WEBVTT 00:00:00.578 --> 00:00:03.675 I'm a brain scientist, and as a brain scientist, 00:00:03.675 --> 00:00:06.747 I'm actually interested in how the brain learns, 00:00:06.747 --> 00:00:10.114 and I'm especially interested in a possibility of 00:00:10.114 --> 00:00:14.846 making our brains smarter, better and faster. NOTE Paragraph 00:00:14.846 --> 00:00:17.722 This is in this context I'm going to tell you 00:00:17.722 --> 00:00:20.472 about video games. When we say video games, 00:00:20.472 --> 00:00:23.010 most of you think about children. 00:00:23.010 --> 00:00:26.988 It's true. Ninety percent of children do play video games. 00:00:26.988 --> 00:00:29.906 But let's be frank. 00:00:29.906 --> 00:00:34.695 When the kids are in bed, who is in front of the PlayStation? 00:00:34.695 --> 00:00:41.179 Most of you. The average age of a gamer is 33 years old, 00:00:41.179 --> 00:00:44.186 not eight years old, and in fact, if we look 00:00:44.186 --> 00:00:47.895 at the projected demographics of video game play, 00:00:47.895 --> 00:00:50.628 the video game players of tomorrow are 00:00:50.628 --> 00:00:53.752 older adults. (Laughter) NOTE Paragraph 00:00:53.752 --> 00:00:58.003 So video [gaming] is pervasive throughout our society. 00:00:58.003 --> 00:01:02.386 It is clearly here to stay. It has an amazing impact 00:01:02.386 --> 00:01:05.773 on our everyday life. Consider these statistics 00:01:05.773 --> 00:01:11.588 released by Activision. After one month of release 00:01:11.588 --> 00:01:16.080 of the game "Call Of Duty: Black Ops," it had been played 00:01:16.080 --> 00:01:19.453 for 68,000 years 00:01:19.453 --> 00:01:21.319 worldwide, right? 00:01:21.319 --> 00:01:24.266 Would any of you complain if this was the case 00:01:24.266 --> 00:01:27.429 about doing linear algebra? NOTE Paragraph 00:01:27.429 --> 00:01:31.724 So what we are asking in the lab is, how can we leverage that power? 00:01:31.724 --> 00:01:33.572 Now I want to step back a bit. 00:01:33.572 --> 00:01:36.813 I know most of you have had the experience of coming back 00:01:36.813 --> 00:01:41.533 home and finding your kids playing these kinds of games. 00:01:41.533 --> 00:01:43.673 (Shooting noises) The name of the game is to get 00:01:43.673 --> 00:01:46.637 after your enemy zombie bad guys 00:01:46.637 --> 00:01:50.227 before they get to you, right? 00:01:50.227 --> 00:01:53.404 And I'm almost sure most of you have thought, 00:01:53.404 --> 00:01:56.725 "Oh, come on, can't you do something more intelligent 00:01:56.725 --> 00:02:00.052 than shooting at zombies?" 00:02:00.052 --> 00:02:03.518 I'd like you to put this kind of knee-jerk reaction 00:02:03.518 --> 00:02:06.015 in the context of what you would have thought 00:02:06.015 --> 00:02:09.524 if you had found your girl playing sudoku 00:02:09.524 --> 00:02:13.875 or your boy reading Shakespeare. Right? 00:02:13.875 --> 00:02:16.612 Most parents would find that great. 00:02:16.612 --> 00:02:19.956 Well, I'm not going to tell you that playing video games 00:02:19.956 --> 00:02:22.924 days in and days out is actually good for your health. 00:02:22.924 --> 00:02:26.124 It's not, and binging is never good. 00:02:26.124 --> 00:02:30.115 But I'm going to argue that in reasonable doses, 00:02:30.115 --> 00:02:33.084 actually the very game I showed you at the beginning, 00:02:33.084 --> 00:02:35.668 those action-packed shooter games 00:02:35.668 --> 00:02:39.444 have quite powerful effects and positive effects 00:02:39.444 --> 00:02:43.302 on many different aspects of our behavior. NOTE Paragraph 00:02:43.302 --> 00:02:46.997 There's not one week that goes without some major 00:02:46.997 --> 00:02:49.773 headlines in the media about whether video games are 00:02:49.773 --> 00:02:54.389 good or bad for you, right? You're all bombarded with that. 00:02:54.389 --> 00:03:00.077 I'd like to put this kind of Friday night bar discussion aside 00:03:00.077 --> 00:03:03.220 and get you to actually step into the lab. 00:03:03.220 --> 00:03:06.093 What we do in the lab is actually measure directly, 00:03:06.093 --> 00:03:08.860 in a quantitative fashion, what is the impact 00:03:08.860 --> 00:03:11.629 of video games on the brain. 