November 20, 2023 • 58 mins
f you look at a brain, how can you immediately tell if it belongs to a piano player or a violinist? How can a dog learn how to walk on its rear legs? And what does this have to do with expertise, or the good news about the brains of digital natives, or how governments respond to change just like brains do? While we all like to talk about brain plasticity, the truth is that most of what happens in your life makes no meaningful change to your brain. So what’s the difference between the stuff that sticks and the stuff that doesn’t?
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Episode Transcript
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Speaker 1 (00:05):
If you take a look at a brain, how can
you tell immediately if it belongs to a piano player
or a violinist? How can a dog learn to walk
on its rear legs like a human? And what does
this have to do with how you become an expert
at something? Or what would happen if Venus and Serena
(00:25):
Williams had a hypothetical brother, Fred who hated tennis? And
how do governments respond to change just like brains do?
And finally, why am I so optimistic about the brains
of digital natives. Welcome to the inner Cosmos with me
(00:46):
David Eagleman. I'm a neuroscientist and author at Stanford and
in these episodes we sail deeply into our three pound
universe to understand why and how our lives look.
Speaker 2 (00:58):
The way they do.
Speaker 1 (01:08):
Today's episode is about brain plasticity, which is the ability
of the brain to change and adapt throughout your life.
The word plasticity comes from the word plastic, which is
a material that you can mold into any shape and
then it holds onto that shape. And that is what
is impressive about brains. You can expose them to any
(01:30):
kind of situation or experience, and they hold on to
the change. The vast forest of neurons in your head,
These connections change their strength, and sometimes they unplug and
they seek around and they replug in somewhere else. It's
a living forest of eighty six billion neurons in your head,
(01:51):
and this constant reconfiguration, this is how you learn and remember.
The interesting part I want to address today is exactly
when these changes in the brain happened, because it's not
all the time. Most of the stuff that happens in
your life makes no change at all to your brain.
(02:12):
So what's the difference between the stuff that sticks and
the stuff that doesn't. So let's start today in Hungary
with an educational psychologist named Laslow Polgar. The thing about
Laslow is that he loves chess, and he's written some
well known chess books. But that's not the super interesting
thing about him. The super interesting thing is that he
(02:33):
got very interested in the theory of child rearing and
he believed quote, geniuses are made, not born. So he
started preparing himself for fatherhood even before he had a spouse,
and he read the biographies of four hundred famous intellectuals
like Socrates and Einstein, and he noted that what they
(02:55):
all had in common is they started their intellectual pursuits
at a young age and they studied intensively. So he
concluded from this research the idea that he could, with
the right effort, turn his future children into geniuses in
a particular area which he and his wife could think
(03:16):
about and pick. So they considered various domains, but they
chose chess in part because the success of these children
could be easily measurable with chess. So he and his
wife had three daughters together, Susan, Sophia and Judete, and
he made the move, which was unusual in Hungary at
the time, to homeschool them, and he taught them German
(03:39):
and English and Russian and high level math, but he
primarily taught them chess from the moment that they were
big enough to play with the pieces.
Speaker 2 (03:49):
So what was the result.
Speaker 1 (03:51):
By the time his eldest daughter, Susan turned fifteen years old,
she was the top ranked chess player in the world.
In nineteen teen eighty six, she qualified for the men's
World Championship, which was a first time achievement for a female,
and within five years she had earned the men's Grand
Master title and then in the middle of Susan's astounding accomplishments,
(04:14):
Her fourteen year old middle sister, Sophia, achieved fame for
her sack of Rome, which was her stunning victory at
a tournament in Italy, which ranked as one of the
strongest performances ever by a fourteen year old. Sofia went
on to become an international master and a woman grand master.
Speaker 2 (04:35):
And then there was.
Speaker 1 (04:36):
The youngest sister, Judite, who is widely considered the best
female chess player on record. She achieved grand master status
at the tender age of fifteen years and four months,
and she remains the only woman on the World Chess
Federation's Top one hundred list, and for a while she
held a position in the top ten. So what accounts
(04:58):
for their success, Well, their parents trained the girls every
single day. They didn't just expose them to chess, they
fed them on chess.
Speaker 2 (05:07):
The girls received hugs.
Speaker 1 (05:10):
And stern looks and approval and attention based on their
chess performance, and as a result, their brains came to
have a great deal of circuitry devoted to chess. Now,
we've seen in other episodes how the brain is always
rewriting itself in response to its inputs. But the fact
(05:32):
is that not all information streaming into the pipelines is
equally important. How brains adjust themselves has everything to do
with what you're spending your time on, and that's why
the Polgar sisters became biological chess machines. And it's the
same thing with your brain. It'll reconfigure to whatever you're doing.
(05:56):
So if you decide to make a career change to ornithology,
the study of birds, more of your neural resources will
become devoted towards learning the subtle differences between birds, like
their wing shape, or their breast coloration, or their beak size,
while maybe previously your neural representation of birds with something
(06:21):
more crude, like is that a birder and airplane. So
let's dive in to unpack how the brain makes changes
and when it doesn't, which will tell us everything we
need to know about how to make changes stick in
your own brain. There's a great story about the violinist
Yetsak Pearlman after one of his concerts and admiring concertgoer
(06:45):
said to him, I would give my life to play
like that, and Pearlman said, I did, Now what did
he mean? Well, every morning, Pearlman drags himself out of
bed at five point fifteen. He takes a shower and batakfast,
and then digs into his four and a half hour
morning practice. He then takes a lunch and an exercise session,
(07:08):
and then launches his afternoon practice for another four and
a half hours. He does this every day of the year,
except for concert days, when he does only the morning
practice session. And you know what, Brain circuitry comes to
reflect what you do. So the cortex of Jasah Pearlman,
(07:28):
or any highly trained musician changes through time into something different.
And this isn't a metaphorical claim. You can see this
with brain imaging, even with an untrained eye.
Speaker 2 (07:41):
Let me tell you how.
Speaker 1 (07:42):
If you look at the strip of brain right underneath
where you wear headphones, that's an area called the motor cortex,
and that's what directs your body how to move all
of its six hundred exquisitely beautiful muscles. Now, if you
zoom in on a region of the cortex involved in
hand movement, you'll find something amazing, which is that musicians
(08:06):
have a little puckered shape on their cortex where non
musicians don't. So think of it like an extra wrinkle
on the wrinkly outer bit of the brain, the cortex.
Speaker 2 (08:17):
Why do the musicians have this.
Speaker 1 (08:19):
It's because they use the muscles of their hands in
an extraordinarily detailed way, much more so than non musicians,
so their.
Speaker 2 (08:29):
Brains devote more real estate to that task.
Speaker 1 (08:33):
The thousands of hours of practice on the instrument physically
molds their brains. And by the way, this is wildly specific.
So imagine that you compare the brain of a violinist
like Pearlman to the brain of a pianist like Vladimir Ashkenazi.
What they both have in common is a deep dedication
(08:56):
to their craft and countless hours of practice, and yet
their brains look sufficiently different that you can easily see
which brain belongs to whom. And that's because string players
like Pearlman show that extra wrinkle mostly on one side
and one hemisphere, because his left fingers are doing all
(09:17):
the detailed work while the right hand mostly just runs
the bow over the strings. In contrast, a pianist like
Ashkenazi has that extra wrinkle in both hemispheres because both
of his hands are performing meticulous patterns on the ivories.
So simply by looking at the brain which used to
(09:38):
be done in autopsy, but now you can do with
a brain scan. You can tell what kind of musician
you have in the scanner. You can discern this just
by looking at the wrinkly bits on the motor cortex.
Speaker 2 (09:51):
And we can read even more from the brain's patterns.
Speaker 1 (09:55):
It represents not only that a hand is doing less
or more, but sometimes what what in particular it's doing.
So let's say you get a job at an assembly
line and you're randomly assigned to one of two jobs.
Either you put little marbles into jars, or your job
is to screw the jar lid shut. Okay, so both
(10:16):
jobs use your right hand, but the first requires fine
use of your fingertips, while screwing the lid on makes
use of your wrist and forearm. So if you're the
jar filler, the real estate in your cortex that represents
your fingers will increase, and this is at the expense
(10:36):
of the real estate devoted to your wrists and forearms.
If you are the lid turner, the opposite happens. You
get more representation for your wrist and forearm and less
for the detailed movement of your fingers. So in this way,
what you do over and over becomes reflected in the
structure of your brain, and these changes involve more than
(11:00):
the motor cortex.
Speaker 2 (11:01):
For example, if.
Speaker 1 (11:02):
You spend months learning to read Braille, the bit of
your cortex that represents touch from the index finger that
will grow. If you take up juggling as an adult,
the visual areas of your brain involved in that they increase.
This is because brains reflect not simply the outside world,
(11:23):
but more specifically your outside world, and this is what
underlies getting good at something. Professional tennis players like Serena
and Venus Williams they spend years training so that the
right moves will come automatically in the heat of the game. Step, pivot, backhand, charge, fallback, aim, smash.
Speaker 2 (11:48):
They train for.
Speaker 1 (11:49):
Thousands of hours to burn the moves down into the
unconscious circuitry of the brain. They craft their brains into
overtrained machinery. He might have heard of the ten thousand
hour rule, which suggests that you need to practice a
skill for that many hours to become an expert, whether
this is surfboarding or spelunking, or saxophone playing or whatever.
(12:13):
Although we can't quantify the exact number of hours, the
general idea is correct. You need massive amounts of repetition
to dig the subway maps of the brain. There's a
guy that I mentioned in an earlier episode. His name
is Destin Sandlin, and he made a video where he
tries to ride a bike that someone gave him with
(12:35):
reversed steering, so when you push the handlebars to the left,
the wheel turns to the right and vice versa. This
is a super difficult thing to learn how to ride.
So what he did is he spent every day working
on this and trying it out, and he crashed and crashed,
but eventually he got it. But the point I want
(12:56):
to make here is that you know, he's an engineer,
and it only took him a few seconds to cognitively
understand how the bike worked, but that proved insufficient to
ride it. He needed to invest weeks and weeks of practice.
Speaker 2 (13:13):
Hence the ten thousand hour rule.
Speaker 1 (13:17):
And this dynamic changing of the brain happens from intensive
physical practice that you do, whether that's swimming or playing
the harmonica, or swinging a tennis racket or using a
rake or whatever. But these measurable brain changes, they don't
just apply to the physical they apply to the mental also,
so for example, when medical students study for their final
(13:39):
exams over the course of three months, particular areas of
their cortex changed so much that you can see this
on brain scans with the naked eye. And you see
something similar if you teach a person how to read
backward through a mirror. And here's another example. Areas of
the brain that are involved in spatial navigation are visibly
(14:04):
different in London taxi drivers from the rest of the population.
