October 28, 2024 • 54 mins
Why can you hear some sounds two different ways, depending on which word you’re looking at? Why do electrical outlets sometimes look like a face? How can you have rich visual experience with your eyes closed? Are some crosswalk buttons fake? Why are some pictures interpretable only once you’ve been told what to look for? And although brains are often celebrated for their parallel processing, what should they really be celebrated for? Tune in to learn what happens when the raw facts of the world collide with your expectations.
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Episode Transcript
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Speaker 1 (00:05):
What's up with those illusions on the Internet where you
can hear the same sound one of two different ways
depending on the word that you're looking at. And why
do electrical outlets sometimes look like a face to you?
How can you have full, rich visual experience with your
eyes closed. And when you want to cross a street
(00:27):
and you hit that crosswalk button, are some of those
buttons fake and they don't actually do anything?
Speaker 2 (00:33):
And why are there some.
Speaker 1 (00:34):
Pictures that you can only see once you're told what
you're looking at. And although brains are often celebrated for
their parallel processing, what did they really be celebrated for.
Welcome to Inner Cosmos with Me David Eagleman. I'm a
neuroscientist and author at Stanford and in these episodes we
(00:57):
sail deeply into our three pounds universe to understand why
we perceive the world in the ways that we do.
Today's episode is about expectations and what that has to
(01:18):
do with perception. Unless you were living in outer space
or off the grid in twenty fifteen, your life was
touched by a very tiny, specific event that happened on
a small island in Scotland. Two young people were going
to get married there, and a week before the wedding,
(01:41):
the mother of the bride was shopping around for what
she was going to wear. So she finds some outfits
at a store down in Chester, England that she thinks
will look nice, and while she's making the decision, she
snaps pictures of each of them and she buys one
of them.
Speaker 2 (01:58):
So she's driving home.
Speaker 1 (01:59):
After words and she texts the pictures of the three
outfits to her daughter and she tells her that she
had bought the third one, and no one could have
ever guessed that this particular piece of clothing that she
sent a picture of, this one piece garment, is about
to become the most famous outfit that ever existed in
(02:22):
the history of humankind, because the daughter writes back to
clarify which outfit the mother had bought, and she texts, oh,
the white and gold one, and the mother texts back, no,
it's blue and black, and the daughter replies, Mom, if
(02:43):
you think that's blue and black, you need to go
and see the doctor. So the mother shows the phone
to her partner in the car, who, despite having been
there and bought the dress with her, looks at the
photo and says, yeah, I think it's white and gold.
So when they get home, they show the picture to
their younger, who agrees with the mother that the photo
looks blue and black. So, given this funny disagreement, the
(03:08):
bride to be posts the photo to her friends on
Facebook to settle this, and to her surprise, she doesn't
find consensus. Some think it's black and blue, others think
it's white and gold, and each person feels totally certain
about what they see. So for about a week, this
(03:29):
debate bubbles around in this small island community. The day
of the wedding arrives and the mother wears the dress
to the event, and the issue about the photo becomes
such a point of discussion that the musicians in the
band allegedly almost didn't make it onto the stage to
play because they were wrapped up in the debate.
Speaker 2 (03:49):
So a few days after.
Speaker 1 (03:50):
The wedding, one of the band members, who was a
friend of the happy couple, she posts the photo to
her blog on Tumblr, and by the end of the
day it gets five thousand comments, and soon enough, the
data scientists at Tumblr are examining this post because it's
getting fourteen thousand views each second. That's close to a
(04:15):
million views each minute. So a woman on the BuzzFeed
social media team sets up a poll about the color
for Tumblr users, and then she packs up and goes
home on the subway. And by the time she gets
off the subway, her phone is overwhelmed, and soon enough
the BuzzFeed page hits new records for how many unique
(04:38):
visitors were on the page at the same time, hitting
almost seven hundred thousand. The number of comments on the
original post increases tenfold that night. By late that night,
there are five thousand tweets per minute using hashtag the dress,
and by the middle of that night it's grown to
eleven thousand tw wheets per minute. Within the week, more
(05:02):
than ten million tweets are talking about the dress. This
was the dress that, as they say, broke the Internet. Now,
if you were, say a space alien, you might look
at all this human activity and think, wait, what, why
is the world stopping over a simple picture of a
piece of clothing in the UK. Now, the answer, as
(05:26):
you know, is that none of us humans would have
found it interesting either, except that someone that you loved
and trusted said, what do you mean you're seeing it
that color? It's so clearly the other color, And you said, wait,
what are you being serious? And they asked you the
same and then the awe sets in. You both realize
(05:48):
that you're looking at the same thing in the outside world,
and you're having different perceptions a different experience on the inside. Now,
no one was more excited about the dress than neuroscientists,
because for neuroscientists this was a terrific demonstration of what
we're going to talk about today. So to start things off,
(06:11):
let's just point out how important these kinds of perceptual
oddities are to neuroscience. I've spent a big chunk of
my career studying illusions. I've published scientific papers about illusions
in journals like Science and Nature, And some years ago
I wrote a review article in the journal Nature Reviews Neuroscience,
(06:34):
and I titled it Visual Illusions and the Brain, And
in that article I laid out how powerful illusions are
for figuring out what is under the hood. Sometimes I
feel like illusions are interesting only to ten year olds
and for most people they become nothing but entertainment. But truthfully,
illusions are microscopes for understanding what is happening in the brain.
(07:00):
Them we can reveal the systematic differences between what is
actually out there in the world and what we believe
is out there, And by dialing the illusion around carefully,
we can usually put constraints on how the network of
neurons must be operating. Now, most illusions are the type
(07:22):
in which we measure what's being presented in the outside world,
like two lines of identical lengths and you see it
as two different lengths, and we say, ah, there's a
systematic difference between what's on the page and what you perceive.
Speaker 2 (07:38):
Or maybe I show you two.
Speaker 1 (07:39):
Parallel lines against some background and you don't see them
as parallel. Or you look at a totally static picture
on a page and you swear that it's moving. But
the dress was interesting because it wasn't that traditional kind
of illusion. Instead, one person sees one thing and the
person standing right next to them sees another.
Speaker 2 (08:02):
Now, what all.
Speaker 1 (08:03):
Illusions, including the dress, tell us right away is a
foundational point that's not always intuitive, which is that we
don't simply look at the world and passively receive what's
out there. Instead, our brains actively construct our perception, and
different brains can do so differently. So now let's move
(08:26):
deeper into this mystery by turning to a different illusion.
That took over the Internet a few years later, in
May of twenty eighteen.
Speaker 3 (08:36):
Laurel Laurel, Laurel.
Speaker 1 (08:41):
Now, this was an audio file that was originally recorded
by a reader in two thousand and seven for vocabulary
dot com, and some students apparently re recorded that file
while there was some background noise in a room. So
a fifteen year old freshman in Georgia named Katie was
listening to that recording and she realized that she was
(09:03):
hearing some funny ambiguity, and she posted this little audio
clip on Instagram, and the next day her friend posted
it on Reddit, and then it got picked up on
Twitter and.
Speaker 2 (09:13):
Soon it went nuts.
Speaker 1 (09:15):
Why Because just like the dress, people can have a
different perception of the same item presented to their senses.
About half the people hear the word yanny and the
other half hear the word Laurel.
Speaker 3 (09:32):
Laurel, Laurel, Laurel, Laurel.
Speaker 1 (09:39):
Now, how can people hear different things? So hang tight,
I'll tell you in a minute. But what I want
to point out for now is that, just like the dress,
some people have one experience, some people have another, same
sound recording, different experiences. Now, the Yanny Laurel clip made
its rounds on the internet, but it about the exact
(10:01):
same time. In May of twenty eighteen, something even better
surfaced on YouTube. A guy had posted a video where
he was reviewing a children's toy from the ben Ten franchise,
and the toy lights up and says something. And here's
what it sounds like. It says the word green needle.
(10:22):
So listen carefully for green needle. Okay, well, that's not
actually what the toy was saying. It was actually saying
the word brainstorm, which is the toy character's name. So
listen for the word brainstorm.
Speaker 2 (10:52):
Now, I just.
Speaker 1 (10:53):
Played the exact same audio file in both cases, but
depending on your expectation what you were listening for, you'll
hear different things. So I'm going to play this file again,
over and over for about twenty seconds, and I want
you to think about brainstorm or think about green needle.
(11:13):
Try to go back and forth about which one you're hearing.
Switch your thinking from one to the other at any point.
Speaker 2 (11:39):
So, what the heck's going on here?
Speaker 1 (11:41):
How can a single audio file be heard two completely
different ways? Seems like magic, but it's actually neuroscience. All
these internet memes actually give deep insight into a fundamental
and rarely appreciated property of the brain. So I'm going
to unpack these illusions in a few steps. The first
(12:04):
clue to the mystery is that the brain does not
tolerate ambiguity. It really wants to come to a conclusion
about exactly what's out there. Now, that's a major daily
challenge for the brain because so much of what you
see or hear is ambiguous. You have data points that
(12:25):
come streaming into the brain through the eyes, or the ears,
or the fingertips, but often they could be interpreted more
than one way. So what does the brain do in
this circumstance. It locks onto a single way of understanding it.
In other words, if there are multiple possibilities, it'll force
(12:46):
an answer. Now let's pause for just a moment to
appreciate something here. When you read about the brain, you
always see it celebrated for its parallel processing. It can
do lots of things at once. But what it should
be equally celebrated for, the thing that no one ever
bothers to highlight is serialization. It takes lots of the
(13:10):
activity and it squeezes it down to one thing.
Speaker 2 (13:14):
It serializes it.
Speaker 1 (13:15):
It takes an information that could be interpreted in lots
of different ways, and it crunches it down to a
single interpretation.
