Chapter 6: Evolution of Brain & Behavior

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Welcome back to another Deep Dive.

Today, we are going to do something that might feel a little uncomfortable.

We are going to stare into a mirror.

Metaphorically speaking, I hope.

Well, literally and metaphorically, we're looking at ourselves as a species, and then we're looking at our closest relatives in the animal kingdom.

And we're trying to solve a math problem.

Exactly.

A math problem that, frankly, keeps me up at night sometimes.

It's the 1 .2 % paradox, isn't it?

It is.

If you just look at the raw instruction manual,

the genome,

humans and chimpanzees are, for all intents and purposes, identical.

We share something like 99 % of our DNA.

The actual difference is just a hair over 1%.

About 1 .2%, give or take.

Which, in genetic terms, that's practically a rounding error.

It's nothing.

But then you step back and you look at the final product.

I mean, I'm sitting here talking to a microphone using abstract language.

Communicating with thousands of people you'll never meet through a global network of computers.

Right.

And the chimp is.

Well, the chimp is doing what chimps have been doing for millions of years.

Which is not nothing.

I mean, they're surviving, they're socializing, they have tool use, complex relationships, but it is on a fundamentally different scale.

The divergence is just massive.

We have complex recursive language.

They have a pretty fixed set of vocalizations and gestures.

We walk on two legs by petalism.

They're primarily knuckle walkers.

And maybe the biggest difference of all.

We have populated every single environment on the planet, from the Arctic tundra to the Sahara Desert.

We're everywhere.

While they're restricted to a very specific equatorial belt in Africa and sadly are facing a massive population collapse,

their numbers are dwindling.

So that's the puzzle for today.

That's the central tension of this deep dive.

If the blueprint is 99 % the same, where does all of this come from?

How do you get Shakespeare and space travel and particle physics out of a 1 .2 % genetic tweak?

It's the ultimate nature versus nurture question, really.

And for a long time, the answer people wanted to believe was nurture.

Oh, yeah.

The idea that biology didn't really matter.

I remember reading about those social experiments.

The whole hypothesis was that we're only different because of how we're raised, right?

Exactly.

The nurture argument taken to its absolute extreme.

You had serious scientists back in the mid 20th century who genuinely believed that if you took an infant chimpanzee and just raised it in a typical suburban home.

Diapers, bottle feeding, bedtime stories, the whole nine yards.

That it would effectively become human.

That it would learn language, adopt human customs, and basically erase that 1 .2 % difference through upbringing alone.

I'm guessing this didn't end with the chimps getting his scholarship to Yale.

It definitively did not.

Several researchers, famously the Hayes family and the Kellogg's, they actually did this.

They brought chimps into their homes to live alongside their own children.

Wow.

I can't even imagine that.

And look, the chimps were incredibly socially affectionate.

They learned to mimic all sorts of behaviors using utensils, flushing toilets, things like that.

But they always, always hit a hard cognitive ceiling.

The text mentions the driver's license test as the sort of ultimate insurmountable bar.

It's a bit of a dry joke in the field, but yeah.

No amount of loving human style parenting ever produced a chimp that could grasp abstract grammar or form a truly complex sentence.

Let alone, you know, parallel part.

Right.

So the lesson was clear.

The biology matters.

The hardware matters.

You can't just nurture your way out of your genetic programming.

So that really sets the stage for our mission today.

We are going to be breaking down chapter six of behavioral neuroscience, which is titled evolution of the brain and behavior.

We're finally going to look at the hardware itself.

That's right.

We're going to trace how nervous systems have changed over millions of years.

And to do that, we have to start with the history of the theory itself.

How did we even figure out that evolution happens?

And then from there, we'll look at how specific brains adapt to specific jobs.

And finally, we'll get into the really tricky business of trying to measure brain size and intelligence.

And we'll try to do that without falling into some of the old, very arrogant traps that people have fallen into in the past.

And as always, just so everyone knows the ground rules for these deep dives, we are sticking strictly to the source text.

No outside theories, no personal speculation.

We are your guides through the material as it is presented in this chapter.

Okay, let's dive in.

So to understand where we are now, we have to go back to where we started.

Let's, I don't know, rewind the clock about 200 years.

It's the early 1800s.

What's the general vibe in the scientific community about where all these animals come from?

The vibe is static.

That's really the best word for it.

The dominant view, especially in Western science, was that species were immutable.

They were fixed.

Created as they are.

Precisely.

A dog was created as a dog, a fish as a fish, a bird as a bird.

They were seen as separate, distinct, and unchanging entities.

Each species was its own special creation.