In each hemisphere, the taxi drivers have an enlarged region
part of the hippocampus, which is an area involved in
your internal maps of the outside world. So what you
(14:38):
spend your time on changes your brain. You are more
than what you eat. You become the information you digest.
And this is how the Polgar sisters were able to
blossom into world champion chess players. It's not because some
gene codes for skill at chess. It's because they practiced
(14:59):
over and over chiseling pathways in their brains to encode
the powers and patterns of knights and rooks and bishops
and ponds and kings and queens. So brains come to
reflect their world.
Speaker 2 (15:14):
But how does this happen? Exactly. Well, let's see the.
Speaker 1 (15:17):
Answer by zooming in on a weird illusion that most
of us have experienced, the phantom phone vibration. I recently
saw a meme online. It was a picture of a
human brain with the title that reads, Hey, I think
your phone just buzzed in your pocket, and then on
the bottom it reads, just kidding. Your phone isn't even
in your pocket, you moron. Now, the phantom cell phone
(15:41):
vibration is a menace that is unique to the twenty
first century. It happens because of a momentary spasm or
quivering or shaking, or a touch on your leg, And
as long as the frequency and the duration of that
feeling is vaguely similar to that made by your phone,
your brain decides on your behalf, that's something interesting is
(16:04):
happening with your phone. So thirty years ago, if you
had noticed a leg twitch, you would have interpreted the
feeling as a fly landing on you, or a movement
of your clothing, or something accidentally brushing past you. So
why does your interpretation differ from one generation to the next,
(16:26):
Because your phone now serves as the optimal explanation for
a whole range of twitchy feelings. So here's how to
understand what's happening there in the brain. Think of a
mountainous landscape. Now, picture a lake somewhere there that's encircled
by mountains. For a rain drop to end up in
(16:48):
that lake, it doesn't need to fall from the sky
and land directly in the water. Instead, it only needs
to hit the surrounding hillsides. It can land on the
northern slope or the southern, or the eastern incline or
the western and in any case it's gonna slide down into
the lake. So the lake is what's known as an
(17:10):
attractor state. Anything nearby will flow to that spot, and
you have lots of such attractor states in your brain.
So the feeling on your thigh doesn't have to be
a buzzing phone.
Speaker 2 (17:24):
It can be a slight shift.
Speaker 1 (17:26):
Of your genes or a twitch of your thigh muscle,
or an itch or graze past the sofa.
Speaker 2 (17:33):
As long as the feeling is close, the signals.
Speaker 1 (17:37):
Slide down the landscape to their attractor state, and then
you reach to check for an important message. The landscape
gets formed by what is important in your world. For
another example, think about the way we interpret the sounds
of language. It feels natural to you that you can
(17:58):
understand the sounds of your native language, but foreign languages
often have really close sounds that you can't hear the
difference between.
Speaker 2 (18:07):
Like ooh and eh. But why why can you not
hear those?
Speaker 1 (18:13):
As it turns out, there is something different about the
brains of the people who speak those languages. But they
weren't born that way, and neither were you. If you
look at the space of all the possible sounds that
humans can make with our mouths, it makes a relatively
smooth continuum. You can kind of make any sound. But
(18:34):
despite this, you learn from experience that specific sounds mean
the same thing, whether they're uttered by your dad, or
your babysitter or your teacher. Your brain figures out that
a drawn out E and eclip to e both belong
to the E category, or maybe your friend from Texas
(18:55):
says a or whatever. But your experience teaches you that
all the speakers mean the same sound, regardless of exactly
how they're pronouncing it, and so your neural networks carve
out a landscape in which all these sounds roll down
the hillsides to the same interpretation. There's a lake in
(19:16):
your brain that represents E, and all the inputs from
all around end up in that lake and in neighboring valleys,
you gather up sounds that are equivalent to A or
I or O and so on. So with time, your
landscape looks different from someone who's grown up in another
(19:37):
language and who needs to distinguish the smooth continuum of
sounds differently than you do. To think about an example
of this, imagine a baby born in Japan call him Hyato,
and a baby born in America call him William. From
their brain's point of view, there is nothing different about them.
(19:59):
But in Osaka, Hayato hears Japanese all around him.
Speaker 2 (20:04):
From day one.
Speaker 1 (20:05):
In Palo Alto, William hears the tones of English, where
different sounds carry meaning. An example of what these two
babies hear differently is the distinction between the.
Speaker 2 (20:17):
R and L sounds.
Speaker 1 (20:19):
So in English, these carry information like the word right
versus light or raw versus law, But in Japanese there's
no distinction between these two sounds. So as a result,
William's internal landscape builds a mountain range between his interpretation
of R and L, such that the difference between these
(20:44):
two sounds is perceptually clear. In Hyato's brain, the landscape
develops into a big valley, so that both R and
L flow into a single lake because they have an
identical interpretation. So as a result, Hyato can't hear the
difference between those two sounds. Now, obviously, the children's brains
(21:08):
were not born this way. Had William's pregnant mother moved
to Osaka and Hyato's pregnant mother to Palo Alto, the
boys would have had no trouble in becoming fluent speakers
and listeners in their new language.
Speaker 2 (21:21):
As opposed to a genetic issue.
Speaker 1 (21:24):
Their neural landscapes are carved by what is relevant in
their immediate environment. And what's fascinating is that you can
see this carving happening even before the children learn how
to speak. For example, make a continuous R sound and
then switch it over to L. So L, now, how
(21:47):
can you tell if an infant here's that change?
Speaker 2 (21:51):
So it turns out the trick.
Speaker 1 (21:53):
To the experiment is this, Infants will suck faster at
the nipple when they detect a chain. When they hear
a change from one sound to another sound, they go
from suck suck suck to suck suck, suck, suck. So
at the age of six months, both Hyato and William
will both suck faster when the R changes to L.
(22:15):
But by twelve months, Hyato stops detecting the change. R
and L sound the same to him. Both sounds are
sliding down into the same valley. Hyato's brain has lost
the ability to distinguish these sounds, while William's brain, having
passively listened to his parents speak tens of thousands of
(22:36):
English words, has learned that there's information carried in the
difference between these two sounds. Hyato's brain, meanwhile, has picked
up on other sound distinctions, which to William would be indistinguishable.
So your auditory system begins universally and then wires itself
(22:57):
to maximize the distinction unique to your language, depending on
where on the planet you happened to stick your head
out of the womb. And similarly, the buzzing phone isn't
something you were born to detect. Instead, it's high relevance
carves your neural landscape such that you have a broad
(23:19):
catch all for neighboring sensations, all of which you will
interpret as a buzzing cell phone in your pocket. Like kyata.
With the R and the L, you combine the twitches
and vibrations and quiverings into a single interpretation of what
just happened. Now, from what we've seen so far, we
might think that repetition is the key to molding the
(23:43):
circuitry in your brain. But in fact, there's a deeper
principle at work. So now we're going to talk about relevance.
There's an old joke that goes, how many psychiatrists does
it take to change a light bulb? And the answer
is only one, But the light bulb has to want
to change. Now, if you listen to episode two, you
(24:05):
may remember a dog that I talked about named Faith.
She is very memorable because Faith was born with out
front legs and she figured out how to walk by
pedaly on her hind legs, sort of like a human.
Speaker 2 (24:18):
Now.
Speaker 1 (24:18):
When I told her story in episode two, I said
it as though her brain had just figured out her
unusual body plan. But we can now dig a little
deeper for a hidden bone. Was there something special about Faith?
Could any dog have pulled us off? And if they
could have, why don't all dogs walk by?
Speaker 2 (24:37):
Peeda Ly?
Speaker 1 (24:39):
Faith's rewritten maps were all about relevance to her life.
Her brain was shaped by her goals. Faith needed to
get to her food. That required a solution. It wasn't
going to be the same one that was used by
her four legged siblings. She had to derive a novel solution,
(24:59):
so her brain tried out various strategies until it found
when that worked balancing on her two back legs and
lurching forward step after step. This allowed her to get
what she needed, and after a while, she became good
at this method of locomotion. In the absence of finding
an answer to her challenge, she would have starved and died.
(25:22):
Her drive for survival allowed the flexible circuitry in her
brain to try out a bunch of hypotheses and solve
the problem getting her to food and shelter and loved ones.
Speaker 2 (25:35):
So goals matter.
Speaker 1 (25:37):
A brain's goals play a critical role in how and
when it changes. For the Polgar sisters, achieving their expertise
depended on a desire to achieve their expertise. Same with
Yitzak Pearlman or Vladimir Ashkenazi. Imagine for a moment that
Serena and Venus Williams had a brother, Fred, and that
(26:02):
their parents had put a tennis racket in Fred's hands
and forced him to go through all the years of
practicing that his sisters went through. But imagine that he
found tennis repulsive. He never got good feedback from his
classmates about his performances, and he didn't win any contests,
and his elders didn't lavish him with praise. The result
(26:24):
of all that practice would be nothing. Fred's brain would
show little reorganization. Although his body was going through the
same motions as his sisters, the motions would be misaligned
with his internal incentives. So this is easily shown in
the laboratory. So imagine an experiment in which someone is
(26:47):
tapping out Morris code on your foot while someone else
totally separately is playing a sequence of sounds.
Speaker 2 (26:55):
Now, if the.
Speaker 1 (26:56):
Task is that you can win cash for decoding the
message on your foot, then the brain regions involved in
touch to that part of your body will develop higher resolution.
The regions involved in your hearing won't change, even though
that brain area is also receiving stimulation. Now imagine the
(27:17):
reverse game. Now, answering questions about subtle differences between the
sounds earns the cash while attending to your foot doesn't
yield anything. Now we'll see changes in the auditory cortex
where you're doing the hearing, but the touch in your
somatosensory cortex won't change. The inputs from the world are
(27:39):
exactly the same in both cases. But what changes in
your brain depends on what is rewarded. And this is
why Fred Williams gets no better on the tennis court.
He derives no reward from it. In his brain, just
like in yours, the maps of the neural territory reflect
(28:00):
to the strategies that have won positive feedback. Now this
kind of understanding about motivation and relevance leading to change
in the brain. This understanding opens new pathways for recovery
from brain damage. So imagine that a friend of yours
suffers a stroke. That damage is part of her motor cortex,
(28:21):
and as a result, one of her arms becomes mostly paralyzed.
