0:03

Hi, I'm Lindsay. And I'm

0:05

Marshall. Welcome to Tumble, the show where we explore

0:07

stories of science discovery. Today

0:10

we're asking, were T-Rexes

0:12

smart? Were they bloodthirsty

0:15

carnivores or just hungry for

0:16

knowledge? Could they be both? We're

0:19

going to find out how the brains

0:21

of extinct dinosaurs can help

0:23

us understand what it means to

0:25

be smart.

0:35

Our listener Penny sent us this question.

0:38

Hi, my name is Penny Jones and

0:40

I'm seven years old. My question is,

0:43

how did smartness begin?

0:45

How did smartness begin? Like,

0:48

like when could we call something smart? It's

0:51

a tricky question. I'm going to guess sometime

0:54

after rocks. Penny

0:56

has an idea of how scientists would

0:59

find out. I also think

1:01

scientists will find out

1:03

how smartness began by studying

1:06

the time of the dinosaurs because dinosaurs

1:08

were quite smart.

1:09

That's an interesting idea,

1:12

but why does Penny think dinosaurs were smart? I

1:14

feel like the stereotype is that they're big dum-dums,

1:17

except for velociraptors.

1:19

Why did velociraptors get

1:21

all the credit for the brain? You got to

1:23

be smart to hunt a...

1:26

what did they hunt? I have no idea. So

1:29

no real reason you can think of why

1:32

velociraptors were smart. But

1:34

it makes me wonder why we think of some

1:37

animals as smart, like a wise

1:39

owl or a wily fox.

1:42

What

1:42

makes an animal smart? And, you

1:45

know, what makes us humans smart?

1:47

Are we even smart? Let's

1:51

ask our listeners, what do you think

1:53

smartness is? And are dinosaurs

1:55

smart? How do you think scientists would find

1:57

out? Think about it, because we'll

1:59

be back.

1:59

with a scientist who studied brains

2:02

and smartness in all kinds of

2:04

animals, including Tyrannosaurus

2:06

Rex.

2:12

Susana Herculano-Hozell

2:15

is a Brazilian-born neuroscientist,

2:17

and she knows that most people don't

2:19

think that T. Rex was very smart.

2:23

Everybody has this image of the improbably

2:26

gigantic creature with

2:28

these person-sized

2:31

teeth, and everybody

2:34

loves to debate whether

2:36

they were just dumb reptiles.

2:40

I mean, T. Rex is definitely a frequent topic

2:42

of conversation in our house, especially

2:44

among the younger members, like me.

2:46

The household

2:48

consensus is that T. Rex is very

2:51

cool, no matter how smart

2:52

they were. They're being person-sized

2:54

teeth. Those are cool. But Susana's

2:57

a neuroscientist, which

2:59

means she wants to go further beyond

3:01

the teeth all the way up to the brains.

3:04

And while T. Rex is impressive in size,

3:07

its brain is not.

3:08

I'll concede

3:11

it's true that when you look at the

3:13

skull in that gigantic

3:15

skull, the brain looks

3:18

like an afterthought. It's like a pear

3:20

sitting in the trunk of a car, really.

3:23

It looks pathetic. It looks meaningless. It's

3:26

like a pear sitting in the trunk of a car.

3:30

That would rattle around a lot. Well,

3:33

that's hilarious. So why was Susana interested

3:35

in studying T. Rex brains? It's

3:37

not like they're going to bring them back from extinction,

3:40

right? I

3:43

hope not. Susana

3:45

had an idea similar to Penny's. Looking

3:48

at dinosaurs might be a good way

3:51

to learn about smartness. She

3:53

wanted to question ideas about how

3:55

smart different animals are. And

3:58

to understand that, Susana.

3:59

Susanna says we have to answer this

4:02

question. First, what is

4:04

this smartness

4:06

thing that we're talking about? Yeah,

4:09

like, I

4:09

mean, I guess smartness can mean a lot of things.

