David Eagleman is a neuroscientist at Stanford. Support this podcast by supporting our sponsors: 
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EPISODE LINKS:
David's Website: https://www.eagleman.com/
David's Twitter: https://twitter.com/davideagleman
Livewired (book): https://amzn.to/3ba4ezv
Incognito (book): https://amzn.to/3lkNASh

PODCAST INFO:
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Apple Podcasts: https://apple.co/2lwqZIr
Spotify: https://spoti.fi/2nEwCF8
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Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4
Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41

OUTLINE:
0:00 - Introduction
5:05 - Livewired
16:39 - Hardware vs software
25:53 - Brain-computer interfaces
35:12 - 2020 is a challenge for neuroplasticity
46:08 - Free will
50:43 - Nature of evil
58:55 - Psychiatry
1:06:28 - GPT-3
1:13:31 - Intelligence in the brain
1:21:51 - Neosensory
1:31:27 - Book recommendations
1:34:07 - Meaning of life
1:36:53 - Advice for young people

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The following is a conversation with David Eagleman, a neuroscientist and 1 of the great science communicators of our time, exploring the beauty and mystery of the human brain.

He's an author of a lot of amazing books about the human mind, and his new 1 called LiveWired.

LiveWired is a work of 10 years on a topic that is fascinating to me, which is neuroplasticity or the malleability of the human brain.

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As a side note, let me say that the adaptability of the human mind at the biological, chemical, cognitive, psychological, and even sociological levels is the very thing that captivated me many years ago when I first began to wonder how we might engineer something like it in the machine.

The open question today in the 21st century is what are the limits of this adaptability?

As new, smarter and smarter devices and AI systems come to life, or as better and better brain-computer interfaces are engineered, will our brain be able to adapt, to catch up, to excel?

I personally believe yes, that we're far from reaching the limitation of the human mind and the human brain, just as we are far from reaching the limitations of our computational systems.

If you enjoy this thing, subscribe on YouTube, review it with 5 Stars and Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman.

As usual, I'll do a few minutes of ads now and no ads in the middle.

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And now, here's my conversation with David Eagleman.

You have a new book coming out on the changing brain.

Can you give a high level overview of the book?

Yeah, The thing is we typically think about the brain in terms of the metaphors we already have, like hardware and software.

But what's happening in the brain is fundamentally so different.

So I coined this new term liveware, which is a system that's constantly reconfiguring itself physically as it learns and adapts to the world around it.

So it's a liveware, meaning like hardware, but changing.

Well, the hardware and the software layers are blended.

And so, you know, typically engineers are praised for their efficiency and making something really clean and clear, like, okay, here's the hardware layer, then I'm gonna run software on top of it.

And there's all sorts of universality that you get out of a piece of hardware like that that's useful.

But what the brain is doing is completely different.

And I am so excited about where this is all going because I feel like this is where our engineering will go.

So currently we build all our devices a particular way, but I can't tear half the circuitry out of your cell phone and expect it to still function.

So just as an example, kids who are under about 7 years old can get 1 half of their brain removed.

They have a slight limp on the other side of their body, but they can function just fine that way.

Sometimes children are born without a hemisphere.

And their visual system rewires so that everything is on the single remaining hemisphere.

What thousands of cases like this teach us is that it's a very malleable system that is simply trying to accomplish the tasks in front of it by rewiring itself with the available real estate.

How much of that is a quirk or a feature of evolution?

Trillions of organisms had to die to create this thing we have in our skull.

Because you said you kind of look forward to the idea that we might be engineering our systems like this in the future, like creating live wire systems.

How hard do you think is it to create systems like that?

It has proven itself to be a difficult challenge.

What I mean by that is even though it's taken evolution a really long time to get where it is now, all we have to do now is peek at the blueprints.

It's just 3 pounds, this organ, and we just figure out how to do it.

But that's the part that I mean is a difficult challenge because there are tens of thousands of neuroscientists.