So after trying many times to use her weakened arm,
she gets frustrated and just uses her good arm to
accomplish all the necessary tasks in her daily routine. This
is a typical scenario, and her weak arm becomes only
weaker because she's never choosing to use it. Now, the
(28:45):
lessons of brain plasticity that we've been talking about offer
a solution that is counterintuitive. The solution is known as
constraint therapy. You strap down her good arm so that
she can't use it, and that forces her to employ
the weak arm. Now, this simple method retrains the damaged
(29:09):
cortex by forcing use of the bad arm and cleverly
taking advantage of these neural mechanisms underlying desire and reward.
Because she has inherent motivation to get the sandwich to
her mouth, or to turn the key in her front door,
or to raise the cell phone to her ear, and
(29:30):
to perform all the other actions that underlie a dignified,
self sufficient life. So while constraint therapy starts off as frustrating,
the approach proves to be the best medicine because it
forces the brain to try new strategies, and the reward
locks in the methods that work. It seems paradoxical that
(29:54):
the solution of the problem is to make things worse,
but that's precisely what solves. So let's return to faith
the dog. Are all dogs able to walk on their
back legs? Sure, but most dogs will never have the
reason or motivation to attempt it, and certainly no reason
(30:15):
to master it. And that's why Faith became famous, not
because she's the only dog in the world who could
do it, but because she's the only one who made
it happen. You may know that some blind people learn
how to navigate using echolocation. They make sounds with their
mouth and they listen for the echo to give them information.
(30:37):
But it turns out that people with perfectly normal vision
can learn how to echo locate. Also, the issue is
just that most cited people simply are insufficiently motivated to
pour the hours and hours into redefining their neural territory. Now,
reward is a powerful way to rewire the brain, but happily,
(31:01):
your brain doesn't require cookies or cash. More generally, change
is tied to anything that's relevant to your goals. If
you're in the far North and you need to learn
about ice fishing and different types of snow, that's what
your brain will come to encode. If instead your equatorial
and you need to learn which snakes to avoid and
(31:23):
which mushrooms to eat, your brain will devote its resources accordingly.
Using relevance as it's north star, the brain flexibly picks
up on important details. It's billions of neurons serve as
a colossal canvas for painting the world that we happen
(31:44):
to find ourselves in, and with it we develop expertise
and whatever has relevance to us, whether that's basketball or
theater or badminton or Greek classics or cliff jumping or
video gaming or line dancing or wine making. Whenever a
task is roughly aligned with our larger goals, our brain.
Speaker 2 (32:06):
Circuitry comes to reflect that.
Speaker 1 (32:10):
Now, with how brains rewire based on what's relevant, I
realized really interesting analogy some years ago. Governments do the
same thing. They continually self design based on what's happening
in the nation. So just look at what happened. In
response to the attacks of September eleventh, two thousand and one,
(32:30):
the United States government altered its structure. It established the
Department of Homeland Security, which absorbed and restructured twenty two
existing agencies, And the same thing happened with the simmering
Cold War. This initiated a large shift in nineteen forty seven,
which spawned the Central Intelligence Agency, and in a thousand
(32:51):
small ways, a government subtly mirrors the current aims of
a nation and the events of its outside world. So
you have budgets swelling and shrinking to echo priorities when
external threats loom. The military pocketbook expands when peacetime follows.
(33:12):
Social initiatives gain. Just like brains, nations respond to changing
situations by shifting their resources and redrawing their organizational charts
to meet the challenges that they face. So how does
the brain know when something important has happened and that
(33:33):
it should change its wire accordingly. Well, one strategy is
to turn on plasticity when events in the world are correlated.
So the idea here is to just encode only those
things that co occur, Like you see a cow and
you hear a move, and in this way related events
(33:55):
become bound together in the brain tissue. Now, you generally
don't want to implement these changes too quickly, because sometimes
there are associations that are spurious.
Speaker 2 (34:06):
You might see a cow.
Speaker 1 (34:08):
But you hear the bark of an unrelated dog, and
you wouldn't want your brain to permanently store every accidental cooccurrence.
Speaker 2 (34:16):
So the brain solution is to change slowly, just a
little at a time.
Speaker 1 (34:22):
And in that way it comes to encode only those
things that commonly coincide real matches distinguish themselves from noise
by occurring together over and over and over. But despite
the wisdom of slow and steady change extracting averages like this,
that's not the whole story. Because just think about one
(34:44):
trial learning in which you, let's say, touch a hot
stove and you learn not to do that again. So
you've got emergency mechanisms that exist to make sure that
life threatening or limb threatening events are permanently retained. The
story of one trial learning goes deeper than that. Think
about when you were young and your aunt taught you
(35:06):
a new word. She says, this is called a pomegranate. Now,
you didn't need to learn that in an emergency situation,
and you didn't need your aunt to say this association
one hundred times. She calmly told you once, and you
got it in one trial. Why It's because it was
(35:26):
salient to you. You loved your aunt, and you derived
social benefit from knowing a new word and being able
to ask for the delicious fruit. This is one trial
learning not because of threat, but instead because of relevance.
Speaker 2 (35:43):
Inside the brain.
Speaker 1 (35:45):
This relevance is expressed through these widely reaching systems that
release chemicals called neuromodulators. By releasing these with high specificity,
these chemicals allow changes to occur only at specific places
and times instead of all over at every moment. An
especially important chemical messenger here is called acetylcholine.
Speaker 2 (36:09):
Neurons that release the.
Speaker 1 (36:10):
Seedlcholine are driven by both reward and punishment, and they're
active whenever you're learning a new task and need to
make changes, but they're not active once the task is
well established.
Speaker 2 (36:22):
So here's what you need to know.
Speaker 1 (36:24):
The presence of acetylcholine at a particular brain area tells
it to change, It doesn't tell it how to change.
In other words, when the neurons that spit out acetal
coline are active, they simply increase plasticity in the target areas.
When they are not active, there's little or no plasticity.
(36:44):
So here's an example. Imagine I play for you a
particular note on the piano, say D flat. The note
triggers activity in your auditory cortex, but it doesn't change
anything about how much territory is devoted to D flat.
Speaker 2 (37:05):
Why not?
Speaker 1 (37:06):
It's because the note doesn't mean anything in particular to you. Now,
let's say every time I play the note, I give
you a warm chocolate chip cookie. Now the note accrues
a meaning, and the brain territory devoted to D flat expands.
Your brain assigns more real estate to that frequency because
(37:27):
the presence of reward suggests it's important. Now, let's say
I don't have any cookies available, so instead of handing
you the treat, I play the D flat. At the
same moment that I stimulate neurons in your head that
release a setal colin. The cortical representation for that tone expands,
(37:49):
just like it did with the cookies. Your brain allocates
more terrain to that frequency because the presence of the
acetyl coline indicates that it must be important. So a
setyl colin broadcasts widely throughout the brain, and as a result,
it can trigger changes with whatever kind of relevant stimulus,
(38:09):
whether that's a musical note or a texture or something verbal.
It's a universal mechanism for saying this is important. Get
better at detecting this. It marks relevance by increasing territory,
and changes in neural territory map on to your performance.
(38:30):
So as an example of that, imagine that you have
to learn how to play some crazy new musical instrument.
So a couple of weeks of practice improves your speed
and your skill, and you have a correspondingly large increase
in the brain areas that are involved. But if you
are a seedyl colin release is blocked with a drug,
(38:51):
those brain areas don't grow and your skill never improves.
So the basis of the behavioral improvement is not simply
the repeated performance of the task. It requires these neuromodulatory
systems to encode relevance. Without the acetyl coline, the ten
thousand hours is wasted time. So with the hypothetical Fred Williams,
(39:16):
who hates tennis, why didn't his brain change even after
the same number of hours of practice as his sisters.
It's because these neuromodulatory systems were not engaged in his
head as he drilled backhands over and over. He's like
you practicing the instrument with no acetal colin.
Speaker 2 (39:37):
As a quick side note, these acetal.
Speaker 1 (39:39):
Colin neurons reach out widely across the brain. So when
these start chattering away, why doesn't that turn on plasticity
everywhere they reach, causing widespread neural changes. The answer is
that acetyl coline's release and its effects are modulated.
Speaker 2 (39:56):
By other neural modulators.
Speaker 1 (39:58):
So while acetal colon turns on plasticity, other neurotransmitters like
dopamine are involved in the direction of change, encoding whether
something was punishing or rewarding. Researchers all over the planet
are still working to decipher this very complex choreography of
the neurotransmitter systems. But what we know is that collectively,
(40:20):
these chemical messengers allow reconfiguration in some areas while keeping
the rest locked down.
Speaker 2 (40:28):
So let's go back to the London taxi drivers.
Speaker 1 (40:32):
They're famous for having to memorize the entire map of
the streets of London, and they train for months and
months on this task, and I mentioned before there are
physical changes in the structure of their brain as a result.
These cavies are able to pull off this staggering feet
because the map is relevant to them. This is their
(40:53):
desired employment, which is going to pay for their home mortgage,
or their child's tuition, or their upcoming marriage. But interestingly,
since the study of the cabbys was first published in
the year two thousand, the need for this kind of
memorization has essentially gone away. Now it's just as easy
to have Google memorize all the streets of London, and
(41:15):
more generally, all the streets interlacing the planet. So the
kind of brain changes that we saw at the turn
of the century, we probably.
Speaker 2 (41:23):
Won't be seeing in them anymore.
Speaker 1 (41:26):
What's interesting is that AI algorithms don't care about relevance.
They memorize whatever we ask them to, which is a
super useful feature of AI, but it's also the reason
that AI is not exactly human like, because AI just
doesn't care which problems are interesting or germane. It just
memorizes whatever we feed it, So whether that's distinguishing a
(41:49):
horse from a zebra in a billion photographs or tracking
flight data from every airport on the planet, it has
no sense of importance except in a statistical sense. Contemporary
AI could never by itself decide that it finds irresistible
a particular sculpture by Michaelangelo, or that it hates the
(42:10):
taste of bitter tea, or that it's aroused by signals
of fertility. AI can dispatch ten thousand hours of intense
practice in ten thousand nanoseconds, but it doesn't favor any
zeros and ones over others. As a result, AI can
accomplish super impressive feats, but not yet the feat of
(42:31):
being anything like a human who cares about some things
more than others. Now, how does the modifiability of the
(42:59):
brain and its relationship to relevance bear on the way
that we teach our young The traditional classroom consists of
a teacher that's droning on, possibly reading from bulleted slides.
This is totally suboptimal for brain changes because the students
aren't engaged, and without engagement there's little or no plasticity.
(43:22):
The information doesn't stick. Now, we are not the first
generation to make this observation. The ancient Greeks had noted this.
They didn't have the tools of modern neuroscience, but they
had a sharp eye, and they defined seven different levels
of learning, and the highest level where the best learning occurs,
is achieved when a student is invested and curious and interested.