Speaker 2 (13:24):
Now, why is it so good at serializing, at.
Speaker 1 (13:28):
Getting possibilities down to a single answer, Because fundamentally, your
brain has the challenge of controlling a giant body made
of trillions of cells, and when you come to a
tree in the path, it has to go either left
or right around the tree. Because of the physics of
(13:48):
the world, it cannot do both, and.
Speaker 2 (13:50):
So it has to make a single.
Speaker 1 (13:53):
Decision, go right or go left, and drag all those
trillions of cells with it. Your brain it has to
be good at taking possibilities and crushing them down to
a single decision. And it's the same with your perceptual life.
Your brain is used to dealing with a world where
(14:14):
it has to come to conclusions, having to say, look,
there are lots of possibilities here, but for me to
function in the world, I have to make an assumption
that what I am looking at is a piece of
food or a boulder, or a bear at a distance
or whatever. So the brain doesn't tolerate ambiguity, but it
(14:36):
always says, all right, this is my answer okay, So
now let's introduce one more perceptual illusion of this flavor,
and then we're going to unpack what's going on.
Speaker 2 (14:49):
So surely you've seen this one before.
Speaker 1 (14:51):
You draw the outline of a cube on a piece
of paper. You just draw a square, and then an
offset square, and then lines connecting the corners of one
to the corners of the other, so it's twelve lines.
It's the outline of a cube. This little wireframe drawing
is known as the Necker cube.
Speaker 2 (15:10):
Now you've seen this before, but as you know, if you've.
Speaker 1 (15:13):
Stared at one, it's perceptually ambiguous because if you stare
at this little wireframe, it looks like it's coming out
one way from the page, even though you could perceive.
Speaker 2 (15:25):
The same drawing in two different ways.
Speaker 1 (15:27):
Either the lower square is the face of the cube
coming toward you, or the upper square is the one
coming out toward you, but your brain makes a choice. Now,
you could imagine a space alien who looks at this
little drawing of the wireframe cube and says, okay, well,
both configurations of the cube are equally probable, so I'll
(15:50):
see it both ways at once. But we can't do that.
We have to see it one way or the other.
Your brain forces a single interpret and this is the
same thing that's happening with the other illusions with the dress.
You don't see it as both blue and black and
white and gold. And in a minute we'll see why.
(16:13):
The part I just want to say now is that
your brain concludes that it is one or the other,
and then it sticks with that. And likewise with Yanny Laurel.
Both sounds are present in the audio file, but you
don't hear Yanny and Laurel at the same time, stacked
on one another. And it's exactly the same thing with
(16:33):
brainstorm and green needle. Both interpretations are possible, but your
brain won't do both at once. It collapses the possibilities
to a single answer. In all these cases, even though
the data is consistent with either interpretation, your brain makes
a call. It goes left or right around the tree.
(16:55):
You very clearly perceive one or the other. And this
is because the brain isn't passively receiving the world. It's
making choices. Okay, but how does your brain know how
(17:25):
to collapse ambiguous data to a single interpretation. It does
so by leveraging assumptions, so let's go a level deeper
with the dress. Why does it happen that some people
see it one way and some people the other. It
happens because your brain sees a picture of a dress
in the shop and it makes dozens of assumptions totally unconsciously. Now,
(17:50):
what's amazing is that the assumptions aren't directly about the dress,
but about things you didn't even know you were thinking about.
What is the light source in the photograph? Is the
dress mostly being lit by fluorescent lights or by sunlight?
Is the dress facing a window or is the window
(18:12):
behind it? What time of day is it, what season
is it? Your brain is considering all of these questions,
and fundamentally, this all has to do with a computation
that it does known as color constancy. Color constancy is
this sophisticated ability of our visual systems to perceive the
(18:35):
color of something as constant even when the light source
the illumination changes. So let's say I'm wearing a white
T shirt and we're standing outside talking in the sunlight.
You will see my shirt as white. Now we go
indoors into the coffee shop and the illuminant changes. In
other words, the light that's bouncing off my t shirt changes.
(18:58):
Now it's fluorescent light compared to sunlight. The fluorescent light
has a different spectrum of colors coming out, and so
when those bounce off my shirt, you have a different
spectrum of colors hitting your eyes, and yet you still
see it as white. And then that night we go
into a dance club and the lighting is blue, and
(19:21):
yet you have no problem seeing the shirt as white,
even though it's mostly blue light reflecting off the shirt
into your eyes. And then afterwards we go sit by
a campfire and my shirt still looks white. Your brain
retains a constant perception of the color of the shirt
(19:41):
even though the wavelengths bouncing off of it are very different.
So what does this tell us, Well, it means that
the way your brain determines the color is not just
about the colors hitting your eye from the shirt. It
has to do with something else. And that's something else
is everything else in the scene. So when you're looking
(20:04):
at my shirt, your eyes are drinking in everything else.
The background, the color of the skin on my arms,
the color of the floors and walls, the colors of
all the other.
Speaker 2 (20:18):
Jeans and shirts and signs in the.
Speaker 4 (20:20):
Whole scene, and it uses all of that to estimate
the background illumination and then make the right computation about
the color of the shirt in the sunlight and the
coffee shop, at the dance club, at the campfire.
Speaker 2 (20:37):
It's doing all of.
Speaker 1 (20:38):
These computations, and this is what allows it to subtract
off the background lighting so that it can see what
color things are most likely to actually be. That's the
phenomenon of color constancy. The color of the shirt remains
constant even under different illumination, and that's what allows us
(21:01):
to see the colors of objects in the world consistently,
whether we're looking under sunlight or moonlight or firelight or whatever.
So the first lesson is you're not just seeing what's
out there. Your brain is actively interpreting information and serving
up a story to you. And I'll go into this
(21:22):
more in a future episode. But this is why we
can see strawberries as red. For example, when we change
the background color such that the actual light bouncing off
the strawberries is gray light, your brain can nonetheless say, okay, well,
given that everything else in the scene is now greenish,
I can subtrack that off and know that I'm looking
(21:44):
at something red. Now, in order to do all of
this that I've been talking about, your brain has to
make lots of assumptions about what the color should be,
and different brains do it differently. With the dress, you
see it as either white and gold or blue and black,
(22:06):
depending on the assumptions your brain is making. When you
glance at the photo on your phone, you have no
idea that your brain is doing all those sophisticated computations
under the hood to tell you what is the actual
color of this garment, given my assumptions about all the
lighting details.
Speaker 2 (22:27):
The issue is that your.
Speaker 1 (22:29):
Brain grew up in a particular environment, maybe with a
lot of snow or a lot of sunlight or fog,
and your brain makes assumptions about the time of day
and the season and the balance of artificial lighting to
natural lighting. To make sense of this little photo, what
hues does the lighting contain. If your brain ignores a
(22:52):
bit of the blue side, you'll see the dress as
white and gold. If your brain pays less attention to
the yellow side of the spectrum, you'll see it as
blue and black. You have no insight into the fact
that your brain is making all these assumptions under the hood.
Was the photo of the dress taken with the window
facing it or behind it.
Speaker 2 (23:13):
Was it morning light or afternoon light?
Speaker 1 (23:15):
And is your experience of the world based on the
fact that you are a mourning lark or you are.
Speaker 2 (23:21):
A night owl.
Speaker 1 (23:23):
One of my colleagues, Pascal Wallash, showed that people who
were early risers were more likely to think that the
dress was lit by natural light, and so they saw
it as white and gold, but night owls presumably had
more assumptions about artificial lighting, and they were more likely
to see the dress as blue and black. Your brain
(23:45):
is determining the color of the dress by comparing it
against the other objects of the background of the photo
and making its best guess at all these parameters. So
your brain relies on the answers to question is that
you didn't even think it was asking and the idea
of imposing assumptions. This is the same with Yanny and
(24:07):
Laurel in the auditory domain, or with green needle and brainstorm.
Your brain is imposing an interpretation. But what's interesting in
this case is that the assumption can be changed more easily,
typically by just staring at the word visually. Because your
brain is trying to disambiguate what it's hearing, and suddenly
(24:31):
it has lots of help from the visual system because
it sees a word. So the frequencies of both words
yany and laurel or green needle, brainstorm, they're contained in
the audio file, so just depending on how you listen
for it, you can hear one or the other. So
(24:52):
the brain constantly nails down its world by making assumptions,
and we see this with everything. And even though these
internet memes get all of our attention, the fact is
that our brains have to make assumptions all the time.
And this is because most of the inputs from the
world are quite noisy. For example, you can still understand
(25:16):
me even if my speech is choppy, or if I'm
speaking and there's lots of background noise like at a restaurant.
What's actually hitting your ears in these scenarios is a
very messy signal, But the brain imposes an interpretation about
what must have been said, and that's what you perceive
what you believe you heard. A lot of your cell
(25:38):
phone conversations are super noisy, but you typically don't realize
it because you keep making your reasonable interpretations. Now, this
is true of most of what is hitting your eyes
and ears. You don't catch a fraction of the data,
but your brain fills in the details to put together
(25:59):
a story. And this, by the way, is what's at
the heart of a lot of art and graphic design.