4:12

Susanna agrees. I don't think

4:14

intelligence is what we

4:16

measure with exams at

4:18

school. So I had to come up with

4:21

a

4:21

working definition of intelligence,

4:24

of smartness. Susanna's

4:26

working definition wasn't something

4:29

she could just go and look up in the dictionary.

4:31

And a working definition to a scientist

4:34

is something that you can

4:36

test.

4:38

So she needed a definition that she could do experiments

4:41

to see if it was correct or not. Exactly.

4:44

She wanted to define smartness so she could

4:47

compare intelligence across

4:49

species. The definition needed

4:51

to work for animals, not just humans.

4:54

So the definition that I came up with

4:57

is that intelligence is

5:00

flexibility. It's behavioral flexibility.

5:03

Behavioral flexibility? What

5:05

does that mean? What that means is

5:08

you're intelligent if you're capable

5:11

of acting in different

5:13

ways, in different circumstances,

5:16

in different situations after

5:19

you've tried something

5:21

and it worked or it didn't work, can you

5:23

change your behavior? Can you do

5:25

things differently?

5:26

Okay, so she's saying that intelligence

5:29

is about being able to adapt your behavior

5:31

to what you've learned. Yes, and

5:33

Susanna looked to what's inside

5:36

the brain to test her ideas about

5:38

smartness. Neurons

5:40

are the cells that form

5:43

brains and that

5:45

move signals along different

5:47

parts of the brain and actually across different

5:50

parts of the body too.

5:59

might determine how smart an

6:02

animal is. Then it follows

6:05

that the more these units that you have,

6:07

then the more capabilities you have

6:10

of doing things with those signals.

6:13

So the

6:14

more neurons you have, the more things you can do with

6:16

them, like build houses, cook meals,

6:18

or circle toys in a catalog

6:20

that you really hope you'll get for your birthday.

6:22

Exactly. So Susanna's

6:25

next step was to find a way to

6:27

count neurons in different types

6:29

of brains.

6:31

So maybe this sounds gross,

6:34

maybe this actually sounds really cool,

6:36

but however that sounds, the truth

6:39

is, I count neurons

6:41

by turning brains into soup.

6:43

She turns

6:46

the brains into soup? Like, is

6:48

it good soup? Does she season

6:50

it with celery?

6:51

So are you coming

6:53

down on the gross or cool side of the

6:55

brain soup dilemma? Um,

6:58

I need to know more. All

7:02

right, let's be clear that brain soup is

7:04

not for eating, it's for

7:06

science. It's science soup, and

7:08

here's the recipe.

7:10

Take your brain of interest, cut out the

7:12

part that you want to study, cut it

7:15

up, dice it. You're gonna turn it

7:17

into mush with detergent. Turn

7:20

it into a soup.

7:20

Sounds like detergent would really

7:23

like cut out the eating element of the

7:25

soup. Yeah, I don't

7:27

like eating soap and other

7:29

non-food ingredients with my soup.

7:32

Pretty much ruins things. It's

7:35

like, man, this is some great brain soup except

7:37

for the detergent part. Could you maybe

7:40

cut that out? Just tastes like soap. Replace

7:42

it with carrots.

7:42

So anyhow, after

7:45

the brain soup is blended up, it's

7:47

ready to study. Yum. Then

7:50

collect some of your soup and go to

7:52

the microscope, count how many cells

7:54

you have.

7:55

It's basically just counting the little noodles

7:57

in your bowl of chicken noodle soup. Yes,

8:00

make that a microscopic bowl of brain

8:03

soup. So

8:06

after Susanna counts the cells, she

8:09

does some math to multiply the number

8:11

of neurons found in different parts

8:13

of the brain. And doing that,

8:16

she discovered something really important,

8:18

which is that a bigger brain doesn't

8:20

necessarily mean more neurons.

8:24

Neurons are maybe the only

8:26

cell in the body that exists

8:28

in different sizes. We have tiny

8:30

little neurons and we also have gigantic

8:33

neurons inside the brain.