00:03:11.629 --> 00:03:14.964 And so I'm going to take a few examples from our work. NOTE Paragraph 00:03:14.964 --> 00:03:17.563 One first saying that I'm sure you all have heard 00:03:17.563 --> 00:03:19.849 is the fact that too much screen time 00:03:19.849 --> 00:03:22.664 makes your eyesight worse. 00:03:22.664 --> 00:03:24.867 That's a statement about vision. 00:03:24.867 --> 00:03:27.403 There may be vision scientists among you. 00:03:27.403 --> 00:03:30.342 We actually know how to test that statement. 00:03:30.342 --> 00:03:33.779 We can step into the lab and measure how good your vision is. 00:03:33.779 --> 00:03:37.460 Well, guess what? People that don't play a lot 00:03:37.460 --> 00:03:40.450 of action games, that don't actually spend a lot of time 00:03:40.450 --> 00:03:43.982 in front of screens, have normal, or what we call 00:03:43.982 --> 00:03:46.636 corrective-to-normal vision. That's okay. 00:03:46.636 --> 00:03:49.085 The issue is what happens with these guys that actually 00:03:49.085 --> 00:03:52.365 indulge into playing video games like five hours per week, 00:03:52.365 --> 00:03:54.240 10 hours per week, 15 hours per week. 00:03:54.240 --> 00:03:57.468 By that statement, their vision should be really bad, right? 00:03:57.468 --> 00:04:00.165 Guess what? Their vision is really, really good. 00:04:00.165 --> 00:04:02.605 It's better than those that don't play. 00:04:02.605 --> 00:04:04.877 And it's better in two different ways. 00:04:04.877 --> 00:04:07.302 The first way is that they're actually able to resolve 00:04:07.302 --> 00:04:10.557 small detail in the context of clutter, and though that means 00:04:10.557 --> 00:04:14.355 being able to read the fine print on a prescription 00:04:14.355 --> 00:04:18.982 rather than using magnifier glasses, you can actually do it 00:04:18.982 --> 00:04:20.548 with just your eyesight. 00:04:20.548 --> 00:04:23.364 The other way that they are better is actually being able 00:04:23.364 --> 00:04:26.273 to resolve different levels of gray. 00:04:26.273 --> 00:04:29.444 Imagine you're driving in a fog. That makes a difference 00:04:29.444 --> 00:04:31.925 between seeing the car in front of you 00:04:31.925 --> 00:04:35.668 and avoiding the accident, or getting into an accident. 00:04:35.668 --> 00:04:38.684 So we're actually leveraging that work to develop games 00:04:38.684 --> 00:04:43.158 for patients with low vision, and to have an impact 00:04:43.158 --> 00:04:46.493 on retraining their brain to see better. 00:04:46.493 --> 00:04:50.142 Clearly, when it comes to action video games, 00:04:50.142 --> 00:04:53.037 screen time doesn't make your eyesight worse. NOTE Paragraph 00:04:53.037 --> 00:04:57.023 Another saying that I'm sure you have all heard around: 00:04:57.023 --> 00:05:01.397 Video games lead to attention problems and greater distractability. 00:05:01.397 --> 00:05:05.302 Okay, we know how to measure attention in the lab. 00:05:05.302 --> 00:05:08.903 I'm actually going to give you an example of how we do so. 00:05:08.903 --> 00:05:11.628 I'm going to ask you to participate, so you're going to have 00:05:11.628 --> 00:05:14.652 to actually play the game with me. I'm going to show you 00:05:14.652 --> 00:05:20.085 colored words. I want you to shout out the color of the ink. 00:05:20.085 --> 00:05:23.468 Right? So this is the first example. 