All language subtitles for Me and My Brain.en

Our brain is often compared
to a control tower

that simply processes

information from all our senses

and makes us react
in the most rational way

possible.

Together, we'll discover

it's not that simple.

Today, a multidisciplinary field

called cognitive science,

which includes neuroscience,

psychology, linguistics,

anthropology, philosophy
and artificial intelligence,

has studied how we function:

our perceptions,
our decision-making,

both individually and collectively.

Thanks to their research

we'll discover
a very different brain.

A brain that filters,
predicts, interprets,

reconstructs reality
and even tricks us.

EPISODE 1: ME AND MY BRAIN

I'm Albert Moukheiber,

clinical psychologist
and cognitive neuroscience PhD.

Follow me to discover

our brain's hidden abilities.

I'm at a fairground
because this magical place

plays with our senses
and perceptions,

especially with our brain.

All these sounds,

lights,

and smells

would just be a chaotic mess

without hundreds of operations

happening in our brain every second.

These are called
cognitive processes.

These mechanisms
that process information

we receive

to react to situations,

make choices, solve problems,

and interact with others.

In short, to live our human lives.

But our brain

doesn't show us the
world accurately.

Nothing is more dangerous

than thinking we can access reality.

The brain is not a passive organ

that just receives information

but rather one that
extrapolates and predicts

missing information.

We perceive reality

but then we need to reconstruct

a three-dimensional world,
the real world,

but not as directly seen
by our eyes.

The brain is a filter that selects

and even distorts
external information.

In our world
of multiple interactions,

understanding how our brain works,

its strengths and weaknesses,
is vital.

We live in a complex world,

constantly bombarded
with information.

At the same time,

our cognitive resources
are very limited.

Yet we manage to function.

To make up
for this lack of resources,

our brain is constantly filtering

a large amount of this information.

FILTERING

For instance, to listen to me

you must have filtered out

a lot of sensory information:

ambient noise,

the texture of the seat
you're sitting on,

your breathing...

Your brain has to deal with

many inputs at once,

but can't retain them all.

So how does it select them?

To understand this,
we need to go back

to the very foundation
of our contact with the world:

our perception,

which isn't as reliable
as we might think.

PERCEPTION

Yves Rossetti

is a physiology professor
at the Lyon Faculty of Medicine.

He studies the links
between perception and action.

We don't have access to reality.

What we have access to

is the effect of
the world around us,

of the matter and energy around us

on our receptors.

Even though I desperately
have the illusion

that I see an object in front of me,

that I see you facing me,

what I perceive in my brain

is only the effect you have
on my retina.

The visual system
is a good way to understand

how we perceive the world around us.

Our retina is made up
of photoreceptors

that capture light

and convert it
into electrical signals

sent to the brain
through the optic nerve.

The image is then reconstructed
almost instantly

in the visual cortex

by activating
different neural networks

that process shape and colour,

orientation and movement.

Our eyes capture

but not everything.

Our brain compensates
for our perception's weaknesses

by constantly adjusting

the information
that hits our retina.

Our retina's colour sensors

are mainly concentrated
in central vision.

As we move away from the centre,

these sensors become less present.

This means our peripheral vision

should appear in black and white.

Your brain colours
your peripheral vision.

It fills in missing information

so your entire visual field
is in colour.

This is one of many reconstructions

it performs without us knowing.

If I see two parallel lines,

they can never be parallel
on my retina.

My retinas are hemispheres.

So parallel lines
don't exist on the retina.

How can I conclude
from these curved images

that move apart and come together,

how can I tell
they're parallel lines?

It's only through experience,
moving around objects,

my actions and experience of reality

that I gradually learn
the concept of parallel lines.

Refining our perception of reality

to have the most coherent vision
of our world

is an integral part
of our development.

When we're born, we see double,

we have two eyes,

perceiving two separate images.

It's only when we start
interacting with objects

that our brain makes the connection

between both images

to create a single one.

This is a perfect example
of learning

which we can lose,
for instance when drunk,

when we start seeing double

as this mechanism stops working.

As you can see,

you don't just see with your eyes,

but with your brain too.

It processes visual information,

comparing it with what
it knows about the world

and its real-life experience

to create - in a fraction
of a second - coherent images

that make sense.

And it works extremely well.

Despite shadows and reflections,

even when part of an object
is hidden,

we can quickly identify what it is.

This also opens the door
to optical illusions.