8:34

Wow, so neurons are the only cells

8:37

that come in different sizes? Yeah,

8:39

which means that you can pack more

8:41

neurons into a smaller brain if

8:44

the neurons are smaller. And to

8:46

see how that's true, you only have

8:48

to take the fact that elephants have much

8:50

bigger brains than us. We

8:53

study elephants and not the other way

8:55

around. So yeah, it would be weird

8:56

if elephants were trying to sign us up

8:58

in their research study. Right,

9:01

and that's because it's not one-size-fits-all

9:04

when it comes to brains. Susanna

9:06

found that each type of animal has

9:09

a different equation behind their number

9:11

of neurons.

9:13

Once you realize that a

9:15

primate brain is made in a completely

9:17

different way from in terms

9:20

of numbers, from a cat

9:22

brain or a dog brain, then

9:24

you really cannot compare one to the

9:26

other.

9:27

So it's kind of like trying to compare apples

9:29

to oranges. It just doesn't work

9:31

unless you're trying to decide which is the better fruit.

9:35

You know, I've done that and it is very hard.

9:37

I'm sure. So Susanna

9:40

had to blend a lot of brains

9:43

to get a good understanding of the animal kingdom

9:46

and she made a lot of interesting

9:48

discoveries about living animals

9:50

along the way. But you might

9:52

be wondering, how does this all work

9:54

with the T-Rex?

9:55

I'd gotten so into the brain soup part

9:58

that I'd kind of forgotten all about the T-Rex. but

10:00

now that you mention it, I am wondering,

10:03

what does this have to do with a T-Rex? Can

10:05

you make T-Rex brain soup? We'll

10:08

find out after this short break.

10:18

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10:20

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10:22

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10:49

Okay, we're back. When we left off,

10:52

Susanna had blended a bunch of

10:54

brains to figure out how many neurons

10:56

are in the brains of each type of animal.

10:59

But

11:00

what does she do when the brain she wants

11:02

to know about doesn't exist

11:05

anymore? So this is where

11:08

science really turns

11:10

into detective work, when

11:12

we try to understand the

11:14

forms of life that existed before

11:16

us.

11:18

Susanna had to find a different way

11:20

to crack the case of the T-Rex

11:23

smarts. Yeah, if this is a detective story,

11:25

where's the evidence? Because it really

11:27

doesn't seem like brains could fossilize.

11:29

That's exactly right. There are

11:32

no T-Rex brains just lying

11:34

around. Instead of turning

11:36

into stone that is

11:38

preserved over millions of years

11:40

like bones are, their brains

11:43

just dissolve away. So

11:45

Susanna turned to the next best thing,

11:48

the dinosaurs that are still alive.

11:51

One really interesting thing about

11:54

dinosaurs that not everybody

11:56

realizes is that there

11:59

are still

11:59

some living dinosaurs

12:02

amongst us. And that's

12:04

the birds, right? Fortunately,

12:07

Susanna had a list of neuron

12:09

estimates for all different birds.

12:12

So she's looking at bird brains. Come

12:15

to think of it, bird brain is sort of an insult for

12:17

being not smart. So how's that going

12:19

to go?

12:20

You might be surprised. Actually,

12:22

the non-flying birds,

12:25

they are the ones

12:28

that are the closest cousins

12:31

to dinosaurs like

12:33

T. rex. And that was exactly

12:35

my starting point.

12:37

So Susanna had a different kind

12:39

of evidence than brain soup. She

12:41

had her neuron estimates for living birds

12:44

and she had an estimate for the

12:46

size of a T. rex brain.

12:49

So what can she do with that? She can make

12:51

some assumptions and then do

12:53

some math. I could

12:55

just presume that, well,

12:58

if they have the brain size

13:00

that you would expect for their bodies, if

13:02

they also had their brains

13:05

made in the same way that other birds,

13:07

the remaining dinosaurs, are still

13:10

made to this day, then

13:12

if I know how large their brain

13:14

was, I can actually calculate

13:18

very quickly with very simple math

13:21

how many neurons that brain must

13:23

have had.