(43:48):
Through a modern lens, we would say that a particular
formula of neurotransmitters is required for neural changes to take place,
and that formula correlates with investment and curiosity and interest
this trick of inspiring curiosity. This is woven into several
traditional forms of learning. So, for example, Jewish religious scholars
(44:12):
will study the Talmud by sitting in pairs and posing
interesting questions to each other, like why does the author
use this particular word instead of a different word? Or
why do these two authorities differ in their account? Everything
gets cast as a question, which forces their learning partner
to engage instead of memorize. And although this is an
(44:33):
ancient study structure, I recently stumbled on a website that
poses talmudic questions about microbial biology. Questions like, given that
spores are so effective in ensuring survival of bacteria, why
don't all species make them? Or do we know for
(44:54):
sure that there are only three domains of life bacteria,
Archaea and Eucaria, Or how come peptides made enzematically don't
seem to get strung together to make a respectably sized protein.
Speaker 2 (45:08):
This site has hundreds.
Speaker 1 (45:09):
Of questions like this, which coaxes an active engagement in
its readers instead of simply telling them answers and more generally,
this is why joining a study group always helps. It
doesn't matter if you're studying calculus or history or whatever.
A study group activates the brain's social mechanisms to motivate engagement.
Speaker 2 (45:31):
Now.
Speaker 1 (45:31):
I saw a wonderful interview in the nineteen eighties where
the author Isaac Asimov gave an interview with the television
journalist Bill Moyers, and Asimov saw the limits of the
traditional education system with really clear eyes. And here's what
he said. He said, quote, today, what people call learning
is forced on you. Everyone is forced to learn the
(45:53):
same thing on the same day, at the same speed
in class. But everyone is different. For some, class goes
to fast, for some, it goes too slow, for some
in the wrong direction. Asimov had a vision for individualized education,
although he couldn't see the details. He was squinting into
the future, and he anticipated the Internet. He said, quote,
(46:17):
give everyone a chance to follow up their own bent
from the start, to find out about whatever they're interested
in by looking it up in their own homes, at
their own speed, in their own time, and everyone will
enjoy learning.
Speaker 2 (46:32):
End quote.
Speaker 1 (46:34):
It's through this lens of triggering interest that a lot
of philanthropists like Bill and Melinda Gates are aiming to
build adaptive learning. The idea is you leverage software that
quickly determines the state of knowledge of each student, and
then instructs each student on exactly what he or she
needs to know next. It's like having a one to
(46:55):
one student teacher ratio. This approach keeps each student the
right pace, meeting him where he is right now, with
the material that will captivate and This past May, Saul
Kahn gave a great talk at TED where he talked
about using AI to personalize learning. With AI, the students
(47:16):
can learn at their own pace and in their own way,
and he's increasingly making con Academy as a way to
show how AI can create totally personalized learning experiences based
on that student's individual strengths and weaknesses, like asm Off
and Gates and con and many others. I am a
cyber optimist on the topic of education. I always find
(47:40):
myself on Wikipedia, where I'm just following my interest. I
click on one link and I'm reading, and then I think, WHOA,
what's that? And I follow that link and after about
twelve links, I'm down some mole hole and I think, Wow,
how did I get from that topic over here? I
think that drilling down through these blind mole holes of
wikiped without any pre specified plan may turn out to
(48:04):
be a near optimal way to learn and more generally,
what the Internet allows is for students and all of
us to answer questions as soon.
Speaker 2 (48:15):
As they pop into our heads.
Speaker 1 (48:17):
We get the answer in the context of our curiosity.
And this is the powerful difference between the way that
many of us grew up with just in case information,
like just in case you need to know it the
Battle of Hastings occurred in ten sixty six, and what's
happening now, which is just in time information, which is
(48:39):
getting the information the moment that you seek the answer.
Generally speaking, it's only in the latter case, when you're
doing just in time information that you find the right
brew of neuromodulators present.
Speaker 2 (48:53):
The Chinese have.
Speaker 1 (48:54):
An expression an hour with a wise person is worth
more than one thousand busos, and this insight is the
ancient equivalent of what the Internet offers.
Speaker 2 (49:06):
When the learner can actively direct her.
Speaker 1 (49:08):
Own learning by asking the wise person precisely the question
that she wants to answer, the molecules of relevance and
reward are present.
Speaker 2 (49:19):
They allow the brain to reconfigure.
Speaker 1 (49:22):
When you toss facts and an unengaged student, it's like
throwing pebbles to dent a stone wall. It's like trying
to get Fred Williams to absorb tennis. So in this
light we have great opportunities because of the gamification of education.
You have this adaptive software which keeps students working at
(49:45):
their point of struggle, where finding the right answer is
frustrating but achievable. If the student can't get the answer,
the questions stay at the same level. When he gets
the right answer, the questions get harder. So there's still
a role for the teacher here to teach foundational concepts
and to guide the path of learning. But fundamentally, given
(50:07):
how brains adapt and rewrite their wiring, a neuroscience compatible
classroom is one in which the students drill into the
vast sphere of human knowledge by following the paths of
their individual passions. So the future of education looks very favorable.
(50:29):
But one question remains, and I just want to address
this here because I get asked this so often. Given
that the brain becomes wired from experience, what are the
neural consequences of growing up on screens? Are the brains
of digital natives different from the brains of the generations
before them. Now, it comes as a surprise to many
(50:50):
people that there aren't more studies on this than neuroscience.
Wouldn't our society want to understand the differences between the
digital and analog raised brain.
Speaker 2 (51:01):
Yes, we would. But the reason there are no.
Speaker 1 (51:04):
Good studies on this is because it's inordinately difficult to
perform meaningful science on this. Why because there's no good
control group against which to compare a digital native's brain.
You can't easily find another group of eighteen year olds
(51:25):
who haven't grown up with the Internet. You might find
some Amish teenagers in Pennsylvania, but there are dozens of
other differences with that group, such as religious and cultural
and educational beliefs. Where else could you find young people
of the same age who grew up without access to
the Internet. You might be able to turn up some
(51:46):
impoverished children in rural China, or in a village in
Central America or in the Kalahari Desert, but there are
going to be other major differences with those children and
the digital natives whom you intended to understand, including wealth
and education and diet, So it's not a useful control group. Okay,
(52:07):
So maybe you could compare millennials against the generation that
came before them, like their parents, who didn't grow up online,
but who instead played street stickball and stuffed twinkies in
their mouths as they watched The Brady Bunch. But this
is also problematic because between two generations there are innumerable
differences of politics and nutrition and pollution and cultural innovation,
(52:33):
such that if you find differences in the brain, you
have no idea what to.
Speaker 2 (52:37):
Attribute it to.
Speaker 1 (52:39):
So this is an intractable problem to pull off a
well controlled experiment about the effect of growing up with
the Internet. Nonetheless, I can tell you the root of
my optimism about this. Never before have we had the
entirety of humankind's knowledge in a rectangle in our pockets,
(52:59):
with constant and immediate access. Some of you will remember
taking trips down to the library and you look around
for the Encyclopedia Britannica, and you find the letter and
you hope there's an article there about what you're looking for,
and if it's there, you hope that it's not too
many decades old and that the information is still relevant.
And if you can find an article there, then you
(53:21):
have to go to the card catalog and you flip
through it and hope that there's a book somewhere in
the library that addresses what you want to know in
a surprisingly brief period. This is all changed, and as
a result, we've all seen the transition of dinner time debates,
where the winner has transitioned from being the loudest or
(53:44):
most pervasive to the person who can whip out the
phone the fastest and google the fact in question. Discussions
move really rapidly now, they leap from one solved question
to the next, and even when we're by ourselves, there's
just no.
Speaker 2 (53:58):
End to the learning that goes on. When we look up.
Speaker 1 (54:01):
The Wikipedia page, which cascades is down the next link
in the next such that six jumps later, we're learning
facts that we didn't even know we didn't know.
Speaker 2 (54:10):
And the great advantage of this comes from a simple fact.
Speaker 1 (54:14):
All new ideas in your brain come from a mashup
of previously learned inputs, and today we get more new
inputs than ever before. And so our children are living
in a time unparalleled in richness. Our knowledge sphere has
exploded in diameter, and as it grows, it offers more
(54:37):
doors for entry. So young minds have the opportunity to
cross link facts from completely different domains to generate ideas
that previous eras couldn't even have imagined, and this partially
explains the exponential increase in human scholarship. We have faster
communication and more mashups than ever before. So it's not
(55:01):
clear what all the social and political consequences of the
Internet will be, but from a neuroscience perspective, it unlocks
a much richer level of education. So in earlier podcasts
we looked at brain changes resulting from changes to the
body plan in terms of either new sensors or new limbs,
(55:22):
and in this episode we turn to changes that result
from practiced motor acts or rewarding sensory inputs. But the
larger principle that ties all these scenarios together is relevance.
Your brain adjusts itself according to what you spend your
time on as long as those tasks have alignment with
(55:43):
rewards or your goals. For a person who goes blind,
expanding the other senses takes on a heightened relevance, and
this is the deeper origin behind the changes that allow
her visual cortex to get taken over. If a person
passes her fingers repeatedly over the bumps of braille but
(56:05):
has no motivation to learn it then no rewiring takes
place because the right.
Speaker 2 (56:10):
Neuromodulators just aren't present.
Speaker 1 (56:14):
And in the same way, if you add a new
telelimb to your body and it has relevance to you,
your body will learn how to use that, just like
Faith the dog mastered a unique body plan and learned
how to walk on her back legs because it mattered
to her. So the lesson I want to leave you
today with is when you need to learn something, find
(56:35):
some aspect of that that matters to you. My students
ask me this all the time about advice on getting
through their final exams, and I tell them it's all
about relevance. Figure out what is the aspect that matters
to you. You're facing this dumb exam that you might
not care about, but you do care about getting into
(56:55):
graduate school and this is one important wrong on the
ladder to get there. Or you want to impress that
girl or boy over there, and so you need to
study so you can have this stuff on the tip
of your tongue. Or you appreciate the sacrifice that your
parents made in getting you here and you want to
make them proud and that would be meaningful to you,
or whatever the personal details don't matter, but the key
(57:19):
is to remind yourself of the relevance so you can
plug into that, so you can get the right neurotransmitters present,
so they can make the impression, so that they can
make the information stick, so that you're not like Fred
Williams who swings at the tennis ball but whose brain
doesn't change, but instead you're taking in the information and
(57:41):
you're making these changes in your forests of neurons so
that you can recall it later.
Speaker 2 (57:47):
That's what brain plasticity is all about.
