hmm.
Poppy Crum: It's to emulate key... So, imagine me as a physical system. I'm going to digitize some of that data, right? And whatever data I have, 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?
Andrew Huberman: Okay, so it's a digital representative more than a digital twin.
Poppy Crum: Yes.
Poppy Crum: Yes.
Andrew Huberman: I think... I'm not trying to split it.
Poppy Crum: There are many digital twins in any digital twin.
Andrew Huberman: Yeah.
Poppy Crum: So like, even you've got data, you live with lots of digital... I think the world would... The digital twin, whatever nomenclature would say is a digital twin, but I like a digital representative.
Poppy Crum: And it's informing some aspect of decision-making, and it's many feedback. So, I'm digitizing different things. And in that situational awareness model, like, just can I give a quick example? So, imagine, so I can digitize an environment, right?
Poppy Crum: I can digitize or let the space we're in right now. And would that be a digital twin? So, first, in situational awareness, there's the state of, okay, so what's the sort of sensor limitations, the acuity of the data I've actually brought in? Okay? So, that's like perception, and 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.
Poppy Crum: 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? And that's where things get interesting, and that's where a lot of... I think the future of AI products is, because then it's the feedback loops of what's happening with that input and that data. And 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 in that space. But that's all about our situational awareness and intelligence in that environment.
Andrew Huberman: Yeah. I can see where 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.
Poppy Crum: Mm-hmm.
Andrew Huberman: I think people are gradually getting on board the idea that AI can be very useful. We have digital representatives already out there for us in these different domains.
Poppy Crum: Yes, absolutely.
Andrew Huberman: I think being able to customize them for our unique challenges and our unique goals is really what's most exciting to me.
Poppy Crum: I love that, because I think what I was trying to say is exactly what you said. Look, they are out there and these are effectively digital twins. Every company that's... You're interacting with social media has effectively a digital twin of you in some place. It's not to emulate your body, but it's to emulate your behaviors in those spaces, or you're using tools that have digital twins 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 an agency of what that can mean for you?
Poppy Crum: If the NFL is using it for a player, you can use it as an athlete, meaning as an athlete at any level, right?
Andrew Huberman: Mm-hmm.
Poppy Crum: 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 not... Your baby's always successful. I don't want to say, but what is maybe not working well for them. The things that... But I would tend to say, the exciting places about digital twins come in 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 one I liked was I had three good, very focused work sessions.
Poppy Crum: 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 the resolution of the data, where the data source, where the data's coming from, meaning whether is it biometric data, is it environmental data?
Poppy Crum: 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.
Andrew Huberman: Mm-hmm.
Poppy Crum: I like to call it situational intelligence, as sort of the overarching goal that we want to have, and that involves my body and systems having situational awareness, but it's really, you know, a lot of integration of data that AI is very powerful for thinking about how does it optimize and give us the insights. It doesn't have to just have systems behave, but it can give us the insights of how effectively we can act in those environments.
Andrew Huberman: Yeah. I think of AI as being able to see what we can't see.
Poppy Crum: Yes.
Andrew Huberman: So, for instance, if I had some sort of AI representative that 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 air conditioner clicked over to silent or back to on, that it would break my focus for the next 10 minutes.
Poppy Crum: Mm-hmm.
Poppy Crum: Yes.
Andrew Huberman: And I wasn't aware of that. And by the way, 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.
Poppy Crum: Mm-hmm.
Andrew Huberman: Or that it's always at the 35-minute mark that my eyes start to have to re-read words or lines, because somehow my attention is drifting, 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.
Poppy Crum: Right.
Poppy Crum: Right.
Andrew Huberman: And so, it can see through our cognitive blind spots, and our functional blind spots. 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, when you have a pain, and you don't know what it is, you go to this thing called the doctor.
Poppy Crum: Yeah.
Andrew Huberman: Or when you have 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.
Poppy Crum: Two examples to your point, which I love. The reading, potentially, there's a point at which you're experiencing fatigue and you want to... Ideally, much like the fish tank, you want to be not reactive, you want to be proactive. You want to mitigate it, stop, or you could have...
Andrew Huberman: Mm-hmm.
