Welcome to the Huberman Lab podcast where we discuss science and science based tools for everyday life. I'm Andrew Huberman and I'm a professor of neurobiology and Ophthalmology at Stanford School of Medicine. My guest today is Dr. Terry Signnowski.
Dr. Terry Signnowski is a professor at the Salk Institute for Biological Studies where he directs the Computational Neurobiology Laboratory. And as his title suggests, he is a computational neuroscientist. That is, he uses math as well as artificial intelligence and computing methods to understand this overarching, ultra important question of how the brain works.
Now I realize that when people hear terms like computational neuroscience, algorithms, large language models and AI that it can be a bit overwhelming and even intimidating. But I assure you that the purpose of Dr. Stnowski's work, and indeed today's discussion, is all about using those methods to clarify how the brain works and indeed to simplify the answer to that question. So, for instance, today you will learn that regardless of who are, regardless of your experience, that all your motivation in all domains of life is governed by a simple algorithm or equation.
Dr. Stanoski explains how a single rule, a single learning rule, drives all of our motivation related behaviors. And it of course relates to the neuromodulator dopamine. And if you're familiar with dopamine as a term today you will really understand how dopamine works to drive your levels of motivation, or in some cases, lack of motivation, and how to overcome that lack of motivation.
Today we also discuss how best to learn. Dr. Snowski shares not just information about how the brain works, but also practical tools that he and colleagues have developed, including a zero cost online portal that teaches you how to learn better based on your particular learning style, the way that you in particular forge for information and implement that information. Dr.
Stanoski also explains how he himself uses physical exercise of a particular type in order to enhance his cognition, that is his brain's ability to learn information and to come up with new ideas. Today we also discuss both the healthy brain and the diseased brain in conditions like Parkinson's and Alzheimer's, and how particular tools that relate to mitochondrial function can perhaps be used in order to treat various diseases, including Alzheimer's, dementia. I'm certain that by the end of today's episode, you will have learned a tremendous amount of new knowledge about how your brain works and practical tools that you can implement in your daily life. Before we begin, I'd like to emphasize that this podcast is separate from my teaching research roles at Stanford it is, however, part of my desired effort to bring zero cost 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 as a condition of being allowed to stay in school, but pretty soon I realized that therapy is an extremely important component to one's overall health. In fact, I consider doing regular therapy just as important as getting regular exercise, including cardiovascular exercise and resistance training, which of course I also do every single week. Now, there are essentially three things that great therapy provides. First of all, it provides a good rapport with somebody that you can trust and talk to about essentially all issues that you want to Second of all, great therapy provides support in the form of emotional support or simply directed guidance what to do or what not to do in given areas of your life.
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For the month of November 2024, Helix is getting up to 25% off on all mattress orders and two free pillows. Again, that's helixleep.com huberman to get up to 25% off and two free pillows. And now for my discussion with Dr. Terry Stjnowski.
Dr. Terry Stjnowski, 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 they're 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. This is a big question, how does the brain work?
What is consciousness, all 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, we're a little groggy, so 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 a Patrick slain. I wrote a book, Context of Brain and in it there's this levels diagram, 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 he described, which is, you know, let's look at all the parts, that's the bottom up approach, you know, take it apart and just 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, you know, the laws of behavior. This is the behaviorist.
But you know, even people in AI, we're trying to do a top down trait 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, you know, you bake a cake, you have to have ingredients and you have to say the order in which they put together and how long and you know, if you get it wrong, you know, it doesn't work.
You know, 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 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 Day and Reid Montague were postdocs in the lab, and it had to do with a 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 you know, what, what's the details of the profession and what works, what doesn't work, and so forth. And it turns out that the basal ganglia interacts with the cortex, not just in the back, which is the action part, but also with 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, go, meaning to actually perform a behavior. But the basal ganglia also instruct no go, don't, don't engage in that behavior. And learning an expert golf swing or even a basic golf swing or a 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, you know, a particular region and thinking about their motor behaviors, what to do and what 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 thing? Well, I mentioned the prefrontal cortex and that part, the loop of the basal ganglia that is one of the last to mature in early adulthood. And, you know, the problem is that for adolescence, it's not the no go part for planning 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, 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, you know, 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? Right?
