0:00:00.474,0:00:03.283 Other people. Everyone is interested in other people. 0:00:03.283,0:00:05.406 Everyone has relationships with other people, 0:00:05.406,0:00:06.998 and they're interested in these relationships 0:00:06.998,0:00:08.853 for a variety of reasons. 0:00:08.853,0:00:10.865 Good relationships, bad relationships, 0:00:10.865,0:00:14.011 annoying relationships, agnostic relationships, 0:00:14.011,0:00:17.435 and what I'm going to do is focus on the central piece 0:00:17.435,0:00:20.738 of an interaction that goes on in a relationship. 0:00:20.738,0:00:23.074 So I'm going to take as inspiration the fact that we're all 0:00:23.074,0:00:25.499 interested in interacting with other people, 0:00:25.499,0:00:29.331 I'm going to completely strip it of all its complicating features, 0:00:29.331,0:00:33.225 and I'm going to turn that object, that simplified object, 0:00:33.225,0:00:37.375 into a scientific probe, and provide the early stages, 0:00:37.375,0:00:39.824 embryonic stages of new insights into what happens 0:00:39.824,0:00:43.474 in two brains while they simultaneously interact. 0:00:43.474,0:00:45.767 But before I do that, let me tell you a couple of things 0:00:45.767,0:00:47.466 that made this possible. 0:00:47.466,0:00:50.247 The first is we can now eavesdrop safely 0:00:50.247,0:00:52.958 on healthy brain activity. 0:00:52.958,0:00:55.535 Without needles and radioactivity, 0:00:55.535,0:00:58.398 without any kind of clinical reason, we can go down the street 0:00:58.398,0:01:01.525 and record from your friends' and neighbors' brains 0:01:01.525,0:01:04.063 while they do a variety of cognitive tasks, and we use 0:01:04.063,0:01:07.797 a method called functional magnetic resonance imaging. 0:01:07.797,0:01:10.122 You've probably all read about it or heard about in some 0:01:10.122,0:01:14.500 incarnation. Let me give you a two-sentence version of it. 0:01:14.500,0:01:17.984 So we've all heard of MRIs. MRIs use magnetic fields 0:01:17.984,0:01:20.013 and radio waves and they take snapshots of your brain 0:01:20.013,0:01:22.374 or your knee or your stomach, 0:01:22.374,0:01:24.419 grayscale images that are frozen in time. 0:01:24.419,0:01:26.740 In the 1990s, it was discovered you could use 0:01:26.740,0:01:29.399 the same machines in a different mode, 0:01:29.399,0:01:31.745 and in that mode, you could make microscopic blood flow 0:01:31.745,0:01:35.045 movies from hundreds of thousands of sites independently in the brain. 0:01:35.045,0:01:38.245 Okay, so what? In fact, the so what is, in the brain, 0:01:38.245,0:01:42.077 changes in neural activity, the things that make your brain work, 0:01:42.077,0:01:44.087 the things that make your software work in your brain, 0:01:44.087,0:01:46.576 are tightly correlated with changes in blood flow. 0:01:46.576,0:01:48.549 You make a blood flow movie, you have an independent 0:01:48.549,0:01:50.888 proxy of brain activity. 0:01:50.888,0:01:53.922 This has literally revolutionized cognitive science. 0:01:53.922,0:01:55.913 Take any cognitive domain you want, memory, 0:01:55.913,0:01:58.054 motor planning, thinking about your mother-in-law, 0:01:58.054,0:02:01.769 getting angry at people, emotional response, it goes on and on, 0:02:01.769,0:02:04.858 put people into functional MRI devices, and 0:02:04.858,0:02:08.241 image how these kinds of variables map onto brain activity. 0:02:08.241,0:02:11.090 It's in its early stages, and it's crude by some measures, 0:02:11.090,0:02:13.658 but in fact, 20 years ago, we were at nothing. 0:02:13.658,0:02:16.017 You couldn't do people like this. You couldn't do healthy people. 0:02:16.017,0:02:18.505 That's caused a literal revolution, and it's opened us up 0:02:18.505,0:02:21.323 to a new experimental preparation. Neurobiologists, 0:02:21.323,0:02:25.083 as you well know, have lots of experimental preps, 0:02:25.083,0:02:28.224 worms and rodents and fruit flies and things like this. 0:02:28.224,0:02:31.621 And now, we have a new experimental prep: human beings. 