Beyond their playful aspect,

optical illusions
have become key tools

used by cognitive
science researchers

like Yves Rossetti.

Optical illusions

help us understand

the mechanisms of perception,

they let us explore
how we perceive things.

They are scientific tools

useful to neuroscientists,

cognitive scientists,

and perception specialists
in experimental psychology.

And beyond that, they allow us

to reveal our true relationship
with the world.

This type of painting is called
"trompe-l'oeil."

But in reality,

the artist is also
fooling our brain.

I'm using this string

as a ruler for drawing
all of the straight lines.

The image radiates out from a point

like a beam of light.

These lines that now diverge,

we perceive them

as straight parallel lines,
as though they were vertical.

But in reality,

when extended,
they point toward the viewer's feet.

This is an aspect I really like

about this technique,

the surprise viewers get

when they're in the right position

and see the illusion working.

Our perception isn't
true to reality.

If you stand at the spot

where all perspective
lines converge,

this painting made

on a flat surface appears 3D.

This is called an anamorphosis.

Anamorphosis is an optical illusion

that only works from one viewpoint.

If you look at it
from another angle,

you can see the
illusion falls apart.

The texture disappears,

as does the depth.

Our visual system
is a great analogy,

a perfect way
to understand our cognition.

Optical illusions reveal
the behind-the-scenes work

our brain constantly does.

It adapts instantly.

Whether I'm balancing
on stacked cubes in mid-air

or walking on images
projected on the floor.

From the information it receives,

the brain interprets what we see.

But let's go further.

The brain predicts what we perceive,

as we will see with Mariam Chammat,

who has studied
the brain's remarkable ability

to predict reality.

MARIAM CHAMMAT,
DOCTOR OF COGNITIVE NEUROSCIENCE

She presents us
with a famous optical illusion

created in 1995 by Edward Adelson,

a neuroscientist at MIT,

which shows how our brain

is key to our perception.

On this checkerboard,
if I ask you to compare

the colour of square A and square B,

most people will say

that square A is
darker than square B.

So square A appears to be dark grey

and B appears to be light grey.

What's absolutely fascinating
about this chessboard

is that these two squares,

square A and square B,
are exactly the same.

If we take this chessboard

and cut out square A
to place it over square B

they're exactly identical.

What we see here is that our brain

isn't interpreting this image

by mapping it point by point

but rather by performing
mental operations,

first recognising
that it's a chessboard.

So on a chessboard,
generally speaking

there's always
an alternation of squares

black/white
or dark grey/light grey.

Second, when looking at square B,

we compare it
to the squares around it

which are indeed darker.

So we perceive it by contrast.

And third, there's a cylinder
casting a shadow here,

and from experience we know

that anything in shadow

appears darker than it really is.

What's fascinating is that
even though we know

both squares are objectively
the same colour,

the same grey,

we still fall for the illusion.

Knowledge is not enough.

And this is once again

an extremely interesting
and powerful sign

showing that our brain

acts like an intuitive statistician

performing many mental operations

very quickly

which make what we see

more like the sum
of many predictions

than an exact projection
of our surroundings.

Beyond reconstructing the world,

a major element has been
added to our knowledge

about how our brain works.

Prediction has emerged
as one of the key operations

of our cognition.

You've probably experienced

getting on a broken escalator

and almost falling over.

Let's break down what happens.

The brain sees the escalator
and makes a prediction.

An escalator is supposed to move.

I need to adjust my pace

to match the escalator's speed.

But it's broken,
so my prediction was wrong.

I lose my balance a bit, adjust

and climb it like stairs.

When I see objects coming toward me,

I can predict their
path instinctively

and move aside to avoid them.

This fascinating ability
to anticipate

is what magicians thrive on.

Magicians constantly play

with our brain's predictions

to surprise and entertain us.

Let's see this with illusionist
and magician Moulla.

You know this?

Show me.

It's very simple.

It looks like...

If I take a purple card here,

and put it on the table right here,

it looks like

I placed a purple card on the table.

Yet we can't just analyse that

I played a green card.

Magic is something
I've been interested in...

for a very long time,
even before neuroscience

because there's this concept of...

movements that are
highly suggestive.

And at some point,
you don't go all the way,

you let the viewer

continue the movement in their mind

while taking them by surprise.

This surprise effect
is what creates the magic.

But for the magic to work,
you need to understand

the most basic physical laws
of our world.

Hi.