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 designs. Yeah, that's right. So Go is to chess with chesses to something like checkers, you know, 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 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 good 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 we're 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 some very important feature, which is that rewards, by the way, 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 behaviors 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 the 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.
You know what you need. You know, you're training a rat to do some tasks with small food rewards. But if you just shock the rat or that rat doesn't forget that, yeah, one really bad relationship will have you learning certain things forever. And this is also ptsd.
Post Traumatic Stress disorder is another good example of that. That can screw you up for the rest of your life. So 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 going to have to be able to become a member of this society. And the things that are expected of you, all of that has to become through experience, through building this value function. So this is, and this is something we discovered in the 20th century. And now it's going into AI it's called reinforcement learning and AI, it's a form of procedural learning as opposed to the cognitive level where you think and you do things.
Cognitive thinking is much less efficient because you have to go step by step with procedural learning. It's automatic. Can you give me an example of procedural learning in the context of a comparison to cognitive learning? Like, is there an example of perhaps like, how to make a decent cup of coffee using, you know, purely knowledge based learning versus procedural learning, where procedural learning wins.
And I can imagine one. But you're the true expert here. Well, you know, you know a lot of examples. But since we've been talking about tennis, can you imagine learning how to play tennis through a book?
Reading a book. That's so funny. On the plane back from Nashville yesterday, the guy sitting across the aisle from me was reading a book about maybe a 1400 pilot's license or something. And I looked over and couldn't help but notice these diagrams of the plane flying.
And I thought, I'm just so glad that this guy is a passenger and not a pilot. And then I thought about how the pilots learned. And presumably it was a combination of practical learning and textbook learning. When you scuba dive this right, I'm scuba dive certified.
And when you get your certification, you learn your dive tables and you learn why you have to wait between dives, et cetera, gas exchange and a number of things. But there's really no way to simulate what it is to take your mask off underwater, put it back on, and then, you know, blow the water out of your mask like that. You just have to do that in a pool and you actually have to do it when you need to for it to really get drilled in. It's really essential for things that have to be executed quickly and expertly to get that really down path so you don't have to think.
And this happens in school, right? In other words, you have classroom lessons where you're given explicit instruction, but then you go do homework. That's procedural learning. You do problems, you solve problems.
And, you know, I'm a PhD physicist, so I went through all the classes in theoretical physics, and it was really the problems that really were the core of becoming a good physicist. You can memorize equations, but that doesn't mean you understand how to use the equations. I think it's worth highlighting something. A lot of times on this podcast we talk about what I call protocols.
It would be, you know, get some morning sunlight in your eyes to simulate your super cosmatic nucleus by way of gangland cells. Audiences of this podcast will recognize the sun. It basically gets sunlight in your eyes in the morning and set your circadian clock, and you can hear that a trillion times. But I do believe that there's some value to both knowing what the protocol is, the underlying mechanisms that are these things in your eye that you know, the sunrise, qualities of light, etc.
Then send them your brain, etc. Etc. But then once we link knowledge, pure knowledge, to a practice, I do believe that the two things merge someplace in a way that, let's say, reinforces both the knowledge and the practice. So these things are not necessarily separate.
They bridge. In other words, doing your theoretical physics problem sets reinforces the examples that you learned in lecture and in your textbooks, and vice versa. So this is a battle that's going on right now in schools. You know, what you just said is absolutely right.
You need both. We have two major learning systems. We have a cognitive learning system, which is critical. We have procedural learning system, which is subcritical basal ganglion.
And the two go hand in hand. If you want to become good at anything, that the two are going to help each other. And what's going on right now in schools in California at least, is that they're trying to get rid of the procedural. That's ridiculous.
They don't want students to practice because it's going to be, you know, you're stressing them. You don't want them to be. To feel that, you know, that they're having difficulty. So.