Poppy Crum: Your devices can have that integration of data, and respond to give you feedback when either your mental acuity, your vigilance, or your just effectiveness has waned, right? But also, on the level of health, we know AI is huge for identifying a lot of different pathologies out of data that as humans we're just not that good at discerning. You know, our voice. In the last 10 years, we've become much more aware of the different pathologies that can be discerned from AI assessments of our speech and not what we say, but how we say it. Right?
Andrew Huberman: Yeah. There's a lab up at University of Washington, I think it's Sam Golden's lab, working on some really impressive algorithms to analyze speech patterns as a way to predict suicidality.
Poppy Crum: Oh, interesting.
Andrew Huberman: And to great success. Where people don't realize that they're drifting in that direction.
Poppy Crum: Mm-hmm.
Poppy Crum: Yeah.
Andrew Huberman: And phones can potentially warn people.
Poppy Crum: Yes.
Andrew Huberman: Warn themselves, right, that they're drifting in a particular direction. People who have cycles of depression or mania can know whether or not they're drifting into that. It can be extremely useful.
Poppy Crum: Yeah.
Andrew Huberman: They can discern who else gets that information. And it's all based on tonality at different times of day.
Poppy Crum: Yeah.
Andrew Huberman: Stuff that even in a 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.
Poppy Crum: Absolutely. Neural degeneration, it shows up and, short assessment of how people speak, they've definitely been able to show potential likelihood of psychosis.
Andrew Huberman: Mm-hmm.
Poppy Crum: And that's with syntactic completion and how people read paragraphs. Neural degeneration though, things like Alzheimer's, show up in speech because of the linguistic cues control but, sometimes 10 years before a typical clinical symptom would show up that would be identified. And 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, something like that, what I just did, which was I purposely stuttered.
Andrew Huberman: Mm-hmm.
Poppy Crum: I started a word again, right? And it's 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 pick up on because it makes us ineffective in communication or... But an algorithm can do so very well. Diabetes, heart disease, both show up in voice.
Poppy Crum: Diabetes shows up because you can pick up on dehydration in the voice. Again, I'm a sound person in my heart and my past, and if you look at the spectrum of sound, you're going to see changes that show up, there are very consistent things in a voice that show up with dehydration in the spectral salience. 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 a partner or a spouse or a child care-taking our parents and listening for like, the four kilohertz modulation, but an algorithm can.
Poppy Crum: And all of these are places where you can identify something that is potentially... Mitigate something proactively before there's a problem. And especially with neural degeneration, we're really just getting to a place where there's pharmacological opportunities to slow something down, and you want to find that as quick as possible. So, you want to have that input so that you can do something about it.
Poppy Crum: You asked me about the babies, like, the type of coughs we have tell us a lot about different pathologies. So, for a baby, their cry, if I'm thinking... You asked me about a digital twin, where would I be most interested in using that information if I had children or... I mean, I do have a child. But in the sort of lowest touch, most opportunity, it's to identify potential pathologies or issues early based on the natural sounds and the natural utterances that are happening to understand if there is something that, you know, there's a way it could be helped, you could proactively make something much better.
Andrew Huberman: Let's talk about you.
Poppy Crum: Oh, boy.
Andrew Huberman: 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, when you were working on auditory perception and physiology, and then years later, now you're involved with AI, neuroplasticity, you were at Dolby. What is, to you, the most interesting question that's driving all of this? What guides your choices about what to work on?
Poppy Crum: Human technology intersection and perception is my core, right? I say perception, but the world is data, and how our brains take in the data that we consume to optimize how we experience the world 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.
Andrew Huberman: Mm-hmm.
Poppy Crum: That it is... 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 we're similar, but, you know, the nuances of how our brains are shaped and how they're influenced, and thus why I care... I've spent so much time in neuroplasticity, and it is at the intersection of everything. It's how are we changing and how do we harness that?
Poppy Crum: 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?
Andrew Huberman: Mm-hmm.
Poppy Crum: So, you asked me, how did I get there? One thing that... So, I was a violinist back in the day. I'm still a violinist and music is a part of my life, but I was studying Music and Engineering when I was an undergrad. And I think we alluded to the fact I have absolute pitch, and absolute pitch is, for anyone that doesn't know, it's not anything that means I always sing in tune.
Poppy Crum: What it means is, I hear the world like... I hear sound like people see color. Okay. And I can't turn it off, really. I can kind of push it back.
Andrew Huberman: 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?
Poppy Crum: 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," right?
Andrew Huberman: I see. You're categorizing.