We're all poking and prodding and trying to figure this out, but it's an extremely complicated system.

But it's only going to be complicated until we figure out the general principles.

Exactly like if you, you know, had a magic camera and you could look inside the nucleus of a cell and you'd see hundreds of thousands of things moving around or whatever.

And then, you know, it takes Crick and Watts and say, oh, you know, you're just trying to maintain the order of the base pairs and all the rest is details.

Then it simplifies it and we come to understand something.

That was my goal in LiveWire, which I've written over 10 years, by the way, is to try to distill things down to the principles of what plastic systems are trying to accomplish.

But to even just linger, you said it's possible to be born with just 1 hemisphere and you still are able to function.

First of all, just to pause on that, I mean, That's amazing.

I don't know if people quite, I mean, you kind of hear things here and there.

This is why I'm kind of, I'm really excited about your book is I don't know if there's definitive sort of popular sources to think about this stuff.

I mean, there's a lot of, I think from my perspective, what I heard is there's like been debates over decades about how much neuroplasticity there is in the brain and so on, and people have learned a lot of things and now it's converging towards people that are understanding this much more in Europe, much more plastic than people realize.

But just like linger on that topic, like how malleable is the hardware of the human brain?

Maybe you said children at each stage of life.

I think part of the confusion about plasticity has been that there are studies at all sorts of different ages, and then people might read that from a distance and they think, oh, well, Fred didn't recover when half his brain was taken out.

And so clearly you're not plastic, but then you do it with a child and they are plastic.

And so part of my goal here was to pull together the tens of thousands of papers on this, both from clinical work and from, you know, all the way down to the molecular and understand what are the principles here.

The principles are that plasticity diminishes, that's no surprise.

By the way, we should just define plasticity, it's the ability of a system to mold into a new shape and then hold that shape.

That's why we make things that we call plastic because they are moldable and they can hold that new shape like a plastic toy or something.

And so maybe we use, maybe we'll use a lot of terms that are synonymous.

So something is plastic, something is malleable, changing, live wire, the name of the book is like.

So I'll tell you, exactly right, but I'll tell you why I chose live wire instead of plasticity.

So I use the term plasticity in the book, but sparingly.

Because that was a term coined by William James over a hundred years ago.

And he was of course very impressed with plastic manufacturing, that you could mold something in shape and then it holds that.

But that's not what's actually happening in the brain.

It's constantly rewiring your entire life.

The whole point is for it to keep changing.

So even in the few minutes of conversation that we've been having, your brain is changing, my brain is changing.

Next time I see your face, I will remember, oh yeah, like that time Lex and I sat together and we did these things.

I wonder if your brain will have a Lex thing going on for the next few months.

Like it'll stay there until you get rid of it.

Yeah, no, I'll probably never get rid of it.

Let's say for some circumstance, you and I don't see each other for the next 35 years.

When I run into you, I'll be like, oh yeah.

And we sat down for a podcast back when there were podcasts.

Back when we lived outside virtual reality.

Exactly, because plastic implies, I mean, it's the term that's used in the field and so that's why we need to use it still for a while.

But yeah, it implies something gets molded into shape and then holds that shape forever.

But in fact, the whole system is completely changing.

Then back to how malleable is the human brain at each stage of life.

So what, just at a high level, is it malleable?

But 1 of the things that I felt like I was able to put together for myself after reading thousands of papers on this issue is that different parts of the brain have different plasticity windows.

So for example, with the visual cortex, that cements itself into place pretty quickly over the course of a few years.

And I argue that's because of the stability of the data.

In other words, what you're getting in from the world, you've got a certain number of angles, colors, shapes.

You know, it's essentially the world is visually stable.

As opposed to, let's say the somatosensory cortex, which is the part that's taking information from your body or the motor cortex right next to it, which is what drives your body.

You get taller over time, you get fatter, thinner over time.

You might break a leg and have to limp for a while, stuff like that.

