1 00:00:00,578 --> 00:00:03,675 I'm a brain scientist, and as a brain scientist, 2 00:00:03,675 --> 00:00:06,747 I'm actually interested in how the brain learns, 3 00:00:06,747 --> 00:00:10,114 and I'm especially interested in a possibility of 4 00:00:10,114 --> 00:00:14,846 making our brains smarter, better and faster. 5 00:00:14,846 --> 00:00:17,722 This is in this context I'm going to tell you 6 00:00:17,722 --> 00:00:20,472 about video games. When we say video games, 7 00:00:20,472 --> 00:00:23,010 most of you think about children. 8 00:00:23,010 --> 00:00:26,988 It's true. Ninety percent of children do play video games. 9 00:00:26,988 --> 00:00:29,906 But let's be frank. 10 00:00:29,906 --> 00:00:34,695 When the kids are in bed, who is in front of the PlayStation? 11 00:00:34,695 --> 00:00:41,179 Most of you. The average age of a gamer is 33 years old, 12 00:00:41,179 --> 00:00:44,186 not eight years old, and in fact, if we look 13 00:00:44,186 --> 00:00:47,895 at the projected demographics of video game play, 14 00:00:47,895 --> 00:00:50,628 the video game players of tomorrow are 15 00:00:50,628 --> 00:00:53,752 older adults. (Laughter) 16 00:00:53,752 --> 00:00:58,003 So video [gaming] is pervasive throughout our society. 17 00:00:58,003 --> 00:01:02,386 It is clearly here to stay. It has an amazing impact 18 00:01:02,386 --> 00:01:05,773 on our everyday life. Consider these statistics 19 00:01:05,773 --> 00:01:11,588 released by Activision. After one month of release 20 00:01:11,588 --> 00:01:16,080 of the game "Call Of Duty: Black Ops," it had been played 21 00:01:16,080 --> 00:01:19,453 for 68,000 years 22 00:01:19,453 --> 00:01:21,319 worldwide, right? 23 00:01:21,319 --> 00:01:24,266 Would any of you complain if this was the case 24 00:01:24,266 --> 00:01:27,429 about doing linear algebra? 25 00:01:27,429 --> 00:01:31,724 So what we are asking in the lab is, how can we leverage that power? 26 00:01:31,724 --> 00:01:33,572 Now I want to step back a bit. 27 00:01:33,572 --> 00:01:36,813 I know most of you have had the experience of coming back 28 00:01:36,813 --> 00:01:41,533 home and finding your kids playing these kinds of games. 29 00:01:41,533 --> 00:01:43,673 (Shooting noises) The name of the game is to get 30 00:01:43,673 --> 00:01:46,637 after your enemy zombie bad guys 31 00:01:46,637 --> 00:01:50,227 before they get to you, right? 32 00:01:50,227 --> 00:01:53,404 And I'm almost sure most of you have thought, 33 00:01:53,404 --> 00:01:56,725 "Oh, come on, can't you do something more intelligent 34 00:01:56,725 --> 00:02:00,052 than shooting at zombies?" 35 00:02:00,052 --> 00:02:03,518 I'd like you to put this kind of knee-jerk reaction 36 00:02:03,518 --> 00:02:06,015 in the context of what you would have thought 37 00:02:06,015 --> 00:02:09,524 if you had found your girl playing sudoku 38 00:02:09,524 --> 00:02:13,875 or your boy reading Shakespeare. Right? 39 00:02:13,875 --> 00:02:16,612 Most parents would find that great. 40 00:02:16,612 --> 00:02:19,956 Well, I'm not going to tell you that playing video games 41 00:02:19,956 --> 00:02:22,924 days in and days out is actually good for your health. 42 00:02:22,924 --> 00:02:26,124 It's not, and binging is never good. 43 00:02:26,124 --> 00:02:30,115 But I'm going to argue that in reasonable doses, 44 00:02:30,115 --> 00:02:33,084 actually the very game I showed you at the beginning, 45 00:02:33,084 --> 00:02:35,668 those action-packed shooter games 46 00:02:35,668 --> 00:02:39,444 have quite powerful effects and positive effects 47 00:02:39,444 --> 00:02:43,302 on many different aspects of our behavior. 