Poppy Crum: 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? So, I can say that's 350 hertz, or that's 400 hertz, or that's 442 hertz, and it has different applications. I mean, I can transcribe a jazz solo when I listen to it. That's a great party trick. But it doesn't mean that... It's not necessarily a good thing for a musician, right?
Poppy Crum: You know, as well as I do that categorical perception is we all have different forms of it, usually for speech and language, like units of vowels or phonetic units, especially vowels, that you can hear many different versions of an E and still hear it as an E. And that's what we would call categorical perception. And my brain does the same thing for a set of frequencies, to hear it as an A.
Poppy Crum: And 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 what key you're in, or 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 get you there somehow if we start somewhere else.
Andrew Huberman: Mm-hmm.
Poppy Crum: So, what happened to me when I was in music school, when I was in conservatory and also engineering school is 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 Shostakovich or play my chamber music in the ways that were... I was having to work too hard to override these sort of categories of sounds I was hearing.
Poppy Crum: So, I started playing early music, Baroque music. For anyone, I think I said earlier, A is a social construct. Today, typically, as a set, as a standard, A is 440 hertz. If you go back to the 1700s, A was 415 hertz in the Baroque era. And 415 hertz is effectively a G sharp. So, it's the difference between "ah" and "ah." Okay?
Poppy Crum: And 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 sharp in my brain. And it was completely... I was terrible. I was, like, always... It was really hard for my brain to override.
Poppy Crum: And I mean, 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... Their brains have evolved through their training in neuroplasticity to be able to not have the same sort of experience I had.
Poppy Crum: Anyhow, long story long, I was also taking a neuroscience course. In this neuroscience course, we were reading papers about sort of different map-making and neuroplasticity. And I read this paper by a professor at Stanford named Eric Knudsen. And Eric Knudsen did these amazing... Well, he did a lot of seminal work for how we understand the auditory pathways, as well as how we form multi-sensory objects, and the way the brain integrates cells' data across our modalities, meaning sight and sound.
Poppy Crum: 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 in all of that giant data set of the world, it's the set of data that optimally causes that cell to respond.
Poppy Crum: And for these cells, they cared about a particular location in auditory and visual space, which, frankly, for mammals, we don't have the same sort of cells because we can move our eyes back and forth in our sockets, unlike owls, and he studied owls. And owls have a very hard-wired map of auditory-visual space.
Andrew Huberman: On the other hand, if I hear a click off to my right, I turn my head to the right.
Poppy Crum: You turn your head, it triggers a different vestibular ocular response that moves, yeah, all of that, yes.
Andrew Huberman: Mm-hmm.
Andrew Huberman: Mm-hmm.
Poppy Crum: But in this case, he had these beautiful hard-wired maps of auditory-visual space, and then he would rear and raise these owls with prism glasses, that effectively shifted their visual system by 15-degrees.
Poppy Crum: And then, he would put them, key to developing neuroplasticity, he would put them in high, important... High, not stress, but let's say, situations where they had to do something critical to their survival or their well-being, and so they would hunt, and they would feed and do things like that with this 15-degree shift.
Poppy Crum: And consequently, he saw the cells, the auditory neurons, he saw their dendrites realign to the now 15-degree visually shifted cells. 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 super interesting for understanding how our brains integrate data and the feedback in neuroplasticity.
Poppy Crum: So, I go back to my baroque violin, where I'm always out of tune, and I'm tuning up 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 Shostakovich right after at A440, and I had that map, and I had nothing in between, but I could modulate between the two.
Poppy Crum: And that's the point at which I said, "I think I just... My brain is a little weird, and I just did something that I need to go better understand." So, that's how I ended up here as a neuroscientist.
Andrew Huberman: I know Eric's work really well. Our labs were next door.
Poppy Crum: Yes, he's wonderful.
Andrew Huberman: Our offices were next door.
Andrew Huberman: He's retired now.
Poppy Crum: I know.
Poppy Crum: He knows, I've told him this story.
Andrew Huberman: Yeah.
Andrew Huberman: He's wonderful. I think one of my favorite things about those studies, that I think people will find interesting, is that if an animal, human, or owl, has a displacement in the world, something's different, something changes, and you need to adjust to it, it could be new information coming to you that you need to learn in order to perform your sport correctly, or to perform well in class, 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.
Poppy Crum: Mm-hmm.
Poppy Crum: Yes.