You just see a few curves and you interpret it
as a face, or a series of segmented lines and
you interpret that as a body. We are always operating
off thin data, but that doesn't stop us from coming
(26:19):
to clear conclusions. And before I explain how our neural
networks go about making these assumptions, let's just take a
second to look at how your brain is so imperfect
at this. Take paridolia, which is when you perceive a
meaningful pattern where none exists, Like when you look at
(26:41):
an electrical outlet and you see a face made up
of little eyes in a sort of surprised mouth. You
can't help but see that. Your brain imposes that interpretation
on it. Or you see a face in the clouds,
or someone sees the face of their local deity in
a piece of toast. Why does this happen, Well, your
(27:03):
brain is really wired up to see faces, and so
it triggers that interpretation whenever it sees three blobs in
the approximately right configuration, and the same thing can happen
with sounds, like when there's some weird sound and your
brain thinks it's a person shouting or someone calling your
name or whatever. This is the brain working to make
(27:26):
sense of the world around it. All it ever does
is look for meaning from data in the world. In fact,
typically the brain will try to impose an interpretation even
if you have random noise. That's the idea with rorshak
ink blots. You have these blobs on a page, and
(27:47):
your brain reaches for some way of explaining them. Oh,
that looks like a rabbit or an airplane, or an
emperor on a throne or whatever. And generally a lot
of life involves forcing patterns on random noise. Here's an
auditory example from my colleague Diana Deutsch, who has spent
her career pioneering auditory illusions. So here's an experiment where
(28:12):
she plays mixed up audio that doesn't say anything, but
it sounds like speech, and people will generally impose the
interpretation of words on these.
Speaker 4 (28:57):
Come come, come, come, come, come, come, come, come come.
Speaker 1 (29:33):
This is essentially the sound version of Rorschach blots. Different
people will generally hear different things, and it seems to
be related to what they are thinking about or what's
on their mind. So this all reminds us of the
power of the brain to impose meaning. Just think about
the situation when you're expecting a friend and you're looking
(29:56):
around for him at a crowded mall. Everyone looks like him.
For just a fraction of a second. You look at
someone's face and you think, oh, that's him, and then
five hundred milliseconds later, your visual system takes in more
information and decides out never mind false alarm, And then
we typically forget that we even thought that. But we
(30:17):
are expecting to see our friend, and so our brains
impose that expectation on lots of faces. Okay, so we've
established that brains take ambiguous signals and squish them down
to a single interpretation by use of assumptions. And that's
why we see the dress as one color or the other,
(30:38):
or we hear brainstorm or a green needle, but not both.
But how do our brains actually make their choice? How
do they pull this off? Neurally speaking, they do it
by combining bottom up information with top down information. Now,
bottom up means information and from the outside from the world.
(31:02):
What are the air compression wave of sitting my ear
drums or what are the photons sitting my retina?
Speaker 2 (31:07):
Those are the signals that I am receiving.
Speaker 1 (31:10):
But we don't interpret those bottom up signals that face
value because they're usually not sufficient. Instead, your brain melds
this with top down information, which means your expectations what
we think is likely to be true in the outside
world given our experience with it, and it's only in
(31:30):
combination the data plus our expectations that we see anything
in the world. And the surprise, I think the counterintuitive
part is that your prior assumptions, your expectations, the.
Speaker 2 (31:45):
Top down part.
Speaker 1 (31:46):
This is the overwhelming majority of what determines what you see.
For example, it seems like you just open your eyes
and there's the world, but in fact, when you look
at the visual cortex at the back of the which
is the place that receives the information from the eyes,
you find that only five percent of the input there
(32:07):
is coming from the eyes.
Speaker 2 (32:09):
And the rest is all feedback activity.
Speaker 1 (32:12):
In other words, ninety five percent of the data is
coming from higher levels of the visual system and other
areas of the brain. In fact, What is so crazy
is that you don't even need your eyes to have full,
rich visual experience. You can have this with your eyes closed.
(32:32):
And this is what we call dreams. And what's happening
here is that this is all internally generated activity and
none of it's entering through the eyes when you're asleep,
and it's not that much different from your normal vision.
So your perception of the world when you're walking around
is something like an awake dream.
Speaker 5 (32:53):
Now.
Speaker 1 (32:53):
I'm going to return to this issue in future episodes,
but what we want to concentrate on right now is
that your eyes are not simply a camera and your
ears are not simply a microphone. For those of you
who have been listening for a while to this podcast,
you know this is a major theme. Your brain is
locked in silence and darkness and needs to make assumptions
(33:16):
based on very thin data. So when I ask you
to think about the words green needle, that is top
down information that shapes how you interpret the bottom up data.
(33:37):
In contrast, imagine that you stare at the word brainstorm
while listening. You lock that in as your top down expectation,
and then that shapes your bottom up data.
Speaker 2 (33:46):
And that's what you hear.
Speaker 1 (33:55):
Even though both interpretations are available, your brain surfaces is
those features out of the landscape of data that match
what you're looking for. In other words, your expectations. What
you listen for is what you hear. And by the way,
all this is related to why lip reading works. When
(34:16):
you're in a noisy environment, you watch somebody's mouth while
they're talking, and in this way you combine a bit
of noisy auditory data with a bit of noisy visual
and that sharpens your guess for what was just said.
During the pandemic, a lot of conversations went misunderstood because
people were wearing masks and lip reading went out the window.
(34:40):
Now amazingly, this top down information is so important that
sometimes you can set up a picture where you don't
have any real prior assumptions and there's not enough information
in the picture to see anything. And only when I
tell you some interpretation does the bottom up information should
(35:00):
make any sense at all.
Speaker 2 (35:01):
You can only see.
Speaker 1 (35:03):
What's in front of you if you're given top down direction.
For example, I've put a cool picture on my website
at eagleman dot com slash podcast. Take a look at
this field of black and white blobs and see what
it looks like to you, And presumably it looks really
like nothing at all, just a bunch of blobs. But
(35:23):
if I tell you what it is while you stare
at it, then you suddenly see it. It seems immediately
obvious and you cannot see anything other than that, And
the only thing that's changed is that you now have
a top down expectation about what you're seeing, and suddenly
all these blobs make clear sense. I'm not going to
(35:43):
tell you what the blobs are here, but if you
go to the website and scroll all the way to
the bottom of the page, I'll give you a hint
there so you can enjoy the experience of not knowing
and then knowing. And because this is a podcast, I'll
give you an auditory example of this, again from Diana Deutsch.
So I'm going to take a piece of music that
(36:04):
you know, but I'm going to shift each note up
or down an octave, so one note might be played
an octave higher and the next note might be played
an octave lower. And I want you to identify the
piece of music. It's definitely one that you know. Now
(36:28):
I assume that you couldn't identify that piece. Now I'm
going to play it for you without the notes shifted
up or down in octaves. Now that you know the tune,
I'm just going to play that first one again and
you should have little or no trouble hearing the correct melody.
Speaker 2 (36:59):
The only difference between the first.
Speaker 1 (37:01):
Time I played it and the last time is that
now you have a top down expectation, and so it
switches from random noise to a tune. And so these
are all examples in which top down expectations are critical.
Without them, you don't have any interpretation at all. And
(37:22):
once you build an expectation, then the data have meaning.
You need to be told what to see in the
picture or to hear in the tune to get it.
And the only difference between before and after is whether
you have something to match it to some top down expectation,
and as soon as you do, then you perceive. Now,
(37:45):
just to be clear, this doesn't mean you can impose
any top down interpretation. It has to match sufficiently well.
The thing about brainstorm green needle is that the bottom
up data can match either one of the top expectations
for either word. You can hear green needle or brainstorm.
(38:06):
Because these are possible words that can roughly match the
bottom up stimulus with all of its noise, But you
can't hear something totally different like blue reader or my
penguin because you can't make a good enough match between
data and expectation. So there has to be a sufficient
(38:26):
match between the top down and the bottom up for
perception to happen. Okay, so let's come back.
Speaker 2 (38:33):
To this issue about the assumptions that we make. How
do we know what to assume about the world.
Speaker 1 (38:40):
Well, this relies almost entirely on our prior experience. For example,
when you're judging depth, like how far different things are
from you, which is again a totally unconscious process, you
can do this by comparing the images from your two eyes,
but this is only useful out to about thirty meters.
So it turns out the brain has other ways to
(39:03):
determine depth, and one of the main ones simply pivots
on its experience with the world. The visual system builds
up prior expectations about the relative sizes of objects. So
if you're standing outside and you see a dog in
the distance, then it takes up about as much space
on your retina as the truck over there. You can
(39:25):
assume that the dog is closer and the truck is
farther away. Why because a close dog will look a
certain size and a far away truck will end up
looking about that same size, and so your brain is
able to instantly make the proper assumption about how far
away things are. And you might be wrong, by the way,
(39:45):
maybe it's a miniature model of a truck that's really
close and a monstrously huge dog that's really far away.
But most of the time your assumptions are fine. So
data doesn't just come in from the world and get seen. Instead,
your visual system capitalizes on prior expectations. And although this
(40:07):
idea isn't always intuitive, it's not a new idea. In
the nineteenth century, the German physician and physicists Hermann von
Helmholtz was one of the first people to entertain this
model of perception. He suspected that the small amounts of
information dribbling in through the eyes were just too slight
(40:27):
to account for the rich experience of vision. So he
deduced that the brain makes assumptions about the incoming data
based on previous experiences, and he correctly surmised that this
is how the brain can use its best guesses to
rapidly turn a little trickle of information into a full picture.
(40:49):
By the way, if you want to look this up
in more depth, look up Helmholtz's notion of unconscious inference.
We infer what's out there, and it all happens unconsciously.
You can also look up Bayes' theorem as a way
of approaching this mathematically. One way to think about this
is that our judgments often rely not only on what's
in front of us, but also on all of our
(41:11):
prior experiences. So where we are so far is that
(41:31):
the process of perceiving the world, of interpreting what we
see or we hear, it's influenced by our past experiences,
which shape our current expectations, and that's what determines what
we think we see and hear. Now, it's sometimes the
case that your brain has more than one prior expectation.