48 00:02:43,302 --> 00:02:46,997 There's not one week that goes without some major 49 00:02:46,997 --> 00:02:49,773 headlines in the media about whether video games are 50 00:02:49,773 --> 00:02:54,389 good or bad for you, right? You're all bombarded with that. 51 00:02:54,389 --> 00:03:00,077 I'd like to put this kind of Friday night bar discussion aside 52 00:03:00,077 --> 00:03:03,220 and get you to actually step into the lab. 53 00:03:03,220 --> 00:03:06,093 What we do in the lab is actually measure directly, 54 00:03:06,093 --> 00:03:08,860 in a quantitative fashion, what is the impact 55 00:03:08,860 --> 00:03:11,629 of video games on the brain. 56 00:03:11,629 --> 00:03:14,964 And so I'm going to take a few examples from our work. 57 00:03:14,964 --> 00:03:17,563 One first saying that I'm sure you all have heard 58 00:03:17,563 --> 00:03:19,849 is the fact that too much screen time 59 00:03:19,849 --> 00:03:22,664 makes your eyesight worse. 60 00:03:22,664 --> 00:03:24,867 That's a statement about vision. 61 00:03:24,867 --> 00:03:27,403 There may be vision scientists among you. 62 00:03:27,403 --> 00:03:30,342 We actually know how to test that statement. 63 00:03:30,342 --> 00:03:33,779 We can step into the lab and measure how good your vision is. 64 00:03:33,779 --> 00:03:37,460 Well, guess what? People that don't play a lot 65 00:03:37,460 --> 00:03:40,450 of action games, that don't actually spend a lot of time 66 00:03:40,450 --> 00:03:43,982 in front of screens, have normal, or what we call 67 00:03:43,982 --> 00:03:46,636 corrective-to-normal vision. That's okay. 68 00:03:46,636 --> 00:03:49,085 The issue is what happens with these guys that actually 69 00:03:49,085 --> 00:03:52,365 indulge into playing video games like five hours per week, 70 00:03:52,365 --> 00:03:54,240 10 hours per week, 15 hours per week. 71 00:03:54,240 --> 00:03:57,468 By that statement, their vision should be really bad, right? 72 00:03:57,468 --> 00:04:00,165 Guess what? Their vision is really, really good. 73 00:04:00,165 --> 00:04:02,605 It's better than those that don't play. 74 00:04:02,605 --> 00:04:04,877 And it's better in two different ways. 75 00:04:04,877 --> 00:04:07,302 The first way is that they're actually able to resolve 76 00:04:07,302 --> 00:04:10,557 small detail in the context of clutter, and though that means 77 00:04:10,557 --> 00:04:14,355 being able to read the fine print on a prescription 78 00:04:14,355 --> 00:04:18,982 rather than using magnifier glasses, you can actually do it 79 00:04:18,982 --> 00:04:20,548 with just your eyesight. 80 00:04:20,548 --> 00:04:23,364 The other way that they are better is actually being able 81 00:04:23,364 --> 00:04:26,273 to resolve different levels of gray. 82 00:04:26,273 --> 00:04:29,444 Imagine you're driving in a fog. That makes a difference 83 00:04:29,444 --> 00:04:31,925 between seeing the car in front of you 84 00:04:31,925 --> 00:04:35,668 and avoiding the accident, or getting into an accident. 85 00:04:35,668 --> 00:04:38,684 So we're actually leveraging that work to develop games 86 00:04:38,684 --> 00:04:43,158 for patients with low vision, and to have an impact 87 00:04:43,158 --> 00:04:46,493 on retraining their brain to see better. 88 00:04:46,493 --> 00:04:50,142 Clearly, when it comes to action video games, 89 00:04:50,142 --> 00:04:53,037 screen time doesn't make your eyesight worse. 90 00:04:53,037 --> 00:04:57,023 Another saying that I'm sure you have all heard around: 91 00:04:57,023 --> 00:05:01,397 Video games lead to attention problems and greater distractability. 92 00:05:01,397 --> 00:05:05,302 Okay, we know how to measure attention in the lab. 93 00:05:05,302 --> 00:05:08,903 I'm actually going to give you an example of how we do so. 94 00:05:08,903 --> 00:05:11,628 I'm going to ask you to participate, so you're going to have 95 00:05:11,628 --> 00:05:14,652 to actually play the game with me. I'm going to show you 96 00:05:14,652 --> 00:05:20,085 colored words. I want you to shout out the color of the ink. 97 00:05:20,085 --> 00:05:23,468 Right? So this is the first example. 