How to Improve at Learning Using Neuroscience & AI | Dr. Terry Sejnowski

Before we begin, I'd like to emphasize that this podcast is separate from my teaching and research roles at Stanford. It is, however, part of my desire and effort to bring zero-cost-to-consumer information about science and science-related tools to the general public. In keeping with that theme, I'd like to thank the sponsors of today's podcast. Our first sponsor is BetterHelp. BetterHelp offers professional therapy with a licensed therapist carried out completely online. I've been doing weekly therapy for well over 30 years. Initially, I didn't have a choice. It was a condition of being allowed to stay in school.

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I started sleeping on a Dusk mattress about three and a half years ago, and it's been far and away the best sleep that I've ever had. If you'd like to try Helix, you can go to helixsleep.com slash Huberman. Take that two minute sleep quiz and Helix will match you to a mattress that is customized for your unique sleep needs. For the month of November, 2024, Helix is giving up to 25% off on all mattress orders and two free pillows. Again, that's helixsleep.com slash Huberman to get up to 25% off and two free pillows. And now for my discussion with Dr. Terry Sejnowski. Dr. Terry Sejnowski, welcome. Great to be here. We go way back and I'm a huge, huge fan of your work because you've worked on a great many different things in the field of neuroscience. You're considered by many a computational neuroscience. So you bring mathematical models to an understanding of the brain and neural networks. And we're also going to talk about AI today, and we're going to make it accessible for everybody, biologist or no, math background or no. To kick things off, I want to understand something. I understand a bit about the parts list of the brain. And most listeners of this podcast will understand a little bit of

the parts list of the brain, even if they've never heard an episode of this podcast before, because they understand there are cells, those cells are neurons, those neurons connect to one another in very specific ways that allow us to see, to hear, to think, et cetera. But I've come to the belief that even if we know the parts list, it doesn't really inform us how the brain works, right? This is the big question. How does the brain work? What is consciousness? All of this stuff. So where and how does an understanding of how neurons talk to one another start to give us a real understanding about like how the brain works? Like what is this piece of meat in our heads? Because it can't just be, okay, the hippocampus remembers stuff and the, you know, the visual cortex perceives stuff. When you sit back and you remove the math from the mental conversation, if that's possible for you. How do you think about, quote unquote, how the brain works? Like at a very basic level, what is this piece of meat in our heads really trying to accomplish from, let's just say the time when we first wake up in the morning and we're a little groggy till we make it to that first cup of coffee or water, or maybe even just to urinate first

thing in the morning? What is going on in there? What a great question. And, you know, I have, Pat Churchley and I wrote a book, Computational Brain, and in it, there's this levels diagram. And levels of investigation at different spatial scales from the molecular at the very bottom to synapses and neurons, circuits, neural circuits, how they're connected with each other, and then brain areas in the cortex and then the whole central nervous system span 10 orders of magnitude you know 10th to the 10th in spatial scale so you know where is consciousness in all of that so there are two approaches that neuroscientists have taken I shouldn't say neuroscientists, I should say that scientists have taken.

And the one you described, which is, you know, let's look at all the parts, that's the bottom-up approach. You know, take it apart and do a reductionist approach. And you make a lot of progress. You can figure out, you know, how things are connected and understand how development works, how neurons connect. But it's very difficult to really make progress because quickly you get lost in the forest. Now, the other approach, which has been successful, but at the end unsatisfying, is the top-down approach. And this is the approach that psychologists have taken looking at behavior and trying to understand the laws of behavior.

This is the behaviorists. But, you know, even people in AI were trying to do a top-down, to write programs that could replicate human behavior, intelligent behavior. And I have to say that both of those approaches, you know, bottom-up or top-down, have really not gotten to the core of answering any of those questions, the big questions. But there's a whole new approach now that is emerging in both neuroscience and AI at exactly the same time. At this moment in history, it's really quite remarkable. So there's an intermediate level between the implementation level at the bottom, how you implement some particular mechanism, and the actual behavior of the whole system is called the algorithmic level. It's in between. So algorithms are like recipes. They're like, when you bake a cake, you have to have ingredients and you have to say the order in which they're put together and how long. And if you get it wrong, it doesn't work. It's just a mess.

Now, it turns out that we're discovering algorithms. We've made a lot of progress with understanding the algorithms that are used in neural circuits. And this speaks to the computational level of how to understand, you know, the function of the neural circuit. But I'm going to give you one example of an algorithm, which is one we worked on back in the 1990s when Peter Dayan and Reid Montague were postdocs in the lab. And it had to do with the part of the brain below the cortex called the basal ganglia, which is responsible for learning sequences of actions in order to achieve some goal. For example, if you want to play tennis, you know, you have to be able to coordinate many muscles and a whole sequence of actions has to be made if you want to be able to serve accurately and you have to practice, practice, practice.

Well, what's going on there is that the basal ganglia basically is taking over from the cortex and producing actions that get better and better and better and better. And that's true not just of the muscles, but it's also true of thinking. If you want to become good in any area, if you want to become a good financier, if you want to become a good doctor or a neuroscientist, right, you have to be practicing, practicing, practicing in terms of understanding what's the details of the profession and what works, what doesn't work, and so forth. And it turns out that this basal ganglia interacts with the cortex, not just in the back, which is the action part, but also with the prefrontal cortex, which is the thinking part.

Can I ask you a question about this briefly? The basal ganglia, as I understand, are involved in the organization of two major types of behaviors. There's go, meaning to actually. perform a behavior, but the basal ganglia also instruct no-go. Don't engage in that behavior. And learning an expert golf swing or even a basic golf swing or tennis racket swing involves both of those things, go and no-go. Given what you just said, which is that the basal ganglia are also involved in generating thoughts of particular kinds, I wonder therefore if it's also involved in suppression of thoughts of particular kinds. I mean, you don't want your surgeon cutting into a particular region and just thinking about their motor behaviors, what to do and what not to do, they presumably need to think about what to think about, but also what to not think about. You don't want that surgeon thinking about how their kid was a brat that morning and they're frustrated because the two things interact. So is there go, no go in terms of action and learning? And is there go, no go in terms of thinking?

Well, I mentioned the prefrontal cortex and that part, the loop with the basal ganglia, That is one of the last to mature in, you know, early adulthood. And, you know, the problem is that for adolescents, it's not the no-go part for, you know, planning and actions isn't quite there yet. And so often it doesn't kick in to prevent you from doing things that are not in your best interest. So, yes, absolutely right. But one of the things, though, is that learning is involved. And this is really a problem that we cracked. first theoretically in the 90s and then experimentally later by recording from neurons and also brain imaging in humans. So it turns out we know the algorithm that is used in the brain for how to learn sequences of actions to achieve a goal. And it's the simplest possible algorithm you can imagine. It's simply to predict the next reward you're going to get. If I do an action, And will it give me something of value?

And you learn every time you try something, whether you got the amount of reward you expected or less, you use that to update the synapses, synaptic plasticity, so that the next time you'll have a better chance of getting a better reward. And you build up what's called a value function. So the cortex now, over your lifetime, is building up a lot of knowledge about things that are good for you, things that are bad for you. Like you go to a restaurant, you order something, how do you know what's good for you? You've had lots of meals in a lot of places. And now that is part of your value function. This is the same algorithm that was used by AlphaGo. This is the program that DeepMind built. This is an AI program that beat the world Go champion. And Go is the most complex game that humans have ever played on a regular basis.

Far more complex than chess, as I understand. Yeah, that's right. So go is to chess, which chess is to something like checkers. In other words, the level of difficulty is another way off above it because you have to think in terms of battles going on all over the place at the same time. And the order in which you put the pieces down are going to affect what's going to happen in the future. So this value function is super interesting. And I wonder whether, and I think you answered this, but I wonder whether this value function is implemented over long periods of time. So you talked about the value function in terms of learning a motor skill.

Let's say swinging a tennis racket to do a perfect tennis serve or even just a decent tennis serve. When somebody goes back to the court, let's say on the weekend, once a month over the course of years, are they able to tap into that same value function every time they go? back, even though there's been a lot of intervening time and learning? That's question number one. And then the other question is, do you think that this value function is also being played out in more complex scenarios, not just motor learning, such as, let's say, a domain of life that for many people involves some trial and error, it would be like human relationships.

We learn how to be friends with people. We learn how to be a good sibling. We learn how to be a romantic partner. We get some things right. We get some things wrong. So it's the same value function being implemented. We're paying attention to what was rewarding. But what I didn't hear you say also was what was punishing. So are we only paying attention to what is rewarding or we're also integrating punishment? We don't get an electric shock when we get the serve wrong, but we can be frustrated. What you identified is a very important feature, which is that rewards, by the way, you know, every time you do something, you're updating this value function every time. And it accumulates. And the answer to your first question, the answer is that it's always going to be there. It doesn't matter. It's a very permanent part of your experience and who you are. And interestingly, and the behaviorists knew this back in the 1950s, that you can get there two ways of trial and error.

