Speaker 1: Why can't you tickle yourself? Why don't hippopotamuses tell stories
Speaker 1: around the campfire? What would I advise the president if
Speaker 1: we find ourselves at war with extraterrestrials? And what does
Speaker 1: any of this have to do with Wayne Gretzky or
Speaker 1: the Greek Goddess of Memory and her children? Or poking
Speaker 1: your finger into the side of your eyeball, or hitting
Speaker 1: a bottle to get ketchup onto your French fries? And
Speaker 1: why do we get so anxious about the world changing
Speaker 1: around us? Welcome to Inner Cosmos with me David Eagleman.
Speaker 1: I'm a neuroscientist and author at Stanford and in these
Speaker 1: episodes we sail deeply into our three pound universe to
Speaker 1: understand why and how our lives look the way they do.
Speaker 1: Today's episode is about one of the most important things
Speaker 1: that brains do, which is the simulation of possible futures.
Speaker 1: The way we teach about brains in the classroom usually
Speaker 1: has to do with the brain figuring out where it
Speaker 1: is and what is happening around it, Like it detects
Speaker 1: touch on its skin, and it detects photons from the
Speaker 1: environment out there, and it picks up on sound waves
Speaker 1: that are happening, and it stitches all of these together
Speaker 1: in the massive hurricane of electrical spikes that race around
Speaker 1: in the silence and darkness of your skull, and all
Speaker 1: of this neural information allows you to put together a
Speaker 1: picture of what is happening in the world out there,
Speaker 1: and that is what allows you to operate in the
Speaker 1: world and to catch that fish and put it in
Speaker 1: your mouth, and to run from the predator, or more hosaically,
Speaker 1: to find the right empty parking space, or tell the
Speaker 1: cashier what you want from the fast food menu, or
Speaker 1: apply the brakes on your bicycle when there's a pothole
Speaker 1: in the road. So the brain gathers data from the
Speaker 1: world around it so that it can operate inside of
Speaker 1: that world. But what we talked about last week was
Speaker 1: something surprising, which is that the brain doesn't spend all
Speaker 1: of its time in the present. In fact, a lot
Speaker 1: of its experiences are not in the here and now
Speaker 1: at all, but instead in the past. Your brain holds
Speaker 1: on to data about previous events in your life. In
Speaker 1: other words, what happened and who was there, and what
Speaker 1: the spatial configuration of the furniture was in the room,
Speaker 1: and the building, and you spend quite a lot of
Speaker 1: your time recalling that past. This whole process is what
Speaker 1: we summarize as memory. And what I emphasized last week
Speaker 1: is that we spend a good deal of our existence
Speaker 1: unhooked from the here and now, and instead we time
Speaker 1: travel to that past. But why do we care about
Speaker 1: the past? This is for one reason only. We do
Speaker 1: it to better simulate possible futures, and that's what today's
Speaker 1: episode is about. It turns out we spend an enormous
Speaker 1: amount of our time traveling to the future. Our time
Speaker 1: travel is not one way, it goes both directions. We
Speaker 1: simulate possibilities. We think of what our actions could lead to.
Speaker 1: If I say this, then my spouse might say this
Speaker 1: other thing back to me. If I open this cabinet
Speaker 1: over here, I will expect to find soup cans in there.
Speaker 1: If I do XYZ, I'll impress my boss, and I'll
Speaker 1: hope to get that promotion. We walk down long paths
Speaker 1: of possible chess moves that we can play in our lives. So,
Speaker 1: as I said, we spend the vast majority of our
Speaker 1: lives not in the here and now, but in the there,
Speaker 1: and then in either direction. We spend most of our
Speaker 1: days in daydreams and stories and confabulations in life narratives
Speaker 1: of reminiscence and future projection. When you tally all this up,
Speaker 1: the years that we spend in the realm of fantasy
Speaker 1: outstrip the time that we spend in the present. So
Speaker 1: why do we simulate the future? Well, first, it's much
Speaker 1: more energy efficient to do that than to try everything
Speaker 1: out in the real world. If I have to haul
Speaker 1: this rock over there, I can sit and simulate several
Speaker 1: possible approaches. I can imagine myself picking it up and
Speaker 1: carrying it over there. But then I realized, now I'll
Speaker 1: never be able to get it o over that big gulch. Well,
Speaker 1: thank goodness that I ran that simulation from the comfort
Speaker 1: of sitting on the ground and thinking about it. That's
Speaker 1: super energy efficient, and I can try out different methods
Speaker 1: of hauling the rock. What if I use a rope
Speaker 1: or a wheelbarrow or a catapult. I can try out
Speaker 1: all these different things without breaking a sweat or burning
Speaker 1: any calories besides the few calories required for simulation, which
Speaker 1: is orders of magnitude less than employing my muscles to
Speaker 1: move my multi trillion cell body. Around in the world,
Speaker 1: and this kind of simulation, this is what we humans
Speaker 1: do all the time. So imagine you are a fire
Speaker 1: chief and you and your team roll up on a
Speaker 1: new fire that's engulfing a building. Your job is to
Speaker 1: quickly make predictions about how to best position your team. So,
Speaker 1: given your past experience with the world, you mentally simulate
Speaker 1: different layouts and you evaluate their effectiveness, and then once
Speaker 1: you've simulated a great plan or the best of what's available,
Speaker 1: then you set it into action. In the real world,
Speaker 1: you don't have to try out every single thing in
Speaker 1: the physical world, and it's not just about energy efficiency.
Speaker 1: More generally, the reason you simulate possible futures is because
Speaker 1: it's much less dangerous than trying everything out in the
Speaker 1: real world. So let's say you're parked in your car
Speaker 1: and you need to go to some door, but there
Speaker 1: is a dog barking at you, So you run a movie.
Speaker 1: You simulate what would it be like if I make
Speaker 1: a run for that door, and your brain might run
Speaker 1: that and decide, you know what, that's not worth the risk.
Speaker 1: So your brain simulates other plans, like maybe you stay
Speaker 1: in the car and you dial the owner, or maybe
Speaker 1: you crack the window and you yell for the owner.
Speaker 1: Things like that, your brain doesn't actually have to run
Speaker 1: the risk of confronting the dog. Or maybe some big
Speaker 1: guy cuts in front of you when you're waiting in line,
Speaker 1: and you might simulate all kinds of things that you
Speaker 1: want to do to him in including calling him names
Speaker 1: or pushing him in the back or whatever. But you
Speaker 1: are usually better running the simulations in your head and
Speaker 1: not taking advantage of all the things that you could do.
Speaker 1: As the philosopher Carl Popper put it, simulation of the
Speaker 1: future allows our hypotheses to die in our stead, So
Speaker 1: intelligent brains do not want to engage in the expensive
Speaker 1: and potentially fatal game of physically testing every action to
Speaker 1: figure out what the consequences are. Instead, it is more
Speaker 1: efficient and safer when possible to envisage consequences of a
Speaker 1: proposed plan before you actually execute it. So by learning
Speaker 1: up the rules of the world and simulating possible outcomes
Speaker 1: and evaluating each one of them, your brain can play
Speaker 1: out scenarios without the risk and expense of attempting them physically.
