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  • Translator: Joseph Geni Reviewer: Thu-Huong Ha

  • I'm going to talk about the strategizing brain.

  • We're going to use an unusual combination of tools

  • from game theory and neuroscience

  • to understand how people interact socially when value is on the line.

  • So game theory is a branch of, originally, applied mathematics,

  • used mostly in economics and political science, a little bit in biology,

  • that gives us a mathematical taxonomy of social life

  • and it predicts what people are likely to do

  • and believe others will do

  • in cases where everyone's actions affect everyone else.

  • That's a lot of things: competition, cooperation, bargaining,

  • games like hide-and-seek, and poker.

  • Here's a simple game to get us started.

  • Everyone chooses a number from zero to 100,

  • we're going to compute the average of those numbers,

  • and whoever's closest to two-thirds of the average wins a fixed prize.

  • So you want to be a little bit below the average number,

  • but not too far below, and everyone else wants to be

  • a little bit below the average number as well.

  • Think about what you might pick.

  • As you're thinking, this is a toy model of something like

  • selling in the stock market during a rising market. Right?

  • You don't want to sell too early, because you miss out on profits,

  • but you don't want to wait too late

  • to when everyone else sells, triggering a crash.

  • You want to be a little bit ahead of the competition, but not too far ahead.

  • Okay, here's two theories about how people might think about this,

  • and then we'll see some data.

  • Some of these will sound familiar because you probably are

  • thinking that way. I'm using my brain theory to see.

  • A lot of people say, "I really don't know what people are going to pick,

  • so I think the average will be 50."

  • They're not being really strategic at all.

  • "And I'll pick two-thirds of 50. That's 33." That's a start.

  • Other people who are a little more sophisticated,

  • using more working memory,

  • say, "I think people will pick 33 because they're going to pick a response to 50,

  • and so I'll pick 22, which is two-thirds of 33."

  • They're doing one extra step of thinking, two steps.

  • That's better. And of course, in principle,

  • you could do three, four or more,

  • but it starts to get very difficult.

  • Just like in language and other domains, we know that it's hard for people to parse

  • very complex sentences with a kind of recursive structure.

  • This is called a cognitive hierarchy theory, by the way.

  • It's something that I've worked on and a few other people,

  • and it indicates a kind of hierarchy along with

  • some assumptions about how many people stop at different steps

  • and how the steps of thinking are affected

  • by lots of interesting variables and variant people, as we'll see in a minute.

  • A very different theory, a much more popular one, and an older one,

  • due largely to John Nash of "A Beautiful Mind" fame,

  • is what's called equilibrium analysis.

  • So if you've ever taken a game theory course at any level,

  • you will have learned a little bit about this.

  • An equilibrium is a mathematical state in which everybody

  • has figured out exactly what everyone else will do.

  • It is a very useful concept, but behaviorally,

  • it may not exactly explain what people do

  • the first time they play these types of economic games

  • or in situations in the outside world.

  • In this case, the equilibrium makes a very bold prediction,

  • which is everyone wants to be below everyone else,

  • therefore they'll play zero.

  • Let's see what happens. This experiment's been done many, many times.

  • Some of the earliest ones were done in the '90s

  • by me and Rosemarie Nagel and others.

  • This is a beautiful data set of 9,000 people who wrote in

  • to three newspapers and magazines that had a contest.

  • The contest said, send in your numbers

  • and whoever is close to two-thirds of the average will win a big prize.

  • And as you can see, there's so much data here, you can see the spikes very visibly.

  • There's a spike at 33. Those are people doing one step.

  • There is another spike visible at 22.

  • And notice, by the way, that most people pick numbers right around there.

  • They don't necessarily pick exactly 33 and 22.

  • There's something a little bit noisy around it.

  • But you can see those spikes, and they're there.

  • There's another group of people who seem to have

  • a firm grip on equilibrium analysis,

  • because they're picking zero or one.

  • But they lose, right?

  • Because picking a number that low is actually a bad choice

  • if other people aren't doing equilibrium analysis as well.

  • So they're smart, but poor.

  • (Laughter)

  • Where are these things happening in the brain?

  • One study by Coricelli and Nagel gives a really sharp, interesting answer.

  • So they had people play this game

  • while they were being scanned in an fMRI,

  • and two conditions: in some trials,

  • they're told you're playing another person

  • who's playing right now and we're going to match up

  • your behavior at the end and pay you if you win.

  • In the other trials, they're told, you're playing a computer.

  • They're just choosing randomly.

  • So what you see here is a subtraction

  • of areas in which there's more brain activity

  • when you're playing people compared to playing the computer.

  • And you see activity in some regions we've seen today,

  • medial prefrontal cortex, dorsomedial, however, up here,

  • ventromedial prefrontal cortex,

  • anterior cingulate, an area that's involved

  • in lots of types of conflict resolution, like if you're playing "Simon Says,"

  • and also the right and left temporoparietal junction.

  • And these are all areas which are fairly reliably known

  • to be part of what's called a "theory of mind" circuit,

  • or "mentalizing circuit."

  • That is, it's a circuit that's used to imagine what other people might do.

  • So these were some of the first studies to see this

  • tied in to game theory.

  • What happens with these one- and two-step types?

  • So we classify people by what they picked,

  • and then we look at the difference between

  • playing humans versus playing computers,

  • which brain areas are differentially active.

  • On the top you see the one-step players.

  • There's almost no difference.

  • The reason is, they're treating other people like a computer, and the brain is too.