You know, small rewards are good because you're constantly coming closer and closer to getting what you're seeking, better tennis player or being able to make a friend. But the negative punishment is much more effective. One trial learning. you don't need to have you know 100 trials to you know what you need you know when you're training a rat to do some tasks with small food rewards but if you if you just shock the rat boy that rat doesn't forget that yeah one really bad relationship will have you have you learning certain things forever and this is also ptsd post-traumatic stress disorder is is another good example of that that can screw you up for the rest of your life so so but the other thing and you pointed out something really important which is that a large part of the prefrontal cortex is devoted to social interactions and this is how humans you know when you come into the world you don't know what language you're going to be speaking you don't know what the cultural values are that you're that you're going to have to be able to become a member of this society and things that are expected of you, all of that has to become through experience, through building this value function. And this is something we discovered in the 20th century. And now

it's going into AI. It's called reinforcement learning in AI. It's a form of procedural learning, as opposed to the cognitive level, where you think and you do things. Cognitive

here. If I understand correctly, there's an action function that's learned from the knowledge and the experience. Exactly. And then where is that action function stored? Is it in one location in the brain or is it kind of an emergent property of multiple brain areas? So that you're right at the cusp here of where we are in neuroscience right now. We don't know the answer to that question in the past it had been thought that uh you know the the cortex had uh were like uh countries on uh that each of which each part of the cortex was dedicated to one function right uh you know there's and and interestingly you record for the neurons and it certainly looks that way right in other words there's a visual cortex in the back and there's a whole series of areas, and then there's the auditory cortex here in the middle, and then the prefrontal cortex for

social interaction. And so it looked really clear-cut that it's modular. And now what we're

Amazing. Obviously, language is one of them, but there are other things in sleep that we've discovered having to do with traveling ways. There are circular traveling ways that go on during sleep, which is astonishing. Nobody ever really saw that before. If you were to ascribe one or two major functions to these traveling waves, what do you think they are accomplishing for us in sleep? And by the way, are they associated with deep sleep, slow wave sleep, or with rapid eye movement sleep, or both?

This is non-REM sleep. This is a jargon. This is during intermediate. Transition states. Transition state. Okay. Our audience will probably keep up. They've heard a lot about slow wave sleep from me and Matt Walker and from rapid eye movements. This is light slow wave sleep, yeah. And so what do these traveling waves accomplish for us? Okay. So in the case of the, they're called sleep spindles. The waves last for about a second or two and they travel, like I say, in a circle around the cortex. and it's known that these spindles are important for consolidating experiences you've had during the day into your long-term memory storage so so it's a very important function and if if you take out see it's the hippocampus that is is is replaying the experiences it's a part of the brain is very important for long-term memory if you don't have a hippocampus you can't learn new things. That is to say, you can't remember what you did yesterday, or for that matter, even an hour earlier. But the hippocampus plays back your experiences, causes the sleep spindles now to need that into the cortex. And it's important you do that right, because you don't want to overwrite the existing knowledge you have. You just want to basically incorporate

the new experience into your existing knowledge base in an efficient way. way that doesn't interfere with what you already know. So that's an example of a very important function that these traveling ways have. I'd like to take a quick break and acknowledge our sponsor, AG1. AG1 is a vitamin mineral probiotic drink that includes prebiotics and adaptogens. I've been drinking AG1 since 2012, and I started doing it at a time when my budget was really limited. In fact, I only had enough money to purchase one supplement, and I'm so glad that I made that supplement AG1. The reason for that is even though I strive to eat whole foods and unprocessed foods, it's very difficult to get enough vitamins and minerals, micronutrients and adaptogens from diet alone in order to make sure that I'm at my best, meaning have enough energy for all the activities I participate in from morning until night, sleeping well at night and keeping my immune system strong. When I take AG1 daily, I find that all aspects of my health, my physical health, my mental health, my performance, recovery from exercise, all of those improve. And I know that because I've had lapses when I didn't take my AG1 and I certainly felt

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That's a true, I think that this is something that is true, not just of drugs for the brain, but steroids for the body. Sure. Yeah, I mean, steroids, even low-dose testosterone therapy, which is very popular nowadays. We'll give people more vigor, et cetera. But it is introducing a sort of second puberty. And puberty is perhaps the most rapid phase of aging in the entire lifespan. Same thing with people take growth hormone would be probably a better example because certainly those therapies can be beneficial to people, but growth hormone gives people more vigor, but it accelerates aging. Look at the quality of skin that people have when they take growth hormone. It looks more aged. They physically change. And I'm not for or against these things.

it's highly individual. But I completely agree with you. I would also venture that with the growing interest in so-called nootropics and people taking things like modafinil, not just for narcolepsy, daytime sleepiness, but also to enhance cognitive function. Okay. Maybe they can get away with doing that every once in a while for a deadline task or something. But my experience is that people who obsess over the use of pharmacology to achieve certain brain states pay in some other way, whether or not stimulants or sedatives or sleep drugs, and that behaviors will always prevail. Behaviors will always prevail as tools.

Yeah. And one of the things about the way the body evolved is that it really has to balance a lot of things. And so with drugs, you're basically unbalancing it somehow. And the consequence is, as you point out, is that in order to make one part better, one part of your body, you sacrifice something else somewhere else. As long as we're talking about brain states and connectivity across areas, I want to ask a particular question. Then I want to return to this issue about how best to learn, especially in kids, but also in adulthood. I've become very interested in and spent a lot of time with the literature and some guests on the topic of psychedelics. Let's leave the discussion about LSD aside, because do you know why there aren't many studies of LSD? This is kind of a fun one. No one is expected to know the answer.

Well, it's against the law, I think. Oh, but there's... So is psilocybin or MDMA, and there are lots of studies going on about this. Yeah, it's changed. But when I was growing up, as you know, it was against the law. Right. So what I learned is that there are far fewer clinical trials exploring the use of LSD as a therapeutic, because with the exception of Switzerland, none of the researchers are willing to stay in the laboratory as long as it takes for the subject to get through an LSD journey, whereas psilocybin tends to be a shorter experience. Okay. Let's talk about psilocybin for a moment. My read of the data on psilocybin is that it's still open to question, but that some of the clinical trials show pretty significant recovery from major depression. It's pretty impressive. But if we just set that aside and say, okay, more needs to be worked out for safety, what is very clear from the brain imaging studies, the sort of before and after resting state task related, et cetera, is that you get more resting state, global connectivity, more areas talking to more areas than was the case prior to the use of the psychedelic. And given the similarity of the psychedelic journey and here specifically talking about psilocybin to things like rapid

eye movement, sleep, and things of that sort, I have a very simple question. Do you think that there's any real benefit to increasing brain-wide connectivity. To me, it seems a little bit haphazard, and yet the clinical data are promising, if nothing else, promising. And so is what we're seeking in life as we acquire new knowledge, as we learn tennis, or golf or, you know, take up singing or what have you, as we go from childhood into the late stages of our life, that whole transition is what we're doing, increasing connectivity and communication between different brain areas. Is that what the human experience is really about?

Or is it that we're getting more modular? We're getting more segregated in terms of this area, talking to this area in this particular way. Feel free to explore this in any way that feels meaningful or to say pass if it's not a good question no it's a great question i mean you have all these great questions and we don't have complete answers yet but uh specifically with regard to connectivity um if you look at what happens in an infant's brain during the first two years there's a tremendous amount of new synapses being formed this is your area by the way you know about this than i do but then you prune them right there's the second phase is that You have overabundant synapses, and now what you want to do is to prune them.

Why would you want to do that? Well, you know, synapses are expensive. It takes a lot of energy to activate all of the neurons and the synapses especially because there's the turnover of the neurotransmitter. and so what you want to do is to reduce the amount of energy and only use those synapses that have been proven to be the most important right now unfortunately as you get older you had the pruning slows down but doesn't go away so the cortex thins and and so forth so i think it goes in the opposite direction i think that as you get older you you you're losing connectivity. But interestingly, you retain the old memories. The old memories are really rock solid because they were put in when you were young.

You had the foundation. The foundation upon which everything else is built. But it's not totally one way in the sense that even as an adult, as you know, you can learn new things, maybe not as quickly. By the way, this is one of the things that surprised me. So Barbara and I have looked at the people who really benefited the most. It turns out that the peak of the demographic is 25 to 35. Barbara? Oakley, Oakley. Yeah, she's really the mastermind. She's a fabulous educator and background in engineering. But what's going on? So it turns out we aimed our MOOC at kids in high school and college because that's their business.

They go every day and they go into work. They have to learn, right? That's their business. But in fact, very few of the students who are actually, you know, they weren't taking the course. Why should they? They spend all day in the class, right? Why do they want to take another class? So this is the learning to learn class? Learning how to learn. Okay. So you did this with Barbara. So we did this. I did with Barbara. And now 25 to 35, we have this huge peak, huge. So what's going on? Here's what's going on. It's very interesting. So you're 25. You've gone to college. Half the people, by the way, who take the course went to college, right? So it's not like filling in for college. This is like topping it off. But you're in the workforce. You have to learn new skill. Maybe you have mortgage. Maybe you have children, right? You can't afford to go off and take a course or get another degree.