00:05:23.468 --> 00:05:24.558 ["Chair"] 00:05:24.558 --> 00:05:27.619 Orange, good. ["Table"] Green. 00:05:27.619 --> 00:05:28.999 ["Board"] Audience: Red.Daphne Bavelier: Red. 00:05:28.999 --> 00:05:30.293 ["Horse"] DB: Yellow. Audience: Yellow. 00:05:30.293 --> 00:05:31.618 ["Yellow"] DB: Red. Audience: Yellow. 00:05:31.618 --> 00:05:33.127 ["Blue"] DB: Yellow. 00:05:33.127 --> 00:05:39.482 Okay, you get my point, right? (Laughter) 00:05:39.482 --> 00:05:42.818 You're getting better, but it's hard. Why is it hard? 00:05:42.818 --> 00:05:46.772 Because I introduced a conflict between 00:05:46.772 --> 00:05:49.685 the word itself and its color. 00:05:49.685 --> 00:05:52.724 How good your attention is determines actually how fast 00:05:52.724 --> 00:05:55.251 you resolve that conflict, so the young guys here 00:05:55.251 --> 00:05:57.812 at the top of their game probably, like, did a little better 00:05:57.812 --> 00:06:00.356 than some of us that are older. 00:06:00.356 --> 00:06:02.924 What we can show is that when you do this kind of task 00:06:02.924 --> 00:06:04.524 with people that play a lot of action games, 00:06:04.524 --> 00:06:07.844 they actually resolve the conflict faster. 00:06:07.844 --> 00:06:11.052 So clearly playing those action games doesn't lead 00:06:11.052 --> 00:06:13.535 to attention problems. NOTE Paragraph 00:06:13.535 --> 00:06:15.506 Actually, those action video game players have 00:06:15.506 --> 00:06:17.823 many other advantages in terms of attention, and one 00:06:17.823 --> 00:06:20.722 aspect of attention which is also improved for the better 00:06:20.722 --> 00:06:25.500 is our ability to track objects around in the world. 00:06:25.500 --> 00:06:28.044 This is something we use all the time. When you're driving, 00:06:28.044 --> 00:06:31.292 you're tracking, keeping track of the cars around you. 00:06:31.292 --> 00:06:34.367 You're also keeping track of the pedestrian, the running dog, 00:06:34.367 --> 00:06:37.420 and that's how you can actually be safe driving, right? NOTE Paragraph 00:06:37.420 --> 00:06:40.484 In the lab, we get people to come to the lab, 00:06:40.484 --> 00:06:42.564 sit in front of a computer screen, and we give them 00:06:42.564 --> 00:06:45.460 little tasks that I'm going to get you to do again. 00:06:45.460 --> 00:06:48.412 You're going to see yellow happy faces 00:06:48.412 --> 00:06:52.228 and a few sad blue faces. These are children 00:06:52.228 --> 00:06:56.048 in the schoolyard in Geneva during a recess 00:06:56.048 --> 00:07:00.349 during the winter. Most kids are happy. It's actually recess. 00:07:00.349 --> 00:07:03.476 But a few kids are sad and blue because they've forgotten their coat. 00:07:03.476 --> 00:07:06.796 Everybody begins to move around, and your task 00:07:06.796 --> 00:07:09.920 is to keep track of who had a coat at the beginning 00:07:09.920 --> 00:07:12.411 and who didn't. So I'm just going to show you an example 00:07:12.411 --> 00:07:15.240 where there is only one sad kid. It's easy because you can 00:07:15.240 --> 00:07:17.577 actually track it with your eyes. You can track, 00:07:17.577 --> 00:07:19.857 you can track, and then when it stops, and there is 00:07:19.857 --> 00:07:23.788 a question mark, and I ask you, did this kid have a coat or not? 00:07:23.788 --> 00:07:26.616 Was it yellow initially or blue? 00:07:26.616 --> 00:07:30.413 I hear a few yellow. Good. So most of you have a brain. (Laughter) 00:07:30.413 --> 00:07:35.209 I'm now going to ask you to do the task, but now with 00:07:35.209 --> 00:07:37.297 a little more challenging task. There are going to be 00:07:37.297 --> 00:07:40.480 three of them that are blue. Don't move your eyes. 00:07:40.480 --> 00:07:42.733 Please don't move your eyes. Keep your eyes fixated 00:07:42.733 --> 00:07:45.379 and expand, pull your attention. That's the only way 00:07:45.379 --> 00:07:48.227 you can actually do it. If you move your eyes, you're doomed. 