Speaker 1 (57:54):
Go to Eagleman dot com slash podcast for more information
and to find further reading on all of this. Send
me an email at podcast at eagleman dot com with
questions or discussion, and I'm making sporadic episodes in which
I address those until next time. I'm David Eagleman, and
this is Inner Cosmos.
If you take a look at a brain, how can
you tell immediately if it belongs to a piano player
or a violinist? How can a dog learn to walk
on its rear legs like a human? And what does
this have to do with how you become an expert
at something? Or what would happen if Venus and Serena
(00:25):
Williams had a hypothetical brother, Fred who hated tennis? And
how do governments respond to change just like brains do?
And finally, why am I so optimistic about the brains
of digital natives. Welcome to the inner Cosmos with me
(00:46):
David Eagleman. I'm a neuroscientist and author at Stanford and
in these episodes we sail deeply into our three pound
universe to understand why and how our lives look.
Speaker 2 (00:58):
The way they do.
Speaker 1 (01:08):
Today's episode is about brain plasticity, which is the ability
of the brain to change and adapt throughout your life.
The word plasticity comes from the word plastic, which is
a material that you can mold into any shape and
then it holds onto that shape. And that is what
is impressive about brains. You can expose them to any
(01:30):
kind of situation or experience, and they hold on to
the change. The vast forest of neurons in your head,
These connections change their strength, and sometimes they unplug and
they seek around and they replug in somewhere else. It's
a living forest of eighty six billion neurons in your head,
(01:51):
and this constant reconfiguration, this is how you learn and remember.
The interesting part I want to address today is exactly
when these changes in the brain happened, because it's not
all the time. Most of the stuff that happens in
your life makes no change at all to your brain.
(02:12):
So what's the difference between the stuff that sticks and
the stuff that doesn't. So let's start today in Hungary
with an educational psychologist named Laslow Polgar. The thing about
Laslow is that he loves chess, and he's written some
well known chess books. But that's not the super interesting
thing about him. The super interesting thing is that he
(02:33):
got very interested in the theory of child rearing and
he believed quote, geniuses are made, not born. So he
started preparing himself for fatherhood even before he had a spouse,
and he read the biographies of four hundred famous intellectuals
like Socrates and Einstein, and he noted that what they
(02:55):
all had in common is they started their intellectual pursuits
at a young age and they studied intensively. So he
concluded from this research the idea that he could, with
the right effort, turn his future children into geniuses in
a particular area which he and his wife could think
(03:16):
about and pick. So they considered various domains, but they
chose chess in part because the success of these children
could be easily measurable with chess. So he and his
wife had three daughters together, Susan, Sophia and Judete, and
he made the move, which was unusual in Hungary at
the time, to homeschool them, and he taught them German
(03:39):
and English and Russian and high level math, but he
primarily taught them chess from the moment that they were
big enough to play with the pieces.
Speaker 2 (03:49):
So what was the result.
Speaker 1 (03:51):
By the time his eldest daughter, Susan turned fifteen years old,
she was the top ranked chess player in the world.
In nineteen teen eighty six, she qualified for the men's
World Championship, which was a first time achievement for a female,
and within five years she had earned the men's Grand
Master title and then in the middle of Susan's astounding accomplishments,
(04:14):
Her fourteen year old middle sister, Sophia, achieved fame for
her sack of Rome, which was her stunning victory at
a tournament in Italy, which ranked as one of the
strongest performances ever by a fourteen year old. Sofia went
on to become an international master and a woman grand master.
Speaker 2 (04:35):
And then there was.
Speaker 1 (04:36):
The youngest sister, Judite, who is widely considered the best
female chess player on record. She achieved grand master status
at the tender age of fifteen years and four months,
and she remains the only woman on the World Chess
Federation's Top one hundred list, and for a while she
held a position in the top ten. So what accounts
(04:58):
for their success, Well, their parents trained the girls every
single day. They didn't just expose them to chess, they
fed them on chess.
Speaker 2 (05:07):
The girls received hugs.
Speaker 1 (05:10):
And stern looks and approval and attention based on their
chess performance, and as a result, their brains came to
have a great deal of circuitry devoted to chess. Now,
we've seen in other episodes how the brain is always
rewriting itself in response to its inputs. But the fact
(05:32):
is that not all information streaming into the pipelines is
equally important. How brains adjust themselves has everything to do
with what you're spending your time on, and that's why
the Polgar sisters became biological chess machines. And it's the
same thing with your brain. It'll reconfigure to whatever you're doing.
(05:56):
So if you decide to make a career change to ornithology,
the study of birds, more of your neural resources will
become devoted towards learning the subtle differences between birds, like
their wing shape, or their breast coloration, or their beak size,
while maybe previously your neural representation of birds with something
(06:21):
more crude, like is that a birder and airplane. So
let's dive in to unpack how the brain makes changes
and when it doesn't, which will tell us everything we
need to know about how to make changes stick in
your own brain. There's a great story about the violinist
Yetsak Pearlman after one of his concerts and admiring concertgoer
(06:45):
said to him, I would give my life to play
like that, and Pearlman said, I did, Now what did
he mean? Well, every morning, Pearlman drags himself out of
bed at five point fifteen. He takes a shower and batakfast,
and then digs into his four and a half hour
morning practice. He then takes a lunch and an exercise session,
(07:08):
and then launches his afternoon practice for another four and
a half hours. He does this every day of the year,
except for concert days, when he does only the morning
practice session. And you know what, Brain circuitry comes to
reflect what you do. So the cortex of Jasah Pearlman,
(07:28):
or any highly trained musician changes through time into something different.
And this isn't a metaphorical claim. You can see this
with brain imaging, even with an untrained eye.
Speaker 2 (07:41):
Let me tell you how.
Speaker 1 (07:42):
If you look at the strip of brain right underneath
where you wear headphones, that's an area called the motor cortex,
and that's what directs your body how to move all
of its six hundred exquisitely beautiful muscles. Now, if you
zoom in on a region of the cortex involved in
hand movement, you'll find something amazing, which is that musicians
(08:06):
have a little puckered shape on their cortex where non
musicians don't. So think of it like an extra wrinkle
on the wrinkly outer bit of the brain, the cortex.
Speaker 2 (08:17):
Why do the musicians have this.
Speaker 1 (08:19):
It's because they use the muscles of their hands in
an extraordinarily detailed way, much more so than non musicians,
so their.
Speaker 2 (08:29):
Brains devote more real estate to that task.
Speaker 1 (08:33):
The thousands of hours of practice on the instrument physically
molds their brains. And by the way, this is wildly specific.
So imagine that you compare the brain of a violinist
like Pearlman to the brain of a pianist like Vladimir Ashkenazi.
What they both have in common is a deep dedication
(08:56):
to their craft and countless hours of practice, and yet
their brains look sufficiently different that you can easily see
which brain belongs to whom. And that's because string players
like Pearlman show that extra wrinkle mostly on one side
and one hemisphere, because his left fingers are doing all
(09:17):
the detailed work while the right hand mostly just runs
the bow over the strings. In contrast, a pianist like
Ashkenazi has that extra wrinkle in both hemispheres because both
of his hands are performing meticulous patterns on the ivories.
So simply by looking at the brain which used to
(09:38):
be done in autopsy, but now you can do with
a brain scan. You can tell what kind of musician
you have in the scanner. You can discern this just
by looking at the wrinkly bits on the motor cortex.
Speaker 2 (09:51):
And we can read even more from the brain's patterns.
Speaker 1 (09:55):
It represents not only that a hand is doing less
or more, but sometimes what what in particular it's doing.
So let's say you get a job at an assembly
line and you're randomly assigned to one of two jobs.
Either you put little marbles into jars, or your job
is to screw the jar lid shut. Okay, so both
(10:16):
jobs use your right hand, but the first requires fine
use of your fingertips, while screwing the lid on makes
use of your wrist and forearm. So if you're the
jar filler, the real estate in your cortex that represents
your fingers will increase, and this is at the expense
(10:36):
of the real estate devoted to your wrists and forearms.
If you are the lid turner, the opposite happens. You
get more representation for your wrist and forearm and less
for the detailed movement of your fingers. So in this way,
what you do over and over becomes reflected in the
structure of your brain, and these changes involve more than
(11:00):
the motor cortex.
Speaker 2 (11:01):
For example, if.
Speaker 1 (11:02):
You spend months learning to read Braille, the bit of
your cortex that represents touch from the index finger that
will grow. If you take up juggling as an adult,
the visual areas of your brain involved in that they increase.
This is because brains reflect not simply the outside world,
(11:23):
but more specifically your outside world, and this is what
underlies getting good at something. Professional tennis players like Serena
and Venus Williams they spend years training so that the
right moves will come automatically in the heat of the game. Step, pivot, backhand, charge, fallback, aim, smash.
Speaker 2 (11:48):
They train for.
Speaker 1 (11:49):
Thousands of hours to burn the moves down into the
unconscious circuitry of the brain. They craft their brains into
overtrained machinery. He might have heard of the ten thousand
hour rule, which suggests that you need to practice a
skill for that many hours to become an expert, whether
this is surfboarding or spelunking, or saxophone playing or whatever.
(12:13):
Although we can't quantify the exact number of hours, the
general idea is correct. You need massive amounts of repetition
to dig the subway maps of the brain. There's a
guy that I mentioned in an earlier episode. His name
is Destin Sandlin, and he made a video where he
tries to ride a bike that someone gave him with
(12:35):
reversed steering, so when you push the handlebars to the left,
the wheel turns to the right and vice versa. This
is a super difficult thing to learn how to ride.
So what he did is he spent every day working
on this and trying it out, and he crashed and crashed,
but eventually he got it. But the point I want
(12:56):
to make here is that you know, he's an engineer,
and it only took him a few seconds to cognitively
understand how the bike worked, but that proved insufficient to
ride it. He needed to invest weeks and weeks of practice.
Speaker 2 (13:13):
Hence the ten thousand hour rule.
Speaker 1 (13:17):
And this dynamic changing of the brain happens from intensive
physical practice that you do, whether that's swimming or playing
the harmonica, or swinging a tennis racket or using a
rake or whatever. But these measurable brain changes, they don't
just apply to the physical they apply to the mental also,
so for example, when medical students study for their final
(13:39):
exams over the course of three months, particular areas of
their cortex changed so much that you can see this
on brain scans with the naked eye. And you see
something similar if you teach a person how to read
backward through a mirror. And here's another example. Areas of
the brain that are involved in spatial navigation are visibly
(14:04):
different in London taxi drivers from the rest of the population.
In each hemisphere, the taxi drivers have an enlarged region
part of the hippocampus, which is an area involved in
your internal maps of the outside world. So what you
(14:38):
spend your time on changes your brain. You are more
than what you eat. You become the information you digest.