98 00:05:23,468 --> 00:05:24,558 ["Chair"] 99 00:05:24,558 --> 00:05:27,619 Orange, good. ["Table"] Green. 100 00:05:27,619 --> 00:05:28,999 ["Board"] Audience: Red.Daphne Bavelier: Red. 101 00:05:28,999 --> 00:05:30,293 ["Horse"] DB: Yellow. Audience: Yellow. 102 00:05:30,293 --> 00:05:31,618 ["Yellow"] DB: Red. Audience: Yellow. 103 00:05:31,618 --> 00:05:33,127 ["Blue"] DB: Yellow. 104 00:05:33,127 --> 00:05:39,482 Okay, you get my point, right? (Laughter) 105 00:05:39,482 --> 00:05:42,818 You're getting better, but it's hard. Why is it hard? 106 00:05:42,818 --> 00:05:46,772 Because I introduced a conflict between 107 00:05:46,772 --> 00:05:49,685 the word itself and its color. 108 00:05:49,685 --> 00:05:52,724 How good your attention is determines actually how fast 109 00:05:52,724 --> 00:05:55,251 you resolve that conflict, so the young guys here 110 00:05:55,251 --> 00:05:57,812 at the top of their game probably, like, did a little better 111 00:05:57,812 --> 00:06:00,356 than some of us that are older. 112 00:06:00,356 --> 00:06:02,924 What we can show is that when you do this kind of task 113 00:06:02,924 --> 00:06:04,524 with people that play a lot of action games, 114 00:06:04,524 --> 00:06:07,844 they actually resolve the conflict faster. 115 00:06:07,844 --> 00:06:11,052 So clearly playing those action games doesn't lead 116 00:06:11,052 --> 00:06:13,535 to attention problems. 117 00:06:13,535 --> 00:06:15,506 Actually, those action video game players have 118 00:06:15,506 --> 00:06:17,823 many other advantages in terms of attention, and one 119 00:06:17,823 --> 00:06:20,722 aspect of attention which is also improved for the better 120 00:06:20,722 --> 00:06:25,500 is our ability to track objects around in the world. 121 00:06:25,500 --> 00:06:28,044 This is something we use all the time. When you're driving, 122 00:06:28,044 --> 00:06:31,292 you're tracking, keeping track of the cars around you. 123 00:06:31,292 --> 00:06:34,367 You're also keeping track of the pedestrian, the running dog, 124 00:06:34,367 --> 00:06:37,420 and that's how you can actually be safe driving, right? 125 00:06:37,420 --> 00:06:40,484 In the lab, we get people to come to the lab, 126 00:06:40,484 --> 00:06:42,564 sit in front of a computer screen, and we give them 127 00:06:42,564 --> 00:06:45,460 little tasks that I'm going to get you to do again. 128 00:06:45,460 --> 00:06:48,412 You're going to see yellow happy faces 129 00:06:48,412 --> 00:06:52,228 and a few sad blue faces. These are children 130 00:06:52,228 --> 00:06:56,048 in the schoolyard in Geneva during a recess 131 00:06:56,048 --> 00:07:00,349 during the winter. Most kids are happy. It's actually recess. 132 00:07:00,349 --> 00:07:03,476 But a few kids are sad and blue because they've forgotten their coat. 133 00:07:03,476 --> 00:07:06,796 Everybody begins to move around, and your task 134 00:07:06,796 --> 00:07:09,920 is to keep track of who had a coat at the beginning 135 00:07:09,920 --> 00:07:12,411 and who didn't. So I'm just going to show you an example 136 00:07:12,411 --> 00:07:15,240 where there is only one sad kid. It's easy because you can 137 00:07:15,240 --> 00:07:17,577 actually track it with your eyes. You can track, 138 00:07:17,577 --> 00:07:19,857 you can track, and then when it stops, and there is 139 00:07:19,857 --> 00:07:23,788 a question mark, and I ask you, did this kid have a coat or not? 140 00:07:23,788 --> 00:07:26,616 Was it yellow initially or blue? 141 00:07:26,616 --> 00:07:30,413 I hear a few yellow. Good. So most of you have a brain. (Laughter) 142 00:07:30,413 --> 00:07:35,209 I'm now going to ask you to do the task, but now with 143 00:07:35,209 --> 00:07:37,297 a little more challenging task. There are going to be 144 00:07:37,297 --> 00:07:40,480 three of them that are blue. Don't move your eyes. 145 00:07:40,480 --> 00:07:42,733 Please don't move your eyes. Keep your eyes fixated 146 00:07:42,733 --> 00:07:45,379 and expand, pull your attention. That's the only way 147 00:07:45,379 --> 00:07:48,227 you can actually do it. If you move your eyes, you're doomed. 