So you take a MOOC and you discover, you know, I'm not quite as agile as I used to be in terms of learning, but it turns out with our course, you can boost your learning. And so that even though you're... you're not as, your brain isn't learning as quickly, you can do it more efficiently. This is amazing. I want to take this course. I will take this course. What sort of time commitment is the course? You already pointed out that it's zero cost, which is amazing. Yeah. Okay. So it's bite-sized videos lasting about 10 minutes each. And there's about 50 or 60 over a course of one month. And are you tested? Are you self-test?

Yeah, there are tests. There are quizzes. There are tests at the end. And there are forums where you can go and talk to other students. You have questions. We have TAs. And anyone can do this. Anyone in the world. In fact, we have people in India, housewives, who say, thank you, thank you, thank you, because I could have never learned about how to be a better learner. And I wish I had known this when I was going to school. Why do more people not know about this learning to learn course? Although, as people know, if I get really excited about it or about anything, I'm never going to shut up about it. But I'm going to take the course first because I want to understand the guts of it.

You'll enjoy it. We have like 98% approval. It's just phenomenal. It's sticky. Is it math, vocabulary? No math. We're not teaching anything specific. We're not trying to give you knowledge. We're trying to tell you how to acquire knowledge and how to do that, how to deal with exam anxiety, for example, or how to... We all procrastinate, right? We put things off. Nah, no, I'm kidding. We all procrastinate. How to avoid that. We teach you how to avoid that. Fantastic. Okay. I'm going to skip back a little bit now with the intention of double-clicking on this learning to learn thing. You pointed out that in particular in California, but elsewhere as well, there isn't as much procedural practice-based learning anymore.

I'm going to play devil's advocate here. And I'm going to point out that this is not what I actually believe. But when I was growing up, you had to do your times tables and your division and then your fractions and your exponents. And they build on one another. And then at some point, you know, you take courses where you might need it like a graphing calculator to some people that can be like, what, what, what is this? But the point being that there were a number of things that you had to learn to implement functions and you learn, you learn by doing, you learn by doing. Likewise, in, in physics class, we, you know, we were attaching things to strings and for macro mechanics and learning that stuff. Okay. And learning from the chalkboard lectures.

I can see the value of both, certainly. And you explained that the brain needs both to really understand knowledge and how to implement and back and forth. But nowadays, you'll hear the argument, well, why should somebody learn how to read a paper map unless it's the only thing available because you have Google Maps? Or if they want to do a calculation, they just put it into the top bar function on the internet and boom, out comes the answer. So there is a world where certain skills are no longer required, and one could argue that the brain space and activity and time and energy in particular could be devoted to learning new forms of knowledge that are going to be more practical in the school and workforce going forward.

So how do we reconcile these things? I mean, I'm of the belief that the brain is doing math and you and I agree. It's electrical signals and chemical signals and it's doing math and it's running algorithms. I think you convinced us of that, certainly. But how are we to discern what we need to learn versus what we don't need to learn in terms of building a brain that's capable of learning the maximum number of things or even enough things so that we can go into this very uncertain future? because as far as you know, and I know. there's no, neither of us have a crystal ball. So what is essential to learn? And for those of us that didn't learn certain things in our formal education, what should we learn how to learn?

Well, this is generational. Okay. So technologies provide us with tools. You mentioned the calculator, right? Well, a calculator didn't eliminate, you know, the education you need to get in math, but it made certain things easier. It made it possible for you to do more things and more accurately. However, interestingly, students in my class often come up with answers that are off by, you know, eight orders of magnitude, and that's a huge amount, right? It's clear that they didn't key in the calculator properly, but they didn't recognize that it was completely way off the beam because they didn't have a good feeling for the numbers.

They don't have a good sense of, you know, exactly how big it should have been, you know, order of magnitude, basic, you know, understanding. So it's kind of a, there's a, the benefit is that you can do things faster, better, but then you also lose some of your intuition if you don't have the procedural system in place. I'm thinking about a kid that wants to be a musician who uses AI to write a song about a bad breakup that then is kind of recovered when they find new love. And I'm guessing that you could do this today and get a pretty good song out of AI, but would you call that kid a songwriter or a musician?

On the face of it, yeah, the AI is helping. And then you'd say, well, that's not the same as sitting down with a guitar and trying out different chords and feeling the intonation in their voice. But I'm guessing that for people that were on the electric guitar, they were criticizing people on the acoustic guitar. So we have this generational thing where we look back and say, that's not the real thing. You need to get the – so what are the key fundamentals is really a critical question. Okay, so I'm going to come back to that because the way you put it at the beginning had to do with how your brain is allocating resources, okay?

So when you're younger, you can take in things. Your brain is more malleable. For example, how good are you on social media? Well, I do all my own Instagram and Twitter. And those accounts have grown in proportion to the amount of time I've been doing it. So, yeah, I would say pretty good. I mean, I'm not the biggest account on social media. But for a science health account, we're doing okay, thanks to the audience. Well, this speaks well for the fact that you've managed to break, you know, to go beyond the generation gap. I can type with my thumbs, Terry. Okay, there you go. That's a manual skill that you learned.

That's a new phenomenon in human evolution. I couldn't believe it. I saw people doing that. Now I can do it too. But the thing is that if you learn how to do that early in life, you're much more good at it. You can move your thumbs much more quickly. Also, you can have many more tweets going. What are they called now? They're not called tweets. It's on X. I think they still call them tweets because it's hard to verb the letter X. Elon didn't think of that one. I like X because it's cool. It's kind of punk and it's got a black kind of format and it fits with kind of the, you know, the engineer, like black X, you know, and that's kind of thing.

But, yeah, we'll still call them tweets. Okay, we'll call them tweets. Okay, that's good. But, you know, I walk across campus and I see everybody, like half the people are tweeting or, you know, they're doing something with their... phone. I mean, it's unbelievable. And you have beautiful sunsets at the Salk Institute. We'll put a link to one of them. I mean, it is truly spectacular, awe-inspiring to see a sunset at the Salk Institute. Every day is different. And everyone's on their phones these days? Sad. And they're looking down at their phone and they're walking along, even people who are skateboarding. Unbelievable. I mean, it's amazing what the human being can do when they get into something. But what happens is the younger generation picks up whatever technology it is and the brain gets really good at it. And you can pick it up later, but you're not quite as agile, not quite as maybe obsessive. It fatigues me. I will point this out, that doing anything on my phone feels fatiguing in a way that reading a paper book or even just writing on a laptop or a desktop computer is fundamentally different. I can do that for many hours. If I'm on social media for more than a few minutes, I can literally feel the energy draining

out of my body. Interesting. I would, I could do sprints or deadlifts for hours and not feel the kind of fatigue that I feel from doing social media. So, you know, this is fascinating. I'd like to know what's going on in your brain. Why is it? And also I'd like to know from younger people, whether they have the same, I think not. I think my guess is that they don't feel fatigue because they got into this early enough. And this is actually a very, very, I think that it has a lot to do with the foundation you put into your brain. In other words, things that you learn when you're really young are foundational and they make things easier, some things easier.

Yeah, I spent a lot of time in my room as a kid either playing with Legos or action figures or building fish tanks or reading about fish. I tended to read about things and then do a lot of procedural-based activities. I would read skateboard magazines and skateboard. I was never one to really just watch a sport and not play it. So bridging across these things. So social media to me feels like an energy sink. But of course, I love the opportunity to be able to teach to people and learn from people at such scale. But at an energetic level, I feel like I don't have a foundation for it. It's like I'm trying to like jerry-rig my cognition into doing something that it wasn't designed to do. Well, there you go. And it's because you don't have the foundation. You didn't do it when you were younger. And now you have to sort of use the cognitive powers to do a lot of what was being done now in a younger person procedurally. I'd like to take a quick break and thank one of our sponsors, Element. Element is an electrolyte drink that has everything you need and nothing you don't. That means the electrolytes, sodium, magnesium, and potassium in the correct ratios, but no sugar. We should all know that proper hydration is critical for

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I'm going to tell you something which is going to help all of your listeners. My book, ChatGDP and the Future of AI, I went through and I looked at other people's experiences with ChatGDP. I just wanted to know what people were thinking. And I came across, it was an article, I think it was the New York Times, of a technical writer who decided she would spend one month using it to help her write things, her articles. And she said that when she started out, you know, at the end of the day, she was drained, completely drained. And it was like, you know, working on a machine, you know, like a tractor or something, you know, struggling, struggling, struggling to get it to work.

And then she started, said, well, wait a second. You know, what if I treat it like a human being? What if I'm polite instead of, you know, being curt? So she said, suddenly, I started getting better answers. By being polite and, you know, back and forth the way you were with a human, you know. So saying, could you please give me information about so-and-so? Yeah, please. I'm really having trouble. And, oh, you know, that answer you gave me was fabulous. It's exactly what I was looking for. And, you know, now I need you to go on to the next part and help me with that too. In other words, the way you talk to a human, right, an assistant.