Speaker 1: For this reason, prediction of possible futures is one of
Speaker 1: the highest priorities of biological systems. Now, fascinatingly, there hasn't
Speaker 1: been that much direct study of how brains do this,
Speaker 1: mostly because of the difficulty of observing it in action,
Speaker 1: because the whole purpose of mental simulation is to make
Speaker 1: action unnecessary, and the traditional way that we study the
Speaker 1: brain is to correlate something in the brain with an
Speaker 1: action and explicit behavior. So this is what makes it
Speaker 1: challenging to study simulation of the future. Nonetheless, what I'm
Speaker 1: gonna tell you about today is the way that we
Speaker 1: can pull together scattered data to begin to understand how
Speaker 1: brains build possible worlds. So let's get started. The important
Speaker 1: place to start is with an idea that I've talked
Speaker 1: about a lot on this podcast, the idea of the
Speaker 1: internal model. The idea is that the brain's job isn't
Speaker 1: just about detecting and reacting in real time, but it's
Speaker 1: about constructing a model on the inside about what's happening
Speaker 1: in the outside world. It's like you're running a simulation
Speaker 1: there in the silence and the darkness of the brain.
Speaker 1: And the key is that the internal model can emulate
Speaker 1: possible scenarios. Now, one of the first places that we
Speaker 1: see this kind of simulation get studied is with our
Speaker 1: physical interactions with the world. For example, think about when
Speaker 1: you hold a ketchup bar bottle in your left hand
Speaker 1: and you pound it with your right hand to try
Speaker 1: to get the ketchup to come out onto your French fries. Now,
Speaker 1: when you do that, your left arm doesn't move very
Speaker 1: much when you pound with your right hand because your
Speaker 1: muscles tighten up. But just the right moment. Now, if
Speaker 1: you want to try an interesting experiment, just hold the
Speaker 1: ketchup bottle and have a friend pound the bottle, and
Speaker 1: what you'll see is that your arm moves a lot.
Speaker 1: You can't keep your arm still when somebody else is
Speaker 1: hitting the bottle, But when you hit it, you are
Speaker 1: the one making the action, and your brain knows how
Speaker 1: to simulate what's about to happen in this case, that
Speaker 1: there's about to be a lot of pressure on your arm,
Speaker 1: and so it can deal in real time with counterbalancing.
Speaker 1: That This is the brain predicting something simple that hasn't
Speaker 1: actually happened yet. Your hand is about to hit the
Speaker 1: bottle and your arm tenses up in expense. Now, why
Speaker 1: does the brain care about prediction? Well, if your brain
Speaker 1: can simulate things into the future that can speed up
Speaker 1: your response time. And this is really useful for potentially
Speaker 1: dangerous things, like if you need to dodge a rock
Speaker 1: that's being thrown at you, or if you need to
Speaker 1: catch some prey and you can figure out where it's heading.
Speaker 1: This reminds us, of course, of the great hockey player
Speaker 1: Wayne Gretzky, who said, I skate to where the puck
Speaker 1: is going to be, not to where it has been. Now,
Speaker 1: you don't have to be Wayne Gretzky for your brain
Speaker 1: to be predicting the next step of everything around you. Why,
Speaker 1: because your brain's architecture is built to anticipate everything in advance.
Speaker 1: How does it do this Well, First, your nervous system
Speaker 1: doesn't just send out motor commands like move your arm.
Speaker 1: It also sends out copies of that motor command along
Speaker 1: other telegraph wires to let other parts of the brain
Speaker 1: know that the command was just sent out. So this
Speaker 1: is what's called an efference copy, and that has all
Speaker 1: kinds of effects on what happens next. For example, when
Speaker 1: you move your eyes around, your eyes are jumping about
Speaker 1: three times per second. The world seems to remain stable
Speaker 1: visually and This is because of the efference copy that
Speaker 1: tells the rest of your brain, okay, visual cortex, get ready.
Speaker 1: The whole world is about to streak past to the left.
Speaker 1: So your visual cortex, which is locked in darkness, isn't
Speaker 1: surprised when the eyes suddenly make a jump and the
Speaker 1: data is now all different. Now contrast that with what
Speaker 1: happens if you get a friend to gently push your
Speaker 1: eyeball from the outside. Now, the visual world appears to shift.
Speaker 1: In the first case, when you are moving your eyes voluntarily,
Speaker 1: the eference copy tells the brain, hey, a move is
Speaker 1: coming up, and that suppresses visual motion detection. But in
Speaker 1: the second case, when somebody pushes your eye, the absence
Speaker 1: of an effherence copy means, hey, that movement isn't mine,
Speaker 1: it's external, And so you perceive visual motion in the world.
Speaker 1: And I'll give you another example. What happens every time
Speaker 1: you blink your eyes. When you do that, for about
Speaker 1: a tenth of a second, the world goes dark. But
Speaker 1: you don't perceive that because you know it is coming.
Speaker 1: Your brain systems that send out the command to blink
Speaker 1: the eyelids also let the visual system know, hey, this
Speaker 1: is what's about to happen. This way, your visual cortex
Speaker 1: can anticipate that's about to happen, so the blink gets ignored. Now,
Speaker 1: if you don't believe me, maybe you think the blink
Speaker 1: is just too fast or something like that. Just sit
Speaker 1: in a room and have your friend flick the light
Speaker 1: switch really fast so that everything goes dark for a
Speaker 1: tenth of a second. You can't miss that. It's really
Speaker 1: obvious since it wasn't you that caused the darkness, you
Speaker 1: notice it. So, as we see with the ketchup bottle
Speaker 1: and eye movements and blinks, brains make predictions about the
Speaker 1: consequences of your own actions. And a great example of
Speaker 1: this is tickling. It turns out that if someone is
Speaker 1: coming after you and sticking their fingers under your underarms,
Speaker 1: it makes you laugh uncontrollably. It tickles. But I don't
Speaker 1: know if you've ever tried this. It turns out you're
Speaker 1: not able to tickle yourself. Why not, It's because of
Speaker 1: the simple fact that your own actions are predictable by
Speaker 1: your brain. You can't surprise your left underarm with your
Speaker 1: right hand because your brain is the one driving the
Speaker 1: fingers of the right hand, and it determines exactly when
Speaker 1: to move the fingers, and so there is zero surprise
Speaker 1: when the left underarm senses that for tickling, you require unpredictability.