13:24

Okay, so what did she find? She

13:27

found something that kind of

13:29

frightened her. Even

13:31

though I'm never going to have a real

13:34

dinosaur brain to study, there's

13:36

very good reason to believe that

13:38

with a brain that big and it

13:41

being a close cousin to living

13:43

birds, then it probably

13:46

had something in the order of two

13:48

to three billion neurons, which makes

13:51

T. rex horribly,

13:54

horribly scary.

13:56

The

14:00

cortex, the part of the brain that scientists

14:02

believe plays the biggest role in

14:04

thinking. So is like two to three billion

14:07

neurons a lot of neurons? It

14:09

seems like a lot.

14:10

When you're a fearsome giant carnivore,

14:13

it is. So let me

14:15

put this into context. The vast

14:17

majority of animals have

14:20

fewer than one billion

14:22

neurons. That's one with nine

14:24

zeros. Very

14:27

few animals have two

14:30

or more billion neurons.

14:31

Also T. rex could be on like

14:34

an elite level of intelligence, like doing

14:36

math with its tiny little arms.

14:38

Why do you need arms to do math

14:40

though? How are you going to hold the chalk? Well

14:44

let's just say that for the animal kingdom,

14:47

T. rex was pretty smart. The

14:49

most neurons you'll find in a living

14:52

bird is in a macaw

14:54

with about two to three billion neurons,

14:57

which is exactly how many I could

14:59

estimate that T.

15:01

rex would have had two to

15:04

three billion neurons.

15:06

Some people say macaws are about

15:08

as smart as a human toddler. Okay,

15:12

I'm starting to get the scary thing because I can only

15:14

imagine the mind of a toddler in a giant

15:16

carnivore that could knock over a building.

15:19

Yeah.

15:20

So you really have to get

15:22

their meals into the right color ball or

15:24

the consequences are going to be

15:27

very, very harsh. But

15:30

Susanna realized that T. rex's

15:33

would have something else in common

15:35

with macaws. They're the ones that

15:37

are pretty crafty. They're

15:39

flexible. So they're smart,

15:41

intelligent in that way that

15:44

I like to define it.

15:45

So basically T. rex's are going to be

15:47

eating us for dinner if they want or,

15:50

you know, whatever they wanted to eat at

15:52

the time when they were alive, like a triceratops

15:54

or something.

15:55

They really had their pick of snacks.

15:58

Anything they could catch. Well, so

16:01

Penny, who asked our original question,

16:03

thought that looking back to the time of the dinosaurs

16:05

would help us find when smartness started. So

16:08

does it? Well Susana

16:10

wanted to study T. rexes to

16:13

get a new perspective on how ancient

16:15

animals may have lived. And

16:18

there was another good reason to study them.

16:20

Come on, how could I not? Totally

16:23

understandable. So

16:26

maybe T. rexes were smarter than

16:28

we give them credit for, but Susana

16:31

says that dinosaurs definitely weren't

16:33

the first smart creatures on

16:35

Earth.

16:37

So to come back to her question, when

16:39

did smartness appear? We

16:42

can say that capability

16:45

of doing things differently, of

16:47

being flexible, that capability

16:50

has been there for a long, long,

16:52

long time, and it's a capability that

16:55

we find in every single bony

16:58

creature. So anything with

17:00

a bone in its body probably has some level

17:02

of intelligence. Right, by Susana's

17:05

definition. The first bony

17:08

animals were also pretty small creatures,

17:10

and they increased over time, and they also

17:13

gained neurons over time.

17:15

So you don't need to have a big brain or lots

17:17

of neurons to be considered smart. Yeah,

17:20

we all make the best of what we've got to

17:22

work with. Certainly I

17:24

try. And T. rexes

17:26

probably would have kept on doing pretty well

17:29

if that meddling asteroid hadn't shown

17:31

up.

17:32

Which you can learn all about in our episode,

17:34

The Dinosaur Asteroid. But

17:36

even though Susana's made a pretty convincing case

17:38

for how smart T. rexes were, is it

17:41

ever really possible to know the truth?