And this is how the Polgar sisters were able to
blossom into world champion chess players. It's not because some
gene codes for skill at chess. It's because they practiced
(14:59):
over and over chiseling pathways in their brains to encode
the powers and patterns of knights and rooks and bishops
and ponds and kings and queens. So brains come to
reflect their world.
Speaker 2 (15:14):
But how does this happen? Exactly. Well, let's see the.
Speaker 1 (15:17):
Answer by zooming in on a weird illusion that most
of us have experienced, the phantom phone vibration. I recently
saw a meme online. It was a picture of a
human brain with the title that reads, Hey, I think
your phone just buzzed in your pocket, and then on
the bottom it reads, just kidding. Your phone isn't even
in your pocket, you moron. Now, the phantom cell phone
(15:41):
vibration is a menace that is unique to the twenty
first century. It happens because of a momentary spasm or
quivering or shaking, or a touch on your leg, And
as long as the frequency and the duration of that
feeling is vaguely similar to that made by your phone,
your brain decides on your behalf, that's something interesting is
(16:04):
happening with your phone. So thirty years ago, if you
had noticed a leg twitch, you would have interpreted the
feeling as a fly landing on you, or a movement
of your clothing, or something accidentally brushing past you. So
why does your interpretation differ from one generation to the next,
(16:26):
Because your phone now serves as the optimal explanation for
a whole range of twitchy feelings. So here's how to
understand what's happening there in the brain. Think of a
mountainous landscape. Now, picture a lake somewhere there that's encircled
by mountains. For a rain drop to end up in
(16:48):
that lake, it doesn't need to fall from the sky
and land directly in the water. Instead, it only needs
to hit the surrounding hillsides. It can land on the
northern slope or the southern, or the eastern incline or
the western and in any case it's gonna slide down into
the lake. So the lake is what's known as an
(17:10):
attractor state. Anything nearby will flow to that spot, and
you have lots of such attractor states in your brain.
So the feeling on your thigh doesn't have to be
a buzzing phone.
Speaker 2 (17:24):
It can be a slight shift.
Speaker 1 (17:26):
Of your genes or a twitch of your thigh muscle,
or an itch or graze past the sofa.
Speaker 2 (17:33):
As long as the feeling is close, the signals.
Speaker 1 (17:37):
Slide down the landscape to their attractor state, and then
you reach to check for an important message. The landscape
gets formed by what is important in your world. For
another example, think about the way we interpret the sounds
of language. It feels natural to you that you can
(17:58):
understand the sounds of your native language, but foreign languages
often have really close sounds that you can't hear the
difference between.
Speaker 2 (18:07):
Like ooh and eh. But why why can you not
hear those?
Speaker 1 (18:13):
As it turns out, there is something different about the
brains of the people who speak those languages. But they
weren't born that way, and neither were you. If you
look at the space of all the possible sounds that
humans can make with our mouths, it makes a relatively
smooth continuum. You can kind of make any sound. But
(18:34):
despite this, you learn from experience that specific sounds mean
the same thing, whether they're uttered by your dad, or
your babysitter or your teacher. Your brain figures out that
a drawn out E and eclip to e both belong
to the E category, or maybe your friend from Texas
(18:55):
says a or whatever. But your experience teaches you that
all the speakers mean the same sound, regardless of exactly
how they're pronouncing it, and so your neural networks carve
out a landscape in which all these sounds roll down
the hillsides to the same interpretation. There's a lake in
(19:16):
your brain that represents E, and all the inputs from
all around end up in that lake and in neighboring valleys,
you gather up sounds that are equivalent to A or
I or O and so on. So with time, your
landscape looks different from someone who's grown up in another
(19:37):
language and who needs to distinguish the smooth continuum of
sounds differently than you do. To think about an example
of this, imagine a baby born in Japan call him Hyato,
and a baby born in America call him William. From
their brain's point of view, there is nothing different about them.
(19:59):
But in Osaka, Hayato hears Japanese all around him.
Speaker 2 (20:04):
From day one.
Speaker 1 (20:05):
In Palo Alto, William hears the tones of English, where
different sounds carry meaning. An example of what these two
babies hear differently is the distinction between the.
Speaker 2 (20:17):
R and L sounds.
Speaker 1 (20:19):
So in English, these carry information like the word right
versus light or raw versus law, But in Japanese there's
no distinction between these two sounds. So as a result,
William's internal landscape builds a mountain range between his interpretation
of R and L, such that the difference between these
(20:44):
two sounds is perceptually clear. In Hyato's brain, the landscape
develops into a big valley, so that both R and
L flow into a single lake because they have an
identical interpretation. So as a result, Hyato can't hear the
difference between those two sounds. Now, obviously, the children's brains
(21:08):
were not born this way. Had William's pregnant mother moved
to Osaka and Hyato's pregnant mother to Palo Alto, the
boys would have had no trouble in becoming fluent speakers
and listeners in their new language.
Speaker 2 (21:21):
As opposed to a genetic issue.
Speaker 1 (21:24):
Their neural landscapes are carved by what is relevant in
their immediate environment. And what's fascinating is that you can
see this carving happening even before the children learn how
to speak. For example, make a continuous R sound and
then switch it over to L. So L, now, how
(21:47):
can you tell if an infant here's that change?
Speaker 2 (21:51):
So it turns out the trick.
Speaker 1 (21:53):
To the experiment is this, Infants will suck faster at
the nipple when they detect a chain. When they hear
a change from one sound to another sound, they go
from suck suck suck to suck suck, suck, suck. So
at the age of six months, both Hyato and William
will both suck faster when the R changes to L.
(22:15):
But by twelve months, Hyato stops detecting the change. R
and L sound the same to him. Both sounds are
sliding down into the same valley. Hyato's brain has lost
the ability to distinguish these sounds, while William's brain, having
passively listened to his parents speak tens of thousands of
(22:36):
English words, has learned that there's information carried in the
difference between these two sounds. Hyato's brain, meanwhile, has picked
up on other sound distinctions, which to William would be indistinguishable.
So your auditory system begins universally and then wires itself
(22:57):
to maximize the distinction unique to your language, depending on
where on the planet you happened to stick your head
out of the womb. And similarly, the buzzing phone isn't
something you were born to detect. Instead, it's high relevance
carves your neural landscape such that you have a broad
(23:19):
catch all for neighboring sensations, all of which you will
interpret as a buzzing cell phone in your pocket. Like kyata.
With the R and the L, you combine the twitches
and vibrations and quiverings into a single interpretation of what
just happened. Now, from what we've seen so far, we
might think that repetition is the key to molding the
(23:43):
circuitry in your brain. But in fact, there's a deeper
principle at work. So now we're going to talk about relevance.
There's an old joke that goes, how many psychiatrists does
it take to change a light bulb? And the answer
is only one, But the light bulb has to want
to change. Now, if you listen to episode two, you
(24:05):
may remember a dog that I talked about named Faith.
She is very memorable because Faith was born with out
front legs and she figured out how to walk by
pedaly on her hind legs, sort of like a human.
Speaker 2 (24:18):
Now.
Speaker 1 (24:18):
When I told her story in episode two, I said
it as though her brain had just figured out her
unusual body plan. But we can now dig a little
deeper for a hidden bone. Was there something special about Faith?
Could any dog have pulled us off? And if they
could have, why don't all dogs walk by?
Speaker 2 (24:37):
Peeda Ly?
Speaker 1 (24:39):
Faith's rewritten maps were all about relevance to her life.
Her brain was shaped by her goals. Faith needed to
get to her food. That required a solution. It wasn't
going to be the same one that was used by
her four legged siblings. She had to derive a novel solution,
(24:59):
so her brain tried out various strategies until it found
when that worked balancing on her two back legs and
lurching forward step after step. This allowed her to get
what she needed, and after a while, she became good
at this method of locomotion. In the absence of finding
an answer to her challenge, she would have starved and died.
(25:22):
Her drive for survival allowed the flexible circuitry in her
brain to try out a bunch of hypotheses and solve
the problem getting her to food and shelter and loved ones.
Speaker 2 (25:35):
So goals matter.
Speaker 1 (25:37):
A brain's goals play a critical role in how and
when it changes. For the Polgar sisters, achieving their expertise
depended on a desire to achieve their expertise. Same with
Yitzak Pearlman or Vladimir Ashkenazi. Imagine for a moment that
Serena and Venus Williams had a brother, Fred, and that
(26:02):
their parents had put a tennis racket in Fred's hands
and forced him to go through all the years of
practicing that his sisters went through. But imagine that he
found tennis repulsive. He never got good feedback from his
classmates about his performances, and he didn't win any contests,
and his elders didn't lavish him with praise. The result
(26:24):
of all that practice would be nothing. Fred's brain would
show little reorganization. Although his body was going through the
same motions as his sisters, the motions would be misaligned
with his internal incentives. So this is easily shown in
the laboratory. So imagine an experiment in which someone is
(26:47):
tapping out Morris code on your foot while someone else
totally separately is playing a sequence of sounds.
Speaker 2 (26:55):
Now, if the.
Speaker 1 (26:56):
Task is that you can win cash for decoding the
message on your foot, then the brain regions involved in
touch to that part of your body will develop higher resolution.
The regions involved in your hearing won't change, even though
that brain area is also receiving stimulation. Now imagine the
(27:17):
reverse game. Now, answering questions about subtle differences between the
sounds earns the cash while attending to your foot doesn't
yield anything. Now we'll see changes in the auditory cortex
where you're doing the hearing, but the touch in your
somatosensory cortex won't change. The inputs from the world are
(27:39):
exactly the same in both cases. But what changes in
your brain depends on what is rewarded. And this is
why Fred Williams gets no better on the tennis court.
He derives no reward from it. In his brain, just
like in yours, the maps of the neural territory reflect
(28:00):
to the strategies that have won positive feedback. Now this
kind of understanding about motivation and relevance leading to change
in the brain. This understanding opens new pathways for recovery
from brain damage. So imagine that a friend of yours
suffers a stroke. That damage is part of her motor cortex,
(28:21):
and as a result, one of her arms becomes mostly paralyzed.
So after trying many times to use her weakened arm,
she gets frustrated and just uses her good arm to
accomplish all the necessary tasks in her daily routine. This
is a typical scenario, and her weak arm becomes only
weaker because she's never choosing to use it. Now, the
(28:45):
lessons of brain plasticity that we've been talking about offer
a solution that is counterintuitive. The solution is known as
constraint therapy. You strap down her good arm so that
she can't use it, and that forces her to employ
the weak arm. Now, this simple method retrains the damaged
(29:09):
cortex by forcing use of the bad arm and cleverly
taking advantage of these neural mechanisms underlying desire and reward.