Speaker 1: That's the whole trick to a tickle. When people study
Speaker 1: this with brain imaging fMRI, they find that when you
Speaker 1: try to tickle yourself, you get activity in the primary
Speaker 1: somatosensory cortex, meaning your brain is detecting that there's a
Speaker 1: feeling there. But the activity doesn't go further. It doesn't
Speaker 1: activate all these other downstream areas that come online when
Speaker 1: someone else is tickling you, like the secondary somatosensory cortex
Speaker 1: and the anterior singular cortex. Your brain sees the tickle
Speaker 1: coming and discounts it. In fact, other neuroimaging studies find
Speaker 1: that these brain areas that come online when you're getting tickled,
Speaker 1: these same areas become active when you are simply anticipating
Speaker 1: a tickle. When somebody's fingers are moving close, your somatis
Speaker 1: sensory areas start to go to town. Now it turns
Speaker 1: out there is one way that you can tickle yourself,
Speaker 1: and that is if you build a little device that
Speaker 1: inserts randomness so you can no longer predict the tickle.
Speaker 1: So imagine you set up a little machine where you
Speaker 1: are moving a lever around like a joystick, and that
Speaker 1: controls a feather that tickles your left underarm. But in
Speaker 1: between the movement of the lever and the movement of
Speaker 1: the feather, the computer injects random time delays. That way,
Speaker 1: your brain can't know when the movement in your under
Speaker 1: is going to occur. And now you rescue the tickle.
Speaker 1: With the help of a little bit of technology, you
Speaker 1: can tickle yourself. Importantly, it also turns out there is
Speaker 1: one group of people who are able to tickle themselves,
Speaker 1: and that is people who are suffering from schizophrenia. So
Speaker 1: in episode thirty three, I talked about my hypothesis that
Speaker 1: schizophrenia might be in part or in whole a disorder
Speaker 1: of time perception. So in this light, it's very instructive
Speaker 1: that people with schizophrenia can tickle themselves. This suggests that
Speaker 1: they're unable to predict their own actions and how those
Speaker 1: actions will lead to the next sensations. This inability to
Speaker 1: understand one's own actions, this is a general deficit that
Speaker 1: we see in schizophrenia. People will have a hard time
Speaker 1: distinguishing things they call from things they didn't cause. A
Speaker 1: person with schizophrenia will say something like, my hand picks
Speaker 1: up the paper clip, but I'm not the one controlling
Speaker 1: my hand. What my hand does has nothing to do
Speaker 1: with me. And of course you've heard of things like
Speaker 1: auditory hallucinations in schizophrenia. In that other episode, I talked
Speaker 1: about how we all have an internal dialogue. You generate
Speaker 1: a voice and you listen to it, and in schizophrenia,
Speaker 1: the timing seems to be slightly off such that the
Speaker 1: internal voice gets attributed to somebody else. Interestingly, my colleague
Speaker 1: Chris Frith and his collaborators ran a study with people
Speaker 1: who had schizophrenia, and they found that if a person
Speaker 1: has schizophrenia but does not have auditory hallucinations, then they
Speaker 1: are more ticklish when other people tickle them. But if
Speaker 1: a person with schizophrenia does have auditory hallucinations, then they
Speaker 1: can tickle them themselves. They judge no difference between someone
Speaker 1: else tickling them and them tickling themselves. They are no
Speaker 1: longer making the appropriate predictions. Okay, so this gives us
Speaker 1: a sense of how our brains, under normal circumstances work
Speaker 1: to constantly make predictions. And it's not just about predicting
Speaker 1: things about your own actions and sensations, but more generally
Speaker 1: about anything to do with the outside world. And the
Speaker 1: key is that our brains are not simply reactive, but
Speaker 1: they have these internal loops that are constantly making predictions
Speaker 1: about what comes next. And having this kind of architecture
Speaker 1: it allows brains to do not just stimulus response, but
Speaker 1: instead to make predictions ahead of actual sensory input. So
Speaker 1: think about trying to catch a baseball that someone is
Speaker 1: tossing to you. If your brain was just doing feed
Speaker 1: forward analysis of these signals, you couldn't catch the ball.
Speaker 1: There'd be a delay of hundreds of milliseconds from the
Speaker 1: time that the light strikes your eye until you could
Speaker 1: execute the motor command of putting your hand up, and
Speaker 1: your hand would always be reaching for a place where
Speaker 1: the ball used to be. We are able to catch
Speaker 1: baseballs because we have deeply hardwired internal models of physics,
Speaker 1: and these internal models generate expectations about when and where
Speaker 1: the ball is going to hit. It's making predictions about
Speaker 1: the future. Now, how does this sort of prediction play
Speaker 1: out in your daily life? Because it's not just about
Speaker 1: hitting catch a bottles and catching baseballs. But prediction applies
Speaker 1: to every decision you make about what you're going to do.
Speaker 1: Let's say you're trying to figure out what you need
Speaker 1: to do in an hour from now. You have a
Speaker 1: bunch of things on your to do list, but given
Speaker 1: the constraints of space and time, you can't do everything
Speaker 1: at once, and so life is a constant series of choices.
Speaker 1: So let's say you're looking at these choices. One you
Speaker 1: have to write a very long and specific email for
Speaker 1: your boss. Two you're thinking of going downtown to get
Speaker 1: a boba tee, or three you're considering going to the gym,
Speaker 1: which you've been promising yourself that you're going to do
Speaker 1: for some days now. So how does the choice actually
Speaker 1: get made in the brain. As far as our conscious
Speaker 1: minds go, we get very little access to the details.
Speaker 1: It just seems like, oh, okay, I've decided to do
Speaker 1: this instead of that, but you don't necessarily know why.
Speaker 1: But the last several decades of neuroscience have surfaced how
Speaker 1: this actually happenins We run the simulations and we feel them.
Speaker 1: So when you think about writing that email, your brain
Speaker 1: actually runs the little movie of you doing that, and
Speaker 1: possibly the ache that you might feel in your shoulder
Speaker 1: from typing too much, and also the satisfaction at finishing
Speaker 1: that task. Then your brain runs the simulation of going
Speaker 1: and getting the boba t how delicious that will be
Speaker 1: and how satisfying it'll be. And you also run the
Speaker 1: simulation of going to the gym. It's gonna be a
Speaker 1: little costly for you in terms of time, and it
Speaker 1: might make your muscles hurt, but boy, are you gonna
Speaker 1: feel great when you're done. You'll feel so satisfied. Now,
Speaker 1: what happens is your brain runs all these simulations and
Speaker 1: you feel the emotions with each one. Now again, this
Speaker 1: happens essentially entirely under the hood. For most of the
Speaker 1: decisions you make in life. You have no conscious access
Speaker 1: to how you made the final call, But your brain
Speaker 1: is simulating the possibilities, and you experience each one with
Speaker 1: your emotions and often with physical sensations. And this is
Speaker 1: how we weigh choices against one another. This is how
Speaker 1: we determine our paths in life. You feel the pain
Speaker 1: or the pleasure from your predicted futures. You think of
Speaker 1: yourself in future times, and you get to live out
Speaker 1: those little movies. Now like everything in our brains. We
Speaker 1: think this just automatically works, but in fact we have
Speaker 1: very particular networks that need to be in place and
Speaker 1: working well for this to function. And the reason we
Speaker 1: know this is because some people get damage to a
Speaker 1: part in the front of their brain, the venture medial
Speaker 1: prefrontal cortex, and they end up displaying a very strange
Speaker 1: and unexpected symptom, which is, if you give them some
Speaker 1: choice to make, like which restaurant do you want to
Speaker 1: go to tonight, they can articulate everything about the decision,
Speaker 1: but they can't decide. They can't land on a decision.