You'll see this with Moulla,

who agreed to try
a challenging experiment:

performing magic tricks
for two babies of different ages.

How will the first one,
only ten months old, react?

For me,
it was like doing magic to a wall.

Because the child lacks experience

I could make a train appear
right in front of him

and I think he'd be like:

"Oh..."

"That's normal."

This time,
Moulla performs his tricks

in front of this 15-month-old child,

five months older
than the previous baby.

Gradually, the child
will be fooled by the trick

as babies between 4 and 18 months

learn some of the rules
that govern our world.

This child understands
the rules of gravity,

that normally
when you drop something,

it falls down, not up.

He has also learned
about object permanence.

He knows that
even if he can't see something,

it still exists out of sight.

The child can create a mental image,

predict where the object should be

and therefore be surprised
and amused

when the magician makes it vanish.

Magic defies all rules

and breaks our sense of reality.

Clearly, we're not
the only ones surprised

when a trick defies our predictions.

We share these predictive models

with other living beings.

What happens is

we have preconceptions
about the world.

A PRIORI

A PRIORI - ASSUMPTION

In cognitive science,
a priori refers to

the physiological state,

knowledge or assumptions

we have before an action
or perception.

For example, you're sitting
on a stationary train.

The train next to yours
starts moving,

but you feel like
your train is moving.

Because when you're
on a moving train,

you're used to seeing
the outside world go by.

It'll take a few seconds to adjust

and realise that your train

hasn't moved at all.

And these assumptions
play a key role

in how we understand things.

Let's look at this in more detail

with this spinning dancer.

Which way is she spinning?

Try it among yourselves,

you might not agree.

Here's a new dancer on the right,

spinning clockwise.

Look right, then centre.

Our dancer syncs
with the one on the right

and spins in the same direction.

But when another dancer
appears on the left

our dancer now starts

spinning counterclockwise.

Let's now display all three dancers.

Look at the right, then the centre.

Our dancer spins like
the one on the right.

Look left, then centre.

And our dancer now spins in reverse.

What happened?

When looking at the centre dancer,

our brain can't determine
which way she's spinning

because it's missing information,

a depth marker

showing which leg and arm
pass in front.

So our brain arbitrarily chooses

a direction,
depending on the person.

However, for the dancers
on the left and right,

there's no doubt about
the direction of their rotation.

So when you look at the dancers
on either side,

you form an a priori
from their rotation

that you apply to the centre dancer.

This illusion helps us understand

how these a prioris guide,

shape and give meaning
to our perceptions.

Now, with everything
you've discovered

since the beginning,

can your brain still
play tricks on you?

To find out,
here's a new magic trick.

Watch carefully,

it's hard to catch all the magic
in this video.

And I should mention

there are no post-production effects

in this sequence.

I have a deck of cards here,

a red deck

printed with different cards

and I'm going to ask you to focus

on the first card,

here the two of spades.

Watch carefully.

One, two, three.

And now, the two of spades

becomes completely white

like my t-shirt.

But remember, all the other cards

are still printed

except the two of spades.

But if we do the
same move right here.

One, two, three.

Now,

it's not just the two of spades
that has turned white,

but

all the cards in the deck.

I know what you're going to say.

You might say I'm only showing you

the face of the cards.

But if you look at the other side,

all the cards have turned white.

But I have a question for you.

Did you notice

that my glasses changed

and don't even have lenses anymore?

Did you notice I had a white t-shirt

and now I'm wearing a black one?

And what's more...

there's a two of spades on my back?

Don't worry if you fell for it.

It proves your brain
is working well.

This is called change blindness.

You had to focus on the trick.

So you didn't have enough attention

to notice the changes
in clothes or glasses.

Your brain does this constantly.

It only processes a fraction

of its surroundings.

It's like being in darkness

and your attention is a torch

illuminating
just a small part of reality.

That's one of the secrets
of how it works so well.

Our brain does more
than filter information.

It reconstructs
and predicts the world.

All these discoveries fuel research

into understanding how we function,

how we learn and make decisions.

This is exactly
what Stefano Palminteri studies

in his cognitive neuroscience lab.

What cognitive mechanisms

are involved in our decision-making?

We humans, and many animals too,

are exposed to probably

millions of micro-decisions daily.

So you can see that our brain

needs to use a lot of resources.

A widespread solution in evolution,

across different species,
including humans,

to solve this massive
information processing issue,

is to automate
as many tasks as possible.