(41:53):
It could be this, or it could be that, And
in this case it's easier to witness something very interesting,
which I want to tell you about now. So let's
return to the Necker cube, that little wireframe drawing. So
it's a very simple drawing, but it exposes something amazing,
which is a competition that is always raging under the hood.
(42:14):
Your brain is always trying to figure out what is
going on out there, and the way it does this
is by assessing probabilities. So this simply means you have
some networks that are saying, yes, it's definitely this, and
you have other networks that are saying, yes, it's definitely
this other thing.
Speaker 2 (42:32):
In the case of the Necker.
Speaker 1 (42:33):
Cube, you have one network saying the cube comes out
of the page this way, and the other network insisting
the cube comes out of the page the other way.
And in other illusions you sometimes have even more networks,
each voting for their thing. But the key to understand
is that it's a competition. All these networks are screaming
off and trying to dominate each other, and it's a
(42:57):
winner take all competition.
Speaker 2 (43:00):
It's like king of the hill.
Speaker 1 (43:02):
Whichever kid is able to get to the top of
the hill gets to push everyone else down. In the
case of local neural networks, when one is successfully firing
on all cylinders, it's able to inhibit the neighboring networks.
It releases neurotransmitters that keep itself propped up and at
the same time inhibiting the activity of the competitors, and
(43:26):
whichever network.
Speaker 2 (43:27):
Is king is what you perceive.
Speaker 1 (43:30):
And because it's a winner take all competition, there's only
one king at any time.
Speaker 2 (43:35):
That's why you don't.
Speaker 1 (43:36):
See all the possibilities at once. You only see the winner.
But here's the wacky thing with the Necker cube. It
really could be either way. It's equally probable that these
lions represent a cube this way or represents a cube
the other way. There's a fifty percent chance of either
of these. This is known as eque probable. So your
(43:58):
brain takes this equa probable stimulus and nails it down
to one choice or the other. But if you have
stared at one of these drawings for more than ten seconds,
you know that your brain changes its interpretation. If you
stare at this wireframe, it looks like it's coming out
one way from the page, but if you keep staring,
(44:19):
it'll switch so that it looks like it's coming out
the other way. And if you stare at this for
a little while, you'll see that it switches back and forth.
You see it one way then the other way. Your
brain will stick with one interpretation for a little while
and tell you that's what's in the world, and then
it will suddenly change its claim. Why because, as I said,
(44:40):
there's a fifty percent chance of interpreting the cube one
way or the other, and the brain cannot see both
interpretations at the same time, so it switches between them.
Speaker 2 (44:50):
It's the king of the hill game, but the king
never lasts.
Speaker 1 (44:55):
Someone always manages to knock that kid off the top,
and then the new kid has to defe and the
throne against other invaders. And that's precisely what happens with
these neural network competitions. One network wins, but it doesn't
last that long before it gets unseated. And then the
other network is active in a loop of self reinforcing
(45:16):
neurons firing. It gets to keep control be king of
the North for a little bit, but then the first
one unseats it again. So what you see with the
simple drawing is the ever present, active battle in your
skull to control perception. So, in other words, if you
have two possible top down models, either.
Speaker 5 (45:39):
Of which could equally be right, they'll fight and you'll
believe whoever the temporary winner is, and then you'll believe
the next guy when he's back in power, and then
the first network.
Speaker 2 (45:51):
Again.
Speaker 1 (45:53):
Now the dress tends not to switch, and this is
because it's not equiprobable. Our brain has developed very clear
prior expectations about lighting and fabric and windows and so on.
So my brain makes an interpretation and your brain makes
an interpretation, and there's no reason for either one of
(46:14):
them to question it. It's like playing King of the
hill against some small puppies. No one's going to knock
you off the throne. And that's why it's so difficult
to change your interpretation of the dress, even when you're
told that some other interpretation is possible.
Speaker 2 (46:31):
Your brain relies on.
Speaker 1 (46:33):
Deep assumptions about the world, and it's generally just too
hard to unseat the monarch. But what the Necker cube
reveals is that our brain's interpretation of the world can
be quite active if there are other equally likely interpretations
to be had, So the way we see the world
can change from moment to moment. Now as just a
(46:56):
one minute tangent. The funny thing is that you think
you are making the cube switch interpretations by yourself. In
other words, you feel like you're doing it consciously when
the cube switches back and forth.
Speaker 2 (47:08):
But let's say we measure this. You stare at the
little cube and you hold down one key when you.
Speaker 1 (47:15):
See it in this configuration, and as soon as your
perception switches and now looks the other way, you hold
down the other key. And you do this for a while,
back and forth and back and forth. You hold down
a key to let me know which perception you are seeing.
And remember how amazing this is because nothing is changing
on the page. It's only in your head.
Speaker 2 (47:35):
Anyway.
Speaker 1 (47:35):
When we look at the data, it's clear that your
results follow a particular mathematical distribution called a gamma distribution,
which comes from a random process. For the efficionados, this
is consistent with a poissone process. All this means is
that this switching is random, and this is exactly the
distribution you would expect from randomness. Sometimes you have the
(47:58):
winning network holding on to the throne for a long time,
so as for a short time, and on average it
lasts this medium amount of time before it switches. The
point is you think you're switching consciously, but it's just random.
The reason you take credit is because you think, Okay,
I'm seeing it this way, and I really want to
(48:19):
make it switch the other way, and I'm going.
Speaker 2 (48:21):
To consciously work to switch it.
Speaker 1 (48:23):
Okay, almost there, not quite working, still trying, and then
it randomly switches and you take credit for it. Here's
an analogy to help us understand that. You know those
pedestrian crossing buttons that you push when you want to
cross the street, and the little walk signal eventually shows
up and lets you know that you're safe to walk.
Speaker 2 (48:44):
Some fraction of those buttons are placebos. They're fake. You
hit them, but they don't do anything.
Speaker 1 (48:50):
You wait for exactly the same amount of time that
you would have waited anyway, but you have a sense
of control, an illusion of power over the light, even
though the timing doesn't change one bit.
Speaker 2 (49:03):
And this is exactly the situation with this switching of
the Necker cube.
Speaker 1 (49:07):
You consciously try to change it, and when it eventually
changes on its own, you think, yeah, that was because
of me. But when we measure the switching times, it
doesn't change anything at all, whether you're trying or not trying,
whether you're banging on that button or ignoring it. Okay,
so now I want to zoom back up to the
(49:28):
big picture about what we've been talking about, which is
how your brain makes assumptions about things, and how in
some circumstances these assumptions can fight it out. So we
see this in language often take the example of puns.
Puns strike us as funny because we're able to switch
back and forth and see the same thing in two
(49:49):
different ways. What do you get when you drop a
piano down a mine shaft a flat minor. The point
about puns is that we know from the s mile
on the other person's face that there's some joke to
be had, and so we search for other interpretations, and
we can switch back and forth between them, just like
(50:09):
a Necker cube. But something I found interesting is that
brains can be lazy, and we don't always bother or
seeking other interpretations. If you don't have a strong enough
reason to have more than one interpretation, then you stick
with what you've got. And this is often true in language,
which is very low bandwidth and depends enormously on assumptions.
(50:33):
So the other night I was at a party and
somehow the conversation moved in a direction where I mentioned
the famous book by Rachel Carson called Silent Spring. It
just so happened that no one there had heard of
this book. So in a sentence. I explained that the
author had argued that if pesticide use continued, there wouldn't
(50:53):
be any more birds, and so the spring season would
come around and we would hear no more chirping. It
would be And I was sort of surprised when everyone said, oh,
like I had just cleared up some confusion for them,
because it turns out that when I had said silent spring,
the person to my left thought I was talking about
(51:14):
a spring like a creek, so she interpreted the title
as silent river, and the person to my right thought
of spring like boeing boeing spring. And the person across
from me thought I was talking about the word spring
like the verb to jump, so he pictured silent spring
as a lion springing on him silently. And this is
(51:37):
typical of the way that we take in little bits
of data and impose an interpretation on them, and then
we're done. Our brains aren't generally incentivized to keep looking
for interpretations. You pick one and that's it. And by
the way, that's typically what happens with Laurel and Yanny.
If you didn't know to listen hard for something else,
(51:58):
you probably wouldn't. And with green needle and brainstorm. Unless
you were told to switch your perception, you probably wouldn't
have even thought to try it. And so I often
wonder about the ways that we do this with many
things around us. We pick some top down model and
that seems to match the bottom up data, and it
(52:20):
doesn't strike us to examine further because we're pretty sure
we have a match. I'll leave this as an open
question for all of us to think about places in
our life that maybe we haven't even thought to re
examine more deeply. So to wrap this up, when this
woman in the UK sent a little cell phone photo
(52:41):
to her daughter about her dress, it not only broke
the Internet, the more importantly, it breaks for us a
critical assumption that almost everyone carries around, the assumption that
when I look at the world and you look at
the world, we see the same thing. The naive umption
is that there is simply truth out there and it's
(53:04):
just a matter of opening your eyes. But the dress
and hundreds of other illusions reveal that we don't see
the world out there directly. Everything is interpretation. We only
have a bit of data dribbling in through our peripheral devices,
our sensory organs, and that data enters into a brain
(53:26):
that's already churning and bubbling with its own activity, its
own expectations, and so all we ever perceive is the
best guess from our neural networks about what is going
on out there, given a little rough data and a
lot of assumptions shaped by our past experiences. So the
(53:48):
next time you see a face in an electrical outlet,
where you see a shape in aurorshack blot, or you
see the dress and feel certain about its color, just
remember you are not seeing the world as it is.
Speaker 2 (54:03):
You are seeing it as you are.
Speaker 1 (54:10):
Go to Eagleman dot com slash podcast for more information
and to find further reading. Send me an email at
podcast at eagleman dot com with questions or discussions, and
I'm going to be making episodes in which I address
those reaching.