Andrew Huberman: 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?
Poppy Crum: Yes.
Andrew Huberman: And I like that study so much because we hear all the time 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.
Poppy Crum: Yeah.
Andrew Huberman: And, you know, of course, if you put a gun to my head right now and you said, "Okay, remap your auditory world," I mean, there are limits at the other end too. I mean, I can't do it that quickly. But I think 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.
Poppy Crum: Yeah.
Andrew Huberman: 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 almost everyone, young and old, has integrated this new technology.
Poppy Crum: Mm-hmm.
Andrew Huberman: I think AI is coming at us very fast, and it's unclear what form it's coming at us and where, and as you said, it's already here, and I think we will adapt, for sure.
Poppy Crum: Yeah.
Andrew Huberman: We'll form the necessary maps. I think being very conscious of which maps are changing is so key. I mean, I think we're still doing a lot of cleanup of the detrimental aspects of smartphones. Short wavelength light late at night.
Poppy Crum: Absolutely.
Andrew Huberman: 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.
Poppy Crum: Well, they do change. Sam Altman had a... I saw him say this, and I actually thought it was a really good description. It's like Gen X, you know, there's a group that is using AI as a tool that's sort of novel, interesting. Then you've got different Millennials are using it as a search algorithm, and maybe that's even Gen X, but, you know, it's a little more deeply integrated. But then you go back to younger generations, and it's an operating system, and it already is. And that has major changes in neural structure for not just maps, but also neural processes, for how we deal with information, and how we learn.
Poppy Crum: 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 what is successful human performance and 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 stimuli, complex situations, and contexts.
Poppy Crum: But that situational awareness or physical behavior in those environments, you want that as fast as possible with as little cognitive load as possible. And, it's like, that execution is critical. You love looking across species. So do I. And looking for these ways where we are...
Poppy Crum: 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... How it can evade a predator, how it can find a target, find a mate. And it's doing things that are critical to it being able to survive, much as you said. Like, if I make it something that is absolutely necessary for success, it's going to do it, you know?
Poppy Crum: One of my favorite examples is a particular moth that bats predate on, echolocating bats. And frankly, echolocating bats are sort of nature's engineered, amazing predatory species. Their brains, when you look at them, are just incredible. They have huge amounts of their brain just dedicated to what's called an FM constant frequency, FM sort of sweep. Some of the bats elicit a call that's sort of like, "ooh, ooh," but really high.
Andrew Huberman: So we can't hear it. Yeah.
Poppy Crum: Yes. Yeah.
Andrew Huberman: What does that do for them?
Poppy Crum: It's doing two things. One, that the constant frequency portion is allowing them to sort of track the Doppler in a moving object.
Andrew Huberman: Mm-hmm.
Poppy Crum: And they're even so... I mean, it's such clever and sophisticated. They're not changing... They're changing subtly, 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.
Andrew Huberman: Mm-hmm.
Poppy Crum: So, otherwise, 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 call.
Andrew Huberman: Mm-hmm.
Andrew Huberman: Just so that people are on board, yeah, bats echolocate.
Poppy Crum: Yeah.
Andrew Huberman: Like, that they're sending out sound, and they can measure distance, and they can essentially see in their mind's eye. They can sense distance, they can sense speed of objects, they can sense the shape of objects by virtue of sounds being sent out and coming back.
Poppy Crum: Correct.
Poppy Crum: Absolutely.
Andrew Huberman: And they're shaping the sounds going out differently, so that they can look at multiple objects simultaneously?
Poppy Crum: But also, they're shaping the sounds they send out so that whatever comes back is in their optimal neural 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.
Andrew Huberman: Mm-hmm.
Poppy Crum: 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.
Andrew Huberman: Mm-hmm.
Poppy Crum: And that's what tells them the speed. So, that constant frequency is a lot like the ambulance sound going by. That's the compression of sound waves that you hear as a "whoo" when things move past you at speed.
Andrew Huberman: Mm-hmm.
Andrew Huberman: Right.
Poppy Crum: That's the Doppler effect. And then they're also... It has, usually, a really fast FM frequency modulated sweep, and that lets me take kind of an imprint of... 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 a sonic imprint of what's there, so I can tell topography, I can tell if there's a moth on a hard surface, right?
Poppy Crum: 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.
Andrew Huberman: How?