But the people who are actually out there in the field, the naturalists, the ones dissecting animals and collecting fossils,

they started noticing things.

Things that didn't quite fit that clean narrative.

They started seeing patterns.

And this brings us to the very first key concept we need to lock down from the chapter.

Homology.

Homology.

Okay, so this is the arm bone thing, right?

It is the arm bone thing.

But it's so much more profound when you really stop and think about it.

The chapter has a great illustration in figure 6 .1.

It shows the forelimbs of four different mammals.

A human, a dog, a seal, and a bat.

Right.

Now just from an engineering perspective, think about the jobs those four limbs have to do.

They're completely different.

I use my hand for typing, for gripping a coffee cup.

A dog uses its foreleg for running, for absorbing shock.

A seal uses its flipper to propel itself through water.

It's a paddle.

And a bat uses its wing to generate aerodynamic lift.

It's an airfoil.

If I were an engineer tasked with designing those four things from scratch, I would never, ever use the same set of parts.

Absolutely not.

You'd design the wing with lightweight hollow struts, not heavy finger bones.

You'd design a flipper to be stiff and paddle -like.

You'd design a running leg for durability.

But that's not what we see in nature.

Not at all.

When you strip away the skin and the muscle and just look at the skeleton, the bone structure is shockingly almost absurdly identical.

They all have one upper arm bone, the humerus.

They all have two forearm bones, the radius and ulna.

They all have wrist bones, the carpals, and hand bones, the metacarpals.

It's the same fundamental set of Lego bricks, just stretched and squashed into different shapes.

The bat's wing is just a hand with ridiculously elongated fingers and skin stretched between them.

And the seal's flipper is basically a hand where the finger bones are short and flattened and bound together.

So the inference, the only logical conclusion you can draw from that observation is that these aren't four separate independent inventions.

They have to be modifications of a single original plan.

Descent with modification.

That was the key phrase.

It implies that the human, the dog, the seal, and the bat all share a common ancestor who had that specific forelimb bone layout, and that trait was passed down and modified for different purposes in each lineage.

Okay, so that's a huge step, knowing that it happened, but it's a whole other thing to figure out how it happened.

And that brings us to the two heavyweights of biology.

Darwin and Wallace.

Charles Darwin and Alfred Russel Wallace.

I always feel a little bit bad for Wallace, you know.

Darwin gets the statues and the credit, but Wallace basically got to the exact same finish line at the same time.

It's a really fascinating contrast in scientific method.

Darwin was the ultimate grinder.

He was meticulous.

He spent 20 years compiling data after his voyage on the HMS Beagle.

20 years.

He was terrified of publishing until he built an absolutely unassailable mountain of evidence.

He was studying barnacles, breeding pigeons, looking at fossils,

everything he could get his hands on.

He was building a case like a lawyer.

He was.

And Wallace.

Wallace was the intuitive genius, the flash of insight.

He was working in what is now Indonesia, and he came up with the entire idea of natural selection basically overnight while suffering from a malarial fever.

Wow.

He just wrote it down in a fever dream and mailed it off.

Pretty much.

He wrote up a short paper and mailed it to the most famous naturals he knew for feedback, which happened to be Charles Darwin.

Which must have caused Darwin a mild panic attack.

It certainly lit a fire under him to finally publish his life's work, and that became on the origin of species in 1859.

But let's look at the engine they both discovered.

The classic example from the text and from Darwin's own work is what he saw in the Galapagos Islands.

Famous finches.

The finches.

He noticed that on these isolated volcanic islands, the finches were all clearly finches.

They looked generally like the finches he'd seen on the mainland of South America, but they were tweaked.

Each island had its own special version.

And what was the tweak?

How were they different?

It was almost all in their beaks.

On one island, where the primary food source was thick, hard -shelled nuts, the finches had these big, powerful stout beaks, almost like pliers, perfect for cracking them open.

But on another island, where the main food was insects hidden in the bark of trees, the finches had these slender, delicate, almost needle -like beaks, perfect for probing and picking.

And Darwin's brilliant insight wasn't just, oh look, their beaks match their food.

Right.

It was deeper than that.

His insight was that they must have all descended from a single ancestral flock that got blown over from the mainland millions of years ago.

And then they diversified.

Exactly.

Imagine that first flock lands.

By random chance, some have slightly heavier beaks, some have slightly skinnier ones.

On the nut island, the ones with the heavier beaks were just a little bit better at getting food.

They survived a bit more often, had a few more babies.

And passed on their slightly heavier beak genes.

Precisely.

Meanwhile, on the insect island,

the birds with the skinnier beaks had the advantage.