But we can. Everybody's listening. I'm covering my eyes because this would be like saying, goodness, there's so many examples, like, here's a textbook on swimming. And then you're going to go out to the ocean someday and you will never actually swum, Right?
And now you're expected to be able to survive, let alone swim. It's crazy. It's crazy. I'll tell you, Barbara Oakley has, and I have a MOOC massive Obama online course.
I'm learning how to learn. And it helps students. We aimed at students, but it actually has been taken by 4 million people in 200 countries ages 10 to 90. What is this called?
Learning how to Learn. Is it. Is there a paywall? No, it's free.
Completely free. Amazing. And, you know, I get incredible feedback, you know, fan letters almost every day. You're about to get a few more.
Okay. In an episode on learning how to learn. And my understanding of the research is that we need to test ourselves on the material. The testing is not just a form of evaluation.
It is a form of identifying the errors that help us then compensate for the errors. But it's very procedural. It's not about just listening and regurgitating. You know, you put your finger on it, which is that, and this is what we teach the students, is that you have to.
The way the brain works, right? It doesn't memorize things like a computer, but it has to be active learning. You have to be actively engaged. In fact, when you're trying to solve a problem on your own, right, this is where you're really learning by trial and error.
And that's procedural system. But if someone tells you what the right answer is, you know, you know, that's just something that is a fact that it gets stored away somewhere, but it's not going to automatically come up if you actually are faced with something that's not exactly the same problem, but similar. And by the way, this is the key to AI, completely essential for the recent success of these large language models, you know, that the public now is beginning to use, is that they're not parrots. They just, they're not, they just don't memorize what they, what the data that they've taken in.
They have to generalize. That means to be able to do well on new things that come in that are similar to the old things that you've seen, but allow you to solve new problems. That's the key to the brain. The brain is really, really good at generalizing.
In fact, in many cases, you only need one example to generalize. Like going to a restaurant for the first time. There are a number of new interactions. There might be a host or hostess, you sit down on these tables you never sat at.
Somebody ask you questions, you read it. Okay, maybe it's a QR code these days. But forever after you understand the process of going to a restaurant doesn't matter what the genre of food happens to be or what city sitting inside or outside, you can pretty much work it out. Sit at the counter, sit outside, sit at the table.
There are a number of key action steps that I think pretty much translate to everywhere. Unless you go to some super high end thing or some super low end thing where it's a buffet or whatever. You can start to fill in the blanks here. If I understand correctly, there's an action function that's learned from the knowledge and the experience.
Exactly. And then where's 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, you know, the cortex had, were like countries on each of which each part of the cortex was dedicated to one function.
Right. You know, and interestingly record 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 an auditory cortex in the here in the middle. And then the prefrontal cortex for social interaction. And so it looks really clear cut that it's modular. And now what we're facing is we have a new way to record from neurons optically.
We can record from tens of thousands, from dozens of areas simultaneously. And what we're discovering is that if you want to do any task you're engaging, not just the area that you might think, you know, has the input coming in, see the visual system, but the visual system is getting input from the motor system. Right. In fact, you know, there's more input coming from the motor system than from the eye.
Really? Yes. Anne Churchill at UCLA has shown that in the mouse. This is.
So now we're looking at global interactions between all these areas. And that's where real complex cognitive behaviors emerge, is from those interactions. And now we have the tools for the first time to actually be able to see them in real time. And we're doing that now first on mice and monkeys, but we now can do this in humans.
So I've been collaborating with a group at Mass General Hospital to record from people with epilepsy. And they have to have an operation for people who are drug resistant to be able to take out, find out where it starts in the cortex, you know, where it is initiated, where the seizure starts. And then to go in, you have to go in and record simultaneously from a lot of parts of the cortex for weeks until you find out where it is. And then you go in and you try to take it out.
And often that helps. Very, very invasive. But for two weeks we have access to all those neurons in that cortex that are being recorded from constantly. And so I've used.