148 00:07:48,227 --> 00:07:49,690 Yellow or blue? 149 00:07:49,690 --> 00:07:51,336 Audience: Yellow.DB: Good. 150 00:07:51,336 --> 00:07:53,839 So your typical normal young adult 151 00:07:53,839 --> 00:07:57,475 can have a span of about three or four objects of attention. 152 00:07:57,475 --> 00:08:00,235 That's what we just did. Your action video game player 153 00:08:00,235 --> 00:08:03,435 has a span of about six to seven objects of attention, 154 00:08:03,435 --> 00:08:06,413 which is what is shown in this video here. 155 00:08:06,413 --> 00:08:09,889 That's for you guys, action video game players. 156 00:08:09,889 --> 00:08:11,774 A bit more challenging, right? (Laughter) 157 00:08:11,774 --> 00:08:15,482 Yellow or blue? Blue. We have some people 158 00:08:15,482 --> 00:08:18,686 that are serious out there. Yeah. (Laughter) 159 00:08:18,686 --> 00:08:22,290 Good. So in the same way that we actually see 160 00:08:22,290 --> 00:08:25,768 the effects of video games on people's behavior, 161 00:08:25,768 --> 00:08:28,833 we can use brain imaging and look at the impact 162 00:08:28,833 --> 00:08:32,618 of video games on the brain, and we do find many changes, 163 00:08:32,618 --> 00:08:35,978 but the main changes are actually to the brain networks 164 00:08:35,978 --> 00:08:40,522 that control attention. So one part is the parietal cortex 165 00:08:40,522 --> 00:08:44,241 which is very well known to control the orientation of attention. 166 00:08:44,241 --> 00:08:46,674 The other one is the frontal lobe, which controls 167 00:08:46,674 --> 00:08:49,384 how we sustain attention, and another one 168 00:08:49,384 --> 00:08:51,953 is the anterior cingulate, which controls how we allocate 169 00:08:51,953 --> 00:08:55,250 and regulate attention and resolve conflict. 170 00:08:55,250 --> 00:08:58,114 Now, when we do brain imaging, we find that all three 171 00:08:58,114 --> 00:09:01,458 of these networks are actually much more efficient 172 00:09:01,458 --> 00:09:04,218 in people that play action games. 173 00:09:04,218 --> 00:09:08,969 This actually leads me to a rather counterintuitive finding 174 00:09:08,969 --> 00:09:12,410 in the literature about technology and the brain. 175 00:09:12,410 --> 00:09:16,859 You all know about multitasking. You all have been faulty 176 00:09:16,859 --> 00:09:19,069 of multitasking when you're driving 177 00:09:19,069 --> 00:09:23,760 and you pick up your cellphone. Bad idea. Very bad idea. 178 00:09:23,760 --> 00:09:27,663 Why? Because as your attention shifts to your cell phone, 179 00:09:27,663 --> 00:09:31,811 you are actually losing the capacity to react swiftly 180 00:09:31,811 --> 00:09:34,259 to the car braking in front of you, and so you're 181 00:09:34,259 --> 00:09:39,830 much more likely to get engaged into a car accident. 182 00:09:39,830 --> 00:09:42,706 Now, we can measure that kind of skills in the lab. 183 00:09:42,706 --> 00:09:45,178 We obviously don't ask people to drive around and see 184 00:09:45,178 --> 00:09:47,523 how many car accidents they have. That would be a little 185 00:09:47,523 --> 00:09:51,070 costly proposition. But we design tasks on the computer 186 00:09:51,070 --> 00:09:54,188 where we can measure, to millisecond accuracy, 187 00:09:54,188 --> 00:09:58,716 how good they are at switching from one task to another. 