Or is it that she was talking to the AI, to chat GPT, it sounds like in this case, in the way that her brain was familiar with asking questions to a human? In other words, so is the AI learning her and therefore giving her the sorts of answers that are more facile for her to integrate with? I think it's both. First of all, the chat GDP is mirroring the way you treat it. It will mirror that back. You treat it like a machine, it will treat you like a machine, okay? Because that's what it's good at. But here's the surprise. surprise is she said once i once i started treating it like a human at the end of the day i wasn't fatigued anymore why well it turns out that all your life you end up you interact with humans in a certain way and your brain is wired to do that and it doesn't take any effort and so by treating the chat gdp as if it were a human you're taking advantage of all the brain circuits in your brain. This is incredible. And I'll tell you why, because I think many people, not just me, but many people really enjoy social media, learn from it. I mean, yesterday I learned a few things that I thought were just fascinating about how we perceive our own identity, according to whether or not we're filtering it through the responses of others or whether or not we

take a couple of minutes and really just sit and think about how we actually feel about ourselves. Very interesting ideas about locus of... of self-perception and things like that. I also looked at a really cool video of a baby raccoon popping bubbles while standing on its hind limbs. And that was really cool. And social media could provide me both those things within a series of minutes. And I was thinking to myself, this is crazy, right? The raccoon is kind of trivial, but it delighted me. And that's not trivial. But here's the question. Could it be that one of the detrimental aspects of social media is that if we're complimenting one another or if we are giving hearts or we're giving thumbs down or we're in an argument with somebody or we're doing a clap back or they're clapping back on us or dunking as it's called on X, that it isn't necessarily the way that we learned to argue.

It's not necessarily the way that we learn to engage in healthy dispute. And so as a consequence, it feels like, and this is my experience, that certain online interactions feel really good and others feel like they're kind of great on me. Because there's almost like an action step that isn't allowed. You can't fully explain yourself or understand the other person. And I am somebody who believes in the power of real face-to-face dialogue, or at least on the phone dialogue. And I feel the same way about text messaging. I hate text messaging. When text messaging first came out, I remember thinking, I was not a kid that passed notes in class. This feels like passing notes in class. In fact, this whole text messaging thing is beneath me. That's how I felt. And over the years, of course, I became a text messager. And it's very useful for certain things, be there in five minutes, running a few minutes late. In my case, that's a common one. But I think this notion of what grates on us and as it relates to whether or not it matches our childhood developed template of how our brain works is really key because it touches on something that I definitely want to talk about today that I know you've worked on quite a bit, which is this

concept of energy. What we're talking about here is energy, not woo biology, woo science, wellness, energy. We're talking about, we only have a finite amount of energy. And years ago, the great Ben Barris sadly passed away. Our former colleague and my postdoc advisor came to me one day in the hallway and he stopped me and he said, he called me Andy, like you do. And he said, Andy, how can we get so, so a rundown of energy as we get older? Why are we, why am I more tired today than I was 10 years ago? I was like, I don't know, how are you sleeping? He's like, I'm sleeping fine. Ben never slept much in the first place, but he had a ton of energy.

And I thought to myself, I don't know. Like, what is this energy thing that we're talking about? I want to make sure that we close the hatch on, on this notion of a template neural system that then you either find experiences invigorating or depleting. I want to make sure we close the hatch on that, but I want to make sure that we relate it at some point to this idea of energy. And why is it that with each passing year of our life, we seem to have less of it? You know, you ask these great questions and I wish that I had great answers. Well, so far you really do have great answers. They're certainly novel to me in the sense that I've not heard answers of this sort. So there's a tremendous amount of learning for me today and i know for the audience so okay so but let's say you're somebody is 20 years old versus 50 years old right versus what should they do i mean we need to integrate with the modern world we also need to relate across generations oh yeah no this is true this is retiring as much they're living longer birth rates are down but we have to get all get along as they say so you know it is interesting and i think it's true that uh we all as we get older uh have have less of the you know

the vigor, vigor, if I could use a somewhat different word from energy. We'll come back to that. But I think there are some who manage to keep an active life. Here's something that, again, in our MOOC, we really emphasize. Could you explain a MOOC? I think most people won't know what a MOOC is, just for their sake. Okay, this is, they've been around for about, actually started at Stanford, Andrew Ng and Daphna Kohler. So they have a company called Coursera. And what happens is that you get professors and, in fact, anybody who has knowledge or professional expertise to give lectures that are available to anybody in the world who have access to the internet.

And, you know, it could, there's like probably tens of thousands now, any specialty, history, science, music, you know, you name it. There's somebody who's done, you know, who's an expert on that and wants to tell you because they're excited about what they're doing. Okay. So, you know, what we wanted to do was to help people with learning. And so part of the problem is that it gets more difficult. It takes more effort as you get older. It depletes your vigor more, if we're going to stay with this language of energy and vigor. Yeah, that's right. So let's actually use the word energy. As you know, in the cell, there is a physical power plant called the mitochondrion, which is supplying us with ATP, which is the coin of the realm for the cell to be able to operate all of its machinery, right?

And so one of the things that happens when you get older is that your mitochondrial run down. You have fewer of them, and they're less efficient. That's right. They're less efficient. And actually, drugs can do that to you, too. They can harm mitochondria. Or recreational drugs. No, the drugs you take for illness. I'm not sure about recreational drugs, but I know it's a case that there are a lot of drugs that people take because they have to. But the other thing, and this is something, that's the bad news. Here's the good news. The good news is that you can replenish your energy by exercise. Exercise is the best drug you could ever take.

It's the cheapest drug you could ever take. That can help every organ in your body. It helps, obviously, your heart. It helps your brain. it rejuvenates your brain it helps your immune system every single organ system in the body benefits from a regular exercise i run on the beach every day at the salk institute i can i and i also at the it's on a mesa 340 foot above the so i go down every day and then i i climb up the cliff yeah those steps down to black's beach are are they're a good workout they are they are And so this is something that has kept me active, and I do hiking. I went hiking in the Alps last fall.

So this is in September. So this is, I think, something that people really ought to realize is that, you know, it's like putting away, you know, reserves of energy for, you know, when you get older. The more you put away, the better off you are. Here's something else. Okay, now this is jumping now to Alzheimer's. So a study that was done in China many, many years ago, when I first came to La Jolla, San Diego, I heard this from the head of the Alzheimer's program. He had done a study in China on onset. And they went and they had three populations. They had peasants who had almost no education. Then they had another group that had high school education.

and then people who were, you know, advanced education. So it turns out that the onset of Alzheimer's was earlier for the people who had no education. And it was the latest for the people who had the most education. Now, this is interesting, isn't it? Because it's, and presumably the genes aren't that different, right? I mean, they're all Chinese. So one possibility, and obviously we don't really know why, but one possibility is that the more you exercise your brain with education, the more reserve you have later in life. I believe in the notion, and I don't have a better word for it, maybe you do, or a phrase for it, is of kind of a cognitive velocity.

You know, I sometimes will play with this. So I'll read slowly or I'll see where my default pace of reading is at a given time of day. And then I'll intentionally try and read a little bit faster while also trying to retain the knowledge I'm reading. So I'm not just reading the words. I'm trying to absorb the information. And you can feel the energetic demand of that. And then I'll play with it. I'll kind of back off a little bit. And then I'll go forward. And I try and find the sweet spot where I'm not reading at the pace that is reflexive, but just a little bit quicker while also trying to retain the information.

And I learned this when I had a lot of catching up to do at one phase of my educational career. Fortunately, it was pretty early and I was able to catch up on most things. You know, occasionally things slip through and I have to go back and learn how to learn, you know. And if I get anything wrong on the internet, they sure as heck pointed out. And then we go back and learn. And guess what? I'd never forget that because punishment, social punishment is a great signal. Yeah. So thank you all. for keeping me learning. But I picked that up from my experience of trying to get good at things like skateboarding or soccer when I was younger. There's a certain thing that happens when skateboarding, that was my sport growing up, where it's actually easier to learn something going faster. Most kids try and learn how to ollie and kickflip standing in the living room on the carpet. That's the worst way to learn how to do it. It's all easier going a bit faster than you're comfortable. It's also the case that if you're not paying attention, you can get hurt.

It's also the case that if you pay too much cognitive attention, you can't perform the motor movements. So there's this sweet spot that eventually I was able to translate into an understanding of when I sit down to read a paper or a news article, or even listen to a podcast, there's a pace of the person's voice. And then I'll adjust the rate of the audio where I have to engage cognitively and I know I'm in a mode of retaining the information and learning. Whereas if I just go with my reflexive pace, it's rare that I'm in that perfect zone. So I point this out because perhaps it will be useful to people. I don't know if it's incorporated into your learning how to learn course, but I do think that there is something which I call kind of cognitive velocity, which is ideal for learning versus kind of leisurely scrolling. And this is why i think that social media is detrimental i think that we train our brain basically to be slow passive and multi-context cycling through and unless something is very high salience it kind of makes us kind of fat and lazy forgive the language but i'm going to be blunt here fat and lazy cognitively unless we make it a point to also engage learning right and my guess is

it's tapping into this mitochondrial system uh very likely uh that's one part of it uh by the way uh you know the way that you've adjusted the speed is very interesting because it turns out that uh stress you know everybody thinks oh stress is bad but no it turns out stress that is transient you know that is only for a limited amount of time that you control is good for you it's good for your brain it's good for your body i run intervals on the beach just the way that you do cognitive intervals when you're reading. In other words, I run like hell for about 10 seconds, and then I go to a jog and I run like hell for another 10 seconds.