Speaker 1: So what's going on here? Well, patients like this have
Speaker 1: been studied by neurologists like Antonio Demacio and his colleagues,
Speaker 1: and what's happening is that their brain can run a
Speaker 1: quick future simulation, but it has become disconnected from the emotions.
Speaker 1: So the different future simulations all feel the same way.
Speaker 1: They all feel neutral, and therefore there's no way to
Speaker 1: distinguish any choice from any other. In other words, you
Speaker 1: need to feel the outcome of a simulation in order
Speaker 1: to do decision making. So it turns out that under
Speaker 1: normal circumstances, there's a core network of brain areas that
Speaker 1: are involved in prospect, which just means seeing ahead. So
Speaker 1: I want to give you a very quick sense of this.
Speaker 1: So you've got this area of your brain, the venture
Speaker 1: medial prefrontal cortex, which connects to areas involved in emotion
Speaker 1: like the anterior insula and the amignla, and it also
Speaker 1: connects to lots of other areas in the brain. And
Speaker 1: activity in this area essentially specifies the things that are
Speaker 1: pertinent to your current needs and goals, and this is
Speaker 1: what guides the construction of relevant scenarios. Now, there are
Speaker 1: a number of other brain areas that show up in
Speaker 1: this core network. One is called the precuneus, and this
Speaker 1: maps the locations of things in space, so its involvement
Speaker 1: contributes to a spatial context for imagine scenarios and the
Speaker 1: features inside of that. There's another area called the temporopridal junction,
Speaker 1: and you see that area become active during the detection
Speaker 1: of targets or events around you that are relevant to
Speaker 1: what you're trying to do at this moment. This area
Speaker 1: seems to run and do the same thing even in
Speaker 1: your imagined scenarios. And then you've got an area called
Speaker 1: the superior temporal sulcus, which is involved with lots of things,
Speaker 1: but one of them is about interpreting social cues. So
Speaker 1: one idea is that this area helps to specify other
Speaker 1: individuals in their actions within imagined scenes. And then you
Speaker 1: have the hippocampus. And one thing that's known is that
Speaker 1: when you get damage to the hippocampus, that seems to
Speaker 1: mess up all of the spatial coherence of a recalled
Speaker 1: or imagined scene. So patients with hippocampal damage they can't
Speaker 1: picture a specific place or detailed surrounding events. Here's one
Speaker 1: way to think about this.
Speaker 2: When you move in a virtual reality world, the goggles
Speaker 2: keep track of where you are and all the objects
Speaker 2: and how things change when you move.
Speaker 1: And this is similar to what's going on in the brain.
Speaker 1: You have special cells in the hippocampus called place cells,
Speaker 1: which help to translate everything into a framework where you
Speaker 1: are at the center of it. And the idea is
Speaker 1: that these cells are critical to your imagination of scenes.
Speaker 1: So as you virtually move through your imagined scene, the
Speaker 1: hippocampal play cells keep the scene coherent and consistent, just
Speaker 1: like the VR goggles would. So this all suggests that
Speaker 1: the hippocampus is crucial for tying together the activity of
Speaker 1: other brain areas to construct this rich and coherent imaginary experience.
Speaker 1: You have this brainwide network of areas that are involved
Speaker 1: when you are imagining future scenarios, and all of this
Speaker 1: is what helps you to experience the movie and to
Speaker 1: feel the emotions. If you are just a robot who
Speaker 1: rolled into a room, you would just sit there because
Speaker 1: you wouldn't have any particular reason to prioritize writing the
Speaker 1: email versus getting the Boba tee versus going to the gym.
Speaker 1: You would have no way to weigh these against one another.
Speaker 1: But we assign feeling to all of our future scenarios.
Speaker 1: So the brain makes predictions. But how does it know
Speaker 1: how to improve these through time. Well, imagine a fire
Speaker 1: department in a city, and every time a fire occurs
Speaker 1: in the city, they go wailing out of the station
Speaker 1: to take care of it, and they suspect that a
Speaker 1: lot of the fires are going to happen around the
Speaker 1: warehouse district, so they put their trucks there so they
Speaker 1: can take care of things quickly. But eventually they realize
Speaker 1: that their prediction was wrong. It's actually another part of
Speaker 1: the city that keeps catching fire. So the area at
Speaker 1: the foot of the mountains where the trees are dense
Speaker 1: and interwoven with power lines, So the fire department starts
Speaker 1: putting their resources there where they need to be in advance,
Speaker 1: and that reduces the energy they need to expend every
Speaker 1: time there's a new fire because they're no longer being
Speaker 1: reactive to fires at the foot of the mountain, but
Speaker 1: now they're making good predictions about it. So cities do
Speaker 1: this kind of thing, by the way, in terms of fires,
Speaker 1: in terms of where they expect crime is going to occur,
Speaker 1: in terms of where and when the power usage is
Speaker 1: going to happen. Everything. So the key about this example
Speaker 1: is that the fire department's first predictions weren't so great,
Speaker 1: and the data tells them, oh, that could be a
Speaker 1: lot better. It tells them that something could be adjusted.
Speaker 1: And that is the same thing that happens in the
Speaker 1: brain all the time. The brain tries to predict everything,
Speaker 1: and it pays attention to what's called the prediction error,
Speaker 1: which means the difference between what it thought would happen
Speaker 1: and what actually happened. And you see various cells in
Speaker 1: the brain, for example, in the dopamine system that are
Speaker 1: responding not to the reward or punishment, but the prediction error.
Speaker 1: In other words, how different the reward or punishment was
Speaker 1: from what was expected. And these dopamine systems broadcast their
Speaker 1: signals all across the territory of the brain to announce
Speaker 1: that the prediction wasn't quite right, there was a prediction error,
Speaker 1: and therefore something needs to be adjusted. So our brain
Speaker 1: has the architecture to make predictions and adjust them all
Speaker 1: the time. And what is all this architecture of the
Speaker 1: brain tell us. It tells us that the brain craves predictability.