188 00:09:58,716 --> 00:10:01,284 When we do that, we actually find that people 189 00:10:01,284 --> 00:10:04,368 that play a lot of action games are really, really good. 190 00:10:04,368 --> 00:10:08,851 They switch really fast, very swiftly. They pay a very small cost. 191 00:10:08,851 --> 00:10:11,509 Now I'd like you to remember that result, and put it 192 00:10:11,509 --> 00:10:15,241 in the context of another group of technology users, 193 00:10:15,241 --> 00:10:17,651 a group which is actually much revered by society, 194 00:10:17,651 --> 00:10:22,190 which are people that engage in multimedia-tasking. 195 00:10:22,190 --> 00:10:25,835 What is multimedia-tasking? It's the fact that most of us, 196 00:10:25,835 --> 00:10:29,116 most of our children, are engaged with listening to music 197 00:10:29,116 --> 00:10:31,863 at the same time as they're doing search on the web 198 00:10:31,863 --> 00:10:35,220 at the same time as they're chatting on Facebook with their friends. 199 00:10:35,220 --> 00:10:37,556 That's a multimedia-tasker. 200 00:10:37,556 --> 00:10:41,116 There was a first study done by colleagues at Stanford 201 00:10:41,116 --> 00:10:43,669 and that we replicated that showed that 202 00:10:43,669 --> 00:10:48,316 those people that identify as being high multimedia-taskers 203 00:10:48,316 --> 00:10:52,163 are absolutely abysmal at multitasking. 204 00:10:52,163 --> 00:10:54,900 When we measure them in the lab, they're really bad. 205 00:10:54,900 --> 00:10:57,606 Right? So these kinds of results really 206 00:10:57,606 --> 00:11:00,092 makes two main points. 207 00:11:00,092 --> 00:11:03,284 The first one is that not all media are created equal. 208 00:11:03,284 --> 00:11:08,196 You can't compare the effect of multimedia-tasking 209 00:11:08,196 --> 00:11:09,842 and the effect of playing action games. They have 210 00:11:09,842 --> 00:11:13,234 totally different effects on different aspects of cognition, 211 00:11:13,234 --> 00:11:16,348 perception and attention. 212 00:11:16,348 --> 00:11:19,188 Even within video games, I'm telling you right now 213 00:11:19,188 --> 00:11:20,941 about these action-packed video games. 214 00:11:20,941 --> 00:11:24,275 Different video games have a different effect on your brains. 215 00:11:24,275 --> 00:11:26,957 So we actually need to step into the lab and really measure 216 00:11:26,957 --> 00:11:29,468 what is the effect of each video game. 217 00:11:29,468 --> 00:11:33,755 The other lesson is that general wisdom carries no weight. 218 00:11:33,755 --> 00:11:36,811 I showed that to you already, like we looked at the fact that 219 00:11:36,811 --> 00:11:39,259 despite a lot of screen time, those action gamers 220 00:11:39,259 --> 00:11:43,267 have a lot of very good vision, etc. 221 00:11:43,267 --> 00:11:46,585 Here, what was really striking is that these undergraduates 222 00:11:46,585 --> 00:11:49,826 that actually report engaging in a lot of high 223 00:11:49,826 --> 00:11:54,803 multimedia-tasking are convinced they aced the test. 224 00:11:54,803 --> 00:11:57,093 So you show them their data, you show them they are bad 225 00:11:57,093 --> 00:11:59,779 and they're like, "Not possible." You know, they have 226 00:11:59,779 --> 00:12:03,635 this sort of gut feeling that, really, they are doing really, really good. 227 00:12:03,635 --> 00:12:06,580 That's another argument for why we need to step into the lab 228 00:12:06,580 --> 00:12:10,172 and really measure the impact of technology on the brain. 229 00:12:10,172 --> 00:12:14,755 Now in a sense, when we think about the effect 230 00:12:14,755 --> 00:12:17,235 of video games on the brain, it's very similar 231 00:12:17,235 --> 00:12:21,099 to the effect of wine on the health. 232 00:12:21,099 --> 00:12:24,139 There are some very poor uses of wine. There are some 233 00:12:24,139 --> 00:12:28,355 very poor uses of video games. But when consumed 234 00:12:28,355 --> 00:12:31,836 in reasonable doses, and at the right age, 235 00:12:31,836 --> 00:12:35,107 wine can be very good for health. There are actually 236 00:12:35,107 --> 00:12:38,371 specific molecules that have been identified 237 00:12:38,371 --> 00:12:44,203 in red wine as leading to greater life expectancy. 