And it's pushing your body into that extra gear that helps the... Muscles, the muscles need to know that this is what they've got to put out. And that's where you gain muscle mass, not from just doing the same running pace every day. Well, your intellectual and physical vigor is undeniable. I've known you a long time. You've always had a slight forward center of mass in your intellect and even the speed at which you walk, Terry, dare I say. Okay. For a Californian, you're a quick walker. Okay. Yeah. so uh that's a compliment by the way um east coasters know what i'm talking about and californians would be like you know um why not slow down the reason to not slow down too much for too long is that these mitochondrial systems the energy of the brain and body as you point out are very linked and i do think that below a certain threshold it makes it very hard to come back just like below a certain threshold it's hard to exercise um without getting very depleted or even injured, that we need to maintain this. So perhaps now would be a good time to close the hatch on this issue of how to teach young people. Everyone should take this learning to learn course as a free resource. Amazing. As it relates to AI, do you think that young people and older people

now, I'm 49, so I'll put myself in the older bracket, should be learning how to use AI? They are already learning how to use AI. And again, it's just like new technology comes along, who picks up first? It's the younger people. And it's astonishing. They're using it a lot more than I am. I use it almost every day, but I know a lot of students who basically... And by the way, It's like any other tool. It's a tool that you need to know how to use it. Where do you suggest people start? So I have started using Claude AI. Okay. This was suggested to me by somebody expert in AI as an alternative to ChatGPT.

I don't have anything against ChatGPT, but I'll tell you, I really like the aesthetic of Claude AI. It's a bit of a softer beige aesthetic. It feels kind of Apple-like. I like the Apple brand. And it gives me answers. Maybe it's the font. Maybe it's the feel. Maybe this goes back to the example used earlier where I like Claude AI. And I'm a big fan of it. And they don't pay me to say this. I have never met them. I have no relationship to them. Except that it gives me answers in a bullet-pointed format that feels very aesthetically easy to transfer that information into my brain or onto a page.

So I like Claude AI. Use ChatGPT. How should people start to explore AI for sake of getting smarter, learning knowledge, just for the sake of knowledge, having fun with it? What's the best way to do that? Well, I think exactly what you did, which is there's now dozens and dozens of different chatbots out there. And different people will feel comfortable with one or the other. Chat GDP is the first, so that's why it's kind of taken over a lot of the cognitive space, right? It's become like Kleenex, that word. That was why I used it as the first word in my new book, because it's iconic. But some of them, I have to say that, for example, there are some that are really much better at math than others.

Such as? Google Gemini recently did some fine-tuning with what's called chain of reasoning. in other words when you reason you go through a sequence of steps and when you solve a math problem you go through a sequence of a partial of steps of doing uh but you know fitting first finding out what's missing and then adding that and it went from 20 correct to 80. right, on those problems. And as people hear that, they probably think, well, that means 20% wrong still. But could you imagine any human or panel of humans behind a wall where if you asked it a question and then another question and another question, that it would give you back better than 80% accurate information in a matter of seconds?

So I think we are being perhaps a little bit unfair to compare these large language models to the best humans rather than the average human, right? As you said, most people couldn't pass the LSAT, the law test to get into law school, or MCAT, the test to get into medical school. And JetGPT has. Is there a world now where we take the existing AI, LLMs, these computers basically that can learn like a collection of human brains and send that somehow into the future, right?

Yeah. I mean, the reason I'm excited about AI and increasingly so across the course of this conversation is because there are very few opportunities to forge information at such large scale and around the circadian clock.

I mean, if there's one thing that we are truly a slave to as humans is the circadian biology. Right. you got to sleep sooner or later. And even if you don't, your cognition really waxes and wanes across the circadian cycle. And if you don't, you're going to die early. We know this. Computers can work, work, work. Sure. You got to power them. There's the cooling thing. There are a bunch of things related to that, but that's, that's tractable. So computers can work, work, work. And the idea that they can provide a portal into the future and that they can just bring it back so we can take a look-see. I'm not saying we have to implement their advice, but to be able to send a panel of diverse, computationally diverse, experientially diverse AI experts into the future and bring us back a panel of potential routes to take, to me is so exciting. Maybe a good example would be treatments for schizophrenia. This is an area that I want to make certain that we talk about. I grew up learning as a neuroscience student that schizophrenia was somehow a disruption of the dopamine system because if you give neuroleptic drugs that block dopamine receptors, that you get some improvement in the motor symptoms and some of the hallucinations, et cetera. You now also have people who say,

no that's not really the basis of schizophrenia i'd love your thoughts and you have incredible work from people like chris palmer at harvard and we even have a department at stanford now focusing we even have people at stanford now focusing on what chris really founded as a field which is metabolic psychiatry the idea that who could imagine i'm being sarcastic here what you eat impacts your mitochondria how you exercise impacts your mitochondria mitochondria impacts brain function and woe and behold metabolic health of the brain and body impacts schizophrenia symptoms. And he's looked at ways that people can use ketogenic diet, maybe not to cure, but to treat. And in some cases, maybe even cure schizophrenia. So here we are at this place where we still don't have a quote unquote cure for schizophrenia, but you could send LLMs into the future and start to forage the most likely, all of the data in those fields, probably could do that in an hour, plus come up with a bunch of hypothesized different positive and negative result clinical trials that don't even exist yet. 10,000 subjects in Scandinavia who go on ketogenic diet, who have a certain level of susceptibility to schizophrenia based on what

we know from twin studies, things that never, ever, ever would be possible to do in an afternoon, maybe even in a year there's isn't funding there isn't and boom get the answers back and let them present us those answers and then you say well it's it's artificial but so are human brains coming up with these experiments so to me i'm starting to realize that it's not that we have to implement everything that ai tells us or offers us it just but it sure as hell gives us a great window into what might be happening or is likely to happen specifically for schizophrenia i'm pretty sure that if we had these large language models 20 years ago, we would have known back then that ketamine would have been a really good drug to try to help these people.

the better we are going to be at extrapolating and coming up with some solutions, at least to prevent it from getting worse. By the way, I'm pretty sure that the large language models could have figured this out long ago. So in an attempt to understand how we might be able to leverage these large language models now, how would we have used these large language models long ago? Let's say you had 2024 AI technology in 1998, the year that I started graduate school. At that time, it was like the dopamine hypothesis is schizophrenia was in every textbook. There was a little bit about glutamate perhaps, but it was all about dopamine.

So how would the large language models have discovered this? Ketamine was known as a drug. Ketamine, by the way, is very similar to PCP, fencyclidine, which also binds the NMDA receptor. Which is also a part of the drug. Which is also, yeah, not one I recommend, nor ketamine. Frankly, I don't recommend any recreational drugs, but I'm not a recreational drug guy. But what would those large language models do if they – so you've got 2024 technology placed into 1998. 1998 they're foraging for existing knowledge but then are they able to make predictions like hey this stuff is going to turn out to be wrong or hey this stuff okay you know you know this is all very very speculative uh and really uh we can begin actually to see this happening now uh so I have a colleague at the Salk Institute, Rusty Gage, very distinguished neuroscientist.

And he discovered that there are new neurons being born in the hippocampus, right, which is something in adults, which is something that in a textbook says that doesn't happen, right? That was around 1998 that Rusty did that. Yeah, that's right. And I actually have a paper with him where we tested LTP, long term potentiation, actually of the effects of exercise on neurogenesis. Exercise increases neurogenesis. It increases the cells, it increases neurogenesis and also the cells that become part of the circuit. More cells become integrated. And this is true in humans as well, right? Yeah, and there was some cancer drug that was given that they showed that there are new cells that they were able to later in post-mortem to actually see that they were born in the adult okay so here we are okay in 1998 and the question is uh can you can you jump can you jump into the future okay so rusty we were at a you know had to happen to talk about this issue about you know he's using these large language models now

you know what we do and what ai does uh and it's it's going to be a partnership it's not going to be adversarial it's going to be a partnership would you say that's the case for things like understanding or discovering um treatments for neurologic illness um for um avoiding large-scale catastrophes? Can it predict macro movements? Let me give an example.

Here in Los Angeles, there's occasionally an accident on the freeway. You have a lot of cameras over freeways nowadays. You have cameras in cars. You can imagine all of the data being sent in in real time, and you could probably predict accidents pretty easily. I mean, these are just moving objects, right? At a specific rate, who's driving haphazardly, but you could also potentially signal takeover of the brakes or the steering wheel of a car and prevent accidents. I mean, certain cars already do that, but could you essentially eliminate, well, let's do something even more important. Let's eliminate traffic.

I don't know if you can do that, but because that's a funnel problem, but um could you could you predict um physical events in the world into the future okay this has already been done not for traffic but for hurricanes so you you know as you know the weather is extremely difficult to predict and except here in california where it's always going to be sunny here But now what they've done is to feed a lot of previous data from previous hurricanes and also simulations of hurricanes. You can simulate them in a supercomputer. It takes days and weeks. So it's not very useful for actually accurately predicting where it's going to hit Florida.

But what they did was after training up the AI on all of this data, it was able to predict with much better accuracy exactly where in Florida it's going to make landfall. And it does that on your laptop in 10 minutes. Incredible. So something just clicked for me. And it's probably obvious to you and to most people, but I think this is true. I think what I'm about to say is true. At the beginning of our conversation, we were talking about the acquisition of knowledge versus the implementation of knowledge, just learning facts versus learning how to implement those facts in the form of physical action or cognitive action, right?