So what happens is

when something becomes routine

we can put it on autopilot.

To turn a task or
action into a habit

we all go through a learning phase.

A baby, for instance,
uses a lot of energy

to complete all the steps

needed to eat independently:

grabbing the spoon,
aiming for their mouth...

Through trial and error

they refine their movements.

This is called
reinforcement learning.

Once this phase is complete,

they can eat almost
without thinking.

All learning materialises
in the brain

through the creation
of new neural networks

that interconnect and strengthen

each time they're used
for this new activity.

As they get stronger,

the activity becomes automatic.

AUTOMATIC

What happens in our brain,
between neurons,

is similar
to what urban planners call

desire lines.

These paths that users create

because they're shorter
or more convenient

to reach a bus stop
or school cafeteria,

and keep getting stronger with use.

One advantage of being on autopilot

is our mind is free to
do something else.

For instance

every morning when I bike to work

I follow the same
route automatically,

and during this time

I have the mental space

to plan or adjust my day.

To ride a bike

my brain performs many operations.

It needs to calculate
where to put my arms,

my inner ear, my centre of gravity.

But despite all these
complex operations,

I can do other things:
I can talk to you,

I can pick up my phone, chat...

Never do that.

These automatic reflexes
I've developed

are called heuristics.

They're deeply ingrained in me,

to the point where they take
almost no effort.

The thing is,
sometimes the rules change.

And these heuristics,
these ingrained habits,

usually so helpful,

become difficult obstacles
to overcome.

Let's change the rules a bit.

Here we have a bike

that looks like the other one
but smaller.

But if you look more closely,

this bike is quite special.

There's a gear system
that makes the wheel turn right

when I steer left, and vice versa.

You might think

it should be easy to ride this bike.

I've been cycling for a long time,

I know how to ride

and it shouldn't be
too hard to adjust

which way to turn the handlebars.

But if I try to do it

you'll notice that...

it's much more complex
than it seems.

I'm completely unable

to move even a few inches,
let alone a yard.

What happens is these heuristics

that are deeply ingrained in me

become a major obstacle
to my ability to change

both my behaviour and opinions.

And I'm not the only one
who can't do this,

or who overestimates
their abilities.

What we're going to do is try

to ask people
to do the experiment with us

and test this backwards bike.

Oh no!

- Too bad.
- Almost!

Since you seem good at balancing,

would you try riding this bike?

It's a special kind of bike.

When you turn right, it goes left,

when you turn left, it goes right.

- Oh yeah...
- I believe in you.

It's completely unnatural.

It's for a documentary
about the brain.

I don't have a brain.

Well, then you might succeed.

Because if you have one,
you won't succeed.

Focus...

I think you have a brain.

Is this funny to you?

- Oh damn, yeah...
- Yeah, right.

See!

I hope I don't end up in the canal.

Why would you invent a bike like
this? What were you thinking!

Scottish YouTuber Mike Boyd

decided to intensively learn
to ride a backward bicycle

by practicing several hours daily.

Ironically, once he mastered it

he needed time to unlearn it

when he wanted to ride
a normal bike again.

The advantage I had
with regular cycling,

being able to multitask
and do complex things

without thinking,
becomes a hindrance

when switching to a backward bike.

While in our daily lives

we don't see many backward bikes,

in our thoughts and behaviours

it happens more often than we think.

Just like learning to ride a bike

helps us develop motor skills,

throughout our lives

we develop
automatic thought patterns

that help us make quick decisions

that are often effective.

But these thought patterns,

while suitable in most situations,

can be completely unsuitable
in others.

These automatic responses
that don't always work

are called cognitive biases.

COGNITIVE BIASES

A bias can be beneficial or harmful.

It depends on context.

For instance, mere exposure bias.

The more we're exposed
to something or someone,

the more likely we are to like it.

We tend to think
that what's familiar

is safe and reliable.

It's a great way
to turn neighbours into friends.

In other contexts,
brands can take advantage of this,

by overexposing us to advertising
to make us

prefer their products
without thinking.

This concept of cognitive bias

was developed in the 1970s

by psychologists Amos Tversky
and Daniel Kahneman.

Their work is a key milestone

in the history of cognitive science.

It helps debunk the myth
of rational humans

making cold, calculated decisions.

Despite what the
word bias suggests,

cognitive biases aren't flaws.

Without them, we couldn't live
in a complex world.

They are the result of our evolution

and adaptation to a context

that we long perceived
as threatening.