I started out because I was interested in sleep and I wanted to understand what happens in the cortex of a human during sleep. But then we realized that, you know, you can also figure, you know, people who have these debilitating problems with seizures, you know, they're there for two weeks and they have nothing to do. So they just love the fact that scientists are interested in helping Them and, you know, teaching them things and finding out where in the cortex things are happening when they learn something. This is a goldmine.
It's unbelievable. And I've learned things from humans that I could have never gotten from any other species. Obviously language is one of them. But there are other things in sleep that we discovered having to do with traveling waves.
There are circular traveling waves that go on during sleep, which is astonishing. Nobody ever really saw that before. But if you were to describe 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.
No, this is non rem sleep. This is a jargon. This is during intermediate transition states. The transition state.
Our audience, they've heard a lot about slow wake sleep for me and that walker light slow wave sleep. And so what do these traveling waves accomplish for. Okay, so in the case of. They're called sleep spindles.
They last. The waves last for about a second or two and they travel, like I say, in a circle around the vortex. 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 it's a very important function.
And if you take out it's the hippocampus that 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's to say, you can't remember what you did yesterday, or for that matter, even an hour earlier.
The hippocampus plays back your experiences, causes the sleep spindles now to knead that into the cortex. And it's important to 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 that doesn't interfere with what you already know. So that's an example of a very important function that these traffic waves have.
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But it's also giving me that 28 grams of very high quality protein with just 150 calories. If you would like to try David, you can go to davidprotein.com huberman Again, the link is davidprotein.com huberman As I recall, there are one or two things that one can do in order to ensure that one gets sufficient sleep spindles at night and thereby incorporate this new knowledge. This was from the episode that we did with Gina Poe from ucla, I believe, and others, including Matt Walker. My recollection is that the number one thing is to make sure you get enough sleep at night so you experience enough of these spindles.
And we're all familiar with the cognitive challenges, including memory challenges and learning challenges associated with lack of sleep insertion sleep. The other was that there was some interesting relationship between daytime exercise and nighttime prevalence of sleep spindles. Are you familiar with that literature? No, this is a fascinating literature and it's all pointing the same direction, which is that, you know, we always neglect to appreciate the importance of sleep.
I mean, obviously you refresh when you wake up, but there's a lot of things happening. It's not that your brain turns off, it's that it goes into a completely different state. And memory consolidation is just one of those things that happens when you fall asleep. And of course, you know, there's dreams and so forth.
We don't fully appreciate or understand exactly how all the different sleep stages are work together. But exercise is a particularly important part of getting the motor system tuned up. And that it's thought that the rem, rapid eye movement sleep may be involved in that. So that's yet another part of the sleep stages you go through.
You go back and forth between dream sleep and the slow wave sleep, back and forth, back and forth during the night. And then when you wake up, you're in the REM stage, more and more rem, more and more rem, but that's all observation. But as a scientist, what you want to do is perturb the system and see if you can. Maybe if you have more sleep spindles, maybe you'd be able to remember things better.
So it turns out Sarah Bednik, who's at UC Irvine, did this fantastic experiment. So it turns out there's a drug called Zolpidem which goes by the name Ambien. You may have some experience with that. I've never taken it, but I'm aware of what it is.
You can use it as a sleep aid. That's right. A lot of people take it in order to sleep. Okay, well, it turns out that it causes more sleep spittles.
Really? Yeah, it doubles the number of spindles. If, you know, if you take the drug, you take the drug after you've done the learning, right? You do the learning at night, and you take the drug, and you have twice as many spindles.
You wake up in the morning, you can remember twice as much from what you learned, and the memories are stable over time. It's in there, it's consolidated. I mean, that's the point. What's the downside of Ambien?
Okay, here's the downside. Okay, so people who take the drug say if you're going to Europe and you take it, and then you sleep really soundly, but often you. You find yourself in the hotel room, you completely have no clue. You have no memory of how you got there.
I've had that experience without Ambien or any other drugs, where I am very badly jet lagged. Yes. And I wake up, and for a few seconds, but what feels like eternity, I have no idea where I am. Okay, well, that's another problem that you have with jet lag.