Math problem is cognitive action, physical action. Okay. AI can do both knowledge acquisition, it can learn facts, long lists of facts and combinations of facts, but presumably it can also run a lot of problem sets and solve a lot of problem sets. I don't think, except with some crude, still to me, examples of robotics that it's very good at action yet, but it will probably get there at some point. Robots are getting better, but they're not doing what we're doing yet. But it seems to me that as long as they can acquire knowledge and then solve different problem sets, different iterations of combinations of knowledge, that basically they are in a position to take any data about prior events or current events and make pretty darn good predictions about the future and run those back to us quickly enough.

and to themselves quickly enough that they could play out the different iterations. And so I'm thinking, you know, one of the problems that seems to have really vexed neuroscientists and the field of medicine and the general public has been like the increase in the, at least diagnosis of autism. I've heard so many different hypotheses over the years. I think we're still pretty much in the fog on this one. Could AI start to come up with new and potential solutions and treatments if they're necessary, but maybe get to the heart of this problem? It might, and it depends on the data you have. It depends on the complexity of the disease.

But it will happen. In other words, we will use those tools the best we can, because obviously, if you can make any progress at all and jump into the future, wow, that would save lives. That would help so many people out there. I really think the promise here is so great that even though there are flaws and there are regulatory problems, we just, we really, really have to really push. And we have to do that in a way that is going to help people, you know, in terms of making their jobs better and helping them solve problems that otherwise they would have had difficulty with and so forth. And it's beginning to happen, but these are early days.

So we're at a stage right now with AI that is similar to what happened after the first flight of the Wright brothers. In other words, the achievement that the Wright brothers made was to get off the ground 10 feet and to power forward with a human being 100 feet. That was it. That was the first flight. and it took an enormous amount of improvements the most difficult thing that had to be solved was control how do you control it how do you make it go in the direction you want it to go and shades of what's happening now in ai is that you know we are off the ground we were not going very far yet but who knows where it will take us into the future let's talk about parkinson's disease a depletion of dopamine neurons that leads to difficulty in smooth movement generation and also some cognitive and mood-based dysfunction.

Tell us about your work on Parkinson's and what did you learn? So as you point out, Parkinson's is first a degenerative disease. It's very interesting because the dopamine cells are a particular part of the brain, the brainstem, and they are the ones that are responsible for procedural learning i told you before about temporal difference it's dopamine cells and uh it's a very powerful way for the it's a global signal it's called a neuromodulator because it modulates all the other signals taking place you know throughout the cortex and also it's uh very important for uh learning uh uh sequences of actions uh you know that produce survival for survival and but the problem is that with certain environmental insults you know of especially you know toxins like pesticides those neurons are very vulnerable and when they die you get all of the symptoms that you just described that is the people who have lost those cells actually before the treatment you know l-dopa which is a dopamine precursor they actually were um it became comatose right they didn't move they were still alive but they just didn't move at all you know they they it's tragic yes it locked in it's called yeah it's Tragic.

Tragic. So when the first trials of L-DOPA were given to them, it was magical because suddenly they started talking again. So, I mean, this is amazing, amazing. I'm curious, when they started talking again, did they report that their brain state during the locked-in phase was slow velocity? Was it sort of like a dreamlike state or they felt like they were in a nap or were they in there like screaming to get out? Because their physical velocity obviously was zero um they're locked in after all and i've long wondered when coming back from a run or from waking up from a great night's sleep when i shift into my you know waking state whether or not physical velocity and cognitive velocity are linked okay that's a wonderful observation or a question you know i'll bet you know the answer okay here's here's something that is really amazing. It was discovered, interestingly, when they tend to move slowly, as you said, but to them, cognitively, they think they're moving fast. Now, it's not because they can't move fast because you can say, well, can you move faster? Sure. And they move normal, right? But to them, they think they're moving at super velocities. So it's a set point issue. So it's a set point

issue yes it's all about set points that's what what's really going on and and and as the set point gets further and further down you know that now now they without moving at all they think they're moving right i mean this is what's going on by the way you can ask them you know what was it like you know we were talking to you and you didn't respond oh i didn't feel like it the brain confabulates an answer they have yeah well they they they that they confabulated it because they didn't have enough energy or they couldn't initiate, they couldn't initiate actions. That's one of the things that they have trouble with it, with movements, starting a movement. Yeah. As you can tell, I'm fascinated by this notion of cognitive velocity. And again, there may be a better or more accurate or official language for it, but I feel like it encompasses so much of what we try to do when we learn. And the fact that during sleep, you have these very vivid dreams during rapid eye movement sleep. So cognitive velocity is very fast. Time perception is different than in slow wave sleep dreams. And I really think there's something to it as at least one metric that relates to brain state. I've long thought that we know so much

more about brain states during sleep than we do about wakeful brain states. Then we talk about focus, motivated, flow. I mean, these are not scientific terms. I'm not being disparaging of them, they're pretty much all we've got until we come up with something better. But like we're biologists and neuroscientists and computational neuroscientists in your case. And we're like trying to figure out like, like what brain state are we in right now? Our cognitive velocity is a, you know, a certain value. But I think the more that people think about this, you know, I'll venture to say that the more that they think a little bit about their cognitive velocity at different times of day, start to notice that there's a, tends to be a few times of day for me it tends to be early to late mid-morning um and then again in the evening after a little bit of trough and energy that boy that hour and a half each like that's the time to get real work done i can i can i can mentally sprint far at those times right but there are other times of day when i don't care how much caffeine i drink i don't care unless it's a stressful event that I need to meet the demands of that stress. You, I just can't, I can't get

to that faster pace while I'm also engaging. You can read faster, you can listen, but you're not using the information. You're not storing the information. That's right. What times a day for you are, are, I get most done in the morning and then you're right later, uh, after, uh, Uh, dinner, uh, is, is also different though. I think in the morning, uh, I'm, I'm better at creative stuff. And then I think that in the evening, I'm better at actually just cranking it out, you know? Interesting. Um, given the relationship between a body temperature and circadian rhythm, I would like to run an experiment that, um, relates, uh, core body temperature to cognitive velocity.

I've actually noticed, this is something that is just purely subjective, but the temperature of the salt inside the building is kept 75. It's like, you know, it's rock solid. But in the afternoon, I feel a little chilly. It's probably my, you know, internal. Sure. You know, body temperature. Body temperature, yeah, it's probably going down. and that may correspond to the loss of energy, you know, the amount of the ability for the brain and everything else. By the way, you know, this is Q10, this is a jargon. Every single enzyme in your, every cell can go at different rates depending on the temperature, right?

And so, yeah, so the body temperature is doing this and all the cells are doing this too, right? So this is, it's an explanation. I'm not sure if it's the right one, but. Yeah, Craig Heller, my colleague at Stanford in the biology department has beautifully described how the enzymatic control over pyruvate, I believe it is, controls muscular failure. That local muscular failure, you know, when people are like trying to move some resistance, has everything to do with the temperature, the local temperature that shuts down certain enzymatic processes that don't allow the muscles to contract the same way. You know, he knows the details and he covered them on this podcast. I'm forgetting the details. You start to go, wow, like these enzymes are so beautifully controlled by temperature. And of course his laboratory is focused on ways to bypass those temperature or to change temperature locally in order to bypass those limitations and have shown them again and again. It's just incredible. Yeah. I don't, I hear we're speculating about what it would mean for cognitive velocity, but I think it's such a different world to think about the underlying biology as opposed to just thinking about like a drug you know you increase dopamine

and norepinephrine and and epinephrine the so-called catecholamines and you're going to increase energy focus and alertness but you're going to pay the price you're going to have a trough in energy focus and alertness that's proportional to how much greater it was when you took the drug boy amphetamines are a good example boy you know you're going a mile a minute when you're taking the drug, of course, you know, you, it's, it's, it's, I understand that that's your impression. And the reality is you don't actually accomplish that much more. Have any LLMs, so AI been used to answer this really pressing question of what is going to be the consequence on cognition for these young brains that have been weaned while taking Ritalin, Adderall, Vyvanse, and other stimulants? Because we have, we have, you know, millions of kids that We've done this experiment on our, you know, whole cadre, a whole generation.