Speaker 2 (54:25):
Out on a narrow road from my internal world to yours.
This is David Eagleman, and thank you for joining me
in the inner cosmos.
What's up with those illusions on the Internet where you
can hear the same sound one of two different ways
depending on the word that you're looking at. And why
do electrical outlets sometimes look like a face to you?
How can you have full, rich visual experience with your
eyes closed. And when you want to cross a street
(00:27):
and you hit that crosswalk button, are some of those
buttons fake and they don't actually do anything?
Speaker 2 (00:33):
And why are there some.
Speaker 1 (00:34):
Pictures that you can only see once you're told what
you're looking at. And although brains are often celebrated for
their parallel processing, what did they really be celebrated for.
Welcome to Inner Cosmos with Me David Eagleman. I'm a
neuroscientist and author at Stanford and in these episodes we
(00:57):
sail deeply into our three pounds universe to understand why
we perceive the world in the ways that we do.
Today's episode is about expectations and what that has to
(01:18):
do with perception. Unless you were living in outer space
or off the grid in twenty fifteen, your life was
touched by a very tiny, specific event that happened on
a small island in Scotland. Two young people were going
to get married there, and a week before the wedding,
(01:41):
the mother of the bride was shopping around for what
she was going to wear. So she finds some outfits
at a store down in Chester, England that she thinks
will look nice, and while she's making the decision, she
snaps pictures of each of them and she buys one
of them.
Speaker 2 (01:58):
So she's driving home.
Speaker 1 (01:59):
After words and she texts the pictures of the three
outfits to her daughter and she tells her that she
had bought the third one, and no one could have
ever guessed that this particular piece of clothing that she
sent a picture of, this one piece garment, is about
to become the most famous outfit that ever existed in
(02:22):
the history of humankind, because the daughter writes back to
clarify which outfit the mother had bought, and she texts, oh,
the white and gold one, and the mother texts back, no,
it's blue and black, and the daughter replies, Mom, if
(02:43):
you think that's blue and black, you need to go
and see the doctor. So the mother shows the phone
to her partner in the car, who, despite having been
there and bought the dress with her, looks at the
photo and says, yeah, I think it's white and gold.
So when they get home, they show the picture to
their younger, who agrees with the mother that the photo
looks blue and black. So, given this funny disagreement, the
(03:08):
bride to be posts the photo to her friends on
Facebook to settle this, and to her surprise, she doesn't
find consensus. Some think it's black and blue, others think
it's white and gold, and each person feels totally certain
about what they see. So for about a week, this
(03:29):
debate bubbles around in this small island community. The day
of the wedding arrives and the mother wears the dress
to the event, and the issue about the photo becomes
such a point of discussion that the musicians in the
band allegedly almost didn't make it onto the stage to
play because they were wrapped up in the debate.
Speaker 2 (03:49):
So a few days after.
Speaker 1 (03:50):
The wedding, one of the band members, who was a
friend of the happy couple, she posts the photo to
her blog on Tumblr, and by the end of the
day it gets five thousand comments, and soon enough, the
data scientists at Tumblr are examining this post because it's
getting fourteen thousand views each second. That's close to a
(04:15):
million views each minute. So a woman on the BuzzFeed
social media team sets up a poll about the color
for Tumblr users, and then she packs up and goes
home on the subway. And by the time she gets
off the subway, her phone is overwhelmed, and soon enough
the BuzzFeed page hits new records for how many unique
(04:38):
visitors were on the page at the same time, hitting
almost seven hundred thousand. The number of comments on the
original post increases tenfold that night. By late that night,
there are five thousand tweets per minute using hashtag the dress,
and by the middle of that night it's grown to
eleven thousand tw wheets per minute. Within the week, more
(05:02):
than ten million tweets are talking about the dress. This
was the dress that, as they say, broke the Internet. Now,
if you were, say a space alien, you might look
at all this human activity and think, wait, what, why
is the world stopping over a simple picture of a
piece of clothing in the UK. Now, the answer, as
(05:26):
you know, is that none of us humans would have
found it interesting either, except that someone that you loved
and trusted said, what do you mean you're seeing it
that color? It's so clearly the other color, And you said, wait,
what are you being serious? And they asked you the
same and then the awe sets in. You both realize
(05:48):
that you're looking at the same thing in the outside world,
and you're having different perceptions a different experience on the inside. Now,
no one was more excited about the dress than neuroscientists,
because for neuroscientists this was a terrific demonstration of what
we're going to talk about today. So to start things off,
(06:11):
let's just point out how important these kinds of perceptual
oddities are to neuroscience. I've spent a big chunk of
my career studying illusions. I've published scientific papers about illusions
in journals like Science and Nature, And some years ago
I wrote a review article in the journal Nature Reviews Neuroscience,
(06:34):
and I titled it Visual Illusions and the Brain, And
in that article I laid out how powerful illusions are
for figuring out what is under the hood. Sometimes I
feel like illusions are interesting only to ten year olds
and for most people they become nothing but entertainment. But truthfully,
illusions are microscopes for understanding what is happening in the brain.
(07:00):
Them we can reveal the systematic differences between what is
actually out there in the world and what we believe
is out there, And by dialing the illusion around carefully,
we can usually put constraints on how the network of
neurons must be operating. Now, most illusions are the type
(07:22):
in which we measure what's being presented in the outside world,
like two lines of identical lengths and you see it
as two different lengths, and we say, ah, there's a
systematic difference between what's on the page and what you perceive.
Speaker 2 (07:38):
Or maybe I show you two.
Speaker 1 (07:39):
Parallel lines against some background and you don't see them
as parallel. Or you look at a totally static picture
on a page and you swear that it's moving. But
the dress was interesting because it wasn't that traditional kind
of illusion. Instead, one person sees one thing and the
person standing right next to them sees another.
Speaker 2 (08:02):
Now, what all.
Speaker 1 (08:03):
Illusions, including the dress, tell us right away is a
foundational point that's not always intuitive, which is that we
don't simply look at the world and passively receive what's
out there. Instead, our brains actively construct our perception, and
different brains can do so differently. So now let's move
(08:26):
deeper into this mystery by turning to a different illusion.
That took over the Internet a few years later, in
May of twenty eighteen.
Speaker 3 (08:36):
Laurel Laurel, Laurel.
Speaker 1 (08:41):
Now, this was an audio file that was originally recorded
by a reader in two thousand and seven for vocabulary
dot com, and some students apparently re recorded that file
while there was some background noise in a room. So
a fifteen year old freshman in Georgia named Katie was
listening to that recording and she realized that she was
(09:03):
hearing some funny ambiguity, and she posted this little audio
clip on Instagram, and the next day her friend posted
it on Reddit, and then it got picked up on
Twitter and.
Speaker 2 (09:13):
Soon it went nuts.
Speaker 1 (09:15):
Why Because just like the dress, people can have a
different perception of the same item presented to their senses.
About half the people hear the word yanny and the
other half hear the word Laurel.
Speaker 3 (09:32):
Laurel, Laurel, Laurel, Laurel.
Speaker 1 (09:39):
Now, how can people hear different things? So hang tight,
I'll tell you in a minute. But what I want
to point out for now is that, just like the dress,
some people have one experience, some people have another, same
sound recording, different experiences. Now, the Yanny Laurel clip made
its rounds on the internet, but it about the exact
(10:01):
same time. In May of twenty eighteen, something even better
surfaced on YouTube. A guy had posted a video where
he was reviewing a children's toy from the ben Ten franchise,
and the toy lights up and says something. And here's
what it sounds like. It says the word green needle.
(10:22):
So listen carefully for green needle. Okay, well, that's not
actually what the toy was saying. It was actually saying
the word brainstorm, which is the toy character's name. So
listen for the word brainstorm.
Speaker 2 (10:52):
Now, I just.
Speaker 1 (10:53):
Played the exact same audio file in both cases, but
depending on your expectation what you were listening for, you'll
hear different things. So I'm going to play this file again,
over and over for about twenty seconds, and I want
you to think about brainstorm or think about green needle.
(11:13):
Try to go back and forth about which one you're hearing.
Switch your thinking from one to the other at any point.
Speaker 2 (11:39):
So, what the heck's going on here?
Speaker 1 (11:41):
How can a single audio file be heard two completely
different ways? Seems like magic, but it's actually neuroscience. All
these internet memes actually give deep insight into a fundamental
and rarely appreciated property of the brain. So I'm going
to unpack these illusions in a few steps. The first
(12:04):
clue to the mystery is that the brain does not
tolerate ambiguity. It really wants to come to a conclusion
about exactly what's out there. Now, that's a major daily
challenge for the brain because so much of what you
see or hear is ambiguous. You have data points that
(12:25):
come streaming into the brain through the eyes, or the ears,
or the fingertips, but often they could be interpreted more
than one way. So what does the brain do in
this circumstance. It locks onto a single way of understanding it.
In other words, if there are multiple possibilities, it'll force
(12:46):
an answer. Now let's pause for just a moment to
appreciate something here. When you read about the brain, you
always see it celebrated for its parallel processing. It can
do lots of things at once. But what it should
be equally celebrated for, the thing that no one ever
bothers to highlight is serialization. It takes lots of the
(13:10):
activity and it squeezes it down to one thing.
Speaker 2 (13:14):
It serializes it.
Speaker 1 (13:15):
It takes an information that could be interpreted in lots
of different ways, and it crunches it down to a
single interpretation.
Speaker 2 (13:24):
Now, why is it so good at serializing, at.