Because she has inherent motivation to get the sandwich to
her mouth, or to turn the key in her front door,
or to raise the cell phone to her ear, and
(29:30):
to perform all the other actions that underlie a dignified,
self sufficient life. So while constraint therapy starts off as frustrating,
the approach proves to be the best medicine because it
forces the brain to try new strategies, and the reward
locks in the methods that work. It seems paradoxical that
(29:54):
the solution of the problem is to make things worse,
but that's precisely what solves. So let's return to faith
the dog. Are all dogs able to walk on their
back legs? Sure, but most dogs will never have the
reason or motivation to attempt it, and certainly no reason
(30:15):
to master it. And that's why Faith became famous, not
because she's the only dog in the world who could
do it, but because she's the only one who made
it happen. You may know that some blind people learn
how to navigate using echolocation. They make sounds with their
mouth and they listen for the echo to give them information.
(30:37):
But it turns out that people with perfectly normal vision
can learn how to echo locate. Also, the issue is
just that most cited people simply are insufficiently motivated to
pour the hours and hours into redefining their neural territory. Now,
reward is a powerful way to rewire the brain, but happily,
(31:01):
your brain doesn't require cookies or cash. More generally, change
is tied to anything that's relevant to your goals. If
you're in the far North and you need to learn
about ice fishing and different types of snow, that's what
your brain will come to encode. If instead your equatorial
and you need to learn which snakes to avoid and
(31:23):
which mushrooms to eat, your brain will devote its resources accordingly.
Using relevance as it's north star, the brain flexibly picks
up on important details. It's billions of neurons serve as
a colossal canvas for painting the world that we happen
(31:44):
to find ourselves in, and with it we develop expertise
and whatever has relevance to us, whether that's basketball or
theater or badminton or Greek classics or cliff jumping or
video gaming or line dancing or wine making. Whenever a
task is roughly aligned with our larger goals, our brain.
Speaker 2 (32:06):
Circuitry comes to reflect that.
Speaker 1 (32:10):
Now, with how brains rewire based on what's relevant, I
realized really interesting analogy some years ago. Governments do the
same thing. They continually self design based on what's happening
in the nation. So just look at what happened. In
response to the attacks of September eleventh, two thousand and one,
(32:30):
the United States government altered its structure. It established the
Department of Homeland Security, which absorbed and restructured twenty two
existing agencies, And the same thing happened with the simmering
Cold War. This initiated a large shift in nineteen forty seven,
which spawned the Central Intelligence Agency, and in a thousand
(32:51):
small ways, a government subtly mirrors the current aims of
a nation and the events of its outside world. So
you have budgets swelling and shrinking to echo priorities when
external threats loom. The military pocketbook expands when peacetime follows.
(33:12):
Social initiatives gain. Just like brains, nations respond to changing
situations by shifting their resources and redrawing their organizational charts
to meet the challenges that they face. So how does
the brain know when something important has happened and that
(33:33):
it should change its wire accordingly. Well, one strategy is
to turn on plasticity when events in the world are correlated.
So the idea here is to just encode only those
things that co occur, Like you see a cow and
you hear a move, and in this way related events
(33:55):
become bound together in the brain tissue. Now, you generally
don't want to implement these changes too quickly, because sometimes
there are associations that are spurious.
Speaker 2 (34:06):
You might see a cow.
Speaker 1 (34:08):
But you hear the bark of an unrelated dog, and
you wouldn't want your brain to permanently store every accidental cooccurrence.
Speaker 2 (34:16):
So the brain solution is to change slowly, just a
little at a time.
Speaker 1 (34:22):
And in that way it comes to encode only those
things that commonly coincide real matches distinguish themselves from noise
by occurring together over and over and over. But despite
the wisdom of slow and steady change extracting averages like this,
that's not the whole story. Because just think about one
(34:44):
trial learning in which you, let's say, touch a hot
stove and you learn not to do that again. So
you've got emergency mechanisms that exist to make sure that
life threatening or limb threatening events are permanently retained. The
story of one trial learning goes deeper than that. Think
about when you were young and your aunt taught you
(35:06):
a new word. She says, this is called a pomegranate. Now,
you didn't need to learn that in an emergency situation,
and you didn't need your aunt to say this association
one hundred times. She calmly told you once, and you
got it in one trial. Why It's because it was
(35:26):
salient to you. You loved your aunt, and you derived
social benefit from knowing a new word and being able
to ask for the delicious fruit. This is one trial
learning not because of threat, but instead because of relevance.
Speaker 2 (35:43):
Inside the brain.
Speaker 1 (35:45):
This relevance is expressed through these widely reaching systems that
release chemicals called neuromodulators. By releasing these with high specificity,
these chemicals allow changes to occur only at specific places
and times instead of all over at every moment. An
especially important chemical messenger here is called acetylcholine.
Speaker 2 (36:09):
Neurons that release the.
Speaker 1 (36:10):
Seedlcholine are driven by both reward and punishment, and they're
active whenever you're learning a new task and need to
make changes, but they're not active once the task is
well established.
Speaker 2 (36:22):
So here's what you need to know.
Speaker 1 (36:24):
The presence of acetylcholine at a particular brain area tells
it to change, It doesn't tell it how to change.
In other words, when the neurons that spit out acetal
coline are active, they simply increase plasticity in the target areas.
When they are not active, there's little or no plasticity.
(36:44):
So here's an example. Imagine I play for you a
particular note on the piano, say D flat. The note
triggers activity in your auditory cortex, but it doesn't change
anything about how much territory is devoted to D flat.
Speaker 2 (37:05):
Why not?
Speaker 1 (37:06):
It's because the note doesn't mean anything in particular to you. Now,
let's say every time I play the note, I give
you a warm chocolate chip cookie. Now the note accrues
a meaning, and the brain territory devoted to D flat expands.
Your brain assigns more real estate to that frequency because
(37:27):
the presence of reward suggests it's important. Now, let's say
I don't have any cookies available, so instead of handing
you the treat, I play the D flat. At the
same moment that I stimulate neurons in your head that
release a setal colin. The cortical representation for that tone expands,
(37:49):
just like it did with the cookies. Your brain allocates
more terrain to that frequency because the presence of the
acetyl coline indicates that it must be important. So a
setyl colin broadcasts widely throughout the brain, and as a result,
it can trigger changes with whatever kind of relevant stimulus,
(38:09):
whether that's a musical note or a texture or something verbal.
It's a universal mechanism for saying this is important. Get
better at detecting this. It marks relevance by increasing territory,
and changes in neural territory map on to your performance.
(38:30):
So as an example of that, imagine that you have
to learn how to play some crazy new musical instrument.
So a couple of weeks of practice improves your speed
and your skill, and you have a correspondingly large increase
in the brain areas that are involved. But if you
are a seedyl colin release is blocked with a drug,
(38:51):
those brain areas don't grow and your skill never improves.
So the basis of the behavioral improvement is not simply
the repeated performance of the task. It requires these neuromodulatory
systems to encode relevance. Without the acetyl coline, the ten
thousand hours is wasted time. So with the hypothetical Fred Williams,
(39:16):
who hates tennis, why didn't his brain change even after
the same number of hours of practice as his sisters.
It's because these neuromodulatory systems were not engaged in his
head as he drilled backhands over and over. He's like
you practicing the instrument with no acetal colin.
Speaker 2 (39:37):
As a quick side note, these acetal.
Speaker 1 (39:39):
Colin neurons reach out widely across the brain. So when
these start chattering away, why doesn't that turn on plasticity
everywhere they reach, causing widespread neural changes. The answer is
that acetyl coline's release and its effects are modulated.
Speaker 2 (39:56):
By other neural modulators.
Speaker 1 (39:58):
So while acetal colon turns on plasticity, other neurotransmitters like
dopamine are involved in the direction of change, encoding whether
something was punishing or rewarding. Researchers all over the planet
are still working to decipher this very complex choreography of
the neurotransmitter systems. But what we know is that collectively,
(40:20):
these chemical messengers allow reconfiguration in some areas while keeping
the rest locked down.
Speaker 2 (40:28):
So let's go back to the London taxi drivers.
Speaker 1 (40:32):
They're famous for having to memorize the entire map of
the streets of London, and they train for months and
months on this task, and I mentioned before there are
physical changes in the structure of their brain as a result.
These cavies are able to pull off this staggering feet
because the map is relevant to them. This is their
(40:53):
desired employment, which is going to pay for their home mortgage,
or their child's tuition, or their upcoming marriage. But interestingly,
since the study of the cabbys was first published in
the year two thousand, the need for this kind of
memorization has essentially gone away. Now it's just as easy
to have Google memorize all the streets of London, and
(41:15):
more generally, all the streets interlacing the planet. So the
kind of brain changes that we saw at the turn
of the century, we probably.
Speaker 2 (41:23):
Won't be seeing in them anymore.
Speaker 1 (41:26):
What's interesting is that AI algorithms don't care about relevance.
They memorize whatever we ask them to, which is a
super useful feature of AI, but it's also the reason
that AI is not exactly human like, because AI just
doesn't care which problems are interesting or germane. It just
memorizes whatever we feed it, So whether that's distinguishing a
(41:49):
horse from a zebra in a billion photographs or tracking
flight data from every airport on the planet, it has
no sense of importance except in a statistical sense. Contemporary
AI could never by itself decide that it finds irresistible
a particular sculpture by Michaelangelo, or that it hates the
(42:10):
taste of bitter tea, or that it's aroused by signals
of fertility. AI can dispatch ten thousand hours of intense
practice in ten thousand nanoseconds, but it doesn't favor any
zeros and ones over others. As a result, AI can
accomplish super impressive feats, but not yet the feat of
(42:31):
being anything like a human who cares about some things
more than others. Now, how does the modifiability of the
(42:59):
brain and its relationship to relevance bear on the way
that we teach our young The traditional classroom consists of
a teacher that's droning on, possibly reading from bulleted slides.
This is totally suboptimal for brain changes because the students
aren't engaged, and without engagement there's little or no plasticity.
(43:22):
The information doesn't stick. Now, we are not the first
generation to make this observation. The ancient Greeks had noted this.
They didn't have the tools of modern neuroscience, but they
had a sharp eye, and they defined seven different levels
of learning, and the highest level where the best learning occurs,
is achieved when a student is invested and curious and interested.