Poppy Crum: Multiple things. I call it almost an acoustic arms race that's happening between the two, and there's a lot of acoustic subterfuge between the moth. You know, but there's also beautiful deterministic responses that they have. And so, first, deterministic behaviors, again, be it an athlete, be it effectiveness, being fast, quick in making good decisions that get you the right answer, are always important.
Poppy Crum: So, moths have just a few neurons. When that echolocating bat is flying at a certain point, when those neurons start firing, they will 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 it's easy for them to continue to track you.
Poppy Crum: So, they'll fly in a random pattern, and then when their neurons saturate, when it gets, those calls get close enough, the moth will drop to the ground with the idea that... 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 echolocating bat to locate you, right? So, that is just a deterministic behavior that will happen regardless.
Poppy Crum: But then, the interesting part is, their body is reflecting, meta-reflectors, effectively, so that the bat may put out its call, and it deflects the energy of the call away from its body. So, you're deflecting it away from critical areas.
Poppy Crum: And, you know, this is all happening, and the changes in the physical body are interesting, but then it's the behavioral differences that are really key. Right? It's how fast does that moth react if it has to question, or if it were cognitively responsive instead of being deterministic in its behavior, it wouldn't escape, right? But it gets away.
Andrew Huberman: Yeah, I've never thought about bats and moths. I never got the insect... I was about to say, I never got the insect bug. But, no pun intended. I never got the insect bug because 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 it's good for me to think about that, you know, one of my favorite people, although I never met him, was Oliver Sacks, the neurologist and writer, and he claimed to have spent a lot of time just sitting in chair and trying to imagine what life would be like as a bat, as a way to enhance his clinical abilities with patients suffering from different neurologic disorders.
Poppy Crum: Huh.
Andrew Huberman: So, when he would interact with somebody with Parkinson's, or with severe autism, or with locked-in syndrome, or any number of different deficits of the nervous system, he would... 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.
Andrew Huberman: And he certainly was very effective at storying out their experience in ways that brought about a lot of compassion and understanding. Like, he never presented a neural condition in a way that made you feel sorry for the person.
Poppy Crum: Mm-hmm.
Andrew Huberman: It was always the opposite.
Poppy Crum: Mm-hmm.
Andrew Huberman: And I should point out, I'm 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 never being able to take care of themselves. We're not talking about along the spectrum. We're talking about the far end of the spectrum of needing assisted living their entire lives and being sensory, from a sensory standpoint, extremely sensitive, couldn't go out in public, that kind of thing.
Poppy Crum: Yeah.
Andrew Huberman: We're not talking about people that are functioning with autism.
Andrew Huberman: So, apparently, thinking in the auditory domain was useful for him, so I should probably do that. So, I have one final question for you, which is... Well, it's really two questions.
Andrew Huberman: First question: Why did you sing to spiders? And second: What does that tell us about spiderwebs? Because I confess I know the answers to these questions, but I was absolutely blown away to learn what spiderwebs are actually for, and you singing to spiders reveals what they're for. So, why did you sing to spiders?
Poppy Crum: Two things, and you can watch me sing to a spider on a TED Talk I gave a few years ago.
Andrew Huberman: We'll put a link to it.
Poppy Crum: Years back. Okay. And so, just 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, you asked me what threads drive me.
Poppy Crum: It's always been... We do experience the world differently, and I believe that our success, everyone's success, and the success of our growth as humans is partly dependent on how we use technology to help improve and optimize each of us, with 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...
Poppy Crum: I know, Andy, you look at how different species respond to color and to information in their world, be it cuttlefish or such. I have jellyfish too, and I can see how their pulsing rates change with their photoreceptors when they... With different light colors.
Andrew Huberman: Oh, cool.
Poppy Crum: It's very obvious that some clearly make... When they're under stress versus when they're in a more calming state. And so, it's like understanding the stimuli in our world that shape us. Those changes are a huge part of being human, in my perspective.
Poppy Crum: In this case, this happens to be an orb spider, the one I sing to, and when I hit about 880 hertz, you will see the spider kind of dances. But, what this particular species, and not all spiders will do this, is predated it on by echolocating bats and birds, which makes sense that, then it tunes its web effectively. And orb weavers are all over California. They show up a lot around Thanksgiving, if you are... October, November, for anyone that's out here on the West Coast.