Our perception developed
in a dangerous world

where predators could eat us.

Quick decisions were essential.

So it's better
to make wrong decisions

that help preserve the species

like thinking you see a tiger

even if it's not really one,

being overly cautious,

what we could call a cognitive bias

but one that helps survival.

And cognitive biases
work in a similar way.

Faced with the complexity around us,

we try to find ways
to reach conclusions

and make quick decisions.

To illustrate this,
let's follow these two volunteers

who will take part in an experiment

that triggers
certain cognitive biases.

They don't know we're taking them

on a nighttime walk in the forest.

You'll see how fear reveals

deeply rooted thought patterns.

You'll walk alone.

- Walk.
- OK

Can I take supplies?

- Nothing.
- OK. Right.

Here we go.

They're city people.

They've never walked
in the forest at night.

Two infrared cameras on a vest

will help us track them.

See you later.

Eli and Tanya,
our two young volunteers,

set off separately

with only a small torch
to guide them.

They'll navigate
through new surroundings

full of uncertainty

they'll need to quickly adapt to.

Watch their reactions.

"We'll put two cameras on you

and you'll walk." That's it.

It'll make nice memories.

Oh my God...

I can't see behind me.
It's all black.

Damn! What was that?

Shit! It's a motorcycle. I'm sorry.

Really far away too.

I thought it was the wind.

Something from over there.

This is getting scary.

I was on my guard.

We call this state hypervigilance,

a kind of heightened awareness.

Any sound, anything at all

- catches our attention.
- Yes.

We tend to imagine
the worst scenario

because our brain thinks:

"If I prepare for the worst,
I can handle it.

If I'm wrong, that's fine.

But if I think it's nothing

and something happens,
I'm not ready..."

- Yes. Ready to react.
- "...then I pay the price."

It's like a generalised
precautionary principle...

in situations of uncertainty.

For a forest guide
used to walking at night,

this would be nothing unusual.

Their thought patterns

have adapted
to this familiar context.

In contrast,
our hypervigilant volunteers

over-analyse
and overreact to this environment

they see as threatening.

I want to run. But I'm scared.

I'm getting chills.

Oh gosh!

I think I need to scream.

Telling myself, "I'll walk alone
in the forest at night",

with all the horror films
I watched as a kid,

or even...

Well, it's not normal.

Since forests at night
are like horror films,

there's also an availability bias

where you imagine
worst-case scenarios

because you think,
"that's what usually happens."

With no experience of night hiking,

Eli's only a prioris,

meaning the only information

he can relate to,

come from horror films.

To quickly make sense
of this new situation,

he connects his experience
to these films.

This is called availability bias.

Availability bias

means automatically
favouring information

that's more readily available,

either because it's recent

or because it left a mark on us,

while more relevant information

might be harder to access.

This bias can be helpful
in emergencies

like when facing potential danger,

but in daily life
it can distort our thinking.

Another example of availability bias

is when a friend
asks you to recommend

the best pizza in town.

You're more likely
to recommend a pizzeria

you've been to recently

than the best pizza place in town

that you visited years ago

and can barely remember now.

LOSS AVERSION

Let's do an experiment
with another well-known bias

called survivorship bias.

SURVIVORSHIP BIAS

Will you be biased?

During World War II,
planes were returning

with bullet holes in their fuselage.

Look at this plane

showing the impact of enemy fire.

Where would you
reinforce the armour?

The engineers' answer at the time

was to protect the areas

with the most red dots,
the most hits.

They based this on planes
that made it back.

The survivors.

The right answer

came from a mathematician
who thought differently.

He thought, "If planes return,

it means the damaged areas
didn't stop them from coming back.

However,
planes hit in other places,

specifically the cockpit and engine,

never made it back."

He concluded that the vital areas

were those without bullet holes.

By thinking outside the box,

this mathematician's reasoning

avoided survivor bias.

Survivorship bias

is our tendency

to focus on success
while ignoring failures.

For instance, when someone praises

a new diet they're following

that's working well for them

while overlooking everyone else

who's trying the same diet

and getting no results.

So when evaluating

the chances of success,

we must consider all attempts,

including failures.

One might think that the ideal

would be to have
no cognitive biases.

In reality, cognitive science

shows this is neither possible
nor desirable.

On the contrary, they're
an inherent part of our cognition

and reasoning ability.

Cognitive biases
are completely unavoidable

due to the brain's
significant limitations.