And over thousands and thousands of generations, these tiny advantages accumulate, and the populations drift apart until they become distinct species.

The text breaks this whole logical process down into four specific observations and one massive inference.

I think it's worth walking through them because people tend to oversimplify evolution as just survival of the fittest.

And that phrase really misses the nuance.

I completely agree.

It's an algorithm, really.

A beautiful, simple algorithm.

So observation one, reproduction will increase a population rapidly unless there are limiting factors.

Elephants, codfish, bacteria, everything has way more offspring than can possibly survive.

Observation two,

individuals are not identical.

There is variation within any species.

Just look at a litter of puppies or a classroom full of kids.

It's obvious.

Right.

Some are bigger, some are faster, some have thicker coats.

Observation three, some of that variation is heritable.

It gets passed down from parents to offspring.

Tall parents tend to have tall kids.

And observation four, which is the grim part.

The grim reality, yes.

Not all offsprings survive to reproduce.

In fact, most don't.

There's competition, predation, disease, starvation.

Life is tough.

So you put those four facts together.

You've got overproduction, variation, heritability, and a high mortality rate.

And you can only draw one conclusion from that, the inference.

The individuals who happen to have the variations that make them better suited to their specific environment will be more likely to survive and reproduce.

And they'll pass those helpful traits on.

The unhelpful traits get filtered out because the individuals carrying them don't do as well.

Exactly.

The environment acts as a filter or a sieve.

It's not a conscious force.

It just is.

Over geologic time, the population as a whole shifts to better fit the sieve.

That is natural selection.

The traits that are selected for are called adaptations.

But then Darwin realized something was missing.

Around 1871, he added another piece to the puzzle.

Because survival isn't the only game in town.

Right.

You can be the strongest, fastest, most well -camouflaged survivor in the entire forest.

But if you can't find a mate, your genes die with you.

Your evolutionary journey ends there.

And this explains all the weird, flashy, seemingly unhelpful stuff we see in nature.

Enter sexual selection.

This is the explanation for things that natural selection on its own can't really account for.

Like the peacock's tail.

The peacock's tail is the classic example.

From a pure survival of the fittest standpoint, that tail is an absolute disaster.

It's metabolically expensive to grow.

It's heavy.

It makes you slow.

And it's basically a giant shimmering neon sign for predators that says, free lunch here.

So it should have been selected against.

So why does it exist?

Because the peahens, the females, are choosy.

And for whatever reason, they evolved a preference for males with big, extravagant, colorful tails.

So the male with the most impressive tail gets to mate more often.

So the reproductive advantage of being sexy outweighs the survival disadvantage of being a target.

In that particular ecological context, yes.

It's basically survival of the sexiest, as you said before.

And this becomes incredibly important later when we talk about things like bird song and the evolution of the brain.

The pressure to attract a mate can be just as powerful, if not more powerful, than the pressure to just stay alive.

OK, before we get to the brain itself, I want to double -click on some of this terminology because it's easy to get confused.

We talked about homology.

That's similarity because of a shared ancestor, like our arm and the bat wing.

Right.

But sometimes things look alike for totally different reasons.

Sometimes two animals arrive at the same design, but they're not related at all.

This is a fantastic concept called convergent evolution.

It's when similar ecological pressures produce similar solutions in completely unrelated animal lineages.

Nature basically stumbling upon the same good idea twice.

Or three times.

Or four times.

The textbook uses the example of a tuna and a dolphin.

Perfect.

A tuna is a fish.

It's been in the ocean forever.

A dolphin is a mammal.

Its distant ancestors were land animals that walked on four legs.

They couldn't be much more different in terms of their evolutionary history, but if you just look at their body shape, that sleek,

powerful, torpedo -like form.

They look incredibly similar.

Because the laws of hydrodynamics are the same for everyone.

If you want to move quickly and efficiently through water, that fusiform shape is the optimal solution.

Both the fish lineage and the mammal lineage evolved towards that shape independently.

The term for that physical resemblance, the chapter says, is homoplasy.

Correct.

Homoplasy is the resemblance due to convergent evolution.

Okay, let's nail this down.

Homology.

Same structure.

Shared ancestor.

My arm, batwing.

Got it.

Homoplasy.

Same shape, different ancestor because of a shared job.

The dolphin and the tuna.

Exactly.

And then there's one more to add to the list.

Analogy.

Analogy.

Which is a similar function, but the structures can look totally different.

Right.

Think about the human hand in an elephant's trunk.

They look nothing alike.

One is a modified fin that became a limb.

The other is a fused nose and upper lip.

