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