Speaker 1 (13:28):
Getting possibilities down to a single answer, Because fundamentally, your
brain has the challenge of controlling a giant body made
of trillions of cells, and when you come to a
tree in the path, it has to go either left
or right around the tree. Because of the physics of
(13:48):
the world, it cannot do both, and.
Speaker 2 (13:50):
So it has to make a single.
Speaker 1 (13:53):
Decision, go right or go left, and drag all those
trillions of cells with it. Your brain it has to
be good at taking possibilities and crushing them down to
a single decision. And it's the same with your perceptual life.
Your brain is used to dealing with a world where
(14:14):
it has to come to conclusions, having to say, look,
there are lots of possibilities here, but for me to
function in the world, I have to make an assumption
that what I am looking at is a piece of
food or a boulder, or a bear at a distance
or whatever. So the brain doesn't tolerate ambiguity, but it
(14:36):
always says, all right, this is my answer okay, So
now let's introduce one more perceptual illusion of this flavor,
and then we're going to unpack what's going on.
Speaker 2 (14:49):
So surely you've seen this one before.
Speaker 1 (14:51):
You draw the outline of a cube on a piece
of paper. You just draw a square, and then an
offset square, and then lines connecting the corners of one
to the corners of the other, so it's twelve lines.
It's the outline of a cube. This little wireframe drawing
is known as the Necker cube.
Speaker 2 (15:10):
Now you've seen this before, but as you know, if you've.
Speaker 1 (15:13):
Stared at one, it's perceptually ambiguous because if you stare
at this little wireframe, it looks like it's coming out
one way from the page, even though you could perceive.
Speaker 2 (15:25):
The same drawing in two different ways.
Speaker 1 (15:27):
Either the lower square is the face of the cube
coming toward you, or the upper square is the one
coming out toward you, but your brain makes a choice. Now,
you could imagine a space alien who looks at this
little drawing of the wireframe cube and says, okay, well,
both configurations of the cube are equally probable, so I'll
(15:50):
see it both ways at once. But we can't do that.
We have to see it one way or the other.
Your brain forces a single interpret and this is the
same thing that's happening with the other illusions with the dress.
You don't see it as both blue and black and
white and gold. And in a minute we'll see why.
(16:13):
The part I just want to say now is that
your brain concludes that it is one or the other,
and then it sticks with that. And likewise with Yanny Laurel.
Both sounds are present in the audio file, but you
don't hear Yanny and Laurel at the same time, stacked
on one another. And it's exactly the same thing with
(16:33):
brainstorm and green needle. Both interpretations are possible, but your
brain won't do both at once. It collapses the possibilities
to a single answer. In all these cases, even though
the data is consistent with either interpretation, your brain makes
a call. It goes left or right around the tree.
(16:55):
You very clearly perceive one or the other. And this
is because the brain isn't passively receiving the world. It's
making choices. Okay, but how does your brain know how
(17:25):
to collapse ambiguous data to a single interpretation. It does
so by leveraging assumptions, so let's go a level deeper
with the dress. Why does it happen that some people
see it one way and some people the other. It
happens because your brain sees a picture of a dress
in the shop and it makes dozens of assumptions totally unconsciously. Now,
(17:50):
what's amazing is that the assumptions aren't directly about the dress,
but about things you didn't even know you were thinking about.
What is the light source in the photograph? Is the
dress mostly being lit by fluorescent lights or by sunlight?
Is the dress facing a window or is the window
(18:12):
behind it? What time of day is it, what season
is it? Your brain is considering all of these questions,
and fundamentally, this all has to do with a computation
that it does known as color constancy. Color constancy is
this sophisticated ability of our visual systems to perceive the
(18:35):
color of something as constant even when the light source
the illumination changes. So let's say I'm wearing a white
T shirt and we're standing outside talking in the sunlight.
You will see my shirt as white. Now we go
indoors into the coffee shop and the illuminant changes. In
other words, the light that's bouncing off my t shirt changes.
(18:58):
Now it's fluorescent light compared to sunlight. The fluorescent light
has a different spectrum of colors coming out, and so
when those bounce off my shirt, you have a different
spectrum of colors hitting your eyes, and yet you still
see it as white. And then that night we go
into a dance club and the lighting is blue, and
(19:21):
yet you have no problem seeing the shirt as white,
even though it's mostly blue light reflecting off the shirt
into your eyes. And then afterwards we go sit by
a campfire and my shirt still looks white. Your brain
retains a constant perception of the color of the shirt
(19:41):
even though the wavelengths bouncing off of it are very different.
So what does this tell us, Well, it means that
the way your brain determines the color is not just
about the colors hitting your eye from the shirt. It
has to do with something else. And that's something else
is everything else in the scene. So when you're looking
(20:04):
at my shirt, your eyes are drinking in everything else.
The background, the color of the skin on my arms,
the color of the floors and walls, the colors of
all the other.
Speaker 2 (20:18):
Jeans and shirts and signs in the.
Speaker 4 (20:20):
Whole scene, and it uses all of that to estimate
the background illumination and then make the right computation about
the color of the shirt in the sunlight and the
coffee shop, at the dance club, at the campfire.
Speaker 2 (20:37):
It's doing all of.
Speaker 1 (20:38):
These computations, and this is what allows it to subtract
off the background lighting so that it can see what
color things are most likely to actually be. That's the
phenomenon of color constancy. The color of the shirt remains
constant even under different illumination, and that's what allows us
(21:01):
to see the colors of objects in the world consistently,
whether we're looking under sunlight or moonlight or firelight or whatever.
So the first lesson is you're not just seeing what's
out there. Your brain is actively interpreting information and serving
up a story to you. And I'll go into this
(21:22):
more in a future episode. But this is why we
can see strawberries as red. For example, when we change
the background color such that the actual light bouncing off
the strawberries is gray light, your brain can nonetheless say, okay, well,
given that everything else in the scene is now greenish,
I can subtrack that off and know that I'm looking
(21:44):
at something red. Now, in order to do all of
this that I've been talking about, your brain has to
make lots of assumptions about what the color should be,
and different brains do it differently. With the dress, you
see it as either white and gold or blue and black,
(22:06):
depending on the assumptions your brain is making. When you
glance at the photo on your phone, you have no
idea that your brain is doing all those sophisticated computations
under the hood to tell you what is the actual
color of this garment, given my assumptions about all the
lighting details.
Speaker 2 (22:27):
The issue is that your.
Speaker 1 (22:29):
Brain grew up in a particular environment, maybe with a
lot of snow or a lot of sunlight or fog,
and your brain makes assumptions about the time of day
and the season and the balance of artificial lighting to
natural lighting. To make sense of this little photo, what
hues does the lighting contain. If your brain ignores a
(22:52):
bit of the blue side, you'll see the dress as
white and gold. If your brain pays less attention to
the yellow side of the spectrum, you'll see it as
blue and black. You have no insight into the fact
that your brain is making all these assumptions under the hood.
Was the photo of the dress taken with the window
facing it or behind it.
Speaker 2 (23:13):
Was it morning light or afternoon light?
Speaker 1 (23:15):
And is your experience of the world based on the
fact that you are a mourning lark or you are.
Speaker 2 (23:21):
A night owl.
Speaker 1 (23:23):
One of my colleagues, Pascal Wallash, showed that people who
were early risers were more likely to think that the
dress was lit by natural light, and so they saw
it as white and gold, but night owls presumably had
more assumptions about artificial lighting, and they were more likely
to see the dress as blue and black. Your brain
(23:45):
is determining the color of the dress by comparing it
against the other objects of the background of the photo
and making its best guess at all these parameters. So
your brain relies on the answers to question is that
you didn't even think it was asking and the idea
of imposing assumptions. This is the same with Yanny and
(24:07):
Laurel in the auditory domain, or with green needle and brainstorm.
Your brain is imposing an interpretation. But what's interesting in
this case is that the assumption can be changed more easily,
typically by just staring at the word visually. Because your
brain is trying to disambiguate what it's hearing, and suddenly
(24:31):
it has lots of help from the visual system because
it sees a word. So the frequencies of both words
yany and laurel or green needle, brainstorm, they're contained in
the audio file, so just depending on how you listen
for it, you can hear one or the other. So
(24:52):
the brain constantly nails down its world by making assumptions,
and we see this with everything. And even though these
internet memes get all of our attention, the fact is
that our brains have to make assumptions all the time.
And this is because most of the inputs from the
world are quite noisy. For example, you can still understand
(25:16):
me even if my speech is choppy, or if I'm
speaking and there's lots of background noise like at a restaurant.
What's actually hitting your ears in these scenarios is a
very messy signal, But the brain imposes an interpretation about
what must have been said, and that's what you perceive
what you believe you heard. A lot of your cell
(25:38):
phone conversations are super noisy, but you typically don't realize
it because you keep making your reasonable interpretations. Now, this
is true of most of what is hitting your eyes
and ears. You don't catch a fraction of the data,
but your brain fills in the details to put together
(25:59):
a story. And this, by the way, is what's at
the heart of a lot of art and graphic design.