It has a great deal
of processing power

for a piece of matter.

But it remains quite limited.

Hugo Mercier
is a CNRS director of research.

He studies reasoning mechanisms

and their performance.

Using cognitive biases

allows this limited processing power

to achieve remarkable results.

For instance,
there's a lot of talk now

about the incredible
achievements of AI.

And if I ask ChatGPT
or another large language model

to write an essay on a given topic,

it will produce a fairly good one.

But it uses as much electricity
as a small town

and needs access
to the entire internet.

While a good student,
after reading two papers,

can write a superior essay,

with infinitely less
processing power.

And this is precisely
because the student

uses a set of shortcuts

that allow them to achieve

a perfectly satisfactory result

with far fewer resources

than ChatGPT for instance.

Research has identified dozens,

if not hundreds of biases
depending on classification.

And these aren't
just isolated biases.

They constantly intertwine
with each other.

There are several ways
to categorise biases,

and some researchers even argue

that certain biases
are more fundamental than others.

Take optimism bias, for example.

OPTIMISM BIAS

Optimism bias
is a tendency to overestimate

the likelihood of positive events

compared to negative ones.

For example, when you get married,

you ignore that half of marriages

end in divorce.

This applies even
to divorce lawyers,

though they're well aware
of this harsh reality.

It works perfectly.

What Stefano Palminteri
and his team found

is that this optimism bias
is deeply rooted

in our cognition and decision-making

and influences how we see the world

from a very young age.

We tried to find

the very spark of optimism bias

in cognitive reinforcement
learning processes,

which is the most common
and simplest form of learning

found throughout human life

And it's something
nearly all animals do.

Reinforcement learning
is an integral part of our lives.

Remember that child
learning to use a spoon.

They'll get different feedback
from reality.

If they miss their mouth,
they can't eat.

That's what is called
negative feedback.

If they manage
to aim for their mouth,

the feedback is clearly positive

since they can feed themselves.

Reinforcement learning
captures nothing more

than all these
behavioural situations

where we change our decisions

to get closer to rewards,

things that make us happy

and avoid negative feedback,

things that cause us pain

or that aren't good for us.

To study optimism bias in the lab

Stefano Palminteri
designed an experiment

based on reinforcement learning,

exposing participants
to positive and negative feedback.

In this task

you have pictograms to choose from.

You'll need to pick one or the other

and each pictogram leads
to winning or losing money.

The value of these symbols
is unknown,

but the subject
can't choose between them.

As experimenters,

we control the value
shown to the subject.

The feedback in this experiment

is winning or losing money.

The player will try to find

the hidden rule
behind these symbols.

He thinks he's being tested
on his ability to find the rule

but the scientists

are measuring something
quite different.

What we want to understand

is how responsive

the subject is to rewards
and punishments.

The data recorded
using an electroencephalogram

shows intensity spikes

matching the participant's wins.

Gains trigger more brain activity

than losses.

Participants' eye movements

are recorded using an eye tracker.

Stefano Palminteri's team observes

when comparing the collected data,

that participants look longer

at their gains than their losses.

A crucial split second

shows that our brain
underestimates failures

and overvalues successes.

This is optimism bias.

A cognitive bias

is like a filter
that filters out information.

For example, when someone
receives three punishments,

three negative feedbacks in a row,

their brain will filter them out
and they'll act

as if they only got
one negative feedback.

To undo the effect of a reward

it takes two to three
negative feedbacks.

So typically, an unbiased person

would be equally likely
to change behaviour

when receiving negative feedback

or positive feedback.

However, someone
with optimism bias

would become less sensitive
to negative feedback.

The purpose of this experiment

is to show you that optimism bias

is essential for our development.

Without it, we couldn't
bounce back from failure

or persist in learning.

Having optimism bias

means somewhat overlooking

those instances where

we don't quite get the results
we expected,

which allows us

to maintain higher motivation.

And there are many situations
where without optimism,

we wouldn't make it.

We need this optimism bias

to grow and evolve,

but also in our relationships.

I need to believe my friends
are the best in the world

to maintain special bonds with them,

even if I forget our fights
and their flaws.

But at the same time,

this optimism bias can be a curse.

Take casinos for example.

If you focus on all your wins

and ignore your total losses,

you might end up broke.

So how do we make decisions?

Now that we know
our perceptions and thinking

are subject
to many automatic processes,

predictions and biases.