00:07:48.227 --> 00:07:49.690 Yellow or blue? 00:07:49.690 --> 00:07:51.336 Audience: Yellow.DB: Good. 00:07:51.336 --> 00:07:53.839 So your typical normal young adult 00:07:53.839 --> 00:07:57.475 can have a span of about three or four objects of attention. 00:07:57.475 --> 00:08:00.235 That's what we just did. Your action video game player 00:08:00.235 --> 00:08:03.435 has a span of about six to seven objects of attention, 00:08:03.435 --> 00:08:06.413 which is what is shown in this video here. 00:08:06.413 --> 00:08:09.889 That's for you guys, action video game players. 00:08:09.889 --> 00:08:11.774 A bit more challenging, right? (Laughter) 00:08:11.774 --> 00:08:15.482 Yellow or blue? Blue. We have some people 00:08:15.482 --> 00:08:18.686 that are serious out there. Yeah. (Laughter) NOTE Paragraph 00:08:18.686 --> 00:08:22.290 Good. So in the same way that we actually see 00:08:22.290 --> 00:08:25.768 the effects of video games on people's behavior, 00:08:25.768 --> 00:08:28.833 we can use brain imaging and look at the impact 00:08:28.833 --> 00:08:32.618 of video games on the brain, and we do find many changes, 00:08:32.618 --> 00:08:35.978 but the main changes are actually to the brain networks 00:08:35.978 --> 00:08:40.522 that control attention. So one part is the parietal cortex 00:08:40.522 --> 00:08:44.241 which is very well known to control the orientation of attention. 00:08:44.241 --> 00:08:46.674 The other one is the frontal lobe, which controls 00:08:46.674 --> 00:08:49.384 how we sustain attention, and another one 00:08:49.384 --> 00:08:51.953 is the anterior cingulate, which controls how we allocate 00:08:51.953 --> 00:08:55.250 and regulate attention and resolve conflict. 00:08:55.250 --> 00:08:58.114 Now, when we do brain imaging, we find that all three 00:08:58.114 --> 00:09:01.458 of these networks are actually much more efficient 00:09:01.458 --> 00:09:04.218 in people that play action games. NOTE Paragraph 00:09:04.218 --> 00:09:08.969 This actually leads me to a rather counterintuitive finding 00:09:08.969 --> 00:09:12.410 in the literature about technology and the brain. 00:09:12.410 --> 00:09:16.859 You all know about multitasking. You all have been faulty 00:09:16.859 --> 00:09:19.069 of multitasking when you're driving 00:09:19.069 --> 00:09:23.760 and you pick up your cellphone. Bad idea. Very bad idea. 00:09:23.760 --> 00:09:27.663 Why? Because as your attention shifts to your cell phone, 00:09:27.663 --> 00:09:31.811 you are actually losing the capacity to react swiftly 00:09:31.811 --> 00:09:34.259 to the car braking in front of you, and so you're 00:09:34.259 --> 00:09:39.830 much more likely to get engaged into a car accident. 00:09:39.830 --> 00:09:42.706 Now, we can measure that kind of skills in the lab. 00:09:42.706 --> 00:09:45.178 We obviously don't ask people to drive around and see 00:09:45.178 --> 00:09:47.523 how many car accidents they have. That would be a little 00:09:47.523 --> 00:09:51.070 costly proposition. But we design tasks on the computer 00:09:51.070 --> 00:09:54.188 where we can measure, to millisecond accuracy, 00:09:54.188 --> 00:09:58.716 how good they are at switching from one task to another. 