0:02:31.621,0:02:35.382 We can now use human beings to study and model 0:02:35.382,0:02:38.332 the software in human beings, and we have a few 0:02:38.332,0:02:41.167 burgeoning biological measures. 0:02:41.167,0:02:45.054 Okay, let me give you one example of the kinds of experiments that people do, 0:02:45.054,0:02:47.731 and it's in the area of what you'd call valuation. 0:02:47.731,0:02:49.866 Valuation is just what you think it is, you know? 0:02:49.866,0:02:52.670 If you went and you were valuing two companies against 0:02:52.670,0:02:55.406 one another, you'd want to know which was more valuable. 0:02:55.406,0:02:59.285 Cultures discovered the key feature of valuation thousands of years ago. 0:02:59.285,0:03:01.975 If you want to compare oranges to windshields, what do you do? 0:03:01.975,0:03:04.331 Well, you can't compare oranges to windshields. 0:03:04.331,0:03:06.586 They're immiscible. They don't mix with one another. 0:03:06.586,0:03:08.937 So instead, you convert them to a common currency scale, 0:03:08.937,0:03:11.643 put them on that scale, and value them accordingly. 0:03:11.643,0:03:15.079 Well, your brain has to do something just like that as well, 0:03:15.079,0:03:17.567 and we're now beginning to understand and identify 0:03:17.567,0:03:19.704 brain systems involved in valuation, 0:03:19.704,0:03:22.336 and one of them includes a neurotransmitter system 0:03:22.336,0:03:24.968 whose cells are located in your brainstem 0:03:24.968,0:03:28.143 and deliver the chemical dopamine to the rest of your brain. 0:03:28.143,0:03:30.585 I won't go through the details of it, but that's an important 0:03:30.585,0:03:32.742 discovery, and we know a good bit about that now, 0:03:32.742,0:03:34.972 and it's just a small piece of it, but it's important because 0:03:34.972,0:03:38.247 those are the neurons that you would lose if you had Parkinson's disease, 0:03:38.247,0:03:40.263 and they're also the neurons that are hijacked by literally 0:03:40.263,0:03:42.495 every drug of abuse, and that makes sense. 0:03:42.495,0:03:44.831 Drugs of abuse would come in, and they would change 0:03:44.831,0:03:46.620 the way you value the world. They change the way 0:03:46.620,0:03:49.819 you value the symbols associated with your drug of choice, 0:03:49.819,0:03:52.333 and they make you value that over everything else. 0:03:52.333,0:03:55.354 Here's the key feature though. These neurons are also 0:03:55.354,0:03:58.855 involved in the way you can assign value to literally abstract ideas, 0:03:58.855,0:04:00.896 and I put some symbols up here that we assign value to 0:04:00.896,0:04:03.616 for various reasons. 0:04:03.616,0:04:06.305 We have a behavioral superpower in our brain, 0:04:06.305,0:04:08.058 and it at least in part involves dopamine. 0:04:08.058,0:04:12.247 We can deny every instinct we have for survival for an idea, 0:04:12.247,0:04:16.252 for a mere idea. No other species can do that. 0:04:16.252,0:04:19.858 In 1997, the cult Heaven's Gate committed mass suicide 0:04:19.858,0:04:22.073 predicated on the idea that there was a spaceship 0:04:22.073,0:04:25.858 hiding in the tail of the then-visible comet Hale-Bopp 0:04:25.858,0:04:30.130 waiting to take them to the next level. It was an incredibly tragic event. 0:04:30.130,0:04:33.615 More than two thirds of them had college degrees. 0:04:33.615,0:04:37.338 But the point here is they were able to deny their instincts for survival 0:04:37.338,0:04:40.204 using exactly the same systems that were put there 0:04:40.204,0:04:44.246 to make them survive. That's a lot of control, okay? 0:04:44.246,0:04:46.335 One thing that I've left out of this narrative 0:04:46.335,0:04:48.569 is the obvious thing, which is the focus of the rest of my 0:04:48.569,0:04:50.728 little talk, and that is other people. 0:04:50.728,0:04:53.724 These same valuation systems are redeployed 0:04:53.724,0:04:56.216 when we're valuing interactions with other people. 