(43:48):
Through a modern lens, we would say that a particular
formula of neurotransmitters is required for neural changes to take place,
and that formula correlates with investment and curiosity and interest
this trick of inspiring curiosity. This is woven into several
traditional forms of learning. So, for example, Jewish religious scholars
(44:12):
will study the Talmud by sitting in pairs and posing
interesting questions to each other, like why does the author
use this particular word instead of a different word? Or
why do these two authorities differ in their account? Everything
gets cast as a question, which forces their learning partner
to engage instead of memorize. And although this is an
(44:33):
ancient study structure, I recently stumbled on a website that
poses talmudic questions about microbial biology. Questions like, given that
spores are so effective in ensuring survival of bacteria, why
don't all species make them? Or do we know for
(44:54):
sure that there are only three domains of life bacteria,
Archaea and Eucaria, Or how come peptides made enzematically don't
seem to get strung together to make a respectably sized protein.
Speaker 2 (45:08):
This site has hundreds.
Speaker 1 (45:09):
Of questions like this, which coaxes an active engagement in
its readers instead of simply telling them answers and more generally,
this is why joining a study group always helps. It
doesn't matter if you're studying calculus or history or whatever.
A study group activates the brain's social mechanisms to motivate engagement.
Speaker 2 (45:31):
Now.
Speaker 1 (45:31):
I saw a wonderful interview in the nineteen eighties where
the author Isaac Asimov gave an interview with the television
journalist Bill Moyers, and Asimov saw the limits of the
traditional education system with really clear eyes. And here's what
he said. He said, quote, today, what people call learning
is forced on you. Everyone is forced to learn the
(45:53):
same thing on the same day, at the same speed
in class. But everyone is different. For some, class goes
to fast, for some, it goes too slow, for some
in the wrong direction. Asimov had a vision for individualized education,
although he couldn't see the details. He was squinting into
the future, and he anticipated the Internet. He said, quote,
(46:17):
give everyone a chance to follow up their own bent
from the start, to find out about whatever they're interested
in by looking it up in their own homes, at
their own speed, in their own time, and everyone will
enjoy learning.
Speaker 2 (46:32):
End quote.
Speaker 1 (46:34):
It's through this lens of triggering interest that a lot
of philanthropists like Bill and Melinda Gates are aiming to
build adaptive learning. The idea is you leverage software that
quickly determines the state of knowledge of each student, and
then instructs each student on exactly what he or she
needs to know next. It's like having a one to
(46:55):
one student teacher ratio. This approach keeps each student the
right pace, meeting him where he is right now, with
the material that will captivate and This past May, Saul
Kahn gave a great talk at TED where he talked
about using AI to personalize learning. With AI, the students
(47:16):
can learn at their own pace and in their own way,
and he's increasingly making con Academy as a way to
show how AI can create totally personalized learning experiences based
on that student's individual strengths and weaknesses, like asm Off
and Gates and con and many others. I am a
cyber optimist on the topic of education. I always find
(47:40):
myself on Wikipedia, where I'm just following my interest. I
click on one link and I'm reading, and then I think, WHOA,
what's that? And I follow that link and after about
twelve links, I'm down some mole hole and I think, Wow,
how did I get from that topic over here? I
think that drilling down through these blind mole holes of
wikiped without any pre specified plan may turn out to
(48:04):
be a near optimal way to learn and more generally,
what the Internet allows is for students and all of
us to answer questions as soon.
Speaker 2 (48:15):
As they pop into our heads.
Speaker 1 (48:17):
We get the answer in the context of our curiosity.
And this is the powerful difference between the way that
many of us grew up with just in case information,
like just in case you need to know it the
Battle of Hastings occurred in ten sixty six, and what's
happening now, which is just in time information, which is
(48:39):
getting the information the moment that you seek the answer.
Generally speaking, it's only in the latter case, when you're
doing just in time information that you find the right
brew of neuromodulators present.
Speaker 2 (48:53):
The Chinese have.
Speaker 1 (48:54):
An expression an hour with a wise person is worth
more than one thousand busos, and this insight is the
ancient equivalent of what the Internet offers.
Speaker 2 (49:06):
When the learner can actively direct her.
Speaker 1 (49:08):
Own learning by asking the wise person precisely the question
that she wants to answer, the molecules of relevance and
reward are present.
Speaker 2 (49:19):
They allow the brain to reconfigure.
Speaker 1 (49:22):
When you toss facts and an unengaged student, it's like
throwing pebbles to dent a stone wall. It's like trying
to get Fred Williams to absorb tennis. So in this
light we have great opportunities because of the gamification of education.
You have this adaptive software which keeps students working at
(49:45):
their point of struggle, where finding the right answer is
frustrating but achievable. If the student can't get the answer,
the questions stay at the same level. When he gets
the right answer, the questions get harder. So there's still
a role for the teacher here to teach foundational concepts
and to guide the path of learning. But fundamentally, given
(50:07):
how brains adapt and rewrite their wiring, a neuroscience compatible
classroom is one in which the students drill into the
vast sphere of human knowledge by following the paths of
their individual passions. So the future of education looks very favorable.
(50:29):
But one question remains, and I just want to address
this here because I get asked this so often. Given
that the brain becomes wired from experience, what are the
neural consequences of growing up on screens? Are the brains
of digital natives different from the brains of the generations
before them. Now, it comes as a surprise to many
(50:50):
people that there aren't more studies on this than neuroscience.
Wouldn't our society want to understand the differences between the
digital and analog raised brain.
Speaker 2 (51:01):
Yes, we would. But the reason there are no.
Speaker 1 (51:04):
Good studies on this is because it's inordinately difficult to
perform meaningful science on this. Why because there's no good
control group against which to compare a digital native's brain.
You can't easily find another group of eighteen year olds
(51:25):
who haven't grown up with the Internet. You might find
some Amish teenagers in Pennsylvania, but there are dozens of
other differences with that group, such as religious and cultural
and educational beliefs. Where else could you find young people
of the same age who grew up without access to
the Internet. You might be able to turn up some
(51:46):
impoverished children in rural China, or in a village in
Central America or in the Kalahari Desert, but there are
going to be other major differences with those children and
the digital natives whom you intended to understand, including wealth
and education and diet, So it's not a useful control group. Okay,
(52:07):
So maybe you could compare millennials against the generation that
came before them, like their parents, who didn't grow up online,
but who instead played street stickball and stuffed twinkies in
their mouths as they watched The Brady Bunch. But this
is also problematic because between two generations there are innumerable
differences of politics and nutrition and pollution and cultural innovation,
(52:33):
such that if you find differences in the brain, you
have no idea what to.
Speaker 2 (52:37):
Attribute it to.
Speaker 1 (52:39):
So this is an intractable problem to pull off a
well controlled experiment about the effect of growing up with
the Internet. Nonetheless, I can tell you the root of
my optimism about this. Never before have we had the
entirety of humankind's knowledge in a rectangle in our pockets,
(52:59):
with constant and immediate access. Some of you will remember
taking trips down to the library and you look around
for the Encyclopedia Britannica, and you find the letter and
you hope there's an article there about what you're looking for,
and if it's there, you hope that it's not too
many decades old and that the information is still relevant.
And if you can find an article there, then you
(53:21):
have to go to the card catalog and you flip
through it and hope that there's a book somewhere in
the library that addresses what you want to know in
a surprisingly brief period. This is all changed, and as
a result, we've all seen the transition of dinner time debates,
where the winner has transitioned from being the loudest or
(53:44):
most pervasive to the person who can whip out the
phone the fastest and google the fact in question. Discussions
move really rapidly now, they leap from one solved question
to the next, and even when we're by ourselves, there's
just no.
Speaker 2 (53:58):
End to the learning that goes on. When we look up.
Speaker 1 (54:01):
The Wikipedia page, which cascades is down the next link
in the next such that six jumps later, we're learning
facts that we didn't even know we didn't know.
Speaker 2 (54:10):
And the great advantage of this comes from a simple fact.
Speaker 1 (54:14):
All new ideas in your brain come from a mashup
of previously learned inputs, and today we get more new
inputs than ever before. And so our children are living
in a time unparalleled in richness. Our knowledge sphere has
exploded in diameter, and as it grows, it offers more
(54:37):
doors for entry. So young minds have the opportunity to
cross link facts from completely different domains to generate ideas
that previous eras couldn't even have imagined, and this partially
explains the exponential increase in human scholarship. We have faster
communication and more mashups than ever before. So it's not
(55:01):
clear what all the social and political consequences of the
Internet will be, but from a neuroscience perspective, it unlocks
a much richer level of education. So in earlier podcasts
we looked at brain changes resulting from changes to the
body plan in terms of either new sensors or new limbs,
(55:22):
and in this episode we turn to changes that result
from practiced motor acts or rewarding sensory inputs. But the
larger principle that ties all these scenarios together is relevance.
Your brain adjusts itself according to what you spend your
time on as long as those tasks have alignment with
(55:43):
rewards or your goals. For a person who goes blind,
expanding the other senses takes on a heightened relevance, and
this is the deeper origin behind the changes that allow
her visual cortex to get taken over. If a person
passes her fingers repeatedly over the bumps of braille but
(56:05):
has no motivation to learn it then no rewiring takes
place because the right.
Speaker 2 (56:10):
Neuromodulators just aren't present.
Speaker 1 (56:14):
And in the same way, if you add a new
telelimb to your body and it has relevance to you,
your body will learn how to use that, just like
Faith the dog mastered a unique body plan and learned
how to walk on her back legs because it mattered
to her. So the lesson I want to leave you
today with is when you need to learn something, find
(56:35):
some aspect of that that matters to you. My students
ask me this all the time about advice on getting
through their final exams, and I tell them it's all
about relevance. Figure out what is the aspect that matters
to you. You're facing this dumb exam that you might
not care about, but you do care about getting into
(56:55):
graduate school and this is one important wrong on the
ladder to get there. Or you want to impress that
girl or boy over there, and so you need to
study so you can have this stuff on the tip
of your tongue. Or you appreciate the sacrifice that your
parents made in getting you here and you want to
make them proud and that would be meaningful to you,
or whatever the personal details don't matter, but the key
(57:19):
is to remind yourself of the relevance so you can
plug into that, so you can get the right neurotransmitters present,
so they can make the impression, so that they can
make the information stick, so that you're not like Fred
Williams who swings at the tennis ball but whose brain
doesn't change, but instead you're taking in the information and
(57:41):
you're making these changes in your forests of neurons so
that you can recall it later.
Speaker 2 (57:47):
That's what brain plasticity is all about.
Speaker 1 (57:54):
Go to Eagleman dot com slash podcast for more information
and to find further reading on all of this. Send
me an email at podcast at eagleman dot com with
questions or discussion, and I'm making sporadic episodes in which
I address those until next time. I'm David Eagleman, and
this is Inner Cosmos.
Host
David Eagleman
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