00:09:58.716 --> 00:10:01.284 When we do that, we actually find that people 00:10:01.284 --> 00:10:04.368 that play a lot of action games are really, really good. 00:10:04.368 --> 00:10:08.851 They switch really fast, very swiftly. They pay a very small cost. NOTE Paragraph 00:10:08.851 --> 00:10:11.509 Now I'd like you to remember that result, and put it 00:10:11.509 --> 00:10:15.241 in the context of another group of technology users, 00:10:15.241 --> 00:10:17.651 a group which is actually much revered by society, 00:10:17.651 --> 00:10:22.190 which are people that engage in multimedia-tasking. 00:10:22.190 --> 00:10:25.835 What is multimedia-tasking? It's the fact that most of us, 00:10:25.835 --> 00:10:29.116 most of our children, are engaged with listening to music 00:10:29.116 --> 00:10:31.863 at the same time as they're doing search on the web 00:10:31.863 --> 00:10:35.220 at the same time as they're chatting on Facebook with their friends. 00:10:35.220 --> 00:10:37.556 That's a multimedia-tasker. 00:10:37.556 --> 00:10:41.116 There was a first study done by colleagues at Stanford 00:10:41.116 --> 00:10:43.669 and that we replicated that showed that 00:10:43.669 --> 00:10:48.316 those people that identify as being high multimedia-taskers 00:10:48.316 --> 00:10:52.163 are absolutely abysmal at multitasking. 00:10:52.163 --> 00:10:54.900 When we measure them in the lab, they're really bad. NOTE Paragraph 00:10:54.900 --> 00:10:57.606 Right? So these kinds of results really 00:10:57.606 --> 00:11:00.092 makes two main points. 00:11:00.092 --> 00:11:03.284 The first one is that not all media are created equal. 00:11:03.284 --> 00:11:08.196 You can't compare the effect of multimedia-tasking 00:11:08.196 --> 00:11:09.842 and the effect of playing action games. They have 00:11:09.842 --> 00:11:13.234 totally different effects on different aspects of cognition, 00:11:13.234 --> 00:11:16.348 perception and attention. 00:11:16.348 --> 00:11:19.188 Even within video games, I'm telling you right now 00:11:19.188 --> 00:11:20.941 about these action-packed video games. 00:11:20.941 --> 00:11:24.275 Different video games have a different effect on your brains. 00:11:24.275 --> 00:11:26.957 So we actually need to step into the lab and really measure 00:11:26.957 --> 00:11:29.468 what is the effect of each video game. NOTE Paragraph 00:11:29.468 --> 00:11:33.755 The other lesson is that general wisdom carries no weight. 00:11:33.755 --> 00:11:36.811 I showed that to you already, like we looked at the fact that 00:11:36.811 --> 00:11:39.259 despite a lot of screen time, those action gamers 00:11:39.259 --> 00:11:43.267 have a lot of very good vision, etc. 00:11:43.267 --> 00:11:46.585 Here, what was really striking is that these undergraduates 00:11:46.585 --> 00:11:49.826 that actually report engaging in a lot of high 00:11:49.826 --> 00:11:54.803 multimedia-tasking are convinced they aced the test. 00:11:54.803 --> 00:11:57.093 So you show them their data, you show them they are bad 00:11:57.093 --> 00:11:59.779 and they're like, "Not possible." You know, they have 00:11:59.779 --> 00:12:03.635 this sort of gut feeling that, really, they are doing really, really good. 00:12:03.635 --> 00:12:06.580 That's another argument for why we need to step into the lab 00:12:06.580 --> 00:12:10.172 and really measure the impact of technology on the brain. NOTE Paragraph 00:12:10.172 --> 00:12:14.755 Now in a sense, when we think about the effect 00:12:14.755 --> 00:12:17.235 of video games on the brain, it's very similar 00:12:17.235 --> 00:12:21.099 to the effect of wine on the health. 00:12:21.099 --> 00:12:24.139 There are some very poor uses of wine. There are some 00:12:24.139 --> 00:12:28.355 very poor uses of video games. But when consumed 00:12:28.355 --> 00:12:31.836 in reasonable doses, and at the right age, 00:12:31.836 --> 00:12:35.107 wine can be very good for health. There are actually 00:12:35.107 --> 00:12:38.371 specific molecules that have been identified 00:12:38.371 --> 00:12:44.203 in red wine as leading to greater life expectancy. 