Speaker 1: Now why does it care about predictability? Well, first of
Speaker 1: all because of energy efficiency. Because if you can predict
Speaker 1: that something is going to happen, then you don't have
Speaker 1: to burn up all this neural energy on it. You
Speaker 1: already know it's coming. But if something is a surprise,
Speaker 1: the brain turns its vast attentional mechanisms to it and
Speaker 1: has to burn a lot of calories on understanding what
Speaker 1: the heck just happened and eventually reshaping the internal model
Speaker 1: to account for that. In the future, all of this
Speaker 1: would be fine. Maybe if we could plug ourselves into
Speaker 1: a wall, but instead we are mobile creatures who run
Speaker 1: on batteries. We have to constantly find food sources and
Speaker 1: stick them in our mouth so that we can have
Speaker 1: enough energy to get to the next food source. So
Speaker 1: mother nature evolved us to be highly efficient creatures. And
Speaker 1: what we do is we make ourselves massively efficient by
Speaker 1: predicting away the future. And this is, by the way,
Speaker 1: why the method of torture referred to as the Chinese
Speaker 1: water torture is so aversive to us. The idea is
Speaker 1: that a drop of cold water drips onto your head,
Speaker 1: and then let's say five seconds later, the next draw hits,
Speaker 1: and then the next one three seconds later, and then
Speaker 1: the next drop eight seconds slater, and the next one
Speaker 1: six seconds slater, and then four seconds and suddenly one second,
Speaker 1: and you get the idea. It's unpredictable. Your brain is
Speaker 1: constantly trying to say when an event is going to happen,
Speaker 1: and it's constantly having to pay attention here because it
Speaker 1: can't make a good prediction. And perhaps you've never experienced
Speaker 1: that form of torture explicitly that most of us have
Speaker 1: at some point in our lives, had a leaky faucet
Speaker 1: at our house, and this can often be just as
Speaker 1: bad if it never falls into a rhythm, it goes drip, drip, drip.
Speaker 1: We love rhythm because we can predict it away, and
Speaker 1: anything that is unpredictable continues to demand all our attention. Now,
Speaker 1: I'll just mention that my colleagues and I have proposed
Speaker 1: in various places that maybe the brain activity that we see,
Speaker 1: the spikes and neurons, these represent just the part of
Speaker 1: the world that is unpredicted. In other words, silence is golden,
Speaker 1: and the brain spends most of its efforts trying to
Speaker 1: make perfect predictions of the world and burn that down
Speaker 1: into the circuitry of the brain so it doesn't have
Speaker 1: to use any activity. Now, of course, of course, the
Speaker 1: world is way too complicated to ever reach perfect prediction.
Speaker 1: Everything changes all the time, and so the speculation is
Speaker 1: that the activity that we can measure in the brain,
Speaker 1: whether that's with electrodes or fMRI or whatever, really that
Speaker 1: activity just represents the surprise, the thing that the brain
Speaker 1: didn't see coming. In other words, if you show a
Speaker 1: yellow ball to a monkey and you find cells in
Speaker 1: his brain, say in the visual cortex that respond vigorously
Speaker 1: to that visual thing, then we say those cells prefer
Speaker 1: yellow balls, or more colloquially, we say it likes the
Speaker 1: yellow ball. But could it just be that the appearance
Speaker 1: of a yellow ball was unpredicted by the system and
Speaker 1: the cells activity is merely a reflection of that. This
Speaker 1: is consistent with the fact that if you hide the
Speaker 1: ball and then reshow it to the monkey five seconds later,
Speaker 1: and then you do that again and again, the response diminishes.
Speaker 1: This is known as repetition suppression, and it's not merely
Speaker 1: about fatigue of the cell. Instead, it's the fact that
Speaker 1: the monkey's brain knows that you're about to show the
Speaker 1: stupid ball again, and so it has a prediction of
Speaker 1: what is coming. And when it knows what is coming,
Speaker 1: it doesn't have to burn any energy. We'll come back
Speaker 1: to this in terms of our deep desired to have
Speaker 1: predictions about our lives in just a few moments. But
Speaker 1: first I want to ask can species other than human
Speaker 1: beings engage in prospection and imagination? This question is difficult
Speaker 1: to answer because animals can't verbally report their experiences to us.
Speaker 1: Some researchers think, well, maybe animals lack the capacity for
Speaker 1: this sort of thing, but in fact they do share
Speaker 1: much of the same circuitry that we've been talking about,
Speaker 1: and careful observation their behavior suggests that they have some
Speaker 1: features of episodic memory and prospection. For example, look at
Speaker 1: the scrubjay, which is a bird that stores food away.
Speaker 1: It can recall not just where it hit a particular item,
Speaker 1: but also what that item was and when it was stored. Now,
Speaker 1: skeptics say, okay, look, maybe this is just procedural memory.
Speaker 1: It's like a basic algorithm that's running. It's not conscious,
Speaker 1: and it's just driven by the needs of the moment.
Speaker 1: But the scrub jays also appear to cash food in
Speaker 1: a way that reflects anticipated future needs. It's not just
Speaker 1: their current motivational state. And when you look at rats,
Speaker 1: when people do direct recordings of the hippocampus, that suggests
Speaker 1: that they too might engage in prospection and recollection. So
Speaker 1: as a rat move through adjacent places, you have these
Speaker 1: hippocampal play cells that fire off in sequences, and these
Speaker 1: play cells sometimes replay the activity sequence when the rat
Speaker 1: is not moving, sometimes even when the rat is sleeping
Speaker 1: after the experiment is over, and these cells can also
Speaker 1: pre play a sequence of activity before the rat has
Speaker 1: started to move along the route. So, for example, if
Speaker 1: the rat has to go down a hallway and then
Speaker 1: turn right or left, this is called a te maze,
Speaker 1: and it's trying to decide which path to take. You
Speaker 1: can see these play cells pre play one route and
Speaker 1: then the other, as if in consideration of both these scenarios. Now,
Speaker 1: this research is still early, but these kinds of findings
Speaker 1: might increasingly point us in the direction of at least
Speaker 1: roughly gauging whether our animal cuts and have internal experiences
Speaker 1: of time travel the way that we do. So what
Speaker 1: I've told you so far is how the brain predicts.
Speaker 1: But how does it know how to do this? How
Speaker 1: does it make good predictions about the world. So suppose
Speaker 1: you're hungry and you decide you're going to get something
Speaker 1: to eat. Where should you go? You need to have
Speaker 1: a map in your head of all the nearby choices.
Speaker 1: Then you have to decide which one would most likely
Speaker 1: satisfy your current craving. And so to plan your excursion
Speaker 1: you need to go through your past experiences of meals
Speaker 1: and the places on your map. So you've got that
Speaker 1: inexpensive tie restaurant which is the closest, but the food
Speaker 1: there you remember, was too spicy for your taste. And
Speaker 1: the food truck over there they make great burritos, but
Speaker 1: it always has a really long line in your past experience.