  • The bottom players, you see all the activity in dorsomedial PFC.

  • So we know that those two-step players are doing something differently.

  • Now if you were to step back and say, "What can we do with this information?"

  • you might be able to look at brain activity and say,

  • "This person's going to be a good poker player,"

  • or, "This person's socially naive,"

  • and we might also be able to study things

  • like development of adolescent brains

  • once we have an idea of where this circuitry exists.

  • Okay. Get ready.

  • I'm saving you some brain activity,

  • because you don't need to use your hair detector cells.

  • You should use those cells to think carefully about this game.

  • This is a bargaining game.

  • Two players who are being scanned using EEG electrodes

  • are going to bargain over one to six dollars.

  • If they can do it in 10 seconds, they're going to actually earn that money.

  • If 10 seconds goes by and they haven't made a deal, they get nothing.

  • That's kind of a mistake together.

  • The twist is that one player, on the left,

  • is informed about how much on each trial there is.

  • They play lots of trials with different amounts each time.

  • In this case, they know there's four dollars.

  • The uninformed player doesn't know,

  • but they know that the informed player knows.

  • So the uninformed player's challenge is to say,

  • "Is this guy really being fair

  • or are they giving me a very low offer

  • in order to get me to think that there's only one or two dollars available to split?"

  • in which case they might reject it and not come to a deal.

  • So there's some tension here between trying to get the most money

  • but trying to goad the other player into giving you more.

  • And the way they bargain is to point on a number line

  • that goes from zero to six dollars,

  • and they're bargaining over how much the uninformed player gets,

  • and the informed player's going to get the rest.

  • So this is like a management-labor negotiation

  • in which the workers don't know how much profits

  • the privately held company has, right,

  • and they want to maybe hold out for more money,

  • but the company might want to create the impression

  • that there's very little to split: "I'm giving you the most that I can."

  • First some behavior. So a bunch of the subject pairs, they play face to face.

  • We have some other data where they play across computers.

  • That's an interesting difference, as you might imagine.

  • But a bunch of the face-to-face pairs

  • agree to divide the money evenly every single time.

  • Boring. It's just not interesting neurally.

  • It's good for them. They make a lot of money.

  • But we're interested in, can we say something about

  • when disagreements occur versus don't occur?

  • So this is the other group of subjects who often disagree.

  • So they have a chance of -- they bicker and disagree

  • and end up with less money.

  • They might be eligible to be on "Real Housewives," the TV show.

  • You see on the left,

  • when the amount to divide is one, two or three dollars,

  • they disagree about half the time,

  • and when the amount is four, five, six, they agree quite often.

  • This turns out to be something that's predicted

  • by a very complicated type of game theory

  • you should come to graduate school at CalTech and learn about.

  • It's a little too complicated to explain right now,

  • but the theory tells you that this shape kind of should occur.

  • Your intuition might tell you that too.

  • Now I'm going to show you the results from the EEG recording.

  • Very complicated. The right brain schematic

  • is the uninformed person, and the left is the informed.

  • Remember that we scanned both brains at the same time,

  • so we can ask about time-synced activity

  • in similar or different areas simultaneously,

  • just like if you wanted to study a conversation

  • and you were scanning two people talking to each other

  • and you'd expect common activity in language regions

  • when they're actually kind of listening and communicating.

  • So the arrows connect regions that are active at the same time,

  • and the direction of the arrows flows

  • from the region that's active first in time,

  • and the arrowhead goes to the region that's active later.

  • So in this case, if you look carefully,

  • most of the arrows flow from right to left.

  • That is, it looks as if the uninformed brain activity

  • is happening first,

  • and then it's followed by activity in the informed brain.

  • And by the way, these were trials where their deals were made.

  • This is from the first two seconds.

  • We haven't finished analyzing this data,

  • so we're still peeking in, but the hope is

  • that we can say something in the first couple of seconds

  • about whether they'll make a deal or not,

  • which could be very useful in thinking about avoiding litigation

  • and ugly divorces and things like that.

  • Those are all cases in which a lot of value is lost

  • by delay and strikes.

  • Here's the case where the disagreements occur.

  • You can see it looks different than the one before.

  • There's a lot more arrows.

  • That means that the brains are synced up

  • more closely in terms of simultaneous activity,

  • and the arrows flow clearly from left to right.

  • That is, the informed brain seems to be deciding,

  • "We're probably not going to make a deal here."

  • And then later there's activity in the uninformed brain.

  • Next I'm going to introduce you to some relatives.

  • They're hairy, smelly, fast and strong.

  • You might be thinking back to your last Thanksgiving.

  • Maybe if you had a chimpanzee with you.

  • Charles Darwin and I and you broke off from the family tree

  • from chimpanzees about five million years ago.

  • They're still our closest genetic kin.

  • We share 98.8 percent of the genes.

  • We share more genes with them than zebras do with horses.

  • And we're also their closest cousin.

  • They have more genetic relation to us than to gorillas.

  • So how humans and chimpanzees behave differently

  • might tell us a lot about brain evolution.

  • So this is an amazing memory test

  • from Nagoya, Japan, Primate Research Institute,

  • where they've done a lot of this research.

  • This goes back quite a ways. They're interested in working memory.

  • The chimp is going to see, watch carefully,

  • they're going to see 200 milliseconds' exposure

  • that's fast, that's eight movie frames

  • of numbers one, two, three, four, five.

  • Then they disappear and they're replaced by squares,

  • and they have to press the squares

  • that correspond to the numbers from low to high

  • to get an apple reward.