238 00:12:44,203 --> 00:12:47,475 So it's the same way, like those action video games 239 00:12:47,475 --> 00:12:49,137 have a number of ingredients that are actually really 240 00:12:49,137 --> 00:12:53,107 powerful for brain plasticity, learning, attention, 241 00:12:53,107 --> 00:12:56,712 vision, etc., and so we need and we're working on 242 00:12:56,712 --> 00:12:59,467 understanding what are those active ingredients so that 243 00:12:59,467 --> 00:13:03,357 we can really then leverage them to deliver better games, 244 00:13:03,357 --> 00:13:07,600 either for education or for rehabilitation of patients. 245 00:13:07,600 --> 00:13:11,379 Now because we are interested in having an impact 246 00:13:11,379 --> 00:13:13,867 for education or rehabilitation of patients, we are actually 247 00:13:13,867 --> 00:13:17,283 not that interested in how those of you that choose 248 00:13:17,283 --> 00:13:21,155 to play video games for many hours on end perform. 249 00:13:21,155 --> 00:13:24,980 I'm much more interested in taking any of you 250 00:13:24,980 --> 00:13:28,760 and showing that by forcing you to play an action game, 251 00:13:28,760 --> 00:13:31,623 I can actually change your vision for the better, 252 00:13:31,623 --> 00:13:33,954 whether you want to play that action game or not, right? 253 00:13:33,954 --> 00:13:36,370 That's the point of rehabilitation or education. 254 00:13:36,370 --> 00:13:38,296 Most of the kids don't go to school saying, 255 00:13:38,296 --> 00:13:41,036 "Great, two hours of math!" 256 00:13:41,036 --> 00:13:45,475 So that's really the crux of the research, and to do that, 257 00:13:45,475 --> 00:13:47,939 we need to go one more step. 258 00:13:47,939 --> 00:13:50,963 And one more step is to do training studies. 259 00:13:50,963 --> 00:13:54,363 So let me illustrate that step with 260 00:13:54,363 --> 00:13:57,931 a task which is called mental rotation. 261 00:13:57,931 --> 00:14:02,106 Mental rotation is a task where I'm going to ask you, 262 00:14:02,106 --> 00:14:03,991 and again you're going to do the task, 263 00:14:03,991 --> 00:14:07,676 to look at this shape. Study it, it's a target shape, 264 00:14:07,676 --> 00:14:10,930 and I'm going to present to you four different shapes. 265 00:14:10,930 --> 00:14:13,770 One of these four different shapes is actually a rotated 266 00:14:13,770 --> 00:14:18,074 version of this shape. I want you to tell me which one: 267 00:14:18,074 --> 00:14:22,915 the first one, second one, third one or fourth one? 268 00:14:22,915 --> 00:14:25,332 Okay, I'll help you. Fourth one. 269 00:14:25,332 --> 00:14:29,862 One more. Get those brains working. Come on. 270 00:14:29,862 --> 00:14:34,836 That's our target shape. 271 00:14:34,836 --> 00:14:38,539 Third. Good! This is hard, right? 272 00:14:38,539 --> 00:14:40,026 Like, the reason that I asked you to do that is because 273 00:14:40,026 --> 00:14:42,760 you really feel your brain cringing, right? 274 00:14:42,760 --> 00:14:46,192 It doesn't really feel like playing mindless action video games. 275 00:14:46,192 --> 00:14:48,897 Well, what we do in these training studies is, people 276 00:14:48,897 --> 00:14:51,506 come to the lab, they do tasks like this one, 277 00:14:51,506 --> 00:14:55,836 we then force them to play 10 hours of action games. 278 00:14:55,836 --> 00:14:58,582 They don't play 10 hours of action games in a row. 279 00:14:58,582 --> 00:15:01,692 They do distributed practice, so little shots of 40 minutes 280 00:15:01,692 --> 00:15:05,993 several days over a period of two weeks. 