Really screws things up. But this is something where it could be an hour. You know, you. You took the train or you.
You took a taxi or something, and you're. And so here. This seems crazy. How could it be a way to improve learning and recall on one hand, and then forgetfulness on the other hand?
Well, it turns out what's important is that when you take the drug. Right. In other words, it helps consolidate experiences you've had in the past before you took the drug. But it'll wipe out experiences you have in the future after you take the drug.
Right. It must be a terrifying experience. But I'm laughing because, you know, there's some beautiful pharmacology and indeed, some wonderfully useful pharmaceuticals out there. You know, some people cringe here and say that there are some very useful drugs out there that save lives and help people deal with symptoms, et cetera.
Side effects are always a concern. But this particular drug profile, Ambien, that is, seems to reveal something perhaps even more important than the discussion about spindles or Ambien or even sleep, which is that you gotta pay the piper somehow, as they say. That's right. You tweak one thing in the brain, something else, something else goes.
You don't get anything for free. That's. 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, will give you more vigor, et cetera. But it is introducing a sort of second puberty. And puberty is perhaps more rapid phase of aging at the entire lifespan. Same thing people take.
Growth hormone would be a probably better example because certainly those therapies to 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 to kind of sleepiness, but also to enhance cognitive function.
Okay, maybe they 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. Absolutely. Whether or not stimulants or sedatives or sleep drugs.
And that behaviors will always prevail. Behaviors will always prevail as tools. Yep. 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 consequences, as you point out, is that, you know, in order to make one part better, one part of your body, you. 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 spend a lot of time with 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 any studies for lsd? This is kind of a fun one.
No one is expected to know. Against the law, I think. Oh, but there's. So is still cybermen.
There are lots of studies going on when I was growing up, you know, as you. 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 of their LSD journey, where psilocybin tends to be a shorter, 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. That'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 that's 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 in 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 brainwide 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, 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 specifically with regard to connectivity, 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. But then you prune them, right? The second phase is that you 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, the Pruning slows down but doesn't go away. So the cortex thins and so forth. So I think it goes in the opposite direction. I think that as you get older, you're losing connectivity, but you interestingly retain the old memories.
The old memories are really rock solid because they were put in when you were young. 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, you know, looked at the people who, you know, really were benefited the most. It turns out that the peak of the demographic is 25 to 35. Barbara Oakley.
Oakley, yeah, she's, she's really the mastermind. She's a fabulous educator and a background in engineering. But what's going on? So it turns out we aimed our, our MOOC at kids in high school and college because that's their business.
They go every day and they go into work. You have to learn, right? That's their business. But in fact, very few of the students are actually, you know, they weren't taking the course.
Why should they? They spent all day in the class. Right. Why do they want to take another class?
So this is your, the learning to learn class. Learning how to learn. Okay, so you did this with Barbara. So we just.
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 this is not like, you know, filling in for college. This is like topping it off. But you're in the workforce, you have to learn a new skill.
Maybe you have mortgage, maybe you have children, right. You can't afford to go off and take a course, 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 not as your brain is learning as quickly, you can do it more efficiently. This is amazing. I want to take this course. I will take this course.
What, what sort of time commitment is the course? You already said at zero cost, which is amazing. Okay, so it's bite sized videos lasting about 10 minutes each. It was about 50 or 60 over a course of one month.
And are you tested? Are you self tested? Yes, 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 if you have questions. We have TAs.
No, 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.
You'll enjoy it. We have like 98% approval. It's just phenomenal. It's sticky.
Is it math vocabulary? No. Math. No, it's not.
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, you know, we all procrastinate, right?
We put things off. 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 you know, when I was growing up, you had to do your times tables and your division and you know, and then your fractions and your exponents and you know, and they build on one another. And then at some point you take courses where you might need like a graphing calculator to some people. What is this?
But the point being that there were number of things that you had to learn to implement functions. And you learn, you learn by doing, you learn by doing. Likewise 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 know, you'll hear the argument, well, why should somebody learn how to Read a paper. Math.