They couldn't be more different structurally.

But they are analogous because they both serve the function of grasping and manipulating objects in the environment.

So similar job, different structure.

Okay, that's clear.

Homology, homoplasy, analogy.

Got it.

Now back to Darwin for a second.

He had this brilliant theory, but there was a huge gaping hole in it.

A massive one.

He could explain why helpful traits would persist, but he had no idea how they were inherited or where the initial variation came from in the first place.

He didn't know about genes.

He was basically working in the dark on the actual mechanism.

He was.

It wasn't until Gregor Mendel, the Austrian monk working with his pea plants, figured out the basic laws of heredity in 1866.

And even then, his work was ignored for decades.

And then the final piece of the puzzle came in the early 1900s with Hugo de Vries.

Right.

De Vries was studying evening primroses, and he's the one who gave us the concept of mutations.

He explained the glitch in the system, the source of the newness.

Exactly.

Evolution needs raw material to work with.

It needs variation.

De Vries observed that sometimes, just by random chance, spontaneous new traits would appear in his primroses.

These were mutations, random changes in the genetic code.

And that's such a critical point that people often misunderstand.

The mutation itself is completely random.

It's a copying error.

Totally random.

The selection process, however, is the opposite of random.

It's highly non -random.

The environment does the selecting.

Precisely.

Evolution doesn't have a goal.

It's not trying to make a wing or an eye.

A random mutation might happen that makes a patch of skin slightly more light sensitive or makes a limb bone slightly longer.

If that tiny change happens to provide a survival or reproductive advantage in that current environment, it gets selected for.

It's a tinkerer, not an architect.

It's just messing with the parts it has.

That's the perfect analogy.

So now we have the full picture.

Darwin's natural selection plus Mendelian genetics.

This is the modern synthesis of evolutionary theory.

And with this framework, we can start to organize all of life.

Which brings us to taxonomy, the science of classification.

The great filing system of biology.

This was started way before Darwin by Coralus Linnaeus.

He's the one who gave us the two -part naming system, the binomial nomenclature.

Genus species, like Homo sapiens for us, or Canis familiaris for the domestic dog.

Right.

And he also gave us the nested hierarchy for classifying things.

I still use the mnemonic I learned in high school biology.

Kindly put clothes on, for goodness sake.

Classic, kingdom phylum, class, order, family, genus, species.

The text gives a really helpful example.

Tracing the domestic dog all the way up the chain.

It helps visualize how we're zooming out at each level.

It does.

So you start with species.

Familiaris, genus, Canis, which includes dogs, wolves, coyotes, family.

Canidae, which brings in the foxes.

And order.

Carnivora, which includes all the cat family, the bear family, the weasel family.

Then class, mammalia.

Now you're including everything with hair and milk, glands, bats, whales, us, then phylum.

Cordata, which is everything with a backbone.

And finally, kingdom,

animalia.

It's an animal.

It's a nice way to see how we're all related at different levels of distance.

But today, we have a tool Linnaeus could only dream of.

We don't just have to classify things based on what they look like.

We can use their DNA.

This is the modern revolution of phylogeny.

Phylogeny being the evolutionary history or the family tree of a species.

Right.

And DNA gives us an incredible tool to build that tree.

The molecular clock.

The molecular clock.

How does that work?

The basic idea is that mutations in DNA accumulate at a relatively steady, predictable rate over long periods of time.

So I want to know how long ago two species split from a common ancestor.

I can compare their DNA sequences.

And just count the number of differences.

Essentially, yes.

The more differences I find, the longer it's been since they shared that common ancestor.

It allows us to put a timeline on the family tree.

And when we apply that clock to ourselves and our closest relatives, the great apes,

what does figure 6 .4 in the book show us?

It shows us just how close we are.

It confirms that our closest living relative is the chimpanzee.

The DNA difference, as we said, is just over one percent.

And the next closest?

The gorilla.

Our DNA differs from a gorilla's by about 2 .3 percent.

And the clock tells us that the split between the lineage that led to us and the one that led to chimps happened very recently in geologic terms.

The text says about four to six million years ago, though it notes some near data might push that back a bit.

Right.

The estimates are always being refined, but we're in that ballpark.

To put that in perspective, the dinosaurs died out 65 million years ago.

So our divergence from our closest relatives is a very, very recent event.

And it's so important to stress this point because people still get it wrong.

We did not evolve from chimpanzees.

Thank you for saying that.

We did not.

We share a common ancestor with them, an ancestor that was neither a modern human nor a modern chimp.

We are evolutionary cousins, not parent and child.