0:04:56.216,0:04:59.487 So this same dopamine system that gets addicted to drugs, 0:04:59.487,0:05:02.011 that makes you freeze when you get Parkinson's disease, 0:05:02.011,0:05:05.088 that contributes to various forms of psychosis, 0:05:05.088,0:05:09.008 is also redeployed to value interactions with other people 0:05:09.008,0:05:11.904 and to assign value to gestures that you do 0:05:11.904,0:05:14.478 when you're interacting with somebody else. 0:05:14.478,0:05:17.055 Let me give you an example of this. 0:05:17.055,0:05:20.022 You bring to the table such enormous processing power 0:05:20.022,0:05:22.646 in this domain that you hardly even notice it. 0:05:22.646,0:05:24.113 Let me just give you a few examples. So here's a baby. 0:05:24.113,0:05:27.843 She's three months old. She still poops in her diapers and she can't do calculus. 0:05:27.843,0:05:31.196 She's related to me. Somebody will be very glad that she's up here on the screen. 0:05:31.196,0:05:33.572 You can cover up one of her eyes, and you can still read 0:05:33.572,0:05:36.327 something in the other eye, and I see sort of curiosity 0:05:36.327,0:05:39.924 in one eye, I see maybe a little bit of surprise in the other. 0:05:39.924,0:05:43.103 Here's a couple. They're sharing a moment together, 0:05:43.103,0:05:44.421 and we've even done an experiment where you can cut out 0:05:44.421,0:05:47.428 different pieces of this frame and you can still see 0:05:47.428,0:05:49.932 that they're sharing it. They're sharing it sort of in parallel. 0:05:49.932,0:05:52.395 Now, the elements of the scene also communicate this 0:05:52.395,0:05:54.630 to us, but you can read it straight off their faces, 0:05:54.630,0:05:58.133 and if you compare their faces to normal faces, it would be a very subtle cue. 0:05:58.133,0:06:01.480 Here's another couple. He's projecting out at us, 0:06:01.480,0:06:04.368 and she's clearly projecting, you know, 0:06:04.368,0:06:06.631 love and admiration at him. 0:06:06.631,0:06:10.266 Here's another couple. (Laughter) 0:06:10.266,0:06:15.416 And I'm thinking I'm not seeing love and admiration on the left. (Laughter) 0:06:15.416,0:06:17.976 In fact, I know this is his sister, and you can just see 0:06:17.976,0:06:20.489 him saying, "Okay, we're doing this for the camera, 0:06:20.489,0:06:26.191 and then afterwards you steal my candy and you punch me in the face." (Laughter) 0:06:26.191,0:06:28.297 He'll kill me for showing that. 0:06:28.297,0:06:31.094 All right, so what does this mean? 0:06:31.094,0:06:34.444 It means we bring an enormous amount of processing power to the problem. 0:06:34.444,0:06:38.092 It engages deep systems in our brain, in dopaminergic 0:06:38.092,0:06:40.910 systems that are there to make you chase sex, food and salt. 0:06:40.910,0:06:43.804 They keep you alive. It gives them the pie, it gives 0:06:43.804,0:06:46.708 that kind of a behavioral punch which we've called a superpower. 0:06:46.708,0:06:50.362 So how can we take that and arrange a kind of staged 0:06:50.362,0:06:53.060 social interaction and turn that into a scientific probe? 0:06:53.060,0:06:55.751 And the short answer is games. 0:06:55.751,0:07:00.155 Economic games. So what we do is we go into two areas. 0:07:00.155,0:07:03.491 One area is called experimental economics. The other area is called behavioral economics. 0:07:03.491,0:07:07.569 And we steal their games. And we contrive them to our own purposes. 0:07:07.569,0:07:10.536 So this shows you one particular game called an ultimatum game. 0:07:10.536,0:07:12.381 Red person is given a hundred dollars and can offer 0:07:12.381,0:07:16.104 a split to blue. Let's say red wants to keep 70, 0:07:16.104,0:07:20.190 and offers blue 30. So he offers a 70-30 split with blue. 0:07:20.190,0:07:23.041 Control passes to blue, and blue says, "I accept it," 0:07:23.041,0:07:24.997 in which case he'd get the money, or blue says, 0:07:24.997,0:07:29.304 "I reject it," in which case no one gets anything. Okay? 0:07:29.304,0:07:32.696 So a rational choice economist would say, well, 0:07:32.696,0:07:34.752 you should take all non-zero offers. 0:07:34.752,0:07:38.514 What do people do? People are indifferent at an 80-20 split. 0:07:38.514,0:07:42.038 At 80-20, it's a coin flip whether you accept that or not. 0:07:42.038,0:07:44.929 Why is that? You know, because you're pissed off. 0:07:44.929,0:07:48.538 You're mad. That's an unfair offer, and you know what an unfair offer is. 0:07:48.538,0:07:51.242 This is the kind of game done by my lab and many around the world. 