00:12:44.203 --> 00:12:47.475 So it's the same way, like those action video games 00:12:47.475 --> 00:12:49.137 have a number of ingredients that are actually really 00:12:49.137 --> 00:12:53.107 powerful for brain plasticity, learning, attention, 00:12:53.107 --> 00:12:56.712 vision, etc., and so we need and we're working on 00:12:56.712 --> 00:12:59.467 understanding what are those active ingredients so that 00:12:59.467 --> 00:13:03.357 we can really then leverage them to deliver better games, 00:13:03.357 --> 00:13:07.600 either for education or for rehabilitation of patients. NOTE Paragraph 00:13:07.600 --> 00:13:11.379 Now because we are interested in having an impact 00:13:11.379 --> 00:13:13.867 for education or rehabilitation of patients, we are actually 00:13:13.867 --> 00:13:17.283 not that interested in how those of you that choose 00:13:17.283 --> 00:13:21.155 to play video games for many hours on end perform. 00:13:21.155 --> 00:13:24.980 I'm much more interested in taking any of you 00:13:24.980 --> 00:13:28.760 and showing that by forcing you to play an action game, 00:13:28.760 --> 00:13:31.623 I can actually change your vision for the better, 00:13:31.623 --> 00:13:33.954 whether you want to play that action game or not, right? 00:13:33.954 --> 00:13:36.370 That's the point of rehabilitation or education. 00:13:36.370 --> 00:13:38.296 Most of the kids don't go to school saying, 00:13:38.296 --> 00:13:41.036 "Great, two hours of math!" NOTE Paragraph 00:13:41.036 --> 00:13:45.475 So that's really the crux of the research, and to do that, 00:13:45.475 --> 00:13:47.939 we need to go one more step. 00:13:47.939 --> 00:13:50.963 And one more step is to do training studies. 00:13:50.963 --> 00:13:54.363 So let me illustrate that step with 00:13:54.363 --> 00:13:57.931 a task which is called mental rotation. 00:13:57.931 --> 00:14:02.106 Mental rotation is a task where I'm going to ask you, 00:14:02.106 --> 00:14:03.991 and again you're going to do the task, 00:14:03.991 --> 00:14:07.676 to look at this shape. Study it, it's a target shape, 00:14:07.676 --> 00:14:10.930 and I'm going to present to you four different shapes. 00:14:10.930 --> 00:14:13.770 One of these four different shapes is actually a rotated 00:14:13.770 --> 00:14:18.074 version of this shape. I want you to tell me which one: 00:14:18.074 --> 00:14:22.915 the first one, second one, third one or fourth one? 00:14:22.915 --> 00:14:25.332 Okay, I'll help you. Fourth one. 00:14:25.332 --> 00:14:29.862 One more. Get those brains working. Come on. 00:14:29.862 --> 00:14:34.836 That's our target shape. 00:14:34.836 --> 00:14:38.539 Third. Good! This is hard, right? 00:14:38.539 --> 00:14:40.026 Like, the reason that I asked you to do that is because 00:14:40.026 --> 00:14:42.760 you really feel your brain cringing, right? 00:14:42.760 --> 00:14:46.192 It doesn't really feel like playing mindless action video games. NOTE Paragraph 00:14:46.192 --> 00:14:48.897 Well, what we do in these training studies is, people 00:14:48.897 --> 00:14:51.506 come to the lab, they do tasks like this one, 00:14:51.506 --> 00:14:55.836 we then force them to play 10 hours of action games. 00:14:55.836 --> 00:14:58.582 They don't play 10 hours of action games in a row. 00:14:58.582 --> 00:15:01.692 They do distributed practice, so little shots of 40 minutes 00:15:01.692 --> 00:15:05.993 several days over a period of two weeks. 