You just see a few curves and you interpret it
as a face, or a series of segmented lines and
you interpret that as a body. We are always operating
off thin data, but that doesn't stop us from coming
(26:19):
to clear conclusions. And before I explain how our neural
networks go about making these assumptions, let's just take a
second to look at how your brain is so imperfect
at this. Take paridolia, which is when you perceive a
meaningful pattern where none exists, Like when you look at
(26:41):
an electrical outlet and you see a face made up
of little eyes in a sort of surprised mouth. You
can't help but see that. Your brain imposes that interpretation
on it. Or you see a face in the clouds,
or someone sees the face of their local deity in
a piece of toast. Why does this happen, Well, your
(27:03):
brain is really wired up to see faces, and so
it triggers that interpretation whenever it sees three blobs in
the approximately right configuration, and the same thing can happen
with sounds, like when there's some weird sound and your
brain thinks it's a person shouting or someone calling your
name or whatever. This is the brain working to make
(27:26):
sense of the world around it. All it ever does
is look for meaning from data in the world. In fact,
typically the brain will try to impose an interpretation even
if you have random noise. That's the idea with rorshak
ink blots. You have these blobs on a page, and
(27:47):
your brain reaches for some way of explaining them. Oh,
that looks like a rabbit or an airplane, or an
emperor on a throne or whatever. And generally a lot
of life involves forcing patterns on random noise. Here's an
auditory example from my colleague Diana Deutsch, who has spent
her career pioneering auditory illusions. So here's an experiment where
(28:12):
she plays mixed up audio that doesn't say anything, but
it sounds like speech, and people will generally impose the
interpretation of words on these.
Speaker 4 (28:57):
Come come, come, come, come, come, come, come, come come.
Speaker 1 (29:33):
This is essentially the sound version of Rorschach blots. Different
people will generally hear different things, and it seems to
be related to what they are thinking about or what's
on their mind. So this all reminds us of the
power of the brain to impose meaning. Just think about
the situation when you're expecting a friend and you're looking
(29:56):
around for him at a crowded mall. Everyone looks like him.
For just a fraction of a second. You look at
someone's face and you think, oh, that's him, and then
five hundred milliseconds later, your visual system takes in more
information and decides out never mind false alarm, And then
we typically forget that we even thought that. But we
(30:17):
are expecting to see our friend, and so our brains
impose that expectation on lots of faces. Okay, so we've
established that brains take ambiguous signals and squish them down
to a single interpretation by use of assumptions. And that's
why we see the dress as one color or the other,
(30:38):
or we hear brainstorm or a green needle, but not both.
But how do our brains actually make their choice? How
do they pull this off? Neurally speaking, they do it
by combining bottom up information with top down information. Now,
bottom up means information and from the outside from the world.
(31:02):
What are the air compression wave of sitting my ear
drums or what are the photons sitting my retina?
Speaker 2 (31:07):
Those are the signals that I am receiving.
Speaker 1 (31:10):
But we don't interpret those bottom up signals that face
value because they're usually not sufficient. Instead, your brain melds
this with top down information, which means your expectations what
we think is likely to be true in the outside
world given our experience with it, and it's only in
(31:30):
combination the data plus our expectations that we see anything
in the world. And the surprise, I think the counterintuitive
part is that your prior assumptions, your expectations, the.
Speaker 2 (31:45):
Top down part.
Speaker 1 (31:46):
This is the overwhelming majority of what determines what you see.
For example, it seems like you just open your eyes
and there's the world, but in fact, when you look
at the visual cortex at the back of the which
is the place that receives the information from the eyes,
you find that only five percent of the input there
(32:07):
is coming from the eyes.
Speaker 2 (32:09):
And the rest is all feedback activity.
Speaker 1 (32:12):
In other words, ninety five percent of the data is
coming from higher levels of the visual system and other
areas of the brain. In fact, What is so crazy
is that you don't even need your eyes to have full,
rich visual experience. You can have this with your eyes closed.
(32:32):
And this is what we call dreams. And what's happening
here is that this is all internally generated activity and
none of it's entering through the eyes when you're asleep,
and it's not that much different from your normal vision.
So your perception of the world when you're walking around
is something like an awake dream.
Speaker 5 (32:53):
Now.
Speaker 1 (32:53):
I'm going to return to this issue in future episodes,
but what we want to concentrate on right now is
that your eyes are not simply a camera and your
ears are not simply a microphone. For those of you
who have been listening for a while to this podcast,
you know this is a major theme. Your brain is
locked in silence and darkness and needs to make assumptions
(33:16):
based on very thin data. So when I ask you
to think about the words green needle, that is top
down information that shapes how you interpret the bottom up data.
(33:37):
In contrast, imagine that you stare at the word brainstorm
while listening. You lock that in as your top down expectation,
and then that shapes your bottom up data.
Speaker 2 (33:46):
And that's what you hear.
Speaker 1 (33:55):
Even though both interpretations are available, your brain surfaces is
those features out of the landscape of data that match
what you're looking for. In other words, your expectations. What
you listen for is what you hear. And by the way,
all this is related to why lip reading works. When
(34:16):
you're in a noisy environment, you watch somebody's mouth while
they're talking, and in this way you combine a bit
of noisy auditory data with a bit of noisy visual
and that sharpens your guess for what was just said.
During the pandemic, a lot of conversations went misunderstood because
people were wearing masks and lip reading went out the window.
(34:40):
Now amazingly, this top down information is so important that
sometimes you can set up a picture where you don't
have any real prior assumptions and there's not enough information
in the picture to see anything. And only when I
tell you some interpretation does the bottom up information should
(35:00):
make any sense at all.
Speaker 2 (35:01):
You can only see.
Speaker 1 (35:03):
What's in front of you if you're given top down direction.
For example, I've put a cool picture on my website
at eagleman dot com slash podcast. Take a look at
this field of black and white blobs and see what
it looks like to you, And presumably it looks really
like nothing at all, just a bunch of blobs. But
(35:23):
if I tell you what it is while you stare
at it, then you suddenly see it. It seems immediately
obvious and you cannot see anything other than that, And
the only thing that's changed is that you now have
a top down expectation about what you're seeing, and suddenly
all these blobs make clear sense. I'm not going to
(35:43):
tell you what the blobs are here, but if you
go to the website and scroll all the way to
the bottom of the page, I'll give you a hint
there so you can enjoy the experience of not knowing
and then knowing. And because this is a podcast, I'll
give you an auditory example of this, again from Diana Deutsch.
So I'm going to take a piece of music that
(36:04):
you know, but I'm going to shift each note up
or down an octave, so one note might be played
an octave higher and the next note might be played
an octave lower. And I want you to identify the
piece of music. It's definitely one that you know. Now
(36:28):
I assume that you couldn't identify that piece. Now I'm
going to play it for you without the notes shifted
up or down in octaves. Now that you know the tune,
I'm just going to play that first one again and
you should have little or no trouble hearing the correct melody.
Speaker 2 (36:59):
The only difference between the first.
Speaker 1 (37:01):
Time I played it and the last time is that
now you have a top down expectation, and so it
switches from random noise to a tune. And so these
are all examples in which top down expectations are critical.
Without them, you don't have any interpretation at all. And
(37:22):
once you build an expectation, then the data have meaning.
You need to be told what to see in the
picture or to hear in the tune to get it.
And the only difference between before and after is whether
you have something to match it to some top down expectation,
and as soon as you do, then you perceive. Now,
(37:45):
just to be clear, this doesn't mean you can impose
any top down interpretation. It has to match sufficiently well.
The thing about brainstorm green needle is that the bottom
up data can match either one of the top expectations
for either word. You can hear green needle or brainstorm.
(38:06):
Because these are possible words that can roughly match the
bottom up stimulus with all of its noise, But you
can't hear something totally different like blue reader or my
penguin because you can't make a good enough match between
data and expectation. So there has to be a sufficient
(38:26):
match between the top down and the bottom up for
perception to happen. Okay, so let's come back.
Speaker 2 (38:33):
To this issue about the assumptions that we make. How
do we know what to assume about the world.
Speaker 1 (38:40):
Well, this relies almost entirely on our prior experience. For example,
when you're judging depth, like how far different things are
from you, which is again a totally unconscious process, you
can do this by comparing the images from your two eyes,
but this is only useful out to about thirty meters.
So it turns out the brain has other ways to
(39:03):
determine depth, and one of the main ones simply pivots
on its experience with the world. The visual system builds
up prior expectations about the relative sizes of objects. So
if you're standing outside and you see a dog in
the distance, then it takes up about as much space
on your retina as the truck over there. You can
(39:25):
assume that the dog is closer and the truck is
farther away. Why because a close dog will look a
certain size and a far away truck will end up
looking about that same size, and so your brain is
able to instantly make the proper assumption about how far
away things are. And you might be wrong, by the way,
(39:45):
maybe it's a miniature model of a truck that's really
close and a monstrously huge dog that's really far away.
But most of the time your assumptions are fine. So
data doesn't just come in from the world and get seen. Instead,
your visual system capitalizes on prior expectations. And although this
(40:07):
idea isn't always intuitive, it's not a new idea. In
the nineteenth century, the German physician and physicists Hermann von
Helmholtz was one of the first people to entertain this
model of perception. He suspected that the small amounts of
information dribbling in through the eyes were just too slight
(40:27):
to account for the rich experience of vision. So he
deduced that the brain makes assumptions about the incoming data
based on previous experiences, and he correctly surmised that this
is how the brain can use its best guesses to
rapidly turn a little trickle of information into a full picture.
(40:49):
By the way, if you want to look this up
in more depth, look up Helmholtz's notion of unconscious inference.
We infer what's out there, and it all happens unconsciously.
You can also look up Bayes' theorem as a way
of approaching this mathematically. One way to think about this
is that our judgments often rely not only on what's
in front of us, but also on all of our
(41:11):
prior experiences. So where we are so far is that
(41:31):
the process of perceiving the world, of interpreting what we
see or we hear, it's influenced by our past experiences,
which shape our current expectations, and that's what determines what
we think we see and hear. Now, it's sometimes the
case that your brain has more than one prior expectation.
(41:53):
It could be this, or it could be that, And
in this case it's easier to witness something very interesting,
which I want to tell you about now. So let's
return to the Necker cube, that little wireframe drawing. So
it's a very simple drawing, but it exposes something amazing,
which is a competition that is always raging under the hood.