And, you know, I really would like to know the answer. I wonder if anybody's studying that. That's really a great question because we gave them speed effectively, you know, the drug that causes the brain to be activated. But by the way, but, you know, there's the consequences that, you know, when it wears off, you have no energy, right? You just completely spent. That's it. That's the pit. That's the pit. But that's why you take more of it. You see, that's the problem. It's a spiral. I love how today you're making it so very clear how computation, how math and computers and AI now are really shaping the way that we think.

think about these biological problems, which are also psychological problems, which are also daily challenges. I also love that we touched on mitochondria and how to replenish mitochondria. I wanna make sure that we talk about a couple of things that I know are in the back of people's minds, no pun intended here, which are consciousness and free will. Normally, I don't like to talk about these things, not because they're sensitive, but because I find the discussions around them typically to be more philosophical than neurobiological. and they tend to be pretty circular and so you get people like kevin mitchell um who's a real i think he has a book about free will he believes in free will um you've got people like robert sapolsky wrote the book determined he doesn't believe in free will how do you feel about free will and is it even a discussion that we should be having well if you go back 500 years you know the middle ages the the concept didn't exist or at least not in the way we use it because everybody it was it was the the way that we that humans felt about the you know the world and how it worked and and and its its impact on them was that it's all fate they had this concept of fate which is that

there's nothing you can you can do that that something is is going to happen to you because of the what's going on in the the gods above or whatever it is right you get you attribute it to the to the physical forces around you that caused it not not to your own free will not that there's something that you did that caused you to this to happen to you right so so i think that it these These words, by the way, that we use, free will, consciousness, intelligence, understanding, they're weasel words, because you can't pin them down. There is no definition of consciousness that everybody agrees on, and it's tough to solve a problem, a scientific problem, if you don't have a definition that you can agree on.

and uh and you know there's this big controversy about whether these large language models understand language or not right the way we do and uh and and what it really is revealing is we don't understand what understanding is we literally we don't have a really good argument or measure you know that you could measure someone's understanding and then apply it to chat GDP and see whether it's the same. It probably isn't exactly the same, but maybe there's some continuum here we're talking about, right? You know, the way I look at it, you know, it's as if an alien suddenly landed on Earth and started talking to us in English, right? And the only thing we can be sure of was that it's not human. I met some people that I wondered about their terrestrial origins. Okay. Okay. Well, okay. Now there's a big diversity amongst humans too.

You're right about that. Yeah. Yeah. Certain colleagues of ours at UCSD years ago, one in particular in the physics department who I absolutely adore as a human being, just had such an unusual pattern of speech, of behavior, totally appropriate behavior, but just unusual in the middle of a faculty meeting would just kind of turn to me and start talking while the other person was presenting. And I was like, maybe not now. And he would say, oh, okay. But in any other domain, you'd say he was very socially adept. And so, you know, there's certain people that just kind of discard with convention and you kind of want to like, is he an alien?

It's kind of cool, you know, in a cool way. Like, you know, he's one of my, again, a friend and somebody I really delight in. It's true. It's true. You know, no, no, not everybody has adopted the same social conventions, you know. It could be a touch of autism. I mean, yeah. That's a problem that, I mean, in other words, there are very high functioning autistic people out there. He's brilliant. And often they are, you know, it's, there are high people who are brilliant with autism. But, you know. Could you build an LLM that was more on one end of the spectrum versus the other to see what kind of information they forage for?

I reviewed a paper. It seemed like it would be a really important thing to do. It's been done. Okay. There was a paper that I reviewed where they took the LLM and they fine-tuned it with different data from people with different disorders, you know, autism and so forth. And sociopaths, you know. That's scary. But you want to know the answer. No, no. And they got, they got these LLMs to behave just like those people who have these disorders. You can get them to behave that way. Yes. Could you do, um, political leaning and values? I haven't seen that, but, uh, it's pretty clear that to me, at least that, that if you can do sociopathy, you can probably do any political belief, you know, but you could also view all this as, um, you could take benevolent tracks. You could also say, um, hyper creative, uh, um, sensitive to, um, uh, uh, emotional tone of voices and find out what kind of information that person brings, uh, excuse me, that LLM brings back versus somebody who is very oriented towards just the content of people's words, as opposed to what, what, you know, because among people you find this, you know, if you've ever left a party with a significant other and And sometimes someone will say, I've had this experience with like, did you see that interaction between so-and-so?

I'm like, no, what are you talking about? Like, did you hear that? I'm like, no, not at all. I didn't hear, I heard the words, but I did not pick up on what you were picking up on. And it was clear that there's two very different experiences of the same content based purely on a difference in interpretation of the tonality. okay there's a lot of information that as you point out which has to do with uh the tone the uh spatial expressions uh you know there's a tremendous amount of information that is passed not just with words but with all the other parts the visual input and so forth and some people are good at picking that up and others are not there's a tremendous variability between individuals and you know that's that's biology is all about diversity and it's all about you know needing gene pool that's very diverse so that you can evolve and and survive catastrophic changes that occur in a climate for example but wouldn't it be wonderful if we could create an LLM that could understand what those differences are.

Now, just think about it, right? Like a truly diverse LLM that integrated all those differences. Yeah, but here's what you'd have to do. What you'd have to do is to train it up on data from a bunch of individuals, human individuals. Now, one of the things about these LLMs is that they don't have a single persona. They can adopt any persona. You have to tell it what you're expecting from. Or ask it in a way that works for you and you'll get back a certain persona. If you, if you, if I once gave it an abstract from a paper, very technical, a computational paper. And I said, you are a neuroscientist.

I want you to explain this abstract to a 10-year-old. it it did it in in a way that i could never have done it it really simplified it it some of the subtleties were not in it but it explained you know What plasticity it was and explain what a synapse is. It did that. It's almost like a qualifying exam for a graduate student. I saw something today on X, formerly known as Twitter, that blew my mind that I wanted your thoughts on that is very appropriate to what you're saying right now, which is someone was asking questions of an LLM on ChatGPT or maybe one of these other, Anthropic or Claude or something like that. I probably misuse those names, one of the AI online sites. And somewhere in the middle of its answers, the LLM decided to just take a break and start looking at pictures of landscapes in Yosemite. Like the LLM was doing what a maybe cognitively fatigued person or what any kind of person online would do, which was to like take a break and look at a couple pictures of something they you know maybe they're thinking about going camping there or something and then get back to whatever task we hear about hallucinations in ai that's something that it can imagine things that aren't there just like a human brain but um that blew my mind i haven't

encountered that but you know isn't it fascinating uh you know that that's a sign of of a real generative internal model uh if it's see here's the thing that um the thing that most distinguishes i think an llm from human is that you know if if you if if you go into a room quiet room and just sit there without any sensory stimulation your brain keeps thinking right in other words you think about what you want to do you know planning ahead or something that happened to you during the day, your brain is always generating internally. After talking to you, one of these large language models just goes blank. There is no self-continuous, self-generated thoughts.

And yet we know self-generated thought and in particular brain activity during sleep, as you illustrated earlier with the example of sleep spindles and rapid eye movement sleep are absolutely critical for shaping the knowledge that we experienced during the day. So these LLMs are not quite where we are at yet. I mean, they can outperform us in certain things like Go, but how soon will we have LLMs, AI that is, with self-generated internal activity? we're getting closer um and so this is something i'm working on myself actually uh trying to understand how that's done in our own brains was generating continual uh brain activity that leads to you know planning and things that we don't know what the answer to that is yet in neuroscience it and by the way you go to a lecture and you you hear the words one after the next over an hour and you see the slides one after the next at the end you ask a question right just let's think about what you just did somehow you're able to integrate all that information over the hour and and then use your long-term memory then to come up with some insight or some issue that you want how did your brain remember all that information working memory traditional working

memory that neuroscientists study is only after a few seconds, like maybe a telephone number or something. But we're talking about long-term working memory. We don't understand how that is done. And LLMs, actually, large language models, can do something. It's called in-context learning. And it was a great surprise because... There is no plasticity. The thing learns at the beginning, you train it up on data, and then all it does after that is to inference, you know, fast loop of activity, one word after the next, right? That's what happens with no learning, no learning. But it's been noticed that as you continue your dialogue, it seems to get better at things.

How could that be? How could it be in context learning, even though there's no plasticity? So that's a mystery. We don't know the answer to that question yet. But we also don't know what the answer is for humans either. Right. Could I ask you a few questions about you and as it relates to science and your trajectory? Building off of what you were just saying, do you have a practice of meditation or eyes closed, sensory input reduced or shut down to drive your thinking in a particular way? Or are you at your computer talking to your students and postdocs and sprinting on the beach? Or asleep. No, it's funny you mention that because I get my best ideas, not sprinting on the beach, but just either walking or jogging.

And it's wonderful. I don't know. I think serotonin goes up. It's another neuromodulator. I think that that stimulates ideas and thoughts. And so inevitably, I come back to my office, and I can't remember any of those great ideas. What do you do about that? Well, now I take notes. Okay. Voice memos? Yeah. Uh-huh. And some of them pan out. You know, there's no doubt about it. Sure. That you're put into a situation. It is a form of meditation. You know, if you're running in a steady pace, nothing distracting about, you know, the beach. Or do you listen to music or podcasts? No, I never listen to anything except my own thoughts.

So there's a former guest on this podcast who she happens to be triple degreed from Harvard, but she's more in the kind of like personal coach space, but very, very high level and impressive mind, impressive human all around. And she has this concept of wordlessness that can be used to accomplish a number of different things, but this idea that allowing oneself or creating conditions for oneself to enter states throughout the day or maybe once a day of very minimal sensory input. No lecture, no podcast, no book, no music, nothing. And allowing the brain to just kind of idle and go a little bit nonlinear, if you will.