00:15:05.993 --> 00:15:07.789 Then, once they are done with the training, they come back 00:15:07.789 --> 00:15:11.762 a few days later and they are tested again on a similar type 00:15:11.762 --> 00:15:15.378 of mental rotation task. So this is work from a colleague 00:15:15.378 --> 00:15:17.913 in Toronto. What they showed is that, initially, 00:15:17.913 --> 00:15:20.111 you know, subjects perform where they are expected 00:15:20.111 --> 00:15:25.321 to perform given their age. After two weeks of training 00:15:25.321 --> 00:15:29.177 on action video games, they actually perform better, 00:15:29.177 --> 00:15:34.533 and the improvement is still there five months after 00:15:34.533 --> 00:15:37.401 having done the training. That's really, really important. 00:15:37.401 --> 00:15:39.881 Why? Because I told you we want to use these games 00:15:39.881 --> 00:15:43.081 for education or for rehabilitation. We need to have effects 00:15:43.081 --> 00:15:46.017 that are going to be long-lasting. NOTE Paragraph 00:15:46.017 --> 00:15:48.870 Now, at this point, a number of you are probably wondering 00:15:48.870 --> 00:15:52.503 well, what are you waiting for, to put on the market 00:15:52.503 --> 00:15:55.055 a game that would be good for the attention 00:15:55.055 --> 00:15:58.575 of my grandmother and that she would actually enjoy, 00:15:58.575 --> 00:16:01.158 or a game that would be great to rehabilitate the vision 00:16:01.158 --> 00:16:04.967 of my grandson who has amblyopia, for example? NOTE Paragraph 00:16:04.967 --> 00:16:09.447 Well, we're working on it, but here is a challenge. 00:16:09.447 --> 00:16:11.358 There are brain scientists like me that are beginning 00:16:11.358 --> 00:16:14.615 to understand what are the good ingredients in games 00:16:14.615 --> 00:16:17.720 to promote positive effects, and that's what I'm going 00:16:17.720 --> 00:16:21.294 to call the broccoli side of the equation. 00:16:21.294 --> 00:16:25.030 There is an entertainment software industry 00:16:25.030 --> 00:16:28.502 which is extremely deft at coming up with 00:16:28.502 --> 00:16:32.646 appealing products that you can't resist. 00:16:32.646 --> 00:16:36.174 That's the chocolate side of the equation. 00:16:36.174 --> 00:16:39.198 The issue is we need to put the two together, 00:16:39.198 --> 00:16:41.454 and it's a little bit like with food. 00:16:41.454 --> 00:16:45.095 Who really wants to eat chocolate-covered broccoli? 00:16:45.095 --> 00:16:47.354 None of you. (Laughter) And you probably have had 00:16:47.354 --> 00:16:49.686 that feeling, right, picking up an education game 00:16:49.686 --> 00:16:53.078 and sort of feeling, hmm, you know, it's not really fun, 00:16:53.078 --> 00:16:55.495 it's not really engaging. So what we need 00:16:55.495 --> 00:16:58.846 is really a new brand of chocolate, a brand of chocolate 00:16:58.846 --> 00:17:02.857 that is irresistible, that you really want to play, 00:17:02.857 --> 00:17:05.842 but that has all the ingredients, the good ingredients 00:17:05.842 --> 00:17:09.070 that are extracted from the broccoli that you can't recognize 00:17:09.070 --> 00:17:11.909 but are still working on your brains. And we're working on it, 00:17:11.909 --> 00:17:16.385 but it takes brain scientists to come and to get together, 00:17:16.385 --> 00:17:19.348 people that work in the entertainment software industry, 00:17:19.348 --> 00:17:22.086 and publishers, so these are not people that usually 00:17:22.086 --> 00:17:24.423 meet every day, but it's actually doable, 00:17:24.423 --> 00:17:27.070 and we are on the right track. 00:17:27.070 --> 00:17:28.852 I'd like to leave you with that thought, 00:17:28.852 --> 00:17:32.219 and thank you for your attention. (Applause) 00:17:32.219 --> 00:17:36.219 (Applause)