0:07:51.242,0:07:53.786 That just gives you an example of the kind of thing that 0:07:53.786,0:07:57.524 these games probe. The interesting thing is, these games 0:07:57.524,0:08:01.231 require that you have a lot of cognitive apparatus on line. 0:08:01.231,0:08:04.159 You have to be able to come to the table with a proper model of another person. 0:08:04.159,0:08:07.372 You have to be able to remember what you've done. 0:08:07.372,0:08:08.792 You have to stand up in the moment to do that. 0:08:08.792,0:08:12.142 Then you have to update your model based on the signals coming back, 0:08:12.142,0:08:15.114 and you have to do something that is interesting, 0:08:15.114,0:08:17.711 which is you have to do a kind of depth of thought assay. 0:08:17.711,0:08:21.044 That is, you have to decide what that other person expects of you. 0:08:21.044,0:08:23.998 You have to send signals to manage your image in their mind. 0:08:23.998,0:08:26.851 Like a job interview. You sit across the desk from somebody, 0:08:26.851,0:08:28.220 they have some prior image of you, 0:08:28.220,0:08:30.971 you send signals across the desk to move their image 0:08:30.971,0:08:34.891 of you from one place to a place where you want it to be. 0:08:34.891,0:08:38.276 We're so good at this we don't really even notice it. 0:08:38.276,0:08:42.043 These kinds of probes exploit it. Okay? 0:08:42.043,0:08:43.850 In doing this, what we've discovered is that humans 0:08:43.850,0:08:46.181 are literal canaries in social exchanges. 0:08:46.181,0:08:49.578 Canaries used to be used as kind of biosensors in mines. 0:08:49.578,0:08:53.138 When methane built up, or carbon dioxide built up, 0:08:53.138,0:08:57.324 or oxygen was diminished, the birds would swoon 0:08:57.324,0:08:59.650 before people would -- so it acted as an early warning system: 0:08:59.650,0:09:02.630 Hey, get out of the mine. Things aren't going so well. 0:09:02.630,0:09:05.584 People come to the table, and even these very blunt, 0:09:05.584,0:09:08.574 staged social interactions, and they, and there's just 0:09:08.574,0:09:11.590 numbers going back and forth between the people, 0:09:11.590,0:09:13.789 and they bring enormous sensitivities to it. 0:09:13.789,0:09:16.478 So we realized we could exploit this, and in fact, 0:09:16.478,0:09:19.034 as we've done that, and we've done this now in 0:09:19.034,0:09:21.728 many thousands of people, I think on the order of 0:09:21.728,0:09:23.893 five or six thousand. We actually, to make this 0:09:23.893,0:09:26.117 a biological probe, need bigger numbers than that, 0:09:26.117,0:09:29.791 remarkably so. But anyway, 0:09:29.791,0:09:31.795 patterns have emerged, and we've been able to take 0:09:31.795,0:09:35.631 those patterns, convert them into mathematical models, 0:09:35.631,0:09:38.320 and use those mathematical models to gain new insights 0:09:38.320,0:09:40.451 into these exchanges. Okay, so what? 0:09:40.451,0:09:43.764 Well, the so what is, that's a really nice behavioral measure, 0:09:43.764,0:09:47.083 the economic games bring to us notions of optimal play. 0:09:47.083,0:09:49.567 We can compute that during the game. 0:09:49.567,0:09:52.520 And we can use that to sort of carve up the behavior. 0:09:52.520,0:09:56.850 Here's the cool thing. Six or seven years ago, 0:09:56.850,0:09:59.400 we developed a team. It was at the time in Houston, Texas. 0:09:59.400,0:10:02.794 It's now in Virginia and London. And we built software 0:10:02.794,0:10:06.001 that'll link functional magnetic resonance imaging devices 0:10:06.001,0:10:10.036 up over the Internet. I guess we've done up to six machines 0:10:10.036,0:10:12.017 at a time, but let's just focus on two. 0:10:12.017,0:10:15.075 So it synchronizes machines anywhere in the world. 