Which brings us directly to a massive pet peeve of mine.

And the text just attacks it head on, which I love.

That awful March of Progress image.

Ugh.

The t -shirt image.

You know the one.

The hunched over ape, then a slightly less hunched over early hominid, then a caveman with a club, and finally the upright suit wearing modern man at the end.

I absolutely hate that image.

Every single evolutionary biologist on the planet hates that image.

Because it gets everything wrong.

It implies that evolution is a straight line, a ladder, with us at the top.

And that everything else is just a less evolved version of us.

Like a chimp is just an incomplete human or a failed attempt at being human.

Like they're trying to climb the ladder but got stuck on a lower rung.

It's fundamentally wrong.

Evolution is not a ladder.

It's a massively branching bush.

A radiation.

A radiation, exactly.

Every twig on that bush represents a species that is perfectly successful at what it does.

A chimp is not a failed human.

A chimp is a brilliantly successful chimp.

Perfectly adapted to its niche in the forest canopy.

And this idea of the ecological niche is so critical.

Especially for behavioral neuroscience.

Because if we want to understand a brain, we have to understand what the animal does, what's its job.

Precisely.

This is why we don't just study rats as simplified humans.

We study a whole range of different animals because they have evolved unique and sometimes extreme adaptations.

The text actually lays out six specific reasons why researchers choose to study a particular species.

Yeah, this is in box 6 .1.

Let's run through them.

Because it really explains why you might find a neuroscientist with a lab full of, say, barn owls or sea slugs.

Okay, reason one is outstanding features.

Sometimes nature pushes one particular system to the absolute limit.

It creates a champion.

Like the barn owl for hearing.

Exactly.

If you want to understand how a brain pinpoints the location of a sound in space, you study the barn owl.

They hunt in total darkness, purely by sound.

Their brain circuitry for auditory localization is huge, exaggerated, and easier to study than ours.

Okay, makes sense.

Reason two is convenience.

This is just the practical side of science.

Rats and mice are convenient.

They're small, they're cheap to house, they breed quickly, and we have their entire genome mapped.

Or think of Trisophila, the fruit fly.

Generations happen in days, not decades.

Reason three is comparison.

This one's my favorite.

It's so clever.

This is where you can really test a specific hypothesis about brain and behavior.

Let's say you have a theory that the hippocampus of brain structure is crucial for spatial memory.

For making mental maps.

Right, so you find two closely related species that have different lifestyles.

The text uses voles.

The meadow vole is polygamous and has a massive home range he has to navigate to visit different mates.

The pine vole is monogamous and lives its whole life in a small cozy burrow with its partner.

So one is a traveler, the other is a homebody.

And when you look at their brains, what do you find?

The meadow vole, the traveler, has a significantly larger hippocampus relative to its brain size.

The behavioral demand for a good mental map drove the evolution of the hardware.

That's so cool.

Okay, the last three are a bit more straightforward.

Reason four is preservation.

Studying the biology of endangered species to help with conservation efforts.

Reason five is economic importance.

Things like agriculture or pest control.

Right.

And reason six, the big one for medicine, is treatment of disease.

Animal models.

Animal models.

We can't ethically induce Alzheimer's or Parkinson's in a human to test a new drug.

So we use genetically modified mice or other animals that mimic the human disease to develop and test potential treatments.

So using that comparison method, let's dig into some more examples of how an animal's life, its niche,

shapes its brain.

The text uses a great simple phrase.

Complicated lives require complicated brains.

It's a fundamental principle.

Brain tissue is the most metabolically expensive tissue in the body.

The human brain is about 2 % of our body weight, but it burns 20 % of our daily calories.

Wow, 20%.

So you don't evolve a big expensive brain unless you absolutely need it.

There has to be a major payoff.

And one of the biggest drivers seems to be finding food, foraging strategy.

Yes.

The text makes a great comparison between animals that eat leaves or grass and animals that eat fruit.

A cow versus a squirrel, for instance.

Or in the primate world, a howler monkey, which mainly eats leaves, versus a spider monkey, which mainly eats fruit.

Leaves are everywhere.

They're easy to find.

It doesn't take a lot of cognitive horsepower to be a grazer.

Or you just wander and chew.

But fruit.

Fruit is a challenge.

It's patchy.

It's only on certain trees, not others.

It's only ripe for a short period of time, and it's a high -value resource, so other animals are competing for it.

So to be a successful fruit eater, you need a mental map of your territory.

You need to remember which trees have fruit and when.

You need a calendar in your head.

It requires memory, planning, and navigation.

It's a much more complex cognitive task.

And sure enough, the data shows this clearly.