So because the data there is always changing, and by the way, you might get on a bicycle, you might get on a surfboard, things like that.

Because the data is always changing, that stays more malleable.

And when you look through the brain, you find that it appears to be this, how stable the data is determines how fast something hardens into place.

But the point is different parts of the brain harden into place at different times.

Do you think it's possible that depending on how much data you get on a different sensors, that it stays more malleable longer?

So like, you know, if you look at different cultures that experience, Like if you keep your eyes closed, or maybe you're blind, I don't know, but let's say you keep your eyes closed for your entire life, then the visual cortex might be much less malleable.

The reason I bring that up is like, maybe we'll talk about brain-computer interfaces a little bit down the line, but, you know, like, is this, is the malleability a genetic thing or is it more about the data, like you said, that comes in?

Ah, so the Malleability itself is a genetic thing.

The big trick that mother nature discovered with humans is make a system that's really flexible as opposed to most other creatures to different degrees.

So if you take an alligator, It's born, its brain does the same thing every generation.

If you compare an alligator 100,000 years ago to an alligator now, they're essentially the same.

We, on the other hand, as humans, drop into a world with a half-baked brain and what we require is to absorb the culture around us and the language and the beliefs and the customs and so on.

That's what Mother Nature has done with us.

And it's been a tremendously successful trick we've taken over the whole planet as a result of this.

I mean, just to linger on it, that I mean this is a nice feature, like if you were to design a thing to survive in this world, do you put it at age 0, already equipped to deal with the world in a like hard-coded way, or do you put it, do you make it malleable and just throw it in, take the risk that you're maybe going to die, but you're going to learn a lot in the process, and if you don't die, you'll learn a hell of a lot to be able to survive in the environment.

So this is the experiment that Mother Nature ran, and it turns out that, for better or worse, we've won.

I mean, we put other animals into zoos and we, yeah.

And maybe what the trick Mother Nature did is just the stepping stone to AI.

So that's a beautiful feature of the human brain, that it's malleable, but let's, on the topic of mother nature, what do we start with?

What it's, terrific engineering that's set up in there, but much of that engineering has to do with, okay, just make sure that things get to the right place.

For example, like the fibers from the eyes getting to the visual cortex or all this very complicated machinery in the ear getting to the auditory cortex and so on.

And then what we also come equipped with is the ability to absorb language and culture and beliefs and so on.

So no matter what you're exposed to, you will absorb some sort of language.

That's the trick is how do you engineer something just enough that it's then a sponge that's ready to take in and fill in the blanks?

How much of the malleability is hardware?

So there's like, there's neurons, there's synapses, and all kinds of different synapses, and there's chemical communication, like electrical signals, and there's chemical communication from the synapses.

What, I would say, the software would be the timing and the nature of the electrical signals, I guess, and the hardware would be the actual synapses.

This is why I really, if we can, I wanna get away from the hardware and software metaphor because what happens is as activity passes through the system, it changes things?

Now, the thing that computer engineers are really used to thinking about is synapses, where 2 neurons connect.

Of course, each neuron connects with 10,000 of its neighbors.

But at a point where they connect, what we're all used to thinking about is the changing of the strength of that connection, the synaptic weight.

The receptor distribution inside that neuron so that you're more or less sensitive to the neurotransmitter, then the structure of the neuron itself and what's happening there, all the way down to biochemical cascades inside the cell, all the way down to the nucleus, And for example, the epigenome, which is the, you know, these little proteins that are attached to the DNA that cause conformational changes that cause more genes to be expressed or repressed, all of these things are plastic.

The reason that most people only talk about the synaptic weights is because that's really all we can measure well.

And all this other stuff is really, really hard to see with our current technology.

But in fact, the system is plastic at all these different levels.

And my way of thinking about this is an analogy to pace layers.

So pace layers is a concept that Stuart Brand suggested about how to think about cities.

So you have fashion, which changes rapidly in cities.