Poppy Crum: They're not bad spiders. They are not spiders you need to get rid of. They're totally happy spiders. There are some that maybe you should worry about more. Anyhow, they tune their webs to resonate like a violin, and when... Yeah, you'll see it. As I hit a certain frequency, it'll effectively tell me to go away. And it's a pretty interesting sort of deterministic response. Other insects do different things.
Poppy Crum: The one kind of 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 asking me when we would see spiders, if it was the kind we should sing to or the kind we shouldn't touch. And so, those were the two classes.
Andrew Huberman: So amazing. So, if I understand correctly, these orb spiders use their web more or less as an instrument to detect certain sound frequencies in their environment so that they can respond appropriately.
Poppy Crum: Yeah.
Poppy Crum: Yes.
Poppy Crum: Resonances, absolutely.
Poppy Crum: Yeah.
Andrew Huberman: Either by raising their legs to protect themselves or to attack or whatever it is.
Poppy Crum: Yeah.
Andrew Huberman: The spider web is a functional thing, not just for catching prey. It's a detection device also. And we know that because when prey are caught in a spider web, they wiggle, and then the spider goes over to it and wraps it and eats it.
Poppy Crum: Yeah.
Andrew Huberman: But the idea that it would be tuned to particular frequencies is really wild.
Poppy Crum: Yeah, not just by any vibration, right? You know, there's the idea that there's any vibration, I know I've got food somewhere, I should go to that food source.
Andrew Huberman: Mm-hmm.
Poppy Crum: But instead, it's something that if I experience a threat or something, I'm going to behave, and that is a more selective response that I've tuned it towards.
Andrew Huberman: 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 closer to dark, our immediate response is to either freeze or flee.
Poppy Crum: Mm-hmm.
Poppy Crum: Yeah.
Andrew Huberman: Like, that's just what we do. The looming response is one of the most fundamental responses.
Poppy Crum: Mm-hmm.
Andrew Huberman: But that's in the visual domain. So, the fact that there would be auditory cues that would bring about what you said, sort of deterministic responses, seems very real. I feel like that the wail of somebody in pain evokes a certain response.
Poppy Crum: Yes.
Andrew Huberman: Yesterday, there was a lot of noise outside my window at night, and there was a moment where I couldn't tell were these shouts of glee or shouts of fear.
Poppy Crum: Hmm.
Andrew Huberman: And I kind of tuned in, and then I heard this kind of high-pitched fluttering that came after the scream, and I realized these were kids playing in the alley outside of my house.
Poppy Crum: Oh.
Andrew Huberman: And I went and looked, and I was like, "Oh, yeah, they're definitely playing." But I knew even before I went and looked, based on kind of the flutter of sound that came after the shriek. It was like, "Ah!" And then it was, "Rrr." It was like, I can't reproduce the sound at that high frequency.
Poppy Crum: No, no. But that's, that's super...
Andrew Huberman: But, so the idea that this would be true all the time 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.
Poppy Crum: So, two interesting things to go with that. So, like, crickets, for example. Crickets have bimodal 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... So, you've got a peak at 6K, and you've got a peak at 40K. And a cricket... And this is the same neuron, a cricket hears 40K from a speaker, run over to it because that's got to be my mate or someone that... And they hear 40K, and they run away.
Poppy Crum: And it's a very predictive behavior. I spent a lot of... Well, I spent a good period of time working with a non-primate, non-human primate species, marmosets. Marmosets are very interesting when you get to a more sophisticated neural system. But marmosets are very social, you know, it's critical to their happiness. If you ever see a single marmoset in the zoo or something, that's a very unhappy animal.
Poppy Crum: But they're native to the Amazon, New World monkeys, native to Brazil and the Amazon, but they're arboreal. They live in trees. And they're very social. So, that kind of can be in conflict with each other because you're in dense foliage, but yet you need to communicate.
Poppy Crum: So, they've evolved very interesting systems to be able to achieve what they needed to, which, one, if you ever see marmosets, they're very stoic, unlike macaque monkeys that often have a lot of visual expression of how they're feeling. Marmosets always look about the same. But their vocalizations are almost like bird song, and they're very rich in the information that they're communicating.
Andrew Huberman: Mm-hmm.
Poppy Crum: They also have a pheromonal system. Like, you know, that you can have a dominant female in the colony who may not be... Because you have to have ways of... When one sense is compromised, the other senses sort of rise up to help assure that the success of what that species or system needs is going to thrive.