Right. Where we're not constructing thoughts or paying attention to anyone else's thoughts through those media venues in any kind of structured way as a source of great ideas and creativity. It's been studied. Psychologists call it mind-wandering. Mind-wandering. Yeah, it is a significant literature. And it's often when you have an aha moment, when your mind is wandering and it's thinking nonlinearly in the sense of not following a sequence that is logical, hopping from thing to thing. Often that's when you get a great idea, just letting your mind wander. Yeah, and that happens to me. I wonder whether social media and just texting and phones in general have eliminated a lot of the, you know, walks to the car after work where one would normally not be on a call or in communication with anyone or anything. I used to do experiments where I was, you know, like pipetting and running, you know, immunohistochemistry and it was very relaxing.

And I could think while I was doing, cause I knew the procedures and then, you know, you had to pay attention to certain things, write them down. But, but I would often feel like, wow, I'm both working and relaxing and thinking of things. And I would listen to music sometimes. Okay, so we have a whole session, you know, a clip in learning how to learn about exactly this phenomenon. Here's what we tell our students, right? Is that, you know, if you're having trouble with some concept or, you know, you don't understand something, you're beating your head against the wall, don't – stop, stop. Just go off and do something.

Go off and clean the dishes. Go off and, you know, walk around the block. And inevitably what happens is when you come back, your mind is clear and you figure out what to do. And that's one of the best pieces of advice that anybody could get because, you know, we don't, nobody has told us how the brain works, right? Some people are really good at intuiting because they've experienced maybe, but everybody, okay, The other thing is everybody I know who's really made important contributions, and I'll bet you're one of them, you know, you're struggling with some problem at night and you go to bed and you wake up in the morning, ah, that's the solution.

That's what I should do, right? First thing in the morning when I wake up is when I'm almost bombarded with, I wouldn't say insight, and not always meaningful insight, but certainly what was unclear becomes immediately clear on waking. That's right. That's the thing that is so amazing about sleep. And you can see people who know this can count on it. In other words, the key is to think about it before you go to sleep. Right? Your brain works on it during the sleep period. right? And so, you know, don't watch TV because then who knows what your brain's going to work on. You know, use, you know, use the time before you fall asleep to think about something that is bothering you or maybe something that, you know, you're trying to understand, maybe, you know, a paper that you read the paper and say, oh, you know, I'm tired. I'm going to go to sleep.

You wake up in the morning and say, oh, I know what's going on in that paper. Yeah. I mean, that's what happens. You can use, you know, once you know something about how the brain works, you can take advantage of that. Do you pay attention to your dreams? Do you record them? No, no. Okay. So here's the problem. Dreams seem so iconic and a lot of people somehow attribute things to them. But there has never been any good theory or any good understanding first of all why we dream we still it's still not completely clear i mean there are some ideas but or uh what trick why this particular dream is this is does that have some significance for you and the only thing that i know uh that might explain a little bit is that uh you know the dreams are often very visual uh you know rapid eye movement sleep so that there's something happening that actually it's interesting all the neuromodulators are down regulated during sleep and then during REM sleep the acetylcholine comes up right so that's a very powerful neuromodulator it's important for attention for example but it doesn't come up in the prefrontal cortex which means that the circuits in the prefrontal cortex that are interpreting what the sensory input coming in are not turned on so any of these whatever happens in your visual

cortex is not being monitored anymore so you get bizarre things you know that you start floating and you know things happen to you and you know it's it's not anchored anymore and so but that still doesn't explain why right why you have that period it's important because if you block it and there are some sleeping pills that do block it you know it really does cause problems with, you know, normal cognitive function. Cannabis as well. People who come off cannabis experience a tremendous REM rebound and lots of dreaming in the, you know, the days and weeks and months after cannabis. Wow. I don't want to call it withdrawal because that has a different meaning.

No, no, it's an imbalance that was caused, you know, because the brain adjusted to the, you know, the endocannabinoid levels. And now it's got to go back and then it takes time, but it's interesting. Isn't it interesting? It affects dreams. I think that may be a clue. Yeah. Very, very common phenomenon. I'm told I'm not a cannabis user, but no judgment there. I just am not. It's actually a book I read years ago when I was in college, so a long time ago, by Alan Hobson, who was out at Harvard. Oh, yeah, I know him. Who, oh, cool. So I never met him, but he had this interesting idea that dreams, in particular rapid eye movement dreams, were so very similar to the experience that one has on certain psychedelics, LSD, lysergic acid, diethamide, or psilocybin, and that perhaps dreams are revealing the unconscious mind, you know, and not saying this in any psychological terms, you know, that, you know, when we're asleep, our conscious mind can't control thought and action in the same way, obviously. And kind of, it's sort of a recession of the waterline, you know, so we're getting more of the unconscious processing revealed. You know, that's an interesting hypothesis. How would you test it? I probably have to put someone in a scanner, have them go to sleep, put them in the

scanner on a psilocybin journey, this kind of thing. It's tough. I mean, any of these observational studies, of course, we both know are deficient in the sense that what you'd really like to do is control the neural activity. You'd like to get in there and tickle the neurons over here and see how the brain changes. And you'd love to get real-time subjective report. This is the problem with sleep and dreaming is you can wake people up and ask them what they were just dreaming about, but you can't really know what they're dreaming about in real time. It's true. Yeah, it's true. By the way, there are two kinds of dreams.

Very interesting. So if you wake someone up during REM sleep, you get very vivid changing. Dreams are always different and changing. But if you wake someone up during slow wave sleep, you often get a dream report, but it's a kind of dream that keeps repeating over and over again every night. And it's a very heavy emotional content. Interesting. That's in slow wave sleep. Yeah. Because I've had a few dreams over and over and over throughout my life. So this would be in slow wave sleep. Yeah, probably slow wave sleep. Yeah. Fascinating. As a neuroscientist who's computationally oriented, but really you incorporate the biology so well into your work.

So that's one of the reasons you're you, you're this luminary of your field. And who's also now really excited about AI. What are you most excited about now? Like if you had, and, you know, of course this isn't the case, but if you had like 24 more months to just pour yourself into something and then you had to hand the keys to your lab over to someone else, what would you go all in on?

Yeah. And should they make the bad decision not to, you know, maybe we'll figure out another way to get it, get the work done. Certainly you will. Terry, I want to thank you. First of all, for coming here today, taking time out of your busy cognitive and running and teaching and research schedule to share your knowledge with us. and also for the incredible work that you're doing on public education and teaching the public, I should say, giving the public resources to learn how to learn better at zero cost. So we will certainly provide links to learning how to learn and your book and to these other incredible resources that you've shared.

And you've also given us a ton of practical tools today related to exercise mitochondria and some of the things that you do, which of course are just your versions of what you do, but that certainly, certainly are going to be a value to people, including me in our cognitive and physical pursuits and frankly, just longevity. I mean, this is not lost on me and those listening that your vigor is, as I mentioned earlier, undeniable. And it's been such a pleasure over the years to just see the amount of focus and energy and enthusiasm that you bring to your work and to observe that it not only hasn't slowed, but you're picking up velocity. So thank you so much for educating us today. I know I speak on behalf of myself and many, many people listening and watching. This is a real gift, a real incredible experience to learn from you.

So thank you so much. Well, thank you. And I have to say that I've been blessed over the years with wonderful students and wonderful colleagues. And I count you among them who really i've learned a lot from thank you but you know we're you know science is a social activity and and we learn from each other and we all make mistakes but we learn from our mistakes that's the beauty of science is that we can make progress now you know your career has been remarkable too because you have affected and influenced more people than anybody else i know personally, with the knowledge that you are broadcasting through your interviews, but also just in terms of your interests. I'm really impressed with what you've done. And I want you to keep at it because we need people like you. We need scientists who can actually express and reach the public. If we don't do that, everything we do is behind closed doors, right? Nothing gets out. And so you're one of the best of the breed in terms of being able to explain things in a clear way that gets through to more people than anybody else I know. Well, thank you. I'm very honored to hear that. It's a labor of love for me and I'll take those words in and I really

appreciate it. It's an honor and a privilege to sit with you today and please come back again. I would love to. I would love to, yeah. All right. Thank you, Terry. You're welcome. on both Spotify and Apple. And on both Spotify and Apple, you can leave us up to a five-star review. Please check out the sponsors mentioned at the beginning and throughout today's episode. That's the best way to support this podcast. If you have questions or comments about the podcast or guests or topics that you'd like me to consider for the Huberman Lab podcast, please put those in the comment section on YouTube. I do read all the comments.

For those of you that 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. The book is now available by presale 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. If you're not already following me on social media, I am Huberman Lab on all social media platforms. So that's Instagram, X, formerly known as Twitter, 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 content on the Huberman Lab podcast. Again, that's Huberman Lab on all social media platforms. If you haven't already subscribed to our Neural Network Newsletter, our Neural Network Newsletter is a zero-cost monthly newsletter that includes podcast summaries as well as protocols in the form of brief one-to-three-page PDFs.

Those one-to-three-page PDFs cover things like deliberate heat exposure, deliberate cold exposure. We have a foundational fitness protocol. We also have protocols for optimizing your sleep, dopamine, and much more. Again, all available, completely zero cost. Simply go to hubermanlab.com, go to the menu tab, scroll down to newsletter, and provide your email. We do not share your email with anybody. Thank you once again for joining me for today's discussion with Dr. Terry Sejnowski. And last, but certainly not least, thank you for your interest in science.