Fruit -eating mammals, whether they're primates or bats or rodents, have consistently larger brains for their body size than their leaf -eating relatives.

The demand for that complex foraging strategy literally paid for the bigger brain.

It did.

And we see the same pattern in birds.

The chapter talks about innovative bird species.

These are the clever ones, the problem solvers.

The text mentions magpies learning to dig up potatoes from a farmer's field, or crows in Japan.

Oh, the crows are amazing.

They'll take a hard nut, like a walnut, that they can't crack with their beak.

So they fly over a street, drop the nut in front of the tires of a car at a red light.

The car runs it over and cracks it for them.

And then they hop down and get the prize.

That is an incredible sequence of planned actions.

That's terrifyingly smart.

It is.

And when researchers measure their brains, these innovative problem -solving species, like crows and magpies, have significantly larger forebrains relative to their body size than birds that just peck at seeds on the ground.

Okay, let's talk about one of the weirdest brains out there, which gets its own special section,

the platypus.

Ah, the platypus.

Yeah.

Box 6 .2, it's evolution's practical joke.

An egg -laying mammal with a duck's bill, a beaver's tail, and venomous spurs.

But for neuroscience, that bill is the main event.

It's not just a beak for scooping, is it?

Not at all.

It's a highly sophisticated sensory scanning device.

The platypus hunts for shrimp and insects in murky riverbeds, often at night.

And when it dives, it closes its eyes, its ears, and its nostrils.

So it's completely cut off from the normal senses of sight, hearing, and smell.

Totally blind and deaf underwater.

So how does it find a tiny shrimp buried in the mud?

The bill.

The skin of the bill is packed with tens of thousands of receptors.

First you have mechanoreceptors, which are for touch.

It can feel the slightest movement of water.

But then there's the really cool part,

electroreceptors.

It can sense electricity.

It can sense the tiny electrical fields generated by the muscle contractions of its prey.

When a shrimp twitches its tail, it creates a faint electrical disturbance in the water, and the platypus's bill picks it up.

So it's using a combination of touch and electrical detection.

Exactly.

And the brain map reflects this specialization.

If you look at a diagram of the platypus's sensory cortex, it's not like ours at all.

Our sensory map is dominated by our hands and our face.

The platypus map is almost entirely devoted to the bill.

The brain's real estate is allocated based on the sensory world, the umwelt of that animal.

That's a perfect illustration of the principle.

Okay, another great example of brain matching behavior is the food stores, the little hoarders of the animal kingdom.

Birds like chickadees, nutcrackers, and jays.

In the autumn, they will hide thousands of individual seeds in thousands of different locations in tree bark under leaves to retrieve later in the winter.

I lose my car keys if I don't put them in the exact same spot every single day.

And they have to remember thousands of locations months later, often when the landscape is covered in snow.

It's an incredible feat of spatial memory.

So you'd predict they have something special in the memory part of their brain.

And they absolutely do.

The hippocampus, which is the key brain structure for forming spatial memories,

is supersized in these food storing birds.

Figure 6 .6 in the text shows it clearly.

It's about twice as large relative to the rest of the brain compared to their non -storing relatives.

And it gets even cooler than that.

It does.

The hippocampus in these birds actually shows neuroplasticity.

It physically grows in the fall, adding new neurons when they're actively cashing food.

And then it can shrink back down later.

The brain is changing with the seasons to meet the cognitive demand.

That's incredible.

OK, one more example of adaptation.

And this one brings us back to sexual selection.

The songbirds.

Right.

The chapter uses European warblers as an example.

In some warbler species, the male has a very simple repetitive song, just one basic tune.

In other closely related species, the males have a huge complex repertoire of dozens of different songs that they string together to impress the females.

And the females, being choosy, prefer the male with the bigger, more complex playlist.

They do.

A complex song is an honest signal of a healthy fit brain.

And if you look at the brains of the males from these different species, you find a specific brain region called the HVC, the Higher Vocal Center.

And you're going to tell me its size correlates with the number of songs.

Perfectly.

Figure 6 .7 shows a beautiful graph.

The bigger the song repertoire, the bigger the HVC.

The female preference for complex songs created a selective pressure that literally sculpted the male brain over generations.

Amazing.

Okay, so we've seen these specific adaptations.

Now let's try to zoom out again and look at the big picture of how vertebrate brains evolved in general.

Right.

And before we jump into vertebrates, we should give a quick nod to the invertebrates, the animals without backbones.

They make up something like 97 % of all animal life on earth.

And they are fantastic models for neuroscience, precisely because they're simple.

They're simple.