Speaker 1: And the fast food joint over here has fries that
Speaker 1: are a little greasy, but you'd rather take the grease
Speaker 1: than the spice or the long lines. So, putting together
Speaker 1: the experiences of your recalled past and your imagined future,
Speaker 1: you decide on your option. But the past and the
Speaker 1: future are intertwined in most of our decisions. In other words,
Speaker 1: the thing that allows the brain to construct possible futures
Speaker 1: is memory. Memory is what allows us to write down
Speaker 1: information and then use that as building blocks to build
Speaker 1: out our future scenarios. Now, interestingly, that's not even a
Speaker 1: new idea. Aristotle suspected this, as did Galen and all
Speaker 1: their medieval commentators. They all emphasized memory as the key
Speaker 1: tool in making successful predictions for the future. And in fact,
Speaker 1: something that I find very interesting, presumably coincidental but maybe not,
Speaker 1: is that in Greek mythology, the goddess of memory, Nemazine,
Speaker 1: is the mother of the nine muses, who are the
Speaker 1: goddesses who spark the imagination. In other words, memory is
Speaker 1: the mother of imagination. Now, my friend and colleague Jeff
Speaker 1: Hawkins made the argument that what we call intelligence boils
Speaker 1: down to the brain's ability to make good predictions about
Speaker 1: the world based on stored memories. In his version of
Speaker 1: the memory prediction paradigm, the cortex is a pattern recognition
Speaker 1: machine that breaks complicated events into smaller bunks. It stores
Speaker 1: experiences in a way that reflects the structure of the world,
Speaker 1: and then it's springboards off these known experiences to make predictions.
Speaker 1: As Hawkins puts it, intelligence is the capacity of the
Speaker 1: brain to predict the future by analogy to the past. Now, fascinatingly,
Speaker 1: in two thousand and seven, Demisesabis and his colleagues at
Speaker 1: London's Institute of Neurology made this really striking observation that
Speaker 1: patience who had damage to their hippocampus not only had
Speaker 1: amnesia for past experiences, but also couldn't imagine new ones.
Speaker 1: So if you ask a patient with this brain damage
Speaker 1: to remember his past, he can't do that, and we
Speaker 1: expected that. But now you ask him to imagine the future,
Speaker 1: and he just can't do it. You ask him to
Speaker 1: imagine standing in a museum full of exhibits and he'll
Speaker 1: say something like there's not a lot coming, I'm not
Speaker 1: picturing anything. Or you might say, hey, look, imagine going
Speaker 1: on a vacation to the beach. Really picture yourself lying
Speaker 1: there on the beach, and describe the scene to me.
Speaker 1: And the person might be able to say, well, there's
Speaker 1: a blue sky, or maybe they describe an isolated sound,
Speaker 1: but that's it. Otherwise they just draw a blank. And
Speaker 1: by the way, if you provide the person with pictures
Speaker 1: and sounds and smells to help them along, that doesn't
Speaker 1: help them to imagine the scene. So unlike a healthy control,
Speaker 1: the patient with hippocampal damage just can't simulate any vivid details.
Speaker 1: It's not like an episode to them the way that
Speaker 1: your imagination is. Their descriptions, if they exist at all,
Speaker 1: are very unspecific. So the healthy control can describe a
Speaker 1: spatial layout and people being present, and descriptions of the
Speaker 1: smells and sights and sounds, thoughts and emotions they might have,
Speaker 1: and actions they might take. But the patient with the
Speaker 1: hippocampal damage can't do any of that. At best. What
Speaker 1: they're able to come up with has a lack of
Speaker 1: spatial coherence. The imagined experience is just a collection of
Speaker 1: fragmentary sensations instead of a unified episode. In a particular setting,
Speaker 1: you can ask them what they'll see if they go
Speaker 1: over to a shopping mall, or what they might want
Speaker 1: to eat if they go to a restaurant, and they
Speaker 1: just draw a blank. They can only put together a
Speaker 1: few details that are not well connected. So the deficits
Speaker 1: in their memories apply to their simulations of the future
Speaker 1: as well. Now, how do we understand this in terms
Speaker 1: of the circuitry. Well, the key came from brain imaging
Speaker 1: studies in the past two decades, which have uncovered that
Speaker 1: there's a network of regions involved both for remembering the
Speaker 1: past and imagining new ones. It's the same areas, so
Speaker 1: the hippocampus and its surrounding area. That's one part of this,
Speaker 1: but we also find several other areas like the medial,
Speaker 1: prial cortex and prefront areas, and the lateral, temporal and
Speaker 1: lateral pride lobes. All these regions are important for elaborating
Speaker 1: on the details of imagined and also for remembered episodes. So,
Speaker 1: in other words, the brain's episodic memory systems, which we
Speaker 1: discussed in the last episode, are just as important for
Speaker 1: imagining future experiences. In other words, this core network underlies
Speaker 1: mental time travel in either direction. So this leads to
Speaker 1: a really interesting thought about something, which is that if
Speaker 1: recall of the past and simulation of the future both
Speaker 1: use the same network, then maybe what we mean by
Speaker 1: memory is something more like simulation. So I want to
Speaker 1: propose this hypothesis that memories are not the fundamental thing,
Speaker 1: but instead simulation is the fundamental thing, and memories are
Speaker 1: just a special type of simulation. A memory is merely
Speaker 1: a simulation that's pinned down to always flow a particular way.
Speaker 1: And if this is the right way to look at it,
Speaker 1: maybe what we call remembrance we will someday call resimulation.
Speaker 1: So instead of dividing the territory into memory and prediction,
Speaker 1: they may in fact be one thing. Any context is
Speaker 1: run through a simulation to predict the outcome. So brains
Speaker 1: simulate possible futures, and we constantly function by making predictions
Speaker 1: about everything in our lives and our communities and our
Speaker 1: nation and the world. But I want to be clear
Speaker 1: that even though we use the word prediction, there's no
Speaker 1: guarantee of accuracy. We are actually pretty bad at capturing
Speaker 1: the future. As the baseball catcher Yogi Bearra said, it's
Speaker 1: tough to make predictions, especially about the future. Why is
Speaker 1: it tough. It's because we only simulate based on our
Speaker 1: experience in the world. So if you've never seen something before,
Speaker 1: you're going to have a pretty bad prediction about it.
Speaker 1: For example, futurists make all kinds of predictions about the
Speaker 1: next decade or two, and most of them turn out
Speaker 1: to be wrong. In one study of famous forecasters, it
Speaker 1: was found that their predictions were between ten to fifty
Speaker 1: percent accuracy, which certainly isn't that great. But it's not
Speaker 1: just futurists. It's all of us, with most of our
Speaker 1: predictions about our lives, and by the way, our inability
Speaker 1: to see the future, well, this is why we have
Speaker 1: the existence of magicians or mystery writers or scam artists.
Speaker 1: These are people who take advantage of the fact that
Speaker 1: our ability to predict the future is not very good.