0:10:15.075,0:10:18.244 We synchronize the machines, set them into these 0:10:18.244,0:10:20.227 staged social interactions, and we eavesdrop on both 0:10:20.227,0:10:21.893 of the interacting brains. So for the first time, 0:10:21.893,0:10:25.500 we don't have to look at just averages over single individuals, 0:10:25.500,0:10:28.397 or have individuals playing computers, or try to make 0:10:28.397,0:10:31.160 inferences that way. We can study individual dyads. 0:10:31.160,0:10:33.945 We can study the way that one person interacts with another person, 0:10:33.945,0:10:36.509 turn the numbers up, and start to gain new insights 0:10:36.509,0:10:39.024 into the boundaries of normal cognition, 0:10:39.024,0:10:41.756 but more importantly, we can put people with 0:10:41.756,0:10:45.093 classically defined mental illnesses, or brain damage, 0:10:45.093,0:10:48.644 into these social interactions, and use these as probes of that. 0:10:48.644,0:10:50.994 So we've started this effort. We've made a few hits, 0:10:50.994,0:10:53.443 a few, I think, embryonic discoveries. 0:10:53.443,0:10:56.255 We think there's a future to this. But it's our way 0:10:56.255,0:10:58.815 of going in and redefining, with a new lexicon, 0:10:58.815,0:11:02.837 a mathematical one actually, as opposed to the standard 0:11:02.837,0:11:05.415 ways that we think about mental illness, 0:11:05.415,0:11:07.482 characterizing these diseases, by using the people 0:11:07.482,0:11:10.489 as birds in the exchanges. That is, we exploit the fact 0:11:10.489,0:11:14.733 that the healthy partner, playing somebody with major depression, 0:11:14.733,0:11:17.643 or playing somebody with autism spectrum disorder, 0:11:17.643,0:11:21.493 or playing somebody with attention deficit hyperactivity disorder, 0:11:21.493,0:11:24.712 we use that as a kind of biosensor, and then we use 0:11:24.712,0:11:27.356 computer programs to model that person, and it gives us 0:11:27.356,0:11:29.826 a kind of assay of this. 0:11:29.826,0:11:31.957 Early days, and we're just beginning, we're setting up sites 0:11:31.957,0:11:35.367 around the world. Here are a few of our collaborating sites. 0:11:35.367,0:11:37.676 The hub, ironically enough, 0:11:37.676,0:11:40.565 is centered in little Roanoke, Virginia. 0:11:40.565,0:11:42.834 There's another hub in London, now, and the rest 0:11:42.834,0:11:46.843 are getting set up. We hope to give the data away 0:11:46.843,0:11:50.516 at some stage. That's a complicated issue 0:11:50.516,0:11:53.510 about making it available to the rest of the world. 0:11:53.510,0:11:55.357 But we're also studying just a small part 0:11:55.357,0:11:57.624 of what makes us interesting as human beings, and so 0:11:57.624,0:11:59.665 I would invite other people who are interested in this 0:11:59.665,0:12:02.234 to ask us for the software, or even for guidance 0:12:02.234,0:12:04.453 on how to move forward with that. 0:12:04.453,0:12:06.794 Let me leave you with one thought in closing. 0:12:06.794,0:12:08.736 The interesting thing about studying cognition 0:12:08.736,0:12:12.468 has been that we've been limited, in a way. 0:12:12.468,0:12:15.411 We just haven't had the tools to look at interacting brains 0:12:15.411,0:12:16.611 simultaneously. 0:12:16.611,0:12:19.081 The fact is, though, that even when we're alone, 0:12:19.081,0:12:23.192 we're a profoundly social creature. We're not a solitary mind 0:12:23.192,0:12:27.565 built out of properties that kept it alive in the world 0:12:27.565,0:12:31.513 independent of other people. In fact, our minds 0:12:31.513,0:12:34.383 depend on other people. They depend on other people, 0:12:34.383,0:12:35.924 and they're expressed in other people, 0:12:35.924,0:12:39.576 so the notion of who you are, you often don't know 0:12:39.576,0:12:42.264 who you are until you see yourself in interaction with people 0:12:42.264,0:12:44.670 that are close to you, people that are enemies of you, 0:12:44.670,0:12:47.215 people that are agnostic to you. 0:12:47.215,0:12:50.991 So this is the first sort of step into using that insight 0:12:50.991,0:12:54.286 into what makes us human beings, turning it into a tool, 0:12:54.286,0:12:56.264 and trying to gain new insights into mental illness. 0:12:56.264,0:12:59.385 Thanks for having me. (Applause) 0:12:59.385,0:13:02.474 (Applause)