We also have a little voice
in our head

that we constantly debate with.

For example,
I'm on this roller coaster

and this little voice tells me

I probably shouldn't have come.

This little voice
is called metacognition.

It's the thoughts we have
about our thoughts.

Metacognition plays a role
in what is called

metacognitive control,

which is our ability to reflect

on our automatic thoughts.

Metacognitive control has been key

in developing
new psychological therapies.

When I'm anxious, for instance,

and automatically think
things will go wrong,

I can use metacognition
to reason with myself.

It's essential for decision-making

and helps us stop being controlled
by our thoughts

and automatic emotions.

It's also very helpful
for high-level athletes.

In sport, we've all experienced it.

This metacognition

is key to staying motivated
and pushing limits.

Who hasn't told themselves
when exhausted,

"Come on, one last push,
you can do it"?

Chloé Lanthier
is a mental performance coach

specialising in ultra-trail running,

very long distance races.

For her, metacognition is key.

It can be incredibly helpful

and that's what she teaches
her athletes.

Every time we do something harder,

we expect it to be very difficult.

Right? We think
we won't be able to do it.

Our perception of effort
is first mental,

and second, physical

sometimes it can be very physical,

but we must use our mind.

For Chloé Lanthier,

like many high-level athletes,

you need to find mental tricks.

Through metacognition,

we can change how we perceive

long-distance effort.

When I start the race,

I don't actually think
about the entire distance

or how much elevation gain.

In the race I just think
about the next aid station.

Because the whole goal is too big,
it's too scary,

it's too overwhelming,

and I think maybe I wouldn't
be able to carry on.

But actually breaking it down
into small goals

and rewards, that really helps.
It's powerful.

You may think of yourself
as thoughtful

like this athlete,

always using your metacognition

and believe you have
no automatic thoughts.

But no one is immune to them.

Let's do one final trick together.

You all know Rubik's Cubes.

And you know when you scramble one,

it's quite hard to solve it.

Here, I'm mixing up my cube.

Let's say you told
me to stop here...

I have a mixed up Rubik's cube

and it's hard to solve.

But I have a magic bag with me

and if I take
my scrambled Rubik's cube

and put it in my magic bag

something quite special happens.

I just need to shake it a bit

and my Rubik's Cube
comes out solved.

So my question is: how did I do it?

Most of you probably

think it's quite simple,

I have a second Rubik's Cube
in my bag,

but actually,
I don't have another cube,

this bag is completely empty.

See, I can flatten it.

What I did is much simpler,

but requires a lot more practice.

I can scramble Rubik's
Cubes one-handed

and solve them one-handed.

And what I do is

when I put the Rubik's Cube
in my bag, I solve it.

It was already solved
while I was shaking the bag.

What matters in this trick
isn't the trick itself.

What's important is your assumption

that I have a second Rubik's Cube
in my bag.

And to get it, you didn't think.

You didn't wonder,
"How did he do it?"

It just appeared automatically.

In everyday life,

our automatic thoughts
are very useful.

That's what allows us to function.

But sometimes,
it's important to learn to doubt.

And to be aware of our
automatic thinking patterns.

It's a fundamental
philosophical dilemma

at every moment.

Knowing how much automatic thinking

I want in my life.

Because this level of automatic
thinking determines my freedom.

At every moment of our lives,

we can either react to a stimulus,

meaning responding
automatically to it,

or make an intentional decision

in response to it.

So the dilemma is,

in the first case,

we can respond extremely quickly,

but automatically.

So we're no longer in control
of our actions.

We are driven
by our cognitive system.

And in the second case,

it requires a lot of attention,
time and thinking

so it makes us waste a lot of time

and limits what we can do.

Am I being intentional?

Am I the one making this decision

or do I accept it's automatic?

Between our automatic thoughts
and metacognition,

between our predictions and biases,

now you know our brains
play tricks on us,

but our brains are who we are.

All these mechanisms

shape our subjectivity.

Each of us

has a different view of the world.

Each of us

creates their own unique world.

For example,

if you see this person in a crowd,

how would you interpret
their state of mind?

Some of you will see them as serene,

having positive
and comforting thoughts,

while others will see
judgement in their eyes.

Our interpretations of reality

can be complete opposites.

Despite this,

we must get along with each other,

because we are highly social beings

who depend on one another.

Others influence
how we act and think

much more than we realise.

This brings us to our next chapter,

where others play tricks on us.