Speaker 1: The magician knows that we're going to predict the location
Speaker 1: of the object incorrectly and then will be surprised. The
Speaker 1: mystery novelist knows that he can lead us down a
Speaker 1: garden path and that we will extrapolate incorrectly in the
Speaker 1: direction that he wants us to, so we don't correctly
Speaker 1: see what's going to happen. The scam artist does the
Speaker 1: same thing, but in real life, getting our brains to
Speaker 1: see a vision of success that doesn't actually match with
Speaker 1: what's going to happen. Now, I'll just note something here,
Speaker 1: which is that's sometimes our inability to make good predictions
Speaker 1: that helps us. So take the origin of the Oxford
Speaker 1: English Dictionary, where a professor who loved words said, you
Speaker 1: know what, I'm going to write down a definition for
Speaker 1: every word there is. This can't take very long, especially
Speaker 1: if I recruit help from others, which he did. But
Speaker 1: despite an insane amount of work, the Oxford English Dictionary
Speaker 1: finally got finished eighty years after his death. He would
Speaker 1: have never started it had he been a good predictor.
Speaker 1: So there's something useful about our optimism bias in the
Speaker 1: form of our bad predictions. Now, we've all experienced this
Speaker 1: kind of bad prediction on smaller levels, where we assume
Speaker 1: that some task is going to take us less time
Speaker 1: than it actually does. We also experience this on the
Speaker 1: level of most of our life trajectories, where we think,
Speaker 1: all right, I generally know where my life is going,
Speaker 1: but if you look back at any decade of your life,
Speaker 1: you'll realize that your predictions generally weren't so good. Why
Speaker 1: it's because the only way we can make predictions is
Speaker 1: by leveraging our memories what has all ready happen to us.
Speaker 1: The memories serve as building blocks, and all we're able
Speaker 1: to do is use those building blocks to make versions
Speaker 1: of the future, which is really just an edifice constructed
Speaker 1: of the bricks that we've seen before. And that's why
Speaker 1: we are so inherently limited in seeing what's coming. And
Speaker 1: there's a very specific way that we're terrible at predicting
Speaker 1: the future. We generally assume the future will just be
Speaker 1: a straightforward extension of the present in our lives. We
Speaker 1: assume that we have changed up to this point, but
Speaker 1: we're going to remain about like this from here on out.
Speaker 1: For example, when people think back to their childhoods, they
Speaker 1: see lots of change in their own bodies and personalities
Speaker 1: and beliefs, and also in the technology that surrounds them.
Speaker 1: But when people are asked to think about the future,
Speaker 1: they generally assume everything is going to be roughly this
Speaker 1: same as it is now. Maybe you'll have a little
Speaker 1: more gray hair, maybe your electric car will have a
Speaker 1: longer range, but that's about it. We feel like we've
Speaker 1: arrived after a steep path and now the world will
Speaker 1: mostly stay fixed as it is. So we think things
Speaker 1: are going to stay as they are. And nowhere is
Speaker 1: this more true than with our predictions about technology. The
Speaker 1: fact is, the world is changing faster than ever as
Speaker 1: a result of the law of accelerating returns, which simply
Speaker 1: says that the more technology advances, the faster the next
Speaker 1: generation of technology is going to advance. And we find
Speaker 1: ourselves now at the cusp of such fundamental revolutions, not
Speaker 1: only artificial intelligence, but also nanotech and biotech and quantum
Speaker 1: computing and room temperature superconductivity and energy storage and genetic
Speaker 1: engineering and on and on. All of these things going
Speaker 1: to weave together in ways that we can't currently imagine.
Speaker 1: And we are standing on an exponential curve that's about
Speaker 1: to rise at a steeper slope than we've ever seen,
Speaker 1: but we can't see it clearly coming. Why again, it's
Speaker 1: because we rely on our memories to paint our vision
Speaker 1: of the future, so our predictions are limited to remixes
Speaker 1: of our past, which makes it really difficult to anticipate
Speaker 1: the significant disruptions heading our way. And there's one other
Speaker 1: issue here for our lives, because we're always trying to
Speaker 1: make good predictions and therefore save brain energy. We really
Speaker 1: hate change. I mentioned before how we don't like the
Speaker 1: dripping faucet because it's unpredictable, But this hatred of the
Speaker 1: unpredictable applies to everything, including being told that things will
Speaker 1: change in the future, like climate change. Climate change makes
Speaker 1: people very anxious because you look at a map of
Speaker 1: the world and you see that over the next x
Speaker 1: number of decades people will be shifting around as temperatures increase.
Speaker 1: And we hate that because fundamentally we feel most comfortable
Speaker 1: if things stay exactly the way they are. Like you
Speaker 1: want to imagine that your house, which is exactly two
Speaker 1: hundred and fifty seven feet from the shore of the ocean,
Speaker 1: will remain precisely where it is centuries from now, But
Speaker 1: of course it won't, even if you put aside everything
Speaker 1: about man made pollution. The shorelines always change. Where I
Speaker 1: live in California, the beach used to extend miles farther out.
Speaker 1: I'm talking about fourteen thousand years ago, and when the
Speaker 1: ice Age ended and the glaciers melted, the sea level
Speaker 1: rose and ate up all of that beach. And that's
Speaker 1: why we don't find coastal settlements from the first people
Speaker 1: from Asia who came across cross the bearing Land Bridge
Speaker 1: and settled here fourteen thousand years ago. Things were totally
Speaker 1: different at that time. For example, there was no San
Speaker 1: Francisco Bay. There was no water there that was all
Speaker 1: locked up in glaciers. When any of us who live
Speaker 1: here look at the San Francisco Bay, we imagine it's permanent,
Speaker 1: but of course it's not. If you were one of
Speaker 1: the first settlers in North America, the place would have
Speaker 1: looked very different to you. You could have walked across
Speaker 1: from what is now the city of San Francisco over
Speaker 1: to Alcatraz without getting a single drop of water on
Speaker 1: your feet. It's easy to study geography retrospectively and say, wow,
Speaker 1: that's interesting. But when we look in the forward direction,
Speaker 1: we get very anxious at the thought that populations of
Speaker 1: people will move around and borders will change. Now that's
Speaker 1: not to minimize what's happening with climate change, but it
Speaker 1: is to say that change has always happened. I mean,
Speaker 1: the last little ice Age just ended in eighteen fifty,
Speaker 1: where for five hundred years it was two degrees colder
Speaker 1: in Europe and mountain glaciers expanded and people had to
Speaker 1: move around. The only issue I'm pointing to here is
Speaker 1: that even though the world has always changed, we want
Speaker 1: it to stay stable now. We fundamentally want to imagine
Speaker 1: the future of the world looking exactly as we know
Speaker 1: it now. And you can see this as easily at
Speaker 1: small scales as you do on the large scales. For example,
Speaker 1: in this past month, there have been a new round
Speaker 1: of company layoffs in Silicon Valley, and this makes people
Speaker 1: so nervous and anxious. Now, most people who have lost
Speaker 1: a job end up saying later that they're happy because
Speaker 1: it opens up new opportunities for them and exposes them
Speaker 1: to things they didn't even know. They didn't know and
Speaker 1: they realized there was more out there to be experienced
Speaker 1: in the world. And yet the change itself proves very
Speaker 1: hard for people in the moment. It's as though their
Speaker 1: brains are screaming out for everything to stay exactly the
Speaker 1: same as it was. Why, Because we are creatures who
Speaker 1: try to predict Our brains are designed to do that
Speaker 1: to save energy, and the most anxiety producing thing for
Speaker 1: the accuracy of our predictions is when the world itself
Speaker 1: changes out from under you. As an example, I've been
Speaker 1: on the boards of many organizations. When somebody resigns and
Speaker 1: so much trauma for the board, there's a long discussion
Speaker 1: about how to keep the organization together. Everybody's feelings are bubbling,
Speaker 1: and then the conversation eventually turns to how this presents
Speaker 1: a real opportunity for us to mix things up, to
Speaker 1: inject new blood, to do things in a way that's
Speaker 1: no longer stale. It's fascinating to watch the conversation always
Speaker 1: follow the same trajectory, as though everyone is reading from
Speaker 1: a script. It reminds me of a notion from The
Speaker 1: Simpsons where Homer is anxious about something and Lisa, his daughter, says,
Speaker 1: look on the bright side, Dad, Did you know that
Speaker 1: the Chinese use the same word for crisis as they
Speaker 1: do for opportunity, and Homer says, yes, chrisis as tunity.