281 00:15:05,993 --> 00:15:07,789 Then, once they are done with the training, they come back 282 00:15:07,789 --> 00:15:11,762 a few days later and they are tested again on a similar type 283 00:15:11,762 --> 00:15:15,378 of mental rotation task. So this is work from a colleague 284 00:15:15,378 --> 00:15:17,913 in Toronto. What they showed is that, initially, 285 00:15:17,913 --> 00:15:20,111 you know, subjects perform where they are expected 286 00:15:20,111 --> 00:15:25,321 to perform given their age. After two weeks of training 287 00:15:25,321 --> 00:15:29,177 on action video games, they actually perform better, 288 00:15:29,177 --> 00:15:34,533 and the improvement is still there five months after 289 00:15:34,533 --> 00:15:37,401 having done the training. That's really, really important. 290 00:15:37,401 --> 00:15:39,881 Why? Because I told you we want to use these games 291 00:15:39,881 --> 00:15:43,081 for education or for rehabilitation. We need to have effects 292 00:15:43,081 --> 00:15:46,017 that are going to be long-lasting. 293 00:15:46,017 --> 00:15:48,870 Now, at this point, a number of you are probably wondering 294 00:15:48,870 --> 00:15:52,503 well, what are you waiting for, to put on the market 295 00:15:52,503 --> 00:15:55,055 a game that would be good for the attention 296 00:15:55,055 --> 00:15:58,575 of my grandmother and that she would actually enjoy, 297 00:15:58,575 --> 00:16:01,158 or a game that would be great to rehabilitate the vision 298 00:16:01,158 --> 00:16:04,967 of my grandson who has amblyopia, for example? 299 00:16:04,967 --> 00:16:09,447 Well, we're working on it, but here is a challenge. 300 00:16:09,447 --> 00:16:11,358 There are brain scientists like me that are beginning 301 00:16:11,358 --> 00:16:14,615 to understand what are the good ingredients in games 302 00:16:14,615 --> 00:16:17,720 to promote positive effects, and that's what I'm going 303 00:16:17,720 --> 00:16:21,294 to call the broccoli side of the equation. 304 00:16:21,294 --> 00:16:25,030 There is an entertainment software industry 305 00:16:25,030 --> 00:16:28,502 which is extremely deft at coming up with 306 00:16:28,502 --> 00:16:32,646 appealing products that you can't resist. 307 00:16:32,646 --> 00:16:36,174 That's the chocolate side of the equation. 308 00:16:36,174 --> 00:16:39,198 The issue is we need to put the two together, 309 00:16:39,198 --> 00:16:41,454 and it's a little bit like with food. 310 00:16:41,454 --> 00:16:45,095 Who really wants to eat chocolate-covered broccoli? 311 00:16:45,095 --> 00:16:47,354 None of you. (Laughter) And you probably have had 312 00:16:47,354 --> 00:16:49,686 that feeling, right, picking up an education game 313 00:16:49,686 --> 00:16:53,078 and sort of feeling, hmm, you know, it's not really fun, 314 00:16:53,078 --> 00:16:55,495 it's not really engaging. So what we need 315 00:16:55,495 --> 00:16:58,846 is really a new brand of chocolate, a brand of chocolate 316 00:16:58,846 --> 00:17:02,857 that is irresistible, that you really want to play, 317 00:17:02,857 --> 00:17:05,842 but that has all the ingredients, the good ingredients 318 00:17:05,842 --> 00:17:09,070 that are extracted from the broccoli that you can't recognize 319 00:17:09,070 --> 00:17:11,909 but are still working on your brains. And we're working on it, 320 00:17:11,909 --> 00:17:16,385 but it takes brain scientists to come and to get together, 321 00:17:16,385 --> 00:17:19,348 people that work in the entertainment software industry, 322 00:17:19,348 --> 00:17:22,086 and publishers, so these are not people that usually 323 00:17:22,086 --> 00:17:24,423 meet every day, but it's actually doable, 324 00:17:24,423 --> 00:17:27,070 and we are on the right track. 325 00:17:27,070 --> 00:17:28,852 I'd like to leave you with that thought, 326 00:17:28,852 --> 00:17:32,219 and thank you for your attention. (Applause) 327 00:17:32,219 --> 00:17:36,219 (Applause)