(42:14):
Your brain is always trying to figure out what is
going on out there, and the way it does this
is by assessing probabilities. So this simply means you have
some networks that are saying, yes, it's definitely this, and
you have other networks that are saying, yes, it's definitely
this other thing.
Speaker 2 (42:32):
In the case of the Necker.
Speaker 1 (42:33):
Cube, you have one network saying the cube comes out
of the page this way, and the other network insisting
the cube comes out of the page the other way.
And in other illusions you sometimes have even more networks,
each voting for their thing. But the key to understand
is that it's a competition. All these networks are screaming
off and trying to dominate each other, and it's a
(42:57):
winner take all competition.
Speaker 2 (43:00):
It's like king of the hill.
Speaker 1 (43:02):
Whichever kid is able to get to the top of
the hill gets to push everyone else down. In the
case of local neural networks, when one is successfully firing
on all cylinders, it's able to inhibit the neighboring networks.
It releases neurotransmitters that keep itself propped up and at
the same time inhibiting the activity of the competitors, and
(43:26):
whichever network.
Speaker 2 (43:27):
Is king is what you perceive.
Speaker 1 (43:30):
And because it's a winner take all competition, there's only
one king at any time.
Speaker 2 (43:35):
That's why you don't.
Speaker 1 (43:36):
See all the possibilities at once. You only see the winner.
But here's the wacky thing with the Necker cube. It
really could be either way. It's equally probable that these
lions represent a cube this way or represents a cube
the other way. There's a fifty percent chance of either
of these. This is known as eque probable. So your
(43:58):
brain takes this equa probable stimulus and nails it down
to one choice or the other. But if you have
stared at one of these drawings for more than ten seconds,
you know that your brain changes its interpretation. If you
stare at this wireframe, it looks like it's coming out
one way from the page, but if you keep staring,
(44:19):
it'll switch so that it looks like it's coming out
the other way. And if you stare at this for
a little while, you'll see that it switches back and forth.
You see it one way then the other way. Your
brain will stick with one interpretation for a little while
and tell you that's what's in the world, and then
it will suddenly change its claim. Why because, as I said,
(44:40):
there's a fifty percent chance of interpreting the cube one
way or the other, and the brain cannot see both
interpretations at the same time, so it switches between them.
Speaker 2 (44:50):
It's the king of the hill game, but the king
never lasts.
Speaker 1 (44:55):
Someone always manages to knock that kid off the top,
and then the new kid has to defe and the
throne against other invaders. And that's precisely what happens with
these neural network competitions. One network wins, but it doesn't
last that long before it gets unseated. And then the
other network is active in a loop of self reinforcing
(45:16):
neurons firing. It gets to keep control be king of
the North for a little bit, but then the first
one unseats it again. So what you see with the
simple drawing is the ever present, active battle in your
skull to control perception. So, in other words, if you
have two possible top down models, either.
Speaker 5 (45:39):
Of which could equally be right, they'll fight and you'll
believe whoever the temporary winner is, and then you'll believe
the next guy when he's back in power, and then
the first network.
Speaker 2 (45:51):
Again.
Speaker 1 (45:53):
Now the dress tends not to switch, and this is
because it's not equiprobable. Our brain has developed very clear
prior expectations about lighting and fabric and windows and so on.
So my brain makes an interpretation and your brain makes
an interpretation, and there's no reason for either one of
(46:14):
them to question it. It's like playing King of the
hill against some small puppies. No one's going to knock
you off the throne. And that's why it's so difficult
to change your interpretation of the dress, even when you're
told that some other interpretation is possible.
Speaker 2 (46:31):
Your brain relies on.
Speaker 1 (46:33):
Deep assumptions about the world, and it's generally just too
hard to unseat the monarch. But what the Necker cube
reveals is that our brain's interpretation of the world can
be quite active if there are other equally likely interpretations
to be had, So the way we see the world
can change from moment to moment. Now as just a
(46:56):
one minute tangent. The funny thing is that you think
you are making the cube switch interpretations by yourself. In
other words, you feel like you're doing it consciously when
the cube switches back and forth.
Speaker 2 (47:08):
But let's say we measure this. You stare at the
little cube and you hold down one key when you.
Speaker 1 (47:15):
See it in this configuration, and as soon as your
perception switches and now looks the other way, you hold
down the other key. And you do this for a while,
back and forth and back and forth. You hold down
a key to let me know which perception you are seeing.
And remember how amazing this is because nothing is changing
on the page. It's only in your head.
Speaker 2 (47:35):
Anyway.
Speaker 1 (47:35):
When we look at the data, it's clear that your
results follow a particular mathematical distribution called a gamma distribution,
which comes from a random process. For the efficionados, this
is consistent with a poissone process. All this means is
that this switching is random, and this is exactly the
distribution you would expect from randomness. Sometimes you have the
(47:58):
winning network holding on to the throne for a long time,
so as for a short time, and on average it
lasts this medium amount of time before it switches. The
point is you think you're switching consciously, but it's just random.
The reason you take credit is because you think, Okay,
I'm seeing it this way, and I really want to
(48:19):
make it switch the other way, and I'm going.
Speaker 2 (48:21):
To consciously work to switch it.
Speaker 1 (48:23):
Okay, almost there, not quite working, still trying, and then
it randomly switches and you take credit for it. Here's
an analogy to help us understand that. You know those
pedestrian crossing buttons that you push when you want to
cross the street, and the little walk signal eventually shows
up and lets you know that you're safe to walk.
Speaker 2 (48:44):
Some fraction of those buttons are placebos. They're fake. You
hit them, but they don't do anything.
Speaker 1 (48:50):
You wait for exactly the same amount of time that
you would have waited anyway, but you have a sense
of control, an illusion of power over the light, even
though the timing doesn't change one bit.
Speaker 2 (49:03):
And this is exactly the situation with this switching of
the Necker cube.
Speaker 1 (49:07):
You consciously try to change it, and when it eventually
changes on its own, you think, yeah, that was because
of me. But when we measure the switching times, it
doesn't change anything at all, whether you're trying or not trying,
whether you're banging on that button or ignoring it. Okay,
so now I want to zoom back up to the
(49:28):
big picture about what we've been talking about, which is
how your brain makes assumptions about things, and how in
some circumstances these assumptions can fight it out. So we
see this in language often take the example of puns.
Puns strike us as funny because we're able to switch
back and forth and see the same thing in two
(49:49):
different ways. What do you get when you drop a
piano down a mine shaft a flat minor. The point
about puns is that we know from the s mile
on the other person's face that there's some joke to
be had, and so we search for other interpretations, and
we can switch back and forth between them, just like
(50:09):
a Necker cube. But something I found interesting is that
brains can be lazy, and we don't always bother or
seeking other interpretations. If you don't have a strong enough
reason to have more than one interpretation, then you stick
with what you've got. And this is often true in language,
which is very low bandwidth and depends enormously on assumptions.
(50:33):
So the other night I was at a party and
somehow the conversation moved in a direction where I mentioned
the famous book by Rachel Carson called Silent Spring. It
just so happened that no one there had heard of
this book. So in a sentence. I explained that the
author had argued that if pesticide use continued, there wouldn't
(50:53):
be any more birds, and so the spring season would
come around and we would hear no more chirping. It
would be And I was sort of surprised when everyone said, oh,
like I had just cleared up some confusion for them,
because it turns out that when I had said silent spring,
the person to my left thought I was talking about
(51:14):
a spring like a creek, so she interpreted the title
as silent river, and the person to my right thought
of spring like boeing boeing spring. And the person across
from me thought I was talking about the word spring
like the verb to jump, so he pictured silent spring
as a lion springing on him silently. And this is
(51:37):
typical of the way that we take in little bits
of data and impose an interpretation on them, and then
we're done. Our brains aren't generally incentivized to keep looking
for interpretations. You pick one and that's it. And by
the way, that's typically what happens with Laurel and Yanny.
If you didn't know to listen hard for something else,
(51:58):
you probably wouldn't. And with green needle and brainstorm. Unless
you were told to switch your perception, you probably wouldn't
have even thought to try it. And so I often
wonder about the ways that we do this with many
things around us. We pick some top down model and
that seems to match the bottom up data, and it
(52:20):
doesn't strike us to examine further because we're pretty sure
we have a match. I'll leave this as an open
question for all of us to think about places in
our life that maybe we haven't even thought to re
examine more deeply. So to wrap this up, when this
woman in the UK sent a little cell phone photo
(52:41):
to her daughter about her dress, it not only broke
the Internet, the more importantly, it breaks for us a
critical assumption that almost everyone carries around, the assumption that
when I look at the world and you look at
the world, we see the same thing. The naive umption
is that there is simply truth out there and it's
(53:04):
just a matter of opening your eyes. But the dress
and hundreds of other illusions reveal that we don't see
the world out there directly. Everything is interpretation. We only
have a bit of data dribbling in through our peripheral devices,
our sensory organs, and that data enters into a brain
(53:26):
that's already churning and bubbling with its own activity, its
own expectations, and so all we ever perceive is the
best guess from our neural networks about what is going
on out there, given a little rough data and a
lot of assumptions shaped by our past experiences. So the
(53:48):
next time you see a face in an electrical outlet,
where you see a shape in aurorshack blot, or you
see the dress and feel certain about its color, just
remember you are not seeing the world as it is.
Speaker 2 (54:03):
You are seeing it as you are.
Speaker 1 (54:10):
Go to Eagleman dot com slash podcast for more information
and to find further reading. Send me an email at
podcast at eagleman dot com with questions or discussions, and
I'm going to be making episodes in which I address
those reaching.
Speaker 2 (54:25):
Out on a narrow road from my internal world to yours.
This is David Eagleman, and thank you for joining me
in the inner cosmos.
Host
David Eagleman
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