Speaker 1: The point is that change of any sort presents a
Speaker 1: crisis to the predictive systems of the brain, but it
Speaker 1: is eventually seen as an opportunity. The bottom line is
Speaker 1: that we get used to the world and we don't
Speaker 1: want things to change. So, given that our predictive ability
Speaker 1: is not so great and that we don't want things
Speaker 1: to change, how did we ever become so successful as
Speaker 1: a species. Well, the first answer is science. When it
Speaker 1: comes to predicting big issues in the real world, our
Speaker 1: intuitions just aren't up for the task. Our brains always
Speaker 1: make predictions, but human brains are small and they're not
Speaker 1: nearly as good as groups of brains working together, and
Speaker 1: the scientific method simply gives us away a set of
Speaker 1: rules for working together to find the most accurate predictions. Fundamentally,
Speaker 1: that's all science is figuring out the rules so we
Speaker 1: can best predict the future. But I want to highlight
Speaker 1: what I propose is a second reason that humans got
Speaker 1: really good at predicting the future, and this is perhaps
Speaker 1: a more surprising reason why our species has become a
Speaker 1: runaway species, and that reason is storytelling. So literature like stories, novels,
Speaker 1: and movies. This is critically important for the success of
Speaker 1: our species because we can take one person's imagined stories
Speaker 1: something they've worked out all the pieces and parts of
Speaker 1: over a long time, and that author can make that
Speaker 1: scenario real for us, He can reify it. So stories
Speaker 1: allow us to experience possible futures. Just think, for example,
Speaker 1: of the nineteen eighties movie The Day After. It was
Speaker 1: about nuclear war and what it is to wake up
Speaker 1: the day after America has been turned to rubble by
Speaker 1: nuclear bombs. It took something that required an unusually rich
Speaker 1: imagination and it allowed us to see it, to experience
Speaker 1: a situation that otherwise would have remained purely conceptual. And
Speaker 1: this is why stories are so important. They allow us
Speaker 1: to live in worlds that we otherwise would not, and
Speaker 1: then that gives us new memories that we can use
Speaker 1: as new building blocks to see a little farther out
Speaker 1: than we would have otherwise. In this sense, literature allows
Speaker 1: us to get out of our heads and share the
Speaker 1: creative headspace of someone else who has thought down a
Speaker 1: particular path, probably in great detail, and then we get
Speaker 1: to enjoy that person's guidance. And the key, as far
Speaker 1: as we can tell, is that other species, for example,
Speaker 1: hippopotamuses don't tell stories around the campfire. And it's not
Speaker 1: just hippopotamuses, but every other one of the millions of
Speaker 1: species of animals on this earth. We have no evidence
Speaker 1: that any of them tells stories. So the way I
Speaker 1: think about this is that they just have a lot
Speaker 1: less practice expanding beyond their own limited experience of the world.
Speaker 1: But we spend a ton of our time imagining what's
Speaker 1: not there. We are mental time travelers, and we use
Speaker 1: other people's stories and books to get there. The class
Speaker 1: that I'm teaching at Stanford this quarter is Literature and
Speaker 1: the Brain. What I find so extraordinary about the active
Speaker 1: reading is that we use a string of symbols to
Speaker 1: fire up this whole imagination engine and to have us
Speaker 1: live through scenarios. And I propose that we have come
Speaker 1: to beat out every animal species on the planet, including
Speaker 1: lions and tigers and bears, all of whom could tear
Speaker 1: us to shreds easily. We have beat them out because
Speaker 1: of stories. We have these fierce animals in our zoos
Speaker 1: in every city, and they have no humans in their zoos.
Speaker 1: It's not just about guns and spears, it's about planning.
Speaker 1: We can capture them because we can outthink them. So
Speaker 1: I posed at the beginning of the episode a question,
Speaker 1: what would I advise the president if we found ourselves
Speaker 1: at war with extraterrestrials. Well, here's what If we land
Speaker 1: on a planet with fierce bug like creatures, we shouldn't
Speaker 1: worry too much about their capacity to be anything but reactive.
Speaker 1: We will probably be able to trick them, to outflank them,
Speaker 1: to outthink them. But if we discover that these creatures
Speaker 1: also have life libraries, we should quietly turn around and
Speaker 1: sneak away, because it means they have exposed themselves to
Speaker 1: thousands of other worlds beyond what they could otherwise experience,
Speaker 1: and that cognitive practice makes them potentially a very wily opponent.
Speaker 1: The degree to which an alien species has literature will
Speaker 1: tell us how good they are at predicting possible futures
Speaker 1: and developing rich scenarios of what ifs. It allows them
Speaker 1: to expand their experiences far beyond a single head. So
Speaker 1: let's wrap up what we saw today is that brains
Speaker 1: simulate possible futures, and brains do this by relying on
Speaker 1: the lessons of the past. This makes your memory the
Speaker 1: mother of your imagination, just like the goddess of memory
Speaker 1: gave birth to the muses. Now, in the last two episodes,
Speaker 1: we've talked about running simulations in the backward direction, which
Speaker 1: we call memory, and running them in the forward direction,
Speaker 1: which is how we envision possible futures. But everything I've
Speaker 1: told you so far is just a setup, because that
Speaker 1: is just the beginning. Come back next week to see
Speaker 1: how now we can leverage this concept of time travel
Speaker 1: to deeply understand why our mental lives are as nuanced
Speaker 1: and colorful and complex as they are simulating. Next week,
Speaker 1: I'm David Eagleman, and this is Inner Cosmos. In the meantime,
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: podcasts at eagleman dot com with questions or discussion, and
Speaker 1: I'll be making episodes in which I address those until
Speaker 1: next time. Thank you for joining me in the outermost
Speaker 1: reaches of the Inner Cosmos