Poppy Crum: And in the case of marmosets, 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 pheromonal interactions that happen in the... Because those are things that can travel even when I can't see you.
Poppy Crum: One thing, when I was working with them, that I thought was... And I never... I like writing patents more than publishing papers. But these things are real, because I was studying pupillometry, is understanding the power of their saccades. I could know what they were hearing based on their eye movements. Right? So, if I play... Marmosets have... Some of their calls are really antiphonal. They're to see, "Hey, are you out there? Am I alone? Who else is around?"
Andrew Huberman: It's like texting for humans.
Poppy Crum: Yeah.
Andrew Huberman: Yeah.
Poppy Crum: Yeah, and sometimes it's light or sometimes it might be like, "Oh," you know, from, "Be careful. There's somebody around that we got to watch out for." Maybe there's a leopard on the ground or 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 antiphonal, "Hey, are you out there?" You see, 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?
Andrew Huberman: Mm-hmm.
Andrew Huberman: Mm-hmm.
Andrew Huberman: Yeah, they paired the right eye movement with the right sound.
Poppy Crum: Exactly. In the case of, look, there's something to be scared, you know, 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. My autonomic system and my cognitive system are reacting differently. And in the case of "You're in my face," it's going to be without even... So, without seeing you, if I hear another sort of aggressive sound, I'm going to react. I'm going to be... I'm not scanning anywhere, but my dilation is going to be fast, and I'm also going to be much more on top of things. But we do this as humans, too, right?
Andrew Huberman: Mm-hmm. Mm-hmm.
Poppy Crum: And it's like, you can walk into a business meeting, walk into a conference room, and it's these subtle cues that are... You know, we don't always suppress them. We show them whether we think we do or we don't. But, when you look at species like that, it's very much like, okay, there's a lot of sophistication in how their bodies are helping them be successful even in a world or an environment that has a lot of things that could maybe come after them.
Andrew Huberman: So interesting to think about that in terms of 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.
Andrew Huberman: 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'm glad we did because you have expertise in a lot of areas, and I love that you are constantly thinking about technology development. And I drew a little diagram for myself that I'll just describe for people, because if I understood correctly, one of the reasons you got into neuroscience and research at all is about this interface between inputs and us.
Andrew Huberman: 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 take on 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.
Andrew Huberman: 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 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 keep us posted. We'll provide links to you singing to spiders and all the rest. My mind's blown. Thank you so much.
Poppy Crum: Thank you, Andy. Great to be here.
Andrew Huberman: Thank you for joining me for today's discussion with Dr. Poppy Crum. 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 zero-cost 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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Andrew Huberman: For those of you who haven't heard, I have a new book coming out. It's my very first book. It's entitled "Protocols: An Operating Manual for the Human Body." This is a book that I've been working on for more than five years, and that's based on more than 30 years of research and experience, and it covers protocols for everything from sleep, to exercise, to stress control, protocols related to focus and motivation, and, of course, I provide the scientific substantiation for the protocols that are included.
Andrew Huberman: The book is now available by pre-sale at protocolsbook.com. There, you can find links to various vendors. You can pick the one that you like best. Again, the book is called "Protocols: An Operating Manual for the Human Body."
Andrew Huberman: And if you're not already following me on social media, I am hubermanlab on all social media platforms. So, that's Instagram, X, Threads, Facebook, and LinkedIn. And on all those platforms, I discuss science and science-related tools, some of which overlaps with the content of the Huberman Lab podcast, but much of which is distinct from the information on the Huberman Lab podcast. Again, it's hubermanlab on all social media platforms.
Andrew Huberman: And if you haven't already subscribed to our Neural Network Newsletter, the Neural Network Newsletter is a zero-cost monthly newsletter that includes podcast summaries as well as what we call protocols in the form of one to three-page PDFs that cover everything from how to optimize your sleep, how to optimize dopamine, and deliberate cold exposure. We have a foundational fitness protocol that covers cardiovascular training and resistance training. All of that is available completely zero-cost.
Andrew Huberman: You simply go to hubermanlab.com, go to the menu tab in the top right corner, scroll down to newsletter, and enter your email. And I should emphasize that we do not share your email with anybody. Thank you once again for joining me for today's discussion with Dr. Poppy Crum. And last but certainly not least, thank you for your interest in science.
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