17:43

Susana says there's only one way

17:45

to know for sure. Well,

17:48

we would love to have a time machine, of course.

17:51

Right? That would be the only way to really

17:53

settle any of these questions.

17:55

I guess those questions and like a

17:57

lot other questions. Yeah,

18:01

well, I think that's Susana's way

18:03

of saying it's impossible to

18:05

know for sure. But science

18:07

is a tool we have to get as close

18:10

as we can to knowing and

18:12

to keep questioning what we think

18:14

we know. I think science

18:17

is made of these

18:20

assumptions, things that we

18:22

believe are true, and then

18:25

somebody gets curious and goes there

18:27

and asks, do we really

18:29

understand

18:29

this? Do we really know how

18:32

this works? So we never have to stop

18:34

asking questions, even if it seems like

18:36

someone has the answer now. Yes,

18:39

and as long as, like Susana, you

18:41

do the work of getting good evidence however

18:44

you can. That's the nature

18:46

of science. It's great.

18:49

It's actually very comforting

18:51

and refreshing in a way to

18:53

realize that everybody can

18:55

ask these questions and everybody

18:58

can challenge an idea

19:00

and have this very healthy

19:03

custom of just hearing

19:06

something the first time stated as

19:08

a fact and going, hmm, I wonder

19:10

if we really, really know that.

19:17

You know, I think that's a pretty good thing to do whenever

19:19

somebody tells you that they know something. It's

19:22

a pretty smart thing to do after all. So

19:30

you've learned that Susana defines smartness as

19:32

being flexible in your behavior. Think

19:34

of how you're smart in this way, and

19:36

then think about animals. Observe

19:39

the animals you see in your own life, in

19:41

your home or around your house. What

19:44

kind of decisions are they making and

19:47

how could they be smart about them?

19:48

Maybe it's your dog figuring out

19:51

how to get you to take it for a walk or a bird

19:53

hanging around where they know humans leave their

19:55

food.

19:56

Try drawing a picture of the smart

19:58

behaviors you see in Send it to us

20:00

at tumblrpodcastedgmail.com.

20:03

We'd love to see what you find.

20:08

Thanks to Dr. Susana Herculano-Hozal,

20:11

Associate Professor at Vanderbilt University.

20:14

Also thanks to our listener Penny and Ian

20:17

for sending in their questions about smartness.

20:20

You can hear more about Susana's research on brains

20:22

in our bonus interview episode on Patreon. Just

20:25

support our show at the $1 level or hire

20:27

at patreon.com slash Tumble Podcasts.

20:29

And we'll have more free resources

20:32

to learn about neuroscience available on

20:34

the blog on our website, sciencepodcastforkids.com.

20:38

Sarah Robertson-Lence edited

20:40

this show and designed the episode Art. Elliott

20:42

Hijaj is our production assistant and Gary

20:45

Calhoun-James engineered and mixed this episode.

20:48

I'm Lindsay Patterson and I wrote this

20:50

episode. And I'm Marshall Escamilla

20:52

and I made all the music and sound design

20:54

for this episode. Tumble is a production

20:56

of Tumble Media. Thanks for listening and

20:59

stay tuned for more stories of science

21:01

discovery.

21:05

Thanks so much for listening to that episode. And

21:07

now that it's over, we've got birthday shout outs

21:10

to give to our supporters on Patreon. Happy

21:12

birthday to Zane on April 30th. Continue

21:15

to keep asking questions and being curious. Eliza

21:18

P, happy birthday on May 2nd. Nisha,

21:21

your family is so proud of you and love that

21:23

you love science. Mommy, daddy

21:25

and Ading Rajitha love you and happy

21:28

birthday on May 2nd.

21:29

Laya Windessai, keep exploring.

21:32

Maybe this year you'll find a baby dinosaur fairy

21:34

under a mushroom. Happy birthday on May

21:36

5th. Felix, your parents

21:38

love you and are so proud of your boundless

21:41

curiosity

21:42

and happy birthday on May 6th.

21:44

Paige, mom and dad love you and happy birthday

21:46

on May 5th.