You have governance, which changes more slowly.

You have the structure, the buildings of a city, which changes more slowly, all the way down to nature.

You've got all these different layers of things that are changing at different paces, at different speeds.

I've taken that idea and mapped it onto the brain, which is to say you have some biochemical cascades that are just changing really rapidly when something happens, all the way down to things that are more and more cemented in there.

And this is actually, this actually allows us to understand a lot about particular kinds of things that happen.

For example, 1 of the oldest, probably the oldest rule in neurology is called Ribo's Law, which is that older memories are more stable than newer memories.

So when you get old and demented, you'll be able to remember things from your young life.

Maybe you'll remember this podcast, but you won't remember what you did a month ago or a year ago.

And this is a very weird structure, right?

No other system works this way, where older memories are more stable than newer memories.

But it's because through time, things get more and more cemented into deeper layers of the system.

And so this is, I think, the way we have to think about the brain, not as, okay, you've got neurons, you've got synaptic weights and that's it.

So yeah, so the idea of liveware and livewired, is that it's like a, it's a gradual, yeah, it's a gradual spectrum between software and hardware.

And so the metaphors completely doesn't make sense.

Cause like when you talk about software and hardware, it's really hard lines.

I mean, of course software is unlike hard, but even hardware, but like, so there's 2 groups, but in the software world, there's levels of abstractions, right?

There's the operating system, there's machine code, and then it gets higher and higher levels.

But somehow that's actually fundamentally different than the layers of abstractions in the hardware.

But in the brain, it's all like the same.

I mean, yeah, it's kind of mind-blowing because it's hard to know what to think about that.

Like if I were to ask the question, this is an important question for machine learning, is how does the brain learn?

So essentially you're saying that, I mean it just learns on all of these different levels at all different paces.

And as a result, what happens is as you practice something, you get good at something, you're physically changing the circuitry, you're adapting your brain around the thing that is relevant to you.

So let's say you take up, do you know how to surf?

Now at this age, what happens is, you know, you'll be terrible at first, you don't know how to operate your body, you don't know how to read the waves, things like that.

And through time, you get better and better.

What you're doing is you're burning that into the actual circuitry of your brain.

You're of course conscious when you're first doing it, you're thinking about, okay, where am I doing?

But eventually when you become a pro at it, you are not conscious of it at all.

In fact, you can't even unpack what it is that you did.

You're changing your balance when you come, you know, you do this to go to a stop and stuff.

So this is what we're constantly doing, is actually shaping our own circuitry based on what is relevant for us.

Survival, of course, being the top thing that's relevant.

But interestingly, especially with humans, we have these particular goals in our lives, computer science, neuroscience, whatever.

And so we actually shape our circuitry around that.

I mean, you mentioned this gets slower and slower with age, but is there, like I've, I think I've read and spoken offline, even on this podcast with a developmental neurobiologist, I guess would be the right terminology, is like looking at the very early, like from embryonic stem cells to the creation of the brain.

That's mind blowing how much stuff happens there.

And then, but after that, at which point does it stop being malleable?

So that's the interesting thing, is that it remains malleable your whole life.

So even when you're an old person, you'll be able to remember new faces and names, you'll be able to learn new sorts of tasks, and thank goodness, because the world is changing rapidly in terms of technology and so on.

I just sent my mother an Alexa and she, you know, figured out how to go in the settings and do the thing.

And I was really impressed by that, that she was able to do it.

So there are parts of the brain that remain malleable their whole life.

The interesting part is that really your goal is to make an internal model of the world.

Your goal is to say, okay, the brain is trapped in silence and darkness, and it's trying to understand how the world works out there, right?

You forget, it's like this lonely thing is sitting in its own container and trying to actually throw a few sensors, figure out what the hell's going on.

You know what I sometimes think about is that movie The Martian with Matt Damon.

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David Eagleman: Neuroplasticity and the Livewired Brain | Lex Fridman Podcast #119