The sea slug, a plesia, has gigantic neurons you can literally see with the naked eye.

This allowed Eric Kandel to figure out the basic molecular mechanisms of memory, which won him a Nobel Prize.

Or the little worm, sea elegans.

My favorite.

A tiny transparent worm that has exactly 302 neurons.

Not about 300, exactly 302.

And scientists have mapped every single connection between every one of those neurons.

It's the only complete wiring diagram or connectome that we have for any animal.

If you want to understand how a neural circuit works at the most fundamental level, you start there.

But for us vertebrates, everything from a lamprey to a human, there is a common architectural plan.

The text lists six main features that all our nervous systems share.

You can think of this as the vertebrate starter pack number one.

We all develop from a hollow neural tube in the embryo.

Number two, bilateral symmetry.

Our nervous system has a left side and a right side that are rough mirror images.

Number three, segmentation.

The spinal cord is organized in segments with pairs of spinal nerves coming out at each level.

Number four, hierarchical control.

The brain is in charge of the spinal cord, which is in charge of the muscles.

There's a clear chain of command.

Number five, we have separate central and peripheral nervous systems.

The CNS brain and spinal cord is protected inside bone.

The PNS is all the nerves that go out to the body.

And finally, number six, localization of function.

Specific parts of the brain do specific jobs.

The back of your brain does vision, a strip on the side does hearing, and so on.

So whether you are a fish, a frog, a bird, or a philosopher, your nervous system is built on that same fundamental blueprint.

But the proportions of the different parts have changed dramatically.

And figure 6 .10 is the classic comparison that shows this.

The rat brain versus the human brain.

Visually, the difference is striking.

The rat brain is about 2 grams the size of a bean, and it's completely smooth.

The human brain is about 1400 grams the size of a small cantaloupe, and it looks like a giant wrinkly walnut.

That wrinkling is the key to everything, isn't it?

It really is.

That wrinkling is called convolution.

The ridges are called gyri, and the grooves are called sulci.

And what this does is it allows you to pack an enormous amount of surface area, which is at the cerebral cortex,

into the limited space of the skull.

If you were to iron out the human cortex, how big would it be?

It would cover a large card table.

If you unfolded a rat's smooth cortex, it would be about the size of a postage stamp.

And the investment in different functions is also totally different.

The rat brain diagram shows this huge structure right at the front.

The olfactory bulb.

It's massive in a rat.

Because for a rat, the world is primarily a world of smells.

Smell is life and death.

Finding food, finding mates, avoiding predators.

All of it.

In humans, our olfactory bulb is tiny in comparison.

But our cerebral hemispheres, especially the parts for vision and for abstract thought and planning, what we call association cortex, are absolutely gigantic.

Once again, the anatomy reflects the ecological niche.

So how do we track these changes over deep evolutionary time?

Brains are soft tissue.

They don't fossilize.

They turn to mush, yeah.

So we have to be clever.

We use two main tricks.

The first is making endocasts.

Endocasts.

You take the fossilized skull of an extinct animal and you pour latex or plaster inside.

It fills the cavity.

And when you pull it out, you have a mold and endocast of the brain's external shape and size.

You can't see the internal wiring, but you can see the proportions of the major lobes.

What's the second trick?

We study living animals that are thought to resemble ancient ancestors.

They're sometimes called living fossils.

Like the opossum.

The opossum is a perfect example.

It's a mammal, but it has a brain structure that's very similar to the earliest mammals that were scurrying around the feet of the dinosaurs.

So studying a living opossum brain gives us a pretty good window into what a primitive mammalian brain looked like.

And when we use these methods to look at the trend line of vertebrate brain evolution,

what's the big story?

The big story, especially for mammals, is the rise of the cortex.

The cerebral cortex.

This is the outer wrinkly layer.

Exactly.

If you look at our distant ancestors, like reptiles, they have a cortex, but it's a simple three -layered structure.

We call it archicortex or old cortex.

The new innovation in mammals was a much more complex six -layered cortex.

The neocortex.

New cortex.

And over the course of mammalian evolution, this neocortex has just exploded in size.

In recent mammals, and especially in us, it makes up more than 50 % of the entire brain's volume.

It's the seat of all our most complex cognitive abilities.

Perception, language, planning, consciousness.

So it seems simple, then.

Bigger is better, right?

The story is just that brains got bigger and bigger.

You have to be careful with that.

It's a very tempting conclusion.

I know.

I know.

I'm setting you up.

This brings us to the whole problem of body size and the encephalization factor.

Exactly.

If you just go by absolute brain weight, humans are not the champions.