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. 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 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, calculator didn't eliminate, you know, the education you need to get in math, but it made certain things easier. It's made it possible for you to do more things.
And miraculous, 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. It was a very far.
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 in 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 a procedural system in place. Think 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 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 run electric guitar, they were criticizing people on the acoustic guitar. You know, so we have this generational thing where we look back and say, that's not the real thing. So what are the key fundamentals?
Is really a critical question. Okay, so I'm coming back to that, because this is how you put it at the beginning had to do with whether your. How your brain is allocating resources. Okay.
So when you're younger, you can take in things your brain's 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'm doing it. So, yeah, I'm pretty good at.
I mean, I'm not the biggest account on social media, but for a Science Health account, we're doing okay. And thanks for the audience. This speaks well for the fact that you've managed to break, you know, to go beyond the generation gap, because I type with my thumbs, Terry. That's a manual skill.
New phenomenon. 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, you know, tweets going in. What are they called?
They're not tweets on X. I think they'll call them tweets because you can't. It's hard to verb the letter X. The London thing of that one.
I like X because it's cool. It's kind of black kind of format and fits with kind of the. The, you know, the engineer, like, black X, you know, that 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 cell phone.
I mean, it's unbelievable. You have beautiful sunsets at Salt Institute. We'll put a link to one of them. I mean, it is truly spectacular, awe inspiring to see a sunset.
Every day is different. And everyone's on their phones these days. Sad. And they're looking down at Their phone and walking along.
Even people who are skateboarding. Unbelievable. I mean, it's amazing what human being can do, you know, when they learn, get into something. But what happens is the young generation picks up whatever technology it is and the brain gets really good at it and you can pick it up later.
But you know, not quite as agile, not quite as maybe obsessive. It fatigues me. I will point this out that doing, doing anything on my phone feels fatiguing in a way that reading a paper just write on a laptop or a desktop computer is fundamentally different. I 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 like what's going on in your brain. Why is it? And also I'd like to know from the younger people whether they have the same. I think not.
I think my guess is that they don't feel fatigued because they got into this early enough. And this is actually very, very. I think that has a lot to do with the foundation you put into your brain. In other words, things that you, that you get, 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. You know, I read skateboard magazines and skateboard.
I was never one to really just watch a sport and not play it. So, you know, 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 wasn't designed to do well. There you go. 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.
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My book, Chat GDP and the Future of AI. I went through and I looked at other people's experiences with Chat gdp. I just wanted to know what people were thinking and what. And I came across.
It was an article, I think it was the New York Times of a technical writer who decided to 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, you're 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 being curt? She said, suddenly I started getting better answers by being polite and back and forth away with a human. She's saying, could you please give me information about so and so? I'm really having trouble.
Oh, you know, that answer you gave me was fabulous. It's exactly what I was looking for. And now I need to go on to the next part and help with that too. In other words, why do you talk to a human?
Right? Or is it that she was Talking to the AI to ChatGPT? 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 your. 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 it asks, 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 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 minutes and really just think about how we actually feel about ourselves. Very interesting ideas about locus of self perception and things like that.
I also looked at a really cool video of a baby raccoon popping bubbles while standing on tiny limbs. And that was really cool on social media. Provided me about those things within a series of minutes. And I was thinking myself, this is crazy, right?
The raccoon is now trivial, but it delighted me and that's not trivial. So. 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 as we're dunking, as it's called on Exxon, that it isn't necessarily the way that we learned to argue, it's not necessarily the way that we learned 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 it's kind of great on me because there's almost an action step that isn't allowed. Like you can't fully explain yourself or understand the other person. Right. And I am somebody who, you know, 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 to pass 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 message. And it's very useful for some 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 Barras 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, call me Andy like you do. And he said, andy, how can we get such a rundown of energy as we get older? Why are we more tired today than I was 10 years ago?
I was like, I know how you sleeping. I was like, I got some new line. Ben never slept much in the first place. We 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 a hatch on this notion of a template neural system that then you either find the experience is 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.