An elephant's brain weighs about 5 ,000 grams.

A sperm whale's brain can be 8 ,000 grams or more.

And ours is only about 1 ,400 grams.

Right.

So if raw mass equaled intelligence,

sperm whales would be doing theoretical physics and would be...

Well, we wouldn't.

So what's wrong with that logic?

The problem is that a huge body requires a huge brain just to run the basic operations.

You have more skin, so you need more sensory cortex to process touch.

You have more muscle, so you need more motor cortex to move it.

A lot of that extra brain mass is just administrative overhead.

So you have to correct for body size.

You need to look at the ratio.

Precisely.

And this is what figure 6 .33 in the book shows so well.

If you plot the brain weight versus the body weight for all kinds of different animals, you find that they don't fall randomly on the graph.

They fall along a pretty straight diagonal line.

The line of S -fit.

Right.

That line basically tells you how big a brain you should have for an animal of your particular body size.

It's the average.

And the really interesting thing is not where you are on the line, but how far you are off the line.

That is the key insight.

This distance above or below the line is called the encephalization factor, or K.

So who's below the line?

The opossum, our primitive mammal example, is well below the line.

It has a smaller brain than you'd expect for its body size.

Average mammals, like a cat, are right on the line.

And above the line.

The chimpanzee is significantly above the line.

It has more brain than it needs for its body size.

And humans.

We are the outliers of the outliers.

We are further above that line than any other animal.

We have a massive amount of extra brain tissue that isn't dedicated to just running the body.

That's our high K factor.

But I feel like I have to make a defense here for an animal that gets a bad rap for being dumb.

The text brings up the dinosaurs.

Yeah.

And that classic Gary Larson far -side cartoon.

Ah, yes.

The one with the stegosaurus at the podium.

The picture is pretty bleak, gentlemen.

The world's climates are changing.

The mammals are taking over.

And we all have a brain the size of a walnut.

It's one of the greatest cartoons of all time.

But from a scientific standpoint, it's a little unfair to the dinosaurs.

Just as for T -Rex.

The text actually corrects this misconception.

An animal like a Tyrannosaurus rex didn't have a brain the size of a walnut.

Based on endocasts, its brain was probably around 700 grams.

Wait, 700 grams?

That's half the size of a human brain.

That's not small at all.

It's not a walnut, that's for sure.

But here's the crucial part.

For a reptile of that enormous body size, a 700 -gram brain puts it right on the line of best fit for reptiles.

So they weren't stupid.

They were exactly as smart as they needed to be.

They had a perfectly appropriate brain for their niche as a giant reptilian predator.

They didn't go extinct because they were dumb.

They went extinct because a six -mile -wide asteroid slammed into the planet.

No amount of encephalization can save you from that.

That's a very fair point.

Okay, so to wrap this all up.

We've gone from Darwin's observations to the modern synthesis with genetics.

We've seen how ecological niches sculpt specific brain regions.

And now we see that it's not raw brain size, but the encephalization factor that makes humans stand out.

We've solved the 1 .2 % mystery, right?

It's just that we have way more brain per pound.

Well, not so fast.

The chapter ends, as good science often does, with a note of caution.

Of course it does, just when I thought we had the answer.

We love to focus on size and neuron counts because those are things we can measure easily.

You can put a brain on a scale.

You can slice it up and count cells.

But the text suggests that the real secret to human uniqueness, the thing that 1 .2 % of DNA is really doing, might not be about size at all.

It's not the size of the hard drive.

It's the software.

Or the wiring.

It's about connectivity and gene expression.

That tiny genetic difference might not be building fundamentally new brain parts.

It might be changing the timing of development.

It might be allowing neurons to grow and form connections for a longer period of time, creating much more complex and flexible neural networks.

So we're not just a chimp with a bigger brain.

We might be a chimp with a brain that is wired up in a fundamentally different way.

That's a great way to put it.

It might be the patterns of connectivity, the speed of signaling, the specific genes that are turned on or off in brain cells.

That's where the real difference lies.

It's not just how many neurons you have, but how they talk to each other.

That is a fascinating and actually a much more humbling thought to leave us with.

We are not just bigger.

We are a unique biological experiment in computational complexity.

I think that's exactly right.

Well, that officially wraps up our deep dive into Chapter 6.

I can safely say I will never look at a squirrel or a platypus or even a crow the same way again.

Just be sure to appreciate their hippocampus and their impressive forebrains.

I will do that.

A huge thanks for listening, everyone.

This has been the Last Minute Lecture Team helping you get to grips with a source material without the headache.

We'll see you next time.

Bye.